Correlation of invasive EEG and scalp EEG.
Ramantani, Georgia; Maillard, Louis; Koessler, Laurent
2016-10-01
Ever since the implementation of invasive EEG recordings in the clinical setting, it has been perceived that a considerable proportion of epileptic discharges present at a cortical level are missed by routine scalp EEG recordings. Several in vitro, in vivo, and simulation studies have been performed in the past decades aiming to clarify the interrelations of cortical sources with their scalp and invasive EEG correlates. The amplitude ratio of cortical potentials to their scalp EEG correlates, the extent of the cortical area involved in the discharge, as well as the localization of the cortical source and its geometry have been each independently linked to the recording of the cortical discharge with scalp electrodes. The need to elucidate these interrelations has been particularly imperative in the field of epilepsy surgery with its rapidly growing EEG-based localization technologies. Simultaneous multiscale EEG recordings with scalp, subdural and/or depth electrodes, applied in presurgical epilepsy workup, offer an excellent opportunity to shed some light to this fundamental issue. Whereas past studies have considered predominantly neocortical sources in the context of temporal lobe epilepsy, current investigations have included deep sources, as in mesial temporal epilepsy, as well as extratemporal sources. Novel computational tools may serve to provide surrogates for the shortcomings of EEG recording methodology and facilitate further developments in modern electrophysiology. Copyright © 2016 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.
Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG
Krishnaswamy, Pavitra; Obregon-Henao, Gabriel; Ahveninen, Jyrki; Khan, Sheraz; Iglesias, Juan Eugenio; Hämäläinen, Matti S.; Purdon, Patrick L.
2017-01-01
Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain. PMID:29138310
Evaluation of Electroencephalography Source Localization Algorithms with Multiple Cortical Sources.
Bradley, Allison; Yao, Jun; Dewald, Jules; Richter, Claus-Peter
2016-01-01
Source localization algorithms often show multiple active cortical areas as the source of electroencephalography (EEG). Yet, there is little data quantifying the accuracy of these results. In this paper, the performance of current source density source localization algorithms for the detection of multiple cortical sources of EEG data has been characterized. EEG data were generated by simulating multiple cortical sources (2-4) with the same strength or two sources with relative strength ratios of 1:1 to 4:1, and adding noise. These data were used to reconstruct the cortical sources using current source density (CSD) algorithms: sLORETA, MNLS, and LORETA using a p-norm with p equal to 1, 1.5 and 2. Precision (percentage of the reconstructed activity corresponding to simulated activity) and Recall (percentage of the simulated sources reconstructed) of each of the CSD algorithms were calculated. While sLORETA has the best performance when only one source is present, when two or more sources are present LORETA with p equal to 1.5 performs better. When the relative strength of one of the sources is decreased, all algorithms have more difficulty reconstructing that source. However, LORETA 1.5 continues to outperform other algorithms. If only the strongest source is of interest sLORETA is recommended, while LORETA with p equal to 1.5 is recommended if two or more of the cortical sources are of interest. These results provide guidance for choosing a CSD algorithm to locate multiple cortical sources of EEG and for interpreting the results of these algorithms.
Evaluation of Electroencephalography Source Localization Algorithms with Multiple Cortical Sources
Bradley, Allison; Yao, Jun; Dewald, Jules; Richter, Claus-Peter
2016-01-01
Background Source localization algorithms often show multiple active cortical areas as the source of electroencephalography (EEG). Yet, there is little data quantifying the accuracy of these results. In this paper, the performance of current source density source localization algorithms for the detection of multiple cortical sources of EEG data has been characterized. Methods EEG data were generated by simulating multiple cortical sources (2–4) with the same strength or two sources with relative strength ratios of 1:1 to 4:1, and adding noise. These data were used to reconstruct the cortical sources using current source density (CSD) algorithms: sLORETA, MNLS, and LORETA using a p-norm with p equal to 1, 1.5 and 2. Precision (percentage of the reconstructed activity corresponding to simulated activity) and Recall (percentage of the simulated sources reconstructed) of each of the CSD algorithms were calculated. Results While sLORETA has the best performance when only one source is present, when two or more sources are present LORETA with p equal to 1.5 performs better. When the relative strength of one of the sources is decreased, all algorithms have more difficulty reconstructing that source. However, LORETA 1.5 continues to outperform other algorithms. If only the strongest source is of interest sLORETA is recommended, while LORETA with p equal to 1.5 is recommended if two or more of the cortical sources are of interest. These results provide guidance for choosing a CSD algorithm to locate multiple cortical sources of EEG and for interpreting the results of these algorithms. PMID:26809000
Simultaneous EEG and MEG source reconstruction in sparse electromagnetic source imaging.
Ding, Lei; Yuan, Han
2013-04-01
Electroencephalography (EEG) and magnetoencephalography (MEG) have different sensitivities to differently configured brain activations, making them complimentary in providing independent information for better detection and inverse reconstruction of brain sources. In the present study, we developed an integrative approach, which integrates a novel sparse electromagnetic source imaging method, i.e., variation-based cortical current density (VB-SCCD), together with the combined use of EEG and MEG data in reconstructing complex brain activity. To perform simultaneous analysis of multimodal data, we proposed to normalize EEG and MEG signals according to their individual noise levels to create unit-free measures. Our Monte Carlo simulations demonstrated that this integrative approach is capable of reconstructing complex cortical brain activations (up to 10 simultaneously activated and randomly located sources). Results from experimental data showed that complex brain activations evoked in a face recognition task were successfully reconstructed using the integrative approach, which were consistent with other research findings and validated by independent data from functional magnetic resonance imaging using the same stimulus protocol. Reconstructed cortical brain activations from both simulations and experimental data provided precise source localizations as well as accurate spatial extents of localized sources. In comparison with studies using EEG or MEG alone, the performance of cortical source reconstructions using combined EEG and MEG was significantly improved. We demonstrated that this new sparse ESI methodology with integrated analysis of EEG and MEG data could accurately probe spatiotemporal processes of complex human brain activations. This is promising for noninvasively studying large-scale brain networks of high clinical and scientific significance. Copyright © 2011 Wiley Periodicals, Inc.
Cuspineda, E R; Machado, C; Virues, T; Martínez-Montes, E; Ojeda, A; Valdés, P A; Bosch, J; Valdes, L
2009-07-01
Conventional EEG and quantitative EEG visual stimuli (close-open eyes) reactivity analysis have shown their usefulness in clinical practice; however studies at the level of EEG generators are limited. The focus of the study was visual reactivity of cortical resources in healthy subjects and in a stroke patient. The 64 channel EEG and T1 magnetic resonance imaging (MRI) studies were obtained from 32 healthy subjects and a middle cerebral artery stroke patient. Low Resolution Electromagnetic Tomography (LORETA) was used to estimate EEG sources for both close eyes (CE) vs. open eyes (OE) conditions using individual MRI. The t-test was performed between source spectra of the two conditions. Thresholds for statistically significant t values were estimated by the local false discovery rate (lfdr) method. The Z transform was used to quantify the differences in cortical reactivity between the patient and healthy subjects. Closed-open eyes alpha reactivity sources were found mainly in posterior regions (occipito-parietal zones), extended in some cases to anterior and thalamic regions. Significant cortical reactivity sources were found in frequencies different from alpha (lower t-values). Significant changes at EEG reactivity sources were evident in the damaged brain hemisphere. Reactivity changes were also found in the "healthy" hemisphere when compared with the normal population. In conclusion, our study of brain sources of EEG alpha reactivity provides information that is not evident in the usual topographic analysis.
Frøkjær, Jens B; Graversen, Carina; Brock, Christina; Khodayari-Rostamabad, Ahmad; Olesen, Søren S; Hansen, Tine M; Søfteland, Eirik; Simrén, Magnus; Drewes, Asbjørn M
2017-02-01
Diabetes mellitus (DM) is associated with structural and functional changes of the central nervous system. We used electroencephalography (EEG) to assess resting state cortical activity and explored associations to relevant clinical features. Multichannel resting state EEG was recorded in 27 healthy controls and 24 patients with longstanding DM and signs of autonomic dysfunction. The power distribution based on wavelet analysis was summarized into frequency bands with corresponding topographic mapping. Source localization analysis was applied to explore the electrical cortical sources underlying the EEG. Compared to controls, DM patients had an overall decreased EEG power in the delta (1-4Hz) and gamma (30-45Hz) bands. Topographic analysis revealed that these changes were confined to the frontal region for the delta band and to central cortical areas for the gamma band. Source localization analysis identified sources with reduced activity in the left postcentral gyrus for the gamma band and in right superior parietal lobule for the alpha1 (8-10Hz) band. DM patients with clinical signs of autonomic dysfunction and gastrointestinal symptoms had evidence of altered resting state cortical processing. This may reflect metabolic, vascular or neuronal changes associated with diabetes. Copyright © 2017 Elsevier Inc. All rights reserved.
A physiologically motivated sparse, compact, and smooth (SCS) approach to EEG source localization.
Cao, Cheng; Akalin Acar, Zeynep; Kreutz-Delgado, Kenneth; Makeig, Scott
2012-01-01
Here, we introduce a novel approach to the EEG inverse problem based on the assumption that principal cortical sources of multi-channel EEG recordings may be assumed to be spatially sparse, compact, and smooth (SCS). To enforce these characteristics of solutions to the EEG inverse problem, we propose a correlation-variance model which factors a cortical source space covariance matrix into the multiplication of a pre-given correlation coefficient matrix and the square root of the diagonal variance matrix learned from the data under a Bayesian learning framework. We tested the SCS method using simulated EEG data with various SNR and applied it to a real ECOG data set. We compare the results of SCS to those of an established SBL algorithm.
Real-time Neuroimaging and Cognitive Monitoring Using Wearable Dry EEG
Mullen, Tim R.; Kothe, Christian A.E.; Chi, Mike; Ojeda, Alejandro; Kerth, Trevor; Makeig, Scott; Jung, Tzyy-Ping; Cauwenberghs, Gert
2015-01-01
Goal We present and evaluate a wearable high-density dry electrode EEG system and an open-source software framework for online neuroimaging and state classification. Methods The system integrates a 64-channel dry EEG form-factor with wireless data streaming for online analysis. A real-time software framework is applied, including adaptive artifact rejection, cortical source localization, multivariate effective connectivity inference, data visualization, and cognitive state classification from connectivity features using a constrained logistic regression approach (ProxConn). We evaluate the system identification methods on simulated 64-channel EEG data. Then we evaluate system performance, using ProxConn and a benchmark ERP method, in classifying response errors in 9 subjects using the dry EEG system. Results Simulations yielded high accuracy (AUC=0.97±0.021) for real-time cortical connectivity estimation. Response error classification using cortical effective connectivity (sdDTF) was significantly above chance with similar performance (AUC) for cLORETA (0.74±0.09) and LCMV (0.72±0.08) source localization. Cortical ERP-based classification was equivalent to ProxConn for cLORETA (0.74±0.16) but significantly better for LCMV (0.82±0.12). Conclusion We demonstrated the feasibility for real-time cortical connectivity analysis and cognitive state classification from high-density wearable dry EEG. Significance This paper is the first validated application of these methods to 64-channel dry EEG. The work addresses a need for robust real-time measurement and interpretation of complex brain activity in the dynamic environment of the wearable setting. Such advances can have broad impact in research, medicine, and brain-computer interfaces. The pipelines are made freely available in the open-source SIFT and BCILAB toolboxes. PMID:26415149
NASA Astrophysics Data System (ADS)
Im, Chang-Hwan; Jung, Hyun-Kyo; Fujimaki, Norio
2005-10-01
This paper proposes an alternative approach to enhance localization accuracy of MEG and EEG focal sources. The proposed approach assumes anatomically constrained spatio-temporal dipoles, initial positions of which are estimated from local peak positions of distributed sources obtained from a pre-execution of distributed source reconstruction. The positions of the dipoles are then adjusted on the cortical surface using a novel updating scheme named cortical surface scanning. The proposed approach has many advantages over the conventional ones: (1) as the cortical surface scanning algorithm uses spatio-temporal dipoles, it is robust with respect to noise; (2) it requires no a priori information on the numbers and initial locations of the activations; (3) as the locations of dipoles are restricted only on a tessellated cortical surface, it is physiologically more plausible than the conventional ECD model. To verify the proposed approach, it was applied to several realistic MEG/EEG simulations and practical experiments. From the several case studies, it is concluded that the anatomically constrained dipole adjustment (ANACONDA) approach will be a very promising technique to enhance accuracy of focal source localization which is essential in many clinical and neurological applications of MEG and EEG.
Muthuraman, Muthuraman; Hellriegel, Helge; Hoogenboom, Nienke; Anwar, Abdul Rauf; Mideksa, Kidist Gebremariam; Krause, Holger; Schnitzler, Alfons; Deuschl, Günther; Raethjen, Jan
2014-01-01
Electroencephalography (EEG) and magnetoencephalography (MEG) are the two modalities for measuring neuronal dynamics at a millisecond temporal resolution. Different source analysis methods, to locate the dipoles in the brain from which these dynamics originate, have been readily applied to both modalities alone. However, direct comparisons and possible advantages of combining both modalities have rarely been assessed during voluntary movements using coherent source analysis. In the present study, the cortical and sub-cortical network of coherent sources at the finger tapping task frequency (2-4 Hz) and the modes of interaction within this network were analysed in 15 healthy subjects using a beamformer approach called the dynamic imaging of coherent sources (DICS) with subsequent source signal reconstruction and renormalized partial directed coherence analysis (RPDC). MEG and EEG data were recorded simultaneously allowing the comparison of each of the modalities separately to that of the combined approach. We found the identified network of coherent sources for the finger tapping task as described in earlier studies when using only the MEG or combined MEG+EEG whereas the EEG data alone failed to detect single sub-cortical sources. The signal-to-noise ratio (SNR) level of the coherent rhythmic activity at the tapping frequency in MEG and combined MEG+EEG data was significantly higher than EEG alone. The functional connectivity analysis revealed that the combined approach had more active connections compared to either of the modalities during the finger tapping (FT) task. These results indicate that MEG is superior in the detection of deep coherent sources and that the SNR seems to be more vital than the sensitivity to theoretical dipole orientation and the volume conduction effect in the case of EEG.
Muthuraman, Muthuraman; Hellriegel, Helge; Hoogenboom, Nienke; Anwar, Abdul Rauf; Mideksa, Kidist Gebremariam; Krause, Holger; Schnitzler, Alfons; Deuschl, Günther; Raethjen, Jan
2014-01-01
Electroencephalography (EEG) and magnetoencephalography (MEG) are the two modalities for measuring neuronal dynamics at a millisecond temporal resolution. Different source analysis methods, to locate the dipoles in the brain from which these dynamics originate, have been readily applied to both modalities alone. However, direct comparisons and possible advantages of combining both modalities have rarely been assessed during voluntary movements using coherent source analysis. In the present study, the cortical and sub-cortical network of coherent sources at the finger tapping task frequency (2–4 Hz) and the modes of interaction within this network were analysed in 15 healthy subjects using a beamformer approach called the dynamic imaging of coherent sources (DICS) with subsequent source signal reconstruction and renormalized partial directed coherence analysis (RPDC). MEG and EEG data were recorded simultaneously allowing the comparison of each of the modalities separately to that of the combined approach. We found the identified network of coherent sources for the finger tapping task as described in earlier studies when using only the MEG or combined MEG+EEG whereas the EEG data alone failed to detect single sub-cortical sources. The signal-to-noise ratio (SNR) level of the coherent rhythmic activity at the tapping frequency in MEG and combined MEG+EEG data was significantly higher than EEG alone. The functional connectivity analysis revealed that the combined approach had more active connections compared to either of the modalities during the finger tapping (FT) task. These results indicate that MEG is superior in the detection of deep coherent sources and that the SNR seems to be more vital than the sensitivity to theoretical dipole orientation and the volume conduction effect in the case of EEG. PMID:24618596
Giacometti, Paolo; Diamond, Solomon G.
2014-01-01
Abstract. This study investigates the correspondence of the cortical sensitivity of electroencephalography (EEG) and near-infrared spectroscopy (NIRS). EEG forward model sensitivity to the cerebral cortex was calculated for 329 EEG electrodes following the 10-5 EEG positioning system using a segmented structural magnetic resonance imaging scan of a human subject. NIRS forward model sensitivity was calculated for the same subject using 156 NIRS source-detector pairs selected from 32 source and 32 detector optodes positioned on the scalp using a subset of the 10-5 EEG positioning system. Sensitivity correlations between colocalized NIRS source-detector pair groups and EEG channels yielded R=0.46±0.08. Groups of NIRS source-detector pairs with maximum correlations to EEG electrode sensitivities are tabulated. The mean correlation between the point spread functions for EEG and NIRS regions of interest (ROI) was R=0.43±0.07. Spherical ROIs with radii of 26 mm yielded the maximum correlation between EEG and NIRS averaged across all cortical mesh nodes. These sensitivity correlations between EEG and NIRS should be taken into account when designing multimodal studies of neurovascular coupling and when using NIRS as a statistical prior for EEG source localization. PMID:25558462
Neuronal Networks during Burst Suppression as Revealed by Source Analysis
Reinicke, Christine; Moeller, Friederike; Anwar, Abdul Rauf; Mideksa, Kidist Gebremariam; Pressler, Ronit; Deuschl, Günther; Stephani, Ulrich; Siniatchkin, Michael
2015-01-01
Introduction Burst-suppression (BS) is an electroencephalography (EEG) pattern consisting of alternant periods of slow waves of high amplitude (burst) and periods of so called flat EEG (suppression). It is generally associated with coma of various etiologies (hypoxia, drug-related intoxication, hypothermia, and childhood encephalopathies, but also anesthesia). Animal studies suggest that both the cortex and the thalamus are involved in the generation of BS. However, very little is known about mechanisms of BS in humans. The aim of this study was to identify the neuronal network underlying both burst and suppression phases using source reconstruction and analysis of functional and effective connectivity in EEG. Material/Methods Dynamic imaging of coherent sources (DICS) was applied to EEG segments of 13 neonates and infants with burst and suppression EEG pattern. The brain area with the strongest power in the analyzed frequency (1–4 Hz) range was defined as the reference region. DICS was used to compute the coherence between this reference region and the entire brain. The renormalized partial directed coherence (RPDC) was used to describe the informational flow between the identified sources. Results/Conclusion Delta activity during the burst phases was associated with coherent sources in the thalamus and brainstem as well as bilateral sources in cortical regions mainly frontal and parietal, whereas suppression phases were associated with coherent sources only in cortical regions. Results of the RPDC analyses showed an upwards informational flow from the brainstem towards the thalamus and from the thalamus to cortical regions, which was absent during the suppression phases. These findings may support the theory that a “cortical deafferentiation” between the cortex and sub-cortical structures exists especially in suppression phases compared to burst phases in burst suppression EEGs. Such a deafferentiation may play a role in the poor neurological outcome of children with these encephalopathies. PMID:25927439
Grova, Christophe; Aiguabella, Maria; Zelmann, Rina; Lina, Jean-Marc; Hall, Jeffery A; Kobayashi, Eliane
2016-05-01
Detection of epileptic spikes in MagnetoEncephaloGraphy (MEG) requires synchronized neuronal activity over a minimum of 4cm2. We previously validated the Maximum Entropy on the Mean (MEM) as a source localization able to recover the spatial extent of the epileptic spike generators. The purpose of this study was to evaluate quantitatively, using intracranial EEG (iEEG), the spatial extent recovered from MEG sources by estimating iEEG potentials generated by these MEG sources. We evaluated five patients with focal epilepsy who had a pre-operative MEG acquisition and iEEG with MRI-compatible electrodes. Individual MEG epileptic spikes were localized along the cortical surface segmented from a pre-operative MRI, which was co-registered with the MRI obtained with iEEG electrodes in place for identification of iEEG contacts. An iEEG forward model estimated the influence of every dipolar source of the cortical surface on each iEEG contact. This iEEG forward model was applied to MEG sources to estimate iEEG potentials that would have been generated by these sources. MEG-estimated iEEG potentials were compared with measured iEEG potentials using four source localization methods: two variants of MEM and two standard methods equivalent to minimum norm and LORETA estimates. Our results demonstrated an excellent MEG/iEEG correspondence in the presumed focus for four out of five patients. In one patient, the deep generator identified in iEEG could not be localized in MEG. MEG-estimated iEEG potentials is a promising method to evaluate which MEG sources could be retrieved and validated with iEEG data, providing accurate results especially when applied to MEM localizations. Hum Brain Mapp 37:1661-1683, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Simultaneous head tissue conductivity and EEG source location estimation.
Akalin Acar, Zeynep; Acar, Can E; Makeig, Scott
2016-01-01
Accurate electroencephalographic (EEG) source localization requires an electrical head model incorporating accurate geometries and conductivity values for the major head tissues. While consistent conductivity values have been reported for scalp, brain, and cerebrospinal fluid, measured brain-to-skull conductivity ratio (BSCR) estimates have varied between 8 and 80, likely reflecting both inter-subject and measurement method differences. In simulations, mis-estimation of skull conductivity can produce source localization errors as large as 3cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15cm(2)-scale cortical patch sources in an MR image-based electrical head model with simulated BSCR of 30. Initialized either with a BSCR of 80 or 20, SCALE estimated BSCR as 32.6. In Adaptive Mixture ICA (AMICA) decompositions of (45-min, 128-channel) EEG data from two young adults we identified sets of 13 independent components having near-dipolar scalp maps compatible with a single cortical source patch. Again initialized with either BSCR 80 or 25, SCALE gave BSCR estimates of 34 and 54 for the two subjects respectively. The ability to accurately estimate skull conductivity non-invasively from any well-recorded EEG data in combination with a stable and non-invasively acquired MR imaging-derived electrical head model could remove a critical barrier to using EEG as a sub-cm(2)-scale accurate 3-D functional cortical imaging modality. Copyright © 2015 Elsevier Inc. All rights reserved.
Simultaneous head tissue conductivity and EEG source location estimation
Acar, Can E.; Makeig, Scott
2015-01-01
Accurate electroencephalographic (EEG) source localization requires an electrical head model incorporating accurate geometries and conductivity values for the major head tissues. While consistent conductivity values have been reported for scalp, brain, and cerebrospinal fluid, measured brain-to-skull conductivity ratio (BSCR) estimates have varied between 8 and 80, likely reflecting both inter-subject and measurement method differences. In simulations, mis-estimation of skull conductivity can produce source localization errors as large as 3 cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15 cm2-scale cortical patch sources in an MR image-based electrical head model with simulated BSCR of 30. Initialized either with a BSCR of 80 or 20, SCALE estimated BSCR as 32.6. In Adaptive Mixture ICA (AMICA) decompositions of (45-min, 128-channel) EEG data from two young adults we identified sets of 13 independent components having near-dipolar scalp maps compatible with a single cortical source patch. Again initialized with either BSCR 80 or 25, SCALE gave BSCR estimates of 34 and 54 for the two subjects respectively. The ability to accurately estimate skull conductivity non-invasively from any well-recorded EEG data in combination with a stable and non-invasively acquired MR imaging-derived electrical head model could remove a critical barrier to using EEG as a sub-cm2-scale accurate 3-D functional cortical imaging modality. PMID:26302675
Zumsteg, Dominik; Andrade, Danielle M; Wennberg, Richard A
2006-06-01
We have investigated the cortical sources and electroencephalographic (EEG) characteristics of small sharp spikes (SSS) by using statistical non-parametric mapping (SNPM) of low resolution electromagnetic tomography (LORETA). We analyzed 7 SSS patterns (501 individual SSS) in 6 patients who underwent sleep EEG studies with 29 or 23 scalp electrodes. The scalp signals were averaged time-locked to the SSS peak activity and subjected to SNPM of LORETA values. All 7 SSS patterns (mean 72 individual SSS, range 11-200) revealed a very similar and highly characteristic transhemispheric oblique scalp voltage distribution comprising a first negative field maximum over ipsilateral lateral temporal areas, followed by a second negative field maximum over the contralateral subtemporal region approximately 30 ms later. SNPM-LORETA consistently localized the first component into the ipsilateral posterior insular region, and the second component into ipsilateral posterior mesial temporo-occipital structures. SSS comprise an amalgam of two sequential, distinct cortical components, showing a very uniform and peculiar EEG pattern and cortical source solutions. As such, they must be clearly distinguished from interictal epileptiform discharges in patients with epilepsy. The awareness of these peculiar EEG characteristics may increase our ability to differentiate SSS from interictal epileptiform activity. The finding of a posterior insular source might serve as an inspiration for new physiological considerations regarding these enigmatic waveforms.
Seeber, Martin; Scherer, Reinhold; Müller-Putz, Gernot R
2016-11-16
Sequencing and timing of body movements are essential to perform motoric tasks. In this study, we investigate the temporal relation between cortical oscillations and human motor behavior (i.e., rhythmic finger movements). High-density EEG recordings were used for source imaging based on individual anatomy. We separated sustained and movement phase-related EEG source amplitudes based on the actual finger movements recorded by a data glove. Sustained amplitude modulations in the contralateral hand area show decrease for α (10-12 Hz) and β (18-24 Hz), but increase for high γ (60-80 Hz) frequencies during the entire movement period. Additionally, we found movement phase-related amplitudes, which resembled the flexion and extension sequence of the fingers. Especially for faster movement cadences, movement phase-related amplitudes included high β (24-30 Hz) frequencies in prefrontal areas. Interestingly, the spectral profiles and source patterns of movement phase-related amplitudes differed from sustained activities, suggesting that they represent different frequency-specific large-scale networks. First, networks were signified by the sustained element, which statically modulate their synchrony levels during continuous movements. These networks may upregulate neuronal excitability in brain regions specific to the limb, in this study the right hand area. Second, movement phase-related networks, which modulate their synchrony in relation to the movement sequence. We suggest that these frequency-specific networks are associated with distinct functions, including top-down control, sensorimotor prediction, and integration. The separation of different large-scale networks, we applied in this work, improves the interpretation of EEG sources in relation to human motor behavior. EEG recordings provide high temporal resolution suitable to relate cortical oscillations to actual movements. Investigating EEG sources during rhythmic finger movements, we distinguish sustained from movement phase-related amplitude modulations. We separate these two EEG source elements motivated by our previous findings in gait. Here, we found two types of large-scale networks, representing the right fingers in distinction from the time sequence of the movements. These findings suggest that EEG source amplitudes reconstructed in a cortical patch are the superposition of these simultaneously present network activities. Separating these frequency-specific networks is relevant for studying function and possible dysfunction of the cortical sensorimotor system in humans as well as to provide more advanced features for brain-computer interfaces. Copyright © 2016 the authors 0270-6474/16/3611671-11$15.00/0.
Piros, Palma; Puskas, Szilvia; Emri, Miklos; Opposits, Gabor; Spisak, Tamas; Fekete, Istvan; Clemens, Bela
2014-03-01
Absence status (AS) epilepticus with generalized spike-wave pattern is frequently found in severely ill patients in whom several disease states co-exist. The cortical generators of the ictal EEG pattern and EEG functional connectivity (EEGfC) of this condition are unknown. The present study investigated the localization of the uppermost synchronized generators of spike-wave activity in AS. Seven patients with late-onset AS were investigated by EEG spectral analysis, LORETA (Low Resolution Electromagnetic Tomography) source imaging, and LSC (LORETA Source Correlation) analysis, which estimates cortico-cortical EEGfC among 23 ROIs (regions of interest) in each hemisphere. All the patients showed generalized ictal EEG activity. Maximum Z-scored spectral power was found in the 1-6 Hz and 12-14 Hz frequency bands. LORETA showed that the uppermost synchronized generators of 1-6 Hz band activity were localized in frontal and temporal cortical areas that are parts of the limbic system. For the 12-14 Hz band, abnormally synchronized generators were found in the antero-medial frontal cortex. Unlike the rather stereotyped spectral and LORETA findings, the individual EEGfC patterns were very dissimilar. The findings are discussed in the context of nonconvulsive seizure types and the role of the underlying cortical areas in late-onset AS. The diversity of the EEGfC patterns remains an enigma. Localizing the cortical generators of the EEG patterns contributes to understanding the neurophysiology of the condition. Copyright © 2013 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Shenoy Handiru, Vikram; Vinod, A. P.; Guan, Cuntai
2017-08-01
Objective. In electroencephalography (EEG)-based brain-computer interface (BCI) systems for motor control tasks the conventional practice is to decode motor intentions by using scalp EEG. However, scalp EEG only reveals certain limited information about the complex tasks of movement with a higher degree of freedom. Therefore, our objective is to investigate the effectiveness of source-space EEG in extracting relevant features that discriminate arm movement in multiple directions. Approach. We have proposed a novel feature extraction algorithm based on supervised factor analysis that models the data from source-space EEG. To this end, we computed the features from the source dipoles confined to Brodmann areas of interest (BA4a, BA4p and BA6). Further, we embedded class-wise labels of multi-direction (multi-class) source-space EEG to an unsupervised factor analysis to make it into a supervised learning method. Main Results. Our approach provided an average decoding accuracy of 71% for the classification of hand movement in four orthogonal directions, that is significantly higher (>10%) than the classification accuracy obtained using state-of-the-art spatial pattern features in sensor space. Also, the group analysis on the spectral characteristics of source-space EEG indicates that the slow cortical potentials from a set of cortical source dipoles reveal discriminative information regarding the movement parameter, direction. Significance. This study presents evidence that low-frequency components in the source space play an important role in movement kinematics, and thus it may lead to new strategies for BCI-based neurorehabilitation.
Heers, Marcel; Chowdhury, Rasheda A; Hedrich, Tanguy; Dubeau, François; Hall, Jeffery A; Lina, Jean-Marc; Grova, Christophe; Kobayashi, Eliane
2016-01-01
Distributed inverse solutions aim to realistically reconstruct the origin of interictal epileptic discharges (IEDs) from noninvasively recorded electroencephalography (EEG) and magnetoencephalography (MEG) signals. Our aim was to compare the performance of different distributed inverse solutions in localizing IEDs: coherent maximum entropy on the mean (cMEM), hierarchical Bayesian implementations of independent identically distributed sources (IID, minimum norm prior) and spatially coherent sources (COH, spatial smoothness prior). Source maxima (i.e., the vertex with the maximum source amplitude) of IEDs in 14 EEG and 19 MEG studies from 15 patients with focal epilepsy were analyzed. We visually compared their concordance with intracranial EEG (iEEG) based on 17 cortical regions of interest and their spatial dispersion around source maxima. Magnetic source imaging (MSI) maxima from cMEM were most often confirmed by iEEG (cMEM: 14/19, COH: 9/19, IID: 8/19 studies). COH electric source imaging (ESI) maxima co-localized best with iEEG (cMEM: 8/14, COH: 11/14, IID: 10/14 studies). In addition, cMEM was less spatially spread than COH and IID for ESI and MSI (p < 0.001 Bonferroni-corrected post hoc t test). Highest positive predictive values for cortical regions with IEDs in iEEG could be obtained with cMEM for MSI and with COH for ESI. Additional realistic EEG/MEG simulations confirmed our findings. Accurate spatially extended sources, as found in cMEM (ESI and MSI) and COH (ESI) are desirable for source imaging of IEDs because this might influence surgical decision. Our simulations suggest that COH and IID overestimate the spatial extent of the generators compared to cMEM.
Liao, Ke; Zhu, Min; Ding, Lei
2013-08-01
The present study investigated the use of transform sparseness of cortical current density on human brain surface to improve electroencephalography/magnetoencephalography (EEG/MEG) inverse solutions. Transform sparseness was assessed by evaluating compressibility of cortical current densities in transform domains. To do that, a structure compression method from computer graphics was first adopted to compress cortical surface structure, either regular or irregular, into hierarchical multi-resolution meshes. Then, a new face-based wavelet method based on generated multi-resolution meshes was proposed to compress current density functions defined on cortical surfaces. Twelve cortical surface models were built by three EEG/MEG softwares and their structural compressibility was evaluated and compared by the proposed method. Monte Carlo simulations were implemented to evaluate the performance of the proposed wavelet method in compressing various cortical current density distributions as compared to other two available vertex-based wavelet methods. The present results indicate that the face-based wavelet method can achieve higher transform sparseness than vertex-based wavelet methods. Furthermore, basis functions from the face-based wavelet method have lower coherence against typical EEG and MEG measurement systems than vertex-based wavelet methods. Both high transform sparseness and low coherent measurements suggest that the proposed face-based wavelet method can improve the performance of L1-norm regularized EEG/MEG inverse solutions, which was further demonstrated in simulations and experimental setups using MEG data. Thus, this new transform on complicated cortical structure is promising to significantly advance EEG/MEG inverse source imaging technologies. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Anwar, A R; Muthalib, M; Perrey, S; Galka, A; Granert, O; Wolff, S; Heute, U; Deuschl, G; Raethjen, J; Muthuraman, Muthuraman
2016-09-01
Recently, interest has been growing to understand the underlying dynamic directional relationship between simultaneously activated regions of the brain during motor task performance. Such directionality analysis (or effective connectivity analysis), based on non-invasive electrophysiological (electroencephalography-EEG) and hemodynamic (functional near infrared spectroscopy-fNIRS; and functional magnetic resonance imaging-fMRI) neuroimaging modalities can provide an estimate of the motor task-related information flow from one brain region to another. Since EEG, fNIRS and fMRI modalities achieve different spatial and temporal resolutions of motor-task related activation in the brain, the aim of this study was to determine the effective connectivity of cortico-cortical sensorimotor networks during finger movement tasks measured by each neuroimaging modality. Nine healthy subjects performed right hand finger movement tasks of different complexity (simple finger tapping-FT, simple finger sequence-SFS, and complex finger sequence-CFS). We focused our observations on three cortical regions of interest (ROIs), namely the contralateral sensorimotor cortex (SMC), the contralateral premotor cortex (PMC) and the contralateral dorsolateral prefrontal cortex (DLPFC). We estimated the effective connectivity between these ROIs using conditional Granger causality (GC) analysis determined from the time series signals measured by fMRI (blood oxygenation level-dependent-BOLD), fNIRS (oxygenated-O2Hb and deoxygenated-HHb hemoglobin), and EEG (scalp and source level analysis) neuroimaging modalities. The effective connectivity analysis showed significant bi-directional information flow between the SMC, PMC, and DLPFC as determined by the EEG (scalp and source), fMRI (BOLD) and fNIRS (O2Hb and HHb) modalities for all three motor tasks. However the source level EEG GC values were significantly greater than the other modalities. In addition, only the source level EEG showed a significantly greater forward than backward information flow between the ROIs. This simultaneous fMRI, fNIRS and EEG study has shown through independent GC analysis of the respective time series that a bi-directional effective connectivity occurs within a cortico-cortical sensorimotor network (SMC, PMC and DLPFC) during finger movement tasks.
Babiloni, Claudio; Pennica, Alfredo; Del Percio, Claudio; Noce, Giuseppe; Cordone, Susanna; Muratori, Chiara; Ferracuti, Stefano; Donato, Nicole; Di Campli, Francesco; Gianserra, Laura; Teti, Elisabetta; Aceti, Antonio; Soricelli, Andrea; Viscione, Magdalena; Limatola, Cristina; Andreoni, Massimo; Onorati, Paolo
2016-03-01
This study tested a simple statistical procedure to recognize single treatment-naïve HIV individuals having abnormal cortical sources of resting state delta (<4 Hz) and alpha (8-13 Hz) electroencephalographic (EEG) rhythms with reference to a control group of sex-, age-, and education-matched healthy individuals. Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values were expected to show worse cognitive status. Resting state eyes-closed EEG data were recorded in 82 treatment-naïve HIV (39.8 ys.±1.2 standard error mean, SE) and 59 age-matched cognitively healthy subjects (39 ys.±2.2 SE). Low-resolution brain electromagnetic tomography (LORETA) estimated delta and alpha sources in frontal, central, temporal, parietal, and occipital cortical regions. Ratio of the activity of parietal delta and high-frequency alpha sources (EEG marker) showed the maximum difference between the healthy and the treatment-naïve HIV group. Z-score of the EEG marker was statistically abnormal in 47.6% of treatment-naïve HIV individuals with reference to the healthy group (p<0.05). Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values exhibited lower mini mental state evaluation (MMSE) score, higher CD4 count, and lower viral load (p<0.05). This statistical procedure permitted for the first time to identify single treatment-naïve HIV individuals having abnormal EEG activity. This procedure might enrich the detection and monitoring of effects of HIV on brain function in single treatment-naïve HIV individuals. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Zerouali, Younes; Lina, Jean-Marc; Sekerovic, Zoran; Godbout, Jonathan; Dube, Jonathan; Jolicoeur, Pierre; Carrier, Julie
2014-01-01
Sleep spindles are a hallmark of NREM sleep. They result from a widespread thalamo-cortical loop and involve synchronous cortical networks that are still poorly understood. We investigated whether brain activity during spindles can be characterized by specific patterns of functional connectivity among cortical generators. For that purpose, we developed a wavelet-based approach aimed at imaging the synchronous oscillatory cortical networks from simultaneous MEG-EEG recordings. First, we detected spindles on the EEG and extracted the corresponding frequency-locked MEG activity under the form of an analytic ridge signal in the time-frequency plane (Zerouali et al., 2013). Secondly, we performed source reconstruction of the ridge signal within the Maximum Entropy on the Mean framework (Amblard et al., 2004), yielding a robust estimate of the cortical sources producing observed oscillations. Lastly, we quantified functional connectivity among cortical sources using phase-locking values. The main innovations of this methodology are (1) to reveal the dynamic behavior of functional networks resolved in the time-frequency plane and (2) to characterize functional connectivity among MEG sources through phase interactions. We showed, for the first time, that the switch from fast to slow oscillatory mode during sleep spindles is required for the emergence of specific patterns of connectivity. Moreover, we show that earlier synchrony during spindles was associated with mainly intra-hemispheric connectivity whereas later synchrony was associated with global long-range connectivity. We propose that our methodology can be a valuable tool for studying the connectivity underlying neural processes involving sleep spindles, such as memory, plasticity or aging. PMID:25389381
Recording human cortical population spikes non-invasively--An EEG tutorial.
Waterstraat, Gunnar; Fedele, Tommaso; Burghoff, Martin; Scheer, Hans-Jürgen; Curio, Gabriel
2015-07-30
Non-invasively recorded somatosensory high-frequency oscillations (sHFOs) evoked by electric nerve stimulation are markers of human cortical population spikes. Previously, their analysis was based on massive averaging of EEG responses. Advanced neurotechnology and optimized off-line analysis can enhance the signal-to-noise ratio of sHFOs, eventually enabling single-trial analysis. The rationale for developing dedicated low-noise EEG technology for sHFOs is unfolded. Detailed recording procedures and tailored analysis principles are explained step-by-step. Source codes in Matlab and Python are provided as supplementary material online. Combining synergistic hardware and analysis improvements, evoked sHFOs at around 600 Hz ('σ-bursts') can be studied in single-trials. Additionally, optimized spatial filters increase the signal-to-noise ratio of components at about 1 kHz ('κ-bursts') enabling their detection in non-invasive surface EEG. sHFOs offer a unique possibility to record evoked human cortical population spikes non-invasively. The experimental approaches and algorithms presented here enable also non-specialized EEG laboratories to combine measurements of conventional low-frequency EEG with the analysis of concomitant cortical population spike responses. Copyright © 2014 Elsevier B.V. All rights reserved.
Brainstorm: A User-Friendly Application for MEG/EEG Analysis
Tadel, François; Baillet, Sylvain; Mosher, John C.; Pantazis, Dimitrios; Leahy, Richard M.
2011-01-01
Brainstorm is a collaborative open-source application dedicated to magnetoencephalography (MEG) and electroencephalography (EEG) data visualization and processing, with an emphasis on cortical source estimation techniques and their integration with anatomical magnetic resonance imaging (MRI) data. The primary objective of the software is to connect MEG/EEG neuroscience investigators with both the best-established and cutting-edge methods through a simple and intuitive graphical user interface (GUI). PMID:21584256
Heers, Marcel; Hirschmann, Jan; Jacobs, Julia; Dümpelmann, Matthias; Butz, Markus; von Lehe, Marec; Elger, Christian E; Schnitzler, Alfons; Wellmer, Jörg
2014-09-01
Spike-based magnetoencephalography (MEG) source localization is an established method in the presurgical evaluation of epilepsy patients. Focal cortical dysplasias (FCDs) are associated with focal epileptic discharges of variable morphologies in the beta frequency band in addition to single epileptic spikes. Therefore, we investigated the potential diagnostic value of MEG-based localization of spike-independent beta band (12-30Hz) activity generated by epileptogenic lesions. Five patients with FCD IIB underwent MEG. In one patient, invasive EEG (iEEG) was recorded simultaneously with MEG. In two patients, iEEG succeeded MEG, and two patients had MEG only. MEG and iEEG were evaluated for epileptic spikes. Two minutes of iEEG data and MEG epochs with no spikes as well as MEG epochs with epileptic spikes were analyzed in the frequency domain. MEG oscillatory beta band activity was localized using Dynamic Imaging of Coherent Sources. Intralesional beta band activity was coherent between simultaneous MEG and iEEG recordings. Continuous 14Hz beta band power correlated with the rate of interictal epileptic discharges detected in iEEG. In cases where visual MEG evaluation revealed epileptic spikes, the sources of beta band activity localized within <2cm of the epileptogenic lesion as shown on magnetic resonance imaging. This result held even when visually marked epileptic spikes were deselected. When epileptic spikes were detectable in iEEG but not MEG, MEG beta band activity source localization failed. Source localization of beta band activity has the potential to contribute to the identification of epileptic foci in addition to source localization of visually marked epileptic spikes. Thus, this technique may assist in the localization of epileptic foci in patients with suspected FCD. Copyright © 2014 Elsevier B.V. All rights reserved.
EEGNET: An Open Source Tool for Analyzing and Visualizing M/EEG Connectome.
Hassan, Mahmoud; Shamas, Mohamad; Khalil, Mohamad; El Falou, Wassim; Wendling, Fabrice
2015-01-01
The brain is a large-scale complex network often referred to as the "connectome". Exploring the dynamic behavior of the connectome is a challenging issue as both excellent time and space resolution is required. In this context Magneto/Electroencephalography (M/EEG) are effective neuroimaging techniques allowing for analysis of the dynamics of functional brain networks at scalp level and/or at reconstructed sources. However, a tool that can cover all the processing steps of identifying brain networks from M/EEG data is still missing. In this paper, we report a novel software package, called EEGNET, running under MATLAB (Math works, inc), and allowing for analysis and visualization of functional brain networks from M/EEG recordings. EEGNET is developed to analyze networks either at the level of scalp electrodes or at the level of reconstructed cortical sources. It includes i) Basic steps in preprocessing M/EEG signals, ii) the solution of the inverse problem to localize / reconstruct the cortical sources, iii) the computation of functional connectivity among signals collected at surface electrodes or/and time courses of reconstructed sources and iv) the computation of the network measures based on graph theory analysis. EEGNET is the unique tool that combines the M/EEG functional connectivity analysis and the computation of network measures derived from the graph theory. The first version of EEGNET is easy to use, flexible and user friendly. EEGNET is an open source tool and can be freely downloaded from this webpage: https://sites.google.com/site/eegnetworks/.
EEGNET: An Open Source Tool for Analyzing and Visualizing M/EEG Connectome
Hassan, Mahmoud; Shamas, Mohamad; Khalil, Mohamad; El Falou, Wassim; Wendling, Fabrice
2015-01-01
The brain is a large-scale complex network often referred to as the “connectome”. Exploring the dynamic behavior of the connectome is a challenging issue as both excellent time and space resolution is required. In this context Magneto/Electroencephalography (M/EEG) are effective neuroimaging techniques allowing for analysis of the dynamics of functional brain networks at scalp level and/or at reconstructed sources. However, a tool that can cover all the processing steps of identifying brain networks from M/EEG data is still missing. In this paper, we report a novel software package, called EEGNET, running under MATLAB (Math works, inc), and allowing for analysis and visualization of functional brain networks from M/EEG recordings. EEGNET is developed to analyze networks either at the level of scalp electrodes or at the level of reconstructed cortical sources. It includes i) Basic steps in preprocessing M/EEG signals, ii) the solution of the inverse problem to localize / reconstruct the cortical sources, iii) the computation of functional connectivity among signals collected at surface electrodes or/and time courses of reconstructed sources and iv) the computation of the network measures based on graph theory analysis. EEGNET is the unique tool that combines the M/EEG functional connectivity analysis and the computation of network measures derived from the graph theory. The first version of EEGNET is easy to use, flexible and user friendly. EEGNET is an open source tool and can be freely downloaded from this webpage: https://sites.google.com/site/eegnetworks/. PMID:26379232
Functional connectivity analysis in EEG source space: The choice of method
Knyazeva, Maria G.
2017-01-01
Functional connectivity (FC) is among the most informative features derived from EEG. However, the most straightforward sensor-space analysis of FC is unreliable owing to volume conductance effects. An alternative—source-space analysis of FC—is optimal for high- and mid-density EEG (hdEEG, mdEEG); however, it is questionable for widely used low-density EEG (ldEEG) because of inadequate surface sampling. Here, using simulations, we investigate the performance of the two source FC methods, the inverse-based source FC (ISFC) and the cortical partial coherence (CPC). To examine the effects of localization errors of the inverse method on the FC estimation, we simulated an oscillatory source with varying locations and SNRs. To compare the FC estimations by the two methods, we simulated two synchronized sources with varying between-source distance and SNR. The simulations were implemented for hdEEG, mdEEG, and ldEEG. We showed that the performance of both methods deteriorates for deep sources owing to their inaccurate localization and smoothing. The accuracy of both methods improves with the increasing between-source distance. The best ISFC performance was achieved using hd/mdEEG, while the best CPC performance was observed with ldEEG. In conclusion, with hdEEG, ISFC outperforms CPC and therefore should be the preferred method. In the studies based on ldEEG, the CPC is a method of choice. PMID:28727750
Sleep affects cortical source modularity in temporal lobe epilepsy: A high-density EEG study.
Del Felice, Alessandra; Storti, Silvia Francesca; Manganotti, Paolo
2015-09-01
Interictal epileptiform discharges (IEDs) constitute a perturbation of ongoing cerebral rhythms, usually more frequent during sleep. The aim of the study was to determine whether sleep influences the spread of IEDs over the scalp and whether their distribution depends on vigilance-related modifications in cortical interactions. Wake and sleep 256-channel electroencephalography (EEG) data were recorded in 12 subjects with right temporal lobe epilepsy (TLE) differentiated by whether they had mesial or neocortical TLE. Spikes were selected during wake and sleep. The averaged waking signal was subtracted from the sleep signal and projected on a bidimensional scalp map; sleep and wake spike distributions were compared by using a t-test. The superimposed signal of sleep and wake traces was obtained; the rising phase of the spike, the peak, and the deflections following the spike were identified, and their cortical generator was calculated using low-resolution brain electromagnetic tomography (LORETA) for each group. A mean of 21 IEDs in wake and 39 in sleep per subject were selected. As compared to wake, a larger IED scalp projection was detected during sleep in both mesial and neocortical TLE (p<0.05). A series of EEG deflections followed the spike, the cortical sources of which displayed alternating activations of different cortical areas in wake, substituted by isolated, stationary activations in sleep in mesial TLE and a silencing in neocortical TLE. During sleep, the IED scalp region increases, while cortical interaction decreases. The interaction of cortical modules in sleep and wake in TLE may influence the appearance of IEDs on scalp EEG; in addition, IEDs could be proxies for cerebral oscillation perturbation. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Stenroos, Matti; Hauk, Olaf
2013-01-01
The conductivity profile of the head has a major effect on EEG signals, but unfortunately the conductivity for the most important compartment, skull, is only poorly known. In dipole modeling studies, errors in modeled skull conductivity have been considered to have a detrimental effect on EEG source estimation. However, as dipole models are very restrictive, those results cannot be generalized to other source estimation methods. In this work, we studied the sensitivity of EEG and combined MEG + EEG source estimation to errors in skull conductivity using a distributed source model and minimum-norm (MN) estimation. We used a MEG/EEG modeling set-up that reflected state-of-the-art practices of experimental research. Cortical surfaces were segmented and realistically-shaped three-layer anatomical head models were constructed, and forward models were built with Galerkin boundary element method while varying the skull conductivity. Lead-field topographies and MN spatial filter vectors were compared across conductivities, and the localization and spatial spread of the MN estimators were assessed using intuitive resolution metrics. The results showed that the MN estimator is robust against errors in skull conductivity: the conductivity had a moderate effect on amplitudes of lead fields and spatial filter vectors, but the effect on corresponding morphologies was small. The localization performance of the EEG or combined MEG + EEG MN estimator was only minimally affected by the conductivity error, while the spread of the estimate varied slightly. Thus, the uncertainty with respect to skull conductivity should not prevent researchers from applying minimum norm estimation to EEG or combined MEG + EEG data. Comparing our results to those obtained earlier with dipole models shows that general judgment on the performance of an imaging modality should not be based on analysis with one source estimation method only. PMID:23639259
Eytan, Danny; Pang, Elizabeth W; Doesburg, Sam M; Nenadovic, Vera; Gavrilovic, Bojan; Laussen, Peter; Guerguerian, Anne-Marie
2016-01-01
Acute brain injury is a common cause of death and critical illness in children and young adults. Fundamental management focuses on early characterization of the extent of injury and optimizing recovery by preventing secondary damage during the days following the primary injury. Currently, bedside technology for measuring neurological function is mainly limited to using electroencephalography (EEG) for detection of seizures and encephalopathic features, and evoked potentials. We present a proof of concept study in patients with acute brain injury in the intensive care setting, featuring a bedside functional imaging set-up designed to map cortical brain activation patterns by combining high density EEG recordings, multi-modal sensory stimulation (auditory, visual, and somatosensory), and EEG source modeling. Use of source-modeling allows for examination of spatiotemporal activation patterns at the cortical region level as opposed to the traditional scalp potential maps. The application of this system in both healthy and brain-injured participants is demonstrated with modality-specific source-reconstructed cortical activation patterns. By combining stimulation obtained with different modalities, most of the cortical surface can be monitored for changes in functional activation without having to physically transport the subject to an imaging suite. The results in patients in an intensive care setting with anatomically well-defined brain lesions suggest a topographic association between their injuries and activation patterns. Moreover, we report the reproducible application of a protocol examining a higher-level cortical processing with an auditory oddball paradigm involving presentation of the patient's own name. This study reports the first successful application of a bedside functional brain mapping tool in the intensive care setting. This application has the potential to provide clinicians with an additional dimension of information to manage critically-ill children and adults, and potentially patients not suited for magnetic resonance imaging technologies.
Reconstructing cortical current density by exploring sparseness in the transform domain
NASA Astrophysics Data System (ADS)
Ding, Lei
2009-05-01
In the present study, we have developed a novel electromagnetic source imaging approach to reconstruct extended cortical sources by means of cortical current density (CCD) modeling and a novel EEG imaging algorithm which explores sparseness in cortical source representations through the use of L1-norm in objective functions. The new sparse cortical current density (SCCD) imaging algorithm is unique since it reconstructs cortical sources by attaining sparseness in a transform domain (the variation map of cortical source distributions). While large variations are expected to occur along boundaries (sparseness) between active and inactive cortical regions, cortical sources can be reconstructed and their spatial extents can be estimated by locating these boundaries. We studied the SCCD algorithm using numerous simulations to investigate its capability in reconstructing cortical sources with different extents and in reconstructing multiple cortical sources with different extent contrasts. The SCCD algorithm was compared with two L2-norm solutions, i.e. weighted minimum norm estimate (wMNE) and cortical LORETA. Our simulation data from the comparison study show that the proposed sparse source imaging algorithm is able to accurately and efficiently recover extended cortical sources and is promising to provide high-accuracy estimation of cortical source extents.
Scalp and Source Power Topography in Sleepwalking and Sleep Terrors: A High-Density EEG Study
Castelnovo, Anna; Riedner, Brady A.; Smith, Richard F.; Tononi, Giulio; Boly, Melanie; Benca, Ruth M.
2016-01-01
Study Objectives: To examine scalp and source power topography in sleep arousals disorders (SADs) using high-density EEG (hdEEG). Methods: Fifteen adult subjects with sleep arousal disorders (SADs) and 15 age- and gender-matched good sleeping healthy controls were recorded in a sleep laboratory setting using a 256 channel EEG system. Results: Scalp EEG analysis of all night NREM sleep revealed a localized decrease in slow wave activity (SWA) power (1–4 Hz) over centro-parietal regions relative to the rest of the brain in SADs compared to good sleeping healthy controls. Source modelling analysis of 5-minute segments taken from N3 during the first half of the night revealed that the local decrease in SWA power was prominent at the level of the cingulate, motor, and sensori-motor associative cortices. Similar patterns were also evident during REM sleep and wake. These differences in local sleep were present in the absence of any detectable clinical or electrophysiological sign of arousal. Conclusions: Overall, results suggest the presence of local sleep differences in the brain of SADs patients during nights without clinical episodes. The persistence of similar topographical changes in local EEG power during REM sleep and wakefulness points to trait-like functional changes that cross the boundaries of NREM sleep. The regions identified by source imaging are consistent with the current neurophysiological understanding of SADs as a disorder caused by local arousals in motor and cingulate cortices. Persistent localized changes in neuronal excitability may predispose affected subjects to clinical episodes. Citation: Castelnovo A, Riedner BA, Smith RF, Tononi G, Boly M, Benca RM. Scalp and source power topography in sleepwalking and sleep terrors: a high-density EEG study. SLEEP 2016;39(10):1815–1825. PMID:27568805
Cosandier-Rimélé, D; Ramantani, G; Zentner, J; Schulze-Bonhage, A; Dümpelmann, M
2017-10-01
Electrical source localization (ESL) deriving from scalp EEG and, in recent years, from intracranial EEG (iEEG), is an established method in epilepsy surgery workup. We aimed to validate the distributed ESL derived from scalp EEG and iEEG, particularly regarding the spatial extent of the source, using a realistic epileptic spike activity simulator. ESL was applied to the averaged scalp EEG and iEEG spikes of two patients with drug-resistant structural epilepsy. The ESL results for both patients were used to outline the location and extent of epileptic cortical patches, which served as the basis for designing a spatiotemporal source model. EEG signals for both modalities were then generated for different anatomic locations and spatial extents. ESL was subsequently performed on simulated signals with sLORETA, a commonly used distributed algorithm. ESL accuracy was quantitatively assessed for iEEG and scalp EEG. The source volume was overestimated by sLORETA at both EEG scales, with the error increasing with source size, particularly for iEEG. For larger sources, ESL accuracy drastically decreased, and reconstruction volumes shifted to the center of the head for iEEG, while remaining stable for scalp EEG. Overall, the mislocalization of the reconstructed source was more pronounced for iEEG. We present a novel multiscale framework for the evaluation of distributed ESL, based on realistic multiscale EEG simulations. Our findings support that reconstruction results for scalp EEG are often more accurate than for iEEG, owing to the superior 3D coverage of the head. Particularly the iEEG-derived reconstruction results for larger, widespread generators should be treated with caution.
NASA Astrophysics Data System (ADS)
Cosandier-Rimélé, D.; Ramantani, G.; Zentner, J.; Schulze-Bonhage, A.; Dümpelmann, M.
2017-10-01
Objective. Electrical source localization (ESL) deriving from scalp EEG and, in recent years, from intracranial EEG (iEEG), is an established method in epilepsy surgery workup. We aimed to validate the distributed ESL derived from scalp EEG and iEEG, particularly regarding the spatial extent of the source, using a realistic epileptic spike activity simulator. Approach. ESL was applied to the averaged scalp EEG and iEEG spikes of two patients with drug-resistant structural epilepsy. The ESL results for both patients were used to outline the location and extent of epileptic cortical patches, which served as the basis for designing a spatiotemporal source model. EEG signals for both modalities were then generated for different anatomic locations and spatial extents. ESL was subsequently performed on simulated signals with sLORETA, a commonly used distributed algorithm. ESL accuracy was quantitatively assessed for iEEG and scalp EEG. Main results. The source volume was overestimated by sLORETA at both EEG scales, with the error increasing with source size, particularly for iEEG. For larger sources, ESL accuracy drastically decreased, and reconstruction volumes shifted to the center of the head for iEEG, while remaining stable for scalp EEG. Overall, the mislocalization of the reconstructed source was more pronounced for iEEG. Significance. We present a novel multiscale framework for the evaluation of distributed ESL, based on realistic multiscale EEG simulations. Our findings support that reconstruction results for scalp EEG are often more accurate than for iEEG, owing to the superior 3D coverage of the head. Particularly the iEEG-derived reconstruction results for larger, widespread generators should be treated with caution.
Electrocortical activity distinguishes between uphill and level walking in humans.
Bradford, J Cortney; Lukos, Jamie R; Ferris, Daniel P
2016-02-01
The objective of this study was to determine if electrocortical activity is different between walking on an incline compared with level surface. Subjects walked on a treadmill at 0% and 15% grades for 30 min while we recorded electroencephalography (EEG). We used independent component (IC) analysis to parse EEG signals into maximally independent sources and then computed dipole estimations for each IC. We clustered cortical source ICs and analyzed event-related spectral perturbations synchronized to gait events. Theta power fluctuated across the gait cycle for both conditions, but was greater during incline walking in the anterior cingulate, sensorimotor and posterior parietal clusters. We found greater gamma power during level walking in the left sensorimotor and anterior cingulate clusters. We also found distinct alpha and beta fluctuations, depending on the phase of the gait cycle for the left and right sensorimotor cortices, indicating cortical lateralization for both walking conditions. We validated the results by isolating movement artifact. We found that the frequency activation patterns of the artifact were different than the actual EEG data, providing evidence that the differences between walking conditions were cortically driven rather than a residual artifact of the experiment. These findings suggest that the locomotor pattern adjustments necessary to walk on an incline compared with level surface may require supraspinal input, especially from the left sensorimotor cortex, anterior cingulate, and posterior parietal areas. These results are a promising step toward the use of EEG as a feed-forward control signal for ambulatory brain-computer interface technologies.
Propofol Anesthesia and Sleep: A High-Density EEG Study
Murphy, Michael; Bruno, Marie-Aurelie; Riedner, Brady A.; Boveroux, Pierre; Noirhomme, Quentin; Landsness, Eric C.; Brichant, Jean-Francois; Phillips, Christophe; Massimini, Marcello; Laureys, Steven; Tononi, Giulio; Boly, Melanie
2011-01-01
Study Objectives: The electrophysiological correlates of anesthetic sedation remain poorly understood. We used high-density electroencephalography (hd-EEG) and source modeling to investigate the cortical processes underlying propofol anesthesia and compare them to sleep. Design: 256-channel EEG recordings in humans during propofol anesthesia. Setting: Hospital operating room. Patients or Participants: 8 healthy subjects (4 males) Interventions: N/A Measurements and Results: Initially, propofol induced increases in EEG power from 12–25 Hz. Loss of consciousness (LOC) was accompanied by the appearance of EEG slow waves that resembled the slow waves of NREM sleep. We compared slow waves in propofol to slow waves recorded during natural sleep and found that both populations of waves share similar cortical origins and preferentially propagate along the mesial components of the default network. However, propofol slow waves were spatially blurred compared to sleep slow waves and failed to effectively entrain spindle activity. Propofol also caused an increase in gamma (25–40 Hz) power that persisted throughout LOC. Source modeling analysis showed that this increase in gamma power originated from the anterior and posterior cingulate cortices. During LOC, we found increased gamma functional connectivity between these regions compared to the wakefulness. Conclusions: Propofol anesthesia is a sleep-like state and slow waves are associated with diminished consciousness even in the presence of high gamma activity. Citation: Murphy M; Bruno MA; Riedner BA; Boveroux P; Noirhomme Q; Landsness EC; Brichant JF; Phillips C; Massimini M; Laureys S; Tononi G; Boly M. Propofol anesthesia and sleep: a high-density EEG study. SLEEP 2011;34(3):283-291. PMID:21358845
Wang, Sheng H; Lobier, Muriel; Siebenhühner, Felix; Puoliväli, Tuomas; Palva, Satu; Palva, J Matias
2018-06-01
Inter-areal functional connectivity (FC), neuronal synchronization in particular, is thought to constitute a key systems-level mechanism for coordination of neuronal processing and communication between brain regions. Evidence to support this hypothesis has been gained largely using invasive electrophysiological approaches. In humans, neuronal activity can be non-invasively recorded only with magneto- and electroencephalography (MEG/EEG), which have been used to assess FC networks with high temporal resolution and whole-scalp coverage. However, even in source-reconstructed MEG/EEG data, signal mixing, or "source leakage", is a significant confounder for FC analyses and network localization. Signal mixing leads to two distinct kinds of false-positive observations: artificial interactions (AI) caused directly by mixing and spurious interactions (SI) arising indirectly from the spread of signals from true interacting sources to nearby false loci. To date, several interaction metrics have been developed to solve the AI problem, but the SI problem has remained largely intractable in MEG/EEG all-to-all source connectivity studies. Here, we advance a novel approach for correcting SIs in FC analyses using source-reconstructed MEG/EEG data. Our approach is to bundle observed FC connections into hyperedges by their adjacency in signal mixing. Using realistic simulations, we show here that bundling yields hyperedges with good separability of true positives and little loss in the true positive rate. Hyperedge bundling thus significantly decreases graph noise by minimizing the false-positive to true-positive ratio. Finally, we demonstrate the advantage of edge bundling in the visualization of large-scale cortical networks with real MEG data. We propose that hypergraphs yielded by bundling represent well the set of true cortical interactions that are detectable and dissociable in MEG/EEG connectivity analysis. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Cortical localization of phase and amplitude dynamics predicting access to somatosensory awareness.
Hirvonen, Jonni; Palva, Satu
2016-01-01
Neural dynamics leading to conscious sensory perception have remained enigmatic in despite of large interest. Human functional magnetic resonance imaging (fMRI) studies have revealed that a co-activation of sensory and frontoparietal areas is crucial for conscious sensory perception in the several second time-scale of BOLD signal fluctuations. Electrophysiological recordings with magneto- and electroencephalography (MEG and EEG) and intracranial EEG (iEEG) have shown that event related responses (ERs), phase-locking of neuronal activity, and oscillation amplitude modulations in sub-second timescales are greater for consciously perceived than for unperceived stimuli. The cortical sources of ER and oscillation dynamics predicting the conscious perception have, however, remained unclear because these prior studies have utilized MEG/EEG sensor-level analyses or iEEG with limited neuroanatomical coverage. We used a somatosensory detection task, magnetoencephalography (MEG), and cortically constrained source reconstruction to identify the cortical areas where ERs, local poststimulus amplitudes and phase-locking of neuronal activity are predictive of the conscious access of somatosensory information. We show here that strengthened ERs, phase-locking to stimulus onset (SL), and induced oscillations amplitude modulations all predicted conscious somatosensory perception, but the most robust and widespread of these was SL that was sustained in low-alpha (6-10 Hz) band. The strength of SL and to a lesser extent that of ER predicted conscious perception in the somatosensory, lateral and medial frontal, posterior parietal, and in the cingulate cortex. These data suggest that a rapid phase-reorganization and concurrent oscillation amplitude modulations in these areas play an instrumental role in the emergence of a conscious percept. © 2015 Wiley Periodicals, Inc.
Kim, Kyungsoo; Punte, Andrea Kleine; Mertens, Griet; Van de Heyning, Paul; Park, Kyung-Joon; Choi, Hongsoo; Choi, Ji-Woong; Song, Jae-Jin
2015-11-30
Quantitative electroencephalography (qEEG) is effective when used to analyze ongoing cortical oscillations in cochlear implant (CI) users. However, localization of cortical activity in such users via qEEG is confounded by the presence of artifacts produced by the device itself. Typically, independent component analysis (ICA) is used to remove CI artifacts in auditory evoked EEG signals collected upon brief stimulation and it is effective for auditory evoked potentials (AEPs). However, AEPs do not reflect the daily environments of patients, and thus, continuous EEG data that are closer to such environments are desirable. In this case, device-related artifacts in EEG data are difficult to remove selectively via ICA due to over-completion of EEG data removal in the absence of preprocessing. EEGs were recorded for a long time under conditions of continuous auditory stimulation. To obviate the over-completion problem, we limited the frequency of CI artifacts to a significant characteristic peak and apply ICA artifact removal. Topographic brain mapping results analyzed via band-limited (BL)-ICA exhibited a better energy distribution, matched to the CI location, than data obtained using conventional ICA. Also, source localization data verified that BL-ICA effectively removed CI artifacts. The proposed method selectively removes CI artifacts from continuous EEG recordings, while ICA removal method shows residual peak and removes important brain activity signals. CI artifacts in EEG data obtained during continuous passive listening can be effectively removed with the aid of BL-ICA, opening up new EEG research possibilities in subjects with CIs. Copyright © 2015 Elsevier B.V. All rights reserved.
A transition in brain state during propofol-induced unconsciousness.
Mukamel, Eran A; Pirondini, Elvira; Babadi, Behtash; Wong, Kin Foon Kevin; Pierce, Eric T; Harrell, P Grace; Walsh, John L; Salazar-Gomez, Andres F; Cash, Sydney S; Eskandar, Emad N; Weiner, Veronica S; Brown, Emery N; Purdon, Patrick L
2014-01-15
Rhythmic oscillations shape cortical dynamics during active behavior, sleep, and general anesthesia. Cross-frequency phase-amplitude coupling is a prominent feature of cortical oscillations, but its role in organizing conscious and unconscious brain states is poorly understood. Using high-density EEG and intracranial electrocorticography during gradual induction of propofol general anesthesia in humans, we discovered a rapid drug-induced transition between distinct states with opposite phase-amplitude coupling and different cortical source distributions. One state occurs during unconsciousness and may be similar to sleep slow oscillations. A second state occurs at the loss or recovery of consciousness and resembles an enhanced slow cortical potential. These results provide objective electrophysiological landmarks of distinct unconscious brain states, and could be used to help improve EEG-based monitoring for general anesthesia.
Scalp and Source Power Topography in Sleepwalking and Sleep Terrors: A High-Density EEG Study.
Castelnovo, Anna; Riedner, Brady A; Smith, Richard F; Tononi, Giulio; Boly, Melanie; Benca, Ruth M
2016-10-01
To examine scalp and source power topography in sleep arousals disorders (SADs) using high-density EEG (hdEEG). Fifteen adult subjects with sleep arousal disorders (SADs) and 15 age- and gender-matched good sleeping healthy controls were recorded in a sleep laboratory setting using a 256 channel EEG system. Scalp EEG analysis of all night NREM sleep revealed a localized decrease in slow wave activity (SWA) power (1-4 Hz) over centro-parietal regions relative to the rest of the brain in SADs compared to good sleeping healthy controls. Source modelling analysis of 5-minute segments taken from N3 during the first half of the night revealed that the local decrease in SWA power was prominent at the level of the cingulate, motor, and sensori-motor associative cortices. Similar patterns were also evident during REM sleep and wake. These differences in local sleep were present in the absence of any detectable clinical or electrophysiological sign of arousal. Overall, results suggest the presence of local sleep differences in the brain of SADs patients during nights without clinical episodes. The persistence of similar topographical changes in local EEG power during REM sleep and wakefulness points to trait-like functional changes that cross the boundaries of NREM sleep. The regions identified by source imaging are consistent with the current neurophysiological understanding of SADs as a disorder caused by local arousals in motor and cingulate cortices. Persistent localized changes in neuronal excitability may predispose affected subjects to clinical episodes. © 2016 Associated Professional Sleep Societies, LLC.
Courellis, Hristos; Mullen, Tim; Poizner, Howard; Cauwenberghs, Gert; Iversen, John R.
2017-01-01
Quantification of dynamic causal interactions among brain regions constitutes an important component of conducting research and developing applications in experimental and translational neuroscience. Furthermore, cortical networks with dynamic causal connectivity in brain-computer interface (BCI) applications offer a more comprehensive view of brain states implicated in behavior than do individual brain regions. However, models of cortical network dynamics are difficult to generalize across subjects because current electroencephalography (EEG) signal analysis techniques are limited in their ability to reliably localize sources across subjects. We propose an algorithmic and computational framework for identifying cortical networks across subjects in which dynamic causal connectivity is modeled among user-selected cortical regions of interest (ROIs). We demonstrate the strength of the proposed framework using a “reach/saccade to spatial target” cognitive task performed by 10 right-handed individuals. Modeling of causal cortical interactions was accomplished through measurement of cortical activity using (EEG), application of independent component clustering to identify cortical ROIs as network nodes, estimation of cortical current density using cortically constrained low resolution electromagnetic brain tomography (cLORETA), multivariate autoregressive (MVAR) modeling of representative cortical activity signals from each ROI, and quantification of the dynamic causal interaction among the identified ROIs using the Short-time direct Directed Transfer function (SdDTF). The resulting cortical network and the computed causal dynamics among its nodes exhibited physiologically plausible behavior, consistent with past results reported in the literature. This physiological plausibility of the results strengthens the framework's applicability in reliably capturing complex brain functionality, which is required by applications, such as diagnostics and BCI. PMID:28566997
Boutin, Arnaud; Pinsard, Basile; Boré, Arnaud; Carrier, Julie; Fogel, Stuart M; Doyon, Julien
2018-04-01
Sleep benefits motor memory consolidation. This mnemonic process is thought to be mediated by thalamo-cortical spindle activity during NREM-stage2 sleep episodes as well as changes in striatal and hippocampal activity. However, direct experimental evidence supporting the contribution of such sleep-dependent physiological mechanisms to motor memory consolidation in humans is lacking. In the present study, we combined EEG and fMRI sleep recordings following practice of a motor sequence learning (MSL) task to determine whether spindle oscillations support sleep-dependent motor memory consolidation by transiently synchronizing and coordinating specialized cortical and subcortical networks. To that end, we conducted EEG source reconstruction on spindle epochs in both cortical and subcortical regions using novel deep-source localization techniques. Coherence-based metrics were adopted to estimate functional connectivity between cortical and subcortical structures over specific frequency bands. Our findings not only confirm the critical and functional role of NREM-stage2 sleep spindles in motor skill consolidation, but provide first-time evidence that spindle oscillations [11-17 Hz] may be involved in sleep-dependent motor memory consolidation by locally reactivating and functionally binding specific task-relevant cortical and subcortical regions within networks including the hippocampus, putamen, thalamus and motor-related cortical regions. Copyright © 2018 Elsevier Inc. All rights reserved.
Vecchio, Fabrizio; Miraglia, Francesca; Bramanti, Placido; Rossini, Paolo Maria
2014-01-01
Modern analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity. To test the hypothesis that aging processes modulate the brain connectivity network, EEG recording was conducted on 113 healthy volunteers. They were divided into three groups in accordance with their ages: 36 Young (15-45 years), 46 Adult (50-70 years), and 31 Elderly (>70 years). To evaluate the stability of the investigated parameters, a subgroup of 10 subjects underwent a second EEG recording two weeks later. Graph theory functions were applied to the undirected and weighted networks obtained by the lagged linear coherence evaluated by eLORETA on cortical sources. EEG frequency bands of interest were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). The spectral connectivity analysis of cortical sources showed that the normalized Characteristic Path Length (λ) presented the pattern Young > Adult>Elderly in the higher alpha band. Elderly also showed a greater increase in delta and theta bands than Young. The correlation between age and λ showed that higher ages corresponded to higher λ in delta and theta and lower in the alpha2 band; this pattern reflects the age-related modulation of higher (alpha) and decreased (delta) connectivity. The Normalized Clustering coefficient (γ) and small-world network modeling (σ) showed non-significant age-modulation. Evidence from the present study suggests that graph theory can aid in the analysis of connectivity patterns estimated from EEG and can facilitate the study of the physiological and pathological brain aging features of functional connectivity networks.
Multiple sparse volumetric priors for distributed EEG source reconstruction.
Strobbe, Gregor; van Mierlo, Pieter; De Vos, Maarten; Mijović, Bogdan; Hallez, Hans; Van Huffel, Sabine; López, José David; Vandenberghe, Stefaan
2014-10-15
We revisit the multiple sparse priors (MSP) algorithm implemented in the statistical parametric mapping software (SPM) for distributed EEG source reconstruction (Friston et al., 2008). In the present implementation, multiple cortical patches are introduced as source priors based on a dipole source space restricted to a cortical surface mesh. In this note, we present a technique to construct volumetric cortical regions to introduce as source priors by restricting the dipole source space to a segmented gray matter layer and using a region growing approach. This extension allows to reconstruct brain structures besides the cortical surface and facilitates the use of more realistic volumetric head models including more layers, such as cerebrospinal fluid (CSF), compared to the standard 3-layered scalp-skull-brain head models. We illustrated the technique with ERP data and anatomical MR images in 12 subjects. Based on the segmented gray matter for each of the subjects, cortical regions were created and introduced as source priors for MSP-inversion assuming two types of head models. The standard 3-layered scalp-skull-brain head models and extended 4-layered head models including CSF. We compared these models with the current implementation by assessing the free energy corresponding with each of the reconstructions using Bayesian model selection for group studies. Strong evidence was found in favor of the volumetric MSP approach compared to the MSP approach based on cortical patches for both types of head models. Overall, the strongest evidence was found in favor of the volumetric MSP reconstructions based on the extended head models including CSF. These results were verified by comparing the reconstructed activity. The use of volumetric cortical regions as source priors is a useful complement to the present implementation as it allows to introduce more complex head models and volumetric source priors in future studies. Copyright © 2014 Elsevier Inc. All rights reserved.
Independent EEG Sources Are Dipolar
Delorme, Arnaud; Palmer, Jason; Onton, Julie; Oostenveld, Robert; Makeig, Scott
2012-01-01
Independent component analysis (ICA) and blind source separation (BSS) methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG) and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI) in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR) effected by each decomposition, and decomposition ‘dipolarity’ defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA); best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison). PMID:22355308
2010-01-01
Background The physiopathological mechanism underlying the tinnitus phenomenon is still the subject of an ongoing debate. Since oscillatory EEG activity is increasingly recognized as a fundamental hallmark of cortical integrative functions, this study investigates deviations from the norm of different resting EEG parameters in patients suffering from chronic tinnitus. Results Spectral parameters of resting EEG of male tinnitus patients (n = 8, mean age 54 years) were compared to those of age-matched healthy males (n = 15, mean age 58.8 years). On average, the patient group exhibited higher spectral power over the frequency range of 2-100 Hz. Using LORETA source analysis, the generators of delta, theta, alpha and beta power increases were localized dominantly to left auditory (Brodmann Areas (BA) 41,42, 22), temporo-parietal, insular posterior, cingulate anterior and parahippocampal cortical areas. Conclusions Tinnitus patients show a deviation from the norm of different resting EEG parameters, characterized by an overproduction of resting state delta, theta and beta brain activities, providing further support for the microphysiological and magnetoencephalographic evidence pointing to a thalamocortical dysrhythmic process at the source of tinnitus. These results also provide further confirmation that reciprocal involvements of both auditory and associative/paralimbic areas are essential in the generation of tinnitus. PMID:20334674
[Magnetoencephalography in the presurgical evaluation of patients with drug-resistant epilepsy].
Koptelova, A M; Arkhipova, N A; Golovteev, A L; Chadaev, V A; Grinenko, O A; Kozlova, A B; Novikova, S I; Stepanenko, A Iu; Melikian, A G; Stroganova, T A
2013-01-01
Magnetoencephalography (MEG) in combination with structural MRI (magnetic source imaging, MSI) plays an increasingly important role as one of the tools for presurgical evaluation of medically intractable focal epilepsy. The aim of the study was to compare the MSI and commonly used video EEG monitoring method (vEEG) in their sensitivity to interictal epileptic discharges (IED) in 22 patients with drug resistant epilepsy. Furthermore, the detection and localization results obtained by both methods were verified using the data of electrocorticography (ECoG) and postsurgical outcome in 13 patients who underwent invasive EEG monitoring and surgery. The results showed that MSI was superior to vEEC in terms of sensitivity to IED with difference in sensitivity of 22%. The data also suggested that MSI superiority to vEEG in detecting epileptic discharges might, at least partly, arise from better MEG responsiveness to epileptic events coming from the medial, opercular and basal aspects of cortical lobes. MSI localization estimates were in the same cortical lobe and at the same lobar aspects as the epileptic foci detected by ECoG in all patients. Thus, magnetic source imaging can provide critical localization information that is not available when other noninvasive methods, such as vEEG and MRI, are used.
Ahlfors, Seppo P.; Jones, Stephanie R.; Ahveninen, Jyrki; Hämäläinen, Matti S.; Belliveau, John W.; Bar, Moshe
2014-01-01
Identifying inter-area communication in terms of the hierarchical organization of functional brain areas is of considerable interest in human neuroimaging. Previous studies have suggested that the direction of magneto- and electroencephalography (MEG, EEG) source currents depends on the layer-specific input patterns into a cortical area. We examined the direction in MEG source currents in a visual object recognition experiment in which there were specific expectations of activation in the fusiform region being driven by either feedforward or feedback inputs. The source for the early non-specific visual evoked response, presumably corresponding to feedforward driven activity, pointed outward, i.e., away from the white matter. In contrast, the source for the later, object-recognition related signals, expected to be driven by feedback inputs, pointed inward, toward the white matter. Associating specific features of the MEG/EEG source waveforms to feedforward and feedback inputs could provide unique information about the activation patterns within hierarchically organized cortical areas. PMID:25445356
Govindan, R B; Kota, Srinivas; Al-Shargabi, Tareq; Massaro, An N; Chang, Taeun; du Plessis, Adre
2016-09-01
Electroencephalogram (EEG) signals are often contaminated by the electrocardiogram (ECG) interference, which affects quantitative characterization of EEG. We propose null-coherence, a frequency-based approach, to attenuate the ECG interference in EEG using simultaneously recorded ECG as a reference signal. After validating the proposed approach using numerically simulated data, we apply this approach to EEG recorded from six newborns receiving therapeutic hypothermia for neonatal encephalopathy. We compare our approach with an independent component analysis (ICA), a previously proposed approach to attenuate ECG artifacts in the EEG signal. The power spectrum and the cortico-cortical connectivity of the ECG attenuated EEG was compared against the power spectrum and the cortico-cortical connectivity of the raw EEG. The null-coherence approach attenuated the ECG contamination without leaving any residual of the ECG in the EEG. We show that the null-coherence approach performs better than ICA in attenuating the ECG contamination without enhancing cortico-cortical connectivity. Our analysis suggests that using ICA to remove ECG contamination from the EEG suffers from redistribution problems, whereas the null-coherence approach does not. We show that both the null-coherence and ICA approaches attenuate the ECG contamination. However, the EEG obtained after ICA cleaning displayed higher cortico-cortical connectivity compared with that obtained using the null-coherence approach. This suggests that null-coherence is superior to ICA in attenuating the ECG interference in EEG for cortico-cortical connectivity analysis. Copyright © 2016 Elsevier B.V. All rights reserved.
EEG functional connectivity is partially predicted by underlying white matter connectivity
Chu, CJ; Tanaka, N; Diaz, J; Edlow, BL; Wu, O; Hämäläinen, M; Stufflebeam, S; Cash, SS; Kramer, MA.
2015-01-01
Over the past decade, networks have become a leading model to illustrate both the anatomical relationships (structural networks) and the coupling of dynamic physiology (functional networks) linking separate brain regions. The relationship between these two levels of description remains incompletely understood and an area of intense research interest. In particular, it is unclear how cortical currents relate to underlying brain structural architecture. In addition, although theory suggests that brain communication is highly frequency dependent, how structural connections influence overlying functional connectivity in different frequency bands has not been previously explored. Here we relate functional networks inferred from statistical associations between source imaging of EEG activity and underlying cortico-cortical structural brain connectivity determined by probabilistic white matter tractography. We evaluate spontaneous fluctuating cortical brain activity over a long time scale (minutes) and relate inferred functional networks to underlying structural connectivity for broadband signals, as well as in seven distinct frequency bands. We find that cortical networks derived from source EEG estimates partially reflect both direct and indirect underlying white matter connectivity in all frequency bands evaluated. In addition, we find that when structural support is absent, functional connectivity is significantly reduced for high frequency bands compared to low frequency bands. The association between cortical currents and underlying white matter connectivity highlights the obligatory interdependence of functional and structural networks in the human brain. The increased dependence on structural support for the coupling of higher frequency brain rhythms provides new evidence for how underlying anatomy directly shapes emergent brain dynamics at fast time scales. PMID:25534110
EEG and MEG: sensitivity to epileptic spike activity as function of source orientation and depth.
Hunold, A; Funke, M E; Eichardt, R; Stenroos, M; Haueisen, J
2016-07-01
Simultaneous electroencephalography (EEG) and magnetoencephalography (MEG) recordings of neuronal activity from epileptic patients reveal situations in which either EEG or MEG or both modalities show visible interictal spikes. While different signal-to-noise ratios (SNRs) of the spikes in EEG and MEG have been reported, a quantitative relation of spike source orientation and depth as well as the background brain activity to the SNR has not been established. We investigated this quantitative relationship for both dipole and patch sources in an anatomically realistic cortex model. Altogether, 5600 dipole and 3300 patch sources were distributed on the segmented cortical surfaces of two volunteers. The sources were classified according to their quantified depths and orientations, ranging from 20 mm to 60 mm below the skin surface and radial and tangential, respectively. The source time-courses mimicked an interictal spike, and the simulated background activity emulated resting activity. Simulations were conducted with individual three-compartment boundary element models. The SNR was evaluated for 128 EEG, 102 MEG magnetometer, and 204 MEG gradiometer channels. For superficial dipole and superficial patch sources, EEG showed higher SNRs for dominantly radial orientations, and MEG showed higher values for dominantly tangential orientations. Gradiometers provided higher SNR than magnetometers for superficial sources, particularly for those with dominantly tangential orientations. The orientation dependent difference in SNR in EEG and MEG gradually changed as the sources were located deeper, where the interictal spikes generated higher SNRs in EEG compared to those in MEG for all source orientations. With deep sources, the SNRs in gradiometers and magnetometers were of the same order. To better detect spikes, both EEG and MEG should be used.
Localization of synchronous cortical neural sources.
Zerouali, Younes; Herry, Christophe L; Jemel, Boutheina; Lina, Jean-Marc
2013-03-01
Neural synchronization is a key mechanism to a wide variety of brain functions, such as cognition, perception, or memory. High temporal resolution achieved by EEG recordings allows the study of the dynamical properties of synchronous patterns of activity at a very fine temporal scale but with very low spatial resolution. Spatial resolution can be improved by retrieving the neural sources of EEG signal, thus solving the so-called inverse problem. Although many methods have been proposed to solve the inverse problem and localize brain activity, few of them target the synchronous brain regions. In this paper, we propose a novel algorithm aimed at localizing specifically synchronous brain regions and reconstructing the time course of their activity. Using multivariate wavelet ridge analysis, we extract signals capturing the synchronous events buried in the EEG and then solve the inverse problem on these signals. Using simulated data, we compare results of source reconstruction accuracy achieved by our method to a standard source reconstruction approach. We show that the proposed method performs better across a wide range of noise levels and source configurations. In addition, we applied our method on real dataset and identified successfully cortical areas involved in the functional network underlying visual face perception. We conclude that the proposed approach allows an accurate localization of synchronous brain regions and a robust estimation of their activity.
Mejia Tobar, Alejandra; Hyoudou, Rikiya; Kita, Kahori; Nakamura, Tatsuhiro; Kambara, Hiroyuki; Ogata, Yousuke; Hanakawa, Takashi; Koike, Yasuharu; Yoshimura, Natsue
2017-01-01
The classification of ankle movements from non-invasive brain recordings can be applied to a brain-computer interface (BCI) to control exoskeletons, prosthesis, and functional electrical stimulators for the benefit of patients with walking impairments. In this research, ankle flexion and extension tasks at two force levels in both legs, were classified from cortical current sources estimated by a hierarchical variational Bayesian method, using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings. The hierarchical prior for the current source estimation from EEG was obtained from activated brain areas and their intensities from an fMRI group (second-level) analysis. The fMRI group analysis was performed on regions of interest defined over the primary motor cortex, the supplementary motor area, and the somatosensory area, which are well-known to contribute to movement control. A sparse logistic regression method was applied for a nine-class classification (eight active tasks and a resting control task) obtaining a mean accuracy of 65.64% for time series of current sources, estimated from the EEG and the fMRI signals using a variational Bayesian method, and a mean accuracy of 22.19% for the classification of the pre-processed of EEG sensor signals, with a chance level of 11.11%. The higher classification accuracy of current sources, when compared to EEG classification accuracy, was attributed to the high number of sources and the different signal patterns obtained in the same vertex for different motor tasks. Since the inverse filter estimation for current sources can be done offline with the present method, the present method is applicable to real-time BCIs. Finally, due to the highly enhanced spatial distribution of current sources over the brain cortex, this method has the potential to identify activation patterns to design BCIs for the control of an affected limb in patients with stroke, or BCIs from motor imagery in patients with spinal cord injury.
Feng, Zhou-yan; Zheng, Xiao-xiang
2002-08-01
Objective. To study the complexity and the power spectrum of cortical EEG and hippocampal potential in rats under waking and sleep states. Method. Cortical EEG and hippocampal potential were collected by implanted electrodes in freely moving rats. Algorithmic complexity (Kc), approximate entropy (ApEn), power spectral density (PSD) and gravity frequency of PSD of the potential waves were calculated. Result. The complexity of hippocampal potential was higher than that of cortical EEG under every state. The complexity of cortical EEG was lowest under the state of non rapid eye movement (NREM) sleep. The complexity of hippocampal potential was highest under waking state. The total power of both potentials in 0.5- 30 Hz frequency band showed their highest values under NREM state. Conclusion. The values of Kc and ApEn are closely related to the distributions of PSD. When there are evident peaks in PSD, the complexities of signals will decrease. The complexities may be used to distinguish the difference between cortical EEG and hippocampal potential, or large differences between the same kind of potentials under different behavioral states.
Diffusion spectral imaging modules correlate with EEG LORETA neuroimaging modules.
Thatcher, Robert W; North, Duane M; Biver, Carl J
2012-05-01
The purpose of this study was to test the hypothesis that the highest temporal correlations between 3-dimensional EEG current source density corresponds to anatomical Modules of high synaptic connectivity. Eyes closed and eyes open EEG was recorded from 19 scalp locations with a linked ears reference from 71 subjects age 13-42 years. LORETA was computed from 1 to 30 Hz in 2,394 cortical gray matter voxels that were grouped into six anatomical Modules corresponding to the ROIs in the Hagmann et al.'s [2008] diffusion spectral imaging (DSI) study. All possible cross-correlations between voxels within a DSI Module were compared with the correlations between Modules. The Hagmann et al. [ 2008] Module correlation structure was replicated in the correlation structure of EEG three-dimensional current source density. EEG Temporal correlation between brain regions is related to synaptic density as measured by diffusion spectral imaging. Copyright © 2011 Wiley-Liss, Inc.
