A resting-state fMRI study of obese females between pre- and postprandial states before and after bariatric surgery.

PubMed

Wiemerslage, Lyle; Zhou, Wei; Olivo, Gaia; Stark, Julia; Hogenkamp, Pleunie S; Larsson, Elna-Marie; Sundbom, Magnus; Schiöth, Helgi B

2017-02-01

Past studies utilizing resting-state functional MRI (rsfMRI), have shown that obese humans exhibit altered activity in brain areas related to reward compared to normal-weight controls. However, to what extent bariatric surgery-induced weight loss alters resting-state brain activity in obese humans is less well-studied. Thus, we measured the fractional amplitude of low-frequency fluctuations from eyes-closed, rsfMRI in obese females (n = 11, mean age = 42 years, mean BMI = 41 kg/m 2 ) in both a pre- and postprandial state at two time points: four weeks before, and four weeks after bariatric surgery. Several brain areas showed altered resting-state activity following bariatric surgery, including the putamen, insula, cingulate, thalamus and frontal regions. Activity augmented by surgery was also dependent on prandial state. For example, in the fasted state, activity in the middle frontal and pre- and postcentral gyri was found to be decreased after surgery. In the sated state, activity within the insula was increased before, but not after surgery. Collectively, our results suggest that resting-state neural functions are rapidly affected following bariatric surgery and the associated weight loss and change in diet. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Investigating the Temporal Patterns within and between Intrinsic Connectivity Networks under Eyes-Open and Eyes-Closed Resting States: A Dynamical Functional Connectivity Study Based on Phase Synchronization

PubMed Central

Wang, Xun-Heng; Li, Lihua; Xu, Tao; Ding, Zhongxiang

2015-01-01

The brain active patterns were organized differently under resting states of eyes open (EO) and eyes closed (EC). The altered voxel-wise and regional-wise resting state active patterns under EO/EC were found by static analysis. More importantly, dynamical spontaneous functional connectivity has been observed in the resting brain. To the best of our knowledge, the dynamical mechanisms of intrinsic connectivity networks (ICNs) under EO/EC remain largely unexplored. The goals of this paper were twofold: 1) investigating the dynamical intra-ICN and inter-ICN temporal patterns during resting state; 2) analyzing the altered dynamical temporal patterns of ICNs under EO/EC. To this end, a cohort of healthy subjects with scan conditions of EO/EC were recruited from 1000 Functional Connectomes Project. Through Hilbert transform, time-varying phase synchronization (PS) was applied to evaluate the inter-ICN synchrony. Meanwhile, time-varying amplitude was analyzed as dynamical intra-ICN temporal patterns. The results found six micro-states of inter-ICN synchrony. The medial visual network (MVN) showed decreased intra-ICN amplitude during EC relative to EO. The sensory-motor network (SMN) and auditory network (AN) exhibited enhanced intra-ICN amplitude during EC relative to EO. Altered inter-ICN PS was found between certain ICNs. Particularly, the SMN and AN exhibited enhanced PS to other ICNs during EC relative to EO. In addition, the intra-ICN amplitude might influence the inter-ICN synchrony. Moreover, default mode network (DMN) might play an important role in information processing during EO/EC. Together, the dynamical temporal patterns within and between ICNs were altered during different scan conditions of EO/EC. Overall, the dynamical intra-ICN and inter-ICN temporal patterns could benefit resting state fMRI-related research, and could be potential biomarkers for human functional connectome. PMID:26469182

Moderating effects of music on resting state networks.

PubMed

Kay, Benjamin P; Meng, Xiangxiang; Difrancesco, Mark W; Holland, Scott K; Szaflarski, Jerzy P

2012-04-04

Resting state networks (RSNs) are spontaneous, synchronous, low-frequency oscillations observed in the brains of subjects who are awake but at rest. A particular RSN called the default mode network (DMN) has been shown to exhibit changes associated with neurological disorders such as temporal lobe epilepsy or Alzheimer's disease. Previous studies have also found that differing experimental conditions such as eyes-open versus eyes-closed can produce measurable changes in the DMN. These condition-associated changes have the potential of confounding the measurements of changes in RSNs related to or caused by disease state(s). In this study, we use fMRI measurements of resting-state connectivity paired with EEG measurements of alpha rhythm and employ independent component analysis, undirected graphs of partial spectral coherence, and spatiotemporal regression to investigate the effect of music-listening on RSNs and the DMN in particular. We observed similar patterns of DMN connectivity in subjects who were listening to music compared with those who were not, with a trend toward a more introspective pattern of resting-state connectivity during music-listening. We conclude that music-listening is a valid condition under which the DMN can be studied. Copyright © 2012 Elsevier B.V. All rights reserved.

Resting-state beta and gamma activity in Internet addiction.

PubMed

Choi, Jung-Seok; Park, Su Mi; Lee, Jaewon; Hwang, Jae Yeon; Jung, Hee Yeon; Choi, Sam-Wook; Kim, Dai Jin; Oh, Sohee; Lee, Jun-Young

2013-09-01

Internet addiction is the inability to control one's use of the Internet and is related to impulsivity. Although a few studies have examined neurophysiological activity as individuals with Internet addiction engage in cognitive processing, no information on spontaneous EEG activity in the eyes-closed resting-state is available. We investigated resting-state EEG activities in beta and gamma bands and examined their relationships with impulsivity among individuals with Internet addiction and healthy controls. Twenty-one drug-naïve patients with Internet addiction (age: 23.33 ± 3.50 years) and 20 age-, sex-, and IQ-matched healthy controls (age: 22.40 ± 2.33 years) were enrolled in this study. Severity of Internet addiction was identified by the total score on Young's Internet Addiction Test. Impulsivity was measured with the Barratt Impulsiveness Scale-11 and a stop-signal task. Resting-state EEG during eyes closed was recorded, and the absolute/relative power of beta and gamma bands was analyzed. The Internet addiction group showed high impulsivity and impaired inhibitory control. The generalized estimating equation showed that the Internet-addiction group showed lower absolute power on the beta band than did the control group (estimate = -3.370, p < 0.01). On the other hand, the Internet-addiction group showed higher absolute power on the gamma band than did the control group (estimate = 0.434, p < 0.01). These EEG activities were significantly associated with the severity of Internet addiction as well as with the extent of impulsivity. The present study suggests that resting-state fast-wave brain activity is related to the impulsivity characterizing Internet addiction. These differences may be neurobiological markers for the pathophysiology of Internet addiction. Copyright © 2013 Elsevier B.V. All rights reserved.

Reactivity of hemodynamic responses and functional connectivity to different states of alpha synchrony: a concurrent EEG-fMRI study.

PubMed

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.

Association between heart rate variability and fluctuations in resting-state functional connectivity

PubMed Central

Chang, Catie; Metzger, Coraline D.; Glover, Gary H.; Duyn, Jeff H.; Heinze, Hans-Jochen; Walter, Martin

2012-01-01

Functional connectivity has been observed to fluctuate across the course of a resting state scan, though the origins and functional relevance of this phenomenon remain to be shown. The present study explores the link between endogenous dynamics of functional connectivity and autonomic state in an eyes-closed resting condition. Using a sliding window analysis on resting state fMRI data from 35 young, healthy male subjects, we examined how heart rate variability (HRV) covaries with temporal changes in whole-brain functional connectivity with seed regions previously described to mediate effects of vigilance and arousal (amygdala and dorsal anterior cingulate cortex; dACC). We identified a set of regions, including brainstem, thalamus, putamen, and dorsolateral prefrontal cortex, that became more strongly coupled with the dACC and amygdala seeds during states of elevated HRV. Effects differed between high and low frequency components of HRV, suggesting specific contributions of parasympathetic and sympathetic tone on individual connections. Furthermore, dynamics of functional connectivity could be separated from those primarily related to BOLD signal fluctuations. The present results contribute novel information about the neural basis of transient changes of autonomic nervous system states, and suggest physiological and psychological components of the recently observed non-stationarity in resting state functional connectivity. PMID:23246859

Structure and dynamics of AMPA receptor GluA2 in resting, pre-open and desensitized states

PubMed Central

Dürr, Katharina L.; Chen, Lei; Stein, Richard A.; De Zorzi, Rita; MihaelaFolea, I.; Walz, Thomas; Mchaourab, Hassane S.; Gouaux, Eric

2014-01-01

Summary Ionotropic glutamate receptors (iGluRs) mediate the majority of fast excitatory signaling in the nervous system. Despite the profound importance of iGluRs in the nervous system, little is known about the structures and dynamics of intact receptors in distinct functional states. Here we elucidate the structures of the intact GluA2 AMPA receptor in an apo resting/closed state, in an activated/pre-open state bound with the partial agonists and a positive allosteric modulator and in a desensitized/closed state in complex with FW alone. To probe the conformational properties of these states, we carried out double electron-electron resonance experiments on cysteine mutants and cryo-electron microscopy studies. We show how agonist binding modulates the conformation of the ligand binding domain 'layer' of the intact receptors and how, upon desensitization, the receptor undergoes large conformational rearrangements of amino-terminal and ligand-binding domains. We define mechanistic principles by which to understand antagonism, activation and desensitization in AMPA iGluRs. PMID:25109876

Effects of resting state condition on reliability, trait specificity, and network connectivity of brain function measured with arterial spin labeled perfusion MRI.

PubMed

Li, Zhengjun; Vidorreta, Marta; Katchmar, Natalie; Alsop, David C; Wolf, Daniel H; Detre, John A

2018-06-01

Resting state fMRI (rs-fMRI) provides imaging biomarkers of task-independent brain function that can be associated with clinical variables or modulated by interventions such as behavioral training or pharmacological manipulations. These biomarkers include time-averaged regional brain function as manifested by regional cerebral blood flow (CBF) measured using arterial spin labeled (ASL) perfusion MRI and correlated temporal fluctuations of function across brain networks with either ASL or blood oxygenation level dependent (BOLD) fMRI. Resting-state studies are typically carried out using just one of several prescribed state conditions such as eyes closed (EC), eyes open (EO), or visual fixation on a cross-hair (FIX), which may affect the reliability and specificity of rs-fMRI. In this study, we collected test-retest ASL MRI data during 4 resting-state task conditions: EC, EO, FIX and PVT (low-frequency psychomotor vigilance task), and examined the effects of these task conditions on reliability and reproducibility as well as trait specificity of regional brain function. We also acquired resting-state BOLD fMRI under FIX and compared the network connectivity reliabilities between the four ASL conditions and the BOLD FIX condition. For resting-state ASL data, EC provided the highest CBF reliability, reproducibility, trait specificity, and network connectivity reliability, followed by EO, while FIX was lowest on all of these measures. PVT demonstrated lower CBF reliability, reproducibility and trait specificity than EO and EC. Overall network connectivity reliability was comparable between ASL and BOLD. Our findings confirm ASL CBF as a reliable, stable, and consistent measure of resting-state regional brain function and support the use of EC or EO over FIX and PVT as the resting-state condition. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Disrupted directed connectivity along the cingulate cortex determines vigilance after sleep deprivation

PubMed Central

Piantoni, Giovanni; Cheung, Bing Leung P.; Van Veen, Barry D.; Romeijn, Nico; Riedner, Brady A.; Tononi, Giulio; Van Der Werf, Ysbrand D.; Van Someren, Eus J.W.

2013-01-01

The cingulate cortex is regarded as the backbone of structural and functional connectivity of the brain. While its functional connectivity has been intensively studied, little is known about its effective connectivity, its modulation by behavioral states, and its involvement in cognitive performance. Given their previously reported effects on cingulate functional connectivity, we investigated how eye-closure and sleep deprivation changed cingulate effective connectivity, estimated from resting-state high-density electroencephalography (EEG) using a novel method to calculate Granger Causality directly in source space. Effective connectivity along the cingulate cortex was dominant in the forward direction. Eyes-open connectivity in the forward direction was greater compared to eyes-closed, in well-rested participants. The difference between eyes-open and eyes-closed connectivity was attenuated and no longer significant after sleep deprivation. Individual variability in the forward connectivity after sleep deprivation predicted subsequent task performance, such that those subjects who showed a greater increase in forward connectivity between the eyes-open and the eyes-closed periods also performed better on a sustained attention task. Effective connectivity in the opposite, backward, direction was not affected by whether the eyes were open or closed or by sleep deprivation. These findings indicate that the effective connectivity from posterior to anterior cingulate regions is enhanced when a well-rested subject has his eyes open compared to when they are closed. Sleep deprivation impairs this directed information flow, proportional to its deleterious effect on vigilance. Therefore, sleep may play a role in the maintenance of waking effective connectivity. PMID:23643925

Endogenous modulation of human visual cortex activity improves perception at twilight.

PubMed

Cordani, Lorenzo; Tagliazucchi, Enzo; Vetter, Céline; Hassemer, Christian; Roenneberg, Till; Stehle, Jörg H; Kell, Christian A

2018-04-10

Perception, particularly in the visual domain, is drastically influenced by rhythmic changes in ambient lighting conditions. Anticipation of daylight changes by the circadian system is critical for survival. However, the neural bases of time-of-day-dependent modulation in human perception are not yet understood. We used fMRI to study brain dynamics during resting-state and close-to-threshold visual perception repeatedly at six times of the day. Here we report that resting-state signal variance drops endogenously at times coinciding with dawn and dusk, notably in sensory cortices only. In parallel, perception-related signal variance in visual cortices decreases and correlates negatively with detection performance, identifying an anticipatory mechanism that compensates for the deteriorated visual signal quality at dawn and dusk. Generally, our findings imply that decreases in spontaneous neural activity improve close-to-threshold perception.

Resting-State Functional Connectivity Emerges from Structurally and Dynamically Shaped Slow Linear Fluctuations

PubMed Central

Deco, Gustavo; Mantini, Dante; Romani, Gian Luca; Hagmann, Patric; Corbetta, Maurizio

2013-01-01

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure–function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure–function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications. PMID:23825427

Resting-state functional connectivity emerges from structurally and dynamically shaped slow linear fluctuations.

PubMed

Deco, Gustavo; Ponce-Alvarez, Adrián; Mantini, Dante; Romani, Gian Luca; Hagmann, Patric; Corbetta, Maurizio

2013-07-03

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure-function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure-function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications.

Changes in resting-state fMRI in vestibular neuritis.

PubMed

Helmchen, Christoph; Ye, Zheng; Sprenger, Andreas; Münte, Thomas F

2014-11-01

Vestibular neuritis (VN) is a sudden peripheral unilateral vestibular failure with often persistent head movement-related dizziness and unsteadiness. Compensation of asymmetrical activity in the primary peripheral vestibular afferents is accomplished by restoration of impaired brainstem vestibulo-ocular and vestibulo-spinal reflexes, but presumably also by changing cortical vestibular tone imbalance subserving, e.g., spatial perception and orientation. The aim of this study was to elucidate (i) whether there are changes of cerebral resting-state networks with respect to functional interregional connectivity (resting-state activity) in VN patients and (ii) whether these are related to neurophysiological, perceptual and functional parameters of vestibular-induced disability. Using independent component analysis (ICA), we compared resting-state networks between 20 patients with unilateral VN and 20 age- and gender-matched healthy control subjects. Patients were examined in the acute VN stage and after 3 months. A neural network (component 50) comprising the parietal lobe, medial aspect of the superior parietal lobule, posterior cingulate cortex, middle frontal gyrus, middle temporal gyrus, parahippocampal gyrus, anterior cingulate cortex, insular cortex, caudate nucleus, thalamus and midbrain was modulated between acute VN patients and healthy controls and in patients over time. Within this network, acute VN patients showed decreased resting-state activity (ICA) in the contralateral intraparietal sulcus (IPS), in close vicinity to the supramarginal gyrus (SMG), which increased after 3 months. Resting-state activity in IPS tended to increase over 3 months in VN patients who improved with respect to functional parameters of vestibular-induced disability (VADL). Resting-state activity in the IPS was not related to perceptual (subjective visual vertical) or neurophysiological parameters of vestibular-induced disability (e.g., gain of vestibulo-ocular reflex, caloric responsiveness, postural sway). VN leads to a change in resting-state activity of the contralateral IPS adjacent to the SMG, which reverses during vestibular compensation over 3 months. The ventral intraparietal area in the IPS contains multimodal regions with directionally selective responses to vestibular stimuli making them suitable for participating in spatial orientation and multisensory integration. The clinical importance is indicated by the fact that the increase in resting-state activity tended to be larger in those patients with only little disability at the follow-up examination. This may indicate powerful restitution-related or compensatory cortical changes in resting-state activity.

Resting State EEG-based biometrics for individual identification using convolutional neural networks.

PubMed

Lan Ma; Minett, James W; Blu, Thierry; Wang, William S-Y

2015-08-01

Biometrics is a growing field, which permits identification of individuals by means of unique physical features. Electroencephalography (EEG)-based biometrics utilizes the small intra-personal differences and large inter-personal differences between individuals' brainwave patterns. In the past, such methods have used features derived from manually-designed procedures for this purpose. Another possibility is to use convolutional neural networks (CNN) to automatically extract an individual's best and most unique neural features and conduct classification, using EEG data derived from both Resting State with Open Eyes (REO) and Resting State with Closed Eyes (REC). Results indicate that this CNN-based joint-optimized EEG-based Biometric System yields a high degree of accuracy of identification (88%) for 10-class classification. Furthermore, rich inter-personal difference can be found using a very low frequency band (0-2Hz). Additionally, results suggest that the temporal portions over which subjects can be individualized is less than 200 ms.

Resting-state qEEG predicts rate of second language learning in adults.

PubMed

Prat, Chantel S; Yamasaki, Brianna L; Kluender, Reina A; Stocco, Andrea

2016-01-01

Understanding the neurobiological basis of individual differences in second language acquisition (SLA) is important for research on bilingualism, learning, and neural plasticity. The current study used quantitative electroencephalography (qEEG) to predict SLA in college-aged individuals. Baseline, eyes-closed resting-state qEEG was used to predict language learning rate during eight weeks of French exposure using an immersive, virtual scenario software. Individual qEEG indices predicted up to 60% of the variability in SLA, whereas behavioral indices of fluid intelligence, executive functioning, and working-memory capacity were not correlated with learning rate. Specifically, power in beta and low-gamma frequency ranges over right temporoparietal regions were strongly positively correlated with SLA. These results highlight the utility of resting-state EEG for studying the neurobiological basis of SLA in a relatively construct-free, paradigm-independent manner. Published by Elsevier Inc.

Independent component analysis of EEG dipole source localization in resting and action state of brain

NASA Astrophysics Data System (ADS)

Almurshedi, Ahmed; Ismail, Abd Khamim

2015-04-01

EEG source localization was studied in order to determine the location of the brain sources that are responsible for the measured potentials at the scalp electrodes using EEGLAB with Independent Component Analysis (ICA) algorithm. Neuron source locations are responsible in generating current dipoles in different states of brain through the measured potentials. The current dipole sources localization are measured by fitting an equivalent current dipole model using a non-linear optimization technique with the implementation of standardized boundary element head model. To fit dipole models to ICA components in an EEGLAB dataset, ICA decomposition is performed and appropriate components to be fitted are selected. The topographical scalp distributions of delta, theta, alpha, and beta power spectrum and cross coherence of EEG signals are observed. In close eyes condition it shows that during resting and action states of brain, alpha band was activated from occipital (O1, O2) and partial (P3, P4) area. Therefore, parieto-occipital area of brain are active in both resting and action state of brain. However cross coherence tells that there is more coherence between right and left hemisphere in action state of brain than that in the resting state. The preliminary result indicates that these potentials arise from the same generators in the brain.

Resting-state EEG delta power is associated with psychological pain in adults with a history of depression.

PubMed

Meerwijk, Esther L; Ford, Judith M; Weiss, Sandra J

2015-02-01

Psychological pain is a prominent symptom of clinical depression. We asked if frontal alpha asymmetry, frontal EEG power, and frontal fractal dimension asymmetry predicted psychological pain in adults with a history of depression. Resting-state frontal EEG (F3/F4) was recorded while participants (N=35) sat upright with their eyes closed. Frontal delta power predicted psychological pain while controlling for depressive symptoms, with participants who exhibited less power experiencing greater psychological pain. Frontal fractal dimension asymmetry, a nonlinear measure of complexity, also predicted psychological pain, such that greater left than right complexity was associated with greater psychological pain. Frontal alpha asymmetry did not contribute unique variance to any regression model of psychological pain. As resting-state delta power is associated with the brain's default mode network, results suggest that the default mode network was less activated during high psychological pain. Findings are consistent with a state of arousal associated with psychological pain. Copyright © 2015 Elsevier B.V. All rights reserved.

Altered cerebral blood flow velocity features in fibromyalgia patients in resting-state conditions

PubMed Central

Rodríguez, Alejandro; Tembl, José; Mesa-Gresa, Patricia; Muñoz, Miguel Ángel; Montoya, Pedro

2017-01-01

The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envelope CBFV and a different distribution of the power spectral density. In addition, it has been observed that complexity and spectral features show correlations with clinical pain parameters and emotional factors. The characterization features were used in a lineal model to discriminate between fibromyalgia patients and healthy controls, providing a high accuracy. These findings indicate that CBFV signals, specifically their complexity and spectral characteristics, contain information that may be relevant for the assessment of fibromyalgia patients in resting-state conditions. PMID:28700720

Altered cerebral blood flow velocity features in fibromyalgia patients in resting-state conditions.

PubMed

Rodríguez, Alejandro; Tembl, José; Mesa-Gresa, Patricia; Muñoz, Miguel Ángel; Montoya, Pedro; Rey, Beatriz

2017-01-01

The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envelope CBFV and a different distribution of the power spectral density. In addition, it has been observed that complexity and spectral features show correlations with clinical pain parameters and emotional factors. The characterization features were used in a lineal model to discriminate between fibromyalgia patients and healthy controls, providing a high accuracy. These findings indicate that CBFV signals, specifically their complexity and spectral characteristics, contain information that may be relevant for the assessment of fibromyalgia patients in resting-state conditions.

Gravitationally confined relativistic neutrinos

NASA Astrophysics Data System (ADS)

Vayenas, C. G.; Fokas, A. S.; Grigoriou, D.

2017-09-01

Combining special relativity, the equivalence principle, and Newton’s universal gravitational law with gravitational rather than rest masses, one finds that gravitational interactions between relativistic neutrinos with kinetic energies above 50 MeV are very strong and can lead to the formation of gravitationally confined composite structures with the mass and other properties of hadrons. One may model such structures by considering three neutrinos moving symmetrically on a circular orbit under the influence of their gravitational attraction, and by assuming quantization of their angular momentum, as in the Bohr model of the H atom. The model contains no adjustable parameters and its solution, using a neutrino rest mass of 0.05 eV/c2, leads to composite state radii close to 1 fm and composite state masses close to 1 GeV/c2. Similar models of relativistic rotating electron - neutrino pairs give a mass of 81 GeV/c2, close to that of W bosons. This novel mechanism of generating mass suggests that the Higgs mass generation mechanism can be modeled as a latent gravitational field which gets activated by relativistic neutrinos.

Spontaneous fluctuation of the resting membrane potential in Paramecium: amplification caused by intracellular Ca2+.

PubMed

Nakaoka, Yasuo; Imaji, Takafumi; Hara, Masahiro; Hashimoto, Noboru

2009-01-01

The ciliated protozoan Paramecium spontaneously changes its swimming direction in the absence of external stimuli. Such behavior is based on resting potential fluctuations, the amplitudes of which reach a few mV. When the resting potential fluctuation is positive and large, a spike-like depolarization is frequently elicited that reverses the beating of the cilia associated with directional changes during swimming. We aimed to study how the resting potential fluctuation is amplified. Simultaneous measurements of the resting potential and intracellular Ca(2+) ([Ca(2+)](i)) from a deciliated cell showed that positive potential fluctuations were frequently accompanied by a small increase in [Ca(2+)](i). This result suggests that Ca(2+) influx through the somatic membrane occurs during the resting state. The mean amplitude of the resting potential fluctuation was largely decreased by either an intracellular injection of a calcium chelater (BAPTA) or by an extracellular addition of Ba(2+). Hence, a small increase in [Ca(2+)](i) amplifies the resting potential fluctuation. Simulation analysis of the potential fluctuation was made by assuming that Ca(2+) and K(+) channels of surface membrane are fluctuating between open and closed states. The simulated fluctuation increased to exhibit almost the same amplitude as the measured fluctuation using the assumption that a small Ca(2+) influx activates Ca(2+) channels in a positive feedback manner.

Close-Out Report for FY2002 - FY2005, DARPA Agreement

DTIC Science & Technology

2010-06-29

controls, programming and software design . Specialized technologies and state-of-the-art and -market equipment available to private industry on a shared...Rest and Following Rest Designed to satisfy machinists’ needs, the Easy Turn represents high quality and value with trouble free use. This model is...fitted with a 3 % inch hole through spindle and a 12 inch chuck. It can handle parts up to 44 inches in length. • Cincinnati U5 6-axis CNC Machining

Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness

PubMed Central

Snyder, Abraham Z.; Tagliazucchi, Enzo; Laufs, Helmut; Elison, Jed; Emerson, Robert W.; Shen, Mark D.; Wolff, Jason J.; Botteron, Kelly N.; Dager, Stephen; Estes, Annette M.; Evans, Alan; Gerig, Guido; Hazlett, Heather C.; Paterson, Sarah J.; Schultz, Robert T.; Styner, Martin A.; Zwaigenbaum, Lonnie; Schlaggar, Bradley L.

2017-01-01

Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI. PMID:29149191

Resting-state fMRI in sleeping infants more closely resembles adult sleep than adult wakefulness.

PubMed

Mitra, Anish; Snyder, Abraham Z; Tagliazucchi, Enzo; Laufs, Helmut; Elison, Jed; Emerson, Robert W; Shen, Mark D; Wolff, Jason J; Botteron, Kelly N; Dager, Stephen; Estes, Annette M; Evans, Alan; Gerig, Guido; Hazlett, Heather C; Paterson, Sarah J; Schultz, Robert T; Styner, Martin A; Zwaigenbaum, Lonnie; Schlaggar, Bradley L; Piven, Joseph; Pruett, John R; Raichle, Marcus

2017-01-01

Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI.

From "rest" to language task: Task activation selects and prunes from broader resting-state network.

PubMed

Doucet, Gaelle E; He, Xiaosong; Sperling, Michael R; Sharan, Ashwini; Tracy, Joseph I

2017-05-01

Resting-state networks (RSNs) show spatial patterns generally consistent with networks revealed during cognitive tasks. However, the exact degree of overlap between these networks has not been clearly quantified. Such an investigation shows promise for decoding altered functional connectivity (FC) related to abnormal language functioning in clinical populations such as temporal lobe epilepsy (TLE). In this context, we investigated the network configurations during a language task and during resting state using FC. Twenty-four healthy controls, 24 right and 24 left TLE patients completed a verb generation (VG) task and a resting-state fMRI scan. We compared the language network revealed by the VG task with three FC-based networks (seeding the left inferior frontal cortex (IFC)/Broca): two from the task (ON, OFF blocks) and one from the resting state. We found that, for both left TLE patients and controls, the RSN recruited regions bilaterally, whereas both VG-on and VG-off conditions produced more left-lateralized FC networks, matching more closely with the activated language network. TLE brings with it variability in both task-dependent and task-independent networks, reflective of atypical language organization. Overall, our findings suggest that our RSN captured bilateral activity, reflecting a set of prepotent language regions. We propose that this relationship can be best understood by the notion of pruning or winnowing down of the larger language-ready RSN to carry out specific task demands. Our data suggest that multiple types of network analyses may be needed to decode the association between language deficits and the underlying functional mechanisms altered by disease. Hum Brain Mapp 38:2540-2552, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Differential resting-state EEG patterns associated with comorbid depression in Internet addiction.

PubMed

Lee, Jaewon; Hwang, Jae Yeon; Park, Su Mi; Jung, Hee Yeon; Choi, Sam-Wook; Kim, Dai Jin; Lee, Jun-Young; Choi, Jung-Seok

2014-04-03

Many researchers have reported a relationship between Internet addiction and depression. In the present study, we compared the resting-state quantitative electroencephalography (QEEG) activity of treatment-seeking patients with comorbid Internet addiction and depression with those of treatment-seeking patients with Internet addiction without depression, and healthy controls to investigate the neurobiological markers that differentiate pure Internet addiction from Internet addiction with comorbid depression. Thirty-five patients diagnosed with Internet addiction and 34 age-, sex-, and IQ-matched healthy controls were enrolled in this study. Patients with Internet addiction were divided into two groups according to the presence (N=18) or absence (N=17) of depression. Resting-state, eye-closed QEEG was recorded, and the absolute and relative power of the brain were analyzed. The Internet addiction group without depression had decreased absolute delta and beta powers in all brain regions, whereas the Internet addiction group with depression had increased relative theta and decreased relative alpha power in all regions. These neurophysiological changes were not related to clinical variables. The current findings reflect differential resting-state QEEG patterns between both groups of participants with Internet addiction and healthy controls and also suggest that decreased absolute delta and beta powers are neurobiological markers of Internet addiction. Copyright © 2013 Elsevier Inc. All rights reserved.

X-ray structures define human P2X(3) receptor gating cycle and antagonist action.

PubMed

Mansoor, Steven E; Lü, Wei; Oosterheert, Wout; Shekhar, Mrinal; Tajkhorshid, Emad; Gouaux, Eric

2016-10-06

P2X receptors are trimeric, non-selective cation channels activated by ATP that have important roles in the cardiovascular, neuronal and immune systems. Despite their central function in human physiology and although they are potential targets of therapeutic agents, there are no structures of human P2X receptors. The mechanisms of receptor desensitization and ion permeation, principles of antagonism, and complete structures of the pore-forming transmembrane domains of these receptors remain unclear. Here we report X-ray crystal structures of the human P2X 3 receptor in apo/resting, agonist-bound/open-pore, agonist-bound/closed-pore/desensitized and antagonist-bound/closed states. The open state structure harbours an intracellular motif we term the 'cytoplasmic cap', which stabilizes the open state of the ion channel pore and creates lateral, phospholipid-lined cytoplasmic fenestrations for water and ion egress. The competitive antagonists TNP-ATP and A-317491 stabilize the apo/resting state and reveal the interactions responsible for competitive inhibition. These structures illuminate the conformational rearrangements that underlie P2X receptor gating and provide a foundation for the development of new pharmacological agents.

The Dynamical Balance of the Brain at Rest

PubMed Central

Deco, Gustavo; Corbetta, Maurizio

2014-01-01

We review evidence that spontaneous, i.e. not stimulus- or task-driven, activity in the brain is not noise, but orderly organized at the level of large scale systems in a series of functional networks that maintain at all times a high level of coherence. These networks of spontaneous activity correlation or resting state networks (RSN) are closely related to the underlying anatomical connectivity, but their topography is also gated by the history of prior task activation. Network coherence does not depend on covert cognitive activity, but its strength and integrity relates to behavioral performance. Some RSN are functionally organized as dynamically competing systems both at rest and during tasks. Computational studies show that one of such dynamics, the anti-correlation between networks, depends on noise driven transitions between different multi-stable cluster synchronization states. These multi-stable states emerge because of transmission delays between regions that are modeled as coupled oscillators systems. Large-scale systems dynamics are useful for keeping different functional sub-networks in a state of heightened competition, which can be stabilized and fired by even small modulations of either sensory or internal signals. PMID:21196530

Resting-state theta-band connectivity and verbal memory in schizophrenia and in the high-risk state.

PubMed

Andreou, Christina; Leicht, Gregor; Nolte, Guido; Polomac, Nenad; Moritz, Steffen; Karow, Anne; Hanganu-Opatz, Ileana L; Engel, Andreas K; Mulert, Christoph

2015-02-01

Disturbed functional connectivity is assumed to underlie neurocognitive deficits in patients with schizophrenia. As neurocognitive deficits are already present in the high-risk state, identification of the neural networks involved in this core feature of schizophrenia is essential to our understanding of the disorder. Resting-state studies enable such investigations, while at the same time avoiding the known confounder of impaired task performance in patients. The aim of the present study was to investigate EEG resting-state connectivity in high-risk individuals (HR) compared to first episode patients with schizophrenia (SZ) and to healthy controls (HC), and its association with cognitive deficits. 64-channel resting-state EEG recordings (eyes closed) were obtained for 28 HR, 19 stable SZ, and 23 HC, matched for age, education, and parental education. The imaginary coherence-based multivariate interaction measure (MIM) was used as a measure of connectivity across 80 cortical regions and six frequency bands. Mean connectivity at each region was compared across groups using the non-parametric randomization approach. Additionally, the network-based statistic was applied to identify affected networks in patients. SZ displayed increased theta-band resting-state MIM connectivity across midline, sensorimotor, orbitofrontal regions and the left temporoparietal junction. HR displayed intermediate theta-band connectivity patterns that did not differ from either SZ or HC. Mean theta-band connectivity within the above network partially mediated verbal memory deficits in SZ and HR. Aberrant theta-band connectivity may represent a trait characteristic of schizophrenia associated with neurocognitive deficits. As such, it might constitute a promising target for novel treatment applications. Copyright © 2014 Elsevier B.V. All rights reserved.

Mining Time-Resolved Functional Brain Graphs to an EEG-Based Chronnectomic Brain Aged Index (CBAI).

PubMed

Dimitriadis, Stavros I; Salis, Christos I

2017-01-01

The brain at rest consists of spatially and temporal distributed but functionally connected regions that called intrinsic connectivity networks (ICNs). Resting state electroencephalography (rs-EEG) is a way to characterize brain networks without confounds associated with task EEG such as task difficulty and performance. A novel framework of how to study dynamic functional connectivity under the notion of functional connectivity microstates (FCμstates) and symbolic dynamics is further discussed. Furthermore, we introduced a way to construct a single integrated dynamic functional connectivity graph (IDFCG) that preserves both the strength of the connections between every pair of sensors but also the type of dominant intrinsic coupling modes (DICM). The whole methodology is demonstrated in a significant and unexplored task for EEG which is the definition of an objective Chronnectomic Brain Aged index (CBAI) extracted from resting-state data ( N = 94 subjects) with both eyes-open and eyes-closed conditions. Novel features have been defined based on symbolic dynamics and the notion of DICM and FCμstates. The transition rate of FCμstates, the symbolic dynamics based on the evolution of FCμstates (the Markovian Entropy, the complexity index), the probability distribution of DICM, the novel Flexibility Index that captures the dynamic reconfiguration of DICM per pair of EEG sensors and the relative signal power constitute a valuable pool of features that can build the proposed CBAI. Here we applied a feature selection technique and Extreme Learning Machine (ELM) classifier to discriminate young adults from middle-aged and a Support Vector Regressor to build a linear model of the actual age based on EEG-based spatio-temporal features. The most significant type of features for both prediction of age and discrimination of young vs. adults age groups was the dynamic reconfiguration of dominant coupling modes derived from a subset of EEG sensor pairs. Specifically, our results revealed a very high prediction of age for eyes-open ( R 2 = 0.60; y = 0.79x + 8.03) and lower for eyes-closed ( R 2 = 0.48; y = 0.71x + 10.91) while we succeeded to correctly classify young vs. middle-age group with 97.8% accuracy in eyes-open and 87.2% for eyes-closed. Our results were reproduced also in a second dataset for further external validation of the whole analysis. The proposed methodology proved valuable for the characterization of the intrinsic properties of dynamic functional connectivity through the age untangling developmental differences using EEG resting-state recordings.

REST and stress resistance in ageing and Alzheimer's disease

NASA Astrophysics Data System (ADS)

Lu, Tao; Aron, Liviu; Zullo, Joseph; Pan, Ying; Kim, Haeyoung; Chen, Yiwen; Yang, Tun-Hsiang; Kim, Hyun-Min; Drake, Derek; Liu, X. Shirley; Bennett, David A.; Colaiácovo, Monica P.; Yankner, Bruce A.

2014-03-01

Human neurons are functional over an entire lifetime, yet the mechanisms that preserve function and protect against neurodegeneration during ageing are unknown. Here we show that induction of the repressor element 1-silencing transcription factor (REST; also known as neuron-restrictive silencer factor, NRSF) is a universal feature of normal ageing in human cortical and hippocampal neurons. REST is lost, however, in mild cognitive impairment and Alzheimer's disease. Chromatin immunoprecipitation with deep sequencing and expression analysis show that REST represses genes that promote cell death and Alzheimer's disease pathology, and induces the expression of stress response genes. Moreover, REST potently protects neurons from oxidative stress and amyloid β-protein toxicity, and conditional deletion of REST in the mouse brain leads to age-related neurodegeneration. A functional orthologue of REST, Caenorhabditis elegans SPR-4, also protects against oxidative stress and amyloid β-protein toxicity. During normal ageing, REST is induced in part by cell non-autonomous Wnt signalling. However, in Alzheimer's disease, frontotemporal dementia and dementia with Lewy bodies, REST is lost from the nucleus and appears in autophagosomes together with pathological misfolded proteins. Finally, REST levels during ageing are closely correlated with cognitive preservation and longevity. Thus, the activation state of REST may distinguish neuroprotection from neurodegeneration in the ageing brain.

Source-reconstruction of the sensorimotor network from resting-state macaque electrocorticography.

PubMed

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.

A compact and realistic cerebral cortical layout derived from prewhitened resting-state fMRI time series: Cherniak's adjacency rule, size law, and metamodule grouping upheld

PubMed Central

Lewis, Scott M.; Christova, Peka; Jerde, Trenton A.; Georgopoulos, Apostolos P.

2012-01-01

We used hierarchical tree clustering to derive a functional organizational chart of 52 human cortical areas (26 per hemisphere) from zero-lag correlations calculated between single-voxel, prewhitened, resting-state BOLD fMRI time series in 18 subjects. No special “resting-state networks” were identified. There were four major features in the resulting tree (dendrogram). First, there was a strong clustering of homotopic, left-right hemispheric areas. Second, cortical areas were concatenated in multiple, partially overlapping clusters. Third, the arrangement of the areas revealed a layout that closely resembled the actual layout of the cerebral cortex, namely an orderly progression from anterior to posterior. And fourth, the layout of the cortical areas in the tree conformed to principles of efficient, compact layout of components proposed by Cherniak. Since the tree was derived on the basis of the strength of neural correlations, these results document an orderly relation between functional interactions and layout, i.e., between structure and function. PMID:22973198

Uncoupling binding of substrate CO from turnover by vanadium nitrogenase.

PubMed

Lee, Chi Chung; Fay, Aaron W; Weng, Tsu-Chien; Krest, Courtney M; Hedman, Britt; Hodgson, Keith O; Hu, Yilin; Ribbe, Markus W

2015-11-10

Biocatalysis by nitrogenase, particularly the reduction of N2 and CO by this enzyme, has tremendous significance in environment- and energy-related areas. Elucidation of the detailed mechanism of nitrogenase has been hampered by the inability to trap substrates or intermediates in a well-defined state. Here, we report the capture of substrate CO on the resting-state vanadium-nitrogenase in a catalytically competent conformation. The close resemblance of this active CO-bound conformation to the recently described structure of CO-inhibited molybdenum-nitrogenase points to the mechanistic relevance of sulfur displacement to the activation of iron sites in the cofactor for CO binding. Moreover, the ability of vanadium-nitrogenase to bind substrate in the resting-state uncouples substrate binding from subsequent turnover, providing a platform for generation of defined intermediate(s) of both CO and N2 reduction.

Heme Structural Perturbation of PEG-Modified Horseradish Peroxidase C in Aromatic Organic Solvents Probed by Optical Absorption and Resonance Raman Dispersion Spectroscopy

PubMed Central

Huang, Qing; Al-Azzam, Wasfi; Griebenow, Kai; Schweitzer-Stenner, Reinhard

2003-01-01

The heme structure perturbation of poly(ethylene glycol)-modified horseradish peroxidase (HRP-PEG) dissolved in benzene and toluene has been probed by resonance Raman dispersion spectroscopy. Analysis of the depolarization ratio dispersion of several Raman bands revealed an increase of rhombic B1g distortion with respect to native HRP in water. This finding strongly supports the notion that a solvent molecule has moved into the heme pocket where it stays in close proximity to one of the heme's pyrrole rings. The interactions between the solvent molecule, the heme, and the heme cavity slightly stabilize the hexacoordinate high spin state without eliminating the pentacoordinate quantum mixed spin state that is dominant in the resting enzyme. On the contrary, the model substrate benzohydroxamic acid strongly favors the hexacoordinate quantum mixed spin state and induces a B2g-type distortion owing to its position close to one of the heme methine bridges. These results strongly suggest that substrate binding must have an influence on the heme geometry of HRP and that the heme structure of the enzyme-substrate complex (as opposed to the resting state) must be the key to understanding the chemical reactivity of HRP. PMID:12719258

Clinical symptoms and alpha band resting-state functional connectivity imaging in patients with schizophrenia: implications for novel approaches to treatment

PubMed Central

Hinkley, Leighton B.N.; Vinogradov, Sophia; Guggisberg, Adrian G.; Fisher, Melissa; Findlay, Anne M.; Nagarajan, Srikantan S.

2011-01-01

Background Schizophrenia is associated with functional decoupling between cortical regions, but we do not know whether and where this occurs in low-frequency electromagnetic oscillations. The goal of this study was to use magnetoencephalography (MEG) to identify brain regions that exhibit abnormal resting-state connectivity in the alpha frequency range in patients with schizophrenia and investigate associations between functional connectivity and clinical symptoms in stable outpatient participants. Method Thirty patients with schizophrenia and fifteen healthy comparison participants were scanned in resting-state MEG (eyes closed). Functional connectivity MEGI (fcMEGI) data were reconstructed globally in the alpha range, quantified by the mean imaginary coherence between a voxel and the rest of the brain. Results In patients, decreased connectivity was observed in left pre-frontal cortex (PFC) and right superior temporal cortex while increased connectivity was observed in left extrastriate cortex and the right inferior PFC. Functional connectivity of left inferior parietal cortex was negatively related to positive symptoms. Low left PFC connectivity was associated with negative symptoms. Functional connectivity of midline PFC was negatively correlated with depressed symptoms. Functional connectivity of right PFC was associated with other (cognitive) symptoms. Conclusions This study demonstrates direct functional disconnection in schizophrenia between specific cortical fields within low-frequency resting-state oscillations. Impaired alpha coupling in frontal, parietal, and temporal regions is associated with clinical symptoms in these stable outpatients. Our findings indicate that this level of functional disconnection between cortical regions is an important treatment target in schizophrenia. PMID:21861988

Higher resting-state activity in reward-related brain circuits in obese versus normal-weight females independent of food intake.

PubMed

Hogenkamp, P S; Zhou, W; Dahlberg, L S; Stark, J; Larsen, A L; Olivo, G; Wiemerslage, L; Larsson, E-M; Sundbom, M; Benedict, C; Schiöth, H B

2016-11-01

In response to food cues, obese vs normal-weight individuals show greater activation in brain regions involved in the regulation of food intake under both fasted and sated conditions. Putative effects of obesity on task-independent low-frequency blood-oxygenation-level-dependent signals-that is, resting-state brain activity-in the context of food intake are, however, less well studied. To compare eyes closed, whole-brain low-frequency BOLD signals between severely obese and normal-weight females, as assessed by functional magnetic resonance imaging (fMRI). Fractional amplitude of low-frequency fluctuations were measured in the morning following an overnight fast in 17 obese (age: 39±11 years, body mass index (BMI): 42.3±4.8 kg m - 2 ) and 12 normal-weight females (age: 36±12 years, BMI: 22.7±1.8 kg m - 2 ), both before and 30 min after consumption of a standardized meal (~260 kcal). Compared with normal-weight controls, obese females had increased low-frequency activity in clusters located in the putamen, claustrum and insula (P<0.05). This group difference was not altered by food intake. Self-reported hunger dropped and plasma glucose concentrations increased after food intake (P<0.05); however, these changes did not differ between the BMI groups. Reward-related brain regions are more active under resting-state conditions in obese than in normal-weight females. This difference was independent of food intake under the experimental settings applied in the current study. Future studies involving males and females, as well as utilizing repeated post-prandial resting-state fMRI scans and various types of meals are needed to further investigate how food intake alters resting-state brain activity in obese humans.

Successful group psychotherapy of depression in adolescents alters fronto-limbic resting-state connectivity.

PubMed

Straub, J; Metzger, C D; Plener, P L; Koelch, M G; Groen, G; Abler, B

2017-02-01

Current resting state imaging findings support suggestions that the neural signature of depression and therefore also its therapy should be conceptualized as a network disorder rather than a dysfunction of specific brain regions. In this study, we compared neural connectivity of adolescent patients with depression (PAT) and matched healthy controls (HC) and analysed pre-to-post changes of seed-based network connectivities in PAT after participation in a cognitive behavioral group psychotherapy (CBT). 38 adolescents (30 female; 19 patients; 13-18 years) underwent an eyes-closed resting-state scan. PAT were scanned before (pre) and after (post) five sessions of CBT. Resting-state functional connectivity was analysed in a seed-based approach for right-sided amygdala and subgenual anterior cingulate cortex (sgACC). Symptom severity was assessed using the Beck Depression Inventory Revision (BDI-II). Prior to group CBT, between groups amygdala and sgACC connectivity with regions of the default mode network was stronger in the patients group relative to controls. Within the PAT group, a similar pattern significantly decreased after successful CBT. Conversely, seed-based connectivity with affective regions and regions processing cognition and salient stimuli was stronger in HC relative to PAT before CBT. Within the PAT group, a similar pattern changed with CBT. Changes in connectivity correlated with the significant pre-to-post symptom improvement, and pre-treatment amygdala connectivity predicted treatment response in depressed adolescents. Sample size and missing long-term follow-up limit the interpretability. Successful group psychotherapy of depression in adolescents involved connectivity changes in resting state networks to that of healthy controls. Copyright © 2016 Elsevier B.V. All rights reserved.

Measurement of Conformational Changes Accompanying Desensitization in an Ionotropic Glutamate Receptor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Armstrong,N.; Jasti, J.; Beich-Frandsen, M.

2006-01-01

The canonical conformational states occupied by most ligand-gated ion channels, and many cell-surface receptors, are the resting, activated, and desensitized states. While the resting and activated states of multiple receptors are well characterized, elaboration of the structural properties of the desensitized state, a state that is by definition inactive, has proven difficult. Here we use electrical, chemical, and crystallographic experiments on the AMPA-sensitive GluR2 receptor, defining the conformational rearrangements of the agonist binding cores that occur upon desensitization of this ligand-gated ion channel. These studies demonstrate that desensitization involves the rupture of an extensive interface between domain 1 of 2-foldmore » related glutamate-binding core subunits, compensating for the ca. 21{sup o} of domain closure induced by glutamate binding. The rupture of the domain 1 interface allows the ion channel to close and thereby provides a simple explanation to the long-standing question of how agonist binding is decoupled from ion channel gating upon receptor desensitization.« less

Upper bound on three-tangles of reduced states of four-qubit pure states

NASA Astrophysics Data System (ADS)

Sharma, S. Shelly; Sharma, N. K.

2017-06-01

Closed formulas for upper bounds on three-tangles of three-qubit reduced states in terms of three-qubit-invariant polynomials of pure four-qubit states are obtained. Our results offer tighter constraints on total three-way entanglement of a given qubit with the rest of the system than those used by Regula et al. [Phys. Rev. Lett. 113, 110501 (2014), 10.1103/PhysRevLett.113.110501 and Phys. Rev. Lett. 116, 049902(E) (2016)], 10.1103/PhysRevLett.116.049902 to verify monogamy of four-qubit quantum entanglement.

GPi Oscillatory Activity Differentiates Tics from the Resting State, Voluntary Movements, and the Unmedicated Parkinsonian State

PubMed Central

Jimenez-Shahed, Joohi; Telkes, Ilknur; Viswanathan, Ashwin; Ince, Nuri F.

2016-01-01

Background: Deep brain stimulation (DBS) is an emerging treatment strategy for severe, medication-refractory Tourette syndrome (TS). Thalamic (Cm-Pf) and pallidal (including globus pallidus interna, GPi) targets have been the most investigated. While the neurophysiological correlates of Parkinson's disease (PD) in the GPi and subthalamic nucleus (STN) are increasingly recognized, these patterns are not well characterized in other disease states. Recent findings indicate that the cross-frequency coupling (CFC) between beta band and high frequency oscillations (HFOs) within the STN in PD patients is pathologic. Methods: We recorded intraoperative local field potentials (LFPs) from the postero-ventrolateral GPi in three adult patients with TS at rest, during voluntary movements, and during tic activity and compared them to the intraoperative GPi-LFP activity recorded from four unmedicated PD patients at rest. Results: In all PD patients, we noted excessive beta band activity (13–30 Hz) at rest which consistently modulated the amplitude of the co-existent HFOs observed between 200 and 400 Hz, indicating the presence of beta-HFO CFC. In all 3TS patients at rest, we observed theta band activity (4–7 Hz) and HFOs. Two patients had beta band activity, though at lower power than theta oscillations. Tic activity was associated with increased high frequency (200–400 Hz) and gamma band (35–200 Hz) activity. There was no beta-HFO CFC in TS patients at rest. However, CFC between the phase of 5–10 Hz band activity and the amplitude of HFOs was found in two TS patients. During tics, this shifted to CFC between the phase of beta band activity and the amplitude of HFOs in all subjects. Conclusions: To our knowledge this is the first study that shows that beta-HFO CFC exists in the GPi of TS patients during tics and at rest in PD patients, and suggests that this pattern might be specific to pathologic/involuntary movements. Furthermore, our findings suggest that during tics, resting state 5–10 Hz-HFO CFC shifts to beta-HFO CFC which can be used to trigger stimulation in a closed loop system when tics are present. PMID:27733815

Meta-analytically informed network analysis of resting state FMRI reveals hyperconnectivity in an introspective socio-affective network in depression.

PubMed

Schilbach, Leonhard; Müller, Veronika I; Hoffstaedter, Felix; Clos, Mareike; Goya-Maldonado, Roberto; Gruber, Oliver; Eickhoff, Simon B

2014-01-01

Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA) network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology.

Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression

PubMed Central

Schilbach, Leonhard; Müller, Veronika I.; Hoffstaedter, Felix; Clos, Mareike; Goya-Maldonado, Roberto

2014-01-01

Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA) network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology. PMID:24759619

The Effect of Electroencephalogram (EEG) Reference Choice on Information-Theoretic Measures of the Complexity and Integration of EEG Signals

PubMed Central

Trujillo, Logan T.; Stanfield, Candice T.; Vela, Ruben D.

2017-01-01

Converging evidence suggests that human cognition and behavior emerge from functional brain networks interacting on local and global scales. We investigated two information-theoretic measures of functional brain segregation and integration—interaction complexity CI(X), and integration I(X)—as applied to electroencephalographic (EEG) signals and how these measures are affected by choice of EEG reference. CI(X) is a statistical measure of the system entropy accounted for by interactions among its elements, whereas I(X) indexes the overall deviation from statistical independence of the individual elements of a system. We recorded 72 channels of scalp EEG from human participants who sat in a wakeful resting state (interleaved counterbalanced eyes-open and eyes-closed blocks). CI(X) and I(X) of the EEG signals were computed using four different EEG references: linked-mastoids (LM) reference, average (AVG) reference, a Laplacian (LAP) “reference-free” transformation, and an infinity (INF) reference estimated via the Reference Electrode Standardization Technique (REST). Fourier-based power spectral density (PSD), a standard measure of resting state activity, was computed for comparison and as a check of data integrity and quality. We also performed dipole source modeling in order to assess the accuracy of neural source CI(X) and I(X) estimates obtained from scalp-level EEG signals. CI(X) was largest for the LAP transformation, smallest for the LM reference, and at intermediate values for the AVG and INF references. I(X) was smallest for the LAP transformation, largest for the LM reference, and at intermediate values for the AVG and INF references. Furthermore, across all references, CI(X) and I(X) reliably distinguished between resting-state conditions (larger values for eyes-open vs. eyes-closed). These findings occurred in the context of the overall expected pattern of resting state PSD. Dipole modeling showed that simulated scalp EEG-level CI(X) and I(X) reflected changes in underlying neural source dependencies, but only for higher levels of integration and with highest accuracy for the LAP transformation. Our observations suggest that the Laplacian-transformation should be preferred for the computation of scalp-level CI(X) and I(X) due to its positive impact on EEG signal quality and statistics, reduction of volume-conduction, and the higher accuracy this provides when estimating scalp-level EEG complexity and integration. PMID:28790884

Identifying Individuals with Antisocial Personality Disorder Using Resting-State fMRI

PubMed Central

Tang, Yan; Jiang, Weixiong; Liao, Jian; Wang, Wei; Luo, Aijing

2013-01-01

Antisocial personality disorder (ASPD) is closely connected to criminal behavior. A better understanding of functional connectivity in the brains of ASPD patients will help to explain abnormal behavioral syndromes and to perform objective diagnoses of ASPD. In this study we designed an exploratory data-driven classifier based on machine learning to investigate changes in functional connectivity in the brains of patients with ASPD using resting state functional magnetic resonance imaging (fMRI) data in 32 subjects with ASPD and 35 controls. The results showed that the classifier achieved satisfactory performance (86.57% accuracy, 77.14% sensitivity and 96.88% specificity) and could extract stabile information regarding functional connectivity that could be used to discriminate ASPD individuals from normal controls. More importantly, we found that the greatest change in the ASPD subjects was uncoupling between the default mode network and the attention network. Moreover, the precuneus, superior parietal gyrus and cerebellum exhibited high discriminative power in classification. A voxel-based morphometry analysis was performed and showed that the gray matter volumes in the parietal lobule and white matter volumes in the precuneus were abnormal in ASPD compared to controls. To our knowledge, this study was the first to use resting-state fMRI to identify abnormal functional connectivity in ASPD patients. These results not only demonstrated good performance of the proposed classifier, which can be used to improve the diagnosis of ASPD, but also elucidate the pathological mechanism of ASPD from a resting-state functional integration viewpoint. PMID:23593272

Identifying individuals with antisocial personality disorder using resting-state FMRI.

PubMed

Tang, Yan; Jiang, Weixiong; Liao, Jian; Wang, Wei; Luo, Aijing

2013-01-01

Antisocial personality disorder (ASPD) is closely connected to criminal behavior. A better understanding of functional connectivity in the brains of ASPD patients will help to explain abnormal behavioral syndromes and to perform objective diagnoses of ASPD. In this study we designed an exploratory data-driven classifier based on machine learning to investigate changes in functional connectivity in the brains of patients with ASPD using resting state functional magnetic resonance imaging (fMRI) data in 32 subjects with ASPD and 35 controls. The results showed that the classifier achieved satisfactory performance (86.57% accuracy, 77.14% sensitivity and 96.88% specificity) and could extract stabile information regarding functional connectivity that could be used to discriminate ASPD individuals from normal controls. More importantly, we found that the greatest change in the ASPD subjects was uncoupling between the default mode network and the attention network. Moreover, the precuneus, superior parietal gyrus and cerebellum exhibited high discriminative power in classification. A voxel-based morphometry analysis was performed and showed that the gray matter volumes in the parietal lobule and white matter volumes in the precuneus were abnormal in ASPD compared to controls. To our knowledge, this study was the first to use resting-state fMRI to identify abnormal functional connectivity in ASPD patients. These results not only demonstrated good performance of the proposed classifier, which can be used to improve the diagnosis of ASPD, but also elucidate the pathological mechanism of ASPD from a resting-state functional integration viewpoint.

Differences in regional homogeneity between patients with Crohn's disease with and without abdominal pain revealed by resting-state functional magnetic resonance imaging

PubMed Central

Wu, Lu-Yi; Jin, Xiao-Ming; Wang, Si-Yao; Shi, Yin; Zhang, Jian-Ye; Zeng, Xiao-Qing; Ma, Li-Li; Qin, Wei; Zhao, Ji-Meng; Calhoun, Vince D.; Tian, Jie; Wu, Huan-Gan

2016-01-01

Abnormal pain processing in the central nervous system may be related to abdominal pain in patients with Crohn's disease (CD). The purpose of this study was to investigate changes in resting-state brain activity in CD patients in remission and its relationship with the presence of abdominal pain. Twenty-five CD patients with abdominal pain, 25 CD patients without abdominal pain, and 32 healthy subjects were scanned using a 3.0 T functional magnetic resonance imaging (fMRI) scanner. Regional homogeneity (ReHo) was used to assess resting-state brain activity. Daily pain scores were collected 1 week before fMRI scanning. We found that patients with abdominal pain exhibited lower ReHo values in the insula, middle cingulate cortex (MCC), and supplementary motor area, and higher ReHo values in the temporal pole. In contrast, patients without abdominal pain exhibited lower ReHo values in the hippocampal/parahippocampal cortex and higher ReHo values in the dorsomedial prefrontal cortex (all P<0.05, corrected). The ReHo values of the insula and MCC were significantly negatively correlated with daily pain scores for patients with abdominal pain (r=−0.53, P=0.008, and r=−0.61, P=0.002, respectively). These findings suggest that resting-state brain activities are different between remissive CD patients with and without abdominal pain, and that abnormal activities in insula and MCC are closely related to the severity of abdominal pain. PMID:26761381

Effect of immobilization on the EEG of the baboon. Comparison with telemetry results from unrestricted animals

NASA Technical Reports Server (NTRS)

Bert, J.; Collomb, H.

1980-01-01

The EEG of the baboon was studied under two very different sets of conditions: 37 were totally immobolized while 12 were studied in their free movements with 4 channel telemetry. For the immobilzed, 3 stages were described: (1) activation, record desynchronized; (2) rest with 13-15 cm/sec rhythm, like the human alpha rhythm stage but with eyes open or closed; (3)relaxation with a decrease in 13-15 rhythm and the appearance of 5-7 cm/sec theta waves, eyelids closed, animal apparently sleeping. For the free animals the rest stage appeared when the animal's attention was not directed anywhere and there was no relaxation stage. It is concluded that the EEG pattern of the immobilized animal that was described as the "relaxation" stage really represents a special functional state which one must distinguish clearly from the physiological stages of sleep.

Fatigue correlates with the decrease in parasympathetic sinus modulation induced by a cognitive challenge

PubMed Central

2014-01-01

Background It is known that enhancement of sympathetic nerve activity based on a decrease in parasympathetic nerve activity is associated with fatigue induced by mental tasks lasting more than 30 min. However, to measure autonomic nerve function and assess fatigue levels in both clinical and industrial settings, shorter experimental durations and more sensitive measurement methods are needed. The aim of the present study was to establish an improved method for inducing fatigue and evaluating the association between it and autonomic nerve activity. Methods Twenty-eight healthy female college students participated in the study. We used a kana pick-out test (KPT) as a brief verbal cognitive task and recorded electrocardiography (ECG) to measure autonomic nerve activity. The experimental design consisted of a 16-min period of ECG: A pre-task resting state with eyes open for 3 min and eyes closed for 3 min, the 4-min KPT, and a post-task resting state with eyes open for 3 min and eyes closed for 3 min. Results Baseline fatigue sensation, measured by a visual analogue scale before the experiment, was associated with the decrease in parasympathetic sinus modulation, as indicated the by ratio of low-frequency component power (LF) to high-frequency component power (HF), during the KPT. The LF/HF ratio during the post-KPT rest with eyes open tended to be greater than the ratio during the KPT and correlated with fatigue sensation. Fatigue sensation was correlated negatively with log-transformed HF, which is an index of parasympathetic sinus modulation, during the post-KPT rest with eyes open. Conclusions The methods described here are useful for assessing the association between fatigue sensation and autonomic nerve activity using a brief cognitive test in healthy females. PMID:25069864

OCCIPITAL SOURCES OF RESTING STATE ALPHA RHYTHMS ARE RELATED TO LOCAL GRAY MATTER DENSITY IN SUBJECTS WITH AMNESIC MILD COGNITIVE IMPAIRMENT AND ALZHEIMER’S DISEASE

PubMed Central

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

When frequencies never synchronize: the golden mean and the resting EEG.

PubMed

Pletzer, Belinda; Kerschbaum, Hubert; Klimesch, Wolfgang

2010-06-04

The classical frequency bands of the EEG can be described as a geometric series with a ratio (between neighbouring frequencies) of 1.618, which is the golden mean. Here we show that a synchronization of the excitatory phases of two oscillations with frequencies f1 and f2 is impossible (in a mathematical sense) when their ratio equals the golden mean, because their excitatory phases never meet. Thus, in a mathematical sense, the golden mean provides a totally uncoupled ('desynchronized') processing state which most likely reflects a 'resting' brain, which is not involved in selective information processing. However, excitatory phases of the f1- and f2-oscillations occasionally come close enough to coincide in a physiological sense. These coincidences are more frequent, the higher the frequencies f1 and f2. We demonstrate that the pattern of excitatory phase meetings provided by the golden mean as the 'most irrational' number is least frequent and most irregular. Thus, in a physiological sense, the golden mean provides (i) the highest physiologically possible desynchronized state in the resting brain, (ii) the possibility for spontaneous and most irregular (!) coupling and uncoupling between rhythms and (iii) the opportunity for a transition from resting state to activity. These characteristics have already been discussed to lay the ground for a healthy interplay between various physiological processes (Buchmann, 2002). Copyright 2010 Elsevier B.V. All rights reserved.

Using Spatial Multiple Regression to Identify Intrinsic Connectivity Networks Involved in Working Memory Performance

PubMed Central

Gordon, Evan M.; Stollstorff, Melanie; Vaidya, Chandan J.

2012-01-01

Many researchers have noted that the functional architecture of the human brain is relatively invariant during task performance and the resting state. Indeed, intrinsic connectivity networks (ICNs) revealed by resting-state functional connectivity analyses are spatially similar to regions activated during cognitive tasks. This suggests that patterns of task-related activation in individual subjects may result from the engagement of one or more of these ICNs; however, this has not been tested. We used a novel analysis, spatial multiple regression, to test whether the patterns of activation during an N-back working memory task could be well described by a linear combination of ICNs delineated using Independent Components Analysis at rest. We found that across subjects, the cingulo-opercular Set Maintenance ICN, as well as right and left Frontoparietal Control ICNs, were reliably activated during working memory, while Default Mode and Visual ICNs were reliably deactivated. Further, involvement of Set Maintenance, Frontoparietal Control, and Dorsal Attention ICNs was sensitive to varying working memory load. Finally, the degree of left Frontoparietal Control network activation predicted response speed, while activation in both left Frontoparietal Control and Dorsal Attention networks predicted task accuracy. These results suggest that a close relationship between resting-state networks and task-evoked activation is functionally relevant for behavior, and that spatial multiple regression analysis is a suitable method for revealing that relationship. PMID:21761505

Medical Education, 1920-1922. Bulletin, 1923, No. 18

ERIC Educational Resources Information Center

Colwell, N. P.

1923-01-01

As shown in previous reports, following the close of the Civil War the number of medical schools in the United States rapidly increased until in 1906 there were 162-- more than in all the rest of the world. The educational standards, however, were considerably lower than those in other leading countries; so that the evident need was for "'fewer…

Implication of the Slow-5 Oscillations in the Disruption of the Default-Mode Network in Healthy Aging and Stroke

PubMed Central

Nair, Veena A.; Mossahebi, Pouria; Young, Brittany M.; Chacon, Marcus; Jensen, Matthew; Birn, Rasmus M.; Meyerand, Mary E.; Prabhakaran, Vivek

2016-01-01

Abstract The processes of normal aging and aging-related pathologies subject the brain to an active re-organization of its brain networks. Among these, the default-mode network (DMN) is consistently implicated with a demonstrated reduction in functional connectivity within the network. However, no clear stipulation on the underlying mechanisms of the de-synchronization has yet been provided. In this study, we examined the spectral distribution of the intrinsic low-frequency oscillations (LFOs) of the DMN sub-networks in populations of young normals, older subjects, and acute and subacute ischemic stroke patients. The DMN sub-networks were derived using a mid-order group independent component analysis with 117 eyes-closed resting-state functional magnetic resonance imaging (rs-fMRI) sessions from volunteers in those population groups, isolating three robust components of the DMN among other resting-state networks. The posterior component of the DMN presented noticeable differences. Measures of amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) of the network component demonstrated a decrease in resting-state cortical oscillation power in the elderly (normal and patient), specifically in the slow-5 (0.01–0.027 Hz) range of oscillations. Furthermore, the contribution of the slow-5 oscillations during the resting state was diminished for a greater influence of the slow-4 (0.027–0.073 Hz) oscillations in the subacute stroke group, not only suggesting a vulnerability of the slow-5 oscillations to disruption but also indicating a change in the distribution of the oscillations within the resting-state frequencies. The reduction of network slow-5 fALFF in the posterior DMN component was found to present a potential association with behavioral measures, suggesting a brain–behavior relationship to those oscillations, with this change in behavior potentially resulting from an altered network integrity induced by a weakening of the slow-5 oscillations during the resting state. The repeated identification of those frequencies in the disruption of DMN stresses a critical role of the slow-5 oscillations in network disruption, and it accentuates the importance of managing those oscillations in the health of the DMN. PMID:27130180

Structure and Topology Dynamics of Hyper-Frequency Networks during Rest and Auditory Oddball Performance.

PubMed

Müller, Viktor; Perdikis, Dionysios; von Oertzen, Timo; Sleimen-Malkoun, Rita; Jirsa, Viktor; Lindenberger, Ulman

2016-01-01

Resting-state and task-related recordings are characterized by oscillatory brain activity and widely distributed networks of synchronized oscillatory circuits. Electroencephalographic recordings (EEG) were used to assess network structure and network dynamics during resting state with eyes open and closed, and auditory oddball performance through phase synchronization between EEG channels. For this assessment, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that CFC generally differentiates between task conditions better than WFC. CFC was the highest during resting state with eyes open. Using a graph-theoretical approach (GTA), we found that HFNs possess small-world network (SWN) topology with a slight tendency to random network characteristics. Moreover, analysis of the temporal fluctuations of HFNs revealed specific network topology dynamics (NTD), i.e., temporal changes of different graph-theoretical measures such as strength, clustering coefficient, characteristic path length (CPL), local, and global efficiency determined for HFNs at different time windows. The different topology metrics showed significant differences between conditions in the mean and standard deviation of these metrics both across time and nodes. In addition, using an artificial neural network approach, we found stimulus-related dynamics that varied across the different network topology metrics. We conclude that functional connectivity dynamics (FCD), or NTD, which was found using the HFN approach during rest and stimulus processing, reflects temporal and topological changes in the functional organization and reorganization of neuronal cell assemblies.

Structure and Topology Dynamics of Hyper-Frequency Networks during Rest and Auditory Oddball Performance

PubMed Central

Müller, Viktor; Perdikis, Dionysios; von Oertzen, Timo; Sleimen-Malkoun, Rita; Jirsa, Viktor; Lindenberger, Ulman

2016-01-01

Resting-state and task-related recordings are characterized by oscillatory brain activity and widely distributed networks of synchronized oscillatory circuits. Electroencephalographic recordings (EEG) were used to assess network structure and network dynamics during resting state with eyes open and closed, and auditory oddball performance through phase synchronization between EEG channels. For this assessment, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that CFC generally differentiates between task conditions better than WFC. CFC was the highest during resting state with eyes open. Using a graph-theoretical approach (GTA), we found that HFNs possess small-world network (SWN) topology with a slight tendency to random network characteristics. Moreover, analysis of the temporal fluctuations of HFNs revealed specific network topology dynamics (NTD), i.e., temporal changes of different graph-theoretical measures such as strength, clustering coefficient, characteristic path length (CPL), local, and global efficiency determined for HFNs at different time windows. The different topology metrics showed significant differences between conditions in the mean and standard deviation of these metrics both across time and nodes. In addition, using an artificial neural network approach, we found stimulus-related dynamics that varied across the different network topology metrics. We conclude that functional connectivity dynamics (FCD), or NTD, which was found using the HFN approach during rest and stimulus processing, reflects temporal and topological changes in the functional organization and reorganization of neuronal cell assemblies. PMID:27799906

Just a minute meditation: Rapid voluntary conscious state shifts in long term meditators.

PubMed

Nair, Ajay Kumar; Sasidharan, Arun; John, John P; Mehrotra, Seema; Kutty, Bindu M

2017-08-01

Meditation induces a modified state of consciousness that remains under voluntary control. Can meditators rapidly and reversibly bring about mental state changes on demand? To check, we carried out 128 channel EEG recordings on Brahma Kumaris Rajayoga meditators (36 long term: median 14240h meditation; 25 short term: 1095h) and controls (25) while they tried to switch every minute between rest and meditation states in different conditions (eyes open and closed; before and after an engaging task). Long term meditators robustly shifted states with enhanced theta power (4-8Hz) during meditation. Short term meditators had limited ability to shift between states and showed increased lower alpha power (8-10Hz) during eyes closed meditation only when pre and post task data were combined. Controls could not shift states. Thus trained beginners can reliably meditate but it takes long term practice to exercise more refined control over meditative states. Copyright © 2017 Elsevier Inc. All rights reserved.

Enhanced phase synchrony in the electroencephalograph γ band for musicians while listening to music

NASA Astrophysics Data System (ADS)

Bhattacharya, Joydeep; Petsche, Hellmuth

2001-07-01

Multichannel electroencephalograph signals from two broad groups, 10 musicians and 10 nonmusicians, recorded in different states (in resting states or no task condition, with eyes opened and eyes closed, and with two musical tasks, listening to two different pieces of music) were studied. Degrees of phase synchrony in various frequency bands were assessed. No differences in the degree of synchronization in any frequency band were found between the two groups in resting conditions. Yet, while listening to music, significant increases of synchronization were found only in the γ-frequency range (>30 Hz) over large cortical areas for the group of musicians. This high degree of synchronization elicited by music in the group of musicians might be due to their ability to host long-term memory representations of music and mediate access to these stored representations.

Linear and Nonlinear Analysis of Brain Dynamics in Children with Cerebral Palsy

ERIC Educational Resources Information Center

Sajedi, Firoozeh; Ahmadlou, Mehran; Vameghi, Roshanak; Gharib, Masoud; Hemmati, Sahel

2013-01-01

This study was carried out to determine linear and nonlinear changes of brain dynamics and their relationships with the motor dysfunctions in CP children. For this purpose power of EEG frequency bands (as a linear analysis) and EEG fractality (as a nonlinear analysis) were computed in eyes-closed resting state and statistically compared between 26…

Dormant state in bacteria: Conceptions and implications for terrestrial biogeoscience and astrobiology

NASA Astrophysics Data System (ADS)

Mulyukin, A.

2003-04-01

Gaining insight into strategies and mechanisms that ensure long term-preservation of microorganisms in various environments, including cold habitats, is a very important issue for terrestrial biogeoscience and astrobiology. This communication has a focus on the analysis of the published and our experimental data regarding the dormant state of different microorganisms, with an emphasis on non-spore-forming bacteria, which are widely spread in numerous ecological niches (e.g. permafrost sediments). Albeit it is recognized that one of the strategies to endure environmental stresses is entering of non-spore-forming bacteria into the viable-but-non-culturable state, a question of whether these microorganisms have the resting stage remains unclear. However, our previous studies showed that non-spore-forming bacteria and yeast could form cyst-like cells that possess many attributes of constitutively resting cells. As applied to the survival strategy of non-spore-forming bacteria in permafrost sediments, recognizing a very important role of the viable-but-nonculturable state in asporogenous bacteria, we however believe that their long-term maintenance in such habitats is due to the formation of cyst-like cells. Interestingly, bacterial isolates from permafrost sediments showed a greater productivity of autoregulatory factors, favoring the transition of cells into the resting state, and a more elevated resistance to some stresses than closely related collection strains. This suggests a greater potentiality of the permafrost isolates to enter the resting stage and thereby to survive for millennia years in natural habitats. However, it is known that only a little part of microorganisms that are present in environmental samples can be enumerated by standard plating on agar media, and a discrepancy between the total number of cells and those capable of forming colonies is a rather common case. Such a discrepancy can be due to either the actual non-culturability of microbial cells and to that the conditions that are most appropriate to wake resting cells to growth are unknown to microbiologists. Furthermore, resting bacterial cells of just the same species differ in their ability to recover the growth and multiplication and profundity of the dormant state, so special 'reanimation' procedures are required. To overcome obstacles due to an expectable underestimation of total cell number in the environmental samples, it is important to find out the criteria, which allow one to distinguish between microbial cells of different physiological state, including the resting cells, by direct methods. Some of such approaches to revealing the specific features of potentially viable resting cells (in laboratory cultures) were developed in our works and used for a primary detection of microbial cells in situ and for appraisal of their physiological state. So, it is worth to discuss what we can propose for a better understanding of the phenomenon of long-term preservation of microorganisms in cold terrestrial ecosystems and whether resting cells of non-spore-forming-bacteria can be regarded as a target in exobiological explorations.

The ladder-shaped polyether toxin gambierol anchors the gating machinery of Kv3.1 channels in the resting state

PubMed Central

Kopljar, Ivan; Labro, Alain J.; de Block, Tessa; Rainier, Jon D.; Tytgat, Jan

2013-01-01

Voltage-gated potassium (Kv) and sodium (Nav) channels are key determinants of cellular excitability and serve as targets of neurotoxins. Most marine ciguatoxins potentiate Nav channels and cause ciguatera seafood poisoning. Several ciguatoxins have also been shown to affect Kv channels, and we showed previously that the ladder-shaped polyether toxin gambierol is a potent Kv channel inhibitor. Most likely, gambierol acts via a lipid-exposed binding site, located outside the K+ permeation pathway. However, the mechanism by which gambierol inhibits Kv channels remained unknown. Using gating and ionic current analysis to investigate how gambierol affected S6 gate opening and voltage-sensing domain (VSD) movements, we show that the resting (closed) channel conformation forms the high-affinity state for gambierol. The voltage dependence of activation was shifted by >120 mV in the depolarizing direction, precluding channel opening in the physiological voltage range. The (early) transitions between the resting and the open state were monitored with gating currents, and provided evidence that strong depolarizations allowed VSD movement up to the activated-not-open state. However, for transition to the fully open (ion-conducting) state, the toxin first needed to dissociate. These dissociation kinetics were markedly accelerated in the activated-not-open state, presumably because this state displayed a much lower affinity for gambierol. A tetrameric concatemer with only one high-affinity binding site still displayed high toxin sensitivity, suggesting that interaction with a single binding site prevented the concerted step required for channel opening. We propose a mechanism whereby gambierol anchors the channel’s gating machinery in the resting state, requiring more work from the VSD to open the channel. This mechanism is quite different from the action of classical gating modifier peptides (e.g., hanatoxin). Therefore, polyether toxins open new opportunities in structure–function relationship studies in Kv channels and in drug design to modulate channel function. PMID:23401573

Influence of anodal transcranial direct current stimulation (tDCS) over the right angular gyrus on brain activity during rest.

PubMed

Clemens, Benjamin; Jung, Stefanie; Mingoia, Gianluca; Weyer, David; Domahs, Frank; Willmes, Klaus

2014-01-01

Although numerous studies examined resting-state networks (RSN) in the human brain, so far little is known about how activity within RSN might be modulated by non-invasive brain stimulation applied over parietal cortex. Investigating changes in RSN in response to parietal cortex stimulation might tell us more about how non-invasive techniques such as transcranial direct current stimulation (tDCS) modulate intrinsic brain activity, and further elaborate our understanding of how the resting brain responds to external stimulation. Here we examined how activity within the canonical RSN changed in response to anodal tDCS applied over the right angular gyrus (AG). We hypothesized that changes in resting-state activity can be induced by a single tDCS session and detected with functional magnetic resonance imaging (fMRI). Significant differences between two fMRI sessions (pre-tDCS and post-tDCS) were found in several RSN, including the cerebellar, medial visual, sensorimotor, right frontoparietal, and executive control RSN as well as the default mode and the task positive network. The present results revealed decreased and increased RSN activity following tDCS. Decreased RSN activity following tDCS was found in bilateral primary and secondary visual areas, and in the right putamen. Increased RSN activity following tDCS was widely distributed across the brain, covering thalamic, frontal, parietal and occipital regions. From these exploratory results we conclude that a single session of anodal tDCS over the right AG is sufficient to induce large-scale changes in resting-state activity. These changes were localized in sensory and cognitive areas, covering regions close to and distant from the stimulation site.

Influence of Anodal Transcranial Direct Current Stimulation (tDCS) over the Right Angular Gyrus on Brain Activity during Rest

PubMed Central

Clemens, Benjamin; Jung, Stefanie; Mingoia, Gianluca; Weyer, David; Domahs, Frank; Willmes, Klaus

2014-01-01

Although numerous studies examined resting-state networks (RSN) in the human brain, so far little is known about how activity within RSN might be modulated by non-invasive brain stimulation applied over parietal cortex. Investigating changes in RSN in response to parietal cortex stimulation might tell us more about how non-invasive techniques such as transcranial direct current stimulation (tDCS) modulate intrinsic brain activity, and further elaborate our understanding of how the resting brain responds to external stimulation. Here we examined how activity within the canonical RSN changed in response to anodal tDCS applied over the right angular gyrus (AG). We hypothesized that changes in resting-state activity can be induced by a single tDCS session and detected with functional magnetic resonance imaging (fMRI). Significant differences between two fMRI sessions (pre-tDCS and post-tDCS) were found in several RSN, including the cerebellar, medial visual, sensorimotor, right frontoparietal, and executive control RSN as well as the default mode and the task positive network. The present results revealed decreased and increased RSN activity following tDCS. Decreased RSN activity following tDCS was found in bilateral primary and secondary visual areas, and in the right putamen. Increased RSN activity following tDCS was widely distributed across the brain, covering thalamic, frontal, parietal and occipital regions. From these exploratory results we conclude that a single session of anodal tDCS over the right AG is sufficient to induce large-scale changes in resting-state activity. These changes were localized in sensory and cognitive areas, covering regions close to and distant from the stimulation site. PMID:24760013

EEG alpha power as an intermediate measure between brain-derived neurotrophic factor Val66Met and depression severity in patients with major depressive disorder.

PubMed

Zoon, Harriët F A; Veth, C P M; Arns, Martijn; Drinkenburg, W H I M; Talloen, Willem; Peeters, Pieter J; Kenemans, J L

2013-06-01

Major depressive disorder has a large impact on patients and society and is projected to be the second greatest global burden of disease by 2020. The brain-derived neurotrophic factor (BDNF) gene is considered to be one of the important factors in the etiology of major depressive disorder. In a recent study, alpha power was found to mediate between BDNF Met and subclinical depressed mood. The current study looked at a population of patients with major depressive disorder (N = 107) to examine the association between the BDNF Val66Met polymorphism, resting state EEG alpha power, and depression severity. For this purpose, repeated-measures analysis of variance, partial correlation, and multiple linear models were used. Results indicated a negative association between parietal-occipital alpha power in the eyes open resting state and depression severity. In addition, Met/Met patients showed lower global absolute alpha power in the eyes closed condition compared with Val-carriers. These findings are in accordance with the previously uncovered pathway between BDNF Val66Met, resting state EEG alpha power, and depression severity. Additional research is needed for the clarification of this tentative pathway and its implication in personalized treatment of major depressive disorder.