Oosugi, Naoya; Kitajo, Keiichi; Hasegawa, Naomi; Nagasaka, Yasuo; Okanoya, Kazuo; Fujii, Naotaka
2017-09-01
Blind source separation (BSS) algorithms extract neural signals from electroencephalography (EEG) data. However, it is difficult to quantify source separation performance because there is no criterion to dissociate neural signals and noise in EEG signals. This study develops a method for evaluating BSS performance. The idea is neural signals in EEG can be estimated by comparison with simultaneously measured electrocorticography (ECoG). Because the ECoG electrodes cover the majority of the lateral cortical surface and should capture most of the original neural sources in the EEG signals. We measured real EEG and ECoG data and developed an algorithm for evaluating BSS performance. First, EEG signals are separated into EEG components using the BSS algorithm. Second, the EEG components are ranked using the correlation coefficients of the ECoG regression and the components are grouped into subsets based on their ranks. Third, canonical correlation analysis estimates how much information is shared between the subsets of the EEG components and the ECoG signals. We used our algorithm to compare the performance of BSS algorithms (PCA, AMUSE, SOBI, JADE, fastICA) via the EEG and ECoG data of anesthetized nonhuman primates. The results (Best case >JADE = fastICA >AMUSE = SOBI ≥ PCA >random separation) were common to the two subjects. To encourage the further development of better BSS algorithms, our EEG and ECoG data are available on our Web site (http://neurotycho.org/) as a common testing platform. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Bulea, Thomas C.; Kim, Jonghyun; Damiano, Diane L.; Stanley, Christopher J.; Park, Hyung-Soon
2015-01-01
Accumulating evidence suggests cortical circuits may contribute to control of human locomotion. Here, noninvasive electroencephalography (EEG) recorded from able-bodied volunteers during a novel treadmill walking paradigm was used to assess neural correlates of walking. A systematic processing method, including a recently developed subspace reconstruction algorithm, reduced movement-related EEG artifact prior to independent component analysis and dipole source localization. We quantified cortical activity while participants tracked slow and fast target speeds across two treadmill conditions: an active mode that adjusted belt speed based on user movements and a passive mode reflecting a typical treadmill. Our results reveal frequency specific, multi-focal task related changes in cortical oscillations elicited by active walking. Low γ band power, localized to the prefrontal and posterior parietal cortices, was significantly increased during double support and early swing phases, critical points in the gait cycle since the active controller adjusted speed based on pelvis position and swing foot velocity. These phasic γ band synchronizations provide evidence that prefrontal and posterior parietal networks, previously implicated in visuo-spatial and somotosensory integration, are engaged to enhance lower limb control during gait. Sustained μ and β band desynchronization within sensorimotor cortex, a neural correlate for movement, was observed during walking thereby validating our methods for isolating cortical activity. Our results also demonstrate the utility of EEG recorded during locomotion for probing the multi-regional cortical networks which underpin its execution. For example, the cortical network engagement elicited by the active treadmill suggests that it may enhance neuroplasticity for more effective motor training. PMID:26029077
High-resolution EEG techniques for brain-computer interface applications.
Cincotti, Febo; Mattia, Donatella; Aloise, Fabio; Bufalari, Simona; Astolfi, Laura; De Vico Fallani, Fabrizio; Tocci, Andrea; Bianchi, Luigi; Marciani, Maria Grazia; Gao, Shangkai; Millan, Jose; Babiloni, Fabio
2008-01-15
High-resolution electroencephalographic (HREEG) techniques allow estimation of cortical activity based on non-invasive scalp potential measurements, using appropriate models of volume conduction and of neuroelectrical sources. In this study we propose an application of this body of technologies, originally developed to obtain functional images of the brain's electrical activity, in the context of brain-computer interfaces (BCI). Our working hypothesis predicted that, since HREEG pre-processing removes spatial correlation introduced by current conduction in the head structures, by providing the BCI with waveforms that are mostly due to the unmixed activity of a small cortical region, a more reliable classification would be obtained, at least when the activity to detect has a limited generator, which is the case in motor related tasks. HREEG techniques employed in this study rely on (i) individual head models derived from anatomical magnetic resonance images, (ii) distributed source model, composed of a layer of current dipoles, geometrically constrained to the cortical mantle, (iii) depth-weighted minimum L(2)-norm constraint and Tikhonov regularization for linear inverse problem solution and (iv) estimation of electrical activity in cortical regions of interest corresponding to relevant Brodmann areas. Six subjects were trained to learn self modulation of sensorimotor EEG rhythms, related to the imagination of limb movements. Off-line EEG data was used to estimate waveforms of cortical activity (cortical current density, CCD) on selected regions of interest. CCD waveforms were fed into the BCI computational pipeline as an alternative to raw EEG signals; spectral features are evaluated through statistical tests (r(2) analysis), to quantify their reliability for BCI control. These results are compared, within subjects, to analogous results obtained without HREEG techniques. The processing procedure was designed in such a way that computations could be split into a setup phase (which includes most of the computational burden) and the actual EEG processing phase, which was limited to a single matrix multiplication. This separation allowed to make the procedure suitable for on-line utilization, and a pilot experiment was performed. Results show that lateralization of electrical activity, which is expected to be contralateral to the imagined movement, is more evident on the estimated CCDs than in the scalp potentials. CCDs produce a pattern of relevant spectral features that is more spatially focused, and has a higher statistical significance (EEG: 0.20+/-0.114 S.D.; CCD: 0.55+/-0.16 S.D.; p=10(-5)). A pilot experiment showed that a trained subject could utilize voluntary modulation of estimated CCDs for accurate (eight targets) on-line control of a cursor. This study showed that it is practically feasible to utilize HREEG techniques for on-line operation of a BCI system; off-line analysis suggests that accuracy of BCI control is enhanced by the proposed method.
Varoli, Erica; Pisoni, Alberto; Mattavelli, Giulia C.; Vergallito, Alessandra; Gallucci, Alessia; Mauro, Lilia D.; Rosanova, Mario; Bolognini, Nadia; Vallar, Giuseppe; Romero Lauro, Leonor J.
2018-01-01
Transcranial direct current stimulation (tDCS) is increasingly used in both research and therapeutic settings, but its precise mechanisms remain largely unknown. At a neuronal level, tDCS modulates cortical excitability by shifting the resting membrane potential in a polarity-dependent way: anodal stimulation increases the spontaneous firing rate, while cathodal decreases it. However, the neurophysiological underpinnings of anodal/cathodal tDCS seem to be different, as well as their behavioral effect, in particular when high order areas are involved, compared to when motor or sensory brain areas are targeted. Previously, we investigated the effect of anodal tDCS on cortical excitability, by means of a combination of Transcranial Magnetic Stimulation (TMS) and Electroencephalography (EEG). Results showed a diffuse rise of cortical excitability in a bilateral fronto-parietal network. In the present study, we tested, with the same paradigm, the effect of cathodal tDCS. Single pulse TMS was delivered over the left posterior parietal cortex (PPC), before, during, and after 10 min of cathodal or sham tDCS over the right PPC, while recording HD-EEG. Indexes of global and local cortical excitability were obtained both at sensors and cortical sources level. At sensors, global and local mean field power (GMFP and LMFP) were computed for three temporal windows (0–50, 50–100, and 100–150 ms), on all channels (GMFP), and in four different clusters of electrodes (LMFP, left and right, in frontal and parietal regions). After source reconstruction, Significant Current Density was computed at the global level, and for four Broadmann's areas (left/right BA 6 and 7). Both sensors and cortical sources results converge in showing no differences during and after cathodal tDCS compared to pre-stimulation sessions, both at global and local level. The same holds for sham tDCS. These data highlight an asymmetric impact of anodal and cathodal stimulation on cortical excitability, with a diffuse effect of anodal and no effect of cathodal tDCS over the parietal cortex. These results are consistent with the current literature: while anodal-excitatory and cathodal-inhibitory effects are well-established in the sensory and motor domains, both at physiological and behavioral levels, results for cathodal stimulation are more controversial for modulation of exitability of higher order areas. PMID:29867330
Marsella, Pasquale; Scorpecci, Alessandro; Vecchiato, Giovanni; Maglione, Anton Giulio; Colosimo, Alfredo; Babiloni, Fabio
2014-05-01
To date, no objective measure of the pleasantness of music perception by children with cochlear implants has been reported. The EEG alpha asymmetries of pre-frontal cortex activation are known to relate to emotional/affective engagement in a perceived stimulus. More specifically, according to the "withdrawal/approach" model, an unbalanced de-synchronization of the alpha activity in the left prefrontal cortex has been associated with a positive affective state/approach toward a stimulus, and an unbalanced de-synchronization of the same activity in the right prefrontal cortex with a negative affective state/withdrawal from a stimulus. In the present study, High-Resolution EEG with Source Reconstruction was used to compare the music-induced alpha asymmetries of the prefrontal cortex in a group of prelingually deaf implanted children and in a control group of normal-hearing children. Six normal-hearing and six age-matched deaf children using a unilateral cochlear implants underwent High-Resolution EEG recordings as they were listening to a musical cartoon. Musical stimuli were delivered in three versions: Normal, Distort (reverse audio flow) and Mute. The EEG alpha rhythm asymmetry was analyzed: Power Spectral Density was calculated for each Region of Interest, together with a right-left imbalance index. A map of cortical activation was then reconstructed on a realistic cortical model. Asymmetries of EEG alpha rhythm in the prefrontal cortices were observed in both groups. In the normal-hearing children, the asymmetries were consistent with the withdrawal/approach model, whereas in cochlear implant users they were not. Moreover, in implanted children a different pattern of alpha asymmetries in extrafrontal cortical areas was noticed as compared to normal-hearing subjects. The peculiar pattern of alpha asymmetries in implanted children's prefrontal cortex in response to musical stimuli suggests an inability by these subjects to discriminate normal from dissonant music and to appreciate the pleasantness of normal music. High-Resolution EEG may prove to be a promising tool for objectively measuring prefrontal cortex alpha asymmetries in child cochlear implant users. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Regional brain activity that determines successful and unsuccessful working memory formation.
Teramoto, Shohei; Inaoka, Tsubasa; Ono, Yumie
2016-08-01
Using EEG source reconstruction with Multiple Sparse Priors (MSP), we investigated the regional brain activity that determines successful memory encoding in two participant groups of high and low accuracy rates. Eighteen healthy young adults performed a sequential fashion of visual Sternberg memory task. The 32-channel EEG was continuously measured during participants performed two 70 trials of memory task. The regional brain activity corresponding to the oscillatory EEG activity in the alpha band (8-13 Hz) during encoding period was analyzed by MSP implemented in SPM8. We divided the data of all participants into 2 groups (low- and highperformance group) and analyzed differences in regional brain activity between trials in which participants answered correctly and incorrectly within each of the group. Participants in low-performance group showed significant activity increase in the visual cortices in their successful trials compared to unsuccessful ones. On the other hand, those in high-performance group showed a significant activity increase in widely distributed cortical regions in the frontal, temporal, and parietal areas including those suggested as Baddeley's working memory model. Further comparison of activated cortical volumes and mean current source intensities within the cortical regions of Baddeley's model during memory encoding demonstrated that participants in high-performance group showed enhanced activity in the right premotor cortex, which plays an important role in maintaining visuospatial attention, compared to those in low performance group. Our results suggest that better ability in memory encoding is associated with distributed and stronger regional brain activities including the premotor cortex, possibly indicating efficient allocation of cognitive load and maintenance of attention.
Heightened eating drive and visual food stimuli attenuate central nociceptive processing
Li, Xiaoyun; Fallon, Nicholas B.; Giesbrecht, Timo; Thomas, Anna; Harrold, Joanne A.; Halford, Jason C. G.; Stancak, Andrej
2014-01-01
Hunger and pain are basic drives that compete for a behavioral response when experienced together. To investigate the cortical processes underlying hunger-pain interactions, we manipulated participants' hunger and presented photographs of appetizing food or inedible objects in combination with painful laser stimuli. Fourteen healthy participants completed two EEG sessions: one after an overnight fast, the other following a large breakfast. Spatio-temporal patterns of cortical activation underlying the hunger-pain competition were explored with 128-channel EEG recordings and source dipole analysis of laser-evoked potentials (LEPs). We found that initial pain ratings were temporarily reduced when participants were hungry compared with fed. Source activity in parahippocampal gyrus was weaker when participants were hungry, and activations of operculo-insular cortex, anterior cingulate cortex, parahippocampal gyrus, and cerebellum were smaller in the context of appetitive food photographs than in that of inedible object photographs. Cortical processing of noxious stimuli in pain-related brain structures is reduced and pain temporarily attenuated when people are hungry or passively viewing food photographs, suggesting a possible interaction between the opposing motivational forces of the eating drive and pain. PMID:25475348
A simple method for EEG guided transcranial electrical stimulation without models.
Cancelli, Andrea; Cottone, Carlo; Tecchio, Franca; Truong, Dennis Q; Dmochowski, Jacek; Bikson, Marom
2016-06-01
There is longstanding interest in using EEG measurements to inform transcranial Electrical Stimulation (tES) but adoption is lacking because users need a simple and adaptable recipe. The conventional approach is to use anatomical head-models for both source localization (the EEG inverse problem) and current flow modeling (the tES forward model), but this approach is computationally demanding, requires an anatomical MRI, and strict assumptions about the target brain regions. We evaluate techniques whereby tES dose is derived from EEG without the need for an anatomical head model, target assumptions, difficult case-by-case conjecture, or many stimulation electrodes. We developed a simple two-step approach to EEG-guided tES that based on the topography of the EEG: (1) selects locations to be used for stimulation; (2) determines current applied to each electrode. Each step is performed based solely on the EEG with no need for head models or source localization. Cortical dipoles represent idealized brain targets. EEG-guided tES strategies are verified using a finite element method simulation of the EEG generated by a dipole, oriented either tangential or radial to the scalp surface, and then simulating the tES-generated electric field produced by each model-free technique. These model-free approaches are compared to a 'gold standard' numerically optimized dose of tES that assumes perfect understanding of the dipole location and head anatomy. We vary the number of electrodes from a few to over three hundred, with focality or intensity as optimization criterion. Model-free approaches evaluated include (1) voltage-to-voltage, (2) voltage-to-current; (3) Laplacian; and two Ad-Hoc techniques (4) dipole sink-to-sink; and (5) sink to concentric. Our results demonstrate that simple ad hoc approaches can achieve reasonable targeting for the case of a cortical dipole, remarkably with only 2-8 electrodes and no need for a model of the head. Our approach is verified directly only for a theoretically localized source, but may be potentially applied to an arbitrary EEG topography. For its simplicity and linearity, our recipe for model-free EEG guided tES lends itself to broad adoption and can be applied to static (tDCS), time-variant (e.g., tACS, tRNS, tPCS), or closed-loop tES.
A simple method for EEG guided transcranial electrical stimulation without models
NASA Astrophysics Data System (ADS)
Cancelli, Andrea; Cottone, Carlo; Tecchio, Franca; Truong, Dennis Q.; Dmochowski, Jacek; Bikson, Marom
2016-06-01
Objective. There is longstanding interest in using EEG measurements to inform transcranial Electrical Stimulation (tES) but adoption is lacking because users need a simple and adaptable recipe. The conventional approach is to use anatomical head-models for both source localization (the EEG inverse problem) and current flow modeling (the tES forward model), but this approach is computationally demanding, requires an anatomical MRI, and strict assumptions about the target brain regions. We evaluate techniques whereby tES dose is derived from EEG without the need for an anatomical head model, target assumptions, difficult case-by-case conjecture, or many stimulation electrodes. Approach. We developed a simple two-step approach to EEG-guided tES that based on the topography of the EEG: (1) selects locations to be used for stimulation; (2) determines current applied to each electrode. Each step is performed based solely on the EEG with no need for head models or source localization. Cortical dipoles represent idealized brain targets. EEG-guided tES strategies are verified using a finite element method simulation of the EEG generated by a dipole, oriented either tangential or radial to the scalp surface, and then simulating the tES-generated electric field produced by each model-free technique. These model-free approaches are compared to a ‘gold standard’ numerically optimized dose of tES that assumes perfect understanding of the dipole location and head anatomy. We vary the number of electrodes from a few to over three hundred, with focality or intensity as optimization criterion. Main results. Model-free approaches evaluated include (1) voltage-to-voltage, (2) voltage-to-current; (3) Laplacian; and two Ad-Hoc techniques (4) dipole sink-to-sink; and (5) sink to concentric. Our results demonstrate that simple ad hoc approaches can achieve reasonable targeting for the case of a cortical dipole, remarkably with only 2-8 electrodes and no need for a model of the head. Significance. Our approach is verified directly only for a theoretically localized source, but may be potentially applied to an arbitrary EEG topography. For its simplicity and linearity, our recipe for model-free EEG guided tES lends itself to broad adoption and can be applied to static (tDCS), time-variant (e.g., tACS, tRNS, tPCS), or closed-loop tES.
The inverse electroencephalography pipeline
NASA Astrophysics Data System (ADS)
Weinstein, David Michael
The inverse electroencephalography (EEG) problem is defined as determining which regions of the brain are active based on remote measurements recorded with scalp EEG electrodes. An accurate solution to this problem would benefit both fundamental neuroscience research and clinical neuroscience applications. However, constructing accurate patient-specific inverse EEG solutions requires complex modeling, simulation, and visualization algorithms, and to date only a few systems have been developed that provide such capabilities. In this dissertation, a computational system for generating and investigating patient-specific inverse EEG solutions is introduced, and the requirements for each stage of this Inverse EEG Pipeline are defined and discussed. While the requirements of many of the stages are satisfied with existing algorithms, others have motivated research into novel modeling and simulation methods. The principal technical results of this work include novel surface-based volume modeling techniques, an efficient construction for the EEG lead field, and the Open Source release of the Inverse EEG Pipeline software for use by the bioelectric field research community. In this work, the Inverse EEG Pipeline is applied to three research problems in neurology: comparing focal and distributed source imaging algorithms; separating measurements into independent activation components for multifocal epilepsy; and localizing the cortical activity that produces the P300 effect in schizophrenia.
Multimodal imaging of spike propagation: a technical case report.
Tanaka, N; Grant, P E; Suzuki, N; Madsen, J R; Bergin, A M; Hämäläinen, M S; Stufflebeam, S M
2012-06-01
We report an 11-year-old boy with intractable epilepsy, who had cortical dysplasia in the right superior frontal gyrus. Spatiotemporal source analysis of MEG and EEG spikes demonstrated a similar time course of spike propagation from the superior to inferior frontal gyri, as observed on intracranial EEG. The tractography reconstructed from DTI showed a fiber connection between these areas. Our multimodal approach demonstrates spike propagation and a white matter tract guiding the propagation.
Liu, Quanying; Ganzetti, Marco; Wenderoth, Nicole; Mantini, Dante
2018-01-01
Resting state networks (RSNs) in the human brain were recently detected using high-density electroencephalography (hdEEG). This was done by using an advanced analysis workflow to estimate neural signals in the cortex and to assess functional connectivity (FC) between distant cortical regions. FC analyses were conducted either using temporal (tICA) or spatial independent component analysis (sICA). Notably, EEG-RSNs obtained with sICA were very similar to RSNs retrieved with sICA from functional magnetic resonance imaging data. It still remains to be clarified, however, what technological aspects of hdEEG acquisition and analysis primarily influence this correspondence. Here we examined to what extent the detection of EEG-RSN maps by sICA depends on the electrode density, the accuracy of the head model, and the source localization algorithm employed. Our analyses revealed that the collection of EEG data using a high-density montage is crucial for RSN detection by sICA, but also the use of appropriate methods for head modeling and source localization have a substantial effect on RSN reconstruction. Overall, our results confirm the potential of hdEEG for mapping the functional architecture of the human brain, and highlight at the same time the interplay between acquisition technology and innovative solutions in data analysis. PMID:29551969
Beta activity in the premotor cortex is increased during stabilized as compared to normal walking
Bruijn, Sjoerd M.; Van Dieën, Jaap H.; Daffertshofer, Andreas
2015-01-01
Walking on two legs is inherently unstable. Still, we humans perform remarkable well at it, mostly without falling. To gain more understanding of the role of the brain in controlling gait stability we measured brain activity using electro-encephalography (EEG) during stabilized and normal walking. Subjects walked on a treadmill in two conditions, each lasting 10 min; normal, and while being laterally stabilized by elastic cords. Kinematics of trunk and feet, electro-myography (EMG) of neck muscles, as well as 64-channel EEG were recorded. To assess gait stability the local divergence exponent, step width, and trunk range of motion were calculated from the kinematic data. We used independent component (IC) analysis to remove movement, EMG, and eyeblink artifacts from the EEG, after which dynamic imaging of coherent sources beamformers were determined to identify cortical sources that showed a significant difference between conditions. Stabilized walking led to a significant increase in gait stability, i.e., lower local divergence exponents. Beamforming analysis of the beta band activity revealed significant sources in bilateral pre-motor cortices. Projection of sensor data on these sources showed a significant difference only in the left premotor area, with higher beta power during stabilized walking, specifically around push-off, although only significant around contralateral push-off. It appears that even during steady gait the cortex is involved in the control of stability. PMID:26578937
EEG signatures of arm isometric exertions in preparation, planning and execution.
Nasseroleslami, Bahman; Lakany, Heba; Conway, Bernard A
2014-04-15
The electroencephalographic (EEG) activity patterns in humans during motor behaviour provide insight into normal motor control processes and for diagnostic and rehabilitation applications. While the patterns preceding brisk voluntary movements, and especially movement execution, are well described, there are few EEG studies that address the cortical activation patterns seen in isometric exertions and their planning. In this paper, we report on time and time-frequency EEG signatures in experiments in normal subjects (n=8), using multichannel EEG during motor preparation, planning and execution of directional centre-out arm isometric exertions performed at the wrist in the horizontal plane, in response to instruction-delay visual cues. Our observations suggest that isometric force exertions are accompanied by transient and sustained event-related potentials (ERP) and event-related (de-)synchronisations (ERD/ERS), comparable to those of a movement task. Furthermore, the ERPs and ERD/ERS are also observed during preparation and planning of the isometric task. Comparison of ear-lobe-referenced and surface Laplacian ERPs indicates the contribution of superficial sources in supplementary and pre-motor (FC(z)), parietal (CP(z)) and primary motor cortical areas (C₁ and FC₁) to ERPs (primarily negative peaks in frontal and positive peaks in parietal areas), but contribution of deep sources to sustained time-domain potentials (negativity in planning and positivity in execution). Transient and sustained ERD patterns in μ and β frequency bands of ear-lobe-referenced and surface Laplacian EEG indicate the contribution of both superficial and deep sources to ERD/ERS. As no physical displacement happens during the task, we can infer that the underlying mechanisms of motor-related ERPs and ERD/ERS patterns do not only depend on change in limb coordinate or muscle-length-dependent ascending sensory information and are primary generated by motor preparation, direction-dependent planning and execution of isometric motor tasks. The results contribute to our understanding of the functions of different brain regions during voluntary motor tasks and their activity signatures in EEG can shed light on the relationships between large-scale recordings such as EEG and other recordings such as single unit activity and fMRI in this context. Copyright © 2013 Elsevier Inc. All rights reserved.
Intelligence and EEG current density using low-resolution electromagnetic tomography (LORETA).
Thatcher, R W; North, D; Biver, C
2007-02-01
The purpose of this study was to compare EEG current source densities in high IQ subjects vs. low IQ subjects. Resting eyes closed EEG was recorded from 19 scalp locations with a linked ears reference from 442 subjects ages 5 to 52 years. The Wechsler Intelligence Test was administered and subjects were divided into low IQ (< or =90), middle IQ (>90 to <120) and high IQ (> or =120) groups. Low-resolution electromagnetic tomographic current densities (LORETA) from 2,394 cortical gray matter voxels were computed from 1-30 Hz based on each subject's EEG. Differences in current densities using t tests, multivariate analyses of covariance, and regression analyses were used to evaluate the relationships between IQ and current density in Brodmann area groupings of cortical gray matter voxels. Frontal, temporal, parietal, and occipital regions of interest (ROIs) consistently exhibited a direct relationship between LORETA current density and IQ. Maximal t test differences were present at 4 Hz, 9 Hz, 13 Hz, 18 Hz, and 30 Hz with different anatomical regions showing different maxima. Linear regression fits from low to high IQ groups were statistically significant (P < 0.0001). Intelligence is directly related to a general level of arousal and to the synchrony of neural populations driven by thalamo-cortical resonances. A traveling frame model of sequential microstates is hypothesized to explain the results.
Dmochowski, Jacek P; Sajda, Paul; Dias, Joao; Parra, Lucas C
2012-01-01
Recent evidence from functional magnetic resonance imaging suggests that cortical hemodynamic responses coincide in different subjects experiencing a common naturalistic stimulus. Here we utilize neural responses in the electroencephalogram (EEG) evoked by multiple presentations of short film clips to index brain states marked by high levels of correlation within and across subjects. We formulate a novel signal decomposition method which extracts maximally correlated signal components from multiple EEG records. The resulting components capture correlations down to a one-second time resolution, thus revealing that peak correlations of neural activity across viewings can occur in remarkable correspondence with arousing moments of the film. Moreover, a significant reduction in neural correlation occurs upon a second viewing of the film or when the narrative is disrupted by presenting its scenes scrambled in time. We also probe oscillatory brain activity during periods of heightened correlation, and observe during such times a significant increase in the theta band for a frontal component and reductions in the alpha and beta frequency bands for parietal and occipital components. Low-resolution EEG tomography of these components suggests that the correlated neural activity is consistent with sources in the cingulate and orbitofrontal cortices. Put together, these results suggest that the observed synchrony reflects attention- and emotion-modulated cortical processing which may be decoded with high temporal resolution by extracting maximally correlated components of neural activity.
Dmochowski, Jacek P.; Sajda, Paul; Dias, Joao; Parra, Lucas C.
2012-01-01
Recent evidence from functional magnetic resonance imaging suggests that cortical hemodynamic responses coincide in different subjects experiencing a common naturalistic stimulus. Here we utilize neural responses in the electroencephalogram (EEG) evoked by multiple presentations of short film clips to index brain states marked by high levels of correlation within and across subjects. We formulate a novel signal decomposition method which extracts maximally correlated signal components from multiple EEG records. The resulting components capture correlations down to a one-second time resolution, thus revealing that peak correlations of neural activity across viewings can occur in remarkable correspondence with arousing moments of the film. Moreover, a significant reduction in neural correlation occurs upon a second viewing of the film or when the narrative is disrupted by presenting its scenes scrambled in time. We also probe oscillatory brain activity during periods of heightened correlation, and observe during such times a significant increase in the theta band for a frontal component and reductions in the alpha and beta frequency bands for parietal and occipital components. Low-resolution EEG tomography of these components suggests that the correlated neural activity is consistent with sources in the cingulate and orbitofrontal cortices. Put together, these results suggest that the observed synchrony reflects attention- and emotion-modulated cortical processing which may be decoded with high temporal resolution by extracting maximally correlated components of neural activity. PMID:22623915
Enhanced inter-subject brain computer interface with associative sensorimotor oscillations.
Saha, Simanto; Ahmed, Khawza I; Mostafa, Raqibul; Khandoker, Ahsan H; Hadjileontiadis, Leontios
2017-02-01
Electroencephalography (EEG) captures electrophysiological signatures of cortical events from the scalp with high-dimensional electrode montages. Usually, excessive sources produce outliers and potentially affect the actual event related sources. Besides, EEG manifests inherent inter-subject variability of the brain dynamics, at the resting state and/or under the performance of task(s), caused probably due to the instantaneous fluctuation of psychophysiological states. A wavelet coherence (WC) analysis for optimally selecting associative inter-subject channels is proposed here and is being used to boost performances of motor imagery (MI)-based inter-subject brain computer interface (BCI). The underlying hypothesis is that optimally associative inter-subject channels can reduce the effects of outliers and, thus, eliminate dissimilar cortical patterns. The proposed approach has been tested on the dataset IVa from BCI competition III, including EEG data acquired from five healthy subjects who were given visual cues to perform 280 trials of MI for the right hand and right foot. Experimental results have shown increased classification accuracy (81.79%) using the WC-based selected 16 channels compared to the one (56.79%) achieved using all the available 118 channels. The associative channels lie mostly around the sensorimotor regions of the brain, reinforced by the previous literature, describing spatial brain dynamics during sensorimotor oscillations. Apparently, the proposed approach paves the way for optimised EEG channel selection that could boost further the efficiency and real-time performance of BCI systems.
Borich, Michael R; Wheaton, Lewis A; Brodie, Sonia M; Lakhani, Bimal; Boyd, Lara A
2016-04-08
TMS-evoked cortical responses can be measured using simultaneous electroencephalography (TMS-EEG) to directly quantify cortical connectivity in the human brain. The purpose of this study was to evaluate interhemispheric cortical connectivity between the primary motor cortices (M1s) in participants with chronic stroke and controls using TMS-EEG. Ten participants with chronic stroke and four controls were tested. TMS-evoked responses were recorded at rest and during a typical TMS assessment of transcallosal inhibition (TCI). EEG recordings from peri-central gyral electrodes (C3 and C4) were evaluated using imaginary phase coherence (IPC) analyses to quantify levels of effective interhemispheric connectivity. Significantly increased TMS-evoked beta (15-30Hz frequency range) IPC was observed in the stroke group during ipsilesional M1 stimulation compared to controls during TCI assessment but not at rest. TMS-evoked beta IPC values were associated with TMS measures of transcallosal inhibition across groups. These results suggest TMS-evoked EEG responses can index abnormal effective interhemispheric connectivity in chronic stroke. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Rogasch, Nigel C; Sullivan, Caley; Thomson, Richard H; Rose, Nathan S; Bailey, Neil W; Fitzgerald, Paul B; Farzan, Faranak; Hernandez-Pavon, Julio C
2017-02-15
The concurrent use of transcranial magnetic stimulation with electroencephalography (TMS-EEG) is growing in popularity as a method for assessing various cortical properties such as excitability, oscillations and connectivity. However, this combination of methods is technically challenging, resulting in artifacts both during recording and following typical EEG analysis methods, which can distort the underlying neural signal. In this article, we review the causes of artifacts in EEG recordings resulting from TMS, as well as artifacts introduced during analysis (e.g. as the result of filtering over high-frequency, large amplitude artifacts). We then discuss methods for removing artifacts, and ways of designing pipelines to minimise analysis-related artifacts. Finally, we introduce the TMS-EEG signal analyser (TESA), an open-source extension for EEGLAB, which includes functions that are specific for TMS-EEG analysis, such as removing and interpolating the TMS pulse artifact, removing and minimising TMS-evoked muscle activity, and analysing TMS-evoked potentials. The aims of TESA are to provide users with easy access to current TMS-EEG analysis methods and to encourage direct comparisons of these methods and pipelines. It is hoped that providing open-source functions will aid in both improving and standardising analysis across the field of TMS-EEG research. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Heightened eating drive and visual food stimuli attenuate central nociceptive processing.
Wright, Hazel; Li, Xiaoyun; Fallon, Nicholas B; Giesbrecht, Timo; Thomas, Anna; Harrold, Joanne A; Halford, Jason C G; Stancak, Andrej
2015-03-01
Hunger and pain are basic drives that compete for a behavioral response when experienced together. To investigate the cortical processes underlying hunger-pain interactions, we manipulated participants' hunger and presented photographs of appetizing food or inedible objects in combination with painful laser stimuli. Fourteen healthy participants completed two EEG sessions: one after an overnight fast, the other following a large breakfast. Spatio-temporal patterns of cortical activation underlying the hunger-pain competition were explored with 128-channel EEG recordings and source dipole analysis of laser-evoked potentials (LEPs). We found that initial pain ratings were temporarily reduced when participants were hungry compared with fed. Source activity in parahippocampal gyrus was weaker when participants were hungry, and activations of operculo-insular cortex, anterior cingulate cortex, parahippocampal gyrus, and cerebellum were smaller in the context of appetitive food photographs than in that of inedible object photographs. Cortical processing of noxious stimuli in pain-related brain structures is reduced and pain temporarily attenuated when people are hungry or passively viewing food photographs, suggesting a possible interaction between the opposing motivational forces of the eating drive and pain. Copyright © 2015 the American Physiological Society.
Correlates of a single cortical action potential in the epidural EEG
Teleńczuk, Bartosz; Baker, Stuart N; Kempter, Richard; Curio, Gabriel
2015-01-01
To identify the correlates of a single cortical action potential in surface EEG, we recorded simultaneously epidural EEG and single-unit activity in the primary somatosensory cortex of awake macaque monkeys. By averaging over EEG segments coincident with more than hundred thousand single spikes, we found short-lived (≈ 0.5 ms) triphasic EEG deflections dominated by high-frequency components > 800 Hz. The peak-to-peak amplitude of the grand-averaged spike correlate was 80 nV, which matched theoretical predictions, while single-neuron amplitudes ranged from 12 to 966 nV. Combining these estimates with post-stimulus-time histograms of single-unit responses to median-nerve stimulation allowed us to predict the shape of the evoked epidural EEG response and to estimate the number of contributing neurons. These findings establish spiking activity of cortical neurons as a primary building block of high-frequency epidural EEG, which thus can serve as a quantitative macroscopic marker of neuronal spikes. PMID:25554430
As above, so below? Towards understanding inverse models in BCI
NASA Astrophysics Data System (ADS)
Lindgren, Jussi T.
2018-02-01
Objective. In brain-computer interfaces (BCI), measurements of the user’s brain activity are classified into commands for the computer. With EEG-based BCIs, the origins of the classified phenomena are often considered to be spatially localized in the cortical volume and mixed in the EEG. We investigate if more accurate BCIs can be obtained by reconstructing the source activities in the volume. Approach. We contrast the physiology-driven source reconstruction with data-driven representations obtained by statistical machine learning. We explain these approaches in a common linear dictionary framework and review the different ways to obtain the dictionary parameters. We consider the effect of source reconstruction on some major difficulties in BCI classification, namely information loss, feature selection and nonstationarity of the EEG. Main results. Our analysis suggests that the approaches differ mainly in their parameter estimation. Physiological source reconstruction may thus be expected to improve BCI accuracy if machine learning is not used or where it produces less optimal parameters. We argue that the considered difficulties of surface EEG classification can remain in the reconstructed volume and that data-driven techniques are still necessary. Finally, we provide some suggestions for comparing approaches. Significance. The present work illustrates the relationships between source reconstruction and machine learning-based approaches for EEG data representation. The provided analysis and discussion should help in understanding, applying, comparing and improving such techniques in the future.
Porkkala, T; Jäntti, V; Kaukinen, S; Häkkinen, V
1997-04-01
Electroencephalogram (EEG) and somatosensory evoked potentials (SEPs) are altered by inhalation anaesthesia. Nitrous oxide is commonly used in combination with volatile anaesthetics. We have studied the effects of nitrous oxide on both EEG and SEPs simultaneously during isoflurane burst-suppression anaesthesia. Twelve ASA I-II patients undergoing abdominal or orthopaedic surgery were anaesthetized with isoflurane by mask. After intubation and relaxation the isoflurane concentration was increased to a level at which an EEG burst-suppression pattern occurred (mean isoflurane end-tidal concentration 1.9 (SD 0.2) %. With a stable isoflurane concentration, the patients received isoflurane-air-oxygen and isoflurane-nitrous oxide-oxygen (FiO2 0.4) in a randomized cross-over manner. EEG and SEPs were simultaneously recorded before, and after wash-out or wash-in periods for nitrous oxide. The proportion of EEG suppressions as well as SEP amplitudes for cortical N20 were calculated. The proportion of EEG suppressions decreased from 53.5% to 34% (P < 0.05) when air was replaced by nitrous oxide. At the same time, the cortical N20 amplitude was reduced by 69% (P < 0.01). The results suggest that during isoflurane anaesthesia, nitrous oxide has a different effect on EEG and cortical SEP at the same time. The effects of nitrous oxide may be mediated by cortical and subcortical generators.
Clemens, Béla; Bánk, József; Piros, Pálma; Bessenyei, Mónika; Veto, Sára; Tóth, Márton; Kondákor, István
2008-09-01
Investigating the brain of migraine patients in the pain-free interval may shed light on the basic cerebral abnormality of migraine, in other words, the liability of the brain to generate migraine attacks from time to time. Twenty unmedicated "migraine without aura" patients and a matched group of healthy controls were investigated in this explorative study. 19-channel EEG was recorded against the linked ears reference and was on-line digitized. 60 x 2-s epochs of eyes-closed, waking-relaxed activity were subjected to spectral analysis and a source localization method, low resolution electromagnetic tomography (LORETA). Absolute power was computed for 19 electrodes and four frequency bands (delta: 1.5-3.5 Hz, theta: 4.0-7.5 Hz, alpha: 8.0-12.5 Hz, beta: 13.0-25.0 Hz). LORETA "activity" (=current source density, ampers/meters squared) was computed for 2394 voxels and the above specified frequency bands. Group comparison was carried out for the specified quantitative EEG variables. Activity in the two groups was compared on a voxel-by-voxel basis for each frequency band. Statistically significant (uncorrected P < 0.01) group differences were projected to cortical anatomy. Spectral findings: there was a tendency for more alpha power in the migraine that in the control group in all but two (F4, C3) derivations. However, statistically significant (P < 0.01, Bonferroni-corrected) spectral difference was only found in the right occipital region. The main LORETA-finding was that voxels with P < 0.01 differences were crowded in anatomically contiguous cortical areas. Increased alpha activity was found in a cortical area including part of the precuneus, and the posterior part of the middle temporal gyrus in the right hemisphere. Decreased alpha activity was found bilaterally in medial parts of the frontal cortex including the anterior cingulate and the superior and medial frontal gyri. Neither spectral analysis, nor LORETA revealed statistically significant differences in the delta, theta, and beta bands. LORETA revealed the anatomical distribution of the cortical sources (generators) of the EEG abnormalities in migraine. The findings characterize the state of the cerebral cortex in the pain-free interval and might be suitable for planning forthcoming investigations.
Ghost interactions in MEG/EEG source space: A note of caution on inter-areal coupling measures.
Palva, J Matias; Wang, Sheng H; Palva, Satu; Zhigalov, Alexander; Monto, Simo; Brookes, Matthew J; Schoffelen, Jan-Mathijs; Jerbi, Karim
2018-06-01
When combined with source modeling, magneto- (MEG) and electroencephalography (EEG) can be used to study long-range interactions among cortical processes non-invasively. Estimation of such inter-areal connectivity is nevertheless hindered by instantaneous field spread and volume conduction, which artificially introduce linear correlations and impair source separability in cortical current estimates. To overcome the inflating effects of linear source mixing inherent to standard interaction measures, alternative phase- and amplitude-correlation based connectivity measures, such as imaginary coherence and orthogonalized amplitude correlation have been proposed. Being by definition insensitive to zero-lag correlations, these techniques have become increasingly popular in the identification of correlations that cannot be attributed to field spread or volume conduction. We show here, however, that while these measures are immune to the direct effects of linear mixing, they may still reveal large numbers of spurious false positive connections through field spread in the vicinity of true interactions. This fundamental problem affects both region-of-interest-based analyses and all-to-all connectome mappings. Most importantly, beyond defining and illustrating the problem of spurious, or "ghost" interactions, we provide a rigorous quantification of this effect through extensive simulations. Additionally, we further show that signal mixing also significantly limits the separability of neuronal phase and amplitude correlations. We conclude that spurious correlations must be carefully considered in connectivity analyses in MEG/EEG source space even when using measures that are immune to zero-lag correlations. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Riedner, Brady A; Goldstein, Michael R; Plante, David T; Rumble, Meredith E; Ferrarelli, Fabio; Tononi, Giulio; Benca, Ruth M
2016-04-01
To examine nonrapid eye movement (NREM) sleep in insomnia using high-density electroencephalography (EEG). All-night sleep recordings with 256 channel high-density EEG were analyzed for 8 insomnia subjects (5 females) and 8 sex and age-matched controls without sleep complaints. Spectral analyses were conducted using unpaired t-tests and topographical differences between groups were assessed using statistical non-parametric mapping. Five minute segments of deep NREM sleep were further analyzed using sLORETA cortical source imaging. The initial topographic analysis of all-night NREM sleep EEG revealed that insomnia subjects had more high-frequency EEG activity (> 16 Hz) compared to good sleeping controls and that the difference between groups was widespread across the scalp. In addition, the analysis also showed that there was a more circumscribed difference in theta (4-8 Hz) and alpha (8-12 Hz) power bands between groups. When deep NREM sleep (N3) was examined separately, the high-frequency difference between groups diminished, whereas the higher regional alpha activity in insomnia subjects persisted. Source imaging analysis demonstrated that sensory and sensorimotor cortical areas consistently exhibited elevated levels of alpha activity during deep NREM sleep in insomnia subjects relative to good sleeping controls. These results suggest that even during the deepest stage of sleep, sensory and sensorimotor areas in insomnia subjects may still be relatively active compared to control subjects and to the rest of the sleeping brain. © 2016 Associated Professional Sleep Societies, LLC.
Combining Different Tools for EEG Analysis to Study the Distributed Character of Language Processing
da Rocha, Armando Freitas; Foz, Flávia Benevides; Pereira, Alfredo
2015-01-01
Recent studies on language processing indicate that language cognition is better understood if assumed to be supported by a distributed intelligent processing system enrolling neurons located all over the cortex, in contrast to reductionism that proposes to localize cognitive functions to specific cortical structures. Here, brain activity was recorded using electroencephalogram while volunteers were listening or reading small texts and had to select pictures that translate meaning of these texts. Several techniques for EEG analysis were used to show this distributed character of neuronal enrollment associated with the comprehension of oral and written descriptive texts. Low Resolution Tomography identified the many different sets (s i) of neurons activated in several distinct cortical areas by text understanding. Linear correlation was used to calculate the information H(e i) provided by each electrode of the 10/20 system about the identified s i. H(e i) Principal Component Analysis (PCA) was used to study the temporal and spatial activation of these sources s i. This analysis evidenced 4 different patterns of H(e i) covariation that are generated by neurons located at different cortical locations. These results clearly show that the distributed character of language processing is clearly evidenced by combining available EEG technologies. PMID:26713089
Rocha, Armando Freitas da; Foz, Flávia Benevides; Pereira, Alfredo
2015-01-01
Recent studies on language processing indicate that language cognition is better understood if assumed to be supported by a distributed intelligent processing system enrolling neurons located all over the cortex, in contrast to reductionism that proposes to localize cognitive functions to specific cortical structures. Here, brain activity was recorded using electroencephalogram while volunteers were listening or reading small texts and had to select pictures that translate meaning of these texts. Several techniques for EEG analysis were used to show this distributed character of neuronal enrollment associated with the comprehension of oral and written descriptive texts. Low Resolution Tomography identified the many different sets (s i ) of neurons activated in several distinct cortical areas by text understanding. Linear correlation was used to calculate the information H(e i ) provided by each electrode of the 10/20 system about the identified s i . H(e i ) Principal Component Analysis (PCA) was used to study the temporal and spatial activation of these sources s i . This analysis evidenced 4 different patterns of H(e i ) covariation that are generated by neurons located at different cortical locations. These results clearly show that the distributed character of language processing is clearly evidenced by combining available EEG technologies.
Naim-Feil, Jodie; Bradshaw, John L; Rogasch, Nigel C; Daskalakis, Zafiris J; Sheppard, Dianne M; Lubman, Dan I; Fitzgerald, Paul B
2016-10-01
Preclinical studies suggest that cortical alterations within the prefrontal cortex (PFC) are critical to the pathophysiology of alcohol dependence. Combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) allows direct assessment of cortical excitability and inhibition within the PFC of human subjects. We report the first application of TMS-EEG to measure these indices within the PFC of alcohol-dependent (ALD) patients post-detoxification. Cortical inhibition was assessed in 12 ALD patients and 14 healthy controls through single and paired-pulse TMS paradigms. Long-interval cortical inhibition indexed cortical inhibition in the PFC. In the motor cortex (MC), short- interval intracortical inhibition and cortical silent period determined inhibition, while intracortical facilitation measured facilitation, resting and active motor threshold indexed cortical excitability. ALD patients demonstrated altered cortical inhibition across the bilateral frontal cortices relative to controls. There was evidence of altered cortical excitability in ALD patients; however, no significant differences in MC inhibition. Our study provides first direct evidence of reduced cortical inhibition in the PFC of ALD patients post-detoxification. Altered cortical excitability in the MC may reflect hyper-excitability within the cortex associated with chronic alcohol consumption. These findings provide initial neurophysiological evidence of disrupted cortical excitability within the PFC of ALD patients.
Bigdely-Shamlo, Nima; Mullen, Tim; Kreutz-Delgado, Kenneth; Makeig, Scott
2013-01-01
A crucial question for the analysis of multi-subject and/or multi-session electroencephalographic (EEG) data is how to combine information across multiple recordings from different subjects and/or sessions, each associated with its own set of source processes and scalp projections. Here we introduce a novel statistical method for characterizing the spatial consistency of EEG dynamics across a set of data records. Measure Projection Analysis (MPA) first finds voxels in a common template brain space at which a given dynamic measure is consistent across nearby source locations, then computes local-mean EEG measure values for this voxel subspace using a statistical model of source localization error and between-subject anatomical variation. Finally, clustering the mean measure voxel values in this locally consistent brain subspace finds brain spatial domains exhibiting distinguishable measure features and provides 3-D maps plus statistical significance estimates for each EEG measure of interest. Applied to sufficient high-quality data, the scalp projections of many maximally independent component (IC) processes contributing to recorded high-density EEG data closely match the projection of a single equivalent dipole located in or near brain cortex. We demonstrate the application of MPA to a multi-subject EEG study decomposed using independent component analysis (ICA), compare the results to k-means IC clustering in EEGLAB (sccn.ucsd.edu/eeglab), and use surrogate data to test MPA robustness. A Measure Projection Toolbox (MPT) plug-in for EEGLAB is available for download (sccn.ucsd.edu/wiki/MPT). Together, MPA and ICA allow use of EEG as a 3-D cortical imaging modality with near-cm scale spatial resolution. PMID:23370059
Wronkiewicz, Mark; Larson, Eric; Lee, Adrian Kc
2016-10-01
Brain-computer interface (BCI) technology allows users to generate actions based solely on their brain signals. However, current non-invasive BCIs generally classify brain activity recorded from surface electroencephalography (EEG) electrodes, which can hinder the application of findings from modern neuroscience research. In this study, we use source imaging-a neuroimaging technique that projects EEG signals onto the surface of the brain-in a BCI classification framework. This allowed us to incorporate prior research from functional neuroimaging to target activity from a cortical region involved in auditory attention. Classifiers trained to detect attention switches performed better with source imaging projections than with EEG sensor signals. Within source imaging, including subject-specific anatomical MRI information (instead of using a generic head model) further improved classification performance. This source-based strategy also reduced accuracy variability across three dimensionality reduction techniques-a major design choice in most BCIs. Our work shows that source imaging provides clear quantitative and qualitative advantages to BCIs and highlights the value of incorporating modern neuroscience knowledge and methods into BCI systems.
Milz, Patricia; Pascual-Marqui, Roberto D; Lehmann, Dietrich; Faber, Pascal L
2016-05-01
Functional states of the brain are constituted by the temporally attuned activity of spatially distributed neural networks. Such networks can be identified by independent component analysis (ICA) applied to frequency-dependent source-localized EEG data. This methodology allows the identification of networks at high temporal resolution in frequency bands of established location-specific physiological functions. EEG measurements are sensitive to neural activity changes in cortical areas of modality-specific processing. We tested effects of modality-specific processing on functional brain networks. Phasic modality-specific processing was induced via tasks (state effects) and tonic processing was assessed via modality-specific person parameters (trait effects). Modality-specific person parameters and 64-channel EEG were obtained from 70 male, right-handed students. Person parameters were obtained using cognitive style questionnaires, cognitive tests, and thinking modality self-reports. EEG was recorded during four conditions: spatial visualization, object visualization, verbalization, and resting. Twelve cross-frequency networks were extracted from source-localized EEG across six frequency bands using ICA. RMANOVAs, Pearson correlations, and path modelling examined effects of tasks and person parameters on networks. Results identified distinct state- and trait-dependent functional networks. State-dependent networks were characterized by decreased, trait-dependent networks by increased alpha activity in sub-regions of modality-specific pathways. Pathways of competing modalities showed opposing alpha changes. State- and trait-dependent alpha were associated with inhibitory and automated processing, respectively. Antagonistic alpha modulations in areas of competing modalities likely prevent intruding effects of modality-irrelevant processing. Considerable research suggested alpha modulations related to modality-specific states and traits. This study identified the distinct electrophysiological cortical frequency-dependent networks within which they operate.
Aydin, Ü; Rampp, S; Wollbrink, A; Kugel, H; Cho, J -H; Knösche, T R; Grova, C; Wellmer, J; Wolters, C H
2017-07-01
In recent years, the use of source analysis based on electroencephalography (EEG) and magnetoencephalography (MEG) has gained considerable attention in presurgical epilepsy diagnosis. However, in many cases the source analysis alone is not used to tailor surgery unless the findings are confirmed by lesions, such as, e.g., cortical malformations in MRI. For many patients, the histology of tissue resected from MRI negative epilepsy shows small lesions, which indicates the need for more sensitive MR sequences. In this paper, we describe a technique to maximize the synergy between combined EEG/MEG (EMEG) source analysis and high resolution MRI. The procedure has three main steps: (1) construction of a detailed and calibrated finite element head model that considers the variation of individual skull conductivities and white matter anisotropy, (2) EMEG source analysis performed on averaged interictal epileptic discharges (IED), (3) high resolution (0.5 mm) zoomed MR imaging, limited to small areas centered at the EMEG source locations. The proposed new diagnosis procedure was then applied in a particularly challenging case of an epilepsy patient: EMEG analysis at the peak of the IED coincided with a right frontal focal cortical dysplasia (FCD), which had been detected at standard 1 mm resolution MRI. Of higher interest, zoomed MR imaging (applying parallel transmission, 'ZOOMit') guided by EMEG at the spike onset revealed a second, fairly subtle, FCD in the left fronto-central region. The evaluation revealed that this second FCD, which had not been detectable with standard 1 mm resolution, was the trigger of the seizures.
Alexander, David M; Trengove, Chris; van Leeuwen, Cees
2015-11-01
An assumption nearly all researchers in cognitive neuroscience tacitly adhere to is that of space-time separability. Historically, it forms the basis of Donders' difference method, and to date, it underwrites all difference imaging and trial-averaging of cortical activity, including the customary techniques for analyzing fMRI and EEG/MEG data. We describe the assumption and how it licenses common methods in cognitive neuroscience; in particular, we show how it plays out in signal differencing and averaging, and how it misleads us into seeing the brain as a set of static activity sources. In fact, rather than being static, the domains of cortical activity change from moment to moment: Recent research has suggested the importance of traveling waves of activation in the cortex. Traveling waves have been described at a range of different spatial scales in the cortex; they explain a large proportion of the variance in phase measurements of EEG, MEG and ECoG, and are important for understanding cortical function. Critically, traveling waves are not space-time separable. Their prominence suggests that the correct frame of reference for analyzing cortical activity is the dynamical trajectory of the system, rather than the time and space coordinates of measurements. We illustrate what the failure of space-time separability implies for cortical activation, and what consequences this should have for cognitive neuroscience.
NASA Astrophysics Data System (ADS)
Safieddine, Doha; Kachenoura, Amar; Albera, Laurent; Birot, Gwénaël; Karfoul, Ahmad; Pasnicu, Anca; Biraben, Arnaud; Wendling, Fabrice; Senhadji, Lotfi; Merlet, Isabelle
2012-12-01
Electroencephalographic (EEG) recordings are often contaminated with muscle artifacts. This disturbing myogenic activity not only strongly affects the visual analysis of EEG, but also most surely impairs the results of EEG signal processing tools such as source localization. This article focuses on the particular context of the contamination epileptic signals (interictal spikes) by muscle artifact, as EEG is a key diagnosis tool for this pathology. In this context, our aim was to compare the ability of two stochastic approaches of blind source separation, namely independent component analysis (ICA) and canonical correlation analysis (CCA), and of two deterministic approaches namely empirical mode decomposition (EMD) and wavelet transform (WT) to remove muscle artifacts from EEG signals. To quantitatively compare the performance of these four algorithms, epileptic spike-like EEG signals were simulated from two different source configurations and artificially contaminated with different levels of real EEG-recorded myogenic activity. The efficiency of CCA, ICA, EMD, and WT to correct the muscular artifact was evaluated both by calculating the normalized mean-squared error between denoised and original signals and by comparing the results of source localization obtained from artifact-free as well as noisy signals, before and after artifact correction. Tests on real data recorded in an epileptic patient are also presented. The results obtained in the context of simulations and real data show that EMD outperformed the three other algorithms for the denoising of data highly contaminated by muscular activity. For less noisy data, and when spikes arose from a single cortical source, the myogenic artifact was best corrected with CCA and ICA. Otherwise when spikes originated from two distinct sources, either EMD or ICA offered the most reliable denoising result for highly noisy data, while WT offered the better denoising result for less noisy data. These results suggest that the performance of muscle artifact correction methods strongly depend on the level of data contamination, and of the source configuration underlying EEG signals. Eventually, some insights into the numerical complexity of these four algorithms are given.
Ghumare, Eshwar; Schrooten, Maarten; Vandenberghe, Rik; Dupont, Patrick
2015-08-01
Kalman filter approaches are widely applied to derive time varying effective connectivity from electroencephalographic (EEG) data. For multi-trial data, a classical Kalman filter (CKF) designed for the estimation of single trial data, can be implemented by trial-averaging the data or by averaging single trial estimates. A general linear Kalman filter (GLKF) provides an extension for multi-trial data. In this work, we studied the performance of the different Kalman filtering approaches for different values of signal-to-noise ratio (SNR), number of trials and number of EEG channels. We used a simulated model from which we calculated scalp recordings. From these recordings, we estimated cortical sources. Multivariate autoregressive model parameters and partial directed coherence was calculated for these estimated sources and compared with the ground-truth. The results showed an overall superior performance of GLKF except for low levels of SNR and number of trials.
Stable Scalp EEG Spatiospectral Patterns Across Paradigms Estimated by Group ICA.
Labounek, René; Bridwell, David A; Mareček, Radek; Lamoš, Martin; Mikl, Michal; Slavíček, Tomáš; Bednařík, Petr; Baštinec, Jaromír; Hluštík, Petr; Brázdil, Milan; Jan, Jiří
2018-01-01
Electroencephalography (EEG) oscillations reflect the superposition of different cortical sources with potentially different frequencies. Various blind source separation (BSS) approaches have been developed and implemented in order to decompose these oscillations, and a subset of approaches have been developed for decomposition of multi-subject data. Group independent component analysis (Group ICA) is one such approach, revealing spatiospectral maps at the group level with distinct frequency and spatial characteristics. The reproducibility of these distinct maps across subjects and paradigms is relatively unexplored domain, and the topic of the present study. To address this, we conducted separate group ICA decompositions of EEG spatiospectral patterns on data collected during three different paradigms or tasks (resting-state, semantic decision task and visual oddball task). K-means clustering analysis of back-reconstructed individual subject maps demonstrates that fourteen different independent spatiospectral maps are present across the different paradigms/tasks, i.e. they are generally stable.
Clemens, Béla; Piros, Pálma; Bessenyei, Mónika; Tóth, Márton; Hollódy, Katalin; Kondákor, István
2008-10-01
Anatomical localization of the cortical effect of lamotrigine (LTG) in patients with idiopathic generalized epilepsy (IGE). 19 patients with untreated IGE were investigated. EEG was recorded in the untreated condition and 3 months later when LTG treatment abolished the seizures. 19-channel EEG was recorded, and a total of 2min artifact-free, waking EEG was processed to low-resolution electromagnetic tomography (LORETA) analysis. Activity (that is, current source density, A/m(2)) was computed in four frequency bands (delta, theta, alpha, and beta), for 2394 voxels that represented the cortical gray matter and the hippocampi. Group differences between the untreated and treated conditions were computed for the four bands and all voxels by multiple t-tests for interdependent datasets. The results were presented in terms of anatomical distribution and statistical significance. p<0.01 (uncorrected) changes (decrease of activity) emerged in the theta and the alpha bands. Theta activity decreased in a large cluster of voxels including parts of the temporal, parietal, occipital cortex bilaterally, and in the transverse temporal gyri, insula, hippocampus, and uncus on the right side. Alpha activity decreased in a relatively smaller cortical area involving the right temporo-parietal junction and surrounding parts of the cortex, and part of the insula on the right side. LTG decreased theta activity in several cortical areas where abnormally increased theta activity had been found in a prior study in another cohort of untreated IGE patients [Clemens, B., Bessenyei, M., Piros, P., Tóth, M., Seress, L., Kondákor, I., 2007b. Characteristic distribution of interictal brain electrical activity in idiopathic generalized epilepsy. Epilepsia 48, 941-949]. These LTG-related changes might be related to the decrease of seizure propensity in IGE.
Katner, S N; Slawecki, C J; Ehlers, C L
2002-03-01
Several studies have provided indirect evidence that neuropeptide Y (NPY) may play a role in the regulation of ethanol consumption. However, the direct effects of central NPY administration on ethanol drinking are unclear. This study examined the effects of NPY on ethanol, sucrose, and food consumption as well as its concomitant effects on the cortical EEG. Wistar rats were implanted with cortical recording electrodes and a cannula in the third ventricle after using a sucrose substitution procedure to establish ethanol self-administration. NPY (0-15 microg/3.0 microl) was infused into the third ventricle prior to drinking sessions, when 10% ethanol (10E), 2% sucrose (2S), 0.5% sucrose (0.5S), or food were available. Behavior and cortical EEG were monitored during the sessions. NPY had no effect on the intake of 10E, 2S, or 0.5S, but NPY (15 microg/3.0 microl) significantly increased food intake. Under baseline drinking conditions, EEG power in the 6-8 Hz range was significantly greater when 2S was consumed compared to 10E. NPY decreased power in the 8-16 Hz range, decreased peak frequency in the 6-8 Hz range, and increased peak frequency in the 32-50 Hz range when 10E or 2S was available. These data suggest that NPY administration into the third ventricle preferentially regulates feeding compared to ethanol or sucrose drinking. In addition, since NPY significantly altered the cortical EEG in the absence of effects on ethanol and sucrose consumption, these data may indicate that NPY's cortical EEG effects are more related to its sedative or anxiolytic properties, rather than any effect on consumption.
Relations among EEG-alpha asymmetry and positivity personality trait.
Alessandri, Guido; Caprara, Gian Vittorio; De Pascalis, Vilfredo
2015-07-01
The present study investigates cortical structures associated with personality dimension of positivity (POS) by using a standardized low-resolution brain electromagnetic tomography (sLORETA), which provides EEG localization measures that are independent of the recording reference. Resting EEG and self-report measures of positivity, self-esteem, life satisfaction, and optimism were collected from 51 female undergraduates. EEG was recorded across 29 scalp sites. Anterior and posterior source alpha asymmetries of cortical activation were obtained by using sLORETA. Based on previous research findings, 10 frontal and 6 parietal regions of interest (ROI) were derived. Alpha asymmetry in the posterior cingulate (i.e., BA23 and BA31) was uniquely associated with both POS scores. These areas are, hypothetically, part of a complex default-mode neural network (DMN). The activity in the DMN usually increases during tasks that invoke self-referential processing, such as responding to statements describing one's personality, attitudes, or preferences. Importantly, the cortical structures associated with POS were different from those associated with indicators. Indeed, measures of "optimism" failed to maintain a significant correlation with any of the previously significant ROI, but "self-esteem" and "life satisfaction" revealed robust associations with alpha asymmetry at the precuneus (i.e., BA7), after controlling for POS residual scores. Present findings support the assumption that POS is a basic disposition that reflects the concerted activity of brain structures that are essential for integrating self-referential thought and autobiographical memories and for assigning a positive valence to one's experience and attitude toward the future. Copyright © 2015 Elsevier Inc. All rights reserved.
Cerebello-cortical network fingerprints differ between essential, Parkinson's and mimicked tremors.
Muthuraman, Muthuraman; Raethjen, Jan; Koirala, Nabin; Anwar, Abdul Rauf; Mideksa, Kidist G; Elble, Rodger; Groppa, Sergiu; Deuschl, Günter
2018-06-01
Cerebello-thalamo-cortical loops play a major role in the emergence of pathological tremors and voluntary rhythmic movements. It is unclear whether these loops differ anatomically or functionally in different types of tremor. We compared age- and sex-matched groups of patients with Parkinson's disease or essential tremor and healthy controls (n = 34 per group). High-density 256-channel EEG and multi-channel EMG from extensor and flexor muscles of both wrists were recorded simultaneously while extending the hands against gravity with the forearms supported. Tremor was thereby recorded from patients, and voluntarily mimicked tremor was recorded from healthy controls. Tomographic maps of EEG-EMG coherence were constructed using a beamformer algorithm coherent source analysis. The direction and strength of information flow between different coherent sources were estimated using time-resolved partial-directed coherence analyses. Tremor severity and motor performance measures were correlated with connection strengths between coherent sources. The topography of oscillatory coherent sources in the cerebellum differed significantly among the three groups, but the cortical sources in the primary sensorimotor region and premotor cortex were not significantly different. The cerebellar and cortical source combinations matched well with known cerebello-thalamo-cortical connections derived from functional MRI resting state analyses according to the Buckner-atlas. The cerebellar sources for Parkinson's tremor and essential tremor mapped primarily to primary sensorimotor cortex, but the cerebellar source for mimicked tremor mapped primarily to premotor cortex. Time-resolved partial-directed coherence analyses revealed activity flow mainly from cerebellum to sensorimotor cortex in Parkinson's tremor and essential tremor and mainly from cerebral cortex to cerebellum in mimicked tremor. EMG oscillation flowed mainly to the cerebellum in mimicked tremor, but oscillation flowed mainly from the cerebellum to EMG in Parkinson's and essential tremor. The topography of cerebellar involvement differed among Parkinson's, essential and mimicked tremors, suggesting different cerebellar mechanisms in tremorogenesis. Indistinguishable areas of sensorimotor cortex and premotor cerebral cortex were involved in all three tremors. Information flow analyses suggest that sensory feedback and cortical efferent copy input to cerebellum are needed to produce mimicked tremor, but tremor in Parkinson's disease and essential tremor do not depend on these mechanisms. Despite the subtle differences in cerebellar source topography, we found no evidence that the cerebellum is the source of oscillation in essential tremor or that the cortico-bulbo-cerebello-thalamocortical loop plays different tremorogenic roles in Parkinson's and essential tremor. Additional studies are needed to decipher the seemingly subtle differences in cerebellocortical function in Parkinson's and essential tremors.
Sivakumar, Siddharth S; Namath, Amalia G; Galán, Roberto F
2016-01-01
Previous work from our lab has demonstrated how the connectivity of brain circuits constrains the repertoire of activity patterns that those circuits can display. Specifically, we have shown that the principal components of spontaneous neural activity are uniquely determined by the underlying circuit connections, and that although the principal components do not uniquely resolve the circuit structure, they do reveal important features about it. Expanding upon this framework on a larger scale of neural dynamics, we have analyzed EEG data recorded with the standard 10-20 electrode system from 41 neurologically normal children and adolescents during stage 2, non-REM sleep. We show that the principal components of EEG spindles, or sigma waves (10-16 Hz), reveal non-propagating, standing waves in the form of spherical harmonics. We mathematically demonstrate that standing EEG waves exist when the spatial covariance and the Laplacian operator on the head's surface commute. This in turn implies that the covariance between two EEG channels decreases as the inverse of their relative distance; a relationship that we corroborate with empirical data. Using volume conduction theory, we then demonstrate that superficial current sources are more synchronized at larger distances, and determine the characteristic length of large-scale neural synchronization as 1.31 times the head radius, on average. Moreover, consistent with the hypothesis that EEG spindles are driven by thalamo-cortical rather than cortico-cortical loops, we also show that 8 additional patients with hypoplasia or complete agenesis of the corpus callosum, i.e., with deficient or no connectivity between cortical hemispheres, similarly exhibit standing EEG waves in the form of spherical harmonics. We conclude that spherical harmonics are a hallmark of spontaneous, large-scale synchronization of neural activity in the brain, which are associated with unconscious, light sleep. The analogy with spherical harmonics in quantum mechanics suggests that the variances (eigenvalues) of the principal components follow a Boltzmann distribution, or equivalently, that standing waves are in a sort of "thermodynamic" equilibrium during non-REM sleep. By extension, we speculate that consciousness emerges as the brain dynamics deviate from such equilibrium.
Sivakumar, Siddharth S.; Namath, Amalia G.; Galán, Roberto F.
2016-01-01
Previous work from our lab has demonstrated how the connectivity of brain circuits constrains the repertoire of activity patterns that those circuits can display. Specifically, we have shown that the principal components of spontaneous neural activity are uniquely determined by the underlying circuit connections, and that although the principal components do not uniquely resolve the circuit structure, they do reveal important features about it. Expanding upon this framework on a larger scale of neural dynamics, we have analyzed EEG data recorded with the standard 10–20 electrode system from 41 neurologically normal children and adolescents during stage 2, non-REM sleep. We show that the principal components of EEG spindles, or sigma waves (10–16 Hz), reveal non-propagating, standing waves in the form of spherical harmonics. We mathematically demonstrate that standing EEG waves exist when the spatial covariance and the Laplacian operator on the head's surface commute. This in turn implies that the covariance between two EEG channels decreases as the inverse of their relative distance; a relationship that we corroborate with empirical data. Using volume conduction theory, we then demonstrate that superficial current sources are more synchronized at larger distances, and determine the characteristic length of large-scale neural synchronization as 1.31 times the head radius, on average. Moreover, consistent with the hypothesis that EEG spindles are driven by thalamo-cortical rather than cortico-cortical loops, we also show that 8 additional patients with hypoplasia or complete agenesis of the corpus callosum, i.e., with deficient or no connectivity between cortical hemispheres, similarly exhibit standing EEG waves in the form of spherical harmonics. We conclude that spherical harmonics are a hallmark of spontaneous, large-scale synchronization of neural activity in the brain, which are associated with unconscious, light sleep. The analogy with spherical harmonics in quantum mechanics suggests that the variances (eigenvalues) of the principal components follow a Boltzmann distribution, or equivalently, that standing waves are in a sort of “thermodynamic” equilibrium during non-REM sleep. By extension, we speculate that consciousness emerges as the brain dynamics deviate from such equilibrium. PMID:27445777
Onojima, Takayuki; Kitajo, Keiichi; Mizuhara, Hiroaki
2017-01-01
Neural oscillation is attracting attention as an underlying mechanism for speech recognition. Speech intelligibility is enhanced by the synchronization of speech rhythms and slow neural oscillation, which is typically observed as human scalp electroencephalography (EEG). In addition to the effect of neural oscillation, it has been proposed that speech recognition is enhanced by the identification of a speaker's motor signals, which are used for speech production. To verify the relationship between the effect of neural oscillation and motor cortical activity, we measured scalp EEG, and simultaneous EEG and functional magnetic resonance imaging (fMRI) during a speech recognition task in which participants were required to recognize spoken words embedded in noise sound. We proposed an index to quantitatively evaluate the EEG phase effect on behavioral performance. The results showed that the delta and theta EEG phase before speech inputs modulated the participant's response time when conducting speech recognition tasks. The simultaneous EEG-fMRI experiment showed that slow EEG activity was correlated with motor cortical activity. These results suggested that the effect of the slow oscillatory phase was associated with the activity of the motor cortex during speech recognition.
Volf, N V; Belousova, L V; Knyazev, G G; Kulikov, A V
2015-01-22
Human brain oscillations represent important features of information processing and are highly heritable. Gender has been observed to affect association between the 5-HTTLPR (serotonin-transporter-linked polymorphic region) polymorphism and various endophenotypes. This study aimed to investigate the effects of 5-HTTLPR on the spontaneous electroencephalography (EEG) activity in healthy male and female subjects. DNA samples extracted from buccal swabs and resting EEG recorded at 60 standard leads were collected from 210 (101 men and 109 women) volunteers. Spectral EEG power estimates and cortical sources of EEG activity were investigated. It was shown that effects of 5-HTTLPR polymorphism on electrical activity of the brain vary as a function of gender. Women with the S/L genotype had greater global EEG power compared to men with the same genotype. In men, current source density was markedly different among genotype groups in only alpha 2 and alpha 3 frequency ranges: S/S allele carriers had higher current source density estimates in the left inferior parietal lobule in comparison with the L/L group. In women, genotype difference in global power asymmetry was found in the central-temporal region. Contrasting L/L and S/L genotype carriers also yielded significant effects in the right hemisphere inferior parietal lobule and the right postcentral gyrus with L/L genotype carriers showing lower current source density estimates than S/L genotype carriers in all but gamma bands. So, in women, the effects of 5-HTTLPR polymorphism were associated with modulation of the EEG activity in a wide range of EEG frequencies. The significance of the results lies in the demonstration of gene by sex interaction with resting EEG that has implications for understanding sex-related differences in affective states, emotion and cognition. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.
Memories of attachment hamper EEG cortical connectivity in dissociative patients.
Farina, Benedetto; Speranza, Anna Maria; Dittoni, Serena; Gnoni, Valentina; Trentini, Cristina; Vergano, Carola Maggiora; Liotti, Giovanni; Brunetti, Riccardo; Testani, Elisa; Della Marca, Giacomo
2014-08-01
In this study, we evaluated cortical connectivity modifications by electroencephalography (EEG) lagged coherence analysis, in subjects with dissociative disorders and in controls, after retrieval of attachment memories. We asked thirteen patients with dissociative disorders and thirteen age- and sex-matched healthy controls to retrieve personal attachment-related autobiographical memories through adult attachment interviews (AAI). EEG was recorded in the closed eyes resting state before and after the AAI. EEG lagged coherence before and after AAI was compared in all subjects. In the control group, memories of attachment promoted a widespread increase in EEG connectivity, in particular in the high-frequency EEG bands. Compared to controls, dissociative patients did not show an increase in EEG connectivity after the AAI. Conclusions: These results shed light on the neurophysiology of the disintegrative effect of retrieval of traumatic attachment memories in dissociative patients.
Acute effects of exercise on mood and EEG activity in healthy young subjects: a systematic review.
Lattari, Eduardo; Portugal, Eduardo; Moraes, Helena; Machado, Sérgio; Santos, Tony M; Deslandes, Andrea C
2014-01-01
Electroencephalography has been used to establish the relationship among cortical activity, exercise and mood, such as asymmetry, absolute and relative power. The purpose of this study was to systematically review the influence of cortical activity on mood state induced by exercise. The Preferred Reporting Items in Systematic reviews and Meta-Analyses was followed in this study. The studies were retrieved from MEDLINE/PubMed, ISI Web of Knowledge and SciELO. Search was conducted in all databases using the following terms: EEG asymmetry, sLORETA, exercise, with affect, mood and emotions. Based on the defined criteria, a total of 727 articles were found in the search conducted in the literature (666 in Pubmed, 54 in ISI Web of Science, 2 in SciELO and 5 in other data sources). Total of 11 studies were selected which properly met the criteria for this review. Nine out of 11 studies used the frontal asymmetry, four used absolute and relative power and one used sLORETA. With regard to changes in cortical activity and mood induced by exercise, six studies attributed this result to different intensities, one to duration, one to type of exercise and one to fitness level. In general, EEG measures showed contradictory evidence of its ability to predict or modulate psychological mood states through exercise intervention.
Sharma, Kanishka; Chandra, Sushil; Dubey, Ashok Kumar
2018-01-01
Background: Rajyoga meditation is taught by Prajapita Brahmakumaris World Spiritual University (Brahmakumaris) and has been followed by more than one million followers across the globe. However, rare studies were conducted on physiological aspects of rajyoga meditation using electroencephalography (EEG). Band power and cortical asymmetry were not studied with Rajyoga meditators. Aims: This study aims to investigate the effect of regular meditation practice on EEG brain dynamics in low-frequency bands of long-term Rajyoga meditators. Settings and Design: Subjects were matched for age in both groups. Lower frequency EEG bands were analyzed in resting and during meditation. Materials and Methods: Twenty-one male long-term meditators (LTMs) and same number of controls were selected to participate in study as par inclusion criteria. Semi high-density EEG was recorded before and during meditation in LTM group and resting in control group. The main outcome of the study was spectral power of alpha and theta bands and cortical (hemispherical) asymmetry calculated using band power. Statistical Analysis: One-way ANOVA was performed to find the significant difference between EEG spectral properties of groups. Pearson's Chi-square test was used to find difference among demographics data. Results: Results reveal high-band power in alpha and theta spectra in meditators. Cortical asymmetry calculated through EEG power was also found to be high in frontal as well as parietal channels. However, no correlation was seen between the experience of meditation (years, hours) practice and EEG indices. Conclusion: Overall findings indicate contribution of smaller frequencies (alpha and theta) while maintaining meditative experience. This suggests a positive impact of meditation on frontal and parietal areas of brain, involved in the processes of regulation of selective and sustained attention as well as provide evidence about their involvement in emotion and cognitive processing. PMID:29343928
Delessert, Alexandre; Espa, Fabrice; Rossetti, Andrea; Lavigne, Gilles; Tafti, Mehdi; Heinzer, Raphael
2010-01-01
Background: During sleep, sudden drops in pulse wave amplitude (PWA) measured by pulse oximetry are commonly associated with simultaneous arousals and are thought to result from autonomic vasoconstriction. In the present study, we determine whether PWA drops were associated with changes in cortical activity as determined by EEG spectral analysis. Methods: A 20% decrease in PWA was chosen as a minimum for a drop. A total of 1085 PWA drops from 10 consecutive sleep recordings were analyzed. EEG spectral analysis was performed over 5 consecutive epochs of 5 seconds: 2 before, 1 during, and 2 after the PWA drop. EEG spectral analysis was performed over delta, theta, alpha, sigma, and beta frequency bands. Within each frequency band, power density was compared across the five 5-sec epochs. Presence or absence of visually scored EEG arousals were adjudicated by an investigator blinded to the PWA signal and considered associated with PWA drop if concomitant. Results: A significant increase in EEG power density in all EEG frequency bands was found during PWA drops (P < 0.001) compared to before and after drop. Even in the absence of visually scored arousals, PWA drops were associated with a significant increase in EEG power density (P < 0.001) in most frequency bands. Conclusions: Drops in PWA are associated with a significant increase in EEG power density, suggesting that these events can be used as a surrogate for changes in cortical activity during sleep. This approach may prove of value in scoring respiratory events on limited-channel (type III) portable monitors. Citation: Delessert A; Espa F; Rossetti A; Lavigne G; Tafti M; Heinzer R. Pulse wave amplitude drops during sleep are reliable surrogate markers of changes in cortical activity. SLEEP 2010;33(12):1687-1692. PMID:21120131
A continuous mapping of sleep states through association of EEG with a mesoscale cortical model.
Lopour, Beth A; Tasoglu, Savas; Kirsch, Heidi E; Sleigh, James W; Szeri, Andrew J
2011-04-01
Here we show that a mathematical model of the human sleep cycle can be used to obtain a detailed description of electroencephalogram (EEG) sleep stages, and we discuss how this analysis may aid in the prediction and prevention of seizures during sleep. The association between EEG data and the cortical model is found via locally linear embedding (LLE), a method of dimensionality reduction. We first show that LLE can distinguish between traditional sleep stages when applied to EEG data. It reliably separates REM and non-REM sleep and maps the EEG data to a low-dimensional output space where the sleep state changes smoothly over time. We also incorporate the concept of strongly connected components and use this as a method of automatic outlier rejection for EEG data. Then, by using LLE on a hybrid data set containing both sleep EEG and signals generated from the mesoscale cortical model, we quantify the relationship between the data and the mathematical model. This enables us to take any sample of sleep EEG data and associate it with a position among the continuous range of sleep states provided by the model; we can thus infer a trajectory of states as the subject sleeps. Lastly, we show that this method gives consistent results for various subjects over a full night of sleep and can be done in real time.
NASA Astrophysics Data System (ADS)
Nguyen, Thinh; Potter, Thomas; Grossman, Robert; Zhang, Yingchun
2018-06-01
Objective. Neuroimaging has been employed as a promising approach to advance our understanding of brain networks in both basic and clinical neuroscience. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) represent two neuroimaging modalities with complementary features; EEG has high temporal resolution and low spatial resolution while fMRI has high spatial resolution and low temporal resolution. Multimodal EEG inverse methods have attempted to capitalize on these properties but have been subjected to localization error. The dynamic brain transition network (DBTN) approach, a spatiotemporal fMRI constrained EEG source imaging method, has recently been developed to address these issues by solving the EEG inverse problem in a Bayesian framework, utilizing fMRI priors in a spatial and temporal variant manner. This paper presents a computer simulation study to provide a detailed characterization of the spatial and temporal accuracy of the DBTN method. Approach. Synthetic EEG data were generated in a series of computer simulations, designed to represent realistic and complex brain activity at superficial and deep sources with highly dynamical activity time-courses. The source reconstruction performance of the DBTN method was tested against the fMRI-constrained minimum norm estimates algorithm (fMRIMNE). The performances of the two inverse methods were evaluated both in terms of spatial and temporal accuracy. Main results. In comparison with the commonly used fMRIMNE method, results showed that the DBTN method produces results with increased spatial and temporal accuracy. The DBTN method also demonstrated the capability to reduce crosstalk in the reconstructed cortical time-course(s) induced by neighboring regions, mitigate depth bias and improve overall localization accuracy. Significance. The improved spatiotemporal accuracy of the reconstruction allows for an improved characterization of complex neural activity. This improvement can be extended to any subsequent brain connectivity analyses used to construct the associated dynamic brain networks.
Ingber, Lester; Nunez, Paul L
2011-02-01
The dynamic behavior of scalp potentials (EEG) is apparently due to some combination of global and local processes with important top-down and bottom-up interactions across spatial scales. In treating global mechanisms, we stress the importance of myelinated axon propagation delays and periodic boundary conditions in the cortical-white matter system, which is topologically close to a spherical shell. By contrast, the proposed local mechanisms are multiscale interactions between cortical columns via short-ranged non-myelinated fibers. A mechanical model consisting of a stretched string with attached nonlinear springs demonstrates the general idea. The string produces standing waves analogous to large-scale coherent EEG observed in some brain states. The attached springs are analogous to the smaller (mesoscopic) scale columnar dynamics. Generally, we expect string displacement and EEG at all scales to result from both global and local phenomena. A statistical mechanics of neocortical interactions (SMNI) calculates oscillatory behavior consistent with typical EEG, within columns, between neighboring columns via short-ranged non-myelinated fibers, across cortical regions via myelinated fibers, and also derives a string equation consistent with the global EEG model. Copyright © 2010 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Hebden, Jeremy C.; Cooper, Robert J.; Gibson, Adam; Everdell, Nick; Austin, Topun
2012-06-01
An optical imaging system has been developed which uses measurements of diffusely reflected near-infrared light to produce maps of changes in blood flow and oxygenation occurring within the cerebral cortex. Optical sources and detectors are coupled to the head via an array of optical fibers, on a probe held in contact with the scalp, and data is collected at a rate of 10 Hz. A clinical electroencephalography (EEG) system has been integrated with the optical system to enable simultaneous observation of electrical and hemodynamic activity in the cortex of neurologically compromised newborn infants diagnosed with seizures. Studies have made a potentially critically important discovery of previously unknown transient hemodynamic events in infants treated with anticonvulsant medication. We observed repeated episodes of small increases in cortical oxyhemoglobin concentration followed by a profound decrease in 3 of 4 infants studied, each with cerebral injury who presented with neonatal seizures. This was not accompanied by clinical or EEG seizure activity and was not present in nineteen matched controls. The underlying cause of these changes is currently unknown. We tentatively suggest that our results may be associated with a phenomenon known as cortical spreading depolarization, not previously observed in the infant brain.
Analysis of electrical and magnetic bio-signals associated with motor performance and fatigue
NASA Astrophysics Data System (ADS)
Yao, Bing
This dissertation reports findings centered principally on comprehensive research related to human bio-signals (EEG, MEG, EMG and fMRI) acquired during repetitive maximal voluntary contractions (MVC) that induced severe fatigue. Fatigue is a common experience that reduces productivity and quality of life and increases chances of injury. Although abundant information has been gained in the last several decades regarding muscular and spinal-level mechanisms of muscle fatigue, very little is known about how cortical centers control and respond to fatigue. The main purpose of this study was to examine the fatigue effects on the central nervous system by analyzing the bio-signals collected in the designed experiments. Healthy human subjects were asked to perform a series of repetitive handgrip MVCs with their dominant hand until exhaustion. Handgrip forces, electrical activity (EMG) from primary and non-primary muscles, and EEG, MEG, or fMRI signals from different locations of the brain were recorded simultaneously. The time series data were segmented into several physiologically meaningful epochs (time phases), from rest to preparation to movement execution/sustaining. A series of studies, including motor-related cortical potential (MRCP) analysis, power spectrum analysis, time-frequency (spectrogram) analysis of EEG, EEG source localization and nonlinear analysis (fractal dimension and largest Lyapunov exponent), and fMRI analysis, was applied to the data. We hypothesized that the fatigue effects would act differently on brain signals of different phases. The MRCP results showed that the negative potential (NP) related to motor task preparation only had minimal changes with fatigue. The power of all EEG frequencies did not alter significantly during the preparation phase but decreased significantly during the sustained phase of the contraction. The fractal dimension and the largest Lyapunov exponent decreased significantly during the sustained phase as fatigue progressed. On the other hand, the fMRI results only exhibited insignificant fatigue-related reductions of brain activation volume and no significant change of dipole strength derived from multi-channel EEG data. These results have been interpreted by a hypothetical neurophysiological model, in which two groups of cortical neurons (phasic and tonic) are preferentially activated in each physiological phase of the voluntary motor action.
Dutta, Anirban; Jacob, Athira; Chowdhury, Shubhajit Roy; Das, Abhijit; Nitsche, Michael A
2015-04-01
A method for electroencephalography (EEG) - near-infrared spectroscopy (NIRS) based assessment of neurovascular coupling (NVC) during anodal transcranial direct current stimulation (tDCS). Anodal tDCS modulates cortical neural activity leading to a hemodynamic response, which was used to identify impaired NVC functionality. In this study, the hemodynamic response was estimated with NIRS. NIRS recorded changes in oxy-hemoglobin (HbO2) and deoxy-hemoglobin (Hb) concentrations during anodal tDCS-induced activation of the cortical region located under the electrode and in-between the light sources and detectors. Anodal tDCS-induced alterations in the underlying neuronal current generators were also captured with EEG. Then, a method for the assessment of NVC underlying the site of anodal tDCS was proposed that leverages the Hilbert-Huang Transform. The case series including four chronic (>6 months) ischemic stroke survivors (3 males, 1 female from age 31 to 76) showed non-stationary effects of anodal tDCS on EEG that correlated with the HbO2 response. Here, the initial dip in HbO2 at the beginning of anodal tDCS corresponded with an increase in the log-transformed mean-power of EEG within 0.5Hz-11.25Hz frequency band. The cross-correlation coefficient changed signs but was comparable across subjects during and after anodal tDCS. The log-transformed mean-power of EEG lagged HbO2 response during tDCS but then led post-tDCS. This case series demonstrated changes in the degree of neurovascular coupling to a 0.526 A/m(2) square-pulse (0-30 s) of anodal tDCS. The initial dip in HbO2 needs to be carefully investigated in a larger cohort, for example in patients with small vessel disease.
Claudio, Babiloni; Claudio, Del Percio; Marina, Boccardi; Roberta, Lizio; Susanna, Lopez; Filippo, Carducci; Nicola, Marzano; Andrea, Soricelli; Raffaele, Ferri; Ivano, Triggiani Antonio; Annapaola, Prestia; Serenella, Salinari; Rasser Paul, E; Erol, Basar; Francesco, Famà; Flavio, Nobili; Görsev, Yener; Durusu, Emek-Savaş Derya; Gesualdo, Loreto; Ciro, Mundi; Thompson Paul, M; Rossini Paolo, M.; Frisoni Giovanni, B
2014-01-01
Occipital sources of resting state electroencephalographic (EEG) alpha rhythms are abnormal, at the group level, in patients with amnesic mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Here we evaluated the hypothesis that amplitude of these occipital sources is related to neurodegeneration in occipital lobe as measured by magnetic resonance imaging (MRI). Resting-state eyes-closed EEG rhythms were recorded in 45 healthy elderly (Nold), 100 MCI, and 90 AD subjects. Neurodegeneration of occipital lobe was indexed by weighted averages of gray matter density (GMD), estimated from structural MRIs. EEG rhythms of interest were alpha 1 (8–10.5 Hz) and alpha 2 (10.5–13 Hz). EEG cortical sources were estimated by low resolution brain electromagnetic tomography (LORETA). Results showed a positive correlation between occipital GMD and amplitude of occipital alpha 1 sources in Nold, MCI and AD subjects as a whole group (r=0.3, p=0.000004, N=235). Furthermore, there was a positive correlation between amplitude of occipital alpha 1 sources and cognitive status as revealed by Mini Mental State Evaluation (MMSE) score across all subjects (r=0.38, p=0.000001, N=235). Finally, amplitude of occipital alpha 1 sources allowed a moderate classification of individual Nold and AD subjects (sensitivity: 87.8%; specificity: 66.7%; area under the Receiver Operating Characteristic (ROC) curve: 0.81). These results suggest that the amplitude of occipital sources of resting state alpha rhythms is related to AD neurodegeneration in occipital lobe along pathological aging. PMID:25442118
Riedner, Brady A.; Goldstein, Michael R.; Plante, David T.; Rumble, Meredith E.; Ferrarelli, Fabio; Tononi, Giulio; Benca, Ruth M.
2016-01-01
Study Objectives: To examine nonrapid eye movement (NREM) sleep in insomnia using high-density electroencephalography (EEG). Methods: All-night sleep recordings with 256 channel high-density EEG were analyzed for 8 insomnia subjects (5 females) and 8 sex and age-matched controls without sleep complaints. Spectral analyses were conducted using unpaired t-tests and topographical differences between groups were assessed using statistical non-parametric mapping. Five minute segments of deep NREM sleep were further analyzed using sLORETA cortical source imaging. Results: The initial topographic analysis of all-night NREM sleep EEG revealed that insomnia subjects had more high-frequency EEG activity (> 16 Hz) compared to good sleeping controls and that the difference between groups was widespread across the scalp. In addition, the analysis also showed that there was a more circumscribed difference in theta (4–8 Hz) and alpha (8–12 Hz) power bands between groups. When deep NREM sleep (N3) was examined separately, the high-frequency difference between groups diminished, whereas the higher regional alpha activity in insomnia subjects persisted. Source imaging analysis demonstrated that sensory and sensorimotor cortical areas consistently exhibited elevated levels of alpha activity during deep NREM sleep in insomnia subjects relative to good sleeping controls. Conclusions: These results suggest that even during the deepest stage of sleep, sensory and sensorimotor areas in insomnia subjects may still be relatively active compared to control subjects and to the rest of the sleeping brain. Citation: Riedner BA, Goldstein MR, Plante DT, Rumble ME, Ferrarelli F, Tononi G, Benca RM. Regional patterns of elevated alpha and high-frequency electroencephalographic activity during nonrapid eye movement sleep in chronic insomnia: a pilot study. SLEEP 2016;39(4):801–812. PMID:26943465
Bluetooth Communication Interface for EEG Signal Recording in Hyperbaric Chambers.
Pastena, Lucio; Formaggio, Emanuela; Faralli, Fabio; Melucci, Massimo; Rossi, Marco; Gagliardi, Riccardo; Ricciardi, Lucio; Storti, Silvia F
2015-07-01
Recording biological signals inside a hyperbaric chamber poses technical challenges (the steel walls enclosing it greatly attenuate or completely block the signals as in a Faraday cage), practical (lengthy cables creating eddy currents), and safety (sparks hazard from power supply to the electronic apparatus inside the chamber) which can be overcome with new wireless technologies. In this technical report we present the design and implementation of a Bluetooth system for electroencephalographic (EEG) recording inside a hyperbaric chamber and describe the feasibility of EEG signal transmission outside the chamber. Differently from older systems, this technology allows the online recording of amplified signals, without interference from eddy currents. In an application of this technology, we measured EEG activity in professional divers under three experimental conditions in a hyperbaric chamber to determine how oxygen, assumed at a constant hyperbaric pressure of 2.8 ATA , affects the bioelectrical activity. The EEG spectral power estimated by fast Fourier transform and the cortical sources of the EEG rhythms estimated by low-resolution brain electromagnetic analysis were analyzed in three different EEG acquisitions: breathing air at sea level; breathing oxygen at a simulated depth of 18 msw, and breathing air at sea level after decompression.
Influences of brain development and ageing on cortical interactive networks.
Zhu, Chengyu; Guo, Xiaoli; Jin, Zheng; Sun, Junfeng; Qiu, Yihong; Zhu, Yisheng; Tong, Shanbao
2011-02-01
To study the effect of brain development and ageing on the pattern of cortical interactive networks. By causality analysis of multichannel electroencephalograph (EEG) with partial directed coherence (PDC), we investigated the different neural networks involved in the whole cortex as well as the anterior and posterior areas in three age groups, i.e., children (0-10 years), mid-aged adults (26-38 years) and the elderly (56-80 years). By comparing the cortical interactive networks in different age groups, the following findings were concluded: (1) the cortical interactive network in the right hemisphere develops earlier than its left counterpart in the development stage; (2) the cortical interactive network of anterior cortex, especially at C3 and F3, is demonstrated to undergo far more extensive changes, compared with the posterior area during brain development and ageing; (3) the asymmetry of the cortical interactive networks declines during ageing with more loss of connectivity in the left frontal and central areas. The age-related variation of cortical interactive networks from resting EEG provides new insights into brain development and ageing. Our findings demonstrated that the PDC analysis of EEG is a powerful approach for characterizing the cortical functional connectivity during brain development and ageing. Copyright © 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Esposito, Fabrizio; Singer, Neomi; Podlipsky, Ilana; Fried, Itzhak; Hendler, Talma; Goebel, Rainer
2013-02-01
Linking regional metabolic changes with fluctuations in the local electromagnetic fields directly on the surface of the human cerebral cortex is of tremendous importance for a better understanding of detailed brain processes. Functional magnetic resonance imaging (fMRI) and intra-cranial electro-encephalography (iEEG) measure two technically unrelated but spatially and temporally complementary sets of functional descriptions of human brain activity. In order to allow fine-grained spatio-temporal human brain mapping at the population-level, an effective comparative framework for the cortex-based inter-subject analysis of iEEG and fMRI data sets is needed. We combined fMRI and iEEG recordings of the same patients with epilepsy during alternated intervals of passive movie viewing and music listening to explore the degree of local spatial correspondence and temporal coupling between blood oxygen level dependent (BOLD) fMRI changes and iEEG spectral power modulations across the cortical surface after cortex-based inter-subject alignment. To this purpose, we applied a simple model of the iEEG activity spread around each electrode location and the cortex-based inter-subject alignment procedure to transform discrete iEEG measurements into cortically distributed group patterns by establishing a fine anatomic correspondence of many iEEG cortical sites across multiple subjects. Our results demonstrate the feasibility of a multi-modal inter-subject cortex-based distributed analysis for combining iEEG and fMRI data sets acquired from multiple subjects with the same experimental paradigm but with different iEEG electrode coverage. The proposed iEEG-fMRI framework allows for improved group statistics in a common anatomical space and preserves the dynamic link between the temporal features of the two modalities. Copyright © 2012 Elsevier Inc. All rights reserved.
Slawecki, Craig J; Grahame, Nicholas J; Roth, Jennifer; Katner, Simon N; Ehlers, C L
2003-01-31
Neurophysiological measures, such as decreased P300 amplitude and altered EEG alpha activity, have been associated with increased alcoholism risk. The purpose of the present study was to extend the assessment of the neurophysiological indices associated with alcohol consumption to a recently developed mouse model of high ethanol consumption, the first replicate line of high alcohol preferring (HAP-1) and low alcohol preferring (LAP-1) mice. Male HAP-1, LAP-1, and HS mice from the Institute for Behavioral Genetics at the University of Colorado Health Science Center (i.e., HS/Ibg mice) were implanted with cortical electrodes. EEG activity, and event related potentials (ERPs) were then examined. Following electrophysiological assessment, ethanol preference was assessed to examine the relationship between neurophysiological indices and ethanol consumption. EEG analyses revealed that HAPs and HS/Ibgs had greater peak frequency in the 2-4-Hz band and lower peak frequency in the 6-8- and 1-50-Hz bands of the cortical EEG compared to LAPs. Compared to HAPs, LAPs and HS/Ibgs had decreased peak EEG frequency in the 8-16-Hz band. Decreased parietal cortical power from 8 to 50 Hz was associated with high initial ethanol preference in HAP mice. In regards to ERPs, P1 amplitude was greater in HAPs compared to both LAPs and HS/Ibgs and the P3 latency in LAPs was decreased compared to both HAPs and HS/Ibgs. As expected, HAPs consumed more ethanol and had higher ethanol preference than LAPs and HS/Ibgs. There were no significant differences in ethanol intake or preference between HS/Ibgs and LAPs. These data indicate that selective breeding of the HAP and LAP lines has resulted in the divergence of EEG and ERP phenotypes. The differences observed suggest that increased cortical P1 amplitude and altered cortical EEG activity in the 8-50-Hz frequency range may be neurophysiological 'risk factors' associated with high ethanol consumption in mice. Decreased P3 latency in LAPs compared to HAPs and HS/Ibgs mice may be a 'protective factor'.
Craniux: A LabVIEW-Based Modular Software Framework for Brain-Machine Interface Research
2011-01-01
open-source BMI software solu- tions are currently available, we feel that the Craniux software package fills a specific need in the realm of BMI...data, such as cortical source imaging using EEG or MEG recordings. It is with these characteristics in mind that we feel the Craniux software package...S. Adee, “Dean Kamen’s ‘luke arm’ prosthesis readies for clinical trials,” IEEE Spectrum, February 2008, http://spectrum .ieee.org/biomedical
Differential Sources for 2 Neural Signatures of Target Detection: An Electrocorticography Study.
Kam, J W Y; Szczepanski, S M; Canolty, R T; Flinker, A; Auguste, K I; Crone, N E; Kirsch, H E; Kuperman, R A; Lin, J J; Parvizi, J; Knight, R T
2018-01-01
Electrophysiology and neuroimaging provide conflicting evidence for the neural contributions to target detection. Scalp electroencephalography (EEG) studies localize the P3b event-related potential component mainly to parietal cortex, whereas neuroimaging studies report activations in both frontal and parietal cortices. We addressed this discrepancy by examining the sources that generate the target-detection process using electrocorticography (ECoG). We recorded ECoG activity from cortex in 14 patients undergoing epilepsy monitoring, as they performed an auditory or visual target-detection task. We examined target-related responses in 2 domains: high frequency band (HFB) activity and the P3b. Across tasks, we observed a greater proportion of electrodes that showed target-specific HFB power relative to P3b over frontal cortex, but their proportions over parietal cortex were comparable. Notably, there was minimal overlap in the electrodes that showed target-specific HFB and P3b activity. These results revealed that the target-detection process is characterized by at least 2 different neural markers with distinct cortical distributions. Our findings suggest that separate neural mechanisms are driving the differential patterns of activity observed in scalp EEG and neuroimaging studies, with the P3b reflecting EEG findings and HFB activity reflecting neuroimaging findings, highlighting the notion that target detection is not a unitary phenomenon. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Back-Projection Cortical Potential Imaging: Theory and Results.
Haor, Dror; Shavit, Reuven; Shapiro, Moshe; Geva, Amir B
2017-07-01
Electroencephalography (EEG) is the single brain monitoring technique that is non-invasive, portable, passive, exhibits high-temporal resolution, and gives a directmeasurement of the scalp electrical potential. Amajor disadvantage of the EEG is its low-spatial resolution, which is the result of the low-conductive skull that "smears" the currents coming from within the brain. Recording brain activity with both high temporal and spatial resolution is crucial for the localization of confined brain activations and the study of brainmechanismfunctionality, whichis then followed by diagnosis of brain-related diseases. In this paper, a new cortical potential imaging (CPI) method is presented. The new method gives an estimation of the electrical activity on the cortex surface and thus removes the "smearing effect" caused by the skull. The scalp potentials are back-projected CPI (BP-CPI) onto the cortex surface by building a well-posed problem to the Laplace equation that is solved by means of the finite elements method on a realistic head model. A unique solution to the CPI problem is obtained by introducing a cortical normal current estimation technique. The technique is based on the same mechanism used in the well-known surface Laplacian calculation, followed by a scalp-cortex back-projection routine. The BP-CPI passed four stages of validation, including validation on spherical and realistic head models, probabilistic analysis (Monte Carlo simulation), and noise sensitivity tests. In addition, the BP-CPI was compared with the minimum norm estimate CPI approach and found superior for multi-source cortical potential distributions with very good estimation results (CC >0.97) on a realistic head model in the regions of interest, for two representative cases. The BP-CPI can be easily incorporated in different monitoring tools and help researchers by maintaining an accurate estimation for the cortical potential of ongoing or event-related potentials in order to have better neurological inferences from the EEG.
Geist, Phillip A; Dulka, Brooke N; Barnes, Abigail; Totty, Michael; Datta, Subimal
2017-08-14
Brain derived neurotrophic factor (BDNF) plays a pivotal role in structural plasticity, learning, and memory. Electroencephalogram (EEG) spectral power in the cortex and hippocampus has also been correlated with learning and memory. In this study, we investigated the effect of globally reduced BDNF levels on learning behavior and EEG power via BDNF heterozygous (KO) rats. We employed several behavioral tests that are thought to depend on cortical and hippocampal plasticity to varying degrees: novel object recognition, a test that is reliant on a variety of cognitive systems; contextual fear, which is highly hippocampal-dependent; and cued fear, which has been shown to be amygdala-dependent. We also examined the effects of BDNF reduction on cortical and hippocampal EEG spectral power via chronically implanted electrodes in the motor cortex and dorsal hippocampus. We found that BDNF KO rats were impaired in novelty recognition and fear memory retention, while hippocampal EEG power was decreased in slow waves and increased in fast waves. Interestingly, our results, for the first time, show sexual dimorphism in each of our tests. These results support the hypothesis that BDNF drives both cognitive plasticity and coordinates EEG activity patterns, potentially serving as a link between the two. Copyright © 2017 Elsevier B.V. All rights reserved.
Effects of A 60 Hz Magnetic Field of Up to 50 milliTesla on Human Tremor and EEG: A Pilot Study.
Davarpanah Jazi, Shirin; Modolo, Julien; Baker, Cadence; Villard, Sebastien; Legros, Alexandre
2017-11-24
Humans are surrounded by sources of daily exposure to power-frequency (60 Hz in North America) magnetic fields (MFs). Such time-varying MFs induce electric fields and currents in living structures which possibly lead to biological effects. The present pilot study examined possible extremely low frequency (ELF) MF effects on human neuromotor control in general, and physiological postural tremor and electroencephalography (EEG) in particular. Since the EEG cortical mu-rhythm (8-12 Hz) from the primary motor cortex and physiological tremor are related, it was hypothesized that a 60 Hz MF exposure focused on this cortical region could acutely modulate human physiological tremor. Ten healthy volunteers (age: 23.8 ± 4 SD) were fitted with a MRI-compatible EEG cap while exposed to 11 MF conditions (60 Hz, 0 to 50 mT rms , 5 mT rms increments). Simultaneously, physiological tremor (recorded from the contralateral index finger) and EEG (from associated motor and somatosensory brain regions) were measured. Results showed no significant main effect of MF exposure conditions on any of the analyzed physiological tremor characteristics. In terms of EEG, no significant effects of the MF were observed for C1, C3, C5 and CP1 electrodes. However, a significant main effect was found for CP3 and CP5 electrodes, both suggesting a decreased mu-rhythm spectral power with increasing MF flux density. This is however not confirmed by Bonferroni corrected pairwise comparisons. Considering both EEG and tremor findings, no effect of the MF exposure on human motor control was observed. However, MF exposure had a subtle effect on the mu-rhythm amplitude in the brain region involved in tactile perception. Current findings are to be considered with caution due to the small size of this pilot work, but they provide preliminary insights to international agencies establishing guidelines regarding electromagnetic field exposure with new experimental data acquired in humans exposed to high mT-range MFs.
Astolfi, Laura; Vecchiato, Giovanni; De Vico Fallani, Fabrizio; Salinari, Serenella; Cincotti, Febo; Aloise, Fabio; Mattia, Donatella; Marciani, Maria Grazia; Bianchi, Luigi; Soranzo, Ramon; Babiloni, Fabio
2009-01-01
We estimate cortical activity in normal subjects during the observation of TV commercials inserted within a movie by using high-resolution EEG techniques. The brain activity was evaluated in both time and frequency domains by solving the associate inverse problem of EEG with the use of realistic head models. In particular, we recover statistically significant information about cortical areas engaged by particular scenes inserted within the TV commercial proposed with respect to the brain activity estimated while watching a documentary. Results obtained in the population investigated suggest that the statistically significant brain activity during the observation of the TV commercial was mainly concentrated in frontoparietal cortical areas, roughly coincident with the Brodmann areas 8, 9, and 7, in the analyzed population. PMID:19584910
Early development of synchrony in cortical activations in the human.
Koolen, N; Dereymaeker, A; Räsänen, O; Jansen, K; Vervisch, J; Matic, V; Naulaers, G; De Vos, M; Van Huffel, S; Vanhatalo, S
2016-05-13
Early intermittent cortical activity is thought to play a crucial role in the growth of neuronal network development, and large scale brain networks are known to provide the basis for higher brain functions. Yet, the early development of the large scale synchrony in cortical activations is unknown. Here, we tested the hypothesis that the early intermittent cortical activations seen in the human scalp EEG show a clear developmental course during the last trimester of pregnancy, the period of intensive growth of cortico-cortical connections. We recorded scalp EEG from altogether 22 premature infants at post-menstrual age between 30 and 44 weeks, and the early cortical synchrony was quantified using recently introduced activation synchrony index (ASI). The developmental correlations of ASI were computed for individual EEG signals as well as anatomically and mathematically defined spatial subgroups. We report two main findings. First, we observed a robust and statistically significant increase in ASI in all cortical areas. Second, there were significant spatial gradients in the synchrony in fronto-occipital and left-to-right directions. These findings provide evidence that early cortical activity is increasingly synchronized across the neocortex. The ASI-based metrics introduced in our work allow direct translational comparison to in vivo animal models, as well as hold promise for implementation as a functional developmental biomarker in future research on human neonates. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Silva Pereira, Silvana; Hindriks, Rikkert; Mühlberg, Stefanie; Maris, Eric; van Ede, Freek; Griffa, Alessandra; Hagmann, Patric; Deco, Gustavo
2017-11-01
A popular way to analyze resting-state electroencephalography (EEG) and magneto encephalography (MEG) data is to treat them as a functional network in which sensors are identified with nodes and the interaction between channel time series and the network connections. Although conceptually appealing, the network-theoretical approach to sensor-level EEG and MEG data is challenged by the fact that EEG and MEG time series are mixtures of source activity. It is, therefore, of interest to assess the relationship between functional networks of source activity and the ensuing sensor-level networks. Since these topological features are of high interest in experimental studies, we address the question of to what extent the network topology can be reconstructed from sensor-level functional connectivity (FC) measures in case of MEG data. Simple simulations that consider only a small number of regions do not allow to assess network properties; therefore, we use a diffusion magnetic resonance imaging-constrained whole-brain computational model of resting-state activity. Our motivation lies behind the fact that still many contributions found in the literature perform network analysis at sensor level, and we aim at showing the discrepancies between source- and sensor-level network topologies by using realistic simulations of resting-state cortical activity. Our main findings are that the effect of field spread on network topology depends on the type of interaction (instantaneous or lagged) and leads to an underestimation of lagged FC at sensor level due to instantaneous mixing of cortical signals, instantaneous interaction is more sensitive to field spread than lagged interaction, and discrepancies are reduced when using planar gradiometers rather than axial gradiometers. We, therefore, recommend using lagged interaction measures on planar gradiometer data when investigating network properties of resting-state sensor-level MEG data.
Huang, Chih-Sheng; Yang, Wen-Yu; Chuang, Chun-Hsiang; Wang, Yu-Kai
2018-01-01
Electroencephalogram (EEG) signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA), feature extraction, and the Gaussian mixture model (GMM) to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research. PMID:29599950
Kasper, Ryan W; Grafton, Scott T; Eckstein, Miguel P; Giesbrecht, Barry
2015-03-01
Visual search can be facilitated by the learning of spatial configurations that predict the location of a target among distractors. Neuropsychological and functional magnetic resonance imaging (fMRI) evidence implicates the medial temporal lobe (MTL) memory system in this contextual cueing effect, and electroencephalography (EEG) studies have identified the involvement of visual cortical regions related to attention. This work investigated two questions: (1) how memory and attention systems are related in contextual cueing; and (2) how these systems are involved in both short- and long-term contextual learning. In one session, EEG and fMRI data were acquired simultaneously in a contextual cueing task. In a second session conducted 1 week later, EEG data were recorded in isolation. The fMRI results revealed MTL contextual modulations that were correlated with short- and long-term behavioral context enhancements and attention-related effects measured with EEG. An fMRI-seeded EEG source analysis revealed that the MTL contributed the most variance to the variability in the attention enhancements measured with EEG. These results support the notion that memory and attention systems interact to facilitate search when spatial context is implicitly learned. © 2015 New York Academy of Sciences.
Curtis, W John; Cicchetti, Dante
2007-01-01
The current study was a multilevel investigation of resilience, emotion regulation, and hemispheric electroencephalogram (EEG) asymmetry in a sample of maltreated and nonmaltreated school age children. It was predicted that the positive emotionality and increased emotion regulatory ability associated with resilient functioning would be associated with relatively greater left frontal EEG activity. The study also investigated differences in pathways to resilience between maltreated and nonmaltreated children. The findings indicated that EEG asymmetry across central cortical regions distinguished between resilient and nonresilient children, with greater left hemisphere activity characterizing those who were resilient. In addition, nonmaltreated children showed greater left hemisphere EEG activity across parietal cortical regions. There was also a significant interaction between resilience, maltreatment status, and gender for asymmetry at anterior frontal electrodes, where nonmaltreated resilient females had greater relative left frontal activity compared to more right frontal activity exhibited by resilient maltreated females. An observational measure of emotion regulation significantly contributed to the prediction of resilience in the maltreated and nonmaltreated children, but EEG asymmetry in central cortical regions independently predicted resilience only in the maltreated group. The findings are discussed in terms of their meaning for the development of resilient functioning.
Cerveau isolé and pretrigeminal rat preparations.
Zernicki, B; Gandolfo, G; Glin, L; Gottesmann, C
1985-01-01
Cortical and hippocampal EEG activity was analysed in cerveau isolé and and pretrigeminal rats. In the acute stage, waking EEG patterns were absent in the cerveau isolé, whereas sleep EGG patterns were absent in the preparations. However, already on the second day the EEG waking sleep cycle recovered in the majority of rats. Paradoxically, stimuli directed to the caudal part of the preparations evoked stronger cortical and hippocampal EEG arousal than olfactory and visual stimuli. The rats exhibited some locomotor and grooming behaviour and could be fed orally. It is concluded that the activity of the isolated cerebrum of the rat is similar to that of cat preparations, but that functions of the caudal neuraxis are superior in rats.
Hindriks, Rikkert; Schmiedt, Joscha; Arsiwalla, Xerxes D; Peter, Alina; Verschure, Paul F M J; Fries, Pascal; Schmid, Michael C; Deco, Gustavo
2017-01-01
Planar intra-cortical electrode (Utah) arrays provide a unique window into the spatial organization of cortical activity. Reconstruction of the current source density (CSD) underlying such recordings, however, requires "inverting" Poisson's equation. For inter-laminar recordings, this is commonly done by the CSD method, which consists in taking the second-order spatial derivative of the recorded local field potentials (LFPs). Although the CSD method has been tremendously successful in mapping the current generators underlying inter-laminar LFPs, its application to planar recordings is more challenging. While for inter-laminar recordings the CSD method seems reasonably robust against violations of its assumptions, is it unclear as to what extent this holds for planar recordings. One of the objectives of this study is to characterize the conditions under which the CSD method can be successfully applied to Utah array data. Using forward modeling, we find that for spatially coherent CSDs, the CSD method yields inaccurate reconstructions due to volume-conducted contamination from currents in deeper cortical layers. An alternative approach is to "invert" a constructed forward model. The advantage of this approach is that any a priori knowledge about the geometrical and electrical properties of the tissue can be taken into account. Although several inverse methods have been proposed for LFP data, the applicability of existing electroencephalographic (EEG) and magnetoencephalographic (MEG) inverse methods to LFP data is largely unexplored. Another objective of our study therefore, is to assess the applicability of the most commonly used EEG/MEG inverse methods to Utah array data. Our main conclusion is that these inverse methods provide more accurate CSD reconstructions than the CSD method. We illustrate the inverse methods using event-related potentials recorded from primary visual cortex of a macaque monkey during a motion discrimination task.
Schmiedt, Joscha; Arsiwalla, Xerxes D.; Peter, Alina; Verschure, Paul F. M. J.; Fries, Pascal; Schmid, Michael C.; Deco, Gustavo
2017-01-01
Planar intra-cortical electrode (Utah) arrays provide a unique window into the spatial organization of cortical activity. Reconstruction of the current source density (CSD) underlying such recordings, however, requires “inverting” Poisson’s equation. For inter-laminar recordings, this is commonly done by the CSD method, which consists in taking the second-order spatial derivative of the recorded local field potentials (LFPs). Although the CSD method has been tremendously successful in mapping the current generators underlying inter-laminar LFPs, its application to planar recordings is more challenging. While for inter-laminar recordings the CSD method seems reasonably robust against violations of its assumptions, is it unclear as to what extent this holds for planar recordings. One of the objectives of this study is to characterize the conditions under which the CSD method can be successfully applied to Utah array data. Using forward modeling, we find that for spatially coherent CSDs, the CSD method yields inaccurate reconstructions due to volume-conducted contamination from currents in deeper cortical layers. An alternative approach is to “invert” a constructed forward model. The advantage of this approach is that any a priori knowledge about the geometrical and electrical properties of the tissue can be taken into account. Although several inverse methods have been proposed for LFP data, the applicability of existing electroencephalographic (EEG) and magnetoencephalographic (MEG) inverse methods to LFP data is largely unexplored. Another objective of our study therefore, is to assess the applicability of the most commonly used EEG/MEG inverse methods to Utah array data. Our main conclusion is that these inverse methods provide more accurate CSD reconstructions than the CSD method. We illustrate the inverse methods using event-related potentials recorded from primary visual cortex of a macaque monkey during a motion discrimination task. PMID:29253006
Cerquera, Alexander; Vollebregt, Madelon A; Arns, Martijn
2018-03-01
Nonlinear analysis of EEG recordings allows detection of characteristics that would probably be neglected by linear methods. This study aimed to determine a suitable epoch length for nonlinear analysis of EEG data based on its recurrence rate in EEG alpha activity (electrodes Fz, Oz, and Pz) from 28 healthy and 64 major depressive disorder subjects. Two nonlinear metrics, Lempel-Ziv complexity and scaling index, were applied in sliding windows of 20 seconds shifted every 1 second and in nonoverlapping windows of 1 minute. In addition, linear spectral analysis was carried out for comparison with the nonlinear results. The analysis with sliding windows showed that the cortical dynamics underlying alpha activity had a recurrence period of around 40 seconds in both groups. In the analysis with nonoverlapping windows, long-term nonstationarities entailed changes over time in the nonlinear dynamics that became significantly different between epochs across time, which was not detected with the linear spectral analysis. Findings suggest that epoch lengths shorter than 40 seconds neglect information in EEG nonlinear studies. In turn, linear analysis did not detect characteristics from long-term nonstationarities in EEG alpha waves of control subjects and patients with major depressive disorder patients. We recommend that application of nonlinear metrics in EEG time series, particularly of alpha activity, should be carried out with epochs around 60 seconds. In addition, this study aimed to demonstrate that long-term nonlinearities are inherent to the cortical brain dynamics regardless of the presence or absence of a mental disorder.
Electric Field Encephalography as a tool for functional brain research: a modeling study.
Petrov, Yury; Sridhar, Srinivas
2013-01-01
We introduce the notion of Electric Field Encephalography (EFEG) based on measuring electric fields of the brain and demonstrate, using computer modeling, that given the appropriate electric field sensors this technique may have significant advantages over the current EEG technique. Unlike EEG, EFEG can be used to measure brain activity in a contactless and reference-free manner at significant distances from the head surface. Principal component analysis using simulated cortical sources demonstrated that electric field sensors positioned 3 cm away from the scalp and characterized by the same signal-to-noise ratio as EEG sensors provided the same number of uncorrelated signals as scalp EEG. When positioned on the scalp, EFEG sensors provided 2-3 times more uncorrelated signals. This significant increase in the number of uncorrelated signals can be used for more accurate assessment of brain states for non-invasive brain-computer interfaces and neurofeedback applications. It also may lead to major improvements in source localization precision. Source localization simulations for the spherical and Boundary Element Method (BEM) head models demonstrated that the localization errors are reduced two-fold when using electric fields instead of electric potentials. We have identified several techniques that could be adapted for the measurement of the electric field vector required for EFEG and anticipate that this study will stimulate new experimental approaches to utilize this new tool for functional brain research.
Ramanand, Pravitha; Bruce, Margaret C; Bruce, Eugene N
2010-08-01
Spontaneous cortical arousals in non-REM sleep increase with age and contribute to sleep fragmentation in the elderly. EEG spectral power in the faster frequencies exhibits well-described shifts during arousals. On the other hand, EEG activities also exhibit correlations, which are interpreted as an index of interdependence between distant cortical neural activities. The possibility of changes to the interdependence between cortical regions due to an arousal has not been considered. In this work, using previously recorded C3A2 and C4A1 EEG signals from two groups of adults, middle-aged (42-50 years) and elderly (71-86 years) women, we examined the effects of spontaneous arousals in NREM sleep on cortical interdependence. We quantified the auto- and cross-correlations in these signals using mutual information and characterized these correlations in periods before the onset and following the end of arousals. The pre-arousal period exhibited significantly higher interdependence between central regions than that following the arousal in both age groups (middle-aged: p=0.004, elderly: p<0.0001). Also, for both EEG signals the auto mutual information had a faster rate of decay, implying lower signal predictability, following the arousal than prior to it (both age groups, p<0.0001). These results indicate that the state of the cortex is different after, compared to before, the arousal even when the spectral power changes characteristic of an arousal are no longer visible. The findings suggest that the state following an arousal characterized by lower interdependence may resemble a more vigilant period during which the system may be vulnerable to more arousals. Copyright 2010 Elsevier B.V. All rights reserved.
Del Percio, Claudio; Drinkenburg, Wilhelmus; Lopez, Susanna; Infarinato, Francesco; Bastlund, Jesper Frank; Laursen, Bettina; Pedersen, Jan T; Christensen, Ditte Zerlang; Forloni, Gianluigi; Frasca, Angelisa; Noè, Francesco M; Bentivoglio, Marina; Fabene, Paolo Francesco; Bertini, Giuseppe; Colavito, Valeria; Kelley, Jonathan; Dix, Sophie; Richardson, Jill C; Babiloni, Claudio
2017-01-01
Resting state electroencephalographic (EEG) rhythms reflect the fluctuation of cortical arousal and vigilance in a typical clinical setting, namely the EEG recording for few minutes with eyes closed (i.e., passive condition) and eyes open (i.e., active condition). Can this procedure be back-translated to C57 (wild type) mice for aging studies? On-going EEG rhythms were recorded from a frontoparietal bipolar channel in 85 (19 females) C57 mice. Male mice were subdivided into 3 groups: 25 young (4.5-6 months), 18 middle-aged (12-15 months), and 23 old (20-24 months) mice to test the effect of aging. EEG power density was compared between short periods (about 5 minutes) of awake quiet behavior (passive) and dynamic exploration of the cage (active). Compared with the passive condition, the active condition induced decreased EEG power at 1-2 Hz and increased EEG power at 6-10 Hz in the group of 85 mice. Concerning the aging effects, the passive condition showed higher EEG power at 1-2 Hz in the old group than that in the others. Furthermore, the active condition exhibited a maximum EEG power at 6-8 Hz in the former group and 8-10 Hz in the latter. In the present conditions, delta and theta EEG rhythms reflected changes in cortical arousal and vigilance in freely behaving C57 mice across aging. These changes resemble the so-called slowing of resting state EEG rhythms observed in humans across physiological and pathological aging. The present EEG procedures may be used to enhance preclinical phases of drug discovery in mice for understanding the neurophysiological effects of new compounds against brain aging. Copyright © 2016 Elsevier Inc. All rights reserved.
Combined MEG-EEG source localisation in patients with sub-acute sclerosing pan-encephalitis.
Velmurugan, J; Sinha, Sanjib; Nagappa, Madhu; Mariyappa, N; Bindu, P S; Ravi, G S; Hazra, Nandita; Thennarasu, K; Ravi, V; Taly, A B; Satishchandra, P
2016-08-01
To study the genesis and propagation patterns of periodic complexes (PCs) associated with myoclonic jerks in sub-acute sclerosing pan-encephalitis (SSPE) using magnetoencephalography (MEG) and electroencephalography (EEG). Simultaneous recording of MEG (306 channels) and EEG (64 channels) in five patients of SSPE (M:F = 3:2; age 10.8 ± 3.2 years; symptom-duration 6.2 ± 10 months) was carried out using Elekta Neuromag(®) TRIUX™ system. Qualitative analysis of 80-160 PCs per patient was performed. Ten isomorphic classical PCs with significant field topography per patient were analysed at the 'onset' and at 'earliest significant peak' of the burst using discrete and distributed source imaging methods. MEG background was asymmetrical in 2 and slow in 3 patients. Complexes were periodic (3) or quasi-periodic (2), occurring every 4-16 s and varied in morphology among patients. Mean source localization at onset of bursts using discrete and distributed source imaging in magnetic source imaging (MSI) was in thalami and or insula (50 and 50 %, respectively) and in electric source imaging (ESI) was also in thalami and or insula (38 and 46 %, respectively). Mean source localization at the earliest rising phase of peak in MSI was in peri-central gyrus (49 and 42 %) and in ESI it was in frontal cortex (52 and 56 %). Further analysis revealed that PCs were generated in thalami and or insula and thereafter propagated to anterolateral surface of the cortices (viz. sensori-motor cortex and frontal cortex) to same side as that of the onset. This novel MEG-EEG based case series of PCs provides newer insights for understanding the plausible generators of myoclonus in SSPE and patterns of their propagation.
Frequency-dependent changes in sensorimotor and pain affective systems induced by empathy for pain.
Motoyama, Yoshimasa; Ogata, Katsuya; Hoka, Sumio; Tobimatsu, Shozo
2017-01-01
Empathy for pain helps us to understand the pain of others indirectly. To better comprehend the processing of empathic pain, we report the frequency-dependent modulation of cortical oscillations induced by watching movies depicting pain using high-density electroencephalography (EEG), magnetoencephalography (MEG), and motor evoked potentials (MEP). Event-related desynchronization of EEG and MEG was assessed while participants viewed videos of painful (needle) or neutral (cotton swab) situations. The amplitudes of MEPs were also compared between the needle and cotton swab conditions. The degree of suppression in α/β band power was significantly increased, whereas that of γ band power was significantly decreased, in the needle condition compared with the cotton swab condition. EEG revealed that significant differences in α/β band were distributed in the right frontocentral and left parietooccipital regions, whereas significant γ band differences were distributed predominantly over the right hemisphere, which were confirmed by source estimation using MEG. There was a significant positive correlation between the difference in γ power of the two conditions and the visual analog scale subjective rating of aversion, but not in the α/β band. The amplitude of MEPs decreased in the needle condition, which confirmed the inhibition of the primary motor cortex. MEP suppression supports that modulation of cortical oscillations by viewing movies depicting pain involves sensorimotor processing. Our results suggest that α/β oscillations underlie the sensory qualities of others' pain, whereas the γ band reflects the cognitive aspect. Therefore, α/β and γ band oscillations are differentially involved in empathic pain processing under the condition of motor cortical suppression.
Coherent Activity in Bilateral Parieto-Occipital Cortices during P300-BCI Operation.
Takano, Kouji; Ora, Hiroki; Sekihara, Kensuke; Iwaki, Sunao; Kansaku, Kenji
2014-01-01
The visual P300 brain-computer interface (BCI), a popular system for electroencephalography (EEG)-based BCI, uses the P300 event-related potential to select an icon arranged in a flicker matrix. In earlier studies, we used green/blue (GB) luminance and chromatic changes in the P300-BCI system and reported that this luminance and chromatic flicker matrix was associated with better performance and greater subject comfort compared with the conventional white/gray (WG) luminance flicker matrix. To highlight areas involved in improved P300-BCI performance, we used simultaneous EEG-fMRI recordings and showed enhanced activities in bilateral and right lateralized parieto-occipital areas. Here, to capture coherent activities of the areas during P300-BCI, we collected whole-head 306-channel magnetoencephalography data. When comparing functional connectivity between the right and left parieto-occipital channels, significantly greater functional connectivity in the alpha band was observed under the GB flicker matrix condition than under the WG flicker matrix condition. Current sources were estimated with a narrow-band adaptive spatial filter, and mean imaginary coherence was computed in the alpha band. Significantly greater coherence was observed in the right posterior parietal cortex under the GB than under the WG condition. Re-analysis of previous EEG-based P300-BCI data showed significant correlations between the power of the coherence of the bilateral parieto-occipital cortices and their performance accuracy. These results suggest that coherent activity in the bilateral parieto-occipital cortices plays a significant role in effectively driving the P300-BCI.
Cerveau isolé and pretrigeminal rats.
Zernicki, B; Gandolfo, G; Glin, L; Gottesmann, C
1984-01-01
Cortical and hippocampal EEG activity was analysed in 14 cerveau isole and 8 pretrigerninal rats. In the acute stage, waking EEG patterns were absent in the cerveau isole, whereas sleep EEG patterns were absent in the pretrigeminal preparations. However, already on the second day the EEG waking-sleep cycle recovered in the majority of rats. Paradoxically, stimuli directed to the caudal part of preparations evoked stronger cortical and hippocampal EEG arousal than olfactory and visual stimuli. The behavior of the caudal part was observed in 25 preparations. Although in abortive form, the rats did show some locomotor and grooming behavior, and could be fed orally. The peripheral events of paradoxical sleep appeared only on the fourth or fifth day of survival of the cerveau isole rats. It is concluded that the activity of the isolated cerebrum of the rat is similar to that of cat preparations, but that functions of the caudal neuraxis are superior in rats.
de Vera, Luis; Pereda, Ernesto; Santana, Alejandro; González, Julián J
2005-03-01
Electroencephalograms of medial cortex and electromyograms of intercostal muscles (EMG-icm) were simultaneously recorded in the lizard, Gallotia galloti, during two daily time periods (at daytime, DTP: 1200-1600 h; by night, NTP: 0000-0400 h), to investigate whether a relationship exists between the respiratory and cortical electrical activity of reptiles, and, if so, how this relationship changes during the night rest period. Testing was carried out by studying interdependence between cortical electrical and respiratory activities, by means of linear and nonlinear signal analysis techniques. Both physiological activities were evaluated through simultaneous power signals, derived from the power of the low-frequency band of the electroencephalogram (pEEG-LF), and from the power of the EMG-icm (pEMG-icm), respectively. During both DTP and NTP, there was a significant coherence between both signals in the main frequency band of pEMG-icm. During both DTP and NTP, the nonlinear index N measured significant linear asymmetric interdependence between pEEG-LF and pEMG-icm. The N value obtained between pEEG-LF vs. pEMG-icm was greater than the one between pEMG-icm vs. pEEG-LF. This means that the system that generates the pEEG-LF is more complex than the one that generates the pEMG-icm, and suggests that the temporal variability of power in the low-frequency cortical electrical activity is driven by the power of the respiratory activity.
Malformations of cortical development and epilepsy: evaluation of 101 cases (part II).
Güngör, Serdal; Yalnizoğlu, Dilek; Turanli, Güzide; Saatçi, Işil; Erdoğan-Bakar, Emel; Topçu, Meral
2007-01-01
Malformations of cortical development (MCD) form a spectrum of lesions produced by insult to the developing neocortex. Clinical presentation and electrophysiologic findings of MCD are variable and depend on the affected cortical area. We evaluated epilepsy, EEG, and response to antiepileptic treatment in patients with MCD with respect to the neuroimaging findings. We studied 101 patients, ranging between 1 month and 19 years of age. Fifty-four patients were diagnosed with polymicrogyria (PMG), 23 patients with lissencephaly, 12 patients with schizencephaly, and 12 patients with heterotopia. With regards to epilepsy and seizure type, 72/101 (71.3%) patients had epilepsy, and 62/101 (61.4%) patients presented with seizures. Overall, 32.7% of patients had generalized seizures, and 25.7% had complex partial seizures. Mean age at the onset of seizures was 2.7 +/- 3.4 years. The onset of epilepsy tended to be younger in patients with lissencephaly and older in patients with heterotopias. Of the cases, 79.2% had abnormal EEG (56.3% with epileptiform abnormality, 22.9% with non-epileptiform abnormality). EEG was abnormal in 44.9% (13/29) of the cases without epilepsy. EEG showed bilateral synchronous and diffuse epileptiform discharges in 90% of patients with lissencephaly. Patients with schizencephaly had mostly focal epileptiform discharges. Heterotopia cases had a high rate of EEG abnormalities (72.7%). Patients with PMG had epileptiform abnormality in 59.5% of the cases. Patients with heterotopias and PMG achieved better seizure control in comparison with the other groups. In conclusion, epilepsy is the most common problem in MCD. Epilepsy and EEG findings of patients with MCD are variable and seem to be correlated with the extent of cortical involvement.
Hippocampal theta activity in the acute cerveau isolé cat.
Gottesmann, C; Zernicki, B; Gandolfo, G
1981-01-01
In three cerveau isole cats, cortical and hippocampal EEG activity were recorded. In the cortical records, spindles alternated with low-voltage activity, whereas theta activity dominated in the hippocampus. The amount and frequency of theta were similar to those described previously for the pretrigeminal cat. In confirmation of previous results on rats, although cortical EEG activity differs in cerveau isole cat and pretrigeminal cat, both preparations show domination of theta activity in the hippocampus. It is concluded that the mesencephalic transection eliminates inhibitory effects from the lower brainstem on generators of the theta rhythm.
Retinoic Acid Signaling Affects Cortical Synchrony During Sleep
NASA Astrophysics Data System (ADS)
Maret, Stéphanie; Franken, Paul; Dauvilliers, Yves; Ghyselinck, Norbert B.; Chambon, Pierre; Tafti, Mehdi
2005-10-01
Delta oscillations, characteristic of the electroencephalogram (EEG) of slow wave sleep, estimate sleep depth and need and are thought to be closely linked to the recovery function of sleep. The cellular mechanisms underlying the generation of delta waves at the cortical and thalamic levels are well documented, but the molecular regulatory mechanisms remain elusive. Here we demonstrate in the mouse that the gene encoding the retinoic acid receptor beta determines the contribution of delta oscillations to the sleep EEG. Thus, retinoic acid signaling, which is involved in the patterning of the brain and dopaminergic pathways, regulates cortical synchrony in the adult.
Ramanand, Pravitha; Bruce, Margaret C.; Bruce, Eugene N.
2010-01-01
Elderly subjects exhibit declining sleep efficiency parameters with longer time spent awake at night and greater sleep fragmentation. In this paper, we report on the changes in cortical interdependence during sleep stages between 15 middle aged (range: 42-50 years) and 15 elderly (range: 71-86 years) women subjects. Cortical interdependence assessed from EEG signals typically exhibits increasing levels of correlation as human subjects progress from wake to deeper stages of sleep. EEG signals acquired from previously existing polysomnogram data sets were subjected to mutual information (MI) analysis to detect changes in information transmission associated with change in sleep stage and to understand how age affects the interdependence values. We observed a significant reduction in the interdependence between central EEG signals of elderly subjects in NREM and REM stage sleep in comparison to middle-aged subjects (age group effect: elderly vs. middle aged p<0.001, sleep stage effect: p<0.001, interaction effect between age group and sleep stage: p=0.007). A narrow band analysis revealed that the reduction in MI was present in delta, theta and sigma frequencies. These findings suggest that the lowered cortical interdependence in sleep of elderly subjects may indicate independently evolving dynamic neural activities at multiple cortical sites. The loss of synchronization between neural activities during sleep in the elderly may make these women more susceptible to localized disturbances that could lead to frequent arousals. PMID:20634711
MNE software for processing MEG and EEG data
Gramfort, A.; Luessi, M.; Larson, E.; Engemann, D.; Strohmeier, D.; Brodbeck, C.; Parkkonen, L.; Hämäläinen, M.
2013-01-01
Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals originating from neural currents in the brain. Using these signals to characterize and locate brain activity is a challenging task, as evidenced by several decades of methodological contributions. MNE, whose name stems from its capability to compute cortically-constrained minimum-norm current estimates from M/EEG data, is a software package that provides comprehensive analysis tools and workflows including preprocessing, source estimation, time–frequency analysis, statistical analysis, and several methods to estimate functional connectivity between distributed brain regions. The present paper gives detailed information about the MNE package and describes typical use cases while also warning about potential caveats in analysis. The MNE package is a collaborative effort of multiple institutes striving to implement and share best methods and to facilitate distribution of analysis pipelines to advance reproducibility of research. Full documentation is available at http://martinos.org/mne. PMID:24161808
Shafi, Mouhsin M.; Whitfield-Gabrieli, Susan; Chu, Catherine J.; Pascual-Leone, Alvaro; Chang, Bernard S.
2017-01-01
Resting-state functional connectivity MRI (rs-fcMRI) is a technique that identifies connectivity between different brain regions based on correlations over time in the blood-oxygenation level dependent signal. rs-fcMRI has been applied extensively to identify abnormalities in brain connectivity in different neurologic and psychiatric diseases. However, the relationship among rs-fcMRI connectivity abnormalities, brain electrophysiology and disease state is unknown, in part because the causal significance of alterations in functional connectivity in disease pathophysiology has not been established. Transcranial Magnetic Stimulation (TMS) is a technique that uses electromagnetic induction to noninvasively produce focal changes in cortical activity. When combined with electroencephalography (EEG), TMS can be used to assess the brain's response to external perturbations. Here we provide a protocol for combining rs-fcMRI, TMS and EEG to assess the physiologic significance of alterations in functional connectivity in patients with neuropsychiatric disease. We provide representative results from a previously published study in which rs-fcMRI was used to identify regions with abnormal connectivity in patients with epilepsy due to a malformation of cortical development, periventricular nodular heterotopia (PNH). Stimulation in patients with epilepsy resulted in abnormal TMS-evoked EEG activity relative to stimulation of the same sites in matched healthy control patients, with an abnormal increase in the late component of the TMS-evoked potential, consistent with cortical hyperexcitability. This abnormality was specific to regions with abnormal resting-state functional connectivity. Electrical source analysis in a subject with previously recorded seizures demonstrated that the origin of the abnormal TMS-evoked activity co-localized with the seizure-onset zone, suggesting the presence of an epileptogenic circuit. These results demonstrate how rs-fcMRI, TMS and EEG can be utilized together to identify and understand the physiological significance of abnormal brain connectivity in human diseases. PMID:27911366
Cortical oscillatory dynamics in a social interaction model.
Knyazev, Gennady G; Slobodskoj-Plusnin, Jaroslav Y; Bocharov, Andrey V; Pylkova, Liudmila V
2013-03-15
In this study we sought to investigate cortical oscillatory dynamics accompanying three major kinds of social behavior: aggressive, friendly, and avoidant. Behavioral and EEG data were collected in 48 participants during a computer game modeling social interactions with virtual 'persons'. 3D source reconstruction and independent component analysis were applied to EEG data. Results showed that social behavior was partly reactive and partly proactive with subject's personality playing an important role in shaping this behavior. Most salient differences were found between avoidance and approach behaviors, whereas the two kinds of approach behavior (i.e., aggression and friendship) did not differ from each other. Comparative to avoidance, approach behaviors were associated with higher induced responses in most frequency bands which were mostly observed in cortical areas overlapping with the default mode network. The difference between approach- and avoidance-related oscillatory dynamics was more salient in subjects predisposed to approach behaviors (i.e., in aggressive or sociable subjects) and was less pronounced in subjects predisposed to avoidance behavior (i.e., in high trait anxiety scorers). There was a trend to higher low frequency phase-locking in motor area in approach than in avoid condition. Results are discussed in light of the concept linking induced responses with top-down and evoked responses with bottom-up processes. Copyright © 2012 Elsevier B.V. All rights reserved.
Allegrini, Paolo; Bedini, Remo; Bergamasco, Massimo; Laurino, Marco; Sebastiani, Laura; Gemignani, Angelo
2016-01-01
Sleep Slow Oscillations (SSOs), paradigmatic EEG markers of cortical bistability (alternation between cellular downstates and upstates), and sleep spindles, paradigmatic EEG markers of thalamic rhythm, are two hallmarks of sleeping brain. Selective thalamic lesions are reportedly associated to reductions of spindle activity and its spectrum ~14 Hz (sigma), and to alterations of SSO features. This apparent, parallel behavior suggests that thalamo-cortical entrainment favors cortical bistability. Here we investigate temporally-causal associations between thalamic sigma activity and shape, topology, and dynamics of SSOs. We recorded sleep EEG and studied whether spatio-temporal variability of SSO amplitude, negative slope (synchronization in downstate falling) and detection rate are driven by cortical-sigma-activity expression (12–18 Hz), in 3 consecutive 1 s-EEG-epochs preceding each SSO event (Baselines). We analyzed: (i) spatial variability, comparing maps of baseline sigma power and of SSO features, averaged over the first sleep cycle; (ii) event-by-event shape variability, computing for each electrode correlations between baseline sigma power and amplitude/slope of related SSOs; (iii) event-by-event spreading variability, comparing baseline sigma power in electrodes showing an SSO event with the homologous ones, spared by the event. The scalp distribution of baseline sigma power mirrored those of SSO amplitude and slope; event-by-event variability in baseline sigma power was associated with that in SSO amplitude in fronto-central areas; within each SSO event, electrodes involved in cortical bistability presented higher baseline sigma activity than those free of SSO. In conclusion, spatio-temporal variability of thalamocortical entrainment, measured by background sigma activity, is a reliable estimate of the cortical proneness to bistability. PMID:26003553
Blinowska, Katarzyna J; Rakowski, Franciszek; Kaminski, Maciej; De Vico Fallani, Fabrizio; Del Percio, Claudio; Lizio, Roberta; Babiloni, Claudio
2017-04-01
This exploratory study provided a proof of concept of a new procedure using multivariate electroencephalographic (EEG) topographic markers of cortical connectivity to discriminate normal elderly (Nold) and Alzheimer's disease (AD) individuals. The new procedure was tested on an existing database formed by resting state eyes-closed EEG data (19 exploring electrodes of 10-20 system referenced to linked-ear reference electrodes) recorded in 42 AD patients with dementia (age: 65.9years±8.5 standard deviation, SD) and 42 Nold non-consanguineous caregivers (age: 70.6years±8.5 SD). In this procedure, spectral EEG coherence estimated reciprocal functional connectivity while non-normalized directed transfer function (NDTF) estimated effective connectivity. Principal component analysis and computation of Mahalanobis distance integrated and combined these EEG topographic markers of cortical connectivity. The area under receiver operating curve (AUC) indexed the classification accuracy. A good classification of Nold and AD individuals was obtained by combining the EEG markers derived from NDTF and coherence (AUC=86%, sensitivity=0.85, specificity=0.70). These encouraging results motivate a cross-validation study of the new procedure in age- and education-matched Nold, stable and progressing mild cognitive impairment individuals, and de novo AD patients with dementia. If cross-validated, the new procedure will provide cheap, broadly available, repeatable over time, and entirely non-invasive EEG topographic markers reflecting abnormal cortical connectivity in AD patients diagnosed by direct or indirect measurement of cerebral amyloid β and hyperphosphorylated tau peptides. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
Reversing pathologically increased EEG power by acoustic coordinated reset neuromodulation
Adamchic, Ilya; Toth, Timea; Hauptmann, Christian; Tass, Peter Alexander
2014-01-01
Acoustic Coordinated Reset (CR) neuromodulation is a patterned stimulation with tones adjusted to the patient's dominant tinnitus frequency, which aims at desynchronizing pathological neuronal synchronization. In a recent proof-of-concept study, CR therapy, delivered 4–6 h/day more than 12 weeks, induced a significant clinical improvement along with a significant long-lasting decrease of pathological oscillatory power in the low frequency as well as γ band and an increase of the α power in a network of tinnitus-related brain areas. As yet, it remains unclear whether CR shifts the brain activity toward physiological levels or whether it induces clinically beneficial, but nonetheless abnormal electroencephalographic (EEG) patterns, for example excessively decreased δ and/or γ. Here, we compared the patients' spontaneous EEG data at baseline as well as after 12 weeks of CR therapy with the spontaneous EEG of healthy controls by means of Brain Electrical Source Analysis source montage and standardized low-resolution brain electromagnetic tomography techniques. The relationship between changes in EEG power and clinical scores was investigated using a partial least squares approach. In this way, we show that acoustic CR neuromodulation leads to a normalization of the oscillatory power in the tinnitus-related network of brain areas, most prominently in temporal regions. A positive association was found between the changes in tinnitus severity and the normalization of δ and γ power in the temporal, parietal, and cingulate cortical regions. Our findings demonstrate a widespread CR-induced normalization of EEG power, significantly associated with a reduction of tinnitus severity. PMID:23907785
Ruehland, Warren R.; O'Donoghue, Fergal J.; Pierce, Robert J.; Thornton, Andrew T.; Singh, Parmjit; Copland, Janet M.; Stevens, Bronwyn; Rochford, Peter D.
2011-01-01
Study Objective: To examine the impact of using American Academy of Sleep Medicine (AASM) recommended EEG derivations (F4/M1, C4/M1, O2/M1) vs. a single derivation (C4/M1) in polysomnography (PSG) on the measurement of sleep and cortical arousals, including inter- and intra-observer variability. Design: Prospective, non-blinded, randomized comparison. Setting: Three Australian tertiary-care hospital clinical sleep laboratories. Patients or Participants: 30 PSGs from consecutive patients investigated for obstructive sleep apnea (OSA) during December 2007 and January 2008. Interventions: N/A Measurements and Results: To examine the impact of EEG derivations on PSG summary statistics, 3 scorers from different Australian clinical sleep laboratories each scored separate sets of 10 PSGs twice, once using 3 EEG derivations and once using 1 EEG derivation. To examine the impact on inter- and intra-scorer reliability, all 3 scorers scored a subset of 10 PSGs 4 times, twice using each method. All PSGs were de-identified and scored in random order according to the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Using 3 referential EEG derivations during PSG, as recommended in the AASM manual, instead of a single central EEG derivation, as originally suggested by Rechtschaffen and Kales (1968), resulted in a mean ± SE decrease in N1 sleep of 9.6 ± 3.9 min (P = 0.018) and an increase in N3 sleep of 10.6 ± 2.8 min (P = 0.001). No significant differences were observed for any other sleep or arousal scoring summary statistics; nor were any differences observed in inter-scorer or intra-scorer reliability for scoring sleep or cortical arousals. Conclusion: This study provides information for those changing practice to comply with the 2007 AASM recommendations for EEG placement in PSG, for those using portable devices that are unable to comply with the recommendations due to limited channel options, and for the development of future standards for PSG scoring and recording. As the use of multiple EEG derivations only led to small changes in the distribution of derived sleep stages and no significant differences in scoring reliability, this study calls into question the need to use multiple EEG derivations in clinical PSG as suggested in the AASM manual. Citation: Ruehland WR; O'Donoghue FJ; Pierce RJ; Thornton AT; Singh P; Copland JM; Stevens B; Rochford PD. The 2007 AASM recommendations for EEG electrode placement in polysomnography: impact on sleep and cortical arousal scoring. SLEEP 2011;34(1):73-81. PMID:21203376
Arichi, Tomoki; Whitehead, Kimberley; Barone, Giovanni; Pressler, Ronit; Padormo, Francesco; Edwards, A David; Fabrizi, Lorenzo
2017-09-12
Electroencephalographic recordings from the developing human brain are characterized by spontaneous neuronal bursts, the most common of which is the delta brush. Although similar events in animal models are known to occur in areas of immature cortex and drive their development, their origin in humans has not yet been identified. Here, we use simultaneous EEG-fMRI to localise the source of delta brush events in 10 preterm infants aged 32-36 postmenstrual weeks. The most frequent patterns were left and right posterior-temporal delta brushes which were associated in the left hemisphere with ipsilateral BOLD activation in the insula only; and in the right hemisphere in both the insular and temporal cortices. This direct measure of neural and hemodynamic activity shows that the insula, one of the most densely connected hubs in the developing cortex, is a major source of the transient bursting events that are critical for brain maturation.
Green, Jessica J; Boehler, Carsten N; Roberts, Kenneth C; Chen, Ling-Chia; Krebs, Ruth M; Song, Allen W; Woldorff, Marty G
2017-08-16
Visual spatial attention has been studied in humans with both electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) individually. However, due to the intrinsic limitations of each of these methods used alone, our understanding of the systems-level mechanisms underlying attentional control remains limited. Here, we examined trial-to-trial covariations of concurrently recorded EEG and fMRI in a cued visual spatial attention task in humans, which allowed delineation of both the generators and modulators of the cue-triggered event-related oscillatory brain activity underlying attentional control function. The fMRI activity in visual cortical regions contralateral to the cued direction of attention covaried positively with occipital gamma-band EEG, consistent with activation of cortical regions representing attended locations in space. In contrast, fMRI activity in ipsilateral visual cortical regions covaried inversely with occipital alpha-band oscillations, consistent with attention-related suppression of the irrelevant hemispace. Moreover, the pulvinar nucleus of the thalamus covaried with both of these spatially specific, attention-related, oscillatory EEG modulations. Because the pulvinar's neuroanatomical geometry makes it unlikely to be a direct generator of the scalp-recorded EEG, these covariational patterns appear to reflect the pulvinar's role as a regulatory control structure, sending spatially specific signals to modulate visual cortex excitability proactively. Together, these combined EEG/fMRI results illuminate the dynamically interacting cortical and subcortical processes underlying spatial attention, providing important insight not realizable using either method alone. SIGNIFICANCE STATEMENT Noninvasive recordings of changes in the brain's blood flow using functional magnetic resonance imaging and electrical activity using electroencephalography in humans have individually shown that shifting attention to a location in space produces spatially specific changes in visual cortex activity in anticipation of a stimulus. The mechanisms controlling these attention-related modulations of sensory cortex, however, are poorly understood. Here, we recorded these two complementary measures of brain activity simultaneously and examined their trial-to-trial covariations to gain insight into these attentional control mechanisms. This multi-methodological approach revealed the attention-related coordination of visual cortex modulation by the subcortical pulvinar nucleus of the thalamus while also disentangling the mechanisms underlying the attentional enhancement of relevant stimulus input and those underlying the concurrent suppression of irrelevant input. Copyright © 2017 the authors 0270-6474/17/377803-08$15.00/0.
Localizing and tracking electrodes using stereovision in epilepsy cases
NASA Astrophysics Data System (ADS)
Fan, Xiaoyao; Ji, Songbai; Roberts, David W.; Paulsen, Keith D.
2015-03-01
In epilepsy cases, subdural electrodes are often implanted to acquire intracranial EEG (iEEG) for seizure localization and resection planning. However, the electrodes may shift significantly between implantation and resection, during the time that the patient is monitored for iEEG recording. As a result, the accuracy of surgical planning based on electrode locations at the time of resection can be compromised. Previous studies have only quantified the electrode shift with respect to the skull, but not with respect to the cortical surface, because tracking cortical shift between surgeries is challenging. In this study, we use an intraoperative stereovision (iSV) system to visualize and localize the cortical surface as well as electrodes, record three-dimensional (3D) locations of the electrodes in MR space at the time of implantation and resection, respectively, and quantify the raw displacements, i.e., with respect to the skull. Furthermore, we track the cortical surface and quantify the shift between surgeries using an optical flow (OF) based motion-tracking algorithm. Finally, we compute the electrode shift with respect to the cortical surface by subtracting the cortical shift from raw measured displacements. We illustrate the method using one patient example. In this particular patient case, the results show that the electrodes not only shifted significantly with respect to the skull (8.79 +/- 3.00 mm in the lateral direction, ranging from 2.88 mm to 12.87 mm), but also with respect to the cortical surface (7.20 +/- 3.58 mm), whereas the cortical surface did not shift significantly in the lateral direction between surgeries (2.23 +/- 0.76 mm).
Liu, Hesheng; Schimpf, Paul H; Dong, Guoya; Gao, Xiaorong; Yang, Fusheng; Gao, Shangkai
2005-10-01
This paper presents a new algorithm called Standardized Shrinking LORETA-FOCUSS (SSLOFO) for solving the electroencephalogram (EEG) inverse problem. Multiple techniques are combined in a single procedure to robustly reconstruct the underlying source distribution with high spatial resolution. This algorithm uses a recursive process which takes the smooth estimate of sLORETA as initialization and then employs the re-weighted minimum norm introduced by FOCUSS. An important technique called standardization is involved in the recursive process to enhance the localization ability. The algorithm is further improved by automatically adjusting the source space according to the estimate of the previous step, and by the inclusion of temporal information. Simulation studies are carried out on both spherical and realistic head models. The algorithm achieves very good localization ability on noise-free data. It is capable of recovering complex source configurations with arbitrary shapes and can produce high quality images of extended source distributions. We also characterized the performance with noisy data in a realistic head model. An important feature of this algorithm is that the temporal waveforms are clearly reconstructed, even for closely spaced sources. This provides a convenient way to estimate neural dynamics directly from the cortical sources.
Frequency-dependent changes in sensorimotor and pain affective systems induced by empathy for pain
Motoyama, Yoshimasa; Ogata, Katsuya; Hoka, Sumio; Tobimatsu, Shozo
2017-01-01
Background Empathy for pain helps us to understand the pain of others indirectly. To better comprehend the processing of empathic pain, we report the frequency-dependent modulation of cortical oscillations induced by watching movies depicting pain using high-density electroencephalography (EEG), magnetoencephalography (MEG), and motor evoked potentials (MEP). Methods Event-related desynchronization of EEG and MEG was assessed while participants viewed videos of painful (needle) or neutral (cotton swab) situations. The amplitudes of MEPs were also compared between the needle and cotton swab conditions. Results The degree of suppression in α/β band power was significantly increased, whereas that of γ band power was significantly decreased, in the needle condition compared with the cotton swab condition. EEG revealed that significant differences in α/β band were distributed in the right frontocentral and left parietooccipital regions, whereas significant γ band differences were distributed predominantly over the right hemisphere, which were confirmed by source estimation using MEG. There was a significant positive correlation between the difference in γ power of the two conditions and the visual analog scale subjective rating of aversion, but not in the α/β band. The amplitude of MEPs decreased in the needle condition, which confirmed the inhibition of the primary motor cortex. Conclusion MEP suppression supports that modulation of cortical oscillations by viewing movies depicting pain involves sensorimotor processing. Our results suggest that α/β oscillations underlie the sensory qualities of others’ pain, whereas the γ band reflects the cognitive aspect. Therefore, α/β and γ band oscillations are differentially involved in empathic pain processing under the condition of motor cortical suppression. PMID:28615963
Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain
Lin, Fa-Hsuan; Witzel, Thomas; Hämäläinen, Matti S.; Dale, Anders M.; Belliveau, John W.; Stufflebeam, Steven M.
2010-01-01
This paper presents a computationally efficient source estimation algorithm that localizes cortical oscillations and their phase relationships. The proposed method employs wavelet-transformed magnetoencephalography (MEG) data and uses anatomical MRI to constrain the current locations to the cortical mantle. In addition, the locations of the sources can be further confined with the help of functional MRI (fMRI) data. As a result, we obtain spatiotemporal maps of spectral power and phase relationships. As an example, we show how the phase locking value (PLV), that is, the trial-by-trial phase relationship between the stimulus and response, can be imaged on the cortex. We apply the method to spontaneous, evoked, and driven cortical oscillations measured with MEG. We test the method of combining MEG, structural MRI, and fMRI using simulated cortical oscillations along Heschl’s gyrus (HG). We also analyze sustained auditory gamma-band neuromagnetic fields from MEG and fMRI measurements. Our results show that combining the MEG recording with fMRI improves source localization for the non-noise-normalized wavelet power. In contrast, noise-normalized spectral power or PLV localization may not benefit from the fMRI constraint. We show that if the thresholds are not properly chosen, noise-normalized spectral power or PLV estimates may contain false (phantom) sources, independent of the inclusion of the fMRI prior information. The proposed algorithm can be used for evoked MEG/EEG and block-designed or event-related fMRI paradigms, or for spontaneous MEG data sets. Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain can provide further understanding of large-scale neural activity and communication between different brain regions. PMID:15488408
EEG Alpha Synchronization Is Related to Top-Down Processing in Convergent and Divergent Thinking
ERIC Educational Resources Information Center
Benedek, Mathias; Bergner, Sabine; Konen, Tanja; Fink, Andreas; Neubauer, Aljoscha C.
2011-01-01
Synchronization of EEG alpha activity has been referred to as being indicative of cortical idling, but according to more recent evidence it has also been associated with active internal processing and creative thinking. The main objective of this study was to investigate to what extent EEG alpha synchronization is related to internal processing…
Helfrich, Christian; Pierau, Simone S.; Freitag, Christine M.; Roeper, Jochen; Ziemann, Ulf; Bender, Stephan
2012-01-01
Background Repetitive transcranial magnetic stimulation (rTMS) allows non-invasive stimulation of the human brain. However, no suitable marker has yet been established to monitor the immediate rTMS effects on cortical areas in children. Objective TMS-evoked EEG potentials (TEPs) could present a well-suited marker for real-time monitoring. Monitoring is particularly important in children where only few data about rTMS effects and safety are currently available. Methods In a single-blind sham-controlled study, twenty-five school-aged children with ADHD received subthreshold 1 Hz-rTMS to the primary motor cortex. The TMS-evoked N100 was measured by 64-channel-EEG pre, during and post rTMS, and compared to sham stimulation as an intraindividual control condition. Results TMS-evoked N100 amplitude decreased during 1 Hz-rTMS and, at the group level, reached a stable plateau after approximately 500 pulses. N100 amplitude to supra-threshold single pulses post rTMS confirmed the amplitude reduction in comparison to the pre-rTMS level while sham stimulation had no influence. EEG source analysis indicated that the TMS-evoked N100 change reflected rTMS effects in the stimulated motor cortex. Amplitude changes in TMS-evoked N100 and MEPs (pre versus post 1 Hz-rTMS) correlated significantly, but this correlation was also found for pre versus post sham stimulation. Conclusion The TMS-evoked N100 represents a promising candidate marker to monitor rTMS effects on cortical excitability in children with ADHD. TMS-evoked N100 can be employed to monitor real-time effects of TMS for subthreshold intensities. Though TMS-evoked N100 was a more sensitive parameter for rTMS-specific changes than MEPs in our sample, further studies are necessary to demonstrate whether clinical rTMS effects can be predicted from rTMS-induced changes in TMS-evoked N100 amplitude and to clarify the relationship between rTMS-induced changes in TMS-evoked N100 and MEP amplitudes. The TMS-evoked N100 amplitude reduction after 1 Hz-rTMS could either reflect a globally decreased cortical response to the TMS pulse or a specific decrease in inhibition. PMID:23185537
Singh, Harsimrat; Cooper, Robert J.; Wai Lee, Chuen; Dempsey, Laura; Edwards, Andrea; Brigadoi, Sabrina; Airantzis, Dimitrios; Everdell, Nick; Michell, Andrew; Holder, David; Hebden, Jeremy C.; Austin, Topun
2014-01-01
Seizures in the newborn brain represent a major challenge to neonatal medicine. Neonatal seizures are poorly classified, under-diagnosed, difficult to treat and are associated with poor neurodevelopmental outcome. Video-EEG is the current gold-standard approach for seizure detection and monitoring. Interpreting neonatal EEG requires expertise and the impact of seizures on the developing brain remains poorly understood. In this case study we present the first ever images of the haemodynamic impact of seizures on the human infant brain, obtained using simultaneous diffuse optical tomography (DOT) and video-EEG with whole-scalp coverage. Seven discrete periods of ictal electrographic activity were observed during a 60 minute recording of an infant with hypoxic–ischaemic encephalopathy. The resulting DOT images show a remarkably consistent, high-amplitude, biphasic pattern of changes in cortical blood volume and oxygenation in response to each electrographic event. While there is spatial variation across the cortex, the dominant haemodynamic response to seizure activity consists of an initial increase in cortical blood volume prior to a large and extended decrease typically lasting several minutes. This case study demonstrates the wealth of physiologically and clinically relevant information that DOT–EEG techniques can yield. The consistency and scale of the haemodynamic responses observed here also suggest that DOT–EEG has the potential to provide improved detection of neonatal seizures. PMID:25161892
Tecchio, Franca; Porcaro, Camillo; Barbati, Giulia; Zappasodi, Filippo
2007-01-01
A brain–computer interface (BCI) can be defined as any system that can track the person's intent which is embedded in his/her brain activity and, from it alone, translate the intention into commands of a computer. Among the brain signal monitoring systems best suited for this challenging task, electroencephalography (EEG) and magnetoencephalography (MEG) are the most realistic, since both are non-invasive, EEG is portable and MEG could provide more specific information that could be later exploited also through EEG signals. The first two BCI steps require set up of the appropriate experimental protocol while recording the brain signal and then to extract interesting features from the recorded cerebral activity. To provide information useful in these BCI stages, our aim is to provide an overview of a new procedure we recently developed, named functional source separation (FSS). As it comes from the blind source separation algorithms, it exploits the most valuable information provided by the electrophysiological techniques, i.e. the waveform signal properties, remaining blind to the biophysical nature of the signal sources. FSS returns the single trial source activity, estimates the time course of a neuronal pool along different experimental states on the basis of a specific functional requirement in a specific time period, and uses the simulated annealing as the optimization procedure allowing the exploit of functional constraints non-differentiable. Moreover, a minor section is included, devoted to information acquired by MEG in stroke patients, to guide BCI applications aiming at sustaining motor behaviour in these patients. Relevant BCI features – spatial and time-frequency properties – are in fact altered by a stroke in the regions devoted to hand control. Moreover, a method to investigate the relationship between sensory and motor hand cortical network activities is described, providing information useful to develop BCI feedback control systems. This review provides a description of the FSS technique, a promising tool for the BCI community for online electrophysiological feature extraction, and offers interesting information to develop BCI applications to sustain hand control in stroke patients. PMID:17331989
BCIs in the Laboratory and at Home: The Wadsworth Research Program
NASA Astrophysics Data System (ADS)
Sellers, Eric W.; McFarland, Dennis J.; Vaughan, Theresa M.; Wolpaw, Jonathan R.
Many people with severe motor disabilities lack the muscle control that would allow them to rely on conventional methods of augmentative communication and control. Numerous studies over the past two decades have indicated that scalp-recorded electroencephalographic (EEG) activity can be the basis for non-muscular communication and control systems, commonly called brain-computer interfaces (BCIs) [55]. EEG-based BCI systems measure specific features of EEG activity and translate these features into device commands. The most commonly used features are rhythms produced by the sensorimotor cortex [38, 55, 56, 59], slow cortical potentials [4, 5, 23], and the P300 event-related potential [12, 17, 46]. Systems based on sensorimotor rhythms or slow cortical potentials use oscillations or transient signals that are spontaneous in the sense that they are not dependent on specific sensory events. Systems based on the P300 response use transient signals in the EEG that are elicited by specific stimuli.
Combined analysis of cortical (EEG) and nerve stump signals improves robotic hand control.
Tombini, Mario; Rigosa, Jacopo; Zappasodi, Filippo; Porcaro, Camillo; Citi, Luca; Carpaneto, Jacopo; Rossini, Paolo Maria; Micera, Silvestro
2012-01-01
Interfacing an amputee's upper-extremity stump nerves to control a robotic hand requires training of the individual and algorithms to process interactions between cortical and peripheral signals. To evaluate for the first time whether EEG-driven analysis of peripheral neural signals as an amputee practices could improve the classification of motor commands. Four thin-film longitudinal intrafascicular electrodes (tf-LIFEs-4) were implanted in the median and ulnar nerves of the stump in the distal upper arm for 4 weeks. Artificial intelligence classifiers were implemented to analyze LIFE signals recorded while the participant tried to perform 3 different hand and finger movements as pictures representing these tasks were randomly presented on a screen. In the final week, the participant was trained to perform the same movements with a robotic hand prosthesis through modulation of tf-LIFE-4 signals. To improve the classification performance, an event-related desynchronization/synchronization (ERD/ERS) procedure was applied to EEG data to identify the exact timing of each motor command. Real-time control of neural (motor) output was achieved by the participant. By focusing electroneurographic (ENG) signal analysis in an EEG-driven time window, movement classification performance improved. After training, the participant regained normal modulation of background rhythms for movement preparation (α/β band desynchronization) in the sensorimotor area contralateral to the missing limb. Moreover, coherence analysis found a restored α band synchronization of Rolandic area with frontal and parietal ipsilateral regions, similar to that observed in the opposite hemisphere for movement of the intact hand. Of note, phantom limb pain (PLP) resolved for several months. Combining information from both cortical (EEG) and stump nerve (ENG) signals improved the classification performance compared with tf-LIFE signals processing alone; training led to cortical reorganization and mitigation of PLP.
Bonjean, Maxime; Baker, Tanya; Bazhenov, Maxim; Cash, Sydney; Halgren, Eric; Sejnowski, Terrence
2012-01-01
Sleep spindles, which are bursts of 11–15 Hz that occur during non-REM sleep, are highly synchronous across the scalp when measured with EEG, but have low spatial coherence and exhibit low correlation with EEG signals when simultaneously measured with MEG spindles in humans. We developed a computational model to explore the hypothesis that the spatial coherence of the EEG spindle is a consequence of diffuse matrix projections of the thalamus to layer 1 compared to the focal projections of the core pathway to layer 4 recorded by the MEG. Increasing the fanout of thalamocortical connectivity in the matrix pathway while keeping the core pathway fixed led to increased synchrony of the spindle activity in the superficial cortical layers in the model. In agreement with cortical recordings, the latency for spindles to spread from the core to the matrix was independent of the thalamocortical fanout but highly dependent on the probability of connections between cortical areas. PMID:22496571
Monge-Pereira, E; Casatorres Perez-Higueras, I; Fernandez-Gonzalez, P; Ibanez-Pereda, J; Serrano, J I; Molina-Rueda, F
2017-04-16
In the last years, new technologies such as the brain-machine interfaces (BMI) have been incorporated in the rehabilitation process of subjects with stroke. These systems are able to detect motion intention, analyzing the cortical signals using different techniques such as the electroencephalography (EEG). This information could guide different interfaces such as robotic devices, electrical stimulation or virtual reality. A 40 years-old man with stroke with two months from the injury participated in this study. We used a BMI based on EEG. The subject's motion intention was analyzed calculating the event-related desynchronization. The upper limb motor function was evaluated with the Fugl-Meyer Assessment and the participant's satisfaction was evaluated using the QUEST 2.0. The intervention using a physical therapist as an interface was carried out without difficulty. The BMI systems detect cortical changes in a subacute stroke subject. These changes are coherent with the evolution observed using the Fugl-Meyer Assessment.
Pérez-Hernández, M; Hernández-González, M; Hidalgo-Aguirre, R M; Amezcua-Gutiérrez, C; Guevara, M A
2017-05-01
Women who adopt babies show caring behaviors and respond to stimuli from their infants just as biological mothers do, but several studies have shown that the cerebral functionality of biological mothers (BM) and adoptive mothers (AM) changes in relation to the type and emotional mean of the stimuli they receive from their babies. The complex perception and processing of different stimuli with emotional content (such as those emitted by babies) require functional synchronization among different cortical and subcortical brain areas. To determine whether the degree of functional synchronization between cortices varies when they perceive such stimuli, this study characterized the degree of cortical electroencephalographic (EEG) synchronization (correlation) among prefrontal, temporal and parietal areas in BM, AM and non-mothers while listening to a recording of a baby crying. BM showed a decreased EEG synchronization between the prefrontal and temporal cortices that may indicate a decrease in the modulatory control that the former exerts on the posterior cortices, and could be associated with deeper emotional involvement and increased sensitivity to the baby crying. The AM, in contrast, had higher degree of EEG synchronization between cortical areas in both hemispheres, likely associated with a greater modulation of the affective information of the crying baby, which allowed them to perceive it as less unpleasant. These data enrich our knowledge of the neurofunctional changes involved in motherhood, and of the neural processes that allow mothers (biological and adoptive) to be sensitive to their infants' cues and respond appropriately. Copyright © 2017 Elsevier Inc. All rights reserved.
Mideksa, K G; Singh, A; Hoogenboom, N; Hellriegel, H; Krause, H; Schnitzler, A; Deuschl, G; Raethjen, J; Schmidt, G; Muthuraman, M
2016-08-01
One of the most commonly used therapy to treat patients with Parkinson's disease (PD) is deep brain stimulation (DBS) of the subthalamic nucleus (STN). Identifying the most optimal target area for the placement of the DBS electrodes have become one of the intensive research area. In this study, the first aim is to investigate the capabilities of different source-analysis techniques in detecting deep sources located at the sub-cortical level and validating it using the a-priori information about the location of the source, that is, the STN. Secondly, we aim at an investigation of whether EEG or MEG is best suited in mapping the DBS-induced brain activity. To do this, simultaneous EEG and MEG measurement were used to record the DBS-induced electromagnetic potentials and fields. The boundary-element method (BEM) have been used to solve the forward problem. The position of the DBS electrodes was then estimated using the dipole (moving, rotating, and fixed MUSIC), and current-density-reconstruction (CDR) (minimum-norm and sLORETA) approaches. The source-localization results from the dipole approaches demonstrated that the fixed MUSIC algorithm best localizes deep focal sources, whereas the moving dipole detects not only the region of interest but also neighboring regions that are affected by stimulating the STN. The results from the CDR approaches validated the capability of sLORETA in detecting the STN compared to minimum-norm. Moreover, the source-localization results using the EEG modality outperformed that of the MEG by locating the DBS-induced activity in the STN.
Vecchiato, Giovanni; Toppi, Jlenia; Maglione, Anton Giulio; Olejarczyk, Elzbieta; Astolfi, Laura; Mattia, Donatella; Colosimo, Alfredo; Babiloni, Fabio
2014-01-01
The present research investigates the neurophysiological activity elicited by fast observations of faces of real candidates during simulated political elections. We used simultaneous recording of electroencephalographic (EEG) signals as well as galvanic skin response (GSR) and heart rate (HR) as measurements of central and autonomic nervous systems. Twenty healthy subjects were asked to give judgments on dominance, trustworthiness, and a preference of vote related to the politicians' faces. We used high-resolution EEG techniques to map statistical differences of power spectral density (PSD) cortical activity onto a realistic head model as well as partial directed coherence (PDC) and graph theory metrics to estimate the functional connectivity networks and investigate the role of cortical regions of interest (ROIs). Behavioral results revealed that judgment of dominance trait is the most predictive of the outcome of the simulated elections. Statistical comparisons related to PSD and PDC values highlighted an asymmetry in the activation of frontal cortical areas associated with the valence of the judged trait as well as to the probability to cast the vote. Overall, our results highlight the existence of cortical EEG features which are correlated with the prediction of vote and with the judgment of trustworthy and dominant faces. PMID:25214884
Welch, Martha G; Stark, Raymond I; Grieve, Philip G; Ludwig, Robert J; Isler, Joseph R; Barone, Joseph L; Myers, Michael M
2017-12-01
Premature delivery and maternal separation during hospitalisation increase infant neurodevelopmental risk. Previously, a randomised controlled trial of Family Nurture Intervention (FNI) in the neonatal intensive care unit demonstrated improvement across multiple mother and infant domains including increased electroencephalographic (EEG) power in the frontal polar region at term age. New aims were to quantify developmental changes in EEG power in all brain regions and frequencies and correlate developmental changes in EEG power among regions. EEG (128 electrodes) was obtained at 34-44 weeks postmenstrual age from preterm infants born 26-34 weeks. Forty-four infants were treated with Standard Care and 53 with FNI. EEG power was computed in 10 frequency bands (1-48 Hz) in 10 brain regions and in active and quiet sleep. Percent change/week in EEG power was increased in FNI in 132/200 tests (p < 0.05), 117 tests passed a 5% False Discovery Rate threshold. In addition, FNI demonstrated greater regional independence in those developmental rates of change. This study strengthens the conclusion that FNI promotes cerebral cortical development of preterm infants. The findings indicate that developmental changes in EEG may provide biomarkers for risk in preterm infants as well as proximal markers of effects of FNI. ©2017 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.
Hybrid EEG-fNIRS-Based Eight-Command Decoding for BCI: Application to Quadcopter Control.
Khan, Muhammad Jawad; Hong, Keum-Shik
2017-01-01
In this paper, a hybrid electroencephalography-functional near-infrared spectroscopy (EEG-fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain-computer interface is presented. A total of eight commands are decoded by fNIRS, as positioned on the prefrontal cortex, and by EEG, around the frontal, parietal, and visual cortices. Mental arithmetic, mental counting, mental rotation, and word formation tasks are decoded with fNIRS, in which the selected features for classification and command generation are the peak, minimum, and mean ΔHbO values within a 2-s moving window. In the case of EEG, two eyeblinks, three eyeblinks, and eye movement in the up/down and left/right directions are used for four-command generation. The features in this case are the number of peaks and the mean of the EEG signal during 1 s window. We tested the generated commands on a quadcopter in an open space. An average accuracy of 75.6% was achieved with fNIRS for four-command decoding and 86% with EEG for another four-command decoding. The testing results show the possibility of controlling a quadcopter online and in real-time using eight commands from the prefrontal and frontal cortices via the proposed hybrid EEG-fNIRS interface.
Brain activation associated with eccentric movement: A narrative review of the literature.
Perrey, Stéphane
2018-02-01
The movement occurring when a muscle exerts tension while lengthening is known as eccentric muscle action. Literature contains limited evidence on how our brain controls eccentric movement. However, how the cortical regions in the motor network are activated during eccentric muscle actions may be critical for understanding the underlying control mechanism of eccentric movements encountered in daily tasks. This is a novel topic that has only recently begun to be investigated through advancements in neuroimaging methods (electroencephalography, EEG; functional magnetic resonance imaging, fMRI). This review summarizes a selection of seven studies indicating mainly: longer time and higher cortical signal amplitude (EEG) for eccentric movement preparation and execution, greater magnitude of cortical signals with wider activated brain area (EEG, fMRI), and weaker brain functional connectivity (fMRI) between primary motor cortex (M1) and other cortical areas involved in the motor network during eccentric muscle actions. Only some differences among studies due to the forms of movement with overload were observed in the contralateral (to the active hand) M1 activity during eccentric movement. Altogether, the findings indicate an important challenge to the brain for controlling the eccentric movement. However, our understanding remains limited regarding the acute effects of eccentric exercise on cortical regions and their cooperation as functional networks that support motor functions. Further analysis and standardized protocols will provide deeper insights into how different cortical regions of the underlying motor network interplay with each other in increasingly demanding muscle exertions in eccentric mode.
Capotosto, Paolo; Perrucci, M Gianni; Brunetti, Marcella; Del Gratta, Cosimo; Doppelmayr, Michael; Grabner, Roland H; Klimesch, Wolfgang; Neubauer, Aljoscha; Neuper, Christa; Pfurtscheller, Gert; Romani, Gian Luca; Babiloni, Claudio
2009-12-28
More intelligent persons (high IQ) typically present a higher cortical activity during tasks requiring the encoding of visuo-spatial information, namely higher alpha (about 10 Hz) event-related desynchronization (ERD; Doppelmayr et al., 2005). The opposite is true ("neural efficiency") during the retrieval of the encoded information, as revealed by both lower alpha ERD and/or lower theta (about 5 Hz) event-related synchronization (ERS; Grabner et al., 2004). To reconcile these contrasting results, here we evaluated the working hypothesis that more intelligent male subjects are characterized by a high cortical activity during the encoding phase. This deep encoding would explain the relatively low cortical activity for the retrieval of the encoded information. To test this hypothesis, electroencephalographic (EEG) data were recorded in 22 healthy young male volunteers during visuo-spatial information processing (encoding) and short-term retrieval of the encoded information. Cortical activity was indexed by theta ERS and alpha ERD. It was found that the higher the subjects' total IQ, the stronger the frontal theta ERS during the encoding task. Furthermore, the higher the subjects' total IQ, the lower the frontal high-frequency alpha ERD (about 10-12 Hz) during the retrieval task. This was not true for parietal counterpart of these EEG rhythms. These results reconcile previous contrasting evidence confirming that more intelligent persons do not ever show event-related cortical responses compatible with "neural efficiency" hypothesis. Rather, their cortical activity would depend on flexible and task-adapting features of frontal activation.
Correlation between disease severity and brain electric LORETA tomography in Alzheimer's disease.
Gianotti, Lorena R R; Künig, Gabriella; Lehmann, Dietrich; Faber, Pascal L; Pascual-Marqui, Roberto D; Kochi, Kieko; Schreiter-Gasser, Ursula
2007-01-01
To compare EEG power spectra and LORETA-computed intracortical activity between Alzheimer's disease (AD) patients and healthy controls, and to correlate the results with cognitive performance in the AD group. Nineteen channel resting EEG was recorded in 21 mild to moderate AD patients and in 23 controls. Power spectra and intracortical LORETA tomography were computed in seven frequency bands and compared between groups. In the AD patients, the EEG results were correlated with cognitive performance (Mini Mental State Examination, MMSE). AD patients showed increased power in EEG delta and theta frequency bands, and decreased power in alpha2, beta1, beta2 and beta3. LORETA specified that increases and decreases of power affected different cortical areas while largely sparing prefrontal cortex. Delta power correlated negatively and alpha1 power positively with the AD patients' MMSE scores; LORETA tomography localized these correlations in left temporo-parietal cortex. The non-invasive EEG method of LORETA localized pathological cortical activity in our mild to moderate AD patients in agreement with the literature, and yielded striking correlations between EEG delta and alpha1 activity and MMSE scores in left temporo-parietal cortex. The present data support the hypothesis of an asymmetrical progression of the Alzheimer's disease.
Preterm EEG: a multimodal neurophysiological protocol.
Stjerna, Susanna; Voipio, Juha; Metsäranta, Marjo; Kaila, Kai; Vanhatalo, Sampsa
2012-02-18
Since its introduction in early 1950s, electroencephalography (EEG) has been widely used in the neonatal intensive care units (NICU) for assessment and monitoring of brain function in preterm and term babies. Most common indications are the diagnosis of epileptic seizures, assessment of brain maturity, and recovery from hypoxic-ischemic events. EEG recording techniques and the understanding of neonatal EEG signals have dramatically improved, but these advances have been slow to penetrate through the clinical traditions. The aim of this presentation is to bring theory and practice of advanced EEG recording available for neonatal units. In the theoretical part, we will present animations to illustrate how a preterm brain gives rise to spontaneous and evoked EEG activities, both of which are unique to this developmental phase, as well as crucial for a proper brain maturation. Recent animal work has shown that the structural brain development is clearly reflected in early EEG activity. Most important structures in this regard are the growing long range connections and the transient cortical structure, subplate. Sensory stimuli in a preterm baby will generate responses that are seen at a single trial level, and they have underpinnings in the subplate-cortex interaction. This brings neonatal EEG readily into a multimodal study, where EEG is not only recording cortical function, but it also tests subplate function via different sensory modalities. Finally, introduction of clinically suitable dense array EEG caps, as well as amplifiers capable of recording low frequencies, have disclosed multitude of brain activities that have as yet been overlooked. In the practical part of this video, we show how a multimodal, dense array EEG study is performed in neonatal intensive care unit from a preterm baby in the incubator. The video demonstrates preparation of the baby and incubator, application of the EEG cap, and performance of the sensory stimulations.
Nessi: An EEG-Controlled Web Browser for Severely Paralyzed Patients
Bensch, Michael; Karim, Ahmed A.; Mellinger, Jürgen; Hinterberger, Thilo; Tangermann, Michael; Bogdan, Martin; Rosenstiel, Wolfgang; Birbaumer, Niels
2007-01-01
We have previously demonstrated that an EEG-controlled web browser based on self-regulation of slow cortical potentials (SCPs) enables severely paralyzed patients to browse the internet independently of any voluntary muscle control. However, this system had several shortcomings, among them that patients could only browse within a limited number of web pages and had to select links from an alphabetical list, causing problems if the link names were identical or if they were unknown to the user (as in graphical links). Here we describe a new EEG-controlled web browser, called Nessi, which overcomes these shortcomings. In Nessi, the open source browser, Mozilla, was extended by graphical in-place markers, whereby different brain responses correspond to different frame colors placed around selectable items, enabling the user to select any link on a web page. Besides links, other interactive elements are accessible to the user, such as e-mail and virtual keyboards, opening up a wide range of hypertext-based applications. PMID:18350132
Marsella, Pasquale; Scorpecci, Alessandro; Vecchiato, Giovanni; Colosimo, Alfredo; Maglione, Anton Giulio; Babiloni, Fabio
2014-05-01
To investigate by means of non-invasive neuroelectrical imaging the differences in the perceived pleasantness of music between children with cochlear implants (CI) and normal-hearing (NH) children. 5 NH children and 5 children who received a sequential bilateral CI were assessed by means of High-Resolution EEG with Source Reconstruction as they watched a musical cartoon. Implanted children were tested before and after the second implant. For each subject the scalp Power Spectral Density was calculated in order to investigate the EEG alpha asymmetry. The scalp topographic distribution of the EEG power spectrum in the alpha band was different in children using one CI as compared to NH children (see figure). With two CIs the cortical activation pattern changed significantly, becoming more similar to the one observed in NH children. The findings support the hypothesis that bilateral CI users have a closer-to-normal perception of the pleasantness of music than unilaterally implanted children.
Zheng, Thomas W; O'Brien, Terence J; Kulikova, Sofya P; Reid, Christopher A; Morris, Margaret J; Pinault, Didier
2014-03-01
A major side effect of carbamazepine (CBZ), a drug used to treat neurological and neuropsychiatric disorders, is drowsiness, a state characterized by increased slow-wave oscillations with the emergence of sleep spindles in the electroencephalogram (EEG). We conducted cortical EEG and thalamic cellular recordings in freely moving or lightly anesthetized rats to explore the impact of CBZ within the intact corticothalamic (CT)-thalamocortical (TC) network, more specifically on CT 5-9-Hz and TC spindle (10-16-Hz) oscillations. Two to three successive 5-9-Hz waves were followed by a spindle in the cortical EEG. A single systemic injection of CBZ (20 mg/kg) induced a significant increase in the power of EEG 5-9-Hz oscillations and spindles. Intracellular recordings of glutamatergic TC neurons revealed 5-9-Hz depolarizing wave-hyperpolarizing wave sequences prolonged by robust, rhythmic spindle-frequency hyperpolarizing waves. This hybrid sequence occurred during a slow hyperpolarizing trough, and was at least 10 times more frequent under the CBZ condition than under the control condition. The hyperpolarizing waves reversed at approximately -70 mV, and became depolarizing when recorded with KCl-filled intracellular micropipettes, indicating that they were GABAA receptor-mediated potentials. In neurons of the GABAergic thalamic reticular nucleus, the principal source of TC GABAergic inputs, CBZ augmented both the number and the duration of sequences of rhythmic spindle-frequency bursts of action potentials. This indicates that these GABAergic neurons are responsible for the generation of at least the spindle-frequency hyperpolarizing waves in TC neurons. In conclusion, CBZ potentiates GABAA receptor-mediated TC spindle oscillations. Furthermore, we propose that CT 5-9-Hz waves can trigger TC spindles. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Spatial and temporal EEG dynamics of dual-task driving performance
2011-01-01
Background Driver distraction is a significant cause of traffic accidents. The aim of this study is to investigate Electroencephalography (EEG) dynamics in relation to distraction during driving. To study human cognition under a specific driving task, simulated real driving using virtual reality (VR)-based simulation and designed dual-task events are built, which include unexpected car deviations and mathematics questions. Methods We designed five cases with different stimulus onset asynchrony (SOA) to investigate the distraction effects between the deviations and equations. The EEG channel signals are first converted into separated brain sources by independent component analysis (ICA). Then, event-related spectral perturbation (ERSP) changes of the EEG power spectrum are used to evaluate brain dynamics in time-frequency domains. Results Power increases in the theta and beta bands are observed in relation with distraction effects in the frontal cortex. In the motor area, alpha and beta power suppressions are also observed. All of the above results are consistently observed across 15 subjects. Additionally, further analysis demonstrates that response time and multiple cortical EEG power both changed significantly with different SOA. Conclusions This study suggests that theta power increases in the frontal area is related to driver distraction and represents the strength of distraction in real-life situations. PMID:21332977
A Space-Time-Frequency Dictionary for Sparse Cortical Source Localization.