X-ray structures define human P2X3 receptor gating cycle and antagonist action

PubMed Central

Mansoor, Steven E.; Lü, Wei; Oosterheert, Wout; Shekhar, Mrinal; Tajkhorshid, Emad; Gouaux, Eric

2016-01-01

Summary P2X receptors are trimeric, non-selective cation channels activated by ATP that play important roles in cardiovascular, neuronal and immune systems. Despite their central function in human physiology and as potential targets of therapeutic agents, there are no structures of human P2X receptors. Mechanisms of receptor desensitization and ion permeation, principles of antagonism, and complete structure of the pore-forming transmembrane domains remain unclear. We report x-ray crystal structures of human P2X3 receptor in apo/resting, agonist-bound/open-pore, agonist-bound/desensitized and antagonist-bound closed states. The open state structure harbors an intracellular motif we term the “cytoplasmic cap”, that stabilizes the open state of the ion channel pore and creates lateral, phospholipid-lined cytoplasmic fenestrations for water and ion egress. Competitive antagonists TNP-ATP and A-317491 stabilize the apo/resting state and reveal the interactions responsible for competitive inhibition. These structures illuminate the conformational rearrangements underpinning P2X receptor gating and provide a foundation for development of new pharmacologic agents. PMID:27626375

Female exposure to high G: effects of simulated combat sorties on cerebral and arterial O2 saturation.

PubMed

Tripp, L D; Chelette, T; Savul, S; Widman, R A

1998-09-01

One of the key factors in maintaining optimal cognitive performance in the high-G environment is the adequate delivery of oxygen to the cerebral tissue. As eye-level blood pressure is compromised at 22 mmHg x G(-1), perfusion to the peripheral cerebral tissues (cerebral cortex) may not be adequate to support the mental demands of flight. This study measured the effect of closed-loop flight simulations (3 min) on cerebral oxygen saturation changes (rSO2), arterial oxygen saturation (SAO2), and heart rate (HR), in both rested (8 h of rest) and sleepless (24 h without sleep) conditions. Subjects (16; 8 males and 8 females) were subjected to G-exposures via closed-loop flight simulations in a series of four 3-min sorties flown by subjects on the Dynamic Environment Simulator (centrifuge) in either a rested or a sleepless state. Prior to the centrifuge flight, subjects were instrumented with sensors for measurement of arterial oxygen saturation (SAO2) and regional cerebral tissue oxygenation (rSO2). Subjects wore the standard flight suit, boots, CSU-13B/P anti-G suit, and the COMBAT EDGE positive-pressure breathing for G-protection system. Significant changes in cerebral and arterial oxygen saturation were observed within groups when comparing pretest baselines and minimum values during the test and pre- and post-G rSO2, SAO2, and HR in both the rested and sleepless state, (p # 0.01), respectively, for each group. Comparisons between groups showed women to have significantly smaller regional cerebral cortex oxygen decreases than men (p # 0.01). No significant changes in SAO2, however, were observed between groups. Both men and women showed a slow recovery of rSO2 values to the prebaseline levels. Sleeplessness had no effect on the rSO2, SAO2, and HR compared with the rested condition. During acceleration, regional cerebral tissue oxygen decreased 13% in men compared with 9% in women. The recovery of cerebral tissue oxygen levels to prebaseline values was retarded somewhat when compared with the recovery response of arterial oxygen saturation.

Increased resting state functional connectivity in the fronto-parietal and default mode network in anorexia nervosa

PubMed Central

Boehm, Ilka; Geisler, Daniel; King, Joseph A.; Ritschel, Franziska; Seidel, Maria; Deza Araujo, Yacila; Petermann, Juliane; Lohmeier, Heidi; Weiss, Jessika; Walter, Martin; Roessner, Veit; Ehrlich, Stefan

2014-01-01

The etiology of anorexia nervosa (AN) is poorly understood. Results from functional brain imaging studies investigating the neural profile of AN using cognitive and emotional task paradigms are difficult to reconcile. Task-related imaging studies often require a high level of compliance and can only partially explore the distributed nature and complexity of brain function. In this study, resting state functional connectivity imaging was used to investigate well-characterized brain networks potentially relevant to understand the neural mechanisms underlying the symptomatology and etiology of AN. Resting state functional magnetic resonance imaging data was obtained from 35 unmedicated female acute AN patients and 35 closely matched healthy controls female participants (HC) and decomposed using spatial group independent component analyses (ICA). Using validated templates, we identified components covering the fronto-parietal “control” network, the default mode network (DMN), the salience network, the visual and the sensory-motor network. Group comparison revealed an increased functional connectivity between the angular gyrus and the other parts of the fronto-parietal network in patients with AN in comparison to HC. Connectivity of the angular gyrus was positively associated with self-reported persistence in HC. In the DMN, AN patients also showed an increased functional connectivity strength in the anterior insula in comparison to HC. Anterior insula connectivity was associated with self-reported problems with interoceptive awareness. This study, with one of the largest sample to date, shows that acute AN is associated with abnormal brain connectivity in two major resting state networks (RSN). The finding of an increased functional connectivity in the fronto-parietal network adds novel support for the notion of AN as a disorder of excessive cognitive control, whereas the elevated functional connectivity of the anterior insula with the DMN may reflect the high levels of self- and body-focused ruminations when AN patients are at rest. PMID:25324749

Continuous Measurements of Eyeball Area and Their Spectrum Analyses -- Toward the Quantification of Rest Rhythm of Horses by Image Processing

DTIC Science & Technology

2001-10-25

analyses of electroencephalogram at half- closed eye and fully closed eye. This study aimed at quantitative estimating rest rhythm of horses by the...analyses of eyeball movement. The mask attached with a miniature CCD camera was newly developed. The continuous images of the horse eye for about 24...eyeball area were calculated. As for the results, the fluctuating status of eyeball area was analyzed quantitatively, and the rest rhythm of horses was

A METHOD FOR USING BLOCKED AND EVENT-RELATED FMRI DATA TO STUDY “RESTING STATE” FUNCTIONAL CONNECTIVITY

PubMed Central

Fair, Damien A.; Schlaggar, Bradley L.; Cohen B.A., Alexander L.; Miezin, Francis M.; Dosenbach, Nico U.F.; Wenger, Kristin K.; Fox, Michael D.; Snyder, Abraham Z.; Raichle, Marcus E.; Petersen, Steven E.

2007-01-01

Resting state functional connectivity MRI (fcMRI) has become a particularly useful tool for studying regional relationships in typical and atypical populations. Because many investigators have already obtained large datasets of task related fMRI, the ability to use this existing task data for resting state fcMRI is of considerable interest. Two classes of datasets could potentially be modified to emulate resting state data. These datasets include: 1) “interleaved” resting blocks from blocked or mixed blocked/event-related sets, and 2) residual timecourses from event-related sets that lack rest blocks. Using correlation analysis, we compared the functional connectivity of resting epochs taken from a mixed blocked/event-related design fMRI data set and the residuals derived from event-related data with standard continuous resting state data to determine which class of data can best emulate resting state data. We show that despite some differences, the functional connectivity for the interleaved resting periods taken from blocked designs is both qualitatively and quantitatively very similar to that of “continuous” resting state data. In contrast, despite being qualitatively similar to “continuous” resting state data, residuals derived from event-related design data had several distinct quantitative differences. These results suggest that the interleaved resting state data such as those taken from blocked or mixed blocked/event-related fMRI designs are well-suited for resting state functional connectivity analyses. Although using event-related data residuals for resting state functional connectivity may still be useful, results should be interpreted with care. PMID:17239622

Resting-State Brain and the FTO Obesity Risk Allele: Default Mode, Sensorimotor, and Salience Network Connectivity Underlying Different Somatosensory Integration and Reward Processing between Genotypes.

PubMed

Olivo, Gaia; Wiemerslage, Lyle; Nilsson, Emil K; Solstrand Dahlberg, Linda; Larsen, Anna L; Olaya Búcaro, Marcela; Gustafsson, Veronica P; Titova, Olga E; Bandstein, Marcus; Larsson, Elna-Marie; Benedict, Christian; Brooks, Samantha J; Schiöth, Helgi B

2016-01-01

Single-nucleotide polymorphisms (SNPs) of the fat mass and obesity associated (FTO) gene are linked to obesity, but how these SNPs influence resting-state neural activation is unknown. Few brain-imaging studies have investigated the influence of obesity-related SNPs on neural activity, and no study has investigated resting-state connectivity patterns. We tested connectivity within three, main resting-state networks: default mode (DMN), sensorimotor (SMN), and salience network (SN) in 30 male participants, grouped based on genotype for the rs9939609 FTO SNP, as well as punishment and reward sensitivity measured by the Behavioral Inhibition (BIS) and Behavioral Activation System (BAS) questionnaires. Because obesity is associated with anomalies in both systems, we calculated a BIS/BAS ratio (BBr) accounting for features of both scores. A prominence of BIS over BAS (higher BBr) resulted in increased connectivity in frontal and paralimbic regions. These alterations were more evident in the obesity-associated AA genotype, where a high BBr was also associated with increased SN connectivity in dopaminergic circuitries, and in a subnetwork involved in somatosensory integration regarding food. Participants with AA genotype and high BBr, compared to corresponding participants in the TT genotype, also showed greater DMN connectivity in regions involved in the processing of food cues, and in the SMN for regions involved in visceral perception and reward-based learning. These findings suggest that neural connectivity patterns influence the sensitivity toward punishment and reward more closely in the AA carriers, predisposing them to developing obesity. Our work explains a complex interaction between genetics, neural patterns, and behavioral measures in determining the risk for obesity and may help develop individually-tailored strategies for obesity prevention.

Resting-State Brain and the FTO Obesity Risk Allele: Default Mode, Sensorimotor, and Salience Network Connectivity Underlying Different Somatosensory Integration and Reward Processing between Genotypes

PubMed Central

Olivo, Gaia; Wiemerslage, Lyle; Nilsson, Emil K.; Solstrand Dahlberg, Linda; Larsen, Anna L.; Olaya Búcaro, Marcela; Gustafsson, Veronica P.; Titova, Olga E.; Bandstein, Marcus; Larsson, Elna-Marie; Benedict, Christian; Brooks, Samantha J.; Schiöth, Helgi B.

2016-01-01

Single-nucleotide polymorphisms (SNPs) of the fat mass and obesity associated (FTO) gene are linked to obesity, but how these SNPs influence resting-state neural activation is unknown. Few brain-imaging studies have investigated the influence of obesity-related SNPs on neural activity, and no study has investigated resting-state connectivity patterns. We tested connectivity within three, main resting-state networks: default mode (DMN), sensorimotor (SMN), and salience network (SN) in 30 male participants, grouped based on genotype for the rs9939609 FTO SNP, as well as punishment and reward sensitivity measured by the Behavioral Inhibition (BIS) and Behavioral Activation System (BAS) questionnaires. Because obesity is associated with anomalies in both systems, we calculated a BIS/BAS ratio (BBr) accounting for features of both scores. A prominence of BIS over BAS (higher BBr) resulted in increased connectivity in frontal and paralimbic regions. These alterations were more evident in the obesity-associated AA genotype, where a high BBr was also associated with increased SN connectivity in dopaminergic circuitries, and in a subnetwork involved in somatosensory integration regarding food. Participants with AA genotype and high BBr, compared to corresponding participants in the TT genotype, also showed greater DMN connectivity in regions involved in the processing of food cues, and in the SMN for regions involved in visceral perception and reward-based learning. These findings suggest that neural connectivity patterns influence the sensitivity toward punishment and reward more closely in the AA carriers, predisposing them to developing obesity. Our work explains a complex interaction between genetics, neural patterns, and behavioral measures in determining the risk for obesity and may help develop individually-tailored strategies for obesity prevention. PMID:26924971

Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks.

PubMed

Smitha, K A; Akhil Raja, K; Arun, K M; Rajesh, P G; Thomas, Bejoy; Kapilamoorthy, T R; Kesavadas, Chandrasekharan

2017-08-01

The inquisitiveness about what happens in the brain has been there since the beginning of humankind. Functional magnetic resonance imaging is a prominent tool which helps in the non-invasive examination, localisation as well as lateralisation of brain functions such as language, memory, etc. In recent years, there is an apparent shift in the focus of neuroscience research to studies dealing with a brain at 'resting state'. Here the spotlight is on the intrinsic activity within the brain, in the absence of any sensory or cognitive stimulus. The analyses of functional brain connectivity in the state of rest have revealed different resting state networks, which depict specific functions and varied spatial topology. However, different statistical methods have been introduced to study resting state functional magnetic resonance imaging connectivity, yet producing consistent results. In this article, we introduce the concept of resting state functional magnetic resonance imaging in detail, then discuss three most widely used methods for analysis, describe a few of the resting state networks featuring the brain regions, associated cognitive functions and clinical applications of resting state functional magnetic resonance imaging. This review aims to highlight the utility and importance of studying resting state functional magnetic resonance imaging connectivity, underlining its complementary nature to the task-based functional magnetic resonance imaging.

Is Rest Really Rest? Resting State Functional Connectivity during Rest and Motor Task Paradigms.

PubMed

Jurkiewicz, Michael T; Crawley, Adrian P; Mikulis, David J

2018-04-18

Numerous studies have identified the default mode network (DMN) within the brain of healthy individuals, which has been attributed to the ongoing mental activity of the brain during the wakeful resting-state. While engaged during specific resting-state fMRI paradigms, it remains unclear as to whether traditional block-design simple movement fMRI experiments significantly influence the default mode network or other areas. Using blood-oxygen level dependent (BOLD) fMRI we characterized the pattern of functional connectivity in healthy subjects during a resting-state paradigm and compared this to the same resting-state analysis performed on motor task data residual time courses after regressing out the task paradigm. Using seed-voxel analysis to define the DMN, the executive control network (ECN), and sensorimotor, auditory and visual networks, the resting-state analysis of the residual time courses demonstrated reduced functional connectivity in the motor network and reduced connectivity between the insula and the ECN compared to the standard resting-state datasets. Overall, performance of simple self-directed motor tasks does little to change the resting-state functional connectivity across the brain, especially in non-motor areas. This would suggest that previously acquired fMRI studies incorporating simple block-design motor tasks could be mined retrospectively for assessment of the resting-state connectivity.

Frequency-Dependent Modulation of Regional Synchrony in the Human Brain by Eyes Open and Eyes Closed Resting-States.

PubMed

Song, Xiaopeng; Zhou, Shuqin; Zhang, Yi; Liu, Yijun; Zhu, Huaiqiu; Gao, Jia-Hong

2015-01-01

The eyes-open (EO) and eyes-closed (EC) states have differential effects on BOLD-fMRI signal dynamics, affecting both the BOLD oscillation frequency of a single voxel and the regional homogeneity (ReHo) of several neighboring voxels. To explore how the two resting-states modulate the local synchrony through different frequency bands, we decomposed the time series of each voxel into several components that fell into distinct frequency bands. The ReHo in each of the bands was calculated and compared between the EO and EC conditions. The cross-voxel correlations between the mean frequency and the overall ReHo of each voxel's original BOLD series in different brain areas were also calculated and compared between the two states. Compared with the EC state, ReHo decreased with EO in a wide frequency band of 0.01-0.25 Hz in the bilateral thalamus, sensorimotor network, and superior temporal gyrus, while ReHo increased significantly in the band of 0-0.01 Hz in the primary visual cortex, and in a higher frequency band of 0.02-0.1 Hz in the higher order visual areas. The cross-voxel correlations between the frequency and overall ReHo were negative in all the brain areas but varied from region to region. These correlations were stronger with EO in the visual network and the default mode network. Our results suggested that different frequency bands of ReHo showed different sensitivity to the modulation of EO-EC states. The better spatial consistency between the frequency and overall ReHo maps indicated that the brain might adopt a stricter frequency-dependent configuration with EO than with EC.

Rest and treatment/rehabilitation following sport-related concussion: a systematic review.

PubMed

Schneider, Kathryn J; Leddy, John J; Guskiewicz, Kevin M; Seifert, Tad; McCrea, Michael; Silverberg, Noah D; Feddermann-Demont, Nina; Iverson, Grant L; Hayden, Alix; Makdissi, Michael

2017-06-01

The objective of this systematic review was to evaluate the evidence regarding rest and active treatment/rehabilitation following sport-related concussion (SRC). Systematic review. MEDLINE (OVID), CINAHL (EbscoHost), PsycInfo (OVID), Cochrane Central Register of Controlled Trials (OVID), SPORTDiscus (EbscoHost), EMBASE (OVID) and Proquest DissertationsandTheses Global (Proquest) were searched systematically. Studies were included if they met the following criteria: (1) original research; (2) reported SRC as the diagnosis; and (3) evaluated the effect of rest or active treatment/rehabilitation. Review articles were excluded. Twenty-eight studies met the inclusion criteria (9 regarding the effects of rest and 19 evaluating active treatment). The methodological quality of the literature was limited; only five randomised controlled trials (RCTs) met the eligibility criteria. Those RCTs included rest, cervical and vestibular rehabilitation, subsymptom threshold aerobic exercise and multifaceted collaborative care. A brief period (24-48 hours) of cognitive and physical rest is appropriate for most patients. Following this, patients should be encouraged to gradually increase activity. The exact amount and duration of rest are not yet well defined and require further investigation. The data support interventions including cervical and vestibular rehabilitation and multifaceted collaborative care. Closely monitored subsymptom threshold, submaximal exercise may be of benefit. PROSPERO 2016:CRD42016039570. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Task vs. rest-different network configurations between the coactivation and the resting-state brain networks.

PubMed

Di, Xin; Gohel, Suril; Kim, Eun H; Biswal, Bharat B

2013-01-01

There is a growing interest in studies of human brain networks using resting-state functional magnetic resonance imaging (fMRI). However, it is unclear whether and how brain networks measured during the resting-state exhibit comparable properties to brain networks during task performance. In the present study, we investigated meta-analytic coactivation patterns among brain regions based upon published neuroimaging studies, and compared the coactivation network configurations with those in the resting-state network. The strength of resting-state functional connectivity between two regions were strongly correlated with the coactivation strength. However, the coactivation network showed greater global efficiency, smaller mean clustering coefficient, and lower modularity compared with the resting-state network, which suggest a more efficient global information transmission and between system integrations during task performing. Hub shifts were also observed within the thalamus and the left inferior temporal cortex. The thalamus and the left inferior temporal cortex exhibited higher and lower degrees, respectively in the coactivation network compared with the resting-state network. These results shed light regarding the reconfiguration of the brain networks between task and resting-state conditions, and highlight the role of the thalamus in change of network configurations in task vs. rest.

The alteration of spontaneous low frequency oscillations caused by acute electromagnetic fields exposure.

PubMed

Lv, Bin; Chen, Zhiye; Wu, Tongning; Shao, Qing; Yan, Duo; Ma, Lin; Lu, Ke; Xie, Yi

2014-02-01

The motivation of this study is to evaluate the possible alteration of regional resting state brain activity induced by the acute radiofrequency electromagnetic field (RF-EMF) exposure (30min) of Long Term Evolution (LTE) signal. We designed a controllable near-field LTE RF-EMF exposure environment. Eighteen subjects participated in a double-blind, crossover, randomized and counterbalanced experiment including two sessions (real and sham exposure). The radiation source was close to the right ear. Then the resting state fMRI signals of human brain were collected before and after the exposure in both sessions. We measured the amplitude of low frequency fluctuation (ALFF) and fractional ALFF (fALFF) to characterize the spontaneous brain activity. We found the decreased ALFF value around in left superior temporal gyrus, left middle temporal gyrus, right superior temporal gyrus, right medial frontal gyrus and right paracentral lobule after the real exposure. And the decreased fALFF value was also detected in right medial frontal gyrus and right paracentral lobule. The study provided the evidences that 30min LTE RF-EMF exposure modulated the spontaneous low frequency fluctuations in some brain regions. With resting state fMRI, we found the alteration of spontaneous low frequency fluctuations induced by the acute LTE RF-EMF exposure. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Differential Resting-State Functional Connectivity of Striatal Subregions in Bipolar Depression and Hypomania

PubMed Central

Altinay, Murat I.; Hulvershorn, Leslie A.; Karne, Harish; Beall, Erik B.

2016-01-01

Abstract Bipolar disorder (BP) is characterized by periods of depression (BPD) and (hypo)mania (BPM), but the underlying state-related brain circuit abnormalities are not fully understood. Striatal functional activation and connectivity abnormalities have been noted in BP, but consistent findings have not been reported. To further elucidate striatal abnormalities in different BP states, this study investigated differences in resting-state functional connectivity of six striatal subregions in BPD, BPM, and healthy control (HC) subjects. Ninety medication-free subjects (30 BPD, 30 BPM, and 30 HC), closely matched for age and gender, were scanned using 3T functional magnetic resonance imaging (fMRI) acquired at resting state. Correlations of low-frequency blood oxygen level dependent signal fluctuations for six previously described striatal subregions were used to obtain connectivity maps of each subregion. Using a factorial design, main effects for differences between groups were obtained and post hoc pairwise group comparisons performed. BPD showed increased connectivity of the dorsal caudal putamen with somatosensory areas such as the insula and temporal gyrus. BPM group showed unique increased connectivity between left dorsal caudate and midbrain regions, as well as increased connectivity between ventral striatum inferior and thalamus. In addition, both BPD and BPM exhibited widespread functional connectivity abnormalities between striatal subregions and frontal cortices, limbic regions, and midbrain structures. In summary, BPD exhibited connectivity abnormalities of associative and somatosensory subregions of the putamen, while BPM exhibited connectivity abnormalities of associative and limbic caudate. Most other striatal subregion connectivity abnormalities were common to both groups and may be trait related. PMID:26824737

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities.

PubMed

Sik, Hin Hung; Gao, Junling; Fan, Jicong; Wu, Bonnie Wai Yan; Leung, Hang Kin; Hung, Yeung Sam

2017-05-10

In both the East and West, traditional teachings say that the mind and heart are somehow closely correlated, especially during spiritual practice. One difficulty in proving this objectively is that the natures of brain and heart activities are quite different. In this paper, we propose a methodology that uses wavelet entropy to measure the chaotic levels of both electroencephalogram (EEG) and electrocardiogram (ECG) data and show how this may be used to explore the potential coordination between the mind and heart under different experimental conditions. Furthermore, Statistical Parametric Mapping (SPM) was used to identify the brain regions in which the EEG wavelet entropy was the most affected by the experimental conditions. As an illustration, the EEG and ECG were recorded under two different conditions (normal rest and mindful breathing) at the beginning of an 8-week standard Mindfulness-based Stress Reduction (MBSR) training course (pretest) and after the course (posttest). Using the proposed method, the results consistently showed that the wavelet entropy of the brain EEG decreased during the MBSR mindful breathing state as compared to that during the closed-eye resting state. Similarly, a lower wavelet entropy of heartrate was found during MBSR mindful breathing. However, no difference in wavelet entropy during MBSR mindful breathing was found between the pretest and posttest. No correlation was observed between the entropy of brain waves and the entropy of heartrate during normal rest in all participants, whereas a significant correlation was observed during MBSR mindful breathing. Additionally, the most well-correlated brain regions were located in the central areas of the brain. This study provides a methodology for the establishment of evidence that mindfulness practice (i.e., mindful breathing) may increase the coordination between mind and heart activities.

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

PubMed Central

Sik, Hin Hung; Gao, Junling; Fan, Jicong; Wu, Bonnie Wai Yan; Leung, Hang Kin; Hung, Yeung Sam

2017-01-01

In both the East and West, traditional teachings say that the mind and heart are somehow closely correlated, especially during spiritual practice. One difficulty in proving this objectively is that the natures of brain and heart activities are quite different. In this paper, we propose a methodology that uses wavelet entropy to measure the chaotic levels of both electroencephalogram (EEG) and electrocardiogram (ECG) data and show how this may be used to explore the potential coordination between the mind and heart under different experimental conditions. Furthermore, Statistical Parametric Mapping (SPM) was used to identify the brain regions in which the EEG wavelet entropy was the most affected by the experimental conditions. As an illustration, the EEG and ECG were recorded under two different conditions (normal rest and mindful breathing) at the beginning of an 8-week standard Mindfulness-based Stress Reduction (MBSR) training course (pretest) and after the course (posttest). Using the proposed method, the results consistently showed that the wavelet entropy of the brain EEG decreased during the MBSR mindful breathing state as compared to that during the closed-eye resting state. Similarly, a lower wavelet entropy of heartrate was found during MBSR mindful breathing. However, no difference in wavelet entropy during MBSR mindful breathing was found between the pretest and posttest. No correlation was observed between the entropy of brain waves and the entropy of heartrate during normal rest in all participants, whereas a significant correlation was observed during MBSR mindful breathing. Additionally, the most well-correlated brain regions were located in the central areas of the brain. This study provides a methodology for the establishment of evidence that mindfulness practice (i.e., mindful breathing) may increase the coordination between mind and heart activities. PMID:28518101

Resting states are resting traits--an FMRI study of sex differences and menstrual cycle effects in resting state cognitive control networks.

PubMed

Hjelmervik, Helene; Hausmann, Markus; Osnes, Berge; Westerhausen, René; Specht, Karsten

2014-01-01

To what degree resting state fMRI is stable or susceptible to internal mind states of the individual is currently an issue of debate. To address this issue, the present study focuses on sex differences and investigates whether resting state fMRI is stable in men and women or changes within relative short-term periods (i.e., across the menstrual cycle). Due to the fact that we recently reported menstrual cycle effects on cognitive control based on data collected during the same sessions, the current study is particularly interested in fronto-parietal resting state networks. Resting state fMRI was measured in sixteen women during three different cycle phases (menstrual, follicular, and luteal). Fifteen men underwent three sessions in corresponding time intervals. We used independent component analysis to identify four fronto-parietal networks. The results showed sex differences in two of these networks with women exhibiting higher functional connectivity in general, including the prefrontal cortex. Menstrual cycle effects on resting states were non-existent. It is concluded that sex differences in resting state fMRI might reflect sexual dimorphisms in the brain rather than transitory activating effects of sex hormones on the functional connectivity in the resting brain.

Resting States Are Resting Traits – An fMRI Study of Sex Differences and Menstrual Cycle Effects in Resting State Cognitive Control Networks

PubMed Central

Hjelmervik, Helene; Hausmann, Markus; Osnes, Berge; Westerhausen, René; Specht, Karsten

2014-01-01

To what degree resting state fMRI is stable or susceptible to internal mind states of the individual is currently an issue of debate. To address this issue, the present study focuses on sex differences and investigates whether resting state fMRI is stable in men and women or changes within relative short-term periods (i.e., across the menstrual cycle). Due to the fact that we recently reported menstrual cycle effects on cognitive control based on data collected during the same sessions, the current study is particularly interested in fronto-parietal resting state networks. Resting state fMRI was measured in sixteen women during three different cycle phases (menstrual, follicular, and luteal). Fifteen men underwent three sessions in corresponding time intervals. We used independent component analysis to identify four fronto-parietal networks. The results showed sex differences in two of these networks with women exhibiting higher functional connectivity in general, including the prefrontal cortex. Menstrual cycle effects on resting states were non-existent. It is concluded that sex differences in resting state fMRI might reflect sexual dimorphisms in the brain rather than transitory activating effects of sex hormones on the functional connectivity in the resting brain. PMID:25057823

Differentiating closed-loop cortical intention from rest: building an asynchronous electrocorticographic BCI.

PubMed

Williams, Jordan J; Rouse, Adam G; Thongpang, Sanitta; Williams, Justin C; Moran, Daniel W

2013-08-01

Recent experiments have shown that electrocorticography (ECoG) can provide robust control signals for a brain-computer interface (BCI). Strategies that attempt to adapt a BCI control algorithm by learning from past trials often assume that the subject is attending to each training trial. Likewise, automatic disabling of movement control would be desirable during resting periods when random brain fluctuations might cause unintended movements of a device. To this end, our goal was to identify ECoG differences that arise between periods of active BCI use and rest. We examined spectral differences in multi-channel, epidural micro-ECoG signals recorded from non-human primates when rest periods were interleaved between blocks of an active BCI control task. Post-hoc analyses demonstrated that these states can be decoded accurately on both a trial-by-trial and real-time basis, and this discriminability remains robust over a period of weeks. In addition, high gamma frequencies showed greater modulation with desired movement direction, while lower frequency components demonstrated greater amplitude differences between task and rest periods, suggesting possible specialized BCI roles for these frequencies. The results presented here provide valuable insight into the neurophysiology of BCI control as well as important considerations toward the design of an asynchronous BCI system.

Differentiating closed-loop cortical intention from rest: building an asynchronous electrocorticographic BCI

NASA Astrophysics Data System (ADS)

Williams, Jordan J.; Rouse, Adam G.; Thongpang, Sanitta; Williams, Justin C.; Moran, Daniel W.

2013-08-01

Objective. Recent experiments have shown that electrocorticography (ECoG) can provide robust control signals for a brain-computer interface (BCI). Strategies that attempt to adapt a BCI control algorithm by learning from past trials often assume that the subject is attending to each training trial. Likewise, automatic disabling of movement control would be desirable during resting periods when random brain fluctuations might cause unintended movements of a device. To this end, our goal was to identify ECoG differences that arise between periods of active BCI use and rest. Approach. We examined spectral differences in multi-channel, epidural micro-ECoG signals recorded from non-human primates when rest periods were interleaved between blocks of an active BCI control task. Main Results. Post-hoc analyses demonstrated that these states can be decoded accurately on both a trial-by-trial and real-time basis, and this discriminability remains robust over a period of weeks. In addition, high gamma frequencies showed greater modulation with desired movement direction, while lower frequency components demonstrated greater amplitude differences between task and rest periods, suggesting possible specialized BCI roles for these frequencies. Significance. The results presented here provide valuable insight into the neurophysiology of BCI control as well as important considerations toward the design of an asynchronous BCI system.

Closing the Skills Gap: A Comprehensive Work-Based Learning Model Developed through Partnerships among Manufacturers, Community Colleges and High Schools in Northeast Ohio

ERIC Educational Resources Information Center

Robinson, Terrence S.

2017-01-01

Northeast Ohio is similar to the rest of the United States in that there is a rise in the need for the products that advanced manufacturers supply (Center for American Progress, 2013). However, advanced manufacturers in Northeast Ohio are unable to find the technically skilled workers to fill the jobs that are currently available in the workforce.…

Unified Bayesian Estimator of EEG Reference at Infinity: rREST (Regularized Reference Electrode Standardization Technique).

PubMed

Hu, Shiang; Yao, Dezhong; Valdes-Sosa, Pedro A

2018-01-01

The choice of reference for the electroencephalogram (EEG) is a long-lasting unsolved issue resulting in inconsistent usages and endless debates. Currently, both the average reference (AR) and the reference electrode standardization technique (REST) are two primary, apparently irreconcilable contenders. We propose a theoretical framework to resolve this reference issue by formulating both (a) estimation of potentials at infinity, and (b) determination of the reference, as a unified Bayesian linear inverse problem, which can be solved by maximum a posterior estimation. We find that AR and REST are very particular cases of this unified framework: AR results from biophysically non-informative prior; while REST utilizes the prior based on the EEG generative model. To allow for simultaneous denoising and reference estimation, we develop the regularized versions of AR and REST, named rAR and rREST, respectively. Both depend on a regularization parameter that is the noise to signal variance ratio. Traditional and new estimators are evaluated with this framework, by both simulations and analysis of real resting EEGs. Toward this end, we leverage the MRI and EEG data from 89 subjects which participated in the Cuban Human Brain Mapping Project. Generated artificial EEGs-with a known ground truth, show that relative error in estimating the EEG potentials at infinity is lowest for rREST. It also reveals that realistic volume conductor models improve the performances of REST and rREST. Importantly, for practical applications, it is shown that an average lead field gives the results comparable to the individual lead field. Finally, it is shown that the selection of the regularization parameter with Generalized Cross-Validation (GCV) is close to the "oracle" choice based on the ground truth. When evaluated with the real 89 resting state EEGs, rREST consistently yields the lowest GCV. This study provides a novel perspective to the EEG reference problem by means of a unified inverse solution framework. It may allow additional principled theoretical formulations and numerical evaluation of performance.

The 10 Hz Frequency: A Fulcrum For Transitional Brain States.

PubMed

Garcia-Rill, E; D'Onofrio, S; Luster, B; Mahaffey, S; Urbano, F J; Phillips, C

A 10 Hz rhythm is present in the occipital cortex when the eyes are closed (alpha waves), in the precentral cortex at rest ( mu rhythm), in the superior and middle temporal lobe ( tau rhythm), in the inferior olive (projection to cerebellar cortex), and in physiological tremor (underlying all voluntary movement). These are all considered resting rhythms in the waking brain which are "replaced" by higher frequency activity with sensorimotor stimulation. That is, the 10 Hz frequency fulcrum is replaced on the one hand by lower frequencies during sleep, or on the other hand by higher frequencies during volition and cognition. The 10 Hz frequency fulcrum is proposed as the natural frequency of the brain during quiet waking, but is replaced by higher frequencies capable of permitting more complex functions, or by lower frequencies during sleep and inactivity. At the center of the transition shifts to and from the resting rhythm is the reticular activating system, a phylogenetically preserved area of the brain essential for preconscious awareness.

The 10 Hz Frequency: A Fulcrum For Transitional Brain States

PubMed Central

Garcia-Rill, E.; D’Onofrio, S.; Luster, B.; Mahaffey, S.; Urbano, F. J.; Phillips, C.

2016-01-01

A 10 Hz rhythm is present in the occipital cortex when the eyes are closed (alpha waves), in the precentral cortex at rest (mu rhythm), in the superior and middle temporal lobe (tau rhythm), in the inferior olive (projection to cerebellar cortex), and in physiological tremor (underlying all voluntary movement). These are all considered resting rhythms in the waking brain which are “replaced” by higher frequency activity with sensorimotor stimulation. That is, the 10 Hz frequency fulcrum is replaced on the one hand by lower frequencies during sleep, or on the other hand by higher frequencies during volition and cognition. The 10 Hz frequency fulcrum is proposed as the natural frequency of the brain during quiet waking, but is replaced by higher frequencies capable of permitting more complex functions, or by lower frequencies during sleep and inactivity. At the center of the transition shifts to and from the resting rhythm is the reticular activating system, a phylogenetically preserved area of the brain essential for preconscious awareness. PMID:27547831

Information Flow Between Resting-State Networks.

PubMed

Diez, Ibai; Erramuzpe, Asier; Escudero, Iñaki; Mateos, Beatriz; Cabrera, Alberto; Marinazzo, Daniele; Sanz-Arigita, Ernesto J; Stramaglia, Sebastiano; Cortes Diaz, Jesus M

2015-11-01

The resting brain dynamics self-organize into a finite number of correlated patterns known as resting-state networks (RSNs). It is well known that techniques such as independent component analysis can separate the brain activity at rest to provide such RSNs, but the specific pattern of interaction between RSNs is not yet fully understood. To this aim, we propose here a novel method to compute the information flow (IF) between different RSNs from resting-state magnetic resonance imaging. After hemodynamic response function blind deconvolution of all voxel signals, and under the hypothesis that RSNs define regions of interest, our method first uses principal component analysis to reduce dimensionality in each RSN to next compute IF (estimated here in terms of transfer entropy) between the different RSNs by systematically increasing k (the number of principal components used in the calculation). When k=1, this method is equivalent to computing IF using the average of all voxel activities in each RSN. For k≥1, our method calculates the k multivariate IF between the different RSNs. We find that the average IF among RSNs is dimension dependent, increasing from k=1 (i.e., the average voxel activity) up to a maximum occurring at k=5 and to finally decay to zero for k≥10. This suggests that a small number of components (close to five) is sufficient to describe the IF pattern between RSNs. Our method--addressing differences in IF between RSNs for any generic data--can be used for group comparison in health or disease. To illustrate this, we have calculated the inter-RSN IF in a data set of Alzheimer's disease (AD) to find that the most significant differences between AD and controls occurred for k=2, in addition to AD showing increased IF w.r.t. The spatial localization of the k=2 component, within RSNs, allows the characterization of IF differences between AD and controls.

Task vs. rest—different network configurations between the coactivation and the resting-state brain networks

PubMed Central

Di, Xin; Gohel, Suril; Kim, Eun H.; Biswal, Bharat B.

2013-01-01

There is a growing interest in studies of human brain networks using resting-state functional magnetic resonance imaging (fMRI). However, it is unclear whether and how brain networks measured during the resting-state exhibit comparable properties to brain networks during task performance. In the present study, we investigated meta-analytic coactivation patterns among brain regions based upon published neuroimaging studies, and compared the coactivation network configurations with those in the resting-state network. The strength of resting-state functional connectivity between two regions were strongly correlated with the coactivation strength. However, the coactivation network showed greater global efficiency, smaller mean clustering coefficient, and lower modularity compared with the resting-state network, which suggest a more efficient global information transmission and between system integrations during task performing. Hub shifts were also observed within the thalamus and the left inferior temporal cortex. The thalamus and the left inferior temporal cortex exhibited higher and lower degrees, respectively in the coactivation network compared with the resting-state network. These results shed light regarding the reconfiguration of the brain networks between task and resting-state conditions, and highlight the role of the thalamus in change of network configurations in task vs. rest. PMID:24062654

Beta oscillations in freely moving Parkinson's subjects are attenuated during deep brain stimulation.

PubMed

Quinn, Emma J; Blumenfeld, Zack; Velisar, Anca; Koop, Mandy Miller; Shreve, Lauren A; Trager, Megan H; Hill, Bruce C; Kilbane, Camilla; Henderson, Jaimie M; Brontë-Stewart, Helen

2015-11-01

Investigations into the effect of deep brain stimulation (DBS) on subthalamic (STN) beta (13-30 Hz) oscillations have been performed in the perioperative period with the subject tethered to equipment. Using an embedded sensing neurostimulator, this study investigated whether beta power was similar in different resting postures and during forward walking in freely moving subjects with Parkinson's disease (PD) and whether STN DBS attenuated beta power in a voltage-dependent manner. Subthalamic local field potentials were recorded from the DBS lead, using a sensing neurostimulator (Activa(®) PC+S, Medtronic, Inc., Food and Drug Administration- Investigational Device Exemption (IDE)-, institutional review board-approved) from 15 PD subjects (30 STNs) off medication during lying, sitting, and standing, during forward walking, and during randomized periods of 140 Hz DBS at 0 V, 1 V, and 2.5/3 V. Continuous video, limb angular velocity, and forearm electromyography recordings were synchronized with neural recordings. Data were parsed to avoid any movement or electrical artifact during resting states. Beta power was similar during lying, sitting, and standing (P = 0.077, n = 28) and during forward walking compared with the averaged resting state (P = 0.466, n = 24), although akinetic rigid PD subjects tended to exhibit decreased beta power when walking. Deep brain stimulation at 3 V and at 1 V attenuated beta power compared with 0 V (P < 0.003, n = 14), and this was voltage dependent (P < 0.001). Beta power was conserved during resting and forward walking states and was attenuated in a voltage-dependent manner during 140-Hz DBS. Phenotype may be an important consideration if this is used for closed-loop DBS. © 2015 International Parkinson and Movement Disorder Society.

Resting state alpha frequency is associated with menstrual cycle phase, estradiol and use of oral contraceptives.

PubMed

Brötzner, Christina P; Klimesch, Wolfgang; Doppelmayr, Michael; Zauner, Andrea; Kerschbaum, Hubert H

2014-08-19

Ongoing intrinsic brain activity in resting, but awake humans is dominated by alpha oscillations. In human, individual alpha frequency (IAF) is associated with cognitive performance. Noticeable, performance in cognitive and emotional tasks in women is associated with menstrual cycle phase and sex hormone levels, respectively. In the present study, we correlated frequency of alpha oscillation in resting women with menstrual cycle phase, sex hormone level, or use of oral contraceptives. Electroencephalogram (EEG) was recorded from 57 women (aged 24.07 ± 3.67 years) having a natural menstrual cycle as well as from 57 women (aged 22.37 ± 2.20 years) using oral contraceptives while they sat in an armchair with eyes closed. Alpha frequency was related to the menstrual cycle phase. Luteal women showed highest and late follicular women showed lowest IAF or center frequency. Furthermore, IAF as well as center frequency correlated negatively with endogenous estradiol level, but did not reveal an association with endogenous progesterone. Women using oral contraceptives showed an alpha frequency similar to women in the early follicular phase. We suggest that endogenous estradiol modulate resting alpha frequency. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Local activity determines functional connectivity in the resting human brain: a simultaneous FDG-PET/fMRI study.

PubMed

Riedl, Valentin; Bienkowska, Katarzyna; Strobel, Carola; Tahmasian, Masoud; Grimmer, Timo; Förster, Stefan; Friston, Karl J; Sorg, Christian; Drzezga, Alexander

2014-04-30

Over the last decade, synchronized resting-state fluctuations of blood oxygenation level-dependent (BOLD) signals between remote brain areas [so-called BOLD resting-state functional connectivity (rs-FC)] have gained enormous relevance in systems and clinical neuroscience. However, the neural underpinnings of rs-FC are still incompletely understood. Using simultaneous positron emission tomography/magnetic resonance imaging we here directly investigated the relationship between rs-FC and local neuronal activity in humans. Computational models suggest a mechanistic link between the dynamics of local neuronal activity and the functional coupling among distributed brain regions. Therefore, we hypothesized that the local activity (LA) of a region at rest determines its rs-FC. To test this hypothesis, we simultaneously measured both LA (glucose metabolism) and rs-FC (via synchronized BOLD fluctuations) during conditions of eyes closed or eyes open. During eyes open, LA increased in the visual system, and the salience network (i.e., cingulate and insular cortices) and the pattern of elevated LA coincided almost exactly with the spatial pattern of increased rs-FC. Specifically, the voxelwise regional profile of LA in these areas strongly correlated with the regional pattern of rs-FC among the same regions (e.g., LA in primary visual cortex accounts for ∼ 50%, and LA in anterior cingulate accounts for ∼ 20% of rs-FC with the visual system). These data provide the first direct evidence in humans that local neuronal activity determines BOLD FC at rest. Beyond its relevance for the neuronal basis of coherent BOLD signal fluctuations, our procedure may translate into clinical research particularly to investigate potentially aberrant links between local dynamics and remote functional coupling in patients with neuropsychiatric disorders.

Age-related Multiscale Changes in Brain Signal Variability in Pre-task versus Post-task Resting-state EEG.

PubMed

Wang, Hongye; McIntosh, Anthony R; Kovacevic, Natasa; Karachalios, Maria; Protzner, Andrea B

2016-07-01

Recent empirical work suggests that, during healthy aging, the variability of network dynamics changes during task performance. Such variability appears to reflect the spontaneous formation and dissolution of different functional networks. We sought to extend these observations into resting-state dynamics. We recorded EEG in young, middle-aged, and older adults during a "rest-task-rest" design and investigated if aging modifies the interaction between resting-state activity and external stimulus-induced activity. Using multiscale entropy as our measure of variability, we found that, with increasing age, resting-state dynamics shifts from distributed to more local neural processing, especially at posterior sources. In the young group, resting-state dynamics also changed from pre- to post-task, where fine-scale entropy increased in task-positive regions and coarse-scale entropy increased in the posterior cingulate, a key region associated with the default mode network. Lastly, pre- and post-task resting-state dynamics were linked to performance on the intervening task for all age groups, but this relationship became weaker with increasing age. Our results suggest that age-related changes in resting-state dynamics occur across different spatial and temporal scales and have consequences for information processing capacity.

The Integrity of the Corpus Callosum Mitigates the Impact of Blood Pressure on the Ventral Attention Network and Information Processing Speed in Healthy Adults

PubMed Central

Wong, Nichol M. L.; Ma, Ernie Po-Wing; Lee, Tatia M. C.

2017-01-01

Hypertension is a risk factor for cognitive impairment in older age. However, evidence of the neural basis of the relationship between the deterioration of cognitive function and elevated blood pressure is sparse. Based on previous research, we speculate that variations in brain connectivity are closely related to elevated blood pressure even before the onset of clinical conditions and apparent cognitive decline in individuals over 60 years of age. Forty cognitively healthy adults were recruited. Each received a blood pressure test before and after the cognitive assessment in various domains. Diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rsfMRI) data were collected. Our findings confirm that elevated blood pressure is associated with brain connectivity variations in cognitively healthy individuals. The integrity of the splenium of the corpus callosum is closely related to individual differences in systolic blood pressure. In particular, elevated systolic blood pressure is related to resting-state ventral attention network (VAN) and information processing speed. Serial mediation analyses have further revealed that lower integrity of the splenium statistically predicts elevated systolic blood pressure, which in turn predicts weakened functional connectivity (FC) within the VAN and eventually poorer processing speed. The current study sheds light on how neural correlates are involved in the impact of elevated blood pressure on cognitive functioning. PMID:28484386

Comparison of connectivity analyses for resting state EEG data

NASA Astrophysics Data System (ADS)

Olejarczyk, Elzbieta; Marzetti, Laura; Pizzella, Vittorio; Zappasodi, Filippo

2017-06-01

Objective. In the present work, a nonlinear measure (transfer entropy, TE) was used in a multivariate approach for the analysis of effective connectivity in high density resting state EEG data in eyes open and eyes closed. Advantages of the multivariate approach in comparison to the bivariate one were tested. Moreover, the multivariate TE was compared to an effective linear measure, i.e. directed transfer function (DTF). Finally, the existence of a relationship between the information transfer and the level of brain synchronization as measured by phase synchronization value (PLV) was investigated. Approach. The comparison between the connectivity measures, i.e. bivariate versus multivariate TE, TE versus DTF, TE versus PLV, was performed by means of statistical analysis of indexes based on graph theory. Main results. The multivariate approach is less sensitive to false indirect connections with respect to the bivariate estimates. The multivariate TE differentiated better between eyes closed and eyes open conditions compared to DTF. Moreover, the multivariate TE evidenced non-linear phenomena in information transfer, which are not evidenced by the use of DTF. We also showed that the target of information flow, in particular the frontal region, is an area of greater brain synchronization. Significance. Comparison of different connectivity analysis methods pointed to the advantages of nonlinear methods, and indicated a relationship existing between the flow of information and the level of synchronization of the brain.

On the invariance of EEG-based signatures of individuality with application in biometric identification.

PubMed

Yunqi Wang; Najafizadeh, Laleh

2016-08-01

One of the main challenges in EEG-based biometric systems is to extract reliable signatures of individuality from recorded EEG data that are also invariant against time. In this paper, we investigate the invariability of features that are extracted based on the spatial distribution of the spectral power of EEG data corresponding to 2-second eyes-closed resting-state (ECRS) recording, in different scenarios. Eyes-closed resting-state EEG signals in 4 healthy adults are recorded in two different sessions with an interval of at least one week between sessions. The performance in terms of correct recognition rate (CRR) is examined when the training and testing datasets are chosen from the same recording session, and when the training and testing datasets are chosen from different sessions. It is shown that an CRR of 92% can be achieved based on the proposed features when the training and testing datasets are taken from different sessions. To reduce the number of recording channels, principal component analysis (PCA) is also employed to identify channels that carry the most discriminatory information across individuals. High CRR is obtained based on the data from channels mostly covering the occipital region. The results suggest that features based on the spatial distribution of the spectral power of the short-time (e.g. 2 seconds) ECRS recordings can have great potentials in EEG-based biometric identification systems.

Intermediate closed state for glycine receptor function revealed by cysteine cross-linking.

PubMed

Prevost, Marie S; Moraga-Cid, Gustavo; Van Renterghem, Catherine; Edelstein, Stuart J; Changeux, Jean-Pierre; Corringer, Pierre-Jean

2013-10-15

Pentameric ligand-gated ion channels (pLGICs) mediate signal transmission by coupling the binding of extracellular ligands to the opening of their ion channel. Agonist binding elicits activation and desensitization of pLGICs, through several conformational states, that are, thus far, incompletely characterized at the structural level. We previously reported for GLIC, a prokaryotic pLGIC, that cross-linking of a pair of cysteines at both sides of the extracellular and transmembrane domain interface stabilizes a locally closed (LC) X-ray structure. Here, we introduced the homologous pair of cysteines on the human α1 glycine receptor. We show by electrophysiology that cysteine cross-linking produces a gain-of-function phenotype characterized by concomitant constitutive openings, increased agonist potency, and equalization of efficacies of full and partial agonists. However, it also produces a reduction of maximal currents at saturating agonist concentrations without change of the unitary channel conductance, an effect reversed by the positive allosteric modulator propofol. The cross-linking thus favors a unique closed state distinct from the resting and longest-lived desensitized states. Fitting the data according to a three-state allosteric model suggests that it could correspond to a LC conformation. Its plausible assignment to a gating intermediate or a fast-desensitized state is discussed. Overall, our data show that relative movement of two loops at the extracellular-transmembrane interface accompanies orthosteric agonist-mediated gating.

Resting state brain dynamics and its transients: a combined TMS-EEG study.

PubMed

Bonnard, Mireille; Chen, Sophie; Gaychet, Jérôme; Carrere, Marcel; Woodman, Marmaduke; Giusiano, Bernard; Jirsa, Viktor

2016-08-04

The brain at rest exhibits a spatio-temporally rich dynamics which adheres to systematic behaviours that persist in task paradigms but appear altered in disease. Despite this hypothesis, many rest state paradigms do not act directly upon the rest state and therefore cannot confirm hypotheses about its mechanisms. To address this challenge, we combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to study brain's relaxation toward rest following a transient perturbation. Specifically, TMS targeted either the medial prefrontal cortex (MPFC), i.e. part of the Default Mode Network (DMN) or the superior parietal lobule (SPL), involved in the Dorsal Attention Network. TMS was triggered by a given brain state, namely an increase in occipital alpha rhythm power. Following the initial TMS-Evoked Potential, TMS at MPFC enhances the induced occipital alpha rhythm, called Event Related Synchronisation, with a longer transient lifetime than TMS at SPL, and a higher amplitude. Our findings show a strong coupling between MPFC and the occipital alpha power. Although the rest state is organized around a core of resting state networks, the DMN functionally takes a special role among these resting state networks.

Stability of whole brain and regional network topology within and between resting and cognitive states.

PubMed

Rzucidlo, Justyna K; Roseman, Paige L; Laurienti, Paul J; Dagenbach, Dale

2013-01-01

Graph-theory based analyses of resting state functional Magnetic Resonance Imaging (fMRI) data have been used to map the network organization of the brain. While numerous analyses of resting state brain organization exist, many questions remain unexplored. The present study examines the stability of findings based on this approach over repeated resting state and working memory state sessions within the same individuals. This allows assessment of stability of network topology within the same state for both rest and working memory, and between rest and working memory as well. fMRI scans were performed on five participants while at rest and while performing the 2-back working memory task five times each, with task state alternating while they were in the scanner. Voxel-based whole brain network analyses were performed on the resulting data along with analyses of functional connectivity in regions associated with resting state and working memory. Network topology was fairly stable across repeated sessions of the same task, but varied significantly between rest and working memory. In the whole brain analysis, local efficiency, Eloc, differed significantly between rest and working memory. Analyses of network statistics for the precuneus and dorsolateral prefrontal cortex revealed significant differences in degree as a function of task state for both regions and in local efficiency for the precuneus. Conversely, no significant differences were observed across repeated sessions of the same state. These findings suggest that network topology is fairly stable within individuals across time for the same state, but also fluid between states. Whole brain voxel-based network analyses may prove to be a valuable tool for exploring how functional connectivity changes in response to task demands.

Parkinsonian Rest Tremor Is Associated With Modulations of Subthalamic High-Frequency Oscillations.

PubMed

Hirschmann, Jan; Butz, Markus; Hartmann, Christian J; Hoogenboom, Nienke; Özkurt, Tolga E; Vesper, Jan; Wojtecki, Lars; Schnitzler, Alfons

2016-10-01

High frequency oscillations (>200 Hz) have been observed in the basal ganglia of PD patients and were shown to be modulated by the administration of levodopa and voluntary movement. The objective of this study was to test whether the power of high-frequency oscillations in the STN is associated with spontaneous manifestation of parkinsonian rest tremor. The electromyogram of both forearms and local field potentials from the STN were recorded in 11 PD patients (10 men, age 58 [9.4] years, disease duration 9.2 [6.3] years). Patients were recorded at rest and while performing repetitive hand movements before and after levodopa intake. High-frequency oscillation power was compared across epochs containing rest tremor, tremor-free rest, or voluntary movement and related to the tremor cycle. We observed prominent slow (200-300 Hz) and fast (300-400 Hz) high-frequency oscillations. The ratio between slow and fast high-frequency oscillation power increased when tremor became manifest. This increase was consistent across nuclei (94%) and occurred in medication ON and OFF. The ratio outperformed other potential markers of tremor, such as power at individual tremor frequency, beta power, or low gamma power. For voluntary movement, we did not observe a significant difference when compared with rest or rest tremor. Finally, rhythmic modulations of high-frequency oscillation power occurred within the tremor cycle. Subthalamic high-frequency oscillation power is closely linked to the occurrence of parkinsonian rest tremor. The balance between slow and fast high-frequency oscillation power combines information on motor and medication state. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

Activity flow over resting-state networks shapes cognitive task activations.

PubMed

Cole, Michael W; Ito, Takuya; Bassett, Danielle S; Schultz, Douglas H

2016-12-01

Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allowed prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations.

Activity flow over resting-state networks shapes cognitive task activations

PubMed Central

Cole, Michael W.; Ito, Takuya; Bassett, Danielle S.; Schultz, Douglas H.

2016-01-01

Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allows prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations. PMID:27723746

Functional connectivity analysis in resting state fMRI with echo-state networks and non-metric clustering for network structure recovery

NASA Astrophysics Data System (ADS)

Wismüller, Axel; DSouza, Adora M.; Abidin, Anas Z.; Wang, Xixi; Hobbs, Susan K.; Nagarajan, Mahesh B.

2015-03-01

Echo state networks (ESN) are recurrent neural networks where the hidden layer is replaced with a fixed reservoir of neurons. Unlike feed-forward networks, neuron training in ESN is restricted to the output neurons alone thereby providing a computational advantage. We demonstrate the use of such ESNs in our mutual connectivity analysis (MCA) framework for recovering the primary motor cortex network associated with hand movement from resting state functional MRI (fMRI) data. Such a framework consists of two steps - (1) defining a pair-wise affinity matrix between different pixel time series within the brain to characterize network activity and (2) recovering network components from the affinity matrix with non-metric clustering. Here, ESNs are used to evaluate pair-wise cross-estimation performance between pixel time series to create the affinity matrix, which is subsequently subject to non-metric clustering with the Louvain method. For comparison, the ground truth of the motor cortex network structure is established with a task-based fMRI sequence. Overlap between the primary motor cortex network recovered with our model free MCA approach and the ground truth was measured with the Dice coefficient. Our results show that network recovery with our proposed MCA approach is in close agreement with the ground truth. Such network recovery is achieved without requiring low-pass filtering of the time series ensembles prior to analysis, an fMRI preprocessing step that has courted controversy in recent years. Thus, we conclude our MCA framework can allow recovery and visualization of the underlying functionally connected networks in the brain on resting state fMRI.

Lithium monotherapy associated clinical improvement effects on amygdala-ventromedial prefrontal cortex resting state connectivity in bipolar disorder.

PubMed

Altinay, Murat; Karne, Harish; Anand, Amit

2018-01-01

This study, for the first time, investigated lithium monotherapy associated effects on amygdala- ventromedial prefrontal cortex (vMPFC) resting-state functional connectivity and correlation with clinical improvement in bipolar disorder (BP) METHODS: Thirty-six medication-free subjects - 24 BP (12 hypomanic BPM) and 12 depressed (BPD)) and 12 closely matched healthy controls (HC), were included. BP subjects were treated with lithium and scanned at baseline, after 2 weeks and 8 weeks. HC were scanned at same time points but were not treated. The effect of lithium was studied for the BP group as a whole using two way (group, time) ANOVA while regressing out effects of state. Next, correlation between changes in amygdala-vMPFC resting-state connectivity and clinical global impression (CGI) of severity and improvement scale scores for overall BP illness was calculated. An exploratory analysis was also conducted for the BPD and BPM subgroups separately. Group by time interaction revealed that lithium monotherapy in patients was associated with increase in amygdala-medial OFC connectivity after 8 weeks of treatment (p = 0.05 (cluster-wise corrected)) compared to repeat testing in healthy controls. Increased amygdala-vMPFC connectivity correlated with clinical improvement at week 2 and week 8 as measured with the CGI-I scale. The results pertain to open-label treatment and do not account for non-treatment related improvement effects. Only functional connectivity was measured which does not give information regarding one regions effect on the other. Lithium monotherapy in BP is associated with modulation of amygdala-vMPFC connectivity which correlates with state-independent global clinical improvement. Copyright © 2017. Published by Elsevier B.V.

Directional patterns of cross frequency phase and amplitude coupling within the resting state mimic patterns of fMRI functional connectivity

PubMed Central

Weaver, Kurt E.; Wander, Jeremiah D.; Ko, Andrew L.; Casimo, Kaitlyn; Grabowski, Thomas J.; Ojemann, Jeffrey G.; Darvas, Felix

2016-01-01

Functional imaging investigations into the brain's resting state interactions have yielded a wealth of insight into the intrinsic and dynamic neural architecture supporting cognition and behavior. Electrophysiological studies however have highlighted the fact that synchrony across large-scale cortical systems is composed of spontaneous interactions occurring at timescales beyond the traditional resolution of fMRI, a feature that limits the capacity of fMRI to draw inference on the true directional relationship between network nodes. To approach the question of directionality in resting state signals, we recorded resting state functional MRI (rsfMRI) and electrocorticography (ECoG) from four human subjects undergoing invasive epilepsy monitoring. Using a seed-point based approach, we employed phase-amplitude coupling (PAC) and biPhase Locking Values (bPLV), two measures of cross-frequency coupling (CFC) to explore both outgoing and incoming connections between the seed and all non-seed, site electrodes. We observed robust PAC between a wide range of low-frequency phase and high frequency amplitude estimates. However, significant bPLV, a CFC measure of phase-phase synchrony, was only observed at specific narrow low and high frequency bandwidths. Furthermore, the spatial patterns of outgoing PAC connectivity were most closely associated with the rsfMRI connectivity maps. Our results support the hypothesis that PAC is relatively ubiquitous phenomenon serving as a mechanism for coordinating high-frequency amplitudes across distant neuronal assemblies even in absence of overt task structure. Additionally, we demonstrate that the spatial distribution of a seed-point rsfMRI sensorimotor network is strikingly similar to specific patterns of directional PAC. Specifically, the high frequency activities of distal patches of cortex owning membership in a rsfMRI sensorimotor network were most likely to be entrained to the phase of a low frequency rhythm engendered from the neural populations at the seed-point, suggestive of greater directional coupling from the seed out to the site electrodes. PMID:26747745

Brain functional connectivity network studies of acupuncture: a systematic review on resting-state fMRI.

PubMed

Cai, Rong-Lin; Shen, Guo-Ming; Wang, Hao; Guan, Yuan-Yuan

2018-01-01

Functional magnetic resonance imaging (fMRI) is a novel method for studying the changes of brain networks due to acupuncture treatment. In recent years, more and more studies have focused on the brain functional connectivity network of acupuncture stimulation. To offer an overview of the different influences of acupuncture on the brain functional connectivity network from studies using resting-state fMRI. The authors performed a systematic search according to PRISMA guidelines. The database PubMed was searched from January 1, 2006 to December 31, 2016 with restriction to human studies in English language. Electronic searches were conducted in PubMed using the keywords "acupuncture" and "neuroimaging" or "resting-state fMRI" or "functional connectivity". Selection of included articles, data extraction and methodological quality assessments were respectively conducted by two review authors. Forty-four resting-state fMRI studies were included in this systematic review according to inclusion criteria. Thirteen studies applied manual acupuncture vs. sham, four studies applied electro-acupuncture vs. sham, two studies also compared transcutaneous electrical acupoint stimulation vs. sham, and nine applied sham acupoint as control. Nineteen studies with a total number of 574 healthy subjects selected to perform fMRI only considered healthy adult volunteers. The brain functional connectivity of the patients had varying degrees of change. Compared with sham acupuncture, verum acupuncture could increase default mode network and sensorimotor network connectivity with pain-, affective- and memory-related brain areas. It has significantly greater connectivity of genuine acupuncture between the periaqueductal gray, anterior cingulate cortex, left posterior cingulate cortex, right anterior insula, limbic/paralimbic and precuneus compared with sham acupuncture. Some research had also shown that acupuncture could adjust the limbic-paralimbic-neocortical network, brainstem, cerebellum, subcortical and hippocampus brain areas. It can be presumed that the functional connectivity network is closely related to the mechanism of acupuncture, and central integration plays a critical role in the acupuncture mechanism. Copyright © 2017 Shanghai Changhai Hospital. Published by Elsevier B.V. All rights reserved.

Human brain arousal in the resting state: a genome-wide association study.

PubMed

Jawinski, Philippe; Kirsten, Holger; Sander, Christian; Spada, Janek; Ulke, Christine; Huang, Jue; Burkhardt, Ralph; Scholz, Markus; Hensch, Tilman; Hegerl, Ulrich

2018-04-27

Arousal affects cognition, emotion, and behavior and has been implicated in the etiology of psychiatric disorders. Although environmental conditions substantially contribute to the level of arousal, stable interindividual characteristics are well-established and a genetic basis has been suggested. Here we investigated the molecular genetics of brain arousal in the resting state by conducting a genome-wide association study (GWAS). We selected N = 1877 participants from the population-based LIFE-Adult cohort. Participants underwent a 20-min eyes-closed resting state EEG, which was analyzed using the computerized VIGALL 2.1 (Vigilance Algorithm Leipzig). At the SNP-level, GWAS analyses revealed no genome-wide significant locus (p < 5E-8), although seven loci were suggestive (p < 1E-6). The strongest hit was an expression quantitative trait locus (eQTL) of TMEM159 (lead-SNP: rs79472635, p = 5.49E-8). Importantly, at the gene-level, GWAS analyses revealed significant evidence for TMEM159 (p = 0.013, Bonferroni-corrected). By mapping our SNPs to the GWAS results from the Psychiatric Genomics Consortium, we found that all corresponding markers of TMEM159 showed nominally significant associations with Major Depressive Disorder (MDD; 0.006 ≤ p ≤ 0.011). More specifically, variants associated with high arousal levels have previously been linked to an increased risk for MDD. In line with this, the MetaXcan database suggests increased expression levels of TMEM159 in MDD, as well as Autism Spectrum Disorder, and Alzheimer's Disease. Furthermore, our pathway analyses provided evidence for a role of sodium/calcium exchangers in resting state arousal. In conclusion, the present GWAS identifies TMEM159 as a novel candidate gene which may modulate the risk for psychiatric disorders through arousal mechanisms. Our results also encourage the elaboration of the previously reported interrelations between ion-channel modulators, sleep-wake behavior, and psychiatric disorders.

Permanency analysis on human electroencephalogram signals for pervasive Brain-Computer Interface systems.

PubMed

Sadeghi, Koosha; Junghyo Lee; Banerjee, Ayan; Sohankar, Javad; Gupta, Sandeep K S

2017-07-01

Brain-Computer Interface (BCI) systems use some permanent features of brain signals to recognize their corresponding cognitive states with high accuracy. However, these features are not perfectly permanent, and BCI system should be continuously trained over time, which is tedious and time consuming. Thus, analyzing the permanency of signal features is essential in determining how often to repeat training. In this paper, we monitor electroencephalogram (EEG) signals, and analyze their behavior through continuous and relatively long period of time. In our experiment, we record EEG signals corresponding to rest state (eyes open and closed) from one subject everyday, for three and a half months. The results show that signal features such as auto-regression coefficients remain permanent through time, while others such as power spectral density specifically in 5-7 Hz frequency band are not permanent. In addition, eyes open EEG data shows more permanency than eyes closed data.

Alterations in Resting-State Activity Relate to Performance in a Verbal Recognition Task

PubMed Central

López Zunini, Rocío A.; Thivierge, Jean-Philippe; Kousaie, Shanna; Sheppard, Christine; Taler, Vanessa

2013-01-01

In the brain, resting-state activity refers to non-random patterns of intrinsic activity occurring when participants are not actively engaged in a task. We monitored resting-state activity using electroencephalogram (EEG) both before and after a verbal recognition task. We show a strong positive correlation between accuracy in verbal recognition and pre-task resting-state alpha power at posterior sites. We further characterized this effect by examining resting-state post-task activity. We found marked alterations in resting-state alpha power when comparing pre- and post-task periods, with more pronounced alterations in participants that attained higher task accuracy. These findings support a dynamical view of cognitive processes where patterns of ongoing brain activity can facilitate –or interfere– with optimal task performance. PMID:23785436

The temporal structure of resting-state brain activity in the medial prefrontal cortex predicts self-consciousness.

PubMed

Huang, Zirui; Obara, Natsuho; Davis, Henry Hap; Pokorny, Johanna; Northoff, Georg

2016-02-01

Recent studies have demonstrated an overlap between the neural substrate of resting-state activity and self-related processing in the cortical midline structures (CMS). However, the neural and psychological mechanisms mediating this so-called "rest-self overlap" remain unclear. To investigate the neural mechanisms, we estimated the temporal structure of spontaneous/resting-state activity, e.g. its long-range temporal correlations or self-affinity across time as indexed by the power-law exponent (PLE). The PLE was obtained in resting-state activity in the medial prefrontal cortex (MPFC) and the posterior cingulate cortex (PCC) in 47 healthy subjects by functional magnetic resonance imaging (fMRI). We performed correlation analyses of the PLE and Revised Self-Consciousness Scale (SCSR) scores, which enabled us to access different dimensions of self-consciousness and specified rest-self overlap in a psychological regard. The PLE in the MPFC's resting-state activity correlated with private self-consciousness scores from the SCSR. Conversely, we found no correlation between the PLE and the other subscales of the SCSR (public, social) or between other resting-state measures, including functional connectivity, and the SCSR subscales. This is the first evidence for the association between the scale-free dynamics of resting-state activity in the CMS and the private dimension of self-consciousness. This finding implies the relationship of especially the private dimension of self with the temporal structure of resting-state activity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cardiovascular consequences of bed rest: effect on maximal oxygen uptake

NASA Technical Reports Server (NTRS)

Convertino, V. A.

1997-01-01

Maximal oxygen uptake (VO2max) is reduced in healthy individuals confined to bed rest, suggesting it is independent of any disease state. The magnitude of reduction in VO2max is dependent on duration of bed rest and the initial level of aerobic fitness (VO2max), but it appears to be independent of age or gender. Bed rest induces an elevated maximal heart rate which, in turn, is associated with decreased cardiac vagal tone, increased sympathetic catecholamine secretion, and greater cardiac beta-receptor sensitivity. Despite the elevation in heart rate, VO2max is reduced primarily from decreased maximal stroke volume and cardiac output. An elevated ejection fraction during exercise following bed rest suggests that the lower stroke volume is not caused by ventricular dysfunction but is primarily the result of decreased venous return associated with lower circulating blood volume, reduced central venous pressure, and higher venous compliance in the lower extremities. VO2max, stroke volume, and cardiac output are further compromised by exercise in the upright posture. The contribution of hypovolemia to reduced cardiac output during exercise following bed rest is supported by the close relationship between the relative magnitude (% delta) and time course of change in blood volume and VO2max during bed rest, and also by the fact that retention of plasma volume is associated with maintenance of VO2max after bed rest. Arteriovenous oxygen difference during maximal exercise is not altered by bed rest, suggesting that peripheral mechanisms may not contribute significantly to the decreased VO2max. However reduction in baseline and maximal muscle blood flow, red blood cell volume, and capillarization in working muscles represent peripheral mechanisms that may contribute to limited oxygen delivery and, subsequently, lowered VO2max. Thus, alterations in cardiac and vascular functions induced by prolonged confinement to bed rest contribute to diminution of maximal oxygen uptake and reserve capacity to perform physical work.

Abnormal functional network connectivity among resting-state networks in children with frontal lobe epilepsy.

PubMed

Widjaja, E; Zamyadi, M; Raybaud, C; Snead, O C; Smith, M L

2013-12-01

Epilepsy is considered a disorder of neural networks. The aims of this study were to assess functional connectivity within resting-state networks and functional network connectivity across resting-state networks by use of resting-state fMRI in children with frontal lobe epilepsy and to relate changes in resting-state networks with neuropsychological function. Fifteen patients with frontal lobe epilepsy and normal MR imaging and 14 healthy control subjects were recruited. Spatial independent component analysis was used to identify the resting-state networks, including frontal, attention, default mode network, sensorimotor, visual, and auditory networks. The Z-maps of resting-state networks were compared between patients and control subjects. The relation between abnormal connectivity and neuropsychological function was assessed. Correlations from all pair-wise combinations of independent components were performed for each group and compared between groups. The frontal network was the only network that showed reduced connectivity in patients relative to control subjects. The remaining 5 networks demonstrated both reduced and increased functional connectivity within resting-state networks in patients. There was a weak association between connectivity in frontal network and executive function (P = .029) and a significant association between sensorimotor network and fine motor function (P = .004). Control subjects had 79 pair-wise independent components that showed significant temporal coherence across all resting-state networks except for default mode network-auditory network. Patients had 66 pairs of independent components that showed significant temporal coherence across all resting-state networks. Group comparison showed reduced functional network connectivity between default mode network-attention, frontal-sensorimotor, and frontal-visual networks and increased functional network connectivity between frontal-attention, default mode network-sensorimotor, and frontal-visual networks in patients relative to control subjects. We found abnormal functional connectivity within and across resting-state networks in children with frontal lobe epilepsy. Impairment in functional connectivity was associated with impaired neuropsychological function.

Comparison of continuously acquired resting state and extracted analogues from active tasks.

PubMed

Ganger, Sebastian; Hahn, Andreas; Küblböck, Martin; Kranz, Georg S; Spies, Marie; Vanicek, Thomas; Seiger, René; Sladky, Ronald; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

2015-10-01

Functional connectivity analysis of brain networks has become an important tool for investigation of human brain function. Although functional connectivity computations are usually based on resting-state data, the application to task-specific fMRI has received growing attention. Three major methods for extraction of resting-state data from task-related signal have been proposed (1) usage of unmanipulated task data for functional connectivity; (2) regression against task effects, subsequently using the residuals; and (3) concatenation of baseline blocks located in-between task blocks. Despite widespread application in current research, consensus on which method best resembles resting-state seems to be missing. We, therefore, evaluated these techniques in a sample of 26 healthy controls measured at 7 Tesla. In addition to continuous resting-state, two different task paradigms were assessed (emotion discrimination and right finger-tapping) and five well-described networks were analyzed (default mode, thalamus, cuneus, sensorimotor, and auditory). Investigating the similarity to continuous resting-state (Dice, Intraclass correlation coefficient (ICC), R(2) ) showed that regression against task effects yields functional connectivity networks most alike to resting-state. However, all methods exhibited significant differences when compared to continuous resting-state and similarity metrics were lower than test-retest of two resting-state scans. Omitting global signal regression did not change these findings. Visually, the networks are highly similar, but through further investigation marked differences can be found. Therefore, our data does not support referring to resting-state when extracting signals from task designs, although functional connectivity computed from task-specific data may indeed yield interesting information. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Complex network analysis of resting-state fMRI of the brain.

PubMed

Anwar, Abdul Rauf; Hashmy, Muhammad Yousaf; Imran, Bilal; Riaz, Muhammad Hussnain; Mehdi, Sabtain Muhammad Muntazir; Muthalib, Makii; Perrey, Stephane; Deuschl, Gunther; Groppa, Sergiu; Muthuraman, Muthuraman

2016-08-01

Due to the fact that the brain activity hardly ever diminishes in healthy individuals, analysis of resting state functionality of the brain seems pertinent. Various resting state networks are active inside the idle brain at any time. Based on various neuro-imaging studies, it is understood that various structurally distant regions of the brain could be functionally connected. Regions of the brain, that are functionally connected, during rest constitutes to the resting state network. In the present study, we employed the complex network measures to estimate the presence of community structures within a network. Such estimate is named as modularity. Instead of using a traditional correlation matrix, we used a coherence matrix taken from the causality measure between different nodes. Our results show that in prolonged resting state the modularity starts to decrease. This decrease was observed in all the resting state networks and on both sides of the brain. Our study highlights the usage of coherence matrix instead of correlation matrix for complex network analysis.

What goes on in the resting-state? A qualitative glimpse into resting-state experience in the scanner

PubMed Central

Hurlburt, Russell T.; Alderson-Day, Ben; Fernyhough, Charles; Kühn, Simone

2015-01-01

The brain’s resting-state has attracted considerable interest in recent years, but currently little is known either about typical experience during the resting-state or about whether there are inter-individual differences in resting-state phenomenology. We used descriptive experience sampling (DES) in an attempt to apprehend high fidelity glimpses of the inner experience of five participants in an extended fMRI study. Results showed that the inner experiences and the neural activation patterns (as quantified by amplitude of low frequency fluctuations analysis) of the five participants were largely consistent across time, suggesting that our extended-duration scanner sessions were broadly similar to typical resting-state sessions. However, there were very large individual differences in inner phenomena, suggesting that the resting-state itself may differ substantially from one participant to the next. We describe these individual differences in experiential characteristics and display some typical moments of resting-state experience. We also show that retrospective characterizations of phenomena can often be very different from moment-by-moment reports. We discuss implications for the assessment of inner experience in neuroimaging studies more generally, concluding that it may be possible to use fMRI to investigate neural correlates of phenomena apprehended in high fidelity. PMID:26500590

Resting-state brain activity in the motor cortex reflects task-induced activity: A multi-voxel pattern analysis.

PubMed

Kusano, Toshiki; Kurashige, Hiroki; Nambu, Isao; Moriguchi, Yoshiya; Hanakawa, Takashi; Wada, Yasuhiro; Osu, Rieko

2015-08-01

It has been suggested that resting-state brain activity reflects task-induced brain activity patterns. In this study, we examined whether neural representations of specific movements can be observed in the resting-state brain activity patterns of motor areas. First, we defined two regions of interest (ROIs) to examine brain activity associated with two different behavioral tasks. Using multi-voxel pattern analysis with regularized logistic regression, we designed a decoder to detect voxel-level neural representations corresponding to the tasks in each ROI. Next, we applied the decoder to resting-state brain activity. We found that the decoder discriminated resting-state neural activity with accuracy comparable to that associated with task-induced neural activity. The distribution of learned weighted parameters for each ROI was similar for resting-state and task-induced activities. Large weighted parameters were mainly located on conjunctive areas. Moreover, the accuracy of detection was higher than that for a decoder whose weights were randomly shuffled, indicating that the resting-state brain activity includes multi-voxel patterns similar to the neural representation for the tasks. Therefore, these results suggest that the neural representation of resting-state brain activity is more finely organized and more complex than conventionally considered.

Synaptic Plasticity Enables Adaptive Self-Tuning Critical Networks

PubMed Central

Stepp, Nigel; Plenz, Dietmar; Srinivasa, Narayan

2015-01-01

During rest, the mammalian cortex displays spontaneous neural activity. Spiking of single neurons during rest has been described as irregular and asynchronous. In contrast, recent in vivo and in vitro population measures of spontaneous activity, using the LFP, EEG, MEG or fMRI suggest that the default state of the cortex is critical, manifested by spontaneous, scale-invariant, cascades of activity known as neuronal avalanches. Criticality keeps a network poised for optimal information processing, but this view seems to be difficult to reconcile with apparently irregular single neuron spiking. Here, we simulate a 10,000 neuron, deterministic, plastic network of spiking neurons. We show that a combination of short- and long-term synaptic plasticity enables these networks to exhibit criticality in the face of intrinsic, i.e. self-sustained, asynchronous spiking. Brief external perturbations lead to adaptive, long-term modification of intrinsic network connectivity through long-term excitatory plasticity, whereas long-term inhibitory plasticity enables rapid self-tuning of the network back to a critical state. The critical state is characterized by a branching parameter oscillating around unity, a critical exponent close to -3/2 and a long tail distribution of a self-similarity parameter between 0.5 and 1. PMID:25590427

Clinical Applications of Resting State Functional Connectivity

PubMed Central

Fox, Michael D.; Greicius, Michael

2010-01-01

During resting conditions the brain remains functionally and metabolically active. One manifestation of this activity that has become an important research tool is spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI). The identification of correlation patterns in these spontaneous fluctuations has been termed resting state functional connectivity (fcMRI) and has the potential to greatly increase the translation of fMRI into clinical care. In this article we review the advantages of the resting state signal for clinical applications including detailed discussion of signal to noise considerations. We include guidelines for performing resting state research on clinical populations, outline the different areas for clinical application, and identify important barriers to be addressed to facilitate the translation of resting state fcMRI into the clinical realm. PMID:20592951

Does resting-state connectivity reflect depressive rumination? A tale of two analyses.

PubMed

Berman, Marc G; Misic, Bratislav; Buschkuehl, Martin; Kross, Ethan; Deldin, Patricia J; Peltier, Scott; Churchill, Nathan W; Jaeggi, Susanne M; Vakorin, Vasily; McIntosh, Anthony R; Jonides, John

2014-12-01

Major Depressive Disorder (MDD) is characterized by rumination. Prior research suggests that resting-state brain activation reflects rumination when depressed individuals are not task engaged. However, no study has directly tested this. Here we investigated whether resting-state epochs differ from induced ruminative states for healthy and depressed individuals. Most previous research on resting-state networks comes from seed-based analyses with the posterior cingulate cortex (PCC). By contrast, we examined resting state connectivity by using the complete multivariate connectivity profile (i.e., connections across all brain nodes) and by comparing these results to seeded analyses. We find that unconstrained resting-state intervals differ from active rumination states in strength of connectivity and that overall connectivity was higher for healthy vs. depressed individuals. Relationships between connectivity and subjective mood (i.e., behavior) were strongly observed during induced rumination epochs. Furthermore, connectivity patterns that related to subjective mood were strikingly different for MDD and healthy control (HC) groups suggesting different mood regulation mechanisms. Copyright © 2014 Elsevier Inc. All rights reserved.

Altered amygdalar resting-state connectivity in depression is explained by both genes and environment.

PubMed

Córdova-Palomera, Aldo; Tornador, Cristian; Falcón, Carles; Bargalló, Nuria; Nenadic, Igor; Deco, Gustavo; Fañanás, Lourdes

2015-10-01

Recent findings indicate that alterations of the amygdalar resting-state fMRI connectivity play an important role in the etiology of depression. While both depression and resting-state brain activity are shaped by genes and environment, the relative contribution of genetic and environmental factors mediating the relationship between amygdalar resting-state connectivity and depression remain largely unexplored. Likewise, novel neuroimaging research indicates that different mathematical representations of resting-state fMRI activity patterns are able to embed distinct information relevant to brain health and disease. The present study analyzed the influence of genes and environment on amygdalar resting-state fMRI connectivity, in relation to depression risk. High-resolution resting-state fMRI scans were analyzed to estimate functional connectivity patterns in a sample of 48 twins (24 monozygotic pairs) informative for depressive psychopathology (6 concordant, 8 discordant and 10 healthy control pairs). A graph-theoretical framework was employed to construct brain networks using two methods: (i) the conventional approach of filtered BOLD fMRI time-series and (ii) analytic components of this fMRI activity. Results using both methods indicate that depression risk is increased by environmental factors altering amygdalar connectivity. When analyzing the analytic components of the BOLD fMRI time-series, genetic factors altering the amygdala neural activity at rest show an important contribution to depression risk. Overall, these findings show that both genes and environment modify different patterns the amygdala resting-state connectivity to increase depression risk. The genetic relationship between amygdalar connectivity and depression may be better elicited by examining analytic components of the brain resting-state BOLD fMRI signals. © 2015 Wiley Periodicals, Inc.

Unified Bayesian Estimator of EEG Reference at Infinity: rREST (Regularized Reference Electrode Standardization Technique)

PubMed Central

Hu, Shiang; Yao, Dezhong; Valdes-Sosa, Pedro A.