Korats, Gundars; Le Cam, Steven; Ranta, Radu; Louis-Dorr, Valerie
2016-09-01
Cortical source imaging aims at identifying activated cortical areas on the surface of the cortex from the raw electroencephalogram (EEG) data. This problem is ill posed, the number of channels being very low compared to the number of possible source positions. In some realistic physiological situations, the active areas are sparse in space and of short time durations, and the amount of spatio-temporal data to carry the inversion is then limited. In this study, we propose an original data driven space-time-frequency (STF) dictionary which takes into account simultaneously both spatial and time-frequency sparseness while preserving smoothness in the time frequency (i.e., nonstationary smooth time courses in sparse locations). Based on these assumptions, we take benefit of the matching pursuit (MP) framework for selecting the most relevant atoms in this highly redundant dictionary. We apply two recent MP algorithms, single best replacement (SBR) and source deflated matching pursuit, and we compare the results using a spatial dictionary and the proposed STF dictionary to demonstrate the improvements of our multidimensional approach. We also provide comparison using well-established inversion methods, FOCUSS and RAP-MUSIC, analyzing performances under different degrees of nonstationarity and signal to noise ratio. Our STF dictionary combined with the SBR approach provides robust performances on realistic simulations. From a computational point of view, the algorithm is embedded in the wavelet domain, ensuring high efficiency in term of computation time. The proposed approach ensures fast and accurate sparse cortical localizations on highly nonstationary and noisy data.
Shepovalnikov, A N; Egorov, M V
2015-01-01
Changes is systemic brain activity under influence of classical music (minor and major music) were studied at two groups of healthy children aged 5-6 years (n = 53). In 25 of studied children the Luscher test showed increased level of anxiety which significantly decreased after music therapy sessions. Bioelectrical cortical activity registered from 20 unipolar leads was subjected to correlation, coherence and factor analysis. Also the dynamics of the power spectrum for each of the EEG was studied. According to EEG all children after listening to both minor and major tones showed reorganization of brain rhythm structure accompanied by a decrease in the level of coherence and correlation of EEG; also was found significant and almost universal decrease in the EEG power spectrum. Registered EEG changes under the influence of classical music seems to reflect a decrease in excess of "internal tension" and weakening degree of "stiffness" to ensure the activity of cerebral structures responsible for mechanisms of "basic integration" which maintain constant readiness of brain to rapid and complete inclusion in action.
Decoding human swallowing via electroencephalography: a state-of-the-art review
Jestrović, Iva; Coyle, James L.
2015-01-01
Swallowing and swallowing disorders have garnered continuing interest over the past several decades. Electroencephalography (EEG) is an inexpensive and non-invasive procedure with very high temporal resolution which enables analysis of short and fast swallowing events, as well as an analysis of the organizational and behavioral aspects of cortical motor preparation, swallowing execution and swallowing regulation. EEG is a powerful technique which can be used alone or in combination with other techniques for monitoring swallowing, detection of swallowing motor imagery for diagnostic or biofeedback purposes, or to modulate and measure the effects of swallowing rehabilitation. This paper provides a review of the existing literature which has deployed EEG in the investigation of oropharyngeal swallowing, smell, taste and texture related to swallowing, cortical pre-motor activation in swallowing, and swallowing motor imagery detection. Furthermore, this paper provides a brief review of the different modalities of brain imaging techniques used to study swallowing brain activities, as well as the EEG components of interest for studies on swallowing and on swallowing motor imagery. Lastly, this paper provides directions for future swallowing investigations using EEG. PMID:26372528
Zazen meditation and no-task resting EEG compared with LORETA intracortical source localization.
Faber, Pascal L; Lehmann, Dietrich; Gianotti, Lorena R R; Milz, Patricia; Pascual-Marqui, Roberto D; Held, Marlene; Kochi, Kieko
2015-02-01
Meditation is a self-induced and willfully initiated practice that alters the state of consciousness. The meditation practice of Zazen, like many other meditation practices, aims at disregarding intrusive thoughts while controlling body posture. It is an open monitoring meditation characterized by detached moment-to-moment awareness and reduced conceptual thinking and self-reference. Which brain areas differ in electric activity during Zazen compared to task-free resting? Since scalp electroencephalography (EEG) waveforms are reference-dependent, conclusions about the localization of active brain areas are ambiguous. Computing intracerebral source models from the scalp EEG data solves this problem. In the present study, we applied source modeling using low resolution brain electromagnetic tomography (LORETA) to 58-channel scalp EEG data recorded from 15 experienced Zen meditators during Zazen and no-task resting. Zazen compared to no-task resting showed increased alpha-1 and alpha-2 frequency activity in an exclusively right-lateralized cluster extending from prefrontal areas including the insula to parts of the somatosensory and motor cortices and temporal areas. Zazen also showed decreased alpha and beta-2 activity in the left angular gyrus and decreased beta-1 and beta-2 activity in a large bilateral posterior cluster comprising the visual cortex, the posterior cingulate cortex and the parietal cortex. The results include parts of the default mode network and suggest enhanced automatic memory and emotion processing, reduced conceptual thinking and self-reference on a less judgmental, i.e., more detached moment-to-moment basis during Zazen compared to no-task resting.
Non-linear Parameter Estimates from Non-stationary MEG Data
Martínez-Vargas, Juan D.; López, Jose D.; Baker, Adam; Castellanos-Dominguez, German; Woolrich, Mark W.; Barnes, Gareth
2016-01-01
We demonstrate a method to estimate key electrophysiological parameters from resting state data. In this paper, we focus on the estimation of head-position parameters. The recovery of these parameters is especially challenging as they are non-linearly related to the measured field. In order to do this we use an empirical Bayesian scheme to estimate the cortical current distribution due to a range of laterally shifted head-models. We compare different methods of approaching this problem from the division of M/EEG data into stationary sections and performing separate source inversions, to explaining all of the M/EEG data with a single inversion. We demonstrate this through estimation of head position in both simulated and empirical resting state MEG data collected using a head-cast. PMID:27597815
Chen, Andrew C N; Liu, Feng-Jun; Wang, Li; Arendt-Nielsen, Lars
2006-02-15
This study determined: (a) if acupuncture stimulation at a traditional site might modulate ongoing EEG as compared with stimulation of a control site; (b) if high-frequency vs. low-frequency stimulation could exert differential effects of acupuncture; (c) if the observed effects of acupuncture were specific to certain EEG bands; and (d) if the acupuncture effect could be isolated at a specific scalp field, with its putative underlying intracranial source. Twelve healthy male volunteers (age range 22-35) participated in two experimental sessions separated by 1 week, which involved transcutaneous acupoint stimulation at selected acupoint (Li 4, HeGu) vs. a mock point at the fourth interosseous muscle area on the left hand in high (HF: 100 Hz) vs. low-frequency (LF: 2 Hz) stimulation by counter-balanced order. 124-ch EEG data were used to analyze the Delta, Theta, Alpha-1, Alpha-2, Beta, and Gamma bands. The absolute EEG powers (muv2) at focal maxima across three stages (baseline, stimulation, post) were examined by two-way (condition, stage) repeated measures ANOVA. The activity of the Theta power significantly decreased (P = 0.02), compared with control during HF but not LF stimulation at acupoint stimulation, however, there was no study effect at the mock point. A decreased Theta EEG power was prominent at the frontal midline sites (FCz, Fz) and the contralateral right hemisphere front site (FCC2h). In contrast, the Theta power of low-frequency stimulation showed an increase from the baseline as those in both controlled mock point stimulations. The observed high-frequency acupoint stimulation effects of Theta EEG were only present during, but not after, simulation. The topographic Theta activity was tentatively identified to originate from the intracranial current source in cingulate cortex, likely ACC. It is likely that short-term cortical plasticity occurs during high-frequency but not low-frequency stimulation at the HeGu point, but not mock point. We suggest that HeGu acupuncture stimulation modulates limbic cingulum by a frequency modulation mode, which then may damp nociceptive processing in the brain.
Human cortical activity related to unilateral movements. A high resolution EEG study.
Urbano, A; Babiloni, C; Onorati, P; Babiloni, F
1996-12-20
In the present study a modern high resolution electroencephalography (EEG) technique was used to investigate the dynamic functional topography of human cortical activity related to simple unilateral internally triggered finger movements. The sensorimotor area (M1-S1) contralateral to the movement as well as the supplementary motor area (SMA) and to a lesser extent the ipsilateral M1-S1 were active during the preparation and execution of these movements. These findings suggest that both hemispheres may cooperate in both planning and production of simple unilateral volitional acts.
Cortical activity during cued picture naming predicts individual differences in stuttering frequency
Mock, Jeffrey R.; Foundas, Anne L.; Golob, Edward J.
2016-01-01
Objective Developmental stuttering is characterized by fluent speech punctuated by stuttering events, the frequency of which varies among individuals and contexts. Most stuttering events occur at the beginning of an utterance, suggesting neural dynamics associated with stuttering may be evident during speech preparation. Methods This study used EEG to measure cortical activity during speech preparation in men who stutter, and compared the EEG measures to individual differences in stuttering rate as well as to a fluent control group. Each trial contained a cue followed by an acoustic probe at one of two onset times (early or late), and then a picture. There were two conditions: a speech condition where cues induced speech preparation of the picture’s name and a control condition that minimized speech preparation. Results Across conditions stuttering frequency correlated to cue-related EEG beta power and auditory ERP slow waves from early onset acoustic probes. Conclusions The findings reveal two new cortical markers of stuttering frequency that were present in both conditions, manifest at different times, are elicited by different stimuli (visual cue, auditory probe), and have different EEG responses (beta power, ERP slow wave). Significance The cue-target paradigm evoked brain responses that correlated to pre-experimental stuttering rate. PMID:27472545
Mock, Jeffrey R; Foundas, Anne L; Golob, Edward J
2016-09-01
Developmental stuttering is characterized by fluent speech punctuated by stuttering events, the frequency of which varies among individuals and contexts. Most stuttering events occur at the beginning of an utterance, suggesting neural dynamics associated with stuttering may be evident during speech preparation. This study used EEG to measure cortical activity during speech preparation in men who stutter, and compared the EEG measures to individual differences in stuttering rate as well as to a fluent control group. Each trial contained a cue followed by an acoustic probe at one of two onset times (early or late), and then a picture. There were two conditions: a speech condition where cues induced speech preparation of the picture's name and a control condition that minimized speech preparation. Across conditions stuttering frequency correlated to cue-related EEG beta power and auditory ERP slow waves from early onset acoustic probes. The findings reveal two new cortical markers of stuttering frequency that were present in both conditions, manifest at different times, are elicited by different stimuli (visual cue, auditory probe), and have different EEG responses (beta power, ERP slow wave). The cue-target paradigm evoked brain responses that correlated to pre-experimental stuttering rate. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Habboush, Nawar; Hamid, Laith; Japaridze, Natia; Wiegand, Gert; Heute, Ulrich; Stephani, Ulrich; Galka, Andreas; Siniatchkin, Michael
2015-08-01
The discretization of the brain and the definition of the Laplacian matrix influence the results of methods based on spatial and spatio-temporal smoothness, since the Laplacian operator is used to define the smoothness based on the neighborhood of each grid point. In this paper, the results of low resolution electromagnetic tomography (LORETA) and the spatiotemporal Kalman filter (STKF) are computed using, first, a greymatter source space with the standard definition of the Laplacian matrix and, second, using a whole-brain source space and a modified definition of the Laplacian matrix. Electroencephalographic (EEG) source imaging results of five inter-ictal spikes from a pre-surgical patient with epilepsy are used to validate the two aforementioned approaches. The results using the whole-brain source space and the modified definition of the Laplacian matrix were concentrated in a single source activation, stable, and concordant with the location of the focal cortical dysplasia (FCD) in the patient's brain compared with the results which use a grey-matter grid and the classical definition of the Laplacian matrix. This proof-of-concept study demonstrates a substantial improvement of source localization with both LORETA and STKF and constitutes a basis for further research in a large population of patients with epilepsy.
Suppression of competing speech through entrainment of cortical oscillations
D'Zmura, Michael; Srinivasan, Ramesh
2013-01-01
People are highly skilled at attending to one speaker in the presence of competitors, but the neural mechanisms supporting this remain unclear. Recent studies have argued that the auditory system enhances the gain of a speech stream relative to competitors by entraining (or “phase-locking”) to the rhythmic structure in its acoustic envelope, thus ensuring that syllables arrive during periods of high neuronal excitability. We hypothesized that such a mechanism could also suppress a competing speech stream by ensuring that syllables arrive during periods of low neuronal excitability. To test this, we analyzed high-density EEG recorded from human adults while they attended to one of two competing, naturalistic speech streams. By calculating the cross-correlation between the EEG channels and the speech envelopes, we found evidence of entrainment to the attended speech's acoustic envelope as well as weaker yet significant entrainment to the unattended speech's envelope. An independent component analysis (ICA) decomposition of the data revealed sources in the posterior temporal cortices that displayed robust correlations to both the attended and unattended envelopes. Critically, in these components the signs of the correlations when attended were opposite those when unattended, consistent with the hypothesized entrainment-based suppressive mechanism. PMID:23515789
Gaetz, M; Weinberg, H; Rzempoluck, E; Jantzen, K J
1998-04-01
It has recently been suggested that reentrant connections are essential in systems that process complex information [A. Damasio, H. Damasio, Cortical systems for the retrieval of concrete knowledge: the convergence zone framework, in: C. Koch, J.L. Davis (Eds.), Large Scale Neuronal Theories of the Brain, The MIT Press, Cambridge, 1995, pp. 61-74; G. Edelman, The Remembered Present, Basic Books, New York, 1989; M.I. Posner, M. Rothbart, Constructing neuronal theories of mind, in: C. Koch, J.L. Davis (Eds.), Large Scale Neuronal Theories of the Brain, The MIT Press, Cambridge, 1995, pp. 183-199; C. von der Malsburg, W. Schneider, A neuronal cocktail party processor, Biol. Cybem., 54 (1986) 29-40]. Reentry is not feedback, but parallel signalling in the time domain between spatially distributed maps, similar to a process of correlation between distributed systems. Accordingly, it was expected that during spontaneous reversals of the Necker cube, complex patterns of correlations between distributed systems would be present in the cortex. The present study included EEG (n=4) and MEG recordings (n=5). Two experimental questions were posed: (1) Can distributed cortical patterns present during perceptual reversals be classified differently using a generalised regression neural network (GRNN) compared to processing of a two-dimensional figure? (2) Does correlated cortical activity increase significantly during perception of a Necker cube reversal? One-second duration single trials of EEG and MEG data were analysed using the GRNN. Electrode/sensor pairings based on cortico-cortical connections were selected to assess correlated activity in each condition. The GRNN significantly classified single trials recorded during Necker cube reversals as different from single trials recorded during perception of a two-dimensional figure for both EEG and MEG. In addition, correlated cortical activity increased significantly in the Necker cube reversal condition for EEG and MEG compared to the perception of a non-reversing stimulus. Coherent MEG activity observed over occipital, parietal and temporal regions is believed to represent neural systems related to the perception of Necker cube reversals. Copyright 1998 Elsevier Science B.V.
Reassessment of the structural basis of the ascending arousal system
Fuller, Patrick M.; Sherman, David; Pedersen, Nigel P.; Saper, Clifford B.; Lu, Jun
2011-01-01
The “ascending reticular activating system” theory proposed that neurons in the upper brainstem reticular formation projected to forebrain targets that promoted wakefulness. More recent formulations have emphasized that most neurons at the pontomesencepahlic junction that participate in these pathways are actually in monoaminergic and cholinergic cell groups. However, cell-specific lesions of these cell groups have never been able to reproduce the deep coma seen after acute paramedian midbrain lesions that transect ascending axons at the caudal midbrain level. To determine whether the cortical afferents from the thalamus or the basal forebrain were more important in maintaining arousal, we first place large cell-body specific lesions in these targets. Surprisingly, extensive thalamic lesions had little effect on EEG or behavioral measures of wakefulness or on c-Fos expression by cortical neurons during wakefulness. In contrast, animals with large basal forebrain lesions were behaviorally unresponsive, had a monotonous sub-1 Hz EEG, and little cortical c-Fos expression during continuous gentle handling. We then retrogradely labeled inputs to the basal forebrain from the upper brainstem, and found a substantial input from glutamatergic neurons in the parabrachial nucleus and adjacent pre-coeruleus area. Cell specific lesions of the parabrachial-precoeruleus complex produced behavioral unresponsiveness, a monotonous sub-1Hz cortical EEG, and loss of cortical c-Fos expression during gentle handling. These experiments indicate that in rats the reticulo-thalamo-cortical pathway may play a very limited role in behavioral or electrocortical arousal, while the projection from the parabrachial nucleus and precoeruleus region, relayed by the basal forebrain to the cerebral cortex, may be critical for this process. PMID:21280045
Kuo, Terry B J; Yang, Cheryl C H
2004-06-15
To explore interactions between cerebral cortical and autonomic functions in different sleep-wake states. Active waking (AW), quiet sleep (QS), and paradoxical sleep (PS) of adult male Wistar-Kyoto rats (WKY) on their daytime sleep were compared. Ten WKY. All rats had electrodes implanted for polygraphic recordings. One week later, a 6-hour daytime sleep-wakefulness recording session was performed. A scatterplot analysis of electroencephalogram (EEG) slow-wave magnitude (0.5-4 Hz) and heart rate variability (HRV) was applied in each rat. The EEG slow-wave-RR interval scatterplot from all of the recordings revealed a propeller-like pattern. If the scatterplot was divided into AW, PS, and QS according to the corresponding EEG mean power frequency and nuchal electromyogram, the EEG slow wave-RR interval relationship became nil, negative, and positive for AW, PS, and QS, respectively. A significant negative relationship was found for EEG slow-wave and high-frequency power of HRV (HF) coupling during PS and for EEG slow wave and low-frequency power of HRV to HF ratio (LF/HF) coupling during QS. The optimal time lags for the slow wave-LF/HF relationship were different between PS and QS. Bradycardia noted in QS and PS was related to sympathetic suppression and vagal excitation, respectively. The EEG slow wave-HRV scatterplot may provide unique insights into studies of sleep, and such a relationship may delineate the sleep-state-dependent fluctuations in autonomic nervous system activity.
An EEG Finger-Print of fMRI deep regional activation.
Meir-Hasson, Yehudit; Kinreich, Sivan; Podlipsky, Ilana; Hendler, Talma; Intrator, Nathan
2014-11-15
This work introduces a general framework for producing an EEG Finger-Print (EFP) which can be used to predict specific brain activity as measured by fMRI at a given deep region. This new approach allows for improved EEG spatial resolution based on simultaneous fMRI activity measurements. Advanced signal processing and machine learning methods were applied on EEG data acquired simultaneously with fMRI during relaxation training guided by on-line continuous feedback on changing alpha/theta EEG measure. We focused on demonstrating improved EEG prediction of activation in sub-cortical regions such as the amygdala. Our analysis shows that a ridge regression model that is based on time/frequency representation of EEG data from a single electrode, can predict the amygdala related activity significantly better than a traditional theta/alpha activity sampled from the best electrode and about 1/3 of the times, significantly better than a linear combination of frequencies with a pre-defined delay. The far-reaching goal of our approach is to be able to reduce the need for fMRI scanning for probing specific sub-cortical regions such as the amygdala as the basis for brain-training procedures. On the other hand, activity in those regions can be characterized with higher temporal resolution than is obtained by fMRI alone thus revealing additional information about their processing mode. Copyright © 2013 Elsevier Inc. All rights reserved.
Thul, Alexander; Lechinger, Julia; Donis, Johann; Michitsch, Gabriele; Pichler, Gerald; Kochs, Eberhard F; Jordan, Denis; Ilg, Rüdiger; Schabus, Manuel
2016-02-01
Clinical assessments that rely on behavioral responses to differentiate Disorders of Consciousness are at times inapt because of some patients' motor disabilities. To objectify patients' conditions of reduced consciousness the present study evaluated the use of electroencephalography to measure residual brain activity. We analyzed entropy values of 18 scalp EEG channels of 15 severely brain-damaged patients with clinically diagnosed Minimally-Conscious-State (MCS) or Unresponsive-Wakefulness-Syndrome (UWS) and compared the results to a sample of 24 control subjects. Permutation entropy (PeEn) and symbolic transfer entropy (STEn), reflecting information processes in the EEG, were calculated for all subjects. Participants were tested on a modified active own-name paradigm to identify correlates of active instruction following. PeEn showed reduced local information content in the EEG in patients, that was most pronounced in UWS. STEn analysis revealed altered directed information flow in the EEG of patients, indicating impaired feed-backward connectivity. Responses to auditory stimulation yielded differences in entropy measures, indicating reduced information processing in MCS and UWS. Local EEG information content and information flow are affected in Disorders of Consciousness. This suggests local cortical information capacity and feedback information transfer as neural correlates of consciousness. The utilized EEG entropy analyses were able to relate to patient groups with different Disorders of Consciousness. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Vecchiato, Giovanni; Astolfi, Laura; De Vico Fallani, Fabrizio; Salinari, Serenella; Cincotti, Febo; Aloise, Fabio; Mattia, Donatella; Marciani, Maria Grazia; Bianchi, Luigi; Soranzo, Ramon; Babiloni, Fabio
2009-01-01
In this paper we illustrate the capability of tracking brain activity during the observation of commercial TV spots by using advanced high resolution EEG statistical techniques in time and frequency domains. In particular, we analyzed the statistically significant cortical spectral power activity in different frequency bands during the observation of a commercial video clip related to the use of a beer in a group of 13 normal subjects. In addition, a TV speech of the prime minister of Italy was analyzed in two groups of swing and "supporter" voters. Results suggested that the cortical activity during the observation of commercial spots could vary consistently across the spot. This fact suggest the possibility to remove the part of the spot that are not particularly attractive by using those cerebral indexes. The cortical activity during the observation of the political speech indicated a major cortical activity in the supporters group when compared to the swing voters. In this case, it is possible to conclude that the communication proposed has failed to raise attention or interest on swing voters. In conclusions, high resolution EEG have been proved able to generate useful insights about the particular fruition of TV messages, related to both commercial as well as political fields.
Babiloni, Claudio; Brancucci, Alfredo; Vecchio, Fabrizio; Arendt-Nielsen, Lars; Chen, Andrew C N; Rossini, Paolo M
2006-05-01
Does functional coupling of centro-parietal EEG rhythms selectively increase during the anticipation of sensorimotor events composed by somatosensory stimulation and visuomotor task? EEG data were recorded in (1) 'simultaneous' condition in which the subjects waited for somatosensory stimulation at left hand concomitant with a Go (or NoGo) visual stimulus triggering (50%) right hand movements and in (2) 'sequential' condition where the somatosensory stimulation was followed (+1.5 s) by a visuomotor Go/NoGo task. Centro-parietal functional coupling was modeled by spectral coherence. Spectral coherence was computed from Laplacian-transformed EEG data at delta-theta (2-7 Hz), alpha (8-14 Hz), beta 1 (15-21 Hz), beta 2 (22-33 Hz), and gamma (34-45 Hz) rhythms. Before 'simultaneous' sensorimotor events, centro-parietal coherence regions increased in both hemispheres and at all rhythms. In the 'sequential' condition, right centro-parietal coherence increased before somatosensory event (left hand), whereas left centro-parietal coherence increased before subsequent Go/NoGo event (right hand). Anticipation of somatosensory and visuomotor events enhances contralateral centro-parietal coupling of slow and fast EEG rhythms. Predictable somatosensory and visuomotor events are anticipated not only by synchronization of cortical pyramidal neurons generating EEG power in parietal and primary sensorimotor cortical areas (Babiloni C, Brancucci A, Capotosto P, Arendt-Nielsen L, Chen ACN, Rossini PM. Expectancy of pain is influenced by motor preparation: a high-resolution EEG study of cortical alpha rhythms. Behav. Neurosci. 2005a;119(2):503-511; Babiloni C, Brancucci A, Pizzella V, Romani G.L, Tecchio F, Torquati K, Zappasodi F, Arendt-Nielsen L, Chen ACN, Rossini PM. Contingent negative variation in the parasylvian cortex increases during expectancy of painful sensorimotor events: a magnetoencephalographic study. Behav. Neurosci. 2005b;119(2):491-502) but also by functional coordination of these areas.
2009-04-30
successfully raised physiological and 15. SUBJECT TERMS brain, cognitive neuroscience, EEG , neurofeedback , competition, stress, neuroendocrine, shooting...efficacy of the Neurofeedback training to elevate frontal EEG asymmetry (F4 minus F3 alpha power) in an attempt to enhance emotion regulation. The...observed a remarkable increase or synchrony of EEG alpha power (i.e., low-alpha) across the general scalp topography for both groups ( neurofeedback
A mesostate-space model for EEG and MEG.
Daunizeau, Jean; Friston, Karl J
2007-10-15
We present a multi-scale generative model for EEG, that entails a minimum number of assumptions about evoked brain responses, namely: (1) bioelectric activity is generated by a set of distributed sources, (2) the dynamics of these sources can be modelled as random fluctuations about a small number of mesostates, (3) mesostates evolve in a temporal structured way and are functionally connected (i.e. influence each other), and (4) the number of mesostates engaged by a cognitive task is small (e.g. between one and a few). A Variational Bayesian learning scheme is described that furnishes the posterior density on the models parameters and its evidence. Since the number of meso-sources specifies the model, the model evidence can be used to compare models and find the optimum number of meso-sources. In addition to estimating the dynamics at each cortical dipole, the mesostate-space model and its inversion provide a description of brain activity at the level of the mesostates (i.e. in terms of the dynamics of meso-sources that are distributed over dipoles). The inclusion of a mesostate level allows one to compute posterior probability maps of each dipole being active (i.e. belonging to an active mesostate). Critically, this model accommodates constraints on the number of meso-sources, while retaining the flexibility of distributed source models in explaining data. In short, it bridges the gap between standard distributed and equivalent current dipole models. Furthermore, because it is explicitly spatiotemporal, the model can embed any stochastic dynamical causal model (e.g. a neural mass model) as a Markov process prior on the mesostate dynamics. The approach is evaluated and compared to standard inverse EEG techniques, using synthetic data and real data. The results demonstrate the added-value of the mesostate-space model and its variational inversion.
Hammer, Jiří; Pistohl, Tobias; Fischer, Jörg; Kršek, Pavel; Tomášek, Martin; Marusič, Petr; Schulze-Bonhage, Andreas; Aertsen, Ad; Ball, Tonio
2016-01-01
How neuronal activity of motor cortex is related to movement is a central topic in motor neuroscience. Motor-cortical single neurons are more closely related to hand movement velocity than speed, that is, the magnitude of the (directional) velocity vector. Recently, there is also increasing interest in the representation of movement parameters in neuronal population activity, such as reflected in the intracranial EEG (iEEG). We show that in iEEG, contrasting to what has been previously found on the single neuron level, speed predominates over velocity. The predominant speed representation was present in nearly all iEEG signal features, up to the 600–1000 Hz range. Using a model of motor-cortical signals arising from neuronal populations with realistic single neuron tuning properties, we show how this reversal can be understood as a consequence of increasing population size. Our findings demonstrate that the information profile in large population signals may systematically differ from the single neuron level, a principle that may be helpful in the interpretation of neuronal population signals in general, including, for example, EEG and functional magnetic resonance imaging. Taking advantage of the robust speed population signal may help in developing brain–machine interfaces exploiting population signals. PMID:26984895
Moyanova, S; Kortenska, L; Kirov, R; Iliev, I
1998-12-01
The powerful vasoconstrictor peptide endothelin-1 (ET1) has been shown to reduce local cerebral blood flow in brain areas supplied by the middle cerebral artery (MCA) to a pathologically low level upon intracerebral injection adjacent to the MCA. This reduction manifests itself as an ischemic infarct, that is fully developed within 3 days after ET1 injection. The aim of the present study is to examine the effect of ET1 on electroencephalographic (EEG) activity. ET1 was microinjected unilaterally at a dose of 60 pmol in 3 microl of saline to the MCA in conscious rats. EEG signals were recorded from the frontoparietal cortical area, supplied by MCA, from the first up to the fourteenth day after ET1 injection. EEG activity was analyzed by the fast Fourier transformation. A significant shift to a lower EEG frequency, i.e., augmentation of slow waves and a reduction of alpha-like and faster EEG waves was found post-ET1. This effect was maximal after 3-7 days when the most severe destruction of neurons in this cortical area occurs, as has been previously demonstrated. The results suggest that the quantitative EEG analysis may provide useful additional information about the functional disturbances associated with focal cerebral ischemia.
Mizuhara, Hiroaki; Sato, Naoyuki; Yamaguchi, Yoko
2015-05-01
Neural oscillations are crucial for revealing dynamic cortical networks and for serving as a possible mechanism of inter-cortical communication, especially in association with mnemonic function. The interplay of the slow and fast oscillations might dynamically coordinate the mnemonic cortical circuits to rehearse stored items during working memory retention. We recorded simultaneous EEG-fMRI during a working memory task involving a natural scene to verify whether the cortical networks emerge with the neural oscillations for memory of the natural scene. The slow EEG power was enhanced in association with the better accuracy of working memory retention, and accompanied cortical activities in the mnemonic circuits for the natural scene. Fast oscillation showed a phase-amplitude coupling to the slow oscillation, and its power was tightly coupled with the cortical activities for representing the visual images of natural scenes. The mnemonic cortical circuit with the slow neural oscillations would rehearse the distributed natural scene representations with the fast oscillation for working memory retention. The coincidence of the natural scene representations could be obtained by the slow oscillation phase to create a coherent whole of the natural scene in the working memory. Copyright © 2015 Elsevier Inc. All rights reserved.
Ruehland, Warren R; O'Donoghue, Fergal J; Pierce, Robert J; Thornton, Andrew T; Singh, Parmjit; Copland, Janet M; Stevens, Bronwyn; Rochford, Peter D
2011-01-01
To examine the impact of using American Academy of Sleep Medicine (AASM) recommended EEG derivations (F4/M1, C4/M1, O2/M1) vs. a single derivation (C4/M1) in polysomnography (PSG) on the measurement of sleep and cortical arousals, including inter- and intra-observer variability. Prospective, non-blinded, randomized comparison. Three Australian tertiary-care hospital clinical sleep laboratories. 30 PSGs from consecutive patients investigated for obstructive sleep apnea (OSA) during December 2007 and January 2008. N/A. To examine the impact of EEG derivations on PSG summary statistics, 3 scorers from different Australian clinical sleep laboratories each scored separate sets of 10 PSGs twice, once using 3 EEG derivations and once using 1 EEG derivation. To examine the impact on inter- and intra-scorer reliability, all 3 scorers scored a subset of 10 PSGs 4 times, twice using each method. All PSGs were de-identified and scored in random order according to the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Using 3 referential EEG derivations during PSG, as recommended in the AASM manual, instead of a single central EEG derivation, as originally suggested by Rechtschaffen and Kales (1968), resulted in a mean ± SE decrease in N1 sleep of 9.6 ± 3.9 min (P = 0.018) and an increase in N3 sleep of 10.6 ± 2.8 min (P = 0.001). No significant differences were observed for any other sleep or arousal scoring summary statistics; nor were any differences observed in inter-scorer or intra-scorer reliability for scoring sleep or cortical arousals. This study provides information for those changing practice to comply with the 2007 AASM recommendations for EEG placement in PSG, for those using portable devices that are unable to comply with the recommendations due to limited channel options, and for the development of future standards for PSG scoring and recording. As the use of multiple EEG derivations only led to small changes in the distribution of derived sleep stages and no significant differences in scoring reliability, this study calls into question the need to use multiple EEG derivations in clinical PSG as suggested in the AASM manual.
Dai, Zhongxiang; de Souza, Joshua; Lim, Julian; Ho, Paul M.; Chen, Yu; Li, Junhua; Thakor, Nitish; Bezerianos, Anastasios; Sun, Yu
2017-01-01
Numerous studies have revealed various working memory (WM)-related brain activities that originate from various cortical regions and oscillate at different frequencies. However, multi-frequency band analysis of the brain network in WM in the cortical space remains largely unexplored. In this study, we employed a graph theoretical framework to characterize the topological properties of the brain functional network in the theta and alpha frequency bands during WM tasks. Twenty-eight subjects performed visual n-back tasks at two difficulty levels, i.e., 0-back (control task) and 2-back (WM task). After preprocessing, Electroencephalogram (EEG) signals were projected into the source space and 80 cortical brain regions were selected for further analysis. Subsequently, the theta- and alpha-band networks were constructed by calculating the Pearson correlation coefficients between the power series (obtained by concatenating the power values of all epochs in each session) of all pairs of brain regions. Graph theoretical approaches were then employed to estimate the topological properties of the brain networks at different WM tasks. We found higher functional integration in the theta band and lower functional segregation in the alpha band in the WM task compared with the control task. Moreover, compared to the 0-back task, altered regional centrality was revealed in the 2-back task in various brain regions that mainly resided in the frontal, temporal and occipital lobes, with distinct presentations in the theta and alpha bands. In addition, significant negative correlations were found between the reaction time with the average path length of the theta-band network and the local clustering of the alpha-band network, which demonstrates the potential for using the brain network metrics as biomarkers for predicting the task performance during WM tasks. PMID:28553215
Dai, Zhongxiang; de Souza, Joshua; Lim, Julian; Ho, Paul M; Chen, Yu; Li, Junhua; Thakor, Nitish; Bezerianos, Anastasios; Sun, Yu
2017-01-01
Numerous studies have revealed various working memory (WM)-related brain activities that originate from various cortical regions and oscillate at different frequencies. However, multi-frequency band analysis of the brain network in WM in the cortical space remains largely unexplored. In this study, we employed a graph theoretical framework to characterize the topological properties of the brain functional network in the theta and alpha frequency bands during WM tasks. Twenty-eight subjects performed visual n -back tasks at two difficulty levels, i.e., 0-back (control task) and 2-back (WM task). After preprocessing, Electroencephalogram (EEG) signals were projected into the source space and 80 cortical brain regions were selected for further analysis. Subsequently, the theta- and alpha-band networks were constructed by calculating the Pearson correlation coefficients between the power series (obtained by concatenating the power values of all epochs in each session) of all pairs of brain regions. Graph theoretical approaches were then employed to estimate the topological properties of the brain networks at different WM tasks. We found higher functional integration in the theta band and lower functional segregation in the alpha band in the WM task compared with the control task. Moreover, compared to the 0-back task, altered regional centrality was revealed in the 2-back task in various brain regions that mainly resided in the frontal, temporal and occipital lobes, with distinct presentations in the theta and alpha bands. In addition, significant negative correlations were found between the reaction time with the average path length of the theta-band network and the local clustering of the alpha-band network, which demonstrates the potential for using the brain network metrics as biomarkers for predicting the task performance during WM tasks.
Lustenberger, Caroline; Mouthon, Anne-Laure; Tesler, Noemi; Kurth, Salome; Ringli, Maya; Buchmann, Andreas; Jenni, Oskar G; Huber, Reto
2017-01-01
Reliable markers for brain maturation are important to identify neural deviations that eventually predict the development of mental illnesses. Recent studies have proposed topographical EEG-derived slow wave activity (SWA) during NREM sleep as a mirror of cortical development. However, studies about the longitudinal stability as well as the relationship with behavioral skills are needed before SWA topography may be considered such a reliable marker. We examined six subjects longitudinally (over 5.1 years) using high-density EEG and a visuomotor learning task. All subjects showed a steady increase of SWA at a frontal electrode and a decrease in central electrodes. Despite these large changes in EEG power, SWA topography was relatively stable within each subject during development indicating individual trait-like characteristics. Moreover, the SWA changes in the central cluster were related to the development of specific visuomotor skills. Taken together with the previous work in this domain, our results suggest that EEG sleep SWA represents a marker for motor skill development and further supports the idea that SWA mirrors cortical development during childhood and adolescence. © 2016 Wiley Periodicals, Inc.
Assessing the memorization of TV commercials with the use of high resolution EEG: a pilot study.
Astolfi, L; Soranzo, R; Cincotti, F; Mattia, D; Scarano, G; Gaudiano, I; Marciani, M G; Salinari, S; De Vico Fallani, F; Babiloni, F
2008-01-01
The present work intends to evaluate the functional characteristics of the cerebral network during the successful memory encoding of TV commercials. We estimated the functional networks in the frequency domain from a set of high-resolution EEG data. High resolution EEG recordings were performed in a group of healthy subjects and the cortical activity during the observation of TV commercials was evaluated in several regions of interest coincident with the Brodmann areas (BAs). Summarizing the main results of the present study, a sign of the memorization of a particular set of TV commercials have been found in a group of investigated subjects with the aid of advanced modern tools for the acquisition and the processing of EEG data. The cerebral processes involved during the observation of TV commercials that were remembered successively by the population examined (RMB dataset) are generated by the posterior parietal cortices and the prefrontal areas, rather bilaterally and are irrespective of the frequency bands analyzed. Such results are compatible with previously results obtained from EEG recordings with superficial electrodes as well as with the brain activations observed with the use of MEG and fMRI devices.
Colon, Elisabeth; Liberati, Giulia; Mouraux, André
2017-01-01
The recording of event-related brain potentials triggered by a transient heat stimulus is used extensively to study nociception and diagnose lesions or dysfunctions of the nociceptive system in humans. However, these responses are related exclusively to the activation of a specific subclass of nociceptive afferents: quickly-adapting thermonociceptors. In fact, except if the activation of Aδ fibers is avoided or if A fibers are blocked, these responses specifically reflect activity triggered by the activation of Type 2 quickly-adapting A fiber mechano-heat nociceptors (AMH-2). Here, we propose a novel method to isolate, in the human electroencephalogram (EEG), cortical activity related to the sustained periodic activation of heat-sensitive thermonociceptors, using very slow (0.2 Hz) and long-lasting (75 s) sinusoidal heat stimulation of the skin between baseline and 50°C. In a first experiment, we show that when such long-lasting thermal stimuli are applied to the hand dorsum of healthy volunteers, the slow rises and decreases of skin temperature elicit a consistent periodic EEG response at 0.2 Hz and its harmonics, as well as a periodic modulation of the magnitude of theta, alpha and beta band EEG oscillations. In a second experiment, we demonstrate using an A fiber block that these EEG responses are predominantly conveyed by unmyelinated C fiber nociceptors. The proposed approach constitutes a novel mean to study C fiber function in humans, and to explore the cortical processing of tonic heat pain in physiological and pathological conditions. PMID:27871921
Practical Designs of Brain-Computer Interfaces Based on the Modulation of EEG Rhythms
NASA Astrophysics Data System (ADS)
Wang, Yijun; Gao, Xiaorong; Hong, Bo; Gao, Shangkai
A brain-computer interface (BCI) is a communication channel which does not depend on the brain's normal output pathways of peripheral nerves and muscles [1-3]. It supplies paralyzed patients with a new approach to communicate with the environment. Among various brain monitoring methods employed in current BCI research, electroencephalogram (EEG) is the main interest due to its advantages of low cost, convenient operation and non-invasiveness. In present-day EEG-based BCIs, the following signals have been paid much attention: visual evoked potential (VEP), sensorimotor mu/beta rhythms, P300 evoked potential, slow cortical potential (SCP), and movement-related cortical potential (MRCP). Details about these signals can be found in chapter "Brain Signals for Brain-Computer Interfaces". These systems offer some practical solutions (e.g., cursor movement and word processing) for patients with motor disabilities.
Analysing coupling architecture in the cortical EEG of a patient with unilateral cerebral palsy
NASA Astrophysics Data System (ADS)
Kornilov, Maksim V.; Baas, C. Marjolein; van Rijn, Clementina M.; Sysoev, Ilya V.
2016-04-01
The detection of coupling presence and direction between cortical areas from the EEG is a popular approach in neuroscience. Granger causality method is promising for this task, since it allows to operate with short time series and to detect nonlinear coupling or coupling between nonlinear systems. In this study EEG multichannel data from adolescent children, suffering from unilateral cerebral palsy were investigated. Signals, obtained in rest and during motor activity of affected and less affected hand, were analysed. The changes in inter-hemispheric and intra-hemispheric interactions were studied over time with an interval of two months. The obtained results of coupling were tested for significance using surrogate times series. In the present proceeding paper we report the data of one patient. The modified nonlinear Granger causality is indeed able to reveal couplings within the human brain.
Besenyei, M; Varga, E; Fekete, I; Puskás, S; Hollódy, K; Fogarasi, A; Emri, M; Opposits, G; Kis, S A; Clemens, B
2012-01-01
Benign rolandic epilepsy of childhood (BERS) is an epilepsy syndrome with presumably genetic-developmental etiology. The pathological basis of this syndrome is completely unknown. We postulated that a developmental abnormality presumably results in abnormal EEG background activity findings. 20 children with typical BERS and an age- and sex-matched group of healthy control children underwent EEG recording and analysis. 60×2 s epochs of waking EEG background activity (without epileptiform potentials and artifacts) were analyzed in the 1-25 Hz frequency range, in very narrow bands (VNB, 1 Hz bandwidth). LORETA (Low Resolution Electromagnetic Tomography) localized multiple distributed sources of EEG background activity in the Talairach space. LORETA activity (current source density) was computed for 2394 voxels and 25 VNBs. Normalized LORETA data were processed to voxel-wise comparison between the BERS and control groups. Bonferroni-corrected p<0.05 Student's t-values were accepted as statistically significant. Increased LORETA activity was found in the BERS group (as compared to the controls) in the left and right temporal lobes (fusiform gyri, posterior parts of the superior, middle and inferior temporal gyri) and in the angular gyri in the parietal lobes, in the 4-6 Hz VNBs, mainly at 5 Hz. (1) Areas of abnormal LORETA activity exactly correspond to the temporal and parietal cortical areas that are major components of the Mirsky attention model and also the perisylvian speech network. Thus the LORETA findings may correspond to impaired attention and speech in BERS patients. (2) The LORETA findings may contribute to delineating the epileptic network in BERS. The novel findings may contribute to investigating neuropsychological disturbances and organization of the epileptic network in BERS. Copyright © 2011 Elsevier B.V. All rights reserved.
EEGLAB, SIFT, NFT, BCILAB, and ERICA: new tools for advanced EEG processing.
Delorme, Arnaud; Mullen, Tim; Kothe, Christian; Akalin Acar, Zeynep; Bigdely-Shamlo, Nima; Vankov, Andrey; Makeig, Scott
2011-01-01
We describe a set of complementary EEG data collection and processing tools recently developed at the Swartz Center for Computational Neuroscience (SCCN) that connect to and extend the EEGLAB software environment, a freely available and readily extensible processing environment running under Matlab. The new tools include (1) a new and flexible EEGLAB STUDY design facility for framing and performing statistical analyses on data from multiple subjects; (2) a neuroelectromagnetic forward head modeling toolbox (NFT) for building realistic electrical head models from available data; (3) a source information flow toolbox (SIFT) for modeling ongoing or event-related effective connectivity between cortical areas; (4) a BCILAB toolbox for building online brain-computer interface (BCI) models from available data, and (5) an experimental real-time interactive control and analysis (ERICA) environment for real-time production and coordination of interactive, multimodal experiments.
[EEG correlates of aggression and anxiety in a social interaction model].
Kniazev, G G; Bocharov, A V; Mitrofanova, L G; Slobodskoĭ-Pliusnin, Ia Iu; Pylkova, L V
2011-01-01
Aggressiveness- and anxiety-related behavioral and oscillatory patterns were investigated in 49 18-30 year old subjects during virtual social interactions. The subjects were presented with pictures of "angry", "happy", and "neutral" faces and had to choose one out of three options: "attack", "avoid", or "make friends". Sources of cortical EEG were localized with sLORETA software. Subjects with high aggressiveness chose attack more frequently and this behavior was accompanied by a stronger induced delta and theta synchronization in the right orbitofrontal cortex. In subjects with high anxiety, delta and theta responses were stronger induced in the right temporal cortex during their more frequent avoidance behavior. Thus, both in anxious and in aggressive subjects, typical behavior was accompanied by increased induced low-frequency synchronization whose localization implies that it is associated with motivational and emotional processes.
George, S Thomas; Balakrishnan, R; Johnson, J Stanly; Jayakumar, J
2017-07-01
EEG records the spontaneous electrical activity of the brain using multiple electrodes placed on the scalp, and it provides a wealth of information related to the functions of brain. Nevertheless, the signals from the electrodes cannot be directly applied to a diagnostic tool like brain mapping as they undergo a "mixing" process because of the volume conduction effect in the scalp. A pervasive problem in neuroscience is determining which regions of the brain are active, given voltage measurements at the scalp. Because of which, there has been a surge of interest among the biosignal processing community to investigate the process of mixing and unmixing to identify the underlying active sources. According to the assumptions of independent component analysis (ICA) algorithms, the resultant mixture obtained from the scalp can be closely approximated by a linear combination of the "actual" EEG signals emanating from the underlying sources of electrical activity in the brain. As a consequence, using these well-known ICA techniques in preprocessing of the EEG signals prior to clinical applications could result in development of diagnostic tool like quantitative EEG which in turn can assist the neurologists to gain noninvasive access to patient-specific cortical activity, which helps in treating neuropathologies like seizure disorders. The popular and proven ICA schemes mentioned in various literature and applications were selected (which includes Infomax, JADE, and SOBI) and applied on generalized seizure disorder samples using EEGLAB toolbox in MATLAB environment to see their usefulness in source separations; and they were validated by the expert neurologist for clinical relevance in terms of pathologies on brain functionalities. The performance of Infomax method was found to be superior when compared with other ICA schemes applied on EEG and it has been established based on the validations carried by expert neurologist for generalized seizure and its clinical correlation. The results are encouraging for furthering the studies in the direction of developing useful brain mapping tools using ICA methods.
Wavelet-based localization of oscillatory sources from magnetoencephalography data.
Lina, J M; Chowdhury, R; Lemay, E; Kobayashi, E; Grova, C
2014-08-01
Transient brain oscillatory activities recorded with Eelectroencephalography (EEG) or magnetoencephalography (MEG) are characteristic features in physiological and pathological processes. This study is aimed at describing, evaluating, and illustrating with clinical data a new method for localizing the sources of oscillatory cortical activity recorded by MEG. The method combines time-frequency representation and an entropic regularization technique in a common framework, assuming that brain activity is sparse in time and space. Spatial sparsity relies on the assumption that brain activity is organized among cortical parcels. Sparsity in time is achieved by transposing the inverse problem in the wavelet representation, for both data and sources. We propose an estimator of the wavelet coefficients of the sources based on the maximum entropy on the mean (MEM) principle. The full dynamics of the sources is obtained from the inverse wavelet transform, and principal component analysis of the reconstructed time courses is applied to extract oscillatory components. This methodology is evaluated using realistic simulations of single-trial signals, combining fast and sudden discharges (spike) along with bursts of oscillating activity. The method is finally illustrated with a clinical application using MEG data acquired on a patient with a right orbitofrontal epilepsy.
Synchronization of EEG activity in patients with bipolar disorder
NASA Astrophysics Data System (ADS)
Panischev, O. Yu; Demin, S. A.; Muhametshin, I. G.; Demina, N. Yu
2015-12-01
In paper we apply the method based on the Flicker-Noise Spectroscopy (FNS) to determine the differences in frequency-phase synchronization of the cortical electroencephalographic (EEG) activities in patients with bipolar disorder (BD). We found that for healthy subjects the frequency-phase synchronization of EEGs from long-range electrodes was significantly better for BD patients. In BD patients a high synchronization of EEGs was observed only for short-range electrodes. Thus, the FNS is a simple graphical method for qualitative analysis can be applied to identify the synchronization effects in EEG activity and, probably, may be used for the diagnosis of this syndrome.
ERP Modulation during Observation of Abstract Paintings by Franz Kline
Sbriscia-Fioretti, Beatrice; Berchio, Cristina; Freedberg, David; Gallese, Vittorio; Umiltà, Maria Alessandra
2013-01-01
The aim of this study was to test the involvement of sensorimotor cortical circuits during the beholding of the static consequences of hand gestures devoid of any meaning.In order to verify this hypothesis we performed an EEG experiment presenting to participants images of abstract works of art with marked traces of brushstrokes. The EEG data were analyzed by using Event Related Potentials (ERPs). We aimed to demonstrate a direct involvement of sensorimotor cortical circuits during the beholding of these selected works of abstract art. The stimuli consisted of three different abstract black and white paintings by Franz Kline. Results verified our experimental hypothesis showing the activation of premotor and motor cortical areas during stimuli observation. In addition, abstract works of art observation elicited the activation of reward-related orbitofrontal areas, and cognitive categorization-related prefrontal areas. The cortical sensorimotor activation is a fundamental neurophysiological demonstration of the direct involvement of the cortical motor system in perception of static meaningless images belonging to abstract art. These results support the role of embodied simulation of artist’s gestures in the perception of works of art. PMID:24130693
Reduced Cortical Activity Impairs Development and Plasticity after Neonatal Hypoxia Ischemia
Ranasinghe, Sumudu; Or, Grace; Wang, Eric Y.; Ievins, Aiva; McLean, Merritt A.; Niell, Cristopher M.; Chau, Vann; Wong, Peter K. H.; Glass, Hannah C.; Sullivan, Joseph
2015-01-01
Survivors of preterm birth are at high risk of pervasive cognitive and learning impairments, suggesting disrupted early brain development. The limits of viability for preterm birth encompass the third trimester of pregnancy, a “precritical period” of activity-dependent development characterized by the onset of spontaneous and evoked patterned electrical activity that drives neuronal maturation and formation of cortical circuits. Reduced background activity on electroencephalogram (EEG) is a sensitive marker of brain injury in human preterm infants that predicts poor neurodevelopmental outcome. We studied a rodent model of very early hypoxic–ischemic brain injury to investigate effects of injury on both general background and specific patterns of cortical activity measured with EEG. EEG background activity is depressed transiently after moderate hypoxia–ischemia with associated loss of spindle bursts. Depressed activity, in turn, is associated with delayed expression of glutamate receptor subunits and transporters. Cortical pyramidal neurons show reduced dendrite development and spine formation. Complementing previous observations in this model of impaired visual cortical plasticity, we find reduced somatosensory whisker barrel plasticity. Finally, EEG recordings from human premature newborns with brain injury demonstrate similar depressed background activity and loss of bursts in the spindle frequency band. Together, these findings suggest that abnormal development after early brain injury may result in part from disruption of specific forms of brain activity necessary for activity-dependent circuit development. SIGNIFICANCE STATEMENT Preterm birth and term birth asphyxia result in brain injury from inadequate oxygen delivery and constitute a major and growing worldwide health problem. Poor outcomes are noted in a majority of very premature (<25 weeks gestation) newborns, resulting in death or life-long morbidity with motor, sensory, learning, behavioral, and language disabilities that limit academic achievement and well-being. Limited progress has been made to develop therapies that improve neurologic outcomes. The overall objective of this study is to understand the effect of early brain injury on activity-dependent brain development and cortical plasticity to develop new treatments that will optimize repair and recovery after brain injury. PMID:26311776
Ji, Hong; Petro, Nathan M; Chen, Badong; Yuan, Zejian; Wang, Jianji; Zheng, Nanning; Keil, Andreas
2018-02-06
Over the past decade, the simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) data has garnered growing interest because it may provide an avenue towards combining the strengths of both imaging modalities. Given their pronounced differences in temporal and spatial statistics, the combination of EEG and fMRI data is however methodologically challenging. Here, we propose a novel screening approach that relies on a Cross Multivariate Correlation Coefficient (xMCC) framework. This approach accomplishes three tasks: (1) It provides a measure for testing multivariate correlation and multivariate uncorrelation of the two modalities; (2) it provides criterion for the selection of EEG features; (3) it performs a screening of relevant EEG information by grouping the EEG channels into clusters to improve efficiency and to reduce computational load when searching for the best predictors of the BOLD signal. The present report applies this approach to a data set with concurrent recordings of steady-state-visual evoked potentials (ssVEPs) and fMRI, recorded while observers viewed phase-reversing Gabor patches. We test the hypothesis that fluctuations in visuo-cortical mass potentials systematically covary with BOLD fluctuations not only in visual cortical, but also in anterior temporal and prefrontal areas. Results supported the hypothesis and showed that the xMCC-based analysis provides straightforward identification of neurophysiological plausible brain regions with EEG-fMRI covariance. Furthermore xMCC converged with other extant methods for EEG-fMRI analysis. © 2018 The Authors Journal of Neuroscience Research Published by Wiley Periodicals, Inc.
Krivonogova, E V; Poskotinova, L V; Demin, D B
2015-01-01
A single session of heart rate variability (HRV) biofeedback in apparently healthy young people and adolescents aged 14-17 years in order to increase vagal effects on heart rhythm and also electroencephalograms were carried out. Different variants of EEG spectral power during the successful HRV biofeedback session were identified. In the case of I variant of EEG activity the increase of power spectrum of alpha-, betal-, theta-components takes place in all parts of the brain. In the case of II variant of EEG activity the reduction of power spectrum of alpha-, betal-, theta-activity in all parts of the brain was observed. I and II variants of EEG activity cause more intensive regime of cortical-subcortical interactions. During the III variant of EEG activity the successful biofeedback is accompanied by increase of alpha activity in the central, front and anteriofrontal brain parts and so indicates the formation of thalamocortical relations of neural network in order to optimize the vegetal regulation of heart function. There was an increase in alpha- and beta1-activity in the parietal, central, frontal and temporal brain parts during the IV variant of EEG activity and so that it provides the relief of neural networks communication for information processing. As a result of V variance of EEG activity there was the increase of power spectrum of theta activity in the central and frontal parts of both cerebral hemispheres, so it was associated with the cortical-hippocampal interactions to achieve a successful biofeedback.
Kuk, Eun-Ju; Kim, Jong-Man; Oh, Duck-Won; Hwang, Han-Jeong
2016-10-01
Previous reports have suggested that action observation training (AOT) is beneficial in enhancing the early learning of new motor tasks; however, EEG-based investigation has received little attention for AOT. The purpose of this study was to illustrate the effects of AOT on hand dexterity and cortical activation in patients with post-stroke hemiparesis. Twenty patients with post-stroke hemiparesis were randomly divided into either the experimental group (EG) or control group (CG), with 10 patients in each group. Prior to the execution of motor tasks (carrying wooden blocks from one box to another), subjects in the EG and CG observed a video clip displaying the execution of the same motor task and pictures showing landscapes, respectively. Outcome measures included the box and block test (BBT) to evaluate hand dexterity and EEG-based brain mapping to detect changes in cortical activation. The BBT scores (EG: 20.50 ± 6.62 at pre-test and 24.40 ± 5.42 at post-test; CG: 20.20 ± 6.12 at pre-test and 20.60 ± 7.17 at post-test) revealed significant main effects for the time and group and significant time-by-group interactions (p < 0.05). For the subjects in the EG, topographical representations obtained with the EEG-based brain mapping system were different in each session of the AOT and remarkable changes occurred from the 2nd session of AOT. Furthermore, the middle frontal gyrus was less active at post-test than at pre-test. These findings support that AOT may be beneficial in altering cortical activation patterns and hand dexterity.
Ferreri, F; Ponzo, D; Vollero, L; Guerra, A; Di Pino, G; Petrichella, S; Benvenuto, A; Tombini, M; Rossini, L; Denaro, L; Micera, S; Iannello, G; Guglielmelli, E; Denaro, V; Rossini, P M
2014-01-01
Following limb amputation, central and peripheral nervous system relays partially maintain their functions and can be exploited for interfacing prostheses. The aim of this study is to investigate, for the first time by means of an EEG-TMS co-registration study, whether and how direct bidirectional connection between brain and hand prosthesis impacts on sensorimotor cortical topography. Within an experimental protocol for robotic hand control, a 26 years-old, left-hand amputated male was selected to have implanted four intrafascicular electrodes (tf-LIFEs-4) in the median and ulnar nerves of the stump for 4 weeks. Before tf-LIFE-4s implant (T0) and after the training period, once electrodes have been removed (T1), experimental subject's cortico-cortical excitability, connectivity and plasticity were tested via a neuronavigated EEG-TMS experiment. The statistical analysis clearly demonstrated a significant modulation (with t-test p < 0.0001) of EEG activity between 30 and 100 ms post-stimulus for the stimulation of the right hemisphere. When studying individual latencies in that time range, a global amplitude modulation was found in most of the TMS-evoked potentials; particularly, the GEE analysis showed significant differences between T0 and T1 condition at 30 ms (p < 0.0404), 46 ms (p < 0.0001) and 60 ms (p < 0.007) latencies. Finally, also a clear local decrement in N46 amplitude over C4 was evident. No differences between conditions were observed for the stimulation of the left hemisphere. The results of this study confirm the hypothesis that bidirectional neural interface could redirect cortical areas -deprived of their original input/output functions- toward restorative neuroplasticity. This reorganization strongly involves bi-hemispheric networks and intracortical and transcortical modulation of GABAergic inhibition.
Roy, Abhrajeet; Baxter, Bryan
2014-01-01
The goal of this study was to develop methods for simultaneously acquiring electrophysiological data during high definition transcranial direct current stimulation (tDCS) using high resolution electroencephalography (EEG). Previous studies have pointed to the after effects of tDCS on both motor and cognitive performance, and there appears to be potential for using tDCS in a variety of clinical applications. However, little is known about the real-time effects of tDCS on rhythmic cortical activity in humans due to the technical challenges of simultaneously obtaining electrophysiological data during ongoing stimulation. Furthermore, the mechanisms of action of tDCS in humans are not well understood. We have conducted a simultaneous tDCS-EEG study in a group of healthy human subjects. Significant acute and persistent changes in spontaneous neural activity and event related synchronization (ERS) were observed during and after the application of high definition tDCS over the left sensorimotor cortex. Both anodal and cathodal stimulation resulted in acute global changes in broadband cortical activity which were significantly different than the changes observed in response to sham stimulation. For the group of 8 subjects studied, broadband individual changes in spontaneous activity during stimulation were apparent both locally and globally. In addition, we found that high definition tDCS of the left sensorimotor cortex can induce significant ipsilateral and contralateral changes in event related desynchronization (ERD) and ERS during motor imagination following the end of the stimulation period. Overall, our results demonstrate the feasibility of acquiring high resolution EEG during high definition tDCS and provide evidence that tDCS in humans directly modulates rhythmic cortical synchronization during and after its administration. PMID:24956615
Source-reconstruction of the sensorimotor network from resting-state macaque electrocorticography.
Hindriks, R; Micheli, C; Bosman, C A; Oostenveld, R; Lewis, C; Mantini, D; Fries, P; Deco, G
2018-06-07
The discovery of hemodynamic (BOLD-fMRI) resting-state networks (RSNs) has brought about a fundamental shift in our thinking about the role of intrinsic brain activity. The electrophysiological underpinnings of RSNs remain largely elusive and it has been shown only recently that electric cortical rhythms are organized into the same RSNs as hemodynamic signals. Most electrophysiological studies into RSNs use magnetoencephalography (MEG) or scalp electroencephalography (EEG), which limits the spatial resolution with which electrophysiological RSNs can be observed. Due to their close proximity to the cortical surface, electrocorticographic (ECoG) recordings can potentially provide a more detailed picture of the functional organization of resting-state cortical rhythms, albeit at the expense of spatial coverage. In this study we propose using source-space spatial independent component analysis (spatial ICA) for identifying generators of resting-state cortical rhythms as recorded with ECoG and for reconstructing their functional connectivity. Network structure is assessed by two kinds of connectivity measures: instantaneous correlations between band-limited amplitude envelopes and oscillatory phase-locking. By simulating rhythmic cortical generators, we find that the reconstruction of oscillatory phase-locking is more challenging than that of amplitude correlations, particularly for low signal-to-noise levels. Specifically, phase-lags can both be over- and underestimated, which troubles the interpretation of lag-based connectivity measures. We illustrate the methodology on somatosensory beta rhythms recorded from a macaque monkey using ECoG. The methodology decomposes the resting-state sensorimotor network into three cortical generators, distributed across primary somatosensory and primary and higher-order motor areas. The generators display significant and reproducible amplitude correlations and phase-locking values with non-zero lags. Our findings illustrate the level of spatial detail attainable with source-projected ECoG and motivates wider use of the methodology for studying resting-state as well as event-related cortical dynamics in macaque and human. Copyright © 2018. Published by Elsevier Inc.
Pietersen, Alexander N.J.; Cheong, Soon Keen; Munn, Brandon; Gong, Pulin; Solomon, Samuel G.
2017-01-01
Key points How parallel are the primate visual pathways? In the present study, we demonstrate that parallel visual pathways in the dorsal lateral geniculate nucleus (LGN) show distinct patterns of interaction with rhythmic activity in the primary visual cortex (V1).In the V1 of anaesthetized marmosets, the EEG frequency spectrum undergoes transient changes that are characterized by fluctuations in delta‐band EEG power.We show that, on multisecond timescales, spiking activity in an evolutionary primitive (koniocellular) LGN pathway is specifically linked to these slow EEG spectrum changes. By contrast, on subsecond (delta frequency) timescales, cortical oscillations can entrain spiking activity throughout the entire LGN.Our results are consistent with the hypothesis that, in waking animals, the koniocellular pathway selectively participates in brain circuits controlling vigilance and attention. Abstract The major afferent cortical pathway in the visual system passes through the dorsal lateral geniculate nucleus (LGN), where nerve signals originating in the eye can first interact with brain circuits regulating visual processing, vigilance and attention. In the present study, we investigated how ongoing and visually driven activity in magnocellular (M), parvocellular (P) and koniocellular (K) layers of the LGN are related to cortical state. We recorded extracellular spiking activity in the LGN simultaneously with local field potentials (LFP) in primary visual cortex, in sufentanil‐anaesthetized marmoset monkeys. We found that asynchronous cortical states (marked by low power in delta‐band LFPs) are linked to high spike rates in K cells (but not P cells or M cells), on multisecond timescales. Cortical asynchrony precedes the increases in K cell spike rates by 1–3 s, implying causality. At subsecond timescales, the spiking activity in many cells of all (M, P and K) classes is phase‐locked to delta waves in the cortical LFP, and more cells are phase‐locked during synchronous cortical states than during asynchronous cortical states. The switch from low‐to‐high spike rates in K cells does not degrade their visual signalling capacity. By contrast, during asynchronous cortical states, the fidelity of visual signals transmitted by K cells is improved, probably because K cell responses become less rectified. Overall, the data show that slow fluctuations in cortical state are selectively linked to K pathway spiking activity, whereas delta‐frequency cortical oscillations entrain spiking activity throughout the entire LGN, in anaesthetized marmosets. PMID:28116750
Spatiotemporal mapping of interictal epileptiform discharges in human absence epilepsy: A MEG study.
Rozendaal, Yvonne J W; van Luijtelaar, Gilles; Ossenblok, Pauly P W
2016-01-01
Although absence epilepsy is considered to be a prototypic type of generalized epilepsy, it is still under debate whether generalized 3 Hz spike-and-wave discharges (SWDs) might have a cortical focal origin. Here it is investigated whether focal interictal epileptiform discharges (IEDs), which typically occur in the electro- (EEG) and magnetoencephalogram (MEG) in case of focal epilepsy, are present in the MEG of children with absence epilepsy. Next, the location of the sources of the IEDs is established, and it is investigated whether the location is concordant to the earlier established focal cortical regions involved in the generalized SWDs of these children. Whole head MEG recordings of seven children with absence epilepsy were reviewed with respect to the presence of IEDs (spikes and sharp waves). These IEDs were grouped into distinct clusters, in which each contribution to a cluster yields a comparable magnetic field distribution. Source localization was then performed onto the average signal of each cluster using an equivalent current dipole model and a realistic head model of the cortical surface. IEDs were detected in 6 out of 7 patients. Source reconstruction indicated most often frontal, central or parietal origins of the IED in either the left and or right hemisphere. Spatiotemporal assessment of the IEDs indicated a stable location of the averages of these discharges, indicating a single underlying cortical source. The outcome of this pilot study shows that MEG is well suited for the detection of IEDs and suggests that their estimated sources coincide rather well with the cortical regions involved during the spikes of the SWDs. It is discussed whether the presence of IEDs, classically seen as a marker of focal epilepsies, indicate that absence epilepsy should be considered as a focal type of epilepsy, in which changes in the network are evolving rapidly. Copyright © 2015 Elsevier B.V. All rights reserved.
Lehmann, Dietrich; Faber, Pascal L; Gianotti, Lorena R R; Kochi, Kieko; Pascual-Marqui, Roberto D
2006-01-01
Brain electric mechanisms of temporary, functional binding between brain regions are studied using computation of scalp EEG coherence and phase locking, sensitive to time differences of few milliseconds. However, such results if computed from scalp data are ambiguous since electric sources are spatially oriented. Non-ambiguous results can be obtained using calculated time series of strength of intracerebral model sources. This is illustrated applying LORETA modeling to EEG during resting and meditation. During meditation, time series of LORETA model sources revealed a tendency to decreased left-right intracerebral coherence in the delta band, and to increased anterior-posterior intracerebral coherence in the theta band. An alternate conceptualization of functional binding is based on the observation that brain electric activity is discontinuous, i.e., that it occurs in chunks of up to about 100 ms duration that are detectable as quasi-stable scalp field configurations of brain electric activity, called microstates. Their functional significance is illustrated in spontaneous and event-related paradigms, where microstates associated with imagery- versus abstract-type mentation, or while reading positive versus negative emotion words showed clearly different regions of cortical activation in LORETA tomography. These data support the concept that complete brain functions of higher order such as a momentary thought might be incorporated in temporal chunks of processing in the range of tens to about 100 ms as quasi-stable brain states; during these time windows, subprocesses would be accepted as members of the ongoing chunk of processing.
Sherman, David; Zhang, Ning; Garg, Shikha; Thakor, Nitish V; Mirski, Marek A; White, Mirinda Anderson; Hinich, Melvin J
2011-04-01
EEG and field potential rhythms established in the cortex and thalamus may accommodate the propagation of seizures. This article describes the interaction between thalamus and cortex during pentylenetetrazol (PTZ) seizures in rats with and without prior treatment with ethosuximide (ESM), a well-known antiepileptic drug (AED) that raises the threshold for seizures, was given before PTZ. The AED was given before PTZ convulsant administration. We track this thalamo-cortical association with a novel measure we have called the cross-bicoherence gain, or BISCOH. This quantity allows us to measure the spectral coherence in a purely higher order spectralmethodology. BISCOH is able to track the formation of nonlinearities at specific frequencies in the recorded EEG. BISCOH showed a strong increase in low alpha wave harmonic generationat 10 and 12.5 Hz after ESM treatment (p < 0.02 and p < 0.007, respectively). Conventional coherence failed to show distinctive and significant changes in thalamo-cortical coupling after ESM treatment at those frequencies and instead showed changes at 5 Hz. This rise in cortical rhythms is evidence of harmonic generation or new frequency formation in the thalamo-cortical system withAED therapy. BISCOH could become a powerful tool in unraveling changes in coherence due to neuroelectric modulation resulting from drug treatment or electrical stimulation.
Jochumsen, Mads; Rovsing, Cecilie; Rovsing, Helene; Niazi, Imran Khan; Dremstrup, Kim; Kamavuako, Ernest Nlandu
2017-01-01
Detection of single-trial movement intentions from EEG is paramount for brain-computer interfacing in neurorehabilitation. These movement intentions contain task-related information and if this is decoded, the neurorehabilitation could potentially be optimized. The aim of this study was to classify single-trial movement intentions associated with two levels of force and speed and three different grasp types using EEG rhythms and components of the movement-related cortical potential (MRCP) as features. The feature importance was used to estimate encoding of discriminative information. Two data sets were used. 29 healthy subjects executed and imagined different hand movements, while EEG was recorded over the contralateral sensorimotor cortex. The following features were extracted: delta, theta, mu/alpha, beta, and gamma rhythms, readiness potential, negative slope, and motor potential of the MRCP. Sequential forward selection was performed, and classification was performed using linear discriminant analysis and support vector machines. Limited classification accuracies were obtained from the EEG rhythms and MRCP-components: 0.48 ± 0.05 (grasp types), 0.41 ± 0.07 (kinetic profiles, motor execution), and 0.39 ± 0.08 (kinetic profiles, motor imagination). Delta activity contributed the most but all features provided discriminative information. These findings suggest that information from the entire EEG spectrum is needed to discriminate between task-related parameters from single-trial movement intentions.
Thornton, Rachel; Vulliemoz, Serge; Rodionov, Roman; Carmichael, David W; Chaudhary, Umair J; Diehl, Beate; Laufs, Helmut; Vollmar, Christian; McEvoy, Andrew W; Walker, Matthew C; Bartolomei, Fabrice; Guye, Maxime; Chauvel, Patrick; Duncan, John S; Lemieux, Louis
2011-01-01
Objective Surgical treatment of focal epilepsy in patients with focal cortical dysplasia (FCD) is most successful if all epileptogenic tissue is resected. This may not be evident on structural magnetic resonance imaging (MRI), so intracranial electroencephalography (icEEG) is needed to delineate the seizure onset zone (SOZ). EEG-functional MRI (fMRI) can reveal interictal discharge (IED)-related hemodynamic changes in the irritative zone (IZ). We assessed the value of EEG-fMRI in patients with FCD-associated focal epilepsy by examining the relationship between IED-related hemodynamic changes, icEEG findings, and postoperative outcome. Methods Twenty-three patients with FCD-associated focal epilepsy undergoing presurgical evaluation including icEEG underwent simultaneous EEG-fMRI at 3T. IED-related hemodynamic changes were modeled, and results were overlaid on coregistered T1-weighted MRI scans fused with computed tomography scans showing the intracranial electrodes. IED-related hemodynamic changes were compared with the SOZ on icEEG and postoperative outcome at 1 year. Results Twelve of 23 patients had IEDs during recording, and 11 of 12 had significant IED-related hemodynamic changes. The fMRI results were concordant with the SOZ in 5 of 11 patients, all of whom had a solitary SOZ on icEEG. Four of 5 had >50% reduction in seizure frequency following resective surgery. The remaining 6 of 11 patients had widespread or discordant regions of IED-related fMRI signal change. Five of 6 had either a poor surgical outcome (<50% reduction in seizure frequency) or widespread SOZ precluding surgery. Interpretation Comparison of EEG-fMRI with icEEG suggests that EEG-fMRI may provide useful additional information about the SOZ in FCD. Widely distributed discordant regions of IED-related hemodynamic change appear to be associated with a widespread SOZ and poor postsurgical outcome. ANN NEUROL 2011 PMID:22162063
Zhavoronkova, L A; Kholodova, N B; Zubovskiĭ, G A; Smirnov, Iu N; Koptelov, Iu M; Ryzhov, N I
1994-01-01
EEG mapping and three-dimensional localization of epileptic activity sources together with a neurological analysis were carried out in subjects having taken part in 1986-1987 in the liquidation of consequences of the Chernobyl accident. Experimental group included 40 right-handed 25-45 years-old men having received a radiation dose of 15-51 Ber stated officially. Control group consisted of 20 healthy men. Neurological examination of the patients revealed vegetative-vascular and endocrine dysfunctions as well as diffuse neurological symptoms. EEG of one group of patients (25 persons) was characterized by slow alpha- and theta-band foci and epileptic waves in the central-frontal regions; epileptic sources were localized at the diencephalic level mainly in the midline being shifted to the right hemisphere. In the EEG of another group (15 persons) delta-waves were recorded in the frontal regions at the background of diffuse beta-activity. The sources of epileptic activity of a diffuse character were localized at the basal level of the brain and in the cortex (predominantly) in the left hemisphere. The results obtained together with SPECT mapping and CT data permit to suppose the organic damage of different brain structures (at the cortical and the midline levels) in the patients, with participation of diencephalic structures in the pathological process hypothalamic-hypophysial system being probably connected with adaptive processes in the CNS.
Math anxiety: Brain cortical network changes in anticipation of doing mathematics.
Klados, Manousos A; Pandria, Niki; Micheloyannis, Sifis; Margulies, Daniel; Bamidis, Panagiotis D
2017-12-01
Following our previous work regarding the involvement of math anxiety (MA) in math-oriented tasks, this study tries to explore the differences in the cerebral networks' topology between self-reported low math-anxious (LMA) and high math-anxious (HMA) individuals, during the anticipation phase prior to a mathematical related experiment. For this reason, multichannel EEG recordings were adopted, while the solution of the inverse problem was applied in a generic head model, in order to obtain the cortical signals. The cortical networks have been computed for each band separately, using the magnitude square coherence metric. The main graph theoretical parameters, showed differences in segregation and integration in almost all EEG bands of the HMAs in comparison to LMAs, indicative of a great influence of the anticipatory anxiety prior to mathematical performance. Copyright © 2017 Elsevier B.V. All rights reserved.
Safety and EEG data quality of concurrent high-density EEG and high-speed fMRI at 3 Tesla.
Foged, Mette Thrane; Lindberg, Ulrich; Vakamudi, Kishore; Larsson, Henrik B W; Pinborg, Lars H; Kjær, Troels W; Fabricius, Martin; Svarer, Claus; Ozenne, Brice; Thomsen, Carsten; Beniczky, Sándor; Paulson, Olaf B; Posse, Stefan
2017-01-01
Concurrent EEG and fMRI is increasingly used to characterize the spatial-temporal dynamics of brain activity. However, most studies to date have been limited to conventional echo-planar imaging (EPI). There is considerable interest in integrating recently developed high-speed fMRI methods with high-density EEG to increase temporal resolution and sensitivity for task-based and resting state fMRI, and for detecting interictal spikes in epilepsy. In the present study using concurrent high-density EEG and recently developed high-speed fMRI methods, we investigate safety of radiofrequency (RF) related heating, the effect of EEG on cortical signal-to-noise ratio (SNR) in fMRI, and assess EEG data quality. The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors that were equipped with 64- and 256-channel MR-compatible EEG systems, respectively, and receive only array head coils. Data were collected in 11 healthy controls (3 males, age range 18-70 years) and 13 patients with epilepsy (8 males, age range 21-67 years). Three of the healthy controls were scanned with the 256-channel EEG system, the other subjects were scanned with the 64-channel EEG system. Scalp surface temperature, SNR in occipital cortex and head movement were measured with and without the EEG cap. The degree of artifacts and the ability to identify background activity was assessed by visual analysis by a trained expert in the 64 channel EEG data (7 healthy controls, 13 patients). RF induced heating at the surface of the EEG electrodes during a 30-minute scan period with stable temperature prior to scanning did not exceed 1.0° C with either EEG system and any of the pulse sequences used in this study. There was no significant decrease in cortical SNR due to the presence of the EEG cap (p > 0.05). No significant differences in the visually analyzed EEG data quality were found between EEG recorded during high-speed fMRI and during conventional EPI (p = 0.78). Residual ballistocardiographic artifacts resulted in 58% of EEG data being rated as poor quality. This study demonstrates that high-density EEG can be safely implemented in conjunction with high-speed fMRI and that high-speed fMRI does not adversely affect EEG data quality. However, the deterioration of the EEG quality due to residual ballistocardiographic artifacts remains a significant constraint for routine clinical applications of concurrent EEG-fMRI.
Decrease of Prefrontal-Posterior EEG Coherence: Loose Control during Social-Emotional Stimulation
ERIC Educational Resources Information Center
Reiser, Eva M.; Schulter, Gunter; Weiss, Elisabeth M.; Fink, Andreas; Rominger, Christian; Papousek, Ilona
2012-01-01
In two experiments we aimed to investigate if individual differences in state-dependent decreases or increases of EEG coherence between prefrontal and posterior cortical regions may be indicative of a mechanism modulating the impact social-emotional information has on an individual. Two independent samples were exposed to an emotional stimulation…
Sleep EEG Changes during Adolescence: An Index of a Fundamental Brain Reorganization
ERIC Educational Resources Information Center
Feinberg, Irwin; Campbell, Ian G.
2010-01-01
Delta (1-4 Hz) EEG power in non-rapid eye movement (NREM) sleep declines massively during adolescence. This observation stimulated the hypothesis that during adolescence the human brain undergoes an extensive reorganization driven by synaptic elimination. The parallel declines in synaptic density, delta wave amplitude and cortical metabolic rate…
Tagging cortical networks in emotion: a topographical analysis
Keil, Andreas; Costa, Vincent; Smith, J. Carson; Sabatinelli, Dean; McGinnis, E. Menton; Bradley, Margaret M.; Lang, Peter J.
2013-01-01
Viewing emotional pictures is associated with heightened perception and attention, indexed by a relative increase in visual cortical activity. Visual cortical modulation by emotion is hypothesized to reflect re-entrant connectivity originating in higher-order cortical and/or limbic structures. The present study used dense-array electroencephalography and individual brain anatomy to investigate functional coupling between the visual cortex and other cortical areas during affective picture viewing. Participants viewed pleasant, neutral, and unpleasant pictures that flickered at a rate of 10 Hz to evoke steady-state visual evoked potentials (ssVEPs) in the EEG. The spectral power of ssVEPs was quantified using Fourier transform, and cortical sources were estimated using beamformer spatial filters based on individual structural magnetic resonance images. In addition to lower-tier visual cortex, a network of occipito-temporal and parietal (bilateral precuneus, inferior parietal lobules) structures showed enhanced ssVEP power when participants viewed emotional (either pleasant or unpleasant), compared to neutral pictures. Functional coupling during emotional processing was enhanced between the bilateral occipital poles and a network of temporal (left middle/inferior temporal gyrus), parietal (bilateral parietal lobules), and frontal (left middle/inferior frontal gyrus) structures. These results converge with findings from hemodynamic analyses of emotional picture viewing and suggest that viewing emotionally engaging stimuli is associated with the formation of functional links between visual cortex and the cortical regions underlying attention modulation and preparation for action. PMID:21954087
Dynamics of corticospinal motor control during overground and treadmill walking in humans.
Roeder, Luisa; Boonstra, Tjeerd Willem; Smith, Simon S; Kerr, Graham K
2018-05-30
Increasing evidence suggests cortical involvement in the control of human gait. However, the nature of corticospinal interactions remains poorly understood. We performed time-frequency analysis of electrophysiological activity acquired during treadmill and overground walking in 22 healthy, young adults. Participants walked at their preferred speed (4.2, SD 0.4 km h -1 ), which was matched across both gait conditions. Event-related power, corticomuscular coherence (CMC) and inter-trial coherence (ITC) were assessed for EEG from bilateral sensorimotor cortices and EMG from the bilateral tibialis anterior (TA) muscles. Cortical power, CMC and ITC at theta, alpha, beta and gamma frequencies (4-45 Hz) increased during the double support phase of the gait cycle for both overground and treadmill walking. High beta (21-30 Hz) CMC and ITC of EMG was significantly increased during overground compared to treadmill walking, as well as EEG power in theta band (4-7 Hz). The phase spectra revealed positive time lags at alpha, beta and gamma frequencies, indicating that the EEG response preceded the EMG response. The parallel increases in power, CMC and ITC during double support suggest evoked responses at spinal and cortical populations rather than a modulation of ongoing corticospinal oscillatory interactions. The evoked responses are not consistent with the idea of synchronization of ongoing corticospinal oscillations, but instead suggest coordinated cortical and spinal inputs during the double support phase. Frequency-band dependent differences in power, CMC and ITC between overground and treadmill walking suggest differing neural control for the two gait modalities, emphasizing the task-dependent nature of neural processes during human walking.
Ortigue, Stephanie; Sinigaglia, Corrado; Rizzolatti, Giacomo; Grafton, Scott T.
2010-01-01
Background When we observe an individual performing a motor act (e.g. grasping a cup) we get two types of information on the basis of how the motor act is done and the context: what the agent is doing (i.e. grasping) and the intention underlying it (i.e. grasping for drinking). Here we examined the temporal dynamics of the brain activations that follow the observation of a motor act and underlie the observer's capacity to understand what the agent is doing and why. Methodology/Principal Findings Volunteers were presented with two-frame video-clips. The first frame (T0) showed an object with or without context; the second frame (T1) showed a hand interacting with the object. The volunteers were instructed to understand the intention of the observed actions while their brain activity was recorded with a high-density 128-channel EEG system. Visual event-related potentials (VEPs) were recorded time-locked with the frame showing the hand-object interaction (T1). The data were analyzed by using electrical neuroimaging, which combines a cluster analysis performed on the group-averaged VEPs with the localization of the cortical sources that give rise to different spatio-temporal states of the global electrical field. Electrical neuroimaging results revealed four major steps: 1) bilateral posterior cortical activations; 2) a strong activation of the left posterior temporal and inferior parietal cortices with almost a complete disappearance of activations in the right hemisphere; 3) a significant increase of the activations of the right temporo-parietal region with simultaneously co-active left hemispheric sources, and 4) a significant global decrease of cortical activity accompanied by the appearance of activation of the orbito-frontal cortex. Conclusions/Significance We conclude that the early striking left hemisphere involvement is due to the activation of a lateralized action-observation/action execution network. The activation of this lateralized network mediates the understanding of the goal of object-directed motor acts (mirror mechanism). The successive right hemisphere activation indicates that this hemisphere plays an important role in understanding the intention of others. PMID:20730095
Lifespan Differences in Cortical Dynamics of Auditory Perception
ERIC Educational Resources Information Center
Muller, Viktor; Gruber, Walter; Klimesch, Wolfgang; Lindenberger, Ulman
2009-01-01
Using electroencephalographic recordings (EEG), we assessed differences in oscillatory cortical activity during auditory-oddball performance between children aged 9-13 years, younger adults, and older adults. From childhood to old age, phase synchronization increased within and between electrodes, whereas whole power and evoked power decreased. We…
Neuroanatomical and resting state EEG power correlates of central hearing loss in older adults.
Giroud, Nathalie; Hirsiger, Sarah; Muri, Raphaela; Kegel, Andrea; Dillier, Norbert; Meyer, Martin
2018-01-01
To gain more insight into central hearing loss, we investigated the relationship between cortical thickness and surface area, speech-relevant resting state EEG power, and above-threshold auditory measures in older adults and younger controls. Twenty-three older adults and 13 younger controls were tested with an adaptive auditory test battery to measure not only traditional pure-tone thresholds, but also above individual thresholds of temporal and spectral processing. The participants' speech recognition in noise (SiN) was evaluated, and a T1-weighted MRI image obtained for each participant. We then determined the cortical thickness (CT) and mean cortical surface area (CSA) of auditory and higher speech-relevant regions of interest (ROIs) with FreeSurfer. Further, we obtained resting state EEG from all participants as well as data on the intrinsic theta and gamma power lateralization, the latter in accordance with predictions of the Asymmetric Sampling in Time hypothesis regarding speech processing (Poeppel, Speech Commun 41:245-255, 2003). Methodological steps involved the calculation of age-related differences in behavior, anatomy and EEG power lateralization, followed by multiple regressions with anatomical ROIs as predictors for auditory performance. We then determined anatomical regressors for theta and gamma lateralization, and further constructed all regressions to investigate age as a moderator variable. Behavioral results indicated that older adults performed worse in temporal and spectral auditory tasks, and in SiN, despite having normal peripheral hearing as signaled by the audiogram. These behavioral age-related distinctions were accompanied by lower CT in all ROIs, while CSA was not different between the two age groups. Age modulated the regressions specifically in right auditory areas, where a thicker cortex was associated with better auditory performance in older adults. Moreover, a thicker right supratemporal sulcus predicted more rightward theta lateralization, indicating the functional relevance of the right auditory areas in older adults. The question how age-related cortical thinning and intrinsic EEG architecture relates to central hearing loss has so far not been addressed. Here, we provide the first neuroanatomical and neurofunctional evidence that cortical thinning and lateralization of speech-relevant frequency band power relates to the extent of age-related central hearing loss in older adults. The results are discussed within the current frameworks of speech processing and aging.
EEG during pedaling: Evidence for cortical control of locomotor tasks
Jain, Sanket; Gourab, Krishnaj; Schindler-Ivens, Sheila; Schmit, Brian D.
2014-01-01
Objective This study characterized the brain electrical activity during pedaling, a locomotor-like task, in humans. We postulated that phasic brain activity would be associated with active pedaling, consistent with a cortical role in locomotor tasks. Methods Sixty four channels of electroencephalogram (EEG) and 10 channels of electromyogram (EMG) data were recorded from 10 neurologically-intact volunteers while they performed active and passive (no effort) pedaling on a custom-designed stationary bicycle. Ensemble averaged waveforms, 2 dimensional topographic maps and amplitude of the β (13–35 Hz) frequency band were analyzed and compared between active and passive trials. Results The peak-to-peak amplitude (peak positive–peak negative) of the EEG waveform recorded at the Cz electrode was higher in the passive than the active trials (p < 0.01). β-band oscillations in electrodes overlying the leg representation area of the cortex were significantly desynchronized during active compared to the passive pedaling (p < 0.01). A significant negative correlation was observed between the average EEG waveform for active trials and the composite EMG (summated EMG from both limbs for each muscle) of the rectus femoris (r = −0.77, p < 0.01) the medial hamstrings (r = −0.85, p < 0.01) and the tibialis anterior (r = −0.70, p < 0.01) muscles. Conclusions These results demonstrated that substantial sensorimotor processing occurs in the brain during pedaling in humans. Further, cortical activity seemed to be greatest during recruitment of the muscles critical for transitioning the legs from flexion to extension and vice versa. Significance This is the first study demonstrating the feasibility of EEG recording during pedaling, and owing to similarities between pedaling and bipedal walking, may provide valuable insight into brain activity during locomotion in humans. PMID:23036179
Spatially Nonlinear Interdependence of Alpha-Oscillatory Neural Networks under Chan Meditation
Chang, Chih-Hao
2013-01-01
This paper reports the results of our investigation of the effects of Chan meditation on brain electrophysiological behaviors from the viewpoint of spatially nonlinear interdependence among regional neural networks. Particular emphasis is laid on the alpha-dominated EEG (electroencephalograph). Continuous-time wavelet transform was adopted to detect the epochs containing substantial alpha activities. Nonlinear interdependence quantified by similarity index S(X∣Y), the influence of source signal Y on sink signal X, was applied to the nonlinear dynamical model in phase space reconstructed from multichannel EEG. Experimental group involved ten experienced Chan-Meditation practitioners, while control group included ten healthy subjects within the same age range, yet, without any meditation experience. Nonlinear interdependence among various cortical regions was explored for five local neural-network regions, frontal, posterior, right-temporal, left-temporal, and central regions. In the experimental group, the inter-regional interaction was evaluated for the brain dynamics under three different stages, at rest (stage R, pre-meditation background recording), in Chan meditation (stage M), and the unique Chakra-focusing practice (stage C). Experimental group exhibits stronger interactions among various local neural networks at stages M and C compared with those at stage R. The intergroup comparison demonstrates that Chan-meditation brain possesses better cortical inter-regional interactions than the resting brain of control group. PMID:24489583
Attentional Selection in a Cocktail Party Environment Can Be Decoded from Single-Trial EEG
O'Sullivan, James A.; Power, Alan J.; Mesgarani, Nima; Rajaram, Siddharth; Foxe, John J.; Shinn-Cunningham, Barbara G.; Slaney, Malcolm; Shamma, Shihab A.; Lalor, Edmund C.
2015-01-01
How humans solve the cocktail party problem remains unknown. However, progress has been made recently thanks to the realization that cortical activity tracks the amplitude envelope of speech. This has led to the development of regression methods for studying the neurophysiology of continuous speech. One such method, known as stimulus-reconstruction, has been successfully utilized with cortical surface recordings and magnetoencephalography (MEG). However, the former is invasive and gives a relatively restricted view of processing along the auditory hierarchy, whereas the latter is expensive and rare. Thus it would be extremely useful for research in many populations if stimulus-reconstruction was effective using electroencephalography (EEG), a widely available and inexpensive technology. Here we show that single-trial (≈60 s) unaveraged EEG data can be decoded to determine attentional selection in a naturalistic multispeaker environment. Furthermore, we show a significant correlation between our EEG-based measure of attention and performance on a high-level attention task. In addition, by attempting to decode attention at individual latencies, we identify neural processing at ∼200 ms as being critical for solving the cocktail party problem. These findings open up new avenues for studying the ongoing dynamics of cognition using EEG and for developing effective and natural brain–computer interfaces. PMID:24429136
Zelinsky, Deborah; Feinberg, Corey
2017-01-01
Abstract. The brain is equipped with a complex system for processing sensory information, including retinal circuitry comprising part of the central nervous system. Retinal stimulation can influence brain function via customized eyeglasses at both subcortical and cortical levels. We investigated cortical effects from wearing therapeutic eyeglasses, hypothesizing that they can create measureable changes in electroencephalogram (EEG) tracings. A Z-BellSM test was performed on a participant to select optimal lenses. An EEG measurement was recorded before and after the participant wore the eyeglasses. Equivalent quantitative electroencephalography (QEEG) analyses (statistical analysis on raw EEG recordings) were performed and compared with baseline findings. With glasses on, the participant’s readings were found to be closer to the normed database. The original objective of our investigation was met, and additional findings were revealed. The Z-bellSM test identified lenses to influence neurotypical brain activity, supporting the paradigm that eyeglasses can be utilized as a therapeutic intervention. Also, EEG analysis demonstrated that encephalographic techniques can be used to identify channels through which neuro-optomertric treatments work. This case study’s preliminary exploration illustrates the potential role of QEEG analysis and EEG-derived brain imaging in neuro-optometric research endeavors to affect brain function. PMID:28386574
[Features of brain biopotentials' spatial organization in adolescents].
Kruchinina, O V; Gal'perina, E I; Shepoval'nikov, A N
2014-01-01
Adolescence is characterized by an intensive formation of inter-regional cortical fields interaction, in this period significantly reorganized the activities of deep brain structures and cortical-subcortical interaction are enhanced. Our objectives were to evaluate the nature of changes in the spatial organization of brain bioelectric potentials with age and characteristics of such an organization in adolescents. For this purpose, EEG studies have been conducted in 230 subjects of both sexes aged 4 to 35 years. We estimated interdependent changes of biopotentials correlations fluctuations in 20-lead EEG, using the integral index Vol. Analyzed age-related changes of EEG correlations in rest condition and during verbal activity (Russian and English texts audition). Verbal tasks were sued in subjects over 8 years. It was found that the spatial synchronization of the EEG both in background and verbal activity increases with age, but after 20 years the rate of change is significantly reduced. In adolescence (12-17 years old), sex differences appear between the degree of EEG coherence processes occurring in the left and right hemispheres in subjects performing verbal tasks. In males 12 to 14 years nonlinear changes in overall correlation (indicators VOL) was observed, whereas in females of this age systemic reorganization of the brain interrelations occurs more smoothly, ahead of 1.5-2 years.
Ruusuvirta, T; Huotilainen, M
2005-01-01
Natural environments typically contain temporal scatters of sounds emitted from multiple sources. The sounds may often physically stand out from one another in their conjoined rather than simple features. This poses a particular challenge for the brain to detect which of these sounds are rare and, therefore, potentially important for survival. We recorded gamma-band (32-40 Hz) electroencephalographic (EEG) oscillations from the scalp of adult humans who passively listened to a repeated tone carrying frequent and rare conjunctions of its frequency and intensity. EEG oscillations that this tone induced, rather than evoked, differed in amplitude between the two conjunction types within the 56-ms analysis window from tone onset. Our finding suggests that, perhaps with the support of its non-phase-locked synchrony in the gamma band, the human brain is able to detect rare sounds as feature conjunctions very rapidly.
Human Decision Making Based on Variations in Internal Noise: An EEG Study
Amitay, Sygal; Guiraud, Jeanne; Sohoglu, Ediz; Zobay, Oliver; Edmonds, Barrie A.; Zhang, Yu-Xuan; Moore, David R.
2013-01-01
Perceptual decision making is prone to errors, especially near threshold. Physiological, behavioural and modeling studies suggest this is due to the intrinsic or ‘internal’ noise in neural systems, which derives from a mixture of bottom-up and top-down sources. We show here that internal noise can form the basis of perceptual decision making when the external signal lacks the required information for the decision. We recorded electroencephalographic (EEG) activity in listeners attempting to discriminate between identical tones. Since the acoustic signal was constant, bottom-up and top-down influences were under experimental control. We found that early cortical responses to the identical stimuli varied in global field power and topography according to the perceptual decision made, and activity preceding stimulus presentation could predict both later activity and behavioural decision. Our results suggest that activity variations induced by internal noise of both sensory and cognitive origin are sufficient to drive discrimination judgments. PMID:23840904
EEGLAB, SIFT, NFT, BCILAB, and ERICA: New Tools for Advanced EEG Processing
Delorme, Arnaud; Mullen, Tim; Kothe, Christian; Akalin Acar, Zeynep; Bigdely-Shamlo, Nima; Vankov, Andrey; Makeig, Scott
2011-01-01
We describe a set of complementary EEG data collection and processing tools recently developed at the Swartz Center for Computational Neuroscience (SCCN) that connect to and extend the EEGLAB software environment, a freely available and readily extensible processing environment running under Matlab. The new tools include (1) a new and flexible EEGLAB STUDY design facility for framing and performing statistical analyses on data from multiple subjects; (2) a neuroelectromagnetic forward head modeling toolbox (NFT) for building realistic electrical head models from available data; (3) a source information flow toolbox (SIFT) for modeling ongoing or event-related effective connectivity between cortical areas; (4) a BCILAB toolbox for building online brain-computer interface (BCI) models from available data, and (5) an experimental real-time interactive control and analysis (ERICA) environment for real-time production and coordination of interactive, multimodal experiments. PMID:21687590
Amico, Enrico; Van Mierlo, Pieter; Marinazzo, Daniele; Laureys, Steven
2015-01-01
Transcranial magnetic stimulation (TMS) has been used for more than 20 years to investigate connectivity and plasticity in the human cortex. By combining TMS with high-density electroencephalography (hd-EEG), one can stimulate any cortical area and measure the effects produced by this perturbation in the rest of the cerebral cortex. The purpose of this paper is to investigate changes of information flow in the brain after TMS from a functional and structural perspective, using multimodal modeling of source reconstructed TMS/hd-EEG recordings and DTI tractography. We prove how brain dynamics induced by TMS is constrained and driven by its structure, at different spatial and temporal scales, especially when considering cross-frequency interactions. These results shed light on the function-structure organization of the brain network at the global level, and on the huge variety of information contained in it.
SCoT: a Python toolbox for EEG source connectivity.
Billinger, Martin; Brunner, Clemens; Müller-Putz, Gernot R
2014-01-01
Analysis of brain connectivity has become an important research tool in neuroscience. Connectivity can be estimated between cortical sources reconstructed from the electroencephalogram (EEG). Such analysis often relies on trial averaging to obtain reliable results. However, some applications such as brain-computer interfaces (BCIs) require single-trial estimation methods. In this paper, we present SCoT-a source connectivity toolbox for Python. This toolbox implements routines for blind source decomposition and connectivity estimation with the MVARICA approach. Additionally, a novel extension called CSPVARICA is available for labeled data. SCoT estimates connectivity from various spectral measures relying on vector autoregressive (VAR) models. Optionally, these VAR models can be regularized to facilitate ill posed applications such as single-trial fitting. We demonstrate basic usage of SCoT on motor imagery (MI) data. Furthermore, we show simulation results of utilizing SCoT for feature extraction in a BCI application. These results indicate that CSPVARICA and correct regularization can significantly improve MI classification. While SCoT was mainly designed for application in BCIs, it contains useful tools for other areas of neuroscience. SCoT is a software package that (1) brings combined source decomposition and connectivtiy estimation to the open Python platform, and (2) offers tools for single-trial connectivity estimation. The source code is released under the MIT license and is available online at github.com/SCoT-dev/SCoT.
SCoT: a Python toolbox for EEG source connectivity
Billinger, Martin; Brunner, Clemens; Müller-Putz, Gernot R.
2014-01-01
Analysis of brain connectivity has become an important research tool in neuroscience. Connectivity can be estimated between cortical sources reconstructed from the electroencephalogram (EEG). Such analysis often relies on trial averaging to obtain reliable results. However, some applications such as brain-computer interfaces (BCIs) require single-trial estimation methods. In this paper, we present SCoT—a source connectivity toolbox for Python. This toolbox implements routines for blind source decomposition and connectivity estimation with the MVARICA approach. Additionally, a novel extension called CSPVARICA is available for labeled data. SCoT estimates connectivity from various spectral measures relying on vector autoregressive (VAR) models. Optionally, these VAR models can be regularized to facilitate ill posed applications such as single-trial fitting. We demonstrate basic usage of SCoT on motor imagery (MI) data. Furthermore, we show simulation results of utilizing SCoT for feature extraction in a BCI application. These results indicate that CSPVARICA and correct regularization can significantly improve MI classification. While SCoT was mainly designed for application in BCIs, it contains useful tools for other areas of neuroscience. SCoT is a software package that (1) brings combined source decomposition and connectivtiy estimation to the open Python platform, and (2) offers tools for single-trial connectivity estimation. The source code is released under the MIT license and is available online at github.com/SCoT-dev/SCoT. PMID:24653694
EEG source reconstruction reveals frontal-parietal dynamics of spatial conflict processing.
Cohen, Michael X; Ridderinkhof, K Richard
2013-01-01
Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (∼200 ms post-stimulus) conflict modulation in stimulus-contralateral parietal gamma (30-50 Hz), followed by a later alpha-band (8-12 Hz) conflict modulation, suggesting an early detection of spatial conflict and inhibition of spatial location processing. Inter-regional connectivity analyses assessed via cross-frequency coupling of theta (4-8 Hz), alpha, and gamma power revealed conflict-induced shifts in cortical network interactions: Congruent trials (relative to incongruent trials) had stronger coupling between frontal theta and stimulus-contrahemifield parietal alpha/gamma power, whereas incongruent trials had increased theta coupling between medial frontal and lateral frontal regions. These findings shed new light into the large-scale network dynamics of spatial conflict processing, and how those networks are shaped by oscillatory interactions.
Guhathakurta, Debarpan; Dutta, Anirban
2016-01-01
Transcranial direct current stimulation (tDCS) modulates cortical neural activity and hemodynamics. Electrophysiological methods (electroencephalography-EEG) measure neural activity while optical methods (near-infrared spectroscopy-NIRS) measure hemodynamics coupled through neurovascular coupling (NVC). Assessment of NVC requires development of NIRS-EEG joint-imaging sensor montages that are sensitive to the tDCS affected brain areas. In this methods paper, we present a software pipeline incorporating freely available software tools that can be used to target vascular territories with tDCS and develop a NIRS-EEG probe for joint imaging of tDCS-evoked responses. We apply this software pipeline to target primarily the outer convexity of the brain territory (superficial divisions) of the middle cerebral artery (MCA). We then present a computational method based on Empirical Mode Decomposition of NIRS and EEG time series into a set of intrinsic mode functions (IMFs), and then perform a cross-correlation analysis on those IMFs from NIRS and EEG signals to model NVC at the lesional and contralesional hemispheres of an ischemic stroke patient. For the contralesional hemisphere, a strong positive correlation between IMFs of regional cerebral hemoglobin oxygen saturation and the log-transformed mean-power time-series of IMFs for EEG with a lag of about -15 s was found after a cumulative 550 s stimulation of anodal tDCS. It is postulated that system identification, for example using a continuous-time autoregressive model, of this coupling relation under tDCS perturbation may provide spatiotemporal discriminatory features for the identification of ischemia. Furthermore, portable NIRS-EEG joint imaging can be incorporated into brain computer interfaces to monitor tDCS-facilitated neurointervention as well as cortical reorganization.
Boonstra, Tjeerd W.; Nikolin, Stevan; Meisener, Ann-Christin; Martin, Donel M.; Loo, Colleen K.
2016-01-01
Transcranial direct current stimulation (tDCS) is proposed as a tool to investigate cognitive functioning in healthy people and as a treatment for various neuropathological disorders. However, the underlying cortical mechanisms remain poorly understood. We aim to investigate whether resting-state electroencephalography (EEG) can be used to monitor the effects of tDCS on cortical activity. To this end we tested whether the spectral content of ongoing EEG activity is significantly different after a single session of active tDCS compared to sham stimulation. Twenty participants were tested in a sham-controlled, randomized, crossover design. Resting-state EEG was acquired before, during and after active tDCS to the left dorsolateral prefrontal cortex (15 min of 2 mA tDCS) and sham stimulation. Electrodes with a diameter of 3.14 cm2 were used for EEG and tDCS. Partial least squares (PLS) analysis was used to examine differences in power spectral density (PSD) and the EEG mean frequency to quantify the slowing of EEG activity after stimulation. PLS revealed a significant increase in spectral power at frequencies below 15 Hz and a decrease at frequencies above 15 Hz after active tDCS (P = 0.001). The EEG mean frequency was significantly reduced after both active tDCS (P < 0.0005) and sham tDCS (P = 0.001), though the decrease in mean frequency was smaller after sham tDCS than after active tDCS (P = 0.073). Anodal tDCS of the left DLPFC using a high current density bi-frontal electrode montage resulted in general slowing of resting-state EEG. The similar findings observed following sham stimulation question whether the standard sham protocol is an appropriate control condition for tDCS. PMID:27375462
Guhathakurta, Debarpan; Dutta, Anirban
2016-01-01
Transcranial direct current stimulation (tDCS) modulates cortical neural activity and hemodynamics. Electrophysiological methods (electroencephalography-EEG) measure neural activity while optical methods (near-infrared spectroscopy-NIRS) measure hemodynamics coupled through neurovascular coupling (NVC). Assessment of NVC requires development of NIRS-EEG joint-imaging sensor montages that are sensitive to the tDCS affected brain areas. In this methods paper, we present a software pipeline incorporating freely available software tools that can be used to target vascular territories with tDCS and develop a NIRS-EEG probe for joint imaging of tDCS-evoked responses. We apply this software pipeline to target primarily the outer convexity of the brain territory (superficial divisions) of the middle cerebral artery (MCA). We then present a computational method based on Empirical Mode Decomposition of NIRS and EEG time series into a set of intrinsic mode functions (IMFs), and then perform a cross-correlation analysis on those IMFs from NIRS and EEG signals to model NVC at the lesional and contralesional hemispheres of an ischemic stroke patient. For the contralesional hemisphere, a strong positive correlation between IMFs of regional cerebral hemoglobin oxygen saturation and the log-transformed mean-power time-series of IMFs for EEG with a lag of about −15 s was found after a cumulative 550 s stimulation of anodal tDCS. It is postulated that system identification, for example using a continuous-time autoregressive model, of this coupling relation under tDCS perturbation may provide spatiotemporal discriminatory features for the identification of ischemia. Furthermore, portable NIRS-EEG joint imaging can be incorporated into brain computer interfaces to monitor tDCS-facilitated neurointervention as well as cortical reorganization. PMID:27378836
Pain Catastrophising Affects Cortical Responses to Viewing Pain in Others
Fallon, Nicholas
2015-01-01
Pain catastrophising is an exaggerated cognitive attitude implemented during pain or when thinking about pain. Catastrophising was previously associated with increased pain severity, emotional distress and disability in chronic pain patients, and is also a contributing factor in the development of neuropathic pain. To investigate the neural basis of how pain catastrophising affects pain observed in others, we acquired EEG data in groups of participants with high (High-Cat) or low (Low-Cat) pain catastrophising scores during viewing of pain scenes and graphically matched pictures not depicting imminent pain. The High-Cat group attributed greater pain to both pain and non-pain pictures. Source dipole analysis of event-related potentials during picture viewing revealed activations in the left (PHGL) and right (PHGR) paraphippocampal gyri, rostral anterior (rACC) and posterior cingulate (PCC) cortices. The late source activity (600–1100 ms) in PHGL and PCC was augmented in High-Cat, relative to Low-Cat, participants. Conversely, greater source activity was observed in the Low-Cat group during the mid-latency window (280–450 ms) in the rACC and PCC. Low-Cat subjects demonstrated a significantly stronger correlation between source activity in PCC and pain and arousal ratings in the long latency window, relative to high pain catastrophisers. Results suggest augmented activation of limbic cortex and higher order pain processing cortical regions during the late processing period in high pain catastrophisers viewing both types of pictures. This pattern of cortical activations is consistent with the distorted and magnified cognitive appraisal of pain threats in high pain catastrophisers. In contrast, high pain catastrophising individuals exhibit a diminished response during the mid-latency period when attentional and top-down resources are ascribed to observed pain. PMID:26186545
Puszta, András; Katona, Xénia; Bodosi, Balázs; Pertich, Ákos; Nyujtó, Diána; Braunitzer, Gábor; Nagy, Attila
2018-01-01
The computer-based Rutgers Acquired Equivalence test (RAET) is a widely used paradigm to test the function of subcortical structures in visual associative learning. The test consists of an acquisition (pair learning) and a test (rule transfer) phase, associated with the function of the basal ganglia and the hippocampi, respectively. Obviously, such a complex task also requires cortical involvement. To investigate the activity of different cortical areas during this test, 64-channel EEG recordings were recorded in 24 healthy volunteers. Fast-Fourier and Morlet wavelet convolution analyses were performed on the recordings. The most robust power changes were observed in the theta (4–7 Hz) and gamma (>30 Hz) frequency bands, in which significant power elevation was observed in the vast majority of the subjects, over the parieto-occipital and temporo-parietal areas during the acquisition phase. The involvement of the frontal areas in the acquisition phase was remarkably weaker. No remarkable cortical power elevations were found in the test phase. In fact, the power of the alpha and beta bands was significantly decreased over the parietooccipital areas. We conclude that the initial acquisition of the image pairs requires strong cortical involvement, but once the pairs have been learned, neither retrieval nor generalization requires strong cortical contribution. PMID:29867412
Puszta, András; Katona, Xénia; Bodosi, Balázs; Pertich, Ákos; Nyujtó, Diána; Braunitzer, Gábor; Nagy, Attila
2018-01-01
The computer-based Rutgers Acquired Equivalence test (RAET) is a widely used paradigm to test the function of subcortical structures in visual associative learning. The test consists of an acquisition (pair learning) and a test (rule transfer) phase, associated with the function of the basal ganglia and the hippocampi, respectively. Obviously, such a complex task also requires cortical involvement. To investigate the activity of different cortical areas during this test, 64-channel EEG recordings were recorded in 24 healthy volunteers. Fast-Fourier and Morlet wavelet convolution analyses were performed on the recordings. The most robust power changes were observed in the theta (4-7 Hz) and gamma (>30 Hz) frequency bands, in which significant power elevation was observed in the vast majority of the subjects, over the parieto-occipital and temporo-parietal areas during the acquisition phase. The involvement of the frontal areas in the acquisition phase was remarkably weaker. No remarkable cortical power elevations were found in the test phase. In fact, the power of the alpha and beta bands was significantly decreased over the parietooccipital areas. We conclude that the initial acquisition of the image pairs requires strong cortical involvement, but once the pairs have been learned, neither retrieval nor generalization requires strong cortical contribution.
Wang, Wuyi; Viswanathan, Shivakumar; Lee, Taraz; Grafton, Scott T
2016-01-01
Cortical theta band oscillations (4-8 Hz) in EEG signals have been shown to be important for a variety of different cognitive control operations in visual attention paradigms. However the synchronization source of these signals as defined by fMRI BOLD activity and the extent to which theta oscillations play a role in multimodal attention remains unknown. Here we investigated the extent to which cross-modal visual and auditory attention impacts theta oscillations. Using a simultaneous EEG-fMRI paradigm, healthy human participants performed an attentional vigilance task with six cross-modal conditions using naturalistic stimuli. To assess supramodal mechanisms, modulation of theta oscillation amplitude for attention to either visual or auditory stimuli was correlated with BOLD activity by conjunction analysis. Negative correlation was localized to cortical regions associated with the default mode network and positively with ventral premotor areas. Modality-associated attention to visual stimuli was marked by a positive correlation of theta and BOLD activity in fronto-parietal area that was not observed in the auditory condition. A positive correlation of theta and BOLD activity was observed in auditory cortex, while a negative correlation of theta and BOLD activity was observed in visual cortex during auditory attention. The data support a supramodal interaction of theta activity with of DMN function, and modality-associated processes within fronto-parietal networks related to top-down theta related cognitive control in cross-modal visual attention. On the other hand, in sensory cortices there are opposing effects of theta activity during cross-modal auditory attention.
The engagement of cortical areas preceding exogenous vergence eye movements.
Wojtczak-Kwaśniewska, Monika; Przekoracka-Krawczyk, Anna; Van der Lubbe, Rob H J
2018-01-01
Source analyses on event related potentials (ERPs) derived from the electroencephalogram (EEG) were performed to examine the respective roles of cortical areas preceding exogenously triggered saccades, combined convergences, and combined divergences. All eye movements were triggered by the offset of a central fixation light emitting diode (LED) and the onset of a lateral LED at various depths in an otherwise fully darkened room. Our analyses revealed that three source pairs, two located in the frontal lobe-the frontal eye fields (FEF) and an anterior frontal area-, and one located within the occipital cortex, can account for 99.2% of the observed ERPs. Overall, the comparison between source activities revealed the largest activity in the occipital cortex, while no difference in activity between FEF and the anterior frontal area was obtained. For all sources, increased activity was observed for combined vergences, especially combined convergences, relative to saccades. Behavioral results revealed that onset latencies were longest for combined convergences, intermediate for combined divergences, and the shortest for saccades. Together, these findings fit within a perspective in which both occipital and frontal areas play an important role in retinal disparity detection. In the case of saccades and combined divergences stimulus-locked activity was larger than response-locked activity, while no difference between stimulus- and response-locked activity was observed for combined convergences. These findings seem to imply that the electrophysiological activity preceding exogenous eye movements consists of a sensory-related part that is under cortical control, while subcortical structures may be held responsible for final execution.
Hasan, Muhammad Abul; Fraser, Matthew; Conway, Bernard A; Allan, David B; Vučković, Aleksandra
2016-09-01
One of the brain signatures of the central neuropathic pain (CNP) is the theta band over-activity of wider cortical structures, during imagination of movement. The objective of the study was to investigate whether this over-activity is reversible following the neurofeedback treatment of CNP. Five paraplegic patients with pain in their legs underwent from twenty to forty neurofeedback sessions that significantly reduced their pain. In order to assess their dynamic cortical activity they were asked to imagine movements of all limbs a week before the first and a week after the last neurofeedback session. Using time-frequency analysis we compared EEG activity during imagination of movement before and after the therapy and further compared it with EEG signals of ten paraplegic patients with no pain and a control group of ten able-bodied people. Neurofeedback treatment resulted in reduced CNP and a wide spread reduction of cortical activity during imagination of movement. The reduction was significant in the alpha and beta band but was largest in the theta band. As a result cortical activity became similar to the activity of other two groups with no pain. Reduction of CNP is accompanied by reduced cortical over-activity during movement imagination. Understanding causes and consequences mechanism through which CNP affects cortical activity. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.
Gersner, R; Ekstein, D; Dhamne, S C; Schachter, S C; Rotenberg, A
2015-11-01
Huperzine A (HupA) is a naturally occurring compound found in the firmoss Huperzia serrata. While HupA is a potent acetylcholinesterase inhibitor, its full pharmacologic profile is incompletely described. Since previous works suggested a capacity for HupA to prophylax against seizures, we tested the HupA antiepileptic potential in pentylenetetrazole (PTZ) rat epilepsy model and explored its mechanism of action by spectral EEG analysis and by paired-pulse transcranial magnetic stimulation (ppTMS), a measure of GABA-mediated intracortical inhibition. We tested whether HupA suppresses seizures in the rat PTZ acute seizure model, and quantified latency to first myoclonus and to generalized tonic-clonic seizure, and spike frequency on EEG. Additionally, we measured power in the EEG gamma frequency band which is associated with GABAergic cortical interneuron activation. Then, as a step toward further examining the HupA antiepileptic mechanism of action, we tested long-interval intracortical inhibition (LICI) using ppTMS coupled with electromyography to assess whether HupA augments GABA-mediated paired-pulse inhibition of the motor evoked potential. We also tested whether the HupA effect on paired-pulse inhibition was central or peripheral by comparison of outcomes following administration of HupA or the peripheral acetylcholinesterase inhibitor pyridostigmine. We also tested whether the HupA effect was dependent on central muscarinic or GABAA receptors by co-administration of HupA and atropine or PTZ, respectively. In tests of antiepileptic potential, HupA suppressed seizures and epileptic spikes on EEG. Spectral EEG analysis also revealed enhanced gamma frequency band power with HupA treatment. By ppTMS we found that HupA increases intracortical inhibition and blocks PTZ-induced cortical excitation. Atropine co-administration with HupA did not alter HupA-induced intracortical inhibition suggesting independent of muscarinic acetylcholine receptors mechanism in this model. Last, pyridostigmine did not affect the ppTMS-measured cortical inhibition suggesting that HupA-induced effect is centrally-mediated. Our data support antiepileptic HupA applications, and suggest that such activity may be via enhancement of GABAergic intracortical inhibition. Copyright © 2015 Elsevier B.V. All rights reserved.
EEG-LORETA endophenotypes of the common idiopathic generalized epilepsy syndromes.
Clemens, B; Puskás, S; Besenyei, M; Emri, M; Opposits, G; Kis, S A; Hollódy, K; Fogarasi, A; Kondákor, I; Füle, K; Bense, K; Fekete, I
2012-05-01
We tested the hypothesis that the cortical areas with abnormal local EEG synchronization are dissimilar in the three common idiopathic generalized epilepsy (IGE) phenotypes: IGE patients with absence seizures (ABS), juvenile myoclonic epilepsy (JME) and epilepsy with generalized tonic-clonic seizures exclusively (EGTCS). Groups of unmedicated ABS, JME and EGTCS patients were investigated. Waking EEG background activity (without any epileptiform potentials) was analyzed by a source localization method, LORETA (Low Resolution Electromagnetic Tomography). Each patient group was compared to a separate, age-matched group of healthy control persons. Voxel-based, normalized broad-band (delta, theta, alpha, and beta) and very narrow band (VNB, 1Hz bandwidth, from 1 to 25Hz) LORETA activity (=current source density, A/m(2)) were computed for each person. Group comparison included subtraction (average patient data minus average control data) and group statistics (multiple t-tests, where Bonferroni-corrected p<0.05 values were accepted as statistically significant). Statistically not significant main findings were: overall increased delta and theta broad band activity in the ABS and JME groups; decrease of alpha and beta activity in the EGTCS group. Statistically significant main findings were as follows. JME group: bilaterally increased theta activity in posterior (temporal, parietal, and occipital) cortical areas; bilaterally increased activity in the medial and basal prefrontal area in the 8Hz VNB; bilaterally decreased activity in the precuneus, posterior cingulate and superior parietal lobule in the 11Hz and 21-22Hz VNBs. ABS group: bilaterally increased theta activity emerged in the basal prefrontal and medial temporal limbic areas. Decreased activity was found at 19-21Hz in the right postcentral gyrus and parts of the right superior and medial temporal gyri. EGTCS group: decreased activity was found in the frontal cortex and the postcentral gyrus at 10-11Hz, increased activity in the right parahippocampal gyrus at 16-18Hz. Increased theta activity in the posterior parts of the cortex is the endophenotype for JME. Increased theta activity in the fronto-temporal limbic areas is the endophenotype for ABS. Statistically not significant findings might indicate diffuse biochemical abnormality of the cortex in JME and ABS. EEG-LORETA endophenotypes may correspond to the selective propensity to generate absence and myoclonic seizures in the ABS and JME syndromes. Copyright © 2011 Elsevier B.V. All rights reserved.
Insomnia is Associated with Cortical Hyperarousal as Early as Adolescence.
Fernandez-Mendoza, Julio; Li, Yun; Vgontzas, Alexandros N; Fang, Jidong; Gaines, Jordan; Calhoun, Susan L; Liao, Duanping; Bixler, Edward O
2016-05-01
To examine whether insomnia is associated with spectral electroencephalographic (EEG) dynamics in the beta (15-35Hz) range during sleep in an adolescent general population sample. A case-control sample of 44 adolescents from the Penn State Child Cohort underwent a 9-h polysomnography, clinical history and physical examination. We examined low-beta (15-25 Hz) and high-beta (25-35 Hz) relative power at central EEG derivations during sleep onset latency (SOL), sleep onset (SO), non-rapid eye movement (NREM) sleep, and wake after sleep onset (WASO). Compared to controls (n = 21), individuals with insomnia (n = 23) showed increased SOL and WASO and decreased sleep duration and efficiency, while no differences in sleep architecture were found. Insomniacs showed increased low-beta and high-beta relative power during SOL, SO, and NREM sleep as compared to controls. High-beta relative power was greater during all sleep and wake states in insomniacs with short sleep duration as compared to individuals with insomnia with normal sleep duration. Adolescent insomnia is associated with increased beta EEG power during sleep, which suggests that cortical hyperarousal is present in individuals with insomnia as early as adolescence. Interestingly, cortical hyperarousal is greatest in individuals with insomnia with short sleep duration and may explain the sleep complaints of those with normal sleep duration. Disturbed cortical networks may be a shared mechanism putting individuals with insomnia at risk of psychiatric disorders. © 2016 Associated Professional Sleep Societies, LLC.
Safety and EEG data quality of concurrent high-density EEG and high-speed fMRI at 3 Tesla
Foged, Mette Thrane; Lindberg, Ulrich; Vakamudi, Kishore; Larsson, Henrik B. W.; Pinborg, Lars H.; Kjær, Troels W.; Fabricius, Martin; Svarer, Claus; Ozenne, Brice; Thomsen, Carsten; Beniczky, Sándor; Posse, Stefan
2017-01-01
Purpose Concurrent EEG and fMRI is increasingly used to characterize the spatial-temporal dynamics of brain activity. However, most studies to date have been limited to conventional echo-planar imaging (EPI). There is considerable interest in integrating recently developed high-speed fMRI methods with high-density EEG to increase temporal resolution and sensitivity for task-based and resting state fMRI, and for detecting interictal spikes in epilepsy. In the present study using concurrent high-density EEG and recently developed high-speed fMRI methods, we investigate safety of radiofrequency (RF) related heating, the effect of EEG on cortical signal-to-noise ratio (SNR) in fMRI, and assess EEG data quality. Materials and methods The study compared EPI, multi-echo EPI, multi-band EPI and multi-slab echo-volumar imaging pulse sequences, using clinical 3 Tesla MR scanners from two different vendors that were equipped with 64- and 256-channel MR-compatible EEG systems, respectively, and receive only array head coils. Data were collected in 11 healthy controls (3 males, age range 18–70 years) and 13 patients with epilepsy (8 males, age range 21–67 years). Three of the healthy controls were scanned with the 256-channel EEG system, the other subjects were scanned with the 64-channel EEG system. Scalp surface temperature, SNR in occipital cortex and head movement were measured with and without the EEG cap. The degree of artifacts and the ability to identify background activity was assessed by visual analysis by a trained expert in the 64 channel EEG data (7 healthy controls, 13 patients). Results RF induced heating at the surface of the EEG electrodes during a 30-minute scan period with stable temperature prior to scanning did not exceed 1.0° C with either EEG system and any of the pulse sequences used in this study. There was no significant decrease in cortical SNR due to the presence of the EEG cap (p > 0.05). No significant differences in the visually analyzed EEG data quality were found between EEG recorded during high-speed fMRI and during conventional EPI (p = 0.78). Residual ballistocardiographic artifacts resulted in 58% of EEG data being rated as poor quality. Conclusion This study demonstrates that high-density EEG can be safely implemented in conjunction with high-speed fMRI and that high-speed fMRI does not adversely affect EEG data quality. However, the deterioration of the EEG quality due to residual ballistocardiographic artifacts remains a significant constraint for routine clinical applications of concurrent EEG-fMRI. PMID:28552957
Insomnia is Associated with Cortical Hyperarousal as Early as Adolescence
Fernandez-Mendoza, Julio; Li, Yun; Vgontzas, Alexandros N.; Fang, Jidong; Gaines, Jordan; Calhoun, Susan L.; Liao, Duanping; Bixler, Edward O.
2016-01-01
Study Objectives: To examine whether insomnia is associated with spectral electroencephalographic (EEG) dynamics in the beta (15–35Hz) range during sleep in an adolescent general population sample. Methods: A case-control sample of 44 adolescents from the Penn State Child Cohort underwent a 9-h polysomnography, clinical history and physical examination. We examined low-beta (15–25 Hz) and high-beta (25–35 Hz) relative power at central EEG derivations during sleep onset latency (SOL), sleep onset (SO), non-rapid eye movement (NREM) sleep, and wake after sleep onset (WASO). Results: Compared to controls (n = 21), individuals with insomnia (n = 23) showed increased SOL and WASO and decreased sleep duration and efficiency, while no differences in sleep architecture were found. Insomniacs showed increased low-beta and high-beta relative power during SOL, SO, and NREM sleep as compared to controls. High-beta relative power was greater during all sleep and wake states in insomniacs with short sleep duration as compared to individuals with insomnia with normal sleep duration. Conclusions: Adolescent insomnia is associated with increased beta EEG power during sleep, which suggests that cortical hyperarousal is present in individuals with insomnia as early as adolescence. Interestingly, cortical hyperarousal is greatest in individuals with insomnia with short sleep duration and may explain the sleep complaints of those with normal sleep duration. Disturbed cortical networks may be a shared mechanism putting individuals with insomnia at risk of psychiatric disorders. Citation: Fernandez-Mendoza J, Li Y, Vgontzas AN, Fang J, Gaines J, Calhoun SL, Liao D, Bixler EO. Insomnia is associated with cortical hyperarousal as early as adolescence. SLEEP 2016;39(5):1029–1036. PMID:26951400
Left hemibody myoclonus due to anomalous right vertebral artery.
Coelho, Miguel; Marti, Maria J; Valls-Solé, Josep; Pujol, Teresa; Tolosa, Eduardo
2005-01-01
A 43-year-old man presented with sporadic, sudden, brief, and involuntary jerks of his left limbs and trunk muscles. The electromyographic recordings showed short-lasting highly synchronized bursts, compatible with myoclonus limited to the left hemibody. Blink reflex, masseter silent period, cortical and spinal magnetic stimulation, somatosensory cortical evoked potentials, and electroencephalogram (EEG) were normal; the EEG back-averaging showed no spikes preceding the myoclonus. Magnetic resonance imaging and magnetic resonance angiography showed the presence of an anomalous nonectasic right vertebral artery compressing the right side of ventral medulla oblongata. We hypothesize that the aberrant right vertebral artery induced abnormal activation of descending motor tracts responsible for the myoclonus. (c) 2004 Movement Disorder Society.
Popivanov, D; Mineva, A; Krekule, I
1999-05-21
In experiments with EEG accompanying continuous slow goal-directed voluntary movements we found abrupt short-term transients (STs) of the coefficients of EEG time-varying autoregressive (TVAR) model. The onset of STs indicated (i) a positive EEG wave related to an increase of 3-7 Hz oscillations in time period before the movement start, (ii) synchronization of 35-40 Hz prior to movement start and during the movement when the target is nearly reached. Both these phenomena are expressed predominantly over supplementary motor area, premotor and parietal cortices. These patterns were detected after averaging of EEG segments synchronized to the abrupt changes of the TVAR coefficients computed in the time course of EEG single records. The results are discussed regarding the cognitive aspect of organization of goal-directed movements.
Spreading Photoparoxysmal EEG Response is Associated with an Abnormal Cortical Excitability Pattern
ERIC Educational Resources Information Center
Siniatchkin, Michael; Groppa, Sergey; Jerosch, Bettina; Muhle, Hiltrud; Kurth, Christoph; Shepherd, Alex J.; Siebner, Hartwig; Stephani, Ulrich
2007-01-01
Photosensitivity or photoparoxysmal response (PPR) is a highly heritable electroencephalographic trait characterized by an abnormal cortical response to intermittent photic stimulation (IPS). In PPR-positive individuals, IPS induces spikes, spike-waves or intermittent slow waves. The PPR may be restricted to posterior visual areas (i.e. local PPR…
Effects of adaptive refinement on the inverse EEG solution
NASA Astrophysics Data System (ADS)
Weinstein, David M.; Johnson, Christopher R.; Schmidt, John A.
1995-10-01
One of the fundamental problems in electroencephalography can be characterized by an inverse problem. Given a subset of electrostatic potentials measured on the surface of the scalp and the geometry and conductivity properties within the head, calculate the current vectors and potential fields within the cerebrum. Mathematically the generalized EEG problem can be stated as solving Poisson's equation of electrical conduction for the primary current sources. The resulting problem is mathematically ill-posed i.e., the solution does not depend continuously on the data, such that small errors in the measurement of the voltages on the scalp can yield unbounded errors in the solution, and, for the general treatment of a solution of Poisson's equation, the solution is non-unique. However, if accurate solutions the general treatment of a solution of Poisson's equation, the solution is non-unique. However, if accurate solutions to such problems could be obtained, neurologists would gain noninvasive accesss to patient-specific cortical activity. Access to such data would ultimately increase the number of patients who could be effectively treated for pathological cortical conditions such as temporal lobe epilepsy. In this paper, we present the effects of spatial adaptive refinement on the inverse EEG problem and show that the use of adaptive methods allow for significantly better estimates of electric and potential fileds within the brain through an inverse procedure. To test these methods, we have constructed several finite element head models from magneteic resonance images of a patient. The finite element meshes ranged in size from 2724 nodes and 12,812 elements to 5224 nodes and 29,135 tetrahedral elements, depending on the level of discretization. We show that an adaptive meshing algorithm minimizes the error in the forward problem due to spatial discretization and thus increases the accuracy of the inverse solution.
Bednar, Adam; Boland, Francis M; Lalor, Edmund C
2017-03-01
The human ability to localize sound is essential for monitoring our environment and helps us to analyse complex auditory scenes. Although the acoustic cues mediating sound localization have been established, it remains unknown how these cues are represented in human cortex. In particular, it is still a point of contention whether binaural and monaural cues are processed by the same or distinct cortical networks. In this study, participants listened to a sequence of auditory stimuli from different spatial locations while we recorded their neural activity using electroencephalography (EEG). The stimuli were presented over a loudspeaker array, which allowed us to deliver realistic, free-field stimuli in both the horizontal and vertical planes. Using a multivariate classification approach, we showed that it is possible to decode sound source location from scalp-recorded EEG. Robust and consistent decoding was shown for stimuli that provide binaural cues (i.e. Left vs. Right stimuli). Decoding location when only monaural cues were available (i.e. Front vs. Rear and elevational stimuli) was successful for a subset of subjects and showed less consistency. Notably, the spatio-temporal pattern of EEG features that facilitated decoding differed based on the availability of binaural and monaural cues. In particular, we identified neural processing of binaural cues at around 120 ms post-stimulus and found that monaural cues are processed later between 150 and 200 ms. Furthermore, different spatial activation patterns emerged for binaural and monaural cue processing. These spatio-temporal dissimilarities suggest the involvement of separate cortical mechanisms in monaural and binaural acoustic cue processing. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
ERIC Educational Resources Information Center
Papousek, Ilona; Murhammer, Daniela; Schulter, Gunter
2011-01-01
The study shows that changes in relative verbal vs. figural working memory and fluency performance from one session to a second session two to 3 weeks apart covary with spontaneously occurring changes of cortical asymmetry in the lateral frontal and central cortex, measured by electroencephalography (EEG) in resting conditions before the execution…
Leveraging anatomical information to improve transfer learning in brain-computer interfaces
Wronkiewicz, Mark; Larson, Eric; Lee, Adrian KC
2015-01-01
Objective Brain-computer interfaces (BCIs) represent a technology with the potential to rehabilitate a range of traumatic and degenerative nervous system conditions but require a time-consuming training process to calibrate. An area of BCI research known as transfer learning is aimed at accelerating training by recycling previously recorded training data across sessions or subjects. Training data, however, is typically transferred from one electrode configuration to another without taking individual head anatomy or electrode positioning into account, which may underutilize the recycled data. Approach We explore transfer learning with the use of source imaging, which estimates neural activity in the cortex. Transferring estimates of cortical activity, in contrast to scalp recordings, provides a way to compensate for variability in electrode positioning and head morphologies across subjects and sessions. Main Results Based on simulated and measured EEG activity, we trained a classifier using data transferred exclusively from other subjects and achieved accuracies that were comparable to or surpassed a benchmark classifier (representative of a real-world BCI). Our results indicate that classification improvements depend on the number of trials transferred and the cortical region of interest. Significance These findings suggest that cortical source-based transfer learning is a principled method to transfer data that improves BCI classification performance and provides a path to reduce BCI calibration time. PMID:26169961
Henz, Sonja; Kutz, Dieter F.; Werner, Jana; Hürster, Walter; Kolb, Florian P.; Nida-Ruemelin, Julian
2015-01-01
The aim of the study was to determine whether a deliberative process, leading to a motor action, is detectable in high density EEG recordings. Subjects were required to press one of two buttons. In a simple motor task the subject knew which button to press, whilst in a color-word Stroop task subjects had to press the right button with the right index finger when meaning and color coincided, or the left button with the left index finger when meaning and color were disparate. EEG recordings obtained during the simple motor task showed a sequence of positive (P) and negative (N) cortical potentials (P1-N1-P2) which are assumed to be related to the processing of the movement. The sequence of cortical potentials was similar in EEG recordings of subjects having to deliberate over how to respond, but the above sequence (P1-N1-P2) was preceded by slowly increasing negativity (N0), with N0 being assumed to represent the end of the deliberation process. Our data suggest the existence of neurophysiological correlates of deliberative processes. PMID:26190987
Irimia, Andrei; Goh, S.-Y. Matthew; Torgerson, Carinna M.; Stein, Nathan R.; Chambers, Micah C.; Vespa, Paul M.; Van Horn, John D.
2013-01-01
Objective To inverse-localize epileptiform cortical electrical activity recorded from severe traumatic brain injury (TBI) patients using electroencephalography (EEG). Methods Three acute TBI cases were imaged using computed tomography (CT) and multimodal magnetic resonance imaging (MRI). Semi-automatic segmentation was performed to partition the complete TBI head into 25 distinct tissue types, including 6 tissue types accounting for pathology. Segmentations were employed to generate a finite element method model of the head, and EEG activity generators were modeled as dipolar currents distributed over the cortical surface. Results We demonstrate anatomically faithful localization of EEG generators responsible for epileptiform discharges in severe TBI. By accounting for injury-related tissue conductivity changes, our work offers the most realistic implementation currently available for the inverse estimation of cortical activity in TBI. Conclusion Whereas standard localization techniques are available for electrical activity mapping in uninjured brains, they are rarely applied to acute TBI. Modern models of TBI-induced pathology can inform the localization of epileptogenic foci, improve surgical efficacy, contribute to the improvement of critical care monitoring and provide guidance for patient-tailored treatment. With approaches such as this, neurosurgeons and neurologists can study brain activity in acute TBI and obtain insights regarding injury effects upon brain metabolism and clinical outcome. PMID:24011495
Irimia, Andrei; Goh, S-Y Matthew; Torgerson, Carinna M; Stein, Nathan R; Chambers, Micah C; Vespa, Paul M; Van Horn, John D
2013-10-01
To inverse-localize epileptiform cortical electrical activity recorded from severe traumatic brain injury (TBI) patients using electroencephalography (EEG). Three acute TBI cases were imaged using computed tomography (CT) and multimodal magnetic resonance imaging (MRI). Semi-automatic segmentation was performed to partition the complete TBI head into 25 distinct tissue types, including 6 tissue types accounting for pathology. Segmentations were employed to generate a finite element method model of the head, and EEG activity generators were modeled as dipolar currents distributed over the cortical surface. We demonstrate anatomically faithful localization of EEG generators responsible for epileptiform discharges in severe TBI. By accounting for injury-related tissue conductivity changes, our work offers the most realistic implementation currently available for the inverse estimation of cortical activity in TBI. Whereas standard localization techniques are available for electrical activity mapping in uninjured brains, they are rarely applied to acute TBI. Modern models of TBI-induced pathology can inform the localization of epileptogenic foci, improve surgical efficacy, contribute to the improvement of critical care monitoring and provide guidance for patient-tailored treatment. With approaches such as this, neurosurgeons and neurologists can study brain activity in acute TBI and obtain insights regarding injury effects upon brain metabolism and clinical outcome. Published by Elsevier B.V.
Wei, Ling; Li, Yingjie; Yang, Xiaoli; Xue, Qing; Wang, Yuping
2015-10-01
The present study evaluated the topological properties of whole brain networks using graph theoretical concepts and investigated the time-evolution characteristic of brain network in mild cognitive impairment patients during a selective attention task. Electroencephalography (EEG) activities were recorded in 10 MCI patients and 17 healthy subjects when they performed a color match task. We calculated the phase synchrony index between each possible pairs of EEG channels in alpha and beta frequency bands and analyzed the local interconnectedness, overall connectedness and small-world characteristic of brain network in different degree for two groups. Relative to healthy normal controls, the properties of cortical networks in MCI patients tend to be a shift of randomization. Lower σ of MCI had suggested that patients had a further loss of small-world attribute both during active and resting states. Our results provide evidence for the functional disconnection of brain regions in MCI. Furthermore, we found the properties of cortical networks could reflect the processing of conflict information in the selective attention task. The human brain tends to be a more regular and efficient neural architecture in the late stage of information processing. In addition, the processing of conflict information needs stronger information integration and transfer between cortical areas. Copyright © 2015 Elsevier B.V. All rights reserved.
Functional Imaging of Sleep Vertex Sharp Transients
Stern, John M.; Caporro, Matteo; Haneef, Zulfi; Yeh, Hsiang J.; Buttinelli, Carla; Lenartowicz, Agatha; Mumford, Jeanette A.; Parvizi, Josef; Poldrack, Russell A.
2011-01-01
Objective The vertex sharp transient (VST) is an electroencephalographic (EEG) discharge that is an early marker of non-REM sleep. It has been recognized since the beginning of sleep physiology research, but its source and function remain mostly unexplained. We investigated VST generation using functional MRI (fMRI). Methods Simultaneous EEG and fMRI were recorded from 7 individuals in drowsiness and light sleep. VST occurrences on EEG were modeled with fMRI using an impulse function convolved with a hemodynamic response function to identify cerebral regions correlating to the VSTs. A resulting statistical image was thresholded at Z>2.3. Results Two hundred VSTs were identified. Significantly increased signal was present bilaterally in medial central, lateral precentral, posterior superior temporal, and medial occipital cortex. No regions of decreased signal were present. Conclusion The regions are consistent with electrophysiologic evidence from animal models and functional imaging of human sleep, but the results are specific to VSTs. The regions principally encompass the primary sensorimotor cortical regions for vision, hearing, and touch. Significance The results depict a network comprising the presumed VST generator and its associated regions. The associated regions functional similarity for primary sensation suggests a role for VSTs in sensory experience during sleep. PMID:21310653
Psychogenic seizures and frontal disconnection: EEG synchronisation study.
Knyazeva, Maria G; Jalili, Mahdi; Frackowiak, Richard S; Rossetti, Andrea O
2011-05-01
Psychogenic non-epileptic seizures (PNES) are paroxysmal events that, in contrast to epileptic seizures, are related to psychological causes without the presence of epileptiform EEG changes. Recent models suggest a multifactorial basis for PNES. A potentially paramount, but currently poorly understood factor is the interplay between psychiatric features and a specific vulnerability of the brain leading to a clinical picture that resembles epilepsy. Hypothesising that functional cerebral network abnormalities may predispose to the clinical phenotype, the authors undertook a characterisation of the functional connectivity in PNES patients. The authors analysed the whole-head surface topography of multivariate phase synchronisation (MPS) in interictal high-density EEG of 13 PNES patients as compared with 13 age- and sex-matched controls. MPS mapping reduces the wealth of dynamic data obtained from high-density EEG to easily readable synchronisation maps, which provide an unbiased overview of any changes in functional connectivity associated with distributed cortical abnormalities. The authors computed MPS maps for both Laplacian and common-average-reference EEGs. In a between-group comparison, only patchy, non-uniform changes in MPS survived conservative statistical testing. However, against the background of these unimpressive group results, the authors found widespread inverse correlations between individual PNES frequency and MPS within the prefrontal and parietal cortices. PNES appears to be associated with decreased prefrontal and parietal synchronisation, possibly reflecting dysfunction of networks within these regions.
Sankari, Ziad; Adeli, Hojjat
2011-04-15
Recently, the authors presented an EEG (electroencephalogram) coherence study of the Alzheimer's disease (AD) and found statistically significant differences between AD and control groups. In this paper a probabilistic neural network (PNN) model is presented for classification of AD and healthy controls using features extracted in coherence and wavelet coherence studies on cortical connectivity in AD. The model is verified using EEGs obtained from 20 AD probable patients and 7 healthy/control subjects based on a standard 10-20 electrode configuration on the scalp. It is shown that extracting features from EEG sub-bands using coherence, as a measure of cortical connectivity, can discriminate AD patients from healthy controls effectively when a mixed band classification model is applied. For the data set used a classification accuracy of 100% is achieved using the conventional coherence and a spread parameter of the Gaussian function in a particular range found in this research. Copyright © 2011 Elsevier B.V. All rights reserved.
Mangia, Anna L.; Pirini, Marco; Cappello, Angelo
2014-01-01
Transcranial direct current stimulation (tDCS) delivers low electric currents to the brain through the scalp. Constant electric currents induce shifts in neuronal membrane excitability, resulting in secondary changes in cortical activity. Concomitant electroencephalography (EEG) monitoring during tDCS can provide valuable information on the tDCS mechanisms of action. This study examined the effects of anodal tDCS on spontaneous cortical activity in a resting brain to disclose possible modulation of spontaneous oscillatory brain activity. EEG activity was measured in ten healthy subjects during and after a session of anodal stimulation of the postero-parietal cortex to detect the tDCS-induced alterations. Changes in the theta, alpha, beta, and gamma power bands were investigated. Three main findings emerged: (1) an increase in theta band activity during the first minutes of stimulation; (2) an increase in alpha and beta power during and after stimulation; (3) a widespread activation in several brain regions. PMID:25147519
Yang, Ping; Fan, Chenggui; Wang, Min; Li, Ling
2017-01-01
In simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) studies, average reference (AR), and digitally linked mastoid (LM) are popular re-referencing techniques in event-related potential (ERP) analyses. However, they may introduce their own physiological signals and alter the EEG/ERP outcome. A reference electrode standardization technique (REST) that calculated a reference point at infinity was proposed to solve this problem. To confirm the advantage of REST in ERP analyses of synchronous EEG-fMRI studies, we compared the reference effect of AR, LM, and REST on task-related ERP results of a working memory task during an fMRI scan. As we hypothesized, we found that the adopted reference did not change the topography map of ERP components (N1 and P300 in the present study), but it did alter the task-related effect on ERP components. LM decreased or eliminated the visual working memory (VWM) load effect on P300, and the AR distorted the distribution of VWM location-related effect at left posterior electrodes as shown in the statistical parametric scalp mapping (SPSM) of N1. ERP cortical source estimates, which are independent of the EEG reference choice, were used as the golden standard to infer the relative utility of different references on the ERP task-related effect. By comparison, REST reference provided a more integrated and reasonable result. These results were further confirmed by the results of fMRI activations and a corresponding EEG-only study. Thus, we recommend the REST, especially with a realistic head model, as the optimal reference method for ERP data analysis in simultaneous EEG-fMRI studies. PMID:28529472
Mathewson, Kyle E.; Beck, Diane M.; Ro, Tony; Maclin, Edward L.; Low, Kathy A.; Fabiani, Monica; Gratton, Gabriele
2015-01-01
We investigated the dynamics of brain processes facilitating conscious experience of external stimuli. Previously we proposed that alpha (8-12 Hz) oscillations, which fluctuate with both sustained and directed attention, represent a pulsed inhibition of ongoing sensory brain activity. Here we tested the prediction that inhibitory alpha oscillations in visual cortex are modulated by top-down signals from frontoparietal attention networks. We measured modulations in phase-coherent alpha oscillations from superficial frontal, parietal, and occipital cortices using the event-related optical signal (EROS), a measure of neuronal activity affording high spatiotemporal resolution, along with concurrently-recorded electroencephalogram (EEG), while subjects performed a visual target-detection task. The pre-target alpha oscillations measured with EEG and EROS from posterior areas were larger for subsequently undetected targets, supporting alpha's inhibitory role. Using EROS, we localized brain correlates of these awareness-related alpha oscillations measured at the scalp to the cuneus and precuneus. Crucially, EROS alpha suppression correlated with posterior EEG alpha power across subjects. Sorting the EROS data based on EEG alpha power quartiles to investigate alpha modulators revealed that suppression of posterior alpha was preceded by increased activity in regions of the dorsal attention network, and decreased activity in regions of the cingulo-opercular network. Cross-correlations revealed the temporal dynamics of activity within these preparatory networks prior to posterior alpha modulation. The novel combination of EEG and EROS afforded localization of the sources and correlates of alpha oscillations and their temporal relationships, supporting our proposal that top-down control from attention networks modulates both posterior alpha and awareness of visual stimuli. PMID:24702458
Yang, Ping; Fan, Chenggui; Wang, Min; Li, Ling
2017-01-01
In simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) studies, average reference (AR), and digitally linked mastoid (LM) are popular re-referencing techniques in event-related potential (ERP) analyses. However, they may introduce their own physiological signals and alter the EEG/ERP outcome. A reference electrode standardization technique (REST) that calculated a reference point at infinity was proposed to solve this problem. To confirm the advantage of REST in ERP analyses of synchronous EEG-fMRI studies, we compared the reference effect of AR, LM, and REST on task-related ERP results of a working memory task during an fMRI scan. As we hypothesized, we found that the adopted reference did not change the topography map of ERP components (N1 and P300 in the present study), but it did alter the task-related effect on ERP components. LM decreased or eliminated the visual working memory (VWM) load effect on P300, and the AR distorted the distribution of VWM location-related effect at left posterior electrodes as shown in the statistical parametric scalp mapping (SPSM) of N1. ERP cortical source estimates, which are independent of the EEG reference choice, were used as the golden standard to infer the relative utility of different references on the ERP task-related effect. By comparison, REST reference provided a more integrated and reasonable result. These results were further confirmed by the results of fMRI activations and a corresponding EEG-only study. Thus, we recommend the REST, especially with a realistic head model, as the optimal reference method for ERP data analysis in simultaneous EEG-fMRI studies.
Cassani, Raymundo; Falk, Tiago H.; Fraga, Francisco J.; Kanda, Paulo A. M.; Anghinah, Renato
2014-01-01
Over the last decade, electroencephalography (EEG) has emerged as a reliable tool for the diagnosis of cortical disorders such as Alzheimer's disease (AD). EEG signals, however, are susceptible to several artifacts, such as ocular, muscular, movement, and environmental. To overcome this limitation, existing diagnostic systems commonly depend on experienced clinicians to manually select artifact-free epochs from the collected multi-channel EEG data. Manual selection, however, is a tedious and time-consuming process, rendering the diagnostic system “semi-automated.” Notwithstanding, a number of EEG artifact removal algorithms have been proposed in the literature. The (dis)advantages of using such algorithms in automated AD diagnostic systems, however, have not been documented; this paper aims to fill this gap. Here, we investigate the effects of three state-of-the-art automated artifact removal (AAR) algorithms (both alone and in combination with each other) on AD diagnostic systems based on four different classes of EEG features, namely, spectral, amplitude modulation rate of change, coherence, and phase. The three AAR algorithms tested are statistical artifact rejection (SAR), blind source separation based on second order blind identification and canonical correlation analysis (BSS-SOBI-CCA), and wavelet enhanced independent component analysis (wICA). Experimental results based on 20-channel resting-awake EEG data collected from 59 participants (20 patients with mild AD, 15 with moderate-to-severe AD, and 24 age-matched healthy controls) showed the wICA algorithm alone outperforming other enhancement algorithm combinations across three tasks: diagnosis (control vs. mild vs. moderate), early detection (control vs. mild), and disease progression (mild vs. moderate), thus opening the doors for fully-automated systems that can assist clinicians with early detection of AD, as well as disease severity progression assessment. PMID:24723886
Gorgoni, Maurizio; Ferlazzo, Fabio; Moroni, Fabio; D'Atri, Aurora; Donarelli, Stefania; Fanelli, Stefania; Gizzi Torriglia, Isabella; Lauri, Giulia; Ferrara, Michele; Marzano, Cristina; Rossini, Paolo Maria; Bramanti, Placido; De Gennaro, Luigi
2014-01-01
Changes of cortical excitability after sleep deprivation (SD) in humans have been investigated mostly in motor cortex, while there is little empirical evidence concerning somatosensory cortex, and its plastic changes across SD. To assess excitability of primary somatosensory cortex (S1) and EEG voltage topographical characteristics associated with somatosensory evoked potentials (SEPs) during SD. Across 41 h of SD, 16 healthy subjects participated in 4 experimental sessions (11.00 a.m. and 11.00 p.m. of the 1st and 2nd day) with: a) subjective sleepiness ratings; b) EEG recordings; c) SEPs recordings; d) behavioral vigilance responses. A clear enhancement of cortical excitability after SD was indexed by: (a) an amplitude increase of different SEPs component in S1; (b) higher voltage in occipital (around 35-43 ms) and fronto-central areas (around 47-62 ms). Circadian fluctuations did not affect cortical excitability. Voltage changes in S1 were strongly related with post-SD fluctuations of subjective and behavioral sleepiness. Sleep may have a role in keeping cortical excitability at optimal (namely below potentially dangerous) levels for the human brain, rebalancing progressive changes in cortical responsiveness to incoming inputs occurred during time spent awake. On the other hand, higher level of cortical responsiveness after sleep loss may be one of the mechanisms accounting for post-SD alterations in vigilance and behavior. Copyright © 2014 Elsevier Inc. All rights reserved.
Sleep EEG Provides Evidence that Cortical Changes Persist into Late Adolescence
Tarokh, Leila; Van Reen, Eliza; LeBourgeois, Monique; Seifer, Ronald; Carskadon, Mary A.
2011-01-01
Study Objectives: To examine developmental changes in the human sleep electroencephalogram (EEG) during late adolescence. Setting: A 4-bed sleep laboratory. Participants: Fourteen adolescents (5 boys) were studied at ages 15 or 16 (initial) and again at ages 17 to 19 (follow-up). Interventions: N/A Measurements and Results: All-night polysomnography was recorded at each assessment and scored according to the criteria of Rechtschaffen and Kales. A 27% decline in duration of slow wave sleep, and a 22% increase of stage 2 sleep was observed from the initial to the follow-up session. All-night spectral analysis of 2 central and 2 occipital leads revealed a significant decline of NREM and REM sleep EEG power with increasing age across frequencies in both states. Time-frequency analysis revealed that the decline in power was consistent across the night for all bands except the delta band. The decreases in power were most pronounced over the left central (C3/A2) and right occipital (O2/A1) derivations. Conclusions: Using longitudinal data, we show that the developmental changes to the sleeping EEG that begin in early adolescence continue into late adolescence. As with early adolescents, we observed hemispheric asymmetry in the decline of sleep EEG power. This decline was state and frequency nonspecific, suggesting that it may be due to the pruning of synapses known to occur during adolescence. Citation: Tarokh L; Van Reen E; LeBourgeois M; Seifer R; Carskadon MA. Sleep EEG provides evidence that cortical changes persist into late adolescence. SLEEP 2011;34(10):1385–1393. PMID:21966070
Dykstra, Andrew R.; Halgren, Eric; Thesen, Thomas; Carlson, Chad E.; Doyle, Werner; Madsen, Joseph R.; Eskandar, Emad N.; Cash, Sydney S.
2011-01-01
The auditory system must constantly decompose the complex mixture of sound arriving at the ear into perceptually independent streams constituting accurate representations of individual sources in the acoustic environment. How the brain accomplishes this task is not well understood. The present study combined a classic behavioral paradigm with direct cortical recordings from neurosurgical patients with epilepsy in order to further describe the neural correlates of auditory streaming. Participants listened to sequences of pure tones alternating in frequency and indicated whether they heard one or two “streams.” The intracranial EEG was simultaneously recorded from sub-dural electrodes placed over temporal, frontal, and parietal cortex. Like healthy subjects, patients heard one stream when the frequency separation between tones was small and two when it was large. Robust evoked-potential correlates of frequency separation were observed over widespread brain areas. Waveform morphology was highly variable across individual electrode sites both within and across gross brain regions. Surprisingly, few evoked-potential correlates of perceptual organization were observed after controlling for physical stimulus differences. The results indicate that the cortical areas engaged during the streaming task are more complex and widespread than has been demonstrated by previous work, and that, by-and-large, correlates of bistability during streaming are probably located on a spatial scale not assessed – or in a brain area not examined – by the present study. PMID:21886615
Vecchiato, Giovanni; Astolfi, Laura; Tabarrini, Alessandro; Salinari, Serenella; Mattia, Donatella; Cincotti, Febo; Bianchi, Luigi; Sorrentino, Domenica; Aloise, Fabio; Soranzo, Ramon; Babiloni, Fabio
2010-01-01
The use of modern brain imaging techniques could be useful to understand what brain areas are involved in the observation of video clips related to commercial advertising, as well as for the support of political campaigns, and also the areas of Public Service Announcements (PSAs). In this paper we describe the capability of tracking brain activity during the observation of commercials, political spots, and PSAs with advanced high-resolution EEG statistical techniques in time and frequency domains in a group of normal subjects. We analyzed the statistically significant cortical spectral power activity in different frequency bands during the observation of a commercial video clip related to the use of a beer in a group of 13 normal subjects. In addition, a TV speech of the Prime Minister of Italy was analyzed in two groups of swing and "supporter" voters. Results suggested that the cortical activity during the observation of commercial spots could vary consistently across the spot. This fact suggest the possibility to remove the parts of the spot that are not particularly attractive by using those cerebral indexes. The cortical activity during the observation of the political speech indicated a major cortical activity in the supporters group when compared to the swing voters. In this case, it is possible to conclude that the communication proposed has failed to raise attention or interest on swing voters. In conclusions, high-resolution EEG statistical techniques have been proved to able to generate useful insights about the particular fruition of TV messages, related to both commercial as well as political fields.
Vecchiato, Giovanni; Astolfi, Laura; Tabarrini, Alessandro; Salinari, Serenella; Mattia, Donatella; Cincotti, Febo; Bianchi, Luigi; Sorrentino, Domenica; Aloise, Fabio; Soranzo, Ramon; Babiloni, Fabio
2010-01-01
The use of modern brain imaging techniques could be useful to understand what brain areas are involved in the observation of video clips related to commercial advertising, as well as for the support of political campaigns, and also the areas of Public Service Announcements (PSAs). In this paper we describe the capability of tracking brain activity during the observation of commercials, political spots, and PSAs with advanced high-resolution EEG statistical techniques in time and frequency domains in a group of normal subjects. We analyzed the statistically significant cortical spectral power activity in different frequency bands during the observation of a commercial video clip related to the use of a beer in a group of 13 normal subjects. In addition, a TV speech of the Prime Minister of Italy was analyzed in two groups of swing and “supporter” voters. Results suggested that the cortical activity during the observation of commercial spots could vary consistently across the spot. This fact suggest the possibility to remove the parts of the spot that are not particularly attractive by using those cerebral indexes. The cortical activity during the observation of the political speech indicated a major cortical activity in the supporters group when compared to the swing voters. In this case, it is possible to conclude that the communication proposed has failed to raise attention or interest on swing voters. In conclusions, high-resolution EEG statistical techniques have been proved to able to generate useful insights about the particular fruition of TV messages, related to both commercial as well as political fields. PMID:20069055
Oscillatory EEG signatures of postponed somatosensory decisions.
Ludwig, Simon; Herding, Jan; Blankenburg, Felix
2018-05-02
In recent electroencephalography (EEG) studies, the vibrotactile frequency comparison task has been used to study oscillatory signatures of perceptual decision making in humans, revealing a choice-selective modulation of premotor upper beta band power shortly before decisions were reported. Importantly, these studies focused on decisions that were (1) indicated immediately after stimulus presentation, and (2) for which a direct motor mapping was provided. Here, we investigated whether the putative beta band choice signal also extends to postponed decisions, and how such a decision signal might be influenced by a response mapping that is dissociated from a specific motor command. We recorded EEG data in two separate experiments, both employing the vibrotactile frequency comparison task with delayed decision reports. In the first experiment, delayed choices were associated with a fixed motor mapping, whereas in the second experiment, choices were mapped onto a color code concealing a specific motor response until the end of the delay phase. In between stimulus presentations, as well as after the second stimulus, prefrontal beta band power indexed stimulus information held in working memory. Beta band power also encoded choices during the response delay, notably, in different cortical areas depending on the provided response mapping. In particular, when decisions were associated with a specific motor mapping, choices were represented in premotor cortices, whereas the color mapping resulted in a choice-selective modulation of beta band power in parietal cortices. Together, our findings imply that how a choice is expressed (i.e., the decision consequence) determines where in the cortical sensorimotor hierarchy an according decision signal is processed. © 2018 Wiley Periodicals, Inc.
EEG Spectral Generators Involved in Motor Imagery: A swLORETA Study
Cebolla, Ana-Maria; Palmero-Soler, Ernesto; Leroy, Axelle; Cheron, Guy
2017-01-01
In order to characterize the neural generators of the brain oscillations related to motor imagery (MI), we investigated the cortical, subcortical, and cerebellar localizations of their respective electroencephalogram (EEG) spectral power and phase locking modulations. The MI task consisted in throwing a ball with the dominant upper limb while in a standing posture, within an ecological virtual reality (VR) environment (tennis court). The MI was triggered by the visual cues common to the control condition, during which the participant remained mentally passive. As previously developed, our paradigm considers the confounding problem that the reference condition allows two complementary analyses: one which uses the baseline before the occurrence of the visual cues in the MI and control resting conditions respectively; and the other which compares the analog periods between the MI and the control resting-state conditions. We demonstrate that MI activates specific, complex brain networks for the power and phase modulations of the EEG oscillations. An early (225 ms) delta phase-locking related to MI was generated in the thalamus and cerebellum and was followed (480 ms) by phase-locking in theta and alpha oscillations, generated in specific cortical areas and the cerebellum. Phase-locking preceded the power modulations (mainly alpha–beta ERD), whose cortical generators were situated in the frontal BA45, BA11, BA10, central BA6, lateral BA13, and posterior cortex BA2. Cerebellar-thalamic involvement through phase-locking is discussed as an underlying mechanism for recruiting at later stages the cortical areas involved in a cognitive role during MI. PMID:29312028
Nayak, Chetan S; Mariyappa, N; Majumdar, Kaushik K; Prasad, Pradeep D; Ravi, G S; Nagappa, M; Kandavel, Thennarasu; Taly, Arun B; Sinha, Sanjib
2018-05-01
Excessive cortical synchrony within neural ensembles has been implicated as an important mechanism driving epileptiform activity. The current study measures and compares background electroencephalographic (EEG) phase synchronization in patients having various types of epilepsies and healthy controls during awake and sleep stages. A total of 120 patients with epilepsy (PWE) subdivided into 3 groups (juvenile myoclonic epilepsy [JME], temporal lobe epilepsy [TLE], and extra-temporal lobe epilepsy [Ex-TLE]; n = 40 in each group) and 40 healthy controls were subjected to overnight polysomnography. EEG phase synchronization (SI) between the 8 EEG channels was assessed for delta, theta, alpha, sigma, and high beta frequency bands using ensemble measure on 10-second representative time windows and compared between patients and controls and also between awake and sleep stages. Mean ± SD of SI was compared using 2-way analysis of variance followed by pairwise comparison ( P ≤ .05). In both delta and theta bands, the SI was significantly higher in patients with JME, TLE, and Ex-TLE compared with controls, whereas in alpha, sigma, and high beta bands, SI was comparable between the groups. On comparison of SI between sleep stages, delta band: progressive increase in SI from wake ⇒ N1 ⇒ N2 ⇒ N3, whereas REM (rapid eye movement) was comparable to wake; theta band: decreased SI during N2 and increase during N3; alpha band: SI was highest in wake and lower in N1, N2, N3, and REM; and sigma and high beta bands: progressive increase in SI from wake ⇒ N1 ⇒ N2 ⇒ N3; however, sigma band showed lower SI during REM. This study found an increased background cortical synchronization in PWE compared with healthy controls in delta and theta bands during wake and sleep. This background hypersynchrony may be an important property of epileptogenic brain circuitry in PWE, which enables them to effortlessly generate a paroxysmal EEG depolarization shift.
Wang, Hui; Tan, Shengzhi; Xu, Xinping; Zhao, Li; Zhang, Jing; Yao, Binwei; Gao, Yabing; Zhou, Hongmei; Peng, Ruiyun
2017-11-01
The long term effects of continuous microwave exposure cannot be ignored for the simulation of the real environment and increasing concerns about the negative cognitive effects of microwave exposure. In this study, 220 male Wistar rats were exposed by a 2.856GHz radiation source with the average power density of 0, 2.5, 5 and 10mW/cm 2 for 6min/day, 5days/week and up to 6weeks. The MWM task, the EEG analysis, the hippocampus structure observation and the western blot were applied until the 12months after microwave exposure to detect the spatial learning and memory abilities, the cortical electrical activity, changes of hippocampal structure and the NMDAR subunits expressions. Results found that the rats in the 10mW/cm 2 group showed the decline of spatial learning and memory abilities and EEG disorders (the decrease of EEG frequencies, and increase of EEG amplitudes and delta wave powers). Moreover, changes of basic structure and ultrastructure of hippocampus also found in the 10 and 5mW/cm 2 groups. The decrease of NR 2A, 2B and p-NR2B might contribute to the impairment of cognitive functions. Our findings suggested that the continuous microwave exposure could cause the dose-dependent long term impairment of spatial learning and memory, the abnormalities of EEG and the hippocampal structure injuries. The decrease of NMDAR key subunits and phosphorylation of NR 2B might contribute to the cognitive impairment. Copyright © 2017 Elsevier Inc. All rights reserved.
Tenke, Craig E.; Kayser, Jürgen
2012-01-01
The topographic ambiguity and reference-dependency that has plagued EEG/ERP research throughout its history are largely attributable to volume conduction, which may be concisely described by a vector form of Ohm’s Law. This biophysical relationship is common to popular algorithms that infer neuronal generators via inverse solutions. It may be further simplified as Poisson’s source equation, which identifies underlying current generators from estimates of the second spatial derivative of the field potential (Laplacian transformation). Intracranial current source density (CSD) studies have dissected the “cortical dipole” into intracortical sources and sinks, corresponding to physiologically-meaningful patterns of neuronal activity at a sublaminar resolution, much of which is locally cancelled (i.e., closed field). By virtue of the macroscopic scale of the scalp-recorded EEG, a surface Laplacian reflects the radial projections of these underlying currents, representing a unique, unambiguous measure of neuronal activity at scalp. Although the surface Laplacian requires minimal assumptions compared to complex, model-sensitive inverses, the resulting waveform topographies faithfully summarize and simplify essential constraints that must be placed on putative generators of a scalp potential topography, even if they arise from deep or partially-closed fields. CSD methods thereby provide a global empirical and biophysical context for generator localization, spanning scales from intracortical to scalp recordings. PMID:22796039
Electroencephalographic imaging of higher brain function
NASA Technical Reports Server (NTRS)
Gevins, A.; Smith, M. E.; McEvoy, L. K.; Leong, H.; Le, J.
1999-01-01
High temporal resolution is necessary to resolve the rapidly changing patterns of brain activity that underlie mental function. Electroencephalography (EEG) provides temporal resolution in the millisecond range. However, traditional EEG technology and practice provide insufficient spatial detail to identify relationships between brain electrical events and structures and functions visualized by magnetic resonance imaging or positron emission tomography. Recent advances help to overcome this problem by recording EEGs from more electrodes, by registering EEG data with anatomical images, and by correcting the distortion caused by volume conduction of EEG signals through the skull and scalp. In addition, statistical measurements of sub-second interdependences between EEG time-series recorded from different locations can help to generate hypotheses about the instantaneous functional networks that form between different cortical regions during perception, thought and action. Example applications are presented from studies of language, attention and working memory. Along with its unique ability to monitor brain function as people perform everyday activities in the real world, these advances make modern EEG an invaluable complement to other functional neuroimaging modalities.
NASA Astrophysics Data System (ADS)
Valderrama, Joaquin T.; de la Torre, Angel; Van Dun, Bram
2018-02-01
Objective. Artifact reduction in electroencephalogram (EEG) signals is usually necessary to carry out data analysis appropriately. Despite the large amount of denoising techniques available with a multichannel setup, there is a lack of efficient algorithms that remove (not only detect) blink-artifacts from a single channel EEG, which is of interest in many clinical and research applications. This paper describes and evaluates the iterative template matching and suppression (ITMS), a new method proposed for detecting and suppressing the artifact associated with the blink activity from a single channel EEG. Approach. The approach of ITMS consists of (a) an iterative process in which blink-events are detected and the blink-artifact waveform of the analyzed subject is estimated, (b) generation of a signal modeling the blink-artifact, and (c) suppression of this signal from the raw EEG. The performance of ITMS is compared with the multi-window summation of derivatives within a window (MSDW) technique using both synthesized and real EEG data. Main results. Results suggest that ITMS presents an adequate performance in detecting and suppressing blink-artifacts from a single channel EEG. When applied to the analysis of cortical auditory evoked potentials (CAEPs), ITMS provides a significant quality improvement in the resulting responses, i.e. in a cohort of 30 adults, the mean correlation coefficient improved from 0.37 to 0.65 when the blink-artifacts were detected and suppressed by ITMS. Significance. ITMS is an efficient solution to the problem of denoising blink-artifacts in single-channel EEG applications, both in clinical and research fields. The proposed ITMS algorithm is stable; automatic, since it does not require human intervention; low-invasive, because the EEG segments not contaminated by blink-artifacts remain unaltered; and easy to implement, as can be observed in the Matlab script implemeting the algorithm provided as supporting material.
Modulation of the COMT Val(158)Met polymorphism on resting-state EEG power.
Solís-Ortiz, Silvia; Pérez-Luque, Elva; Gutiérrez-Muñoz, Mayra
2015-01-01
The catechol-O-methyltransferase (COMT) Val(158)Met polymorphism impacts cortical dopamine (DA) levels and may influence cortical electrical activity in the human brain. This study investigated whether COMT genotype influences resting-state electroencephalogram (EEG) power in the frontal, parietal and midline regions in healthy volunteers. EEG recordings were conducted in the resting-state in 13 postmenopausal healthy woman carriers of the Val/Val genotype and 11 with the Met/Met genotype. The resting EEG spectral absolute power in the frontal (F3, F4, F7, F8, FC3 and FC4), parietal (CP3, CP4, P3 and P4) and midline (Fz, FCz, Cz, CPz, Pz and Oz) was analyzed during the eyes-open and eyes-closed conditions. The frequency bands considered were the delta, theta, alpha1, alpha2, beta1 and beta2. EEG data of the Val/Val and Met/Met genotypes, brain regions and conditions were analyzed using a general linear model analysis. In the individuals with the Met/Met genotype, delta activity was increased in the eyes-closed condition, theta activity was increased in the eyes-closed and in the eyes-open conditions, and alpha1 band, alpha2 band and beta1band activity was increased in the eyes-closed condition. A significant interaction between COMT genotypes and spectral bands was observed. Met homozygote individuals exhibited more delta, theta and beta1 activity than individuals with the Val/Val genotype. No significant interaction between COMT genotypes and the resting-state EEG regional power and conditions were observed for the three brain regions studied. Our findings indicate that the COMT Val(158)Met polymorphism does not directly impact resting-state EEG regional power, but instead suggest that COMT genotype can modulate resting-state EEG spectral power in postmenopausal healthy women.
Modulation of the COMT Val158Met polymorphism on resting-state EEG power
Solís-Ortiz, Silvia; Pérez-Luque, Elva; Gutiérrez-Muñoz, Mayra
2015-01-01
The catechol-O-methyltransferase (COMT) Val158Met polymorphism impacts cortical dopamine (DA) levels and may influence cortical electrical activity in the human brain. This study investigated whether COMT genotype influences resting-state electroencephalogram (EEG) power in the frontal, parietal and midline regions in healthy volunteers. EEG recordings were conducted in the resting-state in 13 postmenopausal healthy woman carriers of the Val/Val genotype and 11 with the Met/Met genotype. The resting EEG spectral absolute power in the frontal (F3, F4, F7, F8, FC3 and FC4), parietal (CP3, CP4, P3 and P4) and midline (Fz, FCz, Cz, CPz, Pz and Oz) was analyzed during the eyes-open and eyes-closed conditions. The frequency bands considered were the delta, theta, alpha1, alpha2, beta1 and beta2. EEG data of the Val/Val and Met/Met genotypes, brain regions and conditions were analyzed using a general linear model analysis. In the individuals with the Met/Met genotype, delta activity was increased in the eyes-closed condition, theta activity was increased in the eyes-closed and in the eyes-open conditions, and alpha1 band, alpha2 band and beta1band activity was increased in the eyes-closed condition. A significant interaction between COMT genotypes and spectral bands was observed. Met homozygote individuals exhibited more delta, theta and beta1 activity than individuals with the Val/Val genotype. No significant interaction between COMT genotypes and the resting-state EEG regional power and conditions were observed for the three brain regions studied. Our findings indicate that the COMT Val158Met polymorphism does not directly impact resting-state EEG regional power, but instead suggest that COMT genotype can modulate resting-state EEG spectral power in postmenopausal healthy women. PMID:25883560
Manoochehri, Mana; Mahmoudzadeh, Mahdi; Bourel-Ponchel, Emilie; Wallois, Fabrice
2017-12-01
Interictal epileptic spikes (IES) represent a signature of the transient synchronous and excessive discharge of a large ensemble of cortical heterogeneous neurons. Epilepsy cannot be reduced to a hypersynchronous activation of neurons whose functioning is impaired, resulting on electroencephalogram (EEG) in epileptic seizures or IES. The complex pathophysiological mechanisms require a global approach to the interactions between neural synaptic and nonsynaptic, vascular, and metabolic systems. In the present study, we focused on the interaction between synaptic and nonsynaptic mechanisms through the simultaneous noninvasive multimodal multiscale recording of high-density EEG (HD-EEG; synaptic) and fast optical signal (FOS; nonsynaptic), which evaluate rapid changes in light scattering related to changes in membrane configuration occurring during neuronal activation of IES. To evaluate changes in light scattering occurring around IES, three children with frontal IES were simultaneously recorded with HD-EEG and FOS. To evaluate change in synchronization, time-frequency representation analysis of the HD-EEG was performed simultaneously around the IES. To independently evaluate our multimodal method, a control experiment with somatosensory stimuli was designed and applied to five healthy volunteers. Alternating increase-decrease-increase in optical signals occurred 200 ms before to 180 ms after the IES peak. These changes started before any changes in EEG signal. In addition, time-frequency domain EEG analysis revealed alternating decrease-increase-decrease in the EEG spectral power concomitantly with changes in the optical signal during IES. These results suggest a relationship between (de)synchronization and neuronal volume changes in frontal lobe epilepsy during IES. These changes in the neuronal environment around IES in frontal lobe epilepsy observed in children, as they have been in rats, raise new questions about the synaptic/nonsynaptic mechanisms that propel the neurons to hypersynchronization, as occurs during IES. We further demonstrate that this noninvasive multiscale multimodal approach is suitable for studying the pathophysiology of the IES in patients. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.
Bozkurt, Gokhan; Ayhan, Selim; Dericioglu, Nese; Saygi, Serap; Akalan, Nejat
2010-08-01
The potential complications of the subdural electrode implantation providing identification of the seizure focus and direct stimulation of the cerebral cortex for defining the eloquent cortical areas are epidural and subdural hematoma, cortical contusions, infection, brain edema, raised intracranial pressure, CSF leakage, and venous infarction have been previously reported in the literature. To present the first case of subelectrode hematoma without subdural component that was detected during invasive EEG monitoring after subdural electrode implantation. A 19-year-old female with drug resistant seizures was decided to undergo invasive monitoring with subdural electrodes. While good quality recordings had been initially obtained from all electrodes placed on the right parietal convexity, no cerebral cortical activity could be obtained from one electrode 2 days after the first operation. Explorative surgery revealed a circumscribed subelectrode hematoma without a subdural component. Awareness of the potential complications of subdural electrode implantation and close follow-up of the clinical findings of the patient are of highest value for early detection and successful management.
Verbeke, Willem J. M. I.; Pozharliev, Rumen; Van Strien, Jan W.; Belschak, Frank; Bagozzi, Richard P.
2014-01-01
We took EEG recordings to measure task-free resting-state cortical brain activity in 35 participants under two conditions, alone (A) or together (T). We also investigated whether psychological attachment styles shape human cortical activity differently in these two settings. The results indicate that social context matters and that participants' cortical activity is moderated by the anxious, but not avoidant attachment style. We found enhanced alpha, beta and theta band activity in the T rather than the A resting-state condition, which was more pronounced in posterior brain regions. We further found a positive correlation between anxious attachment style and enhanced alpha power in the T vs. A condition over frontal and parietal scalp regions. There was no significant correlation between the absolute powers registered in the other two frequency bands and the participants' anxious attachment style. PMID:25071516
Impaired brainstem and thalamic high-frequency oscillatory EEG activity in migraine between attacks.
Porcaro, Camillo; Di Lorenzo, Giorgio; Seri, Stefano; Pierelli, Francesco; Tecchio, Franca; Coppola, Gianluca
2017-09-01
Introduction We investigated whether interictal thalamic dysfunction in migraine without aura (MO) patients is a primary determinant or the expression of its functional disconnection from proximal or distal areas along the somatosensory pathway. Methods Twenty MO patients and twenty healthy volunteers (HVs) underwent an electroencephalographic (EEG) recording during electrical stimulation of the median nerve at the wrist. We used the functional source separation algorithm to extract four functionally constrained nodes (brainstem, thalamus, primary sensory radial, and primary sensory motor tangential parietal sources) along the somatosensory pathway. Two digital filters (1-400 Hz and 450-750 Hz) were applied in order to extract low- (LFO) and high- frequency (HFO) oscillatory activity from the broadband signal. Results Compared to HVs, patients presented significantly lower brainstem (BS) and thalamic (Th) HFO activation bilaterally. No difference between the two cortical HFO as well as in LFO peak activations between the two groups was seen. The age of onset of the headache was positively correlated with HFO power in the right brainstem and thalamus. Conclusions This study provides evidence for complex dysfunction of brainstem and thalamocortical networks under the control of genetic factors that might act by modulating the severity of migraine phenotype.
EEG Source Reconstruction Reveals Frontal-Parietal Dynamics of Spatial Conflict Processing
Cohen, Michael X; Ridderinkhof, K. Richard
2013-01-01
Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (∼200 ms post-stimulus) conflict modulation in stimulus-contralateral parietal gamma (30–50 Hz), followed by a later alpha-band (8–12 Hz) conflict modulation, suggesting an early detection of spatial conflict and inhibition of spatial location processing. Inter-regional connectivity analyses assessed via cross-frequency coupling of theta (4–8 Hz), alpha, and gamma power revealed conflict-induced shifts in cortical network interactions: Congruent trials (relative to incongruent trials) had stronger coupling between frontal theta and stimulus-contrahemifield parietal alpha/gamma power, whereas incongruent trials had increased theta coupling between medial frontal and lateral frontal regions. These findings shed new light into the large-scale network dynamics of spatial conflict processing, and how those networks are shaped by oscillatory interactions. PMID:23451201
Dynamic oscillatory processes governing cued orienting and allocation of auditory attention
Ahveninen, Jyrki; Huang, Samantha; Belliveau, John W.; Chang, Wei-Tang; Hämäläinen, Matti
2013-01-01
In everyday listening situations, we need to constantly switch between alternative sound sources and engage attention according to cues that match our goals and expectations. The exact neuronal bases of these processes are poorly understood. We investigated oscillatory brain networks controlling auditory attention using cortically constrained fMRI-weighted magnetoencephalography/ electroencephalography (MEG/EEG) source estimates. During consecutive trials, subjects were instructed to shift attention based on a cue, presented in the ear where a target was likely to follow. To promote audiospatial attention effects, the targets were embedded in streams of dichotically presented standard tones. Occasionally, an unexpected novel sound occurred opposite to the cued ear, to trigger involuntary orienting. According to our cortical power correlation analyses, increased frontoparietal/temporal 30–100 Hz gamma activity at 200–1400 ms after cued orienting predicted fast and accurate discrimination of subsequent targets. This sustained correlation effect, possibly reflecting voluntary engagement of attention after the initial cue-driven orienting, spread from the temporoparietal junction, anterior insula, and inferior frontal (IFC) cortices to the right frontal eye fields. Engagement of attention to one ear resulted in a significantly stronger increase of 7.5–15 Hz alpha in the ipsilateral than contralateral parieto-occipital cortices 200–600 ms after the cue onset, possibly reflecting crossmodal modulation of the dorsal visual pathway during audiospatial attention. Comparisons of cortical power patterns also revealed significant increases of sustained right medial frontal cortex theta power, right dorsolateral prefrontal cortex and anterior insula/IFC beta power, and medial parietal cortex and posterior cingulate cortex gamma activity after cued vs. novelty-triggered orienting (600–1400 ms). Our results reveal sustained oscillatory patterns associated with voluntary engagement of auditory spatial attention, with the frontoparietal and temporal gamma increases being best predictors of subsequent behavioral performance. PMID:23915050
TMS-EEG: From basic research to clinical applications
NASA Astrophysics Data System (ADS)
Hernandez-Pavon, Julio C.; Sarvas, Jukka; Ilmoniemi, Risto J.
2014-11-01
Transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG) is a powerful technique for non-invasively studying cortical excitability and connectivity. The combination of TMS and EEG has widely been used to perform basic research and recently has gained importance in different clinical applications. In this paper, we will describe the physical and biological principles of TMS-EEG and different applications in basic research and clinical applications. We will present methods based on independent component analysis (ICA) for studying the TMS-evoked EEG responses. These methods have the capability to remove and suppress large artifacts, making it feasible, for instance, to study language areas with TMS-EEG. We will discuss the different applications and limitations of TMS and TMS-EEG in clinical applications. Potential applications of TMS are presented, for instance in neurosurgical planning, depression and other neurological disorders. Advantages and disadvantages of TMS-EEG and its variants such as repetitive TMS (rTMS) are discussed in comparison to other brain stimulation and neuroimaging techniques. Finally, challenges that researchers face when using this technique will be summarized.