2018-01-01

The choice of reference for the electroencephalogram (EEG) is a long-lasting unsolved issue resulting in inconsistent usages and endless debates. Currently, both the average reference (AR) and the reference electrode standardization technique (REST) are two primary, apparently irreconcilable contenders. We propose a theoretical framework to resolve this reference issue by formulating both (a) estimation of potentials at infinity, and (b) determination of the reference, as a unified Bayesian linear inverse problem, which can be solved by maximum a posterior estimation. We find that AR and REST are very particular cases of this unified framework: AR results from biophysically non-informative prior; while REST utilizes the prior based on the EEG generative model. To allow for simultaneous denoising and reference estimation, we develop the regularized versions of AR and REST, named rAR and rREST, respectively. Both depend on a regularization parameter that is the noise to signal variance ratio. Traditional and new estimators are evaluated with this framework, by both simulations and analysis of real resting EEGs. Toward this end, we leverage the MRI and EEG data from 89 subjects which participated in the Cuban Human Brain Mapping Project. Generated artificial EEGs—with a known ground truth, show that relative error in estimating the EEG potentials at infinity is lowest for rREST. It also reveals that realistic volume conductor models improve the performances of REST and rREST. Importantly, for practical applications, it is shown that an average lead field gives the results comparable to the individual lead field. Finally, it is shown that the selection of the regularization parameter with Generalized Cross-Validation (GCV) is close to the “oracle” choice based on the ground truth. When evaluated with the real 89 resting state EEGs, rREST consistently yields the lowest GCV. This study provides a novel perspective to the EEG reference problem by means of a unified inverse solution framework. It may allow additional principled theoretical formulations and numerical evaluation of performance. PMID:29780302

Cognitive performance in healthy older adults relates to spontaneous switching between states of functional connectivity during rest.

PubMed

Cabral, Joana; Vidaurre, Diego; Marques, Paulo; Magalhães, Ricardo; Silva Moreira, Pedro; Miguel Soares, José; Deco, Gustavo; Sousa, Nuno; Kringelbach, Morten L

2017-07-11

Growing evidence has shown that brain activity at rest slowly wanders through a repertoire of different states, where whole-brain functional connectivity (FC) temporarily settles into distinct FC patterns. Nevertheless, the functional role of resting-state activity remains unclear. Here, we investigate how the switching behavior of resting-state FC relates with cognitive performance in healthy older adults. We analyse resting-state fMRI data from 98 healthy adults previously categorized as being among the best or among the worst performers in a cohort study of >1000 subjects aged 50+ who underwent neuropsychological assessment. We use a novel approach focusing on the dominant FC pattern captured by the leading eigenvector of dynamic FC matrices. Recurrent FC patterns - or states - are detected and characterized in terms of lifetime, probability of occurrence and switching profiles. We find that poorer cognitive performance is associated with weaker FC temporal similarity together with altered switching between FC states. These results provide new evidence linking the switching dynamics of FC during rest with cognitive performance in later life, reinforcing the functional role of resting-state activity for effective cognitive processing.

Functional Covariance Networks: Obtaining Resting-State Networks from Intersubject Variability

PubMed Central

Gohel, Suril; Di, Xin; Walter, Martin; Biswal, Bharat B.

2012-01-01

Abstract In this study, we investigate a new approach for examining the separation of the brain into resting-state networks (RSNs) on a group level using resting-state parameters (amplitude of low-frequency fluctuation [ALFF], fractional ALFF [fALFF], the Hurst exponent, and signal standard deviation). Spatial independent component analysis is used to reveal covariance patterns of the relevant resting-state parameters (not the time series) across subjects that are shown to be related to known, standard RSNs. As part of the analysis, nonresting state parameters are also investigated, such as mean of the blood oxygen level-dependent time series and gray matter volume from anatomical scans. We hypothesize that meaningful RSNs will primarily be elucidated by analysis of the resting-state functional connectivity (RSFC) parameters and not by non-RSFC parameters. First, this shows the presence of a common influence underlying individual RSFC networks revealed through low-frequency fluctation (LFF) parameter properties. Second, this suggests that the LFFs and RSFC networks have neurophysiological origins. Several of the components determined from resting-state parameters in this manner correlate strongly with known resting-state functional maps, and we term these “functional covariance networks”. PMID:22765879

Fluctuations of Attentional Networks and Default Mode Network during the Resting State Reflect Variations in Cognitive States: Evidence from a Novel Resting-state Experience Sampling Method.

PubMed

Van Calster, Laurens; D'Argembeau, Arnaud; Salmon, Eric; Peters, Frédéric; Majerus, Steve

2017-01-01

Neuroimaging studies have revealed the recruitment of a range of neural networks during the resting state, which might reflect a variety of cognitive experiences and processes occurring in an individual's mind. In this study, we focused on the default mode network (DMN) and attentional networks and investigated their association with distinct mental states when participants are not performing an explicit task. To investigate the range of possible cognitive experiences more directly, this study proposes a novel method of resting-state fMRI experience sampling, informed by a phenomenological investigation of the fluctuation of mental states during the resting state. We hypothesized that DMN activity would increase as a function of internal mentation and that the activity of dorsal and ventral networks would indicate states of top-down versus bottom-up attention at rest. Results showed that dorsal attention network activity fluctuated as a function of subjective reports of attentional control, providing evidence that activity of this network reflects the perceived recruitment of controlled attentional processes during spontaneous cognition. Activity of the DMN increased when participants reported to be in a subjective state of internal mentation, but not when they reported to be in a state of perception. This study provides direct evidence for a link between fluctuations of resting-state neural activity and fluctuations in specific cognitive processes.

Resting-state connectivity of pre-motor cortex reflects disability in multiple sclerosis.

PubMed

Dogonowski, A-M; Siebner, H R; Soelberg Sørensen, P; Paulson, O B; Dyrby, T B; Blinkenberg, M; Madsen, K H

2013-11-01

To characterize the relationship between motor resting-state connectivity of the dorsal pre-motor cortex (PMd) and clinical disability in patients with multiple sclerosis (MS). A total of 27 patients with relapsing-remitting MS (RR-MS) and 15 patients with secondary progressive MS (SP-MS) underwent functional resting-state magnetic resonance imaging. Clinical disability was assessed using the Expanded Disability Status Scale (EDSS). Independent component analysis was used to characterize motor resting-state connectivity. Multiple regression analysis was performed in SPM8 between the individual expression of motor resting-state connectivity in PMd and EDSS scores including age as covariate. Separate post hoc analyses were performed for patients with RR-MS and SP-MS. The EDSS scores ranged from 0 to 7 with a median score of 4.3. Motor resting-state connectivity of left PMd showed a positive linear relation with clinical disability in patients with MS. This effect was stronger when considering the group of patients with RR-MS alone, whereas patients with SP-MS showed no increase in coupling strength between left PMd and the motor resting-state network with increasing clinical disability. No significant relation between motor resting-state connectivity of the right PMd and clinical disability was detected in MS. The increase in functional coupling between left PMd and the motor resting-state network with increasing clinical disability can be interpreted as adaptive reorganization of the motor system to maintain motor function, which appears to be limited to the relapsing-remitting stage of the disease. © 2013 John Wiley & Sons A/S.

Resting State Networks and Consciousness

PubMed Central

Heine, Lizette; Soddu, Andrea; Gómez, Francisco; Vanhaudenhuyse, Audrey; Tshibanda, Luaba; Thonnard, Marie; Charland-Verville, Vanessa; Kirsch, Murielle; Laureys, Steven; Demertzi, Athena

2012-01-01

In order to better understand the functional contribution of resting state activity to conscious cognition, we aimed to review increases and decreases in functional magnetic resonance imaging (fMRI) functional connectivity under physiological (sleep), pharmacological (anesthesia), and pathological altered states of consciousness, such as brain death, coma, vegetative state/unresponsive wakefulness syndrome, and minimally conscious state. The reviewed resting state networks were the DMN, left and right executive control, salience, sensorimotor, auditory, and visual networks. We highlight some methodological issues concerning resting state analyses in severely injured brains mainly in terms of hypothesis-driven seed-based correlation analysis and data-driven independent components analysis approaches. Finally, we attempt to contextualize our discussion within theoretical frameworks of conscious processes. We think that this “lesion” approach allows us to better determine the necessary conditions under which normal conscious cognition takes place. At the clinical level, we acknowledge the technical merits of the resting state paradigm. Indeed, fast and easy acquisitions are preferable to activation paradigms in clinical populations. Finally, we emphasize the need to validate the diagnostic and prognostic value of fMRI resting state measurements in non-communicating brain damaged patients. PMID:22969735

Amygdala Functional Connectivity is Reduced After the Cold Pressor Task

PubMed Central

Clewett, David; Schoeke, Andrej; Mather, Mara

2013-01-01

The amygdala forms a crucial link between central pain and stress systems. There is much evidence that psychological stress affects amygdala activity, but it is less clear how painful stressors influence subsequent amygdala functional connectivity. In the present study, we used pulsed arterial spin labeling (PASL) to investigate differences in healthy male adults’ resting-state amygdala functional connectivity following a cold pressor versus control task, with the stressor and control conditions conducted on different days. During the period of peak cortisol response to acute stress (approximately fifteen to thirty minutes after stressor onset), participants were asked to rest for six minutes with their eyes closed during a PASL scanning sequence. The cold pressor task led to reduced resting-state functional connectivity between the amygdalae and orbitofrontal cortex (OFC) and ventromedial prefrontal cortex (VMPFC), which occurred irrespective of cortisol release. The stressor also induced greater inverse connectivity between the left amygdala and dorsal anterior cingulate cortex (dACC), a brain region implicated in the down-regulation of amygdala responsivity. Furthermore, the degree of post-stressor left amygdala decoupling with the lateral OFC varied according to self-reported pain intensity during the cold pressor task. These findings indicate that the cold pressor task alters amygdala interactions with prefrontal and ACC regions 15–30 minutes after the stressor, and that these altered functional connectivity patterns are related to pain perception rather than cortisol feedback. PMID:23645370

Resting State Brain Network Disturbances Related to Hypomania and Depression in Medication-Free Bipolar Disorder

PubMed Central

Spielberg, Jeffrey M; Beall, Erik B; Hulvershorn, Leslie A; Altinay, Murat; Karne, Harish; Anand, Amit

2016-01-01

Research on resting functional brain networks in bipolar disorder (BP) has been unable to differentiate between disturbances related to mania or depression, which is necessary to understand the mechanisms leading to each state. Past research has also been unable to elucidate the impact of BP-related network disturbances on the organizational properties of the brain (eg, communication efficiency). Thus, the present work sought to isolate network disturbances related to BP, fractionate these into components associated with manic and depressive symptoms, and characterize the impact of disturbances on network function. Graph theory was used to analyze resting functional magnetic resonance imaging data from 60 medication-free patients meeting the criteria for BP and either a current hypomanic (n=30) or depressed (n=30) episode and 30 closely age/sex-matched healthy controls. Correction for multiple comparisons was carried out. Compared with controls, BP patients evidenced hyperconnectivity in a network involving right amygdala. Fractionation revealed that (hypo)manic symptoms were associated with hyperconnectivity in an overlapping network and disruptions in the brain's ‘small-world' network organization. Depressive symptoms predicted hyperconnectivity in a network involving orbitofrontal cortex along with a less resilient global network organization. Findings provide deeper insight into the differential pathophysiological processes associated with hypomania and depression, along with the particular impact these differential processes have on network function. PMID:27356764

Resting State Brain Network Disturbances Related to Hypomania and Depression in Medication-Free Bipolar Disorder.

PubMed

Spielberg, Jeffrey M; Beall, Erik B; Hulvershorn, Leslie A; Altinay, Murat; Karne, Harish; Anand, Amit

2016-12-01

Research on resting functional brain networks in bipolar disorder (BP) has been unable to differentiate between disturbances related to mania or depression, which is necessary to understand the mechanisms leading to each state. Past research has also been unable to elucidate the impact of BP-related network disturbances on the organizational properties of the brain (eg, communication efficiency). Thus, the present work sought to isolate network disturbances related to BP, fractionate these into components associated with manic and depressive symptoms, and characterize the impact of disturbances on network function. Graph theory was used to analyze resting functional magnetic resonance imaging data from 60 medication-free patients meeting the criteria for BP and either a current hypomanic (n=30) or depressed (n=30) episode and 30 closely age/sex-matched healthy controls. Correction for multiple comparisons was carried out. Compared with controls, BP patients evidenced hyperconnectivity in a network involving right amygdala. Fractionation revealed that (hypo)manic symptoms were associated with hyperconnectivity in an overlapping network and disruptions in the brain's 'small-world' network organization. Depressive symptoms predicted hyperconnectivity in a network involving orbitofrontal cortex along with a less resilient global network organization. Findings provide deeper insight into the differential pathophysiological processes associated with hypomania and depression, along with the particular impact these differential processes have on network function.

Abnormal cortical sources of resting state electroencephalographic rhythms in single treatment-naïve HIV individuals: A statistical z-score index.

PubMed

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.

Cross-frequency coupling in real and virtual brain networks

PubMed Central

Jirsa, Viktor; Müller, Viktor

2013-01-01

Information processing in the brain is thought to rely on the convergence and divergence of oscillatory behaviors of widely distributed brain areas. This information flow is captured in its simplest form via the concepts of synchronization and desynchronization and related metrics. More complex forms of information flow are transient synchronizations and multi-frequency behaviors with metrics related to cross-frequency coupling (CFC). It is supposed that CFC plays a crucial role in the organization of large-scale networks and functional integration across large distances. In this study, we describe different CFC measures and test their applicability in simulated and real electroencephalographic (EEG) data obtained during resting state. For these purposes, we derive generic oscillator equations from full brain network models. We systematically model and simulate the various scenarios of CFC under the influence of noise to obtain biologically realistic oscillator dynamics. We find that (i) specific CFC-measures detect correctly in most cases the nature of CFC under noise conditions, (ii) bispectrum (BIS) and bicoherence (BIC) correctly detect the CFCs in simulated data, (iii) empirical resting state EEG show a prominent delta-alpha CFC as identified by specific CFC measures and the more classic BIS and BIC. This coupling was mostly asymmetric (directed) and generally higher in the eyes closed (EC) than in the eyes open (EO) condition. In conjunction, these two sets of measures provide a powerful toolbox to reveal the nature of couplings from experimental data and as such allow inference on the brain state dependent information processing. Methodological advantages of using CFC measures and theoretical significance of delta and alpha interactions during resting and other brain states are discussed. PMID:23840188

DPARSF: A MATLAB Toolbox for "Pipeline" Data Analysis of Resting-State fMRI.

PubMed

Chao-Gan, Yan; Yu-Feng, Zang

2010-01-01

Resting-state functional magnetic resonance imaging (fMRI) has attracted more and more attention because of its effectiveness, simplicity and non-invasiveness in exploration of the intrinsic functional architecture of the human brain. However, user-friendly toolbox for "pipeline" data analysis of resting-state fMRI is still lacking. Based on some functions in Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST), we have developed a MATLAB toolbox called Data Processing Assistant for Resting-State fMRI (DPARSF) for "pipeline" data analysis of resting-state fMRI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), and fractional ALFF. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest.

Spatial distribution of resting-state BOLD regional homogeneity as a predictor of brain glucose uptake: A study in healthy aging.

PubMed

Bernier, Michaël; Croteau, Etienne; Castellano, Christian-Alexandre; Cunnane, Stephen C; Whittingstall, Kevin

2017-04-15

Positron emission tomography using [18F]-fluorodeoxyglucose (PET-FDG) is the primary imaging modality used to measure glucose metabolism in the brain (CMRGlu). CMRGlu has been used as a biomarker of brain aging and neurodegenerative diseases, but the complexity and invasive nature of PET often limits its use in research. There is therefore great interest in developing non-invasive metrics for estimating brain CMRGlu. We therefore investigated resting state fMRI metrics such as regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF) and regional global connectivity (Closeness) with multiple analytical approaches to determine their relationship to CMRGlu. We investigated this relation in two distinct cognitively healthy populations separated by age (27 young adults and 35 older adults). Overall, we found that both regionally and across participants, ReHo strongly correlated with CMRGlu in healthy young and older adults. Moreover, ReHo demonstrated the same age-related differences as CMRGlu throughout all cortical regions, particularly in the default network and frontal areas. Copyright © 2017 Elsevier Inc. All rights reserved.

Co-activation patterns in resting-state fMRI signals.

PubMed

Liu, Xiao; Zhang, Nanyin; Chang, Catie; Duyn, Jeff H

2018-02-08

The brain is a complex system that integrates and processes information across multiple time scales by dynamically coordinating activities over brain regions and circuits. Correlations in resting-state functional magnetic resonance imaging (rsfMRI) signals have been widely used to infer functional connectivity of the brain, providing a metric of functional associations that reflects a temporal average over an entire scan (typically several minutes or longer). Not until recently was the study of dynamic brain interactions at much shorter time scales (seconds to minutes) considered for inference of functional connectivity. One method proposed for this objective seeks to identify and extract recurring co-activation patterns (CAPs) that represent instantaneous brain configurations at single time points. Here, we review the development and recent advancement of CAP methodology and other closely related approaches, as well as their applications and associated findings. We also discuss the potential neural origins and behavioral relevance of CAPs, along with methodological issues and future research directions in the analysis of fMRI co-activation patterns. Copyright © 2018 Elsevier Inc. All rights reserved.

Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization.

PubMed

Brier, Matthew R; Mitra, Anish; McCarthy, John E; Ances, Beau M; Snyder, Abraham Z

2015-11-01

Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. Copyright © 2015 Elsevier Inc. All rights reserved.

Partial covariance based functional connectivity computation using Ledoit-Wolf covariance regularization

PubMed Central

Brier, Matthew R.; Mitra, Anish; McCarthy, John E.; Ances, Beau M.; Snyder, Abraham Z.

2015-01-01

Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. PMID:26208872

The Use of Closed-Circuit Television for the Teaching of Psychotherapeutic Interviewing to Medical Students

PubMed Central

Yonge, K. A.

1965-01-01

While closed-circuit television has been used in medical schools in the United States for some 12 years, its use for teaching diagnostic and psychotherapeutic interviewing to medical students has not previously been reported in Canada. The procedure involved a class of 64 students in their second year for a total of 38 hours. Concurrently with the demonstration interviews, the students were supervised in individual practice interviews with patients. The principles of psychotherapy had to be carefully related to the rest of the medical curriculum which essentially is biologically oriented. Three basic principles of health and healing were adopted because they were as applicable psychologically as physically. Evaluation of the program was undertaken by polling the students by means of a questionnaire. The general conclusion was that the use of closed-circuit television for these purposes far surpasses any other technique and has no major drawbacks. PMID:14278028

Site-Directed Spin Labeling Reveals Pentameric Ligand-Gated Ion Channel Gating Motions

PubMed Central

Dellisanti, Cosma D.; Ghosh, Borna; Hanson, Susan M.; Raspanti, James M.; Grant, Valerie A.; Diarra, Gaoussou M.; Schuh, Abby M.; Satyshur, Kenneth; Klug, Candice S.; Czajkowski, Cynthia

2013-01-01

Pentameric ligand-gated ion channels (pLGICs) are neurotransmitter-activated receptors that mediate fast synaptic transmission. In pLGICs, binding of agonist to the extracellular domain triggers a structural rearrangement that leads to the opening of an ion-conducting pore in the transmembrane domain and, in the continued presence of neurotransmitter, the channels desensitize (close). The flexible loops in each subunit that connect the extracellular binding domain (loops 2, 7, and 9) to the transmembrane channel domain (M2–M3 loop) are essential for coupling ligand binding to channel gating. Comparing the crystal structures of two bacterial pLGIC homologues, ELIC and the proton-activated GLIC, suggests channel gating is associated with rearrangements in these loops, but whether these motions accurately predict the motions in functional lipid-embedded pLGICs is unknown. Here, using site-directed spin labeling (SDSL) electron paramagnetic resonance (EPR) spectroscopy and functional GLIC channels reconstituted into liposomes, we examined if, and how far, the loops at the ECD/TMD gating interface move during proton-dependent gating transitions from the resting to desensitized state. Loop 9 moves ∼9 Å inward toward the channel lumen in response to proton-induced desensitization. Loop 9 motions were not observed when GLIC was in detergent micelles, suggesting detergent solubilization traps the protein in a nonactivatable state and lipids are required for functional gating transitions. Proton-induced desensitization immobilizes loop 2 with little change in position. Proton-induced motion of the M2–M3 loop was not observed, suggesting its conformation is nearly identical in closed and desensitized states. Our experimentally derived distance measurements of spin-labeled GLIC suggest ELIC is not a good model for the functional resting state of GLIC, and that the crystal structure of GLIC does not correspond to a desensitized state. These findings advance our understanding of the molecular mechanisms underlying pLGIC gating. PMID:24260024

Alcohol Affects the Brain's Resting-State Network in Social Drinkers

PubMed Central

Lithari, Chrysa; Klados, Manousos A.; Pappas, Costas; Albani, Maria; Kapoukranidou, Dorothea; Kovatsi, Leda

2012-01-01

Acute alcohol intake is known to enhance inhibition through facilitation of GABAA receptors, which are present in 40% of the synapses all over the brain. Evidence suggests that enhanced GABAergic transmission leads to increased large-scale brain connectivity. Our hypothesis is that acute alcohol intake would increase the functional connectivity of the human brain resting-state network (RSN). To test our hypothesis, electroencephalographic (EEG) measurements were recorded from healthy social drinkers at rest, during eyes-open and eyes-closed sessions, after administering to them an alcoholic beverage or placebo respectively. Salivary alcohol and cortisol served to measure the inebriation and stress levels. By calculating Magnitude Square Coherence (MSC) on standardized Low Resolution Electromagnetic Tomography (sLORETA) solutions, we formed cortical networks over several frequency bands, which were then analyzed in the context of functional connectivity and graph theory. MSC was increased (p<0.05, corrected with False Discovery Rate, FDR corrected) in alpha, beta (eyes-open) and theta bands (eyes-closed) following acute alcohol intake. Graph parameters were accordingly altered in these bands quantifying the effect of alcohol on the structure of brain networks; global efficiency and density were higher and path length was lower during alcohol (vs. placebo, p<0.05). Salivary alcohol concentration was positively correlated with the density of the network in beta band. The degree of specific nodes was elevated following alcohol (vs. placebo). Our findings support the hypothesis that short-term inebriation considerably increases large-scale connectivity in the RSN. The increased baseline functional connectivity can -at least partially- be attributed to the alcohol-induced disruption of the delicate balance between inhibitory and excitatory neurotransmission in favor of inhibitory influences. Thus, it is suggested that short-term inebriation is associated, as expected, to increased GABA transmission and functional connectivity, while long-term alcohol consumption may be linked to exactly the opposite effect. PMID:23119078

Sleep deprivation compromises resting-state emotional regulatory processes: An EEG study.

PubMed

Zhang, Jinxiao; Lau, Esther Yuet Ying; Hsiao, Janet H

2018-03-01

Resting-state spontaneous neural activities consume far more biological energy than stimulus-induced activities, suggesting their significance. However, existing studies of sleep loss and emotional functioning have focused on how sleep deprivation modulates stimulus-induced emotional neural activities. The current study aimed to investigate the impacts of sleep deprivation on the brain network of emotional functioning using electroencephalogram during a resting state. Two established resting-state electroencephalogram indexes (i.e. frontal alpha asymmetry and frontal theta/beta ratio) were used to reflect the functioning of the emotion regulatory neural network. Participants completed an 8-min resting-state electroencephalogram recording after a well-rested night or 24 hr sleep deprivation. The Sleep Deprivation group had a heightened ratio of the power density in theta band to beta band (theta/beta ratio) in the frontal area than the Sleep Control group, suggesting an effective approach with reduced frontal cortical regulation of subcortical drive after sleep deprivation. There was also marginally more left-lateralized frontal alpha power (left frontal alpha asymmetry) in the Sleep Deprivation group compared with the Sleep Control group. Besides, higher theta/beta ratio and more left alpha lateralization were correlated with higher sleepiness and lower vigilance. The results converged in suggesting compromised emotional regulatory processes during resting state after sleep deprivation. Our work provided the first resting-state neural evidence for compromised emotional functioning after sleep loss, highlighting the significance of examining resting-state neural activities within the affective brain network as a default functional mode in investigating the sleep-emotion relationship. © 2018 European Sleep Research Society.

Characterizing Resting-State Brain Function Using Arterial Spin Labeling

PubMed Central

Jann, Kay; Wang, Danny J.J.

2015-01-01

Abstract Arterial spin labeling (ASL) is an increasingly established magnetic resonance imaging (MRI) technique that is finding broader applications in studying the healthy and diseased brain. This review addresses the use of ASL to assess brain function in the resting state. Following a brief technical description, we discuss the use of ASL in the following main categories: (1) resting-state functional connectivity (FC) measurement: the use of ASL-based cerebral blood flow (CBF) measurements as an alternative to the blood oxygen level-dependent (BOLD) technique to assess resting-state FC; (2) the link between network CBF and FC measurements: the use of network CBF as a surrogate of the metabolic activity within corresponding networks; and (3) the study of resting-state dynamic CBF-BOLD coupling and cerebral metabolism: the use of dynamic CBF information obtained using ASL to assess dynamic CBF-BOLD coupling and oxidative metabolism in the resting state. In addition, we summarize some future challenges and interesting research directions for ASL, including slice-accelerated (multiband) imaging as well as the effects of motion and other physiological confounds on perfusion-based FC measurement. In summary, this work reviews the state-of-the-art of ASL and establishes it as an increasingly viable MRI technique with high translational value in studying resting-state brain function. PMID:26106930

Distinctive time-lagged resting-state networks revealed by simultaneous EEG-fMRI.

PubMed

Feige, Bernd; Spiegelhalder, Kai; Kiemen, Andrea; Bosch, Oliver G; Tebartz van Elst, Ludger; Hennig, Jürgen; Seifritz, Erich; Riemann, Dieter

2017-01-15

Functional activation as evidenced by blood oxygen level-dependent (BOLD) functional MRI changes or event-related EEG is known to closely follow patterns of stimulation or self-paced action. Any lags are compatible with axonal conduction velocities and neural integration times. The important analysis of resting state networks is generally based on the assumption that these principles also hold for spontaneous fluctuations in brain activity. Previous observations using simultaneous EEG and fMRI indicate that slower processes, with delays in the seconds range, determine at least part of the relationship between spontaneous EEG and fMRI. To assess this relationship systematically, we used deconvolution analysis of EEG-fMRI during the resting state, assessing the relationship between EEG frequency bands and fMRI BOLD across the whole brain while allowing for time lags of up to 10.5s. Cluster analysis, identifying similar BOLD time courses in relation to EEG band power peaks, showed a clear segregation of functional subsystems of the brain. Our analysis shows that fMRI BOLD increases commonly precede EEG power increases by seconds. Most zero-lag correlations, on the other hand, were negative. This indicates two main distinct neuromodulatory mechanisms: an "idling" mechanism of simultaneous electric and metabolic network anticorrelation and a "regulatory" mechanism in which metabolic network activity precedes increased EEG power by some seconds. This has to be taken into consideration in further studies which address the causal and functional relationship of metabolic and electric brain activity patterns. Copyright © 2016 Elsevier Inc. All rights reserved.

Effect of hypnosis on masseter EMG recorded during the 'resting' and a slightly open jaw posture.

PubMed

Al-Enaizan, N; Davey, K J; Lyons, M F; Cadden, S W

2015-11-01

The aim of this experimental study was to determine whether minimal levels of electromyographic activity in the masseter muscle are altered when individuals are in a verified hypnotic state. Experiments were performed on 17 volunteer subjects (8 male, 9 female) all of whom gave informed consent. The subjects were dentate and had no symptoms of pain or masticatory dysfunction. Surface electromyograms (EMGs) were made from the masseter muscles and quantified by integration following full-wave rectification and averaging. The EMGs were obtained (i) with the mandible in 'resting' posture; (ii) with the mandible voluntarily lowered (but with the lips closed); (iii) during maximum voluntary clenching (MVC). The first two recordings were made before, during and after the subjects were in a hypnotic state. Susceptibility to hypnosis was assessed with Spiegel's eye-roll test, and the existence of the hypnotic state was verified by changes in ventilatory pattern. On average, EMG levels expressed as percentages of MVC were less: (i) when the jaw was deliberately lowered as opposed to being in the postural position: (ii) during hypnosis compared with during the pre- and post-hypnotic periods. However, analysis of variance followed by post hoc tests with multiple comparison corrections (Bonferroni) revealed that only the differences between the level during hypnosis and those before and after hypnosis were statistically significant (P < 0·05). As the level of masseter EMG when the mandible was in 'resting' posture was reduced by hypnosis, it appears that part of that EMG is of biological origin. © 2015 John Wiley & Sons Ltd.

A pairwise maximum entropy model accurately describes resting-state human brain networks

PubMed Central

Watanabe, Takamitsu; Hirose, Satoshi; Wada, Hiroyuki; Imai, Yoshio; Machida, Toru; Shirouzu, Ichiro; Konishi, Seiki; Miyashita, Yasushi; Masuda, Naoki

2013-01-01

The resting-state human brain networks underlie fundamental cognitive functions and consist of complex interactions among brain regions. However, the level of complexity of the resting-state networks has not been quantified, which has prevented comprehensive descriptions of the brain activity as an integrative system. Here, we address this issue by demonstrating that a pairwise maximum entropy model, which takes into account region-specific activity rates and pairwise interactions, can be robustly and accurately fitted to resting-state human brain activities obtained by functional magnetic resonance imaging. Furthermore, to validate the approximation of the resting-state networks by the pairwise maximum entropy model, we show that the functional interactions estimated by the pairwise maximum entropy model reflect anatomical connexions more accurately than the conventional functional connectivity method. These findings indicate that a relatively simple statistical model not only captures the structure of the resting-state networks but also provides a possible method to derive physiological information about various large-scale brain networks. PMID:23340410

Resting state glutamate predicts elevated pre-stimulus alpha during self-relatedness: A combined EEG-MRS study on "rest-self overlap".

PubMed

Bai, Yu; Nakao, Takashi; Xu, Jiameng; Qin, Pengmin; Chaves, Pedro; Heinzel, Alexander; Duncan, Niall; Lane, Timothy; Yen, Nai-Shing; Tsai, Shang-Yueh; Northoff, Georg

2016-01-01

Recent studies have demonstrated neural overlap between resting state activity and self-referential processing. This "rest-self" overlap occurs especially in anterior cortical midline structures like the perigenual anterior cingulate cortex (PACC). However, the exact neurotemporal and biochemical mechanisms remain to be identified. Therefore, we conducted a combined electroencephalography (EEG)-magnetic resonance spectroscopy (MRS) study. EEG focused on pre-stimulus (e.g., prior to stimulus presentation or perception) power changes to assess the degree to which those changes can predict subjects' perception (and judgment) of subsequent stimuli as high or low self-related. MRS measured resting state concentration of glutamate, focusing on PACC. High pre-stimulus (e.g., prior to stimulus presentation or perception) alpha power significantly correlated with both perception of stimuli judged to be highly self-related and with resting state glutamate concentrations in the PACC. In sum, our results show (i) pre-stimulus (e.g., prior to stimulus presentation or perception) alpha power and resting state glutamate concentration to mediate rest-self overlap that (ii) dispose or incline subjects to assign high degrees of self-relatedness to perceptual stimuli.

Brief Report: Evidence for Normative Resting-State Physiology in Autism

ERIC Educational Resources Information Center

Nuske, Heather J.; Vivanti, Giacomo; Dissanayake, Cheryl

2014-01-01

Although the conception of autism as a disorder of abnormal resting-state physiology has a long history, the evidence remains mixed. Using state-of-the-art eye-tracking pupillometry, resting-state (tonic) pupil size was measured in children with and without autism. No group differences in tonic pupil size were found, and tonic pupil size was not…

A human brain atlas derived via n-cut parcellation of resting-state and task-based fMRI data

PubMed Central

James, G. Andrew; Hazaroglu, Onder; Bush, Keith A.

2015-01-01

The growth of functional MRI has led to development of human brain atlases derived by parcellating resting-state connectivity patterns into functionally independent regions of interest (ROIs). All functional atlases to date have been derived from resting-state fMRI data. But given that functional connectivity between regions varies with task, we hypothesized that an atlas incorporating both resting-state and task-based fMRI data would produce an atlas with finer characterization of task-relevant regions than an atlas derived from resting-state alone. To test this hypothesis, we derived parcellation atlases from twenty-nine healthy adult participants enrolled in the Cognitive Connectome project, an initiative to improve functional MRI’s translation into clinical decision-making by mapping normative variance in brain-behavior relationships. Participants underwent resting-state and task-based fMRI spanning nine cognitive domains: motor, visuospatial, attention, language, memory, affective processing, decision-making, working memory, and executive function. Spatially constrained n-cut parcellation derived brain atlases using (1) all participants’ functional data (Task) or (2) a single resting-state scan (Rest). An atlas was also derived from random parcellation for comparison purposes (Random). Two methods were compared: (1) a parcellation applied to the group’s mean edge weights (mean), and (2) a two-stage approach with parcellation of individual edge weights followed by parcellation of mean binarized edges (two-stage). The resulting Task and Rest atlases had significantly greater similarity with each other (mean Jaccard indices JI= 0.72–0.85) than with the Random atlases (JI=0.59–0.63; all p<0.001 after Bonferroni correction). Task and Rest atlas similarity was greatest for the two-stage method (JI=0.85), which has been shown as more robust than the mean method; these atlases also better reproduced voxelwise seed maps of the left dorsolateral prefrontal cortex during rest and performing the n-back working memory task (r=0.75–0.80) than the Random atlases (r=0.64–0.72), further validating their utility. We expected regions governing higher-order cognition (such as frontal and anterior temporal lobes) to show greatest difference between Task and Rest atlases; contrary to expectations, these areas had greatest similarity between atlases. Our findings indicate that atlases derived from parcellation of task-based and resting-state fMRI data are highly comparable, and existing resting-state atlases are suitable for task-based analyses. We introduce an anatomically labeled fMRI-derived whole-brain human atlas for future Cognitive Connectome analyses. PMID:26523655

A human brain atlas derived via n-cut parcellation of resting-state and task-based fMRI data.

PubMed

James, George Andrew; Hazaroglu, Onder; Bush, Keith A

2016-02-01

The growth of functional MRI has led to development of human brain atlases derived by parcellating resting-state connectivity patterns into functionally independent regions of interest (ROIs). All functional atlases to date have been derived from resting-state fMRI data. But given that functional connectivity between regions varies with task, we hypothesized that an atlas incorporating both resting-state and task-based fMRI data would produce an atlas with finer characterization of task-relevant regions than an atlas derived from resting-state alone. To test this hypothesis, we derived parcellation atlases from twenty-nine healthy adult participants enrolled in the Cognitive Connectome project, an initiative to improve functional MRI's translation into clinical decision-making by mapping normative variance in brain-behavior relationships. Participants underwent resting-state and task-based fMRI spanning nine cognitive domains: motor, visuospatial, attention, language, memory, affective processing, decision-making, working memory, and executive function. Spatially constrained n-cut parcellation derived brain atlases using (1) all participants' functional data (Task) or (2) a single resting-state scan (Rest). An atlas was also derived from random parcellation for comparison purposes (Random). Two methods were compared: (1) a parcellation applied to the group's mean edge weights (mean), and (2) a two-stage approach with parcellation of individual edge weights followed by parcellation of mean binarized edges (two-stage). The resulting Task and Rest atlases had significantly greater similarity with each other (mean Jaccard indices JI=0.72-0.85) than with the Random atlases (JI=0.59-0.63; all p<0.001 after Bonferroni correction). Task and Rest atlas similarity was greatest for the two-stage method (JI=0.85), which has been shown as more robust than the mean method; these atlases also better reproduced voxelwise seed maps of the left dorsolateral prefrontal cortex during rest and performing the n-back working memory task (r=0.75-0.80) than the Random atlases (r=0.64-0.72), further validating their utility. We expected regions governing higher-order cognition (such as frontal and anterior temporal lobes) to show greatest difference between Task and Rest atlases; contrary to expectations, these areas had greatest similarity between atlases. Our findings indicate that atlases derived from parcellation of task-based and resting-state fMRI data are highly comparable, and existing resting-state atlases are suitable for task-based analyses. We introduce an anatomically labeled fMRI-derived whole-brain human atlas for future Cognitive Connectome analyses. Copyright © 2015 Elsevier Inc. All rights reserved.

Intrinsic resting-state activity predicts working memory brain activation and behavioral performance.

PubMed

Zou, Qihong; Ross, Thomas J; Gu, Hong; Geng, Xiujuan; Zuo, Xi-Nian; Hong, L Elliot; Gao, Jia-Hong; Stein, Elliot A; Zang, Yu-Feng; Yang, Yihong

2013-12-01

Although resting-state brain activity has been demonstrated to correspond with task-evoked brain activation, the relationship between intrinsic and evoked brain activity has not been fully characterized. For example, it is unclear whether intrinsic activity can also predict task-evoked deactivation and whether the rest-task relationship is dependent on task load. In this study, we addressed these issues on 40 healthy control subjects using resting-state and task-driven [N-back working memory (WM) task] functional magnetic resonance imaging data collected in the same session. Using amplitude of low-frequency fluctuation (ALFF) as an index of intrinsic resting-state activity, we found that ALFF in the middle frontal gyrus and inferior/superior parietal lobules was positively correlated with WM task-evoked activation, while ALFF in the medial prefrontal cortex, posterior cingulate cortex, superior frontal gyrus, superior temporal gyrus, and fusiform gyrus was negatively correlated with WM task-evoked deactivation. Further, the relationship between the intrinsic resting-state activity and task-evoked activation in lateral/superior frontal gyri, inferior/superior parietal lobules, superior temporal gyrus, and midline regions was stronger at higher WM task loads. In addition, both resting-state activity and the task-evoked activation in the superior parietal lobule/precuneus were significantly correlated with the WM task behavioral performance, explaining similar portions of intersubject performance variance. Together, these findings suggest that intrinsic resting-state activity facilitates or is permissive of specific brain circuit engagement to perform a cognitive task, and that resting activity can predict subsequent task-evoked brain responses and behavioral performance. Copyright © 2012 Wiley Periodicals, Inc.

The brain’s resting state activity is shaped by synchronized cross frequency coupling of neural oscillations (Author’s Manuscript)

DTIC Science & Technology

2015-02-11

uncovered. Using magnetoencephalography ( MEG ) imaging during rest in 12 healthy subjects we analyse the resting state networks and their underlying...across the whole brain of the resting state is generated. Human magnetoencephalography ( MEG ) of the whole brain emphasized the contribution of...frequency oscillations coordinate long-range communication (Stein, Chiang, and König, 2000). However, these MEG findings do not align entirely with

Resting state low-frequency fluctuations in prefrontal cortex reflect degrees of harm avoidance and novelty seeking: an exploratory NIRS study

PubMed Central

Nakao, Takashi; Matsumoto, Tomoya; Shimizu, Daisuke; Morita, Machiko; Yoshimura, Shinpei; Northoff, Georg; Morinobu, Shigeru; Okamoto, Yasumasa; Yamawaki, Shigeto

2013-01-01

Harm avoidance (HA) and novelty seeking (NS) are temperament dimensions defined by Temperament and Character Inventory (TCI), respectively, reflecting a heritable bias for intense response to aversive stimuli or for excitement in response to novel stimuli. High HA is regarded as a risk factor for major depressive disorder and anxiety disorder. In contrast, higher NS is linked to increased risk for substance abuse and pathological gambling disorder. A growing body of evidence suggests that patients with these disorders show abnormality in the power of slow oscillations of resting-state brain activity. It is particularly interesting that previous studies have demonstrated that resting state activities in medial prefrontal cortex (MPFC) are associated with HA or NS scores, although the relation between the power of resting state slow oscillations and these temperament dimensions remains poorly elucidated. This preliminary study investigated the biological bases of these temperament traits by particularly addressing the resting state low-frequency fluctuations in MPFC. Regional hemodynamic changes in channels covering MPFC during 5-min resting states were measured from 22 healthy participants using near-infrared spectroscopy (NIRS). These data were used for correlation analyses. Results show that the power of slow oscillations during resting state around the dorsal part of MPFC is negatively correlated with the HA score. In contrast, NS was positively correlated with the power of resting state slow oscillations around the ventral part of MPFC. These results suggest that the powers of slow oscillation at rest in dorsal or ventral MPFC, respectively, reflect the degrees of HA and NS. This exploratory study therefore uncovers novel neural bases of HA and NS. We discuss a neural mechanism underlying aversion-related and reward-related processing based on results obtained from this study. PMID:24381545

Assisted closed-loop optimization of SSVEP-BCI efficiency

PubMed Central

Fernandez-Vargas, Jacobo; Pfaff, Hanns U.; Rodríguez, Francisco B.; Varona, Pablo

2012-01-01

We designed a novel assisted closed-loop optimization protocol to improve the efficiency of brain-computer interfaces (BCI) based on steady state visually evoked potentials (SSVEP). In traditional paradigms, the control over the BCI-performance completely depends on the subjects' ability to learn from the given feedback cues. By contrast, in the proposed protocol both the subject and the machine share information and control over the BCI goal. Generally, the innovative assistance consists in the delivery of online information together with the online adaptation of BCI stimuli properties. In our case, this adaptive optimization process is realized by (1) a closed-loop search for the best set of SSVEP flicker frequencies and (2) feedback of actual SSVEP magnitudes to both the subject and the machine. These closed-loop interactions between subject and machine are evaluated in real-time by continuous measurement of their efficiencies, which are used as online criteria to adapt the BCI control parameters. The proposed protocol aims to compensate for variability in possibly unknown subjects' state and trait dimensions. In a study with N = 18 subjects, we found significant evidence that our protocol outperformed classic SSVEP-BCI control paradigms. Evidence is presented that it takes indeed into account interindividual variabilities: e.g., under the new protocol, baseline resting state EEG measures predict subjects' BCI performances. This paper illustrates the promising potential of assisted closed-loop protocols in BCI systems. Probably their applicability might be expanded to innovative uses, e.g., as possible new diagnostic/therapeutic tools for clinical contexts and as new paradigms for basic research. PMID:23443214

Assisted closed-loop optimization of SSVEP-BCI efficiency.

PubMed

Fernandez-Vargas, Jacobo; Pfaff, Hanns U; Rodríguez, Francisco B; Varona, Pablo

2013-01-01

We designed a novel assisted closed-loop optimization protocol to improve the efficiency of brain-computer interfaces (BCI) based on steady state visually evoked potentials (SSVEP). In traditional paradigms, the control over the BCI-performance completely depends on the subjects' ability to learn from the given feedback cues. By contrast, in the proposed protocol both the subject and the machine share information and control over the BCI goal. Generally, the innovative assistance consists in the delivery of online information together with the online adaptation of BCI stimuli properties. In our case, this adaptive optimization process is realized by (1) a closed-loop search for the best set of SSVEP flicker frequencies and (2) feedback of actual SSVEP magnitudes to both the subject and the machine. These closed-loop interactions between subject and machine are evaluated in real-time by continuous measurement of their efficiencies, which are used as online criteria to adapt the BCI control parameters. The proposed protocol aims to compensate for variability in possibly unknown subjects' state and trait dimensions. In a study with N = 18 subjects, we found significant evidence that our protocol outperformed classic SSVEP-BCI control paradigms. Evidence is presented that it takes indeed into account interindividual variabilities: e.g., under the new protocol, baseline resting state EEG measures predict subjects' BCI performances. This paper illustrates the promising potential of assisted closed-loop protocols in BCI systems. Probably their applicability might be expanded to innovative uses, e.g., as possible new diagnostic/therapeutic tools for clinical contexts and as new paradigms for basic research.

A Brief History of the Resting State: the Washington University Perspective

PubMed Central

Snyder, Abraham Z.; Raichle, Marcus E.

2012-01-01

We present a history of the concepts and developments that have led us to focus on the resting state as an object of study. We then discuss resting state research performed in our laboratory since 2005 with an emphasis on papers of particular interest. PMID:22266172

EEG correlates of a mental arithmetic task in patients with first episode schizophrenia and schizoaffective disorder.

PubMed

Garakh, Zhanna; Zaytseva, Yuliya; Kapranova, Alexandra; Fiala, Ondrej; Horacek, Jiri; Shmukler, Alexander; Gurovich, Isaac Ya; Strelets, Valeria B

2015-11-01

To evaluate the spectral power of the cortical bands in patients with first episode schizophrenia and schizoaffective disorder at rest and during the performance of a mental arithmetic task. We analyzed EEG spectral power (SP) in the resting state and subsequently while counting down from 200 in steps of 7, in 32 first episode schizophrenia patients (SZ), 32 patients with first episode schizoaffective disorder (SA) and healthy controls (HC, n=40). Behavioral parameters such as accuracy and counting speed were also evaluated. Both SZ and SA patients were slower in counting than HC, no difference was obtained in the accuracy and counting speed in the patient groups. In the resting state patients showed elevated midline theta power, off-midline anterior beta 2 power and decreased central/posterior alpha power. The SA group occupied an intermediate position between the schizophrenia patients and controls. In task performance patients lacked a typical increase of midline theta, left anterior beta 2, and anterior gamma power; however, schizoaffective patients demonstrated a growing trend of power in the gamma band in left anterior off-midline sites similar to HC. Moreover, alpha power was less inhibited in schizoaffective patients and more pronounced in schizophrenia patients indicating distinct inhibitory mechanisms in these psychotic disorders. Patients with SA demonstrate less alteration in the spectral power of bands at rest than SZ, and present spectral power changes during cognitive task performance close to the controls. Our study contributes to the present evidence on the neurophysiological distinction between schizophrenia and schizoaffective disorder. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Resting-state abnormalities in amnestic mild cognitive impairment: a meta-analysis.

PubMed

Lau, W K W; Leung, M-K; Lee, T M C; Law, A C K

2016-04-26

Amnestic mild cognitive impairment (aMCI) is a prodromal stage of Alzheimer's disease (AD). As no effective drug can cure AD, early diagnosis and intervention for aMCI are urgently needed. The standard diagnostic procedure for aMCI primarily relies on subjective neuropsychological examinations that require the judgment of experienced clinicians. The development of other objective and reliable aMCI markers, such as neural markers, is therefore required. Previous neuroimaging findings revealed various abnormalities in resting-state activity in MCI patients, but the findings have been inconsistent. The current study provides an updated activation likelihood estimation meta-analysis of resting-state functional magnetic resonance imaging (fMRI) data on aMCI. The authors searched on the MEDLINE/PubMed databases for whole-brain resting-state fMRI studies on aMCI published until March 2015. We included 21 whole-brain resting-state fMRI studies that reported a total of 156 distinct foci. Significant regional resting-state differences were consistently found in aMCI patients relative to controls, including the posterior cingulate cortex, right angular gyrus, right parahippocampal gyrus, left fusiform gyrus, left supramarginal gyrus and bilateral middle temporal gyri. Our findings support that abnormalities in resting-state activities of these regions may serve as neuroimaging markers for aMCI.

Affective mentalizing and brain activity at rest in the behavioral variant of frontotemporal dementia.

PubMed

Caminiti, Silvia P; Canessa, Nicola; Cerami, Chiara; Dodich, Alessandra; Crespi, Chiara; Iannaccone, Sandro; Marcone, Alessandra; Falini, Andrea; Cappa, Stefano F

2015-01-01

bvFTD patients display an impairment in the attribution of cognitive and affective states to others, reflecting GM atrophy in brain regions associated with social cognition, such as amygdala, superior temporal cortex and posterior insula. Distinctive patterns of abnormal brain functioning at rest have been reported in bvFTD, but their relationship with defective attribution of affective states has not been investigated. To investigate the relationship among resting-state brain activity, gray matter (GM) atrophy and the attribution of mental states in the behavioral variant of fronto-temporal degeneration (bvFTD). We compared 12 bvFTD patients with 30 age- and education-matched healthy controls on a) performance in a task requiring the attribution of affective vs. cognitive mental states; b) metrics of resting-state activity in known functional networks; and c) the relationship between task-performances and resting-state metrics. In addition, we assessed a connection between abnormal resting-state metrics and GM atrophy. Compared with controls, bvFTD patients showed a reduction of intra-network coherent activity in several components, as well as decreased strength of activation in networks related to attentional processing. Anomalous resting-state activity involved networks which also displayed a significant reduction of GM density. In patients, compared with controls, higher affective mentalizing performance correlated with stronger functional connectivity between medial prefrontal sectors of the default-mode and attentional/performance monitoring networks, as well as with increased coherent activity in components of the executive, sensorimotor and fronto-limbic networks. Some of the observed effects may reflect specific compensatory mechanisms for the atrophic changes involving regions in charge of affective mentalizing. The analysis of specific resting-state networks thus highlights an intermediate level of analysis between abnormal brain structure and impaired behavioral performance in bvFTD, reflecting both dysfunction and compensation mechanisms.

40 CFR 81.329 - Nevada.

Code of Federal Regulations, 2010 CFR

2010-07-01

... on the State of Nevada Division of Water Resources' map titled Water Resources and Inter-basin Flows...-26E) X Clovers Area (64)(32-39N, 42-46E) X 1 EPA designation replaces State designation. 2 Rest of... Boulder Flat (61) (31-37N, 45-51E): Upper Unit 61 X Lower Unit 61 X Rest of State 1 X 1 Rest of State...

Measuring alterations in oscillatory brain networks in schizophrenia with resting-state MEG: State-of-the-art and methodological challenges.

PubMed

Alamian, Golnoush; Hincapié, Ana-Sofía; Pascarella, Annalisa; Thiery, Thomas; Combrisson, Etienne; Saive, Anne-Lise; Martel, Véronique; Althukov, Dmitrii; Haesebaert, Frédéric; Jerbi, Karim

2017-09-01

Neuroimaging studies provide evidence of disturbed resting-state brain networks in Schizophrenia (SZ). However, untangling the neuronal mechanisms that subserve these baseline alterations requires measurement of their electrophysiological underpinnings. This systematic review specifically investigates the contributions of resting-state Magnetoencephalography (MEG) in elucidating abnormal neural organization in SZ patients. A systematic literature review of resting-state MEG studies in SZ was conducted. This literature is discussed in relation to findings from resting-state fMRI and EEG, as well as to task-based MEG research in SZ population. Importantly, methodological limitations are considered and recommendations to overcome current limitations are proposed. Resting-state MEG literature in SZ points towards altered local and long-range oscillatory network dynamics in various frequency bands. Critical methodological challenges with respect to experiment design, and data collection and analysis need to be taken into consideration. Spontaneous MEG data show that local and global neural organization is altered in SZ patients. MEG is a highly promising tool to fill in knowledge gaps about the neurophysiology of SZ. However, to reach its fullest potential, basic methodological challenges need to be overcome. MEG-based resting-state power and connectivity findings could be great assets to clinical and translational research in psychiatry, and SZ in particular. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Manufacturing in space: Fluid dynamics numerical analysis

NASA Technical Reports Server (NTRS)

Robertson, S. J.; Nicholson, L. A.; Spradley, L. W.

1982-01-01

Numerical computations were performed for natural convection in circular enclosures under various conditions of acceleration. It was found that subcritical acceleration vectors applied in the direction of the temperature gradient will lead to an eventual state of rest regardless of the initial state of motion. Supercritical acceleration vectors will lead to the same steady state condition of motion regardless of the initial state of motion. Convection velocities were computed for acceleration vectors at various angles of the initial temperature gradient. The results for Rayleigh numbers of 1000 or less were found to closely follow Weinbaum's first order theory. Higher Rayleigh number results were shown to depart significantly from the first order theory. Supercritical behavior was confirmed for Rayleigh numbers greater than the known supercritical value of 9216. Response times were determined to provide an indication of the time required to change states of motion for the various cases considered.

Is the Internet gaming-addicted brain close to be in a pathological state?

PubMed

Park, Chang-Hyun; Chun, Ji-Won; Cho, Huyn; Jung, Young-Chul; Choi, Jihye; Kim, Dai Jin

2017-01-01

Internet gaming addiction (IGA) is becoming a common and widespread mental health concern. Although IGA induces a variety of negative psychosocial consequences, it is yet ambiguous whether the brain addicted to Internet gaming is considered to be in a pathological state. We investigated IGA-induced abnormalities of the brain specifically from the network perspective and qualitatively assessed whether the Internet gaming-addicted brain is in a state similar to the pathological brain. Topological properties of brain functional networks were examined by applying a graph-theoretical approach to analyzing functional magnetic resonance imaging data acquired during a resting state in 19 IGA adolescents and 20 age-matched healthy controls. We compared functional distance-based measures, global and local efficiency of resting state brain functional networks between the two groups to assess how the IGA subjects' brain was topologically altered from the controls' brain. The IGA subjects had severer impulsiveness and their brain functional networks showed higher global efficiency and lower local efficiency relative to the controls. These topological differences suggest that IGA induced brain functional networks to shift toward the random topological architecture, as exhibited in other pathological states. Furthermore, for the IGA subjects, the topological alterations were specifically attributable to interregional connections incident on the frontal region, and the degree of impulsiveness was associated with the topological alterations over the frontolimbic connections. The current findings lend support to the proposition that the Internet gaming-addicted brain could be in the state similar to pathological states in terms of topological characteristics of brain functional networks. © 2015 Society for the Study of Addiction.

Resting-State Functional Magnetic Resonance Imaging for Language Preoperative Planning

PubMed Central

Branco, Paulo; Seixas, Daniela; Deprez, Sabine; Kovacs, Silvia; Peeters, Ronald; Castro, São L.; Sunaert, Stefan

2016-01-01

Functional magnetic resonance imaging (fMRI) is a well-known non-invasive technique for the study of brain function. One of its most common clinical applications is preoperative language mapping, essential for the preservation of function in neurosurgical patients. Typically, fMRI is used to track task-related activity, but poor task performance and movement artifacts can be critical limitations in clinical settings. Recent advances in resting-state protocols open new possibilities for pre-surgical mapping of language potentially overcoming these limitations. To test the feasibility of using resting-state fMRI instead of conventional active task-based protocols, we compared results from fifteen patients with brain lesions while performing a verb-to-noun generation task and while at rest. Task-activity was measured using a general linear model analysis and independent component analysis (ICA). Resting-state networks were extracted using ICA and further classified in two ways: manually by an expert and by using an automated template matching procedure. The results revealed that the automated classification procedure correctly identified language networks as compared to the expert manual classification. We found a good overlay between task-related activity and resting-state language maps, particularly within the language regions of interest. Furthermore, resting-state language maps were as sensitive as task-related maps, and had higher specificity. Our findings suggest that resting-state protocols may be suitable to map language networks in a quick and clinically efficient way. PMID:26869899

A resting state functional magnetic resonance imaging study of concussion in collegiate athletes.

PubMed

Czerniak, Suzanne M; Sikoglu, Elif M; Liso Navarro, Ana A; McCafferty, Joseph; Eisenstock, Jordan; Stevenson, J Herbert; King, Jean A; Moore, Constance M

2015-06-01

Sports-related concussions are currently diagnosed through multi-domain assessment by a medical professional and may utilize neurocognitive testing as an aid. However, these tests have only been able to detect differences in the days to week post-concussion. Here, we investigate a measure of brain function, namely resting state functional connectivity, which may detect residual brain differences in the weeks to months after concussion. Twenty-one student athletes (9 concussed within 6 months of enrollment; 12 non-concussed; between ages 18 and 22 years) were recruited for this study. All participants completed the Wisconsin Card Sorting Task and the Color-Word Interference Test. Neuroimaging data, specifically resting state functional Magnetic Resonance Imaging data, were acquired to examine resting state functional connectivity. Two sample t-tests were used to compare the neurocognitive scores and resting state functional connectivity patterns among concussed and non-concussed participants. Correlations between neurocognitive scores and resting state functional connectivity measures were also determined across all subjects. There were no significant differences in neurocognitive performance between concussed and non-concussed groups. Concussed subjects had significantly increased connections between areas of the brain that underlie executive function. Across all subjects, better neurocognitive performance corresponded to stronger brain connectivity. Even at rest, brains of concussed athletes may have to 'work harder' than their healthy peers to achieve similar neurocognitive results. Resting state brain connectivity may be able to detect prolonged brain differences in concussed athletes in a more quantitative manner than neurocognitive test scores.

Patterns of resting state connectivity in human primary visual cortical areas: a 7T fMRI study.

PubMed

Raemaekers, Mathijs; Schellekens, Wouter; van Wezel, Richard J A; Petridou, Natalia; Kristo, Gert; Ramsey, Nick F

2014-01-01

The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state fluctuations map to the well known architecture of the visual system. We investigated resting state connectivity at both a fine and large scale within and across visual areas V1, V2 and V3 in ten human subjects using a 7Tesla scanner. We found evidence for several coexisting and overlapping connectivity structures at different spatial scales. At the fine-scale level we found enhanced connectivity between the same topographic locations in the fieldmaps of V1, V2 and V3, enhanced connectivity to the contralateral functional homologue, and to a lesser extent enhanced connectivity between iso-eccentric locations within the same visual area. However, by far the largest proportion of the resting state fluctuations occurred within large-scale bilateral networks. These large-scale networks mapped to some extent onto the architecture of the visual system and could thereby obscure fine-scale connectivity. In fact, most of the fine-scale connectivity only became apparent after the large-scale network fluctuations were filtered from the timeseries. We conclude that fMRI resting state fluctuations in the visual cortex may in fact be a composite signal of different overlapping sources. Isolating the different sources could enhance correlations between BOLD and electrophysiological correlates of resting state activity. © 2013 Elsevier Inc. All rights reserved.

Modifications of resting state networks in spinocerebellar ataxia type 2.

PubMed

Cocozza, Sirio; Saccà, Francesco; Cervo, Amedeo; Marsili, Angela; Russo, Cinzia Valeria; Giorgio, Sara Maria Delle Acque; De Michele, Giuseppe; Filla, Alessandro; Brunetti, Arturo; Quarantelli, Mario

2015-09-01

We aimed to investigate the integrity of the Resting State Networks in spinocerebellar ataxia type 2 (SCA2) and the correlations between the modification of these networks and clinical variables. Resting-state functional magnetic resonance imaging (RS-fMRI) data from 19 SCA2 patients and 29 healthy controls were analyzed using an independent component analysis and dual regression, controlling at voxel level for the effect of atrophy by co-varying for gray matter volume. Correlations between the resting state networks alterations and disease duration, age at onset, number of triplets, and clinical score were assessed by Spearman's coefficient, for each cluster which was significantly different in SCA2 patients compared with healthy controls. In SCA2 patients, disruption of the cerebellar components of all major resting state networks was present, with supratentorial involvement only for the default mode network. When controlling at voxel level for gray matter volume, the reduction in functional connectivity in supratentorial regions of the default mode network, and in cerebellar regions within the default mode, executive and right fronto-parietal networks, was still significant. No correlations with clinical variables were found for any of the investigated resting state networks. The SCA2 patients show significant alterations of the resting state networks, only partly explained by the atrophy. The default mode network is the only resting state network that shows also supratentorial changes, which appear unrelated to the cortical gray matter volume. Further studies are needed to assess the clinical significance of these changes. © 2015 International Parkinson and Movement Disorder Society.

Stimulus-Elicited Connectivity Influences Resting-State Connectivity Years Later in Human Development: A Prospective Study.

PubMed

Gabard-Durnam, Laurel Joy; Gee, Dylan Grace; Goff, Bonnie; Flannery, Jessica; Telzer, Eva; Humphreys, Kathryn Leigh; Lumian, Daniel Stephen; Fareri, Dominic Stephen; Caldera, Christina; Tottenham, Nim

2016-04-27

Although the functional architecture of the brain is indexed by resting-state connectivity networks, little is currently known about the mechanisms through which these networks assemble into stable mature patterns. The current study posits and tests the long-term phasic molding hypothesis that resting-state networks are gradually shaped by recurring stimulus-elicited connectivity across development by examining how both stimulus-elicited and resting-state functional connections of the human brain emerge over development at the systems level. Using a sequential design following 4- to 18-year-olds over a 2 year period, we examined the predictive associations between stimulus-elicited and resting-state connectivity in amygdala-cortical circuitry as an exemplar case (given this network's protracted development across these ages). Age-related changes in amygdala functional connectivity converged on the same regions of medial prefrontal cortex (mPFC) and inferior frontal gyrus when elicited by emotional stimuli and when measured at rest. Consistent with the long-term phasic molding hypothesis, prospective analyses for both connections showed that the magnitude of an individual's stimulus-elicited connectivity unidirectionally predicted resting-state functional connectivity 2 years later. For the amygdala-mPFC connection, only stimulus-elicited connectivity during childhood and the transition to adolescence shaped future resting-state connectivity, consistent with a sensitive period ending with adolescence for the amygdala-mPFC circuit. Together, these findings suggest that resting-state functional architecture may arise from phasic patterns of functional connectivity elicited by environmental stimuli over the course of development on the order of years. A fundamental issue in understanding the ontogeny of brain function is how resting-state (intrinsic) functional networks emerge and relate to stimulus-elicited functional connectivity. Here, we posit and test the long-term phasic molding hypothesis that resting-state network development is influenced by recurring stimulus-elicited connectivity through prospective examination of the developing human amygdala-cortical functional connections. Our results provide critical insight into how early environmental events sculpt functional network architecture across development and highlight childhood as a potential developmental period of heightened malleability for the amygdala-medial prefrontal cortex circuit. These findings have implications for how both positive and adverse experiences influence the developing brain and motivate future investigations of whether this molding mechanism reflects a general phenomenon of brain development. Copyright © 2016 the authors 0270-6474/16/364772-14$15.00/0.

Stimulus-Elicited Connectivity Influences Resting-State Connectivity Years Later in Human Development: A Prospective Study

PubMed Central

Gee, Dylan Grace; Goff, Bonnie; Flannery, Jessica; Telzer, Eva; Humphreys, Kathryn Leigh; Lumian, Daniel Stephen; Fareri, Dominic Stephen; Caldera, Christina; Tottenham, Nim

2016-01-01

Although the functional architecture of the brain is indexed by resting-state connectivity networks, little is currently known about the mechanisms through which these networks assemble into stable mature patterns. The current study posits and tests the long-term phasic molding hypothesis that resting-state networks are gradually shaped by recurring stimulus-elicited connectivity across development by examining how both stimulus-elicited and resting-state functional connections of the human brain emerge over development at the systems level. Using a sequential design following 4- to 18-year-olds over a 2 year period, we examined the predictive associations between stimulus-elicited and resting-state connectivity in amygdala-cortical circuitry as an exemplar case (given this network's protracted development across these ages). Age-related changes in amygdala functional connectivity converged on the same regions of medial prefrontal cortex (mPFC) and inferior frontal gyrus when elicited by emotional stimuli and when measured at rest. Consistent with the long-term phasic molding hypothesis, prospective analyses for both connections showed that the magnitude of an individual's stimulus-elicited connectivity unidirectionally predicted resting-state functional connectivity 2 years later. For the amygdala-mPFC connection, only stimulus-elicited connectivity during childhood and the transition to adolescence shaped future resting-state connectivity, consistent with a sensitive period ending with adolescence for the amygdala-mPFC circuit. Together, these findings suggest that resting-state functional architecture may arise from phasic patterns of functional connectivity elicited by environmental stimuli over the course of development on the order of years. SIGNIFICANCE STATEMENT A fundamental issue in understanding the ontogeny of brain function is how resting-state (intrinsic) functional networks emerge and relate to stimulus-elicited functional connectivity. Here, we posit and test the long-term phasic molding hypothesis that resting-state network development is influenced by recurring stimulus-elicited connectivity through prospective examination of the developing human amygdala-cortical functional connections. Our results provide critical insight into how early environmental events sculpt functional network architecture across development and highlight childhood as a potential developmental period of heightened malleability for the amygdala-medial prefrontal cortex circuit. These findings have implications for how both positive and adverse experiences influence the developing brain and motivate future investigations of whether this molding mechanism reflects a general phenomenon of brain development. PMID:27122035

Resting-State Neurophysiological Activity Patterns in Young People with ASD, ADHD, and ASD + ADHD

ERIC Educational Resources Information Center

Shephard, Elizabeth; Tye, Charlotte; Ashwood, Karen L.; Azadi, Bahar; Asherson, Philip; Bolton, Patrick F.; McLoughlin, Grainne

2018-01-01

Altered power of resting-state neurophysiological activity has been associated with autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), which commonly co-occur. We compared resting-state neurophysiological power in children with ASD, ADHD, co-occurring ASD + ADHD, and typically developing controls. Children with ASD…

Establishing the resting state default mode network derived from functional magnetic resonance imaging tasks as an endophenotype: A twins study.

PubMed

Korgaonkar, Mayuresh S; Ram, Kaushik; Williams, Leanne M; Gatt, Justine M; Grieve, Stuart M

2014-08-01

The resting state default mode network (DMN) has been shown to characterize a number of neurological and psychiatric disorders. Evidence suggests an underlying genetic basis for this network and hence could serve as potential endophenotype for these disorders. Heritability is a defining criterion for endophenotypes. The DMN is measured either using a resting-state functional magnetic resonance imaging (fMRI) scan or by extracting resting state activity from task-based fMRI. The current study is the first to evaluate heritability of this task-derived resting activity. 250 healthy adult twins (79 monozygotic and 46 dizygotic same sex twin pairs) completed five cognitive and emotion processing fMRI tasks. Resting state DMN functional connectivity was derived from these five fMRI tasks. We validated this approach by comparing connectivity estimates from task-derived resting activity for all five fMRI tasks, with those obtained using a dedicated task-free resting state scan in an independent cohort of 27 healthy individuals. Structural equation modeling using the classic twin design was used to estimate the genetic and environmental contributions to variance for the resting-state DMN functional connectivity. About 9-41% of the variance in functional connectivity between the DMN nodes was attributed to genetic contribution with the greatest heritability found for functional connectivity between the posterior cingulate and right inferior parietal nodes (P<0.001). Our data provide new evidence that functional connectivity measures from the intrinsic DMN derived from task-based fMRI datasets are under genetic control and have the potential to serve as endophenotypes for genetically predisposed psychiatric and neurological disorders. Copyright © 2014 Wiley Periodicals, Inc.

Age-Related Differences in Dynamic Interactions Among Default Mode, Frontoparietal Control, and Dorsal Attention Networks during Resting-State and Interference Resolution.

PubMed

Avelar-Pereira, Bárbara; Bäckman, Lars; Wåhlin, Anders; Nyberg, Lars; Salami, Alireza

2017-01-01

Resting-state fMRI (rs-fMRI) can identify large-scale brain networks, including the default mode (DMN), frontoparietal control (FPN) and dorsal attention (DAN) networks. Interactions among these networks are critical for supporting complex cognitive functions, yet the way in which they are modulated across states is not well understood. Moreover, it remains unclear whether these interactions are similarly affected in aging regardless of cognitive state. In this study, we investigated age-related differences in functional interactions among the DMN, FPN and DAN during rest and the Multi-Source Interference task (MSIT). Networks were identified using independent component analysis (ICA), and functional connectivity was measured during rest and task. We found that the FPN was more coupled with the DMN during rest and with the DAN during the MSIT. The degree of FPN-DMN connectivity was lower in older compared to younger adults, whereas no age-related differences were observed in FPN-DAN connectivity in either state. This suggests that dynamic interactions of the FPN are stable across cognitive states. The DMN and DAN were anti correlated and age-sensitive during the MSIT only, indicating variation in a task-dependent manner. Increased levels of anticorrelation from rest to task also predicted successful interference resolution. Additional analyses revealed that the degree of DMN-DAN anticorrelation during the MSIT was associated to resting cerebral blood flow (CBF) within the DMN. This suggests that reduced DMN neural activity during rest underlies an impaired ability to achieve higher levels of anticorrelation during a task. Taken together, our results suggest that only parts of age-related differences in connectivity are uncovered at rest and thus, should be studied in the functional connectome across multiple states for a more comprehensive picture.

Age-Related Differences in Dynamic Interactions Among Default Mode, Frontoparietal Control, and Dorsal Attention Networks during Resting-State and Interference Resolution

PubMed Central

Avelar-Pereira, Bárbara; Bäckman, Lars; Wåhlin, Anders; Nyberg, Lars; Salami, Alireza

2017-01-01

Resting-state fMRI (rs-fMRI) can identify large-scale brain networks, including the default mode (DMN), frontoparietal control (FPN) and dorsal attention (DAN) networks. Interactions among these networks are critical for supporting complex cognitive functions, yet the way in which they are modulated across states is not well understood. Moreover, it remains unclear whether these interactions are similarly affected in aging regardless of cognitive state. In this study, we investigated age-related differences in functional interactions among the DMN, FPN and DAN during rest and the Multi-Source Interference task (MSIT). Networks were identified using independent component analysis (ICA), and functional connectivity was measured during rest and task. We found that the FPN was more coupled with the DMN during rest and with the DAN during the MSIT. The degree of FPN-DMN connectivity was lower in older compared to younger adults, whereas no age-related differences were observed in FPN-DAN connectivity in either state. This suggests that dynamic interactions of the FPN are stable across cognitive states. The DMN and DAN were anti correlated and age-sensitive during the MSIT only, indicating variation in a task-dependent manner. Increased levels of anticorrelation from rest to task also predicted successful interference resolution. Additional analyses revealed that the degree of DMN-DAN anticorrelation during the MSIT was associated to resting cerebral blood flow (CBF) within the DMN. This suggests that reduced DMN neural activity during rest underlies an impaired ability to achieve higher levels of anticorrelation during a task. Taken together, our results suggest that only parts of age-related differences in connectivity are uncovered at rest and thus, should be studied in the functional connectome across multiple states for a more comprehensive picture. PMID:28588476

Brain electric correlates of strong belief in paranormal phenomena: intracerebral EEG source and regional Omega complexity analyses.

PubMed

Pizzagalli, D; Lehmann, D; Gianotti, L; Koenig, T; Tanaka, H; Wackermann, J; Brugger, P

2000-12-22

The neurocognitive processes underlying the formation and maintenance of paranormal beliefs are important for understanding schizotypal ideation. Behavioral studies indicated that both schizotypal and paranormal ideation are based on an overreliance on the right hemisphere, whose coarse rather than focussed semantic processing may favor the emergence of 'loose' and 'uncommon' associations. To elucidate the electrophysiological basis of these behavioral observations, 35-channel resting EEG was recorded in pre-screened female strong believers and disbelievers during resting baseline. EEG data were subjected to FFT-Dipole-Approximation analysis, a reference-free frequency-domain dipole source modeling, and Regional (hemispheric) Omega Complexity analysis, a linear approach estimating the complexity of the trajectories of momentary EEG map series in state space. Compared to disbelievers, believers showed: more right-located sources of the beta2 band (18.5-21 Hz, excitatory activity); reduced interhemispheric differences in Omega complexity values; higher scores on the Magical Ideation scale; more general negative affect; and more hypnagogic-like reveries after a 4-min eyes-closed resting period. Thus, subjects differing in their declared paranormal belief displayed different active, cerebral neural populations during resting, task-free conditions. As hypothesized, believers showed relatively higher right hemispheric activation and reduced hemispheric asymmetry of functional complexity. These markers may constitute the neurophysiological basis for paranormal and schizotypal ideation.

Temporal reliability and lateralization of the resting-state language network.

PubMed

Zhu, Linlin; Fan, Yang; Zou, Qihong; Wang, Jue; Gao, Jia-Hong; Niu, Zhendong

2014-01-01

The neural processing loop of language is complex but highly associated with Broca's and Wernicke's areas. The left dominance of these two areas was the earliest observation of brain asymmetry. It was demonstrated that the language network and its functional asymmetry during resting state were reproducible across institutions. However, the temporal reliability of resting-state language network and its functional asymmetry are still short of knowledge. In this study, we established a seed-based resting-state functional connectivity analysis of language network with seed regions located at Broca's and Wernicke's areas, and investigated temporal reliability of language network and its functional asymmetry. The language network was found to be temporally reliable in both short- and long-term. In the aspect of functional asymmetry, the Broca's area was found to be left lateralized, while the Wernicke's area is mainly right lateralized. Functional asymmetry of these two areas revealed high short- and long-term reliability as well. In addition, the impact of global signal regression (GSR) on reliability of the resting-state language network was investigated, and our results demonstrated that GSR had negligible effect on the temporal reliability of the resting-state language network. Our study provided methodology basis for future cross-culture and clinical researches of resting-state language network and suggested priority of adopting seed-based functional connectivity for its high reliability.

Temporal Reliability and Lateralization of the Resting-State Language Network

PubMed Central

Zou, Qihong; Wang, Jue; Gao, Jia-Hong; Niu, Zhendong

2014-01-01

The neural processing loop of language is complex but highly associated with Broca's and Wernicke's areas. The left dominance of these two areas was the earliest observation of brain asymmetry. It was demonstrated that the language network and its functional asymmetry during resting state were reproducible across institutions. However, the temporal reliability of resting-state language network and its functional asymmetry are still short of knowledge. In this study, we established a seed-based resting-state functional connectivity analysis of language network with seed regions located at Broca's and Wernicke's areas, and investigated temporal reliability of language network and its functional asymmetry. The language network was found to be temporally reliable in both short- and long-term. In the aspect of functional asymmetry, the Broca's area was found to be left lateralized, while the Wernicke's area is mainly right lateralized. Functional asymmetry of these two areas revealed high short- and long-term reliability as well. In addition, the impact of global signal regression (GSR) on reliability of the resting-state language network was investigated, and our results demonstrated that GSR had negligible effect on the temporal reliability of the resting-state language network. Our study provided methodology basis for future cross-culture and clinical researches of resting-state language network and suggested priority of adopting seed-based functional connectivity for its high reliability. PMID:24475058

Altered regional homogeneity in patients with late monocular blindness: a resting-state functional MRI study

PubMed Central

Huang, Xin; Ye, Cheng-Long; Zhong, Yu-Lin; Ye, Lei; Yang, Qi-Chen; Li, Hai-Jun; Jiang, Nan; Peng, De-Chang

2017-01-01

Many previous studies have demonstrated that the blindness patients have has functional and anatomical abnormalities in the visual and other vision-related cortex. However, changes in the brain function in late monocular blindness (MB) at rest are largely unknown. In this study, we investigated the underlying regional homogeneity (ReHo) of brain-activity abnormalities in patients with late MB and their relationship with clinical features. A total of 32 patients with MB (25 male and seven female) and 32 healthy controls (HCs) (25 male and seven female) closely matched in age, sex, and education underwent resting-state functional MRI scans. The ReHo method was used to assess local features of spontaneous brain activities. Patients with MB were distinguishable from HCs using the receiver operating characteristic curve. The relationship between the mean ReHo in brain regions and the behavioral performance was calculated using correlation analysis. Compared with HCs, patients with MB showed significantly decreased ReHo values in the right rectal gyrus, right cuneus, right anterior cingulate, and right lateral occipital cortex and increased ReHo values in the right inferior temporal gyrus, right frontal middle orbital, left posterior cingulate/precuneus, and left middle frontal gyrus. However, there was no significant relationship between the different mean ReHo values in the brain regions and the clinical features. Late MB involves abnormalities of the visual cortex and other vision-related brain regions, which may reflect brain dysfunction in these regions. PMID:28858036

The role of resting-state EEG localized activation and central nervous system arousal in executive function performance in children with Attention-Deficit/Hyperactivity Disorder.

PubMed

Zhang, Da-Wei; Johnstone, Stuart J; Roodenrys, Steven; Luo, Xiangsheng; Li, Hui; Wang, Encong; Zhao, Qihua; Song, Yan; Liu, Lu; Qian, Qiujin; Wang, Yufeng; Sun, Li

2018-06-01

This study explored the relationships between resting-state electroencephalogram (RS-EEG) localized activation and two important types of executive functions (EF) to extend the prognostic utilization of RS-EEG in children with Attention-Deficit/Hyperactivity Disorder (AD/HD). Also, the role of central nervous system (CNS) arousal in the relationships was examined. Fifty-eight children with AD/HD participated in the study. RS-EEG localized activation was derived from spectral power differences between EEG in eyes-closed and eyes-open conditions. CNS arousal was measured based on alpha band power. Common and everyday EF scores were obtained as EF outcomes. Frontal delta activation predicted common EF ability and posterior alpha activation predicted everyday EF. A serial mediation analysis found that lower CNS baseline arousal was related to greater arousal and delta activation in series, which in turn related to worse common EF. A follow-up study found that baseline arousal was related to larger interference cost. RS-EEG is indicative of individual differences in two important types of EF in children with AD/HD. Lower CNS arousal may be a driving force for the poorer common EF performance. The current study supports prognostic utilization of RS-EEG and AD/HD models that take resting brain activity into consideration in children with AD/HD. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Strength of Default Mode Resting-State Connectivity Relates to White Matter Integrity in Children

ERIC Educational Resources Information Center

Gordon, Evan M.; Lee, Philip S.; Maisog, Jose M.; Foss-Feig, Jennifer; Billington, Michael E.; VanMeter, John; Vaidya, Chandan J.

2011-01-01

A default mode network of brain regions is known to demonstrate coordinated activity during the resting state. While the default mode network is well characterized in adults, few investigations have focused upon its development. We scanned 9-13-year-old children with diffusion tensor imaging and resting-state functional magnetic resonance imaging.…

Local Network-Level Integration Mediates Effects of Transcranial Alternating Current Stimulation.

PubMed

Fuscà, Marco; Ruhnau, Philipp; Neuling, Toralf; Weisz, Nathan

2018-05-01

Transcranial alternating current stimulation (tACS) has been proposed as a tool to draw causal inferences on the role of oscillatory activity in cognitive functioning and has the potential to induce long-term changes in cerebral networks. However, effectiveness of tACS underlies high variability and dependencies, which, as previous modeling works have suggested, may be mediated by local and network-level brain states. We used magnetoencephalography to record brain activity from 17 healthy participants at rest as they kept their eyes open (EO) or eyes closed (EC) while being stimulated with sham, weak, or strong alpha-tACS using a montage commonly assumed to target occipital areas. We reconstructed the activity of sources in all stimulation conditions by means of beamforming. The analysis of resting-state brain activity revealed an interaction of the external stimulation with the endogenous alpha power increase from EO to EC. This interaction was localized to the posterior cingulate, a region remote from occipital cortex. This suggests state-dependent (EO vs. EC) long-range effects of tACS. In a follow-up analysis of this online-tACS effect, we find evidence that this state-dependency effect is mediated by functional network changes: connection strength from the precuneus was significantly correlated with the state-dependency effect in the posterior cingulate during tACS. No analogous correlation could be found for alpha power modulations in occipital cortex. Altogether, this is the first strong evidence to illustrate how functional network architectures can shape tACS effects.

What is the best?: simple versus visitor restricted rest period.

PubMed

Silvius-Byron, Stephanie A; Florimonte, Christine; Panganiban, Elizabeth G; Ulmer, Janice Fitzgerald

2014-05-01

The aim of this study was to compare a highly structured planned rest protocol that includes visitor and healthcare personnel restrictions with a simple planned rest period that encourages patients to rest during a designated time without restriction of visitors and healthcare personnel. Many hospitals acute care have begun to restrict visitors and nonessential health team interventions during specific times despite the lack of experimentally designed studies. Using a convenience sample of 52 intermediate care unit patients, a randomized experimental design study compared a highly structured planned rest protocol with restriction of visitors/healthcare personnel to a simple planned rest period without restrictions. The primary outcome variable was the patient's perceived quality of rest after a 2-hour rest period. Intermediate care patients' perception of rest and sleep during a designated rest period was similar whether elaborate rest strategies were used, including visitor and healthcare personnel restrictions, or if it was only suggested they rest and the door to their room closed. The restriction of visitors and healthcare personnel during a 2-hour rest period did not improve the patient's perception of rest or how long it took them to go to sleep.

Spatiotemporal psychopathology I: No rest for the brain's resting state activity in depression? Spatiotemporal psychopathology of depressive symptoms.