2012-01-01
Background Catching an object is a complex movement that involves not only programming but also effective motor coordination. Such behavior is related to the activation and recruitment of cortical regions that participates in the sensorimotor integration process. This study aimed to elucidate the cortical mechanisms involved in anticipatory actions when performing a task of catching an object in free fall. Methods Quantitative electroencephalography (qEEG) was recorded using a 20-channel EEG system in 20 healthy right-handed participants performed the catching ball task. We used the EEG coherence analysis to investigate subdivisions of alpha (8-12 Hz) and beta (12-30 Hz) bands, which are related to cognitive processing and sensory-motor integration. Results Notwithstanding, we found the main effects for the factor block; for alpha-1, coherence decreased from the first to sixth block, and the opposite effect occurred for alpha-2 and beta-2, with coherence increasing along the blocks. Conclusion It was concluded that to perform successfully our task, which involved anticipatory processes (i.e. feedback mechanisms), subjects exhibited a great involvement of sensory-motor and associative areas, possibly due to organization of information to process visuospatial parameters and further catch the falling object. PMID:22364485
Myers, M M; Grieve, P G; Stark, R I; Isler, J R; Hofer, M A; Yang, J; Ludwig, R J; Welch, M G
2015-07-01
To assess the impact of Family Nurture Intervention (FNI) on cortical function in preterm infants at term age. Family Nurture Intervention is a NICU-based intervention designed to establish emotional connection between mothers and preterm infants. Infants born at 26-34 weeks postmenstrual age (PMA) were divided into two groups, standard care (SC, N = 49) and FNI (FNI, N = 56). Infants had EEG recordings of ~one hour duration with 124 lead nets between 37 and 44 weeks PMA. Coherence was measured between all pairs of electrodes in ten frequency bands. Data were summarised both within and between 12 regions during two sleep states (active, quiet). Coherence levels were negatively correlated with PMA age in both groups. As compared to SC infants, FNI infants showed significantly lower levels of EEG coherence (1-18 Hz) largely within and between frontal regions. Coherence in FNI infants was decreased in regions where we previously found robust increases in EEG power. As coherence decreases with age, results suggest that FNI may accelerate brain maturation particularly in frontal brain regions, which have been shown in research by others to be involved in regulation of attention, cognition and emotion regulation; domains deficient in preterm infants. ©2015 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.
Ictal EEG/fMRI study of vertiginous seizures.
Morano, Alessandra; Carnì, Marco; Casciato, Sara; Vaudano, Anna Elisabetta; Fattouch, Jinane; Fanella, Martina; Albini, Mariarita; Basili, Luca Manfredi; Lucignani, Giulia; Scapeccia, Marco; Tomassi, Regina; Di Castro, Elisabetta; Colonnese, Claudio; Giallonardo, Anna Teresa; Di Bonaventura, Carlo
2017-03-01
Vertigo and dizziness are extremely common complaints, related to either peripheral or central nervous system disorders. Among the latter, epilepsy has to be taken into consideration: indeed, vertigo may be part of the initial aura of a focal epileptic seizure in association with other signs/symptoms, or represent the only ictal manifestation, a rare phenomenon known as "vertiginous" or "vestibular" seizure. These ictal symptoms are usually related to a discharge arising from/involving temporal or parietal areas, which are supposed to be a crucial component of the so-called "vestibular cortex". In this paper, we describe three patients suffering from drug-resistant focal epilepsy, symptomatic of malformations of cortical development or perinatal hypoxic/ischemic lesions located in the posterior regions, who presented clusters of vertiginous seizures. The high recurrence rate of such events, recorded during video-EEG monitoring sessions, offered the opportunity to perform an ictal EEG/fMRI study to identify seizure-related hemodynamic changes. The ictal EEG/fMRI revealed the main activation clusters in the temporo-parieto-occipital regions, which are widely recognized to be involved in the processing of vestibular information. Interestingly, ictal deactivation was also detected in the ipsilateral cerebellar hemisphere, suggesting the ictal involvement of cortical-subcortical structures known to be part of the vestibular integration network. Copyright © 2016 Elsevier Inc. All rights reserved.
Brain signatures of moral sensitivity in adolescents with early social deprivation.
Escobar, María Josefina; Huepe, David; Decety, Jean; Sedeño, Lucas; Messow, Marie Kristin; Baez, Sandra; Rivera-Rei, Álvaro; Canales-Johnson, Andrés; Morales, Juan Pablo; Gómez, David Maximiliano; Schröeder, Johannes; Manes, Facundo; López, Vladimir; Ibánez, Agustín
2014-06-19
The present study examined neural responses associated with moral sensitivity in adolescents with a background of early social deprivation. Using high-density electroencephalography (hdEEG), brain activity was measured during an intentional inference task, which assesses rapid moral decision-making regarding intentional or unintentional harm to people and objects. We compared the responses to this task in a socially deprived group (DG) with that of a control group (CG). The event-related potentials (ERPs) results showed atypical early and late frontal cortical markers associated with attribution of intentionality during moral decision-making in DG (especially regarding intentional harm to people). The source space of the hdEEG showed reduced activity for DG compared with CG in the right prefrontal cortex, bilaterally in the ventromedial prefrontal cortex (vmPFC), and right insula. Moreover, the reduced response in vmPFC for DG was predicted by higher rates of externalizing problems. These findings demonstrate the importance of the social environment in early moral development, supporting a prefrontal maturation model of social deprivation.
Global cortical activity predicts shape of hand during grasping
Agashe, Harshavardhan A.; Paek, Andrew Y.; Zhang, Yuhang; Contreras-Vidal, José L.
2015-01-01
Recent studies show that the amplitude of cortical field potentials is modulated in the time domain by grasping kinematics. However, it is unknown if these low frequency modulations persist and contain enough information to decode grasp kinematics in macro-scale activity measured at the scalp via electroencephalography (EEG). Further, it is unclear as to whether joint angle velocities or movement synergies are the optimal kinematics spaces to decode. In this offline decoding study, we infer from human EEG, hand joint angular velocities as well as synergistic trajectories as subjects perform natural reach-to-grasp movements. Decoding accuracy, measured as the correlation coefficient (r) between the predicted and actual movement kinematics, was r = 0.49 ± 0.02 across 15 hand joints. Across the first three kinematic synergies, decoding accuracies were r = 0.59 ± 0.04, 0.47 ± 0.06, and 0.32 ± 0.05. The spatial-temporal pattern of EEG channel recruitment showed early involvement of contralateral frontal-central scalp areas followed by later activation of central electrodes over primary sensorimotor cortical areas. Information content in EEG about the grasp type peaked at 250 ms after movement onset. The high decoding accuracies in this study are significant not only as evidence for time-domain modulation in macro-scale brain activity, but for the field of brain-machine interfaces as well. Our decoding strategy, which harnesses the neural “symphony” as opposed to local members of the neural ensemble (as in intracranial approaches), may provide a means of extracting information about motor intent for grasping without the need for penetrating electrodes and suggests that it may be soon possible to develop non-invasive neural interfaces for the control of prosthetic limbs. PMID:25914616
Ehlers, Cindy L; Wills, Derek N; Phillips, Evelyn; Havstad, James
2015-10-01
Low voltage EEG (LVEEG) is a heritable phenotype that differs depending on ancestral heritage, yet its impact on brain networks and cognition remain relatively unexplored. In this study we assessed energy and task related phase locking of event-related oscillation (EROs), behavioral responses, measures of IQ and personality, and expected responses to alcohol in a large sample of individuals with LVEEG compared to those with higher voltage variants. Participants (n=762) were recruited from a Native American community and completed a diagnostic interview, the Quick Test, the Subjective High Assessment Scale Expectation Version (SHAS-E) and the Maudsley Personality Inventory. Clinical and spectral analyzed EEGs were collected for determination of the presence of a LVEEG variant. EROs were generated using a facial expression recognition task. Participants with LVEEG (n=451) were significantly more likely to be older, married and have higher degrees of Native American heritage but did not differ in gender, income or education. Individuals with LVEEG were also found to have decreased energy in their alpha EROs, increased phase locking between stimulus trials, and increased phase-locking between cortical brain areas. No significant differences in the cognitive tests, personality variables or alcohol dependence or anxiety diagnoses were found, however, individuals with LVEEG did report a larger number of drinks ever consumed in a 24-h period and a less intense expected response to alcohol. These data suggest that alpha power in the resting EEG is highly associated with energy and cortical connectivity measures generated by event-related stimuli, as well as potentially increased risk for alcohol use. Copyright © 2015 Elsevier B.V. All rights reserved.
Ethanol modulates cortical activity: direct evidence with combined TMS and EEG.
Kähkönen, S; Kesäniemi, M; Nikouline, V V; Karhu, J; Ollikainen, M; Holi, M; Ilmoniemi, R J
2001-08-01
The motor cortex of 10 healthy subjects was stimulated by transcranial magnetic stimulation (TMS) before and after ethanol challenge (0.8 g/kg resulting in blood concentration of 0.77 +/- 0.14 ml/liter). The electrical brain activity resulting from the brief electromagnetic pulse was recorded with high-resolution electroencephalography (EEG) and located using inversion algorithms. Focal magnetic pulses to the left motor cortex were delivered with a figure-of-eight coil at the random interstimulus interval of 1.5-2.5 s. The stimulation intensity was adjusted to the motor threshold of abductor digiti minimi. Two conditions before and after ethanol ingestion (30 min) were applied: (1) real TMS, with the coil pressed against the scalp; and (2) control condition, with the coil separated from the scalp by a 2-cm-thick piece of plastic. A separate EMG control recording of one subject during TMS was made with two bipolar platinum needle electrodes inserted to the left temporal muscle. In each condition, 120 pulses were delivered. The EEG was recorded from 60 scalp electrodes. A peak in the EEG signals was observed at 43 ms after the TMS pulse in the real-TMS condition but not in the control condition or in the control scalp EMG. Potential maps before and after ethanol ingestion were significantly different from each other (P = 0.01), but no differences were found in the control condition. Ethanol changed the TMS-evoked potentials over right frontal and left parietal areas, the underlying effect appearing to be largest in the right prefrontal area. Our findings suggest that ethanol may have changed the functional connectivity between prefrontal and motor cortices. This new noninvasive method provides direct evidence about the modulation of cortical connectivity after ethanol challenge. Copyright 2001 Academic Press.
Allen, John J. B.; Cohen, Michael X
2010-01-01
Asymmetry in frontal electrocortical alpha-band (8–13 Hz) activity recorded during resting situations (i.e., in absence of a specific task) has been investigated in relation to emotion and depression for over 30 years. This asymmetry reflects an aspect of endogenous cortical dynamics that is stable over repeated measurements and that may serve as an endophenotype for mood or other psychiatric disorders. In nearly all of this research, EEG activity is averaged across several minutes, obscuring transient dynamics that unfold on the scale of milliseconds to seconds. Such dynamic states may ultimately have greater value in linking brain activity to surface EEG asymmetry, thus improving its status as an endophenotype for depression. Here we introduce novel metrics for characterizing frontal alpha asymmetry that provide a more in-depth neurodynamical understanding of recurrent endogenous cortical processes during the resting-state. The metrics are based on transient “bursts” of asymmetry that occur frequently during the resting-state. In a sample of 306 young adults, 143 with a lifetime diagnosis of major depressive disorder (62 currently symptomatic), three questions were addressed: (1) How do novel peri-burst metrics of dynamic asymmetry compare to conventional fast-Fourier transform-based metrics? (2) Do peri-burst metrics adequately differentiate depressed from non-depressed participants? and, (3) what EEG dynamics surround the asymmetry bursts? Peri-burst metrics correlated with traditional measures of asymmetry, and were sensitive to both current and past episodes of major depression. Moreover, asymmetry bursts were characterized by a transient lateralized alpha suppression that is highly consistent in phase across bursts, and a concurrent contralateral transient alpha enhancement that is less tightly phase-locked across bursts. This approach opens new possibilities for investigating rapid cortical dynamics during resting-state EEG. PMID:21228910
Machado, Calixto; Estévez, Mario; Rodríguez, Rafael; Pérez-Nellar, Jesús; Chinchilla, Mauricio; DeFina, Philip; Leisman, Gerry; Carrick, Frederick R; Melillo, Robert; Schiavi, Adam; Gutiérrez, Joel; Carballo, Maylén; Machado, Andrés; Olivares, Ana; Pérez-Cruz, Nuvia
2014-01-01
To study the Zolpidem arousing effect in persistent vegetative state (PVS) patients combining clinical evaluation, autonomic assessment by heart rate variability (HRV), and EEG records. We studied a group of 8 PVS patients and other 8 healthy control subjects, matched by age and gender. The patients and controls received drug or placebo in two experimental sessions, separated by 10-14 days. The first 30 minutes of the session were considered the basal record, and then Zolpidem was administered. All participants were evaluated clinically, by EEG, and by HRV during the basal record, and for 90 minutes after drug intake. We found in all patients, time-related arousing signs after Zolpidem intake: behavioral (yawns and hiccups), activation of EEG cortical activity, and a vagolytic chronotropic effect without a significant increment of the vasomotor sympathetic tone. We demonstrated time-related arousing signs after Zolpidem intake. We discussed possible mechanisms to explain these patho-physiological findings regarding EEG cortical activation and an autonomic vagolytic drug effect. As this autonomic imbalance might induce cardiocirculatory complications, which we didn't find in any of our patients, we suggest developing future trials under control of physiological indices by bedside monitoring. However, considering that this arousing Zolpidem effect might be certainly related to brain function improvement, it should be particularly considered for the development of new neuro-rehabilitation programs in PVS cases. According to the literature review, we claim that this is the first report about the vagolitic effect of Zolpidem in PVS cases.
Sarrigiannis, Ptolemaios G; Zhao, Yifan; He, Fei; Billings, Stephen A; Baster, Kathleen; Rittey, Chris; Yianni, John; Zis, Panagiotis; Wei, Hualiang; Hadjivassiliou, Marios; Grünewald, Richard
2018-03-01
To determine the origin and dynamic characteristics of the generalised hyper-synchronous spike and wave (SW) discharges in childhood absence epilepsy (CAE). We applied nonlinear methods, the error reduction ratio (ERR) causality test and cross-frequency analysis, with a nonlinear autoregressive exogenous (NARX) model, to electroencephalograms (EEGs) from CAE, selected with stringent electro-clinical criteria (17 cases, 42 absences). We analysed the pre-ictal and ictal strength of association between homologous and heterologous EEG derivations and estimated the direction of synchronisation and corresponding time lags. A frontal/fronto-central onset of the absences is detected in 13 of the 17 cases with the highest ictal strength of association between homologous frontal followed by centro-temporal and fronto-central areas. Delays consistently in excess of 4 ms occur at the very onset between these regions, swiftly followed by the emergence of "isochronous" (0-2 ms) synchronisation but dynamic time lag changes occur during SW discharges. In absences an initial cortico-cortical spread leads to dynamic lag changes to include periods of isochronous interhemispheric synchronisation, which we hypothesize is mediated by the thalamus. Absences from CAE show ictal epileptic network dynamics remarkably similar to those observed in WAG/Rij rats which guided the formulation of the cortical focus theory. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.
EEG power during waking and NREM sleep in primary insomnia.
Wu, You Meme; Pietrone, Regina; Cashmere, J David; Begley, Amy; Miewald, Jean M; Germain, Anne; Buysse, Daniel J
2013-10-15
Pathophysiological models of insomnia invoke the concept of 24-hour hyperarousal, which could lead to symptoms and physiological findings during waking and sleep. We hypothesized that this arousal could be seen in the waking electroencephalogram (EEG) of individuals with primary insomnia (PI), and that waking EEG power would correlate with non-REM (NREM) EEG. Subjects included 50 PI and 32 good sleeper controls (GSC). Five minutes of eyes closed waking EEG were collected at subjects' usual bedtimes, followed by polysomnography (PSG) at habitual sleep times. An automated algorithm and visual editing were used to remove artifacts from waking and sleep EEGs, followed by power spectral analysis to estimate power from 0.5-32 Hz. We did not find significant differences in waking or NREM EEG spectral power of PI and GSC. Significant correlations between waking and NREM sleep power were observed across all frequency bands in the PI group and in most frequency bands in the GSC group. The absence of significant differences between groups in waking or NREM EEG power suggests that our sample was not characterized by a high degree of cortical arousal. The consistent correlations between waking and NREM EEG power suggest that, in samples with elevated NREM EEG beta activity, waking EEG power may show a similar pattern.
Jech, Robert; Růzicka, Evzen; Urgosík, Dusan; Serranová, Tereza; Volfová, Markéta; Nováková, Olga; Roth, Jan; Dusek, Petr; Mecír, Petr
2006-05-01
We studied changes of the EEG spectral power induced by deep brain stimulation (DBS) of the subthalamic nucleus (STN) in patients with Parkinson's disease (PD). Also analyzed were changes of visual evoked potentials (VEP) with DBS on and off. Eleven patients with advanced PD treated with bilateral DBS STN were examined after an overnight withdrawal of L-DOPA and 2 h after switching off the neurostimulators. All underwent clinical examination followed by resting EEG and VEP recordings, a procedure repeated after DBS STN was switched on. With DBS switched on, the dominant EEG frequency increased from 9.44+/-1.3 to 9.71+/-1.3 Hz (P<0.01) while its relative spectral power dropped by 11% on average (P<0.05). Switching on the neurostimulators caused a decrease in the N70/P100 amplitude of the VEP (P<0.01), which inversely correlated with the intensity of DBS (black-and-white pattern: P<0.01; color pattern: P<0.05). Despite artifacts generated by neurostimulators, the VEP and resting EEG were suitable for the detection of effects related to DBS STN. The acceleration of dominant frequency in the alpha band may be evidence of DBS STN influence on speeding up of intracortical oscillations. The spectral power decrease, seen mainly in the fronto-central region, might reflect a desynchronization in the premotor and motor circuits, though no movement was executed. Similarly, desynchronization of the cortical activity recorded posteriorly may by responsible for the VEP amplitude decrease implying DBS STN-related influence even on the visual system. Changes in idling EEG activity observed diffusely over scalp together with involvement of the VEP suggest that the effects of DBS STN reach far beyond the motor system influencing the basic mechanisms of rhythmic cortical oscillations.
Rashid, Nasir; Iqbal, Javaid; Javed, Amna; Tiwana, Mohsin I; Khan, Umar Shahbaz
2018-01-01
Brain Computer Interface (BCI) determines the intent of the user from a variety of electrophysiological signals. These signals, Slow Cortical Potentials, are recorded from scalp, and cortical neuronal activity is recorded by implanted electrodes. This paper is focused on design of an embedded system that is used to control the finger movements of an upper limb prosthesis using Electroencephalogram (EEG) signals. This is a follow-up of our previous research which explored the best method to classify three movements of fingers (thumb movement, index finger movement, and first movement). Two-stage logistic regression classifier exhibited the highest classification accuracy while Power Spectral Density (PSD) was used as a feature of the filtered signal. The EEG signal data set was recorded using a 14-channel electrode headset (a noninvasive BCI system) from right-handed, neurologically intact volunteers. Mu (commonly known as alpha waves) and Beta Rhythms (8-30 Hz) containing most of the movement data were retained through filtering using "Arduino Uno" microcontroller followed by 2-stage logistic regression to obtain a mean classification accuracy of 70%.
Sequencing the Cortical Processing of Pitch-Evoking Stimuli using EEG Analysis and Source Estimation
Butler, Blake E.; Trainor, Laurel J.
2012-01-01
Cues to pitch include spectral cues that arise from tonotopic organization and temporal cues that arise from firing patterns of auditory neurons. fMRI studies suggest a common pitch center is located just beyond primary auditory cortex along the lateral aspect of Heschl’s gyrus, but little work has examined the stages of processing for the integration of pitch cues. Using electroencephalography, we recorded cortical responses to high-pass filtered iterated rippled noise (IRN) and high-pass filtered complex harmonic stimuli, which differ in temporal and spectral content. The two stimulus types were matched for pitch saliency, and a mismatch negativity (MMN) response was elicited by infrequent pitch changes. The P1 and N1 components of event-related potentials (ERPs) are thought to arise from primary and secondary auditory areas, respectively, and to result from simple feature extraction. MMN is generated in secondary auditory cortex and is thought to act on feature-integrated auditory objects. We found that peak latencies of both P1 and N1 occur later in response to IRN stimuli than to complex harmonic stimuli, but found no latency differences between stimulus types for MMN. The location of each ERP component was estimated based on iterative fitting of regional sources in the auditory cortices. The sources of both the P1 and N1 components elicited by IRN stimuli were located dorsal to those elicited by complex harmonic stimuli, whereas no differences were observed for MMN sources across stimuli. Furthermore, the MMN component was located between the P1 and N1 components, consistent with fMRI studies indicating a common pitch region in lateral Heschl’s gyrus. These results suggest that while the spectral and temporal processing of different pitch-evoking stimuli involves different cortical areas during early processing, by the time the object-related MMN response is formed, these cues have been integrated into a common representation of pitch. PMID:22740836
Machinskaya, R I; Rozovskaya, R I; Kurgansky, A V; Pechenkova, E V
2016-01-01
A pattern of cortical functional connectivity in the source space was studied in a group of right-handed adult participants (N = 44:17 women, 27 men, aged M = 29.61 ± 6.45 years) who retained in their working memory (WM) traces of realistic pictures of positive, neutral, and negative emotional valence while in their working memory (WM) while performing same different task in which participants had to compare an etalon picture against a target picture that followed after a specified delay. A coherence (COH) between pairs of cortical sources chosen in advance according to fMRI data was estimated in the theta frequency range for the period of time preceding the etalon stimulus, distinct sets of functional links are found. The links of the first type that presumably reflect the involvement of sustained attention were between the dorsal anterior cingulate cortex, the prefrontal areas, and temporal areas of the right hemispheres. When compared to the rest period, links of this type showed strengthening not only during the retention period but also during the period preceding the etalon picture. The links of the second type presumably reflecting a progressive neocortex-to-hippocampus functional integration with increasing memory load and strengthened exclusively during retention period. Those links were between parietal, temporal and prefrontal cortices in the lateral surface of both hemispheres with the additional inclusion of the posterior cingulate cortex and the medial parietal cortex in the left hemisphere. An impact of emotional valence onto the strength and topography of the functional links of the second type was found. In the left hemisphere, an increase in the strength of cortical interaction was more pronounced for pictures of positive valence than for pictures of either neutral or negative valences. When compared to the pictures of neutral valence, the retention of pictorial information of both positive and negative valence showed some extraneous integration of the cortical areas for the theta rhythm. This finding might be related to the additional load exerted by emotionally colored pictures onto the mechanisms of short-time retention of visual information.
Neocortical 40 Hz oscillations during carbachol-induced rapid eye movement sleep and cataplexy.
Torterolo, Pablo; Castro-Zaballa, Santiago; Cavelli, Matías; Chase, Michael H; Falconi, Atilio
2016-02-01
Higher cognitive functions require the integration and coordination of large populations of neurons in cortical and subcortical regions. Oscillations in the gamma band (30-45 Hz) of the electroencephalogram (EEG) have been involved in these cognitive functions. In previous studies, we analysed the extent of functional connectivity between cortical areas employing the 'mean squared coherence' analysis of the EEG gamma band. We demonstrated that gamma coherence is maximal during alert wakefulness and is almost absent during rapid eye movement (REM) sleep. The nucleus pontis oralis (NPO) is critical for REM sleep generation. The NPO is considered to exert executive control over the initiation and maintenance of REM sleep. In the cat, depending on the previous state of the animal, a single microinjection of carbachol (a cholinergic agonist) into the NPO can produce either REM sleep [REM sleep induced by carbachol (REMc)] or a waking state with muscle atonia, i.e. cataplexy [cataplexy induced by carbachol (CA)]. In the present study, in cats that were implanted with electrodes in different cortical areas to record polysomnographic activity, we compared the degree of gamma (30-45 Hz) coherence during REMc, CA and naturally-occurring behavioural states. Gamma coherence was maximal during CA and alert wakefulness. In contrast, gamma coherence was almost absent during REMc as in naturally-occurring REM sleep. We conclude that, in spite of the presence of somatic muscle paralysis, there are remarkable differences in cortical activity between REMc and CA, which confirm that EEG gamma (≈40 Hz) coherence is a trait that differentiates wakefulness from REM sleep. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Neural Markers and Rehabilitation of Executive Functioning in Veterans with TBI and PTSD
2015-10-01
functioning. Functional magnetic resonance imaging ( fMRI ) will be used to evaluate changes in cortical function in frontostriate and frontoparietal circuits...EEG and fMRI will be conducted and then transport Veterans back to our laboratory. We will assure transportation is running efficiently and without...delays before study commencement. Transportation to the EEG and fMRI was arranged through the UNC-Chapel Hill School of Medicine at month 9
Weyhenmeyer, Jonathan; Hernandez, Manuel E; Lainscsek, Claudia; Sejnowski, Terrence J; Poizner, Howard
2014-01-01
Parkinson's disease (PD) is known to lead to marked alterations in cortical-basal ganglia activity that may be amenable to serve as a biomarker for PD diagnosis. Using non-linear delay differential equations (DDE) for classification of PD patients on and off dopaminergic therapy (PD-on, PD-off, respectively) from healthy age-matched controls (CO), we show that 1 second of quasi-resting state clean and raw electroencephalogram (EEG) data can be used to classify CO from PD-on/off based on the area under the receiver operating characteristic curve (AROC). Raw EEG is shown to classify more robustly (AROC=0.59-0.86) than clean EEG data (AROC=0.57-0.72). Decomposition of the raw data into stereotypical and non-stereotypical artifacts provides evidence that increased classification of raw EEG time series originates from muscle artifacts. Thus, non-linear feature extraction and classification of raw EEG data in a low dimensional feature space is a potential biomarker for Parkinson's disease.
Imperatori, Claudio; Farina, Benedetto; Quintiliani, Maria Isabella; Onofri, Antonio; Castelli Gattinara, Paola; Lepore, Marta; Gnoni, Valentina; Mazzucchi, Edoardo; Contardi, Anna; Della Marca, Giacomo
2014-10-01
The aim of the present study was to explore the modifications of EEG power spectra and EEG connectivity of resting state (RS) condition in patients with post-traumatic stress disorder (PTSD). Seventeen patients and seventeen healthy subjects matched for age and gender were enrolled. EEG was recorded during 5min of RS. EEG analysis was conducted by means of the standardized Low Resolution Electric Tomography software (sLORETA). In power spectra analysis PTSD patients showed a widespread increase of theta activity (4.5-7.5Hz) in parietal lobes (Brodmann Area, BA 7, 4, 5, 40) and in frontal lobes (BA 6). In the connectivity analysis PTSD patients also showed increase of alpha connectivity (8-12.5Hz) between the cortical areas explored by Pz-P4 electrode. Our results could reflect the alteration of memory systems and emotional processing consistently altered in PTSD patients. Copyright © 2014 Elsevier B.V. All rights reserved.
Ponz, Aurélie; Montant, Marie; Liegeois-Chauvel, Catherine; Silva, Catarina; Braun, Mario; Jacobs, Arthur M; Ziegler, Johannes C
2014-05-01
This study investigates the spatiotemporal brain dynamics of emotional information processing during reading using a combination of surface and intracranial electroencephalography (EEG). Two different theoretical views were opposed. According to the standard psycholinguistic perspective, emotional responses to words are generated within the reading network itself subsequent to semantic activation. According to the neural re-use perspective, brain regions that are involved in processing emotional information contained in other stimuli (faces, pictures, smells) might be in charge of the processing of emotional information in words as well. We focused on a specific emotion-disgust-which has a clear locus in the brain, the anterior insula. Surface EEG showed differences between disgust and neutral words as early as 200 ms. Source localization suggested a cortical generator of the emotion effect in the left anterior insula. These findings were corroborated through the intracranial recordings of two epileptic patients with depth electrodes in insular and orbitofrontal areas. Both electrodes showed effects of disgust in reading as early as 200 ms. The early emotion effect in a brain region (insula) that responds to specific emotions in a variety of situations and stimuli clearly challenges classic sequential theories of reading in favor of the neural re-use perspective.
Functional imaging of sleep vertex sharp transients.
Stern, John M; Caporro, Matteo; Haneef, Zulfi; Yeh, Hsiang J; Buttinelli, Carla; Lenartowicz, Agatha; Mumford, Jeanette A; Parvizi, Josef; Poldrack, Russell A
2011-07-01
The vertex sharp transient (VST) is an electroencephalographic (EEG) discharge that is an early marker of non-REM sleep. It has been recognized since the beginning of sleep physiology research, but its source and function remain mostly unexplained. We investigated VST generation using functional MRI (fMRI). Simultaneous EEG and fMRI were recorded from seven individuals in drowsiness and light sleep. VST occurrences on EEG were modeled with fMRI using an impulse function convolved with a hemodynamic response function to identify cerebral regions correlating to the VSTs. A resulting statistical image was thresholded at Z>2.3. Two hundred VSTs were identified. Significantly increased signal was present bilaterally in medial central, lateral precentral, posterior superior temporal, and medial occipital cortex. No regions of decreased signal were present. The regions are consistent with electrophysiologic evidence from animal models and functional imaging of human sleep, but the results are specific to VSTs. The regions principally encompass the primary sensorimotor cortical regions for vision, hearing, and touch. The results depict a network comprising the presumed VST generator and its associated regions. The associated regions functional similarity for primary sensation suggests a role for VSTs in sensory experience during sleep. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Soroko, S I; Rozhkov, V P; Bekshaev, S S
2013-12-01
The paper presents a comparative analysis of frequency, spatial-temporal parameters and three-dimensional localization of EEG sources that characterize changes of cortical-subcortical interactions processes in autumn and spring periods at northern schoolchildren living in satisfactory and disadvantaged (risk group) conditions of the social (family) environment. Seasonal rearrangement of interaction between wave components of main EEG rhythms was revealed. School students present regressive changes in the EEG pattern temporal organization in spring compared to autumn, and this effect was more expressed at adolescents from group of risk. Data EEDS-tomography showed increased activity in the prefrontal, cingular and subcallosal areas of the cortex in the autumn period that could be related to the mechanisms of season depression caused by the significant reduction of the day length in the North. The increased activity of the limbic system structures which is persisted in the spring in adolescents from risk group narrows the range of regulation of adaptive reactions. Unfavorable conditions of the family environment are an additional stress factor to increased load on the regulatory mechanisms that have a negative impact on the emotional-motivation behavior of children and adolescents, thus increasing the risk of the school and of social disadaptation.
Time course of EEG background activity level before spontaneous awakening in infants.
Zampi, Chiara; Fagioli, Igino; Salzarulo, Piero
2002-12-01
This research aimed to investigate the time course of the cortical activity level preceding spontaneous awakening as a function of age and state. Two groups of infants (1-4 and 9-14 weeks of age) were continuously monitored by polygraphic recording and behavioural observation during the night. The electroencephalographic (EEG) activity recorded by the C3-O1 lead was analysed through an automatic analysis method which provides, for each 30-s epoch, a single measure, time domain based, of the EEG synchronization. The EEG parameter values were computed in the 6 min preceding each awakening out of non-rapid eye movement (NREM) sleep and out of rapid eye movement (REM) sleep. The EEG background activity level did not change in the minutes preceding awakening out of REM sleep. Awakening out of NREM sleep was preceded by a change of EEG activity level in the direction of higher activation with different time course according to the age. Both REM and NREM sleep results suggest that a high level of EEG activity is a prerequisite for the occurrence of a spontaneous awakening.
[EEG-markers of vertical postural organization in healthy persons].
Zhavoronkova, L A; Zharikova, A V; Kushnir, E M; Mikhalkova, A A
2012-01-01
In 10 healthy persons (22.8 +/- 0.67 years) spectral-coherence parameters of EEG were analyzed in different steps of verticalizations--from gorizontal position to seat and stand one. Maximal changes of all EEG parameters were observed in state with absence of visual control. We observed an increase of power for fast spectral bands of EEG (beta- and gamma-bands) in all conditions and additional increase of these EEG parameters was observed at situation of complication of conditions of vertical pose supporting. Results of EEG coherent analysis in conditions of human verticalization showed specific increase of coherence for the majority of rhythm ranges in the right hemisphere especially in the central-frontal and in occipital-parietal areas and for interhemispheric pairs for these leads. This fact can reflect participation of cortical as well as subcortical structures in these processes. In conditions of complicate conditions of vertical pose supporting the additional increase of EEG coherence in fast bands (beta-rhythm) was observed at the frontal areas. This fact can testify about increasing of executive functions in this conditions.
White, David J; Congedo, Marco; Ciorciari, Joseph; Silberstein, Richard B
2012-03-01
Brain oscillatory correlates of spatial navigation were investigated using blind source separation (BSS) and standardized low resolution electromagnetic tomography (sLORETA) analyses of 62-channel EEG recordings. Twenty-five participants were instructed to navigate to distinct landmark buildings in a previously learned virtual reality town environment. Data from periods of navigation between landmarks were subject to BSS analyses to obtain source components. Two of these cortical sources were found to exhibit significant spectral power differences during navigation with respect to a resting eyes open condition and were subject to source localization using sLORETA. These two sources were localized as a right parietal component with gamma activation and a right medial-temporal-parietal component with activation in theta and gamma bandwidths. The parietal gamma activity was thought to reflect visuospatial processing associated with the task. The medial-temporal-parietal activity was thought to be more specific to the navigational processing, representing the integration of ego- and allo-centric representations of space required for successful navigation, suggesting theta and gamma oscillations may have a role in integrating information from parietal and medial-temporal regions. Theta activity on this medial-temporal-parietal source was positively correlated with more efficient navigation performance. Results are discussed in light of the depth and proposed closed field structure of the hippocampus and potential implications for scalp EEG data. The findings of the present study suggest that appropriate BSS methods are ideally suited to minimizing the effects of volume conduction in noninvasive recordings, allowing more accurate exploration of deep brain processes.
Electroencephalographic monitoring of complex mental tasks
NASA Technical Reports Server (NTRS)
Guisado, Raul; Montgomery, Richard; Montgomery, Leslie; Hickey, Chris
1992-01-01
Outlined here is the development of neurophysiological procedures to monitor operators during the performance of cognitive tasks. Our approach included the use of electroencepalographic (EEG) and rheoencephalographic (REG) techniques to determine changes in cortical function associated with cognition in the operator's state. A two channel tetrapolar REG, a single channel forearm impedance plethysmograph, a Lead I electrocardiogram (ECG) and a 21 channel EEG were used to measure subject responses to various visual-motor cognitive tasks. Testing, analytical, and display procedures for EEG and REG monitoring were developed that extend the state of the art and provide a valuable tool for the study of cerebral circulatory and neural activity during cognition.
Continuous EEG monitoring in the intensive care unit.
Scheuer, Mark L
2002-01-01
Continuous EEG (CEEG) monitoring allows uninterrupted assessment of cerebral cortical activity with good spatial resolution and excellent temporal resolution. Thus, this procedure provides a means of constantly assessing brain function in critically ill obtunded and comatose patients. Recent advances in digital EEG acquisition, storage, quantitative analysis, and transmission have made CEEG monitoring in the intensive care unit (ICU) technically feasible and useful. This article summarizes the indications and methodology of CEEG monitoring in the ICU, and discusses the role of some quantitative EEG analysis techniques in near real-time remote observation of CEEG recordings. Clinical examples of CEEG use, including monitoring of status epilepticus, assessment of ongoing therapy for treatment of seizures in critically ill patients, and monitoring for cerebral ischemia, are presented. Areas requiring further development of CEEG monitoring techniques and indications are discussed.
PyEEG: an open source Python module for EEG/MEG feature extraction.
Bao, Forrest Sheng; Liu, Xin; Zhang, Christina
2011-01-01
Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.
PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction
Bao, Forrest Sheng; Liu, Xin; Zhang, Christina
2011-01-01
Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction. PMID:21512582
NASA Astrophysics Data System (ADS)
Hu, Bin; Dong, Qunxi; Hao, Yanrong; Zhao, Qinglin; Shen, Jian; Zheng, Fang
2017-08-01
Objective. Neuro-electrophysiological tools have been widely used in heroin addiction studies. Previous studies indicated that chronic heroin abuse would result in abnormal functional organization of the brain, while few heroin addiction studies have applied the effective connectivity tool to analyze the brain functional system (BFS) alterations induced by heroin abuse. The present study aims to identify the abnormality of resting-state heroin abstinent BFS using source decomposition and effective connectivity tools. Approach. The resting-state electroencephalograph (EEG) signals were acquired from 15 male heroin abstinent (HA) subjects and 14 male non-addicted (NA) controls. Multivariate autoregressive models combined independent component analysis (MVARICA) was applied for blind source decomposition. Generalized partial directed coherence (GPDC) was applied for effective brain connectivity analysis. Effective brain networks of both HA and NA groups were constructed. The two groups of effective cortical networks were compared by the bootstrap method. Abnormal causal interactions between decomposed source regions were estimated in the 1-45 Hz frequency domain. Main results. This work suggested: (a) there were clear effective network alterations in heroin abstinent subject groups; (b) the parietal region was a dominant hub of the abnormally weaker causal pathways, and the left occipital region was a dominant hub of the abnormally stronger causal pathways. Significance. These findings provide direct evidence that chronic heroin abuse induces brain functional abnormalities. The potential value of combining effective connectivity analysis and brain source decomposition methods in exploring brain alterations of heroin addicts is also implied.
Hu, Bin; Dong, Qunxi; Hao, Yanrong; Zhao, Qinglin; Shen, Jian; Zheng, Fang
2017-08-01
Neuro-electrophysiological tools have been widely used in heroin addiction studies. Previous studies indicated that chronic heroin abuse would result in abnormal functional organization of the brain, while few heroin addiction studies have applied the effective connectivity tool to analyze the brain functional system (BFS) alterations induced by heroin abuse. The present study aims to identify the abnormality of resting-state heroin abstinent BFS using source decomposition and effective connectivity tools. The resting-state electroencephalograph (EEG) signals were acquired from 15 male heroin abstinent (HA) subjects and 14 male non-addicted (NA) controls. Multivariate autoregressive models combined independent component analysis (MVARICA) was applied for blind source decomposition. Generalized partial directed coherence (GPDC) was applied for effective brain connectivity analysis. Effective brain networks of both HA and NA groups were constructed. The two groups of effective cortical networks were compared by the bootstrap method. Abnormal causal interactions between decomposed source regions were estimated in the 1-45 Hz frequency domain. This work suggested: (a) there were clear effective network alterations in heroin abstinent subject groups; (b) the parietal region was a dominant hub of the abnormally weaker causal pathways, and the left occipital region was a dominant hub of the abnormally stronger causal pathways. These findings provide direct evidence that chronic heroin abuse induces brain functional abnormalities. The potential value of combining effective connectivity analysis and brain source decomposition methods in exploring brain alterations of heroin addicts is also implied.
Zhang, L; Gan, J Q; Wang, H
2015-03-19
Previous studies have established the importance of the fronto-parietal brain network in the information processing of reasoning. At the level of cortical source analysis, this eletroencepalogram (EEG) study investigates the functional reorganization of the theta-band (4-8Hz) neurocognitive network of mathematically gifted adolescents during deductive reasoning. Depending on the dense increase of long-range phase synchronizations in the reasoning process, math-gifted adolescents show more significant adaptive reorganization and enhanced "workspace" configuration in the theta network as compared with average-ability control subjects. The salient areas are mainly located in the anterior cortical vertices of the fronto-parietal network. Further correlation analyses have shown that the enhanced workspace configuration with respect to the global topological metrics of the theta network in math-gifted subjects is correlated with the intensive frontal midline theta (fm theta) response that is related to strong neural effort for cognitive events. These results suggest that by investing more cognitive resources math-gifted adolescents temporally mobilize an enhanced task-related global neuronal workspace, which is manifested as a highly integrated fronto-parietal information processing network during the reasoning process. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.
Cortical processes associated with continuous balance control as revealed by EEG spectral power.
Hülsdünker, T; Mierau, A; Neeb, C; Kleinöder, H; Strüder, H K
2015-04-10
Balance is a crucial component in numerous every day activities such as locomotion. Previous research has reported distinct changes in cortical theta activity during transient balance instability. However, there remains little understanding of the neural mechanisms underlying continuous balance control. This study aimed to investigate cortical theta activity during varying difficulties of continuous balance tasks, as well as examining the relationship between theta activity and balance performance. 37 subjects completed nine balance tasks with different levels of surface stability and base of support. Throughout the balancing task, electroencephalogram (EEG) was recorded from 32 scalp locations. ICA-based artifact rejection was applied and spectral power was analyzed in the theta frequency band. Theta power increased in the frontal, central, and parietal regions of the cortex when balance tasks became more challenging. In addition, fronto-central and centro-parietal theta power correlated with balance performance. This study demonstrates the involvement of the cerebral cortex in maintaining upright posture during continuous balance tasks. Specifically, the results emphasize the important role of frontal and parietal theta oscillations in balance control. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Orbitofrontal disinhibition of pain in migraine with aura: an interictal EEG-mapping study.
Lev, Rina; Granovsky, Yelena; Yarnitsky, David
2010-08-01
This study aimed to identify the cortical mechanisms underlying the processes of interictal dishabituation to experimental pain in subjects suffering from migraine with aura (MWA). In 21 subjects with MWA and 22 healthy controls, cortical responses to two successive trials of noxious contact-heat stimuli were analyzed using EEG-tomography software. When compared with controls, MWA patients showed significantly increased pain-evoked potential amplitudes accompanied by reduced activity in the orbitofrontal cortex (OFC) and increased activity in the pain matrix regions, including the primary somatosensory cortex (SI) (p < .05). Similarly to controls, MWA subjects displayed an inverse correlation between the OFC and SI activities, and positive interrelations between other pain-specific regions. The activity changes in the OFC negatively correlated with lifetime headache duration and longevity (p < .05). Reduced inhibitory functioning of the prefrontal cortex is a possible cause for disinhibition of the pain-related sensory cortices in migraine. The finding of OFC hypofunction over the disease course is in keeping with current concepts of migraine as a progressive brain disorder.
Integrated Eye Tracking and Neural Monitoring for Enhanced Assessment of Mild TBI
2016-04-01
but these delays are nearing resolution and we anticipate the initiation of the neuroimaging portion of the study early in Year 3. The fMRI task...resonance imagining ( fMRI ) and diffusion tensor imaging (DTI) to characterize the extent of functional cortical recruitment and white matter injury...respectively. The inclusion of fMRI and DTI will provide an objective basis for cross-validating the EEG and eye tracking system. Both the EEG and eye
Category-Selectivity in Human Visual Cortex Follows Cortical Topology: A Grouped icEEG Study
Conner, Christopher Richard; Whaley, Meagan Lee; Baboyan, Vatche George; Tandon, Nitin
2016-01-01
Neuroimaging studies suggest that category-selective regions in higher-order visual cortex are topologically organized around specific anatomical landmarks: the mid-fusiform sulcus (MFS) in the ventral temporal cortex (VTC) and lateral occipital sulcus (LOS) in the lateral occipital cortex (LOC). To derive precise structure-function maps from direct neural signals, we collected intracranial EEG (icEEG) recordings in a large human cohort (n = 26) undergoing implantation of subdural electrodes. A surface-based approach to grouped icEEG analysis was used to overcome challenges from sparse electrode coverage within subjects and variable cortical anatomy across subjects. The topology of category-selectivity in bilateral VTC and LOC was assessed for five classes of visual stimuli—faces, animate non-face (animals/body-parts), places, tools, and words—using correlational and linear mixed effects analyses. In the LOC, selectivity for living (faces and animate non-face) and non-living (places and tools) classes was arranged in a ventral-to-dorsal axis along the LOS. In the VTC, selectivity for living and non-living stimuli was arranged in a latero-medial axis along the MFS. Written word-selectivity was reliably localized to the intersection of the left MFS and the occipito-temporal sulcus. These findings provide direct electrophysiological evidence for topological information structuring of functional representations within higher-order visual cortex. PMID:27272936
Balconi, Michela; Maria Elide Vanutelli, Maria Elide
2017-01-01
Emotional empathy is crucial to understand how we respond to interpersonal positive or negative situations. In the present research, we aim at identifying the neural networks and the autonomic responsiveness underlying the human ability to perceive and empathize with others’ emotions when positive (cooperative) or negative (uncooperative) interactions are observed. A multimethodological approach was adopted to elucidate the reciprocal interplay of autonomic (peripheral) and central (cortical) activities in empathic behavior. Electroencephalography (EEG, frequency band analysis) and hemodynamic (functional Near-Infrared Spectroscopy, fNIRS) activity were all recorded simultaneously with systemic skin conductance response (SCR) and heart rate (HR) measurements as potential biological markers of emotional empathy. Subjects were required to empathize in interpersonal interactions. As shown by fNIRS/EEG measures, negative situations elicited increased brain responses within the right prefrontal cortex (PFC), whereas positive situations elicited greater responses within the left PFC. Therefore, a relevant lateralization effect was induced by the specific valence (mainly for negative conditions) of the emotional interactions. Also, SCR was modulated by positive/negative conditions. Finally, EEG activity (mainly low-frequency theta and delta bands) intrinsically correlated with the cortical hemodynamic responsiveness, and they both predicted autonomic activity. The integrated central and autonomic measures better elucidated the significance of empathic behavior in interpersonal interactions. PMID:28450977
Neural decoding of treadmill walking from noninvasive electroencephalographic signals
Presacco, Alessandro; Goodman, Ronald; Forrester, Larry
2011-01-01
Chronic recordings from ensembles of cortical neurons in primary motor and somatosensory areas in rhesus macaques provide accurate information about bipedal locomotion (Fitzsimmons NA, Lebedev MA, Peikon ID, Nicolelis MA. Front Integr Neurosci 3: 3, 2009). Here we show that the linear and angular kinematics of the ankle, knee, and hip joints during both normal and precision (attentive) human treadmill walking can be inferred from noninvasive scalp electroencephalography (EEG) with decoding accuracies comparable to those from neural decoders based on multiple single-unit activities (SUAs) recorded in nonhuman primates. Six healthy adults were recorded. Participants were asked to walk on a treadmill at their self-selected comfortable speed while receiving visual feedback of their lower limbs (i.e., precision walking), to repeatedly avoid stepping on a strip drawn on the treadmill belt. Angular and linear kinematics of the left and right hip, knee, and ankle joints and EEG were recorded, and neural decoders were designed and optimized with cross-validation procedures. Of note, the optimal set of electrodes of these decoders were also used to accurately infer gait trajectories in a normal walking task that did not require subjects to control and monitor their foot placement. Our results indicate a high involvement of a fronto-posterior cortical network in the control of both precision and normal walking and suggest that EEG signals can be used to study in real time the cortical dynamics of walking and to develop brain-machine interfaces aimed at restoring human gait function. PMID:21768121
Karimi, Fatemeh; Kofman, Jonathan; Mrachacz-Kersting, Natalie; Farina, Dario; Jiang, Ning
2017-01-01
The movement related cortical potential (MRCP), a slow cortical potential from the scalp electroencephalogram (EEG), has been used in real-time brain-computer-interface (BCI) systems designed for neurorehabilitation. Detecting MPCPs in real time with high accuracy and low latency is essential in these applications. In this study, we propose a new MRCP detection method based on constrained independent component analysis (cICA). The method was tested for MRCP detection during executed and imagined ankle dorsiflexion of 24 healthy participants, and compared with four commonly used spatial filters for MRCP detection in an offline experiment. The effect of cICA and the compared spatial filters on the morphology of the extracted MRCP was evaluated by two indices quantifying the signal-to-noise ratio and variability of the extracted MRCP. The performance of the filters for detection was then directly compared for accuracy and latency. The latency obtained with cICA (-34 ± 29 ms motor execution (ME) and 28 ± 16 ms for motor imagery (MI) dataset) was significantly smaller than with all other spatial filters. Moreover, cICA resulted in greater true positive rates (87.11 ± 11.73 for ME and 86.66 ± 6.96 for MI dataset) and lower false positive rates (20.69 ± 13.68 for ME and 19.31 ± 12.60 for MI dataset) compared to the other methods. These results confirm the superiority of cICA in MRCP detection with respect to previously proposed EEG filtering approaches.
Thalamocortical and intracortical laminar connectivity determines sleep spindle properties.
Krishnan, Giri P; Rosen, Burke Q; Chen, Jen-Yung; Muller, Lyle; Sejnowski, Terrence J; Cash, Sydney S; Halgren, Eric; Bazhenov, Maxim
2018-06-27
Sleep spindles are brief oscillatory events during non-rapid eye movement (NREM) sleep. Spindle density and synchronization properties are different in MEG versus EEG recordings in humans and also vary with learning performance, suggesting spindle involvement in memory consolidation. Here, using computational models, we identified network mechanisms that may explain differences in spindle properties across cortical structures. First, we report that differences in spindle occurrence between MEG and EEG data may arise from the contrasting properties of the core and matrix thalamocortical systems. The matrix system, projecting superficially, has wider thalamocortical fanout compared to the core system, which projects to middle layers, and requires the recruitment of a larger population of neurons to initiate a spindle. This property was sufficient to explain lower spindle density and higher spatial synchrony of spindles in the superficial cortical layers, as observed in the EEG signal. In contrast, spindles in the core system occurred more frequently but less synchronously, as observed in the MEG recordings. Furthermore, consistent with human recordings, in the model, spindles occurred independently in the core system but the matrix system spindles commonly co-occurred with core spindles. We also found that the intracortical excitatory connections from layer III/IV to layer V promote spindle propagation from the core to the matrix system, leading to widespread spindle activity. Our study predicts that plasticity of intra- and inter-cortical connectivity can potentially be a mechanism for increased spindle density as has been observed during learning.
NASA Astrophysics Data System (ADS)
Pichiorri, F.; De Vico Fallani, F.; Cincotti, F.; Babiloni, F.; Molinari, M.; Kleih, S. C.; Neuper, C.; Kübler, A.; Mattia, D.
2011-04-01
The main purpose of electroencephalography (EEG)-based brain-computer interface (BCI) technology is to provide an alternative channel to support communication and control when motor pathways are interrupted. Despite the considerable amount of research focused on the improvement of EEG signal detection and translation into output commands, little is known about how learning to operate a BCI device may affect brain plasticity. This study investigated if and how sensorimotor rhythm-based BCI training would induce persistent functional changes in motor cortex, as assessed with transcranial magnetic stimulation (TMS) and high-density EEG. Motor imagery (MI)-based BCI training in naïve participants led to a significant increase in motor cortical excitability, as revealed by post-training TMS mapping of the hand muscle's cortical representation; peak amplitude and volume of the motor evoked potentials recorded from the opponens pollicis muscle were significantly higher only in those subjects who develop a MI strategy based on imagination of hand grasping to successfully control a computer cursor. Furthermore, analysis of the functional brain networks constructed using a connectivity matrix between scalp electrodes revealed a significant decrease in the global efficiency index for the higher-beta frequency range (22-29 Hz), indicating that the brain network changes its topology with practice of hand grasping MI. Our findings build the neurophysiological basis for the use of non-invasive BCI technology for monitoring and guidance of motor imagery-dependent brain plasticity and thus may render BCI a viable tool for post-stroke rehabilitation.
Kukke, Sahana N.; de Campos, Ana Carolina; Damiano, Diane; Alter, Katharine E.; Patronas, Nicholas; Hallett, Mark
2014-01-01
Objective Dystonia is a disabling motor disorder often without effective therapies. To better understand the genesis of dystonia after childhood stroke, we analyzed electroencephalographic (EEG) recordings in this population. Methods Resting spectral power of EEG signals over bilateral sensorimotor cortices (Powrest), resting inter-hemispheric sensorimotor coherence (Cohrest), and task-related changes in power (TRPow) and coherence (TRCoh) during wrist extension were analyzed in individuals with dystonia (age 20±3 years) and healthy volunteers (age 17±5 years). Results Ipsilesional TRPow decrease was significantly lower in patients than controls during the more affected wrist task. Force deficits of the affected wrist correlated with reduced alpha TRPow decrease on the ipsilesional and not the contralesional hemisphere. Cohrest was significantly lower in patients than controls, and correlated with more severe dystonia and poorer hand function. Powrest and TRCoh were similar between groups. Conclusions The association between weakness and cortical activation during wrist extension highlights the importance of ipsilesional sensorimotor activation on function. Reduction of Cohrest in patients reflects a loss of inter-hemispheric connectivity that may result from structural changes and neuroplasticity, potentially contributing to the development of dystonia. Significance Cortical and motor dysfunction are correlated in patients with childhood stroke and may in part explain the genesis of dystonia. PMID:25499610
Kukke, Sahana N; de Campos, Ana Carolina; Damiano, Diane; Alter, Katharine E; Patronas, Nicholas; Hallett, Mark
2015-08-01
Dystonia is a disabling motor disorder often without effective therapies. To better understand the genesis of dystonia after childhood stroke, we analyzed electroencephalographic (EEG) recordings in this population. Resting spectral power of EEG signals over bilateral sensorimotor cortices (Powrest), resting inter-hemispheric sensorimotor coherence (Cohrest), and task-related changes in power (TRPow) and coherence (TRCoh) during wrist extension were analyzed in individuals with dystonia (age 20±3years) and healthy volunteers (age 17±5years). Ipsilesional TRPow decrease was significantly lower in patients than controls during the more affected wrist task. Force deficits of the affected wrist correlated with reduced alpha TRPow decrease on the ipsilesional and not the contralesional hemisphere. Cohrest was significantly lower in patients than controls, and correlated with more severe dystonia and poorer hand function. Powrest and TRCoh were similar between groups. The association between weakness and cortical activation during wrist extension highlights the importance of ipsilesional sensorimotor activation on function. Reduction of Cohrest in patients reflects a loss of inter-hemispheric connectivity that may result from structural changes and neuroplasticity, potentially contributing to the development of dystonia. Cortical and motor dysfunction are correlated in patients with childhood stroke and may in part explain the genesis of dystonia. Published by Elsevier Ireland Ltd.
Cortical drive to breathe in amyotrophic lateral sclerosis: a dyspnoea-worsening defence?
Georges, Marjolaine; Morawiec, Elise; Raux, Mathieu; Gonzalez-Bermejo, Jésus; Pradat, Pierre-François; Similowski, Thomas; Morélot-Panzini, Capucine
2016-06-01
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease causing diaphragm weakness that can be partially compensated by inspiratory neck muscle recruitment. This disappears during sleep, which is compatible with a cortical contribution to the drive to breathe. We hypothesised that ALS patients with respiratory failure exhibit respiratory-related cortical activity, relieved by noninvasive ventilation (NIV) and related to dyspnoea.We studied 14 ALS patients with respiratory failure. Electroencephalographic recordings (EEGs) and electromyographic recordings of inspiratory neck muscles were performed during spontaneous breathing and NIV. Dyspnoea was evaluated using the Multidimensional Dyspnea Profile.Eight patients exhibited slow EEG negativities preceding inspiration (pre-inspiratory potentials) during spontaneous breathing. Pre-inspiratory potentials were attenuated during NIV (p=0.04). Patients without pre-inspiratory potentials presented more advanced forms of ALS and more severe respiratory impairment, but less severe dyspnoea. Patients with pre-inspiratory potentials had stronger inspiratory neck muscle activation and more severe dyspnoea during spontaneous breathing.ALS-related diaphragm weakness can engage cortical resources to augment the neural drive to breathe. This might reflect a compensatory mechanism, with the intensity of dyspnoea a negative consequence. Disease progression and the corresponding neural loss could abolish this phenomenon. A putative cognitive cost should be investigated. Copyright ©ERS 2016.
Slobounov, S; Chiang, H; Johnston, J; Ray, W
2002-12-01
The present research was designed to address the nature of interdependency between fingers during force production tasks in subjects with varying experience in performing independent finger manipulation. Specifically, behavioral and electroencephalographic (EEG) measures associated with controllability of the most enslaved (ring) and the least enslaved (index) fingers was examined in musicians and non-musicians. Six piano players and 6 age-matched control subjects performed a series of isometric force production tasks with the index and ring fingers. Subjects produced 3 different force levels with either their index or ring fingers. We measured the isometric force output produced by all 4 fingers (index, ring, middle and little), including both ramp and static phases of force production. We applied time-domain averaging of EEG single trials in order to extract 4 components of the movement-related cortical potentials (MRCP) preceding and accompanying force responses. Three behavioral findings were observed. First, musicians were more accurate than non-musicians at reaching the desired force level. Second, musicians showed less enslaving as compared to non-musicians. And third, the amount of enslaving increased with the increment of nominal force levels regardless of whether the index or ring finger was used as the master finger. In terms of EEG measures, we found differences between tasks performed with the index and ring fingers in non-musicians. For musicians, we found larger MRCP amplitudes at most electrode sites for the ring finger. Our data extends previous enslaving research and suggest an important role for previous experience in terms of the independent use of the fingers. Given that a variety of previous work has shown finger independence to be reflected in cortical representation in the brain and our findings of MRCP amplitude associated with greater independence of fingers in musicians, this suggests that what has been considered to be stable constraints in terms of finger movements can be modulated by experience. This work supports the idea that experience is associated with changes in behavioral and EEG correlates of task performance and may have clinical implications in disorders such as stroke or focal hand dystonia. Practice-related procedures offer useful approaches to rehabilitation strategies.
Going local: insights from EEG and stereo-EEG studies of the human sleep-wake cycle.
Ferrara, Michele; De Gennaro, Luigi
2011-01-01
In the present paper, we reviewed a large body of evidence, mainly from quantitative EEG studies of our laboratory, supporting the notion that sleep is a local and use-dependent process. Quantitative analyses of sleep EEG recorded from multiple cortical derivations clearly indicate that every sleep phenomenon, from sleep onset to the awakening, is strictly local in nature. Sleep onset first occurs in frontal areas, and a frontal predominance of low-frequency power persists in the first part of the night, when the homeostatic processes mainly occur, and then it vanishes. Upon awakening, we showed an asynchronous EEG activation of different cortical areas, the more anterior ones being the first to wake up. During extended periods of wakefulness, the increase of sleepiness-related low-EEG frequencies is again evident over the frontal derivations. Similarly, experimental manipulations of sleep length by total sleep deprivation, partial sleep curtailment or even selective slow-wave sleep deprivation lead to a slow-wave activity rebound localized especially on the anterior derivations. Thus, frontal areas are crucially involved in sleep homeostasis. According to the local use-dependent theory, this would derive from a higher sleep need of the frontal cortex, which in turn is due to its higher levels of activity during wakefulness. The fact that different brain regions can simultaneously exhibit different sleep intensities indicates that sleep is not a spatially global and uniform state, as hypothesized in the theory. We have also reviewed recent evidence of localized effects of learning and plasticity on EEG sleep measures. These studies provide crucial support to a key concept in the theory, the one claiming that local sleep characteristics should be use-dependent. Finally, we have reported data corroborating the notion that sleep is not necessarily present simultaneously in the entire brain. Our stereo-EEG recordings clearly indicate that sleep and wakefulness can co-exist in different areas, suggesting that vigilance states are not necessarily temporally discrete states. We conclude that understanding local variations in sleep propensity and depth, especially as a result of brain plasticity, may provide in the near future insightful hints into the fundamental functions of sleep.
Spectral fingerprints of large-scale cortical dynamics during ambiguous motion perception.
Helfrich, Randolph F; Knepper, Hannah; Nolte, Guido; Sengelmann, Malte; König, Peter; Schneider, Till R; Engel, Andreas K
2016-11-01
Ambiguous stimuli have been widely used to study the neuronal correlates of consciousness. Recently, it has been suggested that conscious perception might arise from the dynamic interplay of functionally specialized but widely distributed cortical areas. While previous research mainly focused on phase coupling as a correlate of cortical communication, more recent findings indicated that additional coupling modes might coexist and possibly subserve distinct cortical functions. Here, we studied two coupling modes, namely phase and envelope coupling, which might differ in their origins, putative functions and dynamics. Therefore, we recorded 128-channel EEG while participants performed a bistable motion task and utilized state-of-the-art source-space connectivity analysis techniques to study the functional relevance of different coupling modes for cortical communication. Our results indicate that gamma-band phase coupling in extrastriate visual cortex might mediate the integration of visual tokens into a moving stimulus during ambiguous visual stimulation. Furthermore, our results suggest that long-range fronto-occipital gamma-band envelope coupling sustains the horizontal percept during ambiguous motion perception. Additionally, our results support the idea that local parieto-occipital alpha-band phase coupling controls the inter-hemispheric information transfer. These findings provide correlative evidence for the notion that synchronized oscillatory brain activity reflects the processing of sensory input as well as the information integration across several spatiotemporal scales. The results indicate that distinct coupling modes are involved in different cortical computations and that the rich spatiotemporal correlation structure of the brain might constitute the functional architecture for cortical processing and specific multi-site communication. Hum Brain Mapp 37:4099-4111, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Zorick, Todd; Mandelkern, Mark A
2015-01-01
Electroencephalography (EEG) is typically viewed through the lens of spectral analysis. Recently, multiple lines of evidence have demonstrated that the underlying neuronal dynamics are characterized by scale-free avalanches. These results suggest that techniques from statistical physics may be used to analyze EEG signals. We utilized a publicly available database of fourteen subjects with waking and sleep stage 2 EEG tracings per subject, and observe that power-law dynamics of critical-state neuronal avalanches are not sufficient to fully describe essential features of EEG signals. We hypothesized that this could reflect the phenomenon of discrete scale invariance (DSI) in EEG large voltage deflections (LVDs) as being more prominent in waking consciousness. We isolated LVDs, and analyzed logarithmically transformed LVD size probability density functions (PDF) to assess for DSI. We find evidence of increased DSI in waking, as opposed to sleep stage 2 consciousness. We also show that the signatures of DSI are specific for EEG LVDs, and not a general feature of fractal simulations with similar statistical properties to EEG. Removing only LVDs from waking EEG produces a reduction in power in the alpha and beta frequency bands. These findings may represent a new insight into the understanding of the cortical dynamics underlying consciousness.
Electroencephalography and Brain MRI Patterns in Encephalopathy.
Wabulya, Angela; Lesser, Ronald P; Llinas, Rafael; Kaplan, Peter W
2016-04-01
Using electroencephalography (EEG) and histology in patients with diffuse encephalopathy, Gloor et al reported that paroxysmal synchronous discharges (PSDs) on EEG required combined cortical gray (CG) and "subcortical" gray (SCG) matter pathology, while polymorphic delta activity (PDA) occurred in patients with white matter pathology. In patients with encephalopathy, we compared EEG findings and magnetic resonance imaging (MRI) to determine if MRI reflected similar pathological EEG correlations. Retrospective case control study of 52 cases with EEG evidence of encephalopathy and 50 controls without evidence of encephalopathy. Review of clinical, EEG and MRI data acquired within 4 days of each other. The most common EEG finding in encephalopathy was background slowing, in 96.1%. We found PSDs in 0% of cases with the combination of CG and SCG abnormalities. Although 13.5% (n=7) had PSDs on EEG; 3 of these had CG and 4 had SCG abnormalities. A total of 73.1% (38/52) had white matter abnormalities-of these 28.9% (11/38) had PDA. PSDs were found with either CG or "SCG" MRI abnormalities and did not require a combination of the two. In agreement with Gloor et al, PDA occurred with white matter MRI abnormalities in the absence of gray matter abnormalities. © EEG and Clinical Neuroscience Society (ECNS) 2015.
Wake High-Density Electroencephalographic Spatiospectral Signatures of Insomnia
Colombo, Michele A.; Ramautar, Jennifer R.; Wei, Yishul; Gomez-Herrero, Germán; Stoffers, Diederick; Wassing, Rick; Benjamins, Jeroen S.; Tagliazucchi, Enzo; van der Werf, Ysbrand D.; Cajochen, Christian; Van Someren, Eus J.W.
2016-01-01
Study Objectives: Although daytime complaints are a defining characteristic of insomnia, most EEG studies evaluated sleep only. We used high-density electroencephalography to investigate wake resting state oscillations characteristic of insomnia disorder (ID) at a fine-grained spatiospectral resolution. Methods: A case-control assessment during eyes open (EO) and eyes closed (EC) was performed in a laboratory for human physiology. Participants (n = 94, 74 female, 21–70 y) were recruited through www.sleepregistry.nl: 51 with ID, according to DSM-5 and 43 matched controls. Exclusion criteria were any somatic, neurological or psychiatric condition. Group differences in the spectral power topographies across multiple frequencies (1.5 to 40 Hz) were evaluated using permutation-based inference with Threshold-Free Cluster-Enhancement, to correct for multiple comparisons. Results: As compared to controls, participants with ID showed less power in a narrow upper alpha band (11–12.7 Hz, peak: 11.7 Hz) over bilateral frontal and left temporal regions during EO, and more power in a broad beta frequency range (16.3–40 Hz, peak: 19 Hz) globally during EC. Source estimates suggested global rather than cortically localized group differences. Conclusions: The widespread high power in a broad beta band reported previously during sleep in insomnia is present as well during eyes closed wakefulness, suggestive of a round-the-clock hyperarousal. Low power in the upper alpha band during eyes open is consistent with low cortical inhibition and attentional filtering. The fine-grained HD-EEG findings suggest that, while more feasible than PSG, wake EEG of short duration with a few well-chosen electrodes and frequency bands, can provide valuable features of insomnia. Citation: Colombo MA, Ramautar JR, Wei Y, Gomez-Herrero G, Stoffers D, Wassing R, Benjamins JS, Tagliazucchi E, van der Werf YD, Cajochen C, Van Someren EJW. Wake high-density electroencephalographic spatiospectral signatures of insomnia. SLEEP 2016;39(5):1015–1027. PMID:26951395
MRI with and without a high-density EEG cap--what makes the difference?
Klein, Carina; Hänggi, Jürgen; Luechinger, Roger; Jäncke, Lutz
2015-02-01
Besides the benefit of combining electroencephalography (EEG) and magnetic resonance imaging (MRI), much effort has been spent to develop algorithms aimed at successfully cleaning the EEG data from MRI-related gradient and ballistocardiological artifacts. However, there are also studies showing a negative influence of the EEG on MRI data quality. Therefore, in the present study, we focused for the first time on the influence of the EEG on morphometric measurements of T1-weighted MRI data (voxel- and surfaced-based morphometry). Here, we demonstrate a strong influence of the EEG on cortical thickness, surface area, and volume as well as subcortical volumes due to local EEG-related inhomogeneities of the static magnetic (B0) and the gradient field (B1). In a second step, we analyzed the signal-to-noise ratios for both the anatomical and the functional data when recorded simultaneously with EEG and MRI and compared them to the ratios of the MRI data without simultaneous EEG measurements. These analyses revealed consistently lower signal-to-noise ratios for anatomical as well as functional MRI data during simultaneous EEG registration. In contrast, further analyses of T2*-weighted images provided reliable results independent of whether including the individuals' T1-weighted image with or without the EEG cap in the fMRI preprocessing stream. Based on our findings, we strongly recommend against using the structural images obtained during simultaneous EEG-MRI recordings for further anatomical data analysis. Copyright © 2014 Elsevier Inc. All rights reserved.
Sherwin, Jason; Sajda, Paul
2013-01-01
Humans are extremely good at detecting anomalies in sensory input. For example, while listening to a piece of Western-style music, an anomalous key change or an out-of-key pitch is readily apparent, even to the non-musician. In this paper we investigate differences between musical experts and non-experts during musical anomaly detection. Specifically, we analyzed the electroencephalograms (EEG) of five expert cello players and five non-musicians while they listened to excerpts of J.S. Bach’s Prelude from Cello Suite No.1. All subjects were familiar with the piece, though experts also had extensive experience playing the piece. Subjects were told that anomalous musical events (AMEs) could occur at random within the excerpts of the piece and were told to report the number of AMEs after each excerpt. Furthermore, subjects were instructed to remain still while listening to the excerpts and their lack of movement was verified via visual and EEG monitoring. Experts had significantly better behavioral performance (i.e. correctly reporting AME counts) than non-experts, though both groups had mean accuracies greater than 80%. These group differences were also reflected in the EEG correlates of key-change detection post-stimulus, with experts showing more significant, greater magnitude, longer periods of and earlier peaks in condition-discriminating EEG activity than novices. Using the timing of the maximum discriminating neural correlates, we performed source reconstruction and compared significant differences between cellists and non-musicians. We found significant differences that included a slightly right lateralized motor and frontal source distribution. The right lateralized motor activation is consistent with the cortical representation of the left hand – i.e. the hand a cellist would use, while playing, to generate the anomalous key-changes. In general, these results suggest that sensory anomalies detected by experts may in fact be partially a result of an embodied cognition, with a model of the action for generating the anomaly playing a role in its detection. PMID:24056235
NASA Technical Reports Server (NTRS)
Cajochen, C.; Foy, R.; Dijk, D. J.; Czeisler, C. A. (Principal Investigator)
1999-01-01
The effect of sleep deprivation (40 h) on topographic and temporal aspects of electroencephalographic (EEG) activity during sleep was investigated by all night spectral analysis in six young volunteers. The sleep-deprivation-induced increase of EEG power density in the delta and theta frequencies (1-7 Hz) during nonREM sleep, assessed along the antero-posterior axis (midline: Fz, Cz, Pz, Oz), was significantly larger in the more frontal derivations (Fz, Cz) than in the more parietal derivations (Pz, Oz). This frequency-specific frontal predominance was already present in the first 30 min of recovery sleep, and dissipated in the course of the 8-h sleep episode. The data demonstrate that the enhancement of slow wave EEG activity during sleep following extended wakefulness is most pronounced in frontal cortical areas.
Presurgical EEG-fMRI in a complex clinical case with seizure recurrence after epilepsy surgery
Zhang, Jing; Liu, Qingzhu; Mei, Shanshan; Zhang, Xiaoming; Wang, Xiaofei; Liu, Weifang; Chen, Hui; Xia, Hong; Zhou, Zhen; Li, Yunlin
2013-01-01
Epilepsy surgery has improved over the last decade, but non-seizure-free outcome remains at 10%–40% in temporal lobe epilepsy (TLE) and 40%–60% in extratemporal lobe epilepsy (ETLE). This paper reports a complex multifocal case. With a normal magnetic resonance imaging (MRI) result and nonlocalizing electroencephalography (EEG) findings (bilateral TLE and ETLE, with more interictal epileptiform discharges [IEDs] in the right frontal and temporal regions), a presurgical EEG-functional MRI (fMRI) was performed before the intraoperative intracranial EEG (icEEG) monitoring (icEEG with right hemispheric coverage). Our previous EEG-fMRI analysis results (IEDs in the left hemisphere alone) were contradictory to the EEG and icEEG findings (IEDs in the right frontal and temporal regions). Thus, the EEG-fMRI data were reanalyzed with newly identified IED onsets and different fMRI model options. The reanalyzed EEG-fMRI findings were largely concordant with those of EEG and icEEG, and the failure of our previous EEG-fMRI analysis may lie in the inaccurate identification of IEDs and wrong usage of model options. The right frontal and temporal regions were resected in surgery, and dual pathology (hippocampus sclerosis and focal cortical dysplasia in the extrahippocampal region) was found. The patient became seizure-free for 3 months, but his seizures restarted after antiepileptic drugs (AEDs) were stopped. The seizures were not well controlled after resuming AEDs. Postsurgical EEGs indicated that ictal spikes in the right frontal and temporal regions reduced, while those in the left hemisphere became prominent. This case suggested that (1) EEG-fMRI is valuable in presurgical evaluation, but requires caution; and (2) the intact seizure focus in the remaining brain may cause the non-seizure-free outcome. PMID:23926432
Real-time Adaptive EEG Source Separation using Online Recursive Independent Component Analysis
Hsu, Sheng-Hsiou; Mullen, Tim; Jung, Tzyy-Ping; Cauwenberghs, Gert
2016-01-01
Independent Component Analysis (ICA) has been widely applied to electroencephalographic (EEG) biosignal processing and brain-computer interfaces. The practical use of ICA, however, is limited by its computational complexity, data requirements for convergence, and assumption of data stationarity, especially for high-density data. Here we study and validate an optimized online recursive ICA algorithm (ORICA) with online recursive least squares (RLS) whitening for blind source separation of high-density EEG data, which offers instantaneous incremental convergence upon presentation of new data. Empirical results of this study demonstrate the algorithm's: (a) suitability for accurate and efficient source identification in high-density (64-channel) realistically-simulated EEG data; (b) capability to detect and adapt to non-stationarity in 64-ch simulated EEG data; and (c) utility for rapidly extracting principal brain and artifact sources in real 61-channel EEG data recorded by a dry and wearable EEG system in a cognitive experiment. ORICA was implemented as functions in BCILAB and EEGLAB and was integrated in an open-source Real-time EEG Source-mapping Toolbox (REST), supporting applications in ICA-based online artifact rejection, feature extraction for real-time biosignal monitoring in clinical environments, and adaptable classifications in brain-computer interfaces. PMID:26685257
Vecchio, F; Miraglia, F; Quaranta, D; Granata, G; Romanello, R; Marra, C; Bramanti, P; Rossini, P M
2016-03-01
Functional brain abnormalities including memory loss are found to be associated with pathological changes in connectivity and network neural structures. Alzheimer's disease (AD) interferes with memory formation from the molecular level, to synaptic functions and neural networks organization. Here, we determined whether brain connectivity of resting-state networks correlate with memory in patients affected by AD and in subjects with mild cognitive impairment (MCI). One hundred and forty-four subjects were recruited: 70 AD (MMSE Mini Mental State Evaluation 21.4), 50 MCI (MMSE 25.2) and 24 healthy subjects (MMSE 29.8). Undirected and weighted cortical brain network was built to evaluate graph core measures to obtain Small World parameters. eLORETA lagged linear connectivity as extracted by electroencephalogram (EEG) signals was used to weight the network. A high statistical correlation between Small World and memory performance was found. Namely, higher Small World characteristic in EEG gamma frequency band during the resting state, better performance in short-term memory as evaluated by the digit span tests. Such Small World pattern might represent a biomarker of working memory impairment in older people both in physiological and pathological conditions. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.
Cortical processes of speech illusions in the general population.
Schepers, E; Bodar, L; van Os, J; Lousberg, R
2016-10-18
There is evidence that experimentally elicited auditory illusions in the general population index risk for psychotic symptoms. As little is known about underlying cortical mechanisms of auditory illusions, an experiment was conducted to analyze processing of auditory illusions in a general population sample. In a follow-up design with two measurement moments (baseline and 6 months), participants (n = 83) underwent the White Noise task under simultaneous recording with a 14-lead EEG. An auditory illusion was defined as hearing any speech in a sound fragment containing white noise. A total number of 256 speech illusions (SI) were observed over the two measurements, with a high degree of stability of SI over time. There were 7 main effects of speech illusion on the EEG alpha band-the most significant indicating a decrease in activity at T3 (t = -4.05). Other EEG frequency bands (slow beta, fast beta, gamma, delta, theta) showed no significant associations with SI. SIs are characterized by reduced alpha activity in non-clinical populations. Given the association of SIs with psychosis, follow-up research is required to examine the possibility of reduced alpha activity mediating SIs in high risk and symptomatic populations.
Javed, Amna; Tiwana, Mohsin I.; Khan, Umar Shahbaz
2018-01-01
Brain Computer Interface (BCI) determines the intent of the user from a variety of electrophysiological signals. These signals, Slow Cortical Potentials, are recorded from scalp, and cortical neuronal activity is recorded by implanted electrodes. This paper is focused on design of an embedded system that is used to control the finger movements of an upper limb prosthesis using Electroencephalogram (EEG) signals. This is a follow-up of our previous research which explored the best method to classify three movements of fingers (thumb movement, index finger movement, and first movement). Two-stage logistic regression classifier exhibited the highest classification accuracy while Power Spectral Density (PSD) was used as a feature of the filtered signal. The EEG signal data set was recorded using a 14-channel electrode headset (a noninvasive BCI system) from right-handed, neurologically intact volunteers. Mu (commonly known as alpha waves) and Beta Rhythms (8–30 Hz) containing most of the movement data were retained through filtering using “Arduino Uno” microcontroller followed by 2-stage logistic regression to obtain a mean classification accuracy of 70%. PMID:29888252
Electroencephalographic Monitoring of Cognitive Fatigue
NASA Technical Reports Server (NTRS)
Montgomery, Leslie D.; Montgomery, Richard W.; Ku, Yu-Tsuan E.; Luna, Bernadette
2000-01-01
Mental exhaustion often poses a serious risk, even when performance is not apparently degraded. When such fatigue is associated with sustained performance of a single type of cognitive task it may be related to the metabolic energy required for sustained activation of cortical fields specialized for that task. The objective of this study was to adapt EEG to monitor cortical energy dissipation at a functionally specialized site over a long period of repetitive performance of a cognitive task.
Park, Hae-Jeong; Kwon, Jun Soo; Youn, Tak; Pae, Ji Soo; Kim, Jae-Jin; Kim, Myung-Sun; Ha, Kyoo-Seob
2002-11-01
We describe a method for the statistical parametric mapping of low resolution electromagnetic tomography (LORETA) using high-density electroencephalography (EEG) and individual magnetic resonance images (MRI) to investigate the characteristics of the mismatch negativity (MMN) generators in schizophrenia. LORETA, using a realistic head model of the boundary element method derived from the individual anatomy, estimated the current density maps from the scalp topography of the 128-channel EEG. From the current density maps that covered the whole cortical gray matter (up to 20,000 points), volumetric current density images were reconstructed. Intensity normalization of the smoothed current density images was used to reduce the confounding effect of subject specific global activity. After transforming each image into a standard stereotaxic space, we carried out statistical parametric mapping of the normalized current density images. We applied this method to the source localization of MMN in schizophrenia. The MMN generators, produced by a deviant tone of 1,200 Hz (5% of 1,600 trials) under the standard tone of 1,000 Hz, 80 dB binaural stimuli with 300 msec of inter-stimulus interval, were measured in 14 right-handed schizophrenic subjects and 14 age-, gender-, and handedness-matched controls. We found that the schizophrenic group exhibited significant current density reductions of MMN in the left superior temporal gyrus and the left inferior parietal gyrus (P < 0. 0005). This study is the first voxel-by-voxel statistical mapping of current density using individual MRI and high-density EEG. Copyright 2002 Wiley-Liss, Inc.
Continuous EEG source imaging enhances analysis of EEG-fMRI in focal epilepsy.
Vulliemoz, S; Rodionov, R; Carmichael, D W; Thornton, R; Guye, M; Lhatoo, S D; Michel, C M; Duncan, J S; Lemieux, L
2010-02-15
EEG-correlated fMRI (EEG-fMRI) studies can reveal haemodynamic changes associated with Interictal Epileptic Discharges (IED). Methodological improvements are needed to increase sensitivity and specificity for localising the epileptogenic zone. We investigated whether the estimated EEG source activity improved models of the BOLD changes in EEG-fMRI data, compared to conventional < event-related > designs based solely on the visual identification of IED. Ten patients with pharmaco-resistant focal epilepsy underwent EEG-fMRI. EEG Source Imaging (ESI) was performed on intra-fMRI averaged IED to identify the irritative zone. The continuous activity of this estimated IED source (cESI) over the entire recording was used for fMRI analysis (cESI model). The maps of BOLD signal changes explained by cESI were compared to results of the conventional IED-related model. ESI was concordant with non-invasive data in 13/15 different types of IED. The cESI model explained significant additional BOLD variance in regions concordant with video-EEG, structural MRI or, when available, intracranial EEG in 10/15 IED. The cESI model allowed better detection of the BOLD cluster, concordant with intracranial EEG in 4/7 IED, compared to the IED model. In 4 IED types, cESI-related BOLD signal changes were diffuse with a pattern suggestive of contamination of the source signal by artefacts, notably incompletely corrected motion and pulse artefact. In one IED type, there was no significant BOLD change with either model. Continuous EEG source imaging can improve the modelling of BOLD changes related to interictal epileptic activity and this may enhance the localisation of the irritative zone. Copyright 2009 Elsevier Inc. All rights reserved.
Algorithm based on the short-term Rényi entropy and IF estimation for noisy EEG signals analysis.
Lerga, Jonatan; Saulig, Nicoletta; Mozetič, Vladimir
2017-01-01
Stochastic electroencephalogram (EEG) signals are known to be nonstationary and often multicomponential. Detecting and extracting their components may help clinicians to localize brain neurological dysfunctionalities for patients with motor control disorders due to the fact that movement-related cortical activities are reflected in spectral EEG changes. A new algorithm for EEG signal components detection from its time-frequency distribution (TFD) has been proposed in this paper. The algorithm utilizes the modification of the Rényi entropy-based technique for number of components estimation, called short-term Rényi entropy (STRE), and upgraded by an iterative algorithm which was shown to enhance existing approaches. Combined with instantaneous frequency (IF) estimation, the proposed method was applied to EEG signal analysis both in noise-free and noisy environments for limb movements EEG signals, and was shown to be an efficient technique providing spectral description of brain activities at each electrode location up to moderate additive noise levels. Furthermore, the obtained information concerning the number of EEG signal components and their IFs show potentials to enhance diagnostics and treatment of neurological disorders for patients with motor control illnesses. Copyright © 2016 Elsevier Ltd. All rights reserved.
Quantitative EEG of Rapid-Eye-Movement Sleep: A Marker of Amnestic Mild Cognitive Impairment.
Brayet, Pauline; Petit, Dominique; Frauscher, Birgit; Gagnon, Jean-François; Gosselin, Nadia; Gagnon, Katia; Rouleau, Isabelle; Montplaisir, Jacques
2016-04-01
The basal forebrain cholinergic system, which is impaired in early Alzheimer's disease, is more crucial for the activation of rapid-eye-movement (REM) sleep electroencephalogram (EEG) than it is for wakefulness. Quantitative EEG from REM sleep might thus provide an earlier and more accurate marker of the development of Alzheimer's disease in subjects with mild cognitive impairment (MCI) subjects than that from wakefulness. To assess the superiority of the REM sleep EEG as a screening tool for preclinical Alzheimer's disease, 22 subjects with amnestic MCI (a-MCI; 63.9±7.7 years), 10 subjects with nonamnestic MCI (na-MCI; 64.1±4.5 years) and 32 controls (63.7±6.6 years) participated in the study. Spectral analyses of the waking EEG and REM sleep EEG were performed and the [(delta+theta)/(alpha+beta)] ratio was used to assess between-group differences in EEG slowing. The a-MCI subgroup showed EEG slowing in frontal lateral regions compared to both na-MCI and control groups. This EEG slowing was present in wakefulness (compared to controls) but was much more prominent in REM sleep. Moreover, the comparison between amnestic and nonamnestic subjects was found significant only for the REM sleep EEG. There was no difference in EEG power ratio between na-MCI and controls for any of the 7 cortical regions studied. These findings demonstrate the superiority of the REM sleep EEG in the discrimination between a-MCI and both na-MCI and control subjects. © EEG and Clinical Neuroscience Society (ECNS) 2015.
NASA Astrophysics Data System (ADS)
Phat Luu, Trieu; He, Yongtian; Brown, Samuel; Nakagome, Sho; Contreras-Vidal, Jose L.
2016-06-01
Objective. The control of human bipedal locomotion is of great interest to the field of lower-body brain-computer interfaces (BCIs) for gait rehabilitation. While the feasibility of closed-loop BCI systems for the control of a lower body exoskeleton has been recently shown, multi-day closed-loop neural decoding of human gait in a BCI virtual reality (BCI-VR) environment has yet to be demonstrated. BCI-VR systems provide valuable alternatives for movement rehabilitation when wearable robots are not desirable due to medical conditions, cost, accessibility, usability, or patient preferences. Approach. In this study, we propose a real-time closed-loop BCI that decodes lower limb joint angles from scalp electroencephalography (EEG) during treadmill walking to control a walking avatar in a virtual environment. Fluctuations in the amplitude of slow cortical potentials of EEG in the delta band (0.1-3 Hz) were used for prediction; thus, the EEG features correspond to time-domain amplitude modulated potentials in the delta band. Virtual kinematic perturbations resulting in asymmetric walking gait patterns of the avatar were also introduced to investigate gait adaptation using the closed-loop BCI-VR system over a period of eight days. Main results. Our results demonstrate the feasibility of using a closed-loop BCI to learn to control a walking avatar under normal and altered visuomotor perturbations, which involved cortical adaptations. The average decoding accuracies (Pearson’s r values) in real-time BCI across all subjects increased from (Hip: 0.18 ± 0.31 Knee: 0.23 ± 0.33 Ankle: 0.14 ± 0.22) on Day 1 to (Hip: 0.40 ± 0.24 Knee: 0.55 ± 0.20 Ankle: 0.29 ± 0.22) on Day 8. Significance. These findings have implications for the development of a real-time closed-loop EEG-based BCI-VR system for gait rehabilitation after stroke and for understanding cortical plasticity induced by a closed-loop BCI-VR system.
EEG neural correlates of goal-directed movement intention.
Pereira, Joana; Ofner, Patrick; Schwarz, Andreas; Sburlea, Andreea Ioana; Müller-Putz, Gernot R
2017-04-01
Using low-frequency time-domain electroencephalographic (EEG) signals we show, for the same type of upper limb movement, that goal-directed movements have different neural correlates than movements without a particular goal. In a reach-and-touch task, we explored the differences in the movement-related cortical potentials (MRCPs) between goal-directed and non-goal-directed movements. We evaluated if the detection of movement intention was influenced by the goal-directedness of the movement. In a single-trial classification procedure we found that classification accuracies are enhanced if there is a goal-directed movement in mind. Furthermore, by using the classifier patterns and estimating the corresponding brain sources, we show the importance of motor areas and the additional involvement of the posterior parietal lobule in the discrimination between goal-directed movements and non-goal-directed movements. We discuss next the potential contribution of our results on goal-directed movements to a more reliable brain-computer interface (BCI) control that facilitates recovery in spinal-cord injured or stroke end-users. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Panitz, Christian; Wacker, Jan; Stemmler, Gerhard; Mueller, Erik M
2013-09-01
Prior work on the coupling of cortical and cardiac responses to feedback demonstrated that feedback-evoked single-trial EEG magnitudes 300 ms post-stimulus predict the degree of subsequent cardiac acceleration. The main goal of the current study was to explore the neural sources of this phenomenon using (a) independent component analysis in conjunction with dipole fitting and (b) low resolution electromagnetic tomography (LORETA) in N=14 participants who performed a gambling task with feedback presented after each trial. It was shown that independent components localized near anterior cingulate cortex produced robust within-subjects correlations with feedback-evoked heart-period, suggesting that anterior cingulate cortex activity 300ms after feedback presentation predicts the strength of subsequent cardiac acceleration. Moreover, interindividual differences in evoked left insular cortex LORETA-estimated activity at around 300ms moderated within-subjects EEG-heart period correlations. These results suggest that key regions of central autonomic control are involved in cortico-cardiac coupling evoked by feedback stimuli. Copyright © 2013 Elsevier B.V. All rights reserved.
Aftanas, Ljubomir I; Pavlov, Sergey V
2005-01-01
The main objective of the present investigation was to examine how high trait anxiety would influence cortical EEG asymmetries under non-emotional conditions and while experiencing negative emotions. The 62-channel EEG was recorded in control (n=21) and high anxiety (HA, n=18) non-patient individuals. Results showed that in HA subjects, the lowest level of arousal (eyes closed) was associated with stronger right-sided parieto-temporal theta-1 (4-6 Hz) and beta-1 (12-18 Hz) activity, whereas increased non-emotional arousal (eyes open, viewing neutral movie clip) was marked by persisting favored right hemisphere beta-1 activity. In turn, viewing aversive movie clip by the HA group led to significant lateralized decrease of the right parieto-temporal beta-1 power, which was initially higher in the emotionally neutral conditions. The EEG data suggests that asymmetrical parieto-temporal theta-1 and beta-1 EEG activity might be better interpreted in terms of Gray's BAS and BIS theory.
Soroko, S I; Bekshaev, S S; Rozhkov, V P
2012-01-01
Traditional and original methods of EEG analysis were used to study the brain electrical activity maturation in 156 children and adolescents from 7 to 17 years old who represented the native (Koryaks and Evenks) and newcomers' populations living in severe climatic and geographic conditions of the Russian North-East. New data revealing age-, sex- and ethnic-related features in quantitative EEG parameters are presented. Markers are obtained that characterize alterations in the structure of interaction between different EEG rhythms. The results demonstrate age-dependent transformation of this structure separated in time for both different cortical areas and different EEG frequency bands. These alterations show time lag from 2 to 3 years in children of native population compared to the newcomers. The revealed differences are assumed to reflect geno-phenotypical features of morpho-functional CNS development in children of the native and newcomers' population that depend on strong adaptation tension for extreme environmental conditions.
Seizures and electroencephalography findings in 61 patients with fetal alcohol spectrum disorders.