PubMed

Northoff, Georg

2016-01-15

Despite intense neurobiological investigation in psychiatric disorders like major depressive disorder (MDD), the basic disturbance that underlies the psychopathological symptoms of MDD remains, nevertheless, unclear. Neuroimaging has focused mainly on the brain's extrinsic activity, specifically task-evoked or stimulus-induced activity, as related to the various sensorimotor, affective, cognitive, and social functions. Recently, the focus has shifted to the brain's intrinsic activity, otherwise known as its resting state activity. While various abnormalities have been observed during this activity, their meaning and significance for depression, along with its various psychopathological symptoms, are yet to be defined. Based on findings in healthy brain resting state activity and its particular spatial and temporal structure - defined in a functional and physiological sense rather than anatomical and structural - I claim that the various depressive symptoms are spatiotemporal disturbances of the resting state activity and its spatiotemporal structure. This is supported by recent findings that link ruminations and increased self-focus in depression to abnormal spatial organization of resting state activity. Analogously, affective and cognitive symptoms like anhedonia, suicidal ideation, and thought disorder can be traced to an increased focus on the past, increased past-focus as basic temporal disturbance o the resting state. Based on these findings, I conclude that the various depressive symptoms must be conceived as spatiotemporal disturbances of the brain's resting state's activity and its spatiotemporal structure. Importantly, this entails a new form of psychopathology, "Spatiotemporal Psychopathology" that directly links the brain and psyche, therefore having major diagnostic and therapeutic implications for clinical practice. Copyright © 2015 Elsevier B.V. All rights reserved.

Simultaneous tDCS-fMRI Identifies Resting State Networks Correlated with Visual Search Enhancement.

PubMed

Callan, Daniel E; Falcone, Brian; Wada, Atsushi; Parasuraman, Raja

2016-01-01

This study uses simultaneous transcranial direct current stimulation (tDCS) and functional MRI (fMRI) to investigate tDCS modulation of resting state activity and connectivity that underlies enhancement in behavioral performance. The experiment consisted of three sessions within the fMRI scanner in which participants conducted a visual search task: Session 1: Pre-training (no performance feedback), Session 2: Training (performance feedback given), Session 3: Post-training (no performance feedback). Resting state activity was recorded during the last 5 min of each session. During the 2nd session one group of participants underwent 1 mA tDCS stimulation and another underwent sham stimulation over the right posterior parietal cortex. Resting state spontaneous activity, as measured by fractional amplitude of low frequency fluctuations (fALFF), for session 2 showed significant differences between the tDCS stim and sham groups in the precuneus. Resting state functional connectivity from the precuneus to the substantia nigra, a subcortical dopaminergic region, was found to correlate with future improvement in visual search task performance for the stim over the sham group during active stimulation in session 2. The after-effect of stimulation on resting state functional connectivity was measured following a post-training experimental session (session 3). The left cerebellum Lobule VIIa Crus I showed performance related enhancement in resting state functional connectivity for the tDCS stim over the sham group. The ability to determine the relationship that the relative strength of resting state functional connectivity for an individual undergoing tDCS has on future enhancement in behavioral performance has wide ranging implications for neuroergonomic as well as therapeutic, and rehabilitative applications.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons.

PubMed

Ma, Ying; Shaik, Mohammed A; Kozberg, Mariel G; Kim, Sharon H; Portes, Jacob P; Timerman, Dmitriy; Hillman, Elizabeth M C

2016-12-27

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

PubMed Central

Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

2016-01-01

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609

Neonatal brain resting-state functional connectivity imaging modalities.

PubMed

Mohammadi-Nejad, Ali-Reza; Mahmoudzadeh, Mahdi; Hassanpour, Mahlegha S; Wallois, Fabrice; Muzik, Otto; Papadelis, Christos; Hansen, Anne; Soltanian-Zadeh, Hamid; Gelovani, Juri; Nasiriavanaki, Mohammadreza

2018-06-01

Infancy is the most critical period in human brain development. Studies demonstrate that subtle brain abnormalities during this state of life may greatly affect the developmental processes of the newborn infants. One of the rapidly developing methods for early characterization of abnormal brain development is functional connectivity of the brain at rest. While the majority of resting-state studies have been conducted using magnetic resonance imaging (MRI), there is clear evidence that resting-state functional connectivity (rs-FC) can also be evaluated using other imaging modalities. The aim of this review is to compare the advantages and limitations of different modalities used for the mapping of infants' brain functional connectivity at rest. In addition, we introduce photoacoustic tomography, a novel functional neuroimaging modality, as a complementary modality for functional mapping of infants' brain.

Lag threads organize the brain’s intrinsic activity

PubMed Central

Mitra, Anish; Snyder, Abraham Z.; Blazey, Tyler; Raichle, Marcus E.

2015-01-01

It has been widely reported that intrinsic brain activity, in a variety of animals including humans, is spatiotemporally structured. Specifically, propagated slow activity has been repeatedly demonstrated in animals. In human resting-state fMRI, spontaneous activity has been understood predominantly in terms of zero-lag temporal synchrony within widely distributed functional systems (resting-state networks). Here, we use resting-state fMRI from 1,376 normal, young adults to demonstrate that multiple, highly reproducible, temporal sequences of propagated activity, which we term “lag threads,” are present in the brain. Moreover, this propagated activity is largely unidirectional within conventionally understood resting-state networks. Modeling experiments show that resting-state networks naturally emerge as a consequence of shared patterns of propagation. An implication of these results is that common physiologic mechanisms may underlie spontaneous activity as imaged with fMRI in humans and slowly propagated activity as studied in animals. PMID:25825720

Circadian rhythm asynchrony in man during hypokinesis.

NASA Technical Reports Server (NTRS)

Winget, C. M.; Vernikos-Danellis, J.; Cronin, S. E.; Leach, C. S.; Rambaut, P. C.; Mack, P. B.

1972-01-01

Posture and exercise were investigated as synchronizers of certain physiologic rhythms in eight healthy male subjects in a defined environment. Four subjects exercised during bed rest. Body temperature (BT), heart rate, plasma thyroid hormone, and plasma steroid data were obtained from the subjects for a 6-day ambulatory equilibration period before bed rest, 56 days of bed rest, and a 10-day recovery period after bed rest. The results indicate that the mechanism regulating the circadian rhythmicity of the cardiovascular system is rigorously controlled and independent of the endocrine system, while the BT rhythm is more closely aligned to the endocrine system.

Resting-state connectivity predicts visuo-motor skill learning.

PubMed

Manuel, Aurélie L; Guggisberg, Adrian G; Thézé, Raphaël; Turri, Francesco; Schnider, Armin

2018-08-01

Spontaneous brain activity at rest is highly organized even when the brain is not explicitly engaged in a task. Functional connectivity (FC) in the alpha frequency band (α, 8-12 Hz) during rest is associated with improved performance on various cognitive and motor tasks. In this study we explored how FC is associated with visuo-motor skill learning and offline consolidation. We tested two hypotheses by which resting-state FC might achieve its impact on behavior: preparing the brain for an upcoming task or consolidating training gains. Twenty-four healthy participants were assigned to one of two groups: The experimental group (n = 12) performed a computerized mirror-drawing task. The control group (n = 12) performed a similar task but with concordant cursor direction. High-density 156-channel resting-state EEG was recorded before and after learning. Subjects were tested for offline consolidation 24h later. The Experimental group improved during training and showed offline consolidation. Increased α-FC between the left superior parietal cortex and the rest of the brain before training and decreased α-FC in the same region after training predicted learning. Resting-state FC following training did not predict offline consolidation and none of these effects were present in controls. These findings indicate that resting-state alpha-band FC is primarily implicated in providing optimal neural resources for upcoming tasks. Copyright © 2018 Elsevier Inc. All rights reserved.

Broadband Electrophysiological Dynamics Contribute to Global Resting-State fMRI Signal.

PubMed

Wen, Haiguang; Liu, Zhongming

2016-06-01

Spontaneous activity observed with resting-state fMRI is used widely to uncover the brain's intrinsic functional networks in health and disease. Although many networks appear modular and specific, global and nonspecific fMRI fluctuations also exist and both pose a challenge and present an opportunity for characterizing and understanding brain networks. Here, we used a multimodal approach to investigate the neural correlates to the global fMRI signal in the resting state. Like fMRI, resting-state power fluctuations of broadband and arrhythmic, or scale-free, macaque electrocorticography and human magnetoencephalography activity were correlated globally. The power fluctuations of scale-free human electroencephalography (EEG) were coupled with the global component of simultaneously acquired resting-state fMRI, with the global hemodynamic change lagging the broadband spectral change of EEG by ∼5 s. The levels of global and nonspecific fluctuation and synchronization in scale-free population activity also varied across and depended on arousal states. Together, these results suggest that the neural origin of global resting-state fMRI activity is the broadband power fluctuation in scale-free population activity observable with macroscopic electrical or magnetic recordings. Moreover, the global fluctuation in neurophysiological and hemodynamic activity is likely modulated through diffuse neuromodulation pathways that govern arousal states and vigilance levels. This study provides new insights into the neural origin of resting-state fMRI. Results demonstrate that the broadband power fluctuation of scale-free electrophysiology is globally synchronized and directly coupled with the global component of spontaneous fMRI signals, in contrast to modularly synchronized fluctuations in oscillatory neural activity. These findings lead to a new hypothesis that scale-free and oscillatory neural processes account for global and modular patterns of functional connectivity observed with resting-state fMRI, respectively. Copyright © 2016 the authors 0270-6474/16/366030-11$15.00/0.

Affective mentalizing and brain activity at rest in the behavioral variant of frontotemporal dementia

PubMed Central

Caminiti, Silvia P.; Canessa, Nicola; Cerami, Chiara; Dodich, Alessandra; Crespi, Chiara; Iannaccone, Sandro; Marcone, Alessandra; Falini, Andrea; Cappa, Stefano F.

2015-01-01

Background bvFTD patients display an impairment in the attribution of cognitive and affective states to others, reflecting GM atrophy in brain regions associated with social cognition, such as amygdala, superior temporal cortex and posterior insula. Distinctive patterns of abnormal brain functioning at rest have been reported in bvFTD, but their relationship with defective attribution of affective states has not been investigated. Objective To investigate the relationship among resting-state brain activity, gray matter (GM) atrophy and the attribution of mental states in the behavioral variant of fronto-temporal degeneration (bvFTD). Methods We compared 12 bvFTD patients with 30 age- and education-matched healthy controls on a) performance in a task requiring the attribution of affective vs. cognitive mental states; b) metrics of resting-state activity in known functional networks; and c) the relationship between task-performances and resting-state metrics. In addition, we assessed a connection between abnormal resting-state metrics and GM atrophy. Results Compared with controls, bvFTD patients showed a reduction of intra-network coherent activity in several components, as well as decreased strength of activation in networks related to attentional processing. Anomalous resting-state activity involved networks which also displayed a significant reduction of GM density. In patients, compared with controls, higher affective mentalizing performance correlated with stronger functional connectivity between medial prefrontal sectors of the default-mode and attentional/performance monitoring networks, as well as with increased coherent activity in components of the executive, sensorimotor and fronto-limbic networks. Conclusions Some of the observed effects may reflect specific compensatory mechanisms for the atrophic changes involving regions in charge of affective mentalizing. The analysis of specific resting-state networks thus highlights an intermediate level of analysis between abnormal brain structure and impaired behavioral performance in bvFTD, reflecting both dysfunction and compensation mechanisms. PMID:26594631

Anti-correlated cortical networks of intrinsic connectivity in the rat brain.

PubMed

Schwarz, Adam J; Gass, Natalia; Sartorius, Alexander; Risterucci, Celine; Spedding, Michael; Schenker, Esther; Meyer-Lindenberg, Andreas; Weber-Fahr, Wolfgang

2013-01-01

In humans, resting-state blood oxygen level-dependent (BOLD) signals in the default mode network (DMN) are temporally anti-correlated with those from a lateral cortical network involving the frontal eye fields, secondary somatosensory and posterior insular cortices. Here, we demonstrate the existence of an analogous lateral cortical network in the rat brain, extending laterally from anterior secondary sensorimotor regions to the insular cortex and exhibiting low-frequency BOLD fluctuations that are temporally anti-correlated with a midline "DMN-like" network comprising posterior/anterior cingulate and prefrontal cortices. The primary nexus for this anti-correlation relationship was the anterior secondary motor cortex, close to regions that have been identified with frontal eye fields in the rat brain. The anti-correlation relationship was corroborated after global signal removal, underscoring this finding as a robust property of the functional connectivity signature in the rat brain. These anti-correlated networks demonstrate strong anatomical homology to networks identified in human and monkey connectivity studies, extend the known preserved functional connectivity relationships between rodent and primates, and support the use of resting-state functional magnetic resonance imaging as a translational imaging method between rat models and humans.

Anti-Correlated Cortical Networks of Intrinsic Connectivity in the Rat Brain

PubMed Central

Gass, Natalia; Sartorius, Alexander; Risterucci, Celine; Spedding, Michael; Schenker, Esther; Meyer-Lindenberg, Andreas; Weber-Fahr, Wolfgang

2013-01-01

Abstract In humans, resting-state blood oxygen level-dependent (BOLD) signals in the default mode network (DMN) are temporally anti-correlated with those from a lateral cortical network involving the frontal eye fields, secondary somatosensory and posterior insular cortices. Here, we demonstrate the existence of an analogous lateral cortical network in the rat brain, extending laterally from anterior secondary sensorimotor regions to the insular cortex and exhibiting low-frequency BOLD fluctuations that are temporally anti-correlated with a midline “DMN-like” network comprising posterior/anterior cingulate and prefrontal cortices. The primary nexus for this anti-correlation relationship was the anterior secondary motor cortex, close to regions that have been identified with frontal eye fields in the rat brain. The anti-correlation relationship was corroborated after global signal removal, underscoring this finding as a robust property of the functional connectivity signature in the rat brain. These anti-correlated networks demonstrate strong anatomical homology to networks identified in human and monkey connectivity studies, extend the known preserved functional connectivity relationships between rodent and primates, and support the use of resting-state functional magnetic resonance imaging as a translational imaging method between rat models and humans. PMID:23919836

Altered Functional Connectivity of Cognitive-Related Cerebellar Subregions in Alzheimer’s Disease

PubMed Central

Zheng, Weimin; Liu, Xingyun; Song, Haiqing; Li, Kuncheng; Wang, Zhiqun

2017-01-01

Alzheimer’s disease (AD) is the most common cause of dementia. Previous studies have found disrupted resting state functional connectivities (rsFCs) in various brain networks in the AD patients. However, few studies have focused on the rsFCs of the cerebellum and its sub-regions in the AD patients. In this study, we collected resting-state functional magnetic resonance imaging (rs-fMRI) data including 32 AD patients and 38 healthy controls (HCs). We selected two cognitive-related subregions of the cerebellum as seed region and mapped the whole-brain rsFCs for each subregion. We identified several distinct rsFC patterns of the two cognitive-related cerebellar subregions: default-mode network (DMN), frontoparietal network (FPN), visual network (VN) and sensorimotor network (SMN). Compared with the controls, the AD patients showed disrupted rsFCs in several different networks (DMN, VN and SMN), predicting the impairment of the functional integration in the cerebellum. Notably, these abnormal rsFCs of the two cerebellar subregions were closely associated with cognitive performance. Collectively, we demonstrated the distinct rsFCs patterns of cerebellar sub-regions with various functional networks, which were differentially impaired in the AD patients. PMID:28559843

Caffeine reduces resting-state BOLD functional connectivity in the motor cortex.

PubMed

Rack-Gomer, Anna Leigh; Liau, Joy; Liu, Thomas T

2009-05-15

In resting-state functional magnetic resonance imaging (fMRI), correlations between spontaneous low-frequency fluctuations in the blood oxygenation level dependent (BOLD) signal are used to assess functional connectivity between different brain regions. Changes in resting-state BOLD connectivity measures are typically interpreted as changes in coherent neural activity across spatially distinct brain regions. However, this interpretation can be complicated by the complex dependence of the BOLD signal on both neural and vascular factors. For example, prior studies have shown that vasoactive agents that alter baseline cerebral blood flow, such as caffeine and carbon dioxide, can significantly alter the amplitude and dynamics of the task-related BOLD response. In this study, we examined the effect of caffeine (200 mg dose) on resting-state BOLD connectivity in the motor cortex across a sample of healthy young subjects (N=9). We found that caffeine significantly (p<0.05) reduced measures of resting-state BOLD connectivity in the motor cortex. Baseline cerebral blood flow and spectral energy in the low-frequency BOLD fluctuations were also significantly decreased by caffeine. These results suggest that caffeine usage should be carefully considered in the design and interpretation of resting-state BOLD fMRI studies.

Chiral tunneling of topological states: towards the efficient generation of spin current using spin-momentum locking.

PubMed

Habib, K M Masum; Sajjad, Redwan N; Ghosh, Avik W

2015-05-01

We show that the interplay between chiral tunneling and spin-momentum locking of helical surface states leads to spin amplification and filtering in a 3D topological insulator (TI). Our calculations show that the chiral tunneling across a TI pn junction allows normally incident electrons to transmit, while the rest are reflected with their spins flipped due to spin-momentum locking. The net result is that the spin current is enhanced while the dissipative charge current is simultaneously suppressed, leading to an extremely large, gate-tunable spin-to-charge current ratio (∼20) at the reflected end. At the transmitted end, the ratio stays close to 1 and the electrons are completely spin polarized.

Energy levels of a scalar particle in a static gravitational field close to the black hole limit

NASA Astrophysics Data System (ADS)

Gossel, G. H.; Berengut, J. C.; Flambaum, V. V.

2011-10-01

The bound-state energy levels of a scalar particle in the gravitational field of finite-sized objects with interiors described by the Florides and Schwarzschild metrics are found. For these metrics, bound states with zero energy (where the binding energy is equal to the rest mass of the scalar particle) only exist when a singularity occurs in the metric. Therefore, in contrast to the Coulomb case, no pairs are produced in the non-singular static metric. For the Florides metric the singularity occurs in the black hole limit, while for the Schwarzschild interior metric it corresponds to infinite pressure at the center. Moreover, the energy spectrum is shown to become quasi-continuous as the metric becomes singular.

Tremor frequency characteristics in Parkinson's disease under resting-state and stress-state conditions.

PubMed

Lee, Hong Ji; Lee, Woong Woo; Kim, Sang Kyong; Park, Hyeyoung; Jeon, Hyo Seon; Kim, Han Byul; Jeon, Beom S; Park, Kwang Suk

2016-03-15

Tremor characteristics-amplitude and frequency components-are primary quantitative clinical factors for diagnosis and monitoring of tremors. Few studies have investigated how different patient's conditions affect tremor frequency characteristics in Parkinson's disease (PD). Here, we analyzed tremor characteristics under resting-state and stress-state conditions. Tremor was recorded using an accelerometer on the finger, under resting-state and stress-state (calculation task) conditions, during rest tremor and postural tremor. The changes of peak power, peak frequency, mean frequency, and distribution of power spectral density (PSD) of tremor were evaluated across conditions. Patients whose tremors were considered more than "mild" were selected, for both rest (n=67) and postural (n=25) tremor. Stress resulted in both greater peak powers and higher peak frequencies for rest tremor (p<0.001), but not for postural tremor. Notably, peak frequencies were concentrated around 5 Hz under stress-state condition. The distributions of PSD of tremor were symmetrical, regardless of conditions. Tremor is more evident and typical tremor characteristics, namely a lower frequency as amplitude increases, are different in stressful condition. Patient's conditions directly affect neural oscillations related to tremor frequencies. Therefore, tremor characteristics in PD should be systematically standardized across patient's conditions such as attention and stress levels. Copyright © 2016. Published by Elsevier B.V.

Regional homogeneity and resting state functional connectivity: associations with exposure to early life stress.

PubMed

Philip, Noah S; Kuras, Yuliya I; Valentine, Thomas R; Sweet, Lawrence H; Tyrka, Audrey R; Price, Lawrence H; Carpenter, Linda L

2013-12-30

Early life stress (ELS) confers risk for psychiatric illness. Previous literature suggests ELS is associated with decreased resting-state functional connectivity (rs-FC) in adulthood, but there are no studies of resting-state neuronal activity in this population. This study investigated whether ELS-exposed individuals demonstrate resting-state activity patterns similar to those found in PTSD. Twenty-seven adults (14 with at least moderate ELS), who were medication-free and without psychiatric or medical illness, underwent MRI scans during two 4-minute rest periods. Resting-state activity was examined using regional homogeneity (ReHo), which estimates regional activation patterns through indices of localized concordance. ReHo values were compared between groups, followed by rs-FC analyses utilizing ReHo-localized areas as seeds to identify other involved regions. Relative to controls, ELS subjects demonstrated diminished ReHo in the inferior parietal lobule (IPL) and superior temporal gyrus (STG). ReHo values were inversely correlated with ELS severity. Secondary analyses revealed decreased rs-FC between the IPL and right precuneus/posterior cingulate, left fusiform gyrus, cerebellum and caudate in ELS subjects. These findings indicate that ELS is associated with altered resting-state activity and connectivity in brain regions involved in trauma-related psychiatric disorders. Future studies are needed to evaluate whether these associations represent potential imaging biomarkers of stress exposure. Published by Elsevier Ireland Ltd.

From Anomalies to Essential Scientific Revolution? Intrinsic Brain Activity in the Light of Kuhn's Philosophy of Science.

PubMed

Havlík, Marek

2017-01-01

The first step toward a modern understanding of fMRI resting brain activity was made by Bharat Biswal in 1995. This surprising, and at first rejected, discovery is now associated with many resting state networks, notably the famous default mode network (DMN). Resting state activity and DMN significantly reassessed our traditional beliefs and conventions about the functioning of the brain. For the majority of the twentieth century, neuroscientists assumed that the brain is mainly the "reactive engine" to the environment operating mostly through stimulation. This "reactive convention" was very influential and convenient for the goals of twentieth century neuroscience-non-invasive functional localization based on stimulation. Largely unchallenged, "reactive convention" determined the direction of scientific research for a long time and became the "reactive paradigm" of the twentieth century. Resting state activity brought knowledge that was quite different of the "reactive paradigm." Current research of the DMN, probably the best known resting state network, leads to entirely new observations and conclusions, which were not achievable from the perspective of the "reactive paradigm." This shift from reactive activity to resting state activity of the brain is accompanied by an important question: "Can resting state activity be considered a scientific revolution and the new paradigm of neuroscience, or is it only significant for one branch of neuroscience, such as fMRI?"

Modeling resting-state functional networks when the cortex falls asleep: local and global changes.

PubMed

Deco, Gustavo; Hagmann, Patric; Hudetz, Anthony G; Tononi, Giulio

2014-12-01

The transition from wakefulness to sleep represents the most conspicuous change in behavior and the level of consciousness occurring in the healthy brain. It is accompanied by similarly conspicuous changes in neural dynamics, traditionally exemplified by the change from "desynchronized" electroencephalogram activity in wake to globally synchronized slow wave activity of early sleep. However, unit and local field recordings indicate that the transition is more gradual than it might appear: On one hand, local slow waves already appear during wake; on the other hand, slow sleep waves are only rarely global. Studies with functional magnetic resonance imaging also reveal changes in resting-state functional connectivity (FC) between wake and slow wave sleep. However, it remains unclear how resting-state networks may change during this transition period. Here, we employ large-scale modeling of the human cortico-cortical anatomical connectivity to evaluate changes in resting-state FC when the model "falls asleep" due to the progressive decrease in arousal-promoting neuromodulation. When cholinergic neuromodulation is parametrically decreased, local slow waves appear, while the overall organization of resting-state networks does not change. Furthermore, we show that these local slow waves are structured macroscopically in networks that resemble the resting-state networks. In contrast, when the neuromodulator decrease further to very low levels, slow waves become global and resting-state networks merge into a single undifferentiated, broadly synchronized network. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A SVM-based quantitative fMRI method for resting-state functional network detection.

PubMed

Song, Xiaomu; Chen, Nan-kuei

2014-09-01

Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

Temporal reliability of ultra-high field resting-state MRI for single-subject sensorimotor and language mapping.

PubMed

Branco, Paulo; Seixas, Daniela; Castro, São Luís

2018-03-01

Resting-state fMRI is a well-suited technique to map functional networks in the brain because unlike task-based approaches it requires little collaboration from subjects. This is especially relevant in clinical settings where a number of subjects cannot comply with task demands. Previous studies using conventional scanner fields have shown that resting-state fMRI is able to map functional networks in single subjects, albeit with moderate temporal reliability. Ultra-high resolution (7T) imaging provides higher signal-to-noise ratio and better spatial resolution and is thus well suited to assess the temporal reliability of mapping results, and to determine if resting-state fMRI can be applied in clinical decision making including preoperative planning. We used resting-state fMRI at ultra-high resolution to examine whether the sensorimotor and language networks are reliable over time - same session and one week after. Resting-state networks were identified for all subjects and sessions with good accuracy. Both networks were well delimited within classical regions of interest. Mapping was temporally reliable at short and medium time-scales as demonstrated by high values of overlap in the same session and one week after for both networks. Results were stable independently of data quality metrics and physiological variables. Taken together, these findings provide strong support for the suitability of ultra-high field resting-state fMRI mapping at the single-subject level. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Depression, mood state, and back pain during microgravity simulated by bed rest

NASA Technical Reports Server (NTRS)

Styf, J. R.; Hutchinson, K.; Carlsson, S. G.; Hargens, A. R.

2001-01-01

OBJECTIVE: The objective of this study was to develop a ground-based model for spinal adaptation to microgravity and to study the effects of spinal adaptation on depression, mood state, and pain intensity. METHODS: We investigated back pain, mood state, and depression in six subjects, all of whom were exposed to microgravity, simulated by two forms of bed rest, for 3 days. One form consisted of bed rest with 6 degrees of head-down tilt and balanced traction, and the other consisted of horizontal bed rest. Subjects had a 2-week period of recovery between the studies. The effects of bed rest on pain intensity in the lower back, depression, and mood state were investigated. RESULTS: Subjects experienced significantly more intense lower back pain, lower hemisphere abdominal pain, headache, and leg pain during head-down tilt bed rest. They had higher scores on the Beck Depression Inventory (ie, were more depressed) and significantly lower scores on the activity scale of the Bond-Lader questionnaire. CONCLUSIONS: Bed rest with 6 degrees of head-down tilt may be a better experimental model than horizontal bed rest for inducing the pain and psychosomatic reactions experienced in microgravity. Head-down tilt with balanced traction may be a useful method to induce low back pain, mood changes, and altered self-rated activity level in bed rest studies.

Single-subject structural networks with closed-form rotation invariant matching mprove power in developmental studies of the cortex.

PubMed

Kandel, Benjamin M; Wang, Danny J J; Gee, James C; Avants, Brian B

2014-01-01

Although much attention has recently been focused on single-subject functional networks, using methods such as resting-state functional MRI, methods for constructing single-subject structural networks are in their infancy. Single-subject cortical networks aim to describe the self-similarity across the cortical structure, possibly signifying convergent developmental pathways. Previous methods for constructing single-subject cortical networks have used patch-based correlations and distance metrics based on curvature and thickness. We present here a method for constructing similarity-based cortical structural networks that utilizes a rotation-invariant representation of structure. The resulting graph metrics are closely linked to age and indicate an increasing degree of closeness throughout development in nearly all brain regions, perhaps corresponding to a more regular structure as the brain matures. The derived graph metrics demonstrate a four-fold increase in power for detecting age as compared to cortical thickness. This proof of concept study indicates that the proposed metric may be useful in identifying biologically relevant cortical patterns.

Default mode network abnormalities during state switching in attention deficit hyperactivity disorder.

PubMed

Sidlauskaite, J; Sonuga-Barke, E; Roeyers, H; Wiersema, J R

2016-02-01

Individuals with attention deficit hyperactivity disorder (ADHD) display excess levels of default mode network (DMN) activity during goal-directed tasks, which are associated with attentional disturbances and performance decrements. One hypothesis is that this is due to attenuated down-regulation of this network during rest-to-task switching. A second related hypothesis is that it may be associated with right anterior insula (rAI) dysfunction - a region thought to control the actual state-switching process. These hypotheses were tested in the current fMRI study in which 19 adults with ADHD and 21 typically developing controls undertook a novel state-to-state switching paradigm. Advance cues signalled upcoming switches between rest and task periods and switch-related anticipatory modulation of DMN and rAI was measured. To examine whether rest-to-task switching impairments may be a specific example of a more general state regulation deficit, activity upon task-to-rest cues was also analysed. Against our hypotheses, we found that the process of down-regulating the DMN when preparing to switch from rest to task was unimpaired in ADHD and that there was no switch-specific deficit in rAI modulation. However, individuals with ADHD showed difficulties up-regulating the DMN when switching from task to rest. Rest-to-task DMN attenuation seems to be intact in adults with ADHD and thus appears unrelated to excess DMN activity observed during tasks. Instead, individuals with ADHD exhibit attenuated up-regulation of the DMN, hence suggesting disturbed re-initiation of a rest state.

The Whole-Brain “Global” Signal from Resting State fMRI as a Potential Biomarker of Quantitative State Changes in Glucose Metabolism

PubMed Central

Thompson, Garth J.; Grimmer, Timo; Drzezga, Alexander; Herman, Peter

2016-01-01

Abstract The evolution of functional magnetic resonance imaging to resting state (R-fMRI) allows measurement of changes in brain networks attributed to state changes, such as in neuropsychiatric diseases versus healthy controls. Since these networks are observed by comparing normalized R-fMRI signals, it is difficult to determine the metabolic basis of such group differences. To investigate the metabolic basis of R-fMRI network differences within a normal range, eyes open versus eyes closed in healthy human subjects was used. R-fMRI was recorded simultaneously with fluoro-deoxyglucose positron emission tomography (FDG-PET). Higher baseline FDG was observed in the eyes open state. Variance-based metrics calculated from R-fMRI did not match the baseline shift in FDG. Functional connectivity density (FCD)-based metrics showed a shift similar to the baseline shift of FDG, however, this was lost if R-fMRI “nuisance signals” were regressed before FCD calculation. Average correlation with the mean R-fMRI signal across the whole brain, generally regarded as a “nuisance signal,” also showed a shift similar to the baseline of FDG. Thus, despite lacking a baseline itself, changes in whole-brain correlation may reflect changes in baseline brain metabolism. Conversely, variance-based metrics may remain similar between states due to inherent region-to-region differences overwhelming the differences between normal physiological states. As most previous studies have excluded the spatial means of R-fMRI metrics from their analysis, this work presents the first evidence of a potential R-fMRI biomarker for baseline shifts in quantifiable metabolism between brain states. PMID:27029438

The Whole-Brain "Global" Signal from Resting State fMRI as a Potential Biomarker of Quantitative State Changes in Glucose Metabolism.

PubMed

Thompson, Garth J; Riedl, Valentin; Grimmer, Timo; Drzezga, Alexander; Herman, Peter; Hyder, Fahmeed

2016-07-01

The evolution of functional magnetic resonance imaging to resting state (R-fMRI) allows measurement of changes in brain networks attributed to state changes, such as in neuropsychiatric diseases versus healthy controls. Since these networks are observed by comparing normalized R-fMRI signals, it is difficult to determine the metabolic basis of such group differences. To investigate the metabolic basis of R-fMRI network differences within a normal range, eyes open versus eyes closed in healthy human subjects was used. R-fMRI was recorded simultaneously with fluoro-deoxyglucose positron emission tomography (FDG-PET). Higher baseline FDG was observed in the eyes open state. Variance-based metrics calculated from R-fMRI did not match the baseline shift in FDG. Functional connectivity density (FCD)-based metrics showed a shift similar to the baseline shift of FDG, however, this was lost if R-fMRI "nuisance signals" were regressed before FCD calculation. Average correlation with the mean R-fMRI signal across the whole brain, generally regarded as a "nuisance signal," also showed a shift similar to the baseline of FDG. Thus, despite lacking a baseline itself, changes in whole-brain correlation may reflect changes in baseline brain metabolism. Conversely, variance-based metrics may remain similar between states due to inherent region-to-region differences overwhelming the differences between normal physiological states. As most previous studies have excluded the spatial means of R-fMRI metrics from their analysis, this work presents the first evidence of a potential R-fMRI biomarker for baseline shifts in quantifiable metabolism between brain states.

Decreased electrophysiological activity represents the conscious state of emptiness in meditation

PubMed Central

Hinterberger, Thilo; Schmidt, Stephanie; Kamei, Tsutomu; Walach, Harald

2014-01-01

Many neuroscientific theories explain consciousness with higher order information processing corresponding to an activation of specific brain areas and processes. In contrast, most forms of meditation ask for a down-regulation of certain mental processing activities while remaining fully conscious. To identify the physiological properties of conscious states with decreased mental and cognitive processing, the electrical brain activity (64 channels of EEG) of 50 participants of various meditation proficiencies was measured during distinct and idiosyncratic meditative tasks. The tasks comprised a wakeful “thoughtless emptiness (TE),” a “focused attention,” and an “open monitoring” task asking for mindful presence in the moment and in the environment without attachment to distracting thoughts. Our analysis mainly focused on 30 highly experienced meditators with at least 5 years and 1000 h of meditation experience. Spectral EEG power comparisons of the TE state with the resting state or other forms of meditation showed decreased activities in specific frequency bands. In contrast to a focused attention task the TE task showed significant central and parietal gamma decreases (p < 0.05). Compared to open monitoring TE expressed decreased alpha and beta amplitudes, mainly in parietal areas (p < 0.01). TE presented significantly less delta (p < 0.001) and theta (p < 0.05) waves than a wakeful closed eyes resting condition. A group of participants with none or little meditation practice did not present those differences significantly. Our findings indicate that a conscious state of TE reached by experienced meditators is characterized by reduced high-frequency brain processing with simultaneous reduction of the low frequencies. This suggests that such a state of meditative conscious awareness might be different from higher cognitive and mentally focused states but also from states of sleep and drowsiness. PMID:24596562

Resting site use of giant pandas in Wanglang Nature Reserve.

PubMed

Kang, Dongwei; Wang, Xiaorong; Li, Junqing

2017-10-23

Little is known about the resting sites used by the giant panda (Ailuropoda melanoleuca), which restricts our understanding of their resting habits and limits conservation efforts. To enhance our understanding of resting site requirements and factors affecting the resting time of giant pandas, we investigated the characteristics of resting sites in the Wanglang Nature Reserve, Sichuan Province, China. The results indicated that the resting sites of giant pandas were characterised by a mean slope of 21°, mean nearest tree size of 53.75 cm, mean nearest shrub size of 2.82 cm, and mean nearest bamboo number of 56. We found that the resting sites were closer to bamboo than to trees and shrubs, suggesting that the resting site use of giant pandas is closely related to the presence of bamboo. Considering that giant pandas typically rest near a large-sized tree, protection of large trees in the forests is of considerable importance for the conservation of this species. Furthermore, slope was found to be an important factor affecting the resting time of giant pandas, as they tended to rest for a relatively longer time in sites with a smaller degree of slope.

Brain dynamics of post-task resting state are influenced by expertise: Insights from baseball players.

PubMed

Muraskin, Jordan; Dodhia, Sonam; Lieberman, Gregory; Garcia, Javier O; Verstynen, Timothy; Vettel, Jean M; Sherwin, Jason; Sajda, Paul

2016-12-01

Post-task resting state dynamics can be viewed as a task-driven state where behavioral performance is improved through endogenous, non-explicit learning. Tasks that have intrinsic value for individuals are hypothesized to produce post-task resting state dynamics that promote learning. We measured simultaneous fMRI/EEG and DTI in Division-1 collegiate baseball players and compared to a group of controls, examining differences in both functional and structural connectivity. Participants performed a surrogate baseball pitch Go/No-Go task before a resting state scan, and we compared post-task resting state connectivity using a seed-based analysis from the supplementary motor area (SMA), an area whose activity discriminated players and controls in our previous results using this task. Although both groups were equally trained on the task, the experts showed differential activity in their post-task resting state consistent with motor learning. Specifically, we found (1) differences in bilateral SMA-L Insula functional connectivity between experts and controls that may reflect group differences in motor learning, (2) differences in BOLD-alpha oscillation correlations between groups suggests variability in modulatory attention in the post-task state, and (3) group differences between BOLD-beta oscillations that may indicate cognitive processing of motor inhibition. Structural connectivity analysis identified group differences in portions of the functionally derived network, suggesting that functional differences may also partially arise from variability in the underlying white matter pathways. Generally, we find that brain dynamics in the post-task resting state differ as a function of subject expertise and potentially result from differences in both functional and structural connectivity. Hum Brain Mapp 37:4454-4471, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Fast-slow asymptotic for semi-analytical ignition criteria in FitzHugh-Nagumo system.

PubMed

Bezekci, B; Biktashev, V N

2017-09-01

We study the problem of initiation of excitation waves in the FitzHugh-Nagumo model. Our approach follows earlier works and is based on the idea of approximating the boundary between basins of attraction of propagating waves and of the resting state as the stable manifold of a critical solution. Here, we obtain analytical expressions for the essential ingredients of the theory by singular perturbation using two small parameters, the separation of time scales of the activator and inhibitor and the threshold in the activator's kinetics. This results in a closed analytical expression for the strength-duration curve.

Artist's concept of Surveyor III resting in the Ocean of Storms

NASA Technical Reports Server (NTRS)

1969-01-01

Ryan Aeronautical Company artist's concept depicting a close-up view of Surveyor III resting in the Ocean of Storms on the lunar nearside. Two Apollo 12 astronauts are seen approaching in the background. The Apollo 12 Lunar Module is in the the left background. The Earth is in the right background.

Perceived insufficient rest or sleep among adults - United States, 2008.

PubMed

2009-10-30

The importance of chronic sleep insufficiency is under-recognized as a public health problem, despite being associated with numerous physical and mental health problems, injury, loss of productivity, and mortality. Approximately 29% of U.S. adults report sleeping <7 hours per night and 50-70 million have chronic sleep and wakefulness disorders. A CDC analysis of 2006 data from the Behavioral Risk Factor Surveillance System (BRFSS) in four states showed that an estimated 10.1% of adults reported receiving insufficient rest or sleep on all days during the preceding 30 days. To examine the prevalence of insufficient rest or sleep in all states, CDC analyzed BRFSS data for all 50 states, the District of Columbia (DC), and three U.S. territories (Guam, Puerto Rico, and U.S. Virgin Islands) in 2008. This report summarizes the results, which showed that among 403,981 respondents, 30.7% reported no days of insufficient rest or sleep and 11.1% reported insufficient rest or sleep every day during the preceding 30 days. Females (12.4%) were more likely than males (9.9%) and non-Hispanic blacks (13.3%) were more likely than other racial/ethnic groups to report insufficient rest or sleep. State estimates of 30 days of insufficient rest or sleep ranged from 7.4% in North Dakota to 19.3% in West Virginia. Health-care providers should consider adding an assessment of chronic rest or sleep insufficiency to routine office visits so they can make needed interventions or referrals to sleep specialists.

fMRI reveals reciprocal inhibition between social and physical cognitive domains

PubMed Central

Jack, Anthony I.; Dawson, Abigail; Begany, Katelyn; Leckie, Regina L.; Barry, Kevin; Ciccia, Angela; Snyder, Abraham

2012-01-01

Two lines of evidence indicate that there exists a reciprocal inhibitory relationship between opposed brain networks. First, most attention-demanding cognitive tasks activate a stereotypical set of brain areas, known as the task-positive network and simultaneously deactivate a different set of brain regions, commonly referred to as the task negative or default mode network. Second, functional connectivity analyses show that these same opposed networks are anti-correlated in the resting state. We hypothesize that these reciprocally inhibitory effects reflect two incompatible cognitive modes, each of which is directed towards understanding the external world. Thus, engaging one mode activates one set of regions and suppresses activity in the other. We test this hypothesis by identifying two types of problem-solving task which, on the basis of prior work, have been consistently associated with the task positive and task negative regions: tasks requiring social cognition, i.e., reasoning about the mental states of other persons, and tasks requiring physical cognition, i.e., reasoning about the causal/mechanical properties of inanimate objects. Social and mechanical reasoning tasks were presented to neurologically normal participants during fMRI. Each task type was presented using both text and video clips. Regardless of presentation modality, we observed clear evidence of reciprocal suppression: social tasks deactivated regions associated with mechanical reasoning and mechanical tasks deactivated regions associated with social reasoning. These findings are not explained by self-referential processes, task engagement, mental simulation, mental time travel or external vs. internal attention, all factors previously hypothesized to explain default mode network activity. Analyses of resting state data revealed a close match between the regions our tasks identified as reciprocally inhibitory and regions of maximal anti-correlation in the resting state. These results indicate the reciprocal inhibition is not attributable to constraints inherent in the tasks, but is neural in origin. Hence, there is a physiological constraint on our ability to simultaneously engage two distinct cognitive modes. Further work is needed to more precisely characterize these opposing cognitive domains. PMID:23110882

Redox-dependent open and closed forms of the active site of the bacterial respiratory nitric-oxide reductase revealed by cyanide binding studies.

PubMed

Grönberg, Karin L C; Watmough, Nicholas J; Thomson, Andrew J; Richardson, David J; Field, Sarah J

2004-04-23

The bacterial respiratory nitric-oxide reductase (NOR) catalyzes the respiratory detoxification of nitric oxide in bacteria and Archaea. It is a member of the well known super-family of heme-copper oxidases but has a [heme Fe-non-heme Fe] active site rather than the [heme Fe-Cu(B)] active site normally associated with oxygen reduction. Paracoccus denitrificans NOR is spectrally characterized by a ligand-to-metal charge transfer absorption band at 595 nm, which arises from the high spin ferric heme iron of a micro-oxo-bridged [heme Fe(III)-O-Fe(III)] active site. On reduction of the nonheme iron, the micro-oxo bridge is broken, and the ferric heme iron is hydroxylated or hydrated, depending on the pH. At present, the catalytic cycle of NOR is a matter of much debate, and it is not known to which redox state(s) of the enzyme nitric oxide can bind. This study has used cyanide to probe the nature of the active site in a number of different redox states. Our observations suggest that the micro-oxo-bridged [heme Fe(III)-O-Fe(III)] active site represents a closed or resting state of NOR that can be opened by reduction of the non-heme iron.

Stomach-brain synchrony reveals a novel, delayed-connectivity resting-state network in humans

PubMed Central

Devauchelle, Anne-Dominique; Béranger, Benoît; Tallon-Baudry, Catherine

2018-01-01

Resting-state networks offer a unique window into the brain’s functional architecture, but their characterization remains limited to instantaneous connectivity thus far. Here, we describe a novel resting-state network based on the delayed connectivity between the brain and the slow electrical rhythm (0.05 Hz) generated in the stomach. The gastric network cuts across classical resting-state networks with partial overlap with autonomic regulation areas. This network is composed of regions with convergent functional properties involved in mapping bodily space through touch, action or vision, as well as mapping external space in bodily coordinates. The network is characterized by a precise temporal sequence of activations within a gastric cycle, beginning with somato-motor cortices and ending with the extrastriate body area and dorsal precuneus. Our results demonstrate that canonical resting-state networks based on instantaneous connectivity represent only one of the possible partitions of the brain into coherent networks based on temporal dynamics. PMID:29561263

Neuroplastic Sensorimotor Resting State Network Reorganization in Children With Hemiplegic Cerebral Palsy Treated With Constraint-Induced Movement Therapy.

PubMed

Manning, Kathryn Y; Menon, Ravi S; Gorter, Jan Willem; Mesterman, Ronit; Campbell, Craig; Switzer, Lauren; Fehlings, Darcy

2016-02-01

Using resting state functional magnetic resonance imaging (MRI), we aim to understand the neurologic basis of improved function in children with hemiplegic cerebral palsy treated with constraint-induced movement therapy. Eleven children including 4 untreated comparison subjects diagnosed with hemiplegic cerebral palsy were recruited from 3 clinical centers. MRI and clinical data were gathered at baseline and 1 month for both groups, and 6 months later for the case group only. After constraint therapy, the sensorimotor resting state network became more bilateral, with balanced contributions from each hemisphere, which was sustained 6 months later. Sensorimotor resting state network reorganization after therapy was correlated with a change in the Quality of Upper Extremity Skills Test score at 1 month (r = 0.79, P = .06), and Canadian Occupational Performance Measure scores at 6 months (r = 0.82, P = .05). This clinically correlated resting state network reorganization provides further evidence of the neuroplastic mechanisms underlying constraint-induced movement therapy. © The Author(s) 2015.

Resting-State Retinotopic Organization in the Absence of Retinal Input and Visual Experience

PubMed Central

Binda, Paola; Benson, Noah C.; Bridge, Holly; Watkins, Kate E.

2015-01-01

Early visual areas have neuronal receptive fields that form a sampling mosaic of visual space, resulting in a series of retinotopic maps in which the same region of space is represented in multiple visual areas. It is not clear to what extent the development and maintenance of this retinotopic organization in humans depend on retinal waves and/or visual experience. We examined the corticocortical receptive field organization of resting-state BOLD data in normally sighted, early blind, and anophthalmic (in which both eyes fail to develop) individuals and found that resting-state correlations between V1 and V2/V3 were retinotopically organized for all subject groups. These results show that the gross retinotopic pattern of resting-state connectivity across V1-V3 requires neither retinal waves nor visual experience to develop and persist into adulthood. SIGNIFICANCE STATEMENT Evidence from resting-state BOLD data suggests that the connections between early visual areas develop and are maintained even in the absence of retinal waves and visual experience. PMID:26354906

Resting-state FMRI confounds and cleanup

PubMed Central

Murphy, Kevin; Birn, Rasmus M.; Bandettini, Peter A.

2013-01-01

The goal of resting-state functional magnetic resonance imaging (FMRI) is to investigate the brain’s functional connections by using the temporal similarity between blood oxygenation level dependent (BOLD) signals in different regions of the brain “at rest” as an indicator of synchronous neural activity. Since this measure relies on the temporal correlation of FMRI signal changes between different parts of the brain, any non-neural activity-related process that affects the signals will influence the measure of functional connectivity, yielding spurious results. To understand the sources of these resting-state FMRI confounds, this article describes the origins of the BOLD signal in terms of MR physics and cerebral physiology. Potential confounds arising from motion, cardiac and respiratory cycles, arterial CO2 concentration, blood pressure/cerebral autoregulation, and vasomotion are discussed. Two classes of techniques to remove confounds from resting-state BOLD time series are reviewed: 1) those utilising external recordings of physiology and 2) data-based cleanup methods that only use the resting-state FMRI data itself. Further methods that remove noise from functional connectivity measures at a group level are also discussed. For successful interpretation of resting-state FMRI comparisons and results, noise cleanup is an often over-looked but essential step in the analysis pipeline. PMID:23571418

Automatic classification of schizophrenia using resting-state functional language network via an adaptive learning algorithm

NASA Astrophysics Data System (ADS)

Zhu, Maohu; Jie, Nanfeng; Jiang, Tianzi

2014-03-01

A reliable and precise classification of schizophrenia is significant for its diagnosis and treatment of schizophrenia. Functional magnetic resonance imaging (fMRI) is a novel tool increasingly used in schizophrenia research. Recent advances in statistical learning theory have led to applying pattern classification algorithms to access the diagnostic value of functional brain networks, discovered from resting state fMRI data. The aim of this study was to propose an adaptive learning algorithm to distinguish schizophrenia patients from normal controls using resting-state functional language network. Furthermore, here the classification of schizophrenia was regarded as a sample selection problem where a sparse subset of samples was chosen from the labeled training set. Using these selected samples, which we call informative vectors, a classifier for the clinic diagnosis of schizophrenia was established. We experimentally demonstrated that the proposed algorithm incorporating resting-state functional language network achieved 83.6% leaveone- out accuracy on resting-state fMRI data of 27 schizophrenia patients and 28 normal controls. In contrast with KNearest- Neighbor (KNN), Support Vector Machine (SVM) and l1-norm, our method yielded better classification performance. Moreover, our results suggested that a dysfunction of resting-state functional language network plays an important role in the clinic diagnosis of schizophrenia.

Multiple Resting-State Networks Are Associated With Tremors and Cognitive Features in Essential Tremor.

PubMed

Fang, Weidong; Chen, Huiyue; Wang, Hansheng; Zhang, Han; Liu, Mengqi; Puneet, Munankami; Lv, Fajin; Cheng, Oumei; Wang, Xuefeng; Lu, Xiurong; Luo, Tianyou

2015-12-01

The heterogeneous clinical features of essential tremor indicate that the dysfunctions of this syndrome are not confined to motor networks, but extend to nonmotor networks. Currently, these neural network dysfunctions in essential tremor remain unclear. In this study, independent component analysis of resting-state functional MRI was used to study these neural network mechanisms. Thirty-five essential tremor patients and 35 matched healthy controls with clinical and neuropsychological tests were included, and eight resting-state networks were identified. After considering the structure and head-motion factors and testing the reliability of the selected resting-state networks, we assessed the functional connectivity changes within or between resting-state networks. Finally, image-behavior correlation analysis was performed. Compared to healthy controls, essential tremor patients displayed increased functional connectivity in the sensorimotor and salience networks and decreased functional connectivity in the cerebellum network. Additionally, increased functional network connectivity was observed between anterior and posterior default mode networks, and a decreased functional network connectivity was noted between the cerebellum network and the sensorimotor and posterior default mode networks. Importantly, the functional connectivity changes within and between these resting-state networks were correlated with the tremor severity and total cognitive scores of essential tremor patients. The findings of this study provide the first evidence that functional connectivity changes within and between multiple resting-state networks are associated with tremors and cognitive features of essential tremor, and this work demonstrates a potential approach for identifying the underlying neural network mechanisms of this syndrome. © 2015 International Parkinson and Movement Disorder Society.

Universal relations for differentially rotating relativistic stars at the threshold to collapse

NASA Astrophysics Data System (ADS)

Bozzola, Gabriele; Stergioulas, Nikolaos; Bauswein, Andreas

2018-03-01

A binary neutron star merger produces a rapidly and differentially rotating compact remnant whose lifespan heavily affects the electromagnetic and gravitational emissions. Its stability depends on both the equation of state (EOS) and the rotation law and it is usually investigated through numerical simulations. Nevertheless, by means of a sufficient criterion for secular instability, equilibrium sequences can be used as a computational inexpensive way to estimate the onset of dynamical instability, which, in general, is close to the secular one. This method works well for uniform rotation and relies on the location of turning points: stellar models that are stationary points in a sequence of equilibrium solutions with constant rest mass or angular momentum. Here, we investigate differentially rotating models (using a large number of EOSs and different rotation laws) and find that several universal relations between properly scaled gravitational mass, rest mass and angular momentum of the turning-point models that are valid for uniform rotation are insensitive to the degree of differential rotation, to high accuracy.

Agreement and repeatability of vascular reactivity estimates based on a breath-hold task and a resting state scan.

PubMed

Lipp, Ilona; Murphy, Kevin; Caseras, Xavier; Wise, Richard G

2015-06-01

FMRI BOLD responses to changes in neural activity are influenced by the reactivity of the vasculature. By complementing a task-related BOLD acquisition with a vascular reactivity measure obtained through breath-holding or hypercapnia, this unwanted variance can be statistically reduced in the BOLD responses of interest. Recently, it has been suggested that vascular reactivity can also be estimated using a resting state scan. This study aimed to compare three breath-hold based analysis approaches (block design, sine-cosine regressor and CO2 regressor) and a resting state approach (CO2 regressor) to measure vascular reactivity. We tested BOLD variance explained by the model and repeatability of the measures. Fifteen healthy participants underwent a breath-hold task and a resting state scan with end-tidal CO2 being recorded during both. Vascular reactivity was defined as CO2-related BOLD percent signal change/mmHg change in CO2. Maps and regional vascular reactivity estimates showed high repeatability when the breath-hold task was used. Repeatability and variance explained by the CO2 trace regressor were lower for the resting state data based approach, which resulted in highly variable measures of vascular reactivity. We conclude that breath-hold based vascular reactivity estimations are more repeatable than resting-based estimates, and that there are limitations with replacing breath-hold scans by resting state scans for vascular reactivity assessment. Copyright © 2015. Published by Elsevier Inc.

Agreement and repeatability of vascular reactivity estimates based on a breath-hold task and a resting state scan

PubMed Central

Lipp, Ilona; Murphy, Kevin; Caseras, Xavier; Wise, Richard G.

2015-01-01

FMRI BOLD responses to changes in neural activity are influenced by the reactivity of the vasculature. By complementing a task-related BOLD acquisition with a vascular reactivity measure obtained through breath-holding or hypercapnia, this unwanted variance can be statistically reduced in the BOLD responses of interest. Recently, it has been suggested that vascular reactivity can also be estimated using a resting state scan. This study aimed to compare three breath-hold based analysis approaches (block design, sine–cosine regressor and CO2 regressor) and a resting state approach (CO2 regressor) to measure vascular reactivity. We tested BOLD variance explained by the model and repeatability of the measures. Fifteen healthy participants underwent a breath-hold task and a resting state scan with end-tidal CO2 being recorded during both. Vascular reactivity was defined as CO2-related BOLD percent signal change/mm Hg change in CO2. Maps and regional vascular reactivity estimates showed high repeatability when the breath-hold task was used. Repeatability and variance explained by the CO2 trace regressor were lower for the resting state data based approach, which resulted in highly variable measures of vascular reactivity. We conclude that breath-hold based vascular reactivity estimations are more repeatable than resting-based estimates, and that there are limitations with replacing breath-hold scans by resting state scans for vascular reactivity assessment. PMID:25795342

Intrinsic Resting-State Functional Connectivity in the Human Spinal Cord at 3.0 T.

PubMed

San Emeterio Nateras, Oscar; Yu, Fang; Muir, Eric R; Bazan, Carlos; Franklin, Crystal G; Li, Wei; Li, Jinqi; Lancaster, Jack L; Duong, Timothy Q

2016-04-01

To apply resting-state functional magnetic resonance (MR) imaging to map functional connectivity of the human spinal cord. Studies were performed in nine self-declared healthy volunteers with informed consent and institutional review board approval. Resting-state functional MR imaging was performed to map functional connectivity of the human cervical spinal cord from C1 to C4 at 1 × 1 × 3-mm resolution with a 3.0-T clinical MR imaging unit. Independent component analysis (ICA) was performed to derive resting-state functional MR imaging z-score maps rendered on two-dimensional and three-dimensional images. Seed-based analysis was performed for cross validation with ICA networks by using Pearson correlation. Reproducibility analysis of resting-state functional MR imaging maps from four repeated trials in a single participant yielded a mean z score of 6 ± 1 (P < .0001). The centroid coordinates across the four trials deviated by 2 in-plane voxels ± 2 mm (standard deviation) and up to one adjacent image section ± 3 mm. ICA of group resting-state functional MR imaging data revealed prominent functional connectivity patterns within the spinal cord gray matter. There were statistically significant (z score > 3, P < .001) bilateral, unilateral, and intersegmental correlations in the ventral horns, dorsal horns, and central spinal cord gray matter. Three-dimensional surface rendering provided visualization of these components along the length of the spinal cord. Seed-based analysis showed that many ICA components exhibited strong and significant (P < .05) correlations, corroborating the ICA results. Resting-state functional MR imaging connectivity networks are qualitatively consistent with known neuroanatomic and functional structures in the spinal cord. Resting-state functional MR imaging of the human cervical spinal cord with a 3.0-T clinical MR imaging unit and standard MR imaging protocols and hardware reveals prominent functional connectivity patterns within the spinal cord gray matter, consistent with known functional and anatomic layouts of the spinal cord.

State and Training Effects of Mindfulness Meditation on Brain Networks Reflect Neuronal Mechanisms of Its Antidepressant Effect.

PubMed

Yang, Chuan-Chih; Barrós-Loscertales, Alfonso; Pinazo, Daniel; Ventura-Campos, Noelia; Borchardt, Viola; Bustamante, Juan-Carlos; Rodríguez-Pujadas, Aina; Fuentes-Claramonte, Paola; Balaguer, Raúl; Ávila, César; Walter, Martin

2016-01-01

The topic of investigating how mindfulness meditation training can have antidepressant effects via plastic changes in both resting state and meditation state brain activity is important in the rapidly emerging field of neuroplasticity. In the present study, we used a longitudinal design investigating resting state fMRI both before and after 40 days of meditation training in 13 novices. After training, we compared differences in network connectivity between rest and meditation using common resting state functional connectivity methods. Interregional methods were paired with local measures such as Regional Homogeneity. As expected, significant differences in functional connectivity both between states (rest versus meditation) and between time points (before versus after training) were observed. During meditation, the internal consistency in the precuneus and the temporoparietal junction increased, while the internal consistency of frontal brain regions decreased. A follow-up analysis of regional connectivity of the dorsal anterior cingulate cortex further revealed reduced connectivity with anterior insula during meditation. After meditation training, reduced resting state functional connectivity between the pregenual anterior cingulate and dorsal medical prefrontal cortex was observed. Most importantly, significantly reduced depression/anxiety scores were observed after training. Hence, these findings suggest that mindfulness meditation might be of therapeutic use by inducing plasticity related network changes altering the neuronal basis of affective disorders such as depression.

State and Training Effects of Mindfulness Meditation on Brain Networks Reflect Neuronal Mechanisms of Its Antidepressant Effect

PubMed Central

Yang, Chuan-Chih; Barrós-Loscertales, Alfonso; Pinazo, Daniel; Ventura-Campos, Noelia; Borchardt, Viola; Bustamante, Juan-Carlos; Rodríguez-Pujadas, Aina; Fuentes-Claramonte, Paola; Balaguer, Raúl; Ávila, César; Walter, Martin

2016-01-01

The topic of investigating how mindfulness meditation training can have antidepressant effects via plastic changes in both resting state and meditation state brain activity is important in the rapidly emerging field of neuroplasticity. In the present study, we used a longitudinal design investigating resting state fMRI both before and after 40 days of meditation training in 13 novices. After training, we compared differences in network connectivity between rest and meditation using common resting state functional connectivity methods. Interregional methods were paired with local measures such as Regional Homogeneity. As expected, significant differences in functional connectivity both between states (rest versus meditation) and between time points (before versus after training) were observed. During meditation, the internal consistency in the precuneus and the temporoparietal junction increased, while the internal consistency of frontal brain regions decreased. A follow-up analysis of regional connectivity of the dorsal anterior cingulate cortex further revealed reduced connectivity with anterior insula during meditation. After meditation training, reduced resting state functional connectivity between the pregenual anterior cingulate and dorsal medical prefrontal cortex was observed. Most importantly, significantly reduced depression/anxiety scores were observed after training. Hence, these findings suggest that mindfulness meditation might be of therapeutic use by inducing plasticity related network changes altering the neuronal basis of affective disorders such as depression. PMID:26998365

Spatially distributed effects of mental exhaustion on resting-state FMRI networks.

PubMed

Esposito, Fabrizio; Otto, Tobias; Zijlstra, Fred R H; Goebel, Rainer

2014-01-01

Brain activity during rest is spatially coherent over functional connectivity networks called resting-state networks. In resting-state functional magnetic resonance imaging, independent component analysis yields spatially distributed network representations reflecting distinct mental processes, such as intrinsic (default) or extrinsic (executive) attention, and sensory inhibition or excitation. These aspects can be related to different treatments or subjective experiences. Among these, exhaustion is a common psychological state induced by prolonged mental performance. Using repeated functional magnetic resonance imaging sessions and spatial independent component analysis, we explored the effect of several hours of sustained cognitive performances on the resting human brain. Resting-state functional magnetic resonance imaging was performed on the same healthy volunteers in two days, with and without, and before, during and after, an intensive psychological treatment (skill training and sustained practice with a flight simulator). After each scan, subjects rated their level of exhaustion and performed an N-back task to evaluate eventual decrease in cognitive performance. Spatial maps of selected resting-state network components were statistically evaluated across time points to detect possible changes induced by the sustained mental performance. The intensive treatment had a significant effect on exhaustion and effort ratings, but no effects on N-back performances. Significant changes in the most exhausted state were observed in the early visual processing and the anterior default mode networks (enhancement) and in the fronto-parietal executive networks (suppression), suggesting that mental exhaustion is associated with a more idling brain state and that internal attention processes are facilitated to the detriment of more extrinsic processes. The described application may inspire future indicators of the level of fatigue in the neural attention system.

Brain resting-state networks in adolescents with high-functioning autism: Analysis of spatial connectivity and temporal neurodynamics.

PubMed

Bernas, Antoine; Barendse, Evelien M; Aldenkamp, Albert P; Backes, Walter H; Hofman, Paul A M; Hendriks, Marc P H; Kessels, Roy P C; Willems, Frans M J; de With, Peter H N; Zinger, Svitlana; Jansen, Jacobus F A

2018-02-01

Autism spectrum disorder (ASD) is mainly characterized by functional and communication impairments as well as restrictive and repetitive behavior. The leading hypothesis for the neural basis of autism postulates globally abnormal brain connectivity, which can be assessed using functional magnetic resonance imaging (fMRI). Even in the absence of a task, the brain exhibits a high degree of functional connectivity, known as intrinsic, or resting-state, connectivity. Global default connectivity in individuals with autism versus controls is not well characterized, especially for a high-functioning young population. The aim of this study is to test whether high-functioning adolescents with ASD (HFA) have an abnormal resting-state functional connectivity. We performed spatial and temporal analyses on resting-state networks (RSNs) in 13 HFA adolescents and 13 IQ- and age-matched controls. For the spatial analysis, we used probabilistic independent component analysis (ICA) and a permutation statistical method to reveal the RSN differences between the groups. For the temporal analysis, we applied Granger causality to find differences in temporal neurodynamics. Controls and HFA display very similar patterns and strengths of resting-state connectivity. We do not find any significant differences between HFA adolescents and controls in the spatial resting-state connectivity. However, in the temporal dynamics of this connectivity, we did find differences in the causal effect properties of RSNs originating in temporal and prefrontal cortices. The results show a difference between HFA and controls in the temporal neurodynamics from the ventral attention network to the salience-executive network: a pathway involving cognitive, executive, and emotion-related cortices. We hypothesized that this weaker dynamic pathway is due to a subtle trigger challenging the cognitive state prior to the resting state.

Brain Connectivity and Visual Attention

PubMed Central

Parks, Emily L.

2013-01-01

Abstract Emerging hypotheses suggest that efficient cognitive functioning requires the integration of separate, but interconnected cortical networks in the brain. Although task-related measures of brain activity suggest that a frontoparietal network is associated with the control of attention, little is known regarding how components within this distributed network act together or with other networks to achieve various attentional functions. This review considers both functional and structural studies of brain connectivity, as complemented by behavioral and task-related neuroimaging data. These studies show converging results: The frontal and parietal cortical regions are active together, over time, and identifiable frontoparietal networks are active in relation to specific task demands. However, the spontaneous, low-frequency fluctuations of brain activity that occur in the resting state, without specific task demands, also exhibit patterns of connectivity that closely resemble the task-related, frontoparietal attention networks. Both task-related and resting-state networks exhibit consistent relations to behavioral measures of attention. Further, anatomical structure, particularly white matter pathways as defined by diffusion tensor imaging, places constraints on intrinsic functional connectivity. Lastly, connectivity analyses applied to investigate cognitive differences across individuals in both healthy and diseased states suggest that disconnection of attentional networks is linked to deficits in cognitive functioning, and in extreme cases, to disorders of attention. Thus, comprehensive theories of visual attention and their clinical translation depend on the continued integration of behavioral, task-related neuroimaging, and brain connectivity measures. PMID:23597177

Cleaning up our Federal energy regulatory mess

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kennedy, R.T.

1978-08-01

The new Department of Energy is making much effort to cut back on overlaps of regulations in regard to energy. Several governmental agencies were absorbed into DOE, but many of the previous agencies' policies are still on the books. The Energy Reorganization Act of 1977 did not eliminate the problem of regulatory overlap and confusion, the author says. Also, our future national energy policy will have to rest on this very complex of laws and regulations, he says. The author, being a former deputy administrator of the FEA, uses the nuclear industry to discuss ''the confusion.'' He concludes that eachmore » of us ''has a responsibility to clean up the energy regulation situation. Broad national policy issues must be addressed by Congress and the President. The States must focus hard on ways to simplify and strengthen their processes; and Federal agencies must look to ways to improve their interface with the states and to reduce duplication both with the states and with each other. All regulatory agencies must, mindful of their role in the process, police themselves, and keep a close eye on how that process is working. Finally, each government official and citizen must do his part to bring problems and solutions to the attention of the appropriate officials. For you are the watchdogs in this process, the keystone upon which our system rests.'' (MCW)« less

Altered local spontaneous activity in frontal lobe epilepsy: a resting-state functional magnetic resonance imaging study.

PubMed

Dong, Li; Li, Hechun; He, Zhongqiong; Jiang, Sisi; Klugah-Brown, Benjamin; Chen, Lin; Wang, Pu; Tan, Song; Luo, Cheng; Yao, Dezhong

2016-11-01

The purpose of this study was to investigate the local spatiotemporal consistency of spontaneous brain activity in patients with frontal lobe epilepsy (FLE). Eyes closed resting-state functional magnetic resonance imaging (fMRI) data were collected from 19 FLE patients and 19 age- and gender-matched healthy controls. A novel measure, named FOur-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA) was used to assess the spatiotemporal consistency of local spontaneous activity (emphasizing both local temporal homogeneity and regional stability of brain activity states). Then, two-sample t test was performed to detect the FOCA differences between two groups. Partial correlations between the FOCA values and durations of epilepsy were further analyzed. Compared with controls, FLE patients demonstrated increased FOCA in distant brain regions including the frontal and parietal cortices, as well as the basal ganglia. The decreased FOCA was located in the temporal cortex, posterior default model regions, and cerebellum. In addition, the FOCA measure was linked to the duration of epilepsy in basal ganglia. Our study suggested that alterations of local spontaneous activity in frontoparietal cortex and basal ganglia was associated with the pathophysiology of FLE; and the abnormality in frontal and default model regions might account for the potential cognitive impairment in FLE. We also presumed that the FOCA measure had potential to provide important insights into understanding epilepsy such as FLE.

Lightweight Valve Closes Duct Quickly

NASA Technical Reports Server (NTRS)

Fournier, Walter L.; Burgy, N. Frank

1991-01-01

Expanding balloon serves as lightweight emergency valve to close wide duct. Uninflated balloon stored in housing of duct. Pad resting on burst diaphragm protects balloon from hot gases in duct. Once control system triggers valve, balloon inflates rapidly to block duct. Weighs much less than does conventional butterfly, hot-gas, or poppet valve capable of closing duct of equal diameter.

Resting state activity in patients with disorders of consciousness

PubMed Central

Soddu, Andrea; Vanhaudenhuyse, Audrey; Demertzi, Athena; Bruno, Marie-Aurélie; Tshibanda, Luaba; Di, Haibo; Boly, Mélanie; Papa, Michele; Laureys, Steven; Noirhomme, Quentin

Summary Recent advances in the study of spontaneous brain activity have demonstrated activity patterns that emerge with no task performance or sensory stimulation; these discoveries hold promise for the study of higher-order associative network functionality. Additionally, such advances are argued to be relevant in pathological states, such as disorders of consciousness (DOC), i.e., coma, vegetative and minimally conscious states. Recent studies on resting state activity in DOC, measured with functional magnetic resonance imaging (fMRI) techniques, show that functional connectivity is disrupted in the task-negative or the default mode network. However, the two main approaches employed in the analysis of resting state functional connectivity data (i.e., hypothesis-driven seed-voxel and data-driven independent component analysis) present multiple methodological difficulties, especially in non-collaborative DOC patients. Improvements in motion artifact removal and spatial normalization are needed before fMRI resting state data can be used as proper biomarkers in severe brain injury. However, we anticipate that such developments will boost clinical resting state fMRI studies, allowing for easy and fast acquisitions and ultimately improve the diagnosis and prognosis in the absence of DOC patients’ active collaboration in data acquisition. PMID:21693087

Do resting brain dynamics predict oddball evoked-potential?

PubMed Central

2011-01-01

Background The oddball paradigm is widely applied to the investigation of cognitive function in neuroscience and in neuropsychiatry. Whether cortical oscillation in the resting state can predict the elicited oddball event-related potential (ERP) is still not clear. This study explored the relationship between resting electroencephalography (EEG) and oddball ERPs. The regional powers of 18 electrodes across delta, theta, alpha and beta frequencies were correlated with the amplitude and latency of N1, P2, N2 and P3 components of oddball ERPs. A multivariate analysis based on partial least squares (PLS) was applied to further examine the spatial pattern revealed by multiple correlations. Results Higher synchronization in the resting state, especially at the alpha spectrum, is associated with higher neural responsiveness and faster neural propagation, as indicated by the higher amplitude change of N1/N2 and shorter latency of P2. None of the resting quantitative EEG indices predict P3 latency and amplitude. The PLS analysis confirms that the resting cortical dynamics which explains N1/N2 amplitude and P2 latency does not show regional specificity, indicating a global property of the brain. Conclusions This study differs from previous approaches by relating dynamics in the resting state to neural responsiveness in the activation state. Our analyses suggest that the neural characteristics carried by resting brain dynamics modulate the earlier/automatic stage of target detection. PMID:22114868

How does the 'rest-self overlap' mediate the qualitative and automatic features of self-reference?

PubMed

Northoff, Georg

2016-01-01

The target article points out the qualitative and automatic features of self-reference while leaving open the underlying neural mechanisms. Based on empirical evidence about rest-self overlap and rest-stimulus interaction being special for self-related stimuli, I postulate that the resting state shows self-specific organization. The resting state's self-specific organization may be encoded by activity balances between different networks which in turn predispose the qualitative features of subsequent self-related stimulus-induced activity in, for instance, SAN as well as the automatic features of self-reference effects.

Crystal structure of the ATP-gated P2X[subscript 4] ion channel in the closed state

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kawate, Toshimitsu; Michel, Jennifer Carlisle; Birdsong, William T.

2009-08-13

P2X receptors are cation-selective ion channels gated by extracellular ATP, and are implicated in diverse physiological processes, from synaptic transmission to inflammation to the sensing of taste and pain. Because P2X receptors are not related to other ion channel proteins of known structure, there is at present no molecular foundation for mechanisms of ligand-gating, allosteric modulation and ion permeation. Here we present crystal structures of the zebrafish P2X{sub 4} receptor in its closed, resting state. The chalice-shaped, trimeric receptor is knit together by subunit-subunit contacts implicated in ion channel gating and receptor assembly. Extracellular domains, rich in {beta}-strands, have largemore » acidic patches that may attract cations, through fenestrations, to vestibules near the ion channel. In the transmembrane pore, the 'gate' is defined by an {approx}8 {angstrom} slab of protein. We define the location of three non-canonical, intersubunit ATP-binding sites, and suggest that ATP binding promotes subunit rearrangement and ion channel opening.« less

Applying representational state transfer (REST) architecture to archetype-based electronic health record systems

PubMed Central

2013-01-01

Background The openEHR project and the closely related ISO 13606 standard have defined structures supporting the content of Electronic Health Records (EHRs). However, there is not yet any finalized openEHR specification of a service interface to aid application developers in creating, accessing, and storing the EHR content. The aim of this paper is to explore how the Representational State Transfer (REST) architectural style can be used as a basis for a platform-independent, HTTP-based openEHR service interface. Associated benefits and tradeoffs of such a design are also explored. Results The main contribution is the formalization of the openEHR storage, retrieval, and version-handling semantics and related services into an implementable HTTP-based service interface. The modular design makes it possible to prototype, test, replicate, distribute, cache, and load-balance the system using ordinary web technology. Other contributions are approaches to query and retrieval of the EHR content that takes caching, logging, and distribution into account. Triggering on EHR change events is also explored. A final contribution is an open source openEHR implementation using the above-mentioned approaches to create LiU EEE, an educational EHR environment intended to help newcomers and developers experiment with and learn about the archetype-based EHR approach and enable rapid prototyping. Conclusions Using REST addressed many architectural concerns in a successful way, but an additional messaging component was needed to address some architectural aspects. Many of our approaches are likely of value to other archetype-based EHR implementations and may contribute to associated service model specifications. PMID:23656624

Applying representational state transfer (REST) architecture to archetype-based electronic health record systems.

PubMed

Sundvall, Erik; Nyström, Mikael; Karlsson, Daniel; Eneling, Martin; Chen, Rong; Örman, Håkan

2013-05-09

The openEHR project and the closely related ISO 13606 standard have defined structures supporting the content of Electronic Health Records (EHRs). However, there is not yet any finalized openEHR specification of a service interface to aid application developers in creating, accessing, and storing the EHR content.The aim of this paper is to explore how the Representational State Transfer (REST) architectural style can be used as a basis for a platform-independent, HTTP-based openEHR service interface. Associated benefits and tradeoffs of such a design are also explored. The main contribution is the formalization of the openEHR storage, retrieval, and version-handling semantics and related services into an implementable HTTP-based service interface. The modular design makes it possible to prototype, test, replicate, distribute, cache, and load-balance the system using ordinary web technology. Other contributions are approaches to query and retrieval of the EHR content that takes caching, logging, and distribution into account. Triggering on EHR change events is also explored.A final contribution is an open source openEHR implementation using the above-mentioned approaches to create LiU EEE, an educational EHR environment intended to help newcomers and developers experiment with and learn about the archetype-based EHR approach and enable rapid prototyping. Using REST addressed many architectural concerns in a successful way, but an additional messaging component was needed to address some architectural aspects. Many of our approaches are likely of value to other archetype-based EHR implementations and may contribute to associated service model specifications.

Advanced MRI in Blast-related TBI

DTIC Science & Technology

2012-07-01

test two advanced MRI methods, DTI and resting-state fMRI, in active-duty military blast-related TBI patients acutely after injury and correlate...Introduction: The purpose of the research effort was to test two advanced MRI methods, DTI and resting-state fMRI, in active-duty military blast-related TBI...clinical follow-up assessments and repeat scans on 78 subjects with TBI and 18 controls. 9) We extensively analyzed DTI , resting-state fMRI, and

Sleeper Cab Climate Control Load Reduction for Long-Haul Truck Rest Period Idling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lustbader, J. A.; Kreutzer, C.; Adelman, S.

2015-04-29

Annual fuel use for long-haul truck rest period idling is estimated at 667 million gallons in the United States. The U.S. Department of Energy’s National Renewable Energy Laboratory’s CoolCab project aims to reduce heating, ventilating, and air conditioning (HVAC) loads and resulting fuel use from rest period idling by working closely with industry to design efficient long-haul truck climate control systems while maintaining occupant comfort. Enhancing the thermal performance of cab/sleepers will enable smaller, lighter, and more cost-effective idle reduction solutions. In order for candidate idle reduction technologies to be implemented at the original equipment manufacturer and fleet level, theirmore » effectiveness must be quantified. To address this need, a number of promising candidate technologies were evaluated through experimentation and modeling to determine their effectiveness in reducing rest period HVAC loads. For this study, load reduction strategies were grouped into the focus areas of solar envelope, occupant environment, and conductive pathways. The technologies selected for a complete-cab package of technologies were “ultra-white” paint, advanced insulation, and advanced curtains. To measure the impact of these technologies, a nationally-averaged solar-weighted reflectivity long-haul truck paint color was determined and applied to the baseline test vehicle. Using the complete-cab package of technologies, electrical energy consumption for long-haul truck daytime rest period air conditioning was reduced by at least 35% for summer weather conditions in Colorado. The National Renewable Energy Laboratory's CoolCalc model was then used to extrapolate the performance of the thermal load reduction technologies nationally for 161 major U.S. cities using typical weather conditions for each location over an entire year.« less

The brain's resting-state activity is shaped by synchronized cross-frequency coupling of neural oscillations

PubMed Central

Florin, Esther; Baillet, Sylvain

2015-01-01

Functional imaging of the resting brain consistently reveals broad motifs of correlated blood oxygen level dependent (BOLD) activity that engage cerebral regions from distinct functional systems. Yet, the neurophysiological processes underlying these organized, large-scale fluctuations remain to be uncovered. Using magnetoencephalography (MEG) imaging during rest in 12 healthy subjects we analyse the resting state networks and their underlying neurophysiology. We first demonstrate non-invasively that cortical occurrences of high-frequency oscillatory activity are conditioned to the phase of slower spontaneous fluctuations in neural ensembles. We further show that resting-state networks emerge from synchronized phase-amplitude coupling across the brain. Overall, these findings suggest a unified principle of local-to-global neural signaling for long-range brain communication. PMID:25680519

A descriptive model of resting-state networks using Markov chains.

PubMed

Xie, H; Pal, R; Mitra, S

2016-08-01

Resting-state functional connectivity (RSFC) studies considering pairwise linear correlations have attracted great interests while the underlying functional network structure still remains poorly understood. To further our understanding of RSFC, this paper presents an analysis of the resting-state networks (RSNs) based on the steady-state distributions and provides a novel angle to investigate the RSFC of multiple functional nodes. This paper evaluates the consistency of two networks based on the Hellinger distance between the steady-state distributions of the inferred Markov chain models. The results show that generated steady-state distributions of default mode network have higher consistency across subjects than random nodes from various RSNs.

Age dependent electroencephalographic changes in attention-deficit/hyperactivity disorder (ADHD).

PubMed

Poil, S-S; Bollmann, S; Ghisleni, C; O'Gorman, R L; Klaver, P; Ball, J; Eich-Höchli, D; Brandeis, D; Michels, L

2014-08-01

Objective biomarkers for attention-deficit/hyperactivity disorder (ADHD) could improve diagnostics or treatment monitoring of this psychiatric disorder. The resting electroencephalogram (EEG) provides non-invasive spectral markers of brain function and development. Their accuracy as ADHD markers is increasingly questioned but may improve with pattern classification. This study provides an integrated analysis of ADHD and developmental effects in children and adults using regression analysis and support vector machine classification of spectral resting (eyes-closed) EEG biomarkers in order to clarify their diagnostic value. ADHD effects on EEG strongly depend on age and frequency. We observed typical non-linear developmental decreases in delta and theta power for both ADHD and control groups. However, for ADHD adults we found a slowing in alpha frequency combined with a higher power in alpha-1 (8-10Hz) and beta (13-30Hz). Support vector machine classification of ADHD adults versus controls yielded a notable cross validated sensitivity of 67% and specificity of 83% using power and central frequency from all frequency bands. ADHD children were not classified convincingly with these markers. Resting state electrophysiology is altered in ADHD, and these electrophysiological impairments persist into adulthood. Spectral biomarkers may have both diagnostic and prognostic value. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Functional dissociation of ventral frontal and dorsomedial default mode network components during resting state and emotional autobiographical recall

PubMed Central

Bado, Patricia; Engel, Annerose; de Oliveira-Souza, Ricardo; Bramati, Ivanei E; Paiva, Fernando F; Basilio, Rodrigo; Sato, João R; Tovar-Moll, Fernanda; Moll, Jorge

2014-01-01

Humans spend a substantial share of their lives mind-wandering. This spontaneous thinking activity usually comprises autobiographical recall, emotional, and self-referential components. While neuroimaging studies have demonstrated that a specific brain “default mode network” (DMN) is consistently engaged by the “resting state” of the mind, the relative contribution of key cognitive components to DMN activity is still poorly understood. Here we used fMRI to investigate whether activity in neural components of the DMN can be differentially explained by active recall of relevant emotional autobiographical memories as compared with the resting state. Our study design combined emotional autobiographical memory, neutral memory and resting state conditions, separated by a serial subtraction control task. Shared patterns of activation in the DMN were observed in both emotional autobiographical and resting conditions, when compared with serial subtraction. Directly contrasting autobiographical and resting conditions demonstrated a striking dissociation within the DMN in that emotional autobiographical retrieval led to stronger activation of the dorsomedial core regions (medial prefrontal cortex, posterior cingulate cortex), whereas the resting state condition engaged a ventral frontal network (ventral striatum, subgenual and ventral anterior cingulate cortices) in addition to the IPL. Our results reveal an as yet unreported dissociation within the DMN. Whereas the dorsomedial component can be explained by emotional autobiographical memory, the ventral frontal one is predominantly associated with the resting state proper, possibly underlying fundamental motivational mechanisms engaged during spontaneous unconstrained ideation. Hum Brain Mapp 35:3302–3313, 2014. © 2013 Wiley Periodicals, Inc. PMID:25050426

Detecting brain dynamics during resting state: a tensor based evolutionary clustering approach

NASA Astrophysics Data System (ADS)

Al-sharoa, Esraa; Al-khassaweneh, Mahmood; Aviyente, Selin

2017-08-01

Human brain is a complex network with connections across different regions. Understanding the functional connectivity (FC) of the brain is important both during resting state and task; as disruptions in connectivity patterns are indicators of different psychopathological and neurological diseases. In this work, we study the resting state functional connectivity networks (FCNs) of the brain from fMRI BOLD signals. Recent studies have shown that FCNs are dynamic even during resting state and understanding the temporal dynamics of FCNs is important for differentiating between different conditions. Therefore, it is important to develop algorithms to track the dynamic formation and dissociation of FCNs of the brain during resting state. In this paper, we propose a two step tensor based community detection algorithm to identify and track the brain network community structure across time. First, we introduce an information-theoretic function to reduce the dynamic FCN and identify the time points that are similar topologically to combine them into a tensor. These time points will be used to identify the different FC states. Second, a tensor based spectral clustering approach is developed to identify the community structure of the constructed tensors. The proposed algorithm applies Tucker decomposition to the constructed tensors and extract the orthogonal factor matrices along the connectivity mode to determine the common subspace within each FC state. The detected community structure is summarized and described as FC states. The results illustrate the dynamic structure of resting state networks (RSNs), including the default mode network, somatomotor network, subcortical network and visual network.

Correspondence of the brain's functional architecture during activation and rest.

PubMed

Smith, Stephen M; Fox, Peter T; Miller, Karla L; Glahn, David C; Fox, P Mickle; Mackay, Clare E; Filippini, Nicola; Watkins, Kate E; Toro, Roberto; Laird, Angela R; Beckmann, Christian F

2009-08-04

Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are continuously interacting when the brain is "at rest." In this work, we identify the major explicit activation networks by carrying out an image-based activation network analysis of thousands of separate activation maps derived from the BrainMap database of functional imaging studies, involving nearly 30,000 human subjects. Independently, we extract the major covarying networks in the resting brain, as imaged with functional magnetic resonance imaging in 36 subjects at rest. The sets of major brain networks, and their decompositions into subnetworks, show close correspondence between the independent analyses of resting and activation brain dynamics. We conclude that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically "active" even when at "rest."

Is it possible to automatically distinguish resting EEG data of normal elderly vs. mild cognitive impairment subjects with high degree of accuracy?

PubMed

Rossini, Paolo M; Buscema, Massimo; Capriotti, Massimiliano; Grossi, Enzo; Rodriguez, Guido; Del Percio, Claudio; Babiloni, Claudio

2008-07-01

It has been shown that a new procedure (implicit function as squashing time, IFAST) based on artificial neural networks (ANNs) is able to compress eyes-closed resting electroencephalographic (EEG) data into spatial invariants of the instant voltage distributions for an automatic classification of mild cognitive impairment (MCI) and Alzheimer's disease (AD) subjects with classification accuracy of individual subjects higher than 92%. Here we tested the hypothesis that this is the case also for the classification of individual normal elderly (Nold) vs. MCI subjects, an important issue for the screening of large populations at high risk of AD. Eyes-closed resting EEG data (10-20 electrode montage) were recorded in 171 Nold and in 115 amnesic MCI subjects. The data inputs for the classification by IFAST were the weights of the connections within a nonlinear auto-associative ANN trained to generate the instant voltage distributions of 60-s artifact-free EEG data. The most relevant features were selected and coincidently the dataset was split into two halves for the final binary classification (training and testing) performed by a supervised ANN. The classification of the individual Nold and MCI subjects reached 95.87% of sensitivity and 91.06% of specificity (93.46% of accuracy). These results indicate that IFAST can reliably distinguish eyes-closed resting EEG in individual Nold and MCI subjects. IFAST may be used for large-scale periodic screening of large populations at risk of AD and personalized care.

Wavepacket dynamics of a Rydberg atom monitored by a pair of time-delayed laser pulses

NASA Astrophysics Data System (ADS)

Xin, PeiPei; Cheng, Hong; Zhang, ShanShan; Wang, HanMu; Liu, HongPing

2018-02-01

We have investigated the Rydberg state population of an argon atom by an intense laser pulse and its wavepacket dynamics monitored by another successive laser pulse in the tunneling regime. A wavepacket comprising a superposition of close high-lying Rydberg states is irradiated by a multicycle laser pulse, where the sub-wave components in the wavepacket have fixed relative phases. A time-delayed second laser pulse is employed to apply on the excited Rydberg atom. If the time is properly chosen, one of the sub-wave components will be guided towards the ionization area while the rest remains intact. By means of this pump-probe technique, we could control and monitor the Rydberg wavepacket dynamics and reveal some interesting phenomenon such as the survival rate of individual Rydberg states related to the classical orbital period of electron.

Role of mitochondrial calcium uptake homeostasis in resting state fMRI brain networks.

PubMed

Kannurpatti, Sridhar S; Sanganahalli, Basavaraju G; Herman, Peter; Hyder, Fahmeed

2015-11-01

Mitochondrial Ca(2+) uptake influences both brain energy metabolism and neural signaling. Given that brain mitochondrial organelles are distributed in relation to vascular density, which varies considerably across brain regions, we hypothesized different physiological impacts of mitochondrial Ca(2+) uptake across brain regions. We tested the hypothesis by monitoring brain "intrinsic activity" derived from the resting state functional MRI (fMRI) blood oxygen level dependent (BOLD) fluctuations in different functional networks spanning the somatosensory cortex, caudate putamen, hippocampus and thalamus, in normal and perturbed mitochondrial Ca(2+) uptake states. In anesthetized rats at 11.7 T, mitochondrial Ca(2+) uptake was inhibited or enhanced respectively by treatments with Ru360 or kaempferol. Surprisingly, mitochondrial Ca(2+) uptake inhibition by Ru360 and enhancement by kaempferol led to similar dose-dependent decreases in brain-wide intrinsic activities in both the frequency domain (spectral amplitude) and temporal domain (resting state functional connectivity; RSFC). The fact that there were similar dose-dependent decreases in the frequency and temporal domains of the resting state fMRI-BOLD fluctuations during mitochondrial Ca(2+) uptake inhibition or enhancement indicated that mitochondrial Ca(2+) uptake and its homeostasis may strongly influence the brain's functional organization at rest. Interestingly, the resting state fMRI-derived intrinsic activities in the caudate putamen and thalamic regions saturated much faster with increasing dosage of either drug treatment than the drug-induced trends observed in cortical and hippocampal regions. Regional differences in how the spectral amplitude and RSFC changed with treatment indicate distinct mitochondrion-mediated spontaneous neuronal activity coupling within the various RSFC networks determined by resting state fMRI. Copyright © 2015 John Wiley & Sons, Ltd.

Distinctive Resting State Network Disruptions Among Alzheimer's Disease, Subcortical Vascular Dementia, and Mixed Dementia Patients.

PubMed

Kim, Hee Jin; Cha, Jungho; Lee, Jong-Min; Shin, Ji Soo; Jung, Na-Yeon; Kim, Yeo Jin; Choe, Yearn Seong; Lee, Kyung Han; Kim, Sung Tae; Kim, Jae Seung; Lee, Jae Hong; Na, Duk L; Seo, Sang Won

2016-01-01

Recent advances in resting-state functional MRI have revealed altered functional networks in Alzheimer's disease (AD), especially those of the default mode network (DMN) and central executive network (CEN). However, few studies have evaluated whether small vessel disease (SVD) or combined amyloid and SVD burdens affect the DMN or CEN. The aim of this study was to evaluate whether SVD or combined amyloid and SVD burdens affect the DMN or CEN. In this cross-sectional study, we investigated the resting-state functional connectivity within DMN and CEN in 37 Pittsburgh compound-B (PiB)(+) AD, 37 PiB(-) subcortical vascular dementia (SVaD), 13 mixed dementia patients, and 65 normal controls. When the resting-state DMN of PiB(+) AD and PiB(-) SVaD patients were compared, the PiB(+) AD patients displayed lower functional connectivity in the inferior parietal lobule while the PiB(-) SVaD patients displayed lower functional connectivity in the medial frontal and superior frontal gyri. Compared to the PiB(-) SVaD or PiB(+) AD, the mixed dementia patients displayed lower functional connectivity within the DMN in the posterior cingulate gyrus. When the resting-state CEN connectivity of PiB(+) AD and PiB(-) SVaD patients were compared, the PiB(-) SVaD patients displayed lower functional connectivity in the anterior insular region. Compared to the PiB(-) SVaD or PiB(+) AD, the mixed dementia patients displayed lower functional connectivity within the CEN in the inferior frontal gyrus. Our findings suggest that in PiB(+) AD and PiB(-) SVaD, there is divergent disruptions in resting-state DMN and CEN. Furthermore, patients with combined amyloid and SVD burdens exhibited more disrupted resting-state DMN and CEN than patients with only amyloid or SVD burden.

Differential structural and resting state connectivity between insular subdivisions and other pain-related brain regions.

PubMed

Wiech, K; Jbabdi, S; Lin, C S; Andersson, J; Tracey, I

2014-10-01

Functional neuroimaging studies suggest that the anterior, mid, and posterior division of the insula subserve different functions in the perception of pain. The anterior insula (AI) has predominantly been associated with cognitive-affective aspects of pain, while the mid and posterior divisions have been implicated in sensory-discriminative processing. We examined whether this functional segregation is paralleled by differences in (1) structural and (2) resting state connectivity and (3) in correlations with pain-relevant psychological traits. Analyses were restricted to the 3 insular subdivisions and other pain-related brain regions. Both type of analyses revealed largely overlapping results. The AI division was predominantly connected to the ventrolateral prefrontal cortex (structural and resting state connectivity) and orbitofrontal cortex (structural connectivity). In contrast, the posterior insula showed strong connections to the primary somatosensory cortex (SI; structural connectivity) and secondary somatosensory cortex (SII; structural and resting state connectivity). The mid insula displayed a hybrid connectivity pattern with strong connections with the ventrolateral prefrontal cortex, SII (structural and resting state connectivity) and SI (structural connectivity). Moreover, resting state connectivity revealed strong connectivity of all 3 subdivisions with the thalamus. On the behavioural level, AI structural connectivity was related to the individual degree of pain vigilance and awareness that showed a positive correlation with AI-amygdala connectivity and a negative correlation with AI-rostral anterior cingulate cortex connectivity. In sum, our findings show a differential structural and resting state connectivity for the anterior, mid, and posterior insula with other pain-relevant brain regions, which might at least partly explain their different functional profiles in pain processing. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Altered affective, executive and sensorimotor resting state networks in patients with pediatric mania

PubMed Central

Wu, Minjie; Lu, Lisa H.; Passarotti, Alessandra M.; Wegbreit, Ezra; Fitzgerald, Jacklynn; Pavuluri, Mani N.

2013-01-01

Background The aim of the present study was to map the pathophysiology of resting state functional connectivity accompanying structural and functional abnormalities in children with bipolar disorder. Methods Children with bipolar disorder and demographically matched healthy controls underwent resting-state functional magnetic resonance imaging. A model-free independent component analysis was performed to identify intrinsically interconnected networks. Results We included 34 children with bipolar disorder and 40 controls in our analysis. Three distinct resting state networks corresponding to affective, executive and sensorimotor functions emerged as being significantly different between the pediatric bipolar disorder (PBD) and control groups. All 3 networks showed hyperconnectivity in the PBD relative to the control group. Specifically, the connectivity of the dorsal anterior cingulate cortex (ACC) differentiated the PBD from the control group in both the affective and the executive networks. Exploratory analysis suggests that greater connectivity of the right amygdala within the affective network is associated with better executive function in children with bipolar disorder, but not in controls. Limitations Unique clinical characteristics of the study sample allowed us to evaluate the pathophysiology of resting state connectivity at an early state of PBD, which led to the lack of generalizability in terms of comorbid disorders existing in a typical PBD population. Conclusion Abnormally engaged resting state affective, executive and sensorimotor networks observed in children with bipolar disorder may reflect a biological context in which abnormal task-based brain activity can occur. Dual engagement of the dorsal ACC in affective and executive networks supports the neuroanatomical interface of these networks, and the amygdala’s engagement in moderating executive function illustrates the intricate interplay of these neural operations at rest. PMID:23735583

Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis

DTIC Science & Technology

2016-10-01

AWARD NUMBER: W81XWH-15-2-0032 TITLE: Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis PRINCIPAL...4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis 5b...Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The subject of the project is FY14 PRMRP Topic Area – Tinnitus . The broad

Identifying major depressive disorder using Hurst exponent of resting-state brain networks.

PubMed

Wei, Maobin; Qin, Jiaolong; Yan, Rui; Li, Haoran; Yao, Zhijian; Lu, Qing

2013-12-30

Resting-state functional magnetic resonance imaging (fMRI) studies of major depressive disorder (MDD) have revealed abnormalities of functional connectivity within or among the resting-state networks. They provide valuable insight into the pathological mechanisms of depression. However, few reports were involved in the "long-term memory" of fMRI signals. This study was to investigate the "long-term memory" of resting-state networks by calculating their Hurst exponents for identifying depressed patients from healthy controls. Resting-state networks were extracted from fMRI data of 20 MDD and 20 matched healthy control subjects. The Hurst exponent of each network was estimated by Range Scale analysis for further discriminant analysis. 95% of depressed patients and 85% of healthy controls were correctly classified by Support Vector Machine with an accuracy of 90%. The right fronto-parietal and default mode network constructed a deficit network (lower memory and more irregularity in MDD), while the left fronto-parietal, ventromedial prefrontal and salience network belonged to an excess network (longer memory in MDD), suggesting these dysfunctional networks may be related to a portion of the complex of emotional and cognitive disturbances. The abnormal "long-term memory" of resting-state networks associated with depression may provide a new possibility towards the exploration of the pathophysiological mechanisms of MDD. © 2013 Elsevier Ireland Ltd. All rights reserved.

Predicting efficacy of robot-aided rehabilitation in chronic stroke patients using an MRI-compatible robotic device.

PubMed

Sergi, Fabrizio; Krebs, Hermano Igo; Groissier, Benjamin; Rykman, Avrielle; Guglielmelli, Eugenio; Volpe, Bruce T; Schaechter, Judith D

2011-01-01

We are investigating the neural correlates of motor recovery promoted by robot-mediated therapy in chronic stroke. This pilot study asked whether efficacy of robot-aided motor rehabilitation in chronic stroke could be predicted by a change in functional connectivity within the sensorimotor network in response to a bout of motor rehabilitation. To address this question, two stroke patients participated in a functional connectivity MRI study pre and post a 12-week robot-aided motor rehabilitation program. Functional connectivity was evaluated during three consecutive scans before the rehabilitation program: resting-state; point-to-point reaching movements executed by the paretic upper extremity (UE) using a newly developed MRI-compatible sensorized passive manipulandum; resting-state. A single resting-state scan was conducted after the rehabilitation program. Before the program, UE movement reduced functional connectivity between the ipsilesional and contralesional primary motor cortex. Reduced interhemispheric functional connectivity persisted during the second resting-state scan relative to the first and during the resting-state scan after the rehabilitation program. Greater reduction in interhemispheric functional connectivity during the resting-state was associated with greater gains in UE motor function induced by the 12-week robotic therapy program. These findings suggest that greater reduction in interhemispheric functional connectivity in response to a bout of motor rehabilitation may predict greater efficacy of the full rehabilitation program.

ABERRANT RESTING-STATE BRAIN ACTIVITY IN POSTTRAUMATIC STRESS DISORDER: A META-ANALYSIS AND SYSTEMATIC REVIEW.

PubMed

Koch, Saskia B J; van Zuiden, Mirjam; Nawijn, Laura; Frijling, Jessie L; Veltman, Dick J; Olff, Miranda

2016-07-01

About 10% of trauma-exposed individuals develop PTSD. Although a growing number of studies have investigated resting-state abnormalities in PTSD, inconsistent results suggest a need for a meta-analysis and a systematic review. We conducted a systematic literature search in four online databases using keywords for PTSD, functional neuroimaging, and resting-state. In total, 23 studies matched our eligibility criteria. For the meta-analysis, we included 14 whole-brain resting-state studies, reporting data on 663 participants (298 PTSD patients and 365 controls). We used the activation likelihood estimation approach to identify concurrence of whole-brain hypo- and hyperactivations in PTSD patients during rest. Seed-based studies could not be included in the quantitative meta-analysis. Therefore, a separate qualitative systematic review was conducted on nine seed-based functional connectivity studies. The meta-analysis showed consistent hyperactivity in the ventral anterior cingulate cortex and the parahippocampus/amygdala, but hypoactivity in the (posterior) insula, cerebellar pyramis and middle frontal gyrus in PTSD patients, compared to healthy controls. Partly concordant with these findings, the systematic review on seed-based functional connectivity studies showed enhanced salience network (SN) connectivity, but decreased default mode network (DMN) connectivity in PTSD. Combined, these altered resting-state connectivity and activity patterns could represent neurobiological correlates of increased salience processing and hypervigilance (SN), at the cost of awareness of internal thoughts and autobiographical memory (DMN) in PTSD. However, several discrepancies between findings of the meta-analysis and systematic review were observed, stressing the need for future studies on resting-state abnormalities in PTSD patients. © 2016 Wiley Periodicals, Inc.

Changes in dynamic resting state network connectivity following aphasia therapy.

PubMed

Duncan, E Susan; Small, Steven L

2017-10-24

Resting state magnetic resonance imaging (rsfMRI) permits observation of intrinsic neural networks produced by task-independent correlations in low frequency brain activity. Various resting state networks have been described, with each thought to reflect common engagement in some shared function. There has been limited investigation of the plasticity in these network relationships after stroke or induced by therapy. Twelve individuals with language disorders after stroke (aphasia) were imaged at multiple time points before (baseline) and after an imitation-based aphasia therapy. Language assessment using a narrative production task was performed at the same time points. Group independent component analysis (ICA) was performed on the rsfMRI data to identify resting state networks. A sliding window approach was then applied to assess the dynamic nature of the correlations among these networks. Network correlations during each 30-second window were used to cluster the data into ten states for each window at each time point for each subject. Correlation was performed between changes in time spent in each state and therapeutic gains on the narrative task. The amount of time spent in a single one of the (ten overall) dynamic states was positively associated with behavioral improvement on the narrative task at the 6-week post-therapy maintenance interval, when compared with either baseline or assessment immediately following therapy. This particular state was characterized by minimal correlation among the task-independent resting state networks. Increased functional independence and segregation of resting state networks underlies improvement on a narrative production task following imitation-based aphasia treatment. This has important clinical implications for the targeting of noninvasive brain stimulation in post-stroke remediation.

Effects of Parental Smoking on Exercise Systolic Blood Pressure in Adolescents

PubMed Central

Hacke, Claudia; Weisser, Burkhard

2015-01-01

Background In adults, exercise blood pressure seems to be more closely related to cardiovascular risk than resting blood pressure; however, few data are available on the effects of familial risk factors, including smoking habits, on exercise blood pressure in adolescents. Methods and Results Blood pressure at rest and during exercise, parental smoking, and other familial risk factors were investigated in 532 adolescents aged 12 to 17 years (14.6±1.5 years) in the Kiel EX.PRESS. (EXercise PRESSure) Study. Exercise blood pressure was determined at 1.5 W/kg body weight using a standardized submaximal cycle ergometer test. Mean resting blood pressure was 113.1±12.8/57.2±7.1 mm Hg, and exercise blood pressure was 149.9±19.8/54.2±8.6 mm Hg. Parental smoking increased exercise systolic blood pressure (+4.0 mm Hg, 3.1 to 4.9; P=0.03) but not resting blood pressure of the subjects (adjusted for age, sex, height, body mass index percentile, fitness). Parental overweight and familial hypertension were related to both higher resting and exercise systolic blood pressure values, whereas associations with an inactive lifestyle and a low educational level of the parents were found only with adolescents’ blood pressure during exercise. The cumulative effect of familial risk factors on exercise systolic blood pressure was more pronounced than on blood pressure at rest. Conclusions Parental smoking might be a novel risk factor for higher blood pressure, especially during exercise. In addition, systolic blood pressure during a submaximal exercise test was more closely associated with familial risk factors than was resting blood pressure, even in adolescents. PMID:25964207

Effects of parental smoking on exercise systolic blood pressure in adolescents.

PubMed

Hacke, Claudia; Weisser, Burkhard

2015-05-11

In adults, exercise blood pressure seems to be more closely related to cardiovascular risk than resting blood pressure; however, few data are available on the effects of familial risk factors, including smoking habits, on exercise blood pressure in adolescents. Blood pressure at rest and during exercise, parental smoking, and other familial risk factors were investigated in 532 adolescents aged 12 to 17 years (14.6±1.5 years) in the Kiel EX.PRESS. (EXercise PRESSure) Study. Exercise blood pressure was determined at 1.5 W/kg body weight using a standardized submaximal cycle ergometer test. Mean resting blood pressure was 113.1±12.8/57.2±7.1 mm Hg, and exercise blood pressure was 149.9±19.8/54.2±8.6 mm Hg. Parental smoking increased exercise systolic blood pressure (+4.0 mm Hg, 3.1 to 4.9; P=0.03) but not resting blood pressure of the subjects (adjusted for age, sex, height, body mass index percentile, fitness). Parental overweight and familial hypertension were related to both higher resting and exercise systolic blood pressure values, whereas associations with an inactive lifestyle and a low educational level of the parents were found only with adolescents' blood pressure during exercise. The cumulative effect of familial risk factors on exercise systolic blood pressure was more pronounced than on blood pressure at rest. Parental smoking might be a novel risk factor for higher blood pressure, especially during exercise. In addition, systolic blood pressure during a submaximal exercise test was more closely associated with familial risk factors than was resting blood pressure, even in adolescents. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Posterior resting state EEG asymmetries are associated with hedonic valuation of food.

PubMed

van Bochove, Marlies E; Ketel, Eva; Wischnewski, Miles; Wegman, Joost; Aarts, Esther; de Jonge, Benjamin; Medendorp, W Pieter; Schutter, Dennis J L G

2016-12-01

Research on the hedonic value of food has been important in understanding the motivational and emotional correlates of normal and abnormal eating behaviour. The aim of the present study was to explore associations between hemispheric asymmetries recorded during resting state electroencephalogram (EEG) and hedonic valuation of food. Healthy adult volunteers were recruited and four minutes of resting state EEG were recorded from the scalp. Hedonic food valuation and reward sensitivity were assessed with the hedonic attitude to food and behavioural activation scale. Results showed that parieto-occipital resting state EEG asymmetries in the alpha (8-12Hz) and beta (13-30Hz) frequency range correlate with the hedonic valuation of food. Our findings suggest that self-reported sensory-related attitude towards food is associated with interhemispheric asymmetries in resting state oscillatory activity. Our findings contribute to understanding the electrophysiological correlates of hedonic valuation, and may provide an opportunity to modulate the cortical imbalance by using non-invasive brain stimulation methods to change food consumption. Copyright © 2016 Elsevier B.V. All rights reserved.

Maintenance and Representation of Mind Wandering during Resting-State fMRI.

PubMed

Chou, Ying-Hui; Sundman, Mark; Whitson, Heather E; Gaur, Pooja; Chu, Mei-Lan; Weingarten, Carol P; Madden, David J; Wang, Lihong; Kirste, Imke; Joliot, Marc; Diaz, Michele T; Li, Yi-Ju; Song, Allen W; Chen, Nan-Kuei

2017-01-12

Major advances in resting-state functional magnetic resonance imaging (fMRI) techniques in the last two decades have provided a tool to better understand the functional organization of the brain both in health and illness. Despite such developments, characterizing regulation and cerebral representation of mind wandering, which occurs unavoidably during resting-state fMRI scans and may induce variability of the acquired data, remains a work in progress. Here, we demonstrate that a decrease or decoupling in functional connectivity involving the caudate nucleus, insula, medial prefrontal cortex and other domain-specific regions was associated with more sustained mind wandering in particular thought domains during resting-state fMRI. Importantly, our findings suggest that temporal and between-subject variations in functional connectivity of above-mentioned regions might be linked with the continuity of mind wandering. Our study not only provides a preliminary framework for characterizing the maintenance and cerebral representation of different types of mind wandering, but also highlights the importance of taking mind wandering into consideration when studying brain organization with resting-state fMRI in the future.

Improved sensitivity and specificity for resting state and task fMRI with multiband multi-echo EPI compared to multi-echo EPI at 7 T.

PubMed

Boyacioğlu, Rasim; Schulz, Jenni; Koopmans, Peter J; Barth, Markus; Norris, David G

2015-10-01

A multiband multi-echo (MBME) sequence is implemented and compared to a matched standard multi-echo (ME) protocol to investigate the potential improvement in sensitivity and spatial specificity at 7 T for resting state and task fMRI. ME acquisition is attractive because BOLD sensitivity is less affected by variation in T2*, and because of the potential for separating BOLD and non-BOLD signal components. MBME further reduces TR thus increasing the potential reduction in physiological noise. In this study we used FSL-FIX to clean ME and MBME resting state and task fMRI data (both 3.5mm isotropic). After noise correction, the detection of resting state networks improves with more non-artifactual independent components being observed. Additional activation clusters for task data are discovered for MBME data (increased sensitivity) whereas existing clusters become more localized for resting state (improved spatial specificity). The results obtained indicate that MBME is superior to ME at high field strengths. Copyright © 2015 Elsevier Inc. All rights reserved.

Frequency specific patterns of resting-state networks development from childhood to adolescence: A magnetoencephalography study.

PubMed

Meng, Lu; Xiang, Jing

2016-11-01

The present study investigated frequency dependent developmental patterns of the brain resting-state networks from childhood to adolescence. Magnetoencephalography (MEG) data were recorded from 20 healthy subjects at resting-state with eyes-open. The resting-state networks (RSNs) was analyzed at source-level. Brain network organization was characterized by mean clustering coefficient and average path length. The correlations between brain network measures and subjects' age during development from childhood to adolescence were statistically analyzed in delta (1-4Hz), theta (4-8Hz), alpha (8-12Hz), and beta (12-30Hz) frequency bands. A significant positive correlation between functional connectivity with age was found in alpha and beta frequency bands. A significant negative correlation between average path lengths with age was found in beta frequency band. The results suggest that there are significant developmental changes of resting-state networks from childhood to adolescence, which matures from a lattice network to a small-world network. Copyright © 2016 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Neuroimaging markers of glutamatergic and GABAergic systems in drug addiction: relationships to resting-state functional connectivity

PubMed Central

Moeller, Scott J.; London, Edythe D.; Northoff, Georg

2015-01-01

Drug addiction is characterized by widespread abnormalities in brain function and neurochemistry, including drug-associated effects on concentrations of the excitatory and inhibitory neurotransmitters glutamate and gamma-aminobutyric acid (GABA), respectively. In healthy individuals, these neurotransmitters drive the resting state, a default condition of brain function also disrupted in addiction. Here, our primary goal was to review in vivo magnetic resonance spectroscopy and positron emission tomography studies that examined markers of glutamate and GABA abnormalities in human drug addiction. Addicted individuals tended to show decreases in these markers compared with healthy controls, but findings also varied by individual characteristics (e.g., abstinence length). Interestingly, select corticolimbic brain regions showing glutamatergic and/or GABAergic abnormalities have been similarly implicated in resting-state functional connectivity deficits in drug addiction. Thus, our secondary goals were to provide a brief review of this resting-state literature, and an initial rationale for the hypothesis that abnormalities in glutamatergic and/or GABAergic neurotransmission may underlie resting-state functional deficits in drug addiction. In doing so, we suggest future research directions and possible treatment implications. PMID:26657968

Effect of Acupuncture on Functional Connectivity of Anterior Cingulate Cortex for Bell's Palsy Patients with Different Clinical Duration

PubMed Central

Wu, Hongli; Kan, Hongxing; Li, Chuanfu; Park, Kyungmo; Zhu, Yifang; Mohamed, Abdalla Z.; Xu, Chunsheng; Wu, Yuanyuan; Zhang, Wei

2015-01-01

Acupuncture is widely used in the treatment of Bell's palsy (BP) in many countries, but its underlying physiological mechanism remained controversial. In order to explore the potential mechanism, changes of functional connectivity (FC) of anterior cingulate gyrus (ACC) were investigated. We collected 20 healthy (control group) participants and 28 BP patients with different clinical duration accepted resting state functional MRI (rfMRI) scans before and after acupuncture, respectively. The FC of ACC before and after acupuncture was compared with paired t-test and the detailed results are presented in the paper. Our results showed that effects of the acupuncture on FC were closely related to clinical duration in patients with BP, which suggested that brain response to acupuncture was closely connected with the status of brain functional connectivity and implied that acupuncture plays a homeostatic role in the BP treatment. PMID:26161125

Efficiency at rest: magnetoencephalographic resting-state connectivity and individual differences in verbal working memory.

PubMed

del Río, David; Cuesta, Pablo; Bajo, Ricardo; García-Pacios, Javier; López-Higes, Ramón; del-Pozo, Francisco; Maestú, Fernando

2012-11-01

Inter-individual differences in cognitive performance are based on an efficient use of task-related brain resources. However, little is known yet on how these differences might be reflected on resting-state brain networks. Here we used Magnetoencephalography resting-state recordings to assess the relationship between a behavioral measurement of verbal working memory and functional connectivity as measured through Mutual Information. We studied theta (4-8 Hz), low alpha (8-10 Hz), high alpha (10-13 Hz), low beta (13-18 Hz) and high beta (18-30 Hz) frequency bands. A higher verbal working memory capacity was associated with a lower mutual information in the low alpha band, prominently among right-anterior and left-lateral sensors. The results suggest that an efficient brain organization in the domain of verbal working memory might be related to a lower resting-state functional connectivity across large-scale brain networks possibly involving right prefrontal and left perisylvian areas. Copyright © 2012 Elsevier B.V. All rights reserved.

Sparse dictionary learning for resting-state fMRI analysis

NASA Astrophysics Data System (ADS)

Lee, Kangjoo; Han, Paul Kyu; Ye, Jong Chul

2011-09-01

Recently, there has been increased interest in the usage of neuroimaging techniques to investigate what happens in the brain at rest. Functional imaging studies have revealed that the default-mode network activity is disrupted in Alzheimer's disease (AD). However, there is no consensus, as yet, on the choice of analysis method for the application of resting-state analysis for disease classification. This paper proposes a novel compressed sensing based resting-state fMRI analysis tool called Sparse-SPM. As the brain's functional systems has shown to have features of complex networks according to graph theoretical analysis, we apply a graph model to represent a sparse combination of information flows in complex network perspectives. In particular, a new concept of spatially adaptive design matrix has been proposed by implementing sparse dictionary learning based on sparsity. The proposed approach shows better performance compared to other conventional methods, such as independent component analysis (ICA) and seed-based approach, in classifying the AD patients from normal using resting-state analysis.

Functional connectivity dynamics: modeling the switching behavior of the resting state.

PubMed

Hansen, Enrique C A; Battaglia, Demian; Spiegler, Andreas; Deco, Gustavo; Jirsa, Viktor K

2015-01-15

Functional connectivity (FC) sheds light on the interactions between different brain regions. Besides basic research, it is clinically relevant for applications in Alzheimer's disease, schizophrenia, presurgical planning, epilepsy, and traumatic brain injury. Simulations of whole-brain mean-field computational models with realistic connectivity determined by tractography studies enable us to reproduce with accuracy aspects of average FC in the resting state. Most computational studies, however, did not address the prominent non-stationarity in resting state FC, which may result in large intra- and inter-subject variability and thus preclude an accurate individual predictability. Here we show that this non-stationarity reveals a rich structure, characterized by rapid transitions switching between a few discrete FC states. We also show that computational models optimized to fit time-averaged FC do not reproduce these spontaneous state transitions and, thus, are not qualitatively superior to simplified linear stochastic models, which account for the effects of structure alone. We then demonstrate that a slight enhancement of the non-linearity of the network nodes is sufficient to broaden the repertoire of possible network behaviors, leading to modes of fluctuations, reminiscent of some of the most frequently observed Resting State Networks. Because of the noise-driven exploration of this repertoire, the dynamics of FC qualitatively change now and display non-stationary switching similar to empirical resting state recordings (Functional Connectivity Dynamics (FCD)). Thus FCD bear promise to serve as a better biomarker of resting state neural activity and of its pathologic alterations. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

76 FR 82017 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Notice of Filing of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-29

... the FLEX electronic book and to the FLEX electronic RFQ process, and (v) include a description of...\\ currently resting in the electronic book in the particular series to be traded.\\8\\ Resting FLEX Orders may only be entered in the electronic book as ``day orders'' and are cancelled at the close of each trade...

Exploring the Active Center of the LSD1/CoREST Complex by Molecular Dynamics Simulation Utilizing Its Co-crystallized Co-factor Tetrahydrofolate as a Probe.

PubMed

Zalloum, Waleed A; Zalloum, Hiba M

2017-12-26

Epigenetic targeting of cancer is a recent effort to manipulate the gene without destroying the genetic material. Lysine-specific demethylase 1 (LSD1) is one of the enzymes associated with the chromatin for post-translational modifications, where it demethylates lysine amino acid in the chromatin H3 tail. Many studies showed that inhibiting LSD1 could potentially be used to treat cancer epigenetically. LSD1 is associated with its corepressor protein CoREST, and it uses tetrahydrofolate as a co-factor to accept CH 2 from the demethylation process. In this study, the co-crystallized co-factor tetrahydrofolate was utilized to determine possible binding regions in the active center of the LSD1/CoREST complex. Also, the flexibility of the complex has been investigated by molecular dynamics simulation and subsequent analysis by clustering and principal component analysis. This research supported other studies and showed that LSD1/CoREST complex exists in two main conformational structures: open and closed. Furthermore, this study showed that tetrahydrofolate stably binds to the LSD1/CoREST complex, in its open conformation, at its entrance. It then binds to the core of the complex, inducing the closed conformation. Furthermore, the interactions of tetrahydrofolate to these two binding regions and the corresponding binding mode of tetrahydrofolate were investigated to be used in structure-based drug design.

Frontal-posterior coherence and cognitive function in older adults.

PubMed

Fleck, Jessica I; Kuti, Julia; Brown, Jessica; Mahon, Jessica R; Gayda-Chelder, Christine

2016-12-01

The reliable measurement of brain health and cognitive function is essential in mitigating the negative effects associated with cognitive decline through early and accurate diagnosis of change. The present research explored the relationship between EEG coherence for electrodes within frontal and posterior regions, as well as coherence between frontal and posterior electrodes and performance on standard neuropsychological measures of memory and executive function. EEG coherence for eyes-closed resting-state EEG activity was calculated for delta, theta, alpha, beta, and gamma frequency bands. Participants (N=66; mean age=67.15years) had their resting-state EEGs recorded and completed a neuropsychological battery that assessed memory and executive function, two cognitive domains that are significantly affected during aging. A positive relationship was observed between coherence within the frontal region and performance on measures of memory and executive function for delta and beta frequency bands. In addition, an inverse relationship was observed for coherence between frontal and posterior electrode pairs, particularly within the theta frequency band, and performance on Digit Span Sequencing, a measure of working memory. The present research supports a more substantial link between EEG coherence, rather than spectral power, and cognitive function. Continued study in this area may enable EEG to be applied broadly as a diagnostic measure of cognitive ability. Copyright © 2016 Elsevier B.V. All rights reserved.

Rhodium Phosphine-π-Arene Intermediates in the Hydroamination of Alkenes

PubMed Central

Liu, Zhijian; Yamamichi, Hideaki; Madrahimov, Sherzod T.; Hartwig, John F.

2011-01-01

A detailed mechanistic study of the intramolecular hydroamination of alkenes with amines catalyzed by rhodium complexes of a biaryldialkylphosphine are reported. The active catalyst is shown to contain the phosphine ligand bound in a κ1, η6 form in which the arene is π-bound to rhodium. Addition of deuterated amine to an internal olefin showed that the reaction occurs by trans addition of the N-H bond across the C=C bond, and this stereochemistry implies that the reaction occurs by nucleophilic attack of the amine on a coordinated alkene. Indeed, the cationic rhodium fragment binds the alkene over the secondary amine, and the olefin complex was shown to be the catalyst resting state. The reaction was zero-order in substrate, when the concentration of olefin was high, and a primary isotope effect was observed. The primary isotope effect, in combination with the observation of the alkene complex as the resting state, implies that nucleophilic attack of the amine on the alkene is reversible and is followed by turnover-limiting protonation. This mechanism constitutes an unusual pathway for rhodium-catalyzed additions to alkenes and is more closely related to the mechanism for palladium-catalyzed addition of amide N-H bonds to alkenes. PMID:21309512

Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis

DTIC Science & Technology

2017-10-13

AWARD NUMBER: W81XWH-15-2-0032 TITLE: Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis...TITLE AND SUBTITLE 5a. CONTRACT NUMBER W81XWH-15-2-0032 5b. GRANT NUMBER Identifying Subgroups of Tinnitus Using Novel Resting State fMRI...Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The subject of the project is FY14 PRMRP Topic Area – Tinnitus . The broad goal is

Effects of Methylphenidate on Resting-State Functional Connectivity of the Mesocorticolimbic Dopamine Pathways in Cocaine Addiction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Konova, Anna B.; Moeller, Scott J.; Tomasi, Dardo

Cocaine addiction is associated with altered resting-state functional connectivity among regions of the mesocorticolimbic dopamine pathways. Methylphenidate hydrochloride, an indirect dopamine agonist, normalizes task-related regional brain activity and associated behavior in cocaine users; however, the neural systems–level effects of methylphenidate in this population have not yet been described. To use resting-state functional magnetic resonance imaging to examine changes in mesocorticolimbic connectivity with methylphenidate and how connectivity of affected pathways relates to severity of cocaine addiction.

Sparse dictionary learning of resting state fMRI networks.

PubMed

Eavani, Harini; Filipovych, Roman; Davatzikos, Christos; Satterthwaite, Theodore D; Gur, Raquel E; Gur, Ruben C

2012-07-02

Research in resting state fMRI (rsfMRI) has revealed the presence of stable, anti-correlated functional subnetworks in the brain. Task-positive networks are active during a cognitive process and are anti-correlated with task-negative networks, which are active during rest. In this paper, based on the assumption that the structure of the resting state functional brain connectivity is sparse, we utilize sparse dictionary modeling to identify distinct functional sub-networks. We propose two ways of formulating the sparse functional network learning problem that characterize the underlying functional connectivity from different perspectives. Our results show that the whole-brain functional connectivity can be concisely represented with highly modular, overlapping task-positive/negative pairs of sub-networks.

Resting cardiac vagal tone predicts intraindividual reaction time variability during an attention task in a sample of young and healthy adults.

PubMed

Williams, DeWayne P; Thayer, Julian F; Koenig, Julian

2016-12-01

Intraindividual reaction time variability (IIV), defined as the variability in trial-to-trial response times, is thought to serve as an index of central nervous system function. As such, greater IIV reflects both poorer executive brain function and cognitive control, in addition to lapses in attention. Resting-state vagally mediated heart rate variability (vmHRV), a psychophysiological index of self-regulatory abilities, has been linked with executive brain function and cognitive control such that those with greater resting-state vmHRV often perform better on cognitive tasks. However, research has yet to investigate the direct relationship between resting vmHRV and task IIV. The present study sought to examine this relationship in a sample of 104 young and healthy participants who first completed a 5-min resting-baseline period during which resting-state vmHRV was assessed. Participants then completed an attentional (target detection) task, where reaction time, accuracy, and trial-to-trial IIV were obtained. Results showed resting vmHRV to be significantly related to IIV, such that lower resting vmHRV predicted higher IIV on the task, even when controlling for several covariates (including mean reaction time and accuracy). Overall, our results provide further evidence for the link between resting vmHRV and cognitive control, and extend these notions to the domain of lapses in attention, as indexed by IIV. Implications and recommendations for future research on resting vmHRV and cognition are discussed. © 2016 Society for Psychophysiological Research.

Neural correlate of resting-state functional connectivity under α2 adrenergic receptor agonist, medetomidine.

PubMed

Nasrallah, Fatima A; Lew, Si Kang; Low, Amanda Si-Min; Chuang, Kai-Hsiang

2014-01-01

Correlative fluctuations in functional MRI (fMRI) signals across the brain at rest have been taken as a measure of functional connectivity, but the neural basis of this resting-state MRI (rsMRI) signal is not clear. Previously, we found that the α2 adrenergic agonist, medetomidine, suppressed the rsMRI correlation dose-dependently but not the stimulus evoked activation. To understand the underlying electrophysiology and neurovascular coupling, which might be altered due to the vasoconstrictive nature of medetomidine, somatosensory evoked potential (SEP) and resting electroencephalography (EEG) were measured and correlated with corresponding BOLD signals in rat brains under three dosages of medetomidine. The SEP elicited by electrical stimulation to both forepaws was unchanged regardless of medetomidine dosage, which was consistent with the BOLD activation. Identical relationship between the SEP and BOLD signal under different medetomidine dosages indicates that the neurovascular coupling was not affected. Under resting state, EEG power was the same but a depression of inter-hemispheric EEG coherence in the gamma band was observed at higher medetomidine dosage. Different from medetomidine, both resting EEG power and BOLD power and coherence were significantly suppressed with increased isoflurane level. Such reduction was likely due to suppressed neural activity as shown by diminished SEP and BOLD activation under isoflurane, suggesting different mechanisms of losing synchrony at resting-state. Even though, similarity between electrophysiology and BOLD under stimulation and resting-state implicates a tight neurovascular coupling in both medetomidine and isoflurane. Our results confirm that medetomidine does not suppress neural activity but dissociates connectivity in the somatosensory cortex. The differential effect of medetomidine and its receptor specific action supports the neuronal origin of functional connectivity and implicates the mechanism of its sedative effect. © 2013. Published by Elsevier Inc. All rights reserved.

Is functional integration of resting state brain networks an unspecific biomarker for working memory performance?

PubMed

Alavash, Mohsen; Doebler, Philipp; Holling, Heinz; Thiel, Christiane M; Gießing, Carsten

2015-03-01

Is there one optimal topology of functional brain networks at rest from which our cognitive performance would profit? Previous studies suggest that functional integration of resting state brain networks is an important biomarker for cognitive performance. However, it is still unknown whether higher network integration is an unspecific predictor for good cognitive performance or, alternatively, whether specific network organization during rest predicts only specific cognitive abilities. Here, we investigated the relationship between network integration at rest and cognitive performance using two tasks that measured different aspects of working memory; one task assessed visual-spatial and the other numerical working memory. Network clustering, modularity and efficiency were computed to capture network integration on different levels of network organization, and to statistically compare their correlations with the performance in each working memory test. The results revealed that each working memory aspect profits from a different resting state topology, and the tests showed significantly different correlations with each of the measures of network integration. While higher global network integration and modularity predicted significantly better performance in visual-spatial working memory, both measures showed no significant correlation with numerical working memory performance. In contrast, numerical working memory was superior in subjects with highly clustered brain networks, predominantly in the intraparietal sulcus, a core brain region of the working memory network. Our findings suggest that a specific balance between local and global functional integration of resting state brain networks facilitates special aspects of cognitive performance. In the context of working memory, while visual-spatial performance is facilitated by globally integrated functional resting state brain networks, numerical working memory profits from increased capacities for local processing, especially in brain regions involved in working memory performance. Copyright © 2014 Elsevier Inc. All rights reserved.

Resting-state EEG, Impulsiveness, and Personality in Daily and Nondaily Smokers†

PubMed Central

Rass, Olga; Ahn, Woo-Young; O’Donnell, Brian F.

2015-01-01

Objectives Resting EEG is sensitive to transient, acute effects of nicotine administration and abstinence, but the chronic effects smoking on EEG are poorly characterized. This study measures the resting EEG profile of chronic smokers in a non-deprived, non-peak state to test whether differences in smoking behavior and personality traits affect pharmaco-EEG response. Methods Resting EEG, impulsiveness, and personality measures were collected from daily smokers (n=22), nondaily smokers (n=31), and non-smokers (n=30). Results Daily smokers had reduced resting delta and alpha EEG power and higher impulsiveness (Barratt Impulsiveness Scale) compared to nondaily smokers and non-smokers. Both daily and nondaily smokers discounted delayed rewards more steeply, reported lower conscientiousness (NEO-FFI) and reported greater disinhibition and experience seeking (Sensation Seeking Scale) than non-smokers. Nondaily smokers reported greater sensory hedonia than nonsmokers. Conclusions Altered resting EEG power in daily smokers demonstrates differences in neural signaling that correlated with greater smoking behavior and dependence. Although nondaily smokers share some characteristics with daily smokers that may predict smoking initiation and maintenance, they differ on measures of impulsiveness and resting EEG power. Significance Resting EEG in non-deprived chronic smokers provides a standard for comparison to peak and trough nicotine states and may serve as a biomarker for nicotine dependence, relapse risk, and recovery. PMID:26051750

Impact of 36 h of total sleep deprivation on resting-state dynamic functional connectivity.

PubMed

Xu, Huaze; Shen, Hui; Wang, Lubin; Zhong, Qi; Lei, Yu; Yang, Liu; Zeng, Ling-Li; Zhou, Zongtan; Hu, Dewen; Yang, Zheng

2018-06-01

Resting-state functional magnetic resonance imaging (fMRI) studies using static functional connectivity (sFC) measures have shown that the brain function is severely disrupted after long-term sleep deprivation (SD). However, increasing evidence has suggested that resting-state functional connectivity (FC) is dynamic and exhibits spontaneous fluctuation on a smaller timescale. The process by which long-term SD can influence dynamic functional connectivity (dFC) remains unclear. In this study, 37 healthy subjects participated in the SD experiment, and they were scanned both during rested wakefulness (RW) and after 36 h of SD. A sliding-window based approach and a spectral clustering algorithm were used to evaluate the effects of SD on dFC based on the 26 qualified subjects' data. The outcomes showed that time-averaging FC across specific regions as well as temporal properties of the FC states, such as the dwell time and transition probability, was strongly influenced after SD in contrast to the RW condition. Based on the occurrences of FC states, we further identified some RW-dominant states characterized by anti-correlation between the default mode network (DMN) and other cortices, and some SD-dominant states marked by significantly decreased thalamocortical connectivity. In particular, the temporal features of these FC states were negatively correlated with the correlation coefficients between the DMN and dorsal attention network (dATN) and demonstrated high potential in classification of sleep state (with 10-fold cross-validation accuracy of 88.6% for dwell time and 88.1% for transition probability). Collectively, our results suggested that the temporal properties of the FC states greatly account for changes in the resting-state brain networks following SD, which provides new insights into the impact of SD on the resting-state functional organization in the human brain. Copyright © 2017. Published by Elsevier B.V.

Absolute Measurements of Field Enhanced Dielectronic Recombination and Electron Impact Excitation

NASA Astrophysics Data System (ADS)

Savin, Daniel Wolf

Absolute measurements have been made of the dielectronic recombination (DR) rate coefficient for C^ {3+}, via the 2s-2p core -excitation, in an external electric field of 11.4 +/- 0.9(1sigma) V cm ^{-1}; and of the electron impact excitation (EIE) rate coefficient for C ^{3+}(2s-2p) at energies near threshold. The ion-rest-frame FWHM of the electron energy spread was 1.74 +/- 0.22(1sigma) eV. The measured DR rate, at a mean electron energy of 8.26 +/- 0.07(1sigma ) eV, was (2.76+/- 0.75)times 10^{-10} cm^{3 } s^{-1}. The uncertainty quoted for the DR rate is the total experimental uncertainty at a 1sigma<=vel. The present DR result appears to agree with an intermediate coupling calculation which uses the isolated-resonance, single-configuration approximation. In comparing with theory, a semi-classical formula was used to determine which recombined ions were field-ionized by the 4.65 kV cm^{-1} fields in the final-charge-state analyzer and not detected. A more precise treatment of field-ionization, which includes the lifetime of the high Rydberg C^{2+} ions in the external field and the time evolution and rotation of the fields experienced by the recombined ions, is needed before a definitive comparison between experiment and theory can be made. For the EIE results, at an ion-rest-frame energy of 10.10 eV, the measured rate coefficient was (7.79+/- 2.10)times 10^{ -8} cm^3 s^ {-1}. The measured cross section was (4.15+/- 1.12)times 10^{ -16} cm^2. The uncertainties quoted here represent the total experimental uncertainty at a 90 percent confidence level. Good agreement is found with other measurements. Agreement is not good with Coulomb -Born with exchange and two-state close-coupling calculations which fall outside the 90-percent-confidence uncertainty limits. Agreement is better with a nine-state close-coupling calculation which lies at the extreme of the uncertainty limits. Taking into account previous measurements in C ^{3+} and also a measurement of EIE in Be^+ which lies 19 percent below close-coupling calculations, there is a suggestion that the C^{3+}(2s-2p) EIE rate coefficient may fall slightly below presently accepted values.

Negative functional coupling between the right fronto-parietal and limbic resting state networks predicts increased self-control and later substance use onset in adolescence.

PubMed

Lee, Tae-Ho; Telzer, Eva H

2016-08-01

Recent developmental brain imaging studies have demonstrated that negatively coupled prefrontal-limbic circuitry implicates the maturation of brain development in adolescents. Using resting-state functional magnetic resonance imaging (rs-fMRI) and independent component analysis (ICA), the present study examined functional network coupling between prefrontal and limbic systems and links to self-control and substance use onset in adolescents. Results suggest that negative network coupling (anti-correlated temporal dynamics) between the right fronto-parietal and limbic resting state networks is associated with greater self-control and later substance use onset in adolescents. These findings increase our understanding of the developmental importance of prefrontal-limbic circuitry for adolescent substance use at the resting-state network level. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Overview of potential procedural and participant-related confounds for neuroimaging of the resting state

PubMed Central

Duncan, Niall W.; Northoff, Georg

2013-01-01

Studies of intrinsic brain activity in the resting state have become increasingly common. A productive discussion of what analysis methods are appropriate, of the importance of physiologic correction and of the potential interpretations of results has been ongoing. However, less attention has been paid to factors other than physiologic noise that may confound resting-state experiments. These range from straightforward factors, such as ensuring that participants are all instructed in the same manner, to more obscure participant-related factors, such as body weight. We provide an overview of such potentially confounding factors, along with some suggested approaches for minimizing their impact. A particular theme that emerges from the overview is the range of systematic differences between types of study groups (e.g., between patients and controls) that may influence resting-state study results. PMID:22964258

Time course based artifact identification for independent components of resting-state FMRI.

PubMed

Rummel, Christian; Verma, Rajeev Kumar; Schöpf, Veronika; Abela, Eugenio; Hauf, Martinus; Berruecos, José Fernando Zapata; Wiest, Roland

2013-01-01

In functional magnetic resonance imaging (fMRI) coherent oscillations of the blood oxygen level-dependent (BOLD) signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting-state networks (RSN). Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA) and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting-state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82, and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting-state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting-state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

Quantifying fluctuations of resting state networks using arterial spin labeling perfusion MRI

PubMed Central

Varma, Gopal; Scheidegger, Rachel; Alsop, David C

2015-01-01

Blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) has been widely used to investigate spontaneous low-frequency signal fluctuations across brain resting state networks. However, BOLD only provides relative measures of signal fluctuations. Arterial Spin Labeling (ASL) MRI holds great potential for quantitative measurements of resting state network fluctuations. This study systematically quantified signal fluctuations of the large-scale resting state networks using ASL data from 20 healthy volunteers by separating them from global signal fluctuations and fluctuations caused by residual noise. Global ASL signal fluctuation was 7.59% ± 1.47% relative to the ASL baseline perfusion. Fluctuations of seven detected resting state networks vary from 2.96% ± 0.93% to 6.71% ± 2.35%. Fluctuations of networks and residual noise were 6.05% ± 1.18% and 6.78% ± 1.16% using 4-mm resolution ASL data applied with Gaussian smoothing kernel of 6mm. However, network fluctuations were reduced by 7.77% ± 1.56% while residual noise fluctuation was markedly reduced by 39.75% ± 2.90% when smoothing kernel of 12 mm was applied to the ASL data. Therefore, global and network fluctuations are the dominant structured noise sources in ASL data. Quantitative measurements of resting state networks may enable improved noise reduction and provide insights into the function of healthy and diseased brain. PMID:26661226

Quantifying fluctuations of resting state networks using arterial spin labeling perfusion MRI.

PubMed

Dai, Weiying; Varma, Gopal; Scheidegger, Rachel; Alsop, David C

2016-03-01

Blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) has been widely used to investigate spontaneous low-frequency signal fluctuations across brain resting state networks. However, BOLD only provides relative measures of signal fluctuations. Arterial Spin Labeling (ASL) MRI holds great potential for quantitative measurements of resting state network fluctuations. This study systematically quantified signal fluctuations of the large-scale resting state networks using ASL data from 20 healthy volunteers by separating them from global signal fluctuations and fluctuations caused by residual noise. Global ASL signal fluctuation was 7.59% ± 1.47% relative to the ASL baseline perfusion. Fluctuations of seven detected resting state networks vary from 2.96% ± 0.93% to 6.71% ± 2.35%. Fluctuations of networks and residual noise were 6.05% ± 1.18% and 6.78% ± 1.16% using 4-mm resolution ASL data applied with Gaussian smoothing kernel of 6mm. However, network fluctuations were reduced by 7.77% ± 1.56% while residual noise fluctuation was markedly reduced by 39.75% ± 2.90% when smoothing kernel of 12 mm was applied to the ASL data. Therefore, global and network fluctuations are the dominant structured noise sources in ASL data. Quantitative measurements of resting state networks may enable improved noise reduction and provide insights into the function of healthy and diseased brain. © The Author(s) 2015.

Measuring vascular reactivity with resting-state blood oxygenation level-dependent (BOLD) signal fluctuations: A potential alternative to the breath-holding challenge?

PubMed

Jahanian, Hesamoddin; Christen, Thomas; Moseley, Michael E; Pajewski, Nicholas M; Wright, Clinton B; Tamura, Manjula K; Zaharchuk, Greg

2017-07-01

Measurement of the ability of blood vessels to dilate and constrict, known as vascular reactivity, is often performed with breath-holding tasks that transiently raise arterial blood carbon dioxide (P a CO 2 ) levels. However, following the proper commands for a breath-holding experiment may be difficult or impossible for many patients. In this study, we evaluated two approaches for obtaining vascular reactivity information using blood oxygenation level-dependent signal fluctuations obtained from resting-state functional magnetic resonance imaging data: physiological fluctuation regression and coefficient of variation of the resting-state functional magnetic resonance imaging signal. We studied a cohort of 28 older adults (69 ± 7 years) and found that six of them (21%) could not perform the breath-holding protocol, based on an objective comparison with an idealized respiratory waveform. In the subjects that could comply, we found a strong linear correlation between data extracted from spontaneous resting-state functional magnetic resonance imaging signal fluctuations and the blood oxygenation level-dependent percentage signal change during breath-holding challenge ( R 2  = 0.57 and 0.61 for resting-state physiological fluctuation regression and resting-state coefficient of variation methods, respectively). This technique may eliminate the need for subject cooperation, thus allowing the evaluation of vascular reactivity in a wider range of clinical and research conditions in which it may otherwise be impractical.

Motor imagery learning modulates functional connectivity of multiple brain systems in resting state.

PubMed

Zhang, Hang; Long, Zhiying; Ge, Ruiyang; Xu, Lele; Jin, Zhen; Yao, Li; Liu, Yijun

2014-01-01

Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning. We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN. These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning.

EEG microstates of wakefulness and NREM sleep.

PubMed

Brodbeck, Verena; Kuhn, Alena; von Wegner, Frederic; Morzelewski, Astrid; Tagliazucchi, Enzo; Borisov, Sergey; Michel, Christoph M; Laufs, Helmut

2012-09-01

EEG-microstates exploit spatio-temporal EEG features to characterize the spontaneous EEG as a sequence of a finite number of quasi-stable scalp potential field maps. So far, EEG-microstates have been studied mainly in wakeful rest and are thought to correspond to functionally relevant brain-states. Four typical microstate maps have been identified and labeled arbitrarily with the letters A, B, C and D. We addressed the question whether EEG-microstate features are altered in different stages of NREM sleep compared to wakefulness. 32-channel EEG of 32 subjects in relaxed wakefulness and NREM sleep was analyzed using a clustering algorithm, identifying the most dominant amplitude topography maps typical of each vigilance state. Fitting back these maps into the sleep-scored EEG resulted in a temporal sequence of maps for each sleep stage. All 32 subjects reached sleep stage N2, 19 also N3, for at least 1 min and 45 s. As in wakeful rest we found four microstate maps to be optimal in all NREM sleep stages. The wake maps were highly similar to those described in the literature for wakefulness. The sleep stage specific map topographies of N1 and N3 sleep showed a variable but overall relatively high degree of spatial correlation to the wake maps (Mean: N1 92%; N3 87%). The N2 maps were the least similar to wake (mean: 83%). Mean duration, total time covered, global explained variance and transition probabilities per subject, map and sleep stage were very similar in wake and N1. In wake, N1 and N3, microstate map C was most dominant w.r.t. global explained variance and temporal presence (ratio total time), whereas in N2 microstate map B was most prominent. In N3, the mean duration of all microstate maps increased significantly, expressed also as an increase in transition probabilities of all maps to themselves in N3. This duration increase was partly--but not entirely--explained by the occurrence of slow waves in the EEG. The persistence of exactly four main microstate classes in all NREM sleep stages might speak in favor of an in principle maintained large scale spatial brain organization from wakeful rest to NREM sleep. In N1 and N3 sleep, despite spectral EEG differences, the microstate maps and characteristics were surprisingly close to wakefulness. This supports the notion that EEG microstates might reflect a large scale resting state network architecture similar to preserved fMRI resting state connectivity. We speculate that the incisive functional alterations which can be observed during the transition to deep sleep might be driven by changes in the level and timing of activity within this architecture. Copyright © 2012 Elsevier Inc. All rights reserved.

Managing the Diabetic Foot Ulcer: How Best Practices Fit the Real 2018 United States.

PubMed

Ilonzo, Nicole; Patel, Munir; Lantis, John C

2018-06-01

Diabetes Mellitus is a serious systemic illness that has an epidemic-like increasing prevalence in the United States, as well as the rest of the world. With the increasing number of people with diabetes comes the higher incidence of diabetes-related complications. One of these known complications, diabetic foot ulcers (DFU), has an estimated lifetime incidence of 15% in diabetics. Having a DFU increases the risk of infection, amputation, and even death, which is why prompt treatment and surveillance of such ulcers is imperative. Multiple organizations and journals have recently published best practices to heal and close DFU. Despite these guidelines, it is estimated that only 50% of all diabetic foot ulcers close within one year in the United States. To further confuse this picture, many trials include postoperative wounds that behave in a very different way than chronic wounds. The management of diabetic ulcers requires an understanding of not only the pathophysiology along with a multi-modal approach involving local wound care, pressure prevention, infection control, and, in some, revascularization, but also how care is delivered in the United States presently. In this review, we hope to elucidate the current knowledge and modalities used in ulcer management and to focus on key areas and best practices to inform the clinician, both in what they should do and what they can do.

MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG

PubMed Central

Dong, Li; Li, Fali; Liu, Qiang; Wen, Xin; Lai, Yongxiu; Xu, Peng; Yao, Dezhong

2017-01-01

Reference electrode standardization technique (REST) has been increasingly acknowledged and applied as a re-reference technique to transform an actual multi-channels recordings to approximately zero reference ones in electroencephalography/event-related potentials (EEG/ERPs) community around the world in recent years. However, a more easy-to-use toolbox for re-referencing scalp EEG data to zero reference is still lacking. Here, we have therefore developed two open-source MATLAB toolboxes for REST of scalp EEG. One version of REST is closely integrated into EEGLAB, which is a popular MATLAB toolbox for processing the EEG data; and another is a batch version to make it more convenient and efficient for experienced users. Both of them are designed to provide an easy-to-use for novice researchers and flexibility for experienced researchers. All versions of the REST toolboxes can be freely downloaded at http://www.neuro.uestc.edu.cn/rest/Down.html, and the detailed information including publications, comments and documents on REST can also be found from this website. An example of usage is given with comparative results of REST and average reference. We hope these user-friendly REST toolboxes could make the relatively novel technique of REST easier to study, especially for applications in various EEG studies. PMID:29163006

MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG.

PubMed

Dong, Li; Li, Fali; Liu, Qiang; Wen, Xin; Lai, Yongxiu; Xu, Peng; Yao, Dezhong

2017-01-01

Reference electrode standardization technique (REST) has been increasingly acknowledged and applied as a re-reference technique to transform an actual multi-channels recordings to approximately zero reference ones in electroencephalography/event-related potentials (EEG/ERPs) community around the world in recent years. However, a more easy-to-use toolbox for re-referencing scalp EEG data to zero reference is still lacking. Here, we have therefore developed two open-source MATLAB toolboxes for REST of scalp EEG. One version of REST is closely integrated into EEGLAB, which is a popular MATLAB toolbox for processing the EEG data; and another is a batch version to make it more convenient and efficient for experienced users. Both of them are designed to provide an easy-to-use for novice researchers and flexibility for experienced researchers. All versions of the REST toolboxes can be freely downloaded at http://www.neuro.uestc.edu.cn/rest/Down.html, and the detailed information including publications, comments and documents on REST can also be found from this website. An example of usage is given with comparative results of REST and average reference. We hope these user-friendly REST toolboxes could make the relatively novel technique of REST easier to study, especially for applications in various EEG studies.

Resting blood pressure differentially predicts time course in a tonic pain experiment.

PubMed

Horing, Bjoern; McCubbin, James A; Moore, Dewayne; Muth, Eric R

2016-10-01

Resting blood pressure (BP) shows a negative relationship with pain sensitivity (BP-related hypoalgesia). In chronic pain conditions, this relationship is inverted. The precise mechanisms responsible for the inversion are unknown. Using a tonic pain protocol, we report findings closely resembling this inversion in healthy participants. Resting BP and state measures of anxiety and mood were assessed from 33 participants (21 female). Participants then immersed their dominant hand in painfully hot water (47 °C) for five trials of 1-min duration, with 30-s intertrial intervals. Throughout the trials, participants continually registered their pain. After a 35-min intermission, the trial sequence was repeated. A disassociation of the negative relationship of resting systolic BP (as per Trial 1) was found using hierarchical linear modeling (p < .001, R(2)  = .07). The disassociation unfolds over each consecutive trial, with an increasingly positive relationship. In Sequence 2, the initially negative relationship is almost completely absent. Furthermore, the association of BP and pain was found to be moderated by anxiety, such that only persons with low anxiety exhibited BP hypoalgesia. Our findings expand the existing literature by incorporating anxiety as a moderator of BP hypoalgesia. Furthermore, the protocol emulates the changing relationship between BP and pain observed in chronic pain patients. The protocol has potential as a model for chronic pain; however, future research should determine if similar physiological systems are involved. The finding holds potential diagnostic or prognostic relevance for certain clinical pain conditions, especially those involving dysfunction of the descending modulation of pain. © 2016 Society for Psychophysiological Research.

Wide-area mapping of resting state hemodynamic correlations at microvascular resolution with multi-contrast optical imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Senarathna, Janaka; Hadjiabadi, Darian; Gil, Stacy; Thakor, Nitish V.; Pathak, Arvind P.

2017-02-01

Different brain regions exhibit complex information processing even at rest. Therefore, assessing temporal correlations between regions permits task-free visualization of their `resting state connectivity'. Although functional MRI (fMRI) is widely used for mapping resting state connectivity in the human brain, it is not well suited for `microvascular scale' imaging in rodents because of its limited spatial resolution. Moreover, co-registered cerebral blood flow (CBF) and total hemoglobin (HbT) data are often unavailable in conventional fMRI experiments. Therefore, we built a customized system that combines laser speckle contrast imaging (LSCI), intrinsic optical signal (IOS) imaging and fluorescence imaging (FI) to generate multi-contrast functional connectivity maps at a spatial resolution of 10 μm. This system comprised of three illumination sources: a 632 nm HeNe laser (for LSCI), a 570 nm ± 5 nm filtered white light source (for IOS), and a 473 nm blue laser (for FI), as well as a sensitive CCD camera operating at 10 frames per second for image acquisition. The acquired data enabled visualization of changes in resting state neurophysiology at microvascular spatial scales. Moreover, concurrent mapping of CBF and HbT-based temporal correlations enabled in vivo mapping of how resting brain regions were linked in terms of their hemodynamics. Additionally, we complemented this approach by exploiting the transit times of a fluorescent tracer (Dextran-FITC) to distinguish arterial from venous perfusion. Overall, we demonstrated the feasibility of wide area mapping of resting state connectivity at microvascular resolution and created a new toolbox for interrogating neurovascular function.

Reliability of Three Dimentional Pseudo-continuous Arterial Spin Labeling: A Volumetric Cerebral Perfusion Imaging with Different Post-labeling Time and Functional State in Health Adults.

PubMed

Liu, Meng-Qi; Chen, Zhi-Ye; Ma, Lin

2018-03-30

Objective To evaluate the reliability of three dimensional spiral fast spin echo pseudo-continuous arterial spin labeling (3D pc-ASL) in measuring cerebral blood flow (CBF) with different post-labeling delay time (PLD) in the resting state and the right finger taping state. Methods 3D pc-ASL and three dimensional T1-weighted fast spoiled gradient recalled echo (3D T1-FSPGR) sequence were applied to eight healthy subjects twice at the same time each day for one week interval. ASL data acquisition was performed with post-labeling delay time (PLD) 1.5 seconds and 2.0 seconds in the resting state and the right finger taping state respectively. CBF mapping was calculated and CBF value of both the gray matter (GM) and white matter (WM) was automatically extracted. The reliability was evaluated using the intraclass correlation coefficient (ICC) and Bland and Altman plot. Results ICC of the GM (0.84) and WM (0.92) was lower at PLD 1.5 seconds than that (GM, 0.88; WM, 0.94) at PLD 2.0 seconds in the resting state, and ICC of GM (0.88) was higher in the right finger taping state than that in the resting state at PLD 1.5 seconds. ICC of the GM and WM was 0.71 and 0.78 for PLD 1.5 seconds and PLD 2.0 seconds in the resting state at the first scan, and ICC of the GM and WM was 0.83 and 0.79 at the second scan, respectively. Conclusion This work demonstrated that 3D pc-ASL might be a reliable imaging technique to measure CBF over the whole brain at different PLD in the resting state or controlled state.

Resting-state fMRI and social cognition: An opportunity to connect.

PubMed

Doruyter, Alex; Groenewold, Nynke A; Dupont, Patrick; Stein, Dan J; Warwick, James M

2017-09-01

Many psychiatric disorders are characterized by altered social cognition. The importance of social cognition has previously been recognized by the National Institute of Mental Health Research Domain Criteria project, in which it features as a core domain. Social task-based functional magnetic resonance imaging (fMRI) currently offers the most direct insight into how the brain processes social information; however, resting-state fMRI may be just as important in understanding the biology and network nature of social processing. Resting-state fMRI allows researchers to investigate the functional relationships between brain regions in a neutral state: so-called resting functional connectivity (RFC). There is evidence that RFC is predictive of how the brain processes information during social tasks. This is important because it shifts the focus from possibly context-dependent aberrations to context-independent aberrations in functional network architecture. Rather than being analysed in isolation, the study of resting-state brain networks shows promise in linking results of task-based fMRI results, structural connectivity, molecular imaging findings, and performance measures of social cognition-which may prove crucial in furthering our understanding of the social brain. Copyright © 2017 John Wiley & Sons, Ltd.

Relationships between the resting-state network and the P3: Evidence from a scalp EEG study

NASA Astrophysics Data System (ADS)

Li, Fali; Liu, Tiejun; Wang, Fei; Li, He; Gong, Diankun; Zhang, Rui; Jiang, Yi; Tian, Yin; Guo, Daqing; Yao, Dezhong; Xu, Peng

2015-10-01

The P3 is an important event-related potential that can be used to identify neural activity related to the cognitive processes of the human brain. However, the relationships, especially the functional correlations, between resting-state brain activity and the P3 have not been well established. In this study, we investigated the relationships between P3 properties (i.e., amplitude and latency) and resting-state brain networks. The results indicated that P3 amplitude was significantly correlated with resting-state network topology, and in general, larger P3 amplitudes could be evoked when the resting-state brain network was more efficient. However, no significant relationships were found for the corresponding P3 latency. Additionally, the long-range connections between the prefrontal/frontal and parietal/occipital brain regions, which represent the synchronous activity of these areas, were functionally related to the P3 parameters, especially P3 amplitude. The findings of the current study may help us better understand inter-subject variation in the P3, which may be instructive for clinical diagnosis, cognitive neuroscience studies, and potential subject selection for brain-computer interface applications.

Neuroimaging markers of glutamatergic and GABAergic systems in drug addiction: Relationships to resting-state functional connectivity.

PubMed

Moeller, Scott J; London, Edythe D; Northoff, Georg

2016-02-01

Drug addiction is characterized by widespread abnormalities in brain function and neurochemistry, including drug-associated effects on concentrations of the excitatory and inhibitory neurotransmitters glutamate and gamma-aminobutyric acid (GABA), respectively. In healthy individuals, these neurotransmitters drive the resting state, a default condition of brain function also disrupted in addiction. Here, our primary goal was to review in vivo magnetic resonance spectroscopy and positron emission tomography studies that examined markers of glutamate and GABA abnormalities in human drug addiction. Addicted individuals tended to show decreases in these markers compared with healthy controls, but findings also varied by individual characteristics (e.g., abstinence length). Interestingly, select corticolimbic brain regions showing glutamatergic and/or GABAergic abnormalities have been similarly implicated in resting-state functional connectivity deficits in drug addiction. Thus, our secondary goals were to provide a brief review of this resting-state literature, and an initial rationale for the hypothesis that abnormalities in glutamatergic and/or GABAergic neurotransmission may underlie resting-state functional deficits in drug addiction. In doing so, we suggest future research directions and possible treatment implications. Copyright © 2015 Elsevier Ltd. All rights reserved.

Reliability of resting-state microstate features in electroencephalography.

PubMed

Khanna, Arjun; Pascual-Leone, Alvaro; Farzan, Faranak

2014-01-01

Electroencephalographic (EEG) microstate analysis is a method of identifying quasi-stable functional brain states ("microstates") that are altered in a number of neuropsychiatric disorders, suggesting their potential use as biomarkers of neurophysiological health and disease. However, use of EEG microstates as neurophysiological biomarkers requires assessment of the test-retest reliability of microstate analysis. We analyzed resting-state, eyes-closed, 30-channel EEG from 10 healthy subjects over 3 sessions spaced approximately 48 hours apart. We identified four microstate classes and calculated the average duration, frequency, and coverage fraction of these microstates. Using Cronbach's α and the standard error of measurement (SEM) as indicators of reliability, we examined: (1) the test-retest reliability of microstate features using a variety of different approaches; (2) the consistency between TAAHC and k-means clustering algorithms; and (3) whether microstate analysis can be reliably conducted with 19 and 8 electrodes. The approach of identifying a single set of "global" microstate maps showed the highest reliability (mean Cronbach's α > 0.8, SEM ≈ 10% of mean values) compared to microstates derived by each session or each recording. There was notably low reliability in features calculated from maps extracted individually for each recording, suggesting that the analysis is most reliable when maps are held constant. Features were highly consistent across clustering methods (Cronbach's α > 0.9). All features had high test-retest reliability with 19 and 8 electrodes. High test-retest reliability and cross-method consistency of microstate features suggests their potential as biomarkers for assessment of the brain's neurophysiological health.

Sparse SPM: Group Sparse-dictionary learning in SPM framework for resting-state functional connectivity MRI analysis.

PubMed

Lee, Young-Beom; Lee, Jeonghyeon; Tak, Sungho; Lee, Kangjoo; Na, Duk L; Seo, Sang Won; Jeong, Yong; Ye, Jong Chul

2016-01-15

Recent studies of functional connectivity MR imaging have revealed that the default-mode network activity is disrupted in diseases such as Alzheimer's disease (AD). However, there is not yet a consensus on the preferred method for resting-state analysis. Because the brain is reported to have complex interconnected networks according to graph theoretical analysis, the independency assumption, as in the popular independent component analysis (ICA) approach, often does not hold. Here, rather than using the independency assumption, we present a new statistical parameter mapping (SPM)-type analysis method based on a sparse graph model where temporal dynamics at each voxel position are described as a sparse combination of global brain dynamics. In particular, a new concept of a spatially adaptive design matrix has been proposed to represent local connectivity that shares the same temporal dynamics. If we further assume that local network structures within a group are similar, the estimation problem of global and local dynamics can be solved using sparse dictionary learning for the concatenated temporal data across subjects. Moreover, under the homoscedasticity variance assumption across subjects and groups that is often used in SPM analysis, the aforementioned individual and group analyses using sparse dictionary learning can be accurately modeled by a mixed-effect model, which also facilitates a standard SPM-type group-level inference using summary statistics. Using an extensive resting fMRI data set obtained from normal, mild cognitive impairment (MCI), and Alzheimer's disease patient groups, we demonstrated that the changes in the default mode network extracted by the proposed method are more closely correlated with the progression of Alzheimer's disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Preserved dichotomy but highly irregular and burst discharge in the basal ganglia in alert dystonic rats at rest.

PubMed

Kumbhare, Deepak; Chaniary, Kunal D; Baron, Mark S

2015-10-22

Despite its prevalence, the underlying pathophysiology of dystonia remains poorly understood. Using our novel tri-component classification algorithm, extracellular neuronal activity in the globus pallidus (GP), STN, and the entopeduncular nucleus (EP) was characterized in 34 normal and 25 jaundiced dystonic Gunn rats with their heads restrained while at rest. In normal rats, neurons in each nucleus were similarly characterized by two physiologically distinct types: regular tonic with moderate discharge frequencies (mean rates in GP, STN and EP ranging from 35-41 spikes/s) or irregular at slower frequencies (17-20 spikes/s), with a paucity of burst activity. In dystonic rats, these nuclei were also characterized by two distinct principal neuronal patterns. However, in marked difference, in the dystonic rats, neurons were primarily slow and highly irregular (12-15 spikes/s) or burst predominant (14-17 spikes/s), with maintained modest differences between nuclei. In GP and EP, with increasing severity of dystonia, burstiness was moderately further increased, irregularity mildly further increased, and discharge rates mildly further reduced. In contrast, these features did not appreciably change in STN with worsening dystonia. Findings of a lack of bursting in GP, STN and EP in normal rats in an alert resting state and prominent bursting in dystonic Gunn rats suggest that cortical or other external drive is normally required for bursting in these nuclei and that spontaneous bursting, as seen in dystonia and Parkinson's disease, is reflective of an underlying pathophysiological state. Moreover, the extent of burstiness appears to most closely correlate with the severity of the dystonia. Published by Elsevier B.V.

Electroencephalographic markers of robot-aided therapy in stroke patients for the evaluation of upper limb rehabilitation.

PubMed

Sale, Patrizio; Infarinato, Francesco; Del Percio, Claudio; Lizio, Roberta; Babiloni, Claudio; Foti, Calogero; Franceschini, Marco

2015-12-01

Stroke is the leading cause of permanent disability in developed countries; its effects may include sensory, motor, and cognitive impairment as well as a reduced ability to perform self-care and participate in social and community activities. A number of studies have shown that the use of robotic systems in upper limb motor rehabilitation programs provides safe and intensive treatment to patients with motor impairments because of a neurological injury. Furthermore, robot-aided therapy was shown to be well accepted and tolerated by all patients; however, it is not known whether a specific robot-aided rehabilitation can induce beneficial cortical plasticity in stroke patients. Here, we present a procedure to study neural underpinning of robot-aided upper limb rehabilitation in stroke patients. Neurophysiological recordings use the following: (a) 10-20 system electroencephalographic (EEG) electrode montage; (b) bipolar vertical and horizontal electrooculographies; and (c) bipolar electromyography from the operating upper limb. Behavior monitoring includes the following: (a) clinical data and (b) kinematic and dynamic of the operant upper limb movements. Experimental conditions include the following: (a) resting state eyes closed and eyes open, and (b) robotic rehabilitation task (maximum 80 s each block to reach 4-min EEG data; interblock pause of 1 min). The data collection is performed before and after a program of 30 daily rehabilitation sessions. EEG markers include the following: (a) EEG power density in the eyes-closed condition; (b) reactivity of EEG power density to eyes opening; and (c) reactivity of EEG power density to robotic rehabilitation task. The above procedure was tested on a subacute patient (29 poststroke days) and on a chronic patient (21 poststroke months). After the rehabilitation program, we observed (a) improved clinical condition; (b) improved performance during the robotic task; (c) reduced delta rhythms (1-4 Hz) and increased alpha rhythms (8-12 Hz) during the resting state eyes-closed condition; (d) increased alpha desynchronization to eyes opening; and (e) decreased alpha desynchronization during the robotic rehabilitation task. We conclude that the present procedure is suitable for evaluation of the neural underpinning of robot-aided upper limb rehabilitation.

Changes in resting-state functionally connected parietofrontal networks after videogame practice.

PubMed

Martínez, Kenia; Solana, Ana Beatriz; Burgaleta, Miguel; Hernández-Tamames, Juan Antonio; Alvarez-Linera, Juan; Román, Francisco J; Alfayate, Eva; Privado, Jesús; Escorial, Sergio; Quiroga, María A; Karama, Sherif; Bellec, Pierre; Colom, Roberto

2013-12-01

Neuroimaging studies provide evidence for organized intrinsic activity under task-free conditions. This activity serves functionally relevant brain systems supporting cognition. Here, we analyze changes in resting-state functional connectivity after videogame practice applying a test-retest design. Twenty young females were selected from a group of 100 participants tested on four standardized cognitive ability tests. The practice and control groups were carefully matched on their ability scores. The practice group played during two sessions per week across 4 weeks (16 h total) under strict supervision in the laboratory, showing systematic performance improvements in the game. A group independent component analysis (GICA) applying multisession temporal concatenation on test-retest resting-state fMRI, jointly with a dual-regression approach, was computed. Supporting the main hypothesis, the key finding reveals an increased correlated activity during rest in certain predefined resting state networks (albeit using uncorrected statistics) attributable to practice with the cognitively demanding tasks of the videogame. Observed changes were mainly concentrated on parietofrontal networks involved in heterogeneous cognitive functions. Copyright © 2012 Wiley Periodicals, Inc.

Synchronized delta oscillations correlate with the resting-state functional MRI signal

PubMed Central

Lu, Hanbing; Zuo, Yantao; Gu, Hong; Waltz, James A.; Zhan, Wang; Scholl, Clara A.; Rea, William; Yang, Yihong; Stein, Elliot A.