Boronat, S; Vicente, M; Lainez, E; Sánchez-Montañez, A; Vázquez, E; Mangado, L; Martínez-Ribot, L; Del Campo, M
2017-01-01
Fetal alcohol spectrum disorders (FASD) cause neurodevelopmental abnormalities. However, publications about epilepsy and electroencephalographic features are scarce. In this study, we prospectively performed electroencephalography (EEG) and brain magnetic resonance (MR) imaging in 61 patients with diagnosis of FASD. One patient had multiple febrile seizures with normal EEGs. Fourteen children showed EEG anomalies, including slow background activity and interictal epileptiform discharges, focal and/or generalized, and 3 of them had epilepsy. In one patient, seizures were first detected during the EEG recording and one case had an encephalopathy with electrical status epilepticus during slow sleep (ESES). Focal interictal discharges in our patients did not imply the presence of underlying visible focal brain lesions in the neuroimaging studies, such as cortical dysplasia or polymicrogyria. However, they had nonspecific brain MR abnormalities, including corpus callosum hypoplasia, vermis hypoplasia or cavum septum pellucidum. The latter was significantly more frequent in the group with EEG abnormal findings (p < 0.01). Copyright © 2016 Elsevier Masson SAS. All rights reserved.
Reflection enhances creativity: Beneficial effects of idea evaluation on idea generation.
Hao, Ning; Ku, Yixuan; Liu, Meigui; Hu, Yi; Bodner, Mark; Grabner, Roland H; Fink, Andreas
2016-03-01
The present study aimed to explore the neural correlates underlying the effects of idea evaluation on idea generation in creative thinking. Participants were required to generate original uses of conventional objects (alternative uses task) during EEG recording. A reflection task (mentally evaluating the generated ideas) or a distraction task (object characteristics task) was inserted into the course of idea generation. Behavioral results revealed that participants generated ideas with higher originality after evaluating the generated ideas than after performing the distraction task. The EEG results revealed that idea evaluation was accompanied with upper alpha (10-13 Hz) synchronization, most prominent at frontal cortical sites. Moreover, upper alpha activity in frontal cortices during idea generation was enhanced after idea evaluation. These findings indicate that idea evaluation may elicit a state of heightened internal attention or top-down activity that facilitates efficient retrieval and integration of internal memory representations. Copyright © 2016 Elsevier Inc. All rights reserved.
Dependence of cerebral-cortex activation in women on environmental factors
NASA Astrophysics Data System (ADS)
Pavlov, K. I.; Mukhin, V. N.; Kamenskaya, V. G.; Klimenko, V. M.
2016-12-01
The investigation of female physiological reactions to different meteorological conditions and space weather is relevant, since there are little experimental findings in this field. The purpose of this work is to determine how the level of cerebral-cortex activity in women depends on the meteorological and cosmophysical parameters of weather and space processes. We studied electroencephalograms (EEGs) recorded at rest in the sitting position and with eyes closed. We performed four series of measurements of brain bioelectrical activity from February to June 2013. We found that the level of cortical activity recorded by EEG changed significantly during these 6 months. Significant differences were detected between the cortical activity and the parameters of weather and space processes; namely, an increase in the air temperature and a decrease in the wind speed and cosmic-ray energy result in a decrease in the activity rate of the right occipital lobe.
Individual neurophysiological profile in external effects investigation
NASA Astrophysics Data System (ADS)
Schastlivtseva, Daria; Tatiana Kotrovskaya, D..
Cortex biopotentials are the significant elements in human psychophysiological individuality. Considered that cortical biopotentials are diverse and individually stable, therefore there is the existence of certain dependence between the basic properties of higher nervous activity and cerebral bioelectric activity. The main purpose of the study was to reveal the individual neurophysiological profile and CNS initial functional state manifestation in human electroencephalogram (EEG) under effect of inert gases (argon, xenon, helium), hypoxia, pressure changes (0.02 and 0.2 MPa). We obtained 5-minute eyes closed background EEG on 19 scalp positions using Ag/AgCl electrodes mounted in an electrode cap. All EEG signals were re-referenced to average earlobes; Fast Furies Transformation analysis was used to calculate the relative power spectrum of delta-, theta-, alpha- and beta frequency band in artifact-free EEG. The study involved 26 healthy men who provided written informed consent, aged 20 to 35 years. Data obtained depend as individual EEG type and initial central nervous functional state as intensity, duration and mix of factors. Pronounced alpha rhythm in the raw EEG correlated with their adaptive capacity under studied factor exposure. Representation change and zonal distribution perversion of EEG alpha rhythm were accompanied by emotional instability, increased anxiety and difficulty adapting subjects. High power factor or combination factor with psychological and emotional or physical exertion minimizes individual EEG pattern.
Huart, Caroline; Legrain, Valéry; Hummel, Thomas; Rombaux, Philippe; Mouraux, André
2012-01-01
Background The recording of olfactory and trigeminal chemosensory event-related potentials (ERPs) has been proposed as an objective and non-invasive technique to study the cortical processing of odors in humans. Until now, the responses have been characterized mainly using across-trial averaging in the time domain. Unfortunately, chemosensory ERPs, in particular, olfactory ERPs, exhibit a relatively low signal-to-noise ratio. Hence, although the technique is increasingly used in basic research as well as in clinical practice to evaluate people suffering from olfactory disorders, its current clinical relevance remains very limited. Here, we used a time-frequency analysis based on the wavelet transform to reveal EEG responses that are not strictly phase-locked to onset of the chemosensory stimulus. We hypothesized that this approach would significantly enhance the signal-to-noise ratio of the EEG responses to chemosensory stimulation because, as compared to conventional time-domain averaging, (1) it is less sensitive to temporal jitter and (2) it can reveal non phase-locked EEG responses such as event-related synchronization and desynchronization. Methodology/Principal Findings EEG responses to selective trigeminal and olfactory stimulation were recorded in 11 normosmic subjects. A Morlet wavelet was used to characterize the elicited responses in the time-frequency domain. We found that this approach markedly improved the signal-to-noise ratio of the obtained EEG responses, in particular, following olfactory stimulation. Furthermore, the approach allowed characterizing non phase-locked components that could not be identified using conventional time-domain averaging. Conclusion/Significance By providing a more robust and complete view of how odors are represented in the human brain, our approach could constitute the basis for a robust tool to study olfaction, both for basic research and clinicians. PMID:22427997
Völker, Martin; Fiederer, Lukas D J; Berberich, Sofie; Hammer, Jiří; Behncke, Joos; Kršek, Pavel; Tomášek, Martin; Marusič, Petr; Reinacher, Peter C; Coenen, Volker A; Helias, Moritz; Schulze-Bonhage, Andreas; Burgard, Wolfram; Ball, Tonio
2018-06-01
Error detection in motor behavior is a fundamental cognitive function heavily relying on local cortical information processing. Neural activity in the high-gamma frequency band (HGB) closely reflects such local cortical processing, but little is known about its role in error processing, particularly in the healthy human brain. Here we characterize the error-related response of the human brain based on data obtained with noninvasive EEG optimized for HGB mapping in 31 healthy subjects (15 females, 16 males), and additional intracranial EEG data from 9 epilepsy patients (4 females, 5 males). Our findings reveal a multiscale picture of the global and local dynamics of error-related HGB activity in the human brain. On the global level as reflected in the noninvasive EEG, the error-related response started with an early component dominated by anterior brain regions, followed by a shift to parietal regions, and a subsequent phase characterized by sustained parietal HGB activity. This phase lasted for more than 1 s after the error onset. On the local level reflected in the intracranial EEG, a cascade of both transient and sustained error-related responses involved an even more extended network, spanning beyond frontal and parietal regions to the insula and the hippocampus. HGB mapping appeared especially well suited to investigate late, sustained components of the error response, possibly linked to downstream functional stages such as error-related learning and behavioral adaptation. Our findings establish the basic spatio-temporal properties of HGB activity as a neural correlate of error processing, complementing traditional error-related potential studies. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Cortical oscillatory activity and the induction of plasticity in the human motor cortex.
McAllister, Suzanne M; Rothwell, John C; Ridding, Michael C
2011-05-01
Repetitive transcranial magnetic stimulation paradigms such as continuous theta burst stimulation (cTBS) induce long-term potentiation- and long-term depression-like plasticity in the human motor cortex. However, responses to cTBS are highly variable and may depend on the activity of the cortex at the time of stimulation. We investigated whether power in different electroencephalogram (EEG) frequency bands predicted the response to subsequent cTBS, and conversely whether cTBS had after-effects on the EEG. cTBS may utilize similar mechanisms of plasticity to motor learning; thus, we conducted a parallel set of experiments to test whether ongoing electroencephalography could predict performance of a visuomotor training task, and whether training itself had effects on the EEG. Motor evoked potentials (MEPs) provided an index of cortical excitability pre- and post-intervention. The EEG was recorded over the motor cortex pre- and post-intervention, and power spectra were computed. cTBS reduced MEP amplitudes; however, baseline power in the delta, theta, alpha or beta frequencies did not predict responses to cTBS or learning of the visuomotor training task. cTBS had no effect on delta, theta, alpha or beta power. In contrast, there was an increase in alpha power following visuomotor training that was positively correlated with changes in MEP amplitude post-training. The results suggest that the EEG is not a useful state-marker for predicting responses to plasticity-inducing paradigms. The correlation between alpha power and changes in corticospinal excitability following visuomotor training requires further investigation, but may be related to disengagement of the somatosensory system important for motor memory consolidation. © 2011 The Authors. European Journal of Neuroscience © 2011 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.
Wu, Lei; Eichele, Tom; Calhoun, Vince D
2010-10-01
Concurrent EEG-fMRI studies have provided increasing details of the dynamics of intrinsic brain activity during the resting state. Here, we investigate a prominent effect in EEG during relaxed resting, i.e. the increase of the alpha power when the eyes are closed compared to when the eyes are open. This phenomenon is related to changes in thalamo-cortical and cortico-cortical synchronization. In order to investigate possible changes to EEG-fMRI coupling and fMRI functional connectivity during the two states we adopted a data-driven approach that fuses the multimodal data on the basis of parallel ICA decompositions of the fMRI data in the spatial domain and of the EEG data in the spectral domain. The power variation of a posterior alpha component was used as a reference function to deconvolve the hemodynamic responses from occipital, frontal, temporal, and subcortical fMRI components. Additionally, we computed the functional connectivity between these components. The results showed widespread alpha hemodynamic responses and high functional connectivity during eyes-closed (EC) rest, while eyes open (EO) resting abolished many of the hemodynamic responses and markedly decreased functional connectivity. These data suggest that generation of local hemodynamic responses is highly sensitive to state changes that do not involve changes of mental effort or awareness. They also indicate the localized power differences in posterior alpha between EO and EC in resting state data are accompanied by spatially widespread amplitude changes in hemodynamic responses and inter-regional functional connectivity, i.e. low frequency hemodynamic signals display an equivalent of alpha reactivity. Copyright 2010 Elsevier Inc. All rights reserved.
Electrocortical correlates of human level-ground, slope, and stair walking
Nakagome, Sho; Zhu, Fangshi; Contreras-Vidal, Jose L.
2017-01-01
This study investigated electrocortical dynamics of human walking across different unconstrained walking conditions (i.e., level ground (LW), ramp ascent (RA), and stair ascent (SA)). Non-invasive active-electrode scalp electroencephalography (EEG) signals were recorded and a systematic EEG processing method was implemented to reduce artifacts. Source localization combined with independent component analysis and k-means clustering revealed the involvement of four clusters in the brain during the walking tasks: Left and Right Occipital Lobe (LOL, ROL), Posterior Parietal Cortex (PPC), and Central Sensorimotor Cortex (SMC). Results showed that the changes of spectral power in the PPC and SMC clusters were associated with the level of motor task demands. Specifically, we observed α and β suppression at the beginning of the gait cycle in both SA and RA walking (relative to LW) in the SMC. Additionally, we observed significant β rebound (synchronization) at the initial swing phase of the gait cycle, which may be indicative of active cortical signaling involved in maintaining the current locomotor state. An increase of low γ band power in this cluster was also found in SA walking. In the PPC, the low γ band power increased with the level of task demands (from LW to RA and SA). Additionally, our results provide evidence that electrocortical amplitude modulations (relative to average gait cycle) are correlated with the level of difficulty in locomotion tasks. Specifically, the modulations in the PPC shifted to higher frequency bands when the subjects walked in RA and SA conditions. Moreover, low γ modulations in the central sensorimotor area were observed in the LW walking and shifted to lower frequency bands in RA and SA walking. These findings extend our understanding of cortical dynamics of human walking at different level of locomotion task demands and reinforces the growing body of literature supporting a shared-control paradigm between spinal and cortical networks during locomotion. PMID:29190704
[11C]Flumazenil PET in patients with epilepsy with dual pathology.
Juhász, C; Nagy, F; Muzik, O; Watson, C; Shah, J; Chugani, H T
1999-05-01
Coexistence of hippocampal sclerosis and a potentially epileptogenic cortical lesion is referred to as dual pathology and can be responsible for poor surgical outcome in patients with medically intractable partial epilepsy. [11C]Flumazenil (FMZ) positron emission tomography (PET) is a sensitive method for visualizing epileptogenic foci. In this study of 12 patients with dual pathology, we addressed the sensitivity of FMZ PET to detect hippocampal abnormalities and compared magnetic resonance imaging (MRI) with visual as well as quantitative FMZ PET findings. All patients underwent volumetric MRI, prolonged video-EEG monitoring, and glucose metabolism PET before the FMZ PET. MRI-coregistered partial volume-corrected PET images were used to measure FMZ-binding asymmetries by using asymmetry indices (AIs) in the whole hippocampus and in three (anterior, middle, and posterior) hippocampal subregions. Cortical sites of decreased FMZ binding also were evaluated by using AIs for regions with MRI-verified cortical lesions as well as for non-lesional areas with visually detected asymmetry. Abnormally decreased FMZ binding could be detected by quantitative analysis in the atrophic hippocampus of all 12 patients, including three patients with discordant or inconclusive EEG findings. Decreased FMZ binding was restricted to only one subregion of the hippocampus in three patients. Areas of decreased cortical FMZ binding were obvious visually in all patients. Decreased FMZ binding was detected visually in nonlesional cortical areas in four patients. The AIs for these nonlesional regions with visual asymmetry were significantly lower than those for regions showing MRI lesions (paired t test, p = 0.0075). Visual as well as quantitative analyses of FMZ-binding asymmetry are sensitive methods to detect decreased benzodiazepine-receptor binding in the hippocampus and neocortex of patients with dual pathology. MRI-defined hippocampal atrophy is always associated with decreased FMZ binding, although the latter may be localized to only one sub-region within the hippocampus. FMZ PET abnormalities can occur in areas with normal appearance on MRI, but FMZ-binding asymmetry of these regions is lower when compared with that of lesional areas. FMZ PET can be especially helpful when MRI and EEG findings of patients with intractable epilepsy are discordant.
NASA Astrophysics Data System (ADS)
Hu, Jin; Tian, Jie; Pan, Xiaohong; Liu, Jiangang
2007-03-01
The purpose of this paper is to compare between EEG source localization and fMRI during emotional processing. 108 pictures for EEG (categorized as positive, negative and neutral) and 72 pictures for fMRI were presented to 24 healthy, right-handed subjects. The fMRI data were analyzed using statistical parametric mapping with SPM2. LORETA was applied to grand averaged ERP data to localize intracranial sources. Statistical analysis was implemented to compare spatiotemporal activation of fMRI and EEG. The fMRI results are in accordance with EEG source localization to some extent, while part of mismatch in localization between the two methods was also observed. In the future we should apply the method for simultaneous recording of EEG and fMRI to our study.
Kozunov, Vladimir V.; Ossadtchi, Alexei
2015-01-01
Although MEG/EEG signals are highly variable between subjects, they allow characterizing systematic changes of cortical activity in both space and time. Traditionally a two-step procedure is used. The first step is a transition from sensor to source space by the means of solving an ill-posed inverse problem for each subject individually. The second is mapping of cortical regions consistently active across subjects. In practice the first step often leads to a set of active cortical regions whose location and timecourses display a great amount of interindividual variability hindering the subsequent group analysis. We propose Group Analysis Leads to Accuracy (GALA)—a solution that combines the two steps into one. GALA takes advantage of individual variations of cortical geometry and sensor locations. It exploits the ensuing variability in electromagnetic forward model as a source of additional information. We assume that for different subjects functionally identical cortical regions are located in close proximity and partially overlap and their timecourses are correlated. This relaxed similarity constraint on the inverse solution can be expressed within a probabilistic framework, allowing for an iterative algorithm solving the inverse problem jointly for all subjects. A systematic simulation study showed that GALA, as compared with the standard min-norm approach, improves accuracy of true activity recovery, when accuracy is assessed both in terms of spatial proximity of the estimated and true activations and correct specification of spatial extent of the activated regions. This improvement obtained without using any noise normalization techniques for both solutions, preserved for a wide range of between-subject variations in both spatial and temporal features of regional activation. The corresponding activation timecourses exhibit significantly higher similarity across subjects. Similar results were obtained for a real MEG dataset of face-specific evoked responses. PMID:25954141
Cortical processing during smartphone text messaging.
Tatum, William O; DiCiaccio, Benedetto; Yelvington, Kirsten H
2016-06-01
The objective of this study was to report the EEG features of text messaging using smartphones. One hundred twenty-nine patients were prospectively evaluated during video-EEG monitoring (VEM) over 16months. A reproducible texting rhythm (TR) present during active text messaging with a smartphone was compared with passive and forced audio telephone use, thumb/finger movements, cognitive testing/calculation, scanning eye movements, and speech/language tasks in patients with and without epilepsy. Statistical significance was set at p<0.05. Twenty-seven patients with a TR were identified from a cohort of 129 (93 female, mean age: 36; range: 18-71) unselected VEM patients. Fifty-three out of 129 patients had epileptic seizures (ES), 74/129 had nonepileptic seizures (NES), and 2/129 were dual-diagnosed. A reproducible TR was present in 27/129 (20.9%) specific to text messaging (p<0.0001) and present in 28% of patients with ES and 16% of patients with NES (p=NS). The TR was absent during independent tasks and audio cellular telephone use (p<0.0001). Age, gender, epilepsy type, MRI results, and EEG lateralization in patients with focal seizures were unrelated (p=NS). Our results suggest that the TR on scalp EEG represents a novel technology-specific neurophysiological alteration of brain networks. We propose that cortical processing in the contemporary brain is uniquely activated by the use of PEDs. These findings have practical implications that could impact industry and research in nonverbal communication. Copyright © 2016 Elsevier Inc. All rights reserved.
Boulogne, Sébastien; Andre-Obadia, Nathalie; Kimiskidis, Vasilios K; Ryvlin, Philippe; Rheims, Sylvain
2016-11-01
Paired-pulse (PP) paradigms are commonly employed to assess in vivo cortical excitability using transcranial magnetic stimulation (TMS) to stimulate the primary motor cortex and modulate the induced motor evoked potential (MEP). Single-pulse cortical direct electrical stimulation (DES) during intracerebral EEG monitoring allows the investigation of brain connectivity by eliciting cortico-cortical evoked potentials (CCEPs). However, PP paradigm using intracerebral DES has rarely been reported and has never been previously compared with TMS. The work was intended (i) to verify that the well-established modulations of MEPs following PP TMS remain similar using DES in the motor cortex, and (ii) to evaluate if a similar pattern could be observed in distant cortico-cortical connections through modulations of CCEP. Three patients undergoing intracerebral EEG monitoring with electrodes implanted in the central region were studied. Single-pulse DES (1-3 mA, 1 ms, 0.2 Hz) and PP DES using six interstimulus intervals (5, 15, 30, 50, 100, and 200 ms) in the motor cortex with concomitant recording of CCEPs and MEPs in contralateral muscles were performed. Finally, a navigated PP TMS session targeted the intracranial stimulation site to record TMS-induced MEPs in two patients. MEP modulations elicited by PP intracerebral DES proved similar among the three patients and to those obtained by PP TMS. CCEP modulations elicited by PP intracerebral DES usually showed a pattern comparable to that of MEP, although a different pattern could be observed occasionally. PP intracerebral DES seems to involve excitatory and inhibitory mechanisms similar to PP TMS and allows the recording of intracortical inhibition and facilitation modulation on cortico-cortical connections. Hum Brain Mapp 37:3767-3778, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Tracking the time-varying cortical connectivity patterns by adaptive multivariate estimators.
Astolfi, L; Cincotti, F; Mattia, D; De Vico Fallani, F; Tocci, A; Colosimo, A; Salinari, S; Marciani, M G; Hesse, W; Witte, H; Ursino, M; Zavaglia, M; Babiloni, F
2008-03-01
The directed transfer function (DTF) and the partial directed coherence (PDC) are frequency-domain estimators that are able to describe interactions between cortical areas in terms of the concept of Granger causality. However, the classical estimation of these methods is based on the multivariate autoregressive modelling (MVAR) of time series, which requires the stationarity of the signals. In this way, transient pathways of information transfer remains hidden. The objective of this study is to test a time-varying multivariate method for the estimation of rapidly changing connectivity relationships between cortical areas of the human brain, based on DTF/PDC and on the use of adaptive MVAR modelling (AMVAR) and to apply it to a set of real high resolution EEG data. This approach will allow the observation of rapidly changing influences between the cortical areas during the execution of a task. The simulation results indicated that time-varying DTF and PDC are able to estimate correctly the imposed connectivity patterns under reasonable operative conditions of signal-to-noise ratio (SNR) ad number of trials. An SNR of five and a number of trials of at least 20 provide a good accuracy in the estimation. After testing the method by the simulation study, we provide an application to the cortical estimations obtained from high resolution EEG data recorded from a group of healthy subject during a combined foot-lips movement and present the time-varying connectivity patterns resulting from the application of both DTF and PDC. Two different cortical networks were detected with the proposed methods, one constant across the task and the other evolving during the preparation of the joint movement.
Barlow, Steven M; Jegatheesan, Priya; Weiss, Sunshine; Govindaswami, Balaji; Wang, Jingyan; Lee, Jaehoon; Oder, Austin; Song, Dongli
2013-01-01
Background Controlled somatosensory stimulation strategies have demonstrated merit in developing oral feeding skills in premature infants who lack a functional suck, however, the effects of orosensory entrainment stimulation on electrocortical dynamics is unknown. Objective To determine the effects of servo-controlled pneumatic orocutaneous stimulation presented during gavage feedings on the modulation of aEEG and rEEG activity. Methods Two-channel EEG recordings were collected during 180 sessions that included orocutaneous stimulation and non-stimulation epochs among 22 preterm infants (mean gestational age = 28.56 weeks) who were randomized to treatment and control ‘sham’ conditions. The study was initiated at around 32 weeks post-menstrual age (PMA). The raw EEG was transformed into amplitude-integrated EEG (aEEG) margins, and range-EEG (rEEG) amplitude bands measured at 1-minute intervals and subjected to a mixed models statistical analysis. Results Multiple significant effects were observed in the processed EEG during and immediately following 3-minute periods of orocutaneous stimulation, including modulation of the upper and lower margins of the aEEG, and a reorganization of rEEG with an apparent shift from amplitude bands D and E to band C throughout the 23-minute recording period that followed the first stimulus block when compared to the sham condition. Cortical asymmetry also was apparent in both EEG measures. Conclusions Orocutaneous stimulation represents a salient trigeminal input which has both short- and long-term effects in modulating electrocortical activity, and thus, is hypothesized to represent a form of neural adaptation or plasticity that may benefit the preterm infant during this critical period of brain maturation. PMID:24310443
Thibaut, Aurore; Simis, Marcel; Battistella, Linamara Rizzo; Fanciullacci, Chiara; Bertolucci, Federica; Huerta-Gutierrez, Rodrigo; Chisari, Carmelo; Fregni, Felipe
2017-01-01
What determines motor recovery in stroke is still unknown and finding markers that could predict and improve stroke recovery is a challenge. In this study, we aimed at understanding the neural mechanisms of motor function recovery after stroke using neurophysiological markers by means of cortical excitability (transcranial magnetic stimulation—TMS) and brain oscillations (electroencephalography—EEG). In this cross-sectional study, 55 subjects with chronic stroke (62 ± 14 yo, 17 women, 32 ± 42 months post-stroke) were recruited in two sites. We analyzed TMS measures (i.e., motor threshold—MT—of the affected and unaffected sides) and EEG variables (i.e., power spectrum in different frequency bands and different brain regions of the affected and unaffected hemispheres) and their correlation with motor impairment as measured by Fugl-Meyer. Multiple univariate and multivariate linear regression analyses were performed to identify the predictors of good motor function. A significant interaction effect of MT in the affected hemisphere and power in beta bandwidth over the central region for both affected and unaffected hemispheres was found. We identified that motor function positively correlates with beta rhythm over the central region of the unaffected hemisphere, while it negatively correlates with beta rhythm in the affected hemisphere. Our results suggest that cortical activity in the affected and unaffected hemisphere measured by EEG provides new insights on the association between high-frequency rhythms and motor impairment, highlighting the role of an excess of beta in the affected central cortical region in poor motor function in stroke recovery. PMID:28539912
Electrical Brain Responses to an Auditory Illusion and the Impact of Musical Expertise
Ioannou, Christos I.; Pereda, Ernesto; Lindsen, Job P.; Bhattacharya, Joydeep
2015-01-01
The presentation of two sinusoidal tones, one to each ear, with a slight frequency mismatch yields an auditory illusion of a beating frequency equal to the frequency difference between the two tones; this is known as binaural beat (BB). The effect of brief BB stimulation on scalp EEG is not conclusively demonstrated. Further, no studies have examined the impact of musical training associated with BB stimulation, yet musicians' brains are often associated with enhanced auditory processing. In this study, we analysed EEG brain responses from two groups, musicians and non-musicians, when stimulated by short presentation (1 min) of binaural beats with beat frequency varying from 1 Hz to 48 Hz. We focused our analysis on alpha and gamma band EEG signals, and they were analysed in terms of spectral power, and functional connectivity as measured by two phase synchrony based measures, phase locking value and phase lag index. Finally, these measures were used to characterize the degree of centrality, segregation and integration of the functional brain network. We found that beat frequencies belonging to alpha band produced the most significant steady-state responses across groups. Further, processing of low frequency (delta, theta, alpha) binaural beats had significant impact on cortical network patterns in the alpha band oscillations. Altogether these results provide a neurophysiological account of cortical responses to BB stimulation at varying frequencies, and demonstrate a modulation of cortico-cortical connectivity in musicians' brains, and further suggest a kind of neuronal entrainment of a linear and nonlinear relationship to the beating frequencies. PMID:26065708
Electrical Brain Responses to an Auditory Illusion and the Impact of Musical Expertise.
Ioannou, Christos I; Pereda, Ernesto; Lindsen, Job P; Bhattacharya, Joydeep
2015-01-01
The presentation of two sinusoidal tones, one to each ear, with a slight frequency mismatch yields an auditory illusion of a beating frequency equal to the frequency difference between the two tones; this is known as binaural beat (BB). The effect of brief BB stimulation on scalp EEG is not conclusively demonstrated. Further, no studies have examined the impact of musical training associated with BB stimulation, yet musicians' brains are often associated with enhanced auditory processing. In this study, we analysed EEG brain responses from two groups, musicians and non-musicians, when stimulated by short presentation (1 min) of binaural beats with beat frequency varying from 1 Hz to 48 Hz. We focused our analysis on alpha and gamma band EEG signals, and they were analysed in terms of spectral power, and functional connectivity as measured by two phase synchrony based measures, phase locking value and phase lag index. Finally, these measures were used to characterize the degree of centrality, segregation and integration of the functional brain network. We found that beat frequencies belonging to alpha band produced the most significant steady-state responses across groups. Further, processing of low frequency (delta, theta, alpha) binaural beats had significant impact on cortical network patterns in the alpha band oscillations. Altogether these results provide a neurophysiological account of cortical responses to BB stimulation at varying frequencies, and demonstrate a modulation of cortico-cortical connectivity in musicians' brains, and further suggest a kind of neuronal entrainment of a linear and nonlinear relationship to the beating frequencies.
Thibaut, Aurore; Russo, Cristina; Hurtado-Puerto, Aura Maria; Morales-Quezada, Jorge Leon; Deitos, Alícia; Petrozza, John Christopher; Freedman, Steven; Fregni, Felipe
2017-01-01
Chronic visceral pain (CVP) syndromes are persistently painful disorders with a remarkable lack of effective treatment options. This study aimed at evaluating the effects of different neuromodulation techniques in patients with CVP on cortical activity, through electreocephalography (EEG) and on pain perception, through clinical tests. A pilot crossover randomized controlled study. Out-patient. Adults with CVP (>3 months). Participants received four interventions in a randomized order: (1) transcranial pulsed current stimulation (tPCS) and active transcranial direct current stimulation (tDCS) combined, (2) tPCS alone, (3) tDCS alone, and (4) sham condition. Resting state quantitative electroencephalography (qEEG) and pain assessments were performed before and after each intervention. Results were compared with a cohort of 47 healthy controls. We enrolled six patients with CVP for a total of 21 visits completed. Compared with healthy participants, patients with CVP showed altered cortical activity characterized by increased power in theta, alpha and beta bands, and a significant reduction in the alpha/beta ratio. Regarding tES, the combination of tDCS with tPCS had no effect on power in any of the bandwidths, nor brain regions. Comparing tPCS with tDCS alone, we found that tPCS induced higher increase in power within the theta and alpha bandwidths. This study confirms that patients with CVP present abnormal EEG-indexed cortical activity compared with healthy controls. Moreover, we showed that combining two types of neurostimulation techniques had no effect, whereas the two interventions, when applied individually, have different neural signatures.
Perdikis, Dionysios; Müller, Viktor; Blanc, Jean-Luc; Huys, Raoul; Temprado, Jean-Jacques
2015-01-01
Abstract The present work focused on the study of fluctuations of cortical activity across time scales in young and older healthy adults. The main objective was to offer a comprehensive characterization of the changes of brain (cortical) signal variability during aging, and to make the link with known underlying structural, neurophysiological, and functional modifications, as well as aging theories. We analyzed electroencephalogram (EEG) data of young and elderly adults, which were collected at resting state and during an auditory oddball task. We used a wide battery of metrics that typically are separately applied in the literature, and we compared them with more specific ones that address their limits. Our procedure aimed to overcome some of the methodological limitations of earlier studies and verify whether previous findings can be reproduced and extended to different experimental conditions. In both rest and task conditions, our results mainly revealed that EEG signals presented systematic age-related changes that were time-scale-dependent with regard to the structure of fluctuations (complexity) but not with regard to their magnitude. Namely, compared with young adults, the cortical fluctuations of the elderly were more complex at shorter time scales, but less complex at longer scales, although always showing a lower variance. Additionally, the elderly showed signs of spatial, as well as between, experimental conditions dedifferentiation. By integrating these so far isolated findings across time scales, metrics, and conditions, the present study offers an overview of age-related changes in the fluctuation electrocortical activity while making the link with underlying brain dynamics. PMID:26464983
Thibaut, Aurore; Simis, Marcel; Battistella, Linamara Rizzo; Fanciullacci, Chiara; Bertolucci, Federica; Huerta-Gutierrez, Rodrigo; Chisari, Carmelo; Fregni, Felipe
2017-01-01
What determines motor recovery in stroke is still unknown and finding markers that could predict and improve stroke recovery is a challenge. In this study, we aimed at understanding the neural mechanisms of motor function recovery after stroke using neurophysiological markers by means of cortical excitability (transcranial magnetic stimulation-TMS) and brain oscillations (electroencephalography-EEG). In this cross-sectional study, 55 subjects with chronic stroke (62 ± 14 yo, 17 women, 32 ± 42 months post-stroke) were recruited in two sites. We analyzed TMS measures (i.e., motor threshold-MT-of the affected and unaffected sides) and EEG variables (i.e., power spectrum in different frequency bands and different brain regions of the affected and unaffected hemispheres) and their correlation with motor impairment as measured by Fugl-Meyer. Multiple univariate and multivariate linear regression analyses were performed to identify the predictors of good motor function. A significant interaction effect of MT in the affected hemisphere and power in beta bandwidth over the central region for both affected and unaffected hemispheres was found. We identified that motor function positively correlates with beta rhythm over the central region of the unaffected hemisphere, while it negatively correlates with beta rhythm in the affected hemisphere. Our results suggest that cortical activity in the affected and unaffected hemisphere measured by EEG provides new insights on the association between high-frequency rhythms and motor impairment, highlighting the role of an excess of beta in the affected central cortical region in poor motor function in stroke recovery.
Effects of somatosensory electrical stimulation on motor function and cortical oscillations.
Tu-Chan, Adelyn P; Natraj, Nikhilesh; Godlove, Jason; Abrams, Gary; Ganguly, Karunesh
2017-11-13
Few patients recover full hand dexterity after an acquired brain injury such as stroke. Repetitive somatosensory electrical stimulation (SES) is a promising method to promote recovery of hand function. However, studies using SES have largely focused on gross motor function; it remains unclear if it can modulate distal hand functions such as finger individuation. The specific goal of this study was to monitor the effects of SES on individuation as well as on cortical oscillations measured using EEG, with the additional goal of identifying neurophysiological biomarkers. Eight participants with a history of acquired brain injury and distal upper limb motor impairments received a single two-hour session of SES using transcutaneous electrical nerve stimulation. Pre- and post-intervention assessments consisted of the Action Research Arm Test (ARAT), finger fractionation, pinch force, and the modified Ashworth scale (MAS), along with resting-state EEG monitoring. SES was associated with significant improvements in ARAT, MAS and finger fractionation. Moreover, SES was associated with a decrease in low frequency (0.9-4 Hz delta) ipsilesional parietomotor EEG power. Interestingly, changes in ipsilesional motor theta (4.8-7.9 Hz) and alpha (8.8-11.7 Hz) power were significantly correlated with finger fractionation improvements when using a multivariate model. We show the positive effects of SES on finger individuation and identify cortical oscillations that may be important electrophysiological biomarkers of individual responsiveness to SES. These biomarkers can be potential targets when customizing SES parameters to individuals with hand dexterity deficits. NCT03176550; retrospectively registered.
Ertl, M; Moser, M; Boegle, R; Conrad, J; Zu Eulenburg, P; Dieterich, M
2017-07-15
The vestibular organ senses linear and rotational acceleration of the head during active and passive motion. These signals are necessary for bipedal locomotion, navigation, the coordination of eye and head movements in 3D space. The temporal dynamics of vestibular processing in cortical structures have hardly been studied in humans, let alone with natural stimulation. The aim was to investigate the cortical vestibular network related to natural otolith stimulation using a hexapod motion platform. We conducted two experiments, 1. to estimate the sources of the vestibular evoked potentials (VestEPs) by means of distributed source localization (n=49), and 2. to reveal modulations of the VestEPs through the underlying acceleration intensity (n=24). For both experiments subjects were accelerated along the main axis (left/right, up/down, fore/aft) while the EEG was recorded. We were able to identify five VestEPs (P1, N1, P2, N2, P3) with latencies between 38 and 461 ms as well as an evoked beta-band response peaking with a latency of 68 ms in all subjects and for all acceleration directions. Source localization gave the cingulate sulcus visual (CSv) area and the opercular-insular region as the main origin of the evoked potentials. No lateralization effects due to handedness could be observed. In the second experiment, area CSv was shown to be integral in the processing of acceleration intensities as sensed by the otolith organs, hinting at its potential role in ego-motion detection. These robust VestEPs could be used to investigate the mechanisms of inter-regional interaction in the natural context of vestibular processing and multisensory integration. Copyright © 2017 Elsevier Inc. All rights reserved.
Rissling, Anthony J.; Miyakoshi, Makoto; Sugar, Catherine A.; Braff, David L.; Makeig, Scott; Light, Gregory A.
2014-01-01
Although sensory processing abnormalities contribute to widespread cognitive and psychosocial impairments in schizophrenia (SZ) patients, scalp-channel measures of averaged event-related potentials (ERPs) mix contributions from distinct cortical source-area generators, diluting the functional relevance of channel-based ERP measures. SZ patients (n = 42) and non-psychiatric comparison subjects (n = 47) participated in a passive auditory duration oddball paradigm, eliciting a triphasic (Deviant−Standard) tone ERP difference complex, here termed the auditory deviance response (ADR), comprised of a mid-frontal mismatch negativity (MMN), P3a positivity, and re-orienting negativity (RON) peak sequence. To identify its cortical sources and to assess possible relationships between their response contributions and clinical SZ measures, we applied independent component analysis to the continuous 68-channel EEG data and clustered the resulting independent components (ICs) across subjects on spectral, ERP, and topographic similarities. Six IC clusters centered in right superior temporal, right inferior frontal, ventral mid-cingulate, anterior cingulate, medial orbitofrontal, and dorsal mid-cingulate cortex each made triphasic response contributions. Although correlations between measures of SZ clinical, cognitive, and psychosocial functioning and standard (Fz) scalp-channel ADR peak measures were weak or absent, for at least four IC clusters one or more significant correlations emerged. In particular, differences in MMN peak amplitude in the right superior temporal IC cluster accounted for 48% of the variance in SZ-subject performance on tasks necessary for real-world functioning and medial orbitofrontal cluster P3a amplitude accounted for 40%/54% of SZ-subject variance in positive/negative symptoms. Thus, source-resolved auditory deviance response measures including MMN may be highly sensitive to SZ clinical, cognitive, and functional characteristics. PMID:25379456
Regional Slow Waves and Spindles in Human Sleep
Nir, Yuval; Staba, Richard J.; Andrillon, Thomas; Vyazovskiy, Vladyslav V.; Cirelli, Chiara; Fried, Itzhak; Tononi, Giulio
2011-01-01
SUMMARY The most prominent EEG events in sleep are slow waves, reflecting a slow (<1 Hz) oscillation between up and down states in cortical neurons. It is unknown whether slow oscillations are synchronous across the majority or the minority of brain regions—are they a global or local phenomenon? To examine this, we recorded simultaneously scalp EEG, intracerebral EEG, and unit firing in multiple brain regions of neurosurgical patients. We find that most sleep slow waves and the underlying active and inactive neuronal states occur locally. Thus, especially in late sleep, some regions can be active while others are silent. We also find that slow waves can propagate, usually from medial prefrontal cortex to the medial temporal lobe and hippocampus. Sleep spindles, the other hallmark of NREM sleep EEG, are likewise predominantly local. Thus, intracerebral communication during sleep is constrained because slow and spindle oscillations often occur out-of-phase in different brain regions. PMID:21482364
Ragazzoni, Aldo; Pirulli, Cornelia; Veniero, Domenica; Feurra, Matteo; Cincotta, Massimo; Giovannelli, Fabio; Chiaramonti, Roberta; Lino, Mario; Rossi, Simone; Miniussi, Carlo
2013-01-01
Differential diagnoses between vegetative and minimally conscious states (VS and MCS, respectively) are frequently incorrect. Hence, further research is necessary to improve the diagnostic accuracy at the bedside. The main neuropathological feature of VS is the diffuse damage of cortical and subcortical connections. Starting with this premise, we used electroencephalography (EEG) recordings to evaluate the cortical reactivity and effective connectivity during transcranial magnetic stimulation (TMS) in chronic VS or MCS patients. Moreover, the TMS-EEG data were compared with the results from standard somatosensory-evoked potentials (SEPs) and event-related potentials (ERPs). Thirteen patients with chronic consciousness disorders were examined at their bedsides. A group of healthy volunteers served as the control group. The amplitudes (reactivity) and scalp distributions (connectivity) of the cortical potentials evoked by TMS (TEPs) of the primary motor cortex were measured. Short-latency median nerve SEPs and auditory ERPs were also recorded. Reproducible TEPs were present in all control subjects in both the ipsilateral and the contralateral hemispheres relative to the site of the TMS. The amplitudes of the ipsilateral and contralateral TEPs were reduced in four of the five MCS patients, and the TEPs were bilaterally absent in one MCS patient. Among the VS patients, five did not manifest ipsilateral or contralateral TEPs, and three of the patients exhibited only ipsilateral TEPs with reduced amplitudes. The SEPs were altered in five VS and two MCS patients but did not correlate with the clinical diagnosis. The ERPs were impaired in all patients and did not correlate with the clinical diagnosis. These TEP results suggest that cortical reactivity and connectivity are severely impaired in all VS patients, whereas in most MCS patients, the TEPs are preserved but with abnormal features. Therefore, TEPs may add valuable information to the current clinical and neurophysiological assessment of chronic consciousness disorders.
Ragazzoni, Aldo; Pirulli, Cornelia; Veniero, Domenica; Feurra, Matteo; Cincotta, Massimo; Giovannelli, Fabio; Chiaramonti, Roberta; Lino, Mario; Rossi, Simone; Miniussi, Carlo
2013-01-01
Differential diagnoses between vegetative and minimally conscious states (VS and MCS, respectively) are frequently incorrect. Hence, further research is necessary to improve the diagnostic accuracy at the bedside. The main neuropathological feature of VS is the diffuse damage of cortical and subcortical connections. Starting with this premise, we used electroencephalography (EEG) recordings to evaluate the cortical reactivity and effective connectivity during transcranial magnetic stimulation (TMS) in chronic VS or MCS patients. Moreover, the TMS-EEG data were compared with the results from standard somatosensory-evoked potentials (SEPs) and event-related potentials (ERPs). Thirteen patients with chronic consciousness disorders were examined at their bedsides. A group of healthy volunteers served as the control group. The amplitudes (reactivity) and scalp distributions (connectivity) of the cortical potentials evoked by TMS (TEPs) of the primary motor cortex were measured. Short-latency median nerve SEPs and auditory ERPs were also recorded. Reproducible TEPs were present in all control subjects in both the ipsilateral and the contralateral hemispheres relative to the site of the TMS. The amplitudes of the ipsilateral and contralateral TEPs were reduced in four of the five MCS patients, and the TEPs were bilaterally absent in one MCS patient. Among the VS patients, five did not manifest ipsilateral or contralateral TEPs, and three of the patients exhibited only ipsilateral TEPs with reduced amplitudes. The SEPs were altered in five VS and two MCS patients but did not correlate with the clinical diagnosis. The ERPs were impaired in all patients and did not correlate with the clinical diagnosis. These TEP results suggest that cortical reactivity and connectivity are severely impaired in all VS patients, whereas in most MCS patients, the TEPs are preserved but with abnormal features. Therefore, TEPs may add valuable information to the current clinical and neurophysiological assessment of chronic consciousness disorders. PMID:23460826
Kitazawa, Yu; Jin, Kazutaka; Iwasaki, Masaki; Suzuki, Hiroyoshi; Tanaka, Fumiaki; Nakasato, Nobukazu
2017-11-25
A 26-year-old right-handed woman, with a history of left temporal lobe contusion caused by a fall at the age of 9 months, started to have complex partial seizures with oral automatism at the age of 7 years. The seizures occurred once or twice a month despite combination therapy with several antiepileptic agents. Her history and imaging studies suggested the diagnosis of epilepsy arising from traumatic neocortical temporal lesion. Comprehensive assessment including long-term video EEG monitoring, MRI, FDG-PET, MEG, and neuropsychological evaluation was performed at the age of 26 years. The diagnosis was left mesial temporal lobe epilepsy associated with hippocampal atrophy and traumatic temporal cortical lesion. The patient was readmitted for surgical treatment at the age of 27 years. Intracranial EEG monitoring showed that ictal discharges started in the left hippocampus and spread to the traumatic lesion in the left posterior superior temporal gyrus 10 seconds after the onset. This case could not be classified as dual pathology exactly, because the traumatic left temporal cortical lesion did not show independent epileptogenicity. However, the traumatic lesion was highly likely to be the source of the epileptogenicity, and she had right hemispheric dominance for language and functional deterioration in the whole temporal cortex. Therefore, left amygdalo-hippocampectomy and left temporal lobectomy including the traumatic lesion were performed according to the diagnosis of dual pathology. Subsequently, she remained seizure-free for 3 years. Comprehensive assessment of seizure semiology, neurophysiology, neuroradiology, and neuropsychology is important to determine the optimum therapeutic strategies for drug-resistant epilepsy.
A High-Density EEG Investigation into Steady State Binaural Beat Stimulation
Goodin, Peter; Ciorciari, Joseph; Baker, Kate; Carrey, Anne-Marie; Harper, Michelle; Kaufman, Jordy
2012-01-01
Binaural beats are an auditory phenomenon that has been suggested to alter physiological and cognitive processes including vigilance and brainwave entrainment. Some personality traits measured by the NEO Five Factor Model have been found to alter entrainment using pulsing light stimuli, but as yet no studies have examined if this occurs using steady state presentation of binaural beats for a relatively short presentation of two minutes. This study aimed to examine if binaural beat stimulation altered vigilance or cortical frequencies and if personality traits were involved. Thirty-one participants were played binaural beat stimuli designed to elicit a response at either the Theta (7 Hz) or Beta (16 Hz) frequency bands while undertaking a zero-back vigilance task. EEG was recorded from a high-density electrode cap. No significant differences were found in vigilance or cortical frequency power during binaural beat stimulation compared to a white noise control period. Furthermore, no significant relationships were detected between the above and the Big Five personality traits. This suggests a short presentation of steady state binaural beats are not sufficient to alter vigilance or entrain cortical frequencies at the two bands examined and that certain personality traits were not more susceptible than others. PMID:22496862
A high-density EEG investigation into steady state binaural beat stimulation.
Goodin, Peter; Ciorciari, Joseph; Baker, Kate; Carey, Anne-Marie; Carrey, Anne-Marie; Harper, Michelle; Kaufman, Jordy
2012-01-01
Binaural beats are an auditory phenomenon that has been suggested to alter physiological and cognitive processes including vigilance and brainwave entrainment. Some personality traits measured by the NEO Five Factor Model have been found to alter entrainment using pulsing light stimuli, but as yet no studies have examined if this occurs using steady state presentation of binaural beats for a relatively short presentation of two minutes. This study aimed to examine if binaural beat stimulation altered vigilance or cortical frequencies and if personality traits were involved. Thirty-one participants were played binaural beat stimuli designed to elicit a response at either the Theta (7 Hz) or Beta (16 Hz) frequency bands while undertaking a zero-back vigilance task. EEG was recorded from a high-density electrode cap. No significant differences were found in vigilance or cortical frequency power during binaural beat stimulation compared to a white noise control period. Furthermore, no significant relationships were detected between the above and the Big Five personality traits. This suggests a short presentation of steady state binaural beats are not sufficient to alter vigilance or entrain cortical frequencies at the two bands examined and that certain personality traits were not more susceptible than others.
[Recurrent cortical blindness after LSD-intake].
Bernhard, M K; Ulrich, K
2009-02-01
Recurrent disturbances of vision associated with headaches are typical signs of a migraine. A 15-year-old girl suffered from common migraine. The patient had a headache and nausea five days after a first and proved intake of LSD. Shortly later, a complete blindness of both eyes developed within seconds. These symptoms continued for 48 hours. As the pupillar reactions were intact the findings were consistent with cortical blindness. MRI and MR-angiography of the brain, analysis of the cerebrospinal fluid and blood investigations for thrombophilia were normal. The EEG showed a bilateral symmetrical delta wave slowing over the occipital areas. Within the following three months the girl had three more episodes with complete blindness over a period of 12-36 hours. There have never been any visual disturbances in between the episodes and afterwards. Extended diagnosis with long term blood pressure measurement, Doppler sonography and visual evoked potentials were normal. The occipital slowing in the EEG persisted for 18 months. As the symptoms were unusually long and severe for a complicated migraine it is possible that the temporary blindness was the correlate of flash backs caused by the LSD. LSD intake could trigger additional, local cortical dysfunction (e. g. in the occipital areas) in preexisting migraine.
Trial-by-trial fluctuations in CNV amplitude reflect anticipatory adjustment of response caution.
Boehm, Udo; van Maanen, Leendert; Forstmann, Birte; van Rijn, Hedderik
2014-08-01
The contingent negative variation, a slow cortical potential, occurs when humans are warned by a stimulus about an upcoming task. The cognitive processes that give rise to this EEG potential are not yet well understood. To explain these processes, we adopt a recently developed theoretical framework from the area of perceptual decision-making. This framework assumes that the basal ganglia control the tradeoff between fast and accurate decision-making in the cortex. It suggests that an increase in cortical excitability serves to lower response caution, which results in faster but more error prone responding. We propose that the CNV reflects this increased cortical excitability. To test this hypothesis, we conducted an EEG experiment in which participants performed the random dot motion task either under speed or under accuracy stress. Our results show that trial-by-trial fluctuations in participants' response speed as well as model-based estimates of response caution correlated with single-trial CNV amplitude under conditions of speed but not accuracy stress. We conclude that the CNV might reflect adjustments of response caution, which serves to enhance quick decision-making. Copyright © 2014 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie
2017-06-01
Objective. Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Approach. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys + EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. Main results. The Open Ephys + EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys + EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Significance. Open Ephys + EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.
Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie
2017-06-01
Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys + EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. The Open Ephys + EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys + EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Open Ephys + EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.
Leamy, Darren J; Kocijan, Juš; Domijan, Katarina; Duffin, Joseph; Roche, Richard Ap; Commins, Sean; Collins, Ronan; Ward, Tomas E
2014-01-28
Brain-Computer Interfaces (BCI) can potentially be used to aid in the recovery of lost motor control in a limb following stroke. BCIs are typically used by subjects with no damage to the brain therefore relatively little is known about the technical requirements for the design of a rehabilitative BCI for stroke. 32-channel electroencephalogram (EEG) was recorded during a finger-tapping task from 10 healthy subjects for one session and 5 stroke patients for two sessions approximately 6 months apart. An off-line BCI design based on Filter Bank Common Spatial Patterns (FBCSP) was implemented to test and compare the efficacy and accuracy of training a rehabilitative BCI with both stroke-affected and healthy data. Stroke-affected EEG datasets have lower 10-fold cross validation results than healthy EEG datasets. When training a BCI with healthy EEG, average classification accuracy of stroke-affected EEG is lower than the average for healthy EEG. Classification accuracy of the late session stroke EEG is improved by training the BCI on the corresponding early stroke EEG dataset. This exploratory study illustrates that stroke and the accompanying neuroplastic changes associated with the recovery process can cause significant inter-subject changes in the EEG features suitable for mapping as part of a neurofeedback therapy, even when individuals have scored largely similar with conventional behavioural measures. It appears such measures can mask this individual variability in cortical reorganization. Consequently we believe motor retraining BCI should initially be tailored to individual patients.
Barrès, Victor; Simons, Arthur; Arbib, Michael
2013-01-01
Our previous work developed Synthetic Brain Imaging to link neural and schema network models of cognition and behavior to PET and fMRI studies of brain function. We here extend this approach to Synthetic Event-Related Potentials (Synthetic ERP). Although the method is of general applicability, we focus on ERP correlates of language processing in the human brain. The method has two components: Phase 1: To generate cortical electro-magnetic source activity from neural or schema network models; and Phase 2: To generate known neurolinguistic ERP data (ERP scalp voltage topographies and waveforms) from putative cortical source distributions and activities within a realistic anatomical model of the human brain and head. To illustrate the challenges of Phase 2 of the methodology, spatiotemporal information from Friederici's 2002 model of auditory language comprehension was used to define cortical regions and time courses of activation for implementation within a forward model of ERP data. The cortical regions from the 2002 model were modeled using atlas-based masks overlaid on the MNI high definition single subject cortical mesh. The electromagnetic contribution of each region was modeled using current dipoles whose position and orientation were constrained by the cortical geometry. In linking neural network computation via EEG forward modeling to empirical results in neurolinguistics, we emphasize the need for neural network models to link their architecture to geometrically sound models of the cortical surface, and the need for conceptual models to refine and adopt brain-atlas based approaches to allow precise brain anchoring of their modules. The detailed analysis of Phase 2 sets the stage for a brief introduction to Phase 1 of the program, including the case for a schema-theoretic approach to language production and perception presented in detail elsewhere. Unlike Dynamic Causal Modeling (DCM) and Bojak's mean field model, Synthetic ERP builds on models of networks that mediate the relation between the brain's inputs, outputs, and internal states in executing a specific task. The neural networks used for Synthetic ERP must include neuroanatomically realistic placement and orientation of the cortical pyramidal neurons. These constraints pose exciting challenges for future work in neural network modeling that is applicable to systems and cognitive neuroscience. Copyright © 2012 Elsevier Ltd. All rights reserved.
Hamid, Laith; Al Farawn, Ali; Merlet, Isabelle; Japaridze, Natia; Heute, Ulrich; Stephani, Ulrich; Galka, Andreas; Wendling, Fabrice; Siniatchkin, Michael
2017-07-01
The clinical routine of non-invasive electroencephalography (EEG) is usually performed with 8-40 electrodes, especially in long-term monitoring, infants or emergency care. There is a need in clinical and scientific brain imaging to develop inverse solution methods that can reconstruct brain sources from these low-density EEG recordings. In this proof-of-principle paper we investigate the performance of the spatiotemporal Kalman filter (STKF) in EEG source reconstruction with 9-, 19- and 32- electrodes. We used simulated EEG data of epileptic spikes generated from lateral frontal and lateral temporal brain sources using state-of-the-art neuronal population models. For validation of source reconstruction, we compared STKF results to the location of the simulated source and to the results of low-resolution brain electromagnetic tomography (LORETA) standard inverse solution. STKF consistently showed less localization bias compared to LORETA, especially when the number of electrodes was decreased. The results encourage further research into the application of the STKF in source reconstruction of brain activity from low-density EEG recordings.
Changes in EEG alpha power to different disgust elicitors: the specificity of mutilations.
Sarlo, Michela; Buodo, Giulia; Poli, Silvia; Palomba, Daniela
2005-07-15
It is unclear in the literature whether the various disgust elicitors are differentially processed by the brain and/or able to elicit distinct psychophysiological response patterns. On the other hand, disgusting stimuli depicting mutilations have been proved to elicit a distinct autonomic response pattern and to demand greater attentional resources, as compared with other unpleasant visual stimuli. In this EEG study, 34 participants viewed 4 film-clips depicting surgery, cockroach invasion, human attack and neutral landscape during EEG recording, and then rated the clips for valence, arousal and the basic emotions. Independent of location, the highest cortical activation was found during the viewing of the surgery scene. Moreover, the above activation was prominent over the right posterior regions.
Cortical excitability and neurology: insights into the pathophysiology
Badawy, Radwa A.B.; Loetscher, Tobias; Macdonell, Richard A.L.; Brodtmann, Amy
2012-01-01
Summary Transcranial magnetic stimulation (TMS) is a technique developed to non-invasively investigate the integrity of human motor corticospinal tracts. Over the last three decades, the use of stimulation paradigms including single-pulse TMS, paired-pulse TMS, repetitive TMS, and integration with EEG and functional imaging have been developed to facilitate measurement of cortical excitability. Through the use of these protocols, TMS has evolved into an excellent tool for measuring cortical excitability. TMS has high sensitivity in detecting subtle changes in cortical excitability, and therefore it is also a good measure of disturbances associated with brain disorders. In this review, we appraise the current literature on cortical excitability studies using TMS in neurological disorders. We begin with a brief overview of current TMS measures and then show how these have added to our understanding of the underlying mechanisms of brain disorders. PMID:23402674
Removal of EOG Artifacts from EEG Recordings Using Stationary Subspace Analysis
Zeng, Hong; Song, Aiguo
2014-01-01
An effective approach is proposed in this paper to remove ocular artifacts from the raw EEG recording. The proposed approach first conducts the blind source separation on the raw EEG recording by the stationary subspace analysis (SSA) algorithm. Unlike the classic blind source separation algorithms, SSA is explicitly tailored to the understanding of distribution changes, where both the mean and the covariance matrix are taken into account. In addition, neither independency nor uncorrelation is required among the sources by SSA. Thereby, it can concentrate artifacts in fewer components than the representative blind source separation methods. Next, the components that are determined to be related to the ocular artifacts are projected back to be subtracted from EEG signals, producing the clean EEG data eventually. The experimental results on both the artificially contaminated EEG data and real EEG data have demonstrated the effectiveness of the proposed method, in particular for the cases where limited number of electrodes are used for the recording, as well as when the artifact contaminated signal is highly nonstationary and the underlying sources cannot be assumed to be independent or uncorrelated. PMID:24550696
Campbell, Julia; Sharma, Anu
2016-01-01
Measures of visual cortical development in children demonstrate high variability and inconsistency throughout the literature. This is partly due to the specificity of the visual system in processing certain features. It may then be advantageous to activate multiple cortical pathways in order to observe maturation of coinciding networks. Visual stimuli eliciting the percept of apparent motion and shape change is designed to simultaneously activate both dorsal and ventral visual streams. However, research has shown that such stimuli also elicit variable visual evoked potential (VEP) morphology in children. The aim of this study was to describe developmental changes in VEPs, including morphological patterns, and underlying visual cortical generators, elicited by apparent motion and shape change in school-aged children. Forty-one typically developing children underwent high-density EEG recordings in response to a continuously morphing, radially modulated, circle-star grating. VEPs were then compared across the age groups of 5-7, 8-10, and 11-15 years according to latency and amplitude. Current density reconstructions (CDR) were performed on VEP data in order to observe activated cortical regions. It was found that two distinct VEP morphological patterns occurred in each age group. However, there were no major developmental differences between the age groups according to each pattern. CDR further demonstrated consistent visual generators across age and pattern. These results describe two novel VEP morphological patterns in typically developing children, but with similar underlying cortical sources. The importance of these morphological patterns is discussed in terms of future studies and the investigation of a relationship to visual cognitive performance.
Campbell, Julia; Sharma, Anu
2016-01-01
Measures of visual cortical development in children demonstrate high variability and inconsistency throughout the literature. This is partly due to the specificity of the visual system in processing certain features. It may then be advantageous to activate multiple cortical pathways in order to observe maturation of coinciding networks. Visual stimuli eliciting the percept of apparent motion and shape change is designed to simultaneously activate both dorsal and ventral visual streams. However, research has shown that such stimuli also elicit variable visual evoked potential (VEP) morphology in children. The aim of this study was to describe developmental changes in VEPs, including morphological patterns, and underlying visual cortical generators, elicited by apparent motion and shape change in school-aged children. Forty-one typically developing children underwent high-density EEG recordings in response to a continuously morphing, radially modulated, circle-star grating. VEPs were then compared across the age groups of 5–7, 8–10, and 11–15 years according to latency and amplitude. Current density reconstructions (CDR) were performed on VEP data in order to observe activated cortical regions. It was found that two distinct VEP morphological patterns occurred in each age group. However, there were no major developmental differences between the age groups according to each pattern. CDR further demonstrated consistent visual generators across age and pattern. These results describe two novel VEP morphological patterns in typically developing children, but with similar underlying cortical sources. The importance of these morphological patterns is discussed in terms of future studies and the investigation of a relationship to visual cognitive performance. PMID:27445738
Graph properties of synchronized cortical networks during visual working memory maintenance.
Palva, Satu; Monto, Simo; Palva, J Matias
2010-02-15
Oscillatory synchronization facilitates communication in neuronal networks and is intimately associated with human cognition. Neuronal activity in the human brain can be non-invasively imaged with magneto- (MEG) and electroencephalography (EEG), but the large-scale structure of synchronized cortical networks supporting cognitive processing has remained uncharacterized. We combined simultaneous MEG and EEG (MEEG) recordings with minimum-norm-estimate-based inverse modeling to investigate the structure of oscillatory phase synchronized networks that were active during visual working memory (VWM) maintenance. Inter-areal phase-synchrony was quantified as a function of time and frequency by single-trial phase-difference estimates of cortical patches covering the entire cortical surfaces. The resulting networks were characterized with a number of network metrics that were then compared between delta/theta- (3-6 Hz), alpha- (7-13 Hz), beta- (16-25 Hz), and gamma- (30-80 Hz) frequency bands. We found several salient differences between frequency bands. Alpha- and beta-band networks were more clustered and small-world like but had smaller global efficiency than the networks in the delta/theta and gamma bands. Alpha- and beta-band networks also had truncated-power-law degree distributions and high k-core numbers. The data converge on showing that during the VWM-retention period, human cortical alpha- and beta-band networks have a memory-load dependent, scale-free small-world structure with densely connected core-like structures. These data further show that synchronized dynamic networks underlying a specific cognitive state can exhibit distinct frequency-dependent network structures that could support distinct functional roles. Copyright 2009 Elsevier Inc. All rights reserved.
Verdonck, Olivier; Reed, Sean J; Hall, Jeffery; Gotman, Jean; Plourde, Gilles
2014-03-01
Brain imaging studies suggest that loss of consciousness induced by general anesthetics is associated with impairment of thalamic function. There is, however, limited information on the time course of these changes. We recently obtained intracranial electroencephalogram (EEG) recordings from the ventroposterolateral (VPL) nucleus of the thalamus and from the motor cortex during induction of anesthesia in three patients to study the time course of the alterations of cortical and thalamic function. The patients were American Society of Anesthesiologists physical status I-II males aged 33-57 yr with intractable central pain caused by brachial plexus injury (patient 1 and 2) or insular infarct (patient 3). Anesthesia was induced with propofol (2.5-3.1 mg·kg(-1) over 30-45 sec) followed, after loss of consciousness, by rocuronium for tracheal intubation. The data retained for analysis are from one minute before the start of propofol to 110 sec later during ventilation of the patients' lungs before tracheal intubation. Spectral analysis was used to measure absolute EEG power. Propofol caused significant increases of cortical and thalamic power in the delta to beta frequency bands (1-30 Hz). These increases of cortical and thalamic power occurred either concomitantly or within seconds of each other. Propofol also caused a decrease in cortical and thalamic high-gamma (62-200 Hz) power that also followed a similar time course. We conclude that induction of anesthesia with propofol in these patients was associated with concurrent alterations of cortical and sensory thalamic activity.
Auriat, Angela M.; Neva, Jason L.; Peters, Sue; Ferris, Jennifer K.; Boyd, Lara A.
2015-01-01
Following stroke, the brain undergoes various stages of recovery where the central nervous system can reorganize neural circuitry (neuroplasticity) both spontaneously and with the aid of behavioral rehabilitation and non-invasive brain stimulation. Multiple neuroimaging techniques can characterize common structural and functional stroke-related deficits, and importantly, help predict recovery of function. Diffusion tensor imaging (DTI) typically reveals increased overall diffusivity throughout the brain following stroke, and is capable of indexing the extent of white matter damage. Magnetic resonance spectroscopy (MRS) provides an index of metabolic changes in surviving neural tissue after stroke, serving as a marker of brain function. The neural correlates of altered brain activity after stroke have been demonstrated by abnormal activation of sensorimotor cortices during task performance, and at rest, using functional magnetic resonance imaging (fMRI). Electroencephalography (EEG) has been used to characterize motor dysfunction in terms of increased cortical amplitude in the sensorimotor regions when performing upper limb movement, indicating abnormally increased cognitive effort and planning in individuals with stroke. Transcranial magnetic stimulation (TMS) work reveals changes in ipsilesional and contralesional cortical excitability in the sensorimotor cortices. The severity of motor deficits indexed using TMS has been linked to the magnitude of activity imbalance between the sensorimotor cortices. In this paper, we will provide a narrative review of data from studies utilizing DTI, MRS, fMRI, EEG, and brain stimulation techniques focusing on TMS and its combination with uni- and multimodal neuroimaging methods to assess recovery after stroke. Approaches that delineate the best measures with which to predict or positively alter outcomes will be highlighted. PMID:26579069
Source-Modeling Auditory Processes of EEG Data Using EEGLAB and Brainstorm.
Stropahl, Maren; Bauer, Anna-Katharina R; Debener, Stefan; Bleichner, Martin G
2018-01-01
Electroencephalography (EEG) source localization approaches are often used to disentangle the spatial patterns mixed up in scalp EEG recordings. However, approaches differ substantially between experiments, may be strongly parameter-dependent, and results are not necessarily meaningful. In this paper we provide a pipeline for EEG source estimation, from raw EEG data pre-processing using EEGLAB functions up to source-level analysis as implemented in Brainstorm. The pipeline is tested using a data set of 10 individuals performing an auditory attention task. The analysis approach estimates sources of 64-channel EEG data without the prerequisite of individual anatomies or individually digitized sensor positions. First, we show advanced EEG pre-processing using EEGLAB, which includes artifact attenuation using independent component analysis (ICA). ICA is a linear decomposition technique that aims to reveal the underlying statistical sources of mixed signals and is further a powerful tool to attenuate stereotypical artifacts (e.g., eye movements or heartbeat). Data submitted to ICA are pre-processed to facilitate good-quality decompositions. Aiming toward an objective approach on component identification, the semi-automatic CORRMAP algorithm is applied for the identification of components representing prominent and stereotypic artifacts. Second, we present a step-wise approach to estimate active sources of auditory cortex event-related processing, on a single subject level. The presented approach assumes that no individual anatomy is available and therefore the default anatomy ICBM152, as implemented in Brainstorm, is used for all individuals. Individual noise modeling in this dataset is based on the pre-stimulus baseline period. For EEG source modeling we use the OpenMEEG algorithm as the underlying forward model based on the symmetric Boundary Element Method (BEM). We then apply the method of dynamical statistical parametric mapping (dSPM) to obtain physiologically plausible EEG source estimates. Finally, we show how to perform group level analysis in the time domain on anatomically defined regions of interest (auditory scout). The proposed pipeline needs to be tailored to the specific datasets and paradigms. However, the straightforward combination of EEGLAB and Brainstorm analysis tools may be of interest to others performing EEG source localization.
Chowdhury, Rasheda Arman; Lina, Jean Marc; Kobayashi, Eliane; Grova, Christophe
2013-01-01
Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG) or Magneto-EncephaloGraphy (MEG) signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data. Source localization methods based on two types of realistic models have been investigated: (i) brain activity may be modeled using cortical parcels and (ii) brain activity is assumed to be locally smooth within each parcel. A Data Driven Parcellization (DDP) method was used to segment the cortical surface into non-overlapping parcels and diffusion-based spatial priors were used to model local spatial smoothness within parcels. These models were implemented within the Maximum Entropy on the Mean (MEM) and the Hierarchical Bayesian (HB) source localization frameworks. We proposed new methods in this context and compared them with other standard ones using Monte Carlo simulations of realistic MEG data involving sources of several spatial extents and depths. Detection accuracy of each method was quantified using Receiver Operating Characteristic (ROC) analysis and localization error metrics. Our results showed that methods implemented within the MEM framework were sensitive to all spatial extents of the sources ranging from 3 cm(2) to 30 cm(2), whatever were the number and size of the parcels defining the model. To reach a similar level of accuracy within the HB framework, a model using parcels larger than the size of the sources should be considered.
Chowdhury, Rasheda Arman; Lina, Jean Marc; Kobayashi, Eliane; Grova, Christophe
2013-01-01
Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG) or Magneto-EncephaloGraphy (MEG) signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data. Source localization methods based on two types of realistic models have been investigated: (i) brain activity may be modeled using cortical parcels and (ii) brain activity is assumed to be locally smooth within each parcel. A Data Driven Parcellization (DDP) method was used to segment the cortical surface into non-overlapping parcels and diffusion-based spatial priors were used to model local spatial smoothness within parcels. These models were implemented within the Maximum Entropy on the Mean (MEM) and the Hierarchical Bayesian (HB) source localization frameworks. We proposed new methods in this context and compared them with other standard ones using Monte Carlo simulations of realistic MEG data involving sources of several spatial extents and depths. Detection accuracy of each method was quantified using Receiver Operating Characteristic (ROC) analysis and localization error metrics. Our results showed that methods implemented within the MEM framework were sensitive to all spatial extents of the sources ranging from 3 cm2 to 30 cm2, whatever were the number and size of the parcels defining the model. To reach a similar level of accuracy within the HB framework, a model using parcels larger than the size of the sources should be considered. PMID:23418485
Diekmann, Volker; Hoppner, Anselm Cornelius
2014-03-01
Patients suffering from musicogenic epilepsy have focal seizures triggered by auditory stimuli. In some of these patients, the emotions associated with the music appear to play a role in the process triggering the seizure, however, the significance of these emotions and the brain regions involved are unclear. In order to shed some light on this, we conducted fMRI and EEG in a case of musicogenic epilepsy. In a 32-year-old male patient with seizures induced by a specific piece of Russian music, we performed video-EEG monitoring as well as simultaneous fMRI and EEG registration. Video-EEG monitoring revealed a left temporo-frontal epileptogenic focus. During fMRI-EEG co-registration, BOLD signal alterations were not only found in the epileptogenic focus but also in areas known for their role in the processing of emotions. Prior to a seizure in some of these areas, BOLD contrasts exponentially increased or decreased. These results suggest that in our case, dysfunction of the regulation processes of the musically-induced emotions, and not the musical stimulus itself, led to the seizures.
EEG-based functional networks evoked by acupuncture at ST 36: A data-driven thresholding study
NASA Astrophysics Data System (ADS)
Li, Huiyan; Wang, Jiang; Yi, Guosheng; Deng, Bin; Zhou, Hexi
2017-10-01
This paper investigates how acupuncture at ST 36 modulates the brain functional network. 20 channel EEG signals from 15 healthy subjects are respectively recorded before, during and after acupuncture. The correlation between two EEG channels is calculated by using Pearson’s coefficient. A data-driven approach is applied to determine the threshold, which is performed by considering the connected set, connected edge and network connectivity. Based on such thresholding approach, the functional network in each acupuncture period is built with graph theory, and the associated functional connectivity is determined. We show that acupuncturing at ST 36 increases the connectivity of the EEG-based functional network, especially for the long distance ones between two hemispheres. The properties of the functional network in five EEG sub-bands are also characterized. It is found that the delta and gamma bands are affected more obviously by acupuncture than the other sub-bands. These findings highlight the modulatory effects of acupuncture on the EEG-based functional connectivity, which is helpful for us to understand how it participates in the cortical or subcortical activities. Further, the data-driven threshold provides an alternative approach to infer the functional connectivity under other physiological conditions.
Scalp EEG does not predict hemispherectomy outcome
Greiner, Hansel M.; Park, Yong D.; Holland, Katherine; Horn, Paul S.; Byars, Anna W.; Mangano, Francesco T.; Smith, Joseph R.; Lee, Mark R.; Lee, Ki-Hyeong
2012-01-01
Background Functional hemispherectomy is effective in carefully selected patients, resulting in a reduction of seizure burden up to complete resolution, improvement of intellectual development, and developmental benefit despite possible additional neurological deficit. Despite apparent hemispheric pathology on brain magnetic resonance imaging (MRI) or other imaging tests, scalp electroencephalography (EEG) could be suggestive of bilateral ictal onset or even ictal onset contralateral to the dominant imaging abnormality. We aimed to investigate the role of scalp EEG lateralization pre-operatively in predicting outcome. Methods We retrospectively reviewed 54 patients who underwent hemispherectomy between 1991 and 2009 at Medical College of Georgia (1991–2006) and Cincinnati Children’s Hospital Medical Center (2006–2009) and had at least one year post-operative follow-up. All preoperative EEGs were reviewed, and classified as either lateralizing or nonlateralizing, for both ictal and interictal EEG recordings. Results Of 54 patients, 42 (78%) became seizure free. Twenty-four (44%) of 54 had a nonlateralizing ictal or interictal EEG. Further analysis was based on etiology of epilepsy, including malformation of cortical development (MCD), Rasmussen syndrome (RS), and stroke (CVA). EEG nonlateralization did not predict poor outcome in any of the etiology groups evaluated. Conclusion Scalp EEG abnormalities in contralateral or bilateral hemispheres do not, in isolation, predict a poor outcome from hemispherectomy. Results of other non-invasive and invasive evaluations should be used to determine candidacy. PMID:21813300
EEG Topographic Mapping of Visual and Kinesthetic Imagery in Swimmers.
Wilson, V E; Dikman, Z; Bird, E I; Williams, J M; Harmison, R; Shaw-Thornton, L; Schwartz, G E
2016-03-01
This study investigated differences in QEEG measures between kinesthetic and visual imagery of a 100-m swim in 36 elite competitive swimmers. Background information and post-trial checks controlled for the modality of imagery, swimming skill level, preferred imagery style, intensity of image and task equality. Measures of EEG relative magnitude in theta, low (7-9 Hz) and high alpha (8-10 Hz), and low and high beta were taken from 19 scalp sites during baseline, visual, and kinesthetic imagery. QEEG magnitudes in the low alpha band during the visual and kinesthetic conditions were attenuated from baseline in low band alpha but no changes were seen in any other bands. Swimmers produced more low alpha EEG magnitude during visual versus kinesthetic imagery. This was interpreted as the swimmers having a greater efficiency at producing visual imagery. Participants who reported a strong intensity versus a weaker feeling of the image (kinesthetic) had less low alpha magnitude, i.e., there was use of more cortical resources, but not for the visual condition. These data suggest that low band (7-9 Hz) alpha distinguishes imagery modalities from baseline, visual imagery requires less cortical resources than kinesthetic imagery, and that intense feelings of swimming requires more brain activity than less intense feelings.
Graph theory network function in Parkinson's disease assessed with electroencephalography.
Utianski, Rene L; Caviness, John N; van Straaten, Elisabeth C W; Beach, Thomas G; Dugger, Brittany N; Shill, Holly A; Driver-Dunckley, Erika D; Sabbagh, Marwan N; Mehta, Shyamal; Adler, Charles H; Hentz, Joseph G
2016-05-01
To determine what differences exist in graph theory network measures derived from electroencephalography (EEG), between Parkinson's disease (PD) patients who are cognitively normal (PD-CN) and matched healthy controls; and between PD-CN and PD dementia (PD-D). EEG recordings were analyzed via graph theory network analysis to quantify changes in global efficiency and local integration. This included minimal spanning tree analysis. T-tests and correlations were used to assess differences between groups and assess the relationship with cognitive performance. Network measures showed increased local integration across all frequency bands between control and PD-CN; in contrast, decreased local integration occurred in PD-D when compared to PD-CN in the alpha1 frequency band. Differences found in PD-MCI mirrored PD-D. Correlations were found between network measures and assessments of global cognitive performance in PD. Our results reveal distinct patterns of band and network measure type alteration and breakdown for PD, as well as with cognitive decline in PD. These patterns suggest specific ways that interaction between cortical areas becomes abnormal and contributes to PD symptoms at various stages. Graph theory analysis by EEG suggests that network alteration and breakdown are robust attributes of PD cortical dysfunction pathophysiology. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Kim, Shin Hye; Jang, Ji Hye; Lee, Sang-Yeon; Han, Jae Joon; Koo, Ja-Won; Vanneste, Sven; De Ridder, Dirk; Song, Jae-Jin
2016-01-01
Although tinnitus retraining therapy (TRT) is efficacious in most patients, the exact mechanism is unclear and no predictor of improvement is available. We correlated the extent of improvement with pre-TRT quantitative electroencephalography (qEEG) findings to identify neural predictors of improvement after TRT. Thirty-two patients with debilitating tinnitus were prospectively enrolled, and qEEG data were recorded before their initial TRT sessions. Three months later, these qEEG findings were correlated with the percentage improvements in the Tinnitus Handicap Inventory (THI) scores, and numeric rating scale (NRS) scores of tinnitus loudness and tinnitus perception. The THI score improvement was positively correlated with the pre-treatment activities of the left insula and the left rostral and pregenual anterior cingulate cortices (rACC/pgACC), which control parasympathetic activity. Additionally, the activities of the right auditory cortices and the parahippocampus, areas that generate tinnitus, negatively correlated with improvements in loudness. Improvements in the NRS scores of tinnitus perception correlated positively with the pre-TRT activities of the bilateral rACC/pgACC, areas suggested to form the core of the noise-canceling system. The current study supports both the classical neurophysiological and integrative models of tinnitus; our results serve as a milestone in the development of precision medicine in the context of TRT. PMID:27381994
Detection of movement intention from single-trial movement-related cortical potentials
NASA Astrophysics Data System (ADS)
Niazi, Imran Khan; Jiang, Ning; Tiberghien, Olivier; Feldbæk Nielsen, Jørgen; Dremstrup, Kim; Farina, Dario
2011-10-01
Detection of movement intention from neural signals combined with assistive technologies may be used for effective neurofeedback in rehabilitation. In order to promote plasticity, a causal relation between intended actions (detected for example from the EEG) and the corresponding feedback should be established. This requires reliable detection of motor intentions. In this study, we propose a method to detect movements from EEG with limited latency. In a self-paced asynchronous BCI paradigm, the initial negative phase of the movement-related cortical potentials (MRCPs), extracted from multi-channel scalp EEG was used to detect motor execution/imagination in healthy subjects and stroke patients. For MRCP detection, it was demonstrated that a new optimized spatial filtering technique led to better accuracy than a large Laplacian spatial filter and common spatial pattern. With the optimized spatial filter, the true positive rate (TPR) for detection of movement execution in healthy subjects (n = 15) was 82.5 ± 7.8%, with latency of -66.6 ± 121 ms. Although TPR decreased with motor imagination in healthy subject (n = 10, 64.5 ± 5.33%) and with attempted movements in stroke patients (n = 5, 55.01 ± 12.01%), the results are promising for the application of this approach to provide patient-driven real-time neurofeedback.
Kim, Shin Hye; Jang, Ji Hye; Lee, Sang-Yeon; Han, Jae Joon; Koo, Ja-Won; Vanneste, Sven; De Ridder, Dirk; Song, Jae-Jin
2016-07-06
Although tinnitus retraining therapy (TRT) is efficacious in most patients, the exact mechanism is unclear and no predictor of improvement is available. We correlated the extent of improvement with pre-TRT quantitative electroencephalography (qEEG) findings to identify neural predictors of improvement after TRT. Thirty-two patients with debilitating tinnitus were prospectively enrolled, and qEEG data were recorded before their initial TRT sessions. Three months later, these qEEG findings were correlated with the percentage improvements in the Tinnitus Handicap Inventory (THI) scores, and numeric rating scale (NRS) scores of tinnitus loudness and tinnitus perception. The THI score improvement was positively correlated with the pre-treatment activities of the left insula and the left rostral and pregenual anterior cingulate cortices (rACC/pgACC), which control parasympathetic activity. Additionally, the activities of the right auditory cortices and the parahippocampus, areas that generate tinnitus, negatively correlated with improvements in loudness. Improvements in the NRS scores of tinnitus perception correlated positively with the pre-TRT activities of the bilateral rACC/pgACC, areas suggested to form the core of the noise-canceling system. The current study supports both the classical neurophysiological and integrative models of tinnitus; our results serve as a milestone in the development of precision medicine in the context of TRT.
McDonald, Carrie R; Thesen, Thomas; Carlson, Chad; Blumberg, Mark; Girard, Holly M; Trongnetrpunya, Amy; Sherfey, Jason S; Devinsky, Orrin; Kuzniecky, Rubin; Dolye, Werner K; Cash, Sydney S; Leonard, Matthew K; Hagler, Donald J; Dale, Anders M; Halgren, Eric
2010-11-01
Repetition priming is a core feature of memory processing whose anatomical correlates remain poorly understood. In this study, we use advanced multimodal imaging (functional magnetic resonance imaging (fMRI) and magnetoencephalography; MEG) to investigate the spatiotemporal profile of repetition priming. We use intracranial electroencephalography (iEEG) to validate our fMRI/MEG measurements. Twelve controls completed a semantic judgment task with fMRI and MEG that included words presented once (new, 'N') and words that repeated (old, 'O'). Six patients with epilepsy completed the same task during iEEG recordings. Blood-oxygen level dependent (BOLD) responses for N vs. O words were examined across the cortical surface and within regions of interest. MEG waveforms for N vs. O words were estimated using a noise-normalized minimum norm solution, and used to interpret the timecourse of fMRI. Spatial concordance was observed between fMRI and MEG repetition effects from 350 to 450 ms within bilateral occipitotemporal and medial temporal, left prefrontal, and left posterior temporal cortex. Additionally, MEG revealed widespread sources within left temporoparietal regions, whereas fMRI revealed bilateral reductions in occipitotemporal and left superior frontal, and increases in inferior parietal, precuneus, and dorsolateral prefrontal activity. BOLD suppression in left posterior temporal, left inferior prefrontal, and right occipitotemporal cortex correlated with MEG repetition-related reductions. IEEG responses from all three regions supported the timecourse of MEG and localization of fMRI. Furthermore, iEEG decreases to repeated words were associated with decreased gamma power in several regions, providing evidence that gamma oscillations are tightly coupled to cognitive phenomena and reflect regional activations seen in the BOLD signal. Copyright 2010 Elsevier Inc. All rights reserved.
McDonald, Carrie R.; Thesen, Thomas; Carlson, Chad; Blumberg, Mark; Girard, Holly M.; Trongnetrpunya, Amy; Sherfey, Jason S.; Devinsky, Orrin; Kuzniecky, Rubin; Dolye, Werner K.; Cash, Sydney S.; Leonard, Matt K.; Hagler, Donald J.; Dale, Anders M.; Halgren, Eric
2010-01-01
Repetition priming is a core feature of memory processing whose anatomical correlates remain poorly understood. In this study, we use advanced multimodal imaging (functional magnetic resonance imaging (fMRI) and magnetoencephalography; MEG) to investigate the spatiotemporal profile of repetition priming. We use intracranial electroencephalography (iEEG) to validate our fMRI/MEG measurements. Twelve controls completed a semantic judgment task with fMRI and MEG that included words presented once (new, ‘N’) and words that repeated (old, ‘O’). Six patients with epilepsy completed the same task during iEEG recordings. Blood-oxygen level dependent (BOLD) responses for N vs O words were examined across the cortical surface and within regions of interest. MEG waveforms for N vs O words were estimated using a noise-normalized minimum norm solution, and used to interpret the timecourse of fMRI. Spatial concordance was observed between fMRI and MEG repetition effects from 350–450ms within bilateral occipitotemporal and medial temporal, left prefrontal, and left posterior temporal cortex. Additionally, MEG revealed widespread sources within left temporoparietal regions, whereas fMRI revealed bilateral reductions in occipitotemporal and left superior frontal, and increases in inferior parietal, precuneus, and dorsolateral prefrontal activity. BOLD suppression in left posterior temporal, left inferior prefrontal, and right occipitotemporal cortex correlated with MEG repetition-related reductions. IEEG responses from all three regions supported the timecourse of MEG and localization of fMRI. Furthermore, iEEG decreases to repeated words were associated with decreased gamma power in several regions, providing evidence that gamma oscillations are tightly coupled to cognitive phenomena and reflect regional activations seen in the BOLD signal. PMID:20620212
Keuper, Kati; Zwitserlood, Pienie; Rehbein, Maimu A.; Eden, Annuschka S.; Laeger, Inga; Junghöfer, Markus; Zwanzger, Peter; Dobel, Christian
2013-01-01
The hedonic meaning of words affects word recognition, as shown by behavioral, functional imaging, and event-related potential (ERP) studies. However, the spatiotemporal dynamics and cognitive functions behind are elusive, partly due to methodological limitations of previous studies. Here, we account for these difficulties by computing combined electro-magnetoencephalographic (EEG/MEG) source localization techniques. Participants covertly read emotionally high-arousing positive and negative nouns, while EEG and MEG were recorded simultaneously. Combined EEG/MEG current-density reconstructions for the P1 (80–120 ms), P2 (150–190 ms) and EPN component (200–300 ms) were computed using realistic individual head models, with a cortical constraint. Relative to negative words, the P1 to positive words predominantly involved language-related structures (left middle temporal and inferior frontal regions), and posterior structures related to directed attention (occipital and parietal regions). Effects shifted to the right hemisphere in the P2 component. By contrast, negative words received more activation in the P1 time-range only, recruiting prefrontal regions, including the anterior cingulate cortex (ACC). Effects in the EPN were not statistically significant. These findings show that different neuronal networks are active when positive versus negative words are processed. We account for these effects in terms of an “emotional tagging” of word forms during language acquisition. These tags then give rise to different processing strategies, including enhanced lexical processing of positive words and a very fast language-independent alert response to negative words. The valence-specific recruitment of different networks might underlie fast adaptive responses to both approach- and withdrawal-related stimuli, be they acquired or biological. PMID:23940642
Insomnia and sleep misperception.
Bastien, C H; Ceklic, T; St-Hilaire, P; Desmarais, F; Pérusse, A D; Lefrançois, J; Pedneault-Drolet, M
2014-10-01
Sleep misperception is often observed in insomnia individuals (INS). The extent of misperception varies between different types of INS. The following paper comprised sections which will be aimed at studying the sleep EEG and compares it to subjective reports of sleep in individuals suffering from either psychophysiological insomnia or paradoxical insomnia and good sleeper controls. The EEG can be studied without any intervention (thus using the raw data) via either PSG or fine quantitative EEG analyses (power spectral analysis [PSA]), identifying EEG patterns as in the case of cyclic alternating patterns (CAPs) or by decorticating the EEG while scoring the different transient or phasic events (K-Complexes or sleep spindles). One can also act on the on-going EEG by delivering stimuli so to study their impact on cortical measures as in the case of event-related potential studies (ERPs). From the paucity of studies available using these different techniques, a general conclusion can be reached: sleep misperception is not an easy phenomenon to quantify and its clinical value is not well recognized. Still, while none of the techniques or EEG measures defined in the paper is available and/or recommended to diagnose insomnia, ERPs might be the most indicated technique to study hyperarousal and sleep quality in different types of INS. More research shall also be dedicated to EEG patterns and transient phasic events as these EEG scoring techniques can offer a unique insight of sleep misperception. Copyright © 2014 Elsevier Masson SAS. All rights reserved.
Neural Mechanisms of Emotion Regulation in Childhood Anxiety
ERIC Educational Resources Information Center
Hum, Kathryn M.; Manassis, Katharina; Lewis, Marc D.
2013-01-01
Background: The present study was designed to examine the cortical processes that mediate cognitive regulation in response to emotion-eliciting stimuli in anxious children. Methods: Electroencephalographic (EEG) activity was recorded from clinically anxious children ("n" = 29) and typically developing children ("n" = 34).…
Chowdhury, Rasheda Arman; Zerouali, Younes; Hedrich, Tanguy; Heers, Marcel; Kobayashi, Eliane; Lina, Jean-Marc; Grova, Christophe
2015-11-01
The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the underlying generators of inter-ictal epileptic discharges (IEDs). The key element in this study is the integration of the complementary information from EEG and MEG data within the MEM framework. MEEG was compared with EEG and MEG when localizing single transient IEDs. The fusion approach was evaluated using realistic simulation models involving one or two spatially extended sources mimicking propagation patterns of IEDs. We also assessed the impact of the number of EEG electrodes required for an efficient EEG-MEG fusion. MEM was compared with minimum norm estimate, dynamic statistical parametric mapping, and standardized low-resolution electromagnetic tomography. The fusion approach was finally assessed on real epileptic data recorded from two patients showing IEDs simultaneously in EEG and MEG. Overall the localization of MEEG data using MEM provided better recovery of the source spatial extent, more sensitivity to the source depth and more accurate detection of the onset and propagation of IEDs than EEG or MEG alone. MEM was more accurate than the other methods. MEEG proved more robust than EEG and MEG for single IED localization in low signal-to-noise ratio conditions. We also showed that only few EEG electrodes are required to bring additional relevant information to MEG during MEM fusion.
EEG gamma coherence and other correlates of subjective reports during ayahuasca experiences.
Stuckey, David E; Lawson, Robert; Luna, Luis Eduardo
2005-06-01
The current study examined QEEG power and coherence of ayahuasca experiences with two experienced participants in a Brazilian jungle setting. An exploratory case series design was adopted for naturalistic field research. EEGs recorded during visual imagery was compared to eyes-closed baselines. The most important findings were increases in global EEG coherence in the 36-44 Hz and 50-64 Hz frequency bands for both subjects. Widely distributed cortical hyper-coherence seems reasonable given the intense synesthesia during ayahuasca experiences. Other findings include increased modal EEG alpha frequency and global power decreases across the cortex in most frequency bands, which concur with the EEG of psychedelics literature. Exploratory analysis revealed the usefulness of analyzing single Hz bins over the standard wide-band analysis. The discovery-oriented naturalistic approach developed for this study resulted in potentially important findings. We believe that finding increases in global gamma coherence during peak psychedelic experiences might contribute to the discussion of binding theory. Also, in light of recent research with gamma coherence during advanced meditative conditions, our findings might further the comparison of shamanic psychedelic practices with meditation.