2007-01-01

Synchronized low-frequency spontaneous fluctuations of the functional MRI (fMRI) signal have recently been applied to investigate large-scale neuronal networks of the brain in the absence of specific task instructions. However, the underlying neural mechanisms of these fluctuations remain largely unknown. To this end, electrophysiological recordings and resting-state fMRI measurements were conducted in α-chloralose-anesthetized rats. Using a seed-voxel analysis strategy, region-specific, anesthetic dose-dependent fMRI resting-state functional connectivity was detected in bilateral primary somatosensory cortex (S1FL) of the resting brain. Cortical electroencephalographic signals were also recorded from bilateral S1FL; a visual cortex locus served as a control site. Results demonstrate that, unlike the evoked fMRI response that correlates with power changes in the γ bands, the resting-state fMRI signal correlates with the power coherence in low-frequency bands, particularly the δ band. These data indicate that hemodynamic fMRI signal differentially registers specific electrical oscillatory frequency band activity, suggesting that fMRI may be able to distinguish the ongoing from the evoked activity of the brain. PMID:17991778

Sustainable Rest Area Design and Operations

DOT National Transportation Integrated Search

2017-10-01

One way in which State Departments of Transportation (DOTs) can modernize their rest areas while reducing operations and maintenance costs is by incorporating sustainable practices into rest area design and operations. Sustainability practices that D...

Correspondence of the brain's functional architecture during activation and rest

PubMed Central

Smith, Stephen M.; Fox, Peter T.; Miller, Karla L.; Glahn, David C.; Fox, P. Mickle; Mackay, Clare E.; Filippini, Nicola; Watkins, Kate E.; Toro, Roberto; Laird, Angela R.; Beckmann, Christian F.

2009-01-01

Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are continuously interacting when the brain is “at rest.” In this work, we identify the major explicit activation networks by carrying out an image-based activation network analysis of thousands of separate activation maps derived from the BrainMap database of functional imaging studies, involving nearly 30,000 human subjects. Independently, we extract the major covarying networks in the resting brain, as imaged with functional magnetic resonance imaging in 36 subjects at rest. The sets of major brain networks, and their decompositions into subnetworks, show close correspondence between the independent analyses of resting and activation brain dynamics. We conclude that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically “active” even when at “rest.” PMID:19620724

Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index.

PubMed

Smitha, K A; Arun, K M; Rajesh, P G; Thomas, B; Kesavadas, C

2017-06-01

Language is a cardinal function that makes human unique. Preservation of language function poses a great challenge for surgeons during resection. The aim of the study was to assess the efficacy of resting-state fMRI in the lateralization of language function in healthy subjects to permit its further testing in patients who are unable to perform task-based fMRI. Eighteen healthy right-handed volunteers were prospectively evaluated with resting-state fMRI and task-based fMRI to assess language networks. The laterality indices of Broca and Wernicke areas were calculated by using task-based fMRI via a voxel-value approach. We adopted seed-based resting-state fMRI connectivity analysis together with parameters such as amplitude of low-frequency fluctuation and fractional amplitude of low-frequency fluctuation (fALFF). Resting-state fMRI connectivity maps for language networks were obtained from Broca and Wernicke areas in both hemispheres. We performed correlation analysis between the laterality index and the z scores of functional connectivity, amplitude of low-frequency fluctuation, and fALFF. Pearson correlation analysis between signals obtained from the z score of fALFF and the laterality index yielded a correlation coefficient of 0.849 ( P < .05). Regression analysis of the fALFF with the laterality index yielded an R 2 value of 0.721, indicating that 72.1% of the variance in the laterality index of task-based fMRI could be predicted from the fALFF of resting-state fMRI. The present study demonstrates that fALFF can be used as an alternative to task-based fMRI for assessing language laterality. There was a strong positive correlation between the fALFF of the Broca area of resting-state fMRI with the laterality index of task-based fMRI. Furthermore, we demonstrated the efficacy of fALFF for predicting the laterality of task-based fMRI. © 2017 by American Journal of Neuroradiology.

Does preoperative measurement of cerebral blood flow with acetazolamide challenge in addition to preoperative measurement of cerebral blood flow at the resting state increase the predictive accuracy of development of cerebral hyperperfusion after carotid endarterectomy? Results from 500 cases with brain perfusion single-photon emission computed tomography study.

PubMed

Oshida, Sotaro; Ogasawara, Kuniaki; Saura, Hiroaki; Yoshida, Koji; Fujiwara, Shunro; Kojima, Daigo; Kobayashi, Masakazu; Yoshida, Kenji; Kubo, Yoshitaka; Ogawa, Akira

2015-01-01

The purpose of the present study was to determine whether preoperative measurement of cerebral blood flow (CBF) with acetazolamide in addition to preoperative measurement of CBF at the resting state increases the predictive accuracy of development of cerebral hyperperfusion after carotid endarterectomy (CEA). CBF at the resting state and cerebrovascular reactivity (CVR) to acetazolamide were quantitatively assessed using N-isopropyl-p-[(123)I]-iodoamphetamine (IMP)-autoradiography method with single-photon emission computed tomography (SPECT) before CEA in 500 patients with ipsilateral internal carotid artery stenosis (≥ 70%). CBF measurement using (123)I-IMP SPECT was also performed immediately and 3 days after CEA. A region of interest (ROI) was automatically placed in the middle cerebral artery territory in the affected cerebral hemisphere using a three-dimensional stereotactic ROI template. Preoperative decreases in CBF at the resting state [95% confidence intervals (CIs), 0.855 to 0.967; P = 0.0023] and preoperative decreases in CVR to acetazolamide (95% CIs, 0.844 to 0.912; P < 0.0001) were significant independent predictors of post-CEA hyperperfusion. The area under the receiver operating characteristic curve for prediction of the development of post-CEA hyperperfusion was significantly greater for CVR to acetazolamide than for CBF at the resting state (difference between areas, 0.173; P < 0.0001). Sensitivity, specificity, and positive- and negative-predictive values for the prediction of the development of post-CEA hyperperfusion were significantly greater for CVR to acetazolamide than for CBF at the resting state (P < 0.05, respectively). The present study demonstrated that preoperative measurement of CBF with acetazolamide in addition to preoperative measurement of CBF at the resting state increases the predictive accuracy of the development of post-CEA hyperperfusion.

Resting-state slow wave power, healthy aging and cognitive performance.

PubMed

Vlahou, Eleni L; Thurm, Franka; Kolassa, Iris-Tatjana; Schlee, Winfried

2014-05-29

Cognitive functions and spontaneous neural activity show significant changes over the life-span, but the interrelations between age, cognition and resting-state brain oscillations are not well understood. Here, we assessed performance on the Trail Making Test and resting-state magnetoencephalographic (MEG) recordings from 53 healthy adults (18-89 years old) to investigate associations between age-dependent changes in spontaneous oscillatory activity and cognitive performance. Results show that healthy aging is accompanied by a marked and linear decrease of resting-state activity in the slow frequency range (0.5-6.5 Hz). The effects of slow wave power on cognitive performance were expressed as interactions with age: For older (>54 years), but not younger participants, enhanced delta and theta power in temporal and central regions was positively associated with perceptual speed and executive functioning. Consistent with previous work, these findings substantiate further the important role of slow wave oscillations in neurocognitive function during healthy aging.

Soft drink effects on sensorimotor rhythm brain computer interface performance and resting-state spectral power.

PubMed

Mundahl, John; Jianjun Meng; He, Jeffrey; Bin He

2016-08-01

Brain-computer interface (BCI) systems allow users to directly control computers and other machines by modulating their brain waves. In the present study, we investigated the effect of soft drinks on resting state (RS) EEG signals and BCI control. Eight healthy human volunteers each participated in three sessions of BCI cursor tasks and resting state EEG. During each session, the subjects drank an unlabeled soft drink with either sugar, caffeine, or neither ingredient. A comparison of resting state spectral power shows a substantial decrease in alpha and beta power after caffeine consumption relative to control. Despite attenuation of the frequency range used for the control signal, caffeine average BCI performance was the same as control. Our work provides a useful characterization of caffeine, the world's most popular stimulant, on brain signal frequencies and their effect on BCI performance.

Resting-State Functional Connectivity in Autism Spectrum Disorders: A Review

PubMed Central

Hull, Jocelyn V.; Jacokes, Zachary J.; Torgerson, Carinna M.; Irimia, Andrei; Van Horn, John Darrell

2017-01-01

Ongoing debate exists within the resting-state functional MRI (fMRI) literature over how intrinsic connectivity is altered in the autistic brain, with reports of general over-connectivity, under-connectivity, and/or a combination of both. Classifying autism using brain connectivity is complicated by the heterogeneous nature of the condition, allowing for the possibility of widely variable connectivity patterns among individuals with the disorder. Further differences in reported results may be attributable to the age and sex of participants included, designs of the resting-state scan, and to the analysis technique used to evaluate the data. This review systematically examines the resting-state fMRI autism literature to date and compares studies in an attempt to draw overall conclusions that are presently challenging. We also propose future direction for rs-fMRI use to categorize individuals with autism spectrum disorder, serve as a possible diagnostic tool, and best utilize data-sharing initiatives. PMID:28101064

Modulation of Brain Resting-State Networks by Sad Mood Induction

PubMed Central

Harrison, Ben J.; Pujol, Jesus; Ortiz, Hector; Fornito, Alex; Pantelis, Christos; Yücel, Murat

2008-01-01

Background There is growing interest in the nature of slow variations of the blood oxygen level-dependent (BOLD) signal observed in functional MRI resting-state studies. In humans, these slow BOLD variations are thought to reflect an underlying or intrinsic form of brain functional connectivity in discrete neuroanatomical systems. While these ‘resting-state networks’ may be relatively enduring phenomena, other evidence suggest that dynamic changes in their functional connectivity may also emerge depending on the brain state of subjects during scanning. Methodology/Principal Findings In this study, we examined healthy subjects (n = 24) with a mood induction paradigm during two continuous fMRI recordings to assess the effects of a change in self-generated mood state (neutral to sad) on the functional connectivity of these resting-state networks (n = 24). Using independent component analysis, we identified five networks that were common to both experimental states, each showing dominant signal fluctuations in the very low frequency domain (∼0.04 Hz). Between the two states, we observed apparent increases and decreases in the overall functional connectivity of these networks. Primary findings included increased connectivity strength of a paralimbic network involving the dorsal anterior cingulate and anterior insula cortices with subjects' increasing sadness and decreased functional connectivity of the ‘default mode network’. Conclusions/Significance These findings support recent studies that suggest the functional connectivity of certain resting-state networks may, in part, reflect a dynamic image of the current brain state. In our study, this was linked to changes in subjective mood. PMID:18350136

Resting-state EEG, impulsiveness, and personality in daily and nondaily smokers.

PubMed

Rass, Olga; Ahn, Woo-Young; O'Donnell, Brian F

2016-01-01

Resting EEG is sensitive to transient, acute effects of nicotine administration and abstinence, but the chronic effects of smoking on EEG are poorly characterized. This study measures the resting EEG profile of chronic smokers in a non-deprived, non-peak state to test whether differences in smoking behavior and personality traits affect pharmaco-EEG response. Resting EEG, impulsiveness, and personality measures were collected from daily smokers (n=22), nondaily smokers (n=31), and non-smokers (n=30). Daily smokers had reduced resting delta and alpha EEG power and higher impulsiveness (Barratt Impulsiveness Scale) compared to nondaily smokers and non-smokers. Both daily and nondaily smokers discounted delayed rewards more steeply, reported lower conscientiousness (NEO-FFI), and reported greater disinhibition and experience seeking (Sensation Seeking Scale) than non-smokers. Nondaily smokers reported greater sensory hedonia than nonsmokers. Altered resting EEG power in daily smokers demonstrates differences in neural signaling that correlated with greater smoking behavior and dependence. Although nondaily smokers share some characteristics with daily smokers that may predict smoking initiation and maintenance, they differ on measures of impulsiveness and resting EEG power. Resting EEG in non-deprived chronic smokers provides a standard for comparison to peak and trough nicotine states and may serve as a biomarker for nicotine dependence, relapse risk, and recovery. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Block of Inactivation-deficient Na+ Channels by Local Anesthetics in Stably Transfected Mammalian Cells

PubMed Central

Wang, Sho-Ya; Mitchell, Jane; Moczydlowski, Edward; Wang, Ging Kuo

2004-01-01

According to the classic modulated receptor hypothesis, local anesthetics (LAs) such as benzocaine and lidocaine bind preferentially to fast-inactivated Na+ channels with higher affinities. However, an alternative view suggests that activation of Na+ channels plays a crucial role in promoting high-affinity LA binding and that fast inactivation per se is not a prerequisite for LA preferential binding. We investigated the role of activation in LA action in inactivation-deficient rat muscle Na+ channels (rNav1.4-L435W/L437C/A438W) expressed in stably transfected Hek293 cells. The 50% inhibitory concentrations (IC50) for the open-channel block at +30 mV by lidocaine and benzocaine were 20.9 ± 3.3 μM (n = 5) and 81.7 ± 10.6 μM (n = 5), respectively; both were comparable to inactivated-channel affinities. In comparison, IC50 values for resting-channel block at −140 mV were >12-fold higher than those for open-channel block. With 300 μM benzocaine, rapid time-dependent block (τ ≈ 0.8 ms) of inactivation-deficient Na+ currents occurred at +30 mV, but such a rapid time-dependent block was not evident at −30 mV. The peak current at −30 mV, however, was reduced more severely than that at +30 mV. This phenomenon suggested that the LA block of intermediate closed states took place notably when channel activation was slow. Such closed-channel block also readily accounted for the LA-induced hyperpolarizing shift in the conventional steady-state inactivation measurement. Our data together illustrate that the Na+ channel activation pathway, including most, if not all, transient intermediate closed states and the final open state, promotes high-affinity LA binding. PMID:15545401

Bupropion Administration Increases Resting-State Functional Connectivity in Dorso-Medial Prefrontal Cortex.

PubMed

Rzepa, Ewelina; Dean, Zola; McCabe, Ciara

2017-06-01

Patients on the selective serotonergic reuptake inhibitors like citalopram report emotional blunting. We showed previously that citalopram reduces resting-state functional connectivity in healthy volunteers in a number of brain regions, including the dorso-medial prefrontal cortex, which may be related to its clinical effects. Bupropion is a dopaminergic and noradrenergic reuptake inhibitor and is not reported to cause emotional blunting. However, how bupropion affects resting-state functional connectivity in healthy controls remains unknown. Using a within-subjects, repeated-measures, double-blind, crossover design, we examined 17 healthy volunteers (9 female, 8 male). Volunteers received 7 days of bupropion (150 mg/d) and 7 days of placebo treatment and underwent resting-state functional Magnetic Resonance Imaging. We selected seed regions in the salience network (amygdala and pregenual anterior cingulate cortex) and the central executive network (dorsal medial prefrontal cortex). Mood and anhedonia measures were also recorded and examined in relation to resting-state functional connectivity. Relative to placebo, bupropion increased resting-state functional connectivity in healthy volunteers between the dorsal medial prefrontal cortex seed region and the posterior cingulate cortex and the precuneus cortex, key parts of the default mode network. These results are opposite to that which we found with 7 days treatment of citalopram in healthy volunteers. These results reflect a different mechanism of action of bupropion compared with selective serotonergic reuptake inhibitors. These results help explain the apparent lack of emotional blunting caused by bupropion in depressed patients. © The Author 2017. Published by Oxford University Press on behalf of CINP.

Motor Imagery Learning Modulates Functional Connectivity of Multiple Brain Systems in Resting State

PubMed Central

Zhang, Hang; Long, Zhiying; Ge, Ruiyang; Xu, Lele; Jin, Zhen; Yao, Li; Liu, Yijun

2014-01-01

Background Learning motor skills involves subsequent modulation of resting-state functional connectivity in the sensory-motor system. This idea was mostly derived from the investigations on motor execution learning which mainly recruits the processing of sensory-motor information. Behavioral evidences demonstrated that motor skills in our daily lives could be learned through imagery procedures. However, it remains unclear whether the modulation of resting-state functional connectivity also exists in the sensory-motor system after motor imagery learning. Methodology/Principal Findings We performed a fMRI investigation on motor imagery learning from resting state. Based on previous studies, we identified eight sensory and cognitive resting-state networks (RSNs) corresponding to the brain systems and further explored the functional connectivity of these RSNs through the assessments, connectivity and network strengths before and after the two-week consecutive learning. Two intriguing results were revealed: (1) The sensory RSNs, specifically sensory-motor and lateral visual networks exhibited greater connectivity strengths in precuneus and fusiform gyrus after learning; (2) Decreased network strength induced by learning was proved in the default mode network, a cognitive RSN. Conclusions/Significance These results indicated that resting-state functional connectivity could be modulated by motor imagery learning in multiple brain systems, and such modulation displayed in the sensory-motor, visual and default brain systems may be associated with the establishment of motor schema and the regulation of introspective thought. These findings further revealed the neural substrates underlying motor skill learning and potentially provided new insights into the therapeutic benefits of motor imagery learning. PMID:24465577

Errors on interrupter tasks presented during spatial and verbal working memory performance are linearly linked to large-scale functional network connectivity in high temporal resolution resting state fMRI.

PubMed

Magnuson, Matthew Evan; Thompson, Garth John; Schwarb, Hillary; Pan, Wen-Ju; McKinley, Andy; Schumacher, Eric H; Keilholz, Shella Dawn

2015-12-01

The brain is organized into networks composed of spatially separated anatomical regions exhibiting coherent functional activity over time. Two of these networks (the default mode network, DMN, and the task positive network, TPN) have been implicated in the performance of a number of cognitive tasks. To directly examine the stable relationship between network connectivity and behavioral performance, high temporal resolution functional magnetic resonance imaging (fMRI) data were collected during the resting state, and behavioral data were collected from 15 subjects on different days, exploring verbal working memory, spatial working memory, and fluid intelligence. Sustained attention performance was also evaluated in a task interleaved between resting state scans. Functional connectivity within and between the DMN and TPN was related to performance on these tasks. Decreased TPN resting state connectivity was found to significantly correlate with fewer errors on an interrupter task presented during a spatial working memory paradigm and decreased DMN/TPN anti-correlation was significantly correlated with fewer errors on an interrupter task presented during a verbal working memory paradigm. A trend for increased DMN resting state connectivity to correlate to measures of fluid intelligence was also observed. These results provide additional evidence of the relationship between resting state networks and behavioral performance, and show that such results can be observed with high temporal resolution fMRI. Because cognitive scores and functional connectivity were collected on nonconsecutive days, these results highlight the stability of functional connectivity/cognitive performance coupling.

Reconfiguration of Brain Network Architectures between Resting-State and Complexity-Dependent Cognitive Reasoning.

PubMed

Hearne, Luke J; Cocchi, Luca; Zalesky, Andrew; Mattingley, Jason B

2017-08-30

Our capacity for higher cognitive reasoning has a measurable limit. This limit is thought to arise from the brain's capacity to flexibly reconfigure interactions between spatially distributed networks. Recent work, however, has suggested that reconfigurations of task-related networks are modest when compared with intrinsic "resting-state" network architecture. Here we combined resting-state and task-driven functional magnetic resonance imaging to examine how flexible, task-specific reconfigurations associated with increasing reasoning demands are integrated within a stable intrinsic brain topology. Human participants (21 males and 28 females) underwent an initial resting-state scan, followed by a cognitive reasoning task involving different levels of complexity, followed by a second resting-state scan. The reasoning task required participants to deduce the identity of a missing element in a 4 × 4 matrix, and item difficulty was scaled parametrically as determined by relational complexity theory. Analyses revealed that external task engagement was characterized by a significant change in functional brain modules. Specifically, resting-state and null-task demand conditions were associated with more segregated brain-network topology, whereas increases in reasoning complexity resulted in merging of resting-state modules. Further increments in task complexity did not change the established modular architecture, but affected selective patterns of connectivity between frontoparietal, subcortical, cingulo-opercular, and default-mode networks. Larger increases in network efficiency within the newly established task modules were associated with higher reasoning accuracy. Our results shed light on the network architectures that underlie external task engagement, and highlight selective changes in brain connectivity supporting increases in task complexity. SIGNIFICANCE STATEMENT Humans have clear limits in their ability to solve complex reasoning problems. It is thought that such limitations arise from flexible, moment-to-moment reconfigurations of functional brain networks. It is less clear how such task-driven adaptive changes in connectivity relate to stable, intrinsic networks of the brain and behavioral performance. We found that increased reasoning demands rely on selective patterns of connectivity within cortical networks that emerged in addition to a more general, task-induced modular architecture. This task-driven architecture reverted to a more segregated resting-state architecture both immediately before and after the task. These findings reveal how flexibility in human brain networks is integral to achieving successful reasoning performance across different levels of cognitive demand. Copyright © 2017 the authors 0270-6474/17/378399-13$15.00/0.

Resting-state functional magnetic resonance imaging for surgical planning in pediatric patients: a preliminary experience.

PubMed

Roland, Jarod L; Griffin, Natalie; Hacker, Carl D; Vellimana, Ananth K; Akbari, S Hassan; Shimony, Joshua S; Smyth, Matthew D; Leuthardt, Eric C; Limbrick, David D

2017-12-01

OBJECTIVE Cerebral mapping for surgical planning and operative guidance is a challenging task in neurosurgery. Pediatric patients are often poor candidates for many modern mapping techniques because of inability to cooperate due to their immature age, cognitive deficits, or other factors. Resting-state functional MRI (rs-fMRI) is uniquely suited to benefit pediatric patients because it is inherently noninvasive and does not require task performance or significant cooperation. Recent advances in the field have made mapping cerebral networks possible on an individual basis for use in clinical decision making. The authors present their initial experience translating rs-fMRI into clinical practice for surgical planning in pediatric patients. METHODS The authors retrospectively reviewed cases in which the rs-fMRI analysis technique was used prior to craniotomy in pediatric patients undergoing surgery in their institution. Resting-state analysis was performed using a previously trained machine-learning algorithm for identification of resting-state networks on an individual basis. Network maps were uploaded to the clinical imaging and surgical navigation systems. Patient demographic and clinical characteristics, including need for sedation during imaging and use of task-based fMRI, were also recorded. RESULTS Twenty patients underwent rs-fMRI prior to craniotomy between December 2013 and June 2016. Their ages ranged from 1.9 to 18.4 years, and 12 were male. Five of the 20 patients also underwent task-based fMRI and one underwent awake craniotomy. Six patients required sedation to tolerate MRI acquisition, including resting-state sequences. Exemplar cases are presented including anatomical and resting-state functional imaging. CONCLUSIONS Resting-state fMRI is a rapidly advancing field of study allowing for whole brain analysis by a noninvasive modality. It is applicable to a wide range of patients and effective even under general anesthesia. The nature of resting-state analysis precludes any need for task cooperation. These features make rs-fMRI an ideal technology for cerebral mapping in pediatric neurosurgical patients. This review of the use of rs-fMRI mapping in an initial pediatric case series demonstrates the feasibility of utilizing this technique in pediatric neurosurgical patients. The preliminary experience presented here is a first step in translating this technique to a broader clinical practice.

Discovering EEG resting state alterations of semantic dementia.

PubMed

Grieder, Matthias; Koenig, Thomas; Kinoshita, Toshihiko; Utsunomiya, Keita; Wahlund, Lars-Olof; Dierks, Thomas; Nishida, Keiichiro

2016-05-01

Diagnosis of semantic dementia relies on cost-intensive MRI or PET, although resting EEG markers of other dementias have been reported. Yet the view still holds that resting EEG in patients with semantic dementia is normal. However, studies using increasingly sophisticated EEG analysis methods have demonstrated that slightest alterations of functional brain states can be detected. We analyzed the common four resting EEG microstates (A, B, C, and D) of 8 patients with semantic dementia in comparison with 8 healthy controls and 8 patients with Alzheimer's disease. Topographical differences between the groups were found in microstate classes B and C, while microstate classes A and D were comparable. The data showed that the semantic dementia group had a peculiar microstate E, but the commonly found microstate C was lacking. Furthermore, the presence of microstate E was significantly correlated with lower MMSE and language scores. Alterations in resting EEG can be found in semantic dementia. Topographical shifts in microstate C might be related to semantic memory deficits. This is the first study that discovered resting state EEG abnormality in semantic dementia. The notion that resting EEG in this dementia subtype is normal has to be revised. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

fMRI reveals reciprocal inhibition between social and physical cognitive domains.

PubMed

Jack, Anthony I; Dawson, Abigail J; Begany, Katelyn L; Leckie, Regina L; Barry, Kevin P; Ciccia, Angela H; Snyder, Abraham Z

2013-02-01

Two lines of evidence indicate that there exists a reciprocal inhibitory relationship between opposed brain networks. First, most attention-demanding cognitive tasks activate a stereotypical set of brain areas, known as the task-positive network and simultaneously deactivate a different set of brain regions, commonly referred to as the task negative or default mode network. Second, functional connectivity analyses show that these same opposed networks are anti-correlated in the resting state. We hypothesize that these reciprocally inhibitory effects reflect two incompatible cognitive modes, each of which may be directed towards understanding the external world. Thus, engaging one mode activates one set of regions and suppresses activity in the other. We test this hypothesis by identifying two types of problem-solving task which, on the basis of prior work, have been consistently associated with the task positive and task negative regions: tasks requiring social cognition, i.e., reasoning about the mental states of other persons, and tasks requiring physical cognition, i.e., reasoning about the causal/mechanical properties of inanimate objects. Social and mechanical reasoning tasks were presented to neurologically normal participants during fMRI. Each task type was presented using both text and video clips. Regardless of presentation modality, we observed clear evidence of reciprocal suppression: social tasks deactivated regions associated with mechanical reasoning and mechanical tasks deactivated regions associated with social reasoning. These findings are not explained by self-referential processes, task engagement, mental simulation, mental time travel or external vs. internal attention, all factors previously hypothesized to explain default mode network activity. Analyses of resting state data revealed a close match between the regions our tasks identified as reciprocally inhibitory and regions of maximal anti-correlation in the resting state. These results indicate the reciprocal inhibition is not attributable to constraints inherent in the tasks, but is neural in origin. Hence, there is a physiological constraint on our ability to simultaneously engage two distinct cognitive modes. Further work is needed to more precisely characterize these opposing cognitive domains. Copyright © 2012 Elsevier Inc. All rights reserved.

Decreased resting-state interhemispheric functional connectivity in unaffected siblings of schizophrenia patients.

PubMed

Guo, Wenbin; Jiang, Jiajing; Xiao, Changqing; Zhang, Zhikun; Zhang, Jian; Yu, Liuyu; Liu, Jianrong; Liu, Guiying

2014-01-01

Neuroimaging studies in unaffected siblings of schizophrenia patients can provide clues to the pathophysiology for the development of schizophrenia. However, little is known about the alterations of the interhemispheric resting-state functional connectivity (FC) in siblings, although the dysconnectivity hypothesis is prevailing in schizophrenia for years. In the present study, we used a newly validated voxel-mirrored homotopic connectivity (VMHC) method to identify whether aberrant interhemispheric FC was present in unaffected siblings at increased risk of developing schizophrenia at rest. Forty-six unaffected siblings of schizophrenia patients and 50 age-, sex-, and education-matched healthy controls underwent a resting-state functional magnetic resonance imaging (fMRI). Automated VMHC was used to analyze the data. The sibling group had lower VMHC than the control group in the angular gyrus (AG) and the lingual gyrus/cerebellum lobule VI. No region exhibited higher VMHC in the sibling group than in the control group. There was no significant sex difference of the VMHC values between male siblings and female siblings or between male controls and female controls, although evidence has been accumulated that size and shape of the corpus callosum, and functional homotopy differ between men and women. Our results first suggest that interhemispheric resting-state FC of VMHC is disrupted in unaffected siblings of schizophrenia patients, and add a new clue of abnormal interhemispheric resting-state FC to the pathophysiology for the development of schizophrenia. Copyright © 2013 Elsevier B.V. All rights reserved.

A method for functional network connectivity among spatially independent resting-state components in schizophrenia.

PubMed

Jafri, Madiha J; Pearlson, Godfrey D; Stevens, Michael; Calhoun, Vince D

2008-02-15

Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in healthy individuals as well as in patients with brain disorders. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject's ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients.

A Method for Functional Network Connectivity Among Spatially Independent Resting-State Components in Schizophrenia

PubMed Central

Jafri, Madiha J; Pearlson, Godfrey D; Stevens, Michael; Calhoun, Vince D

2011-01-01

Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in patients versus controls. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject’s ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients. PMID:18082428

Steady-state kinetic modeling constrains cellular resting states and dynamic behavior.

PubMed

Purvis, Jeremy E; Radhakrishnan, Ravi; Diamond, Scott L

2009-03-01

A defining characteristic of living cells is the ability to respond dynamically to external stimuli while maintaining homeostasis under resting conditions. Capturing both of these features in a single kinetic model is difficult because the model must be able to reproduce both behaviors using the same set of molecular components. Here, we show how combining small, well-defined steady-state networks provides an efficient means of constructing large-scale kinetic models that exhibit realistic resting and dynamic behaviors. By requiring each kinetic module to be homeostatic (at steady state under resting conditions), the method proceeds by (i) computing steady-state solutions to a system of ordinary differential equations for each module, (ii) applying principal component analysis to each set of solutions to capture the steady-state solution space of each module network, and (iii) combining optimal search directions from all modules to form a global steady-state space that is searched for accurate simulation of the time-dependent behavior of the whole system upon perturbation. Importantly, this stepwise approach retains the nonlinear rate expressions that govern each reaction in the system and enforces constraints on the range of allowable concentration states for the full-scale model. These constraints not only reduce the computational cost of fitting experimental time-series data but can also provide insight into limitations on system concentrations and architecture. To demonstrate application of the method, we show how small kinetic perturbations in a modular model of platelet P2Y(1) signaling can cause widespread compensatory effects on cellular resting states.

“I am resting but rest less well with you.” The moderating effect of anxious attachment style on alpha power during EEG resting state in a social context

PubMed Central

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

The effect of low-frequency oscillations on cardio-respiratory synchronization. Observations during rest and exercise

NASA Astrophysics Data System (ADS)

Kenwright, D. A.; Bahraminasab, A.; Stefanovska, A.; McClintock, P. V. E.

2008-10-01

We show that the transitions which occur between close orders of synchronization in the cardiorespiratory system are mainly due to modulation of the cardiac and respiratory processes by low-frequency components. The experimental evidence is derived from recordings on healthy subjects at rest and during exercise. Exercise acts as a perturbation of the system that alters the mean cardiac and respiratory frequencies and changes the amount of their modulation by low-frequency oscillations. The conclusion is supported by numerical evidence based on a model of phase-coupled oscillators, with white noise and lowfrequency noise. Both the experimental and numerical approaches confirm that low-frequency oscillations play a significant role in the transitional behavior between close orders of synchronization.

Resting State Correlates of Subdimensions of Anxious Affect

PubMed Central

Bijsterbosch, Janine; Smith, Stephen; Forster, Sophie; John, Oliver P.; Bishop, Sonia J.

2014-01-01

Resting state fMRI may help identify markers of risk for affective disorder. Given the comorbidity of anxiety and depressive disorders and the heterogeneity of these disorders as defined by DSM, an important challenge is to identify alterations in resting state brain connectivity uniquely associated with distinct profiles of negative affect. The current study aimed to address this by identifying differences in brain connectivity specifically linked to cognitive and physiological profiles of anxiety, controlling for depressed affect. We adopted a two-stage multivariate approach. Hierarchical clustering was used to independently identify dimensions of negative affective style and resting state brain networks. Combining the clustering results, we examined individual differences in resting state connectivity uniquely associated with subdimensions of anxious affect, controlling for depressed affect. Physiological and cognitive subdimensions of anxious affect were identified. Physiological anxiety was associated with widespread alterations in insula connectivity, including decreased connectivity between insula subregions and between the insula and other medial frontal and subcortical networks. This is consistent with the insula facilitating communication between medial frontal and subcortical regions to enable control of physiological affective states. Meanwhile, increased connectivity within a frontoparietal–posterior cingulate cortex–precunous network was specifically associated with cognitive anxiety, potentially reflecting increased spontaneous negative cognition (e.g., worry). These findings suggest that physiological and cognitive anxiety comprise subdimensions of anxiety-related affect and reveal associated alterations in brain connectivity. PMID:24168223

5-HTTLPR Polymorphism Impacts Task-Evoked and Resting-State Activities of the Amygdala in Han Chinese

PubMed Central

Li, Sufang; Zou, Qihong; Li, Jun; Li, Jin; Wang, Deyi; Yan, Chaogan; Dong, Qi; Zang, Yu-Feng

2012-01-01

Background Prior research has shown that the amygdala of carriers of the short allele (s) of the serotonin transporter (5-HTT) gene (5-HTTLPR) have a larger response to negative emotional stimuli and higher spontaneous activity during the resting state than non-carriers. However, recent studies have suggested that the effects of 5-HTTLPR may be specific to different ethnic groups. Few studies have been conducted to address this issue. Methodology/Principal Findings Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) was conducted on thirty-eight healthy Han Chinese subjects (l/l group, n = 19; s/s group, n = 19) during the resting state and during an emotional processing task. Compared with the s/s group, the l/l group showed significantly increased regional homogeneity or local synchronization in the right amygdala during the resting state (|t|>2.028, p<0.05, corrected), but no significant difference was found in the bilateral amygdala in response to negative stimuli in the emotional processing task. Conclusions/Significance 5-HTTLPR can alter the spontaneous activity of the amygdala in Han Chinese. However, the effect of 5-HTTLPR on the amygdala both in task state and resting state in Asian population was no similar with Caucasians. They suggest that the effect of 5-HTTLPR on the amygdala may be modulated by ethnic differences. PMID:22574175

Resting-state networks in healthy adult subjects: a comparison between a 32-element and an 8-element phased array head coil at 3.0 Tesla.

PubMed

Paolini, Marco; Keeser, Daniel; Ingrisch, Michael; Werner, Natalie; Kindermann, Nicole; Reiser, Maximilian; Blautzik, Janusch

2015-05-01

Little research exists on the influence of a magnetic resonance imaging (MRI) head coil's channel count on measured resting-state functional connectivity. To compare a 32-element (32ch) and an 8-element (8ch) phased array head coil with respect to their potential to detect functional connectivity within resting-state networks. Twenty-six healthy adults (mean age, 21.7 years; SD, 2.1 years) underwent resting-state functional MRI at 3.0 Tesla with both coils using equal standard imaging parameters and a counterbalanced design. Independent component analysis (ICA) at different model orders and a dual regression approach were performed. Voxel-wise non-parametric statistical between-group contrasts were determined using permutation-based non-parametric inference. Phantom measurements demonstrated a generally higher image signal-to-noise ratio using the 32ch head coil. However, the results showed no significant differences between corresponding resting-state networks derived from both coils (p < 0.05, FWE-corrected). Using the identical standard acquisition parameters, the 32ch head coil does not offer any significant advantages in detecting ICA-based functional connectivity within RSNs. © The Foundation Acta Radiologica 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Altered resting-state neural activity and changes following a craving behavioral intervention for Internet gaming disorder.

PubMed

Zhang, Jin-Tao; Yao, Yuan-Wei; Potenza, Marc N; Xia, Cui-Cui; Lan, Jing; Liu, Lu; Wang, Ling-Jiao; Liu, Ben; Ma, Shan-Shan; Fang, Xiao-Yi

2016-07-06

Internet gaming disorder (IGD) has become a serious mental health issue worldwide. Evaluating the benefits of interventions for IGD is of great significance. Thirty-six young adults with IGD and 19 healthy comparison (HC) subjects were recruited and underwent resting-state fMRI scanning. Twenty IGD subjects participated in a group craving behavioral intervention (CBI) and were scanned before and after the intervention. The remaining 16 IGD subjects did not receive an intervention. The results showed that IGD subjects showed decreased amplitude of low fluctuation in the orbital frontal cortex and posterior cingulate cortex, and exhibited increased resting-state functional connectivity between the posterior cingulate cortex and dorsolateral prefrontal cortex, compared with HC subjects. Compared with IGD subjects who did not receive the intervention, those receiving CBI demonstrated significantly reduced resting-state functional connectivity between the: (1) orbital frontal cortex with hippocampus/parahippocampal gyrus; and, (2) posterior cingulate cortex with supplementary motor area, precentral gyrus, and postcentral gyrus. These findings suggest that IGD is associated with abnormal resting-state neural activity in reward-related, default mode and executive control networks. Thus, the CBI may exert effects by reducing interactions between regions within a reward-related network, and across the default mode and executive control networks.

Electrophysiological resting-state biomarker for diagnosing mesial temporal lobe epilepsy with hippocampal sclerosis.

PubMed

Jin, Seung-Hyun; Chung, Chun Kee

2017-01-01

The main aim of the present study was to evaluate whether resting-state functional connectivity of magnetoencephalography (MEG) signals can differentiate patients with mesial temporal lobe epilepsy (MTLE) from healthy controls (HC) and can differentiate between right and left MTLE as a diagnostic biomarker. To this end, a support vector machine (SVM) method among various machine learning algorithms was employed. We compared resting-state functional networks between 46 MTLE (right MTLE=23; left MTLE=23) patients with histologically proven HS who were free of seizure after surgery, and 46 HC. The optimal SVM group classifier distinguished MTLE patients with a mean accuracy of 95.1% (sensitivity=95.8%; specificity=94.3%). Increased connectivity including the right posterior cingulate gyrus and decreased connectivity including at least one sensory-related resting-state network were key features reflecting the differences between MTLE patients and HC. The optimal SVM model distinguished between right and left MTLE patients with a mean accuracy of 76.2% (sensitivity=76.0%; specificity=76.5%). We showed the potential of electrophysiological resting-state functional connectivity, which reflects brain network reorganization in MTLE patients, as a possible diagnostic biomarker to differentiate MTLE patients from HC and differentiate between right and left MTLE patients. Copyright © 2016 Elsevier B.V. All rights reserved.

Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

PubMed

Grooms, Joshua K; Thompson, Garth J; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H; Epstein, Charles M; Keilholz, Shella D

2017-06-01

A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.

Infraslow Electroencephalographic and Dynamic Resting State Network Activity

PubMed Central

Grooms, Joshua K.; Thompson, Garth J.; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H.; Epstein, Charles M.

2017-01-01

Abstract A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies. PMID:28462586

Altered resting-state neural activity and changes following a craving behavioral intervention for Internet gaming disorder

PubMed Central

Zhang, Jin-Tao; Yao, Yuan-Wei; Potenza, Marc N.; Xia, Cui-Cui; Lan, Jing; Liu, Lu; Wang, Ling-Jiao; Liu, Ben; Ma, Shan-Shan; Fang, Xiao-Yi

2016-01-01

Internet gaming disorder (IGD) has become a serious mental health issue worldwide. Evaluating the benefits of interventions for IGD is of great significance. Thirty-six young adults with IGD and 19 healthy comparison (HC) subjects were recruited and underwent resting-state fMRI scanning. Twenty IGD subjects participated in a group craving behavioral intervention (CBI) and were scanned before and after the intervention. The remaining 16 IGD subjects did not receive an intervention. The results showed that IGD subjects showed decreased amplitude of low fluctuation in the orbital frontal cortex and posterior cingulate cortex, and exhibited increased resting-state functional connectivity between the posterior cingulate cortex and dorsolateral prefrontal cortex, compared with HC subjects. Compared with IGD subjects who did not receive the intervention, those receiving CBI demonstrated significantly reduced resting-state functional connectivity between the: (1) orbital frontal cortex with hippocampus/parahippocampal gyrus; and, (2) posterior cingulate cortex with supplementary motor area, precentral gyrus, and postcentral gyrus. These findings suggest that IGD is associated with abnormal resting-state neural activity in reward-related, default mode and executive control networks. Thus, the CBI may exert effects by reducing interactions between regions within a reward-related network, and across the default mode and executive control networks. PMID:27381822

When structure affects function--the need for partial volume effect correction in functional and resting state magnetic resonance imaging studies.

PubMed

Dukart, Juergen; Bertolino, Alessandro

2014-01-01

Both functional and also more recently resting state magnetic resonance imaging have become established tools to investigate functional brain networks. Most studies use these tools to compare different populations without controlling for potential differences in underlying brain structure which might affect the functional measurements of interest. Here, we adapt a simulation approach combined with evaluation of real resting state magnetic resonance imaging data to investigate the potential impact of partial volume effects on established functional and resting state magnetic resonance imaging analyses. We demonstrate that differences in the underlying structure lead to a significant increase in detected functional differences in both types of analyses. Largest increases in functional differences are observed for highest signal-to-noise ratios and when signal with the lowest amount of partial volume effects is compared to any other partial volume effect constellation. In real data, structural information explains about 25% of within-subject variance observed in degree centrality--an established resting state connectivity measurement. Controlling this measurement for structural information can substantially alter correlational maps obtained in group analyses. Our results question current approaches of evaluating these measurements in diseased population with known structural changes without controlling for potential differences in these measurements.

Temperature Swing Adsorption Compressor Development

NASA Technical Reports Server (NTRS)

Finn, John E.; Mulloth, Lila M.; Affleck, Dave L.

2001-01-01

Closing the oxygen loop in an air revitalization system based on four-bed molecular sieve and Sabatier reactor technology requires a vacuum pump-compressor that can take the low-pressure CO, from the 4BMS and compress and store for use by a Sabatier reactor. NASA Ames Research Center proposed a solid-state temperature-swing adsorption (TSA) compressor that appears to meet performance requirements, be quiet and reliable, and consume less power than a comparable mechanical compressor/accumulator combination. Under this task, TSA compressor technology is being advanced through development of a complete prototype system. A liquid-cooled TSA compressor has been partially tested, and the rest of the system is being fabricated. An air-cooled TSA compressor is also being designed.

The Effects of Long Duration Bed Rest on Functional Mobility and Balance: Relationship to Resting State Motor Cortex Connectivity

NASA Technical Reports Server (NTRS)

Erdeniz, B.; Koppelmans, V.; Bloomberg, J. J.; Kofman, I. S.; DeDios, Y. E.; Riascos-Castaneda, R. F.; Wood, S. J.; Mulavara, A. P.; Seidler, R. D.

2014-01-01

NASA offers researchers from a variety of backgrounds the opportunity to study bed rest as an experimental analog for space flight. Extended exposure to a head-down tilt position during long duration bed rest can resemble many of the effects of a low-gravity environment such as reduced sensory inputs, body unloading and increased cephalic fluid distribution. The aim of our study is to a) identify changes in brain function that occur with prolonged bed rest and characterize their recovery time course; b) assess whether and how these changes impact behavioral and neurocognitive performance. Thus far, we completed data collection from six participants that include task based and resting state fMRI. The data have been acquired through the bed rest facility located at the University of Texas Medical Branch (Galveston, TX). Subjects remained in bed with their heads tilted down 6 degrees below their feet for 70 consecutive days. Behavioral measures and neuroimaging assessments were obtained at seven time points: a) 7 and 12 days before bed rest; b) 7, 30, and 65 days during bed rest; and c) 7 and 12 days after bed rest. Functional connectivity magnetic resonance imaging (FcMRI) analysis was performed to assess the connectivity of motor cortex in and out of bed rest. We found a decrease in motor cortex connectivity with vestibular cortex and the cerebellum from pre bed rest to in bed rest. We also used a battery of behavioral measures including the functional mobility test and computerized dynamic posturography collected before and after bed rest. We will report the preliminary results of analyses relating brain and behavior changes. Furthermore, we will also report the preliminary results of a spatial working memory task and vestibular stimulation during in and out of bed rest.

Resting state signatures of domain and demand-specific working memory performance.

PubMed

van Dam, Wessel O; Decker, Scott L; Durbin, Jeffery S; Vendemia, Jennifer M C; Desai, Rutvik H

2015-09-01

Working memory (WM) is one of the key constructs in understanding higher-level cognition. We examined whether patterns of activity in the resting state of individual subjects are correlated with their off-line working and short-term memory capabilities. Participants completed a resting-state fMRI scan and off-line working and short-term memory (STM) tests with both verbal and visual materials. We calculated fractional amplitude of low frequency fluctuations (fALFF) from the resting state data, and also computed connectivity between seeds placed in frontal and parietal lobes. Correlating fALFF values with behavioral measures showed that the fALFF values in a widespread fronto-parietal network during rest were positively correlated with a combined memory measure. In addition, STM showed a significant correlation with fALFF within the right angular gyrus and left middle occipital gyrus, whereas WM was correlated with fALFF values within the right IPS and left dorsomedial cerebellar cortex. Furthermore, verbal and visuospatial memory capacities were associated with dissociable patterns of low-frequency fluctuations. Seed-based connectivity showed correlations with the verbal WM measure in the left hemisphere, and with the visual WM measure in the right hemisphere. These findings contribute to our understanding of how differences in spontaneous low-frequency fluctuations at rest are correlated with differences in cognitive performance. Copyright © 2015 Elsevier Inc. All rights reserved.

Auditory Hallucinations and the Brain’s Resting-State Networks: Findings and Methodological Observations

PubMed Central

Alderson-Day, Ben; Diederen, Kelly; Fernyhough, Charles; Ford, Judith M.; Horga, Guillermo; Margulies, Daniel S.; McCarthy-Jones, Simon; Northoff, Georg; Shine, James M.; Turner, Jessica; van de Ven, Vincent; van Lutterveld, Remko; Waters, Flavie; Jardri, Renaud

2016-01-01

In recent years, there has been increasing interest in the potential for alterations to the brain’s resting-state networks (RSNs) to explain various kinds of psychopathology. RSNs provide an intriguing new explanatory framework for hallucinations, which can occur in different modalities and population groups, but which remain poorly understood. This collaboration from the International Consortium on Hallucination Research (ICHR) reports on the evidence linking resting-state alterations to auditory hallucinations (AH) and provides a critical appraisal of the methodological approaches used in this area. In the report, we describe findings from resting connectivity fMRI in AH (in schizophrenia and nonclinical individuals) and compare them with findings from neurophysiological research, structural MRI, and research on visual hallucinations (VH). In AH, various studies show resting connectivity differences in left-hemisphere auditory and language regions, as well as atypical interaction of the default mode network and RSNs linked to cognitive control and salience. As the latter are also evident in studies of VH, this points to a domain-general mechanism for hallucinations alongside modality-specific changes to RSNs in different sensory regions. However, we also observed high methodological heterogeneity in the current literature, affecting the ability to make clear comparisons between studies. To address this, we provide some methodological recommendations and options for future research on the resting state and hallucinations. PMID:27280452

Large-scale brain networks in the awake, truly resting marmoset monkey.

PubMed

Belcher, Annabelle M; Yen, Cecil C; Stepp, Haley; Gu, Hong; Lu, Hanbing; Yang, Yihong; Silva, Afonso C; Stein, Elliot A

2013-10-16

Resting-state functional MRI is a powerful tool that is increasingly used as a noninvasive method for investigating whole-brain circuitry and holds great potential as a possible diagnostic for disease. Despite this potential, few resting-state studies have used animal models (of which nonhuman primates represent our best opportunity of understanding complex human neuropsychiatric disease), and no work has characterized networks in awake, truly resting animals. Here we present results from a small New World monkey that allows for the characterization of resting-state networks in the awake state. Six adult common marmosets (Callithrix jacchus) were acclimated to light, comfortable restraint using individualized helmets. Following behavioral training, resting BOLD data were acquired during eight consecutive 10 min scans for each conscious subject. Group independent component analysis revealed 12 brain networks that overlap substantially with known anatomically constrained circuits seen in the awake human. Specifically, we found eight sensory and "lower-order" networks (four visual, two somatomotor, one cerebellar, and one caudate-putamen network), and four "higher-order" association networks (one default mode-like network, one orbitofrontal, one frontopolar, and one network resembling the human salience network). In addition to their functional relevance, these network patterns bear great correspondence to those previously described in awake humans. This first-of-its-kind report in an awake New World nonhuman primate provides a platform for mechanistic neurobiological examination for existing disease models established in the marmoset.

Structural connectivity allows for multi-threading during rest: the structure of the cortex leads to efficient alternation between resting state exploratory behavior and default mode processing.

PubMed

Senden, Mario; Goebel, Rainer; Deco, Gustavo

2012-05-01

Despite the absence of stimulation or task conditions the cortex exhibits highly structured spatio-temporal activity patterns. These patterns are known as resting state networks (RSNs) and emerge as low-frequency fluctuations (<0.1 Hz) observed in the fMRI signal of human subjects during rest. We are interested in the relationship between structural connectivity of the cortex and the fluctuations exhibited during resting conditions. We are especially interested in the effect of degree of connectivity on resting state dynamics as the default mode network (DMN) is highly connected. We find in experimental resting fMRI data that the DMN is the functional network that is most frequently active and for the longest time. In large-scale computational simulations of the cortex based on the corresponding underlying DTI/DSI based neuroanatomical connectivity matrix, we additionally find a strong correlation between the mean degree of functional networks and the proportion of time they are active. By artificially modifying different types of neuroanatomical connectivity matrices in the model, we were able to demonstrate that only models based on structural connectivity containing hubs give rise to this relationship. We conclude that, during rest, the cortex alternates efficiently between explorations of its externally oriented functional repertoire and internally oriented processing as a consequence of the DMN's high degree of connectivity. Copyright © 2012 Elsevier Inc. All rights reserved.

Reduced brain resting-state network specificity in infants compared with adults.

PubMed

Wylie, Korey P; Rojas, Donald C; Ross, Randal G; Hunter, Sharon K; Maharajh, Keeran; Cornier, Marc-Andre; Tregellas, Jason R

2014-01-01

Infant resting-state networks do not exhibit the same connectivity patterns as those of young children and adults. Current theories of brain development emphasize developmental progression in regional and network specialization. We compared infant and adult functional connectivity, predicting that infants would exhibit less regional specificity and greater internetwork communication compared with adults. Functional magnetic resonance imaging at rest was acquired in 12 healthy, term infants and 17 adults. Resting-state networks were extracted, using independent components analysis, and the resulting components were then compared between the adult and infant groups. Adults exhibited stronger connectivity in the posterior cingulate cortex node of the default mode network, but infants had higher connectivity in medial prefrontal cortex/anterior cingulate cortex than adults. Adult connectivity was typically higher than infant connectivity within structures previously associated with the various networks, whereas infant connectivity was frequently higher outside of these structures. Internetwork communication was significantly higher in infants than in adults. We interpret these findings as consistent with evidence suggesting that resting-state network development is associated with increasing spatial specificity, possibly reflecting the corresponding functional specialization of regions and their interconnections through experience.

Distributed effects of methylphenidate on the network structure of the resting brain: a connectomic pattern classification analysis.

PubMed

Sripada, Chandra Sekhar; Kessler, Daniel; Welsh, Robert; Angstadt, Michael; Liberzon, Israel; Phan, K Luan; Scott, Clayton

2013-11-01

Methylphenidate is a psychostimulant medication that produces improvements in functions associated with multiple neurocognitive systems. To investigate the potentially distributed effects of methylphenidate on the brain's intrinsic network architecture, we coupled resting state imaging with multivariate pattern classification. In a within-subject, double-blind, placebo-controlled, randomized, counterbalanced, cross-over design, 32 healthy human volunteers received either methylphenidate or placebo prior to two fMRI resting state scans separated by approximately one week. Resting state connectomes were generated by placing regions of interest at regular intervals throughout the brain, and these connectomes were submitted for support vector machine analysis. We found that methylphenidate produces a distributed, reliably detected, multivariate neural signature. Methylphenidate effects were evident across multiple resting state networks, especially visual, somatomotor, and default networks. Methylphenidate reduced coupling within visual and somatomotor networks. In addition, default network exhibited decoupling with several task positive networks, consistent with methylphenidate modulation of the competitive relationship between these networks. These results suggest that connectivity changes within and between large-scale networks are potentially involved in the mechanisms by which methylphenidate improves attention functioning. Copyright © 2013 Elsevier Inc. All rights reserved.

ZNF804A Variation May Affect Hippocampal-Prefrontal Resting-State Functional Connectivity in Schizophrenic and Healthy Individuals.

PubMed

Zhang, Yuyanan; Yan, Hao; Liao, Jinmin; Yu, Hao; Jiang, Sisi; Liu, Qi; Zhang, Dai; Yue, Weihua

2018-06-01

The ZNF804A variant rs1344706 has consistently been associated with schizophrenia and plays a role in hippocampal-prefrontal functional connectivity during working memory. Whether the effect exists in the resting state and in patients with schizophrenia remains unclear. In this study, we investigated the ZNF804A polymorphism at rs1344706 in 92 schizophrenic patients and 99 healthy controls of Han Chinese descent, and used resting-state functional magnetic resonance imaging to explore the functional connectivity in the participants. We found a significant main effect of genotype on the resting-state functional connectivity (RSFC) between the hippocampus and the dorsolateral prefrontal cortex (DLPFC) in both schizophrenic patients and healthy controls. The homozygous ZNF804A rs1344706 genotype (AA) conferred a high risk of schizophrenia, and also exhibited significantly decreased resting functional coupling between the left hippocampus and right DLPFC (F(2,165) = 13.43, P < 0.001). The RSFC strength was also correlated with cognitive performance and the severity of psychosis in schizophrenia. The current findings identified the neural impact of the ZNF804A rs1344706 on hippocampal-prefrontal RSFC associated with schizophrenia.

Predicting Risk-Taking Behavior from Prefrontal Resting-State Activity and Personality

PubMed Central

Studer, Bettina; Pedroni, Andreas; Rieskamp, Jörg

2013-01-01

Risk-taking is subject to considerable individual differences. In the current study, we tested whether resting-state activity in the prefrontal cortex and trait sensitivity to reward and punishment can help predict risk-taking behavior. Prefrontal activity at rest was assessed in seventy healthy volunteers using electroencephalography, and compared to their choice behavior on an economic risk-taking task. The Behavioral Inhibition System/Behavioral Activation System scale was used to measure participants’ trait sensitivity to reward and punishment. Our results confirmed both prefrontal resting-state activity and personality traits as sources of individual differences in risk-taking behavior. Right-left asymmetry in prefrontal activity and scores on the Behavioral Inhibition System scale, reflecting trait sensitivity to punishment, were correlated with the level of risk-taking on the task. We further discovered that scores on the Behavioral Inhibition System scale modulated the relationship between asymmetry in prefrontal resting-state activity and risk-taking. The results of this study demonstrate that heterogeneity in risk-taking behavior can be traced back to differences in the basic physiology of decision-makers’ brains, and suggest that baseline prefrontal activity and personality traits might interplay in guiding risk-taking behavior. PMID:24116176

Framework for ReSTful Web Services in OSGi

NASA Technical Reports Server (NTRS)

Shams, Khawaja S.; Norris, Jeffrey S.; Powell, Mark W.; Crockett, Thomas M.; Mittman, David S.; Fox, Jason M.; Joswig, Joseph C.; Wallick, Michael N.; Torres, Recaredo J.; Rabe, Kenneth

2009-01-01

Ensemble ReST is a software system that eases the development, deployment, and maintenance of server-side application programs to perform functions that would otherwise be performed by client software. Ensemble ReST takes advantage of the proven disciplines of ReST (Representational State Transfer. ReST leverages the standardized HTTP protocol to enable developers to offer services to a diverse variety of clients: from shell scripts to sophisticated Java application suites

The Effects of Long Duration Bed Rest as a Spaceflight Analogue on Resting State Sensorimotor Network Functional Connectivity and Neurocognitive Performance

NASA Technical Reports Server (NTRS)

Cassady, K.; Koppelmans, V.; Yuan, P.; Cooke, K.; De Dios, Y.; Stepanyan, V.; Szecsy, D.; Gadd, N.; Wood, S.; Reuter-Lorenz, P.;

Long-Haul Truck Sleeper Heating Load Reduction Package for Rest Period Idling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lustbader, Jason Aaron; Kekelia, Bidzina; Tomerlin, Jeff

Annual fuel use for sleeper cab truck rest period idling is estimated at 667 million gallons in the United States, or 6.8% of long-haul truck fuel use. Truck idling during a rest period represents zero freight efficiency and is largely done to supply accessory power for climate conditioning of the cab. The National Renewable Energy Laboratory's CoolCab project aims to reduce heating, ventilating, and air conditioning (HVAC) loads and resulting fuel use from rest period idling by working closely with industry to design efficient long-haul truck thermal management systems while maintaining occupant comfort. Enhancing the thermal performance of cab/sleepers willmore » enable smaller, lighter, and more cost-effective idle reduction solutions. In addition, if the fuel savings provide a one- to three-year payback period, fleet owners will be economically motivated to incorporate them. For candidate idle reduction technologies to be implemented by original equipment manufacturers and fleets, their effectiveness must be quantified. To address this need, several promising candidate technologies were evaluated through experimentation and modeling to determine their effectiveness in reducing rest period HVAC loads. Load reduction strategies were grouped into the focus areas of solar envelope, occupant environment, conductive pathways, and efficient equipment. Technologies in each of these focus areas were investigated in collaboration with industry partners. The most promising of these technologies were then combined with the goal of exceeding a 30% reduction in HVAC loads. These technologies included 'ultra-white' paint, advanced insulation, and advanced curtain design. Previous testing showed more than a 35.7% reduction in air conditioning loads. This paper describes the overall heat transfer coefficient testing of this advanced load reduction technology package that showed more than a 43% reduction in heating load. Adding an additional layer of advanced insulation with a reflective barrier to the thermal load reduction package resulted in a 53.3% reduction in the overall heat transfer coefficient.« less

Long-Haul Truck Sleeper Heating Load Reduction Package for Rest Period Idling: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lustbader, Jason; Kekelia, Bidzina; Tomerlin, Jeff

Annual fuel use for sleeper cab truck rest period idling is estimated at 667 million gallons in the United States, or 6.8% of long-haul truck fuel use. Truck idling during a rest period represents zero freight efficiency and is largely done to supply accessory power for climate conditioning of the cab. The National Renewable Energy Laboratory's CoolCab project aims to reduce heating, ventilating, and air conditioning (HVAC) loads and resulting fuel use from rest period idling by working closely with industry to design efficient long-haul truck thermal management systems while maintaining occupant comfort. Enhancing the thermal performance of cab/sleepers willmore » enable smaller, lighter, and more cost-effective idle reduction solutions. In addition, if the fuel savings provide a one- to three-year payback period, fleet owners will be economically motivated to incorporate them. For candidate idle reduction technologies to be implemented by original equipment manufacturers and fleets, their effectiveness must be quantified. To address this need, several promising candidate technologies were evaluated through experimentation and modeling to determine their effectiveness in reducing rest period HVAC loads. Load reduction strategies were grouped into the focus areas of solar envelope, occupant environment, conductive pathways, and efficient equipment. Technologies in each of these focus areas were investigated in collaboration with industry partners. The most promising of these technologies were then combined with the goal of exceeding a 30% reduction in HVAC loads. These technologies included 'ultra-white' paint, advanced insulation, and advanced curtain design. Previous testing showed more than a 35.7% reduction in air conditioning loads. This paper describes the overall heat transfer coefficient testing of this advanced load reduction technology package that showed more than a 43% reduction in heating load. Adding an additional layer of advanced insulation with a reflective barrier to the thermal load reduction package resulted in a 53.3% reduction in the overall heat transfer coefficient.« less

Altered Gray Matter Volume and Resting-State Connectivity in Individuals With Internet Gaming Disorder: A Voxel-Based Morphometry and Resting-State Functional Magnetic Resonance Imaging Study

PubMed Central

Seok, Ji-Woo; Sohn, Jin-Hun

2018-01-01

Neuroimaging studies on the characteristics of individuals with Internet gaming disorder (IGD) have been accumulating due to growing concerns regarding the psychological and social problems associated with Internet use. However, relatively little is known about the brain characteristics underlying IGD, such as the associated functional connectivity and structure. The aim of this study was to investigate alterations in gray matter (GM) volume and functional connectivity during resting state in individuals with IGD using voxel-based morphometry and a resting-state connectivity analysis. The participants included 20 individuals with IGD and 20 age- and sex-matched healthy controls. Resting-state functional and structural images were acquired for all participants using 3 T magnetic resonance imaging. We also measured the severity of IGD and impulsivity using psychological scales. The results show that IGD severity was positively correlated with GM volume in the left caudate (p < 0.05, corrected for multiple comparisons), and negatively associated with functional connectivity between the left caudate and the right middle frontal gyrus (p < 0.05, corrected for multiple comparisons). This study demonstrates that IGD is associated with neuroanatomical changes in the right middle frontal cortex and the left caudate. These are important brain regions for reward and cognitive control processes, and structural and functional abnormalities in these regions have been reported for other addictions, such as substance abuse and pathological gambling. The findings suggest that structural deficits and resting-state functional impairments in the frontostriatal network may be associated with IGD and provide new insights into the underlying neural mechanisms of IGD. PMID:29636704

Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study

PubMed Central

Liu, Peng; Qin, Wei; Wang, Jingjing; Zeng, Fang; Zhou, Guangyu; Wen, Haixia; von Deneen, Karen M.; Liang, Fanrong; Gong, Qiyong; Tian, Jie

2013-01-01

Background Previous imaging studies on functional dyspepsia (FD) have focused on abnormal brain functions during special tasks, while few studies concentrated on the resting-state abnormalities of FD patients, which might be potentially valuable to provide us with direct information about the neural basis of FD. The main purpose of the current study was thereby to characterize the distinct patterns of resting-state function between FD patients and healthy controls (HCs). Methodology/Principal Findings Thirty FD patients and thirty HCs were enrolled and experienced 5-mintue resting-state scanning. Based on the support vector machine (SVM), we applied multivariate pattern analysis (MVPA) to investigate the differences of resting-state function mapped by regional homogeneity (ReHo). A classifier was designed by using the principal component analysis and the linear SVM. Permutation test was then employed to identify the significant contribution to the final discrimination. The results displayed that the mean classifier accuracy was 86.67%, and highly discriminative brain regions mainly included the prefrontal cortex (PFC), orbitofrontal cortex (OFC), supplementary motor area (SMA), temporal pole (TP), insula, anterior/middle cingulate cortex (ACC/MCC), thalamus, hippocampus (HIPP)/parahippocamus (ParaHIPP) and cerebellum. Correlation analysis revealed significant correlations between ReHo values in certain regions of interest (ROI) and the FD symptom severity and/or duration, including the positive correlations between the dmPFC, pACC and the symptom severity; whereas, the positive correlations between the MCC, OFC, insula, TP and FD duration. Conclusions These findings indicated that significantly distinct patterns existed between FD patients and HCs during the resting-state, which could expand our understanding of the neural basis of FD. Meanwhile, our results possibly showed potential feasibility of functional magnetic resonance imaging diagnostic assay for FD. PMID:23874543

Rest but busy: Aberrant resting-state functional connectivity of triple network model in insomnia.

PubMed

Dong, Xiaojuan; Qin, Haixia; Wu, Taoyu; Hu, Hua; Liao, Keren; Cheng, Fei; Gao, Dong; Lei, Xu

2018-02-01

One classical hypothesis among many models to explain the etiology and maintenance of insomnia disorder (ID) is hyperarousal. Aberrant functional connectivity among resting-state large-scale brain networks may be the underlying neurological mechanisms of this hypothesis. The aim of current study was to investigate the functional network connectivity (FNC) among large-scale brain networks in patients with insomnia disorder (ID) during resting state. In the present study, the resting-state fMRI was used to evaluate whether patients with ID showed aberrant FNC among dorsal attention network (DAN), frontoparietal control network (FPC), anterior default mode network (aDMN), and posterior default mode network (pDMN) compared with healthy good sleepers (HGSs). The Pearson's correlation analysis was employed to explore whether the abnormal FNC observed in patients with ID was associated with sleep parameters, cognitive and emotional scores, and behavioral performance assessed by questionnaires and tasks. Patients with ID had worse subjective thought control ability measured by Thought Control Ability Questionnaire (TCAQ) and more negative affect than HGSs. Intriguingly, relative to HGSs, patients with ID showed a significant increase in FNC between DAN and FPC, but a significant decrease in FNC between aDMN and pDMN. Exploratory analysis in patients with ID revealed a significantly positive correlation between the DAN-FPC FNC and reaction time (RT) of psychomotor vigilance task (PVT). The current study demonstrated that even during the resting state, the task-activated and task-deactivated large-scale brain networks in insomniacs may still maintain a hyperarousal state, looking quite similar to the pattern in a task condition with external stimuli. Those results support the hyperarousal model of insomnia.

Superior colliculus resting state networks in post-traumatic stress disorder and its dissociative subtype.

PubMed

Olivé, Isadora; Densmore, Maria; Harricharan, Sherain; Théberge, Jean; McKinnon, Margaret C; Lanius, Ruth

2018-01-01

The innate alarm system (IAS) models the neurocircuitry involved in threat processing in posttraumatic stress disorder (PTSD). Here, we investigate a primary subcortical structure of the IAS model, the superior colliculus (SC), where the SC is thought to contribute to the mechanisms underlying threat-detection in PTSD. Critically, the functional connectivity between the SC and other nodes of the IAS remains unexplored. We conducted a resting-state fMRI study to investigate the functional architecture of the IAS, focusing on connectivity of the SC in PTSD (n = 67), its dissociative subtype (n = 41), and healthy controls (n = 50) using region-of-interest seed-based analysis. We observed group-specific resting state functional connectivity between the SC for both PTSD and its dissociative subtype, indicative of dedicated IAS collicular pathways in each group of patients. When comparing PTSD to its dissociative subtype, we observed increased resting state functional connectivity between the left SC and the right dorsolateral prefrontal cortex (DLPFC) in PTSD. The DLPFC is involved in modulation of emotional processes associated with active defensive responses characterising PTSD. Moreover, when comparing PTSD to its dissociative subtype, increased resting state functional connectivity was observed between the right SC and the right temporoparietal junction in the dissociative subtype. The temporoparietal junction is involved in depersonalization responses associated with passive defensive responses typical of the dissociative subtype. Our findings suggest that unique resting state functional connectivity of the SC parallels the unique symptom profile and defensive responses observed in PTSD and its dissociative subtype. Hum Brain Mapp 39:563-574, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Differences in Paracingulate Connectivity Associated with Epileptiform Discharges and Uncontrolled Seizures in Genetic Generalized Epilepsy

PubMed Central

Kay, Benjamin P; Holland, Scott K; Privitera, Michael D; Szaflarski, Jerzy P

2014-01-01

Summary Objective Patients with genetic generalized epilepsy (GGE) frequently continue to suffer from seizures despite appropriate clinical management. GGE is associated with changes in the resting-state networks modulated by clinical factors such as duration of disease and response to treatment. However, the effect of GSWDs and/or seizures on resting-state functional connectivity (RSFC) is not well understood. Methods We investigated the effects of GSWD frequency (in GGE patients), GGE (patients vs. healthy controls), and seizures (uncontrolled vs. controlled) on RSFC using seed-based voxel correlation in simultaneous EEG and resting-state fMRI (EEG/fMRI) data from 72 GGE patients (23 w/uncontrolled seizures) and 38 healthy controls. We used seeds in paracingulate cortex, thalamus, cerebellum, and posterior cingulate cortex to examine changes in cortical-subcortical resting-state networks and the default mode network (DMN). We excluded from analyses time points surrounding GSWDs to avoid possible contamination of the resting state. Results (1) Higher frequency of GSWDs was associated with an increase in seed-based voxel correlation with cortical and subcortical brain regions associated with executive function, attention, and the DMN, (2) RSFC in patients with GGE, when compared to healthy controls, was increased between paracingulate cortex and anterior, but not posterior, thalamus, and (3) GGE patients with uncontrolled seizures exhibited decreased cereballar RSFC. Significance Our findings in this large sample of patients with GGE (1) demonstrate an effect of interictal GSWDs on resting-state networks, (2) provide evidence that different thalamic nuclei may be affected differently by GGE, and (3) suggest that cerebellum is a modulator of ictogenic circuits. PMID:24447031

Sedation of Patients With Disorders of Consciousness During Neuroimaging: Effects on Resting State Functional Brain Connectivity.

PubMed

Kirsch, Muriëlle; Guldenmund, Pieter; Ali Bahri, Mohamed; Demertzi, Athena; Baquero, Katherine; Heine, Lizette; Charland-Verville, Vanessa; Vanhaudenhuyse, Audrey; Bruno, Marie-Aurélie; Gosseries, Olivia; Di Perri, Carol; Ziegler, Erik; Brichant, Jean-François; Soddu, Andrea; Bonhomme, Vincent; Laureys, Steven

2017-02-01

To reduce head movement during resting state functional magnetic resonance imaging, post-coma patients with disorders of consciousness (DOC) are frequently sedated with propofol. However, little is known about the effects of this sedation on the brain connectivity patterns in the damaged brain essential for differential diagnosis. In this study, we aimed to assess these effects. Using resting state functional magnetic resonance imaging 3T data obtained over several years of scanning patients for diagnostic and research purposes, we employed a seed-based approach to examine resting state connectivity in higher-order (default mode, bilateral external control, and salience) and lower-order (auditory, sensorimotor, and visual) resting state networks and connectivity with the thalamus, in 20 healthy unsedated controls, 8 unsedated patients with DOC, and 8 patients with DOC sedated with propofol. The DOC groups were matched for age at onset, etiology, time spent in DOC, diagnosis, standardized behavioral assessment scores, movement intensities, and pattern of structural brain injury (as assessed with T1-based voxel-based morphometry). DOC were associated with severely impaired resting state network connectivity in all but the visual network. Thalamic connectivity to higher-order network regions was also reduced. Propofol administration to patients was associated with minor further decreases in thalamic and insular connectivity. Our findings indicate that connectivity decreases associated with propofol sedation, involving the thalamus and insula, are relatively small compared with those already caused by DOC-associated structural brain injury. Nonetheless, given the known importance of the thalamus in brain arousal, its disruption could well reflect the diminished movement obtained in these patients. However, more research is needed on this topic to fully address the research question.

Functional connectivity between somatosensory and motor brain areas predicts individual differences in motor learning by observing.

PubMed

McGregor, Heather R; Gribble, Paul L

2017-08-01

Action observation can facilitate the acquisition of novel motor skills; however, there is considerable individual variability in the extent to which observation promotes motor learning. Here we tested the hypothesis that individual differences in brain function or structure can predict subsequent observation-related gains in motor learning. Subjects underwent an anatomical MRI scan and resting-state fMRI scans to assess preobservation gray matter volume and preobservation resting-state functional connectivity (FC), respectively. On the following day, subjects observed a video of a tutor adapting her reaches to a novel force field. After observation, subjects performed reaches in a force field as a behavioral assessment of gains in motor learning resulting from observation. We found that individual differences in resting-state FC, but not gray matter volume, predicted postobservation gains in motor learning. Preobservation resting-state FC between left primary somatosensory cortex and bilateral dorsal premotor cortex, primary motor cortex, and primary somatosensory cortex and left superior parietal lobule was positively correlated with behavioral measures of postobservation motor learning. Sensory-motor resting-state FC can thus predict the extent to which observation will promote subsequent motor learning. NEW & NOTEWORTHY We show that individual differences in preobservation brain function can predict subsequent observation-related gains in motor learning. Preobservation resting-state functional connectivity within a sensory-motor network may be used as a biomarker for the extent to which observation promotes motor learning. This kind of information may be useful if observation is to be used as a way to boost neuroplasticity and sensory-motor recovery for patients undergoing rehabilitation for diseases that impair movement such as stroke. Copyright © 2017 the American Physiological Society.

Increased power spectral density in resting-state pain-related brain networks in fibromyalgia.

PubMed

Kim, Ji-Young; Kim, Seong-Ho; Seo, Jeehye; Kim, Sang-Hyon; Han, Seung Woo; Nam, Eon Jeong; Kim, Seong-Kyu; Lee, Hui Joong; Lee, Seung-Jae; Kim, Yang-Tae; Chang, Yongmin

2013-09-01

Fibromyalgia (FM), characterized by chronic widespread pain, is known to be associated with heightened responses to painful stimuli and atypical resting-state functional connectivity among pain-related regions of the brain. Previous studies of FM using resting-state functional magnetic resonance imaging (rs-fMRI) have focused on intrinsic functional connectivity, which maps the spatial distribution of temporal correlations among spontaneous low-frequency fluctuation in functional MRI (fMRI) resting-state data. In the current study, using rs-fMRI data in the frequency domain, we investigated the possible alteration of power spectral density (PSD) of low-frequency fluctuation in brain regions associated with central pain processing in patients with FM. rsfMRI data were obtained from 19 patients with FM and 20 age-matched healthy female control subjects. For each subject, the PSDs for each brain region identified from functional connectivity maps were computed for the frequency band of 0.01 to 0.25 Hz. For each group, the average PSD was determined for each brain region and a 2-sample t test was performed to determine the difference in power between the 2 groups. According to the results, patients with FM exhibited significantly increased frequency power in the primary somatosensory cortex (S1), supplementary motor area (SMA), dorsolateral prefrontal cortex, and amygdala. In patients with FM, the increase in PSD did not show an association with depression or anxiety. Therefore, our findings of atypical increased frequency power during the resting state in pain-related brain regions may implicate the enhanced resting-state baseline neural activity in several brain regions associated with pain processing in FM. Copyright © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Snack food as a modulator of human resting-state functional connectivity.

PubMed

Mendez-Torrijos, Andrea; Kreitz, Silke; Ivan, Claudiu; Konerth, Laura; Rösch, Julie; Pischetsrieder, Monika; Moll, Gunther; Kratz, Oliver; Dörfler, Arnd; Horndasch, Stefanie; Hess, Andreas

2018-04-04

To elucidate the mechanisms of how snack foods may induce non-homeostatic food intake, we used resting state functional magnetic resonance imaging (fMRI), as resting state networks can individually adapt to experience after short time exposures. In addition, we used graph theoretical analysis together with machine learning techniques (support vector machine) to identifying biomarkers that can categorize between high-caloric (potato chips) vs. low-caloric (zucchini) food stimulation. Seventeen healthy human subjects with body mass index (BMI) 19 to 27 underwent 2 different fMRI sessions where an initial resting state scan was acquired, followed by visual presentation of different images of potato chips and zucchini. There was then a 5-minute pause to ingest food (day 1=potato chips, day 3=zucchini), followed by a second resting state scan. fMRI data were further analyzed using graph theory analysis and support vector machine techniques. Potato chips vs. zucchini stimulation led to significant connectivity changes. The support vector machine was able to accurately categorize the 2 types of food stimuli with 100% accuracy. Visual, auditory, and somatosensory structures, as well as thalamus, insula, and basal ganglia were found to be important for food classification. After potato chips consumption, the BMI was associated with the path length and degree in nucleus accumbens, middle temporal gyrus, and thalamus. The results suggest that high vs. low caloric food stimulation in healthy individuals can induce significant changes in resting state networks. These changes can be detected using graph theory measures in conjunction with support vector machine. Additionally, we found that the BMI affects the response of the nucleus accumbens when high caloric food is consumed.

Longitudinal Changes of Resting-State Functional Connectivity during Motor Recovery after Stroke

PubMed Central

Park, Chang-hyun; Chang, Won Hyuk; Ohn, Suk Hoon; Kim, Sung Tae; Bang, Oh Young; Pascual-Leone, Alvaro; Kim, Yun-Hee

2013-01-01

Background and Purpose Functional magnetic resonance imaging (fMRI) studies could provide crucial information on the neural mechanisms of motor recovery in stroke patients. Resting-state fMRI is applicable to stroke patients who are not capable of proper performance of the motor task. In this study, we explored neural correlates of motor recovery in stroke patients by investigating longitudinal changes in resting-state functional connectivity of the ipsilesional primary motor cortex (M1). Methods A longitudinal observational study using repeated fMRI experiments was conducted in 12 patients with stroke. Resting-state fMRI data were acquired four times over a period of 6 months. Patients participated in the first session of fMRI shortly after onset, and thereafter in subsequent sessions at 1, 3, and 6 months after onset. Resting-state functional connectivity of the ipsilesional M1 was assessed and compared with that of healthy subjects. Results Compared with healthy subjects, patients demonstrated higher functional connectivity with the ipsilesional frontal and parietal cortices, bilateral thalamus, and cerebellum. Instead, functional connectivity with the contralesional M1 and occipital cortex were decreased in stroke patients. Functional connectivity between the ipsilesional and contralesional M1 showed the most asymmetry at 1 month after onset to the ipsilesional side. Functional connectivity of the ipsilesional M1 with the contralesional thalamus, supplementary motor area, and middle frontal gyrus at onset was positively correlated with motor recovery at 6 months after stroke. Conclusions Resting-state fMRI elicited distinctive but comparable results with previous task-based fMRI, presenting complementary and practical values for use in the study of stroke patients. PMID:21441147

Correcting for Blood Arrival Time in Global Mean Regression Enhances Functional Connectivity Analysis of Resting State fMRI-BOLD Signals.

PubMed

Erdoğan, Sinem B; Tong, Yunjie; Hocke, Lia M; Lindsey, Kimberly P; deB Frederick, Blaise

2016-01-01

Resting state functional connectivity analysis is a widely used method for mapping intrinsic functional organization of the brain. Global signal regression (GSR) is commonly employed for removing systemic global variance from resting state BOLD-fMRI data; however, recent studies have demonstrated that GSR may introduce spurious negative correlations within and between functional networks, calling into question the meaning of anticorrelations reported between some networks. In the present study, we propose that global signal from resting state fMRI is composed primarily of systemic low frequency oscillations (sLFOs) that propagate with cerebral blood circulation throughout the brain. We introduce a novel systemic noise removal strategy for resting state fMRI data, "dynamic global signal regression" (dGSR), which applies a voxel-specific optimal time delay to the global signal prior to regression from voxel-wise time series. We test our hypothesis on two functional systems that are suggested to be intrinsically organized into anticorrelated networks: the default mode network (DMN) and task positive network (TPN). We evaluate the efficacy of dGSR and compare its performance with the conventional "static" global regression (sGSR) method in terms of (i) explaining systemic variance in the data and (ii) enhancing specificity and sensitivity of functional connectivity measures. dGSR increases the amount of BOLD signal variance being modeled and removed relative to sGSR while reducing spurious negative correlations introduced in reference regions by sGSR, and attenuating inflated positive connectivity measures. We conclude that incorporating time delay information for sLFOs into global noise removal strategies is of crucial importance for optimal noise removal from resting state functional connectivity maps.

Correlation between resting state fMRI total neuronal activity and PET metabolism in healthy controls and patients with disorders of consciousness.

PubMed

Soddu, Andrea; Gómez, Francisco; Heine, Lizette; Di Perri, Carol; Bahri, Mohamed Ali; Voss, Henning U; Bruno, Marie-Aurélie; Vanhaudenhuyse, Audrey; Phillips, Christophe; Demertzi, Athena; Chatelle, Camille; Schrouff, Jessica; Thibaut, Aurore; Charland-Verville, Vanessa; Noirhomme, Quentin; Salmon, Eric; Tshibanda, Jean-Flory Luaba; Schiff, Nicholas D; Laureys, Steven

2016-01-01

The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure 'resting state' cerebral metabolism. This technique made it possible to assess changes in metabolic activity in clinical applications, such as the study of severe brain injury and disorders of consciousness. We assessed the possibility of creating functional MRI activity maps, which could estimate the relative levels of activity in FDG-PET cerebral metabolic maps. If no metabolic absolute measures can be extracted, our approach may still be of clinical use in centers without access to FDG-PET. It also overcomes the problem of recognizing individual networks of independent component selection in functional magnetic resonance imaging (fMRI) resting state analysis. We extracted resting state fMRI functional connectivity maps using independent component analysis and combined only components of neuronal origin. To assess neuronality of components a classification based on support vector machine (SVM) was used. We compared the generated maps with the FDG-PET maps in 16 healthy controls, 11 vegetative state/unresponsive wakefulness syndrome patients and four locked-in patients. The results show a significant similarity with ρ = 0.75 ± 0.05 for healthy controls and ρ = 0.58 ± 0.09 for vegetative state/unresponsive wakefulness syndrome patients between the FDG-PET and the fMRI based maps. FDG-PET, fMRI neuronal maps, and the conjunction analysis show decreases in frontoparietal and medial regions in vegetative patients with respect to controls. Subsequent analysis in locked-in syndrome patients produced also consistent maps with healthy controls. The constructed resting state fMRI functional connectivity map points toward the possibility for fMRI resting state to estimate relative levels of activity in a metabolic map.

Spectral power and functional connectivity changes during mindfulness meditation with eyes open: A magnetoencephalography (MEG) study in long-term meditators.

PubMed

Wong, W P; Camfield, D A; Woods, W; Sarris, J; Pipingas, A

2015-10-01

Whilst a number of previous studies have been conducted in order to investigate functional brain changes associated with eyes-closed meditation techniques, there is a relative scarcity in the literature with regards to changes occurring during eyes-open meditation. The current project used magnetoencephalography (MEG) to investigate differences in spectral power and functional connectivity between 11 long-term mindfulness meditators (LTMMs) with >5 years of experience and 12 meditation-naïve control participants both during baseline eyes-open rest and eyes-open open-monitoring (OM) mindfulness meditation. During resting with eyes-open, prior to meditating, greater mean alpha power was observed for LTMMs in comparison to controls. However, during the course of OM meditation, a significantly greater increase in theta power was observed over a broad fronto-centro-parietal region for control participants in comparison to LTMMs. In contrast, whole-head mean connectivity was found to be significantly greater for long-term meditators in comparison to controls in the theta band both during rest as well as during meditation. Additionally, mean connectivity was significantly lower for long-term meditators in the low gamma band during rest and significantly lower in both low and high gamma bands during meditation; and the variance of low-gamma connectivity scores for long-term meditators was significantly decreased compared to the control group. The current study provides important new information as to the trait functional changes in brain activity associated with long-term mindfulness meditation, as well as the state changes specifically associated with eyes-open open monitoring meditation techniques. Copyright © 2015 Elsevier B.V. All rights reserved.

Impact of Paint Color on Rest Period Climate Control Loads in Long-Haul Trucks: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lustbader, J.; Kreutzer, C.; Jeffers, M.

Cab climate conditioning is one of the primary reasons for operating the main engine in a long-haul truck during driver rest periods. In the United States, sleeper cab trucks use approximately 667 million gallons of fuel annually for rest period idling. The U.S. Department of Energy's National Renewable Energy Laboratory's (NREL) CoolCab Project works closely with industry to design efficient thermal management systems for long-haul trucks that minimize engine idling and fuel use while maintaining occupant comfort. Heat transfer to the vehicle interior from opaque exterior surfaces is one of the major heat pathways that contribute to air conditioning loadsmore » during long-haul truck daytime rest period idling. To quantify the impact of paint color and the opportunity for advanced paints, NREL collaborated with Volvo Group North America, PPG Industries, and Dometic Environmental Corporation. Initial screening simulations using CoolCalc, NREL's rapid HVAC load estimation tool, showed promising air-conditioning load reductions due to paint color selection. Tests conducted at NREL's Vehicle Testing and Integration Facility using long-haul truck cab sections, 'test bucks,' showed a 31.1% of maximum possible reduction in rise over ambient temperature and a 20.8% reduction in daily electric air conditioning energy use by switching from black to white paint. Additionally, changing from blue to an advanced color-matched solar reflective blue paint resulted in a 7.3% reduction in daily electric air conditioning energy use for weather conditions tested in Colorado. National-level modeling results using weather data from major U.S. cities indicated that the increase in heating loads due to lighter paint colors is much smaller than the reduction in cooling loads.« less

Addiction Related Alteration in Resting-state Brain Connectivity

PubMed Central

Ma, Ning; Liu, Ying; Li, Nan; Wang, Chang-Xin; Zhang, Hao; Jiang, Xiao-Feng; Xu, Hu-Sheng; Fu, Xian-Ming; Hu, Xiaoping; Zhang, Da-Ren

2009-01-01

It is widely accepted that addictive drug use is related to abnormal functional organization in the user’s brain. The present study aimed to identify this type of abnormality within the brain networks implicated in addiction by resting-state functional connectivity measured with functional magnetic resonance imaging (fMRI). With fMRI data acquired during resting state from 14 chronic heroin users (12 of whom were being treated with methadone) and 13 non-addicted controls, we investigated the addiction related alteration in functional connectivity between the regions in the circuits implicated in addiction with seed-based correlation analysis. Compared with controls, chronic heroin users showed increased functional connectivity between nucleus accumbens and ventral/rostral anterior cingulate cortex (ACC), and orbital frontal cortex (OFC), between amygdala and OFC; and reduced functional connectivity between prefrontal cortex and OFC, and ACC. These observations of altered resting-state functional connectivity suggested abnormal functional organization in the addicted brain and may provide additional evidence supporting the theory of addiction that emphasizes enhanced salience value of a drug and its related cues but weakened cognitive control in the addictive state. PMID:19703568

An investigation into resting behavior in Asian elephants in UK zoos.

PubMed

Williams, Ellen; Bremner-Harrison, Samantha; Harvey, Naomi; Evison, Emma; Yon, Lisa

2015-01-01

Maintaining adequate welfare in captive elephants is challenging. Few studies have investigated overnight rest behavior in zoo elephants, yet time spent resting has been identified as a welfare indicator in some species. We investigated resting behavior in Asian elephants (Elephas maximus) in UK zoos, with the aim of identifying patterns or preferences in lying rest. Details of standing (SR) and lying (LR) rest behavior were identified by observing video footage of inside enclosures collected for 14 elephants (2 male, 12 female) housed at three UK zoos (Zoo A: 18 nights; Zoo B: 27 nights; Zoo C: 46 nights) from 16:00 to 08:30 (approximately). Elephants engaged in a mean of 58-337 min rest per night. Time of night affected mean duration of LR bouts (P < 0.001); longest bouts were observed between 22:01 and 06:00. Elephants showed a substrate preference when lying to rest; LR was not observed on concrete or tiled flooring. Where sand was available (to 11/14 elephants), all elephants engaged in LR on sand flooring. Only two elephants engaged in LR on rubber flooring (available to 7/14 elephants). Mean duration of rest bouts was greater when a conspecific was within two body lengths than when conspecifics were not (P < 0.01). Our study indicated that elephants show substrate preferences when choosing an area for rest and engage in more rest when conspecifics are in close proximity. The results of this study could be used as a basis for future studies investigating the link between rest and welfare in captive elephants. © 2015 Wiley Periodicals, Inc.

Modeling the safety impacts of driving hours and rest breaks on truck drivers considering time-dependent covariates.

PubMed

Chen, Chen; Xie, Yuanchang

2014-12-01

Driving hours and rest breaks are closely related to driver fatigue, which is a major contributor to truck crashes. This study investigates the effects of driving hours and rest breaks on commercial truck driver safety. A discrete-time logistic regression model is used to evaluate the crash odds ratios of driving hours and rest breaks. Driving time is divided into 11 one hour intervals. These intervals and rest breaks are modeled as dummy variables. In addition, a Cox proportional hazards regression model with time-dependent covariates is used to assess the transient effects of rest breaks, which consists of a fixed effect and a variable effect. Data collected from two national truckload carriers in 2009 and 2010 are used. The discrete-time logistic regression result indicates that only the crash odds ratio of the 11th driving hour is statistically significant. Taking one, two, and three rest breaks can reduce drivers' crash odds by 68%, 83%, and 85%, respectively, compared to drivers who did not take any rest breaks. The Cox regression result shows clear transient effects for rest breaks. It also suggests that drivers may need some time to adjust themselves to normal driving tasks after a rest break. Overall, the third rest break's safety benefit is very limited based on the results of both models. The findings of this research can help policy makers better understand the impact of driving time and rest breaks and develop more effective rules to improve commercial truck safety. Copyright © 2014 National Safety Council and Elsevier Ltd. All rights reserved.

A Pilot Computer-Aided Design and Manufacturing Curriculum that Promotes Engineering

NASA Technical Reports Server (NTRS)

2002-01-01

Elizabeth City State University (ECSU) is located in a community that is mostly rural in nature. The area is economically deprived when compared to the rest of the state. Many businesses lack the computerized equipment and skills needed to propel upward in today's technologically advanced society. This project will close the ever-widening gap between advantaged and disadvantaged workers as well as increase their participation with industry, NASA and/or other governmental agencies. Everyone recognizes computer technology as the catalyst for advances in design, prototyping, and manufacturing or the art of machining. Unprecedented quality control and cost-efficiency improvements are recognized through the use of computer technology. This technology has changed the manufacturing industry with advanced high-tech capabilities needed by NASA. With the ever-widening digital divide, we must continue to provide computer technology to those who are socio-economically disadvantaged.

Resting-state brain networks revealed by granger causal connectivity in frogs.

PubMed

Xue, Fei; Fang, Guangzhan; Yue, Xizi; Zhao, Ermi; Brauth, Steven E; Tang, Yezhong

2016-10-15

Resting-state networks (RSNs) refer to the spontaneous brain activity generated under resting conditions, which maintain the dynamic connectivity of functional brain networks for automatic perception or higher order cognitive functions. Here, Granger causal connectivity analysis (GCCA) was used to explore brain RSNs in the music frog (Babina daunchina) during different behavioral activity phases. The results reveal that a causal network in the frog brain can be identified during the resting state which reflects both brain lateralization and sexual dimorphism. Specifically (1) ascending causal connections from the left mesencephalon to both sides of the telencephalon are significantly higher than those from the right mesencephalon, while the right telencephalon gives rise to the strongest efferent projections among all brain regions; (2) causal connections from the left mesencephalon in females are significantly higher than those in males and (3) these connections are similar during both the high and low behavioral activity phases in this species although almost all electroencephalograph (EEG) spectral bands showed higher power in the high activity phase for all nodes. The functional features of this network match important characteristics of auditory perception in this species. Thus we propose that this causal network maintains auditory perception during the resting state for unexpected auditory inputs as resting-state networks do in other species. These results are also consistent with the idea that females are more sensitive to auditory stimuli than males during the reproductive season. In addition, these results imply that even when not behaviorally active, the frogs remain vigilant for detecting external stimuli. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Abnormal resting-state brain activities in patients with first-episode obsessive-compulsive disorder

PubMed Central

Niu, Qihui; Yang, Lei; Song, Xueqin; Chu, Congying; Liu, Hao; Zhang, Lifang; Li, Yan; Zhang, Xiang; Cheng, Jingliang; Li, Youhui

2017-01-01

Objective This paper attempts to explore the brain activity of patients with obsessive-compulsive disorder (OCD) and its correlation with the disease at resting duration in patients with first-episode OCD, providing a forceful imaging basis for clinic diagnosis and pathogenesis of OCD. Methods Twenty-six patients with first-episode OCD and 25 healthy controls (HC group; matched for age, sex, and education level) underwent functional magnetic resonance imaging (fMRI) scanning at resting state. Statistical parametric mapping 8, data processing assistant for resting-state fMRI analysis toolkit, and resting state fMRI data analysis toolkit packages were used to process the fMRI data on Matlab 2012a platform, and the difference of regional homogeneity (ReHo) values between the OCD group and HC group was detected with independent two-sample t-test. With age as a concomitant variable, the Pearson correlation analysis was adopted to study the correlation between the disease duration and ReHo value of whole brain. Results Compared with HC group, the ReHo values in OCD group were decreased in brain regions, including left thalamus, right thalamus, right paracentral lobule, right postcentral gyrus, and the ReHo value was increased in the left angular gyrus region. There was a negative correlation between disease duration and ReHo value in the bilateral orbitofrontal cortex (OFC). Conclusion OCD is a multifactorial disease generally caused by abnormal activities of many brain regions at resting state. Worse brain activity of the OFC is related to the OCD duration, which provides a new insight to the pathogenesis of OCD. PMID:28243104

How restful is it with all that noise? Comparison of Interleaved silent steady state (ISSS) and conventional imaging in resting-state fMRI.

PubMed

Andoh, J; Ferreira, M; Leppert, I R; Matsushita, R; Pike, B; Zatorre, R J

2017-02-15

Resting-state fMRI studies have become very important in cognitive neuroscience because they are able to identify BOLD fluctuations in brain circuits involved in motor, cognitive, or perceptual processes without the use of an explicit task. Such approaches have been fruitful when applied to various disordered populations, or to children or the elderly. However, insufficient attention has been paid to the consequences of the loud acoustic scanner noise associated with conventional fMRI acquisition, which could be an important confounding factor affecting auditory and/or cognitive networks in resting-state fMRI. Several approaches have been developed to mitigate the effects of acoustic noise on fMRI signals, including sparse sampling protocols and interleaved silent steady state (ISSS) acquisition methods, the latter being used only for task-based fMRI. Here, we developed an ISSS protocol for resting-state fMRI (rs-ISSS) consisting of rapid acquisition of a set of echo planar imaging volumes following each silent period, during which the steady state longitudinal magnetization was maintained with a train of relatively silent slice-selective excitation pulses. We evaluated the test-retest reliability of intensity and spatial extent of connectivity networks of fMRI BOLD signal across three different days for rs-ISSS and compared it with a standard resting-state fMRI (rs-STD). We also compared the strength and distribution of connectivity networks between rs-ISSS and rs-STD. We found that both rs-ISSS and rs-STD showed high reproducibility of fMRI signal across days. In addition, rs-ISSS showed a more robust pattern of functional connectivity within the somatosensory and motor networks, as well as an auditory network compared with rs-STD. An increased connectivity between the default mode network and the language network and with the anterior cingulate cortex (ACC) network was also found for rs-ISSS compared with rs-STD. Finally, region of interest analysis showed higher interhemispheric connectivity in Heschl's gyri in rs-ISSS compared with rs-STD, with lower variability across days. The present findings suggest that rs-ISSS may be advantageous for detecting network connectivity in a less noisy environment, and that resting-state studies carried out with standard scanning protocols should consider the potential effects of loud noise on the measured networks. Copyright © 2017 Elsevier Inc. All rights reserved.

Global and system-specific resting-state fMRI fluctuations are uncorrelated: principal component analysis reveals anti-correlated networks.

PubMed

Carbonell, Felix; Bellec, Pierre; Shmuel, Amir

2011-01-01

The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)-based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed robust anti-correlations between resting-state fluctuations in the default-mode and the task-positive networks. We conclude that resting-state global fluctuations and network-specific fluctuations are uncorrelated, supporting a Resting-State Linear-Additive Model. In addition, we conclude that the network-specific resting-state fluctuations of the default-mode and task-positive networks show artifact-free anti-correlations.

Anxiety Modulates Insula Recruitment in Resting-State Functional Magnetic Resonance Imaging in Youth and Adults

PubMed Central

Gotlib, Ian H.; Thompson, Paul M.; Thomason, Moriah E.

2011-01-01

Abstract Research on resting-state functional connectivity reveals intrinsically connected networks in the brain that are largely consistent across the general population. However, there are individual differences in these networks that have not been elucidated. Here, we measured the influence of naturally occurring mood on functional connectivity. In particular, we examined the association between self-reported levels of anxiety and connectivity in the default mode network (DMN). Healthy youth (n=43; ages 10–18) and adult participants (n=24, ages 19–59) completed a 6-min resting-state functional magnetic resonance imaging scan, then immediately completed questionnaires assessing their mood and thoughts during the scan. Regression analyses conducted separately for the youth and adult samples revealed brain regions in which increases in connectivity differentially corresponded to higher anxiety in each group. In one area, the left insular cortex, both groups showed similar increased connectivity to the DMN (youth: -30, 26, 14; adults: -33, 12, 14) with increased anxiety. State anxiety assessed during scanning was not correlated with trait anxiety, so our results likely reflect state levels of anxiety. To our knowledge, this is the first study to relate naturally occurring mood to resting state connectivity. PMID:22433052

A close examination of under-actuated attitude control subsystem design for future satellite missions' life extension

NASA Astrophysics Data System (ADS)

Lam, Quang M.; Barkana, Itzhak

2014-12-01

Satellite mission life, maintained and prolonged beyond its typical norm of their expectancy, are primarily dictated by the state of health of its Reaction Wheel Assembly (RWA), especially for commercial GEO satellites since torquer bars are no longer applicable while thruster assistant is unacceptable due to pointing accuracy impact during jet firing. The RWA is the primary set of actuators (as compared to thrusters for orbit maintenance and maneuvering) mainly responsible for the satellite mission for accurately and precisely pointing its payloads to the right targets to conduct its mission operations. The RWA consisting of either a set of four in pyramid or three in orthogonal is the primary set of actuators to allow the satellite to achieve accurate and precise pointing of the satellite payloads towards the desired targets. Future space missions will be required to achieve much longer lives and are currently perceived by the GEO satellite community as an "expected norm" of 20 years or longer. Driven by customers' demands/goals and competitive market have challenged Attitude Control Subsystems (ACS) engineers to develop better ACS algorithms to address such an emerging need. There are two main directions to design satellite's under-actuated control subsystem: (1) Attitude Feedback with Zero Momentum Principle and (2) Attitude Control by Angular Velocity Tracking via Small Time Local Controllability concept. Successful applications of these control laws have been largely demonstrated via simulation for the rest to rest case. Limited accuracy and oscillatory behaviors are observed in three axes for non-zero wheel momentum while realistic loss of a wheel scenario (i.e., fully actuated to under-actuated) has not been closely examined! This study revisits the under-actuated control design with detailed set ups of multiple scenarios reflecting real life operating conditions which have put current under-actuated control laws mentioned earlier into a re-evaluation mode since rest to rest case is not adequate to truly represent an on orbit failure of a single wheel. The study is intended to facilitate the ACS community to further develop a more practical under-actuated control law and present a path to extend these current thinking to address a more realistic reconfigurable ACS subject to a dynamic transition from a 3 RWs mode to 2 RWs mode.

Resting-state blood oxygen level-dependent functional magnetic resonance imaging for presurgical planning.

PubMed

Kamran, Mudassar; Hacker, Carl D; Allen, Monica G; Mitchell, Timothy J; Leuthardt, Eric C; Snyder, Abraham Z; Shimony, Joshua S

2014-11-01

Resting-state functional MR imaging (rsfMR imaging) measures spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal and can be used to elucidate the brain's functional organization. It is used to simultaneously assess multiple distributed resting-state networks. Unlike task-based functional MR imaging, rsfMR imaging does not require task performance. This article presents a brief introduction of rsfMR imaging processing methods followed by a detailed discussion on the use of rsfMR imaging in presurgical planning. Example cases are provided to highlight the strengths and limitations of the technique. Copyright © 2014 Elsevier Inc. All rights reserved.

The wandering mood: psychological and neural determinants of rest-related negative affect.

PubMed

Gruberger, Michal; Maron-Katz, Adi; Sharon, Haggai; Hendler, Talma; Ben-Simon, Eti

2013-01-01

Rest related negative affect (RRNA) has gained scientific interest in the past decade. However, it is mostly studied within the context of mind-wandering (MW), and the relevance of other psychological and neural aspects of the resting state to its' occurrence has never been studied. Several indications associate RRNA with internally directed attention, yet the nature of this relation remains largely unknown. Moreover, the role of neural networks associated with rest related phenomenology - the default mode (DMN), executive (EXE), and salience (SAL) networks, has not been studied in this context. To this end, we explored two 5 (baseline) and 15-minute resting-state simultaneous fMRI-EEG scans of 29 participants. As vigilance has been shown to affect attention, and thus its availability for inward allocation, EEG-based vigilance levels were computed for each participant. Questionnaires for affective assessment were administered before and after scans, and retrospective reports of MW were additionally collected. Results revealed increased negative affect following rest, but only among participants who retained high vigilance levels. Among low-vigilance participants, changes in negative affect were negligible, despite reports of MW occurrence in both groups. In addition, in the high-vigilance group only, a significant increase in functional connectivity (FC) levels was found between the DMN-related ventral anterior cingulate cortex (ACC), associated with emotional processing, and the EXE-related dorsal ACC, associated with monitoring of self and other's behavior. These heightened FC levels further correlated with reported negative affect among this group. Taken together, these results demonstrate that, rather than an unavoidable outcome of the resting state, RRNA depends on internal allocation of attention at rest. Results are discussed in terms of two rest-related possible scenarios which defer in mental and neural processing, and subsequently, in the occurrence of RRNA.

Behavioral Interpretations of Intrinsic Connectivity Networks

ERIC Educational Resources Information Center

Laird, Angela R.; Fox, P. Mickle; Eickhoff, Simon B.; Turner, Jessica A.; Ray, Kimberly L.; McKay, D. Reese; Glahn, David C.; Beckmann, Christian F.; Smith, Stephen M.; Fox, Peter T.

2011-01-01

An increasingly large number of neuroimaging studies have investigated functionally connected networks during rest, providing insight into human brain architecture. Assessment of the functional qualities of resting state networks has been limited by the task-independent state, which results in an inability to relate these networks to specific…

Microstates in resting-state EEG: current status and future directions.

PubMed

Khanna, Arjun; Pascual-Leone, Alvaro; Michel, Christoph M; Farzan, Faranak

2015-02-01

Electroencephalography (EEG) is a powerful method of studying the electrophysiology of the brain with high temporal resolution. Several analytical approaches to extract information from the EEG signal have been proposed. One method, termed microstate analysis, considers the multichannel EEG recording as a series of quasi-stable "microstates" that are each characterized by a unique topography of electric potentials over the entire channel array. Because this technique simultaneously considers signals recorded from all areas of the cortex, it is capable of assessing the function of large-scale brain networks whose disruption is associated with several neuropsychiatric disorders. In this review, we first introduce the method of EEG microstate analysis. We then review studies that have discovered significant changes in the resting-state microstate series in a variety of neuropsychiatric disorders and behavioral states. We discuss the potential utility of this method in detecting neurophysiological impairments in disease and monitoring neurophysiological changes in response to an intervention. Finally, we discuss how the resting-state microstate series may reflect rapid switching among neural networks while the brain is at rest, which could represent activity of resting-state networks described by other neuroimaging modalities. We conclude by commenting on the current and future status of microstate analysis, and suggest that EEG microstates represent a promising neurophysiological tool for understanding and assessing brain network dynamics on a millisecond timescale in health and disease. Copyright © 2014 Elsevier Ltd. All rights reserved.

Microstates in Resting-State EEG: Current Status and Future Directions

PubMed Central

Khanna, Arjun; Pascual-Leone, Alvaro; Michel, Christoph M.; Farzan, Faranak

2015-01-01

Electroencephalography (EEG) is a powerful method of studying the electrophysiology of the brain with high temporal resolution. Several analytical approaches to extract information from the EEG signal have been proposed. One method, termed microstate analysis, considers the multichannel EEG recording as a series of quasi-stable “microstates” that are each characterized by a unique topography of electric potentials over the entire channel array. Because this technique simultaneously considers signals recorded from all areas of the cortex, it is capable of assessing the function of large-scale brain networks whose disruption is associated with several neuropsychiatric disorders. In this review, we first introduce the method of EEG microstate analysis. We then review studies that have discovered significant changes in the resting-state microstate series in a variety of neuropsychiatric disorders and behavioral states. We discuss the potential utility of this method in detecting neurophysiological impairments in disease and monitoring neurophysiological changes in response to an intervention. Finally, we discuss how the resting-state microstate series may reflect rapid switching among neural networks while the brain is at rest, which could represent activity of resting-state networks described by other neuroimaging modalities. We conclude by commenting on the current and future status of microstate analysis, and suggest that EEG microstates represent a promising neurophysiological tool for understanding and assessing brain network dynamics on a millisecond timescale in health and disease. PMID:25526823

The development of regional functional connectivity in preterm infants into early childhood.

PubMed

Lee, Wayne; Morgan, Benjamin R; Shroff, Manohar M; Sled, John G; Taylor, Margot J

2013-09-01

Resting state networks are proposed to reflect the neuronal connectivity that underlies cognitive processes. Consequently, abnormal behaviour of these networks due to disease or altered development may predict poor cognitive outcome. To understand how very preterm birth may affect the development of resting state connectivity, we followed a cohort of very preterm-born infants from birth through to 4 years of age using resting state functional MRI. From a larger longitudinal cohort of infants born very preterm (<32 weeks gestational age), 36 at birth, 30 at term, 21 two-year and 22 four-year resting state fMRI datasets were acquired. Using seed-based connectivity analyses with seeds in the anterior cingulate cortex, posterior cingulate cortex, left and right motor-hand regions and left and right temporal lobes, we investigated local and inter-region connectivity as a function of group and age. We found strong local connectivity during the preterm period, which matured into inter-hemispheric and preliminary default-mode network correlations by 4 years of age. This development is comparable to the resting state networks found in term-born infants of equivalent age. The results of this study suggest that differences in developmental trajectory between preterm-born and term-born infants are small and, if present, would require a large sample from both populations to be detected.

Resting-State fMRI Activity Predicts Unsupervised Learning and Memory in an Immersive Virtual Reality Environment

PubMed Central

Wong, Chi Wah; Olafsson, Valur; Plank, Markus; Snider, Joseph; Halgren, Eric; Poizner, Howard; Liu, Thomas T.

2014-01-01

In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI) measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment. PMID:25286145

Estimating repetitive spatiotemporal patterns from resting-state brain activity data.

PubMed

Takeda, Yusuke; Hiroe, Nobuo; Yamashita, Okito; Sato, Masa-Aki

2016-06-01

Repetitive spatiotemporal patterns in spontaneous brain activities have been widely examined in non-human studies. These studies have reported that such patterns reflect past experiences embedded in neural circuits. In human magnetoencephalography (MEG) and electroencephalography (EEG) studies, however, spatiotemporal patterns in resting-state brain activities have not been extensively examined. This is because estimating spatiotemporal patterns from resting-state MEG/EEG data is difficult due to their unknown onsets. Here, we propose a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data, including MEG/EEG. Without the information of onsets, the proposed method can estimate several spatiotemporal patterns, even if they are overlapping. We verified the performance of the method by detailed simulation tests. Furthermore, we examined whether the proposed method could estimate the visual evoked magnetic fields (VEFs) without using stimulus onset information. The proposed method successfully detected the stimulus onsets and estimated the VEFs, implying the applicability of this method to real MEG data. The proposed method was applied to resting-state functional magnetic resonance imaging (fMRI) data and MEG data. The results revealed informative spatiotemporal patterns representing consecutive brain activities that dynamically change with time. Using this method, it is possible to reveal discrete events spontaneously occurring in our brains, such as memory retrieval. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Cortical connective field estimates from resting state fMRI activity.

PubMed

Gravel, Nicolás; Harvey, Ben; Nordhjem, Barbara; Haak, Koen V; Dumoulin, Serge O; Renken, Remco; Curčić-Blake, Branislava; Cornelissen, Frans W

2014-01-01

One way to study connectivity in visual cortical areas is by examining spontaneous neural activity. In the absence of visual input, such activity remains shaped by the underlying neural architecture and, presumably, may still reflect visuotopic organization. Here, we applied population connective field (CF) modeling to estimate the spatial profile of functional connectivity in the early visual cortex during resting state functional magnetic resonance imaging (RS-fMRI). This model-based analysis estimates the spatial integration between blood-oxygen level dependent (BOLD) signals in distinct cortical visual field maps using fMRI. Just as population receptive field (pRF) mapping predicts the collective neural activity in a voxel as a function of response selectivity to stimulus position in visual space, CF modeling predicts the activity of voxels in one visual area as a function of the aggregate activity in voxels in another visual area. In combination with pRF mapping, CF locations on the cortical surface can be interpreted in visual space, thus enabling reconstruction of visuotopic maps from resting state data. We demonstrate that V1 ➤ V2 and V1 ➤ V3 CF maps estimated from resting state fMRI data show visuotopic organization. Therefore, we conclude that-despite some variability in CF estimates between RS scans-neural properties such as CF maps and CF size can be derived from resting state data.

Resting state neural networks for visual Chinese word processing in Chinese adults and children.

PubMed

Li, Ling; Liu, Jiangang; Chen, Feiyan; Feng, Lu; Li, Hong; Tian, Jie; Lee, Kang

2013-07-01

This study examined the resting state neural networks for visual Chinese word processing in Chinese children and adults. Both the functional connectivity (FC) and amplitude of low frequency fluctuation (ALFF) approaches were used to analyze the fMRI data collected when Chinese participants were not engaged in any specific explicit tasks. We correlated time series extracted from the visual word form area (VWFA) with those in other regions in the brain. We also performed ALFF analysis in the resting state FC networks. The FC results revealed that, regarding the functionally connected brain regions, there exist similar intrinsically organized resting state networks for visual Chinese word processing in adults and children, suggesting that such networks may already be functional after 3-4 years of informal exposure to reading plus 3-4 years formal schooling. The ALFF results revealed that children appear to recruit more neural resources than adults in generally reading-irrelevant brain regions. Differences between child and adult ALFF results suggest that children's intrinsic word processing network during the resting state, though similar in functional connectivity, is still undergoing development. Further exposure to visual words and experience with reading are needed for children to develop a mature intrinsic network for word processing. The developmental course of the intrinsically organized word processing network may parallel that of the explicit word processing network. Copyright © 2013 Elsevier Ltd. All rights reserved.

Finer parcellation reveals detailed correlational structure of resting-state fMRI signals.

PubMed

Dornas, João V; Braun, Jochen

2018-01-15

Even in resting state, the human brain generates functional signals (fMRI) with complex correlational structure. To simplify this structure, it is common to parcellate a standard brain into coarse chunks. Finer parcellations are considered less reproducible and informative, due to anatomical and functional variability of individual brains. Grouping signals with similar local correlation profiles, restricted to each anatomical region (Tzourio-Mazoyer et al., 2002), we divide a standard brain into 758 'functional clusters' averaging 1.7cm 3 gray matter volume ('MD758' parcellation). We compare 758 'spatial clusters' of similar size ('S758'). 'Functional clusters' are spatially contiguous and cluster quality (integration and segregation of temporal variance) is far superior to 'spatial clusters', comparable to multi-modal parcellations of half the resolution (Craddock et al., 2012; Glasser et al., 2016). Moreover, 'functional clusters' capture many long-range functional correlations, with O(10 5 ) reproducibly correlated cluster pairs in different anatomical regions. The pattern of functional correlations closely mirrors long-range anatomical connectivity established by fibre tracking. MD758 is comparable to coarser parcellations (Craddock et al., 2012; Glasser et al., 2016) in terms of cluster quality, correlational structure (54% relative mutual entropy vs 60% and 61%), and sparseness (35% significant pairwise correlations vs 36% and 44%). We describe and evaluate a simple path to finer functional parcellations of the human brain. Detailed correlational structure is surprisingly consistent between individuals, opening new possibilities for comparing functional correlations between cognitive conditions, states of health, or pharmacological interventions. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Changes in mood status and neurotic levels during a 20-day bed rest

NASA Astrophysics Data System (ADS)

Ishizaki, Yuko; Ishizaki, Tatsuro; Fukuoka, Hideoki; Kim, Chang-Sun; Fujita, Masayo; Maegawa, Yuko; Fujioka, Hiroshi; Katsura, Taisaku; Suzuki, Yoji; Gunji, Atsuaki

2002-04-01

This study evaluated changes of mood status and depressive and neurotic levels in nine young male subjects during a 20-day 6° head-down tilting bed rest and examined whether exercise training modified these changes. Participants were asked to complete psychometrical inventories on before, during, and after the bed rest experiment. Depressive and neurotic levels were enhanced during bed rest period according to the Japanese version of Zung's Self-rating Depression Scale and the Japanese version of the General Health Questionnaire. Mood state "vigor" was impaired and "confusion" was increased during bed rest and recumbent control periods compared to pre-bed rest and ambulatory control periods according to the Japanese version of Profiles of Mood State, whereas the mood "tension-anxiety", "depression-dejection", "anger-hostility" and "fatigue" were relatively stable during experiment. Isometric exercise training did not modify these results. Microgravity, along with confinement to bed and isolation from familiar environments, induced impairment of mental status.

Bound states of spin-half particles in a static gravitational field close to the black hole field

NASA Astrophysics Data System (ADS)

Spencer-Smith, A. F.; Gossel, G. H.; Berengut, J. C.; Flambaum, V. V.

2013-03-01

We consider the bound-state energy levels of a spin-1/2 fermion in the gravitational field of a near-black hole object. In the limit that the metric of the body becomes singular, all binding energies tend to the rest-mass energy (i.e. total energy approaches zero). We present calculations of the ground state energy for three specific interior metrics (Florides, Soffel and Schwarzschild) for which the spectrum collapses and becomes quasi-continuous in the singular metric limit. The lack of zero or negative energy states prior to this limit being reached prevents particle pair production occurring. Therefore, in contrast to the Coulomb case, no pairs are produced in the non-singular static metric. For the Florides and Soffel metrics the singularity occurs in the black hole limit, while for the Schwarzschild interior metric it corresponds to infinite pressure at the centre. The behaviour of the energy level spectrum is discussed in the context of the semi-classical approximation and using general properties of the metric.

Mapping white-matter functional organization at rest and during naturalistic visual perception.

PubMed

Marussich, Lauren; Lu, Kun-Han; Wen, Haiguang; Liu, Zhongming

2017-02-01

Despite the wide applications of functional magnetic resonance imaging (fMRI) to mapping brain activation and connectivity in cortical gray matter, it has rarely been utilized to study white-matter functions. In this study, we investigated the spatiotemporal characteristics of fMRI data within the white matter acquired from humans both in the resting state and while watching a naturalistic movie. By using independent component analysis and hierarchical clustering, resting-state fMRI data in the white matter were de-noised and decomposed into spatially independent components, which were further assembled into hierarchically organized axonal fiber bundles. Interestingly, such components were partly reorganized during natural vision. Relative to resting state, the visual task specifically induced a stronger degree of temporal coherence within the optic radiations, as well as significant correlations between the optic radiations and multiple cortical visual networks. Therefore, fMRI contains rich functional information about the activity and connectivity within white matter at rest and during tasks, challenging the conventional practice of taking white-matter signals as noise or artifacts. Copyright © 2016 Elsevier Inc. All rights reserved.

Disturbed resting state EEG synchronization in bipolar disorder: A graph-theoretic analysis☆

PubMed Central

Kim, Dae-Jin; Bolbecker, Amanda R.; Howell, Josselyn; Rass, Olga; Sporns, Olaf; Hetrick, William P.; Breier, Alan; O'Donnell, Brian F.

2013-01-01

Disruption of functional connectivity may be a key feature of bipolar disorder (BD) which reflects disturbances of synchronization and oscillations within brain networks. We investigated whether the resting electroencephalogram (EEG) in patients with BD showed altered synchronization or network properties. Resting-state EEG was recorded in 57 BD type-I patients and 87 healthy control subjects. Functional connectivity between pairs of EEG channels was measured using synchronization likelihood (SL) for 5 frequency bands (δ, θ, α, β, and γ). Graph-theoretic analysis was applied to SL over the electrode array to assess network properties. BD patients showed a decrease of mean synchronization in the alpha band, and the decreases were greatest in fronto-central and centro-parietal connections. In addition, the clustering coefficient and global efficiency were decreased in BD patients, whereas the characteristic path length increased. We also found that the normalized characteristic path length and small-worldness were significantly correlated with depression scores in BD patients. These results suggest that BD patients show impaired neural synchronization at rest and a disruption of resting-state functional connectivity. PMID:24179795

Task-related modulations of BOLD low-frequency fluctuations within the default mode network

NASA Astrophysics Data System (ADS)

Tommasin, Silvia; Mascali, Daniele; Gili, Tommaso; Eid Assan, Ibrahim; Moraschi, Marta; Fratini, Michela; Wise, Richard G.; Macaluso, Emiliano; Mangia, Silvia; Giove, Federico

2017-07-01

Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD) signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN), are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33±6 years, 8F/12M) the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the steady-state execution of a sustained working memory n-back task. We found that the steady state execution of such a task impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to steady-state task execution, can contribute to a better understanding of how brain networks rearrange themselves in response of a task.

Multi-scale integration and predictability in resting state brain activity

PubMed Central

Kolchinsky, Artemy; van den Heuvel, Martijn P.; Griffa, Alessandra; Hagmann, Patric; Rocha, Luis M.; Sporns, Olaf; Goñi, Joaquín

2014-01-01

The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales. PMID:25104933

BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

PubMed

Richiardi, Jonas; Altmann, Andre; Milazzo, Anna-Clare; Chang, Catie; Chakravarty, M Mallar; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Bromberg, Uli; Büchel, Christian; Conrod, Patricia; Fauth-Bühler, Mira; Flor, Herta; Frouin, Vincent; Gallinat, Jürgen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Lemaître, Hervé; Mann, Karl F; Martinot, Jean-Luc; Nees, Frauke; Paus, Tomáš; Pausova, Zdenka; Rietschel, Marcella; Robbins, Trevor W; Smolka, Michael N; Spanagel, Rainer; Ströhle, Andreas; Schumann, Gunter; Hawrylycz, Mike; Poline, Jean-Baptiste; Greicius, Michael D

2015-06-12

During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched for ion channels. Polymorphisms in this set of genes significantly affect resting-state functional connectivity in a large sample of healthy adolescents. Expression levels of these genes are also significantly associated with axonal connectivity in the mouse. The results provide convergent, multimodal evidence that resting-state functional networks correlate with the orchestrated activity of dozens of genes linked to ion channel activity and synaptic function. Copyright © 2015, American Association for the Advancement of Science.

TGF-beta(1) gene-race interactions for resting and exercise blood pressure in the HERITAGE Family Study.

PubMed

Rivera, M A; Echegaray, M; Rankinen, T; Pérusse, L; Rice, T; Gagnon, J; Leon, A S; Skinner, J S; Wilmore, J H; Rao, D C; Bouchard, C

2001-10-01

We examined the possible association between a transforming growth factor (TGF)-beta(1) gene polymorphism in codon 10 and blood pressure (BP) at rest, in acute response to exercise in the pretrained (sedentary) and trained states, as well as in its training response (Delta) to 20 wk of endurance exercise. Subjects were 257 black and 480 white, healthy sedentary normotensive subjects from the HERITAGE Family Study. The polymorphism was detected by polymerase chain reaction and digestion with the Msp A1 I endonuclease yielding a wild (leucine-10) and a mutant (proline-10) allele. Resting and exercise [50 W plus 60, 80, and 100% maximal oxygen consumption (VO(2)(max))] BP were determined before and after training. Significant (P < 0.05) race-genotype interactions were found for systolic (S) BP in both the sedentary and trained states. Among whites but not in blacks, the TGF-beta(1) genotypes were significantly (P < 0.05) associated with sedentary-state SBP at rest, at 50 W, and at 60 and 100% VO(2)(max)as well as with trained-state SBP at rest and at 80 and 100% VO(2)(max). The leucine-10 homozygotes had significantly (P < 0.05) lower SBP than proline-10 homozygotes. DeltaBP was not significantly associated with genotype. These results support the hypothesis of an association between the TGF-beta(1) marker in codon 10 and SBP at rest and in response to acute exercise in whites but not in blacks.

Auditory Hallucinations and the Brain's Resting-State Networks: Findings and Methodological Observations.

PubMed

Alderson-Day, Ben; Diederen, Kelly; Fernyhough, Charles; Ford, Judith M; Horga, Guillermo; Margulies, Daniel S; McCarthy-Jones, Simon; Northoff, Georg; Shine, James M; Turner, Jessica; van de Ven, Vincent; van Lutterveld, Remko; Waters, Flavie; Jardri, Renaud

2016-09-01

In recent years, there has been increasing interest in the potential for alterations to the brain's resting-state networks (RSNs) to explain various kinds of psychopathology. RSNs provide an intriguing new explanatory framework for hallucinations, which can occur in different modalities and population groups, but which remain poorly understood. This collaboration from the International Consortium on Hallucination Research (ICHR) reports on the evidence linking resting-state alterations to auditory hallucinations (AH) and provides a critical appraisal of the methodological approaches used in this area. In the report, we describe findings from resting connectivity fMRI in AH (in schizophrenia and nonclinical individuals) and compare them with findings from neurophysiological research, structural MRI, and research on visual hallucinations (VH). In AH, various studies show resting connectivity differences in left-hemisphere auditory and language regions, as well as atypical interaction of the default mode network and RSNs linked to cognitive control and salience. As the latter are also evident in studies of VH, this points to a domain-general mechanism for hallucinations alongside modality-specific changes to RSNs in different sensory regions. However, we also observed high methodological heterogeneity in the current literature, affecting the ability to make clear comparisons between studies. To address this, we provide some methodological recommendations and options for future research on the resting state and hallucinations. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

Frequency-specific electrophysiologic correlates of resting state fMRI networks.

PubMed

Hacker, Carl D; Snyder, Abraham Z; Pahwa, Mrinal; Corbetta, Maurizio; Leuthardt, Eric C

2017-04-01

Resting state functional MRI (R-fMRI) studies have shown that slow (<0.1Hz), intrinsic fluctuations of the blood oxygen level dependent (BOLD) signal are temporally correlated within hierarchically organized functional systems known as resting state networks (RSNs) (Doucet et al., 2011). Most broadly, this hierarchy exhibits a dichotomy between two opposed systems (Fox et al., 2005). One system engages with the environment and includes the visual, auditory, and sensorimotor (SMN) networks as well as the dorsal attention network (DAN), which controls spatial attention. The other system includes the default mode network (DMN) and the fronto-parietal control system (FPC), RSNs that instantiate episodic memory and executive control, respectively. Here, we test the hypothesis, based on the spectral specificity of electrophysiologic responses to perceptual vs. memory tasks (Klimesch, 1999; Pfurtscheller and Lopes da Silva, 1999), that these two large-scale neural systems also manifest frequency specificity in the resting state. We measured the spatial correspondence between electrocorticographic (ECoG) band-limited power (BLP) and R-fMRI correlation patterns in awake, resting, human subjects. Our results show that, while gamma BLP correspondence was common throughout the brain, theta (4-8Hz) BLP correspondence was stronger in the DMN and FPC, whereas alpha (8-12Hz) correspondence was stronger in the SMN and DAN. Thus, the human brain, at rest, exhibits frequency specific electrophysiology, respecting both the spectral structure of task responses and the hierarchical organization of RSNs. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Frequency-specific electrophysiologic correlates of resting state fMRI networks

PubMed Central

Hacker, Carl D.; Snyder, Abraham Z.; Pahwa, Mrinal; Corbetta, Maurizio; Leuthardt, Eric C.

2017-01-01

Resting state functional MRI (R-fMRI) studies have shown that slow (< 0.1 Hz), intrinsic fluctuations of the blood oxygen level dependent (BOLD) signal are temporally correlated within hierarchically organized functional systems known as resting state networks (RSNs) (Doucet et al., 2011). Most broadly, this hierarchy exhibits a dichotomy between two opposed systems (Fox et al., 2005). One system engages with the environment and includes the visual, auditory, and sensorimotor (SMN) networks as well as the dorsal attention network (DAN), which controls spatial attention. The other system includes the default mode network (DMN) and the fronto-parietal control system (FPC), RSNs that instantiate episodic memory and executive control, respectively. Here, we test the hypothesis, based on the spectral specificity of electrophysiologic responses to perceptual vs. memory tasks (Klimesch, 1999; Pfurtscheller and Lopes da Silva, 1999), that these two large-scale neural systems also manifest frequency specificity in the resting state. We measured the spatial correspondence between electrocorticographic (ECoG) band-limited power (BLP) and R-fMRI correlation patterns in awake, resting, human subjects. Our results show that, while gamma BLP correspondence was common throughout the brain, theta (4–8 Hz) BLP correspondence was stronger in the DMN and FPC, whereas alpha (8–12 Hz) correspondence was stronger in the SMN and DAN. Thus, the human brain, at rest, exhibits frequency specific electrophysiology, respecting both the spectral structure of task responses and the hierarchical organization of RSNs. PMID:28159686

Disrupted resting-state functional architecture of the brain after 45-day simulated microgravity

PubMed Central

Zhou, Yuan; Wang, Yun; Rao, Li-Lin; Liang, Zhu-Yuan; Chen, Xiao-Ping; Zheng, Dang; Tan, Cheng; Tian, Zhi-Qiang; Wang, Chun-Hui; Bai, Yan-Qiang; Chen, Shan-Guang; Li, Shu

2014-01-01

Long-term spaceflight induces both physiological and psychological changes in astronauts. To understand the neural mechanisms underlying these physiological and psychological changes, it is critical to investigate the effects of microgravity on the functional architecture of the brain. In this study, we used resting-state functional MRI (rs-fMRI) to study whether the functional architecture of the brain is altered after 45 days of −6° head-down tilt (HDT) bed rest, which is a reliable model for the simulation of microgravity. Sixteen healthy male volunteers underwent rs-fMRI scans before and after 45 days of −6° HDT bed rest. Specifically, we used a commonly employed graph-based measure of network organization, i.e., degree centrality (DC), to perform a full-brain exploration of the regions that were influenced by simulated microgravity. We subsequently examined the functional connectivities of these regions using a seed-based resting-state functional connectivity (RSFC) analysis. We found decreased DC in two regions, the left anterior insula (aINS) and the anterior part of the middle cingulate cortex (MCC; also called the dorsal anterior cingulate cortex in many studies), in the male volunteers after 45 days of −6° HDT bed rest. Furthermore, seed-based RSFC analyses revealed that a functional network anchored in the aINS and MCC was particularly influenced by simulated microgravity. These results provide evidence that simulated microgravity alters the resting-state functional architecture of the brains of males and suggest that the processing of salience information, which is primarily subserved by the aINS–MCC functional network, is particularly influenced by spaceflight. The current findings provide a new perspective for understanding the relationships between microgravity, cognitive function, autonomic neural function, and central neural activity. PMID:24926242

Reduced functional connectivity within and between ‘social’ resting state networks in autism spectrum conditions

PubMed Central

Stoyanova, Raliza S.; Baron-Cohen, Simon; Calder, Andrew J.

2013-01-01

Individuals with Autism Spectrum Conditions (ASC) have difficulties in social interaction and communication, which is reflected in hypoactivation of brain regions engaged in social processing, such as medial prefrontal cortex (mPFC), amygdala and insula. Resting state studies in ASC have identified reduced connectivity of the default mode network (DMN), which includes mPFC, suggesting that other resting state networks incorporating ‘social’ brain regions may also be abnormal. Using Seed-based Connectivity and Group Independent Component Analysis (ICA) approaches, we looked at resting functional connectivity in ASC between specific ‘social’ brain regions, as well as within and between whole networks incorporating these regions. We found reduced functional connectivity within the DMN in individuals with ASC, using both ICA and seed-based approaches. Two further networks identified by ICA, the salience network, incorporating the insula and a medial temporal lobe network, incorporating the amygdala, showed reduced inter-network connectivity. This was underlined by reduced seed-based connectivity between the insula and amygdala. The results demonstrate significantly reduced functional connectivity within and between resting state networks incorporating ‘social’ brain regions. This reduced connectivity may result in difficulties in communication and integration of information across these networks, which could contribute to the impaired processing of social signals in ASC. PMID:22563003

Decreased resting-state interhemispheric coordination in first-episode, drug-naive paranoid schizophrenia.

PubMed

Guo, Wenbin; Xiao, Changqing; Liu, Guiying; Wooderson, Sarah C; Zhang, Zhikun; Zhang, Jian; Yu, Liuyu; Liu, Jianrong

2014-01-03

Dysconnectivity hypothesis posits that schizophrenia relates to abnormalities in neuronal connectivity. However, little is known about the alterations of the interhemispheric resting-state functional connectivity (FC) in patients with paranoid schizophrenia. In the present study, we used a newly developed voxel-mirrored homotopic connectivity (VMHC) method to investigate the interhemispheric FC of the whole brain in patients with paranoid schizophrenia at rest. Forty-nine first-episode, drug-naive patients with paranoid schizophrenia and 50 age-, gender-, and education-matched healthy subjects underwent a resting-state functional magnetic resonance imaging (fMRI) scans. An automated VMHC approach was used to analyze the data. Patients exhibited lower VMHC than healthy subjects in the precuneus (PCu), the precentral gyrus, the superior temporal gyrus (STG), the middle occipital gyrus (MOG), and the fusiform gyrus/cerebellum lobule VI. No region showed greater VMHC in the patient group than in the control group. Significantly negative correlation was observed between VMHC in the precentral gyrus and the PANSS positive/total scores, and between VMHC in the STG and the PANSS positive/negative/total scores. Our results suggest that interhemispheric resting-state FC of VMHC is reduced in paranoid schizophrenia with clinical implications for psychiatric symptomatology thus further contribute to the dysconnectivity hypothesis of schizophrenia. © 2013.

Alterations in task-induced activity and resting-state fluctuations in visual and DMN areas revealed in long-term meditators.

PubMed

Berkovich-Ohana, Aviva; Harel, Michal; Hahamy, Avital; Arieli, Amos; Malach, Rafael

2016-07-15

Recently we proposed that the information contained in spontaneously emerging (resting-state) fluctuations may reflect individually unique neuro-cognitive traits. One prediction of this conjecture, termed the "spontaneous trait reactivation" (STR) hypothesis, is that resting-state activity patterns could be diagnostic of unique personalities, talents and life-styles of individuals. Long-term meditators could provide a unique experimental group to test this hypothesis. Using fMRI we found that, during resting-state, the amplitude of spontaneous fluctuations in long-term mindfulness meditation (MM) practitioners was enhanced in the visual cortex and significantly reduced in the DMN compared to naïve controls. Importantly, during a visual recognition memory task, the MM group showed heightened visual cortex responsivity, concomitant with weaker negative responses in Default Mode Network (DMN) areas. This effect was also reflected in the behavioral performance, where MM practitioners performed significantly faster than the control group. Thus, our results uncover opposite changes in the visual and default mode systems in long-term meditators which are revealed during both rest and task. The results support the STR hypothesis and extend it to the domain of local changes in the magnitude of the spontaneous fluctuations. Copyright © 2016 Elsevier Inc. All rights reserved.

16 CFR 1211.9 - Additional entrapment protection requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

... is capable of being moved open from any position other than the last (closing) 2 inches (50.8 mm) of travel, and (2) The door is capable of being moved to the 2-inch point from any position between closed... distinguishable from the rest of the operator. It shall be capable of being adjusted to a height of 6 feet (1.8 m...

Altered regional and circuit resting-state activity in patients with occult spastic diplegic cerebral palsy.

PubMed

Mu, Xuetao; Wang, Zhiqun; Nie, Binbin; Duan, Shaofeng; Ma, Qiaozhi; Dai, Guanghui; Wu, Chunnan; Dong, Yuru; Shan, Baoci; Ma, Lin

2017-10-07

Very few studies have been made to investigate functional activity changes in occult spastic diplegic cerebral palsy (SDCP). The purpose of this study was to analyze whole-brain resting state regional brain activity and functional connectivity (FC) changes in patients with SDCP. We examined 12 occult SDCP and 14 healthy control subjects using resting-state functional magnetic resonance imaging. The data were analyzed using Resting-State fMRI Data Analysis Toolkit (REST) software. The regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), and whole brain FC of the motor cortex and thalamus were analyzed and compared between the occult SDCP and control groups. Compared with the control group, the occult SDCP group showed decreased ReHo regions, including the bilateral frontal, parietal, and temporal lobes, the cerebellum, right cingulate gyrus, and right lenticular nucleus, whereas an increased ReHo value was observed in the left precuneus, calcarine, fusiform gyrus, and right precuneus. Compared with the control group, no significant differences in ALFF were noted in the occult SDCP group. With the motor cortex as the region of interest, the occult SDCP group showed decreased connectivity regions in the bilateral fusiform and lingual gyrus, but increased connectivity regions in the contralateral precentral and postcentral gyrus, supplementary motor area, and the ipsilateral postcentral gyrus. With the thalamus being regarded as the region of interest, the occult SDCP group showed decreased connectivity regions in the bilateral basal ganglia, cingulate, and prefrontal cortex, but increased connectivity regions in the bilateral precentral gyrus, the contralateral cerebellum, and inferior temporal gyrus. Resting-state regional brain activities and FC changes in the patients with occult SDCP exhibited a special distribution pattern, which is consistent with the pathology of the disease. Copyright © 2017. Published by Elsevier B.V.

Resting State Synchrony in Long-Term Abstinent Alcoholics

PubMed Central

Camchong, Jazmin; Stenger, Andy; Fein, George

2012-01-01

BACKGROUND Alcohol dependence (ALC) is a disorder with an impulsive and compulsive “drive” towards alcohol consumption and an inability to inhibit alcohol consumption. Neuroimaging studies suggest that these behavioral components correspond to an increased involvement of regions that mediate appetitive drive and reduced involvement of regions that mediate executive control within top-down networks. Little is known, however, about whether these characteristics are present after long periods of abstinence. METHODS Resting state functional magnetic resonance imaging data were collected to examine resting state synchrony (RSS) differences between 23 long-term abstinent alcoholics (LTAA; 8 females, age: M=48.46, SD=7.10), and 23 non-substance abusing controls (NSAC; 8 females, age: M=47.99, SD=6.70). Using seed-based measures, we examined resting-state synchrony with the nucleus accumbens (NAcc) and the subgenual anterior cingulate cortex (ACC). All participants were assessed with the intra/extradimensional set shift task outside of the scanner to explore the relationship between RSS and cognitive flexibility. RESULTS Compared to NSAC, LTAA showed (a) decreased synchrony of limbic reward regions (e.g., caudate and thalamus) with both the ACC seed and the NAcc seed and (b) increased synchrony of executive control regions (e.g., DLPFC) with both the NAcc seed and the subgenual ACC seed. RSS differences were significantly correlated with task performance. CONCLUSIONS The results are consistent with an interpretation of an ongoing compensatory mechanism in long-term abstinent alcoholics evident during rest, in which decision making networks show reduced synchrony with appetitive drive regions and increased synchrony with inhibitory control regions. In addition, RSS differences were associated with cognitive flexibility. These resting state findings indicate an adaptive mechanism present in long-term abstinence that may facilitate the behavioral control required for to maintain abstinence. PMID:22725701

Best practices for providing traveler information services to motorists at rest areas and welcome centers.

DOT National Transportation Integrated Search

2009-06-01

The objective of this study to look at what Kentucky and other states are doing to provide wireless Internet connectivity (i.e., Wi-Fi service) for motorists at rest areas, weigh stations, and truck rest havens, and to identify technologies and best ...

Less head motion during MRI under task than resting-state conditions.

PubMed

Huijbers, Willem; Van Dijk, Koene R A; Boenniger, Meta M; Stirnberg, Rüdiger; Breteler, Monique M B

2017-02-15

Head motion reduces data quality of neuroimaging data. In three functional magnetic resonance imaging (MRI) experiments we demonstrate that people make less head movements under task than resting-state conditions. In Experiment 1, we observed less head motion during a memory encoding task than during the resting-state condition. In Experiment 2, using publicly shared data from the UCLA Consortium for Neuropsychiatric Phenomics LA5c Study, we again found less head motion during several active task conditions than during a resting-state condition, although some task conditions also showed comparable motion. In the healthy controls, we found more head motion in men than in women and more motion with increasing age. When comparing clinical groups, we found that patients with a clinical diagnosis of bipolar disorder, or schizophrenia, move more compared to healthy controls or patients with ADHD. Both these experiments had a fixed acquisition order across participants, and we could not rule out that a first or last scan during a session might be particularly prone to more head motion. Therefore, we conducted Experiment 3, in which we collected several task and resting-state fMRI runs with an acquisition order counter-balanced. The results of Experiment 3 show again less head motion during several task conditions than during rest. Together these experiments demonstrate that small head motions occur during MRI even with careful instruction to remain still and fixation with foam pillows, but that head motion is lower when participants are engaged in a cognitive task. These finding may inform the choice of functional runs when studying difficult-to-scan populations, such as children or certain patient populations. Our findings also indicate that differences in head motion complicate direct comparisons of measures of functional neuronal networks between task and resting-state fMRI because of potential differences in data quality. In practice, a task to reduce head motion might be especially useful when acquiring structural MRI data such as T1/T2-weighted and diffusion MRI in research and clinical settings. Copyright © 2016 Elsevier Inc. All rights reserved.

Resting lateralized activity predicts the cortical response and appraisal of emotions: an fNIRS study.

PubMed

Balconi, Michela; Grippa, Elisabetta; Vanutelli, Maria Elide

2015-12-01

This study explored the effect of lateralized left-right resting brain activity on prefrontal cortical responsiveness to emotional cues and on the explicit appraisal (stimulus evaluation) of emotions based on their valence. Indeed subjective responses to different emotional stimuli should be predicted by brain resting activity and should be lateralized and valence-related (positive vs negative valence). A hemodynamic measure was considered (functional near-infrared spectroscopy). Indeed hemodynamic resting activity and brain response to emotional cues were registered when subjects (N = 19) viewed emotional positive vs negative stimuli (IAPS). Lateralized index response during resting state, LI (lateralized index) during emotional processing and self-assessment manikin rating were considered. Regression analysis showed the significant predictive effect of resting activity (more left or right lateralized) on both brain response and appraisal of emotional cues based on stimuli valence. Moreover, significant effects were found as a function of valence (more right response to negative stimuli; more left response to positive stimuli) during emotion processing. Therefore, resting state may be considered a predictive marker of the successive cortical responsiveness to emotions. The significance of resting condition for emotional behavior was discussed. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Recovery to resting metabolic state after walking.

PubMed

Frankenfield, David C; Coleman, Abigail

2009-11-01

Metabolic rate is usually measured in a resting state. To achieve this, a period of up to 30 minutes is given to recover from walking prior to the test. A work group from the American Dietetic Association recommends that 10 to 20 minutes is sufficient to achieve rest, but supporting data are limited. The purpose of this prospective observational study then was to determine how much time is needed for adults to recover to rest after walking 300 meters. Each participant's metabolic rate was measured with indirect calorimetry for 30 minutes after a 30-minute rest. The participant then walked 300 meters on a measured course, and metabolic rate was measured again for 30 minutes. Recovery to rest was considered to have occurred when the measured metabolic rate returned to a level of less than 6% above the resting measurement. Forty healthy ambulatory adults completed this study. Analysis of variance indicated that after a 300-meter walk, resting level of metabolic rate was achieved by the 10th minute of rest. However, it took 20 minutes for 95% of all participants to meet the 6% threshold (the remaining 5% who did not reach the threshold were observed to be moving during the measurement). The results of this study indicate that if a person lies still, recovery to rest after walking occurs by 20 minutes, validating the recommendation made by the expert panel of the American Dietetic Association's work group on indirect calorimetry. Rest periods of 30 minutes are not required, but the person should be observed for movement.

Neuroaging through the Lens of the Resting State Networks

PubMed Central

2018-01-01

Resting state functional magnetic resonance imaging (rs-fMRI) allows studying spontaneous brain activity in absence of task, recording changes of Blood Oxygenation Level Dependent (BOLD) signal. rs-fMRI enables identification of brain networks also called Resting State Networks (RSNs) including the most studied Default Mode Network (DMN). The simplicity and speed of execution make rs-fMRI applicable in a variety of normal and pathological conditions. Since it does not require any task, rs-fMRI is particularly useful for protocols on patients, children, and elders, increasing participant's compliance and reducing intersubjective variability due to the task performance. rs-fMRI has shown high sensitivity in identification of RSNs modifications in several diseases also in absence of structural modifications. In this narrative review, we provide the state of the art of rs-fMRI studies about physiological and pathological aging processes. First, we introduce the background of resting state; then we review clinical findings provided by rs-fMRI in physiological aging, Mild Cognitive Impairment (MCI), Alzheimer Dementia (AD), and Late Life Depression (LLD). Finally, we suggest future directions in this field of research and its potential clinical applications. PMID:29568755

Effect of leg exercise training on vascular volumes during 30 days of 6 deg head-down bed rest

NASA Technical Reports Server (NTRS)

Greenleaf, J. E.; Vernikos, J.; Wade, C. E.; Barnes, P. R.

1992-01-01

In order to investigate the effects of leg exercise training on vascular volumes during 30 d of 6-deg head-down bed rest, plasma and red cell volumes, body density, and water balance were measured in 19 men confined to bed rest (BR). One group had no exercise training (NOE), another near-maximal variable-intensity isotonic exercise (ITE) for 60 min/d, and the third near-maximal intermittent isokinetic exercise (IKE) for 60 min/d. Mean energy costs for the NOE, IKE, and ITE regimens were determined. Body densities within groups and mean urine volumes between groups were unchanged during BR. Changes in red cell volume followed changes in plasma volume. There was close coupling between resting plasma volume and plasma protein and osmotic content. It is argued that the ITE training protocol is better than the IKE protocol for maintaining plasma volume during prolonged exposure to BR.

Joint Analysis of Band-Specific Functional Connectivity and Signal Complexity in Autism

ERIC Educational Resources Information Center

Ghanbari, Yasser; Bloy, Luke; Edgar, J. Christopher; Blaskey, Lisa; Verma, Ragini; Roberts, Timothy P. L.

2015-01-01

Examination of resting state brain activity using electrophysiological measures like complexity as well as functional connectivity is of growing interest in the study of autism spectrum disorders (ASD). The present paper jointly examined complexity and connectivity to obtain a more detailed characterization of resting state brain activity in ASD.…

Resting-state theta band connectivity and graph analysis in generalized social anxiety disorder.

PubMed

Xing, Mengqi; Tadayonnejad, Reza; MacNamara, Annmarie; Ajilore, Olusola; DiGangi, Julia; Phan, K Luan; Leow, Alex; Klumpp, Heide

2017-01-01

Functional magnetic resonance imaging (fMRI) resting-state studies show generalized social anxiety disorder (gSAD) is associated with disturbances in networks involved in emotion regulation, emotion processing, and perceptual functions, suggesting a network framework is integral to elucidating the pathophysiology of gSAD. However, fMRI does not measure the fast dynamic interconnections of functional networks. Therefore, we examined whole-brain functional connectomics with electroencephalogram (EEG) during resting-state. Resting-state EEG data was recorded for 32 patients with gSAD and 32 demographically-matched healthy controls (HC). Sensor-level connectivity analysis was applied on EEG data by using Weighted Phase Lag Index (WPLI) and graph analysis based on WPLI was used to determine clustering coefficient and characteristic path length to estimate local integration and global segregation of networks. WPLI results showed increased oscillatory midline coherence in the theta frequency band indicating higher connectivity in the gSAD relative to HC group during rest. Additionally, WPLI values positively correlated with state anxiety levels within the gSAD group but not the HC group. Our graph theory based connectomics analysis demonstrated increased clustering coefficient and decreased characteristic path length in theta-based whole brain functional organization in subjects with gSAD compared to HC. Theta-dependent interconnectivity was associated with state anxiety in gSAD and an increase in information processing efficiency in gSAD (compared to controls). Results may represent enhanced baseline self-focused attention, which is consistent with cognitive models of gSAD and fMRI studies implicating emotion dysregulation and disturbances in task negative networks (e.g., default mode network) in gSAD.

Spatially Regularized Machine Learning for Task and Resting-state fMRI

PubMed Central

Song, Xiaomu; Panych, Lawrence P.; Chen, Nan-kuei

2015-01-01

Background Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades. New Method A spatially regularized support vector machine (SVM) technique was developed for the reliable brain mapping in task- and resting-state. Unlike most existing SVM-based brain mapping techniques, which implement supervised classifications of specific brain functional states or disorders, the proposed method performs a semi-supervised classification for the general brain function mapping where spatial correlation of fMRI is integrated into the SVM learning. The method can adapt to intra- and inter-subject variations induced by fMRI nonstationarity, and identify a true boundary between active and inactive voxels, or between functionally connected and unconnected voxels in a feature space. Results The method was evaluated using synthetic and experimental data at the individual and group level. Multiple features were evaluated in terms of their contributions to the spatially regularized SVM learning. Reliable mapping results in both task- and resting-state were obtained from individual subjects and at the group level. Comparison with Existing Methods A comparison study was performed with independent component analysis, general linear model, and correlation analysis methods. Experimental results indicate that the proposed method can provide a better or comparable mapping performance at the individual and group level. Conclusions The proposed method can provide accurate and reliable mapping of brain function in task- and resting-state, and is applicable to a variety of quantitative fMRI studies. PMID:26470627

Time-frequency dynamics of resting-state brain connectivity measured with fMRI.

PubMed

Chang, Catie; Glover, Gary H

2010-03-01

Most studies of resting-state functional connectivity using fMRI employ methods that assume temporal stationarity, such as correlation and data-driven decompositions computed across the duration of the scan. However, evidence from both task-based fMRI studies and animal electrophysiology suggests that functional connectivity may exhibit dynamic changes within time scales of seconds to minutes. In the present study, we investigated the dynamic behavior of resting-state connectivity across the course of a single scan, performing a time-frequency coherence analysis based on the wavelet transform. We focused on the connectivity of the posterior cingulate cortex (PCC), a primary node of the default-mode network, examining its relationship with both the "anticorrelated" ("task-positive") network as well as other nodes of the default-mode network. It was observed that coherence and phase between the PCC and the anticorrelated network was variable in time and frequency, and statistical testing based on Monte Carlo simulations revealed the presence of significant scale-dependent temporal variability. In addition, a sliding-window correlation procedure identified other regions across the brain that exhibited variable connectivity with the PCC across the scan, which included areas previously implicated in attention and salience processing. Although it is unclear whether the observed coherence and phase variability can be attributed to residual noise or modulation of cognitive state, the present results illustrate that resting-state functional connectivity is not static, and it may therefore prove valuable to consider measures of variability, in addition to average quantities, when characterizing resting-state networks. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Dexmedetomidine Disrupts the Local and Global Efficiencies of Large-scale Brain Networks.

PubMed

Hashmi, Javeria A; Loggia, Marco L; Khan, Sheraz; Gao, Lei; Kim, Jieun; Napadow, Vitaly; Brown, Emery N; Akeju, Oluwaseun

2017-03-01

A clear understanding of the neural basis of consciousness is fundamental to research in clinical and basic neuroscience disciplines and anesthesia. Recently, decreased efficiency of information integration was suggested as a core network feature of propofol-induced unconsciousness. However, it is unclear whether this finding can be generalized to dexmedetomidine, which has a different molecular target. Dexmedetomidine was administered as a 1-μg/kg bolus over 10 min, followed by a 0.7-μg · kg · h infusion to healthy human volunteers (age range, 18 to 36 yr; n = 15). Resting-state functional magnetic resonance imaging data were acquired during baseline, dexmedetomidine-induced altered arousal, and recovery states. Zero-lag correlations between resting-state functional magnetic resonance imaging signals extracted from 131 brain parcellations were used to construct weighted brain networks. Network efficiency, degree distribution, and node strength were computed using graph analysis. Parcellated brain regions were also mapped to known resting-state networks to study functional connectivity changes. Dexmedetomidine significantly reduced the local and global efficiencies of graph theory-derived networks. Dexmedetomidine also reduced the average brain connectivity strength without impairing the degree distribution. Functional connectivity within and between all resting-state networks was modulated by dexmedetomidine. Dexmedetomidine is associated with a significant drop in the capacity for efficient information transmission at both the local and global levels. These changes result from reductions in the strength of connectivity and also manifest as reduced within and between resting-state network connectivity. These findings strengthen the hypothesis that conscious processing relies on an efficient system of information transfer in the brain.

Face Patch Resting State Networks Link Face Processing to Social Cognition

PubMed Central

Schwiedrzik, Caspar M.; Zarco, Wilbert; Everling, Stefan; Freiwald, Winrich A.

2015-01-01

Faces transmit a wealth of social information. How this information is exchanged between face-processing centers and brain areas supporting social cognition remains largely unclear. Here we identify these routes using resting state functional magnetic resonance imaging in macaque monkeys. We find that face areas functionally connect to specific regions within frontal, temporal, and parietal cortices, as well as subcortical structures supporting emotive, mnemonic, and cognitive functions. This establishes the existence of an extended face-recognition system in the macaque. Furthermore, the face patch resting state networks and the default mode network in monkeys show a pattern of overlap akin to that between the social brain and the default mode network in humans: this overlap specifically includes the posterior superior temporal sulcus, medial parietal, and dorsomedial prefrontal cortex, areas supporting high-level social cognition in humans. Together, these results reveal the embedding of face areas into larger brain networks and suggest that the resting state networks of the face patch system offer a new, easily accessible venue into the functional organization of the social brain and into the evolution of possibly uniquely human social skills. PMID:26348613

Resting-state fMRI study of patients with fragile X syndrome

NASA Astrophysics Data System (ADS)

Isanova, E.; Petrovskiy, E.; Savelov, A.; Yudkin, D.; Tulupov, A.

2017-08-01

The study aimed to assess the neural activity of different brain regions in patients with fragile X syndrome (FXS) and the healthy volunteers by resting-state functional magnetic resonance imaging (fMRI) on a 1.5 T MRI Achieva scanner (Philips). Results: The fMRI study showed a DMN of brain function in patients with FXS, as well as in the healthy volunteers. Furthermore, it was found that a default mode network of the brain in patients with FXS and healthy volunteers does not have statistically significant differences (p>0.05), which may indicate that the basal activity of neurons in patients with FXS is not reduced. In addition, we have found a significant (p<0.001) increase in the FC within the right inferior parietal and right angular gyrus in the resting state in patients with FXS. Conclusion: New data of functional status of the brain in patients with FXS were received. The significant increase in the resting state functional connectivity within the right inferior parietal and right angular gyrus (p<0.001) in patients with FXS was found.

Sources of Disconnection in Neurocognitive Aging: Cerebral White Matter Integrity, Resting-state Functional Connectivity, and White Matter Hyperintensity Volume

PubMed Central

Madden, David J.; Parks, Emily L.; Tallman, Catherine W.; Boylan, Maria A.; Hoagey, David A.; Cocjin, Sally B.; Packard, Lauren E.; Johnson, Micah A.; Chou, Ying-hui; Potter, Guy G.; Chen, Nan-kuei; Siciliano, Rachel E.; Monge, Zachary A.; Honig, Jesse A.; Diaz, Michele T.

2017-01-01

Age-related decline in fluid cognition can be characterized as a disconnection among specific brain structures, leading to a decline in functional efficiency. The potential sources of disconnection, however, are unclear. We investigated imaging measures of cerebral white matter integrity, resting-state functional connectivity, and white matter hyperintensity (WMH) volume as mediators of the relation between age and fluid cognition, in 145 healthy, community-dwelling adults 19–79 years of age. At a general level of analysis, with a single composite measure of fluid cognition and single measures of each of the three imaging modalities, age exhibited an independent influence on the cognitive and imaging measures, and the imaging variables did not mediate the age-cognition relation. At a more specific level of analysis, resting-state functional connectivity of sensorimotor networks was a significant mediator of the age-related decline in executive function. These findings suggest that different levels of analysis lead to different models of neurocognitive disconnection, and that resting-state functional connectivity, in particular, may contribute to age-related decline in executive function. PMID:28389085

Opportunities and methodological challenges in EEG and MEG resting state functional brain network research.

PubMed

van Diessen, E; Numan, T; van Dellen, E; van der Kooi, A W; Boersma, M; Hofman, D; van Lutterveld, R; van Dijk, B W; van Straaten, E C W; Hillebrand, A; Stam, C J

2015-08-01

Electroencephalogram (EEG) and magnetoencephalogram (MEG) recordings during resting state are increasingly used to study functional connectivity and network topology. Moreover, the number of different analysis approaches is expanding along with the rising interest in this research area. The comparison between studies can therefore be challenging and discussion is needed to underscore methodological opportunities and pitfalls in functional connectivity and network studies. In this overview we discuss methodological considerations throughout the analysis pipeline of recording and analyzing resting state EEG and MEG data, with a focus on functional connectivity and network analysis. We summarize current common practices with their advantages and disadvantages; provide practical tips, and suggestions for future research. Finally, we discuss how methodological choices in resting state research can affect the construction of functional networks. When taking advantage of current best practices and avoid the most obvious pitfalls, functional connectivity and network studies can be improved and enable a more accurate interpretation and comparison between studies. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Circulating androgens correlate with resting-state MRI in transgender men.

PubMed

Mueller, Sven C; Wierckx, Katrien; Jackson, Kathryn; T'Sjoen, Guy

2016-11-01

Despite mounting evidence regarding the underlying neurobiology in transgender persons, information regarding resting-state activity, particularly after hormonal treatment, is lacking. The present study examined differences between transgender persons on long-term cross-sex hormone therapy and comparisons on two measures of local functional connectivity, intensity of spontaneous resting-state activity (low frequency fluctuations, LFF) and local synchronization of specific brain areas (regional homogeneity, ReHo). Nineteen transgender women (TW, male-to-female), 19 transgender men (TM, female-to-male), 21 non-transgender men (NTM) and 20 non-transgender women (NTW) underwent a resting-state MRI scan. The results showed differences between transgender persons and non-transgender comparisons on both LFF and ReHo measures in the frontal cortex, medial temporal lobe, and cerebellum. More interestingly, circulating androgens correlated for TM in the cerebellum and regions of the frontal cortex, an effect that was associated with treatment duration in the cerebellum. By comparison, no associations were found for TW with estrogens. These data provide first evidence for a potential masculinization of local functional connectivity in hormonally-treated transgender men. Copyright © 2016 Elsevier Ltd. All rights reserved.

Detecting Mild Traumatic Brain Injury Using Resting State Magnetoencephalographic Connectivity

PubMed Central

da Costa, Leodante; Jetly, Rakesh; Pang, Elizabeth W.; Taylor, Margot J.

2016-01-01

Accurate means to detect mild traumatic brain injury (mTBI) using objective and quantitative measures remain elusive. Conventional imaging typically detects no abnormalities despite post-concussive symptoms. In the present study, we recorded resting state magnetoencephalograms (MEG) from adults with mTBI and controls. Atlas-guided reconstruction of resting state activity was performed for 90 cortical and subcortical regions, and calculation of inter-regional oscillatory phase synchrony at various frequencies was performed. We demonstrate that mTBI is associated with reduced network connectivity in the delta and gamma frequency range (>30 Hz), together with increased connectivity in the slower alpha band (8–12 Hz). A similar temporal pattern was associated with correlations between network connectivity and the length of time between the injury and the MEG scan. Using such resting state MEG network synchrony we were able to detect mTBI with 88% accuracy. Classification confidence was also correlated with clinical symptom severity scores. These results provide the first evidence that imaging of MEG network connectivity, in combination with machine learning, has the potential to accurately detect and determine the severity of mTBI. PMID:27906973

Resting State Network Topology of the Ferret Brain

PubMed Central

Zhou, Zhe Charles; Salzwedel, Andrew P.; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K.; Gilmore, John H.; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-01-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4 tesla MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. PMID:27596024

I Keep a Close Watch on This Heart of Mine: Increased Interoception in Insomnia

PubMed Central

Wei, Yishul; Ramautar, Jennifer R.; Colombo, Michele A.; Stoffers, Diederick; Gómez-Herrero, Germán; van der Meijden, Wisse P.; te Lindert, Bart H.W.; van der Werf, Ysbrand D.; Van Someren, Eus J.W.

2016-01-01

Study Objectives: Whereas both insomnia and altered interoception are core symptoms in affective disorders, their neural mechanisms remain insufficiently understood and have not previously been linked. Insomnia Disorder (ID) is characterized by sensory hypersensitivity during wakefulness and sleep. Previous studies on sensory processing in ID addressed external stimuli only, but not interoception. Interoceptive sensitivity can be studied quantitatively by measuring the cerebral cortical response to one's heartbeat (heartbeat-evoked potential, HEP). We here investigated whether insomnia is associated with increased interoceptive sensitivity as indexed by the HEP amplitude. Methods: Sixty-four participants aged 21–70 years were recruited through www.sleepregistry.nl including 32 people suffering from ID and 32 age- and sex-matched controls without sleep complaints. HEPs were obtained from resting-state high-density electroencephalography (HD-EEG) recorded during evening wakeful rest in eyes-open (EO) and eyes-closed (EC) conditions of 5-minute duration each. Significance of group differences in HEP amplitude and their topographical distribution over the scalp were assessed by means of cluster-based permutation tests. Results: In particular during EC, and to a lesser extent during EO, people with ID had a larger amplitude late HEP component than controls at frontal electrodes 376–500 ms after the R-wave peak. Source localization suggested increased neural activity time-locked to heartbeats in people with ID mainly in anterior cingulate/medial frontal cortices. Conclusions: People with insomnia show insufficient adaptation of their brain responses to the ever-present heartbeats. Abnormalities in the neural circuits involved in interoceptive awareness including the salience network may be of key importance to the pathophysiology of insomnia. Citation: Wei Y, Ramautar JR, Colombo MA, Stoffers D, Gómez-Herrero G, van der Meijden WP, te Lindert BHW, van der Werf YD, Van Someren EJW. I keep a close watch on this heart of mine: increased interoception in insomnia. SLEEP 2016;39(12):2113–2124. PMID:27634787

Joint US/USSR study: Comparison of effects of horizontal and head-down bed rest

NASA Technical Reports Server (NTRS)

Sandler, Harold; Grigoriev, Anatoli I.

1990-01-01

An account is given of the results of the first joint U.S./U.S.S.R. bed rest study. The study was accomplished in two parts: A soviet part (May to June 1979) and an American part (July to August 1979). Both studies were conducted under identical conditions and provided a basis for comparison of physiologic reactions and standardizing procedures and methods. Each experiment consisted of three periods: 14 days of pre-bed rest control, 7 days of bed rest, and a 10 to 14 day recovery period. Ten males participated in each study, with five subjects experiencing horizontal bed rest and five subjects a -6 deg head-down body position. Biochemical and hormonal measurements were made of blood and urine, with particular attention to electrolyte metabolism and kidney function; cardio-pulmonary changes at rest and exercise; influence of Lower Body Negative Pressure (LBNP); and incremental exercise using a bicyle ergometer while supine and sitting. Expected moderate changes were noted to occur for various physiologic parameters. Clinical evidence pointed to the fact that head-down bed rest when compared to horizontal conditions more closely matched the conditions seen after manned spaceflight. For the most part, statistically significant differences between the two body positions were not observed.

Adolescent obesity adversely affects blood pressure and resting heart rate.

PubMed

Baba, Reizo; Koketsu, Masaaki; Nagashima, Masami; Inasaka, Hiroshi; Yoshinaga, Masao; Yokota, Mitsuhiro

2007-05-01

Obesity is associated with hypertension (HT) and high resting heart rate (HR), as well as metabolic disturbances. However, little is known about how strongly these hemodynamic abnormalities are associated with the degree of obesity in adolescents. Height, body weight, resting HR, and systolic and diastolic blood pressures were measured in 20,165 male and 19,683 female high-school students. Adiposity levels were classified into 6 groups by body mass index: group 1 (<20th percentile), group 2 (20th-39.9th percentile), group 3 (40th-59.9th percentile), group 4 (60th-79.9th percentile), group 5 (80th-98.9th percentile), and group 6 (> or =99th percentile). Systolic and diastolic hypertensions were defined as > or =140 mmHg and > or =85 mmHg, respectively. Resting tachycardia was defined as the corresponding 95th percentile or greater. Resting HR and systolic and diastolic blood pressures increased with adiposity level in both sexes (p<0.0001). Both systolic HT and diastolic HT were associated with high resting HR, and the clustering of these unfavorable conditions increased with the degree of obesity. Hemodynamic abnormalities, such as HT and a high resting HR, are closely associated with adolescent obesity and are probably explained by impaired autonomic nerve function.

Comparison of heart rate variability between resting state and external-cuff-inflation-and-deflation state: a pilot study.

PubMed

Ji, Lizhen; Liu, Chengyu; Li, Peng; Wang, Xinpei; Yan, Chang; Liu, Changchun

2015-10-01

Heart rate variability (HRV) has been widely used in clinical research to provide an insight into the autonomic control of the cardiovascular system. Measurement of HRV is generally performed under a relaxed resting state. The effects of other conditions on HRV measurement, such as running, mountaineering, head-up tilt, etc, have also been investigated. This study aimed to explore whether an inflation-and-deflation process applied to a unilateral upper arm cuff would influence the HRV measurement. Fifty healthy young volunteers aged between 21 and 30 were enrolled in this study. Electrocardiogram (ECG) signals were recorded for each subject over a five minute resting state followed by a five minute external-cuff-inflation-and-deflation state (ECID state). A one minute gap was scheduled between the two measurements. Consecutive RR intervals in the ECG were extracted automatically to form the HRV data for each of the two states. Time domain (SDNN, RMSSD and PNN50), frequency domain (LFn, HFn and LF/HF) and nonlinear (VLI, VAI and SampEn) HRV indices were analyzed and compared between the two states. In addition, the effects of mean artery pressure (MAP) and heart rate (HR) on the aforementioned HRV indices were assessed for the two states, respectively, by Pearson correlation analysis. The results showed no significant difference in all aforementioned HRV indices between the resting and the ECID states (all p  >  0.05). The corresponding HRV indices had significant positive correlation (all p  <  0.01) between the two states. None of the indices showed MAP-related change (all p  >  0.05) for either state. Besides, none of the indices showed HR-related change (all p  >  0.05) for either state except the index of VLI in the resting state. To conclude, this pilot study suggested that the applied ECID process hardly influenced those commonly used HRV indices. It would thus be applicable to simultaneously measure both blood pressure and HRV indices in clinical practice.

Exercise Improves Mood State in Normobaric Hypoxia.

PubMed

Seo, Yongsuk; Fennell, Curtis; Burns, Keith; Pollock, Brandon S; Gunstad, John; McDaniel, John; Glickman, Ellen

2015-11-01

The purpose of this study was to quantify the efficacy of using exercise to alleviate the impairments in mood state associated with hypoxic exposure. Nineteen young, healthy men completed Automated Neuropsychological Assessment Metrics-4(th) Edition (ANAM4) versions of the mood state test before hypoxia exposure, after 60 min of hypoxia exposure (12.5% O(2)), and during and after two intensities of cycling exercise (40% and 60% adjusted Vo(2max)) under the same hypoxic conditions. Peripheral oxygen saturation (Spo(2)) and regional cerebral oxygen saturation (rSo(2)) were continuously monitored. At rest in hypoxia, Total Mood Disturbance (TMD) was significantly increased compared to baseline in both the 40% and 60% groups. TMD was significantly decreased during exercise compared to rest in hypoxia. TMD was also significantly decreased during recovery compared to rest in hypoxia. Spo(2) significantly decreased at 60 min rest in hypoxia, during exercise, and recovery compared to baseline. Regional cerebral oxygen saturation was also reduced at 60 min rest in hypoxia, during exercise, and recovery compared to baseline. The current study demonstrated that exercise at 40% and 60% of adjusted Vo(2max) attenuated the adverse effects of hypoxia on mood. These findings may have significant applied value, as negative mood states are known to impair performance in hypoxia. Further studies are needed to replicate the current finding and to clarify the possible mechanisms associated with the potential benefits of exercise on mood state in normobaric hypoxia.

Altered resting-state functional connectivity in women with chronic fatigue syndrome.

PubMed

Kim, Byung-Hoon; Namkoong, Kee; Kim, Jae-Jin; Lee, Seojung; Yoon, Kang Joon; Choi, Moonjong; Jung, Young-Chul

2015-12-30

The biological underpinnings of the psychological factors characterizing chronic fatigue syndrome (CFS) have not been extensively studied. Our aim was to evaluate alterations of resting-state functional connectivity in CFS patients. Participants comprised 18 women with CFS and 18 age-matched female healthy controls who were recruited from the local community. Structural and functional magnetic resonance images were acquired during a 6-min passive-viewing block scan. Posterior cingulate cortex seeded resting-state functional connectivity was evaluated, and correlation analyses of connectivity strength were performed. Graph theory analysis of 90 nodes of the brain was conducted to compare the global and local efficiency of connectivity networks in CFS patients with that in healthy controls. The posterior cingulate cortex in CFS patients showed increased resting-state functional connectivity with the dorsal and rostral anterior cingulate cortex. Connectivity strength of the posterior cingulate cortex to the dorsal anterior cingulate cortex significantly correlated with the Chalder Fatigue Scale score, while the Beck Depression Inventory (BDI) score was controlled. Connectivity strength to the rostral anterior cingulate cortex significantly correlated with the Chalder Fatigue Scale score. Global efficiency of the posterior cingulate cortex was significantly lower in CFS patients, while local efficiency showed no difference from findings in healthy controls. The findings suggest that CFS patients show inefficient increments in resting-state functional connectivity that are linked to the psychological factors observed in the syndrome. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Hubs of Anticorrelation in High-Resolution Resting-State Functional Connectivity Network Architecture.

PubMed

Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Cabanban, Romeo; Crosson, Bruce A

2015-06-01

A major focus of brain research recently has been to map the resting-state functional connectivity (rsFC) network architecture of the normal brain and pathology through functional magnetic resonance imaging. However, the phenomenon of anticorrelations in resting-state signals between different brain regions has not been adequately examined. The preponderance of studies on resting-state fMRI (rsFMRI) have either ignored anticorrelations in rsFC networks or adopted methods in data analysis, which have rendered anticorrelations in rsFC networks uninterpretable. The few studies that have examined anticorrelations in rsFC networks using conventional methods have found anticorrelations to be weak in strength and not very reproducible across subjects. Anticorrelations in rsFC network architecture could reflect mechanisms that subserve a number of important brain processes. In this preliminary study, we examined the properties of anticorrelated rsFC networks by systematically focusing on negative cross-correlation coefficients (CCs) among rsFMRI voxel time series across the brain with graph theory-based network analysis. A number of methods were implemented to enhance the neuronal specificity of resting-state functional connections that yield negative CCs, although at the cost of decreased sensitivity. Hubs of anticorrelation were seen in a number of cortical and subcortical brain regions. Examination of the anticorrelation maps of these hubs indicated that negative CCs in rsFC network architecture highlight a number of regulatory interactions between brain networks and regions, including reciprocal modulations, suppression, inhibition, and neurofeedback.

Cognitive and default-mode resting state networks: do male and female brains "rest" differently?

PubMed

Weissman-Fogel, Irit; Moayedi, Massieh; Taylor, Keri S; Pope, Geoff; Davis, Karen D

2010-11-01

Variability in human behavior related to sex is supported by neuroimaging studies showing differences in brain activation patterns during cognitive task performance. An emerging field is examining the human connectome, including networks of brain regions that are not only temporally-correlated during different task conditions, but also networks that show highly correlated spontaneous activity during a task-free state. Both task-related and task-free network activity has been associated with individual task performance and behavior under certain conditions. Therefore, our aim was to determine whether sex differences exist during a task-free resting state for two networks associated with cognitive task performance (executive control network (ECN), salience network (SN)) and the default mode network (DMN). Forty-nine healthy subjects (26 females, 23 males) underwent a 5-min task-free fMRI scan in a 3T MRI. An independent components analysis (ICA) was performed to identify the best-fit IC for each network based on specific spatial nodes defined in previous studies. To determine the consistency of these networks across subjects we performed self-organizing group-level ICA analyses. There were no significant differences between sexes in the functional connectivity of the brain areas within the ECN, SN, or the DMN. These important findings highlight the robustness of intrinsic connectivity of these resting state networks and their similarity between sexes. Furthermore, our findings suggest that resting state fMRI studies do not need to be controlled for sex. © 2010 Wiley-Liss, Inc.

Do all roads lead to Rome? A comparison of brain networks derived from inter-subject volumetric and metabolic covariance and moment-to-moment hemodynamic correlations in old individuals.

PubMed

Di, Xin; Gohel, Suril; Thielcke, Andre; Wehrl, Hans F; Biswal, Bharat B

2017-11-01

Relationships between spatially remote brain regions in human have typically been estimated by moment-to-moment correlations of blood-oxygen-level dependent signals in resting-state using functional MRI (fMRI). Recently, studies using subject-to-subject covariance of anatomical volumes, cortical thickness, and metabolic activity are becoming increasingly popular. However, question remains on whether these measures reflect the same inter-region connectivity and brain network organizations. In the current study, we systematically analyzed inter-subject volumetric covariance from anatomical MRI images, metabolic covariance from fluorodeoxyglucose positron emission tomography images from 193 healthy subjects, and resting-state moment-to-moment correlations from fMRI images of a subset of 44 subjects. The correlation matrices calculated from the three methods were found to be minimally correlated, with higher correlation in the range of 0.31, as well as limited proportion of overlapping connections. The volumetric network showed the highest global efficiency and lowest mean clustering coefficient, leaning toward random-like network, while the metabolic and resting-state networks conveyed properties more resembling small-world networks. Community structures of the volumetric and metabolic networks did not reflect known functional organizations, which could be observed in resting-state network. The current results suggested that inter-subject volumetric and metabolic covariance do not necessarily reflect the inter-regional relationships and network organizations as resting-state correlations, thus calling for cautions on interpreting results of inter-subject covariance networks.

Regional homogeneity, resting-state functional connectivity and amplitude of low frequency fluctuation associated with creativity measured by divergent thinking in a sex-specific manner.

PubMed

Takeuchi, Hikaru; Taki, Yasuyuki; Nouchi, Rui; Yokoyama, Ryoichi; Kotozaki, Yuka; Nakagawa, Seishu; Sekiguchi, Atsushi; Iizuka, Kunio; Yamamoto, Yuki; Hanawa, Sugiko; Araki, Tsuyoshi; Makoto Miyauchi, Carlos; Shinada, Takamitsu; Sakaki, Kohei; Nozawa, Takayuki; Ikeda, Shigeyuki; Yokota, Susumu; Daniele, Magistro; Sassa, Yuko; Kawashima, Ryuta

2017-05-15

Brain connectivity is traditionally thought to be important for creativity. Here we investigated the associations of creativity measured by divergent thinking (CMDT) with resting-state functional magnetic imaging (fMRI) measures and their sex differences. We examined these relationships in the brains of 1277 healthy young adults. Whole-brain analyses revealed a significant interaction between verbal CMDT and sex on (a) regional homogeneity within an area from the left anterior temporal lobe (b) on the resting state functional connectivity (RSFC) between the mPFC and the left inferior frontal gyrus and (c) on fractional amplitude of low frequency fluctuations (fALFF) in several distinct areas, including the precuneus and middle cingulate gyrus, left middle temporal gyrus, right middle frontal gyrus, and cerebellum. These interactions were mediated by positive correlations in females and negative correlations in males. These findings suggest that greater CMDT in females is reflected by (a) regional coherence (regional homogeneity) of brain areas responsible for representing and combining concepts as well as (b) the efficient functional connection (RSFC) between the key areas for the default state of cognitive activity and speech production, and (c) greater spontaneous neural activity (fALFF) during the resting of brain areas involved in frontal lobe functions, default cognitive activities, and language functions. Furthermore, these findings suggest that the associations between creativity and resting state brain connectivity patterns are different between males and females. Copyright © 2017 Elsevier Inc. All rights reserved.

Possible Peroxo State of the Dicopper Site of Particulate Methane Monooxygenase from Combined Quantum Mechanics and Molecular Mechanics Calculations.

PubMed

Itoyama, Shuhei; Doitomi, Kazuki; Kamachi, Takashi; Shiota, Yoshihito; Yoshizawa, Kazunari

2016-03-21

Enzymatic methane hydroxylation is proposed to efficiently occur at the dinuclear copper site of particulate methane monooxygenase (pMMO), which is an integral membrane metalloenzyme in methanotrophic bacteria. The resting state and a possible peroxo state of the dicopper active site of pMMO are discussed by using combined quantum mechanics and molecular mechanics calculations on the basis of reported X-ray crystal structures of the resting state of pMMO by Rosenzweig and co-workers. The dicopper site has a unique structure, in which one copper is coordinated by two histidine imidazoles and another is chelated by a histidine imidazole and primary amine of an N-terminal histidine. The resting state of the dicopper site is assignable to the mixed-valent Cu(I)Cu(II) state from a computed Cu-Cu distance of 2.62 Å from calculations at the B3LYP-D/TZVP level of theory. A μ-η(2):η(2)-peroxo-Cu(II)2 structure similar to those of hemocyanin and tyrosinase is reasonably obtained by using the resting state structure and dioxygen. Computed Cu-Cu and O-O distances are 3.63 and 1.46 Å, respectively, in the open-shell singlet state. Structural features of the dicopper peroxo species of pMMO are compared with those of hemocyanin and tyrosinase and synthetic dicopper model compounds. Optical features of the μ-η(2):η(2)-peroxo-Cu(II)2 state are calculated and analyzed with TD-DFT calculations.

Visual food stimulus changes resting oscillatory brain activities related to appetitive motive.

PubMed

Yoshikawa, Takahiro; Tanaka, Masaaki; Ishii, Akira; Yamano, Yoko; Watanabe, Yasuyoshi

2016-09-26

Changes of resting brain activities after visual food stimulation might affect the feeling of pleasure in eating food in daily life and spontaneous appetitive motives. We used magnetoencephalography (MEG) to identify brain areas related to the activity changes. Fifteen healthy, right-handed males [age, 25.4 ± 5.5 years; body mass index, 22.5 ± 2.7 kg/m 2 (mean ± SD)] were enrolled. They were asked to watch food or mosaic pictures for 5 min and to close their eyes for 3 min before and after the picture presentation without thinking of anything. Resting brain activities were recorded during two eye-closed sessions. The feeling of pleasure in eating food in daily life and appetitive motives in the study setting were assessed by visual analogue scale (VAS) scores. The γ-band power of resting oscillatory brain activities was decreased after the food picture presentation in the right insula [Brodmann's area (BA) 13], the left orbitofrontal cortex (OFC) (BA11), and the left frontal pole (BA10). Significant reductions of the α-band power were observed in the dorsolateral prefrontal cortex (DLPFC) (BA46). Particularly, the feeling of pleasure in eating food was positively correlated with the power decrease in the insula and negatively with that in the DLPFC. The changes in appetitive motives were associated with the power decrease in the frontal pole. These findings suggest automatic brain mechanics whereby changes of the resting brain activity might be associated with positive feeling in dietary life and have an impact on the irresistible appetitive motives through emotional and cognitive brain functions.

Task-Rest Modulation of Basal Ganglia Connectivity in Mild to Moderate Parkinson’s Disease

PubMed Central

Müller-Oehring, Eva M.; Sullivan, Edith V.; Pfefferbaum, Adolf; Huang, Neng C.; Poston, Kathleen L.; Bronte-Stewart, Helen M.; Schulte, Tilman

2014-01-01

Parkinson’s disease (PD) is associated with abnormal synchronization in basal ganglia-thalamo-cortical loops. We tested whether early PD patients without demonstrable cognitive impairment exhibit abnormal modulation of functional connectivity at rest, while engaged in a task, or both. PD and healthy controls underwent two functional MRI scans: a resting-state scan and a Stroop Match-to-Sample task scan. Rest-task modulation of basal ganglia (BG) connectivity was tested using seed-to-voxel connectivity analysis with task and rest time series as conditions. Despite substantial overlap of BG–cortical connectivity patterns in both groups, connectivity differences between groups had clinical and behavioral correlates. During rest, stronger putamen–medial parietal and pallidum–occipital connectivity in PD than controls was associated with worse task performance and more severe PD symptoms suggesting that abnormalities in resting-state connectivity denote neural network dedifferentiation. During the executive task, PD patients showed weaker BG-cortical connectivity than controls, i.e., between caudate–supramarginal gyrus and pallidum–inferior prefrontal regions, that was related to more severe PD symptoms and worse task performance. Yet, task processing also evoked stronger striatal–cortical connectivity, specifically between caudate–prefrontal, caudate–precuneus, and putamen–motor/premotor regions in PD relative to controls, which was related to less severe PD symptoms and better performance on the Stroop task. Thus, stronger task-evoked striatal connectivity in PD demonstrated compensatory neural network enhancement to meet task demands and improve performance levels. fMRI-based network analysis revealed that despite resting-state BG network compromise in PD, BG connectivity to prefrontal, premotor, and precuneus regions can be adequately invoked during executive control demands enabling near normal task performance. PMID:25280970

How Visual Is the Visual Cortex? Comparing Connectional and Functional Fingerprints between Congenitally Blind and Sighted Individuals.

PubMed

Wang, Xiaoying; Peelen, Marius V; Han, Zaizhu; He, Chenxi; Caramazza, Alfonso; Bi, Yanchao

2015-09-09

Classical animal visual deprivation studies and human neuroimaging studies have shown that visual experience plays a critical role in shaping the functionality and connectivity of the visual cortex. Interestingly, recent studies have additionally reported circumscribed regions in the visual cortex in which functional selectivity was remarkably similar in individuals with and without visual experience. Here, by directly comparing resting-state and task-based fMRI data in congenitally blind and sighted human subjects, we obtained large-scale continuous maps of the degree to which connectional and functional "fingerprints" of ventral visual cortex depend on visual experience. We found a close agreement between connectional and functional maps, pointing to a strong interdependence of connectivity and function. Visual experience (or the absence thereof) had a pronounced effect on the resting-state connectivity and functional response profile of occipital cortex and the posterior lateral fusiform gyrus. By contrast, connectional and functional fingerprints in the anterior medial and posterior lateral parts of the ventral visual cortex were statistically indistinguishable between blind and sighted individuals. These results provide a large-scale mapping of the influence of visual experience on the development of both functional and connectivity properties of visual cortex, which serves as a basis for the formulation of new hypotheses regarding the functionality and plasticity of specific subregions. Significance statement: How is the functionality and connectivity of the visual cortex shaped by visual experience? By directly comparing resting-state and task-based fMRI data in congenitally blind and sighted subjects, we obtained large-scale continuous maps of the degree to which connectional and functional "fingerprints" of ventral visual cortex depend on visual experience. In addition to revealing regions that are strongly dependent on visual experience (early visual cortex and posterior fusiform gyrus), our results showed regions in which connectional and functional patterns are highly similar in blind and sighted individuals (anterior medial and posterior lateral ventral occipital temporal cortex). These results serve as a basis for the formulation of new hypotheses regarding the functionality and plasticity of specific subregions of the visual cortex. Copyright © 2015 the authors 0270-6474/15/3512545-15$15.00/0.

An Inverse U-Shaped Curve of Resting-State Networks in Individuals at High Risk of Alzheimer's Disease.

PubMed

Ye, Qing; Chen, Haifeng; Su, Fan; Shu, Hao; Gong, Liang; Xie, Chunming; Zhou, Hong; Bai, Feng

Higher functional connectivity (FC) in resting-state networks has been shown in individuals at risk of Alzheimer's disease (AD) by many studies. However, the longitudinal trajectories of the FC remain unknown. The present 35-month follow-up study aimed to explore longitudinal changes in higher FC in multiple resting-state networks in subjects with the apolipoprotein E ε4 allele (ApoE4) and/or amnestic mild cognitive impairment (aMCI). Fifty-one subjects with aMCI and 64 cognitively normal (CN) subjects underwent neuropsychological tests and resting-state functional magnetic resonance imaging (fMRI) scans twice from April 2011 to June 2015. Subjects were divided into 4 groups according to diagnosis and ApoE4 status. The CN non-ApoE4 group served as a control group, and other groups served as AD risk groups. The cross-sectional and longitudinal patterns of multiple resting-state networks, including default mode network, hippocampus network, executive control network, and salience network, were explored by comparing FC data between groups and between time points, respectively. At baseline, compared with the control group, the AD risk groups showed higher FC with 8 regions in multiple networks. At follow-up, 6 of the regions displayed longitudinally decreased FC in AD risk groups. In contrast, the FC with all of these regions was maintained in the control group. Notably, among the 3 risk groups, most of the higher FC at baseline (5 of the 8 regions) and longitudinally decreased FC at follow-up (4 of the 6 regions) were shown in the aMCI ApoE4 group. Higher resting-state FC is followed by a decline in subjects at AD risk, and this inverse U-shaped trajectory is more notable in subjects with higher risk. © Copyright 2018 Physicians Postgraduate Press, Inc.

The CB1 Neutral Antagonist Tetrahydrocannabivarin Reduces Default Mode Network and Increases Executive Control Network Resting State Functional Connectivity in Healthy Volunteers.

PubMed

Rzepa, Ewelina; Tudge, Luke; McCabe, Ciara

2015-09-10

The cannabinoid cannabinoid type 1 (CB1) neutral antagonist tetrahydrocannabivarin (THCv) has been suggested as a possible treatment for obesity, but without the depressogenic side-effects of inverse antagonists such as Rimonabant. However, how THCv might affect the resting state functional connectivity of the human brain is as yet unknown. We examined the effects of a single 10mg oral dose of THCv and placebo in 20 healthy volunteers in a randomized, within-subject, double-blind design. Using resting state functional magnetic resonance imaging and seed-based connectivity analyses, we selected the amygdala, insula, orbitofrontal cortex, and dorsal medial prefrontal cortex (dmPFC) as regions of interest. Mood and subjective experience were also measured before and after drug administration using self-report scales. Our results revealed, as expected, no significant differences in the subjective experience with a single dose of THCv. However, we found reduced resting state functional connectivity between the amygdala seed region and the default mode network and increased resting state functional connectivity between the amygdala seed region and the dorsal anterior cingulate cortex and between the dmPFC seed region and the inferior frontal gyrus/medial frontal gyrus. We also found a positive correlation under placebo for the amygdala-precuneus connectivity with the body mass index, although this correlation was not apparent under THCv. Our findings are the first to show that treatment with the CB1 neutral antagonist THCv decreases resting state functional connectivity in the default mode network and increases connectivity in the cognitive control network and dorsal visual stream network. This effect profile suggests possible therapeutic activity of THCv for obesity, where functional connectivity has been found to be altered in these regions. © The Author 2015. Published by Oxford University Press on behalf of CINP.

A Novel Data-Driven Approach to Preoperative Mapping of Functional Cortex Using Resting-State Functional Magnetic Resonance Imaging

PubMed Central

Mitchell, Timothy J.; Hacker, Carl D.; Breshears, Jonathan D.; Szrama, Nick P.; Sharma, Mohit; Bundy, David T.; Pahwa, Mrinal; Corbetta, Maurizio; Snyder, Abraham Z.; Shimony, Joshua S.

2013-01-01

BACKGROUND: Recent findings associated with resting-state cortical networks have provided insight into the brain's organizational structure. In addition to their neuroscientific implications, the networks identified by resting-state functional magnetic resonance imaging (rs-fMRI) may prove useful for clinical brain mapping. OBJECTIVE: To demonstrate that a data-driven approach to analyze resting-state networks (RSNs) is useful in identifying regions classically understood to be eloquent cortex as well as other functional networks. METHODS: This study included 6 patients undergoing surgical treatment for intractable epilepsy and 7 patients undergoing tumor resection. rs-fMRI data were obtained before surgery and 7 canonical RSNs were identified by an artificial neural network algorithm. Of these 7, the motor and language networks were then compared with electrocortical stimulation (ECS) as the gold standard in the epilepsy patients. The sensitivity and specificity for identifying these eloquent sites were calculated at varying thresholds, which yielded receiver-operating characteristic (ROC) curves and their associated area under the curve (AUC). RSNs were plotted in the tumor patients to observe RSN distortions in altered anatomy. RESULTS: The algorithm robustly identified all networks in all patients, including those with distorted anatomy. When all ECS-positive sites were considered for motor and language, rs-fMRI had AUCs of 0.80 and 0.64, respectively. When the ECS-positive sites were analyzed pairwise, rs-fMRI had AUCs of 0.89 and 0.76 for motor and language, respectively. CONCLUSION: A data-driven approach to rs-fMRI may be a new and efficient method for preoperative localization of numerous functional brain regions. ABBREVIATIONS: AUC, area under the curve BA, Brodmann area BOLD, blood oxygen level dependent ECS, electrocortical stimulation fMRI, functional magnetic resonance imaging ICA, independent component analysis MLP, multilayer perceptron MP-RAGE, magnetization-prepared rapid gradient echo ROC, receiver-operating characteristic rs-fMRI, resting-state functional magnetic resonance imaging RSN, resting-state network PMID:24264234

Exploring variations in functional connectivity of the resting state default mode network in mild traumatic brain injury.

PubMed

Nathan, Dominic E; Oakes, Terrence R; Yeh, Ping Hong; French, Louis M; Harper, Jamie F; Liu, Wei; Wolfowitz, Rachel D; Wang, Bin Quan; Graner, John L; Riedy, Gerard

2015-03-01

A definitive diagnosis of mild traumatic brain injury (mTBI) is difficult due to the absence of biomarkers in standard clinical imaging. The brain is a complex network of interconnected neurons and subtle changes can modulate key networks of cognitive function. The resting state default mode network (DMN) has been shown to be sensitive to changes induced by pathology. This study seeks to determine whether quantitative measures of the DMN are sensitive in distinguishing mTBI subjects. Resting state functional magnetic resonance imaging data were obtained for healthy (n=12) and mTBI subjects (n=15). DMN maps were computed using dual-regression Independent Component Analysis (ICA). A goodness-of-fit (GOF) index was calculated to assess the degree of spatial specificity and sensitivity between healthy controls and mTBI subjects. DMN regions and neuropsychological assessments were examined to identify potential relationships. The resting state DMN maps indicate an increase in spatial coactivity in mTBI subjects within key regions of the DMN. Significant coactivity within the cerebellum and supplementary motor areas of mTBI subjects were also observed. This has not been previously reported in seed-based resting state network analysis. The GOF suggested the presence of high variability within the mTBI subject group, with poor sensitivity and specificity. The neuropsychological data showed correlations between areas of coactivity within the resting state network in the brain with a number of measures of emotion and cognitive functioning. The poor performance of the GOF highlights the key challenge associated with mTBI injury: the high variability in injury mechanisms and subsequent recovery. However, the quantification of the DMN using dual-regression ICA has potential to distinguish mTBI from healthy subjects, and provide information on the relationship of aspects of cognitive and emotional functioning with their potential neural correlates.

Resting-state functional brain networks in first-episode psychosis: A 12-month follow-up study.

PubMed

Ganella, Eleni P; Seguin, Caio; Pantelis, Christos; Whittle, Sarah; Baune, Bernhard T; Olver, James; Amminger, G Paul; McGorry, Patrick D; Cropley, Vanessa; Zalesky, Andrew; Bartholomeusz, Cali F

2018-05-01

Schizophrenia is increasingly conceived as a disorder of brain network connectivity and organization. However, reports of network abnormalities during the early illness stage of psychosis are mixed. This study adopted a data-driven whole-brain approach to investigate functional connectivity and network architecture in a first-episode psychosis cohort relative to healthy controls and whether functional network properties changed abnormally over a 12-month period in first-episode psychosis. Resting-state functional connectivity was performed at two time points. At baseline, 29 first-episode psychosis individuals and 30 healthy controls were assessed, and at 12 months, 14 first-episode psychosis individuals and 20 healthy controls completed follow-up. Whole-brain resting-state functional connectivity networks were mapped for each individual and analyzed using graph theory to investigate whether network abnormalities associated with first-episode psychosis were evident and whether functional network properties changed abnormally over 12 months relative to controls. This study found no evidence of abnormal resting-state functional connectivity or topology in first-episode psychosis individuals relative to healthy controls at baseline or at 12-months follow-up. Furthermore, longitudinal changes in network properties over a 12-month period did not significantly differ between first-episode psychosis individuals and healthy control. Network measures did not significantly correlate with symptomatology, duration of illness or antipsychotic medication. This is the first study to show unaffected resting-state functional connectivity and topology in the early psychosis stage of illness. In light of previous literature, this suggests that a subgroup of first-episode psychosis individuals who have a neurotypical resting-state functional connectivity and topology may exist. Our preliminary longitudinal analyses indicate that there also does not appear to be deterioration in these network properties over a 12-month period. Future research in a larger sample is necessary to confirm our longitudinal findings.

Global and System-Specific Resting-State fMRI Fluctuations Are Uncorrelated: Principal Component Analysis Reveals Anti-Correlated Networks

PubMed Central

Carbonell, Felix; Bellec, Pierre

2011-01-01

Abstract The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)–based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed robust anti-correlations between resting-state fluctuations in the default-mode and the task-positive networks. We conclude that resting-state global fluctuations and network-specific fluctuations are uncorrelated, supporting a Resting-State Linear-Additive Model. In addition, we conclude that the network-specific resting-state fluctuations of the default-mode and task-positive networks show artifact-free anti-correlations. PMID:22444074

The Ensembl REST API: Ensembl Data for Any Language.

PubMed

Yates, Andrew; Beal, Kathryn; Keenan, Stephen; McLaren, William; Pignatelli, Miguel; Ritchie, Graham R S; Ruffier, Magali; Taylor, Kieron; Vullo, Alessandro; Flicek, Paul

2015-01-01

We present a Web service to access Ensembl data using Representational State Transfer (REST). The Ensembl REST server enables the easy retrieval of a wide range of Ensembl data by most programming languages, using standard formats such as JSON and FASTA while minimizing client work. We also introduce bindings to the popular Ensembl Variant Effect Predictor tool permitting large-scale programmatic variant analysis independent of any specific programming language. The Ensembl REST API can be accessed at http://rest.ensembl.org and source code is freely available under an Apache 2.0 license from http://github.com/Ensembl/ensembl-rest. © The Author 2014. Published by Oxford University Press.

A Meta-analysis on Resting State High-frequency Heart Rate Variability in Bulimia Nervosa.

PubMed

Peschel, Stephanie K V; Feeling, Nicole R; Vögele, Claus; Kaess, Michael; Thayer, Julian F; Koenig, Julian

2016-09-01

Autonomic nervous system function is altered in eating disorders. We aimed to quantify differences in resting state vagal activity, indexed by high-frequency heart rate variability comparing patients with bulimia nervosa (BN) and healthy controls. A systematic search of the literature to identify studies eligible for inclusion and meta-analytical methods were applied. Meta-regression was used to identify potential covariates. Eight studies reporting measures of resting high-frequency heart rate variability in individuals with BN (n = 137) and controls (n = 190) were included. Random-effects meta-analysis revealed a sizeable main effect (Z = 2.22, p = .03; Hedge's g = 0.52, 95% CI [0.06;0.98]) indicating higher resting state vagal activity in individuals with BN. Meta-regression showed that body mass index and medication intake are significant covariates. Findings suggest higher vagal activity in BN at rest, particularly in unmedicated samples with lower body mass index. Potential mechanisms underlying these findings and implications for routine clinical care are discussed. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association.

Modulation of critical brain dynamics using closed-loop neurofeedback stimulation.

PubMed

Zhigalov, Alexander; Kaplan, Alexander; Palva, J Matias

2016-08-01

EEG long-range temporal correlations (LRTCs) are a significant for both human cognition and brain disorders, but beyond suppression by sensory disruption, there are little means for influencing them non-invasively. We hypothesized that LRTCs could be controlled by engaging intrinsic neuroregulation through closed-loop neurofeedback stimulation. We used a closed-loop-stimulation paradigm where supra-threshold α-waves trigger visual flash stimuli while the subject performs the standard eyes-closed resting-state task. As a "sham" control condition, we applied similar stimulus sequences without the neurofeedback. Over three sessions, a significant difference in the LRTCs of α-band oscillations (U=89, p<0.028, Wilcoxon rank sum test) and their scalp topography (T=-2.92, p<0.010, T-test) emerged between the neurofeedback and sham conditions so that the LRTCs were stronger during neurofeedback than sham. No changes (F=0.16, p>0.69, ANOVA test) in the scalp topography of α-band power were observed in either condition. This study provides proof-of-concept for that EEG LRTCs, and hence critical brain dynamics, can be modulated with closed-loop stimulation in an automatic, involuntary fashion. We suggest that this modulation is mediated by an excitation-inhibition balance change achieved by the closed-loop neuroregulation. Automatic LRTC modulation opens novel avenues for both examining the functional roles of brain criticality in healthy subjects and for developing novel therapeutic approaches for brain disorders associated with abnormal LRTCs. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Computing the stability of steady-state solutions of mathematical models of the electrical activity in the heart.

PubMed

Tveito, Aslak; Skavhaug, Ola; Lines, Glenn T; Artebrant, Robert

2011-08-01

Instabilities in the electro-chemical resting state of the heart can generate ectopic waves that in turn can initiate arrhythmias. We derive methods for computing the resting state for mathematical models of the electro-chemical process underpinning a heartbeat, and we estimate the stability of the resting state by invoking the largest real part of the eigenvalues of a linearized model. The implementation of the methods is described and a number of numerical experiments illustrate the feasibility of the methods. In particular, we test the methods for problems where we can compare the solutions with analytical results, and problems where we have solutions computed by independent software. The software is also tested for a fairly realistic 3D model. Copyright © 2011 Elsevier Ltd. All rights reserved.

Identification of Propofol Binding Sites in a Nicotinic Acetylcholine Receptor with a Photoreactive Propofol Analog*

PubMed Central

Jayakar, Selwyn S.; Dailey, William P.; Eckenhoff, Roderic G.; Cohen, Jonathan B.

2013-01-01

Propofol, a widely used intravenous general anesthetic, acts at anesthetic concentrations as a positive allosteric modulator of γ-aminobutyric acid type A receptors and at higher concentration as an inhibitor of nicotinic acetylcholine receptors (nAChRs). Here, we characterize propofol binding sites in a muscle-type nAChR by use of a photoreactive analog of propofol, 2-isopropyl-5-[3-(trifluoromethyl)-3H-diazirin-3-yl]phenol (AziPm). Based upon radioligand binding assays, AziPm stabilized the Torpedo nAChR in the resting state, whereas propofol stabilized the desensitized state. nAChR-rich membranes were photolabeled with [3H]AziPm, and labeled amino acids were identified by Edman degradation. [3H]AziPm binds at three sites within the nAChR transmembrane domain: (i) an intrasubunit site in the δ subunit helix bundle, photolabeling in the nAChR desensitized state (+agonist) δM2-18′ and two residues in δM1 (δPhe-232 and δCys-236); (ii) in the ion channel, photolabeling in the nAChR resting, closed channel state (−agonist) amino acids in the M2 helices (αM2-6′, βM2-6′ and -13′, and δM2-13′) that line the channel lumen (with photolabeling reduced by >90% in the desensitized state); and (iii) at the γ-α interface, photolabeling αM2-10′. Propofol enhanced [3H]AziPm photolabeling at αM2-10′. Propofol inhibited [3H]AziPm photolabeling within the δ subunit helix bundle at lower concentrations (IC50 = 40 μm) than it inhibited ion channel photolabeling (IC50 = 125 μm). These results identify for the first time a single intrasubunit propofol binding site in the nAChR transmembrane domain and suggest that this is the functionally relevant inhibitory binding site. PMID:23300078

Altered functional connectivity in early Alzheimer's disease: a resting-state fMRI study.

PubMed

Wang, Kun; Liang, Meng; Wang, Liang; Tian, Lixia; Zhang, Xinqing; Li, Kuncheng; Jiang, Tianzi

2007-10-01

Previous studies have led to the proposal that patients with Alzheimer's disease (AD) may have disturbed functional connectivity between different brain regions. Furthermore, recent resting-state functional magnetic resonance imaging (fMRI) studies have also shown that low-frequency (<0.08 Hz) fluctuations (LFF) of the blood oxygenation level-dependent signals were abnormal in several brain areas of AD patients. However, few studies have investigated disturbed LFF connectivity in AD patients. By using resting-state fMRI, this study sought to investigate the abnormal functional connectivities throughout the entire brain of early AD patients, and analyze the global distribution of these abnormalities. For this purpose, the authors divided the whole brain into 116 regions and identified abnormal connectivities by comparing the correlation coefficients of each pair. Compared with healthy controls, AD patients had decreased positive correlations between the prefrontal and parietal lobes, but increased positive correlations within the prefrontal lobe, parietal lobe, and occipital lobe. The AD patients also had decreased negative correlations (closer to zero) between two intrinsically anti-correlated networks that had previously been found in the resting brain. By using resting-state fMRI, our results supported previous studies that have reported an anterior-posterior disconnection phenomenon and increased within-lobe functional connectivity in AD patients. In addition, the results also suggest that AD may disturb the correlation/anti-correlation effect in the two intrinsically anti-correlated networks. Wiley-Liss, Inc.

Effects of Soft Drinks on Resting State EEG and Brain-Computer Interface Performance.

PubMed

Meng, Jianjun; Mundahl, John; Streitz, Taylor; Maile, Kaitlin; Gulachek, Nicholas; He, Jeffrey; He, Bin

2017-01-01

Motor imagery-based (MI based) brain-computer interface (BCI) using electroencephalography (EEG) allows users to directly control a computer or external device by modulating and decoding the brain waves. A variety of factors could potentially affect the performance of BCI such as the health status of subjects or the environment. In this study, we investigated the effects of soft drinks and regular coffee on EEG signals under resting state and on the performance of MI based BCI. Twenty-six healthy human subjects participated in three or four BCI sessions with a resting period in each session. During each session, the subjects drank an unlabeled soft drink with either sugar (Caffeine Free Coca-Cola), caffeine (Diet Coke), neither ingredient (Caffeine Free Diet Coke), or a regular coffee if there was a fourth session. The resting state spectral power in each condition was compared; the analysis showed that power in alpha and beta band after caffeine consumption were decreased substantially compared to control and sugar condition. Although the attenuation of powers in the frequency range used for the online BCI control signal was shown, group averaged BCI online performance after consuming caffeine was similar to those of other conditions. This work, for the first time, shows the effect of caffeine, sugar intake on the online BCI performance and resting state brain signal.

Patients with Chronic Visceral Pain Show Sex-Related Alterations in Intrinsic Oscillations of the Resting Brain

PubMed Central

Hong, Jui-Yang; Kilpatrick, Lisa A.; Labus, Jennifer; Gupta, Arpana; Jiang, Zhiguo; Ashe-McNalley, Cody; Stains, Jean; Heendeniya, Nuwanthi; Ebrat, Bahar; Smith, Suzanne; Tillisch, Kirsten; Naliboff, Bruce

2013-01-01

Abnormal responses of the brain to delivered and expected aversive gut stimuli have been implicated in the pathophysiology of irritable bowel syndrome (IBS), a visceral pain syndrome occurring more commonly in women. Task-free resting-state functional magnetic resonance imaging (fMRI) can provide information about the dynamics of brain activity that may be involved in altered processing and/or modulation of visceral afferent signals. Fractional amplitude of low-frequency fluctuation is a measure of the power spectrum intensity of spontaneous brain oscillations. This approach was used here to identify differences in the resting-state activity of the human brain in IBS subjects compared with healthy controls (HCs) and to identify the role of sex-related differences. We found that both the female HCs and female IBS subjects had a frequency power distribution skewed toward high frequency to a greater extent in the amygdala and hippocampus compared with male subjects. In addition, female IBS subjects had a frequency power distribution skewed toward high frequency in the insula and toward low frequency in the sensorimotor cortex to a greater extent than male IBS subjects. Correlations were observed between resting-state blood oxygen level-dependent signal dynamics and some clinical symptom measures (e.g., abdominal discomfort). These findings provide the first insight into sex-related differences in IBS subjects compared with HCs using resting-state fMRI. PMID:23864686

Altered spontaneous activity in antisocial personality disorder revealed by regional homogeneity.

PubMed

Tang, Yan; Liu, Wangyong; Chen, Jingang; Liao, Jian; Hu, Dewen; Wang, Wei

2013-08-07

There is increasing evidence that antisocial personality disorder (ASPD) stems from brain abnormalities. However, there are only a few studies investigating brain structure in ASPD. The aim of this study was to find regional coherence abnormalities in resting-state functional MRI of ASPD. Thirty-two ASPD individuals and 34 controls underwent a resting-state functional MRI scan. The regional homogeneity (ReHo) approach was used to examine whether ASPD was related to alterations in resting-state neural activity. Support vector machine discriminant analysis was used to evaluate the sensitivity/specificity characteristics of the ReHo index in discriminating between the ASPD individuals and controls. The results showed that, compared with controls, ASPD individuals show lower ReHo in the right cerebellum posterior lobe (Crus1) and the right middle frontal gyrus, as well as higher ReHo in the right middle occipital gyrus (BA 19), left inferior temporal gyrus (BA 37), and right inferior occipital gyrus (cuneus, BA 18). All alternation regions reported a predictive accuracy above 70%. To our knowledge, this study was the first to study the change in regional activity coherence in the resting brain of ASPD individuals. These results not only elucidated the pathological mechanism of ASPD from a resting-state functional viewpoint but also showed that these alterations in ReHo may serve as potential markers for the detection of ASPD.

Abnormal resting state corticolimbic blood flow in depressed unmedicated patients with major depression: a (15)O-H(2)O PET study.

PubMed

Monkul, E Serap; Silva, Leandro A P; Narayana, Shalini; Peluso, Marco A M; Zamarripa, Frank; Nery, Fabiano G; Najt, Pablo; Li, John; Lancaster, Jack L; Fox, Peter T; Lafer, Beny; Soares, Jair C

2012-02-01

We investigated the differences in the resting state corticolimbic blood flow between 20 unmedicated depressed patients and 21 healthy comparisons. Resting state cerebral blood flow (CBF) was measured with H(2)(15)O PET. Anatomical MRI scans were performed on an Elscint 1.9 T Prestige system for PET-MRI coregistration. Significant changes in cerebral blood flow indicating neural activity were detected using an ROI-free image subtraction strategy. In addition, the resting blood flow in patients was correlated with the severity of depression as measured by HAM-D scores. Depressed patients showed decreases in blood flow in right anterior cingulate (Brodmann areas 24 and 32) and increased blood flow in left and right posterior cingulate (Brodmann areas 23, 29, 30), left parahippocampal gyrus (Brodmann area 36), and right caudate compared with healthy volunteers. The severity of depression was inversely correlated with the left middle and inferior frontal gyri (Brodmann areas 9 and 47) and right medial frontal gyrus (Brodmann area 10) and right anterior cingulate (Brodmann areas 24, 32) blood flow, and directly correlated with the right thalamus blood flow. These findings support previous reports of abnormalities in the resting state blood flow in the limbic-frontal structures in depressed patients compared to healthy volunteers. Copyright © 2011 Wiley Periodicals, Inc.

Splines and polynomial tools for flatness-based constrained motion planning

NASA Astrophysics Data System (ADS)

Suryawan, Fajar; De Doná, José; Seron, María

2012-08-01

This article addresses the problem of trajectory planning for flat systems with constraints. Flat systems have the useful property that the input and the state can be completely characterised by the so-called flat output. We propose a spline parametrisation for the flat output, the performance output, the states and the inputs. Using this parametrisation the problem of constrained trajectory planning can be cast into a simple quadratic programming problem. An important result is that the B-spline parametrisation used gives exact results for constrained linear continuous-time system. The result is exact in the sense that the constrained signal can be made arbitrarily close to the boundary without having intersampling issues (as one would have in sampled-data systems). Simulation examples are presented, involving the generation of rest-to-rest trajectories. In addition, an experimental result of the method is also presented, where two methods to generate trajectories for a magnetic-levitation (maglev) system in the presence of constraints are compared and each method's performance is discussed. The first method uses the nonlinear model of the plant, which turns out to belong to the class of flat systems. The second method uses a linearised version of the plant model around an operating point. In every case, a continuous-time description is used. The experimental results on a real maglev system reported here show that, in most scenarios, the nonlinear and linearised models produce almost similar, indistinguishable trajectories.

Dynamics and Physiological Roles of Stochastic Firing Patterns Near Bifurcation Points

NASA Astrophysics Data System (ADS)

Jia, Bing; Gu, Huaguang

2017-06-01

Different stochastic neural firing patterns or rhythms that appeared near polarization or depolarization resting states were observed in biological experiments on three nervous systems, and closely matched those simulated near bifurcation points between stable equilibrium point and limit cycle in a theoretical model with noise. The distinct dynamics of spike trains and interspike interval histogram (ISIH) of these stochastic rhythms were identified and found to build a relationship to the coexisting behaviors or fixed firing frequency of four different types of bifurcations. Furthermore, noise evokes coherence resonances near bifurcation points and plays important roles in enhancing information. The stochastic rhythms corresponding to Hopf bifurcation points with fixed firing frequency exhibited stronger coherence degree and a sharper peak in the power spectrum of the spike trains than those corresponding to saddle-node bifurcation points without fixed firing frequency. Moreover, the stochastic firing patterns changed to a depolarization resting state as the extracellular potassium concentration increased for the injured nerve fiber related to pathological pain or static blood pressure level increased for aortic depressor nerve fiber, and firing frequency decreased, which were different from the physiological viewpoint that firing frequency increased with increasing pressure level or potassium concentration. This shows that rhythms or firing patterns can reflect pressure or ion concentration information related to pathological pain information. Our results present the dynamics of stochastic firing patterns near bifurcation points, which are helpful for the identification of both dynamics and physiological roles of complex neural firing patterns or rhythms, and the roles of noise.

BCI Use and Its Relation to Adaptation in Cortical Networks.

PubMed

Casimo, Kaitlyn; Weaver, Kurt E; Wander, Jeremiah; Ojemann, Jeffrey G

2017-10-01

Brain-computer interfaces (BCIs) carry great potential in the treatment of motor impairments. As a new motor output, BCIs interface with the native motor system, but acquisition of BCI proficiency requires a degree of learning to integrate this new function. In this review, we discuss how BCI designs often take advantage of the brain's motor system infrastructure as sources of command signals. We highlight a growing body of literature examining how this approach leads to changes in activity across cortex, including beyond motor regions, as a result of learning the new skill of BCI control. We discuss the previous research identifying patterns of neural activity associated with BCI skill acquisition and use that closely resembles those associated with learning traditional native motor tasks. We then discuss recent work in animals probing changes in connectivity of the BCI control site, which were linked to BCI skill acquisition, and use this as a foundation for our original work in humans. We present our novel work showing changes in resting state connectivity across cortex following the BCI learning process. We find substantial, heterogeneous changes in connectivity across regions and frequencies, including interactions that do not involve the BCI control site. We conclude from our review and original work that BCI skill acquisition may potentially lead to significant changes in evoked and resting state connectivity across multiple cortical regions. We recommend that future studies of BCIs look beyond motor regions to fully describe the cortical networks involved and long-term adaptations resulting from BCI skill acquisition.

Closing Kynect and Restructuring Medicaid Threaten Kentucky's Health and Economy.

PubMed

Wright, Charles B; Vanderford, Nathan L

2017-08-01

Following passage of the Patient Protection and Affordable Care Act (ACA) in the United States, the Kentucky Health Benefit Exchange, Kynect, began operating in Kentucky in October 2013. Kentucky expanded Medicaid eligibility in January 2014. Together, Kynect and Medicaid expansion provided access to affordable health care coverage to hundreds of thousands of individuals in Kentucky. However, following the Kentucky gubernatorial election in 2015, the newly inaugurated governor moved to dismantle Kynect and restructure the Medicaid expansion, jeopardizing public health gains and the state economy. As the first state to announce both the closure and restructuring of a state health insurance marketplace and Medicaid expansion, Kentucky may serve as a test case for the rest of the nation for reversal of ACA-related health policies. This article describes Kynect and the Kentucky Medicaid expansion and examines the potential short-term and long-term impacts that may occur following changes in state health policy. Furthermore, this article will offer potential strategies to ameliorate the expected negative impacts of disruption of both Kynect and the Medicaid expansion, such as the creation of a new state insurance marketplace under a new governor, the implementation of a private option, and increasing the state minimum wage for workers. Copyright © 2017 by Duke University Press.

Resting state functional connectivity of the anterior striatum and prefrontal cortex predicts reading performance in school-age children.

PubMed

Alcauter, Sarael; García-Mondragón, Liliana; Gracia-Tabuenca, Zeus; Moreno, Martha B; Ortiz, Juan J; Barrios, Fernando A

2017-11-01

The current study investigated the neural basis of reading performance in 60 school-age Spanish-speaking children, aged 6 to 9years. By using a data-driven approach and an automated matching procedure, we identified a left-lateralized resting state network that included typical language regions (Wernicke's and Broca's regions), prefrontal cortex, pre- and post-central gyri, superior and middle temporal gyri, cerebellum, and subcortical regions, and explored its relevance for reading performance (accuracy, comprehension and speed). Functional connectivity of the left frontal and temporal cortices and subcortical regions predicted reading speed. These results extend previous findings on the relationship between functional connectivity and reading competence in children, providing new evidence about such relationships in previously unexplored regions in the resting brain, including the left caudate, putamen and thalamus. This work highlights the relevance of a broad network, functionally synchronized in the resting state, for the acquisition and perfecting of reading abilities in young children. Copyright © 2017 Elsevier Inc. All rights reserved.

Resting-State Alpha in Autism Spectrum Disorder and Alpha Associations with Thalamic Volume

ERIC Educational Resources Information Center

Edgar, J. Christopher; Heiken, Kory; Chen, Yu-Han; Herrington, John D.; Chow, Vivian; Liu, Song; Bloy, Luke; Huang, Mingxiong; Pandey, Juhi; Cannon, Katelyn M.; Qasmieh, Saba; Levy, Susan E.; Schultz, Robert T.; Roberts, Timothy P. L.

2015-01-01

Alpha circuits (8-12 Hz), necessary for basic and complex brain processes, are abnormal in autism spectrum disorder (ASD). The present study obtained estimates of resting-state (RS) alpha activity in children with ASD and examined associations between alpha activity, age, and clinical symptoms. Given that the thalamus modulates cortical RS alpha…

Brain Structure and Resting-State Functional Connectivity in University Professors with High Academic Achievement

ERIC Educational Resources Information Center

Li, Weiwei; Yang, Wenjing; Li, Wenfu; Li, Yadan; Wei, Dongtao; Li, Huimin; Qiu, Jiang; Zhang, Qinglin

2015-01-01

Creative persons play an important role in technical innovation and social progress. There is little research on the neural correlates with researchers with high academic achievement. We used a combined structural (regional gray matter volume, rGMV) and functional (resting-state functional connectivity analysis, rsFC) approach to examine the…

Reproducibility of resting state spinal cord networks in healthy volunteers at 7 Tesla.

PubMed

Barry, Robert L; Rogers, Baxter P; Conrad, Benjamin N; Smith, Seth A; Gore, John C

2016-06-01

We recently reported our findings of resting state functional connectivity in the human spinal cord: in a cohort of healthy volunteers we observed robust functional connectivity between left and right ventral (motor) horns and between left and right dorsal (sensory) horns (Barry et al., 2014). Building upon these results, we now quantify the within-subject reproducibility of bilateral motor and sensory networks (intraclass correlation coefficient=0.54-0.56) and explore the impact of including frequencies up to 0.13Hz. Our results suggest that frequencies above 0.08Hz may enhance the detectability of these resting state networks, which would be beneficial for practical studies of spinal cord functional connectivity. Copyright © 2016 Elsevier Inc. All rights reserved.

Disrupted metabolic and functional connectivity patterns of the posterior cingulate cortex in cirrhotic patients: a study combining magnetic resonance spectroscopy and resting-state functional magnetic resonance imaging.

PubMed

Lu, Li; Wang, Junpeng; Zhang, Longjiang; Zhang, Zhiqiang; Ni, Ling; Qi, Rongfeng; Kong, Xiang; Lu, Mengjie; Sami, Muhammad U; Xu, Kai; Lu, Guangming

2018-06-26

The association between metabolic activity and functional coupling of the posterior cingulate cortex (PCC) in cirrhotic patients remains undefined. Therefore, this study aimed to assess the association of functional coupling with metabolic patterns of PCC in resting cirrhotic patients. Twenty-six cirrhotic patients, including 10 with hepatic encephalopathy (HE) and 16 without HE, were assessed, alongside 21 control participants. Single-voxel proton magnetic resonance spectroscopy (MRS) of the PCC and resting-state functional MRI (rs-fMRI) were performed on a 3.0-T MR scanner. The ratios of all metabolites to creatine (Cr) and rs-fMRI parameters [including amplitude of low-frequency fluctuation (ALFF), node degree (Ki), and betweenness centrality (Bi)] were evaluated by analysis of variance. Associations of metabolite ratios with rs-fMRI parameters and venous ammonia were determined by Pearson's correlation analysis. Lower chlorine (Cho)/Cr (0.6±0.2 vs. 0.9±0.1, P<0.001) and higher ALFF (1.3±0.5 vs. 1.1±0.3, P=0.01) were found in cirrhotic patients in comparison with controls. In cirrhotic patients, the ALFF values correlated negatively with Cho/Cr (r=-0.397, P=0.044). Meanwhile, Bi values showed positive associations with glutamine+glutamate/Cr (r=0.500, P=0.009) and N-acetyl aspartate/Cr (r=0.581, P=0.006). In the HE subgroup, Ki correlated positively with Cho/Cr (r=0.867, P=0.001). In cirrhotic patients without HE, Bi values showed a high positive correlation with glutamate+glutamine/Cr (r=0.690, P=0.013). These findings suggest a close association between metabolic activity and functional coupling of the PCC in cirrhotic patients, especially those with HE, whose node degree of the PCC shows an overt positive correlation with Cho/Cr.

Effects of thyroid status on cold-adaptive thermogenesis in Brandt's vole, Microtus brandti.

PubMed

Liu, X T; LI, Q F; Huang, C X; Sun, R Y

1997-01-01

Hyper- and hypothyroidism were induced by subcutaneous injection of thyroxine and by oral administration of methimazol in Brandt's voles. The effects of the two treatments on metabolic thermogenesis at 25 degrees C and 4 degrees C were investigated. The level of resting metabolic rate was closely related to thyroid status: high in the hyperthyroid case and low in the hypothyroid case. However, no increase in resting metabolic rate occurred in either case during further cold acclimation. Hyperthyroidism resulted in an increased nonshivering thermogenesis, which was much enhanced by lower temperature, but hypothyroidism led to a suppressed nonshivering thermogenesis in the cold. The state-4 and state-3 respirations and the activities of cytochrome-c oxidase of liver mitochondria were elevated in hyperthyroid animals but attenuated in hypothyroid ones. However, these levels were scarcely changed after further cold acclimation. Both hyperthyroidism and cold acclimation induced the recruitment of brown adipose tissue, but brown adipose tissue was different biochemically in the two cases: in hyperthyroidism, the total protein was reduced, while fat content increased; in cold acclimation, the total and mitochondrial proteins were increased. However, in hypothyroid voles, the normal adaptive changes in brown adipose tissue were impaired in further cold acclimation. The activity of cytochromec oxidase in brown adipose tissue was increased by hyperthyroidism and enhanced in further cold. In contrast, its activity was inhibited in hypothyroid animals, though activated to some extent in cold. These results demonstrate that normal thyroid function is essential for the cold-induced increase of resting metabolic rate and nonshivering thermogenesis and that there is a synergism between thyroid hormone and cold acclimation in the regulation of nonshivering thermogenesis in Brandt's vole. In addition, the blunted response of brown adipocytes to the cold may be the cytological mechanism for the suppressed nonshivering thermogenesis found with hypothyroidism.

Bursting and critical layer frequencies in minimal turbulent dynamics and connections to exact coherent states

NASA Astrophysics Data System (ADS)

Park, Jae Sung; Shekar, Ashwin; Graham, Michael D.

2018-01-01

The dynamics of the turbulent near-wall region is known to be dominated by coherent structures. These near-wall coherent structures are observed to burst in a very intermittent fashion, exporting turbulent kinetic energy to the rest of the flow. In addition, they are closely related to invariant solutions known as exact coherent states (ECS), some of which display nonlinear critical layer dynamics (motions that are highly localized around the surface on which the streamwise velocity matches the wave speed of ECS). The present work aims to investigate temporal coherence in minimal channel flow relevant to turbulent bursting and critical layer dynamics and its connection to the instability of ECS. It is seen that the minimal channel turbulence displays frequencies very close to those displayed by an ECS family recently identified in the channel flow geometry. The frequencies of these ECS are determined by critical layer structures and thus might be described as "critical layer frequencies." While the bursting frequency is predominant near the wall, the ECS frequencies (critical layer frequencies) become predominant over the bursting frequency at larger distances from the wall, and increasingly so as Reynolds number increases. Turbulent bursts are classified into strong and relatively weak classes with respect to an intermittent approach to a lower branch ECS. This temporally intermittent approach is closely related to an intermittent low drag event, called hibernating turbulence, found in minimal and large domains. The relationship between the strong burst and the instability of the lower branch ECS is further discussed in state space. The state-space dynamics of strong bursts is very similar to that of the unstable manifolds of the lower branch ECS. In particular, strong bursting processes are always preceded by hibernation events. This precursor dynamics to strong turbulence may aid in development of more effective control schemes by a way of anticipating dynamics such as intermittent hibernating dynamics.

The tetramerization domain potentiates Kv4 channel function by suppressing closed-state inactivation.

PubMed

Tang, Yi-Quan; Zhou, Jing-Heng; Yang, Fan; Zheng, Jie; Wang, KeWei

2014-09-02

A-type Kv4 potassium channels undergo a conformational change toward a nonconductive state at negative membrane potentials, a dynamic process known as pre-open closed states or closed-state inactivation (CSI). CSI causes inhibition of channel activity without the prerequisite of channel opening, thus providing a dynamic regulation of neuronal excitability, dendritic signal integration, and synaptic plasticity at resting. However, the structural determinants underlying Kv4 CSI remain largely unknown. We recently showed that the auxiliary KChIP4a subunit contains an N-terminal Kv4 inhibitory domain (KID) that directly interacts with Kv4.3 channels to enhance CSI. In this study, we utilized the KChIP4a KID to probe key structural elements underlying Kv4 CSI. Using fluorescence resonance energy transfer two-hybrid mapping and bimolecular fluorescence complementation-based screening combined with electrophysiology, we identified the intracellular tetramerization (T1) domain that functions to suppress CSI and serves as a receptor for the binding of KID. Disrupting the Kv4.3 T1-T1 interaction interface by mutating C110A within the C3H1 motif of T1 domain facilitated CSI and ablated the KID-mediated enhancement of CSI. Furthermore, replacing the Kv4.3 T1 domain with the T1 domain from Kv1.4 (without the C3H1 motif) or Kv2.1 (with the C3H1 motif) resulted in channels functioning with enhanced or suppressed CSI, respectively. Taken together, our findings reveal a novel (to our knowledge) role of the T1 domain in suppressing Kv4 CSI, and that KChIP4a KID directly interacts with the T1 domain to facilitate Kv4.3 CSI, thus leading to inhibition of channel function. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Risperidone Effects on Brain Dynamic Connectivity-A Prospective Resting-State fMRI Study in Schizophrenia.

PubMed

Lottman, Kristin K; Kraguljac, Nina V; White, David M; Morgan, Charity J; Calhoun, Vince D; Butt, Allison; Lahti, Adrienne C

2017-01-01

Resting-state functional connectivity studies in schizophrenia evaluating average connectivity over the entire experiment have reported aberrant network integration, but findings are variable. Examining time-varying (dynamic) functional connectivity may help explain some inconsistencies. We assessed dynamic network connectivity using resting-state functional MRI in patients with schizophrenia, while unmedicated ( n  = 34), after 1 week ( n  = 29) and 6 weeks of treatment with risperidone ( n  = 24), as well as matched controls at baseline ( n  = 35) and after 6 weeks ( n  = 19). After identifying 41 independent components (ICs) comprising resting-state networks, sliding window analysis was performed on IC timecourses using an optimal window size validated with linear support vector machines. Windowed correlation matrices were then clustered into three discrete connectivity states (a relatively sparsely connected state, a relatively abundantly connected state, and an intermediately connected state). In unmedicated patients, static connectivity was increased between five pairs of ICs and decreased between two pairs of ICs when compared to controls, dynamic connectivity showed increased connectivity between the thalamus and somatomotor network in one of the three states. State statistics indicated that, in comparison to controls, unmedicated patients had shorter mean dwell times and fraction of time spent in the sparsely connected state, and longer dwell times and fraction of time spent in the intermediately connected state. Risperidone appeared to normalize mean dwell times after 6 weeks, but not fraction of time. Results suggest that static connectivity abnormalities in schizophrenia may partly be related to altered brain network temporal dynamics rather than consistent dysconnectivity within and between functional networks and demonstrate the importance of implementing complementary data analysis techniques.

Altered resting-state functional connectivity in patients with chronic bilateral vestibular failure.

PubMed

Göttlich, Martin; Jandl, Nico M; Wojak, Jann F; Sprenger, Andreas; von der Gablentz, Janina; Münte, Thomas F; Krämer, Ulrike M; Helmchen, Christoph

2014-01-01

Patients with bilateral vestibular failure (BVF) suffer from gait unsteadiness, oscillopsia and impaired spatial orientation. Brain imaging studies applying caloric irrigation to patients with BVF have shown altered neural activity of cortical visual-vestibular interaction: decreased bilateral neural activity in the posterior insula and parietal operculum and decreased deactivations in the visual cortex. It is unknown how this affects functional connectivity in the resting brain and how changes in connectivity are related to vestibular impairment. We applied a novel data driven approach based on graph theory to investigate altered whole-brain resting-state functional connectivity in BVF patients (n= 22) compared to age- and gender-matched healthy controls (n= 25) using resting-state fMRI. Changes in functional connectivity were related to subjective (vestibular scores) and objective functional parameters of vestibular impairment, specifically, the adaptive changes during active (self-guided) and passive (investigator driven) head impulse test (HIT) which reflects the integrity of the vestibulo-ocular reflex (VOR). BVF patients showed lower bilateral connectivity in the posterior insula and parietal operculum but higher connectivity in the posterior cerebellum compared to controls. Seed-based analysis revealed stronger connectivity from the right posterior insula to the precuneus, anterior insula, anterior cingulate cortex and the middle frontal gyrus. Excitingly, functional connectivity in the supramarginal gyrus (SMG) of the inferior parietal lobe and posterior cerebellum correlated with the increase of VOR gain during active as compared to passive HIT, i.e., the larger the adaptive VOR changes the larger was the increase in regional functional connectivity. Using whole brain resting-state connectivity analysis in BVF patients we show that enduring bilateral deficient or missing vestibular input leads to changes in resting-state connectivity of the brain. These changes in the resting brain are robust and task-independent as they were found in the absence of sensory stimulation and without a region-related a priori hypothesis. Therefore they may indicate a fundamental disease-related change in the resting brain. They may account for the patients' persistent deficits in visuo-spatial attention, spatial orientation and unsteadiness. The relation of increasing connectivity in the inferior parietal lobe, specifically SMG, to improvement of VOR during active head movements reflects cortical plasticity in BVF and may play a clinical role in vestibular rehabilitation.

A computational study of whole-brain connectivity in resting state and task fMRI

PubMed Central

Goparaju, Balaji; Rana, Kunjan D.; Calabro, Finnegan J.; Vaina, Lucia Maria

2014-01-01

Background We compared the functional brain connectivity produced during resting-state in which subjects were not actively engaged in a task with that produced while they actively performed a visual motion task (task-state). Material/Methods In this paper we employed graph-theoretical measures and network statistics in novel ways to compare, in the same group of human subjects, functional brain connectivity during resting-state fMRI with brain connectivity during performance of a high level visual task. We performed a whole-brain connectivity analysis to compare network statistics in resting and task states among anatomically defined Brodmann areas to investigate how brain networks spanning the cortex changed when subjects were engaged in task performance. Results In the resting state, we found strong connectivity among the posterior cingulate cortex (PCC), precuneus, medial prefrontal cortex (MPFC), lateral parietal cortex, and hippocampal formation, consistent with previous reports of the default mode network (DMN). The connections among these areas were strengthened while subjects actively performed an event-related visual motion task, indicating a continued and strong engagement of the DMN during task processing. Regional measures such as degree (number of connections) and betweenness centrality (number of shortest paths), showed that task performance induces stronger inter-regional connections, leading to a denser processing network, but that this does not imply a more efficient system as shown by the integration measures such as path length and global efficiency, and from global measures such as small-worldness. Conclusions In spite of the maintenance of connectivity and the “hub-like” behavior of areas, our results suggest that the network paths may be rerouted when performing the task condition. PMID:24947491

Electroencephalographic Fractal Dimension in Healthy Ageing and Alzheimer’s Disease

PubMed Central

Cottone, Carlo; Cancelli, Andrea; Rossini, Paolo Maria; Tecchio, Franca

2016-01-01

Brain activity is complex; a reflection of its structural and functional organization. Among other measures of complexity, the fractal dimension is emerging as being sensitive to neuronal damage secondary to neurological and psychiatric diseases. Here, we calculated Higuchi’s fractal dimension (HFD) in resting-state eyes-closed electroencephalography (EEG) recordings from 41 healthy controls (age: 20–89 years) and 67 Alzheimer’s Disease (AD) patients (age: 50–88 years), to investigate whether HFD is sensitive to brain activity changes typical in healthy aging and in AD. Additionally, we considered whether AD-accelerating effects of the copper fraction not bound to ceruloplasmin (also called “free” copper) are reflected in HFD fluctuations. The HFD measure showed an inverted U-shaped relationship with age in healthy people (R2 = .575, p < .001). Onset of HFD decline appeared around the age of 60, and was most evident in central-parietal regions. In this region, HFD decreased with aging stronger in the right than in the left hemisphere (p = .006). AD patients demonstrated reduced HFD compared to age- and education-matched healthy controls, especially in temporal-occipital regions. This was associated with decreasing cognitive status as assessed by mini-mental state examination, and with higher levels of non-ceruloplasmin copper. Taken together, our findings show that resting-state EEG complexity increases from youth to maturity and declines in healthy, aging individuals. In AD, brain activity complexity is further reduced in correlation with cognitive impairment. In addition, elevated levels of non-ceruloplasmin copper appear to accelerate the reduction of neural activity complexity. Overall, HDF appears to be a proper indicator for monitoring EEG-derived brain activity complexity in healthy and pathological aging. PMID:26872349

An aromatic amino acid in the coiled-coil 1 domain plays a crucial role in the auto-inhibitory mechanism of STIM1.

PubMed

Yu, Junwei; Zhang, Haining; Zhang, Mingshu; Deng, Yongqiang; Wang, Huiyu; Lu, Jingze; Xu, Tao; Xu, Pingyong

2013-09-15

STIM1 (stromal interaction molecule 1) is one of the key elements that mediate store-operated Ca²⁺ entry via CRAC (Ca²⁺- release-activated Ca²⁺) channels in immune and non-excitable cells. Under physiological conditions, the intramolecular auto-inhibitions in STIM1 C- and STIM1 N-termini play essential roles in keeping STIM1 in an inactive state. However, the auto-inhibitory mechanism of the STIM1 C-terminus is still unclear. In the present study, we first predicted a short inhibitory domain (residues 310-317) in human STIM1 that might determine the different localizations of human STIM1 from Caenorhabditis elegans STIM1 in resting cells. Next, we confirmed the prediction and further identified an aromatic amino acid residue, Tyr³¹⁶, that played a crucial role in maintaining STIM1 in a closed conformation in quiescent cells. Full-length STIM1-Y316A formed constitutive clusters near the plasma membrane and activated the CRAC channel in the resting state when co-expressed with Orai1. The introduction of a Y316A mutation caused the higher-order oligomerization of the in vitro purified STIM1 fragment containing both the auto-inhibitory domain and CAD(CRAC-activating domain).We propose that the Tyr³¹⁶ residue may be involved in the auto-inhibitory mechanism of the STIM1 C-terminus in the quiescent state. This inhibition could be achieved either by interacting with the CAD using hydrogen and/or hydrophobic bonds, or by an intermolecular interaction using repulsive forces, which maintained a dimeric STIM1.

Neural correlates of establishing, maintaining, and switching brain states

PubMed Central

Tang, Yi-Yuan; Rothbart, Mary K.; Posner, Michael I.

2012-01-01

Although the study of brain states is an old one in neuroscience, there has been growing interest in brain state specification owing to MRI studies tracing brain connectivity at rest. In this review, we summarize recent research on three relatively well-described brain states: the resting, alert, and meditation states. We explore the neural correlates of maintaining a state or switching between states, and argue that the anterior cingulate cortex and striatum play a critical role in state maintenance, whereas the insula has a major role in switching between states. Brain state may serve as a predictor of performance in a variety of perceptual, memory, and problem solving tasks. Thus, understanding brain states is critical for understanding human performance. PMID:22613871

Effects of emotional exposure on state anxiety after acute exercise.

PubMed

Smith, J Carson

2013-02-01

Despite the well-known anxiolytic effect of acute exercise, it is unknown if anxiety reductions after acute exercise conditions survive in the face of a subsequently experienced arousing emotional exposure. The purpose of this study was to compare the effects of moderate-intensity cycle ergometer exercise to a seated rest control condition on state anxiety symptoms after exposure to a variety of highly arousing pleasant and unpleasant stimuli. Thirty-seven healthy and normally physically active young adults completed two conditions on separate days: 1) 30 min of seated rest and 2) 30 min of moderate-intensity cycle ergometer exercise (RPE = 13; "somewhat hard"). After each condition, participants viewed 90 arousing pleasant, unpleasant, and neutral pictures from the International Affective Picture System for 30 min. State anxiety was measured before and 15 min after each condition, and again after exposure to the affective pictures. State anxiety significantly decreased from baseline to after the exercise and seated rest conditions (P = 0.003). After the emotional picture-viewing period, state anxiety significantly increased to baseline values after the seated rest condition (P = 0.001) but remained reduced after the exercise condition. These findings suggest that the anxiolytic effects of acute exercise may be resistant to the potentially detrimental effects on mood after exposure to arousing emotional stimuli.

Hearing voices in the resting brain: A review of intrinsic functional connectivity research on auditory verbal hallucinations

PubMed Central

Alderson-Day, Ben; McCarthy-Jones, Simon; Fernyhough, Charles

2018-01-01

Resting state networks (RSNs) are thought to reflect the intrinsic functional connectivity of brain regions. Alterations to RSNs have been proposed to underpin various kinds of psychopathology, including the occurrence of auditory verbal hallucinations (AVH). This review outlines the main hypotheses linking AVH and the resting state, and assesses the evidence for alterations to intrinsic connectivity provided by studies of resting fMRI in AVH. The influence of hallucinations during data acquisition, medication confounds, and movement are also considered. Despite a large variety of analytic methods and designs being deployed, it is possible to conclude that resting connectivity in the left temporal lobe in general and left superior temporal gyrus in particular are disrupted in AVH. There is also preliminary evidence of atypical connectivity in the default mode network and its interaction with other RSNs. Recommendations for future research include the adoption of a common analysis protocol to allow for more overlapping datasets and replication of intrinsic functional connectivity alterations. PMID:25956256

Whole brain resting-state analysis reveals decreased functional connectivity in major depression.

PubMed

Veer, Ilya M; Beckmann, Christian F; van Tol, Marie-José; Ferrarini, Luca; Milles, Julien; Veltman, Dick J; Aleman, André; van Buchem, Mark A; van der Wee, Nic J; Rombouts, Serge A R B

2010-01-01

Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within 6 months before inclusion) and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxel-wise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: (1) decreased bilateral amygdala and left anterior insula connectivity in an affective network, (2) reduced connectivity of the left frontal pole in a network associated with attention and working memory, and (3) decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or gray matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder.

Whole Brain Resting-State Analysis Reveals Decreased Functional Connectivity in Major Depression

PubMed Central

Veer, Ilya M.; Beckmann, Christian F.; van Tol, Marie-José; Ferrarini, Luca; Milles, Julien; Veltman, Dick J.; Aleman, André; van Buchem, Mark A.; van der Wee, Nic J.; Rombouts, Serge A.R.B.

2010-01-01

Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within 6 months before inclusion) and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxel-wise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: (1) decreased bilateral amygdala and left anterior insula connectivity in an affective network, (2) reduced connectivity of the left frontal pole in a network associated with attention and working memory, and (3) decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or gray matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder. PMID:20941370

The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced?

PubMed Central

Murphy, Kevin; Birn, Rasmus M.; Handwerker, Daniel A.; Jones, Tyler B.; Bandettini, Peter A.

2009-01-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step. PMID:18976716

The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?

PubMed

Murphy, Kevin; Birn, Rasmus M; Handwerker, Daniel A; Jones, Tyler B; Bandettini, Peter A

2009-02-01

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

Resting State Dense Array Gamma Oscillatory Activity as a Response Marker for Cerebellar-Repetitive Transcranial Magnetic Stimulation (rTMS) in Schizophrenia.

PubMed

Tikka, Sai Krishna; Garg, Shobit; Sinha, Vinod Kumar; Nizamie, S Haque; Goyal, Nishant

2015-12-01

As cerebellum and its abnormalities have been implicated in the pathophysiology of schizophrenia, repetitive transcranial magnetic stimulation (rTMS) of this alternate site has been suggested as a novel target for treating patients with this disorder. As resting state gamma activity measures functional brain connectivity, it could be used as a specific treatment marker. To investigate the effect of cerebellar-rTMS on resting state gamma activity, while studying its efficacy in recent onset schizophrenia patients. This rater-blinded prospective study was completed by 11 schizophrenia patients. They received 10 sessions of high-frequency (theta patterned) rTMS to midline cerebellum over 2 weeks. Resting state EEG was recorded using high (192-channel) resolution EEG at baseline and post rTMS. Gamma spectral power was calculated using fast Fourier transformation, Hanning window averaged over 8 scalp segments corresponding 8 lobes. Clinical improvement rated on the Positive and Negative Syndrome Scale and depressive symptoms assessed using the Calgary Depression Scale for Schizophrenia were other outcome variables. Nonparametric statistics were used. Over the treatment course, significant reduction was seen on negative syndrome and depression scores. Gamma spectral power in left frontal and temporal segments reduced significantly. Spearman correlation analysis showed that percentage reduction in psychopathology scores had significant positive correlation with percentage reduction in gamma spectral power. Cerebellar-rTMS might be an effective adjunct to treat intricate and lingering negative and affective symptoms. Resting state gamma spectral power in frontal and temporal regions might be used as a biomarker for treatment response.

Detection of resting state functional connectivity using partial correlation analysis: A study using multi-distance and whole-head probe near-infrared spectroscopy.

PubMed

Sakakibara, Eisuke; Homae, Fumitaka; Kawasaki, Shingo; Nishimura, Yukika; Takizawa, Ryu; Koike, Shinsuke; Kinoshita, Akihide; Sakurada, Hanako; Yamagishi, Mika; Nishimura, Fumichika; Yoshikawa, Akane; Inai, Aya; Nishioka, Masaki; Eriguchi, Yosuke; Matsuoka, Jun; Satomura, Yoshihiro; Okada, Naohiro; Kakiuchi, Chihiro; Araki, Tsuyoshi; Kan, Chiemi; Umeda, Maki; Shimazu, Akihito; Uga, Minako; Dan, Ippeita; Hashimoto, Hideki; Kawakami, Norito; Kasai, Kiyoto

2016-11-15

Multichannel near-infrared spectroscopy (NIRS) is a functional neuroimaging modality that enables easy-to-use and noninvasive measurement of changes in blood oxygenation levels. We developed a clinically-applicable method for estimating resting state functional connectivity (RSFC) with NIRS using a partial correlation analysis to reduce the influence of extraneural components. Using a multi-distance probe arrangement NIRS, we measured resting state brain activity for 8min in 17 healthy participants. Independent component analysis was used to extract shallow and deep signals from the original NIRS data. Pearson's correlation calculated from original signals was significantly higher than that calculated from deep signals, while partial correlation calculated from original signals was comparable to that calculated from deep (cerebral-tissue) signals alone. To further test the validity of our method, we also measured 8min of resting state brain activity using a whole-head NIRS arrangement consisting of 17 cortical regions in 80 healthy participants. Significant RSFC between neighboring, interhemispheric homologous, and some distant ipsilateral brain region pairs was revealed. Additionally, females exhibited higher RSFC between interhemispheric occipital region-pairs, in addition to higher connectivity between some ipsilateral pairs in the left hemisphere, when compared to males. The combined results of the two component experiments indicate that partial correlation analysis is effective in reducing the influence of extracerebral signals, and that NIRS is able to detect well-described resting state networks and sex-related differences in RSFC. Copyright © 2016 Elsevier Inc. All rights reserved.

Regional homogeneity changes between heroin relapse and non-relapse patients under methadone maintenance treatment: a resting-state fMRI study.

PubMed

Chang, Haifeng; Li, Wei; Li, Qiang; Chen, Jiajie; Zhu, Jia; Ye, Jianjun; Liu, Jierong; Li, Zhe; Li, Yongbin; Shi, Ming; Wang, Yarong; Wang, Wei

2016-08-18

Methadone maintenance treatment (MMT) is recognized as one of the most effective treatments for heroin addiction but its effect is dimmed by the high incidence of heroin relapse. However, underlying neurobiology mechanism of heroin relapse under MMT is still largely unknown. Here, we took advantage of a resting-state fMRI technique by analysis of regional homogeneity (ReHo), and tried to explore the difference of brain function between heroin relapsers and non-relapsers in MMT. Forty MMT patients were included and received a 12-month follow-up. All patients were given baseline resting-state fMRI scans by using a 3.0 T GE Signa Excite HD whole-body MRI system. Monthly self-report and urine test were used to assess heroin relapse or non-relapse. Subjective craving was measured with visual analog scale. The correlation between ReHo and the degree of heroin relapse was analyzed. Compared with the non-relapsers, ReHo values were increased in the bilateral medial orbitofrontal cortex, right caudate, and right cerebellum of the heroin relapsers while those in the left parahippocampal gyrus, left middle temporal gyrus, right lingual gyrus, and precuneus were decreased in heroin relapsers. Importantly, altered ReHo in the right caudate were positively correlated with heroin relapse rates or subjective craving response. Using the resting-state fMRI technique by analysis of ReHo, we provided the first resting-state fMRI evidence that right caudate may serve as a potential biomarker for heroin relapse prediction and also as a promising target for reducing relapse risk.

Intra-regional and inter-regional abnormalities and cognitive control deficits in young adult smokers.

PubMed

Feng, Dan; Yuan, Kai; Li, Yangding; Cai, Chenxi; Yin, Junsen; Bi, Yanzhi; Cheng, Jiadong; Guan, Yanyan; Shi, Sha; Yu, Dahua; Jin, Chenwang; Lu, Xiaoqi; Qin, Wei; Tian, Jie

2016-06-01

Tobacco use during later adolescence and young adulthood may cause serious neurophysiological changes; rationally, it is extremely important to study the relationship between brain dysfunction and behavioral performances in young adult smokers. Previous resting state studies investigated the neural mechanisms in smokers. Unfortunately, few studies focused on spontaneous activity differences between young adult smokers and nonsmokers from both intra-regional and inter-regional levels, less is known about the association between resting state abnormalities and behavioral deficits. Therefore, we used fractional amplitude of low frequency fluctuation (fALFF) and resting state functional connectivity (RSFC) to investigate the resting state spontaneous activity differences between young adult smokers and nonsmokers. A correlation analysis was carried out to assess the relationship between neuroimaging findings and clinical information (pack-years, cigarette dependence, age of onset and craving score) as well as cognitive control deficits measured by the Stroop task. Consistent with previous addiction findings, our results revealed the resting state abnormalities within frontostriatal circuits, i.e., enhanced spontaneous activity of the caudate and reduced functional strength between the caudate and anterior cingulate cortex (ACC) in young adult smokers. Moreover, the fALFF values of the caudate were correlated with craving and RSFC strength between the caudate and ACC was associated with the cognitive control impairments in young adult smokers. Our findings could lead to a better understanding of intrinsic functional architecture of baseline brain activity in young smokers by providing regional and brain circuit spontaneous neuronal activity properties as well as their association with cognitive control impairments.