Quantitative EEG analysis in minimally conscious state patients during postural changes.
Greco, A; Carboncini, M C; Virgillito, A; Lanata, A; Valenza, G; Scilingo, E P
2013-01-01
Mobilization and postural changes of patients with cognitive impairment are standard clinical practices useful for both psychic and physical rehabilitation process. During this process, several physiological signals, such as Electroen-cephalogram (EEG), Electrocardiogram (ECG), Photopletysmography (PPG), Respiration activity (RESP), Electrodermal activity (EDA), are monitored and processed. In this paper we investigated how quantitative EEG (qEEG) changes with postural modifications in minimally conscious state patients. This study is quite novel and no similar experimental data can be found in the current literature, therefore, although results are very encouraging, a quantitative analysis of the cortical area activated in such postural changes still needs to be deeply investigated. More specifically, this paper shows EEG power spectra and brain symmetry index modifications during a verticalization procedure, from 0 to 60 degrees, of three patients in Minimally Consciousness State (MCS) with focused region of impairment. Experimental results show a significant increase of the power in β band (12 - 30 Hz), commonly associated to human alertness process, thus suggesting that mobilization and postural changes can have beneficial effects in MCS patients.
Frontal and Parietal Cortices Show Different Spatiotemporal Dynamics across Problem-solving Stages.
Tschentscher, Nadja; Hauk, Olaf
2016-08-01
Arithmetic problem-solving can be conceptualized as a multistage process ranging from task encoding over rule and strategy selection to step-wise task execution. Previous fMRI research suggested a frontal-parietal network involved in the execution of complex numerical and nonnumerical tasks, but evidence is lacking on the particular contributions of frontal and parietal cortices across time. In an arithmetic task paradigm, we evaluated individual participants' "retrieval" and "multistep procedural" strategies on a trial-by-trial basis and contrasted those in time-resolved analyses using combined EEG and MEG. Retrieval strategies relied on direct retrieval of arithmetic facts (e.g., 2 + 3 = 5). Procedural strategies required multiple solution steps (e.g., 12 + 23 = 12 + 20 + 3 or 23 + 10 + 2). Evoked source analyses revealed independent activation dynamics within the first second of problem-solving in brain areas previously described as one network, such as the frontal-parietal cognitive control network: The right frontal cortex showed earliest effects of strategy selection for multistep procedural strategies around 300 msec, before parietal cortex activated around 700 msec. In time-frequency source power analyses, memory retrieval and multistep procedural strategies were differentially reflected in theta, alpha, and beta frequencies: Stronger beta and alpha desynchronizations emerged for procedural strategies in right frontal, parietal, and temporal regions as function of executive demands. Arithmetic fact retrieval was reflected in right prefrontal increases in theta power. Our results demonstrate differential brain dynamics within frontal-parietal networks across the time course of a problem-solving process, and analyses of different frequency bands allowed us to disentangle cortical regions supporting the underlying memory and executive functions.
Koirala, Gyan Raj; Lee, Dongpyo; Eom, Soyong; Kim, Nam-Young; Kim, Heung Dong
2017-11-01
The objective of this study was to elucidate alteration in functional connectivity (FC) in patients with benign epilepsy with centrotemporal spikes (BECTS) as induced by physical exercise therapy and their correlation to the neuropsychological (NP) functions. We analyzed 115 artifact- and spike-free 2-second epochs extracted from resting state EEG recordings before and after 5weeks of physical exercise in eight patients with BECTS. The exact Low Resolution Electromagnetic Tomography (eLORETA) was used for source reconstruction. We evaluated the cortical current source density (CSD) power across five different frequency bands (delta, theta, alpha, beta, and gamma). Altered FC between 34 regions of interests (ROIs) was then examined using lagged phase synchronization (LPS) method. We further investigated the correlation between the altered FC measures and the changes in NP test scores. We observed changes in CSD power following the exercise for all frequency bands and statistically significant increases in the right temporal region for the alpha band. There were a number of altered FC between the cortical ROIs in all frequency bands of interest. Furthermore, significant correlations were observed between FC measures and NP test scores at theta and alpha bands. The increased localization power at alpha band may be an indication of the positive impact of exercise in patients with BECTS. Frequency band-specific alterations in FC among cortical regions were associated with the modulation of cognitive and NP functions. The significant correlation between FC and NP tests suggests that physical exercise may mitigate the severity of BECTS, thereby enhancing NP function. Copyright © 2017 Elsevier Inc. All rights reserved.
Lustenberger, Caroline; Murbach, Manuel; Dürr, Roland; Schmid, Marc Ralph; Kuster, Niels; Achermann, Peter; Huber, Reto
2013-09-01
Sleep-dependent performance improvements seem to be closely related to sleep spindles (12-15 Hz) and sleep slow-wave activity (SWA, 0.75-4.5 Hz). Pulse-modulated radiofrequency electromagnetic fields (RF EMF, carrier frequency 900 MHz) are capable to modulate these electroencephalographic (EEG) characteristics of sleep. The aim of our study was to explore possible mechanisms how RF EMF affect cortical activity during sleep and to test whether such effects on cortical activity during sleep interact with sleep-dependent performance changes. Sixteen male subjects underwent 2 experimental nights, one of them with all-night 0.25-0.8 Hz pulsed RF EMF exposure. All-night EEG was recorded. To investigate RF EMF induced changes in overnight performance improvement, subjects were trained for both nights on a motor task in the evening and the morning. We obtained good sleep quality in all subjects under both conditions (mean sleep efficiency > 90%). After pulsed RF EMF we found increased SWA during exposure to pulse-modulated RF EMF compared to sham exposure (P < 0.05) toward the end of the sleep period. Spindle activity was not affected. Moreover, subjects showed an increased RF EMF burst-related response in the SWA range, indicated by an increase in event-related EEG spectral power and phase changes in the SWA range. Notably, during exposure, sleep-dependent performance improvement in the motor sequence task was reduced compared to the sham condition (-20.1%, P = 0.03). The changes in the time course of SWA during the exposure night may reflect an interaction of RF EMF with the renormalization of cortical excitability during sleep, with a negative impact on sleep-dependent performance improvement. Copyright © 2013 Elsevier Inc. All rights reserved.
Minati, Ludovico; Grisoli, Marina; Franceschetti, Silvana; Epifani, Francesca; Granvillano, Alice; Medford, Nick; Harrison, Neil A; Piacentini, Sylvie; Critchley, Hugo D
2012-01-01
Adaptive behaviour requires an ability to obtain rewards by choosing between different risky options. Financial gambles can be used to study effective decision-making experimentally, and to distinguish processes involved in choice option evaluation from outcome feedback and other contextual factors. Here, we used a paradigm where participants evaluated 'mixed' gambles, each presenting a potential gain and a potential loss and an associated variable outcome probability. We recorded neural responses using autonomic monitoring, electroencephalography (EEG) and functional neuroimaging (fMRI), and used a univariate, parametric design to test for correlations with the eleven economic parameters that varied across gambles, including expected value (EV) and amount magnitude. Consistent with behavioural economic theory, participants were risk-averse. Gamble evaluation generated detectable autonomic responses, but only weak correlations with outcome uncertainty were found, suggesting that peripheral autonomic feedback does not play a major role in this task. Long-latency stimulus-evoked EEG potentials were sensitive to expected gain and expected value, while alpha-band power reflected expected loss and amount magnitude, suggesting parallel representations of distinct economic qualities in cortical activation and central arousal. Neural correlates of expected value representation were localized using fMRI to ventromedial prefrontal cortex, while the processing of other economic parameters was associated with distinct patterns across lateral prefrontal, cingulate, insula and occipital cortices including default-mode network and early visual areas. These multimodal data provide complementary evidence for distributed substrates of choice evaluation across multiple, predominantly cortical, brain systems wherein distinct regions are preferentially attuned to specific economic features. Our findings extend biologically-plausible models of risky decision-making while providing potential biomarkers of economic representations that can be applied to the study of deficits in motivational behaviour in neurological and psychiatric patients.
Fisher, Jonathan A N; Huang, Stanley; Ye, Meijun; Nabili, Marjan; Wilent, W Bryan; Krauthamer, Victor; Myers, Matthew R; Welle, Cristin G
2016-09-01
Rapid detection and diagnosis of a traumatic brain injury (TBI) can significantly improve the prognosis for recovery. Helmet-mounted sensors that detect impact severity based on measurements of acceleration or pressure show promise for aiding triage and transport decisions in active, field environments such as professional sports or military combat. The detected signals, however, report on the mechanics of an impact rather than directly indicating the presence and severity of an injury. We explored the use of cortical somatosensory evoked electroencephalographic potentials (SSEPs) to detect and track, in real-time, neural electrophysiological abnormalities within the first hour following head injury in an animal model. To study the immediate electrophysiological effects of injury in vivo, we developed an experimental paradigm involving focused ultrasound that permits continuous, real-time measurements and minimizes mechanical artifact. Injury was associated with a dramatic reduction of amplitude over the damaged hemisphere directly after the injury. The amplitude systematically improved over time but remained significantly decreased at one hour, compared with baseline. In contrast, at one hour there was a concomitant enhancement of the cortical SSEP amplitude evoked from the uninjured hemisphere. Analysis of the inter-trial electroencephalogram (EEG) also revealed significant changes in low-frequency components and an increase in EEG entropy up to 30 minutes after injury, likely reflecting altered EEG reactivity to somatosensory stimuli. Injury-induced alterations in SSEPs were also observed using noninvasive epidermal electrodes, demonstrating viability of practical implementation. These results suggest cortical SSEPs recorded at just a few locations by head-mounted sensors and associated multiparametric analyses could potentially be used to rapidly detect and monitor brain injury in settings that normally present significant levels of mechanical and electrical noise.
Cognitive impairment and spontaneous epilepsy in rats with malformations of cortical development.
Ye-wei, Xiao; Rong, Wang; Xun-tai, Ma; Shan, Zhang; Qian, Chen; Shi-hua, Huang; Fu-qun, Mao; Xiao-ming, Xiong
2015-12-01
To examine the cognition, spontaneous epilepsy, and electroencephalography (EEG) characteristics of rats with malformations of cortical development (MCD) and their use as an animal model for investigating the pathogenesis of intractable epilepsy and screening novel antiepileptic drugs. An epileptic rat model of MCD was established with the F1 generation of pregnant rats after X-irradiation with 175 cGy (Group L), 195 cGy (Group M), or 215 cGy (Group H). Long-term video-EEG monitoring was used to record the seizures in the rats with MCD. Cognition was assessed with the Morris water maze. The EEGs were recorded and analyzed in the frontal and parietal lobes and hippocampi of adult rats. Finally, the brain tissues were processed for Nissl staining. The model groups exhibited markedly prolonged escape latencies and distinct decrements in the percent distance traveled in the target quadrant and platform-crossing frequency. These findings were dose-dependent. Frequent interictal epileptiform discharges were observed in the frontal and parietal lobes and hippocampi of adult rats, and their incidences were markedly higher in the model groups compared with that in the normal controls, with Group M having the highest incidence. Spontaneous seizures were observed in the model groups (mean incidence, 46.7%). The daily mean frequency of seizures and the incidence of spontaneous seizures were highest in Group M. Nissl staining revealed a dose-dependent pattern of hippocampal abnormalities, cortical and subcortical nodular heterotopia, and callosal agenesis in the model groups. The 195 cGy dose was most appropriate for establishing an epileptic model of MCD with X-irradiation. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.
Monoamine Release during Unihemispheric Sleep and Unihemispheric Waking in the Fur Seal
Lyamin, Oleg I.; Lapierre, Jennifer L.; Kosenko, Peter O.; Kodama, Tohru; Bhagwandin, Adhil; Korneva, Svetlana M.; Peever, John H.; Mukhametov, Lev M.; Siegel, Jerome M.
2016-01-01
Study Objectives: Our understanding of the role of neurotransmitters in the control of the electroencephalogram (EEG) has been entirely based on studies of animals with bilateral sleep. The study of animals with unihemispheric sleep presents the opportunity of separating the neurochemical substrates of waking and sleep EEG from the systemic, bilateral correlates of sleep and waking states. Methods: The release of histamine (HI), norepinephrine (NE), and serotonin (5HT) in cortical and subcortical areas (hypothalamus, thalamus and caudate nucleus) was measured in unrestrained northern fur seals (Callorhinus ursinus) using in vivo microdialysis, in combination with, polygraphic recording of EEG, electrooculogram, and neck electromyogram. Results: The pattern of cortical and subcortical HI, NE, and 5HT release in fur seals is similar during bilaterally symmetrical states: highest in active waking, reduced in quiet waking and bilateral slow wave sleep, and lowest in rapid eye movement (REM) sleep. Cortical and subcortical HI, NE, and 5HT release in seals is highly elevated during certain waking stimuli and behaviors, such as being sprayed with water and feeding. However, in contrast to acetylcholine (ACh), which we have previously studied, the release of HI, NE, and 5HT during unihemispheric sleep is not lateralized in the fur seal. Conclusions: Among the studied neurotransmitters most strongly implicated in waking control, only ACh release is asymmetric in unihemispheric sleep and waking, being greatly increased on the activated side of the brain. Commentary: A commentary on this article appears in this issue on page 491. Citation: Lyamin OI, Lapierre JL, Kosenko PO, Kodama T, Bhagwandin A, Korneva SM, Peever JH, Mukhametov LM, Siegel JM. Monoamine release during unihemispheric sleep and unihemispheric waking in the fur seal. SLEEP 2016;39(3):625–636. PMID:26715233
Gianotti, Lorena R R; Künig, Gabriella; Faber, Pascal L; Lehmann, Dietrich; Pascual-Marqui, Roberto D; Kochi, Kieko; Schreiter-Gasser, Ursula
2008-06-01
The objective of the study is to investigate the electrocortical and the global cognitive effects of 3 months rivastigmine medication in a group of mild to moderate Alzheimer's disease patients. Multichannel EEG and cognitive performances measured with the Mini Mental State Examination in a group of 16 patients with mild to moderate Alzheimer's Disease were collected before and 3 months after the onset of rivastigmine medication. Spectral analysis of the EEG data showed a significant power decrease in the delta and theta frequency bands during rivastigmine medication, i.e., a shift of the power spectrum towards 'normalization'. Three-dimensional low resolution electromagnetic tomography (LORETA) functional imaging localized rivastigmine effects in a network that includes left fronto-parietal regions, posterior cingulate cortex, bilateral parahippocampal regions, and the hippocampus. Moreover, a correlation analysis between differences in the cognitive performances during the two recordings and LORETA-computed intracortical activity showed, in the alpha1 frequency band, better cognitive performance with increased cortical activity in the left insula. The results point to a 'normalization' of the EEG power spectrum due to medication, and the intracortical localization of these effects showed an increase of cortical activity in frontal, parietal, and temporal regions that are well-known to be affected in Alzheimer's disease. The topographic convergence of the present results with the memory network proposed by Vincent et al. (J. Neurophysiol. 96:3517-3531, 2006) leads to the speculation that in our group of patients, rivastigmine specifically activates brain regions that are involved in memory functions, notably a key symptom in this degenerative disease.
Tomkins, Oren; Feintuch, Akiva; Benifla, Moni; Cohen, Avi; Friedman, Alon; Shelef, Ilan
2011-01-01
Recent animal experiments indicate a critical role for opening of the blood-brain barrier (BBB) in the pathogenesis of post-traumatic epilepsy (PTE). This study aimed to investigate the frequency, extent, and functional correlates of BBB disruption in epileptic patients following mild traumatic brain injury (TBI). Thirty-seven TBI patients were included in this study, 19 of whom suffered from PTE. All underwent electroencephalographic (EEG) recordings and brain magnetic resonance imaging (bMRI). bMRIs were evaluated for BBB disruption using novel quantitative techniques. Cortical dysfunction was localized using standardized low-resolution brain electromagnetic tomography (sLORETA). TBI patients displayed significant EEG slowing compared to controls with no significant differences between PTE and nonepileptic patients. BBB disruption was found in 82.4% of PTE compared to 25% of non-epileptic patients (P = .001) and could be observed even years following the trauma. The volume of cerebral cortex with BBB disruption was significantly larger in PTE patients (P = .001). Slow wave EEG activity was localized to the same region of BBB disruption in 70% of patients and correlated to the volume of BBB disrupted cortex. We finally present a patient suffering from early cortical dysfunction and BBB breakdown with a gradual and parallel resolution of both pathologies. Our findings demonstrate that BBB pathology is frequently found following mild TBI. Lasting BBB breakdown is found with increased frequency and extent in PTE patients. Based on recent animal studies and the colocalization found between the region of disrupted BBB and abnormal EEG activity, we suggest a role for a vascular lesion in the pathogenesis of PTE. PMID:21436875
Losing the struggle to stay awake: divergent thalamic and cortical activity during microsleeps.
Poudel, Govinda R; Innes, Carrie R H; Bones, Philip J; Watts, Richard; Jones, Richard D
2014-01-01
Maintaining alertness is critical for safe and successful performance of most human activities. Consequently, microsleeps during continuous visuomotor tasks, such as driving, can be very serious, not only disrupting performance but sometimes leading to injury or death due to accidents. We have investigated the neural activity underlying behavioral microsleeps--brief (0.5-15 s) episodes of complete failure to respond accompanied by slow eye-closures--and EEG theta activity during drowsiness in a continuous task. Twenty healthy normally-rested participants performed a 50-min continuous tracking task while fMRI, EEG, eye-video, and responses were simultaneously recorded. Visual rating of performance and eye-video revealed that 70% of the participants had frequent microsleeps. fMRI analysis revealed a transient decrease in thalamic, posterior cingulate, and occipital cortex activity and an increase in frontal, posterior parietal, and parahippocampal activity during microsleeps. The transient activity was modulated by the duration of the microsleep. In subjects with frequent microsleeps, power in the post-central EEG theta was positively correlated with the BOLD signal in the thalamus, basal forebrain, and visual, posterior parietal, and prefrontal cortices. These results provide evidence for distinct neural changes associated with microsleeps and with EEG theta activity during drowsiness in a continuous task. They also suggest that the occurrence of microsleeps during an active task is not a global deactivation process but involves localized activation of fronto-parietal cortex, which, despite a transient loss of arousal, may constitute a mechanism by which these regions try to restore responsiveness. Copyright © 2012 Wiley Periodicals, Inc.
Aoki, Yasunori; Kazui, Hiroaki; Tanaka, Toshihisa; Ishii, Ryouhei; Wada, Tamiki; Ikeda, Shunichiro; Hata, Masahiro; Canuet, Leonides; Musha, Toshimitsu; Matsuzaki, Haruyasu; Imajo, Kaoru; Yoshiyama, Kenji; Yoshida, Tetsuhiko; Shimizu, Yoshiro; Nomura, Keiko; Iwase, Masao; Takeda, Masatoshi
2013-01-01
Idiopathic normal pressure hydrocephalus (iNPH) is a neuropsychiatric syndrome characterized by gait disturbance, cognitive impairment and urinary incontinence that affect elderly individuals. These symptoms can potentially be reversed by cerebrospinal fluid (CSF) drainage or shunt operation. Prior to shunt operation, drainage of a small amount of CSF or “CSF tapping” is usually performed to ascertain the effect of the operation. Unfortunately, conventional neuroimaging methods such as single photon emission computed tomography (SPECT) and functional magnetic resonance imaging (fMRI), as well as electroencephalogram (EEG) power analysis seem to have failed to detect the effect of CSF tapping on brain function. In this work, we propose the use of Neuronal Activity Topography (NAT) analysis, which calculates normalized power variance (NPV) of EEG waves, to detect cortical functional changes induced by CSF tapping in iNPH. Based on clinical improvement by CSF tapping and shunt operation, we classified 24 iNPH patients into responders (N = 11) and nonresponders (N = 13), and performed both EEG power analysis and NAT analysis. We also assessed correlations between changes in NPV and changes in functional scores on gait and cognition scales before and after CSF tapping. NAT analysis showed that after CSF tapping there was a significant decrease in alpha NPV at the medial frontal cortex (FC) (Fz) in responders, while nonresponders exhibited an increase in alpha NPV at the right dorsolateral prefrontal cortex (DLPFC) (F8). Furthermore, we found correlations between cortical functional changes and clinical symptoms. In particular, delta and alpha NPV changes in the left-dorsal FC (F3) correlated with changes in gait status, while alpha and beta NPV changes in the right anterior prefrontal cortex (PFC) (Fp2) and left DLPFC (F7) as well as alpha NPV changes in the medial FC (Fz) correlated with changes in gait velocity. In addition, alpha NPV changes in the right DLPFC (F8) correlated with changes in WMS-R Mental Control scores in iNPH patients. An additional analysis combining the changes in values of alpha NPV over the left-dorsal FC (∆alpha-F3-NPV) and the medial FC (∆alpha-Fz-NPV) induced by CSF tapping (cut-off value of ∆alpha-F3-NPV + ∆alpha-Fz-NPV = 0), could correctly identified “shunt responders” and “shunt nonresponders” with a positive predictive value of 100% (10/10) and a negative predictive value of 66% (2/3). In contrast, EEG power spectral analysis showed no function related changes in cortical activity at the frontal cortex before and after CSF tapping. These results indicate that the clinical changes in gait and response suppression induced by CSF tapping in iNPH patients manifest as NPV changes, particularly in the alpha band, rather than as EEG power changes. Our findings suggest that NAT analysis can detect CSF tapping-induced functional changes in cortical activity, in a way that no other neuroimaging methods have been able to do so far, and can predict clinical response to shunt operation in patients with iNPH. PMID:24273735
Aoki, Yasunori; Kazui, Hiroaki; Tanaka, Toshihisa; Ishii, Ryouhei; Wada, Tamiki; Ikeda, Shunichiro; Hata, Masahiro; Canuet, Leonides; Musha, Toshimitsu; Matsuzaki, Haruyasu; Imajo, Kaoru; Yoshiyama, Kenji; Yoshida, Tetsuhiko; Shimizu, Yoshiro; Nomura, Keiko; Iwase, Masao; Takeda, Masatoshi
2013-01-01
Idiopathic normal pressure hydrocephalus (iNPH) is a neuropsychiatric syndrome characterized by gait disturbance, cognitive impairment and urinary incontinence that affect elderly individuals. These symptoms can potentially be reversed by cerebrospinal fluid (CSF) drainage or shunt operation. Prior to shunt operation, drainage of a small amount of CSF or "CSF tapping" is usually performed to ascertain the effect of the operation. Unfortunately, conventional neuroimaging methods such as single photon emission computed tomography (SPECT) and functional magnetic resonance imaging (fMRI), as well as electroencephalogram (EEG) power analysis seem to have failed to detect the effect of CSF tapping on brain function. In this work, we propose the use of Neuronal Activity Topography (NAT) analysis, which calculates normalized power variance (NPV) of EEG waves, to detect cortical functional changes induced by CSF tapping in iNPH. Based on clinical improvement by CSF tapping and shunt operation, we classified 24 iNPH patients into responders (N = 11) and nonresponders (N = 13), and performed both EEG power analysis and NAT analysis. We also assessed correlations between changes in NPV and changes in functional scores on gait and cognition scales before and after CSF tapping. NAT analysis showed that after CSF tapping there was a significant decrease in alpha NPV at the medial frontal cortex (FC) (Fz) in responders, while nonresponders exhibited an increase in alpha NPV at the right dorsolateral prefrontal cortex (DLPFC) (F8). Furthermore, we found correlations between cortical functional changes and clinical symptoms. In particular, delta and alpha NPV changes in the left-dorsal FC (F3) correlated with changes in gait status, while alpha and beta NPV changes in the right anterior prefrontal cortex (PFC) (Fp2) and left DLPFC (F7) as well as alpha NPV changes in the medial FC (Fz) correlated with changes in gait velocity. In addition, alpha NPV changes in the right DLPFC (F8) correlated with changes in WMS-R Mental Control scores in iNPH patients. An additional analysis combining the changes in values of alpha NPV over the left-dorsal FC (∆alpha-F3-NPV) and the medial FC (∆alpha-Fz-NPV) induced by CSF tapping (cut-off value of ∆alpha-F3-NPV + ∆alpha-Fz-NPV = 0), could correctly identified "shunt responders" and "shunt nonresponders" with a positive predictive value of 100% (10/10) and a negative predictive value of 66% (2/3). In contrast, EEG power spectral analysis showed no function related changes in cortical activity at the frontal cortex before and after CSF tapping. These results indicate that the clinical changes in gait and response suppression induced by CSF tapping in iNPH patients manifest as NPV changes, particularly in the alpha band, rather than as EEG power changes. Our findings suggest that NAT analysis can detect CSF tapping-induced functional changes in cortical activity, in a way that no other neuroimaging methods have been able to do so far, and can predict clinical response to shunt operation in patients with iNPH.
Wang, Chao; Rajagovindan, Rajasimhan; Han, Sahng-Min; Ding, Mingzhou
2016-01-01
Alpha oscillations (8–12 Hz) are thought to inversely correlate with cortical excitability. Goal-oriented modulation of alpha has been studied extensively. In visual spatial attention, alpha over the region of visual cortex corresponding to the attended location decreases, signifying increased excitability to facilitate the processing of impending stimuli. In contrast, in retention of verbal working memory, alpha over visual cortex increases, signifying decreased excitability to gate out stimulus input to protect the information held online from sensory interference. According to the prevailing model, this goal-oriented biasing of sensory cortex is effected by top-down control signals from frontal and parietal cortices. The present study tests and substantiates this hypothesis by (a) identifying the signals that mediate the top-down biasing influence, (b) examining whether the cortical areas issuing these signals are task-specific or task-independent, and (c) establishing the possible mechanism of the biasing action. High-density human EEG data were recorded in two experimental paradigms: a trial-by-trial cued visual spatial attention task and a modified Sternberg working memory task. Applying Granger causality to both sensor-level and source-level data we report the following findings. In covert visual spatial attention, the regions exerting top-down control over visual activity are lateralized to the right hemisphere, with the dipoles located at the right frontal eye field (FEF) and the right inferior frontal gyrus (IFG) being the main sources of top-down influences. During retention of verbal working memory, the regions exerting top-down control over visual activity are lateralized to the left hemisphere, with the dipoles located at the left middle frontal gyrus (MFG) being the main source of top-down influences. In both experiments, top-down influences are mediated by alpha oscillations, and the biasing effect is likely achieved via an inhibition-disinhibition mechanism. PMID:26834601
Periodic leg movements during sleep and cerebral hemodynamic changes detected by NIRS.
Pizza, Fabio; Biallas, Martin; Wolf, Martin; Valko, Philipp O; Bassetti, Claudio L
2009-07-01
Periodic leg movements during sleep (PLMS) have been shown to be associated with changes in autonomic and hemispheric activities. Near infrared spectroscopy (NIRS) assesses hemodynamic changes linked to hemispheric/cortical activity. We applied NIRS to test whether cerebral hemodynamic alterations accompany PLMS. Three PLMS patients underwent nocturnal polysomnography coupled with cerebral NIRS. EEG correlates of PLMS were scored and NIRS data were analysed for the identification of correspondent hemodynamic changes. PLMS were constantly associated with cerebral hemodynamic fluctuations that showed greater amplitude when associated to changes in EEG and were present also in absence of any visually detectable arousal or A phase in the EEG. This is the first study documenting cerebral hemodynamic changes linked to PLMS. The clinical relevance of these observations remains to be determined.
Dresler, Martin; Wehrle, Renate; Spoormaker, Victor I; Koch, Stefan P; Holsboer, Florian; Steiger, Axel; Obrig, Hellmuth; Sämann, Philipp G; Czisch, Michael
2012-07-01
To investigate the neural correlates of lucid dreaming. Parallel EEG/fMRI recordings of night sleep. Sleep laboratory and fMRI facilities. Four experienced lucid dreamers. N/A. Out of 4 participants, one subject had 2 episodes of verified lucid REM sleep of sufficient length to be analyzed by fMRI. During lucid dreaming the bilateral precuneus, cuneus, parietal lobules, and prefrontal and occipito-temporal cortices activated strongly as compared with non-lucid REM sleep. In line with recent EEG data, lucid dreaming was associated with a reactivation of areas which are normally deactivated during REM sleep. This pattern of activity can explain the recovery of reflective cognitive capabilities that are the hallmark of lucid dreaming.
Giacometti, Paolo; Perdue, Katherine L.; Diamond, Solomon G.
2014-01-01
Background Interpretation and analysis of electroencephalography (EEG) measurements relies on the correspondence of electrode scalp coordinates to structural and functional regions of the brain. New Method An algorithm is introduced for automatic calculation of the International 10–20, 10-10, and 10-5 scalp coordinates of EEG electrodes on a boundary element mesh of a human head. The EEG electrode positions are then used to generate parcellation regions of the cerebral cortex based on proximity to the EEG electrodes. Results The scalp electrode calculation method presented in this study effectively and efficiently identifies EEG locations without prior digitization of coordinates. The average of electrode proximity parcellations of the cortex were tabulated with respect to structural and functional regions of the brain in a population of 20 adult subjects. Comparison with Existing Methods Parcellations based on electrode proximity and EEG sensitivity were compared. The parcellation regions based on sensitivity and proximity were found to have 44.0 ± 11.3% agreement when demarcated by the International 10–20, 32.4 ± 12.6% by the 10-10, and 24.7 ± 16.3% by the 10-5 electrode positioning system. Conclusions The EEG positioning algorithm is a fast and easy method of locating EEG scalp coordinates without the need for digitized electrode positions. The parcellation method presented summarizes the EEG scalp locations with respect to brain regions without computation of a full EEG forward model solution. The reference table of electrode proximity versus cortical regions may be used by experimenters to select electrodes that correspond to anatomical and functional regions of interest. PMID:24769168
Anderson, Clare; Horne, James A
2004-06-01
Others have shown that frontally dominant EEG activity of around 7-8 Hz is linked to ongoing cognitive performance. Interestingly, we have found that this EEG activity is particularly evident during the relatively artefact-free period following "lights out" at bedtime when people report "thinking" when lying relaxed in their own beds prior to the appearance of EEG-determined sleepiness. Here, we explore the extent to which this localised activity is indicative of 'trait' performance on left frontal neuropsychological tasks, as well as with less localised, more general tasks. Twelve right-handed young adults (mean age: 21.3 years) and 12 right-handed older adults (mean age: 67.2 years) underwent (i) morning, laboratory-based, waking EEGs comprising (eyes closed) contrived thinking tasks, and (ii) a home-based wake EEG at bedtime. EEGs divided the cortex into the four comparable quadrants: Fp1-F3; Fp2-F4; O1-P3; and O2-P4. From a wide frequency band of 3-10 Hz analysed in 1-Hz bins, only 7-8 Hz was associated with the neuropsychological performance (nonverbal planning, verbal fluency) for both younger and older participants. This was most evident during relaxed waking after 'lights out,' and from the left frontal EEG. Such associations were not apparent for the other EEG channels or for the nonspecific tasks. Laboratory-based daytime, frontal EEG recordings are problematic because of eye movement artefact and when participants are not fully relaxed. In contrast, the nighttime data are almost artefact-free and from fully relaxed participants. This particular EEG is useful for assessing cortically localised behaviour and indicates that a more traditional approach of using large bandwidths (e.g., the whole of "alpha" or "theta" ranges) may mask subfrequencies of functional importance.
Giacometti, Paolo; Perdue, Katherine L; Diamond, Solomon G
2014-05-30
Interpretation and analysis of electroencephalography (EEG) measurements relies on the correspondence of electrode scalp coordinates to structural and functional regions of the brain. An algorithm is introduced for automatic calculation of the International 10-20, 10-10, and 10-5 scalp coordinates of EEG electrodes on a boundary element mesh of a human head. The EEG electrode positions are then used to generate parcellation regions of the cerebral cortex based on proximity to the EEG electrodes. The scalp electrode calculation method presented in this study effectively and efficiently identifies EEG locations without prior digitization of coordinates. The average of electrode proximity parcellations of the cortex were tabulated with respect to structural and functional regions of the brain in a population of 20 adult subjects. Parcellations based on electrode proximity and EEG sensitivity were compared. The parcellation regions based on sensitivity and proximity were found to have 44.0 ± 11.3% agreement when demarcated by the International 10-20, 32.4 ± 12.6% by the 10-10, and 24.7 ± 16.3% by the 10-5 electrode positioning system. The EEG positioning algorithm is a fast and easy method of locating EEG scalp coordinates without the need for digitized electrode positions. The parcellation method presented summarizes the EEG scalp locations with respect to brain regions without computation of a full EEG forward model solution. The reference table of electrode proximity versus cortical regions may be used by experimenters to select electrodes that correspond to anatomical and functional regions of interest. Copyright © 2014 Elsevier B.V. All rights reserved.
Neural and behavioral associations of manipulated determination facial expressions.
Price, Tom F; Hortensius, Ruud; Harmon-Jones, Eddie
2013-09-01
Past research associated relative left frontal cortical activity with positive affect and approach motivation, or the urge to move toward a stimulus. Less work has examined relative left frontal activity and positive emotions ranging from low to high approach motivation, to test whether positive affects that differ in approach motivational intensity influence relative left frontal cortical activity. Participants in the present experiment adopted determination (high approach positive), satisfaction (low approach positive), or neutral facial expressions while electroencephalographic (EEG) activity was recorded. Next, participants completed a task measuring motivational persistence behavior and then they completed self-report emotion questionnaires. Determination compared to satisfaction and neutral facial expressions caused greater relative left frontal activity relative to baseline EEG recordings. Facial expressions did not directly influence task persistence. However, relative left frontal activity correlated positively with persistence on insolvable tasks in the determination condition. These results extend embodiment theories and motivational interpretations of relative left frontal activity. Published by Elsevier B.V.
Semantic memory retrieval circuit: role of pre-SMA, caudate, and thalamus.
Hart, John; Maguire, Mandy J; Motes, Michael; Mudar, Raksha Anand; Chiang, Hsueh-Sheng; Womack, Kyle B; Kraut, Michael A
2013-07-01
We propose that pre-supplementary motor area (pre-SMA)-thalamic interactions govern processes fundamental to semantic retrieval of an integrated object memory. At the onset of semantic retrieval, pre-SMA initiates electrical interactions between multiple cortical regions associated with semantic memory subsystems encodings as indexed by an increase in theta-band EEG power. This starts between 100-150 ms after stimulus presentation and is sustained throughout the task. We posit that this activity represents initiation of the object memory search, which continues in searching for an object memory. When the correct memory is retrieved, there is a high beta-band EEG power increase, which reflects communication between pre-SMA and thalamus, designates the end of the search process and resultant in object retrieval from multiple semantic memory subsystems. This high beta signal is also detected in cortical regions. This circuit is modulated by the caudate nuclei to facilitate correct and suppress incorrect target memories. Copyright © 2012 Elsevier Inc. All rights reserved.
Cortical dendritic activity correlates with spindle-rich oscillations during sleep in rodents.
Seibt, Julie; Richard, Clément J; Sigl-Glöckner, Johanna; Takahashi, Naoya; Kaplan, David I; Doron, Guy; de Limoges, Denis; Bocklisch, Christina; Larkum, Matthew E
2017-09-25
How sleep influences brain plasticity is not known. In particular, why certain electroencephalographic (EEG) rhythms are linked to memory consolidation is poorly understood. Calcium activity in dendrites is known to be necessary for structural plasticity changes, but this has never been carefully examined during sleep. Here, we report that calcium activity in populations of neocortical dendrites is increased and synchronised during oscillations in the spindle range in naturally sleeping rodents. Remarkably, the same relationship is not found in cell bodies of the same neurons and throughout the cortical column. Spindles during sleep have been suggested to be important for brain development and plasticity. Our results provide evidence for a physiological link of spindles in the cortex specific to dendrites, the main site of synaptic plasticity.Different stages of sleep, marked by particular electroencephalographic (EEG) signatures, have been linked to memory consolidation, but underlying mechanisms are poorly understood. Here, the authors show that dendritic calcium synchronisation correlates with spindle-rich sleep phases.
Aydin, Ümit; Vorwerk, Johannes; Dümpelmann, Matthias; Küpper, Philipp; Kugel, Harald; Heers, Marcel; Wellmer, Jörg; Kellinghaus, Christoph; Haueisen, Jens; Rampp, Stefan; Stefan, Hermann; Wolters, Carsten H.
2015-01-01
We investigated two important means for improving source reconstruction in presurgical epilepsy diagnosis. The first investigation is about the optimal choice of the number of epileptic spikes in averaging to (1) sufficiently reduce the noise bias for an accurate determination of the center of gravity of the epileptic activity and (2) still get an estimation of the extent of the irritative zone. The second study focuses on the differences in single modality EEG (80-electrodes) or MEG (275-gradiometers) and especially on the benefits of combined EEG/MEG (EMEG) source analysis. Both investigations were validated with simultaneous stereo-EEG (sEEG) (167-contacts) and low-density EEG (ldEEG) (21-electrodes). To account for the different sensitivity profiles of EEG and MEG, we constructed a six-compartment finite element head model with anisotropic white matter conductivity, and calibrated the skull conductivity via somatosensory evoked responses. Our results show that, unlike single modality EEG or MEG, combined EMEG uses the complementary information of both modalities and thereby allows accurate source reconstructions also at early instants in time (epileptic spike onset), i.e., time points with low SNR, which are not yet subject to propagation and thus supposed to be closer to the origin of the epileptic activity. EMEG is furthermore able to reveal the propagation pathway at later time points in agreement with sEEG, while EEG or MEG alone reconstructed only parts of it. Subaveraging provides important and accurate information about both the center of gravity and the extent of the epileptogenic tissue that neither single nor grand-averaged spike localizations can supply. PMID:25761059
Vecchio, Fabrizio; Miraglia, Francesca; Piludu, Francesca; Granata, Giuseppe; Romanello, Roberto; Caulo, Massimo; Onofrj, Valeria; Bramanti, Placido; Colosimo, Cesare; Rossini, Paolo Maria
2017-04-01
Brain imaging plays an important role in the study of Alzheimer's disease (AD), where atrophy has been found to occur in the hippocampal formation during the very early disease stages and to progress in parallel with the disease's evolution. The aim of the present study was to evaluate a possible correlation between "Small World" characteristics of the brain connectivity architecture-as extracted from EEG recordings-and hippocampal volume in AD patients. A dataset of 144 subjects, including 110 AD (MMSE 21.3) and 34 healthy Nold (MMSE 29.8) individuals, was evaluated. Weighted and undirected networks were built by the eLORETA solutions of the cortical sources' activities moving from EEG recordings. The evaluation of the hippocampal volume was carried out on a subgroup of 60 AD patients who received a high-resolution T1-weighted sequence and underwent processing for surface-based cortex reconstruction and volumetric segmentation using the Freesurfer image analysis software. Results showed that, quantitatively, more correlation was observed in the right hemisphere, but the same trend was seen in both hemispheres. Alpha band connectivity was negatively correlated, while slow (delta) and fast-frequency (beta, gamma) bands positively correlated with hippocampal volume. Namely, the larger the hippocampal volume, the lower the alpha and the higher the delta, beta, and gamma Small World characteristics of connectivity. Accordingly, the Small World connectivity pattern could represent a functional counterpart of structural hippocampal atrophying and related-network disconnection.
Neural basis for brain responses to TV commercials: a high-resolution EEG study.
Astolfi, Laura; De Vico Fallani, F; Cincotti, F; Mattia, D; Bianchi, L; Marciani, M G; Salinari, S; Colosimo, A; Tocci, A; Soranzo, R; Babiloni, F
2008-12-01
We investigated brain activity during the observation of TV commercials by tracking the cortical activity and the functional connectivity changes in normal subjects. The aim was to elucidate if the TV commercials that were remembered by the subjects several days after their first observation elicited particular brain activity and connectivity compared with those generated during the observation of TV commercials that were quickly forgotten. High-resolution electroencephalogram (EEG) recordings were performed in a group of healthy subjects and the cortical activity during the observation of TV commercials was evaluated in several regions of interest coincident with the Brodmann areas (BAs). The patterns of cortical connectivity were obtained in the four principal frequency bands, Theta (3-7 Hz), Alpha (8-12 Hz), Beta (13-30 Hz), Gamma (30-40 Hz) and the directed influences between any given pair of the estimated cortical signals were evaluated by use of a multivariate spectral technique known as partial directed coherence. The topology of the cortical networks has been identified with tools derived from graph theory. Results suggest that the cortical activity and connectivity elicited by the viewing of the TV commercials that were remembered by the experimental subjects are markedly different from the brain activity elicited during the observation of the TV commercials that were forgotten. In particular, during the observation of the TV commercials that were remembered, the amount of cortical spectral activity from the frontal areas (BA 8 and 9) and from the parietal areas (BA 5, 7, and 40) is higher compared with the activity elicited by the observation of TV commercials that were forgotten. In addition, network analysis suggests a clear role of the parietal areas as a target of the incoming flow of information from all the other parts of the cortex during the observation of TV commercials that have been remembered. The techniques presented here shed new light on all the cortical networks and their behavior during the memorization of TV commercials. Such techniques could also be relevant in neuroeconomics and neuromarketing for the investigation of the neural substrates subserving other decision-making and recognition tasks.
Williams, Anthony J; Zhou, Chen; Sun, Qian-Quan
2016-01-01
Focal cortical dysplasias (FCDs) are a common cause of brain seizures and are often associated with intractable epilepsy. Here we evaluated aberrant brain neurophysiology in an in vivo mouse model of FCD induced by neonatal freeze lesions (FLs) to the right cortical hemisphere (near S1). Linear multi-electrode arrays were used to record extracellular potentials from cortical and subcortical brain regions near the FL in anesthetized mice (5-13 months old) followed by 24 h cortical electroencephalogram (EEG) recordings. Results indicated that FL animals exhibit a high prevalence of spontaneous spike-wave discharges (SWDs), predominately during sleep (EEG), and an increase in the incidence of hyper-excitable burst/suppression activity under general anesthesia (extracellular recordings, 0.5%-3.0% isoflurane). Brief periods of burst activity in the local field potential (LFP) typically presented as an arrhythmic pattern of increased theta-alpha spectral peaks (4-12 Hz) on a background of low-amplitude delta activity (1-4 Hz), were associated with an increase in spontaneous spiking of cortical neurons, and were highly synchronized in control animals across recording sites in both cortical and subcortical layers (average cross-correlation values ranging from +0.73 to +1.0) with minimal phase shift between electrodes. However, in FL animals, cortical vs. subcortical burst activity was strongly out of phase with significantly lower cross-correlation values compared to controls (average values of -0.1 to +0.5, P < 0.05 between groups). In particular, a marked reduction in the level of synchronous burst activity was observed, the closer the recording electrodes were to the malformation (Pearson's Correlation = 0.525, P < 0.05). In a subset of FL animals (3/9), burst activity also included a spike or spike-wave pattern similar to the SWDs observed in unanesthetized animals. In summary, neonatal FLs increased the hyperexcitable pattern of burst activity induced by anesthesia and disrupted field potential synchrony between cortical and subcortical brain regions near the site of the cortical malformation. Monitoring the altered electrophysiology of burst activity under general anesthesia with multi-dimensional micro-electrode arrays may serve to define distinct neurophysiological biomarkers of epileptogenesis in human brain and improve techniques for surgical resection of epileptogenic malformed brain tissue.
Daou, Marcos; Sassi, Julia Montagner; Miller, Matthew W; Gonzalez, Adam M
2018-03-13
This study assessed whether a multi-ingredient energy supplement (MIES) could enhance cerebral-cortical activation and cognitive performance during an attention-switching task. Cerebral-cortical activation was recorded in 24 young adults (12 males, 12 females; 22.8 ± 3.8 yrs) via electroencephalography (EEG) both at rest and during the attention-switching task before (pretest) and 30 min after (posttest) consumption of a single serving of a MIES (MIES-1), two servings of a MIES (MIES-2), or a placebo (PL) in a double-blinded, randomized crossover experimental design. EEG upper-alpha power was assessed at rest and during the task, wherein d' (Z[hit rate]-Z[false alarm rate]) and median reaction time (RT) for correct responses to targets on attention-hold and attention-switch trials were analyzed. For both d' and RT, the Session (MIES-1, MIES-2, PL) × Time (pretest, posttest) interaction approached statistical significance (p = .07, η 2 p = 0.106). Exploring these interactions with linear contrasts, a significant linear effect of supplement dose on the linear effect of time was observed (ps ≤.034), suggesting the pretest-to-posttest improvement in sensitivity to task target stimuli (d') and RT increased as a function of supplement dose. With respect to upper-alpha power, the Session × Time interaction was significant (p < .001, η 2 p = 0.422). Exploring this interaction with linear contrasts, a significant linear effect of supplement dose on the linear effect of time was observed (p < .001), suggesting pretest-to-posttest increases in cerebral-cortical activation were a function of supplement dose. In conclusion, our findings suggest that MIES can increase cerebral-cortical activation and RT during task performance while increasing sensitivity to target stimuli in a dose-dependent manner.
Nunez, Paul L.; Srinivasan, Ramesh
2013-01-01
The brain is treated as a nested hierarchical complex system with substantial interactions across spatial scales. Local networks are pictured as embedded within global fields of synaptic action and action potentials. Global fields may act top-down on multiple networks, acting to bind remote networks. Because of scale-dependent properties, experimental electrophysiology requires both local and global models that match observational scales. Multiple local alpha rhythms are embedded in a global alpha rhythm. Global models are outlined in which cm-scale dynamic behaviors result largely from propagation delays in cortico-cortical axons and cortical background excitation level, controlled by neuromodulators on long time scales. The idealized global models ignore the bottom-up influences of local networks on global fields so as to employ relatively simple mathematics. The resulting models are transparently related to several EEG and steady state visually evoked potentials correlated with cognitive states, including estimates of neocortical coherence structure, traveling waves, and standing waves. The global models suggest that global oscillatory behavior of self-sustained (limit-cycle) modes lower than about 20 Hz may easily occur in neocortical/white matter systems provided: Background cortical excitability is sufficiently high; the strength of long cortico-cortical axon systems is sufficiently high; and the bottom-up influence of local networks on the global dynamic field is sufficiently weak. The global models provide "entry points" to more detailed studies of global top-down influences, including binding of weakly connected networks, modulation of gamma oscillations by theta or alpha rhythms, and the effects of white matter deficits. PMID:24505628
Küssner, Mats B
2017-01-01
The question of whether background music is able to enhance cognitive task performance is of interest to scholars, educators, and stakeholders in business alike. Studies have shown that background music can have beneficial, detrimental or no effects on cognitive task performance. Extraversion-and its postulated underlying cause, cortical arousal-is regarded as an important factor influencing the outcome of such studies. According to Eysenck's theory of personality, extraverts' cortical arousal at rest is lower compared to that of introverts. Scholars have thus hypothesized that extraverts should benefit from background music in cognitive tasks, whereas introverts' performance should decline with music in the background. Reviewing studies that have considered extraversion as a mediator of the effect of background music on cognitive task performance, it is demonstrated that there is as much evidence in favor as there is against Eysenck's theory of personality. Further, revisiting Eysenck's concept of cortical arousal-which has traditionally been assessed by activity in the EEG alpha band-and reviewing literature on the link between extraversion and cortical arousal, it is revealed that there is conflicting evidence. Due to Eysenck's focus on alpha power, scholars have largely neglected higher frequency bands in the EEG signal as indicators of cortical arousal. Based on recent findings, it is suggested that beta power might not only be an indicator of alertness and attention but also a predictor of cognitive task performance. In conclusion, it is proposed that focused music listening prior to cognitive tasks might be a more efficient way to boost performance than listening to background music during cognitive tasks.
Küssner, Mats B.
2017-01-01
The question of whether background music is able to enhance cognitive task performance is of interest to scholars, educators, and stakeholders in business alike. Studies have shown that background music can have beneficial, detrimental or no effects on cognitive task performance. Extraversion—and its postulated underlying cause, cortical arousal—is regarded as an important factor influencing the outcome of such studies. According to Eysenck's theory of personality, extraverts' cortical arousal at rest is lower compared to that of introverts. Scholars have thus hypothesized that extraverts should benefit from background music in cognitive tasks, whereas introverts' performance should decline with music in the background. Reviewing studies that have considered extraversion as a mediator of the effect of background music on cognitive task performance, it is demonstrated that there is as much evidence in favor as there is against Eysenck's theory of personality. Further, revisiting Eysenck's concept of cortical arousal—which has traditionally been assessed by activity in the EEG alpha band—and reviewing literature on the link between extraversion and cortical arousal, it is revealed that there is conflicting evidence. Due to Eysenck's focus on alpha power, scholars have largely neglected higher frequency bands in the EEG signal as indicators of cortical arousal. Based on recent findings, it is suggested that beta power might not only be an indicator of alertness and attention but also a predictor of cognitive task performance. In conclusion, it is proposed that focused music listening prior to cognitive tasks might be a more efficient way to boost performance than listening to background music during cognitive tasks. PMID:29184523
Luu, Trieu Phat; He, Yongtian; Brown, Samuel; Nakagame, Sho; Contreras-Vidal, Jose L.
2017-01-01
Objective The control of human bipedal locomotion is of great interest to the field of lower-body brain computer interfaces (BCIs) for gait rehabilitation. While the feasibility of closed-loop BCI systems for the control of a lower body exoskeleton has been recently shown, multi-day closed-loop neural decoding of human gait in a BCI virtual reality (BCI-VR) environment has yet to be demonstrated. BCI-VR systems provide valuable alternatives for movement rehabilitation when wearable robots are not desirable due to medical conditions, cost, accessibility, usability, or patient preferences. Approach In this study, we propose a real-time closed-loop BCI that decodes lower limb joint angles from scalp electroencephalography (EEG) during treadmill walking to control a walking avatar in a virtual environment. Fluctuations in the amplitude of slow cortical potentials of EEG in the delta band (0.1 – 3 Hz) were used for prediction; thus, the EEG features correspond to time-domain amplitude modulated (AM) potentials in the delta band. Virtual kinematic perturbations resulting in asymmetric walking gait patterns of the avatar were also introduced to investigate gait adaptation using the closed-loop BCI-VR system over a period of eight days. Main results Our results demonstrate the feasibility of using a closed-loop BCI to learn to control a walking avatar under normal and altered visuomotor perturbations, which involved cortical adaptations. The average decoding accuracies (Pearson’s r values) in real-time BCI across all subjects increased from (Hip: 0.18 ± 0.31; Knee: 0.23 ± 0.33; Ankle: 0.14 ± 0.22) on Day 1 to (Hip: 0.40 ± 0.24; Knee: 0.55 ± 0.20; Ankle: 0.29 ± 0.22) on Day 8. Significance These findings have implications for the development of a real-time closed-loop EEG-based BCI-VR system for gait rehabilitation after stroke and for understanding cortical plasticity induced by a closed-loop BCI-VR system. PMID:27064824
Luu, Trieu Phat; He, Yongtian; Brown, Samuel; Nakagame, Sho; Contreras-Vidal, Jose L
2016-06-01
The control of human bipedal locomotion is of great interest to the field of lower-body brain-computer interfaces (BCIs) for gait rehabilitation. While the feasibility of closed-loop BCI systems for the control of a lower body exoskeleton has been recently shown, multi-day closed-loop neural decoding of human gait in a BCI virtual reality (BCI-VR) environment has yet to be demonstrated. BCI-VR systems provide valuable alternatives for movement rehabilitation when wearable robots are not desirable due to medical conditions, cost, accessibility, usability, or patient preferences. In this study, we propose a real-time closed-loop BCI that decodes lower limb joint angles from scalp electroencephalography (EEG) during treadmill walking to control a walking avatar in a virtual environment. Fluctuations in the amplitude of slow cortical potentials of EEG in the delta band (0.1-3 Hz) were used for prediction; thus, the EEG features correspond to time-domain amplitude modulated potentials in the delta band. Virtual kinematic perturbations resulting in asymmetric walking gait patterns of the avatar were also introduced to investigate gait adaptation using the closed-loop BCI-VR system over a period of eight days. Our results demonstrate the feasibility of using a closed-loop BCI to learn to control a walking avatar under normal and altered visuomotor perturbations, which involved cortical adaptations. The average decoding accuracies (Pearson's r values) in real-time BCI across all subjects increased from (Hip: 0.18 ± 0.31; Knee: 0.23 ± 0.33; Ankle: 0.14 ± 0.22) on Day 1 to (Hip: 0.40 ± 0.24; Knee: 0.55 ± 0.20; Ankle: 0.29 ± 0.22) on Day 8. These findings have implications for the development of a real-time closed-loop EEG-based BCI-VR system for gait rehabilitation after stroke and for understanding cortical plasticity induced by a closed-loop BCI-VR system.
Cheaha, Dania; Keawpradub, Niwat; Sawangjaroen, Kitja; Phukpattaranont, Pimpimol; Kumarnsit, Ekkasit
2015-10-15
Many antidepressants are effective in alleviating ethanol withdrawal symptoms. However, most of them suppress rapid eye movement (REM) sleep. Thus, development of antidepressants without undesirable side effects would be preferable. Previously, crude alkaloid extract from Mitragyna speciosa (MS) Korth was found to produce antidepressant activities. It was hypothesized that the alkaloid extract from MS may attenuate ethanol withdrawal without REM sleep disturbance. Adult male Wistar rats implanted with electrodes over the frontal and parietal cortices were used for two separated studies. For an acute study, 10 mg/kg fluoxetine or 60 mg/kg alkaloid extract from MS were administered intragastrically. Electroencephalographic (EEG) signals were recorded for 3 h to examine sleep profiles and EEG fingerprints. Another set of animal was used for an ethanol withdrawal study. They were rendered dependent on ethanol via a modified liquid diet (MLD) containing ethanol ad libitum for 28 days. On day 29, fluoxetine (10 mg/kg) or alkaloid extract from MS (60 mg/kg) were administered 15 min before the ethanol-containing MLD was replaced with an isocaloric ethanol-free MLD to induced ethanol withdrawal symptoms. The sleep analysis revealed that alkaloid extract from MS did not change any REM parameters which included average duration of each REM episode, total REM time, number of REM episode and REM latency whereas fluoxetine significantly suppressed all REM parameters and delayed REM latency. However, power spectral analysis revealed similar fingerprints for fluoxetine and alkaloid extract from MS characterized by decreasing powers in the slow frequency range in frontal and parietal cortical EEG. Neither treatment affected spontaneous motor activity. Finally, both alkaloid extract from MS and fluoxetine were found to significantly attenuate ethanol withdrawal-induced hyperexcitability (increases gamma activity) in both cortices and to reduce locomotor activity. The present study demonstrated that the alkaloid extract from MS alleviates ethanol withdrawal severity with no side effect on REM sleep. In addition, these data suggest that suppressive effects on slow frequency powers but not REM sleep may be hallmarks of effective antidepressants for ethanol withdrawal treatment. Copyright © 2015 Elsevier GmbH. All rights reserved.
The functional significance of EEG microstates--Associations with modalities of thinking.
Milz, P; Faber, P L; Lehmann, D; Koenig, T; Kochi, K; Pascual-Marqui, R D
2016-01-15
The momentary, global functional state of the brain is reflected by its electric field configuration. Cluster analytical approaches consistently extracted four head-surface brain electric field configurations that optimally explain the variance of their changes across time in spontaneous EEG recordings. These four configurations are referred to as EEG microstate classes A, B, C, and D and have been associated with verbal/phonological, visual, subjective interoceptive-autonomic processing, and attention reorientation, respectively. The present study tested these associations via an intra-individual and inter-individual analysis approach. The intra-individual approach tested the effect of task-induced increased modality-specific processing on EEG microstate parameters. The inter-individual approach tested the effect of personal modality-specific parameters on EEG microstate parameters. We obtained multichannel EEG from 61 healthy, right-handed, male students during four eyes-closed conditions: object-visualization, spatial-visualization, verbalization (6 runs each), and resting (7 runs). After each run, we assessed participants' degrees of object-visual, spatial-visual, and verbal thinking using subjective reports. Before and after the recording, we assessed modality-specific cognitive abilities and styles using nine cognitive tests and two questionnaires. The EEG of all participants, conditions, and runs was clustered into four classes of EEG microstates (A, B, C, and D). RMANOVAs, ANOVAs and post-hoc paired t-tests compared microstate parameters between conditions. TANOVAs compared microstate class topographies between conditions. Differences were localized using eLORETA. Pearson correlations assessed interrelationships between personal modality-specific parameters and EEG microstate parameters during no-task resting. As hypothesized, verbal as opposed to visual conditions consistently affected the duration, occurrence, and coverage of microstate classes A and B. Contrary to associations suggested by previous reports, parameters were increased for class A during visualization, and class B during verbalization. In line with previous reports, microstate D parameters were increased during no-task resting compared to the three internal, goal-directed tasks. Topographic differences between conditions included particular sub-regions of components of the metabolic default mode network. Modality-specific personal parameters did not consistently correlate with microstate parameters except verbal cognitive style which correlated negatively with microstate class A duration and positively with class C occurrence. This is the first study that aimed to induce EEG microstate class parameter changes based on their hypothesized functional significance. Beyond the associations of microstate classes A and B with visual and verbal processing, respectively, our results suggest that a finely-tuned interplay between all four EEG microstate classes is necessary for the continuous formation of visual and verbal thoughts. Our results point to the possibility that the EEG microstate classes may represent the head-surface measured activity of intra-cortical sources primarily exhibiting inhibitory functions. However, additional studies are needed to verify and elaborate on this hypothesis. Copyright © 2015 Elsevier Inc. All rights reserved.
High-Intensity Chronic Stroke Motor Imagery Neurofeedback Training at Home: Three Case Reports.
Zich, Catharina; Debener, Stefan; Schweinitz, Clara; Sterr, Annette; Meekes, Joost; Kranczioch, Cornelia
2017-11-01
Motor imagery (MI) with neurofeedback has been suggested as promising for motor recovery after stroke. Evidence suggests that regular training facilitates compensatory plasticity, but frequent training is difficult to integrate into everyday life. Using a wireless electroencephalogram (EEG) system, we implemented a frequent and efficient neurofeedback training at the patients' home. Aiming to overcome maladaptive changes in cortical lateralization patterns we presented a visual feedback, representing the degree of contralateral sensorimotor cortical activity and the degree of sensorimotor cortex lateralization. Three stroke patients practiced every other day, over a period of 4 weeks. Training-related changes were evaluated on behavioral, functional, and structural levels. All 3 patients indicated that they enjoyed the training and were highly motivated throughout the entire training regime. EEG activity induced by MI of the affected hand became more lateralized over the course of training in all three patients. The patient with a significant functional change also showed increased white matter integrity as revealed by diffusion tensor imaging, and a substantial clinical improvement of upper limb motor functions. Our study provides evidence that regular, home-based practice of MI neurofeedback has the potential to facilitate cortical reorganization and may also increase associated improvements of upper limb motor function in chronic stroke patients.
QEEG-based neural correlates of decision making in a well-trained eight year-old chess player.
Alipour, Abolfazl; Seifzadeh, Sahar; Aligholi, Hadi; Nami, Mohammad
2017-10-25
The neurocognitive substrates of decision making (DM) in the context of chess has appealed to researchers' interest for decades. Expert and beginner chess players are hypothesized to employ different brain functional networks when involved in episodes of critical DM upon chess. Cognitive capacities including, but not restricted to pattern recognition, visuospatial search, reasoning, planning and DM are perhaps the key determinants of rewarding and judgmental decisions in chess. Meanwhile, the precise neural correlates of DM in this context has largely remained elusive. The quantitative electroencephalography (QEEG) is an investigation tool possessing a proper temporal resolution in the study of neural correlates of cognitive tasks at cortical level. Here, we used a 22-channel EEG setup and digital polygraphy in a well-trained 8 year-old boy while engaged in playing chess against the computer. Quantitative analyses were done to map and source-localize the EEG signals. Our analyses indicated a lower power spectral density (PSD) for higher frequency bands in the right hemisphere upon DM-related epochs. Moreover, the information flow upon DM blocks in this particular case was more of posterior towards anterior brain regions.
Ianof, Jéssica Natuline; Fraga, Francisco José; Ferreira, Leonardo Alves; Ramos, Renato Teodoro; Demario, José Luiz Carlos; Baratho, Regina; Basile, Luís Fernando Hindi; Nitrini, Ricardo; Anghinah, Renato
2017-01-01
Alzheimer's disease (AD) is a dementia that affects a large contingent of the elderly population characterized by the presence of neurofibrillary tangles and senile plaques. Traumatic brain injury (TBI) is a non-degenerative injury caused by an external mechanical force. One of the main causes of TBI is diffuse axonal injury (DAI), promoted by acceleration-deceleration mechanisms. To understand the electroencephalographic differences in functional mechanisms between AD and DAI groups. The study included 20 subjects with AD, 19 with DAI and 17 healthy adults submitted to high resolution EEG with 128 channels. Cortical sources of EEG rhythms were estimated by exact low-resolution electromagnetic tomography (eLORETA) analysis. The eLORETA analysis showed that, in comparison to the control (CTL) group, the AD group had increased theta activity in the parietal and frontal lobes and decreased alpha 2 activity in the parietal, frontal, limbic and occipital lobes. In comparison to the CTL group, the DAI group had increased theta activity in the limbic, occipital sublobar and temporal areas. The results suggest that individuals with AD and DAI have impairment of electrical activity in areas important for memory and learning.
An exploratory data analysis of electroencephalograms using the functional boxplots approach
Ngo, Duy; Sun, Ying; Genton, Marc G.; Wu, Jennifer; Srinivasan, Ramesh; Cramer, Steven C.; Ombao, Hernando
2015-01-01
Many model-based methods have been developed over the last several decades for analysis of electroencephalograms (EEGs) in order to understand electrical neural data. In this work, we propose to use the functional boxplot (FBP) to analyze log periodograms of EEG time series data in the spectral domain. The functional bloxplot approach produces a median curve—which is not equivalent to connecting medians obtained from frequency-specific boxplots. In addition, this approach identifies a functional median, summarizes variability, and detects potential outliers. By extending FBPs analysis from one-dimensional curves to surfaces, surface boxplots are also used to explore the variation of the spectral power for the alpha (8–12 Hz) and beta (16–32 Hz) frequency bands across the brain cortical surface. By using rank-based nonparametric tests, we also investigate the stationarity of EEG traces across an exam acquired during resting-state by comparing the spectrum during the early vs. late phases of a single resting-state EEG exam. PMID:26347598
Krause, C M; Viemerö, V; Rosenqvist, A; Sillanmäki, L; Aström, T
2000-05-26
The reactivity of different narrow electroencephalographic (EEG) frequencies (4-6, 6-8, 8-10 and 10-12 Hz) to three types of emotionally laden film clips (aggressive, sad, neutral) were examined. We observed that different EEG frequency bands responded differently to the three types of film content. In the 4-6 Hz frequency band, the viewing of aggressive film content elicited greater relative synchronization as compared the responses elicited by the viewing of sad and neutral film content. The 6-8 Hz and 8-10 Hz frequency bands exhibited reactivity to the chronological succession of film viewing whereas the responses of the 10-12 Hz frequency band evolved within minutes during film viewing. Our results propose dissociations between the responses of different frequencies within the EEG to different emotion-related stimuli. Narrow frequency band EEG analysis offers an adequate tool for studying cortical activation patterns during emotion-related information processing.
Thomas, Bianca Lee; Viljoen, Margaretha
2016-01-01
The aim of this study was to assess baseline EEG brain wave activity in children with attention-deficit/hyperactivity disorder (ADHD) and to examine the effects of evoked attention and methylphenidate on this activity. Children with ADHD (n = 19) were tested while they were stimulant free and during a period in which they were on stimulant (methylphenidate) medication. Control subjects (n = 18) were tested once. EEG brain wave activity was tested both at baseline and during focussed attention. Attention was evoked and EEG brain wave activity was determined by means of the BioGraph Infiniti biofeedback apparatus. The main finding of this study was that control subjects and stimulant-free children with ADHD exhibited the expected reactivity in high alpha-wave activity (11-12 Hz) from baseline to focussed attention; however, methylphenidate appeared to abolish this reactivity. Methylphenidate attenuates the normal cortical response to a cognitive challenge. © 2016 S. Karger AG, Basel.
Dreaming and the default network: A review, synthesis, and counterintuitive research proposal.
Domhoff, G William; Fox, Kieran C R
2015-05-01
This article argues that the default network, augmented by secondary visual and sensorimotor cortices, is the likely neural correlate of dreaming. This hypothesis is based on a synthesis of work on dream content, the findings on the contents and neural correlates of mind-wandering, and the results from EEG and neuroimaging studies of REM sleep. Relying on studies in the 1970s that serendipitously discovered episodes of dreaming during waking mind-wandering, this article presents the seemingly counterintuitive hypothesis that the neural correlates for dreaming could be further specified in the process of carrying out EEG/fMRI studies of mind-wandering and default network activity. This hypothesis could be tested by asking participants for experiential reports during moments of differentially high levels of default network activation, as indicated by mixed EEG/fMRI criteria. Evidence from earlier EEG/fMRI studies of mind-wandering and from laboratory studies of dreaming during the sleep-onset process is used to support the argument. Copyright © 2015 Elsevier Inc. All rights reserved.
Dog EEG for wake-promotion studies.
Parmentier, Régis; Bricout, Denis; Brousseau, Emmanuel; Giboulot, Thierry
2006-10-01
Described in this unit is a protocol for investigating the wake-promoting activity of new chemical entities (NCEs) in dog. The experimental approach is based on scoring of sleep/wake stages in animals implanted with a telemetry device for recording EMG and cortical EEG signals. A major advantage of this procedure is that it is conducted in nontethered animals, limiting possible bias and complications encountered with conventional recording systems. In this procedure, polygraphic recording is conducted using four implanted beagles. Results of studies with modafinil, a wake-promoting agent, are described to demonstrate the utility of this test procedure.
On the Synchronization of EEG Spindle Waves
NASA Astrophysics Data System (ADS)
Long, Wen; Zhang, ChengFu; Zhao, SiLan; Shi, RuiHong
2000-06-01
Based on recently sleeping cellular substrates, a network model synaptically coupled by N three-cell circuits is provided. Simulation results show that: (i) the dynamic behavior of every circuit is chaotic; (ii) the synchronization of the network is incomplete; (iii) the incomplete synchronization can integrate burst firings of cortical cells into waxing-and-wanning EEG spindle waves. These results enlighten us that this kind of incomplete synchronization may integrate microscopic, electrical activities of neurons in billions into macroscopic, functional states in human brain. In addition, the effects of coupling strength, connectional mode and noise to the synchronization are discussed.
Smirnov, Michael S.; Kiyatkin, Eugene A.
2009-01-01
Many important physiological, behavioral and subjective effects of intravenous (iv) cocaine (COC) are exceptionally rapid and transient, suggesting a possible involvement of peripheral neural substrates in their triggering. In the present study, we used high-speed EEG and EMG recordings (4-s resolution) in freely moving rats to characterize the central electrophysiological effects of iv COC at low doses within a self-administration range (0.25-1.0 mg/kg). We found that COC induces rapid, strong, and prolonged desynchronization of cortical EEG (decrease in alpha and increase in beta and gamma activity) and activation of the neck EMG that begin within 2-6 s following the start of a 10-s injection; immediate components of both effects were dose-independent. The rapid effects of COC were mimicked by iv COC methiodide, a derivative that cannot cross the blood-brain barrier. At equimolar doses (0.33-1.33 mg/kg), COC methiodide had equally fast and strong effects on EEG and EMG total powers, decreasing alpha and increasing beta and gamma activities. Rapid EEG desynchronization and EMG activation was also induced by iv procaine, a structurally similar, short-acting local anesthetic with virtually no effects on monoamine uptake; at equipotential doses (1.25-5.0 mg/kg), these effects were weaker and shorter in duration than those of COC. Surprisingly, iv saline injection delivered during slow-wave sleep (but not during quiet wakefulness) also induced a transient EEG desynchronization but without changes in EMG and motor activity; these effects were significantly weaker and much shorter than those induced by all tested drugs. These data suggest that in awake animals, iv COC induces rapid cortical activation and a subsequent motor response via its action on peripheral non-monoamine neural elements, involving neural transmission via visceral sensory pathways. By providing a rapid neural signal and triggering neural activation, such an action might play a crucial role in the sensory effects of COC, thus contributing to the learning and development of drug-taking behavior. PMID:19861149
Early somatosensory processing in individuals at risk for developing psychoses.
Hagenmuller, Florence; Heekeren, Karsten; Theodoridou, Anastasia; Walitza, Susanne; Haker, Helene; Rössler, Wulf; Kawohl, Wolfram
2014-01-01
Human cortical somatosensory evoked potentials (SEPs) allow an accurate investigation of thalamocortical and early cortical processing. SEPs reveal a burst of superimposed early (N20) high-frequency oscillations around 600 Hz. Previous studies reported alterations of SEPs in patients with schizophrenia. This study addresses the question whether those alterations are also observable in populations at risk for developing schizophrenia or bipolar disorders. To our knowledge to date, this is the first study investigating SEPs in a population at risk for developing psychoses. Median nerve SEPs were investigated using multichannel EEG in individuals at risk for developing bipolar disorders (n = 25), individuals with high-risk status (n = 59) and ultra-high-risk status for schizophrenia (n = 73) and a gender and age-matched control group (n = 45). Strengths and latencies of low- and high-frequency components as estimated by dipole source analysis were compared between groups. Low- and high-frequency source activity was reduced in both groups at risk for schizophrenia, in comparison to the group at risk for bipolar disorders. HFO amplitudes were also significant reduced in subjects with high-risk status for schizophrenia compared to healthy controls. These differences were accentuated among cannabis non-users. Reduced N20 source strengths were related to higher positive symptom load. These results suggest that the risk for schizophrenia, in contrast to bipolar disorders, may involve an impairment of early cerebral somatosensory processing. Neurophysiologic alterations in schizophrenia precede the onset of initial psychotic episode and may serve as indicator of vulnerability for developing schizophrenia.
Early somatosensory processing in individuals at risk for developing psychoses
Hagenmuller, Florence; Heekeren, Karsten; Theodoridou, Anastasia; Walitza, Susanne; Haker, Helene; Rössler, Wulf; Kawohl, Wolfram
2014-01-01
Human cortical somatosensory evoked potentials (SEPs) allow an accurate investigation of thalamocortical and early cortical processing. SEPs reveal a burst of superimposed early (N20) high-frequency oscillations around 600 Hz. Previous studies reported alterations of SEPs in patients with schizophrenia. This study addresses the question whether those alterations are also observable in populations at risk for developing schizophrenia or bipolar disorders. To our knowledge to date, this is the first study investigating SEPs in a population at risk for developing psychoses. Median nerve SEPs were investigated using multichannel EEG in individuals at risk for developing bipolar disorders (n = 25), individuals with high-risk status (n = 59) and ultra-high-risk status for schizophrenia (n = 73) and a gender and age-matched control group (n = 45). Strengths and latencies of low- and high-frequency components as estimated by dipole source analysis were compared between groups. Low- and high-frequency source activity was reduced in both groups at risk for schizophrenia, in comparison to the group at risk for bipolar disorders. HFO amplitudes were also significant reduced in subjects with high-risk status for schizophrenia compared to healthy controls. These differences were accentuated among cannabis non-users. Reduced N20 source strengths were related to higher positive symptom load. These results suggest that the risk for schizophrenia, in contrast to bipolar disorders, may involve an impairment of early cerebral somatosensory processing. Neurophysiologic alterations in schizophrenia precede the onset of initial psychotic episode and may serve as indicator of vulnerability for developing schizophrenia. PMID:25309363
Broyd, Samantha J.; Helps, Suzannah K.; Sonuga-Barke, Edmund J. S.
2011-01-01
Background The default-mode network (DMN) is characterised by coherent very low frequency (VLF) brain oscillations. The cognitive significance of this VLF profile remains unclear, partly because of the temporally constrained nature of the blood oxygen-level dependent (BOLD) signal. Previously we have identified a VLF EEG network of scalp locations that shares many features of the DMN. Here we explore the intracranial sources of VLF EEG and examine their overlap with the DMN in adults with high and low ADHD ratings. Methodology/Principal Findings DC-EEG was recorded using an equidistant 66 channel electrode montage in 25 adult participants with high- and 25 participants with low-ratings of ADHD symptoms during a rest condition and an attention demanding Eriksen task. VLF EEG power was calculated in the VLF band (0.02 to 0.2 Hz) for the rest and task condition and compared for high and low ADHD participants. sLORETA was used to identify brain sources associated with the attention-induced deactivation of VLF EEG power, and to examine these sources in relation to ADHD symptoms. There was significant deactivation of VLF EEG power between the rest and task condition for the whole sample. Using s-LORETA the sources of this deactivation were localised to medial prefrontal regions, posterior cingulate cortex/precuneus and temporal regions. However, deactivation sources were different for high and low ADHD groups: In the low ADHD group attention-induced VLF EEG deactivation was most significant in medial prefrontal regions while for the high ADHD group this deactivation was predominantly localised to the temporal lobes. Conclusions/Significance Attention-induced VLF EEG deactivations have intracranial sources that appear to overlap with those of the DMN. Furthermore, these seem to be related to ADHD symptom status, with high ADHD adults failing to significantly deactivate medial prefrontal regions while at the same time showing significant attenuation of VLF EEG power in temporal lobes. PMID:21408092
Improved method for retinotopy constrained source estimation of visual evoked responses
Hagler, Donald J.; Dale, Anders M.
2011-01-01
Retinotopy constrained source estimation (RCSE) is a method for non-invasively measuring the time courses of activation in early visual areas using magnetoencephalography (MEG) or electroencephalography (EEG). Unlike conventional equivalent current dipole or distributed source models, the use of multiple, retinotopically-mapped stimulus locations to simultaneously constrain the solutions allows for the estimation of independent waveforms for visual areas V1, V2, and V3, despite their close proximity to each other. We describe modifications that improve the reliability and efficiency of this method. First, we find that increasing the number and size of visual stimuli results in source estimates that are less susceptible to noise. Second, to create a more accurate forward solution, we have explicitly modeled the cortical point spread of individual visual stimuli. Dipoles are represented as extended patches on the cortical surface, which take into account the estimated receptive field size at each location in V1, V2, and V3 as well as the contributions from contralateral, ipsilateral, dorsal, and ventral portions of the visual areas. Third, we implemented a map fitting procedure to deform a template to match individual subject retinotopic maps derived from functional magnetic resonance imaging (fMRI). This improves the efficiency of the overall method by allowing automated dipole selection, and it makes the results less sensitive to physiological noise in fMRI retinotopy data. Finally, the iteratively reweighted least squares (IRLS) method was used to reduce the contribution from stimulus locations with high residual error for robust estimation of visual evoked responses. PMID:22102418
Wang, Sheng H; Lobier, Muriel; Siebenhühner, Felix; Puoliväli, Tuomas; Palva, Satu; Palva, J Matias
2018-06-01
It has not been well documented that MEG/EEG functional connectivity graphs estimated with zero-lag-free interaction metrics are severely confounded by a multitude of spurious interactions (SI), i.e., the false-positive "ghosts" of true interactions [1], [2]. These SI are caused by the multivariate linear mixing between sources, and thus they pose a severe challenge to the validity of connectivity analysis. Due to the complex nature of signal mixing and the SI problem, there is a need to intuitively demonstrate how the SI are discovered and how they can be attenuated using a novel approach that we termed hyperedge bundling. Here we provide a dataset with software with which the readers can perform simulations in order to better understand the theory and the solution to SI. We include the supplementary material of [1] that is not directly relevant to the hyperedge bundling per se but reflects important properties of the MEG source model and the functional connectivity graphs. For example, the gyri of dorsal-lateral cortices are the most accurately modeled areas; the sulci of inferior temporal, frontal and the insula have the least modeling accuracy. Importantly, we found the interaction estimates are heavily biased by the modeling accuracy between regions, which means the estimates cannot be straightforwardly interpreted as the coupling between brain regions. This raise a red flag that the conventional method of thresholding graphs by estimate values is rather suboptimal: because the measured topology of the graph reflects the geometric property of source-model instead of the cortical interactions under investigation.
De novo status epilepticus with isolated aphasia.
Flügel, Dominique; Kim, Olaf Chan-Hi; Felbecker, Ansgar; Tettenborn, Barbara
2015-08-01
Sudden onset of aphasia is usually due to stroke. Rapid diagnostic workup is necessary if reperfusion therapy is considered. Ictal aphasia is a rare condition but has to be excluded. Perfusion imaging may differentiate acute ischemia from other causes. In dubious cases, EEG is required but is time-consuming and laborious. We report a case where we considered de novo status epilepticus as a cause of aphasia without any lesion even at follow-up. A 62-year-old right-handed woman presented to the emergency department after nurses found her aphasic. She had undergone operative treatment of varicosis 3 days earlier. Apart from hypertension and obesity, no cardiovascular risk factors and no intake of medication other than paracetamol were reported. Neurological examination revealed global aphasia and right pronation in the upper extremity position test. Computed tomography with angiography and perfusion showed no abnormalities. Electroencephalogram performed after the CT scan showed left-sided slowing with high-voltage rhythmic 2/s delta waves but no clear ictal pattern. Intravenous lorazepam did improve EEG slightly, while aphasia did not change. Lumbar puncture was performed which likely excluded encephalitis. Magnetic resonance imaging showed cortical pathological diffusion imaging (restriction) and cortical hyperperfusion in the left parietal region. Intravenous anticonvulsant therapy under continuous EEG resolved neurological symptoms. The patient was kept on anticonvulsant therapy. Magnetic resonance imaging after 6 months showed no abnormalities along with no clinical abnormalities. Magnetic resonance imaging findings were only subtle, and EEG was without clear ictal pattern, so the diagnosis of aphasic status remains with some uncertainty. However, status epilepticus can mimic stroke symptoms and has to be considered in patients with aphasia even when no previous stroke or structural lesions are detectable and EEG shows no epileptic discharges. Epileptic origin is favored when CT or MR imaging reveal no hypoperfusion. In this case, MRI was superior to CT in detecting hyperperfusion. This article is part of a Special Issue entitled "Status Epilepticus". Copyright © 2015 Elsevier Inc. All rights reserved.
Stimulus-dependent spiking relationships with the EEG
Snyder, Adam C.
2015-01-01
The development and refinement of noninvasive techniques for imaging neural activity is of paramount importance for human neuroscience. Currently, the most accessible and popular technique is electroencephalography (EEG). However, nearly all of what we know about the neural events that underlie EEG signals is based on inference, because of the dearth of studies that have simultaneously paired EEG recordings with direct recordings of single neurons. From the perspective of electrophysiologists there is growing interest in understanding how spiking activity coordinates with large-scale cortical networks. Evidence from recordings at both scales highlights that sensory neurons operate in very distinct states during spontaneous and visually evoked activity, which appear to form extremes in a continuum of coordination in neural networks. We hypothesized that individual neurons have idiosyncratic relationships to large-scale network activity indexed by EEG signals, owing to the neurons' distinct computational roles within the local circuitry. We tested this by recording neuronal populations in visual area V4 of rhesus macaques while we simultaneously recorded EEG. We found substantial heterogeneity in the timing and strength of spike-EEG relationships and that these relationships became more diverse during visual stimulation compared with the spontaneous state. The visual stimulus apparently shifts V4 neurons from a state in which they are relatively uniformly embedded in large-scale network activity to a state in which their distinct roles within the local population are more prominent, suggesting that the specific way in which individual neurons relate to EEG signals may hold clues regarding their computational roles. PMID:26108954
Epileptogenic developmental venous anomaly: insights from simultaneous EEG/fMRI.
Scheidegger, Olivier; Wiest, Roland; Jann, Kay; König, Thomas; Meyer, Klaus; Hauf, Martinus
2013-04-01
Developmental venous anomalies (DVAs) are associated with epileptic seizures; however, the role of DVA in the epileptogenesis is still not established. Simultaneous interictal electroencephalogram/functional magnetic resonance imaging (EEG/fMRI) recordings provide supplementary information to electroclinical data about the epileptic generators, and thus aid in the differentiation of clinically equivocal epilepsy syndromes. The main objective of our study was to characterize the epileptic network in a patient with DVA and epilepsy by simultaneous EEG/fMRI recordings. A 17-year-old woman with recently emerging generalized tonic-clonic seizures, and atypical generalized discharges, was investigated using simultaneous EEG/fMRI at the university hospital. Previous high-resolution MRI showed no structural abnormalities, except a DVA in the right frontal operculum. Interictal EEG recordings showed atypical generalized discharges, corresponding to positive focal blood oxygen level dependent (BOLD) correlates in the right frontal operculum, a region drained by the DVA. Additionally, widespread cortical bilateral negative BOLD correlates in the frontal and parietal lobes were delineated, resembling a generalized epileptic network. The EEG/fMRI recordings support a right frontal lobe epilepsy, originating in the vicinity of the DVA, propagating rapidly to both frontal and parietal lobes, as expressed on the scalp EEG by secondary bilateral synchrony. The DVA may be causative of focal epilepsies in cases where no concomitant epileptogenic lesions can be detected. Advanced imaging techniques, such as simultaneous EEG/fMRI, may thus aid in the differentiation of clinically equivocal epilepsy syndromes.
Envelope responses in single-trial EEG indicate attended speaker in a 'cocktail party'.
Horton, Cort; Srinivasan, Ramesh; D'Zmura, Michael
2014-08-01
Recent studies have shown that auditory cortex better encodes the envelope of attended speech than that of unattended speech during multi-speaker ('cocktail party') situations. We investigated whether these differences were sufficiently robust within single-trial electroencephalographic (EEG) data to accurately determine where subjects attended. Additionally, we compared this measure to other established EEG markers of attention. High-resolution EEG was recorded while subjects engaged in a two-speaker 'cocktail party' task. Cortical responses to speech envelopes were extracted by cross-correlating the envelopes with each EEG channel. We also measured steady-state responses (elicited via high-frequency amplitude modulation of the speech) and alpha-band power, both of which have been sensitive to attention in previous studies. Using linear classifiers, we then examined how well each of these features could be used to predict the subjects' side of attention at various epoch lengths. We found that the attended speaker could be determined reliably from the envelope responses calculated from short periods of EEG, with accuracy improving as a function of sample length. Furthermore, envelope responses were far better indicators of attention than changes in either alpha power or steady-state responses. These results suggest that envelope-related signals recorded in EEG data can be used to form robust auditory BCI's that do not require artificial manipulation (e.g., amplitude modulation) of stimuli to function.
Mideksa, Kidist Gebremariam; Anwar, Abdul Rauf; Stephani, Ulrich; Deuschl, Günther; Freitag, Christine M.; Siniatchkin, Michael
2015-01-01
At the sensor level many aspects, such as spectral power, functional and effective connectivity as well as relative-power-ratio ratio (RPR) and spatial resolution have been comprehensively investigated through both electroencephalography (EEG) and magnetoencephalography (MEG). Despite this, differences between both modalities have not yet been systematically studied by direct comparison. It remains an open question as to whether the integration of EEG and MEG data would improve the information obtained from the above mentioned parameters. Here, EEG (64-channel system) and MEG (275 sensor system) were recorded simultaneously in conditions with eyes open (EO) and eyes closed (EC) in 29 healthy adults. Spectral power, functional and effective connectivity, RPR, and spatial resolution were analyzed at five different frequency bands (delta, theta, alpha, beta and gamma). Networks of functional and effective connectivity were described using a spatial filter approach called the dynamic imaging of coherent sources (DICS) followed by the renormalized partial directed coherence (RPDC). Absolute mean power at the sensor level was significantly higher in EEG than in MEG data in both EO and EC conditions. At the source level, there was a trend towards a better performance of the combined EEG+MEG analysis compared with separate EEG or MEG analyses for the source mean power, functional correlation, effective connectivity for both EO and EC. The network of coherent sources and the spatial resolution were similar for both the EEG and MEG data if they were analyzed separately. Results indicate that the combined approach has several advantages over the separate analyses of both EEG and MEG. Moreover, by a direct comparison of EEG and MEG, EEG was characterized by significantly higher values in all measured parameters in both sensor and source level. All the above conclusions are specific to the resting state task and the specific analysis used in this study to have general conclusion multi-center studies would be helpful. PMID:26509448
EEG source analysis of data from paralysed subjects
NASA Astrophysics Data System (ADS)
Carabali, Carmen A.; Willoughby, John O.; Fitzgibbon, Sean P.; Grummett, Tyler; Lewis, Trent; DeLosAngeles, Dylan; Pope, Kenneth J.
2015-12-01
One of the limitations of Encephalography (EEG) data is its quality, as it is usually contaminated with electric signal from muscle. This research intends to study results of two EEG source analysis methods applied to scalp recordings taken in paralysis and in normal conditions during the performance of a cognitive task. The aim is to determinate which types of analysis are appropriate for dealing with EEG data containing myogenic components. The data used are the scalp recordings of six subjects in normal conditions and during paralysis while performing different cognitive tasks including the oddball task which is the object of this research. The data were pre-processed by filtering it and correcting artefact, then, epochs of one second long for targets and distractors were extracted. Distributed source analysis was performed in BESA Research 6.0, using its results and information from the literature, 9 ideal locations for source dipoles were identified. The nine dipoles were used to perform discrete source analysis, fitting them to the averaged epochs for obtaining source waveforms. The results were statistically analysed comparing the outcomes before and after the subjects were paralysed. Finally, frequency analysis was performed for better explain the results. The findings were that distributed source analysis could produce confounded results for EEG contaminated with myogenic signals, conversely, statistical analysis of the results from discrete source analysis showed that this method could help for dealing with EEG data contaminated with muscle electrical signal.
Aarabi, A; Grebe, R; Berquin, P; Bourel Ponchel, E; Jalin, C; Fohlen, M; Bulteau, C; Delalande, O; Gondry, C; Héberlé, C; Moullart, V; Wallois, F
2012-06-01
This case study aims to demonstrate that spatiotemporal spike discrimination and source analysis are effective to monitor the development of sources of epileptic activity in time and space. Therefore, they can provide clinically useful information allowing a better understanding of the pathophysiology of individual seizures with time- and space-resolved characteristics of successive epileptic states, including interictal, preictal, postictal, and ictal states. High spatial resolution scalp EEGs (HR-EEG) were acquired from a 2-year-old girl with refractory central epilepsy and single-focus seizures as confirmed by intracerebral EEG recordings and ictal single-photon emission computed tomography (SPECT). Evaluation of HR-EEG consists of the following three global steps: (1) creation of the initial head model, (2) automatic spike and seizure detection, and finally (3) source localization. During the source localization phase, epileptic states are determined to allow state-based spike detection and localization of underlying sources for each spike. In a final cluster analysis, localization results are integrated to determine the possible sources of epileptic activity. The results were compared with the cerebral locations identified by intracerebral EEG recordings and SPECT. The results obtained with this approach were concordant with those of MRI, SPECT and distribution of intracerebral potentials. Dipole cluster centres found for spikes in interictal, preictal, ictal and postictal states were situated an average of 6.3mm from the intracerebral contacts with the highest voltage. Both amplitude and shape of spikes change between states. Dispersion of the dipoles was higher in the preictal state than in the postictal state. Two clusters of spikes were identified. The centres of these clusters changed position periodically during the various epileptic states. High-resolution surface EEG evaluated by an advanced algorithmic approach can be used to investigate the spatiotemporal characteristics of sources located in the epileptic focus. The results were validated by standard methods, ensuring good spatial resolution by MRI and SPECT and optimal temporal resolution by intracerebral EEG. Surface EEG can be used to identify different spike clusters and sources of the successive epileptic states. The method that was used in this study will provide physicians with a better understanding of the pathophysiological characteristics of epileptic activities. In particular, this method may be useful for more effective positioning of implantable intracerebral electrodes. Copyright © 2011 Elsevier Masson SAS. All rights reserved.
Brain Oscillations in Sport: Toward EEG Biomarkers of Performance.
Cheron, Guy; Petit, Géraldine; Cheron, Julian; Leroy, Axelle; Cebolla, Anita; Cevallos, Carlos; Petieau, Mathieu; Hoellinger, Thomas; Zarka, David; Clarinval, Anne-Marie; Dan, Bernard
2016-01-01
Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators.