Removal of muscle artifact from EEG data: comparison between stochastic (ICA and CCA) and deterministic (EMD and wavelet-based) approaches

NASA Astrophysics Data System (ADS)

Safieddine, Doha; Kachenoura, Amar; Albera, Laurent; Birot, Gwénaël; Karfoul, Ahmad; Pasnicu, Anca; Biraben, Arnaud; Wendling, Fabrice; Senhadji, Lotfi; Merlet, Isabelle

2012-12-01

Electroencephalographic (EEG) recordings are often contaminated with muscle artifacts. This disturbing myogenic activity not only strongly affects the visual analysis of EEG, but also most surely impairs the results of EEG signal processing tools such as source localization. This article focuses on the particular context of the contamination epileptic signals (interictal spikes) by muscle artifact, as EEG is a key diagnosis tool for this pathology. In this context, our aim was to compare the ability of two stochastic approaches of blind source separation, namely independent component analysis (ICA) and canonical correlation analysis (CCA), and of two deterministic approaches namely empirical mode decomposition (EMD) and wavelet transform (WT) to remove muscle artifacts from EEG signals. To quantitatively compare the performance of these four algorithms, epileptic spike-like EEG signals were simulated from two different source configurations and artificially contaminated with different levels of real EEG-recorded myogenic activity. The efficiency of CCA, ICA, EMD, and WT to correct the muscular artifact was evaluated both by calculating the normalized mean-squared error between denoised and original signals and by comparing the results of source localization obtained from artifact-free as well as noisy signals, before and after artifact correction. Tests on real data recorded in an epileptic patient are also presented. The results obtained in the context of simulations and real data show that EMD outperformed the three other algorithms for the denoising of data highly contaminated by muscular activity. For less noisy data, and when spikes arose from a single cortical source, the myogenic artifact was best corrected with CCA and ICA. Otherwise when spikes originated from two distinct sources, either EMD or ICA offered the most reliable denoising result for highly noisy data, while WT offered the better denoising result for less noisy data. These results suggest that the performance of muscle artifact correction methods strongly depend on the level of data contamination, and of the source configuration underlying EEG signals. Eventually, some insights into the numerical complexity of these four algorithms are given.

Detailed Characterization of Local Field Potential Oscillations and Their Relationship to Spike Timing in the Antennal Lobe of the Moth Manduca sexta

PubMed Central

Daly, Kevin C.; Galán, Roberto F.; Peters, Oakland J.; Staudacher, Erich M.

2011-01-01

The transient oscillatory model of odor identity encoding seeks to explain how odorants with spatially overlapped patterns of input into primary olfactory networks can be discriminated. This model provides several testable predictions about the distributed nature of network oscillations and how they control spike timing. To test these predictions, 16 channel electrode arrays were placed within the antennal lobe (AL) of the moth Manduca sexta. Unitary spiking and multi site local field potential (LFP) recordings were made during spontaneous activity and in response to repeated presentations of an odor panel. We quantified oscillatory frequency, cross correlations between LFP recording sites, and spike–LFP phase relationships. We show that odor-driven AL oscillations in Manduca are frequency modulating (FM) from ∼100 to 30 Hz; this was odorant and stimulus duration dependent. FM oscillatory responses were localized to one or two recording sites suggesting a localized (perhaps glomerular) not distributed source. LFP cross correlations further demonstrated that only a small (r < 0.05) distributed and oscillatory component was present. Cross spectral density analysis demonstrated the frequency of these weakly distributed oscillations was state dependent (spontaneous activity = 25–55 Hz; odor-driven = 55–85 Hz). Surprisingly, vector strength analysis indicated that unitary phase locking of spikes to the LFP was strongest during spontaneous activity and dropped significantly during responses. Application of bicuculline, a GABAA receptor antagonist, significantly lowered the frequency content of odor-driven distributed oscillatory activity. Bicuculline significantly reduced spike phase locking generally, but the ubiquitous pattern of increased phase locking during spontaneous activity persisted. Collectively, these results indicate that oscillations perform poorly as a stimulus-mediated spike synchronizing mechanism for Manduca and hence are incongruent with the transient oscillatory model. PMID:22046161

Uppermost synchronized generators of spike-wave activity are localized in limbic cortical areas in late-onset absence status epilepticus.

PubMed

Piros, Palma; Puskas, Szilvia; Emri, Miklos; Opposits, Gabor; Spisak, Tamas; Fekete, Istvan; Clemens, Bela

2014-03-01

Absence status (AS) epilepticus with generalized spike-wave pattern is frequently found in severely ill patients in whom several disease states co-exist. The cortical generators of the ictal EEG pattern and EEG functional connectivity (EEGfC) of this condition are unknown. The present study investigated the localization of the uppermost synchronized generators of spike-wave activity in AS. Seven patients with late-onset AS were investigated by EEG spectral analysis, LORETA (Low Resolution Electromagnetic Tomography) source imaging, and LSC (LORETA Source Correlation) analysis, which estimates cortico-cortical EEGfC among 23 ROIs (regions of interest) in each hemisphere. All the patients showed generalized ictal EEG activity. Maximum Z-scored spectral power was found in the 1-6 Hz and 12-14 Hz frequency bands. LORETA showed that the uppermost synchronized generators of 1-6 Hz band activity were localized in frontal and temporal cortical areas that are parts of the limbic system. For the 12-14 Hz band, abnormally synchronized generators were found in the antero-medial frontal cortex. Unlike the rather stereotyped spectral and LORETA findings, the individual EEGfC patterns were very dissimilar. The findings are discussed in the context of nonconvulsive seizure types and the role of the underlying cortical areas in late-onset AS. The diversity of the EEGfC patterns remains an enigma. Localizing the cortical generators of the EEG patterns contributes to understanding the neurophysiology of the condition. Copyright © 2013 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Large-scale recording of neuronal ensembles.

PubMed

Buzsáki, György

2004-05-01

How does the brain orchestrate perceptions, thoughts and actions from the spiking activity of its neurons? Early single-neuron recording research treated spike pattern variability as noise that needed to be averaged out to reveal the brain's representation of invariant input. Another view is that variability of spikes is centrally coordinated and that this brain-generated ensemble pattern in cortical structures is itself a potential source of cognition. Large-scale recordings from neuronal ensembles now offer the opportunity to test these competing theoretical frameworks. Currently, wire and micro-machined silicon electrode arrays can record from large numbers of neurons and monitor local neural circuits at work. Achieving the full potential of massively parallel neuronal recordings, however, will require further development of the neuron-electrode interface, automated and efficient spike-sorting algorithms for effective isolation and identification of single neurons, and new mathematical insights for the analysis of network properties.

Thalamic inhibition: diverse sources, diverse scales

PubMed Central

Halassa, Michael M.; Acsády, László

2016-01-01

The thalamus is the major source of cortical inputs shaping sensation, action and cognition. Thalamic circuits are targeted by two major inhibitory systems: the thalamic reticular nucleus (TRN) and extra-thalamic inhibitory (ETI) inputs. A unifying framework of how these systems operate is currently lacking. Here, we propose that TRN circuits are specialized to exert thalamic control at different spatiotemporal scales. Local inhibition of thalamic spike rates prevails during attentional selection whereas global inhibition more likely during sleep. In contrast, the ETI (arising from basal ganglia, zona incerta, anterior pretectum and pontine reticular formation) provides temporally-precise and focal inhibition, impacting spike timing. Together, these inhibitory systems allow graded control of thalamic output, enabling thalamocortical operations to dynamically match ongoing behavioral demands. PMID:27589879

Spike sorting of synchronous spikes from local neuron ensembles

PubMed Central

Pröpper, Robert; Alle, Henrik; Meier, Philipp; Geiger, Jörg R. P.; Obermayer, Klaus; Munk, Matthias H. J.

2015-01-01

Synchronous spike discharge of cortical neurons is thought to be a fingerprint of neuronal cooperativity. Because neighboring neurons are more densely connected to one another than neurons that are located further apart, near-synchronous spike discharge can be expected to be prevalent and it might provide an important basis for cortical computations. Using microelectrodes to record local groups of neurons does not allow for the reliable separation of synchronous spikes from different cells, because available spike sorting algorithms cannot correctly resolve the temporally overlapping waveforms. We show that high spike sorting performance of in vivo recordings, including overlapping spikes, can be achieved with a recently developed filter-based template matching procedure. Using tetrodes with a three-dimensional structure, we demonstrate with simulated data and ground truth in vitro data, obtained by dual intracellular recording of two neurons located next to a tetrode, that the spike sorting of synchronous spikes can be as successful as the spike sorting of nonoverlapping spikes and that the spatial information provided by multielectrodes greatly reduces the error rates. We apply the method to tetrode recordings from the prefrontal cortex of behaving primates, and we show that overlapping spikes can be identified and assigned to individual neurons to study synchronous activity in local groups of neurons. PMID:26289473

The Role of Skull Modeling in EEG Source Imaging for Patients with Refractory Temporal Lobe Epilepsy.

PubMed

Montes-Restrepo, Victoria; Carrette, Evelien; Strobbe, Gregor; Gadeyne, Stefanie; Vandenberghe, Stefaan; Boon, Paul; Vonck, Kristl; Mierlo, Pieter van

2016-07-01

We investigated the influence of different skull modeling approaches on EEG source imaging (ESI), using data of six patients with refractory temporal lobe epilepsy who later underwent successful epilepsy surgery. Four realistic head models with different skull compartments, based on finite difference methods, were constructed for each patient: (i) Three models had skulls with compact and spongy bone compartments as well as air-filled cavities, segmented from either computed tomography (CT), magnetic resonance imaging (MRI) or a CT-template and (ii) one model included a MRI-based skull with a single compact bone compartment. In all patients we performed ESI of single and averaged spikes marked in the clinical 27-channel EEG by the epileptologist. To analyze at which time point the dipole estimations were closer to the resected zone, ESI was performed at two time instants: the half-rising phase and peak of the spike. The estimated sources for each model were validated against the resected area, as indicated by the postoperative MRI. Our results showed that single spike analysis was highly influenced by the signal-to-noise ratio (SNR), yielding estimations with smaller distances to the resected volume at the peak of the spike. Although averaging reduced the SNR effects, it did not always result in dipole estimations lying closer to the resection. The proposed skull modeling approaches did not lead to significant differences in the localization of the irritative zone from clinical EEG data with low spatial sampling density. Furthermore, we showed that a simple skull model (MRI-based) resulted in similar accuracy in dipole estimation compared to more complex head models (based on CT- or CT-template). Therefore, all the considered head models can be used in the presurgical evaluation of patients with temporal lobe epilepsy to localize the irritative zone from low-density clinical EEG recordings.

Reliability of directional information in unsorted spikes and local field potentials recorded in human motor cortex.

PubMed

Perge, János A; Zhang, Shaomin; Malik, Wasim Q; Homer, Mark L; Cash, Sydney; Friehs, Gerhard; Eskandar, Emad N; Donoghue, John P; Hochberg, Leigh R

2014-08-01

Action potentials and local field potentials (LFPs) recorded in primary motor cortex contain information about the direction of movement. LFPs are assumed to be more robust to signal instabilities than action potentials, which makes LFPs, along with action potentials, a promising signal source for brain-computer interface applications. Still, relatively little research has directly compared the utility of LFPs to action potentials in decoding movement direction in human motor cortex. We conducted intracortical multi-electrode recordings in motor cortex of two persons (T2 and [S3]) as they performed a motor imagery task. We then compared the offline decoding performance of LFPs and spiking extracted from the same data recorded across a one-year period in each participant. We obtained offline prediction accuracy of movement direction and endpoint velocity in multiple LFP bands, with the best performance in the highest (200-400 Hz) LFP frequency band, presumably also containing low-pass filtered action potentials. Cross-frequency correlations of preferred directions and directional modulation index showed high similarity of directional information between action potential firing rates (spiking) and high frequency LFPs (70-400 Hz), and increasing disparity with lower frequency bands (0-7, 10-40 and 50-65 Hz). Spikes predicted the direction of intended movement more accurately than any individual LFP band, however combined decoding of all LFPs was statistically indistinguishable from spike-based performance. As the quality of spiking signals (i.e. signal amplitude) and the number of significantly modulated spiking units decreased, the offline decoding performance decreased 3.6[5.65]%/month (for T2 and [S3] respectively). The decrease in the number of significantly modulated LFP signals and their decoding accuracy followed a similar trend (2.4[2.85]%/month, ANCOVA, p = 0.27[0.03]). Field potentials provided comparable offline decoding performance to unsorted spikes. Thus, LFPs may provide useful external device control using current human intracortical recording technology. ( NCT00912041.).

A Neocortical Delta Rhythm Facilitates Reciprocal Interlaminar Interactions via Nested Theta Rhythms

PubMed Central

Carracedo, Lucy M.; Kjeldsen, Henrik; Cunnington, Leonie; Jenkins, Alastair; Schofield, Ian; Cunningham, Mark O.; Davies, Ceri H.; Traub, Roger D.

2013-01-01

Delta oscillations (1–4 Hz) associate with deep sleep and are implicated in memory consolidation and replay of cortical responses elicited during wake states. A potent local generator has been characterized in thalamus, and local generators in neocortex have been suggested. Here we demonstrate that isolated rat neocortex generates delta rhythms in conditions mimicking the neuromodulatory state during deep sleep (low cholinergic and dopaminergic tone). The rhythm originated in an NMDA receptor-driven network of intrinsic bursting (IB) neurons in layer 5, activating a source of GABAB receptor-mediated inhibition. In contrast, regular spiking (RS) neurons in layer 5 generated theta-frequency outputs. In layer 2/3 principal cells, outputs from IB cells associated with IPSPs, whereas those from layer 5 RS neurons related to nested bursts of theta-frequency EPSPs. Both interlaminar spike and field correlations revealed a sequence of events whereby sparse spiking in layer 2/3 was partially reflected back from layer 5 on each delta period. We suggest that these reciprocal, interlaminar interactions may represent a “Helmholtz machine”-like process to control synaptic rescaling during deep sleep. PMID:23804097

Source localization of small sharp spikes: low resolution electromagnetic tomography (LORETA) reveals two distinct cortical sources.

PubMed

Zumsteg, Dominik; Andrade, Danielle M; Wennberg, Richard A

2006-06-01

We have investigated the cortical sources and electroencephalographic (EEG) characteristics of small sharp spikes (SSS) by using statistical non-parametric mapping (SNPM) of low resolution electromagnetic tomography (LORETA). We analyzed 7 SSS patterns (501 individual SSS) in 6 patients who underwent sleep EEG studies with 29 or 23 scalp electrodes. The scalp signals were averaged time-locked to the SSS peak activity and subjected to SNPM of LORETA values. All 7 SSS patterns (mean 72 individual SSS, range 11-200) revealed a very similar and highly characteristic transhemispheric oblique scalp voltage distribution comprising a first negative field maximum over ipsilateral lateral temporal areas, followed by a second negative field maximum over the contralateral subtemporal region approximately 30 ms later. SNPM-LORETA consistently localized the first component into the ipsilateral posterior insular region, and the second component into ipsilateral posterior mesial temporo-occipital structures. SSS comprise an amalgam of two sequential, distinct cortical components, showing a very uniform and peculiar EEG pattern and cortical source solutions. As such, they must be clearly distinguished from interictal epileptiform discharges in patients with epilepsy. The awareness of these peculiar EEG characteristics may increase our ability to differentiate SSS from interictal epileptiform activity. The finding of a posterior insular source might serve as an inspiration for new physiological considerations regarding these enigmatic waveforms.

Simultaneous deblending and interpolation using structure-oriented filters

NASA Astrophysics Data System (ADS)

Zhou, Yatong; Li, Song

2018-03-01

Simultaneous source shooting is a modern marine acquisition technology that accelerates field acquisition tremendously. However, we need to carefully remove the spike-like noise in the recorded seismic data, the process of which is called deblending. Considering the field obstacles, the recorded data may also contain missing traces. In this paper, we propose a very efficient way to simultaneously remove the spike-like noise to separate simultaneous sources and fill the data gaps in the recorded data. We propose to apply structure-oriented median and mean filters to reject the spike-like noise and restore the missing data. The commonly used median and mean filters guarantee the efficiency and convenience of the proposed algorithm framework. We use a robust slope estimation method to calculate the local slope of the structure patterns in the seismic data. Both synthetic and field data examples demonstrate the successful performance of the proposed algorithm. When compared with the state-of-the-art FK transform based projection onto convex sets (POCS) method, the presented method can obtain better performance with much less computational cost.

The value of magnetoencephalography for seizure-onset zone localization in magnetic resonance imaging-negative partial epilepsy

PubMed Central

Bouet, Romain; Delpuech, Claude; Ryvlin, Philippe; Isnard, Jean; Guenot, Marc; Bertrand, Olivier; Hammers, Alexander; Mauguière, François

2013-01-01

Surgical treatment of epilepsy is a challenge for patients with non-contributive brain magnetic resonance imaging. However, surgery is feasible if the seizure-onset zone is precisely delineated through intracranial electroencephalography recording. We recently described a method, volumetric imaging of epileptic spikes, to delineate the spiking volume of patients with focal epilepsy using magnetoencephalography. We postulated that the extent of the spiking volume delineated with volumetric imaging of epileptic spikes could predict the localizability of the seizure-onset zone by intracranial electroencephalography investigation and outcome of surgical treatment. Twenty-one patients with non-contributive magnetic resonance imaging findings were included. All patients underwent intracerebral electroencephalography investigation through stereotactically implanted depth electrodes (stereo-electroencephalography) and magnetoencephalography with delineation of the spiking volume using volumetric imaging of epileptic spikes. We evaluated the spatial congruence between the spiking volume determined by magnetoencephalography and the localization of the seizure-onset zone determined by stereo-electroencephalography. We also evaluated the outcome of stereo-electroencephalography and surgical treatment according to the extent of the spiking volume (focal, lateralized but non-focal or non-lateralized). For all patients, we found a spatial overlap between the seizure-onset zone and the spiking volume. For patients with a focal spiking volume, the seizure-onset zone defined by stereo-electroencephalography was clearly localized in all cases and most patients (6/7, 86%) had a good surgical outcome. Conversely, stereo-electroencephalography failed to delineate a seizure-onset zone in 57% of patients with a lateralized spiking volume, and in the two patients with bilateral spiking volume. Four of the 12 patients with non-focal spiking volumes were operated upon, none became seizure-free. As a whole, patients having focal magnetoencephalography results with volumetric imaging of epileptic spikes are good surgical candidates and the implantation strategy should incorporate volumetric imaging of epileptic spikes results. On the contrary, patients with non-focal magnetoencephalography results are less likely to have a localized seizure-onset zone and stereo electroencephalography is not advised unless clear localizing information is provided by other presurgical investigation methods. PMID:24014520

The value of magnetoencephalography for seizure-onset zone localization in magnetic resonance imaging-negative partial epilepsy.

PubMed

Jung, Julien; Bouet, Romain; Delpuech, Claude; Ryvlin, Philippe; Isnard, Jean; Guenot, Marc; Bertrand, Olivier; Hammers, Alexander; Mauguière, François

2013-10-01

Surgical treatment of epilepsy is a challenge for patients with non-contributive brain magnetic resonance imaging. However, surgery is feasible if the seizure-onset zone is precisely delineated through intracranial electroencephalography recording. We recently described a method, volumetric imaging of epileptic spikes, to delineate the spiking volume of patients with focal epilepsy using magnetoencephalography. We postulated that the extent of the spiking volume delineated with volumetric imaging of epileptic spikes could predict the localizability of the seizure-onset zone by intracranial electroencephalography investigation and outcome of surgical treatment. Twenty-one patients with non-contributive magnetic resonance imaging findings were included. All patients underwent intracerebral electroencephalography investigation through stereotactically implanted depth electrodes (stereo-electroencephalography) and magnetoencephalography with delineation of the spiking volume using volumetric imaging of epileptic spikes. We evaluated the spatial congruence between the spiking volume determined by magnetoencephalography and the localization of the seizure-onset zone determined by stereo-electroencephalography. We also evaluated the outcome of stereo-electroencephalography and surgical treatment according to the extent of the spiking volume (focal, lateralized but non-focal or non-lateralized). For all patients, we found a spatial overlap between the seizure-onset zone and the spiking volume. For patients with a focal spiking volume, the seizure-onset zone defined by stereo-electroencephalography was clearly localized in all cases and most patients (6/7, 86%) had a good surgical outcome. Conversely, stereo-electroencephalography failed to delineate a seizure-onset zone in 57% of patients with a lateralized spiking volume, and in the two patients with bilateral spiking volume. Four of the 12 patients with non-focal spiking volumes were operated upon, none became seizure-free. As a whole, patients having focal magnetoencephalography results with volumetric imaging of epileptic spikes are good surgical candidates and the implantation strategy should incorporate volumetric imaging of epileptic spikes results. On the contrary, patients with non-focal magnetoencephalography results are less likely to have a localized seizure-onset zone and stereo electroencephalography is not advised unless clear localizing information is provided by other presurgical investigation methods.

Multichannel interictal spike activity detection using time-frequency entropy measure.

PubMed

Thanaraj, Palani; Parvathavarthini, B

2017-06-01

Localization of interictal spikes is an important clinical step in the pre-surgical assessment of pharmacoresistant epileptic patients. The manual selection of interictal spike periods is cumbersome and involves a considerable amount of analysis workload for the physician. The primary focus of this paper is to automate the detection of interictal spikes for clinical applications in epilepsy localization. The epilepsy localization procedure involves detection of spikes in a multichannel EEG epoch. Therefore, a multichannel Time-Frequency (T-F) entropy measure is proposed to extract features related to the interictal spike activity. Least squares support vector machine is used to train the proposed feature to classify the EEG epochs as either normal or interictal spike period. The proposed T-F entropy measure, when validated with epilepsy dataset of 15 patients, shows an interictal spike classification accuracy of 91.20%, sensitivity of 100% and specificity of 84.23%. Moreover, the area under the curve of Receiver Operating Characteristics plot of 0.9339 shows the superior classification performance of the proposed T-F entropy measure. The results of this paper show a good spike detection accuracy without any prior information about the spike morphology.

Estimating Extracellular Spike Waveforms from CA1 Pyramidal Cells with Multichannel Electrodes

PubMed Central

Molden, Sturla; Moldestad, Olve; Storm, Johan F.

2013-01-01

Extracellular (EC) recordings of action potentials from the intact brain are embedded in background voltage fluctuations known as the “local field potential” (LFP). In order to use EC spike recordings for studying biophysical properties of neurons, the spike waveforms must be separated from the LFP. Linear low-pass and high-pass filters are usually insufficient to separate spike waveforms from LFP, because they have overlapping frequency bands. Broad-band recordings of LFP and spikes were obtained with a 16-channel laminar electrode array (silicone probe). We developed an algorithm whereby local LFP signals from spike-containing channel were modeled using locally weighted polynomial regression analysis of adjoining channels without spikes. The modeled LFP signal was subtracted from the recording to estimate the embedded spike waveforms. We tested the method both on defined spike waveforms added to LFP recordings, and on in vivo-recorded extracellular spikes from hippocampal CA1 pyramidal cells in anaesthetized mice. We show that the algorithm can correctly extract the spike waveforms embedded in the LFP. In contrast, traditional high-pass filters failed to recover correct spike shapes, albeit produceing smaller standard errors. We found that high-pass RC or 2-pole Butterworth filters with cut-off frequencies below 12.5 Hz, are required to retrieve waveforms comparable to our method. The method was also compared to spike-triggered averages of the broad-band signal, and yielded waveforms with smaller standard errors and less distortion before and after the spike. PMID:24391714

Local flow measurements at the inlet spike tip of a Mach 3 supersonic cruise airplane

NASA Technical Reports Server (NTRS)

Johnson, H. J.; Montoya, E. J.

1973-01-01

The flow field at the left inlet spike tip of a YF-12A airplane was examined using at 26 deg included angle conical flow sensor to obtain measurements at free-stream Mach numbers from 1.6 to 3.0. Local flow angularity, Mach number, impact pressure, and mass flow were determined and compared with free-stream values. Local flow changes occurred at the same time as free-stream changes. The local flow usually approached the spike centerline from the upper outboard side because of spike cant and toe-in. Free-stream Mach number influenced the local flow angularity; as Mach number increased above 2.2, local angle of attack increased and local sideslip angle decreased. Local Mach number was generally 3 percent less than free-stream Mach number. Impact-pressure ratio and mass flow ratio increased as free-stream Mach number increased above 2.2, indicating a beneficial forebody compression effect. No degradation of the spike tip instrumentation was observed after more than 40 flights in the high-speed thermal environment encountered by the airplane. The sensor is rugged, simple, and sensitive to small flow changes. It can provide accurate imputs necessary to control an inlet.

A Neural Code That Is Isometric to Vocal Output and Correlates with Its Sensory Consequences

PubMed Central

Vyssotski, Alexei L.; Stepien, Anna E.; Keller, Georg B.; Hahnloser, Richard H. R.

2016-01-01

What cortical inputs are provided to motor control areas while they drive complex learned behaviors? We study this question in the nucleus interface of the nidopallium (NIf), which is required for normal birdsong production and provides the main source of auditory input to HVC, the driver of adult song. In juvenile and adult zebra finches, we find that spikes in NIf projection neurons precede vocalizations by several tens of milliseconds and are insensitive to distortions of auditory feedback. We identify a local isometry between NIf output and vocalizations: quasi-identical notes produced in different syllables are preceded by highly similar NIf spike patterns. NIf multiunit firing during song precedes responses in auditory cortical neurons by about 50 ms, revealing delayed congruence between NIf spiking and a neural representation of auditory feedback. Our findings suggest that NIf codes for imminent acoustic events within vocal performance. PMID:27723764

EEG and MEG: sensitivity to epileptic spike activity as function of source orientation and depth.

PubMed

Hunold, A; Funke, M E; Eichardt, R; Stenroos, M; Haueisen, J

2016-07-01

Simultaneous electroencephalography (EEG) and magnetoencephalography (MEG) recordings of neuronal activity from epileptic patients reveal situations in which either EEG or MEG or both modalities show visible interictal spikes. While different signal-to-noise ratios (SNRs) of the spikes in EEG and MEG have been reported, a quantitative relation of spike source orientation and depth as well as the background brain activity to the SNR has not been established. We investigated this quantitative relationship for both dipole and patch sources in an anatomically realistic cortex model. Altogether, 5600 dipole and 3300 patch sources were distributed on the segmented cortical surfaces of two volunteers. The sources were classified according to their quantified depths and orientations, ranging from 20 mm to 60 mm below the skin surface and radial and tangential, respectively. The source time-courses mimicked an interictal spike, and the simulated background activity emulated resting activity. Simulations were conducted with individual three-compartment boundary element models. The SNR was evaluated for 128 EEG, 102 MEG magnetometer, and 204 MEG gradiometer channels. For superficial dipole and superficial patch sources, EEG showed higher SNRs for dominantly radial orientations, and MEG showed higher values for dominantly tangential orientations. Gradiometers provided higher SNR than magnetometers for superficial sources, particularly for those with dominantly tangential orientations. The orientation dependent difference in SNR in EEG and MEG gradually changed as the sources were located deeper, where the interictal spikes generated higher SNRs in EEG compared to those in MEG for all source orientations. With deep sources, the SNRs in gradiometers and magnetometers were of the same order. To better detect spikes, both EEG and MEG should be used.

Reliability of directional information in unsorted spikes and local field potentials recorded in human motor cortex

PubMed Central

Perge, János A.; Zhang, Shaomin; Malik, Wasim Q.; Homer, Mark L.; Cash, Sydney; Friehs, Gerhard; Eskandar, Emad N.; Donoghue, John P.; Hochberg, Leigh R.

2014-01-01

Objective Action potentials and local field potentials (LFPs) recorded in primary motor cortex contain information about the direction of movement. LFPs are assumed to be more robust to signal instabilities than action potentials, which makes LFPs along with action potentials a promising signal source for brain-computer interface applications. Still, relatively little research has directly compared the utility of LFPs to action potentials in decoding movement direction in human motor cortex. Approach We conducted intracortical multielectrode recordings in motor cortex of two persons (T2 and [S3]) as they performed a motor imagery task. We then compared the offline decoding performance of LFPs and spiking extracted from the same data recorded across a one-year period in each participant. Main results We obtained offline prediction accuracy of movement direction and endpoint velocity in multiple LFP bands, with the best performance in the highest (200–400Hz) LFP frequency band, presumably also containing low-pass filtered action potentials. Cross-frequency correlations of preferred directions and directional modulation index showed high similarity of directional information between action potential firing rates (spiking) and high frequency LFPs (70–400Hz), and increasing disparity with lower frequency bands (0–7, 10–40 and 50–65Hz). Spikes predicted the direction of intended movement more accurately than any individual LFP band, however combined decoding of all LFPs was statistically indistinguishable from spike based performance. As the quality of spiking signals (i.e. signal amplitude) and the number of significantly modulated spiking units decreased, the offline decoding performance decreased 3.6[5.65]%/month (for T2 and [S3] respectively). The decrease in the number of significantly modulated LFP signals and their decoding accuracy followed a similar trend (2.4[2.85]%/month, ANCOVA, p=0.27[0.03]). Significance Field potentials provided comparable offline decoding performance to unsorted spikes. Thus, LFPs may provide useful external device control using current human intracortical recording technology. (Clinical trial registration number: NCT00912041) PMID:24921388

Mixed Signal Learning by Spike Correlation Propagation in Feedback Inhibitory Circuits

PubMed Central

Hiratani, Naoki; Fukai, Tomoki

2015-01-01

The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory. PMID:25910189

Dynamic Hebbian Cross-Correlation Learning Resolves the Spike Timing Dependent Plasticity Conundrum.

PubMed

Olde Scheper, Tjeerd V; Meredith, Rhiannon M; Mansvelder, Huibert D; van Pelt, Jaap; van Ooyen, Arjen

2017-01-01

Spike Timing-Dependent Plasticity has been found to assume many different forms. The classic STDP curve, with one potentiating and one depressing window, is only one of many possible curves that describe synaptic learning using the STDP mechanism. It has been shown experimentally that STDP curves may contain multiple LTP and LTD windows of variable width, and even inverted windows. The underlying STDP mechanism that is capable of producing such an extensive, and apparently incompatible, range of learning curves is still under investigation. In this paper, it is shown that STDP originates from a combination of two dynamic Hebbian cross-correlations of local activity at the synapse. The correlation of the presynaptic activity with the local postsynaptic activity is a robust and reliable indicator of the discrepancy between the presynaptic neuron and the postsynaptic neuron's activity. The second correlation is between the local postsynaptic activity with dendritic activity which is a good indicator of matching local synaptic and dendritic activity. We show that this simple time-independent learning rule can give rise to many forms of the STDP learning curve. The rule regulates synaptic strength without the need for spike matching or other supervisory learning mechanisms. Local differences in dendritic activity at the synapse greatly affect the cross-correlation difference which determines the relative contributions of different neural activity sources. Dendritic activity due to nearby synapses, action potentials, both forward and back-propagating, as well as inhibitory synapses will dynamically modify the local activity at the synapse, and the resulting STDP learning rule. The dynamic Hebbian learning rule ensures furthermore, that the resulting synaptic strength is dynamically stable, and that interactions between synapses do not result in local instabilities. The rule clearly demonstrates that synapses function as independent localized computational entities, each contributing to the global activity, not in a simply linear fashion, but in a manner that is appropriate to achieve local and global stability of the neuron and the entire dendritic structure.

Contribution of LFP dynamics to single-neuron spiking variability in motor cortex during movement execution

PubMed Central

Rule, Michael E.; Vargas-Irwin, Carlos; Donoghue, John P.; Truccolo, Wilson

2015-01-01

Understanding the sources of variability in single-neuron spiking responses is an important open problem for the theory of neural coding. This variability is thought to result primarily from spontaneous collective dynamics in neuronal networks. Here, we investigate how well collective dynamics reflected in motor cortex local field potentials (LFPs) can account for spiking variability during motor behavior. Neural activity was recorded via microelectrode arrays implanted in ventral and dorsal premotor and primary motor cortices of non-human primates performing naturalistic 3-D reaching and grasping actions. Point process models were used to quantify how well LFP features accounted for spiking variability not explained by the measured 3-D reach and grasp kinematics. LFP features included the instantaneous magnitude, phase and analytic-signal components of narrow band-pass filtered (δ,θ,α,β) LFPs, and analytic signal and amplitude envelope features in higher-frequency bands. Multiband LFP features predicted single-neuron spiking (1ms resolution) with substantial accuracy as assessed via ROC analysis. Notably, however, models including both LFP and kinematics features displayed marginal improvement over kinematics-only models. Furthermore, the small predictive information added by LFP features to kinematic models was redundant to information available in fast-timescale (<100 ms) spiking history. Overall, information in multiband LFP features, although predictive of single-neuron spiking during movement execution, was redundant to information available in movement parameters and spiking history. Our findings suggest that, during movement execution, collective dynamics reflected in motor cortex LFPs primarily relate to sensorimotor processes directly controlling movement output, adding little explanatory power to variability not accounted by movement parameters. PMID:26157365

Do solar decimetric spikes originate in coronal X-ray sources?

NASA Astrophysics Data System (ADS)

Battaglia, M.; Benz, A. O.

2009-06-01

Context: In the standard solar flare scenario, a large number of particles are accelerated in the corona. Nonthermal electrons emit both X-rays and radio waves. Thus, correlated signatures of the acceleration process are predicted at both wavelengths, coinciding either close to the footpoints of a magnetic loop or near the coronal X-ray source. Aims: We attempt to study the spatial connection between coronal X-ray emission and decimetric radio spikes to determine the site and geometry of the acceleration process. Methods: The positions of radio-spike sources and coronal X-ray sources are determined and analyzed in a well-observed limb event. Radio spikes are identified in observations from the Phoenix-2 spectrometer. Data from the Nançay radioheliograph are used to determine the position of the radio spikes. RHESSI images in soft and hard X-ray wavelengths are used to determine the X-ray flare geometry. Those observations are complemented by images from GOES/SXI. Results: We find that the radio emission originates at altitudes much higher than the coronal X-ray source, having an offset from the coronal X-ray source amounting to 90´´ and to 113´´ and 131´´ from the two footpoints, averaged over time and frequency. Conclusions: Decimetric spikes do not originate from coronal X-ray flare sources contrary to previous expectations. However, the observations suggest a causal link between the coronal X-ray source, related to the major energy release site, and simultaneous activity in the higher corona.

Local Resistance Profiling of Ultra Shallow Junction Annealed with Combination of Spike Lamp and Laser Annealing Processes using Scanning Spreading Resistance Microscope

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

Abo, Satoshi; Nishikawa, Kazuhisa; Ushigome, Naoya

2011-01-07

Local resistance profiles of ultra shallow boron and arsenic implanted into silicon with energies of 2.0 and 4.0 keV and doses of 2.0x10{sup 15} and 1.0x10{sup 15} ions/cm{sup 2} activated by a combination of conventional spike lamp and laser annealing processes were measured by scanning spreading resistance microscope (SSRM) with a depth resolution of less than 10 nm. The lowest local resistance at the low resistance region in 2.0 keV boron implanted silicon with 1050 deg. C spike lamp annealing followed by 0.35 kW/mm{sup 2} laser annealing was half of that without laser annealing. The lowest local resistance at themore » low resistance region in the arsenic implanted silicon activated by 1050 deg. C spike lamp annealing followed by 0.39 kW/mm{sup 2} laser annealing was 74% lower than that followed by 0.36 kW/mm{sup 2} laser annealing. The lowest local resistances at the low resistance regions in the arsenic implanted silicon with 0.36 and 0.39 kW/mm{sup 2} laser annealing followed by 1050 deg. C spike lamp annealing were 41 and 33% lower than those with spike lamp annealing followed by laser annealing. Laser annealing followed by spike lamp annealing could suppress the diffusion of the impurities and was suitable for making the ultra shallow and low resistance regions.« less

Robust spike sorting of retinal ganglion cells tuned to spot stimuli.

PubMed

Ghahari, Alireza; Badea, Tudor C

2016-08-01

We propose an automatic spike sorting approach for the data recorded from a microelectrode array during visual stimulation of wild type retinas with tiled spot stimuli. The approach first detects individual spikes per electrode by their signature local minima. With the mixture probability distribution of the local minima estimated afterwards, it applies a minimum-squared-error clustering algorithm to sort the spikes into different clusters. A template waveform for each cluster per electrode is defined, and a number of reliability tests are performed on it and its corresponding spikes. Finally, a divisive hierarchical clustering algorithm is used to deal with the correlated templates per cluster type across all the electrodes. According to the measures of performance of the spike sorting approach, it is robust even in the cases of recordings with low signal-to-noise ratio.

Neuromagnetic Evidence of Spatially Distributed Sources Underlying Epileptiform Spikes in the Human Brain

NASA Astrophysics Data System (ADS)

Barth, Daniel S.; Sutherling, William; Engle, Jerome; Beatty, Jackson

1984-01-01

Neuromagnetic measurements were performed on 17 subjects with focal seizure disorders. In all of the subjects, the interictal spike in the scalp electroencephalogram was associated with an orderly extracranial magnetic field pattern. In eight of these subjects, multiple current sources underlay the magnetic spike complex. The multiple sources within a given subject displayed a fixed chronological sequence of discharge, demonstrating a high degree of spatial and temporal organization within the interictal focus.

Differences in the Electrophysiological Properties of Mouse Somatosensory Layer 2/3 Neurons In Vivo and Slice Stem from Intrinsic Sources Rather than a Network-Generated High Conductance State

PubMed Central

2018-01-01

Abstract Synaptic activity in vivo can potentially alter the integration properties of neurons. Using recordings in awake mice, we targeted somatosensory layer 2/3 pyramidal neurons and compared neuronal properties with those from slices. Pyramidal cells in vivo had lower resistance and gain values, as well as broader spikes and increased spike frequency adaptation compared to the same cells in slices. Increasing conductance in neurons using dynamic clamp to levels observed in vivo, however, did not lessen the differences between in vivo and slice conditions. Further, local application of tetrodotoxin (TTX) in vivo blocked synaptic-mediated membrane voltage fluctuations but had little impact on pyramidal cell membrane input resistance and time constant values. Differences in electrophysiological properties of layer 2/3 neurons in mouse somatosensory cortex, therefore, stem from intrinsic sources separate from synaptic-mediated membrane voltage fluctuations. PMID:29662946

Effect of sound level on virtual and free-field localization of brief sounds in the anterior median plane.

PubMed

Marmel, Frederic; Marrufo-Pérez, Miriam I; Heeren, Jan; Ewert, Stephan; Lopez-Poveda, Enrique A

2018-06-14

The detection of high-frequency spectral notches has been shown to be worse at 70-80 dB sound pressure level (SPL) than at higher levels up to 100 dB SPL. The performance improvement at levels higher than 70-80 dB SPL has been related to an 'ideal observer' comparison of population auditory nerve spike trains to stimuli with and without high-frequency spectral notches. Insofar as vertical localization partly relies on information provided by pinna-based high-frequency spectral notches, we hypothesized that localization would be worse at 70-80 dB SPL than at higher levels. Results from a first experiment using a virtual localization set-up and non-individualized head-related transfer functions (HRTFs) were consistent with this hypothesis, but a second experiment using a free-field set-up showed that vertical localization deteriorates monotonically with increasing level up to 100 dB SPL. These results suggest that listeners use different cues when localizing sound sources in virtual and free-field conditions. In addition, they confirm that the worsening in vertical localization with increasing level continues beyond 70-80 dB SPL, the highest levels tested by previous studies. Further, they suggest that vertical localization, unlike high-frequency spectral notch detection, does not rely on an 'ideal observer' analysis of auditory nerve spike trains. Copyright © 2018 Elsevier B.V. All rights reserved.

A high performing brain-machine interface driven by low-frequency local field potentials alone and together with spikes

NASA Astrophysics Data System (ADS)

Stavisky, Sergey D.; Kao, Jonathan C.; Nuyujukian, Paul; Ryu, Stephen I.; Shenoy, Krishna V.

2015-06-01

Objective. Brain-machine interfaces (BMIs) seek to enable people with movement disabilities to directly control prosthetic systems with their neural activity. Current high performance BMIs are driven by action potentials (spikes), but access to this signal often diminishes as sensors degrade over time. Decoding local field potentials (LFPs) as an alternative or complementary BMI control signal may improve performance when there is a paucity of spike signals. To date only a small handful of LFP decoding methods have been tested online; there remains a need to test different LFP decoding approaches and improve LFP-driven performance. There has also not been a reported demonstration of a hybrid BMI that decodes kinematics from both LFP and spikes. Here we first evaluate a BMI driven by the local motor potential (LMP), a low-pass filtered time-domain LFP amplitude feature. We then combine decoding of both LMP and spikes to implement a hybrid BMI. Approach. Spikes and LFP were recorded from two macaques implanted with multielectrode arrays in primary and premotor cortex while they performed a reaching task. We then evaluated closed-loop BMI control using biomimetic decoders driven by LMP, spikes, or both signals together. Main results. LMP decoding enabled quick and accurate cursor control which surpassed previously reported LFP BMI performance. Hybrid decoding of both spikes and LMP improved performance when spikes signal quality was mediocre to poor. Significance. These findings show that LMP is an effective BMI control signal which requires minimal power to extract and can substitute for or augment impoverished spikes signals. Use of this signal may lengthen the useful lifespan of BMIs and is therefore an important step towards clinically viable BMIs.

Localization of interictal epileptic spikes with MEG: optimization of an automated beamformer screening method (SAMepi) in a diverse epilepsy population

PubMed Central

Scott, Jonathan M.; Robinson, Stephen E.; Holroyd, Tom; Coppola, Richard; Sato, Susumu; Inati, Sara K.

2016-01-01

OBJECTIVE To describe and optimize an automated beamforming technique followed by identification of locations with excess kurtosis (g2) for efficient detection and localization of interictal spikes in medically refractory epilepsy patients. METHODS Synthetic Aperture Magnetometry with g2 averaged over a sliding time window (SAMepi) was performed in 7 focal epilepsy patients and 5 healthy volunteers. The effect of varied window lengths on detection of spiking activity was evaluated. RESULTS Sliding window lengths of 0.5–10 seconds performed similarly, with 0.5 and 1 second windows detecting spiking activity in one of the 3 virtual sensor locations with highest kurtosis. These locations were concordant with the region of eventual surgical resection in these 7 patients who remained seizure free at one year. Average g2 values increased with increasing sliding window length in all subjects. In healthy volunteers kurtosis values stabilized in datasets longer than two minutes. CONCLUSIONS SAMepi using g2 averaged over 1 second sliding time windows in datasets of at least 2 minutes duration reliably identified interictal spiking and the presumed seizure focus in these 7 patients. Screening the 5 locations with highest kurtosis values for spiking activity is an efficient and accurate technique for localizing interictal activity using MEG. SIGNIFICANCE SAMepi should be applied using the parameter values and procedure described for optimal detection and localization of interictal spikes. Use of this screening procedure could significantly improve the efficiency of MEG analysis if clinically validated. PMID:27760068

Neuronal Ensemble Synchrony during Human Focal Seizures

PubMed Central

Ahmed, Omar J.; Harrison, Matthew T.; Eskandar, Emad N.; Cosgrove, G. Rees; Madsen, Joseph R.; Blum, Andrew S.; Potter, N. Stevenson; Hochberg, Leigh R.; Cash, Sydney S.

2014-01-01

Seizures are classically characterized as the expression of hypersynchronous neural activity, yet the true degree of synchrony in neuronal spiking (action potentials) during human seizures remains a fundamental question. We quantified the temporal precision of spike synchrony in ensembles of neocortical neurons during seizures in people with pharmacologically intractable epilepsy. Two seizure types were analyzed: those characterized by sustained gamma (∼40–60 Hz) local field potential (LFP) oscillations or by spike-wave complexes (SWCs; ∼3 Hz). Fine (<10 ms) temporal synchrony was rarely present during gamma-band seizures, where neuronal spiking remained highly irregular and asynchronous. In SWC seizures, phase locking of neuronal spiking to the SWC spike phase induced synchrony at a coarse 50–100 ms level. In addition, transient fine synchrony occurred primarily during the initial ∼20 ms period of the SWC spike phase and varied across subjects and seizures. Sporadic coherence events between neuronal population spike counts and LFPs were observed during SWC seizures in high (∼80 Hz) gamma-band and during high-frequency oscillations (∼130 Hz). Maximum entropy models of the joint neuronal spiking probability, constrained only on single neurons' nonstationary coarse spiking rates and local network activation, explained most of the fine synchrony in both seizure types. Our findings indicate that fine neuronal ensemble synchrony occurs mostly during SWC, not gamma-band, seizures, and primarily during the initial phase of SWC spikes. Furthermore, these fine synchrony events result mostly from transient increases in overall neuronal network spiking rates, rather than changes in precise spiking correlations between specific pairs of neurons. PMID:25057195

Combined EEG/MEG Can Outperform Single Modality EEG or MEG Source Reconstruction in Presurgical Epilepsy Diagnosis

PubMed Central

Aydin, Ümit; Vorwerk, Johannes; Dümpelmann, Matthias; Küpper, Philipp; Kugel, Harald; Heers, Marcel; Wellmer, Jörg; Kellinghaus, Christoph; Haueisen, Jens; Rampp, Stefan; Stefan, Hermann; Wolters, Carsten H.

2015-01-01

We investigated two important means for improving source reconstruction in presurgical epilepsy diagnosis. The first investigation is about the optimal choice of the number of epileptic spikes in averaging to (1) sufficiently reduce the noise bias for an accurate determination of the center of gravity of the epileptic activity and (2) still get an estimation of the extent of the irritative zone. The second study focuses on the differences in single modality EEG (80-electrodes) or MEG (275-gradiometers) and especially on the benefits of combined EEG/MEG (EMEG) source analysis. Both investigations were validated with simultaneous stereo-EEG (sEEG) (167-contacts) and low-density EEG (ldEEG) (21-electrodes). To account for the different sensitivity profiles of EEG and MEG, we constructed a six-compartment finite element head model with anisotropic white matter conductivity, and calibrated the skull conductivity via somatosensory evoked responses. Our results show that, unlike single modality EEG or MEG, combined EMEG uses the complementary information of both modalities and thereby allows accurate source reconstructions also at early instants in time (epileptic spike onset), i.e., time points with low SNR, which are not yet subject to propagation and thus supposed to be closer to the origin of the epileptic activity. EMEG is furthermore able to reveal the propagation pathway at later time points in agreement with sEEG, while EEG or MEG alone reconstructed only parts of it. Subaveraging provides important and accurate information about both the center of gravity and the extent of the epileptogenic tissue that neither single nor grand-averaged spike localizations can supply. PMID:25761059

Surface mapping of spike potential fields: experienced EEGers vs. computerized analysis.

PubMed

Koszer, S; Moshé, S L; Legatt, A D; Shinnar, S; Goldensohn, E S

1996-03-01

An EEG epileptiform spike focus recorded with scalp electrodes is clinically localized by visual estimation of the point of maximal voltage and the distribution of its surrounding voltages. We compared such estimated voltage maps, drawn by experienced electroencephalographers (EEGers), with a computerized spline interpolation technique employed in the commercially available software package FOCUS. Twenty-two spikes were recorded from 15 patients during long-term continuous EEG monitoring. Maps of voltage distribution from the 28 electrodes surrounding the points of maximum change in slope (the spike maximum) were constructed by the EEGer. The same points of maximum spike and voltage distributions at the 29 electrodes were mapped by computerized spline interpolation and a comparison between the two methods was made. The findings indicate that the computerized spline mapping techniques employed in FOCUS construct voltage maps with similar maxima and distributions as the maps created by experienced EEGers. The dynamics of spike activity, including correlations, are better visualized using the computerized technique than by manual interpretation alone. Its use as a technique for spike localization is accurate and adds information of potential clinical value.

Unbiased and robust quantification of synchronization between spikes and local field potential.

PubMed

Li, Zhaohui; Cui, Dong; Li, Xiaoli

2016-08-30

In neuroscience, relating the spiking activity of individual neurons to the local field potential (LFP) of neural ensembles is an increasingly useful approach for studying rhythmic neuronal synchronization. Many methods have been proposed to measure the strength of the association between spikes and rhythms in the LFP recordings, and most existing measures are dependent upon the total number of spikes. In the present work, we introduce a robust approach for quantifying spike-LFP synchronization which performs reliably for limited samples of data. The measure is termed as spike-triggered correlation matrix synchronization (SCMS), which takes LFP segments centered on each spike as multi-channel signals and calculates the index of spike-LFP synchronization by constructing a correlation matrix. The simulation based on artificial data shows that the SCMS output almost does not change with the sample size. This property is of crucial importance when making comparisons between different experimental conditions. When applied to actual neuronal data recorded from the monkey primary visual cortex, it is found that the spike-LFP synchronization strength shows orientation selectivity to drifting gratings. In comparison to another unbiased method, pairwise phase consistency (PPC), the proposed SCMS behaves better for noisy spike trains by means of numerical simulations. This study demonstrates the basic idea and calculating process of the SCMS method. Considering its unbiasedness and robustness, the measure is of great advantage to characterize the synchronization between spike trains and rhythms present in LFP. Copyright © 2016 Elsevier B.V. All rights reserved.

Space-filling, multifractal, localized thermal spikes in Si, Ge and ZnO

NASA Astrophysics Data System (ADS)

Ahmad, Shoaib; Abbas, Muhammad Sabtain; Yousuf, Muhammad; Javeed, Sumera; Zeeshan, Sumaira; Yaqub, Kashif

2018-04-01

The mechanism responsible for the emission of clusters from heavy ion irradiated solids is proposed to be thermal spikes. Collision cascade-based theories describe atomic sputtering but cannot explain the consistently observed experimental evidence for significant cluster emission. Statistical thermodynamic arguments for thermal spikes are employed here for qualitative and quantitative estimation of the thermal spike-induced cluster emission from Si, Ge and ZnO. The evolving cascades and spikes in elemental and molecular semiconducting solids are shown to have fractal characteristics. Power law potential is used to calculate the fractal dimension. With the loss of recoiling particles' energy the successive branching ratios get smaller. The fractal dimension is shown to be dependent upon the exponent of the power law interatomic potential D = 1/2m. Each irradiating ion has the probability of initiating a space-filling, multifractal thermal spike that may sublime a localized region near the surface by emitting clusters in relative ratios that depend upon the energies of formation of respective surface vacancies.

Decoding intravesical pressure from local field potentials in rat lumbosacral spinal cord

NASA Astrophysics Data System (ADS)

Im, Changkyun; Park, Hae Yong; Koh, Chin Su; Ryu, Sang Baek; Seo, In Seok; Kim, Yong Jung; Kim, Kyung Hwan; Shin, Hyung-Cheul

2016-10-01

Chronic monitoring of intravesical pressure is required to detect the onset of intravesical hypertension and the progression of a more severe condition. Recent reports demonstrate the bladder state can be monitored from the spiking activity of the dorsal root ganglia or lumbosacral spinal cord. However, one of the most serious challenges for these methods is the difficulty of sustained spike signal acquisition due to the high-electrode-location-sensitivity of spikes or neuro-degeneration. Alternatively, it has been demonstrated that local field potential recordings are less affected by encapsulation reactions or electrode location changes. Here, we hypothesized that local field potential (LFP) from the lumbosacral dorsal horn may provide information concerning the intravesical pressure. LFP and spike activities were simultaneously recorded from the lumbosacral spinal cord of anesthetized rats during bladder filling. The results show that the LFP activities carry significant information about intravesical pressure along with spiking activities. Importantly, the intravesical pressure is decoded from the power in high-frequency bands (83.9-256 Hz) with a substantial performance similar to that of the spike train decoding. These findings demonstrate that high-frequency LFP activity can be an alternative intravesical pressure monitoring signal, which could lead to a proper closed loop system for urinary control.

Python for large-scale electrophysiology.

PubMed

Spacek, Martin; Blanche, Tim; Swindale, Nicholas

2008-01-01

Electrophysiology is increasingly moving towards highly parallel recording techniques which generate large data sets. We record extracellularly in vivo in cat and rat visual cortex with 54-channel silicon polytrodes, under time-locked visual stimulation, from localized neuronal populations within a cortical column. To help deal with the complexity of generating and analysing these data, we used the Python programming language to develop three software projects: one for temporally precise visual stimulus generation ("dimstim"); one for electrophysiological waveform visualization and spike sorting ("spyke"); and one for spike train and stimulus analysis ("neuropy"). All three are open source and available for download (http://swindale.ecc.ubc.ca/code). The requirements and solutions for these projects differed greatly, yet we found Python to be well suited for all three. Here we present our software as a showcase of the extensive capabilities of Python in neuroscience.

The Effect of Neural Noise on Spike Time Precision in a Detailed CA3 Neuron Model

PubMed Central

Kuriscak, Eduard; Marsalek, Petr; Stroffek, Julius; Wünsch, Zdenek

2012-01-01

Experimental and computational studies emphasize the role of the millisecond precision of neuronal spike times as an important coding mechanism for transmitting and representing information in the central nervous system. We investigate the spike time precision of a multicompartmental pyramidal neuron model of the CA3 region of the hippocampus under the influence of various sources of neuronal noise. We describe differences in the contribution to noise originating from voltage-gated ion channels, synaptic vesicle release, and vesicle quantal size. We analyze the effect of interspike intervals and the voltage course preceding the firing of spikes on the spike-timing jitter. The main finding of this study is the ranking of different noise sources according to their contribution to spike time precision. The most influential is synaptic vesicle release noise, causing the spike jitter to vary from 1 ms to 7 ms of a mean value 2.5 ms. Of second importance was the noise incurred by vesicle quantal size variation causing the spike time jitter to vary from 0.03 ms to 0.6 ms. Least influential was the voltage-gated channel noise generating spike jitter from 0.02 ms to 0.15 ms. PMID:22778784

Spatiotemporal mapping of interictal epileptiform discharges in human absence epilepsy: A MEG study.

PubMed

Rozendaal, Yvonne J W; van Luijtelaar, Gilles; Ossenblok, Pauly P W

2016-01-01

Although absence epilepsy is considered to be a prototypic type of generalized epilepsy, it is still under debate whether generalized 3 Hz spike-and-wave discharges (SWDs) might have a cortical focal origin. Here it is investigated whether focal interictal epileptiform discharges (IEDs), which typically occur in the electro- (EEG) and magnetoencephalogram (MEG) in case of focal epilepsy, are present in the MEG of children with absence epilepsy. Next, the location of the sources of the IEDs is established, and it is investigated whether the location is concordant to the earlier established focal cortical regions involved in the generalized SWDs of these children. Whole head MEG recordings of seven children with absence epilepsy were reviewed with respect to the presence of IEDs (spikes and sharp waves). These IEDs were grouped into distinct clusters, in which each contribution to a cluster yields a comparable magnetic field distribution. Source localization was then performed onto the average signal of each cluster using an equivalent current dipole model and a realistic head model of the cortical surface. IEDs were detected in 6 out of 7 patients. Source reconstruction indicated most often frontal, central or parietal origins of the IED in either the left and or right hemisphere. Spatiotemporal assessment of the IEDs indicated a stable location of the averages of these discharges, indicating a single underlying cortical source. The outcome of this pilot study shows that MEG is well suited for the detection of IEDs and suggests that their estimated sources coincide rather well with the cortical regions involved during the spikes of the SWDs. It is discussed whether the presence of IEDs, classically seen as a marker of focal epilepsies, indicate that absence epilepsy should be considered as a focal type of epilepsy, in which changes in the network are evolving rapidly. Copyright © 2015 Elsevier B.V. All rights reserved.

PySpike-A Python library for analyzing spike train synchrony

NASA Astrophysics Data System (ADS)

Mulansky, Mario; Kreuz, Thomas

Understanding how the brain functions is one of the biggest challenges of our time. The analysis of experimentally recorded neural firing patterns (spike trains) plays a crucial role in addressing this problem. Here, the PySpike library is introduced, a Python package for spike train analysis providing parameter-free and time-scale independent measures of spike train synchrony. It allows to compute similarity and dissimilarity profiles, averaged values and distance matrices. Although mainly focusing on neuroscience, PySpike can also be applied in other contexts like climate research or social sciences. The package is available as Open Source on Github and PyPI.

Local Variation of Hashtag Spike Trains and Popularity in Twitter

PubMed Central

Sanlı, Ceyda; Lambiotte, Renaud

2015-01-01

We draw a parallel between hashtag time series and neuron spike trains. In each case, the process presents complex dynamic patterns including temporal correlations, burstiness, and all other types of nonstationarity. We propose the adoption of the so-called local variation in order to uncover salient dynamical properties, while properly detrending for the time-dependent features of a signal. The methodology is tested on both real and randomized hashtag spike trains, and identifies that popular hashtags present regular and so less bursty behavior, suggesting its potential use for predicting online popularity in social media. PMID:26161650

Spike sorting using locality preserving projection with gap statistics and landmark-based spectral clustering.

PubMed

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2014-12-30

Understanding neural functions requires knowledge from analysing electrophysiological data. The process of assigning spikes of a multichannel signal into clusters, called spike sorting, is one of the important problems in such analysis. There have been various automated spike sorting techniques with both advantages and disadvantages regarding accuracy and computational costs. Therefore, developing spike sorting methods that are highly accurate and computationally inexpensive is always a challenge in the biomedical engineering practice. An automatic unsupervised spike sorting method is proposed in this paper. The method uses features extracted by the locality preserving projection (LPP) algorithm. These features afterwards serve as inputs for the landmark-based spectral clustering (LSC) method. Gap statistics (GS) is employed to evaluate the number of clusters before the LSC can be performed. The proposed LPP-LSC is highly accurate and computationally inexpensive spike sorting approach. LPP spike features are very discriminative; thereby boost the performance of clustering methods. Furthermore, the LSC method exhibits its efficiency when integrated with the cluster evaluator GS. The proposed method's accuracy is approximately 13% superior to that of the benchmark combination between wavelet transformation and superparamagnetic clustering (WT-SPC). Additionally, LPP-LSC computing time is six times less than that of the WT-SPC. LPP-LSC obviously demonstrates a win-win spike sorting solution meeting both accuracy and computational cost criteria. LPP and LSC are linear algorithms that help reduce computational burden and thus their combination can be applied into real-time spike analysis. Copyright © 2014 Elsevier B.V. All rights reserved.

Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex

PubMed Central

Storchi, Riccardo; Zippo, Antonio G.; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E. M.

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role. PMID:22586452

Predicting spike occurrence and neuronal responsiveness from LFPs in primary somatosensory cortex.

PubMed

Storchi, Riccardo; Zippo, Antonio G; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E M

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neuronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role.

Python for Large-Scale Electrophysiology

PubMed Central

Spacek, Martin; Blanche, Tim; Swindale, Nicholas

2008-01-01

Electrophysiology is increasingly moving towards highly parallel recording techniques which generate large data sets. We record extracellularly in vivo in cat and rat visual cortex with 54-channel silicon polytrodes, under time-locked visual stimulation, from localized neuronal populations within a cortical column. To help deal with the complexity of generating and analysing these data, we used the Python programming language to develop three software projects: one for temporally precise visual stimulus generation (“dimstim”); one for electrophysiological waveform visualization and spike sorting (“spyke”); and one for spike train and stimulus analysis (“neuropy”). All three are open source and available for download (http://swindale.ecc.ubc.ca/code). The requirements and solutions for these projects differed greatly, yet we found Python to be well suited for all three. Here we present our software as a showcase of the extensive capabilities of Python in neuroscience. PMID:19198646

Activity-dependent stochastic resonance in recurrent neuronal networks

NASA Astrophysics Data System (ADS)

Volman, Vladislav

2009-03-01

An important source of noise for neuronal networks is that of the stochastic nature of synaptic transmission. In particular, there can occur spontaneous asynchronous release of neurotransmitter at a rate that is strongly dependent on the presynaptic Ca2+ concentration and hence strongly dependent on the rate of spike induced Ca2+. Here it is shown that this noise can lead to a new form of stochastic resonance for local circuits consisting of roughly 100 neurons - a ``microcolumn''- coupled via noisy plastic synapses. Furthermore, due to the plastic coupling and activity-dependent noise component, the detection of weak stimuli will also depend on the structure of the latter. In addition, the circuit can exhibit short-term memory, by which we mean that spiking will continue to occur for a transient period following removal of the stimulus. These results can be directly tested in experiments on cultured networks.

Closed-loop optical neural stimulation based on a 32-channel low-noise recording system with online spike sorting

NASA Astrophysics Data System (ADS)

Nguyen, T. K. T.; Navratilova, Z.; Cabral, H.; Wang, L.; Gielen, G.; Battaglia, F. P.; Bartic, C.

2014-08-01

Objective. Closed-loop operation of neuro-electronic systems is desirable for both scientific and clinical (neuroprosthesis) applications. Integrating optical stimulation with recording capability further enhances the selectivity of neural stimulation. We have developed a system enabling the local delivery of optical stimuli and the simultaneous electrical measuring of the neural activities in a closed-loop approach. Approach. The signal analysis is performed online through the implementation of a template matching algorithm. The system performance is demonstrated with the recorded data and in awake rats. Main results. Specifically, the neural activities are simultaneously recorded, detected, classified online (through spike sorting) from 32 channels, and used to trigger a light emitting diode light source using generated TTL signals. Significance. A total processing time of 8 ms is achieved, suitable for optogenetic studies of brain mechanisms online.

Nonlinear decoding of a complex movie from the mammalian retina

PubMed Central

Deny, Stéphane; Martius, Georg

2018-01-01

Retina is a paradigmatic system for studying sensory encoding: the transformation of light into spiking activity of ganglion cells. The inverse problem, where stimulus is reconstructed from spikes, has received less attention, especially for complex stimuli that should be reconstructed “pixel-by-pixel”. We recorded around a hundred neurons from a dense patch in a rat retina and decoded movies of multiple small randomly-moving discs. We constructed nonlinear (kernelized and neural network) decoders that improved significantly over linear results. An important contribution to this was the ability of nonlinear decoders to reliably separate between neural responses driven by locally fluctuating light signals, and responses at locally constant light driven by spontaneous-like activity. This improvement crucially depended on the precise, non-Poisson temporal structure of individual spike trains, which originated in the spike-history dependence of neural responses. We propose a general principle by which downstream circuitry could discriminate between spontaneous and stimulus-driven activity based solely on higher-order statistical structure in the incoming spike trains. PMID:29746463

NeoAnalysis: a Python-based toolbox for quick electrophysiological data processing and analysis.

PubMed

Zhang, Bo; Dai, Ji; Zhang, Tao

2017-11-13

In a typical electrophysiological experiment, especially one that includes studying animal behavior, the data collected normally contain spikes, local field potentials, behavioral responses and other associated data. In order to obtain informative results, the data must be analyzed simultaneously with the experimental settings. However, most open-source toolboxes currently available for data analysis were developed to handle only a portion of the data and did not take into account the sorting of experimental conditions. Additionally, these toolboxes require that the input data be in a specific format, which can be inconvenient to users. Therefore, the development of a highly integrated toolbox that can process multiple types of data regardless of input data format and perform basic analysis for general electrophysiological experiments is incredibly useful. Here, we report the development of a Python based open-source toolbox, referred to as NeoAnalysis, to be used for quick electrophysiological data processing and analysis. The toolbox can import data from different data acquisition systems regardless of their formats and automatically combine different types of data into a single file with a standardized format. In cases where additional spike sorting is needed, NeoAnalysis provides a module to perform efficient offline sorting with a user-friendly interface. Then, NeoAnalysis can perform regular analog signal processing, spike train, and local field potentials analysis, behavioral response (e.g. saccade) detection and extraction, with several options available for data plotting and statistics. Particularly, it can automatically generate sorted results without requiring users to manually sort data beforehand. In addition, NeoAnalysis can organize all of the relevant data into an informative table on a trial-by-trial basis for data visualization. Finally, NeoAnalysis supports analysis at the population level. With the multitude of general-purpose functions provided by NeoAnalysis, users can easily obtain publication-quality figures without writing complex codes. NeoAnalysis is a powerful and valuable toolbox for users doing electrophysiological experiments.

EVALUATION OF SPIKING PROCEDURES FOR RECOVERY OF CRYPTOSPORIDIUM IN STREAM WATERS USING USEPA METHOD 1623

EPA Science Inventory

U.S. Environmental Protection Agency Method 1623 is widely used to monitor source waters and drinking water supplies for Cryptosporidium oocysts. Analyzing matrix spikes is an important component of Method 1623. Matrix spikes are used to determine the effect of the environmental...

Action Potentials Initiate in the Axon Initial Segment and Propagate Through Axon Collaterals Reliably in Cerebellar Purkinje Neurons

PubMed Central

Foust, Amanda; Popovic, Marko; Zecevic, Dejan; McCormick, David A.

2010-01-01

Purkinje neurons are the output cells of the cerebellar cortex and generate spikes in two distinct modes, known as simple and complex spikes. Revealing the point of origin of these action potentials, and how they conduct into local axon collaterals, is important for understanding local and distal neuronal processing and communication. By utilizing a recent improvement in voltage sensitive dye imaging technique that provided exceptional spatial and temporal resolution, we were able to resolve the region of spike initiation as well as follow spike propagation into axon collaterals for each action potential initiated on single trials. All fast action potentials, for both simple and complex spikes, whether occurring spontaneously or in response to a somatic current pulse or synaptic input, initiated in the axon initial segment. At discharge frequencies of less than approximately 250 Hz, spikes propagated faithfully through the axon and axon collaterals, in a saltatory manner. Propagation failures were only observed for very high frequencies or for the spikelets associated with complex spikes. These results demonstrate that the axon initial segment is a critical decision point in Purkinje cell processing and that the properties of axon branch points are adjusted to maintain faithful transmission. PMID:20484631

A Low Cost VLSI Architecture for Spike Sorting Based on Feature Extraction with Peak Search.

PubMed

Chang, Yuan-Jyun; Hwang, Wen-Jyi; Chen, Chih-Chang

2016-12-07

The goal of this paper is to present a novel VLSI architecture for spike sorting with high classification accuracy, low area costs and low power consumption. A novel feature extraction algorithm with low computational complexities is proposed for the design of the architecture. In the feature extraction algorithm, a spike is separated into two portions based on its peak value. The area of each portion is then used as a feature. The algorithm is simple to implement and less susceptible to noise interference. Based on the algorithm, a novel architecture capable of identifying peak values and computing spike areas concurrently is proposed. To further accelerate the computation, a spike can be divided into a number of segments for the local feature computation. The local features are subsequently merged with the global ones by a simple hardware circuit. The architecture can also be easily operated in conjunction with the circuits for commonly-used spike detection algorithms, such as the Non-linear Energy Operator (NEO). The architecture has been implemented by an Application-Specific Integrated Circuit (ASIC) with 90-nm technology. Comparisons to the existing works show that the proposed architecture is well suited for real-time multi-channel spike detection and feature extraction requiring low hardware area costs, low power consumption and high classification accuracy.

Local Resistance Profiling of Ultra-Shallow Junction with Spike Lamp and Laser Annealing Using Scanning Spreading Resistance Microscopy

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

Abo, Satoshi; Tanaka, Yuji; Nishikawa, Kazuhisa

2008-11-03

Local resistance profiles of ultra-shallow arsenic implanted into silicon with an energy of 3.5 keV and a dose of 1.2x10{sup 15} ions/cm{sup 2} activated by conventional spike lamp and laser annealing were measured by SSRM in a nitrogen atmosphere with a depth resolution of less than 10 nm for investigating the combination of the conventional spike lamp and laser annealing. Spike lamp annealing at 1050 deg. C followed by laser annealing at a power density of 0.42 kW/mm{sup 2} was found to give the lowest sheet resistance. The resistance profiles obtained by SSRM also indicated the lowest resistance for themore » sample after spike lamp annealing at 1050 deg. C followed by laser annealing with a power density of 0.42 kW/mm{sup 2}. Laser annealing alone with a power density of 0.42 kW/mm{sup 2} resulted in the higher sheet resistance, though the shallower resistance profile could be obtained. Spike lamp annealing followed by laser annealing procedures are effective in activating shallow arsenic profiles.« less

Millimeter-scale epileptiform spike propagation patterns and their relationship to seizures

PubMed Central

Vanleer, Ann C; Blanco, Justin A; Wagenaar, Joost B; Viventi, Jonathan; Contreras, Diego; Litt, Brian

2016-01-01

Objective Current mapping of epileptic networks in patients prior to epilepsy surgery utilizes electrode arrays with sparse spatial sampling (∼1.0 cm inter-electrode spacing). Recent research demonstrates that sub-millimeter, cortical-column-scale domains have a role in seizure generation that may be clinically significant. We use high-resolution, active, flexible surface electrode arrays with 500 μm inter-electrode spacing to explore epileptiform local field potential spike propagation patterns in two dimensions recorded from subdural micro-electrocorticographic signals in vivo in cat. In this study, we aimed to develop methods to quantitatively characterize the spatiotemporal dynamics of epileptiform activity at high-resolution. Approach We topically administered a GABA-antagonist, picrotoxin, to induce acute neocortical epileptiform activity leading up to discrete electrographic seizures. We extracted features from local field potential spikes to characterize spatiotemporal patterns in these events. We then tested the hypothesis that two dimensional spike patterns during seizures were different from those between seizures. Main results We showed that spatially correlated events can be used to distinguish ictal versus interictal spikes. Significance We conclude that sub-millimeter-scale spatiotemporal spike patterns reveal network dynamics that are invisible to standard clinical recordings and contain information related to seizure-state. PMID:26859260

Multimodal imaging of spike propagation: a technical case report.

PubMed

Tanaka, N; Grant, P E; Suzuki, N; Madsen, J R; Bergin, A M; Hämäläinen, M S; Stufflebeam, S M

2012-06-01

We report an 11-year-old boy with intractable epilepsy, who had cortical dysplasia in the right superior frontal gyrus. Spatiotemporal source analysis of MEG and EEG spikes demonstrated a similar time course of spike propagation from the superior to inferior frontal gyri, as observed on intracranial EEG. The tractography reconstructed from DTI showed a fiber connection between these areas. Our multimodal approach demonstrates spike propagation and a white matter tract guiding the propagation.

Essential role of axonal VGSC inactivation in time-dependent deceleration and unreliability of spike propagation at cerebellar Purkinje cells

PubMed Central

2014-01-01

Background The output of the neuronal digital spikes is fulfilled by axonal propagation and synaptic transmission to influence postsynaptic cells. Similar to synaptic transmission, spike propagation on the axon is not secure, especially in cerebellar Purkinje cells whose spiking rate is high. The characteristics, mechanisms and physiological impacts of propagation deceleration and infidelity remain elusive. The spike propagation is presumably initiated by local currents that raise membrane potential to the threshold of activating voltage-gated sodium channels (VGSC). Results We have investigated the natures of spike propagation and the role of VGSCs in this process by recording spikes simultaneously on the somata and axonal terminals of Purkinje cells in cerebellar slices. The velocity and fidelity of spike propagation decreased during long-lasting spikes, to which the velocity change was more sensitive than fidelity change. These time-dependent deceleration and infidelity of spike propagation were improved by facilitating axonal VGSC reactivation, and worsen by intensifying VGSC inactivation. Conclusion Our studies indicate that the functional status of axonal VGSCs is essential to influencing the velocity and fidelity of spike propagation. PMID:24382121

A realistic multimodal modeling approach for the evaluation of distributed source analysis: application to sLORETA.

PubMed

Cosandier-Rimélé, D; Ramantani, G; Zentner, J; Schulze-Bonhage, A; Dümpelmann, M

2017-10-01

Electrical source localization (ESL) deriving from scalp EEG and, in recent years, from intracranial EEG (iEEG), is an established method in epilepsy surgery workup. We aimed to validate the distributed ESL derived from scalp EEG and iEEG, particularly regarding the spatial extent of the source, using a realistic epileptic spike activity simulator. ESL was applied to the averaged scalp EEG and iEEG spikes of two patients with drug-resistant structural epilepsy. The ESL results for both patients were used to outline the location and extent of epileptic cortical patches, which served as the basis for designing a spatiotemporal source model. EEG signals for both modalities were then generated for different anatomic locations and spatial extents. ESL was subsequently performed on simulated signals with sLORETA, a commonly used distributed algorithm. ESL accuracy was quantitatively assessed for iEEG and scalp EEG. The source volume was overestimated by sLORETA at both EEG scales, with the error increasing with source size, particularly for iEEG. For larger sources, ESL accuracy drastically decreased, and reconstruction volumes shifted to the center of the head for iEEG, while remaining stable for scalp EEG. Overall, the mislocalization of the reconstructed source was more pronounced for iEEG. We present a novel multiscale framework for the evaluation of distributed ESL, based on realistic multiscale EEG simulations. Our findings support that reconstruction results for scalp EEG are often more accurate than for iEEG, owing to the superior 3D coverage of the head. Particularly the iEEG-derived reconstruction results for larger, widespread generators should be treated with caution.

A realistic multimodal modeling approach for the evaluation of distributed source analysis: application to sLORETA

NASA Astrophysics Data System (ADS)

Cosandier-Rimélé, D.; Ramantani, G.; Zentner, J.; Schulze-Bonhage, A.; Dümpelmann, M.

2017-10-01

Objective. Electrical source localization (ESL) deriving from scalp EEG and, in recent years, from intracranial EEG (iEEG), is an established method in epilepsy surgery workup. We aimed to validate the distributed ESL derived from scalp EEG and iEEG, particularly regarding the spatial extent of the source, using a realistic epileptic spike activity simulator. Approach. ESL was applied to the averaged scalp EEG and iEEG spikes of two patients with drug-resistant structural epilepsy. The ESL results for both patients were used to outline the location and extent of epileptic cortical patches, which served as the basis for designing a spatiotemporal source model. EEG signals for both modalities were then generated for different anatomic locations and spatial extents. ESL was subsequently performed on simulated signals with sLORETA, a commonly used distributed algorithm. ESL accuracy was quantitatively assessed for iEEG and scalp EEG. Main results. The source volume was overestimated by sLORETA at both EEG scales, with the error increasing with source size, particularly for iEEG. For larger sources, ESL accuracy drastically decreased, and reconstruction volumes shifted to the center of the head for iEEG, while remaining stable for scalp EEG. Overall, the mislocalization of the reconstructed source was more pronounced for iEEG. Significance. We present a novel multiscale framework for the evaluation of distributed ESL, based on realistic multiscale EEG simulations. Our findings support that reconstruction results for scalp EEG are often more accurate than for iEEG, owing to the superior 3D coverage of the head. Particularly the iEEG-derived reconstruction results for larger, widespread generators should be treated with caution.

Functional signature of recovering cortex: dissociation of local field potentials and spiking activity in somatosensory cortices of spinal cord injured monkeys.

PubMed

Wang, Zheng; Qi, Hui-Xin; Kaas, Jon H; Roe, Anna W; Chen, Li Min

2013-11-01

After disruption of dorsal column afferents at high cervical spinal levels in adult monkeys, somatosensory cortical neurons recover responsiveness to tactile stimulation of the hand; this reactivation correlates with a recovery of hand use. However, it is not known if all neuronal response properties recover, and whether different cortical areas recover in a similar manner. To address this, we recorded neuronal activity in cortical area 3b and S2 in adult squirrel monkeys weeks after unilateral lesion of the dorsal columns. We found that in response to vibrotactile stimulation, local field potentials remained robust at all frequency ranges. However, neuronal spiking activity failed to follow at high frequencies (≥15 Hz). We suggest that the failure to generate spiking activity at high stimulus frequency reflects a changed balance of inhibition and excitation in both area 3b and S2, and that this mismatch in spiking and local field potential is a signature of an early phase of recovering cortex (

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

PubMed Central

Bill, Johannes; Buesing, Lars; Habenschuss, Stefan; Nessler, Bernhard; Maass, Wolfgang; Legenstein, Robert

2015-01-01

During the last decade, Bayesian probability theory has emerged as a framework in cognitive science and neuroscience for describing perception, reasoning and learning of mammals. However, our understanding of how probabilistic computations could be organized in the brain, and how the observed connectivity structure of cortical microcircuits supports these calculations, is rudimentary at best. In this study, we investigate statistical inference and self-organized learning in a spatially extended spiking network model, that accommodates both local competitive and large-scale associative aspects of neural information processing, under a unified Bayesian account. Specifically, we show how the spiking dynamics of a recurrent network with lateral excitation and local inhibition in response to distributed spiking input, can be understood as sampling from a variational posterior distribution of a well-defined implicit probabilistic model. This interpretation further permits a rigorous analytical treatment of experience-dependent plasticity on the network level. Using machine learning theory, we derive update rules for neuron and synapse parameters which equate with Hebbian synaptic and homeostatic intrinsic plasticity rules in a neural implementation. In computer simulations, we demonstrate that the interplay of these plasticity rules leads to the emergence of probabilistic local experts that form distributed assemblies of similarly tuned cells communicating through lateral excitatory connections. The resulting sparse distributed spike code of a well-adapted network carries compressed information on salient input features combined with prior experience on correlations among them. Our theory predicts that the emergence of such efficient representations benefits from network architectures in which the range of local inhibition matches the spatial extent of pyramidal cells that share common afferent input. PMID:26284370

An empirical investigation of motion effects in eMRI of interictal epileptiform spikes.

PubMed

Sundaram, Padmavathi; Mulkern, Robert V; Wells, William M; Triantafyllou, Christina; Loddenkemper, Tobias; Bubrick, Ellen J; Orbach, Darren B

2011-12-01

We recently developed a functional neuroimaging technique called encephalographic magnetic resonance imaging (eMRI). Our method acquires rapid single-shot gradient-echo echo-planar MRI (repetition time=47 ms); it attempts to measure an MR signal more directly linked to neuronal electromagnetic activity than existing methods. To increase the likelihood of detecting such an MR signal, we recorded concurrent MRI and scalp electroencephalography (EEG) during fast (20-200 ms), localized, high-amplitude (>50 μV on EEG) cortical discharges in a cohort of focal epilepsy patients. Seen on EEG as interictal spikes, these discharges occur in between seizures and induced easily detectable MR magnitude and phase changes concurrent with the spikes with a lag of milliseconds to tens of milliseconds. Due to the time scale of the responses, localized changes in blood flow or hemoglobin oxygenation are unlikely to cause the MR signal changes that we observed. While the precise underlying mechanisms are unclear, in this study, we empirically investigate one potentially important confounding variable - motion. Head motion in the scanner affects both EEG and MR recording. It can produce brief "spike-like" artifacts on EEG and induce large MR signal changes similar to our interictal spike-related signal changes. In order to explore the possibility that interictal spikes were associated with head motions (although such an association had never been reported), we had previously tracked head position in epilepsy patients during interictal spikes and explicitly demonstrated a lack of associated head motion. However, that study was performed outside the MR scanner, and the root-mean-square error in the head position measurement was 0.7 mm. The large inaccuracy in this measurement therefore did not definitively rule out motion as a possible signal generator. In this study, we instructed healthy subjects to make deliberate brief (<500 ms) head motions inside the MR scanner and imaged these head motions with concurrent EEG and MRI. We compared these artifactual MR and EEG data to genuine interictal spikes. While per-voxel MR and per-electrode EEG time courses for the motion case can mimic the corresponding time courses associated with a genuine interictal spike, head motion can be unambiguously differentiated from interictal spikes via scalp EEG potential maps. Motion induces widespread changes in scalp potential, whereas interictal spikes are localized and have a regional fall-off in amplitude. These findings make bulk head motion an unlikely generator of the large spike-related MR signal changes that we had observed. Further work is required to precisely identify the underlying mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

Wavelet-based localization of oscillatory sources from magnetoencephalography data.

PubMed

Lina, J M; Chowdhury, R; Lemay, E; Kobayashi, E; Grova, C

2014-08-01

Transient brain oscillatory activities recorded with Eelectroencephalography (EEG) or magnetoencephalography (MEG) are characteristic features in physiological and pathological processes. This study is aimed at describing, evaluating, and illustrating with clinical data a new method for localizing the sources of oscillatory cortical activity recorded by MEG. The method combines time-frequency representation and an entropic regularization technique in a common framework, assuming that brain activity is sparse in time and space. Spatial sparsity relies on the assumption that brain activity is organized among cortical parcels. Sparsity in time is achieved by transposing the inverse problem in the wavelet representation, for both data and sources. We propose an estimator of the wavelet coefficients of the sources based on the maximum entropy on the mean (MEM) principle. The full dynamics of the sources is obtained from the inverse wavelet transform, and principal component analysis of the reconstructed time courses is applied to extract oscillatory components. This methodology is evaluated using realistic simulations of single-trial signals, combining fast and sudden discharges (spike) along with bursts of oscillating activity. The method is finally illustrated with a clinical application using MEG data acquired on a patient with a right orbitofrontal epilepsy.

Study design and percent recoveries of anthropogenic organic compounds with and without the addition of ascorbic acid to preserve water samples containing free chlorine, 2004-06

USGS Publications Warehouse

Valder, Joshua F.; Delzer, Gregory C.; Price, Curtis V.; Sandstrom, Mark W.

2008-01-01

The National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey (USGS) began implementing Source Water-Quality Assessments (SWQAs) in 2002 that focus on characterizing the quality of source water and finished water of aquifers and major rivers used by some of the larger community water systems in the United States. As used for SWQA studies, source water is the raw (ambient) water collected at the supply well prior to water treatment (for ground water) or the raw (ambient) water collected from the river near the intake (for surface water). Finished water is the water that is treated, which typically involves, in part, the addition of chlorine or other disinfection chemicals to remove pathogens, and is ready to be delivered to consumers. Finished water is collected before the water enters the distribution system. This report describes the study design and percent recoveries of anthropogenic organic compounds (AOCs) with and without the addition of ascorbic acid to preserve water samples containing free chlorine. The percent recoveries were determined by using analytical results from a laboratory study conducted in 2004 by the USGS's National Water Quality Laboratory (NWQL) and from data collected during 2004-06 for a field study currently (2008) being conducted by the USGS's NAWQA Program. The laboratory study was designed to determine if preserving samples with ascorbic acid (quenching samples) adversely affects analytical performance under controlled conditions. During the laboratory study, eight samples of reagent water were spiked for each of five analytical schedules evaluated. Percent recoveries from these samples were then compared in two ways: (1) four quenched reagent spiked samples analyzed on day 0 were compared with four quenched reagent spiked samples analyzed on day 7 or 14, and (2) the combined eight quenched reagent spiked samples analyzed on day 0, 7, or 14 were compared with eight laboratory reagent spikes (LRSs). Percent recoveries from the quenched reagent spiked samples that were analyzed at two different times (day 0 and day 7 or 14) can be used to determine the stability of the quenched samples held for an amount of time representative of the normal amount of time between sample collection and analysis. The comparison between the quenched reagent spiked samples and the LRSs can be used to determine if quenching samples adversely affects the analytical performance under controlled conditions. The field study began in 2004 and is continuing today (February 2008) to characterize the effect of quenching on field-matrix spike recoveries and to better understand the potential oxidation and transformation of 277 AOCs. Three types of samples were collected from 11 NAWQA Study Units across the Nation: (1) quenched finished-water samples (not spiked), (2) quenched finished-water spiked samples, and (3) nonquenched finished-water spiked samples. Percent recoveries of AOCs in quenched and nonquenched finished-water spiked samples collected during 2004-06 are presented. Comparisons of percent recoveries between quenched and nonquenched spiked samples can be used to show how quenching affects finished-water samples. A maximum of 6 surface-water and 7 ground-water quenched finished-water spiked samples paired with nonquenched finished-water spiked samples were analyzed. Analytical results for the field study are presented in two ways: (1) by surface-water supplies or ground-water supplies, and (2) by use (or source) group category for surface-water and ground-water supplies. Graphical representations of percent recoveries for the quenched and nonquenched finished-water spiked samples also are presented.

A Feedforward Inhibitory Circuit Mediated by CB1-Expressing Fast-Spiking Interneurons in the Nucleus Accumbens.

PubMed

Wright, William J; Schlüter, Oliver M; Dong, Yan

2017-04-01

The nucleus accumbens (NAc) gates motivated behaviors through the functional output of principle medium spiny neurons (MSNs), whereas dysfunctional output of NAc MSNs contributes to a variety of psychiatric disorders. Fast-spiking interneurons (FSIs) are sparsely distributed throughout the NAc, forming local feedforward inhibitory circuits. It remains elusive how FSI-based feedforward circuits regulate the output of NAc MSNs. Here, we investigated a distinct subpopulation of NAc FSIs that express the cannabinoid receptor type-1 (CB1). Using a combination of paired electrophysiological recordings and pharmacological approaches, we characterized and compared feedforward inhibition of NAc MSNs from CB1 + FSIs and lateral inhibition from recurrent MSN collaterals. We observed that CB1 + FSIs exerted robust inhibitory control over a large percentage of nearby MSNs in contrast to local MSN collaterals that provided only sparse and weak inhibitory input to their neighboring MSNs. Furthermore, CB1 + FSI-mediated feedforward inhibition was preferentially suppressed by endocannabinoid (eCB) signaling, whereas MSN-mediated lateral inhibition was unaffected. Finally, we demonstrated that CB1 + FSI synapses onto MSNs are capable of undergoing experience-dependent long-term depression in a voltage- and eCB-dependent manner. These findings demonstrated that CB1 + FSIs are a major source of local inhibitory control of MSNs and a critical component of the feedforward inhibitory circuits regulating the output of the NAc.

A Feedforward Inhibitory Circuit Mediated by CB1-Expressing Fast-Spiking Interneurons in the Nucleus Accumbens

PubMed Central

Wright, William J; Schlüter, Oliver M; Dong, Yan

2017-01-01

The nucleus accumbens (NAc) gates motivated behaviors through the functional output of principle medium spiny neurons (MSNs), whereas dysfunctional output of NAc MSNs contributes to a variety of psychiatric disorders. Fast-spiking interneurons (FSIs) are sparsely distributed throughout the NAc, forming local feedforward inhibitory circuits. It remains elusive how FSI-based feedforward circuits regulate the output of NAc MSNs. Here, we investigated a distinct subpopulation of NAc FSIs that express the cannabinoid receptor type-1 (CB1). Using a combination of paired electrophysiological recordings and pharmacological approaches, we characterized and compared feedforward inhibition of NAc MSNs from CB1+ FSIs and lateral inhibition from recurrent MSN collaterals. We observed that CB1+ FSIs exerted robust inhibitory control over a large percentage of nearby MSNs in contrast to local MSN collaterals that provided only sparse and weak inhibitory input to their neighboring MSNs. Furthermore, CB1+ FSI-mediated feedforward inhibition was preferentially suppressed by endocannabinoid (eCB) signaling, whereas MSN-mediated lateral inhibition was unaffected. Finally, we demonstrated that CB1+ FSI synapses onto MSNs are capable of undergoing experience-dependent long-term depression in a voltage- and eCB-dependent manner. These findings demonstrated that CB1+ FSIs are a major source of local inhibitory control of MSNs and a critical component of the feedforward inhibitory circuits regulating the output of the NAc. PMID:27929113

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.

PubMed

Gilra, Aditya; Gerstner, Wulfram

2017-11-27

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.

Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network

PubMed Central

Gerstner, Wulfram

2017-01-01

The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically. PMID:29173280

Data on copula modeling of mixed discrete and continuous neural time series.

PubMed

Hu, Meng; Li, Mingyao; Li, Wu; Liang, Hualou

2016-06-01

Copula is an important tool for modeling neural dependence. Recent work on copula has been expanded to jointly model mixed time series in neuroscience ("Hu et al., 2016, Joint Analysis of Spikes and Local Field Potentials using Copula" [1]). Here we present further data for joint analysis of spike and local field potential (LFP) with copula modeling. In particular, the details of different model orders and the influence of possible spike contamination in LFP data from the same and different electrode recordings are presented. To further facilitate the use of our copula model for the analysis of mixed data, we provide the Matlab codes, together with example data.

From neurons to circuits: linear estimation of local field potentials.

PubMed

Rasch, Malte; Logothetis, Nikos K; Kreiman, Gabriel

2009-11-04

Extracellular physiological recordings are typically separated into two frequency bands: local field potentials (LFPs) (a circuit property) and spiking multiunit activity (MUA). Recently, there has been increased interest in LFPs because of their correlation with functional magnetic resonance imaging blood oxygenation level-dependent measurements and the possibility of studying local processing and neuronal synchrony. To further understand the biophysical origin of LFPs, we asked whether it is possible to estimate their time course based on the spiking activity from the same electrode or nearby electrodes. We used "signal estimation theory" to show that a linear filter operation on the activity of one or a few neurons can explain a significant fraction of the LFP time course in the macaque monkey primary visual cortex. The linear filter used to estimate the LFPs had a stereotypical shape characterized by a sharp downstroke at negative time lags and a slower positive upstroke for positive time lags. The filter was similar across different neocortical regions and behavioral conditions, including spontaneous activity and visual stimulation. The estimations had a spatial resolution of approximately 1 mm and a temporal resolution of approximately 200 ms. By considering a causal filter, we observed a temporal asymmetry such that the positive time lags in the filter contributed more to the LFP estimation than the negative time lags. Additionally, we showed that spikes occurring within approximately 10 ms of spikes from nearby neurons yielded better estimation accuracies than nonsynchronous spikes. In summary, our results suggest that at least some circuit-level local properties of the field potentials can be predicted from the activity of one or a few neurons.

From neurons to circuits: linear estimation of local field potentials

PubMed Central

Rasch, Malte; Logthetis, Nikos K.; Kreiman, Gabriel

2010-01-01

Extracellular physiological recordings are typically separated into two frequency bands: local field potentials (LFPs, a circuit property) and spiking multi-unit activity (MUA). There has been increased interest in LFPs due to their correlation with fMRI measurements and the possibility of studying local processing and neuronal synchrony. To further understand the biophysical origin of LFPs, we asked whether it is possible to estimate their time course based on the spiking activity from the same or nearby electrodes. We used Signal Estimation Theory to show that a linear filter operation on the activity of one/few neurons can explain a significant fraction of the LFP time course in the macaque primary visual cortex. The linear filter used to estimate the LFPs had a stereotypical shape characterized by a sharp downstroke at negative time lags and a slower positive upstroke for positve time lags. The filter was similar across neocortical regions and behavioral conditions including spontaneous activity and visual stimulation. The estimations had a spatial resolution of ~1 mm and a temporal resolution of ~200 ms. By considering a causal filter, we observed a temporal asymmetry such that the positive time lags in the filter contributed more to the LFP estimation than negative time lags. Additionally, we showed that spikes occurring within ~10 ms of spikes from nearby neurons yielded better estimation accuracies than nonsynchronous spikes. In sum, our results suggest that at least some circuit-level local properties of the field potentials can be predicted from the activity of one or a few neurons. PMID:19889990

Interictal EEG spikes identify the region of electrographic seizure onset in some, but not all, pediatric epilepsy patients.

PubMed

Marsh, Eric D; Peltzer, Bradley; Brown, Merritt W; Wusthoff, Courtney; Storm, Phillip B; Litt, Brian; Porter, Brenda E

2010-04-01

The role of sharps and spikes, interictal epileptiform discharges (IEDs), in guiding epilepsy surgery in children remains controversial, particularly with intracranial electroencephalography (IEEG). Although ictal recording is the mainstay of localizing epileptic networks for surgical resection, current practice dictates removing regions generating frequent IEDs if they are near the ictal onset zone. Indeed, past studies suggest an inconsistent relationship between IED and seizure-onset location, although these studies were based upon relatively short EEG epochs. We employ a previously validated, computerized spike detector to measure and localize IED activity over prolonged, representative segments of IEEG recorded from 19 children with intractable, mostly extratemporal lobe epilepsy. Approximately 8 h of IEEG, randomly selected 30-min segments of continuous interictal IEEG per patient, were analyzed over all intracranial electrode contacts. When spike frequency was averaged over the 16-time segments, electrodes with the highest mean spike frequency were found to be within the seizure-onset region in 11 of 19 patients. There was significant variability between individual 30-min segments in these patients, indicating that large statistical samples of interictal activity were required for improved localization. Low-voltage fast EEG at seizure onset was the only clinical factor predicting IED localization to the seizure-onset region. Our data suggest that automated IED detection over multiple representative samples of IEEG may be of utility in planning epilepsy surgery for children with intractable epilepsy. Further research is required to better determine which patients may benefit from this technique a priori.

Interictal EEG spikes identify the region of seizure onset in some, but not all pediatric epilepsy patients

PubMed Central

Marsh, Eric D.; Peltzer, Bradley; Brown, Merritt W.; Wusthoff, Courtney; Storm, Phillip B.; Litt, Brian; Porter, Brenda E.

2010-01-01

Purpose The role of sharps and spikes, interictal epileptiform discharges (IEDs), in guiding epilepsy surgery in children remains controversial, particularly with intracranial EEG (IEEG). While ictal recording is the mainstay of localizing epileptic networks for surgical resection, current practice dictates removing regions generating frequent IEDs if they are near the ictal onset zone. Indeed, past studies suggest an inconsistent relationship between IED and seizure onset location, though these studies were based upon relatively short EEG epochs. Methods We employ a previously validated, computerized spike detector, to measure and localize IED activity over prolonged, representative segments of IEEG recorded from 19 children with intractable, mostly extra temporal lobe epilepsy. Approximately 8 hours of IEEG, randomly selected thirty-minute segments of continuous interictal IEEG per patient were analyzed over all intracranial electrode contacts. Results When spike frequency was averaged over the 16-time segments, electrodes with the highest mean spike frequency were found to be within the seizure onset region in 11 of 19 patients. There was significant variability between individual 30-minute segments in these patients, indicating that large statistical samples of interictal activity were required for improved localization. Low voltage fast EEG at seizure onset was the only clinical factor predicting IED localization to the seizure onset region. Conclusions Our data suggest that automated IED detection over multiple representative samples of IEEG may be of utility in planning epilepsy surgery for children with intractable epilepsy. Further research is required to better determine which patients may benefit from this technique a priori. PMID:19780794

Phase Locking of Multiple Single Neurons to the Local Field Potential in Cat V1.

PubMed

Martin, Kevan A C; Schröder, Sylvia

2016-02-24

The local field potential (LFP) is thought to reflect a temporal reference for neuronal spiking, which may facilitate information coding and orchestrate the communication between neural populations. To explore this proposed role, we recorded the LFP and simultaneously the spike activity of one to three nearby neurons in V1 of anesthetized cats during the presentation of drifting sinusoidal gratings, binary dense noise stimuli, and natural movies. In all stimulus conditions and during spontaneous activity, the average LFP power at frequencies >20 Hz was higher when neurons were spiking versus not spiking. The spikes were weakly but significantly phase locked to all frequencies of the LFP. The average spike phase of the LFP was stable across high and low levels of LFP power, but the strength of phase locking at low frequencies (≤10 Hz) increased with increasing LFP power. In a next step, we studied how strong stimulus responses of single neurons are reflected in the LFP and the LFP-spike relationship. We found that LFP power was slightly increased and phase locking was slightly stronger during strong compared with weak stimulus-locked responses. In summary, the coupling strength between high frequencies of the LFP and spikes was not strongly modulated by LFP power, which is thought to reflect spiking synchrony, nor was it strongly influenced by how strongly the neuron was driven by the stimulus. Furthermore, a comparison between neighboring neurons showed no clustering of preferred LFP phase. We argue that hypotheses on the relevance of phase locking in their current form are inconsistent with our findings. Copyright © 2016 the authors 0270-6474/16/362494-09$15.00/0.

Galactic center gamma-ray excess from dark matter annihilation: is there a black hole spike?

PubMed

Fields, Brian D; Shapiro, Stuart L; Shelton, Jessie

2014-10-10

If the supermassive black hole Sgr A* at the center of the Milky Way grew adiabatically from an initial seed embedded in a Navarro-Frenk-White dark matter (DM) halo, then the DM profile near the hole has steepened into a spike. We calculate the dramatic enhancement to the gamma-ray flux from the Galactic center (GC) from such a spike if the 1-3 GeV excess observed in Fermi data is due to DM annihilations. We find that for the parameter values favored in recent fits, the point-source-like flux from the spike is 35 times greater than the flux from the inner 1° of the halo, far exceeding all Fermi point source detections near the GC. We consider the dependence of the spike signal on astrophysical and particle parameters and conclude that if the GC excess is due to DM, then a canonical adiabatic spike is disfavored by the data. We discuss alternative Galactic histories that predict different spike signals, including (i) the nonadiabatic growth of the black hole, possibly associated with halo and/or black hole mergers, (ii) gravitational interaction of DM with baryons in the dense core, such as heating by stars, or (iii) DM self-interactions. We emphasize that the spike signal is sensitive to a different combination of particle parameters than the halo signal and that the inclusion of a spike component to any DM signal in future analyses would provide novel information about both the history of the GC and the particle physics of DM annihilations.

Causal Inference and Explaining Away in a Spiking Network

PubMed Central

Moreno-Bote, Rubén; Drugowitsch, Jan

2015-01-01

While the brain uses spiking neurons for communication, theoretical research on brain computations has mostly focused on non-spiking networks. The nature of spike-based algorithms that achieve complex computations, such as object probabilistic inference, is largely unknown. Here we demonstrate that a family of high-dimensional quadratic optimization problems with non-negativity constraints can be solved exactly and efficiently by a network of spiking neurons. The network naturally imposes the non-negativity of causal contributions that is fundamental to causal inference, and uses simple operations, such as linear synapses with realistic time constants, and neural spike generation and reset non-linearities. The network infers the set of most likely causes from an observation using explaining away, which is dynamically implemented by spike-based, tuned inhibition. The algorithm performs remarkably well even when the network intrinsically generates variable spike trains, the timing of spikes is scrambled by external sources of noise, or the network is mistuned. This type of network might underlie tasks such as odor identification and classification. PMID:26621426

Causal Inference and Explaining Away in a Spiking Network.

PubMed

Moreno-Bote, Rubén; Drugowitsch, Jan

2015-12-01

While the brain uses spiking neurons for communication, theoretical research on brain computations has mostly focused on non-spiking networks. The nature of spike-based algorithms that achieve complex computations, such as object probabilistic inference, is largely unknown. Here we demonstrate that a family of high-dimensional quadratic optimization problems with non-negativity constraints can be solved exactly and efficiently by a network of spiking neurons. The network naturally imposes the non-negativity of causal contributions that is fundamental to causal inference, and uses simple operations, such as linear synapses with realistic time constants, and neural spike generation and reset non-linearities. The network infers the set of most likely causes from an observation using explaining away, which is dynamically implemented by spike-based, tuned inhibition. The algorithm performs remarkably well even when the network intrinsically generates variable spike trains, the timing of spikes is scrambled by external sources of noise, or the network is mistuned. This type of network might underlie tasks such as odor identification and classification.

Current source density correlates of cerebellar Golgi and Purkinje cell responses to tactile input

PubMed Central

Tahon, Koen; Wijnants, Mike; De Schutter, Erik

2011-01-01

The overall circuitry of the cerebellar cortex has been known for over a century, but the function of many synaptic connections remains poorly characterized in vivo. We used a one-dimensional multielectrode probe to estimate the current source density (CSD) of Crus IIa in response to perioral tactile stimuli in anesthetized rats and to correlate current sinks and sources to changes in the spike rate of corecorded Golgi and Purkinje cells. The punctate stimuli evoked two distinct early waves of excitation (at <10 and ∼20 ms) associated with current sinks in the granular layer. The second wave was putatively of corticopontine origin, and its associated sink was located higher in the granular layer than the first trigeminal sink. The distinctive patterns of granular-layer sinks correlated with the spike responses of corecorded Golgi cells. In general, Golgi cell spike responses could be linearly reconstructed from the CSD profile. A dip in simple-spike activity of coregistered Purkinje cells correlated with a current source deep in the molecular layer, probably generated by basket cell synapses, interspersed between sparse early sinks presumably generated by synapses from granule cells. The late (>30 ms) enhancement of simple-spike activity in Purkinje cells was characterized by the absence of simultaneous sinks in the granular layer and by the suppression of corecorded Golgi cell activity, pointing at inhibition of Golgi cells by Purkinje axon collaterals as a likely mechanism of late Purkinje cell excitation. PMID:21228303

Recent progress in multi-electrode spike sorting methods

PubMed Central

Lefebvre, Baptiste; Yger, Pierre; Marre, Olivier

2017-01-01

In recent years, arrays of extracellular electrodes have been developed and manufactured to record simultaneously from hundreds of electrodes packed with a high density. These recordings should allow neuroscientists to reconstruct the individual activity of the neurons spiking in the vicinity of these electrodes, with the help of signal processing algorithms. Algorithms need to solve a source separation problem, also known as spike sorting. However, these new devices challenge the classical way to do spike sorting. Here we review different methods that have been developed to sort spikes from these large-scale recordings. We describe the common properties of these algorithms, as well as their main differences. Finally, we outline the issues that remain to be solved by future spike sorting algorithms. PMID:28263793

Convex relaxations of spectral sparsity for robust super-resolution and line spectrum estimation

NASA Astrophysics Data System (ADS)

Chi, Yuejie

2017-08-01

We consider recovering the amplitudes and locations of spikes in a point source signal from its low-pass spectrum that may suffer from missing data and arbitrary outliers. We first review and provide a unified view of several recently proposed convex relaxations that characterize and capitalize the spectral sparsity of the point source signal without discretization under the framework of atomic norms. Next we propose a new algorithm when the spikes are known a priori to be positive, motivated by applications such as neural spike sorting and fluorescence microscopy imaging. Numerical experiments are provided to demonstrate the effectiveness of the proposed approach.

Locally Contractive Dynamics in Generalized Integrate-and-Fire Neurons*

PubMed Central

Jimenez, Nicolas D.; Mihalas, Stefan; Brown, Richard; Niebur, Ernst; Rubin, Jonathan

2013-01-01

Integrate-and-fire models of biological neurons combine differential equations with discrete spike events. In the simplest case, the reset of the neuronal voltage to its resting value is the only spike event. The response of such a model to constant input injection is limited to tonic spiking. We here study a generalized model in which two simple spike-induced currents are added. We show that this neuron exhibits not only tonic spiking at various frequencies but also the commonly observed neuronal bursting. Using analytical and numerical approaches, we show that this model can be reduced to a one-dimensional map of the adaptation variable and that this map is locally contractive over a broad set of parameter values. We derive a sufficient analytical condition on the parameters for the map to be globally contractive, in which case all orbits tend to a tonic spiking state determined by the fixed point of the return map. We then show that bursting is caused by a discontinuity in the return map, in which case the map is piecewise contractive. We perform a detailed analysis of a class of piecewise contractive maps that we call bursting maps and show that they robustly generate stable bursting behavior. To the best of our knowledge, this work is the first to point out the intimate connection between bursting dynamics and piecewise contractive maps. Finally, we discuss bifurcations in this return map, which cause transitions between spiking patterns. PMID:24489486

Fast numerical methods for simulating large-scale integrate-and-fire neuronal networks.

PubMed

Rangan, Aaditya V; Cai, David

2007-02-01

We discuss numerical methods for simulating large-scale, integrate-and-fire (I&F) neuronal networks. Important elements in our numerical methods are (i) a neurophysiologically inspired integrating factor which casts the solution as a numerically tractable integral equation, and allows us to obtain stable and accurate individual neuronal trajectories (i.e., voltage and conductance time-courses) even when the I&F neuronal equations are stiff, such as in strongly fluctuating, high-conductance states; (ii) an iterated process of spike-spike corrections within groups of strongly coupled neurons to account for spike-spike interactions within a single large numerical time-step; and (iii) a clustering procedure of firing events in the network to take advantage of localized architectures, such as spatial scales of strong local interactions, which are often present in large-scale computational models-for example, those of the primary visual cortex. (We note that the spike-spike corrections in our methods are more involved than the correction of single neuron spike-time via a polynomial interpolation as in the modified Runge-Kutta methods commonly used in simulations of I&F neuronal networks.) Our methods can evolve networks with relatively strong local interactions in an asymptotically optimal way such that each neuron fires approximately once in [Formula: see text] operations, where N is the number of neurons in the system. We note that quantifications used in computational modeling are often statistical, since measurements in a real experiment to characterize physiological systems are typically statistical, such as firing rate, interspike interval distributions, and spike-triggered voltage distributions. We emphasize that it takes much less computational effort to resolve statistical properties of certain I&F neuronal networks than to fully resolve trajectories of each and every neuron within the system. For networks operating in realistic dynamical regimes, such as strongly fluctuating, high-conductance states, our methods are designed to achieve statistical accuracy when very large time-steps are used. Moreover, our methods can also achieve trajectory-wise accuracy when small time-steps are used.

Synaptic depolarization is more effective than back-propagating action potentials during induction of associative long-term potentiation in hippocampal pyramidal neurons.

PubMed

Hardie, Jason; Spruston, Nelson

2009-03-11

Long-term potentiation (LTP) requires postsynaptic depolarization that can result from EPSPs paired with action potentials or larger EPSPs that trigger dendritic spikes. We explored the relative contribution of these sources of depolarization to LTP induction during synaptically driven action potential firing in hippocampal CA1 pyramidal neurons. Pairing of a weak test input with a strong input resulted in large LTP (approximately 75% increase) when the weak and strong inputs were both located in the apical dendrites. This form of LTP did not require somatic action potentials. When the strong input was located in the basal dendrites, the resulting LTP was smaller (< or =25% increase). Pairing the test input with somatically evoked action potentials mimicked this form of LTP. Thus, back-propagating action potentials may contribute to modest LTP, but local synaptic depolarization and/or dendritic spikes mediate a stronger form of LTP that requires spatial proximity of the associated synaptic inputs.

Can green roof act as a sink for contaminants? A methodological study to evaluate runoff quality from green roofs.

PubMed

Vijayaraghavan, K; Joshi, Umid Man

2014-11-01

The present study examines whether green roofs act as a sink or source of contaminants based on various physico-chemical parameters (pH, conductivity and total dissolved solids) and metals (Na, K, Ca, Mg, Al, Fe, Cr, Cu, Ni, Zn, Cd and Pb). The performance of green roof substrate prepared using perlite, vermiculite, sand, crushed brick, and coco-peat, was compared with local garden soil based on improvement of runoff quality. Portulaca grandiflora was used as green roof vegetation. Four different green roof configurations, with vegetated and non-vegetated systems, were examined for several artificial rain events (un-spiked and metal-spiked). In general, the vegetated green roof assemblies generated better-quality runoff with less conductivity and total metal ion concentration compared to un-vegetated assemblies. Of the different green roof configurations examined, P. grandiflora planted on green roof substrate acted as sink for various metals and showed the potential to generate better runoff. Copyright © 2014 Elsevier Ltd. All rights reserved.

Independent component analysis separates spikes of different origin in the EEG.

PubMed

Urrestarazu, Elena; Iriarte, Jorge; Artieda, Julio; Alegre, Manuel; Valencia, Miguel; Viteri, César

2006-02-01

Independent component analysis (ICA) is a novel system that finds independent sources in recorded signals. Its usefulness in separating epileptiform activity of different origin has not been determined. The goal of this study was to demonstrate that ICA is useful for separating different spikes using samples of EEG of patients with focal epilepsy. Digital EEG samples from four patients with focal epilepsy were included. The patients had temporal (n = 2), centrotemporal (n = 1) or frontal spikes (n = 1). Twenty-six samples with two (or more) spikes from two different patients were created. The selection of the two spikes for each mixed EEG was performed randomly, trying to have all the different combinations and rejecting the mixture of two spikes from the same patient. Two different examiners studied the EEGs using ICA with JADE paradigm in Matlab platform, trying to separate and to identify the spikes. They agreed in the correct separation of the spikes in 24 of the 26 samples, classifying the spikes as frontal, temporal or centrotemporal, left or right sided. The demonstration of the possibility of detecting different artificially mixed spikes confirms that ICA may be useful in separating spikes or other elements in real EEGs.

Conversion of Phase Information into a Spike-Count Code by Bursting Neurons

PubMed Central

Samengo, Inés; Montemurro, Marcelo A.

2010-01-01

Single neurons in the cerebral cortex are immersed in a fluctuating electric field, the local field potential (LFP), which mainly originates from synchronous synaptic input into the local neural neighborhood. As shown by recent studies in visual and auditory cortices, the angular phase of the LFP at the time of spike generation adds significant extra information about the external world, beyond the one contained in the firing rate alone. However, no biologically plausible mechanism has yet been suggested that allows downstream neurons to infer the phase of the LFP at the soma of their pre-synaptic afferents. Therefore, so far there is no evidence that the nervous system can process phase information. Here we study a model of a bursting pyramidal neuron, driven by a time-dependent stimulus. We show that the number of spikes per burst varies systematically with the phase of the fluctuating input at the time of burst onset. The mapping between input phase and number of spikes per burst is a robust response feature for a broad range of stimulus statistics. Our results suggest that cortical bursting neurons could play a crucial role in translating LFP phase information into an easily decodable spike count code. PMID:20300632

NeuroGrid: recording action potentials from the surface of the brain.

PubMed

Khodagholy, Dion; Gelinas, Jennifer N; Thesen, Thomas; Doyle, Werner; Devinsky, Orrin; Malliaras, George G; Buzsáki, György

2015-02-01

Recording from neural networks at the resolution of action potentials is critical for understanding how information is processed in the brain. Here, we address this challenge by developing an organic material-based, ultraconformable, biocompatible and scalable neural interface array (the 'NeuroGrid') that can record both local field potentials(LFPs) and action potentials from superficial cortical neurons without penetrating the brain surface. Spikes with features of interneurons and pyramidal cells were simultaneously acquired by multiple neighboring electrodes of the NeuroGrid, allowing for the isolation of putative single neurons in rats. Spiking activity demonstrated consistent phase modulation by ongoing brain oscillations and was stable in recordings exceeding 1 week's duration. We also recorded LFP-modulated spiking activity intraoperatively in patients undergoing epilepsy surgery. The NeuroGrid constitutes an effective method for large-scale, stable recording of neuronal spikes in concert with local population synaptic activity, enhancing comprehension of neural processes across spatiotemporal scales and potentially facilitating diagnosis and therapy for brain disorders.

Dendritic Na+ spikes enable cortical input to drive action potential output from hippocampal CA2 pyramidal neurons

PubMed Central

Sun, Qian; Srinivas, Kalyan V; Sotayo, Alaba; Siegelbaum, Steven A

2014-01-01

Synaptic inputs from different brain areas are often targeted to distinct regions of neuronal dendritic arbors. Inputs to proximal dendrites usually produce large somatic EPSPs that efficiently trigger action potential (AP) output, whereas inputs to distal dendrites are greatly attenuated and may largely modulate AP output. In contrast to most other cortical and hippocampal neurons, hippocampal CA2 pyramidal neurons show unusually strong excitation by their distal dendritic inputs from entorhinal cortex (EC). In this study, we demonstrate that the ability of these EC inputs to drive CA2 AP output requires the firing of local dendritic Na+ spikes. Furthermore, we find that CA2 dendritic geometry contributes to the efficient coupling of dendritic Na+ spikes to AP output. These results provide a striking example of how dendritic spikes enable direct cortical inputs to overcome unfavorable distal synaptic locale to trigger axonal AP output and thereby enable efficient cortico-hippocampal information flow. DOI: http://dx.doi.org/10.7554/eLife.04551.001 PMID:25390033

Temporal coding of reward-guided choice in the posterior parietal cortex

PubMed Central

Hawellek, David J.; Wong, Yan T.; Pesaran, Bijan

2016-01-01

Making a decision involves computations across distributed cortical and subcortical networks. How such distributed processing is performed remains unclear. We test how the encoding of choice in a key decision-making node, the posterior parietal cortex (PPC), depends on the temporal structure of the surrounding population activity. We recorded spiking and local field potential (LFP) activity in the PPC while two rhesus macaques performed a decision-making task. We quantified the mutual information that neurons carried about an upcoming choice and its dependence on LFP activity. The spiking of PPC neurons was correlated with LFP phases at three distinct time scales in the theta, beta, and gamma frequency bands. Importantly, activity at these time scales encoded upcoming decisions differently. Choice information contained in neural firing varied with the phase of beta and gamma activity. For gamma activity, maximum choice information occurred at the same phase as the maximum spike count. However, for beta activity, choice information and spike count were greatest at different phases. In contrast, theta activity did not modulate the encoding properties of PPC units directly but was correlated with beta and gamma activity through cross-frequency coupling. We propose that the relative timing of local spiking and choice information reveals temporal reference frames for computations in either local or large-scale decision networks. Differences between the timing of task information and activity patterns may be a general signature of distributed processing across large-scale networks. PMID:27821752

Recent progress in multi-electrode spike sorting methods.

PubMed

Lefebvre, Baptiste; Yger, Pierre; Marre, Olivier

2016-11-01

In recent years, arrays of extracellular electrodes have been developed and manufactured to record simultaneously from hundreds of electrodes packed with a high density. These recordings should allow neuroscientists to reconstruct the individual activity of the neurons spiking in the vicinity of these electrodes, with the help of signal processing algorithms. Algorithms need to solve a source separation problem, also known as spike sorting. However, these new devices challenge the classical way to do spike sorting. Here we review different methods that have been developed to sort spikes from these large-scale recordings. We describe the common properties of these algorithms, as well as their main differences. Finally, we outline the issues that remain to be solved by future spike sorting algorithms. Copyright © 2017 Elsevier Ltd. All rights reserved.

Local Field Potentials: Myths and Misunderstandings

PubMed Central

Herreras, Oscar

2016-01-01

The intracerebral local field potential (LFP) is a measure of brain activity that reflects the highly dynamic flow of information across neural networks. This is a composite signal that receives contributions from multiple neural sources, yet interpreting its nature and significance may be hindered by several confounding factors and technical limitations. By and large, the main factor defining the amplitude of LFPs is the geometry of the current sources, over and above the degree of synchronization or the properties of the media. As such, similar levels of activity may result in potentials that differ in several orders of magnitude in different populations. The geometry of these sources has been experimentally inaccessible until intracerebral high density recordings enabled the co-activating sources to be revealed. Without this information, it has proven difficult to interpret a century's worth of recordings that used temporal cues alone, such as event or spike related potentials and frequency bands. Meanwhile, a collection of biophysically ill-founded concepts have been considered legitimate, which can now be corrected in the light of recent advances. The relationship of LFPs to their sources is often counterintuitive. For instance, most LFP activity is not local but remote, it may be larger further from rather than close to the source, the polarity does not define its excitatory or inhibitory nature, and the amplitude may increase when source's activity is reduced. As technological developments foster the use of LFPs, the time is now ripe to raise awareness of the need to take into account spatial aspects of these signals and of the errors derived from neglecting to do so. PMID:28018180

Advanced correlation grid: Analysis and visualisation of functional connectivity among multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman; Stuart, Liz

2017-07-15

This study analyses multiple spike trains (MST) data, defines its functional connectivity and subsequently visualises an accurate diagram of connections. This is a challenging problem. For example, it is difficult to distinguish the common input and the direct functional connection of two spike trains. The new method presented in this paper is based on the traditional pairwise cross-correlation function (CCF) and a new combination of statistical techniques. First, the CCF is used to create the Advanced Correlation Grid (ACG) correlation where both the significant peak of the CCF and the corresponding time delay are used for detailed analysis of connectivity. Second, these two features of functional connectivity are used to classify connections. Finally, the visualization technique is used to represent the topology of functional connections. Examples are presented in the paper to demonstrate the new Advanced Correlation Grid method and to show how it enables discrimination between (i) influence from one spike train to another through an intermediate spike train and (ii) influence from one common spike train to another pair of analysed spike trains. The ACG method enables scientists to automatically distinguish between direct connections from spurious connections such as common source connection and indirect connection whereas existing methods require in-depth analysis to identify such connections. The ACG is a new and effective method for studying functional connectivity of multiple spike trains. This method can identify accurately all the direct connections and can distinguish common source and indirect connections automatically. Copyright © 2017 Elsevier B.V. All rights reserved.

Object localization through the lateral line system of fish: theory and experiment.

PubMed

Goulet, Julie; Engelmann, Jacob; Chagnaud, Boris P; Franosch, Jan-Moritz P; Suttner, Maria D; van Hemmen, J Leo

2008-01-01

Fish acquire information about their aquatic environment by means of their mechanosensory lateral-line system. This system consists of superficial and canal neuromasts that sense perturbations in the water surrounding them. Based on a hydrodynamic model presented here, we propose a mechanism through which fish can localize the source of these perturbations. In doing so we include the curvature of the fish body, a realistic lateral line canal inter-pore distance for the lateral-line canals, and the surface boundary layer. Using our model to explore receptor behavior based on experimental data of responses to dipole stimuli we suggest that superficial and canal neuromasts employ the same mechanism, hence provide the same type of input to the central nervous system. The analytical predictions agree well with spiking responses recorded experimentally from primary lateral-line nerve fibers. From this, and taking into account the central organization of the lateral-line system, we present a simple biophysical model for determining the distance to a source.

The mechanisms of repetitive spike generation in an axonless retinal interneuron

PubMed Central

Cembrowski, Mark S.; Logan, Stephen M.; Tian, Miao; Jia, Li; Li, Wei; Kath, William L.; Riecke, Hermann; Singer, Joshua H.

2012-01-01

SUMMARY Several types of retinal interneurons exhibit spikes but lack axons. One such neuron is the AII amacrine cell, in which spikes recorded at the soma exhibit small amplitudes (<10 mV) and broad time courses (>5 ms). Here, we used electrophysiological recordings and computational analysis to examine the mechanisms underlying this atypical spiking. We found that somatic spikes likely represent large, brief action potential-like events initiated in a single, electrotonically-distal dendritic compartment. In this same compartment, spiking undergoes slow modulation, likely by an M-type K conductance. The structural correlate of this compartment is a thin neurite that extends from the primary dendritic tree: local application of TTX to this neurite, or excision of it, eliminates spiking. Thus, the physiology of the axonless AII is much more complex than would be anticipated from morphological descriptions and somatic recordings; in particular, the AII possesses a single dendritic structure that controls its firing pattern. PMID:22832164

Correlated Disruption of Resting-State fMRI, LFP, and Spike Connectivity between Area 3b and S2 following Spinal Cord Injury in Monkeys.

PubMed

Wu, Ruiqi; Yang, Pai-Feng; Chen, Li Min

2017-11-15

This study aims to understand how functional connectivity (FC) between areas 3b and S2 alters following input deprivation and the neuronal basis of disrupted FC of resting-state fMRI signals. We combined submillimeter fMRI with microelectrode recordings to localize the deafferented digit regions in areas 3b and S2 by mapping tactile stimulus-evoked fMRI activations before and after cervical dorsal column lesion in each male monkey. An average afferent disruption of 97% significantly reduced fMRI, local field potential (LFP), and spike responses to stimuli in both areas. Analysis of resting-state fMRI signal correlation, LFP coherence, and spike cross-correlation revealed significantly reduced functional connectivity between deafferented areas 3b and S2. The degrees of reductions in stimulus responsiveness and FC after deafferentation differed across fMRI, LFP, and spiking signals. The reduction of FC was much weaker than that of stimulus-evoked responses. Whereas the largest stimulus-evoked signal drop (∼80%) was observed in LFP signals, the greatest FC reduction was detected in the spiking activity (∼30%). fMRI signals showed mild reductions in stimulus responsiveness (∼25%) and FC (∼20%). The overall deafferentation-induced changes were quite similar in areas 3b and S2 across signals. Here we demonstrated that FC strength between areas 3b and S2 was much weakened by dorsal column lesion, and stimulus response reduction and FC disruption in fMRI covary with those of LFP and spiking signals in deafferented areas 3b and S2. These findings have important implications for fMRI studies aiming to probe FC alterations in pathological conditions involving deafferentation in humans. SIGNIFICANCE STATEMENT By directly comparing fMRI, local field potential, and spike signals in both tactile stimulation and resting states before and after severe disruption of dorsal column afferent, we demonstrated that reduction in fMRI responses to stimuli is accompanied by weakened resting-state fMRI functional connectivity (FC) in input-deprived and reorganized digit regions in area 3b of the S1 and S2. Concurrent reductions in local field potential and spike FC validated the use of resting-state fMRI signals for probing neural intrinsic FC alterations in pathological deafferented cortex, and indicated that disrupted FC between mesoscale functionally highly related regions may contribute to the behavioral impairments. Copyright © 2017 the authors 0270-6474/17/3711192-12$15.00/0.

Correlated Disruption of Resting-State fMRI, LFP, and Spike Connectivity between Area 3b and S2 following Spinal Cord Injury in Monkeys

PubMed Central

2017-01-01

This study aims to understand how functional connectivity (FC) between areas 3b and S2 alters following input deprivation and the neuronal basis of disrupted FC of resting-state fMRI signals. We combined submillimeter fMRI with microelectrode recordings to localize the deafferented digit regions in areas 3b and S2 by mapping tactile stimulus-evoked fMRI activations before and after cervical dorsal column lesion in each male monkey. An average afferent disruption of 97% significantly reduced fMRI, local field potential (LFP), and spike responses to stimuli in both areas. Analysis of resting-state fMRI signal correlation, LFP coherence, and spike cross-correlation revealed significantly reduced functional connectivity between deafferented areas 3b and S2. The degrees of reductions in stimulus responsiveness and FC after deafferentation differed across fMRI, LFP, and spiking signals. The reduction of FC was much weaker than that of stimulus-evoked responses. Whereas the largest stimulus-evoked signal drop (∼80%) was observed in LFP signals, the greatest FC reduction was detected in the spiking activity (∼30%). fMRI signals showed mild reductions in stimulus responsiveness (∼25%) and FC (∼20%). The overall deafferentation-induced changes were quite similar in areas 3b and S2 across signals. Here we demonstrated that FC strength between areas 3b and S2 was much weakened by dorsal column lesion, and stimulus response reduction and FC disruption in fMRI covary with those of LFP and spiking signals in deafferented areas 3b and S2. These findings have important implications for fMRI studies aiming to probe FC alterations in pathological conditions involving deafferentation in humans. SIGNIFICANCE STATEMENT By directly comparing fMRI, local field potential, and spike signals in both tactile stimulation and resting states before and after severe disruption of dorsal column afferent, we demonstrated that reduction in fMRI responses to stimuli is accompanied by weakened resting-state fMRI functional connectivity (FC) in input-deprived and reorganized digit regions in area 3b of the S1 and S2. Concurrent reductions in local field potential and spike FC validated the use of resting-state fMRI signals for probing neural intrinsic FC alterations in pathological deafferented cortex, and indicated that disrupted FC between mesoscale functionally highly related regions may contribute to the behavioral impairments. PMID:29038239

Dendritic sodium spikes are required for long-term potentiation at distal synapses on hippocampal pyramidal neurons

PubMed Central

Kim, Yujin; Hsu, Ching-Lung; Cembrowski, Mark S; Mensh, Brett D; Spruston, Nelson

2015-01-01

Dendritic integration of synaptic inputs mediates rapid neural computation as well as longer-lasting plasticity. Several channel types can mediate dendritically initiated spikes (dSpikes), which may impact information processing and storage across multiple timescales; however, the roles of different channels in the rapid vs long-term effects of dSpikes are unknown. We show here that dSpikes mediated by Nav channels (blocked by a low concentration of TTX) are required for long-term potentiation (LTP) in the distal apical dendrites of hippocampal pyramidal neurons. Furthermore, imaging, simulations, and buffering experiments all support a model whereby fast Nav channel-mediated dSpikes (Na-dSpikes) contribute to LTP induction by promoting large, transient, localized increases in intracellular calcium concentration near the calcium-conducting pores of NMDAR and L-type Cav channels. Thus, in addition to contributing to rapid neural processing, Na-dSpikes are likely to contribute to memory formation via their role in long-lasting synaptic plasticity. DOI: http://dx.doi.org/10.7554/eLife.06414.001 PMID:26247712

Gamma Oscillations of Spiking Neural Populations Enhance Signal Discrimination

PubMed Central

Masuda, Naoki; Doiron, Brent

2007-01-01

Selective attention is an important filter for complex environments where distractions compete with signals. Attention increases both the gamma-band power of cortical local field potentials and the spike-field coherence within the receptive field of an attended object. However, the mechanisms by which gamma-band activity enhances, if at all, the encoding of input signals are not well understood. We propose that gamma oscillations induce binomial-like spike-count statistics across noisy neural populations. Using simplified models of spiking neurons, we show how the discrimination of static signals based on the population spike-count response is improved with gamma induced binomial statistics. These results give an important mechanistic link between the neural correlates of attention and the discrimination tasks where attention is known to enhance performance. Further, they show how a rhythmicity of spike responses can enhance coding schemes that are not temporally sensitive. PMID:18052541

A Basic Experiment on the Aerodynamics of Sniffing

NASA Astrophysics Data System (ADS)

Settles, Gary S.; Kester, Douglas A.

1999-11-01

Our previous work (APS/DFD97:Ii1 and 98:FA10) used flow visualization to observe canine olfaction. The results raised some basic questions about the aerodynamics of sniffing, e.g. what flow rate is required, as a function of distance from a scent source, to acquire a detectable scent? Commercial sampler technology does not address such questions. A basic experiment was thus designed to investigate the aerodynamic phenomena and performance of sniffing. A stable thermal layer on a horizontal plane was used as a "scent" source per Reynolds Analogy. The detector was a thermocouple inside a sniffer tube. Flow patterns were observed by schlieren. Results show the importance of sniffer proximity to localize a scent source. A transient scent spike occurs at the sniff onset, followed by signal decline due to source depletion. Sniffing shows extreme sensitivity to disruptive air currents. Unstably-stratified scent sources (thermal plumes) are also considered. These results help us understand evolved sniffing behavior, and they suggest sampler design criteria for electronic-nose devices. (Research supported by DARPA.)

Regulation of Local Ambient GABA Levels via Transporter-Mediated GABA Import and Export for Subliminal Learning.

PubMed

Hoshino, Osamu

2015-06-01

Perception of supraliminal stimuli might in general be reflected in bursts of action potentials (spikes), and their memory traces could be formed through spike-timing-dependent plasticity (STDP). Memory traces for subliminal stimuli might be formed in a different manner, because subliminal stimulation evokes a fraction (but not a burst) of spikes. Simulations of a cortical neural network model showed that a subliminal stimulus that was too brief (10 msec) to perceive transiently (more than about 500 msec) depolarized stimulus-relevant principal cells and hyperpolarized stimulus-irrelevant principal cells in a subthreshold manner. This led to a small increase or decrease in ongoing-spontaneous spiking activity frequency (less than 1 Hz). Synaptic modification based on STDP during this period effectively enhanced relevant synaptic weights, by which subliminal learning was improved. GABA transporters on GABAergic interneurons modulated local levels of ambient GABA. Ambient GABA molecules acted on extrasynaptic receptors, provided principal cells with tonic inhibitory currents, and contributed to achieving the subthreshold neuronal state. We suggest that ongoing-spontaneous synaptic alteration through STDP following subliminal stimulation may be a possible neuronal mechanism for leaving its memory trace in cortical circuitry. Regulation of local ambient GABA levels by transporter-mediated GABA import and export may be crucial for subliminal learning.

Spatio-temporal conditional inference and hypothesis tests for neural ensemble spiking precision

PubMed Central

Harrison, Matthew T.; Amarasingham, Asohan; Truccolo, Wilson

2014-01-01

The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spatio-temporal conditional inference (STCI) is introduced here as a semiparametric statistical framework for investigating the nature of precise spiking patterns from collections of neurons that is robust to arbitrarily complex and nonstationary coarse spiking dynamics. The main idea is to focus statistical modeling and inference, not on the full distribution of the data, but rather on families of conditional distributions of precise spiking given different types of coarse spiking. The framework is then used to develop families of hypothesis tests for probing the spatio-temporal precision of spiking patterns. Relationships among different conditional distributions are used to improve multiple hypothesis testing adjustments and to design novel Monte Carlo spike resampling algorithms. Of special note are algorithms that can locally jitter spike times while still preserving the instantaneous peri-stimulus time histogram (PSTH) or the instantaneous total spike count from a group of recorded neurons. The framework can also be used to test whether first-order maximum entropy models with possibly random and time-varying parameters can account for observed patterns of spiking. STCI provides a detailed example of the generic principle of conditional inference, which may be applicable in other areas of neurostatistical analysis. PMID:25380339

Dissecting local circuits in vivo: integrated optogenetic and electrophysiology approaches for exploring inhibitory regulation of cortical activity.

PubMed

Cardin, Jessica A

2012-01-01

Local cortical circuit activity in vivo comprises a complex and flexible series of interactions between excitatory and inhibitory neurons. Our understanding of the functional interactions between these different neural populations has been limited by the difficulty of identifying and selectively manipulating the diverse and sparsely represented inhibitory interneuron classes in the intact brain. The integration of recently developed optical tools with traditional electrophysiological techniques provides a powerful window into the role of inhibition in regulating the activity of excitatory neurons. In particular, optogenetic targeting of specific cell classes reveals the distinct impacts of local inhibitory populations on other neurons in the surrounding local network. In addition to providing the ability to activate or suppress spiking in target cells, optogenetic activation identifies extracellularly recorded neurons by class, even when naturally occurring spike rates are extremely low. However, there are several important limitations on the use of these tools and the interpretation of resulting data. The purpose of this article is to outline the uses and limitations of optogenetic tools, along with current methods for achieving cell type-specific expression, and to highlight the advantages of an experimental approach combining optogenetics and electrophysiology to explore the role of inhibition in active networks. To illustrate the efficacy of these combined approaches, I present data comparing targeted manipulations of cortical fast-spiking, parvalbumin-expressing and low threshold-spiking, somatostatin-expressing interneurons in vivo. Copyright © 2011 Elsevier Ltd. All rights reserved.

Electron Demagnetization and Collisionless Magnetic Reconnection in βe ≪ 1 Plasmas: Theory and Observations

NASA Astrophysics Data System (ADS)

Scudder, J. D.; Mozer, F. S.

2005-05-01

Abrupt, intense bipolar and unipolar electric spikes with E > 100mV/m surveyed over 3 years of Polar data (Mozer et al 2005) have been organized to answer the limited question: can they be involved in the local demagnetization of thermal electrons? We determine a lower bound on the electric strength sufficient to cause non-gyrotropic effects on the electron pressure tensor of the form E>E*=B{we}/{8c Im}, where B is the ambient magnetic field strength, we=√2kTe/me, c is the speed of light, and Im is an electron velocity space weighted average displacement along the electric field while transiting the layer (assumed localized with a scale Δ x=a ρe, where ρe is the electron thermal gyroradius). The variation of Im as a function of a for equal mean energy Maxwellian and more typical κ distributions seen in the Earth's magnetosphere provides strong evidence that the surveyed electric field spikes are generally smaller than E* (assuming ≍ 1), although 23% (n=57) exceed E* . Only 11% (n=6) of the bipolar class exceed E* ; the frequency of occurrence distribution for the bipolar class of spikes is peaked at 0.1E*. The unipolar occurrence is flat below E*, but has a significant 26% subgroup (n=51) that exceed E* . While E* does not depend on the ambient density, the occurrence distribution of all demagnetizing events is well organized by the ratio ℜ=λDe/ρe=&Omegace/ωpe, residing almost exclusively in the regime ℜ <1. Spikes with E < E* generally occur with ℜ >1 . All the electrostatic spike events surveyed occur in the regime 10-8≤βe≤3×10-2. The demagnetizing events of either class occupy the more restricted low beta regime 10-3≤βe≤3×10-2. Because these demagnetizing events occur in βe ≪ 1 they would not, however, be considered unmagnetized at current channels as thin as the electron skin depth, de, since for such current channels ρe ≡ βe-1/2de ≪ de. As a group the subset of unipolar events with E > E* are consistently understood as sites where the electron pressure tensor could become deformed from cylindrical symmetry by electric field enhancement in layers with scale sizes up to the local thermal electron's gyroradius. Such a deformation is critical for a viable mechanism that supports collisionless reconnection. After selecting events as demagnetizing based on the size of the relevant forces and work done, the geophysical locale of their detection has been investigated. Previously, all E spikes in this survey were found near the invariant latitudes Λ of the earth's magnetic cusps but at all magnetic local times. The demagnetizing events identified here via E* are strongly organized at magnetic local noon (with a secondary, much shallower maximum at local magnetic midnight), occur preferentially at orbit apogee, and without significant preference for the magnetic latitude of the spacecraft. These geophysical organizations are consistent with the demagnetizing E spikes as indices of ongoing, collisionless reconnection in low βe regimes at the earth's subsolar magnetopause. The identification of this sub-class of electric spikes at low βe with E>E* widens the observed venues in the E and B fields where topology changing departures from ideal MHD should be anticipated in collisionless astrophysical plasmas.

Source reconstruction via the spatiotemporal Kalman filter and LORETA from EEG time series with 32 or fewer electrodes.

PubMed

Hamid, Laith; Al Farawn, Ali; Merlet, Isabelle; Japaridze, Natia; Heute, Ulrich; Stephani, Ulrich; Galka, Andreas; Wendling, Fabrice; Siniatchkin, Michael

2017-07-01

The clinical routine of non-invasive electroencephalography (EEG) is usually performed with 8-40 electrodes, especially in long-term monitoring, infants or emergency care. There is a need in clinical and scientific brain imaging to develop inverse solution methods that can reconstruct brain sources from these low-density EEG recordings. In this proof-of-principle paper we investigate the performance of the spatiotemporal Kalman filter (STKF) in EEG source reconstruction with 9-, 19- and 32- electrodes. We used simulated EEG data of epileptic spikes generated from lateral frontal and lateral temporal brain sources using state-of-the-art neuronal population models. For validation of source reconstruction, we compared STKF results to the location of the simulated source and to the results of low-resolution brain electromagnetic tomography (LORETA) standard inverse solution. STKF consistently showed less localization bias compared to LORETA, especially when the number of electrodes was decreased. The results encourage further research into the application of the STKF in source reconstruction of brain activity from low-density EEG recordings.

Poisson-Like Spiking in Circuits with Probabilistic Synapses

PubMed Central

Moreno-Bote, Rubén

2014-01-01

Neuronal activity in cortex is variable both spontaneously and during stimulation, and it has the remarkable property that it is Poisson-like over broad ranges of firing rates covering from virtually zero to hundreds of spikes per second. The mechanisms underlying cortical-like spiking variability over such a broad continuum of rates are currently unknown. We show that neuronal networks endowed with probabilistic synaptic transmission, a well-documented source of variability in cortex, robustly generate Poisson-like variability over several orders of magnitude in their firing rate without fine-tuning of the network parameters. Other sources of variability, such as random synaptic delays or spike generation jittering, do not lead to Poisson-like variability at high rates because they cannot be sufficiently amplified by recurrent neuronal networks. We also show that probabilistic synapses predict Fano factor constancy of synaptic conductances. Our results suggest that synaptic noise is a robust and sufficient mechanism for the type of variability found in cortex. PMID:25032705

Spreading Photoparoxysmal EEG Response is Associated with an Abnormal Cortical Excitability Pattern

ERIC Educational Resources Information Center

Siniatchkin, Michael; Groppa, Sergey; Jerosch, Bettina; Muhle, Hiltrud; Kurth, Christoph; Shepherd, Alex J.; Siebner, Hartwig; Stephani, Ulrich

2007-01-01

Photosensitivity or photoparoxysmal response (PPR) is a highly heritable electroencephalographic trait characterized by an abnormal cortical response to intermittent photic stimulation (IPS). In PPR-positive individuals, IPS induces spikes, spike-waves or intermittent slow waves. The PPR may be restricted to posterior visual areas (i.e. local PPR…

Stellar occultation spikes as probes of atmospheric structure and composition. [for Jupiter

NASA Technical Reports Server (NTRS)

Elliot, J. L.; Veverka, J.

1976-01-01

The characteristics of spikes observed in occultation light curves of Beta Scorpii by Jupiter are discussed in terms of the gravity-gradient model. The occultation of Beta Sco by Jupiter on May 13, 1971, is reviewed, and the gravity-gradient model is defined as an isothermal atmosphere of constant composition in which the refractivity is a function only of the radial coordinate from the center of refraction, which is assumed to lie parallel to the local gravity gradient. The derivation of the occultation light curve in terms of the atmosphere, the angular diameter of the occulted star, and the occultation geometry is outlined. It is shown that analysis of the light-curve spikes can yield the He/H2 concentration ratio in a well-mixed atmosphere, information on fine-scale atmospheric structure, high-resolution images of the occulted star, and information on ray crossing. Observational limits are placed on the magnitude of horizontal refractivity gradients, and it is concluded that the spikes are the result of local atmospheric density variations: atmospheric layers, density waves, or turbulence.

Modeling somatic and dendritic spike mediated plasticity at the single neuron and network level.

PubMed

Bono, Jacopo; Clopath, Claudia

2017-09-26

Synaptic plasticity is thought to be the principal neuronal mechanism underlying learning. Models of plastic networks typically combine point neurons with spike-timing-dependent plasticity (STDP) as the learning rule. However, a point neuron does not capture the local non-linear processing of synaptic inputs allowed for by dendrites. Furthermore, experimental evidence suggests that STDP is not the only learning rule available to neurons. By implementing biophysically realistic neuron models, we study how dendrites enable multiple synaptic plasticity mechanisms to coexist in a single cell. In these models, we compare the conditions for STDP and for synaptic strengthening by local dendritic spikes. We also explore how the connectivity between two cells is affected by these plasticity rules and by different synaptic distributions. Finally, we show that how memory retention during associative learning can be prolonged in networks of neurons by including dendrites.Synaptic plasticity is the neuronal mechanism underlying learning. Here the authors construct biophysical models of pyramidal neurons that reproduce observed plasticity gradients along the dendrite and show that dendritic spike dependent LTP which is predominant in distal sections can prolong memory retention.

α-Oscillations in the monkey sensorimotor network influence discrimination performance by rhythmical inhibition of neuronal spiking.

PubMed

Haegens, Saskia; Nácher, Verónica; Luna, Rogelio; Romo, Ranulfo; Jensen, Ole

2011-11-29

Extensive work in humans using magneto- and electroencephalography strongly suggests that decreased oscillatory α-activity (8-14 Hz) facilitates processing in a given region, whereas increased α-activity serves to actively suppress irrelevant or interfering processing. However, little work has been done to understand how α-activity is linked to neuronal firing. Here, we simultaneously recorded local field potentials and spikes from somatosensory, premotor, and motor regions while a trained monkey performed a vibrotactile discrimination task. In the local field potentials we observed strong activity in the α-band, which decreased in the sensorimotor regions during the discrimination task. This α-power decrease predicted better discrimination performance. Furthermore, the α-oscillations demonstrated a rhythmic relation with the spiking, such that firing was highest at the trough of the α-cycle. Firing rates increased with a decrease in α-power. These findings suggest that α-oscillations exercise a strong inhibitory influence on both spike timing and firing rate. Thus, the pulsed inhibition by α-oscillations plays an important functional role in the extended sensorimotor system.

Low-noise encoding of active touch by layer 4 in the somatosensory cortex.

PubMed

Hires, Samuel Andrew; Gutnisky, Diego A; Yu, Jianing; O'Connor, Daniel H; Svoboda, Karel

2015-08-06

Cortical spike trains often appear noisy, with the timing and number of spikes varying across repetitions of stimuli. Spiking variability can arise from internal (behavioral state, unreliable neurons, or chaotic dynamics in neural circuits) and external (uncontrolled behavior or sensory stimuli) sources. The amount of irreducible internal noise in spike trains, an important constraint on models of cortical networks, has been difficult to estimate, since behavior and brain state must be precisely controlled or tracked. We recorded from excitatory barrel cortex neurons in layer 4 during active behavior, where mice control tactile input through learned whisker movements. Touch was the dominant sensorimotor feature, with >70% spikes occurring in millisecond timescale epochs after touch onset. The variance of touch responses was smaller than expected from Poisson processes, often reaching the theoretical minimum. Layer 4 spike trains thus reflect the millisecond-timescale structure of tactile input with little noise.

Energetic Constraints Produce Self-sustained Oscillatory Dynamics in Neuronal Networks

PubMed Central

Burroni, Javier; Taylor, P.; Corey, Cassian; Vachnadze, Tengiz; Siegelmann, Hava T.

2017-01-01

Overview: We model energy constraints in a network of spiking neurons, while exploring general questions of resource limitation on network function abstractly. Background: Metabolic states like dietary ketosis or hypoglycemia have a large impact on brain function and disease outcomes. Glia provide metabolic support for neurons, among other functions. Yet, in computational models of glia-neuron cooperation, there have been no previous attempts to explore the effects of direct realistic energy costs on network activity in spiking neurons. Currently, biologically realistic spiking neural networks assume that membrane potential is the main driving factor for neural spiking, and do not take into consideration energetic costs. Methods: We define local energy pools to constrain a neuron model, termed Spiking Neuron Energy Pool (SNEP), which explicitly incorporates energy limitations. Each neuron requires energy to spike, and resources in the pool regenerate over time. Our simulation displays an easy-to-use GUI, which can be run locally in a web browser, and is freely available. Results: Energy dependence drastically changes behavior of these neural networks, causing emergent oscillations similar to those in networks of biological neurons. We analyze the system via Lotka-Volterra equations, producing several observations: (1) energy can drive self-sustained oscillations, (2) the energetic cost of spiking modulates the degree and type of oscillations, (3) harmonics emerge with frequencies determined by energy parameters, and (4) varying energetic costs have non-linear effects on energy consumption and firing rates. Conclusions: Models of neuron function which attempt biological realism may benefit from including energy constraints. Further, we assert that observed oscillatory effects of energy limitations exist in networks of many kinds, and that these findings generalize to abstract graphs and technological applications. PMID:28289370

Microbiological effectiveness of locally produced ceramic filters for drinking water treatment in Cambodia.

PubMed

Brown, Joe; Sobsey, Mark D

2010-03-01

Low-cost options for the treatment of drinking water at the household level are being explored by the Cambodian government and non-governmental organizations (NGOs) working in Cambodia, where many lack access to improved drinking water sources and diarrhoeal diseases are the most prevalent cause of death in children under 5 years of age. The ceramic water purifier (CWP), a locally produced, low-cost ceramic filter, is now being implemented by several NGOs, and an estimated 100,000+households in the country now use them for drinking water treatment. Two candidate filters were tested for the reduction of bacterial and viral surrogates for waterborne pathogens using representative Cambodian drinking water sources (rainwater and surface water) spiked with Escherichia coli and bacteriophage MS2. Results indicate that filters were capable of reducing key microbes in the laboratory with mean reductions of E. coli of approximately 99% and mean reduction of bacteriophages of 90-99% over >600 litres throughput. Increased effectiveness was not observed in filters with an AgNO3 amendment. At under US$10 per filter, locally produced ceramic filters may be a promising option for drinking water treatment and safe storage at the household level.

Independent components of neural activity carry information on individual populations.

PubMed

Głąbska, Helena; Potworowski, Jan; Łęski, Szymon; Wójcik, Daniel K

2014-01-01

Local field potential (LFP), the low-frequency part of the potential recorded extracellularly in the brain, reflects neural activity at the population level. The interpretation of LFP is complicated because it can mix activity from remote cells, on the order of millimeters from the electrode. To understand better the relation between the recordings and the local activity of cells we used a large-scale network thalamocortical model to compute simultaneous LFP, transmembrane currents, and spiking activity. We used this model to study the information contained in independent components obtained from the reconstructed Current Source Density (CSD), which smooths transmembrane currents, decomposed further with Independent Component Analysis (ICA). We found that the three most robust components matched well the activity of two dominating cell populations: superior pyramidal cells in layer 2/3 (rhythmic spiking) and tufted pyramids from layer 5 (intrinsically bursting). The pyramidal population from layer 2/3 could not be well described as a product of spatial profile and temporal activation, but by a sum of two such products which we recovered in two of the ICA components in our analysis, which correspond to the two first principal components of PCA decomposition of layer 2/3 population activity. At low noise one more cell population could be discerned but it is unlikely that it could be recovered in experiment given typical noise ranges.

Independent Components of Neural Activity Carry Information on Individual Populations

PubMed Central

Głąbska, Helena; Potworowski, Jan; Łęski, Szymon; Wójcik, Daniel K.

2014-01-01

Local field potential (LFP), the low-frequency part of the potential recorded extracellularly in the brain, reflects neural activity at the population level. The interpretation of LFP is complicated because it can mix activity from remote cells, on the order of millimeters from the electrode. To understand better the relation between the recordings and the local activity of cells we used a large-scale network thalamocortical model to compute simultaneous LFP, transmembrane currents, and spiking activity. We used this model to study the information contained in independent components obtained from the reconstructed Current Source Density (CSD), which smooths transmembrane currents, decomposed further with Independent Component Analysis (ICA). We found that the three most robust components matched well the activity of two dominating cell populations: superior pyramidal cells in layer 2/3 (rhythmic spiking) and tufted pyramids from layer 5 (intrinsically bursting). The pyramidal population from layer 2/3 could not be well described as a product of spatial profile and temporal activation, but by a sum of two such products which we recovered in two of the ICA components in our analysis, which correspond to the two first principal components of PCA decomposition of layer 2/3 population activity. At low noise one more cell population could be discerned but it is unlikely that it could be recovered in experiment given typical noise ranges. PMID:25153730

Magnetoencephalography with temporal spread imaging to visualize propagation of epileptic activity.

PubMed

Shibata, Sumiya; Matsuhashi, Masao; Kunieda, Takeharu; Yamao, Yukihiro; Inano, Rika; Kikuchi, Takayuki; Imamura, Hisaji; Takaya, Shigetoshi; Matsumoto, Riki; Ikeda, Akio; Takahashi, Ryosuke; Mima, Tatsuya; Fukuyama, Hidenao; Mikuni, Nobuhiro; Miyamoto, Susumu

2017-05-01

We describe temporal spread imaging (TSI) that can identify the spatiotemporal pattern of epileptic activity using Magnetoencephalography (MEG). A three-dimensional grid of voxels covering the brain is created. The array-gain minimum-variance spatial filter is applied to an interictal spike to estimate the magnitude of the source and the time (Ta) when the magnitude exceeds a predefined threshold at each voxel. This calculation is performed through all spikes. Each voxel has the mean Ta () and spike number (N sp ), which is the number of spikes whose source exceeds the threshold. Then, a random resampling method is used to determine the cutoff value of N sp for the statistically reproducible pattern of the activity. Finally, all the voxels where the source exceeds the threshold reproducibly shown on the MRI with a color scale representing . Four patients with intractable mesial temporal lobe epilepsy (MTLE) were analyzed. In three patients, the common pattern of the overlap between the propagation and the hypometabolism shown by fluorodeoxyglucose-positron emission tomography (FDG-PET) was identified. TSI can visualize statistically reproducible patterns of the temporal and spatial spread of epileptic activity. TSI can assess the statistical significance of the spatiotemporal pattern based on its reproducibility. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

ϒ Spike-Field Coherence in a Population of Olfactory Bulb Neurons Differentiates between Odors Irrespective of Associated Outcome

PubMed Central

Li, Anan; Gire, David H.

2015-01-01

Studies in different sensory systems indicate that short spike patterns within a spike train that carry items of sensory information can be extracted from the overall train by using field potential oscillations as a reference (Kayser et al., 2012; Panzeri et al., 2014). Here we test the hypothesis that the local field potential (LFP) provides the temporal reference frame needed to differentiate between odors regardless of associated outcome. Experiments were performed in the olfactory system of the mouse (Mus musculus) where the mitral/tufted (M/T) cell spike rate develops differential responses to rewarded and unrewarded odors as the animal learns to associate one of the odors with a reward in a go–no go behavioral task. We found that coherence of spiking in M/T cells with the ϒ LFP (65 to 95 Hz) differentiates between odors regardless of the associated behavioral outcome of odor presentation. PMID:25855190

Unsupervised learning of temporal features for word categorization in a spiking neural network model of the auditory brain.

PubMed

Higgins, Irina; Stringer, Simon; Schnupp, Jan

2017-01-01

The nature of the code used in the auditory cortex to represent complex auditory stimuli, such as naturally spoken words, remains a matter of debate. Here we argue that such representations are encoded by stable spatio-temporal patterns of firing within cell assemblies known as polychronous groups, or PGs. We develop a physiologically grounded, unsupervised spiking neural network model of the auditory brain with local, biologically realistic, spike-time dependent plasticity (STDP) learning, and show that the plastic cortical layers of the network develop PGs which convey substantially more information about the speaker independent identity of two naturally spoken word stimuli than does rate encoding that ignores the precise spike timings. We furthermore demonstrate that such informative PGs can only develop if the input spatio-temporal spike patterns to the plastic cortical areas of the model are relatively stable.

Unsupervised learning of temporal features for word categorization in a spiking neural network model of the auditory brain

PubMed Central

Stringer, Simon

2017-01-01

The nature of the code used in the auditory cortex to represent complex auditory stimuli, such as naturally spoken words, remains a matter of debate. Here we argue that such representations are encoded by stable spatio-temporal patterns of firing within cell assemblies known as polychronous groups, or PGs. We develop a physiologically grounded, unsupervised spiking neural network model of the auditory brain with local, biologically realistic, spike-time dependent plasticity (STDP) learning, and show that the plastic cortical layers of the network develop PGs which convey substantially more information about the speaker independent identity of two naturally spoken word stimuli than does rate encoding that ignores the precise spike timings. We furthermore demonstrate that such informative PGs can only develop if the input spatio-temporal spike patterns to the plastic cortical areas of the model are relatively stable. PMID:28797034

Multivariate cross-frequency coupling via generalized eigendecomposition

PubMed Central

Cohen, Michael X

2017-01-01

This paper presents a new framework for analyzing cross-frequency coupling in multichannel electrophysiological recordings. The generalized eigendecomposition-based cross-frequency coupling framework (gedCFC) is inspired by source-separation algorithms combined with dynamics of mesoscopic neurophysiological processes. It is unaffected by factors that confound traditional CFC methods—such as non-stationarities, non-sinusoidality, and non-uniform phase angle distributions—attractive properties considering that brain activity is neither stationary nor perfectly sinusoidal. The gedCFC framework opens new opportunities for conceptualizing CFC as network interactions with diverse spatial/topographical distributions. Five specific methods within the gedCFC framework are detailed, these are validated in simulated data and applied in several empirical datasets. gedCFC accurately recovers physiologically plausible CFC patterns embedded in noise that causes traditional CFC methods to perform poorly. The paper also demonstrates that spike-field coherence in multichannel local field potential data can be analyzed using the gedCFC framework, which provides significant advantages over traditional spike-field coherence analyses. Null-hypothesis testing is also discussed. DOI: http://dx.doi.org/10.7554/eLife.21792.001 PMID:28117662

Using the virtual brain to reveal the role of oscillations and plasticity in shaping brain's dynamical landscape.

PubMed

Roy, Dipanjan; Sigala, Rodrigo; Breakspear, Michael; McIntosh, Anthony Randal; Jirsa, Viktor K; Deco, Gustavo; Ritter, Petra

2014-12-01

Spontaneous brain activity, that is, activity in the absence of controlled stimulus input or an explicit active task, is topologically organized in multiple functional networks (FNs) maintaining a high degree of coherence. These "resting state networks" are constrained by the underlying anatomical connectivity between brain areas. They are also influenced by the history of task-related activation. The precise rules that link plastic changes and ongoing dynamics of resting-state functional connectivity (rs-FC) remain unclear. Using the framework of the open source neuroinformatics platform "The Virtual Brain," we identify potential computational mechanisms that alter the dynamical landscape, leading to reconfigurations of FNs. Using a spiking neuron model, we first demonstrate that network activity in the absence of plasticity is characterized by irregular oscillations between low-amplitude asynchronous states and high-amplitude synchronous states. We then demonstrate the capability of spike-timing-dependent plasticity (STDP) combined with intrinsic alpha (8-12 Hz) oscillations to efficiently influence learning. Further, we show how alpha-state-dependent STDP alters the local area dynamics from an irregular to a highly periodic alpha-like state. This is an important finding, as the cortical input from the thalamus is at the rate of alpha. We demonstrate how resulting rhythmic cortical output in this frequency range acts as a neuronal tuner and, hence, leads to synchronization or de-synchronization between brain areas. Finally, we demonstrate that locally restricted structural connectivity changes influence local as well as global dynamics and lead to altered rs-FC.

[Multi-channel in vivo recording techniques: analysis of phase coupling between spikes and rhythmic oscillations of local field potentials].

PubMed

Wang, Ce-Qun; Chen, Qiang; Zhang, Lu; Xu, Jia-Min; Lin, Long-Nian

2014-12-25

The purpose of this article is to introduce the measurements of phase coupling between spikes and rhythmic oscillations of local field potentials (LFPs). Multi-channel in vivo recording techniques allow us to record ensemble neuronal activity and LFPs simultaneously from the same sites in the brain. Neuronal activity is generally characterized by temporal spike sequences, while LFPs contain oscillatory rhythms in different frequency ranges. Phase coupling analysis can reveal the temporal relationships between neuronal firing and LFP rhythms. As the first step, the instantaneous phase of LFP rhythms can be calculated using Hilbert transform, and then for each time-stamped spike occurred during an oscillatory epoch, we marked instantaneous phase of the LFP at that time stamp. Finally, the phase relationships between the neuronal firing and LFP rhythms were determined by examining the distribution of the firing phase. Phase-locked spikes are revealed by the non-random distribution of spike phase. Theta phase precession is a unique phase relationship between neuronal firing and LFPs, which is one of the basic features of hippocampal place cells. Place cells show rhythmic burst firing following theta oscillation within a place field. And phase precession refers to that rhythmic burst firing shifted in a systematic way during traversal of the field, moving progressively forward on each theta cycle. This relation between phase and position can be described by a linear model, and phase precession is commonly quantified with a circular-linear coefficient. Phase coupling analysis helps us to better understand the temporal information coding between neuronal firing and LFPs.

Synchronous inhibitory potentials precede seizure-like events in acute models of focal limbic seizures.

PubMed

Uva, Laura; Breschi, Gian Luca; Gnatkovsky, Vadym; Taverna, Stefano; de Curtis, Marco

2015-02-18

Interictal spikes in models of focal seizures and epilepsies are sustained by the synchronous activation of glutamatergic and GABAergic networks. The nature of population spikes associated with seizure initiation (pre-ictal spikes; PSs) is still undetermined. We analyzed the networks involved in the generation of both interictal and PSs in acute models of limbic cortex ictogenesis induced by pharmacological manipulations. Simultaneous extracellular and intracellular recordings from both principal cells and interneurons were performed in the medial entorhinal cortex of the in vitro isolated guinea pig brain during focal interictal and ictal discharges induced in the limbic network by intracortical and brief arterial infusions of either bicuculline methiodide (BMI) or 4-aminopyridine (4AP). Local application of BMI in the entorhinal cortex did not induce seizure-like events (SLEs), but did generate periodic interictal spikes sensitive to the glutamatergic non-NMDA receptor antagonist DNQX. Unlike local applications, arterial perfusion of either BMI or 4AP induced focal limbic SLEs. PSs just ahead of SLE were associated with hyperpolarizing potentials coupled with a complete blockade of firing in principal cells and burst discharges in putative interneurons. Interictal population spikes recorded from principal neurons between two SLEs correlated with a depolarizing potential. We demonstrate in two models of acute limbic SLE that PS events are different from interictal spikes and are sustained by synchronous activation of inhibitory networks. Our findings support a prominent role of synchronous network inhibition in the initiation of a focal seizure. Copyright © 2015 the authors 0270-6474/15/353048-08$15.00/0.

Consensus-Based Sorting of Neuronal Spike Waveforms

PubMed Central

Fournier, Julien; Mueller, Christian M.; Shein-Idelson, Mark; Hemberger, Mike

2016-01-01

Optimizing spike-sorting algorithms is difficult because sorted clusters can rarely be checked against independently obtained “ground truth” data. In most spike-sorting algorithms in use today, the optimality of a clustering solution is assessed relative to some assumption on the distribution of the spike shapes associated with a particular single unit (e.g., Gaussianity) and by visual inspection of the clustering solution followed by manual validation. When the spatiotemporal waveforms of spikes from different cells overlap, the decision as to whether two spikes should be assigned to the same source can be quite subjective, if it is not based on reliable quantitative measures. We propose a new approach, whereby spike clusters are identified from the most consensual partition across an ensemble of clustering solutions. Using the variability of the clustering solutions across successive iterations of the same clustering algorithm (template matching based on K-means clusters), we estimate the probability of spikes being clustered together and identify groups of spikes that are not statistically distinguishable from one another. Thus, we identify spikes that are most likely to be clustered together and therefore correspond to consistent spike clusters. This method has the potential advantage that it does not rely on any model of the spike shapes. It also provides estimates of the proportion of misclassified spikes for each of the identified clusters. We tested our algorithm on several datasets for which there exists a ground truth (simultaneous intracellular data), and show that it performs close to the optimum reached by a support vector machine trained on the ground truth. We also show that the estimated rate of misclassification matches the proportion of misclassified spikes measured from the ground truth data. PMID:27536990

Consensus-Based Sorting of Neuronal Spike Waveforms.

PubMed

Fournier, Julien; Mueller, Christian M; Shein-Idelson, Mark; Hemberger, Mike; Laurent, Gilles

2016-01-01

Optimizing spike-sorting algorithms is difficult because sorted clusters can rarely be checked against independently obtained "ground truth" data. In most spike-sorting algorithms in use today, the optimality of a clustering solution is assessed relative to some assumption on the distribution of the spike shapes associated with a particular single unit (e.g., Gaussianity) and by visual inspection of the clustering solution followed by manual validation. When the spatiotemporal waveforms of spikes from different cells overlap, the decision as to whether two spikes should be assigned to the same source can be quite subjective, if it is not based on reliable quantitative measures. We propose a new approach, whereby spike clusters are identified from the most consensual partition across an ensemble of clustering solutions. Using the variability of the clustering solutions across successive iterations of the same clustering algorithm (template matching based on K-means clusters), we estimate the probability of spikes being clustered together and identify groups of spikes that are not statistically distinguishable from one another. Thus, we identify spikes that are most likely to be clustered together and therefore correspond to consistent spike clusters. This method has the potential advantage that it does not rely on any model of the spike shapes. It also provides estimates of the proportion of misclassified spikes for each of the identified clusters. We tested our algorithm on several datasets for which there exists a ground truth (simultaneous intracellular data), and show that it performs close to the optimum reached by a support vector machine trained on the ground truth. We also show that the estimated rate of misclassification matches the proportion of misclassified spikes measured from the ground truth data.

The Effects of Context and Attention on Spiking Activity in Human Early Visual Cortex.

PubMed

Self, Matthew W; Peters, Judith C; Possel, Jessy K; Reithler, Joel; Goebel, Rainer; Ris, Peterjan; Jeurissen, Danique; Reddy, Leila; Claus, Steven; Baayen, Johannes C; Roelfsema, Pieter R

2016-03-01

Here we report the first quantitative analysis of spiking activity in human early visual cortex. We recorded multi-unit activity from two electrodes in area V2/V3 of a human patient implanted with depth electrodes as part of her treatment for epilepsy. We observed well-localized multi-unit receptive fields with tunings for contrast, orientation, spatial frequency, and size, similar to those reported in the macaque. We also observed pronounced gamma oscillations in the local-field potential that could be used to estimate the underlying spiking response properties. Spiking responses were modulated by visual context and attention. We observed orientation-tuned surround suppression: responses were suppressed by image regions with a uniform orientation and enhanced by orientation contrast. Additionally, responses were enhanced on regions that perceptually segregated from the background, indicating that neurons in the human visual cortex are sensitive to figure-ground structure. Spiking responses were also modulated by object-based attention. When the patient mentally traced a curve through the neurons' receptive fields, the accompanying shift of attention enhanced neuronal activity. These results demonstrate that the tuning properties of cells in the human early visual cortex are similar to those in the macaque and that responses can be modulated by both contextual factors and behavioral relevance. Our results, therefore, imply that the macaque visual system is an excellent model for the human visual cortex.

The Effects of Context and Attention on Spiking Activity in Human Early Visual Cortex

PubMed Central

Reithler, Joel; Goebel, Rainer; Ris, Peterjan; Jeurissen, Danique; Reddy, Leila; Claus, Steven; Baayen, Johannes C.; Roelfsema, Pieter R.

2016-01-01

Here we report the first quantitative analysis of spiking activity in human early visual cortex. We recorded multi-unit activity from two electrodes in area V2/V3 of a human patient implanted with depth electrodes as part of her treatment for epilepsy. We observed well-localized multi-unit receptive fields with tunings for contrast, orientation, spatial frequency, and size, similar to those reported in the macaque. We also observed pronounced gamma oscillations in the local-field potential that could be used to estimate the underlying spiking response properties. Spiking responses were modulated by visual context and attention. We observed orientation-tuned surround suppression: responses were suppressed by image regions with a uniform orientation and enhanced by orientation contrast. Additionally, responses were enhanced on regions that perceptually segregated from the background, indicating that neurons in the human visual cortex are sensitive to figure-ground structure. Spiking responses were also modulated by object-based attention. When the patient mentally traced a curve through the neurons’ receptive fields, the accompanying shift of attention enhanced neuronal activity. These results demonstrate that the tuning properties of cells in the human early visual cortex are similar to those in the macaque and that responses can be modulated by both contextual factors and behavioral relevance. Our results, therefore, imply that the macaque visual system is an excellent model for the human visual cortex. PMID:27015604

ION SOURCE

DOEpatents

Brobeck, W.M.

1959-04-14

This patent deals with calutrons and more particularly to an arrangement therein whereby charged bottles in a calutron source unit may be replaced without admitting atmospheric air to the calutron vacuum chamber. As described, an ion unit is disposed within a vacuum tank and has a reservoir open toward a wall of the tank. A spike projects from thc source into the reservoir. When a charge bottle is placed in the reservoir, the spike breaks a frangible seal on the bottle. After the contents of the bottle are expended the bottle may be withdrawn and replaced with another charge bottle by a varuum lock arrangement in conjunction with an arm for manipulating the bottle.

Ion source

DOEpatents

Brobeck, W. M.

1959-04-14

This patent deals with calutrons and more particularly to an arrangement therein whereby charged bottles in a calutron source unit may be replaced without admitting atmospheric air to the calutron vacuum chamber. As described, an ion unit is disposed within a vacuum tank and has a reservoir open toward a wall of the tank. A spike projects from the source into the reservoir. When a charge bottle is placed in the reservoir, the spike breaks a frangible seal on the bottle. After the contents of the bottle are expended the bottle may be withdrawn and replaced with another charge bottle by a vacuum lock arrangement in conjunction with an arm for manipulating the bottle.

Development of on-off spiking in superior paraolivary nucleus neurons of the mouse

PubMed Central

Felix, Richard A.; Vonderschen, Katrin; Berrebi, Albert S.

2013-01-01

The superior paraolivary nucleus (SPON) is a prominent cell group in the auditory brain stem that has been increasingly implicated in representing temporal sound structure. Although SPON neurons selectively respond to acoustic signals important for sound periodicity, the underlying physiological specializations enabling these responses are poorly understood. We used in vitro and in vivo recordings to investigate how SPON neurons develop intrinsic cellular properties that make them well suited for encoding temporal sound features. In addition to their hallmark rebound spiking at the stimulus offset, SPON neurons were characterized by spiking patterns termed onset, adapting, and burst in response to depolarizing stimuli in vitro. Cells with burst spiking had some morphological differences compared with other SPON neurons and were localized to the dorsolateral region of the nucleus. Both membrane and spiking properties underwent strong developmental regulation, becoming more temporally precise with age for both onset and offset spiking. Single-unit recordings obtained in young mice demonstrated that SPON neurons respond with temporally precise onset spiking upon tone stimulation in vivo, in addition to the typical offset spiking. Taken together, the results of the present study demonstrate that SPON neurons develop sharp on-off spiking, which may confer sensitivity to sound amplitude modulations or abrupt sound transients. These findings are consistent with the proposed involvement of the SPON in the processing of temporal sound structure, relevant for encoding communication cues. PMID:23515791

A new approach to spike sorting for multi-neuronal activities recorded with a tetrode--how ICA can be practical.

PubMed

Takahashi, Susumu; Anzai, Yuichiro; Sakurai, Yoshio

2003-07-01

Multi-neuronal recording with a tetrode is a powerful technique to reveal neuronal interactions in local circuits. However, it is difficult to detect precise spike timings among closely neighboring neurons because the spike waveforms of individual neurons overlap on the electrode when more than two neurons fire simultaneously. In addition, the spike waveforms of single neurons, especially in the presence of complex spikes, are often non-stationary. These problems limit the ability of ordinary spike sorting to sort multi-neuronal activities recorded using tetrodes into their single-neuron components. Though sorting with independent component analysis (ICA) can solve these problems, it has one serious limitation that the number of separated neurons must be less than the number of electrodes. Using a combination of ICA and the efficiency of ordinary spike sorting technique (k-means clustering), we developed an automatic procedure to solve the spike-overlapping and the non-stationarity problems with no limitation on the number of separated neurons. The results for the procedure applied to real multi-neuronal data demonstrated that some outliers which may be assigned to distinct clusters if ordinary spike-sorting methods were used can be identified as overlapping spikes, and that there are functional connections between a putative pyramidal neuron and its putative dendrite. These findings suggest that the combination of ICA and k-means clustering can provide insights into the precise nature of functional circuits among neurons, i.e. cell assemblies.

Multiscale decoding for reliable brain-machine interface performance over time.

PubMed

Han-Lin Hsieh; Wong, Yan T; Pesaran, Bijan; Shanechi, Maryam M

2017-07-01

Recordings from invasive implants can degrade over time, resulting in a loss of spiking activity for some electrodes. For brain-machine interfaces (BMI), such a signal degradation lowers control performance. Achieving reliable performance over time is critical for BMI clinical viability. One approach to improve BMI longevity is to simultaneously use spikes and other recording modalities such as local field potentials (LFP), which are more robust to signal degradation over time. We have developed a multiscale decoder that can simultaneously model the different statistical profiles of multi-scale spike/LFP activity (discrete spikes vs. continuous LFP). This decoder can also run at multiple time-scales (millisecond for spikes vs. tens of milliseconds for LFP). Here, we validate the multiscale decoder for estimating the movement of 7 major upper-arm joint angles in a non-human primate (NHP) during a 3D reach-to-grasp task. The multiscale decoder uses motor cortical spike/LFP recordings as its input. We show that the multiscale decoder can improve decoding accuracy by adding information from LFP to spikes, while running at the fast millisecond time-scale of the spiking activity. Moreover, this improvement is achieved using relatively few LFP channels, demonstrating the robustness of the approach. These results suggest that using multiscale decoders has the potential to improve the reliability and longevity of BMIs.

Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.

PubMed

Albers, Christian; Westkott, Maren; Pawelzik, Klaus

2016-01-01

Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns.

Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity

PubMed Central

Albers, Christian; Westkott, Maren; Pawelzik, Klaus

2016-01-01

Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns. PMID:26900845

Non-linear amplification of graded voltage signals in the first-order visual interneurons of the butterfly Papilio xuthus.

PubMed

Rusanen, Juha; Frolov, Roman; Weckström, Matti; Kinoshita, Michiyo; Arikawa, Kentaro

2018-04-30

Lamina monopolar cells (LMCs) are the first-order visual interneurons of insects and crustacea, primarily involved in achromatic vision. Here we investigated morphological and electrophysiological properties of LMCs in the butterfly Papilio xuthus Using intracellular recording coupled with dye injection, we found two types of LMCs. Cells with roundish terminals near the distal surface of the medulla demonstrating no or small depolarizing spikes were classified as L1/2. LMCs with elongated terminals deep in the medulla that showed prominent spiking were classified as L3/4. The majority of LMCs of both types had broad spectral sensitivities, peaking between 480 and 570 nm. Depending on the experimental conditions, spikes varied from small to action potential-like events, with their amplitudes and rates decreasing as stimulus brightness increased. When the eye was stimulated with naturalistic contrast-modulated time series, spikes were reliably triggered by high-contrast components of the stimulus. Spike-triggered average functions showed that spikes emphasize rapid membrane depolarizations. Our results suggest that spikes are mediated by voltage-activated Na + channels, which are mainly inactivated at rest. Strong local minima in the coherence functions of spiking LMCs indicate that the depolarizing conductance contributes to the amplification of graded responses even when detectable spikes are not evoked. We propose that the information transfer strategies of spiking LMCs change with light intensity. In dim light, both graded voltage signals and large spikes are used together without mutual interference, due to separate transmission bandwidths. In bright light, signals are non-linearly amplified by the depolarizing conductance in the absence of detectable spikes. © 2018. Published by The Company of Biologists Ltd.

Electrophysiology of connection current spikes.

PubMed

Fish, Raymond M; Geddes, Leslie A

2008-12-01

Connection to a 60-Hz or other voltage source can result in cardiac dysrhythmias, a startle reaction, muscle contractions, and a variety of other physiological responses. Such responses can lead to injury, especially if significant ventricular cardiac dysrhythmias occur, or if a person is working at some height above ground and falls as a result of a musculoskeletal response. Physiological reactions are known to relate to intensity and duration of current exposure. The connection current that flows is a function of the applied voltage at the instant of connection, and the electrical impedance encountered by the voltage source in contact with the skin or other body tissues. In this article we describe a rarely investigated phenomenon, namely a contact, or connection, current spike that is many times higher than the steady-state current. This current spike occurs when an electrical connection is made at a non-zero voltage time in a sine wave or other waveform. Such current spikes may occur when electronic or manual switching or connecting of conductors occurs in electronic instrumentation connected to a patient. These findings are relevant to medical devices and instrumentation and to electrical safety in general.

Mapping cortical mesoscopic networks of single spiking cortical or sub-cortical neurons

PubMed Central

Xiao, Dongsheng; Vanni, Matthieu P; Mitelut, Catalin C; Chan, Allen W; LeDue, Jeffrey M; Xie, Yicheng; Chen, Andrew CN; Swindale, Nicholas V; Murphy, Timothy H

2017-01-01

Understanding the basis of brain function requires knowledge of cortical operations over wide-spatial scales, but also within the context of single neurons. In vivo, wide-field GCaMP imaging and sub-cortical/cortical cellular electrophysiology were used in mice to investigate relationships between spontaneous single neuron spiking and mesoscopic cortical activity. We make use of a rich set of cortical activity motifs that are present in spontaneous activity in anesthetized and awake animals. A mesoscale spike-triggered averaging procedure allowed the identification of motifs that are preferentially linked to individual spiking neurons by employing genetically targeted indicators of neuronal activity. Thalamic neurons predicted and reported specific cycles of wide-scale cortical inhibition/excitation. In contrast, spike-triggered maps derived from single cortical neurons yielded spatio-temporal maps expected for regional cortical consensus function. This approach can define network relationships between any point source of neuronal spiking and mesoscale cortical maps. DOI: http://dx.doi.org/10.7554/eLife.19976.001 PMID:28160463

Spiking Models for Level-Invariant Encoding

PubMed Central

Brette, Romain

2012-01-01

Levels of ecological sounds vary over several orders of magnitude, but the firing rate and membrane potential of a neuron are much more limited in range. In binaural neurons of the barn owl, tuning to interaural delays is independent of level differences. Yet a monaural neuron with a fixed threshold should fire earlier in response to louder sounds, which would disrupt the tuning of these neurons. How could spike timing be independent of input level? Here I derive theoretical conditions for a spiking model to be insensitive to input level. The key property is a dynamic change in spike threshold. I then show how level invariance can be physiologically implemented, with specific ionic channel properties. It appears that these ingredients are indeed present in monaural neurons of the sound localization pathway of birds and mammals. PMID:22291634

Learning to Select Actions with Spiking Neurons in the Basal Ganglia

PubMed Central

Stewart, Terrence C.; Bekolay, Trevor; Eliasmith, Chris

2012-01-01

We expand our existing spiking neuron model of decision making in the cortex and basal ganglia to include local learning on the synaptic connections between the cortex and striatum, modulated by a dopaminergic reward signal. We then compare this model to animal data in the bandit task, which is used to test rodent learning in conditions involving forced choice under rewards. Our results indicate a good match in terms of both behavioral learning results and spike patterns in the ventral striatum. The model successfully generalizes to learning the utilities of multiple actions, and can learn to choose different actions in different states. The purpose of our model is to provide both high-level behavioral predictions and low-level spike timing predictions while respecting known neurophysiology and neuroanatomy. PMID:22319465

Research and development of a field-ready protocol for sampling of phosgene from stationary source emissions: Diethylamine reagent studies. Research report, 11 July 1995--30 September 1996

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

Steger, J.L.; Bursey, J.T.; Merrill, R.G.

1999-03-01

This report presents the results of laboratory studies to develop and evaluate a method for the sampling and analysis of phosgene from stationary sources of air emissions using diethylamine (DEA) in toluene as the collection media. The method extracts stack gas from emission sources and stabilizes the reactive gas for subsequent analysis. DEA was evaluated both in a benchtop study and in a laboratory train spiking study. This report includes results for both the benchtop study and the train spiking study. Benchtop studies to evaluate the suitability of DEA for collecting and analyzing phosgene investigated five variables: storage time, DEAmore » concentration, moisture/pH, phosgene concentration, and sample storage temperature. Prototype sampling train studies were performed to determine if the benchtop chemical studies were transferable to a Modified Method 5 sampling train collecting phosgene in the presence of clean air mixed with typical stack gas components. Four conditions, which varied the moisture and phosgene spike were evaluated in triplicate. In addition to research results, the report includes a detailed draft method for sampling and analysis of phosgene from stationary source emissions.« less

Sensory Coding by Cerebellar Mossy Fibres through Inhibition-Driven Phase Resetting and Synchronisation

PubMed Central

Holtzman, Tahl; Jörntell, Henrik

2011-01-01

Temporal coding of spike-times using oscillatory mechanisms allied to spike-time dependent plasticity could represent a powerful mechanism for neuronal communication. However, it is unclear how temporal coding is constructed at the single neuronal level. Here we investigate a novel class of highly regular, metronome-like neurones in the rat brainstem which form a major source of cerebellar afferents. Stimulation of sensory inputs evoked brief periods of inhibition that interrupted the regular firing of these cells leading to phase-shifted spike-time advancements and delays. Alongside phase-shifting, metronome cells also behaved as band-pass filters during rhythmic sensory stimulation, with maximal spike-stimulus synchronisation at frequencies close to the idiosyncratic firing frequency of each neurone. Phase-shifting and band-pass filtering serve to temporally align ensembles of metronome cells, leading to sustained volleys of near-coincident spike-times, thereby transmitting synchronised sensory information to downstream targets in the cerebellar cortex. PMID:22046297

Electrical source localization by LORETA in patients with epilepsy: Confirmation by postoperative MRI

PubMed Central

Akdeniz, Gülsüm

2016-01-01

Background: Few studies have been conducted that have compared electrical source localization (ESL) results obtained by analyzing ictal patterns in scalp electroencephalogram (EEG) with the brain areas that are found to be responsible for seizures using other brain imaging techniques. Additionally, adequate studies have not been performed to confirm the accuracy of ESL methods. Materials and Methods: In this study, ESL was conducted using LORETA (Low Resolution Brain Electromagnetic Tomography) in 9 patients with lesions apparent on magnetic resonance imaging (MRI) and in 6 patients who did not exhibit lesions on their MRIs. EEGs of patients who underwent surgery for epilepsy and had follow-ups for at least 1 year after operations were analyzed for ictal spike, rhythmic, paroxysmal fast, and obscured EEG activities. Epileptogenic zones identified in postoperative MRIs were then compared with localizations obtained by LORETA model we employed. Results: We found that brain areas determined via ESL were in concordance with resected brain areas for 13 of the 15 patients evaluated, and those 13 patients were post-operatively determined as being seizure-free. Conclusion: ESL, which is a noninvasive technique, may contribute to the correct delineation of epileptogenic zones in patients who will eventually undergo surgery to treat epilepsy, (regardless of neuroimaging status). Moreover, ESL may aid in deciding on the number and localization of intracranial electrodes to be used in patients who are candidates for invasive recording. PMID:27011626

Electrical source localization by LORETA in patients with epilepsy: Confirmation by postoperative MRI.

PubMed

Akdeniz, Gülsüm

2016-01-01

Few studies have been conducted that have compared electrical source localization (ESL) results obtained by analyzing ictal patterns in scalp electroencephalogram (EEG) with the brain areas that are found to be responsible for seizures using other brain imaging techniques. Additionally, adequate studies have not been performed to confirm the accuracy of ESL methods. In this study, ESL was conducted using LORETA (Low Resolution Brain Electromagnetic Tomography) in 9 patients with lesions apparent on magnetic resonance imaging (MRI) and in 6 patients who did not exhibit lesions on their MRIs. EEGs of patients who underwent surgery for epilepsy and had follow-ups for at least 1 year after operations were analyzed for ictal spike, rhythmic, paroxysmal fast, and obscured EEG activities. Epileptogenic zones identified in postoperative MRIs were then compared with localizations obtained by LORETA model we employed. We found that brain areas determined via ESL were in concordance with resected brain areas for 13 of the 15 patients evaluated, and those 13 patients were post-operatively determined as being seizure-free. ESL, which is a noninvasive technique, may contribute to the correct delineation of epileptogenic zones in patients who will eventually undergo surgery to treat epilepsy, (regardless of neuroimaging status). Moreover, ESL may aid in deciding on the number and localization of intracranial electrodes to be used in patients who are candidates for invasive recording.

Inferring oscillatory modulation in neural spike trains

PubMed Central

Arai, Kensuke; Kass, Robert E.

2017-01-01

Oscillations are observed at various frequency bands in continuous-valued neural recordings like the electroencephalogram (EEG) and local field potential (LFP) in bulk brain matter, and analysis of spike-field coherence reveals that spiking of single neurons often occurs at certain phases of the global oscillation. Oscillatory modulation has been examined in relation to continuous-valued oscillatory signals, and independently from the spike train alone, but behavior or stimulus triggered firing-rate modulation, spiking sparseness, presence of slow modulation not locked to stimuli and irregular oscillations with large variability in oscillatory periods, present challenges to searching for temporal structures present in the spike train. In order to study oscillatory modulation in real data collected under a variety of experimental conditions, we describe a flexible point-process framework we call the Latent Oscillatory Spike Train (LOST) model to decompose the instantaneous firing rate in biologically and behaviorally relevant factors: spiking refractoriness, event-locked firing rate non-stationarity, and trial-to-trial variability accounted for by baseline offset and a stochastic oscillatory modulation. We also extend the LOST model to accommodate changes in the modulatory structure over the duration of the experiment, and thereby discover trial-to-trial variability in the spike-field coherence of a rat primary motor cortical neuron to the LFP theta rhythm. Because LOST incorporates a latent stochastic auto-regressive term, LOST is able to detect oscillations when the firing rate is low, the modulation is weak, and when the modulating oscillation has a broad spectral peak. PMID:28985231

A point process approach to identifying and tracking transitions in neural spiking dynamics in the subthalamic nucleus of Parkinson's patients

NASA Astrophysics Data System (ADS)

Deng, Xinyi; Eskandar, Emad N.; Eden, Uri T.

2013-12-01

Understanding the role of rhythmic dynamics in normal and diseased brain function is an important area of research in neural electrophysiology. Identifying and tracking changes in rhythms associated with spike trains present an additional challenge, because standard approaches for continuous-valued neural recordings—such as local field potential, magnetoencephalography, and electroencephalography data—require assumptions that do not typically hold for point process data. Additionally, subtle changes in the history dependent structure of a spike train have been shown to lead to robust changes in rhythmic firing patterns. Here, we propose a point process modeling framework to characterize the rhythmic spiking dynamics in spike trains, test for statistically significant changes to those dynamics, and track the temporal evolution of such changes. We first construct a two-state point process model incorporating spiking history and develop a likelihood ratio test to detect changes in the firing structure. We then apply adaptive state-space filters and smoothers to track these changes through time. We illustrate our approach with a simulation study as well as with experimental data recorded in the subthalamic nucleus of Parkinson's patients performing an arm movement task. Our analyses show that during the arm movement task, neurons underwent a complex pattern of modulation of spiking intensity characterized initially by a release of inhibitory control at 20-40 ms after a spike, followed by a decrease in excitatory influence at 40-60 ms after a spike.

Reactivity of rolandic spikes.

PubMed

Fonseca, L C; Tedrus, G M; Bastos, A; Bosco, A; Laloni, D T

1996-07-01

Factors influencing the frequency of rolandic spikes are rarely reported. We examined the influence of movement, tactile stimulation and cognitive test on the discharge rate of rolandic spikes. We studied 35 children with EEG rolandic spikes. Eighteen children had nonfebrile convulsions. Benign childhood epilepsy with centrotemporal spikes was diagnosed in 12 cases. Testing during the EEG included hand and tongue movements, cognitive tasks and tactile stimulation of face and hands. Rolandic spikes were counted by visual analysis in each phase of the test and the frequency expressed as mean number per min. During tongue movements there was a significantly lower discharge rate when compared to previous and subsequent rest phases. For the left hemisphere there was reduction in discharge rate during right hand movements and looking at colored spots but only when compared with the previous rest phase. The reduction in mean number of spikes/min by tongue movements occurred in patients with and without epilepsy. For patients with cerebral lesion the decrease in discharge rate during tongue movements was not significant whereas for those without cerebral lesion a significant reduction was evident. A decrease in the mean number of spikes/min of 50% or more was significantly more frequent among 29 patients without than among 6 patients with cerebral lesion. Our study showed the inhibition of rolandic spikes by tongue movements confirming the hypothesis that the localization of discharges is an important factor in determining its reactivity. The presence or not of cerebral lesion may be an important factor in the degree of reactivity.

[Multi-channel in vivo recording techniques: signal processing of action potentials and local field potentials].

PubMed

Xu, Jia-Min; Wang, Ce-Qun; Lin, Long-Nian

2014-06-25

Multi-channel in vivo recording techniques are used to record ensemble neuronal activity and local field potentials (LFP) simultaneously. One of the key points for the technique is how to process these two sets of recorded neural signals properly so that data accuracy can be assured. We intend to introduce data processing approaches for action potentials and LFP based on the original data collected through multi-channel recording system. Action potential signals are high-frequency signals, hence high sampling rate of 40 kHz is normally chosen for recording. Based on waveforms of extracellularly recorded action potentials, tetrode technology combining principal component analysis can be used to discriminate neuronal spiking signals from differently spatially distributed neurons, in order to obtain accurate single neuron spiking activity. LFPs are low-frequency signals (lower than 300 Hz), hence the sampling rate of 1 kHz is used for LFPs. Digital filtering is required for LFP analysis to isolate different frequency oscillations including theta oscillation (4-12 Hz), which is dominant in active exploration and rapid-eye-movement (REM) sleep, gamma oscillation (30-80 Hz), which is accompanied by theta oscillation during cognitive processing, and high frequency ripple oscillation (100-250 Hz) in awake immobility and slow wave sleep (SWS) state in rodent hippocampus. For the obtained signals, common data post-processing methods include inter-spike interval analysis, spike auto-correlation analysis, spike cross-correlation analysis, power spectral density analysis, and spectrogram analysis.

Spikes, Local Field Potentials, and Electrocorticogram Characterization during Motor Learning in Rats for Brain Machine Interface Tasks.

PubMed

Marzullo, T C; Dudley, J R; Miller, C R; Trejo, L; Kipke, D R

2005-01-01

Brain machine interface development typically falls into two arenas, invasive extracellular recording and non-invasive electroencephalogram recording methods. The relationship between action potentials and field potentials is not well understood, and investigation of interrelationships may improve design of neuroprosthetic control systems. Rats were trained on a motor learning task whereby they had to insert their noses into an aperture while simultaneously pressing down on levers with their forepaws; spikes, local field potentials (LFPs), and electrocorticograms (ECoGs) over the motor cortex were recorded and characterized. Preliminary results suggest that the LFP activity in lower cortical layers oscillates with the ECoG.

Targeted Nanoparticle Thermometry: A Method to Measure Local Temperature at the Nanoscale Point Where Water Vapor Nucleation Occurs.

PubMed

Alaulamie, Arwa A; Baral, Susil; Johnson, Samuel C; Richardson, Hugh H

2017-01-01

An optical nanothermometer technique based on laser trapping, moving and targeted attaching an erbium oxide nanoparticle cluster is developed to measure the local temperature. The authors apply this new nanoscale temperature measuring technique (limited by the size of the nanoparticles) to measure the temperature of vapor nucleation in water. Vapor nucleation is observed after superheating water above the boiling point for degassed and nondegassed water. The average nucleation temperature for water without gas is 560 K but this temperature is lowered by 100 K when gas is introduced into the water. The authors are able to measure the temperature inside the bubble during bubble formation and find that the temperature inside the bubble spikes to over 1000 K because the heat source (optically-heated nanorods) is no longer connected to liquid water and heat dissipation is greatly reduced. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Low Background Levels of Mars Methane at Gale Crater Indicate Seasonal Cycle: Updated Results from TLS-SAM on Curiosity

NASA Astrophysics Data System (ADS)

Webster, C. R.; Mahaffy, P. R.; Atreya, S. K.

2016-12-01

In situ measurements of atmospheric methane have been made over a 3-year period at Gale Crater on Mars using the Tunable Laser Spectrometer (TLS) instrument in the Sample Analysis at Mars (SAM) suite on the Curiosity rover. We have reported two important observations: (i) a background level of 0.5 ppbv that is about five times lower than some model predictions based on generation from UV degradation of micro-meteorites or interplanetary dust delivered to the martian surface; (ii) a "spike" of elevated levels of 7 ppbv that were seen1 on four sequential observations over a 2-month period before dropping to background levels. This spike was attributed to an episodic release from a small local source, probably to the north of Gale crater. While the elevated levels of the spike did not return (repeat) one Mars year later, we have seen what appears to be a seasonal variation to the background levels that are all < 1ppbv. The variation ranges from a low of 0.2 ppbv in the northern hemisphere spring to 0.9 ppbv in the northern hemisphere late summer, a change in mixing ratio over a range larger than expected from our current understanding of methane sources and sinks. We will present recent atmospheric methane measurements, and their correlations with a variety of environmental conditions at the location of Curiosity, and discuss the mechanisms that are believed to be contributing to the low background methane signals and their variation. 1 "Mars Methane Detection and Variability at Gale Crater", C. R. Webster et al., Science, 347, 415-417 (2015) and references therein. The research described here was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA).

Calcium-Activated Potassium Channels at Nodes of Ranvier Secure Axonal Spike Propagation

PubMed Central

Gründemann, Jan; Clark, Beverley A.

2015-01-01

Summary Functional connectivity between brain regions relies on long-range signaling by myelinated axons. This is secured by saltatory action potential propagation that depends fundamentally on sodium channel availability at nodes of Ranvier. Although various potassium channel types have been anatomically localized to myelinated axons in the brain, direct evidence for their functional recruitment in maintaining node excitability is scarce. Cerebellar Purkinje cells provide continuous input to their targets in the cerebellar nuclei, reliably transmitting axonal spikes over a wide range of rates, requiring a constantly available pool of nodal sodium channels. We show that the recruitment of calcium-activated potassium channels (IK, KCa3.1) by local, activity-dependent calcium (Ca2+) influx at nodes of Ranvier via a T-type voltage-gated Ca2+ current provides a powerful mechanism that likely opposes depolarizing block at the nodes and is thus pivotal to securing continuous axonal spike propagation in spontaneously firing Purkinje cells. PMID:26344775

Recording temporal lobe epileptic activity with MEG in a light-weight magnetic shield.

PubMed

Carrette, Evelien; Op de Beeck, Marc; Bourguignon, Mathieu; Boon, Paul; Vonck, Kristl; Legros, Benjamin; Goldman, Serge; Van Bogaert, Patrick; De Tiège, Xavier

2011-06-01

To assess the interictal epileptic discharges (IEDs) detection rate of magnetoencephalography (MEG) recordings performed in a new light-weight magnetic shielding (LMSR) concept in a large group of consecutive patients with presumed mesiotemporal lobe epilepsy (MTLE). Thirty-eight patients (23 women; age range: 6-63 years) with presumed MTLE were prospectively studied. MEG investigations were performed with the 306-channel Elekta Neuromag® MEG-system installed in a normal hospital environment into a LMSR (MaxShield, Elekta Oy). Equivalent current dipoles (ECD, g/% > 80%) corresponding to epileptic events were fitted to each patient's spherical head model at IEDs onset and peak and then superimposed on the patient's co-registered MRI. IEDs were observed in 26 out of 38 patients (68.4%). Temporal ECDs were mesial in 14 patients, anterior in 23 patients and posterior in 8 patients. Interestingly, in 6 patients, ECDs fitted at spike-onset were localized in the hippocampus while at the peak of the spike, they had an anterior temporal location. MEG using LMSR provides adequate signal to noise ratio (SNR) to allow reliable detection and localization of single epileptic abnormalities on continuous MEG data in 68% of patients with presumed MTLE. Moreover, mesial temporal epileptic sources were detected in 54% of patients with abnormal MEG. The SNR of MEG data acquired using the LMSR is therefore suitable for the non-invasive localization of epileptic foci in patients with MTLE. The use of LMSR, which are cheaper and smaller than conventional MSR, should facilitate the development of MEG in clinical environments. Copyright © 2011 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Basic data features and results from a spatially dense seismic array on the San Jacinto fault zone

NASA Astrophysics Data System (ADS)

Ben-Zion, Yehuda; Vernon, Frank L.; Ozakin, Yaman; Zigone, Dimitri; Ross, Zachary E.; Meng, Haoran; White, Malcolm; Reyes, Juan; Hollis, Dan; Barklage, Mitchell

2015-07-01

We discuss several outstanding aspects of seismograms recorded during >4 weeks by a spatially dense Nodal array, straddling the damage zone of the San Jacinto fault in southern California, and some example results. The waveforms contain numerous spikes and bursts of high-frequency waves (up to the recorded 200 Hz) produced in part by minute failure events in the shallow crust. The high spatial density of the array facilitates the detection of 120 small local earthquakes in a single day, most of which not detected by the surrounding ANZA and regional southern California networks. Beamforming results identify likely ongoing cultural noise sources dominant in the frequency range 1-10 Hz and likely ongoing earthquake sources dominant in the frequency range 20-40 Hz. Matched-field processing and back-projection of seismograms provide alternate event location. The median noise levels during the experiment at different stations, waves generated by Betsy gunshots, and wavefields from nearby earthquakes point consistently to several structural units across the fault. Seismic trapping structure and local sedimentary basin produce localized motion amplification and stronger attenuation than adjacent regions. Cross correlations of high-frequency noise recorded at closely spaced stations provide a structural image of the subsurface material across the fault zone. The high spatial density and broad frequency range of the data can be used for additional high resolution studies of structure and source properties in the shallow crust.

Fine structure of microwave spike bursts and associated cross-field energy transport

NASA Technical Reports Server (NTRS)

Winglee, R. M.; Dulk, G. A.; Pritchett, P. L.

1988-01-01

The characteristics of the maser emission from a driven system where energetic electrons continue to flow through the source region is investigated using electronic particle simulations. It is shown that, under appropriate conditions, the maser can efficiently radiate a significant portion of the energy of the fast electrons in a very short time. The radiation is emitted in pulses even though the flow of electrons through the system is at a constant rate. The mission of these pulses is proposed as the source of the fine structure. Under other conditions the dominant maser emission changes from fundamental x-mode to either fundamental z-mode or to electrostatic upper hybrid or Bernstein modes. The bulk of the emission from the maser instability cannot propagate across field lines in this regime, and hence strong local plasma heating is expected, with little energy transport across the magnetic field lines.

Dracaena marginata biofilter: design of growth substrate and treatment of stormwater runoff.

PubMed

Vijayaraghavan, K; Praveen, R S

2016-01-01

The purpose of this research was to investigate the efficiency of Dracaena marginata planted biofilters to decontaminate urban runoff. A new biofilter growth substrate was prepared using low-cost and locally available materials such as red soil, fine sand, perlite, vermiculite, coco-peat and Sargassum biomass. The performance of biofilter substrate was compared with local garden soil based on physical and water quality parameters. Preliminary analyses indicated that biofilter substrate exhibited desirable characteristics such as low bulk density (1140 kg/m(3)), high water holding capacity (59.6%), air-filled porosity (7.82%) and hydraulic conductivity (965 mm/h). Four different biofilter assemblies, with vegetated and non-vegetated systems, were examined for several artificial rain events (un-spiked and metal-spiked). Results from un-spiked artificial rain events suggested that concentrations of most of the chemical components in effluent were highest at the beginning of rain events and thereafter subsided during the subsequent rain events. Biofilter growth substrate showed superior potential over garden soil to retain metal ions such as Al, Fe, Cu, Cr, Ni, Zn, Cd and Pb during metal-spiked rain events. Significant differences were also observed between non-vegetated and vegetated biofilter assemblies in runoff quality, with the latter producing better results.

Percent recoveries of anthropogenic organic compounds with and without the addition of ascorbic acid to preserve finished-water samples containing free chlorine, 2004-10

USGS Publications Warehouse

Valder, Joshua F.; Delzer, Gregory C.; Bender, David A.; Price, Curtis V.

2011-01-01

This report presents finished-water matrix-spike recoveries of 270 anthropogenic organic compounds with and without the addition of ascorbic acid to preserve water samples containing free chlorine. Percent recoveries were calculated using analytical results from a study conducted during 2004-10 for the National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey (USGS). The study was intended to characterize the effect of quenching on finished-water matrix-spike recoveries and to better understand the potential oxidation and transformation of 270 anthropogenic organic compounds. The anthropogenic organic compounds studied include those on analytical schedules 1433, 2003, 2033, 2060, 2020, and 4024 of the USGS National Water Quality Laboratory. Three types of samples were collected from 34 NAWQA locations across the Nation: (1) quenched finished-water samples (not spiked), (2) quenched finished-water matrix-spike samples, and (3) nonquenched finished-water matrix-spike samples. Percent recoveries of anthropogenic organic compounds in quenched and nonquenched finished-water matrix-spike samples are presented. Comparisons of percent recoveries between quenched and nonquenched spiked samples can be used to show how quenching affects finished-water samples. A maximum of 18 surface-water and 34 groundwater quenched finished-water matrix-spike samples paired with nonquenched finished-water matrix-spike samples were analyzed. Percent recoveries for the study are presented in two ways: (1) finished-water matrix-spike samples supplied by surface-water or groundwater, and (2) by use (or source) group category for surface-water and groundwater supplies. Graphical representations of percent recoveries for the quenched and nonquenched finished-water matrix-spike samples also are presented.

Millimeter-scale epileptiform spike propagation patterns and their relationship to seizures

NASA Astrophysics Data System (ADS)

Vanleer, Ann C.; Blanco, Justin A.; Wagenaar, Joost B.; Viventi, Jonathan; Contreras, Diego; Litt, Brian

2016-04-01

Objective. Current mapping of epileptic networks in patients prior to epilepsy surgery utilizes electrode arrays with sparse spatial sampling (∼1.0 cm inter-electrode spacing). Recent research demonstrates that sub-millimeter, cortical-column-scale domains have a role in seizure generation that may be clinically significant. We use high-resolution, active, flexible surface electrode arrays with 500 μm inter-electrode spacing to explore epileptiform local field potential (LFP) spike propagation patterns in two dimensions recorded from subdural micro-electrocorticographic signals in vivo in cat. In this study, we aimed to develop methods to quantitatively characterize the spatiotemporal dynamics of epileptiform activity at high-resolution. Approach. We topically administered a GABA-antagonist, picrotoxin, to induce acute neocortical epileptiform activity leading up to discrete electrographic seizures. We extracted features from LFP spikes to characterize spatiotemporal patterns in these events. We then tested the hypothesis that two-dimensional spike patterns during seizures were different from those between seizures. Main results. We showed that spatially correlated events can be used to distinguish ictal versus interictal spikes. Significance. We conclude that sub-millimeter-scale spatiotemporal spike patterns reveal network dynamics that are invisible to standard clinical recordings and contain information related to seizure-state.

Spike Code Flow in Cultured Neuronal Networks.

PubMed

Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime; Kamimura, Takuya; Yagi, Yasushi; Mizuno-Matsumoto, Yuko; Chen, Yen-Wei

2016-01-01

We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of "1101" and "1011," which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the "maximum cross-correlations" among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.

Bifurcation and Spike Adding Transition in Chay-Keizer Model

NASA Astrophysics Data System (ADS)

Lu, Bo; Liu, Shenquan; Liu, Xuanliang; Jiang, Xiaofang; Wang, Xiaohui

Electrical bursting is an activity which is universal in excitable cells such as neurons and various endocrine cells, and it encodes rich physiological information. As burst delay identifies that the signal integration has reached the threshold at which it can generate an action potential, the number of spikes in a burst may have essential physiological implications, and the transition of bursting in excitable cells is associated with the bifurcation phenomenon closely. In this paper, we focus on the transition of the spike count per burst of the pancreatic β-cells within a mathematical model and bifurcation phenomenon in the Chay-Keizer model, which is utilized to simulate the pancreatic β-cells. By the fast-slow dynamical bifurcation analysis and the bi-parameter bifurcation analysis, the local dynamics of the Chay-Keizer system around the Bogdanov-Takens bifurcation is illustrated. Then the variety of the number of spikes per burst is discussed by changing the settings of a single parameter and bi-parameter. Moreover, results on the number of spikes within a burst are summarized in ISIs (interspike intervals) sequence diagrams, maximum and minimum, and the number of spikes under bi-parameter value changes.

SPIKY: a graphical user interface for monitoring spike train synchrony

PubMed Central

Mulansky, Mario; Bozanic, Nebojsa

2015-01-01

Techniques for recording large-scale neuronal spiking activity are developing very fast. This leads to an increasing demand for algorithms capable of analyzing large amounts of experimental spike train data. One of the most crucial and demanding tasks is the identification of similarity patterns with a very high temporal resolution and across different spatial scales. To address this task, in recent years three time-resolved measures of spike train synchrony have been proposed, the ISI-distance, the SPIKE-distance, and event synchronization. The Matlab source codes for calculating and visualizing these measures have been made publicly available. However, due to the many different possible representations of the results the use of these codes is rather complicated and their application requires some basic knowledge of Matlab. Thus it became desirable to provide a more user-friendly and interactive interface. Here we address this need and present SPIKY, a graphical user interface that facilitates the application of time-resolved measures of spike train synchrony to both simulated and real data. SPIKY includes implementations of the ISI-distance, the SPIKE-distance, and the SPIKE-synchronization (an improved and simplified extension of event synchronization) that have been optimized with respect to computation speed and memory demand. It also comprises a spike train generator and an event detector that makes it capable of analyzing continuous data. Finally, the SPIKY package includes additional complementary programs aimed at the analysis of large numbers of datasets and the estimation of significance levels. PMID:25744888

SPIKY: a graphical user interface for monitoring spike train synchrony.

PubMed

Kreuz, Thomas; Mulansky, Mario; Bozanic, Nebojsa

2015-05-01

Techniques for recording large-scale neuronal spiking activity are developing very fast. This leads to an increasing demand for algorithms capable of analyzing large amounts of experimental spike train data. One of the most crucial and demanding tasks is the identification of similarity patterns with a very high temporal resolution and across different spatial scales. To address this task, in recent years three time-resolved measures of spike train synchrony have been proposed, the ISI-distance, the SPIKE-distance, and event synchronization. The Matlab source codes for calculating and visualizing these measures have been made publicly available. However, due to the many different possible representations of the results the use of these codes is rather complicated and their application requires some basic knowledge of Matlab. Thus it became desirable to provide a more user-friendly and interactive interface. Here we address this need and present SPIKY, a graphical user interface that facilitates the application of time-resolved measures of spike train synchrony to both simulated and real data. SPIKY includes implementations of the ISI-distance, the SPIKE-distance, and the SPIKE-synchronization (an improved and simplified extension of event synchronization) that have been optimized with respect to computation speed and memory demand. It also comprises a spike train generator and an event detector that makes it capable of analyzing continuous data. Finally, the SPIKY package includes additional complementary programs aimed at the analysis of large numbers of datasets and the estimation of significance levels. Copyright © 2015 the American Physiological Society.

Dynamic network communication as a unifying neural basis for cognition, development, aging, and disease.

PubMed

Voytek, Bradley; Knight, Robert T

2015-06-15

Perception, cognition, and social interaction depend upon coordinated neural activity. This coordination operates within noisy, overlapping, and distributed neural networks operating at multiple timescales. These networks are built upon a structural scaffolding with intrinsic neuroplasticity that changes with development, aging, disease, and personal experience. In this article, we begin from the perspective that successful interregional communication relies upon the transient synchronization between distinct low-frequency (<80 Hz) oscillations, allowing for brief windows of communication via phase-coordinated local neuronal spiking. From this, we construct a theoretical framework for dynamic network communication, arguing that these networks reflect a balance between oscillatory coupling and local population spiking activity and that these two levels of activity interact. We theorize that when oscillatory coupling is too strong, spike timing within the local neuronal population becomes too synchronous; when oscillatory coupling is too weak, spike timing is too disorganized. Each results in specific disruptions to neural communication. These alterations in communication dynamics may underlie cognitive changes associated with healthy development and aging, in addition to neurological and psychiatric disorders. A number of neurological and psychiatric disorders-including Parkinson's disease, autism, depression, schizophrenia, and anxiety-are associated with abnormalities in oscillatory activity. Although aging, psychiatric and neurological disease, and experience differ in the biological changes to structural gray or white matter, neurotransmission, and gene expression, our framework suggests that any resultant cognitive and behavioral changes in normal or disordered states or their treatment are a product of how these physical processes affect dynamic network communication. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Neuronal Spike Timing Adaptation Described with a Fractional Leaky Integrate-and-Fire Model

PubMed Central

Teka, Wondimu; Marinov, Toma M.; Santamaria, Fidel

2014-01-01

The voltage trace of neuronal activities can follow multiple timescale dynamics that arise from correlated membrane conductances. Such processes can result in power-law behavior in which the membrane voltage cannot be characterized with a single time constant. The emergent effect of these membrane correlations is a non-Markovian process that can be modeled with a fractional derivative. A fractional derivative is a non-local process in which the value of the variable is determined by integrating a temporal weighted voltage trace, also called the memory trace. Here we developed and analyzed a fractional leaky integrate-and-fire model in which the exponent of the fractional derivative can vary from 0 to 1, with 1 representing the normal derivative. As the exponent of the fractional derivative decreases, the weights of the voltage trace increase. Thus, the value of the voltage is increasingly correlated with the trajectory of the voltage in the past. By varying only the fractional exponent, our model can reproduce upward and downward spike adaptations found experimentally in neocortical pyramidal cells and tectal neurons in vitro. The model also produces spikes with longer first-spike latency and high inter-spike variability with power-law distribution. We further analyze spike adaptation and the responses to noisy and oscillatory input. The fractional model generates reliable spike patterns in response to noisy input. Overall, the spiking activity of the fractional leaky integrate-and-fire model deviates from the spiking activity of the Markovian model and reflects the temporal accumulated intrinsic membrane dynamics that affect the response of the neuron to external stimulation. PMID:24675903

Statistical technique for analysing functional connectivity of multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman

2011-03-15

A new statistical technique, the Cox method, used for analysing functional connectivity of simultaneously recorded multiple spike trains is presented. This method is based on the theory of modulated renewal processes and it estimates a vector of influence strengths from multiple spike trains (called reference trains) to the selected (target) spike train. Selecting another target spike train and repeating the calculation of the influence strengths from the reference spike trains enables researchers to find all functional connections among multiple spike trains. In order to study functional connectivity an "influence function" is identified. This function recognises the specificity of neuronal interactions and reflects the dynamics of postsynaptic potential. In comparison to existing techniques, the Cox method has the following advantages: it does not use bins (binless method); it is applicable to cases where the sample size is small; it is sufficiently sensitive such that it estimates weak influences; it supports the simultaneous analysis of multiple influences; it is able to identify a correct connectivity scheme in difficult cases of "common source" or "indirect" connectivity. The Cox method has been thoroughly tested using multiple sets of data generated by the neural network model of the leaky integrate and fire neurons with a prescribed architecture of connections. The results suggest that this method is highly successful for analysing functional connectivity of simultaneously recorded multiple spike trains. Copyright © 2011 Elsevier B.V. All rights reserved.

Genome-wide mapping of spike-related and agronomic traits in a common wheat population derived from a supernumerary parent and an elite parent

USDA-ARS?s Scientific Manuscript database

In wheat (Triticum aestivum L), exotic genotypes express a broad range of spike-related traits and could be used as a source of new genes to enrich the germplasm for wheat breeding programs. In the present study, a population of 163 recombinant inbred lines derived from a cross between an elite line...

Detrital zircon provenance of Mesoproterozoic to Cambrian arenites in the Western United States and Northwestern Mexico

USGS Publications Warehouse

Stewart, John H.; Gehrels, G.E.; Barth, A.P.; Link, P.K.; Christie-Blick, N.; Wrucke, C.T.

2001-01-01

U-Pb isotopic dating of detrital zircon from supracrustal Proterozoic and Cambrian arenites from the western United States and northern Mexico reveal three main age groups, 1.90 to 1.62 Ga, 1.45 to 1.40 Ga, and 1.2 to 1.0 Ga. Small amounts of zircons with ages of 3.1 to 2.5 Ga, 1.57 Ga, 1.32 Ga, 1.26 Ga, 0.7 Ga, and 0.5 Ga are also present. Detrital zircons ranging in age from 1.90 to 1.62 Ga and from 1.45 to 1.40 Ga are considered to have been derived from Proterozoic crystalline basement rocks of these known ages, and probably in part from reworked Proterozoic supracrustal sedimentary rocks, of the western United States. The 1.2 to 1.0 Ga detrital zircon ages from California, Arizona, and Sonora are characterized by distinct spikes (1.11 Ga, in particular) in the age-probability plots. These spikes are interpreted to indicate the influx of zircon from major silicic volcanic fields. Igneous rocks such as the Pikes Peak Granite (1.093 Ga) of Colorado, and the Aibo Granite (1.110 Ga) of Sonora, Mexico, may represent the deeply eroded roots of such volcanic fields. Samples from farther north along the Cordilleran margin that contain abundant 1.2-1.0 Ga detrital zircons do not show spikes in the age distribution, but rather ages spread out across the entire 1.2-1.0 Ga range. These age spectra resemble those for detrital zircons from the Grenville province, which is considered their source. Less common detrital zircons had a variety of sources. Zircons ranging in age from 3.36 to 2.31 Ga were apparently derived from inland parts of the North American continent from Wyoming to Canada. Zircons of about 1.577 Ga are highly unusual and may have had an exotic source; they may have come from Australia and been deposited in North America when Australia and North America were juxtaposed as part of the hypothetical Rodinian supercontinent. Detrital zircon of ??1.320 Ga apparently had the same source as that for tuff (1.320 Ga) in the Pioneer Shale of the Apache Group in Arizona. Detrital zircons of about 1.26 Ga in the Apache Group and Troy Quartzite appear to be related to local, approximately coeval volcanic fields. Zircons of about 0.7 Ga may have had a source in igneous rocks related to rifting of the Proterozoic supercontinent of Rodinia, and 0.5 Ga zircons a source in relatively small areas of granitic rocks of this known, or inferred, age in Oklahoma, Texas, New Mexico, and Colorado.

Programmable neural processing on a smartdust for brain-computer interfaces.

PubMed

Yuwen Sun; Shimeng Huang; Oresko, Joseph J; Cheng, Allen C

2010-10-01

Brain-computer interfaces (BCIs) offer tremendous promise for improving the quality of life for disabled individuals. BCIs use spike sorting to identify the source of each neural firing. To date, spike sorting has been performed by either using off-chip analysis, which requires a wired connection penetrating the skull to a bulky external power/processing unit, or via custom application-specific integrated circuits that lack the programmability to perform different algorithms and upgrades. In this research, we propose and test the feasibility of performing on-chip, real-time spike sorting on a programmable smartdust, including feature extraction, classification, compression, and wireless transmission. A detailed power/performance tradeoff analysis using DVFS is presented. Our experimental results show that the execution time and power density meet the requirements to perform real-time spike sorting and wireless transmission on a single neural channel.

The Global Spike: Conserved Dendritic Properties Enable Unique Ca2+ Spike Generation in Low-Threshold Spiking Neurons.

PubMed

Connelly, William M; Crunelli, Vincenzo; Errington, Adam C

2015-11-25

Low-threshold Ca(2+) spikes (LTS) are an indispensible signaling mechanism for neurons in areas including the cortex, cerebellum, basal ganglia, and thalamus. They have critical physiological roles and have been strongly associated with disorders including epilepsy, Parkinson's disease, and schizophrenia. However, although dendritic T-type Ca(2+) channels have been implicated in LTS generation, because the properties of low-threshold spiking neuron dendrites are unknown, the precise mechanism has remained elusive. Here, combining data from fluorescence-targeted dendritic recordings and Ca(2+) imaging from low-threshold spiking cells in rat brain slices with computational modeling, the cellular mechanism responsible for LTS generation is established. Our data demonstrate that key somatodendritic electrical conduction properties are highly conserved between glutamatergic thalamocortical neurons and GABAergic thalamic reticular nucleus neurons and that these properties are critical for LTS generation. In particular, the efficiency of soma to dendrite voltage transfer is highly asymmetric in low-threshold spiking cells, and in the somatofugal direction, these neurons are particularly electrotonically compact. Our data demonstrate that LTS have remarkably similar amplitudes and occur synchronously throughout the dendritic tree. In fact, these Ca(2+) spikes cannot occur locally in any part of the cell, and hence we reveal that LTS are generated by a unique whole-cell mechanism that means they always occur as spatially global spikes. This all-or-none, global electrical and biochemical signaling mechanism clearly distinguishes LTS from other signals, including backpropagating action potentials and dendritic Ca(2+)/NMDA spikes, and has important consequences for dendritic function in low-threshold spiking neurons. Low-threshold Ca(2+) spikes (LTS) are critical for important physiological processes, including generation of sleep-related oscillations, and are implicated in disorders including epilepsy, Parkinson's disease, and schizophrenia. However, the mechanism underlying LTS generation in neurons, which is thought to involve dendritic T-type Ca(2+) channels, has remained elusive due to a lack of knowledge of the dendritic properties of low-threshold spiking cells. Combining dendritic recordings, two-photon Ca(2+) imaging, and computational modeling, this study reveals that dendritic properties are highly conserved between two prominent low-threshold spiking neurons and that these properties underpin a whole-cell somatodendritic spike generation mechanism that makes the LTS a unique global electrical and biochemical signal in neurons. Copyright © 2015 Connelly et al.

The choice of the source space and the Laplacian matrix in LORETA and the spatio-temporal Kalman filter EEG inverse methods.

PubMed

Habboush, Nawar; Hamid, Laith; Japaridze, Natia; Wiegand, Gert; Heute, Ulrich; Stephani, Ulrich; Galka, Andreas; Siniatchkin, Michael

2015-08-01

The discretization of the brain and the definition of the Laplacian matrix influence the results of methods based on spatial and spatio-temporal smoothness, since the Laplacian operator is used to define the smoothness based on the neighborhood of each grid point. In this paper, the results of low resolution electromagnetic tomography (LORETA) and the spatiotemporal Kalman filter (STKF) are computed using, first, a greymatter source space with the standard definition of the Laplacian matrix and, second, using a whole-brain source space and a modified definition of the Laplacian matrix. Electroencephalographic (EEG) source imaging results of five inter-ictal spikes from a pre-surgical patient with epilepsy are used to validate the two aforementioned approaches. The results using the whole-brain source space and the modified definition of the Laplacian matrix were concentrated in a single source activation, stable, and concordant with the location of the focal cortical dysplasia (FCD) in the patient's brain compared with the results which use a grey-matter grid and the classical definition of the Laplacian matrix. This proof-of-concept study demonstrates a substantial improvement of source localization with both LORETA and STKF and constitutes a basis for further research in a large population of patients with epilepsy.

Dynamics of the functional link between area MT LFPs and motion detection

PubMed Central

Smith, Jackson E. T.; Beliveau, Vincent; Schoen, Alan; Remz, Jordana; Zhan, Chang'an A.

2015-01-01

The evolution of a visually guided perceptual decision results from multiple neural processes, and recent work suggests that signals with different neural origins are reflected in separate frequency bands of the cortical local field potential (LFP). Spike activity and LFPs in the middle temporal area (MT) have a functional link with the perception of motion stimuli (referred to as neural-behavioral correlation). To cast light on the different neural origins that underlie this functional link, we compared the temporal dynamics of the neural-behavioral correlations of MT spikes and LFPs. Wide-band activity was simultaneously recorded from two locations of MT from monkeys performing a threshold, two-stimuli, motion pulse detection task. Shortly after the motion pulse occurred, we found that high-gamma (100–200 Hz) LFPs had a fast, positive correlation with detection performance that was similar to that of the spike response. Beta (10–30 Hz) LFPs were negatively correlated with detection performance, but their dynamics were much slower, peaked late, and did not depend on stimulus configuration or reaction time. A late change in the correlation of all LFPs across the two recording electrodes suggests that a common input arrived at both MT locations prior to the behavioral response. Our results support a framework in which early high-gamma LFPs likely reflected fast, bottom-up, sensory processing that was causally linked to perception of the motion pulse. In comparison, late-arriving beta and high-gamma LFPs likely reflected slower, top-down, sources of neural-behavioral correlation that originated after the perception of the motion pulse. PMID:25948867

Extraction of Inter-Aural Time Differences Using a Spiking Neuron Network Model of the Medial Superior Olive.

PubMed

Encke, Jörg; Hemmert, Werner

2018-01-01

The mammalian auditory system is able to extract temporal and spectral features from sound signals at the two ears. One important cue for localization of low-frequency sound sources in the horizontal plane are inter-aural time differences (ITDs) which are first analyzed in the medial superior olive (MSO) in the brainstem. Neural recordings of ITD tuning curves at various stages along the auditory pathway suggest that ITDs in the mammalian brainstem are not represented in form of a Jeffress-type place code. An alternative is the hemispheric opponent-channel code, according to which ITDs are encoded as the difference in the responses of the MSO nuclei in the two hemispheres. In this study, we present a physiologically-plausible, spiking neuron network model of the mammalian MSO circuit and apply two different methods of extracting ITDs from arbitrary sound signals. The network model is driven by a functional model of the auditory periphery and physiological models of the cochlear nucleus and the MSO. Using a linear opponent-channel decoder, we show that the network is able to detect changes in ITD with a precision down to 10 μs and that the sensitivity of the decoder depends on the slope of the ITD-rate functions. A second approach uses an artificial neuronal network to predict ITDs directly from the spiking output of the MSO and ANF model. Using this predictor, we show that the MSO-network is able to reliably encode static and time-dependent ITDs over a large frequency range, also for complex signals like speech.

Locally induced neuronal synchrony precisely propagates to specific cortical areas without rhythm distortion.

PubMed

Toda, Haruo; Kawasaki, Keisuke; Sato, Sho; Horie, Masao; Nakahara, Kiyoshi; Bepari, Asim K; Sawahata, Hirohito; Suzuki, Takafumi; Okado, Haruo; Takebayashi, Hirohide; Hasegawa, Isao

2018-05-16

Propagation of oscillatory spike firing activity at specific frequencies plays an important role in distributed cortical networks. However, there is limited evidence for how such frequency-specific signals are induced or how the signal spectra of the propagating signals are modulated during across-layer (radial) and inter-areal (tangential) neuronal interactions. To directly evaluate the direction specificity of spectral changes in a spiking cortical network, we selectively photostimulated infragranular excitatory neurons in the rat primary visual cortex (V1) at a supra-threshold level with various frequencies, and recorded local field potentials (LFPs) at the infragranular stimulation site, the cortical surface site immediately above the stimulation site in V1, and cortical surface sites outside V1. We found a significant reduction of LFP powers during radial propagation, especially at high-frequency stimulation conditions. Moreover, low-gamma-band dominant rhythms were transiently induced during radial propagation. Contrastingly, inter-areal LFP propagation, directed to specific cortical sites, accompanied no significant signal reduction nor gamma-band power induction. We propose an anisotropic mechanism for signal processing in the spiking cortical network, in which the neuronal rhythms are locally induced/modulated along the radial direction, and then propagate without distortion via intrinsic horizontal connections for spatiotemporally precise, inter-areal communication.

Sediment evidence of industrial leakage-induced asynchronous changes in polycyclic aromatic hydrocarbons and trace metals from a sub-trophic lake, southwest China.

PubMed

Wang, Lei; Chen, Guangjie; Kang, Wengang; Wang, Jiaoyuan; Liu, Yuanyuan; Chen, Li

2018-05-01

It has been well established that regional patterns of atmosphere-borne polycyclic aromatic hydrocarbons (PAHs) and trace metals were predominantly associated with the trajectory of socio-economic development; however, they could be potentially modulated by anthropogenic fingerprint of local sources such as industrial spill. Here, we established historical pollution data of both PAHs and trace metals from a well-dated sediment core from Yangzong Lake of Southwest China, which experienced a severe tailing leakage accident derived from a zinc concentrate smelting plant in 2007, aiming to evaluate the heterogeneity in their temporal trajectories and their sources of contamination in the context of regional deposition patterns. Sedimentary records show that the concentrations and fluxes of both PAHs and trace metals remained a consistently low level before the 1950s. An increasing trend and the synchronous changes of both PAHs and trace metals during ~ 1950-2002 were well consistent with the temporal pattern of socio-economic development in western China, with coal combustion and smelting industries as the main sources of contamination in this region. However, arsenic (As) and PAHs exhibited a concurrent spike for the period of ~ 2007-2013, contrasting strongly to the regional pattern of these contaminants. The modern concentrations of As revealed a 5- to 14-fold increase over the pre-1950 level, with the contemporary concentrations of PAHs rising by ~ 10-14 times. The sediment records reveal that local fingerprints of smelting activities in the catchment of Yangzong Lake have overridden the temporary pattern of regional atmosphere-borne As and PAHs over the last decade. This highlights the important role of local pollution sources in modulating or even overriding the regional pattern of anthropogenic contamination in highly impacted systems.

Solution to the inverse problem of estimating gap-junctional and inhibitory conductance in inferior olive neurons from spike trains by network model simulation.

PubMed

Onizuka, Miho; Hoang, Huu; Kawato, Mitsuo; Tokuda, Isao T; Schweighofer, Nicolas; Katori, Yuichi; Aihara, Kazuyuki; Lang, Eric J; Toyama, Keisuke

2013-11-01

The inferior olive (IO) possesses synaptic glomeruli, which contain dendritic spines from neighboring neurons and presynaptic terminals, many of which are inhibitory and GABAergic. Gap junctions between the spines electrically couple neighboring neurons whereas the GABAergic synaptic terminals are thought to act to decrease the effectiveness of this coupling. Thus, the glomeruli are thought to be important for determining the oscillatory and synchronized activity displayed by IO neurons. Indeed, the tendency to display such activity patterns is enhanced or reduced by the local administration of the GABA-A receptor blocker picrotoxin (PIX) or the gap junction blocker carbenoxolone (CBX), respectively. We studied the functional roles of the glomeruli by solving the inverse problem of estimating the inhibitory (gi) and gap-junctional conductance (gc) using an IO network model. This model was built upon a prior IO network model, in which the individual neurons consisted of soma and dendritic compartments, by adding a glomerular compartment comprising electrically coupled spines that received inhibitory synapses. The model was used in the forward mode to simulate spike data under PIX and CBX conditions for comparison with experimental data consisting of multi-electrode recordings of complex spikes from arrays of Purkinje cells (complex spikes are generated in a one-to-one manner by IO spikes and thus can substitute for directly measuring IO spike activity). The spatiotemporal firing dynamics of the experimental and simulation spike data were evaluated as feature vectors, including firing rates, local variation, auto-correlogram, cross-correlogram, and minimal distance, and were contracted onto two-dimensional principal component analysis (PCA) space. gc and gi were determined as the solution to the inverse problem such that the simulation and experimental spike data were closely matched in the PCA space. The goodness of the match was confirmed by an analysis of variance (ANOVA) of the PCA scores between the experimental and simulation spike data. In the PIX condition, gi was found to decrease to approximately half its control value. CBX caused an approximately 30% decrease in gc from control levels. These results support the hypothesis that the glomeruli are control points for determining the spatiotemporal characteristics of olivocerebellar activity and thus may shape its ability to convey signals to the cerebellum that may be used for motor learning or motor control purposes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Investigation into the Effects of Microsecond Power Line Transients on Line-Connected Capacitors

NASA Technical Reports Server (NTRS)

Javor, K.

2000-01-01

An investigation was conducted into the effect of power-line transients on capacitors used by NASA and installed on platform primary power inputs to avionics. The purpose was to investigate whether capacitor voltage ratings needs to be derated for expected spike potentials. Concerns had been voiced in the past by NASA suppliers that MIL-STD-461 CS06-like requirements were overly harsh and led to physically large capacitors. The author had previously predicted that electrical-switching spike requirements representative of actual power-line transient potentials, durations. and source impedance would require no derating. This investigation bore out that prediction. It was further determined that traditional low source impedance CS06-like transients also will not damage a capacitor, although the spikes themselves are not nearly as well filtered. This report should be used to allay fears that CS06-like requirements drive capacitor voltage derating. Only that derating required by the relatively long duration transients in power quality specification need concern the equipment designer.

Investigation Into The Effects of Microsecond Power Line Transients On Line-Connected Capacitors

NASA Technical Reports Server (NTRS)

Javor, Ken

1999-01-01

An investigation was conducted into the effect of power-line transients on capacitors used by NASA and installed on platform primary power inputs to avionics. The purpose was to investigate whether capacitor voltage rating needs to be derated for expected spike potentials. Concerns had been voiced in the past by NASA suppliers that MIL-STD-461 CS06-like requirements were overly harsh and led to physically large capacitors. The author had previously predicted that electrical-switching spike requirements representative of actual power-line transient potentials, durations and source impedance would require no derating. This investigation bore out that prediction. It was further determined that traditional low source impedance CS06-like transients also will not damage a capacitor, although the spikes themselves are not nearly as well filtered. This report should be used to allay fears that CS06-like requirements drive capacitor voltage derating. Only that derating required by the relatively long duration transients in power quality specification need concern the equipment designer.

Selective detection and characterization of nanoparticles from motor vehicles.

PubMed

Johnston, Murray V; Klems, Joseph P; Zordan, Christopher A; Pennington, M Ross; Smith, James N

2013-02-01

Numerous studies have shown that exposure to motor vehicle emissions increases the probability of heart attacks, asthma attacks, and hospital visits among at-risk individuals. However, while many studies have focused on measurements of ambient nanoparticles near highways, they have not focused on specific road-level domains, such as intersections near population centers. At these locations, very intense spikes in particle number concentration have been observed. These spikes have been linked to motor vehicle activity and have the potential to increase exposure dramatically. Characterizing both the contribution and composition of these spikes is critical in developing exposure models and abatement strategies. To determine the contribution of the particle spikes to the ambient number concentration, we implemented wavelet-based algorithms to isolate the particle spikes from measurements taken during the summer and winter of 2009 in Wilmington, Delaware, adjacent to a roadway intersection that approximately 28,000 vehicles pass through daily. These measurements included both number concentration and size distributions recorded once every second by a condensation particle counter (CPC*; TSI, Inc., St. Paul, MN) and a fast mobility particle sizer (FMPS). The high-frequency portion of the signal, consisting of a series of abrupt spikes in number concentration that varied in length from a few seconds to tens of seconds, accounted for 3% to 35% of the daily ambient number concentration, with spike contributions sometimes greater than 50% of hourly number concentrations. When the data were weighted by particle volume, this portion of the signal contributed an average of 10% to 20% to the daily concentration of particulate matter (PM) < or = 0.1 microm in aerodynamic diameter (PM0.1). The preferred locations for observing particle concentration spikes were those surrounding the measurement site at which motor vehicles accelerated after a red traffic light turned green. As the distance or transit time from emission to sampling increased, the size distribution shifted to a larger particle size, which confirmed the source assignments. To determine the distribution of emissions from individual vehicles, we correlated camera images with the spike contribution to particle number concentration at each time point. A small percentage of motor vehicles were found to emit a disproportionally large concentration of nanoparticles, and these high emitters included both spark-ignition (SI) and heavy-duty diesel (HDD) vehicles. In addition to characterizing the contribution of the spikes (local sources) to the ambient number concentration, we developed a method to determine the net contribution of motor vehicles (all sources) to the total mass concentration of ambient nanoparticles. To do this, we correlated the concentration of spikes with measurements of fast changes in the chemical composition of nanoparticles measured with the nano aerosol mass spectrometer (NAMS; built by the Johnston group). The NAMS irradiates individual, size-selected nanoparticles with a high-energy laser pulse to generate a mass spectrum consisting of multiply charged atomic ions. The elemental composition of each particle was determined from the ion signal intensities of each element. However, overlapping mass-to-charge ratios (m/z) at 4 m/z (O(+4) and C(+3)) and at 8 m/z (O(+2) and S(+4)) needed to be separated into their component ions to obtain a representative composition. To do this, we developed a method to deconvolute these ion signals using sucrose and ammonium sulfate [(NH4)2SO4] as calibration standards. With this approach, the differences between the expected and measured elemental mole fractions of carbon (C), oxygen (O), nitrogen (N), and sulfur (S) for a variety of test particles were generally much less than 10%. Ambient nanoparticles were found to consist mostly of C, O, N, and S. Many particles also contained silicon (Si). The elemental compositions were apportioned into molecular species that are commonly found in ambient aerosol: sulfate (SO4(2-)), nitrate (NO3-), ammonium (NH4+), carbonaceous matter, and when present, silicon dioxide (SiO2). Correlating NAMS chemical-composition measurements with spike contributions allowed for the development of a chemical profile representing motor vehicle emissions, which could be used to apportion their total contribution to the ambient nanoparticle mass. Particles originating from motor vehicles had compositions dominated by unoxidized carbonaceous matter, whereas non-motor vehicle particles consisted mostly of SO42-, NO3-, and oxidized carbonaceous matter. Motor vehicles were found to contribute up to 48% and 60% of the nanoparticle mass and number concentrations, respectively, in the winter measurement period, but only 16% and 49% of the nanoparticle mass and number concentrations, respectively, in the summer period. Chemical-composition profiles and contributions of SI versus HDD vehicles to the nanoparticle mass concentration were estimated by correlating still camera images, chemical composition, and spike contributions at each time point. The total mass contributions from SI and HDD vehicles were roughly equal, but the uncertainty in the split was large. The results of this study suggest that nanoparticle concentrations will be higher adjacent to an intersection than along the same roadway but further from an intersection. Possible ways to reduce the motor vehicle contribution to ambient nanoparticulate matter include minimizing stop-and-go activity at an intersection (i.e., vehicles accelerating after a red light turns green) and identifying the small fraction of motor vehicles that emit a disproportionally large number of nanoparticles.

Synaptic convergence regulates synchronization-dependent spike transfer in feedforward neural networks.

PubMed

Sailamul, Pachaya; Jang, Jaeson; Paik, Se-Bum

2017-12-01

Correlated neural activities such as synchronizations can significantly alter the characteristics of spike transfer between neural layers. However, it is not clear how this synchronization-dependent spike transfer can be affected by the structure of convergent feedforward wiring. To address this question, we implemented computer simulations of model neural networks: a source and a target layer connected with different types of convergent wiring rules. In the Gaussian-Gaussian (GG) model, both the connection probability and the strength are given as Gaussian distribution as a function of spatial distance. In the Uniform-Constant (UC) and Uniform-Exponential (UE) models, the connection probability density is a uniform constant within a certain range, but the connection strength is set as a constant value or an exponentially decaying function, respectively. Then we examined how the spike transfer function is modulated under these conditions, while static or synchronized input patterns were introduced to simulate different levels of feedforward spike synchronization. We observed that the synchronization-dependent modulation of the transfer function appeared noticeably different for each convergence condition. The modulation of the spike transfer function was largest in the UC model, and smallest in the UE model. Our analysis showed that this difference was induced by the different spike weight distributions that was generated from convergent synapses in each model. Our results suggest that, the structure of the feedforward convergence is a crucial factor for correlation-dependent spike control, thus must be considered important to understand the mechanism of information transfer in the brain.

Annual atmospheric mercury species in downtown Toronto, Canada.

PubMed

Song, Xinjie; Cheng, Irene; Lu, Julia

2009-03-01

Real-time concentrations of atmospheric gaseous elemental mercury (GEM), reactive gaseous mercury (RGM), and mercury associated with particles having sizes <2.5 microm (P-Hg < 2.5) were simultaneously measured in downtown Toronto from December 2003 to November 2004. The annual mean concentrations of GEM, P-Hg < 2.5 and RGM were 4.5 +/- 3.1 ng m(-3) (99.2%), 21.5 +/- 16.4 pg m(-3) (0.5%) and 14.2 +/- 13.2 pg m(-3) (0.3%), respectively. The concentrations for all the measured Hg species were highly variable throughout the year and were lower in winter than in the other three seasons. The maximum concentrations of Hg species were observed in June and were a result of the high number of Hg spikes (using [GEM] >10 ng m(-3) as an indicator) that occurred in the month. Nighttime (between 9pm-6am) concentrations of Hg species were higher than those of daytime. The results revealed: (1) an urban area is a continuous source of Hg species that have the potential to pose impacts on local, regional and global scales; (2) local/regional anthropogenic sources contributed significantly to the levels and the distributions of the Hg species in the urban atmosphere. More studies are needed to identify and quantify the anthropogenic sources of Hg and the Hg species emitted from these sources; (3) surface emission and photochemical reactions (including the reactions involving ozone) did not have significant influence on the levels of Hg species and their distribution in the urban atmosphere.

A role for the mevalonate pathway in early plant symbiotic signaling

PubMed Central

Venkateshwaran, Muthusubramanian; Jayaraman, Dhileepkumar; Chabaud, Mireille; Genre, Andrea; Balloon, Allison J.; Maeda, Junko; Forshey, Kari; den Os, Désirée; Kwiecien, Nicholas W.; Coon, Joshua J.; Barker, David G.; Ané, Jean-Michel

2015-01-01

Rhizobia and arbuscular mycorrhizal fungi produce signals that are perceived by host legume receptors at the plasma membrane and trigger sustained oscillations of the nuclear and perinuclear Ca2+ concentration (Ca2+ spiking), which in turn leads to gene expression and downstream symbiotic responses. The activation of Ca2+ spiking requires the plasma membrane-localized receptor-like kinase Does not Make Infections 2 (DMI2) as well as the nuclear cation channel DMI1. A key enzyme regulating the mevalonate (MVA) pathway, 3-Hydroxy-3-Methylglutaryl CoA Reductase 1 (HMGR1), interacts with DMI2 and is required for the legume–rhizobium symbiosis. Here, we show that HMGR1 is required to initiate Ca2+ spiking and symbiotic gene expression in Medicago truncatula roots in response to rhizobial and arbuscular mycorrhizal fungal signals. Furthermore, MVA, the direct product of HMGR1 activity, is sufficient to induce nuclear-associated Ca2+ spiking and symbiotic gene expression in both wild-type plants and dmi2 mutants, but interestingly not in dmi1 mutants. Finally, MVA induced Ca2+ spiking in Human Embryonic Kidney 293 cells expressing DMI1. This demonstrates that the nuclear cation channel DMI1 is sufficient to support MVA-induced Ca2+ spiking in this heterologous system. PMID:26199419

A role for the mevalonate pathway in early plant symbiotic signaling.

PubMed

Venkateshwaran, Muthusubramanian; Jayaraman, Dhileepkumar; Chabaud, Mireille; Genre, Andrea; Balloon, Allison J; Maeda, Junko; Forshey, Kari; den Os, Désirée; Kwiecien, Nicholas W; Coon, Joshua J; Barker, David G; Ané, Jean-Michel

2015-08-04

Rhizobia and arbuscular mycorrhizal fungi produce signals that are perceived by host legume receptors at the plasma membrane and trigger sustained oscillations of the nuclear and perinuclear Ca(2+) concentration (Ca(2+) spiking), which in turn leads to gene expression and downstream symbiotic responses. The activation of Ca(2+) spiking requires the plasma membrane-localized receptor-like kinase Does not Make Infections 2 (DMI2) as well as the nuclear cation channel DMI1. A key enzyme regulating the mevalonate (MVA) pathway, 3-Hydroxy-3-Methylglutaryl CoA Reductase 1 (HMGR1), interacts with DMI2 and is required for the legume-rhizobium symbiosis. Here, we show that HMGR1 is required to initiate Ca(2+) spiking and symbiotic gene expression in Medicago truncatula roots in response to rhizobial and arbuscular mycorrhizal fungal signals. Furthermore, MVA, the direct product of HMGR1 activity, is sufficient to induce nuclear-associated Ca(2+) spiking and symbiotic gene expression in both wild-type plants and dmi2 mutants, but interestingly not in dmi1 mutants. Finally, MVA induced Ca(2+) spiking in Human Embryonic Kidney 293 cells expressing DMI1. This demonstrates that the nuclear cation channel DMI1 is sufficient to support MVA-induced Ca(2+) spiking in this heterologous system.

High voltage MOSFET switching circuit

DOEpatents

McEwan, Thomas E.

1994-01-01

The problem of source lead inductance in a MOSFET switching circuit is compensated for by adding an inductor to the gate circuit. The gate circuit inductor produces an inductive spike which counters the source lead inductive drop to produce a rectangular drive voltage waveform at the internal gate-source terminals of the MOSFET.

Differentiability of simulated MEG hippocampal, medial temporal and neocortical temporal epileptic spike activity.

PubMed

Stephen, Julia M; Ranken, Doug M; Aine, Cheryl J; Weisend, Michael P; Shih, Jerry J

2005-12-01

Previous studies have shown that magnetoencephalography (MEG) can measure hippocampal activity, despite the cylindrical shape and deep location in the brain. The current study extended this work by examining the ability to differentiate the hippocampal subfields, parahippocampal cortex, and neocortical temporal sources using simulated interictal epileptic activity. A model of the hippocampus was generated on the MRIs of five subjects. CA1, CA3, and dentate gyrus of the hippocampus were activated as well as entorhinal cortex, presubiculum, and neocortical temporal cortex. In addition, pairs of sources were activated sequentially to emulate various hypotheses of mesial temporal lobe seizure generation. The simulated MEG activity was added to real background brain activity from the five subjects and modeled using a multidipole spatiotemporal modeling technique. The waveforms and source locations/orientations for hippocampal and parahippocampal sources were differentiable from neocortical temporal sources. In addition, hippocampal and parahippocampal sources were differentiated to varying degrees depending on source. The sequential activation of hippocampal and parahippocampal sources was adequately modeled by a single source; however, these sources were not resolvable when they overlapped in time. These results suggest that MEG has the sensitivity to distinguish parahippocampal and hippocampal spike generators in mesial temporal lobe epilepsy.

Simultaneous recording of brain extracellular glucose, spike and local field potential in real time using an implantable microelectrode array with nano-materials

NASA Astrophysics Data System (ADS)

Wei, Wenjing; Song, Yilin; Fan, Xinyi; Zhang, Song; Wang, Li; Xu, Shengwei; Wang, Mixia; Cai, Xinxia

2016-03-01

Glucose is the main substrate for neurons in the central nervous system. In order to efficiently characterize the brain glucose mechanism, it is desirable to determine the extracellular glucose dynamics as well as the corresponding neuroelectrical activity in vivo. In the present study, we fabricated an implantable microelectrode array (MEA) probe composed of platinum electrochemical and electrophysiology microelectrodes by standard micro electromechanical system (MEMS) processes. The MEA probe was modified with nano-materials and implanted in a urethane-anesthetized rat for simultaneous recording of striatal extracellular glucose, local field potential (LFP) and spike on the same spatiotemporal scale when the rat was in normoglycemia, hypoglycemia and hyperglycemia. During these dual-mode recordings, we observed that increase of extracellular glucose enhanced the LFP power and spike firing rate, while decrease of glucose had an opposite effect. This dual mode MEA probe is capable of examining specific spatiotemporal relationships between electrical and chemical signaling in the brain, which will contribute significantly to improve our understanding of the neuron physiology.

Entorhinal stellate cells show preferred spike phase-locking to theta inputs that is enhanced by correlations in synaptic activity

PubMed Central

Fernandez, Fernando R.; Malerba, Paola; Bressloff, Paul C.; White, John A.

2013-01-01

In active networks, excitatory and inhibitory synaptic inputs generate membrane voltage fluctuations that drive spike activity in a probabilistic manner. Despite this, some cells in vivo show a strong propensity to precisely lock to the local field potential and maintain a specific spike-phase relationship relative to other cells. In recordings from rat medial entorhinal cortical stellate cells, we measured spike phase-locking in response to sinusoidal “test” inputs in the presence of different forms of background membrane voltage fluctuations, generated via dynamic clamp. We find that stellate cells show strong and robust spike phase-locking to theta (4–12 Hz) inputs. This response occurs under a wide variety of background membrane voltage fluctuation conditions that include a substantial increase in overall membrane conductance. Furthermore, the IH current present in stellate cells is critical to the enhanced spike phase-locking response at theta. Finally, we show that correlations between inhibitory and excitatory conductance fluctuations, which can arise through feed-back and feed-forward inhibition, can substantially enhance the spike phase-locking response. The enhancement in locking is a result of a selective reduction in the size of low frequency membrane voltage fluctuations due to cancelation of inhibitory and excitatory current fluctuations with correlations. Hence, our results demonstrate that stellate cells have a strong preference for spike phase-locking to theta band inputs and that the absolute magnitude of locking to theta can be modulated by the properties of background membrane voltage fluctuations. PMID:23554484

Cell type- and activity-dependent extracellular correlates of intracellular spiking

PubMed Central

Perin, Rodrigo; Buzsáki, György; Markram, Henry; Koch, Christof

2015-01-01

Despite decades of extracellular action potential (EAP) recordings monitoring brain activity, the biophysical origin and inherent variability of these signals remain enigmatic. We performed whole cell patch recordings of excitatory and inhibitory neurons in rat somatosensory cortex slice while positioning a silicon probe in their vicinity to concurrently record intra- and extracellular voltages for spike frequencies under 20 Hz. We characterize biophysical events and properties (intracellular spiking, extracellular resistivity, temporal jitter, etc.) related to EAP recordings at the single-neuron level in a layer-specific manner. Notably, EAP amplitude was found to decay as the inverse of distance between the soma and the recording electrode with similar (but not identical) resistivity across layers. Furthermore, we assessed a number of EAP features and their variability with spike activity: amplitude (but not temporal) features varied substantially (∼30–50% compared with mean) and nonmonotonically as a function of spike frequency and spike order. Such EAP variation only partly reflects intracellular somatic spike variability and points to the plethora of processes contributing to the EAP. Also, we show that the shape of the EAP waveform is qualitatively similar to the negative of the temporal derivative to the intracellular somatic voltage, as expected from theory. Finally, we tested to what extent EAPs can impact the lowpass-filtered part of extracellular recordings, the local field potential (LFP), typically associated with synaptic activity. We found that spiking of excitatory neurons can significantly impact the LFP at frequencies as low as 20 Hz. Our results question the common assertion that the LFP acts as proxy for synaptic activity. PMID:25995352

A flexible super-capacitive solid-state power supply for miniature implantable medical devices.

PubMed

Meng, Chuizhou; Gall, Oren Z; Irazoqui, Pedro P

2013-12-01

We present a high-energy local power supply based on a flexible and solid-state supercapacitor for miniature wireless implantable medical devices. Wireless radio-frequency (RF) powering recharges the supercapacitor through an antenna with an RF rectifier. A power management circuit for the super-capacitive system includes a boost converter to increase the breakdown voltage required for powering device circuits, and a parallel conventional capacitor as an intermediate power source to deliver current spikes during high current transients (e.g., wireless data transmission). The supercapacitor has an extremely high area capacitance of ~1.3 mF/mm(2), and is in the novel form of a 100 μm-thick thin film with the merit of mechanical flexibility and a tailorable size down to 1 mm(2) to meet various clinical dimension requirements. We experimentally demonstrate that after fully recharging the capacitor with an external RF powering source, the supercapacitor-based local power supply runs a full system for electromyogram (EMG) recording that consumes ~670 μW with wireless-data-transmission functionality for a period of ~1 s in the absence of additional RF powering. Since the quality of wireless powering for implantable devices is sensitive to the position of those devices within the RF electromagnetic field, this high-energy local power supply plays a crucial role in providing continuous and reliable power for medical device operations.

Use of Interrupted Helium Flow in the Analysis of Vapor Samples with Flowing Atmospheric-Pressure Afterglow-Mass Spectrometry

NASA Astrophysics Data System (ADS)

Storey, Andrew P.; Zeiri, Offer M.; Ray, Steven J.; Hieftje, Gary M.

2017-02-01

The flowing atmospheric-pressure afterglow (FAPA) source was used for the mass-spectrometric analysis of vapor samples introduced between the source and mass spectrometer inlet. Through interrupted operation of the plasma-supporting helium flow, helium consumption is greatly reduced and dynamic gas behavior occurs that was characterized by schlieren imaging. Moreover, mass spectra acquired immediately after the onset of helium flow exhibit a signal spike before declining and ultimately reaching a steady level. This initial signal appears to be due to greater interaction of sample vapor with the afterglow of the source when helium flow resumes. In part, the initial spike in signal can be attributed to a pooling of analyte vapor in the absence of helium flow from the source. Time-resolved schlieren imaging of the helium flow during on and off cycles provided insight into gas-flow patterns between the FAPA source and the MS inlet that were correlated with mass-spectral data.

Use of Interrupted Helium Flow in the Analysis of Vapor Samples with Flowing Atmospheric-Pressure Afterglow-Mass Spectrometry.

PubMed

Storey, Andrew P; Zeiri, Offer M; Ray, Steven J; Hieftje, Gary M

2017-02-01

The flowing atmospheric-pressure afterglow (FAPA) source was used for the mass-spectrometric analysis of vapor samples introduced between the source and mass spectrometer inlet. Through interrupted operation of the plasma-supporting helium flow, helium consumption is greatly reduced and dynamic gas behavior occurs that was characterized by schlieren imaging. Moreover, mass spectra acquired immediately after the onset of helium flow exhibit a signal spike before declining and ultimately reaching a steady level. This initial signal appears to be due to greater interaction of sample vapor with the afterglow of the source when helium flow resumes. In part, the initial spike in signal can be attributed to a pooling of analyte vapor in the absence of helium flow from the source. Time-resolved schlieren imaging of the helium flow during on and off cycles provided insight into gas-flow patterns between the FAPA source and the MS inlet that were correlated with mass-spectral data. Graphical Abstract ᅟ.

Identification of Major Sources of Atmospheric NH3 in an Urban Environment in Northern China During Wintertime.

PubMed

Teng, Xiaolin; Hu, Qingjing; Zhang, Leiming; Qi, Jiajia; Shi, Jinhui; Xie, Huan; Gao, Huiwang; Yao, Xiaohong

2017-06-20

To assess the relative contributions of traffic emission and other potential sources to high levels of atmospheric ammonia (NH 3 ) in urban areas in the wintertime, atmospheric NH 3 and related pollutants were measured at an urban site, ∼300 m from a major traffic road, in northern China in November and December 2015. Hourly average NH 3 varied from 0.3 to 10.8 ppb with an average of 2.4 ppb during the campaign. Contrary to the common perspective in literature, traffic emission was demonstrated to be a negligible contributor to atmospheric NH 3 . Atmospheric NH 3 correlated well with ambient water vapor during many time periods lasting from tens of hours to several days, implying NH 3 released from water evaporation is an important source. Emissions from local green space inside the urban areas were identified to significantly contribute to the observed atmospheric NH 3 during ∼60% of the sampling times. Evaporation of predeposited NH x through wet precipitation combined with emissions from local green space likely caused the spikes of atmospheric NH 3 mostly occurring 1-4 h after morning rush hours or after and during slight shower events. There are still ∼30% of the data samples with appreciable NH 3 level for which major contributors are yet to be identified.

Adjustment of Pesticide Concentrations for Temporal Changes in Analytical Recovery, 1992-2006

USGS Publications Warehouse

Martin, Jeffrey D.; Stone, Wesley W.; Wydoski, Duane S.; Sandstrom, Mark W.

2009-01-01

Recovery is the proportion of a target analyte that is quantified by an analytical method and is a primary indicator of the analytical bias of a measurement. Recovery is measured by analysis of quality-control (QC) water samples that have known amounts of target analytes added ('spiked' QC samples). For pesticides, recovery is the measured amount of pesticide in the spiked QC sample expressed as percentage of the amount spiked, ideally 100 percent. Temporal changes in recovery have the potential to adversely affect time-trend analysis of pesticide concentrations by introducing trends in environmental concentrations that are caused by trends in performance of the analytical method rather than by trends in pesticide use or other environmental conditions. This report examines temporal changes in the recovery of 44 pesticides and 8 pesticide degradates (hereafter referred to as 'pesticides') that were selected for a national analysis of time trends in pesticide concentrations in streams. Water samples were analyzed for these pesticides from 1992 to 2006 by gas chromatography/mass spectrometry. Recovery was measured by analysis of pesticide-spiked QC water samples. Temporal changes in pesticide recovery were investigated by calculating robust, locally weighted scatterplot smooths (lowess smooths) for the time series of pesticide recoveries in 5,132 laboratory reagent spikes; 1,234 stream-water matrix spikes; and 863 groundwater matrix spikes. A 10-percent smoothing window was selected to show broad, 6- to 12-month time scale changes in recovery for most of the 52 pesticides. Temporal patterns in recovery were similar (in phase) for laboratory reagent spikes and for matrix spikes for most pesticides. In-phase temporal changes among spike types support the hypothesis that temporal change in method performance is the primary cause of temporal change in recovery. Although temporal patterns of recovery were in phase for most pesticides, recovery in matrix spikes was greater than recovery in reagent spikes for nearly every pesticide. Models of recovery based on matrix spikes are deemed more appropriate for adjusting concentrations of pesticides measured in groundwater and stream-water samples than models based on laboratory reagent spikes because (1) matrix spikes are expected to more closely match the matrix of environmental water samples than are reagent spikes and (2) method performance is often matrix dependent, as was shown by higher recovery in matrix spikes for most of the pesticides. Models of recovery, based on lowess smooths of matrix spikes, were developed separately for groundwater and stream-water samples. The models of recovery can be used to adjust concentrations of pesticides measured in groundwater or stream-water samples to 100 percent recovery to compensate for temporal changes in the performance (bias) of the analytical method.

Heterogeneity induces spatiotemporal oscillations in reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Krause, Andrew L.; Klika, Václav; Woolley, Thomas E.; Gaffney, Eamonn A.

2018-05-01

We report on an instability arising in activator-inhibitor reaction-diffusion (RD) systems with a simple spatial heterogeneity. This instability gives rise to periodic creation, translation, and destruction of spike solutions that are commonly formed due to Turing instabilities. While this behavior is oscillatory in nature, it occurs purely within the Turing space such that no region of the domain would give rise to a Hopf bifurcation for the homogeneous equilibrium. We use the shadow limit of the Gierer-Meinhardt system to show that the speed of spike movement can be predicted from well-known asymptotic theory, but that this theory is unable to explain the emergence of these spatiotemporal oscillations. Instead, we numerically explore this system and show that the oscillatory behavior is caused by the destabilization of a steady spike pattern due to the creation of a new spike arising from endogeneous activator production. We demonstrate that on the edge of this instability, the period of the oscillations goes to infinity, although it does not fit the profile of any well-known bifurcation of a limit cycle. We show that nearby stationary states are either Turing unstable or undergo saddle-node bifurcations near the onset of the oscillatory instability, suggesting that the periodic motion does not emerge from a local equilibrium. We demonstrate the robustness of this spatiotemporal oscillation by exploring small localized heterogeneity and showing that this behavior also occurs in the Schnakenberg RD model. Our results suggest that this phenomenon is ubiquitous in spatially heterogeneous RD systems, but that current tools, such as stability of spike solutions and shadow-limit asymptotics, do not elucidate understanding. This opens several avenues for further mathematical analysis and highlights difficulties in explaining how robust patterning emerges from Turing's mechanism in the presence of even small spatial heterogeneity.

Power Management in Regenerative Life Support Systems

NASA Technical Reports Server (NTRS)

Crawford, Sekou; Pawlowski, Christopher; Finn, Cory; Mead, Susan C. (Technical Monitor)

1999-01-01

Effective management of power can reduce the cost of launch and operation of regenerative life support systems. Variations in power may be quite severe and may manifest as surges or spikes, While the power plant may have some ability to deal with these variations, with batteries for example, over-capacity is expensive and does nothing to address the fundamental issue of excessive demand. Because the power unit must be sized to accommodate the largest demand, avoiding power spikes has the potential to reduce the required size of the power plant while at the same time increasing the dependability of the system. Scheduling of processors can help to reduce potential power spikes. However, not all power-consuming equipment is easily scheduled. Therefore, active power management is needed to further decrease the risk of surges or spikes. We investigate the use of a hierarchical scheme to actively manage power for a model of a regenerative life support system. Local level controllers individually determine subsystem power usage. A higher level controller monitors overall system power and detects surges or spikes. When a surge condition is detected, the higher level controller conducts an 'auction' and describes subsystem power usage to re-allocate power. The result is an overall reduction in total power during a power surge. The auction involves each subsystem making a 'bid' to buy or sell power based on local needs. However, this re-allocation cannot come at the expense of life support function. To this end, participation in the auction is restricted to those processes meeting certain tolerance constraints. These tolerances represent acceptable limits within which system processes can be operated. We present a simulation model and discuss some of our results.

Reduced gamma frequency in the medial frontal cortex of aged rats during behavior and rest: implications for age-related behavioral slowing

PubMed Central

Insel, Nathan; Patron, Lilian A.; Hoang, Lan T.; Nematollahi, Saman; Schimanski, Lesley A.; Lipa, Peter; Barnes, Carol A.

2012-01-01

Age-related cognitive and behavioral slowing may be caused by changes in the speed of neural signaling or by changes in the number of signaling steps necessary to achieve a given function. In the mammalian cortex, neural communication is organized by a 30–100 Hz “gamma” oscillation. There is a putative link between the gamma frequency and the speed of processing in a neural network: the dynamics of pyramidal neuron membrane time constants suggest that synaptic integration is framed by the gamma cycle, and pharmacological slowing of gamma also slows reaction times on behavioral tasks. The present experiments identify reductions in a robust 40–70 Hz gamma oscillation in the aged rat medial frontal cortex. The reductions were observed in the form of local field potentials (LFPs), later peaks in fast-spiking neuron autocorrelations, and delays in the spiking of inhibitory neurons following local excitatory signals. Gamma frequency did not vary with movement speed, but rats with slower gamma also moved more slowly. Gamma frequency age differences were not observed in hippocampus. Hippocampal CA1 fast-spiking neurons exhibited inter-spike intervals consistent with a fast (70–100 Hz) gamma frequency, a pattern maintained across theta phases and theta frequencies independent of fluctuations in the neurons’ average firing rates. We propose that an average lengthening of the cortical 15–25 ms gamma cycle is one factor contributing to age-related slowing, and that future attempts to offset cognitive declines will find a target in the response of fast-spiking inhibitory neurons to excitatory inputs. PMID:23152616

Feedforward and feedback inhibition in neostriatal GABAergic spiny neurons.

PubMed

Tepper, James M; Wilson, Charles J; Koós, Tibor

2008-08-01

There are two distinct inhibitory GABAergic circuits in the neostriatum. The feedforward circuit consists of a relatively small population of GABAergic interneurons that receives excitatory input from the neocortex and exerts monosynaptic inhibition onto striatal spiny projection neurons. The feedback circuit comprises the numerous spiny projection neurons and their interconnections via local axon collaterals. This network has long been assumed to provide the majority of striatal GABAergic inhibition and to sharpen and shape striatal output through lateral inhibition, producing increased activity in the most strongly excited spiny cells at the expense of their less strongly excited neighbors. Recent results, mostly from recording experiments of synaptically connected pairs of neurons, have revealed that the two GABAergic circuits differ markedly in terms of the total number of synapses made by each, the strength of the postsynaptic response detected at the soma, the extent of presynaptic convergence and divergence and the net effect of the activation of each circuit on the postsynaptic activity of the spiny neuron. These data have revealed that the feedforward inhibition is powerful and widespread, with spiking in a single interneuron being capable of significantly delaying or even blocking the generation of spikes in a large number of postsynaptic spiny neurons. In contrast, the postsynaptic effects of spiking in a single presynaptic spiny neuron on postsynaptic spiny neurons are weak when measured at the soma, and unable to significantly affect spike timing or generation. Further, reciprocity of synaptic connections between spiny neurons is only rarely observed. These results suggest that the bulk of the fast inhibition that has the strongest effects on spiny neuron spike timing comes from the feedforward interneuronal system whereas the axon collateral feedback system acts principally at the dendrites to control local excitability as well as the overall level of activity of the spiny neuron.

Nonlinear dynamics of a pulse-coupled neural oscillator model of orientation tuning in the visual cortex

NASA Astrophysics Data System (ADS)

Bressloff, P. C.; Bressloff, N. W.

2000-02-01

Orientation tuning in a ring of pulse-coupled integrate-and-fire (IF) neurons is analyzed in terms of spontaneous pattern formation. It is shown how the ring bifurcates from a synchronous state to a non-phase-locked state whose spike trains are characterized by quasiperiodic variations of the inter-spike intervals (ISIs) on closed invariant circles. The separation of these invariant circles in phase space results in a localized peak of activity as measured by the time-averaged firing rate of the neurons. This generates a sharp orientation tuning curve that can lock to a slowly rotating, weakly tuned external stimulus. For fast synapses, breakup of the quasiperiodic orbits occurs leading to high spike time variability suggestive of chaos.

Different pools of glutamate receptors mediate sensitivity to ambient glutamate in the cochlear nucleus

PubMed Central

Yang, Yang

2015-01-01

Ambient glutamate plays an important role in pathological conditions, such as stroke, but its role during normal activity is not clear. In addition, it is not clear how ambient glutamate acts on glutamate receptors with varying affinities or subcellular localizations. To address this, we studied “endbulb of Held” synapses, which are formed by auditory nerve fibers onto bushy cells (BCs) in the anteroventral cochlear nucleus. When ambient glutamate was increased by applying the glutamate reuptake inhibitor TFB-TBOA, BCs depolarized as a result of activation of N-methyl-d-aspartate receptors (NMDARs) and group I metabotropic glutamate receptors (mGluRs). Application of antagonists against NMDARs (in 0 Mg2+) or mGluRs caused hyperpolarization, indicating that these receptors were bound by a tonic source of glutamate. AMPA receptors did not show these effects, consistent with their lower glutamate affinity. We also evaluated the subcellular localization of the receptors activated by ambient glutamate. The mGluRs were not activated by synaptic stimulation and thus appear to be exclusively extrasynaptic. By contrast, NMDARs in both synaptic and extrasynaptic compartments were activated by ambient glutamate, as shown using the use-dependent antagonist MK-801. Levels of ambient glutamate appeared to be regulated in a spike-independent manner, and glia likely play a major role. These low levels of ambient glutamate likely have functional consequences, as even low concentrations of TBOA caused significant increases in BC spiking following synaptic stimulation. These results indicate that normal resting potential appears to be poised in the region of maximal sensitivity to small changes in ambient glutamate. PMID:25855696

Exact subthreshold integration with continuous spike times in discrete-time neural network simulations.

PubMed

Morrison, Abigail; Straube, Sirko; Plesser, Hans Ekkehard; Diesmann, Markus

2007-01-01

Very large networks of spiking neurons can be simulated efficiently in parallel under the constraint that spike times are bound to an equidistant time grid. Within this scheme, the subthreshold dynamics of a wide class of integrate-and-fire-type neuron models can be integrated exactly from one grid point to the next. However, the loss in accuracy caused by restricting spike times to the grid can have undesirable consequences, which has led to interest in interpolating spike times between the grid points to retrieve an adequate representation of network dynamics. We demonstrate that the exact integration scheme can be combined naturally with off-grid spike events found by interpolation. We show that by exploiting the existence of a minimal synaptic propagation delay, the need for a central event queue is removed, so that the precision of event-driven simulation on the level of single neurons is combined with the efficiency of time-driven global scheduling. Further, for neuron models with linear subthreshold dynamics, even local event queuing can be avoided, resulting in much greater efficiency on the single-neuron level. These ideas are exemplified by two implementations of a widely used neuron model. We present a measure for the efficiency of network simulations in terms of their integration error and show that for a wide range of input spike rates, the novel techniques we present are both more accurate and faster than standard techniques.

SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

PubMed

Pastore, Vito Paolo; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

2018-01-01

We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with Microsoft Visual Studio based on .NET framework 4.5 development environment. Accepted input data formats are HDF5, level 5 MAT and text files, containing recorded or generated time series spike signals data. SPICODYN processes such electrophysiological signals focusing on: spiking and bursting dynamics and functional-effective connectivity analysis. In particular, for inferring network connectivity, a new implementation of the transfer entropy method is presented dealing with multiple time delays (temporal extension) and with multiple binary patterns (high order extension). SPICODYN is specifically tailored to process data coming from different Multi-Electrode Arrays setups, guarantying, in those specific cases, automated processing. The optimized implementation of the Delayed Transfer Entropy and the High-Order Transfer Entropy algorithms, allows performing accurate and rapid analysis on multiple spike trains from thousands of electrodes.

Frequency and time properties of decimeter narrowband spikes in solar flares

NASA Astrophysics Data System (ADS)

Wang, Shujuan

2013-07-01

In this paper, we focus to study the frequency and time properties of a group of spikes recorded by the 1.08-2.04 GHz spectrometer of NAOC on 27 October 2003. At the first we calculate the mean and minimum bandwidth of the spikes. We apply two different methods based on the wavelet analysis according to Messmer & Benz (2000). The first method determines the dominant spike bandwidth scale based on their scalegram, and the second method is a feature detection algorithm in the time-frequency plane. Secondly the time profile of each single spike was fitted and analyzed. In particular, we determined the e-folding rise and decay times corresponding to the ascending and decaying parts of the time profile, respectively. Several important correlations were studied and compared with the results in earlier literature, i.e. those between duration and frequency, e-folding rise time and decay time, e-folding decay time and duration, and e-folding decay time and peak flux. Finally some parameters of source region were estimated and the possible decaying mechanism was discussed.

Simulation of networks of spiking neurons: A review of tools and strategies

PubMed Central

Brette, Romain; Rudolph, Michelle; Carnevale, Ted; Hines, Michael; Beeman, David; Bower, James M.; Diesmann, Markus; Morrison, Abigail; Goodman, Philip H.; Harris, Frederick C.; Zirpe, Milind; Natschläger, Thomas; Pecevski, Dejan; Ermentrout, Bard; Djurfeldt, Mikael; Lansner, Anders; Rochel, Olivier; Vieville, Thierry; Muller, Eilif; Davison, Andrew P.; El Boustani, Sami

2009-01-01

We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin–Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks. PMID:17629781

Generation and characterization of ultra-short electron beams for single spike infrared FEL radiation at SPARC_LAB

NASA Astrophysics Data System (ADS)

Villa, F.; Anania, M. P.; Artioli, M.; Bacci, A.; Bellaveglia, M.; Bisesto, F. G.; Biagioni, A.; Carpanese, M.; Cardelli, F.; Castorina, G.; Chiadroni, E.; Cianchi, A.; Ciocci, F.; Croia, M.; Curcio, A.; Dattoli, G.; Gallo, A.; Di Giovenale, D.; Di Palma, E.; Di Pirro, G.; Ferrario, M.; Filippi, F.; Giannessi, L.; Giribono, A.; Marocchino, A.; Massimo, F.; Mostacci, A.; Petralia, A.; Petrarca, M.; Petrillo, V.; Piersanti, L.; Pioli, S.; Pompili, R.; Romeo, S.; Rossi, A. R.; Scifo, J.; Shpakov, V.; Vaccarezza, C.

2017-09-01

The technique for producing and measuring few tens of femtosecond electron beams, and the consequent generation of few tens femtoseconds single spike FEL radiation pulses at SPARC_LAB is presented. The undulator has been used in the double role of radiation source and diagnostic tool for the characterization of the electron beam. The connection between the electron bunch length and the radiation bandwidth is analyzed.

Combining EEG and MEG for the Reconstruction of Epileptic Activity Using a Calibrated Realistic Volume Conductor Model

PubMed Central

Aydin, Ümit; Vorwerk, Johannes; Küpper, Philipp; Heers, Marcel; Kugel, Harald; Galka, Andreas; Hamid, Laith; Wellmer, Jörg; Kellinghaus, Christoph; Rampp, Stefan; Wolters, Carsten Hermann

2014-01-01

To increase the reliability for the non-invasive determination of the irritative zone in presurgical epilepsy diagnosis, we introduce here a new experimental and methodological source analysis pipeline that combines the complementary information in EEG and MEG, and apply it to data from a patient, suffering from refractory focal epilepsy. Skull conductivity parameters in a six compartment finite element head model with brain anisotropy, constructed from individual MRI data, are estimated in a calibration procedure using somatosensory evoked potential (SEP) and field (SEF) data. These data are measured in a single run before acquisition of further runs of spontaneous epileptic activity. Our results show that even for single interictal spikes, volume conduction effects dominate over noise and need to be taken into account for accurate source analysis. While cerebrospinal fluid and brain anisotropy influence both modalities, only EEG is sensitive to skull conductivity and conductivity calibration significantly reduces the difference in especially depth localization of both modalities, emphasizing its importance for combining EEG and MEG source analysis. On the other hand, localization differences which are due to the distinct sensitivity profiles of EEG and MEG persist. In case of a moderate error in skull conductivity, combined source analysis results can still profit from the different sensitivity profiles of EEG and MEG to accurately determine location, orientation and strength of the underlying sources. On the other side, significant errors in skull modeling are reflected in EEG reconstruction errors and could reduce the goodness of fit to combined datasets. For combined EEG and MEG source analysis, we therefore recommend calibrating skull conductivity using additionally acquired SEP/SEF data. PMID:24671208

Importance of vesicle release stochasticity in neuro-spike communication.

PubMed

Ramezani, Hamideh; Akan, Ozgur B

2017-07-01

Aim of this paper is proposing a stochastic model for vesicle release process, a part of neuro-spike communication. Hence, we study biological events occurring in this process and use microphysiological simulations to observe functionality of these events. Since the most important source of variability in vesicle release probability is opening of voltage dependent calcium channels (VDCCs) followed by influx of calcium ions through these channels, we propose a stochastic model for this event, while using a deterministic model for other variability sources. To capture the stochasticity of calcium influx to pre-synaptic neuron in our model, we study its statistics and find that it can be modeled by a distribution defined based on Normal and Logistic distributions.

[Quantitative evaluation of inhibitory effects of epileptic spikes on theta rhythms in the network of hippocampal CA3 and entorhinal cortex in patients with temporal lobe epilepsy].

PubMed

Ge, Man-Ling; Guo, Jun-Dan; Chen, Sheng-Hua; Zhang, Ji-Chang; Fu, Xiao-Xuan; Chen, Yu-Min

2017-02-25

Epileptic spike is an indicator of hyper-excitability and hyper-synchrony in the neural networks. The inhibitory effects of spikes on theta rhythms (4-8 Hz) might be helpful to understand the mechanism of epileptic damage on the cognitive functions. To quantitatively evaluate the inhibitory effects of spikes on theta rhythms, intracerebral electroencephalogram (EEG) recordings with both sporadic spikes (SSs) and spike-free transient period between adjacent spikes were selected in 4 patients in the status of rapid eyes movement (REM) sleep with temporal lobe epilepsy (TLE) under the pre-surgical monitoring. The electrodes of hippocampal CA3 and entorhinal cortex (EC) were employed, since CA3 and EC built up one of key loops to investigate cognition and epilepsy. These SSs occurred only in CA3, only in EC, or in both CA3 and EC synchronously. Theta power was respectively estimated around SSs and during the spike-free transient period by Gabor wavelet transform and Hilbert transform. The intermittent extent was then estimated to represent for the loss of theta rhythms during the spike-free transient period. The following findings were obtained: (1) The prominent rhythms were in theta frequency band; (2) The spikes could transiently reduce theta power, and the inhibitory effect was severer around SSs in both CA3 and EC synchronously than that around either SSs only in EC or SSs only in CA3; (3) During the spike-free transient period, theta rhythms were interrupted with the intermittent theta rhythms left and theta power level continued dropping, implying the inhibitory effect was sustained. Additionally, the intermittent extent of theta rhythms was converged to the inhibitory extent around SSs; (4) The average theta power level during the spike-free transient period might not be in line with the inhibitory extent of theta rhythms around SSs. It was concluded that the SSs had negative effects on theta rhythms transiently and directly, the inhibitory effects aroused by SSs sustained during the spike-free transient period and were directly related to the intermittent extent. It was indicated that the loss of theta rhythms might qualify exactly the sustained inhibitory effects on theta rhythms aroused by spikes in EEG. The work provided an argumentation about the relationship between the transient negative impact of interictal spike and the loss of theta rhythms during spike-free activity for the first time, offered an intuitive methodology to estimate the inhibitory effect of spikes by EEG, and might be helpful to the analysis of EEG rhythms based on local field potentials (LFPs) in deep brain.

Effects of non-local electron transport in one-dimensional and two-dimensional simulations of shock-ignited inertial confinement fusion targets

NASA Astrophysics Data System (ADS)

Marocchino, A.; Atzeni, S.; Schiavi, A.

2014-01-01

In some regions of a laser driven inertial fusion target, the electron mean-free path can become comparable to or even longer than the electron temperature gradient scale-length. This can be particularly important in shock-ignited (SI) targets, where the laser-spike heated corona reaches temperatures of several keV. In this case, thermal conduction cannot be described by a simple local conductivity model and a Fick's law. Fluid codes usually employ flux-limited conduction models, which preserve causality, but lose important features of the thermal flow. A more accurate thermal flow modeling requires convolution-like non-local operators. In order to improve the simulation of SI targets, the non-local electron transport operator proposed by Schurtz-Nicolaï-Busquet [G. P. Schurtz et al., Phys. Plasmas 7, 4238 (2000)] has been implemented in the DUED fluid code. Both one-dimensional (1D) and two-dimensional (2D) simulations of SI targets have been performed. 1D simulations of the ablation phase highlight that while the shock profile and timing might be mocked up with a flux-limiter; the electron temperature profiles exhibit a relatively different behavior with no major effects on the final gain. The spike, instead, can only roughly be reproduced with a fixed flux-limiter value. 1D target gain is however unaffected, provided some minor tuning of laser pulses. 2D simulations show that the use of a non-local thermal conduction model does not affect the robustness to mispositioning of targets driven by quasi-uniform laser irradiation. 2D simulations performed with only two final polar intense spikes yield encouraging results and support further studies.

Autaptic pacemaker mediated propagation of weak rhythmic activity across small-world neuronal networks

NASA Astrophysics Data System (ADS)

Yilmaz, Ergin; Baysal, Veli; Ozer, Mahmut; Perc, Matjaž

2016-02-01

We study the effects of an autapse, which is mathematically described as a self-feedback loop, on the propagation of weak, localized pacemaker activity across a Newman-Watts small-world network consisting of stochastic Hodgkin-Huxley neurons. We consider that only the pacemaker neuron, which is stimulated by a subthreshold periodic signal, has an electrical autapse that is characterized by a coupling strength and a delay time. We focus on the impact of the coupling strength, the network structure, the properties of the weak periodic stimulus, and the properties of the autapse on the transmission of localized pacemaker activity. Obtained results indicate the existence of optimal channel noise intensity for the propagation of the localized rhythm. Under optimal conditions, the autapse can significantly improve the propagation of pacemaker activity, but only for a specific range of the autaptic coupling strength. Moreover, the autaptic delay time has to be equal to the intrinsic oscillation period of the Hodgkin-Huxley neuron or its integer multiples. We analyze the inter-spike interval histogram and show that the autapse enhances or suppresses the propagation of the localized rhythm by increasing or decreasing the phase locking between the spiking of the pacemaker neuron and the weak periodic signal. In particular, when the autaptic delay time is equal to the intrinsic period of oscillations an optimal phase locking takes place, resulting in a dominant time scale of the spiking activity. We also investigate the effects of the network structure and the coupling strength on the propagation of pacemaker activity. We find that there exist an optimal coupling strength and an optimal network structure that together warrant an optimal propagation of the localized rhythm.

Neurophysiological analytics for all! Free open-source software tools for documenting, analyzing, visualizing, and sharing using electronic notebooks.

PubMed

Rosenberg, David M; Horn, Charles C

2016-08-01

Neurophysiology requires an extensive workflow of information analysis routines, which often includes incompatible proprietary software, introducing limitations based on financial costs, transfer of data between platforms, and the ability to share. An ecosystem of free open-source software exists to fill these gaps, including thousands of analysis and plotting packages written in Python and R, which can be implemented in a sharable and reproducible format, such as the Jupyter electronic notebook. This tool chain can largely replace current routines by importing data, producing analyses, and generating publication-quality graphics. An electronic notebook like Jupyter allows these analyses, along with documentation of procedures, to display locally or remotely in an internet browser, which can be saved as an HTML, PDF, or other file format for sharing with team members and the scientific community. The present report illustrates these methods using data from electrophysiological recordings of the musk shrew vagus-a model system to investigate gut-brain communication, for example, in cancer chemotherapy-induced emesis. We show methods for spike sorting (including statistical validation), spike train analysis, and analysis of compound action potentials in notebooks. Raw data and code are available from notebooks in data supplements or from an executable online version, which replicates all analyses without installing software-an implementation of reproducible research. This demonstrates the promise of combining disparate analyses into one platform, along with the ease of sharing this work. In an age of diverse, high-throughput computational workflows, this methodology can increase efficiency, transparency, and the collaborative potential of neurophysiological research. Copyright © 2016 the American Physiological Society.

Altered brain functional connectivity induced by physical exercise may improve neuropsychological functions in patients with benign epilepsy.

PubMed

Koirala, Gyan Raj; Lee, Dongpyo; Eom, Soyong; Kim, Nam-Young; Kim, Heung Dong

2017-11-01

The objective of this study was to elucidate alteration in functional connectivity (FC) in patients with benign epilepsy with centrotemporal spikes (BECTS) as induced by physical exercise therapy and their correlation to the neuropsychological (NP) functions. We analyzed 115 artifact- and spike-free 2-second epochs extracted from resting state EEG recordings before and after 5weeks of physical exercise in eight patients with BECTS. The exact Low Resolution Electromagnetic Tomography (eLORETA) was used for source reconstruction. We evaluated the cortical current source density (CSD) power across five different frequency bands (delta, theta, alpha, beta, and gamma). Altered FC between 34 regions of interests (ROIs) was then examined using lagged phase synchronization (LPS) method. We further investigated the correlation between the altered FC measures and the changes in NP test scores. We observed changes in CSD power following the exercise for all frequency bands and statistically significant increases in the right temporal region for the alpha band. There were a number of altered FC between the cortical ROIs in all frequency bands of interest. Furthermore, significant correlations were observed between FC measures and NP test scores at theta and alpha bands. The increased localization power at alpha band may be an indication of the positive impact of exercise in patients with BECTS. Frequency band-specific alterations in FC among cortical regions were associated with the modulation of cognitive and NP functions. The significant correlation between FC and NP tests suggests that physical exercise may mitigate the severity of BECTS, thereby enhancing NP function. Copyright © 2017 Elsevier Inc. All rights reserved.

Neurophysiological analytics for all! Free open-source software tools for documenting, analyzing, visualizing, and sharing using electronic notebooks

PubMed Central

2016-01-01

Neurophysiology requires an extensive workflow of information analysis routines, which often includes incompatible proprietary software, introducing limitations based on financial costs, transfer of data between platforms, and the ability to share. An ecosystem of free open-source software exists to fill these gaps, including thousands of analysis and plotting packages written in Python and R, which can be implemented in a sharable and reproducible format, such as the Jupyter electronic notebook. This tool chain can largely replace current routines by importing data, producing analyses, and generating publication-quality graphics. An electronic notebook like Jupyter allows these analyses, along with documentation of procedures, to display locally or remotely in an internet browser, which can be saved as an HTML, PDF, or other file format for sharing with team members and the scientific community. The present report illustrates these methods using data from electrophysiological recordings of the musk shrew vagus—a model system to investigate gut-brain communication, for example, in cancer chemotherapy-induced emesis. We show methods for spike sorting (including statistical validation), spike train analysis, and analysis of compound action potentials in notebooks. Raw data and code are available from notebooks in data supplements or from an executable online version, which replicates all analyses without installing software—an implementation of reproducible research. This demonstrates the promise of combining disparate analyses into one platform, along with the ease of sharing this work. In an age of diverse, high-throughput computational workflows, this methodology can increase efficiency, transparency, and the collaborative potential of neurophysiological research. PMID:27098025

High voltage MOSFET switching circuit

DOEpatents

McEwan, T.E.

1994-07-26

The problem of source lead inductance in a MOSFET switching circuit is compensated for by adding an inductor to the gate circuit. The gate circuit inductor produces an inductive spike which counters the source lead inductive drop to produce a rectangular drive voltage waveform at the internal gate-source terminals of the MOSFET. 2 figs.

Optimal sparse approximation with integrate and fire neurons.

PubMed

Shapero, Samuel; Zhu, Mengchen; Hasler, Jennifer; Rozell, Christopher

2014-08-01

Sparse approximation is a hypothesized coding strategy where a population of sensory neurons (e.g. V1) encodes a stimulus using as few active neurons as possible. We present the Spiking LCA (locally competitive algorithm), a rate encoded Spiking Neural Network (SNN) of integrate and fire neurons that calculate sparse approximations. The Spiking LCA is designed to be equivalent to the nonspiking LCA, an analog dynamical system that converges on a ℓ(1)-norm sparse approximations exponentially. We show that the firing rate of the Spiking LCA converges on the same solution as the analog LCA, with an error inversely proportional to the sampling time. We simulate in NEURON a network of 128 neuron pairs that encode 8 × 8 pixel image patches, demonstrating that the network converges to nearly optimal encodings within 20 ms of biological time. We also show that when using more biophysically realistic parameters in the neurons, the gain function encourages additional ℓ(0)-norm sparsity in the encoding, relative both to ideal neurons and digital solvers.

Robust transmission of rate coding in the inhibitory Purkinje cell to cerebellar nuclei pathway in awake mice

PubMed Central

Abbasi, Samira; Maran, Selva K.; Cao, Ying; Abbasi, Ataollah; Heck, Detlef H.

2017-01-01

Neural coding through inhibitory projection pathways remains poorly understood. We analyze the transmission properties of the Purkinje cell (PC) to cerebellar nucleus (CN) pathway in a modeling study using a data set recorded in awake mice containing respiratory rate modulation. We find that inhibitory transmission from tonically active PCs can transmit a behavioral rate code with high fidelity. We parameterized the required population code in PC activity and determined that 20% of PC inputs to a full compartmental CN neuron model need to be rate-comodulated for transmission of a rate code. Rate covariance in PC inputs also accounts for the high coefficient of variation in CN spike trains, while the balance between excitation and inhibition determines spike rate and local spike train variability. Overall, our modeling study can fully account for observed spike train properties of cerebellar output in awake mice, and strongly supports rate coding in the cerebellum. PMID:28617798

Parameter estimation in spiking neural networks: a reverse-engineering approach.

PubMed

Rostro-Gonzalez, H; Cessac, B; Vieville, T

2012-04-01

This paper presents a reverse engineering approach for parameter estimation in spiking neural networks (SNNs). We consider the deterministic evolution of a time-discretized network with spiking neurons, where synaptic transmission has delays, modeled as a neural network of the generalized integrate and fire type. Our approach aims at by-passing the fact that the parameter estimation in SNN results in a non-deterministic polynomial-time hard problem when delays are to be considered. Here, this assumption has been reformulated as a linear programming (LP) problem in order to perform the solution in a polynomial time. Besides, the LP problem formulation makes the fact that the reverse engineering of a neural network can be performed from the observation of the spike times explicit. Furthermore, we point out how the LP adjustment mechanism is local to each neuron and has the same structure as a 'Hebbian' rule. Finally, we present a generalization of this approach to the design of input-output (I/O) transformations as a practical method to 'program' a spiking network, i.e. find a set of parameters allowing us to exactly reproduce the network output, given an input. Numerical verifications and illustrations are provided.

Standardized Methods to Generate Mock (Spiked) Clinical Specimens by Spiking Blood or Plasma with Cultured Pathogens

PubMed Central

Dong, Ming; Fisher, Carolyn; Añez, Germán; Rios, Maria; Nakhasi, Hira L.; Hobson, J. Peyton; Beanan, Maureen; Hockman, Donna; Grigorenko, Elena; Duncan, Robert

2016-01-01

Aims To demonstrate standardized methods for spiking pathogens into human matrices for evaluation and comparison among diagnostic platforms. Methods and Results This study presents detailed methods for spiking bacteria or protozoan parasites into whole blood and virus into plasma. Proper methods must start with a documented, reproducible pathogen source followed by steps that include standardized culture, preparation of cryopreserved aliquots, quantification of the aliquots by molecular methods, production of sufficient numbers of individual specimens and testing of the platform with multiple mock specimens. Results are presented following the described procedures that showed acceptable reproducibility comparing in-house real-time PCR assays to a commercially available multiplex molecular assay. Conclusions A step by step procedure has been described that can be followed by assay developers who are targeting low prevalence pathogens. Significance and Impact of Study The development of diagnostic platforms for detection of low prevalence pathogens such as biothreat or emerging agents is challenged by the lack of clinical specimens for performance evaluation. This deficit can be overcome using mock clinical specimens made by spiking cultured pathogens into human matrices. To facilitate evaluation and comparison among platforms, standardized methods must be followed in the preparation and application of spiked specimens. PMID:26835651

Evaluation of Lead Release in a Simulated Lead-Free Premise Plumbing System Using a Sequential Sampling Approach

PubMed Central

Ng, Ding-Quan; Lin, Yi-Pin

2016-01-01

In this pilot study, a modified sampling protocol was evaluated for the detection of lead contamination and locating the source of lead release in a simulated premise plumbing system with one-, three- and seven-day stagnation for a total period of 475 days. Copper pipes, stainless steel taps and brass fittings were used to assemble the “lead-free” system. Sequential sampling using 100 mL was used to detect lead contamination while that using 50 mL was used to locate the lead source. Elevated lead levels, far exceeding the World Health Organization (WHO) guideline value of 10 µg·L−1, persisted for as long as five months in the system. “Lead-free” brass fittings were identified as the source of lead contamination. Physical disturbances, such as renovation works, could cause short-term spikes in lead release. Orthophosphate was able to suppress total lead levels below 10 µg·L−1, but caused “blue water” problems. When orthophosphate addition was ceased, total lead levels began to spike within one week, implying that a continuous supply of orthophosphate was required to control total lead levels. Occasional total lead spikes were observed in one-day stagnation samples throughout the course of the experiments. PMID:26927154

Evaluation of Lead Release in a Simulated Lead-Free Premise Plumbing System Using a Sequential Sampling Approach.

PubMed

Ng, Ding-Quan; Lin, Yi-Pin

2016-02-27

In this pilot study, a modified sampling protocol was evaluated for the detection of lead contamination and locating the source of lead release in a simulated premise plumbing system with one-, three- and seven-day stagnation for a total period of 475 days. Copper pipes, stainless steel taps and brass fittings were used to assemble the "lead-free" system. Sequential sampling using 100 mL was used to detect lead contamination while that using 50 mL was used to locate the lead source. Elevated lead levels, far exceeding the World Health Organization (WHO) guideline value of 10 µg · L(-1), persisted for as long as five months in the system. "Lead-free" brass fittings were identified as the source of lead contamination. Physical disturbances, such as renovation works, could cause short-term spikes in lead release. Orthophosphate was able to suppress total lead levels below 10 µg · L(-1), but caused "blue water" problems. When orthophosphate addition was ceased, total lead levels began to spike within one week, implying that a continuous supply of orthophosphate was required to control total lead levels. Occasional total lead spikes were observed in one-day stagnation samples throughout the course of the experiments.

Stochastic IMT (Insulator-Metal-Transition) Neurons: An Interplay of Thermal and Threshold Noise at Bifurcation

PubMed Central

Parihar, Abhinav; Jerry, Matthew; Datta, Suman; Raychowdhury, Arijit

2018-01-01

Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Boltzmann machines and other stochastic neural networks have been shown to outperform their deterministic counterparts by allowing dynamical systems to escape local energy minima. Electronic implementation of such stochastic networks is currently limited to addition of algorithmic noise to digital machines which is inherently inefficient; albeit recent efforts to harness physical noise in devices for stochasticity have shown promise. To succeed in fabricating electronic neuromorphic networks we need experimental evidence of devices with measurable and controllable stochasticity which is complemented with the development of reliable statistical models of such observed stochasticity. Current research literature has sparse evidence of the former and a complete lack of the latter. This motivates the current article where we demonstrate a stochastic neuron using an insulator-metal-transition (IMT) device, based on electrically induced phase-transition, in series with a tunable resistance. We show that an IMT neuron has dynamics similar to a piecewise linear FitzHugh-Nagumo (FHN) neuron and incorporates all characteristics of a spiking neuron in the device phenomena. We experimentally demonstrate spontaneous stochastic spiking along with electrically controllable firing probabilities using Vanadium Dioxide (VO2) based IMT neurons which show a sigmoid-like transfer function. The stochastic spiking is explained by two noise sources - thermal noise and threshold fluctuations, which act as precursors of bifurcation. As such, the IMT neuron is modeled as an Ornstein-Uhlenbeck (OU) process with a fluctuating boundary resulting in transfer curves that closely match experiments. The moments of interspike intervals are calculated analytically by extending the first-passage-time (FPT) models for Ornstein-Uhlenbeck (OU) process to include a fluctuating boundary. We find that the coefficient of variation of interspike intervals depend on the relative proportion of thermal and threshold noise, where threshold noise is the dominant source in the current experimental demonstrations. As one of the first comprehensive studies of a stochastic neuron hardware and its statistical properties, this article would enable efficient implementation of a large class of neuro-mimetic networks and algorithms. PMID:29670508

Stochastic IMT (Insulator-Metal-Transition) Neurons: An Interplay of Thermal and Threshold Noise at Bifurcation.

PubMed

Parihar, Abhinav; Jerry, Matthew; Datta, Suman; Raychowdhury, Arijit

2018-01-01

Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Boltzmann machines and other stochastic neural networks have been shown to outperform their deterministic counterparts by allowing dynamical systems to escape local energy minima. Electronic implementation of such stochastic networks is currently limited to addition of algorithmic noise to digital machines which is inherently inefficient; albeit recent efforts to harness physical noise in devices for stochasticity have shown promise. To succeed in fabricating electronic neuromorphic networks we need experimental evidence of devices with measurable and controllable stochasticity which is complemented with the development of reliable statistical models of such observed stochasticity. Current research literature has sparse evidence of the former and a complete lack of the latter. This motivates the current article where we demonstrate a stochastic neuron using an insulator-metal-transition (IMT) device, based on electrically induced phase-transition, in series with a tunable resistance. We show that an IMT neuron has dynamics similar to a piecewise linear FitzHugh-Nagumo (FHN) neuron and incorporates all characteristics of a spiking neuron in the device phenomena. We experimentally demonstrate spontaneous stochastic spiking along with electrically controllable firing probabilities using Vanadium Dioxide (VO 2 ) based IMT neurons which show a sigmoid-like transfer function. The stochastic spiking is explained by two noise sources - thermal noise and threshold fluctuations, which act as precursors of bifurcation. As such, the IMT neuron is modeled as an Ornstein-Uhlenbeck (OU) process with a fluctuating boundary resulting in transfer curves that closely match experiments. The moments of interspike intervals are calculated analytically by extending the first-passage-time (FPT) models for Ornstein-Uhlenbeck (OU) process to include a fluctuating boundary. We find that the coefficient of variation of interspike intervals depend on the relative proportion of thermal and threshold noise, where threshold noise is the dominant source in the current experimental demonstrations. As one of the first comprehensive studies of a stochastic neuron hardware and its statistical properties, this article would enable efficient implementation of a large class of neuro-mimetic networks and algorithms.

Evaluating the quantity of native H2 in Enceladus' plumes with the Cassini-INMS closed source data: constraints from modeling of ice grains impact in the instrument

NASA Astrophysics Data System (ADS)

Bouquet, A.; Brockwell, T.; Waite, J. H., Jr.; Chocron, S.; Teolis, B. D.; Perryman, R.; Walker, J. D.

2016-12-01

The data from the closed source of the Cassini Ion and Neutral Mass Spectrometer (INMS) at Enceladus' plumes shows a signal of H2 in significant quantities (15% mole fraction for low speed flybys). H2 would be considered a "smoking gun" for the suspected hydrothermal activity in Enceladus' ocean. However the H2 quantity varies with the speed of the flyby, which is attributed to the presence of ice grains in the plumes hitting the walls of the titanium antechamber of INMS and exposing fresh titanium that may react with water to form hydrogen. The large number of small ice grains arriving during a single INMS integration period creates a back-ground signal in addition to large grains causing punctual spikes. We have developed a surface chemistry model of the INMS, taking into account adsorption and chemisorption of species of interest to determine how much H2 is produced from the expected ice grains distribution for each flyby (given by Cassini CAPS data ). CTH simulations have been used to assess the contribution of grains of different size in terms of titanium produced. We show that the spikes in the mass 2 channel can be explained by microns-sized grains, and that smaller grains (below 500 nm) are the major contributors to reactions with titanium, accounting for most of the non-spike signal. We find that the mass 2 background signal due to titanium is strongly driven by the water available, and therefore its shape versus time can't follow the sharp rises in the data (see Figure). This makes the structures seen in flyby E18 either the product of several big grains or the observation of locally high density of H2 (jets). We will analyze the effect of grains on other mass channels and comparison to CDA data to de-termine whether the peaks can be attributed to multiple ice grains or to native H2. The work will be extended to the E17 and E14 flybys to reach a definitive assessment of the native H2 abundance in the Enceladus plume.

Noise influence on spike activation in a Hindmarsh-Rose small-world neural network

NASA Astrophysics Data System (ADS)

Zhe, Sun; Micheletto, Ruggero

2016-07-01

We studied the role of noise in neural networks, especially focusing on its relation to the propagation of spike activity in a small sized system. We set up a source of information using a single neuron that is constantly spiking. This element called initiator x o feeds spikes to the rest of the network that is initially quiescent and subsequently reacts with vigorous spiking after a transitional period of time. We found that noise quickly suppresses the initiator’s influence and favors spontaneous spike activity and, using a decibel representation of noise intensity, we established a linear relationship between noise amplitude and the interval from the initiator’s first spike and the rest of the network activation. We studied the same process with networks of different sizes (number of neurons) and found that the initiator x o has a measurable influence on small networks, but as the network grows in size, spontaneous spiking emerges disrupting its effects on networks of more than about N = 100 neurons. This suggests that the mechanism of internal noise generation allows information transmission within a small neural neighborhood, but decays for bigger network domains. We also analyzed the Fourier spectrum of the whole network membrane potential and verified that noise provokes the reduction of main θ and α peaks before transitioning into chaotic spiking. However, network size does not reproduce a similar phenomena; instead we recorded a reduction in peaks’ amplitude, a better sharpness and definition of Fourier peaks, but not the evident degeneration to chaos observed with increasing external noise. This work aims to contribute to the understanding of the fundamental mechanisms of propagation of spontaneous spiking in neural networks and gives a quantitative assessment of how noise can be used to control and modulate this phenomenon in Hindmarsh-Rose (H-R) neural networks.

Attention improves memory by suppressing spiking-neuron activity in the human anterior temporal lobe.

PubMed

Wittig, John H; Jang, Anthony I; Cocjin, John B; Inati, Sara K; Zaghloul, Kareem A

2018-06-01

We identify a memory-specific attention mechanism in the human anterior temporal lobe, an area implicated in semantic processing and episodic memory formation. Spiking neuron activity is suppressed and becomes more reliable in preparation for verbal memory formation. Intracranial electroencephalography signals implicate this region as a source of executive control for attentional selection. Consistent with this interpretation, its surgical removal causes significant memory impairment for attended words relative to unattended words.

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

Anthony, Stephen

The Sandia hyperspectral upper-bound spectrum algorithm (hyper-UBS) is a cosmic ray despiking algorithm for hyperspectral data sets. When naturally-occurring, high-energy (gigaelectronvolt) cosmic rays impact the earth’s atmosphere, they create an avalanche of secondary particles which will register as a large, positive spike on any spectroscopic detector they hit. Cosmic ray spikes are therefore an unavoidable spectroscopic contaminant which can interfere with subsequent analysis. A variety of cosmic ray despiking algorithms already exist and can potentially be applied to hyperspectral data matrices, most notably the upper-bound spectrum data matrices (UBS-DM) algorithm by Dongmao Zhang and Dor Ben-Amotz which served as themore » basis for the hyper-UBS algorithm. However, the existing algorithms either cannot be applied to hyperspectral data, require information that is not always available, introduce undesired spectral bias, or have otherwise limited effectiveness for some experimentally relevant conditions. Hyper-UBS is more effective at removing a wider variety of cosmic ray spikes from hyperspectral data without introducing undesired spectral bias. In addition to the core algorithm the Sandia hyper-UBS software package includes additional source code useful in evaluating the effectiveness of the hyper-UBS algorithm. The accompanying source code includes code to generate simulated hyperspectral data contaminated by cosmic ray spikes, several existing despiking algorithms, and code to evaluate the performance of the despiking algorithms on simulated data.« less

Photospheric Current Spikes And Their Possible Association With Flares - Results from an HMI Data Driven Model

NASA Astrophysics Data System (ADS)

Goodman, M. L.; Kwan, C.; Ayhan, B.; Eric, S. L.

2016-12-01

A data driven, near photospheric magnetohydrodynamic model predicts spikes in the horizontal current density, and associated resistive heating rate. The spikes appear as increases by orders of magnitude above background values in neutral line regions (NLRs) of active regions (ARs). The largest spikes typically occur a few hours to a few days prior to M or X flares. The spikes correspond to large vertical derivatives of the horizontal magnetic field. The model takes as input the photospheric magnetic field observed by the Helioseismic & Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO) satellite. This 2.5 D field is used to determine an analytic expression for a 3 D magnetic field, from which the current density, vector potential, and electric field are computed in every AR pixel for 14 ARs. The field is not assumed to be force-free. The spurious 6, 12, and 24 hour Doppler periods due to SDO orbital motion are filtered out of the time series of the HMI magnetic field for each pixel. The subset of spikes analyzed at the pixel level are found to occur on HMI and granulation scales of 1 arcsec and 12 minutes. Spikes are found in ARs with and without M or X flares, and outside as well as inside NLRs, but the largest spikes are localized in the NLRs of ARs with M or X flares. The energy to drive the heating associated with the largest current spikes comes from bulk flow kinetic energy, not the electromagnetic field, and the current density is highly non-force free. The results suggest that, in combination with the model, HMI is revealing strong, convection driven, non-force free heating events on granulation scales, and it is plausible these events are correlated with subsequent M or X flares. More and longer time series need to be analyzed to determine if such a correlation exists.

Generation of stable subfemtosecond hard x-ray pulses with optimized nonlinear bunch compression

DOE PAGES

Huang, Senlin; Ding, Yuantao; Huang, Zhirong; ...

2014-12-15

In this paper, we propose a simple scheme that leverages existing x-ray free-electron laser hardware to produce stable single-spike, subfemtosecond x-ray pulses. By optimizing a high-harmonic radio-frequency linearizer to achieve nonlinear compression of a low-charge (20 pC) electron beam, we obtain a sharp current profile possessing a few-femtosecond full width at half maximum temporal duration. A reverse undulator taper is applied to enable lasing only within the current spike, where longitudinal space charge forces induce an electron beam time-energy chirp. Simulations based on the Linac Coherent Light Source parameters show that stable single-spike x-ray pulses with a duration less thanmore » 200 attoseconds can be obtained.« less

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks

PubMed Central

de Santos-Sierra, Daniel; Sanchez-Jimenez, Abel; Garcia-Vellisca, Mariano A.; Navas, Adrian; Villacorta-Atienza, Jose A.

2015-01-01

Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though, the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions (Pyragiene and Pyragas, 2013), where the slave neuron is able to anticipate in time the behavior of the master one. In this paper, we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI), one of the main features of the neural response associated with the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh–Rose neurons. PMID:26648863

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks.

PubMed

de Santos-Sierra, Daniel; Sanchez-Jimenez, Abel; Garcia-Vellisca, Mariano A; Navas, Adrian; Villacorta-Atienza, Jose A

2015-01-01

Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though, the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions (Pyragiene and Pyragas, 2013), where the slave neuron is able to anticipate in time the behavior of the master one. In this paper, we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI), one of the main features of the neural response associated with the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.

Modeling Whistler Wave Generation Regimes In Magnetospheric Cyclotron Maser

NASA Astrophysics Data System (ADS)

Pasmanik, D. L.; Demekhov, A. G.; Trakhtengerts, V. Y.; Parrot, M.

Numerical analysis of the model for cyclotron instability development in the Earth magnetosphere is made.This model, based on the self-consistent set of equations of quasi-linear plasma theory, describes different regimes of wave generation and related energetic particle precipitation. As the source of free energy the injection of energetic electrons with transverse anisotropic distribution function to the interaction region is considered. Two different mechanisms of energetic electron loss from the interaction region are discussed. The first one is precipitation of energetic particles via the loss cone. The other mechanism is drift of particles away from the interaction region across the mag- netic field line. In the case of interaction in plasmasphere or rather large areas of cold plasma density enhancement the loss cone precipitation are dominant. For interaction in a subauroral duct losses due to drift are most effective. A parametric study of the model for both mechanisms of particle losses is made. The main attention is paid to the analysis of generation regimes for different characteristics of energetic electron source, such as the shape of pitch-angle distributions and elec- tron density. We show that in addition to the well-known stationary generation and periodic regime with successive spikes of similar shape, more complex forms of wave spectrum exist. In particular, we found a periodic regime, in which a single period in- cludes two separate spikes with different spectral shapes. In another regime, periodic generation of spikes at higher frequencies together with quasi-stationary generation at lower frequencies occurs. Quasi-periodic regime with spike overlapping, i.e. when generation of a new spike begins before the previous one is over is also found. Results obtained are compared with experimental data on quasi-periodic regimes of whistler wave generation.

Sleep affects cortical source modularity in temporal lobe epilepsy: A high-density EEG study.

PubMed

Del Felice, Alessandra; Storti, Silvia Francesca; Manganotti, Paolo

2015-09-01

Interictal epileptiform discharges (IEDs) constitute a perturbation of ongoing cerebral rhythms, usually more frequent during sleep. The aim of the study was to determine whether sleep influences the spread of IEDs over the scalp and whether their distribution depends on vigilance-related modifications in cortical interactions. Wake and sleep 256-channel electroencephalography (EEG) data were recorded in 12 subjects with right temporal lobe epilepsy (TLE) differentiated by whether they had mesial or neocortical TLE. Spikes were selected during wake and sleep. The averaged waking signal was subtracted from the sleep signal and projected on a bidimensional scalp map; sleep and wake spike distributions were compared by using a t-test. The superimposed signal of sleep and wake traces was obtained; the rising phase of the spike, the peak, and the deflections following the spike were identified, and their cortical generator was calculated using low-resolution brain electromagnetic tomography (LORETA) for each group. A mean of 21 IEDs in wake and 39 in sleep per subject were selected. As compared to wake, a larger IED scalp projection was detected during sleep in both mesial and neocortical TLE (p<0.05). A series of EEG deflections followed the spike, the cortical sources of which displayed alternating activations of different cortical areas in wake, substituted by isolated, stationary activations in sleep in mesial TLE and a silencing in neocortical TLE. During sleep, the IED scalp region increases, while cortical interaction decreases. The interaction of cortical modules in sleep and wake in TLE may influence the appearance of IEDs on scalp EEG; in addition, IEDs could be proxies for cerebral oscillation perturbation. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Fast fMRI provides high statistical power in the analysis of epileptic networks.

PubMed

Jacobs, Julia; Stich, Julia; Zahneisen, Benjamin; Assländer, Jakob; Ramantani, Georgia; Schulze-Bonhage, Andreas; Korinthenberg, Rudolph; Hennig, Jürgen; LeVan, Pierre

2014-03-01

EEG-fMRI is a unique method to combine the high temporal resolution of EEG with the high spatial resolution of MRI to study generators of intrinsic brain signals such as sleep grapho-elements or epileptic spikes. While the standard EPI sequence in fMRI experiments has a temporal resolution of around 2.5-3s a newly established fast fMRI sequence called MREG (Magnetic-Resonance-Encephalography) provides a temporal resolution of around 100ms. This technical novelty promises to improve statistics, facilitate correction of physiological artifacts and improve the understanding of epileptic networks in fMRI. The present study compares simultaneous EEG-EPI and EEG-MREG analyzing epileptic spikes to determine the yield of fast MRI in the analysis of intrinsic brain signals. Patients with frequent interictal spikes (>3/20min) underwent EEG-MREG and EEG-EPI (3T, 20min each, voxel size 3×3×3mm, EPI TR=2.61s, MREG TR=0.1s). Timings of the spikes were used in an event-related analysis to generate activation maps of t-statistics. (FMRISTAT, |t|>3.5, cluster size: 7 voxels, p<0.05 corrected). For both sequences, the amplitude and location of significant BOLD activations were compared with the spike topography. 13 patients were recorded and 33 different spike types could be analyzed. Peak T-values were significantly higher in MREG than in EPI (p<0.0001). Positive BOLD effects correlating with the spike topography were found in 8/29 spike types using the EPI and in 22/33 spikes types using the MREG sequence. Negative BOLD responses in the default mode network could be observed in 3/29 spike types with the EPI and in 19/33 with the MREG sequence. With the latter method, BOLD changes were observed even when few spikes occurred during the investigation. Simultaneous EEG-MREG thus is possible with good EEG quality and shows higher sensitivity in regard to the localization of spike-related BOLD responses than EEG-EPI. The development of new methods of analysis for this sequence such as modeling of physiological noise, temporal analysis of the BOLD signal and defining appropriate thresholds is required to fully profit from its high temporal resolution. © 2013.

[Chromosomal localization of the speltoidy gene, introgressed into bread wheat from Aegilops speltoides Tausch., and its interaction with the Q gene of Triticum spelta L].

PubMed

Simonov, A V; Pshenichnikova, T A

2012-11-01

The differences between bread wheat (Triticum aestivum L.) and spelt (Triticum spelta L.) in the shape of the spike and threshing character are determined by the allelic status of one major Q gene, mapped to the long arm of chromosome 5A. This gene is a member of the APETALA2 family of transcription factors and plays an important role in domestication of wheat. In the present study, using monosomic analysis, we determined the chromosomal localization of the Q(S)gene, introgressed into bread wheat from Aegilops speltoides Tausch. and homoallelic to the Q gene. It was demonstrated that the Q(S) gene was located in chromosome 5A of the bread wheat line from the Arsenal collection. This gene conferred spike speltoidy in the line itself, as well as in its hybrids with bread wheat cultivars. The Q(S) gene dominated over the bread wheat Q gene and was equally effective in the homo-, hemi-, and heterozygous states. In hybrids between the introgression line and a number of spring spelt accessions, interaction between the Q and Q(S) genes was observed, manifested as the formation of superspeltoid spike.

Attention Influences Single Unit and Local Field Potential Response Latencies in Visual Cortical Area V4

PubMed Central

Sundberg, Kristy A.; Mitchell, Jude F.; Gawne, Timothy J.

2012-01-01

Many previous studies have demonstrated that changes in selective attention can alter the response magnitude of visual cortical neurons, but there has been little evidence for attention affecting response latency. Small latency differences, though hard to detect, can potentially be of functional importance, and may also give insight into the mechanisms of neuronal computation. We therefore reexamined the effect of attention on the response latency of both single units and the local field potential (LFP) in primate visual cortical area V4. We find that attention does produce small (1–2 ms) but significant reductions in the latency of both the spiking and LFP responses. Though attention, like contrast elevation, reduces response latencies, we find that the two have different effects on the magnitude of the LFP. Contrast elevations increase and attention decreases the magnitude of the initial deflection of the stimulus-evoked LFP. Both contrast elevation and attention increase the magnitude of the spiking response. We speculate that latencies may be reduced at higher contrast because stronger stimulus inputs drive neurons more rapidly to spiking threshold, while attention may reduce latencies by placing neurons in a more depolarized state closer to threshold before stimulus onset. PMID:23136440

Open source tools for the information theoretic analysis of neural data.

PubMed

Ince, Robin A A; Mazzoni, Alberto; Petersen, Rasmus S; Panzeri, Stefano

2010-01-01

The recent and rapid development of open source software tools for the analysis of neurophysiological datasets consisting of simultaneous multiple recordings of spikes, field potentials and other neural signals holds the promise for a significant advance in the standardization, transparency, quality, reproducibility and variety of techniques used to analyze neurophysiological data and for the integration of information obtained at different spatial and temporal scales. In this review we focus on recent advances in open source toolboxes for the information theoretic analysis of neural responses. We also present examples of their use to investigate the role of spike timing precision, correlations across neurons, and field potential fluctuations in the encoding of sensory information. These information toolboxes, available both in MATLAB and Python programming environments, hold the potential to enlarge the domain of application of information theory to neuroscience and to lead to new discoveries about how neurons encode and transmit information.

Local inhibition modulates learning-dependent song encoding in the songbird auditory cortex

PubMed Central

Thompson, Jason V.; Jeanne, James M.

2013-01-01

Changes in inhibition during development are well documented, but the role of inhibition in adult learning-related plasticity is not understood. In songbirds, vocal recognition learning alters the neural representation of songs across the auditory forebrain, including the caudomedial nidopallium (NCM), a region analogous to mammalian secondary auditory cortices. Here, we block local inhibition with the iontophoretic application of gabazine, while simultaneously measuring song-evoked spiking activity in NCM of European starlings trained to recognize sets of conspecific songs. We find that local inhibition differentially suppresses the responses to learned and unfamiliar songs and enhances spike-rate differences between learned categories of songs. These learning-dependent response patterns emerge, in part, through inhibitory modulation of selectivity for song components and the masking of responses to specific acoustic features without altering spectrotemporal tuning. The results describe a novel form of inhibitory modulation of the encoding of learned categories and demonstrate that inhibition plays a central role in shaping the responses of neurons to learned, natural signals. PMID:23155175

Classification of Neurons in the Primate Reticular Formation and Changes After Recovery From Pyramidal Tract Lesion.

PubMed

Zaaimi, Boubker; Soteropoulos, Demetris S; Fisher, Karen M; Riddle, C Nicholas; Baker, Stuart N

2018-05-23

The reticular formation is important in primate motor control, both in health and during recovery after brain damage. Little is known about the different neurons present in the reticular nuclei. Here we recorded extracellular spikes from the reticular formation in five healthy female awake behaving monkeys (193 cells), and in two female monkeys one year after recovery from a unilateral pyramidal tract lesion (125 cells). Analysis of spike shape, and four measures derived from the inter-spike interval distribution identified four clusters of neurons in control animals. Cluster 1 cells had slow firing rate; Cluster 2 had narrow spikes, and irregular firing which often included high frequency bursts. Cluster 3 were highly rhythmic and fast firing. Cluster 4 showed negative spikes. A separate population of 42 cells were antidromically identified as reticulospinal neurons in five anesthetized female monkeys. The distribution of spike width in these cells closely overlaid the distribution for cluster 2, leading us tentatively to suggest that cluster 2 included neurons with reticulospinal projections. In animals after corticospinal lesion, cells could be identified in all four clusters. The firing rate of cells in clusters 1 and 2 was increased in lesioned relative to control animals (by 52% and 60%, respectively); cells in cluster 2 were also more regular and more bursting in the lesioned animals. We suggest that changes in both membrane properties and local circuits within the reticular formation occur following lesion, potentially increasing reticulospinal output to help compensate for lost corticospinal descending drive. SIGNIFICANCE STATEMENT This work is the first to sub-classify neurons in the reticular formation, providing insights into the local circuitry of this important but little-understood structure. The approach developed can be applied to any extracellular recording from this region, allowing future studies to place their data within our current framework of four neural types. Changes in reticular neurons may be important to subserve functional recovery after damage in human patients, such as after stroke or spinal cord injury. Copyright © 2018 Zaaimi et al.

Associative spike timing-dependent potentiation of the basal dendritic excitatory synapses in the hippocampus in vivo.

PubMed

Fung, Thomas K; Law, Clayton S; Leung, L Stan

2016-06-01

Spike timing-dependent plasticity in the hippocampus has rarely been studied in vivo. Using extracellular potential and current source density analysis in urethane-anesthetized adult rats, we studied synaptic plasticity at the basal dendritic excitatory synapse in CA1 after excitation-spike (ES) pairing; E was a weak basal dendritic excitation evoked by stratum oriens stimulation, and S was a population spike evoked by stratum radiatum apical dendritic excitation. We hypothesize that positive ES pairing-generating synaptic excitation before a spike-results in long-term potentiation (LTP) while negative ES pairing results in long-term depression (LTD). Pairing (50 pairs at 5 Hz) at ES intervals of -10 to 0 ms resulted in significant input-specific LTP of the basal dendritic excitatory sink, lasting 60-120 min. Pairing at +10- to +20-ms ES intervals, or unpaired 5-Hz stimulation, did not induce significant basal dendritic or apical dendritic LTP or LTD. No basal dendritic LTD was found after stimulation of stratum oriens with 200 pairs of high-intensity pulses at 25-ms interval. Pairing-induced LTP was abolished by pretreatment with an N-methyl-d-aspartate receptor antagonist, 3-(2-carboxypiperazin-4-yl)-propyl-1-phosphonic acid (CPP), which also reduced spike bursting during 5-Hz pairing. Pairing at 0.5 Hz did not induce spike bursts or basal dendritic LTP. In conclusion, ES pairing at 5 Hz resulted in input-specific basal dendritic LTP at ES intervals of -10 ms to 0 ms but no LTD at ES intervals of -20 to +20 ms. Associative LTP likely occurred because of theta-rhythmic coincidence of subthreshold excitation with a backpropagated spike burst, which are conditions that can occur naturally in the hippocampus. Copyright © 2016 the American Physiological Society.

Local and global synchronization transitions induced by time delays in small-world neuronal networks with chemical synapses.

PubMed

Yu, Haitao; Wang, Jiang; Du, Jiwei; Deng, Bin; Wei, Xile

2015-02-01

Effects of time delay on the local and global synchronization in small-world neuronal networks with chemical synapses are investigated in this paper. Numerical results show that, for both excitatory and inhibitory coupling types, the information transmission delay can always induce synchronization transitions of spiking neurons in small-world networks. In particular, regions of in-phase and out-of-phase synchronization of connected neurons emerge intermittently as the synaptic delay increases. For excitatory coupling, all transitions to spiking synchronization occur approximately at integer multiples of the firing period of individual neurons; while for inhibitory coupling, these transitions appear at the odd multiples of the half of the firing period of neurons. More importantly, the local synchronization transition is more profound than the global synchronization transition, depending on the type of coupling synapse. For excitatory synapses, the local in-phase synchronization observed for some values of the delay also occur at a global scale; while for inhibitory ones, this synchronization, observed at the local scale, disappears at a global scale. Furthermore, the small-world structure can also affect the phase synchronization of neuronal networks. It is demonstrated that increasing the rewiring probability can always improve the global synchronization of neuronal activity, but has little effect on the local synchronization of neighboring neurons.

Ear-EEG detects ictal and interictal abnormalities in focal and generalized epilepsy - A comparison with scalp EEG monitoring.

PubMed

Zibrandtsen, I C; Kidmose, P; Christensen, C B; Kjaer, T W

2017-12-01

Ear-EEG is recording of electroencephalography from a small device in the ear. This is the first study to compare ictal and interictal abnormalities recorded with ear-EEG and simultaneous scalp-EEG in an epilepsy monitoring unit. We recorded and compared simultaneous ear-EEG and scalp-EEG from 15 patients with suspected temporal lobe epilepsy. EEGs were compared visually by independent neurophysiologists. Correlation and time-frequency analysis was used to quantify the similarity between ear and scalp electrodes. Spike-averages were used to assess similarity of interictal spikes. There were no differences in sensitivity or specificity for seizure detection. Mean correlation coefficient between ear-EEG and nearest scalp electrode was above 0.6 with a statistically significant decreasing trend with increasing distance away from the ear. Ictal morphology and frequency dynamics can be observed from visual inspection and time-frequency analysis. Spike averages derived from ear-EEG electrodes yield a recognizable spike appearance. Our results suggest that ear-EEG can reliably detect electroencephalographic patterns associated with focal temporal lobe seizures. Interictal spike morphology from sufficiently large temporal spike sources can be sampled using ear-EEG. Ear-EEG is likely to become an important tool in clinical epilepsy monitoring and diagnosis. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Neuronal correlates of ketamine and walking induced gamma oscillations in the medial prefrontal cortex and mediodorsal thalamus.

PubMed

Furth, Katrina E; McCoy, Alex J; Dodge, Caroline; Walters, Judith R; Buonanno, Andres; Delaville, Claire

2017-01-01

Alterations in the function of the medial prefrontal cortex (mPFC) and its major thalamic source of innervation, the mediodorsal (MD) thalamus, have been hypothesized to contribute to the symptoms of schizophrenia. The NMDAR antagonist ketamine, used to model schizophrenia, elicits a brain state resembling early stage schizophrenia characterized by cognitive deficits and increases in cortical low gamma (40-70 Hz) power. Here we sought to determine how ketamine differentially affects spiking and gamma local field potential (LFP) activity in the rat mPFC and MD thalamus. Additionally, we investigated the ability of drugs targeting the dopamine D4 receptor (D4R) to modify the effects of ketamine on gamma activity as a measure of potential cognitive therapeutic efficacy. Rats were trained to walk on a treadmill to reduce confounds related to hyperactivity after ketamine administration (10 mg/kg s.c.) while recordings were obtained from electrodes chronically implanted in the mPFC and MD thalamus. Ketamine increased gamma LFP power in mPFC and MD thalamus in a similar frequency range, yet did not increase thalamocortical synchronization. Ketamine also increased firing rates and spike synchronization to gamma oscillations in the mPFC but decreased both measures in MD thalamus. Conversely, walking alone increased both firing rates and spike-gamma LFP correlations in both mPFC and MD thalamus. The D4R antagonist alone (L-745,870) had no effect on gamma LFP power during treadmill walking, although it reversed increases induced by the D4R agonist (A-412997) in both mPFC and MD thalamus. Neither drug altered ketamine-induced changes in gamma power or firing rates in the mPFC. However, in MD thalamus, the D4R agonist increased ketamine-induced gamma power and prevented ketamine's inhibitory effect on firing rates. Results provide new evidence that ketamine differentially modulates spiking and gamma power in MD thalamus and mPFC, supporting a potential role for both areas in contributing to ketamine-induced schizophrenia-like symptoms.

Neuronal correlates of ketamine and walking induced gamma oscillations in the medial prefrontal cortex and mediodorsal thalamus

PubMed Central

McCoy, Alex J.; Dodge, Caroline; Walters, Judith R.; Buonanno, Andres; Delaville, Claire

2017-01-01

Alterations in the function of the medial prefrontal cortex (mPFC) and its major thalamic source of innervation, the mediodorsal (MD) thalamus, have been hypothesized to contribute to the symptoms of schizophrenia. The NMDAR antagonist ketamine, used to model schizophrenia, elicits a brain state resembling early stage schizophrenia characterized by cognitive deficits and increases in cortical low gamma (40–70 Hz) power. Here we sought to determine how ketamine differentially affects spiking and gamma local field potential (LFP) activity in the rat mPFC and MD thalamus. Additionally, we investigated the ability of drugs targeting the dopamine D4 receptor (D4R) to modify the effects of ketamine on gamma activity as a measure of potential cognitive therapeutic efficacy. Rats were trained to walk on a treadmill to reduce confounds related to hyperactivity after ketamine administration (10 mg/kg s.c.) while recordings were obtained from electrodes chronically implanted in the mPFC and MD thalamus. Ketamine increased gamma LFP power in mPFC and MD thalamus in a similar frequency range, yet did not increase thalamocortical synchronization. Ketamine also increased firing rates and spike synchronization to gamma oscillations in the mPFC but decreased both measures in MD thalamus. Conversely, walking alone increased both firing rates and spike-gamma LFP correlations in both mPFC and MD thalamus. The D4R antagonist alone (L-745,870) had no effect on gamma LFP power during treadmill walking, although it reversed increases induced by the D4R agonist (A-412997) in both mPFC and MD thalamus. Neither drug altered ketamine-induced changes in gamma power or firing rates in the mPFC. However, in MD thalamus, the D4R agonist increased ketamine-induced gamma power and prevented ketamine’s inhibitory effect on firing rates. Results provide new evidence that ketamine differentially modulates spiking and gamma power in MD thalamus and mPFC, supporting a potential role for both areas in contributing to ketamine-induced schizophrenia-like symptoms. PMID:29095852

Different pools of glutamate receptors mediate sensitivity to ambient glutamate in the cochlear nucleus.

PubMed

Yang, Yang; Xu-Friedman, Matthew A

2015-06-01

Ambient glutamate plays an important role in pathological conditions, such as stroke, but its role during normal activity is not clear. In addition, it is not clear how ambient glutamate acts on glutamate receptors with varying affinities or subcellular localizations. To address this, we studied "endbulb of Held" synapses, which are formed by auditory nerve fibers onto bushy cells (BCs) in the anteroventral cochlear nucleus. When ambient glutamate was increased by applying the glutamate reuptake inhibitor TFB-TBOA, BCs depolarized as a result of activation of N-methyl-D-aspartate receptors (NMDARs) and group I metabotropic glutamate receptors (mGluRs). Application of antagonists against NMDARs (in 0 Mg(2+)) or mGluRs caused hyperpolarization, indicating that these receptors were bound by a tonic source of glutamate. AMPA receptors did not show these effects, consistent with their lower glutamate affinity. We also evaluated the subcellular localization of the receptors activated by ambient glutamate. The mGluRs were not activated by synaptic stimulation and thus appear to be exclusively extrasynaptic. By contrast, NMDARs in both synaptic and extrasynaptic compartments were activated by ambient glutamate, as shown using the use-dependent antagonist MK-801. Levels of ambient glutamate appeared to be regulated in a spike-independent manner, and glia likely play a major role. These low levels of ambient glutamate likely have functional consequences, as even low concentrations of TBOA caused significant increases in BC spiking following synaptic stimulation. These results indicate that normal resting potential appears to be poised in the region of maximal sensitivity to small changes in ambient glutamate. Copyright © 2015 the American Physiological Society.

Effect of stimulus intensity on spike-LFP relationship in Secondary Somatosensory cortex

PubMed Central

Hsiao, Steven S.; Crone, Nathan E.; Franaszczuk, Piotr J.; Niebur, Ernst

2008-01-01

Neuronal oscillations in the gamma frequency range have been reported in many cortical areas, but the role they play in cortical processing remains unclear. We tested a recently proposed hypothesis that the intensity of sensory input is coded in the timing of action potentials relative to the phase of gamma oscillations, thus converting amplitude information to a temporal code. We recorded spikes and local field potential (LFP) from secondary somatosensory (SII) cortex in awake monkeys while presenting a vibratory stimulus at different amplitudes. We developed a novel technique based on matching pursuit to study the interaction between the highly transient gamma oscillations and spikes with high time-frequency resolution. We found that spikes were weakly coupled to LFP oscillations in the gamma frequency range (40−80 Hz), and strongly coupled to oscillations in higher gamma frequencies. However, the phase relationship of neither low-gamma nor high-gamma oscillations changed with stimulus intensity, even with a ten-fold increase. We conclude that, in SII, gamma oscillations are synchronized with spikes, but their phase does not vary with stimulus intensity. Furthermore, high-gamma oscillations (>60 Hz) appear to be closely linked to the occurrence of action potentials, suggesting that LFP high-gamma power could be a sensitive index of the population firing rate near the microelectrode. PMID:18632937

Synaptically activated Ca2+ waves and NMDA spikes locally suppress voltage-dependent Ca2+ signalling in rat pyramidal cell dendrites

PubMed Central

Manita, Satoshi; Miyazaki, Kenichi; Ross, William N

2011-01-01

Abstract Postsynaptic [Ca2+]i changes contribute to several kinds of plasticity in pyramidal neurons. We examined the effects of synaptically activated Ca2+ waves and NMDA spikes on subsequent Ca2+ signalling in CA1 pyramidal cell dendrites in hippocampal slices. Tetanic synaptic stimulation evoked a localized Ca2+ wave in the primary apical dendrites. The [Ca2+]i increase from a backpropagating action potential (bAP) or subthreshold depolarization was reduced if it was generated immediately after the wave. The suppression had a recovery time of 30–60 s. The suppression only occurred where the wave was generated and was not due to a change in bAP amplitude or shape. The suppression also could be generated by Ca2+ waves evoked by uncaging IP3, showing that other signalling pathways activated by the synaptic tetanus were not required. The suppression was proportional to the amplitude of the [Ca2+]i change of the Ca2+ wave and was not blocked by a spectrum of kinase or phosphatase inhibitors, consistent with suppression due to Ca2+-dependent inactivation of Ca2+ channels. The waves also reduced the frequency and amplitude of spontaneous, localized Ca2+ release events in the dendrites by a different mechanism, probably by depleting the stores at the site of wave generation. The same synaptic tetanus often evoked NMDA spike-mediated [Ca2+]i increases in the oblique dendrites where Ca2+ waves do not propagate. These NMDA spikes suppressed the [Ca2+]i increase caused by bAPs in those regions. [Ca2+]i increases by Ca2+ entry through voltage-gated Ca2+ channels also suppressed the [Ca2+]i increases from subsequent bAPs in regions where the voltage-gated [Ca2+]i increases were largest, showing that all ways of raising [Ca2+]i could cause suppression. PMID:21844002

The Analysis and Suppression of the spike noise in vibrator record

NASA Astrophysics Data System (ADS)

Jia, H.; Jiang, T.; Xu, X.; Ge, L.; Lin, J.; Yang, Z.

2013-12-01

During the seismic exploration with vibrator, seismic recording systems have often been affected by random spike noise in the background, which leads to strong data distortions as a result of the cross-correlation processing of the vibrator method. Partial or total loss of the desired seismic information is possible if no automatic spike reduction is available in the field prior to correlation of the field record. Generally speaking, original record of vibrator is uncorrelated data, in which the signal is non-wavelet form. In order to obtain the seismic record similar to explosive source, the signal of uncorrelated data needs to use the correlation algorithm to compress into wavelet form. The correlation process results in that the interference of spike in correlated data is not only being suppressed, but also being expanded. So the spike noise suppression of vibrator is indispensable. According to numerical simulation results, the effect of spike in the vibrator record is mainly affected by the amplitude and proportional points in the uncorrelated record. When the spike noise ratio in uncorrelated record reaches 1.5% and the average amplitude exceeds 200, it will make the SNR(signal-to-noise ratio) of the correlated record lower than 0dB, so that it is difficult to separate the signal. While the amplitude and ratio is determined by the intensity of background noise. Therefore, when the noise level is strong, in order to improve SNR of the seismic data, the uncorrelated record of vibrator need to take necessary steps to suppress spike noise. For the sake of reducing the influence of the spike noise, we need to make the detection and suppression of spike noise process for the uncorrelated record. Because vibrator works by inputting sweep signal into the underground long time, ideally, the peak and valley values of each trace have little change. On the basis of the peak and valley values, we can get a reference amplitude value. Then the spike can be detected and suppressed. After this process, it can reduce the effection of spike noise in the uncorrelated record to improve the SNR. At present, because the memory space of vibrator uncorrelated data is always very large, in order to reduce acquisition costs, we usually record correlated data directly. It's reasonable if there is no strong spike sneaking into uncorrelated record. However, due to the fact that the random spike in the background is not avoidable in the acquisition process, and the instantaneous input energy of the vibrator is probably smaller than spike noise, which makes the uncorrelated data contain a certain amount of spike noise, it severely reduces the acquisition quality of vibrator if there is no noise suppression module beforehand. Of course, the suppressing process of spike noise can be carried out in the field acquisition or data processing stage. In the field of vibrator acquisition system, we can use the spike noise suppression before the correlated module, so that it can directly record correlated data without the spike affection. If in the stage of data processing, it is necessary to record uncorrelated data.

Spike timing precision of neuronal circuits.

PubMed

Kilinc, Deniz; Demir, Alper

2018-06-01

Spike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuronal circuits. These techniques, which are orders of magnitude faster than traditional Monte Carlo type simulations, can be used to directly compute the spike timing jitter variance, power spectral densities, correlation functions, and other stochastic characterizations of neuronal circuit operation. We consider three distinct neuronal circuit motifs: Feedback inhibition, synaptic integration, and synaptic coupling. First, we show that both the spike timing precision and the energy efficiency of a spiking neuron are improved with feedback inhibition. We unveil the underlying mechanism through which this is achieved. Then, we demonstrate that a neuron can improve on the timing precision of its synaptic inputs, coming from multiple sources, via synaptic integration: The phase of the output spikes of the integrator neuron has the same variance as that of the sample average of the phases of its inputs. Finally, we reveal that weak synaptic coupling among neurons, in a fully connected network, enables them to behave like a single neuron with a larger membrane area, resulting in an improvement in the timing precision through cooperation.

Self-organization of synchronous activity propagation in neuronal networks driven by local excitation

PubMed Central

Bayati, Mehdi; Valizadeh, Alireza; Abbassian, Abdolhossein; Cheng, Sen

2015-01-01

Many experimental and theoretical studies have suggested that the reliable propagation of synchronous neural activity is crucial for neural information processing. The propagation of synchronous firing activity in so-called synfire chains has been studied extensively in feed-forward networks of spiking neurons. However, it remains unclear how such neural activity could emerge in recurrent neuronal networks through synaptic plasticity. In this study, we investigate whether local excitation, i.e., neurons that fire at a higher frequency than the other, spontaneously active neurons in the network, can shape a network to allow for synchronous activity propagation. We use two-dimensional, locally connected and heterogeneous neuronal networks with spike-timing dependent plasticity (STDP). We find that, in our model, local excitation drives profound network changes within seconds. In the emergent network, neural activity propagates synchronously through the network. This activity originates from the site of the local excitation and propagates through the network. The synchronous activity propagation persists, even when the local excitation is removed, since it derives from the synaptic weight matrix. Importantly, once this connectivity is established it remains stable even in the presence of spontaneous activity. Our results suggest that synfire-chain-like activity can emerge in a relatively simple way in realistic neural networks by locally exciting the desired origin of the neuronal sequence. PMID:26089794

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

Pirozhkov, A.S.; Kando, M.; Esirkepov, T.Zh.

We propose a new mechanism of high-order harmonic generation during an interaction of a high-intensity laser pulse with underdense plasma. A tightly focused laser pulse creates a cavity in plasma pushing electrons aside and exciting the wake wave and the bow wave. At the joint of the cavity wall and the bow wave boundary, an annular spike of electron density is formed. This spike surrounds the cavity and moves together with the laser pulse. Collective motion of electrons in the spike driven by the laser field generates high-order harmonics. A strong localization of the electron spike, its robustness to oscillationsmore » imposed by the laser field and, consequently, its ability to produce high-order harmonics is explained by catastrophe theory. The proposed mechanism explains the experimental observations of high-order harmonics with the 9 TW J-KAREN laser (JAEA, Japan) and the 120 TW Astra Gemini laser (CLF RAL, UK) [A. S. Pirozhkov, et al., arXiv:1004.4514 (2010); A. S. Pirozhkov et al, AIP Proceedings, this volume]. The theory is corroborated by high-resolution two-and three-dimensional particle-in-cell simulations.« less

Exploring the Epileptic Brain Network Using Time-Variant Effective Connectivity and Graph Theory.

PubMed

Storti, Silvia Francesca; Galazzo, Ilaria Boscolo; Khan, Sehresh; Manganotti, Paolo; Menegaz, Gloria

2017-09-01

The application of time-varying measures of causality between source time series can be very informative to elucidate the direction of communication among the regions of an epileptic brain. The aim of the study was to identify the dynamic patterns of epileptic networks in focal epilepsy by applying multivariate adaptive directed transfer function (ADTF) analysis and graph theory to high-density electroencephalographic recordings. The cortical network was modeled after source reconstruction and topology modulations were detected during interictal spikes. First a distributed linear inverse solution, constrained to the individual grey matter, was applied to the averaged spikes and the mean source activity over 112 regions, as identified by the Harvard-Oxford Atlas, was calculated. Then, the ADTF, a dynamic measure of causality, was used to quantify the connectivity strength between pairs of regions acting as nodes in the graph, and the measure of node centrality was derived. The proposed analysis was effective in detecting the focal regions as well as in characterizing the dynamics of the spike propagation, providing evidence of the fact that the node centrality is a reliable feature for the identification of the epileptogenic zones. Validation was performed by multimodal analysis as well as from surgical outcomes. In conclusion, the time-variant connectivity analysis applied to the epileptic patients can distinguish the generator of the abnormal activity from the propagation spread and identify the connectivity pattern over time.

Power feasibility of implantable digital spike-sorting circuits for neural prosthetic systems.

PubMed

Zumsteg, Zachary S; Ahmed, Rizwan E; Santhanam, Gopal; Shenoy, Krishna V; Meng, Teresa H

2004-01-01

A new class of neural prosthetic systems aims to assist disabled patients by translating cortical neural activity into control signals for prosthetic devices. Based on the success of proof-of-concept systems in the laboratory, there is now considerable interest in increasing system performance and creating implantable electronics for use in clinical systems. A critical question that impacts system performance and the overall architecture of these systems is whether it is possible to identify the neural source of each action potential (spike sorting) in real-time and with low power. Low power is essential both for power supply considerations and heat dissipation in the brain. In this paper we report that several state-of-the-art spike sorting algorithms implemented in modern CMOS VLSI processes are expected to be power realistic.

Task-Dependent Changes in Cross-Level Coupling between Single Neurons and Oscillatory Activity in Multiscale Networks

PubMed Central

Canolty, Ryan T.; Ganguly, Karunesh; Carmena, Jose M.

2012-01-01

Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP) activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC) or under direct neural control through a brain-machine interface (Brain Control, BC). In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10–45 Hz) during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to spike rate and timing may hold for models of computation and communication in distributed functional brain networks. PMID:23284276

Relationships among low-frequency local field potentials, spiking activity, and three-dimensional reach and grasp kinematics in primary motor and ventral premotor cortices

PubMed Central

Vargas-Irwin, Carlos E.; Truccolo, Wilson; Donoghue, John P.

2011-01-01

A prominent feature of motor cortex field potentials during movement is a distinctive low-frequency local field potential (lf-LFP) (<4 Hz), referred to as the movement event-related potential (mEP). The lf-LFP appears to be a global signal related to regional synaptic input, but its relationship to nearby output signaled by single unit spiking activity (SUA) or to movement remains to be established. Previous studies comparing information in primary motor cortex (MI) lf-LFPs and SUA in the context of planar reaching tasks concluded that lf-LFPs have more information than spikes about movement. However, the relative performance of these signals was based on a small number of simultaneously recorded channels and units, or for data averaged across sessions, which could miss information of larger-scale spiking populations. Here, we simultaneously recorded LFPs and SUA from two 96-microelectrode arrays implanted in two major motor cortical areas, MI and ventral premotor (PMv), while monkeys freely reached for and grasped objects swinging in front of them. We compared arm end point and grip aperture kinematics′ decoding accuracy for lf-LFP and SUA ensembles. The results show that lf-LFPs provide enough information to reconstruct kinematics in both areas with little difference in decoding performance between MI and PMv. Individual lf-LFP channels often provided more accurate decoding of single kinematic variables than any one single unit. However, the decoding performance of the best single unit among the large population usually exceeded that of the best single lf-LFP channel. Furthermore, ensembles of SUA outperformed the pool of lf-LFP channels, in disagreement with the previously reported superiority of lf-LFP decoding. Decoding results suggest that information in lf-LFPs recorded from intracortical arrays may allow the reconstruction of reach and grasp for real-time neuroprosthetic applications, thus potentially supplementing the ability to decode these same features from spiking populations. PMID:21273313

State-dependent spike and local field synchronization between motor cortex and substantia nigra in hemiparkinsonian rats.

PubMed

Brazhnik, Elena; Cruz, Ana V; Avila, Irene; Wahba, Marian I; Novikov, Nikolay; Ilieva, Neda M; McCoy, Alex J; Gerber, Colin; Walters, Judith R

2012-06-06

Excessive beta frequency oscillatory and synchronized activity has been reported in the basal ganglia of parkinsonian patients and animal models of the disease. To gain insight into processes underlying this activity, this study explores relationships between oscillatory activity in motor cortex and basal ganglia output in behaving rats after dopamine cell lesion. During inattentive rest, 7 d after lesion, increases in motor cortex-substantia nigra pars reticulata (SNpr) coherence emerged in the 8-25 Hz range, with significant increases in local field potential (LFP) power in SNpr but not motor cortex. In contrast, during treadmill walking, marked increases in both motor cortex and SNpr LFP power, as well as coherence, emerged in the 25-40 Hz band with a peak frequency at 30-35 Hz. Spike-triggered waveform averages showed that 77% of SNpr neurons, 77% of putative cortical interneurons, and 44% of putative pyramidal neurons were significantly phase-locked to the increased cortical LFP activity in the 25-40 Hz range. Although the mean lag between cortical and SNpr LFPs fluctuated around zero, SNpr neurons phase-locked to cortical LFP oscillations fired, on average, 17 ms after synchronized spiking in motor cortex. High coherence between LFP oscillations in cortex and SNpr supports the view that cortical activity facilitates entrainment and synchronization of activity in basal ganglia after loss of dopamine. However, the dramatic increases in cortical power and relative timing of phase-locked spiking in these areas suggest that additional processes help shape the frequency-specific tuning of the basal ganglia-thalamocortical network during ongoing motor activity.

Reduced gamma frequency in the medial frontal cortex of aged rats during behavior and rest: implications for age-related behavioral slowing.

PubMed

Insel, Nathan; Patron, Lilian A; Hoang, Lan T; Nematollahi, Saman; Schimanski, Lesley A; Lipa, Peter; Barnes, Carol A

2012-11-14

Age-related cognitive and behavioral slowing may be caused by changes in the speed of neural signaling or by changes in the number of signaling steps necessary to achieve a given function. In the mammalian cortex, neural communication is organized by a 30-100 Hz "gamma" oscillation. There is a putative link between the gamma frequency and the speed of processing in a neural network: the dynamics of pyramidal neuron membrane time constants suggest that synaptic integration is framed by the gamma cycle, and pharmacological slowing of gamma also slows reaction times on behavioral tasks. The present experiments identify reductions in a robust 40-70 Hz gamma oscillation in the aged rat medial frontal cortex. The reductions were observed in the form of local field potentials, later peaks in fast-spiking neuron autocorrelations, and delays in the spiking of inhibitory neurons following local excitatory signals. Gamma frequency did not vary with movement speed, but rats with slower gamma also moved more slowly. Gamma frequency age differences were not observed in hippocampus. Hippocampal CA1 fast-spiking neurons exhibited interspike intervals consistent with a fast (70-100 Hz) gamma frequency, a pattern maintained across theta phases and theta frequencies independent of fluctuations in the average firing rates of the neurons. We propose that an average lengthening of the cortical 15-25 ms gamma cycle is one factor contributing to age-related slowing and that future attempts to offset cognitive declines will find a target in the response of fast-spiking inhibitory neurons to excitatory inputs.

In situ microbial metabolism as a cause of gas anomalies in ice.

PubMed

Rohde, Robert A; Price, P Buford; Bay, Ryan C; Bramall, Nathan E

2008-06-24

Isolated spikes of anomalously high concentrations of N(2)O have been reported at depths in Greenland and Antarctic ice cores corresponding to narrow time intervals over the past approximately 10(5) years. Now, using a calibrated spectrofluorimeter to map protein-bound Trp, a proxy for microbes, versus depth in the 3,053-m GISP2 ice core, we find six depths at which localized spikes of high cell concentrations coincide with N(2)O spikes. We show that the excess gases are consistent with accumulation of in situ metabolic wastes during residence times of the excess microbes in the ice. Because of sparseness of N(2)O measurements and our spectrofluorimetry versus depth, the total number of microbially produced N(2)O spikes in GISP2 is probably much larger than six. Spikes of excess methanogens coincident with CH(4) spikes are found at three depths in the bottom 3% of GISP2, most likely because of methanogenic metabolism in the underlying silty ice, followed by turbulent flow of the lowest approximately 90 m of ice. The apparent rates of in situ production of N(2)O and CH(4) spikes by metabolism are observed to be consistent with a single activation energy, U, and maintain proportionality to exp(-U/RT) over the entire temperature range down to -40 degrees C. Fluorescence of nonmicrobial aerosols in GISP2 ice is distinguishable from microbial fluorescence by its different emission spectra. Our spectrofluorimetric scans throughout the GISP2 ice core lead us to conclude that both microbes and nonmicrobial aerosols are deposited in discontinuous bursts, which may provide a tool for studying wind storms in the distant past.

Spike avalanches in vivo suggest a driven, slightly subcritical brain state

PubMed Central

Priesemann, Viola; Wibral, Michael; Valderrama, Mario; Pröpper, Robert; Le Van Quyen, Michel; Geisel, Theo; Triesch, Jochen; Nikolić, Danko; Munk, Matthias H. J.

2014-01-01

In self-organized critical (SOC) systems avalanche size distributions follow power-laws. Power-laws have also been observed for neural activity, and so it has been proposed that SOC underlies brain organization as well. Surprisingly, for spiking activity in vivo, evidence for SOC is still lacking. Therefore, we analyzed highly parallel spike recordings from awake rats and monkeys, anesthetized cats, and also local field potentials from humans. We compared these to spiking activity from two established critical models: the Bak-Tang-Wiesenfeld model, and a stochastic branching model. We found fundamental differences between the neural and the model activity. These differences could be overcome for both models through a combination of three modifications: (1) subsampling, (2) increasing the input to the model (this way eliminating the separation of time scales, which is fundamental to SOC and its avalanche definition), and (3) making the model slightly sub-critical. The match between the neural activity and the modified models held not only for the classical avalanche size distributions and estimated branching parameters, but also for two novel measures (mean avalanche size, and frequency of single spikes), and for the dependence of all these measures on the temporal bin size. Our results suggest that neural activity in vivo shows a mélange of avalanches, and not temporally separated ones, and that their global activity propagation can be approximated by the principle that one spike on average triggers a little less than one spike in the next step. This implies that neural activity does not reflect a SOC state but a slightly sub-critical regime without a separation of time scales. Potential advantages of this regime may be faster information processing, and a safety margin from super-criticality, which has been linked to epilepsy. PMID:25009473

Fast spiking interneuron control of seizure propagation in a cortical slice model of focal epilepsy

PubMed Central

Cammarota, Mario; Losi, Gabriele; Chiavegato, Angela; Zonta, Micaela; Carmignoto, Giorgio

2013-01-01

In different animal models of focal epilepsy, seizure-like ictal discharge propagation is transiently opposed by feedforward inhibition. The specific cellular source of this signal and the mechanism by which inhibition ultimately becomes ineffective are, however, undefined. We used a brain slice model to study how focal ictal discharges that were repetitively evoked from the same site, and at precise times, propagate across the cortex. We used Ca2+ imaging and simultaneous single/dual cell recordings from pyramidal neurons (PyNs) and different classes of interneurons in rodents, including G42 and GIN transgenic mice expressing the green fluorescence protein in parvalbumin (Pv)-fast spiking (FS) and somatostatin (Som) interneurons, respectively. We found that these two classes of interneurons fired intensively shortly after ictal discharge generation at the focus. The inhibitory barrages that were recorded in PyNs occurred in coincidence with Pv-FS, but not with Som interneuron burst discharges. Furthermore, the strength of inhibitory barrages increased or decreased in parallel with increased or decreased firing in Pv-FS interneurons but not in Som interneurons. A firing impairment of Pv-FS interneurons caused by a membrane depolarization was found to precede ictal discharge onset in neighbouring pyramidal neurons. This event may account for the collapse of local inhibition that allows spatially defined clusters of PyNs to be recruited into propagating ictal discharges. Our study demonstrates that Pv-FS interneurons are a major source of the inhibitory barrages that oppose ictal discharge propagation and raises the possibility that targeting Pv-FS interneurons represents a new therapeutic strategy to prevent the generalization of human focal seizures. PMID:23207591

Development of solar flares and features of the fine structure of solar radio emission

NASA Astrophysics Data System (ADS)

Chernov, G. P.; Fomichev, V. V.; Yan, Y.; Tan, B.; Tan, Ch.; Fu, Q.

2017-11-01

The reason for the occurrence of different elements of the fine structure of solar radio bursts in the decimeter and centimeter wavelength ranges has been determined based on all available data from terrestrial and satellite observations. In some phenomena, fast pulsations, a zebra structre, fiber bursts, and spikes have been observed almost simultaneously. Two phenomena have been selected to show that the pulsations of radio emission are caused by particles accelerated in the magnetic reconnection region and that the zebra structure is excited in a source, such as a magnetic trap for fast particles. The complex combination of unusual fiber bursts, zebra structure, and spikes in the phenomenon on December 1, 2004, is associated with a single source, a magnetic island formed after a coronal mass ejection.

Parametric models to relate spike train and LFP dynamics with neural information processing.

PubMed

Banerjee, Arpan; Dean, Heather L; Pesaran, Bijan

2012-01-01

Spike trains and local field potentials (LFPs) resulting from extracellular current flows provide a substrate for neural information processing. Understanding the neural code from simultaneous spike-field recordings and subsequent decoding of information processing events will have widespread applications. One way to demonstrate an understanding of the neural code, with particular advantages for the development of applications, is to formulate a parametric statistical model of neural activity and its covariates. Here, we propose a set of parametric spike-field models (unified models) that can be used with existing decoding algorithms to reveal the timing of task or stimulus specific processing. Our proposed unified modeling framework captures the effects of two important features of information processing: time-varying stimulus-driven inputs and ongoing background activity that occurs even in the absence of environmental inputs. We have applied this framework for decoding neural latencies in simulated and experimentally recorded spike-field sessions obtained from the lateral intraparietal area (LIP) of awake, behaving monkeys performing cued look-and-reach movements to spatial targets. Using both simulated and experimental data, we find that estimates of trial-by-trial parameters are not significantly affected by the presence of ongoing background activity. However, including background activity in the unified model improves goodness of fit for predicting individual spiking events. Uncovering the relationship between the model parameters and the timing of movements offers new ways to test hypotheses about the relationship between neural activity and behavior. We obtained significant spike-field onset time correlations from single trials using a previously published data set where significantly strong correlation was only obtained through trial averaging. We also found that unified models extracted a stronger relationship between neural response latency and trial-by-trial behavioral performance than existing models of neural information processing. Our results highlight the utility of the unified modeling framework for characterizing spike-LFP recordings obtained during behavioral performance.

A Hammer-Impact, Aluminum, Shear-Wave Seismic Source

USGS Publications Warehouse

Haines, Seth

2007-01-01

Near-surface seismic surveys often employ hammer impacts to create seismic energy. Shear-wave surveys using horizontally polarized waves require horizontal hammer impacts against a rigid object (the source) that is coupled to the ground surface. I have designed, built, and tested a source made out of aluminum and equipped with spikes to improve coupling. The source is effective in a variety of settings, and it is relatively simple and inexpensive to build.

High resolution observations with Artemis-IV and the NRH. I. Type IV associated narrow-band bursts

NASA Astrophysics Data System (ADS)

Bouratzis, C.; Hillaris, A.; Alissandrakis, C. E.; Preka-Papadema, P.; Moussas, X.; Caroubalos, C.; Tsitsipis, P.; Kontogeorgos, A.

2016-02-01

Context. Narrow-band bursts appear on dynamic spectra from microwave to decametric frequencies as fine structures with very small duration and bandwidth. They are believed to be manifestations of small scale energy release through magnetic reconnection. Aims: We analyzed 27 metric type IV events with embedded narrow-band bursts, which were observed by the ARTEMIS-IV radio spectrograph from 30 June 1999 to 1 August 2010. We examined the morphological characteristics of isolated narrow-band structures (mostly spikes) and groups or chains of structures. Methods: The events were recorded with the SAO high resolution (10 ms cadence) receiver of ARTEMIS-IV in the 270-450 MHz range. We measured the duration, spectral width, and frequency drift of ~12 000 individual narrow-band bursts, groups, and chains. Spike sources were imaged with the Nançay radioheliograph (NRH) for the event of 21 April 2003. Results: The mean duration of individual bursts at fixed frequency was ~100 ms, while the instantaneous relative bandwidth was ~2%. Some bursts had measurable frequency drift, either positive or negative. Quite often spikes appeared in chains, which were closely spaced in time (column chains) or in frequency (row chains). Column chains had frequency drifts similar to type-IIId bursts, while most of the row chains exhibited negative frequently drifts with a rate close to that of fiber bursts. From the analysis of NRH data, we found that spikes were superimposed on a larger, slowly varying, background component. They were polarized in the same sense as the background source, with a slightly higher degree of polarization of ~65%, and their size was about 60% of their size in total intensity. Conclusions: The duration and bandwidth distributions did not show any clear separation in groups. Some chains tended to assume the form of zebra, lace stripes, fiber bursts, or bursts of the type-III family, suggesting that such bursts might be resolved in spikes when viewed with high resolution. The NRH data indicate that the spikes are not fluctuations of the background, but represent additional emission such as what would be expected from small-scale reconnection.

Modulation of Olfactory Bulb Network Activity by Serotonin: Synchronous Inhibition of Mitral Cells Mediated by Spatially Localized GABAergic Microcircuits

ERIC Educational Resources Information Center

Schmidt, Loren J.; Strowbridge, Ben W.

2014-01-01

Although inhibition has often been proposed as a central mechanism for coordinating activity in the olfactory system, relatively little is known about how activation of different inhibitory local circuit pathways can generate coincident inhibition of principal cells. We used serotonin (5-HT) as a pharmacological tool to induce spiking in ensembles…

Receptive Field Inference with Localized Priors

PubMed Central

Park, Mijung; Pillow, Jonathan W.

2011-01-01

The linear receptive field describes a mapping from sensory stimuli to a one-dimensional variable governing a neuron's spike response. However, traditional receptive field estimators such as the spike-triggered average converge slowly and often require large amounts of data. Bayesian methods seek to overcome this problem by biasing estimates towards solutions that are more likely a priori, typically those with small, smooth, or sparse coefficients. Here we introduce a novel Bayesian receptive field estimator designed to incorporate locality, a powerful form of prior information about receptive field structure. The key to our approach is a hierarchical receptive field model that flexibly adapts to localized structure in both spacetime and spatiotemporal frequency, using an inference method known as empirical Bayes. We refer to our method as automatic locality determination (ALD), and show that it can accurately recover various types of smooth, sparse, and localized receptive fields. We apply ALD to neural data from retinal ganglion cells and V1 simple cells, and find it achieves error rates several times lower than standard estimators. Thus, estimates of comparable accuracy can be achieved with substantially less data. Finally, we introduce a computationally efficient Markov Chain Monte Carlo (MCMC) algorithm for fully Bayesian inference under the ALD prior, yielding accurate Bayesian confidence intervals for small or noisy datasets. PMID:22046110

Localized thermal anomalies in haloclines of coastal Yucatan sinkholes.

PubMed

Stoessell, Ronald K; Coke, James G; Easley, Dale H

2002-01-01

A temperature spike is reported in the haloclines of three Yucatan sinkholes along a 1 km NW-SE transect from 5 to 4 km inland from the Caribbean coast. The temperature spike decreases in magnitude from 3.5 degrees C to 0.2 degrees C, approaching the coast. The anomaly does not vary diurnally and does not extend down into the underlying sea water. These conditions are inconsistent with explanations such as radiation absorption within the halocline, in situ microbially mediated sulfate reduction within the halocline and the underlying sea water, and sulfide oxidation by photosynthetic purple and green bacteria within the halocline. One explanation consistent with the shape and halocline location of the temperature spike involves a localized sea water convection cell operating near the coast. Cold sea water from the Caribbean Sea enters the coastal limestone at depths of a few hundred meters and heats up because of the geothermal gradient, buoyantly rising in vertical fractures within the unconfined aquifer. Blocked by the less dense fresh water, the movement stops in the halocline where the warm sea water mixes with brackish water. The convection cycle would be completed by the coastward movement of cooling brackish water. The observed temperature anomalies could possibly be snapshots of this warm layer moving coastward.

Analysis of intracerebral EEG recordings of epileptic spikes: insights from a neural network model

PubMed Central

Demont-Guignard, Sophie; Benquet, Pascal; Gerber, Urs; Wendling, Fabrice

2009-01-01

The pathophysiological interpretation of EEG signals recorded with depth electrodes (i.e. local field potentials, LFPs) during interictal (between seizures) or ictal (during seizures) periods is fundamental in the pre-surgical evaluation of patients with drug-resistant epilepsy. Our objective was to explain specific shape features of interictal spikes in the hippocampus (observed in LFPs) in terms of cell and network-related parameters of neuronal circuits that generate these events. We developed a neural network model based on “minimal” but biologically-relevant neuron models interconnected through GABAergic and glutamatergic synapses that reproduces the main physiological features of the CA1 subfield. Simulated LFPs were obtained by solving the forward problem (dipole theory) from networks including a large number (~3000) of cells. Insertion of appropriate parameters allowed the model to simulate events that closely resemble actual epileptic spikes. Moreover, the shape of the early fast component (‘spike’) and the late slow component (‘negative wave’) was linked to the relative contribution of glutamatergic and GABAergic synaptic currents in pyramidal cells. In addition, the model provides insights about the sensitivity of electrode localization with respect to recorded tissue volume and about the relationship between the LFP and the intracellular activity of principal cells and interneurons represented in the network. PMID:19651549

Stimulus-induced dissociation of neuronal firing rates and local field potential gamma power and its relationship to the blood oxygen level-dependent signal in macaque primary visual cortex

PubMed Central

Bartolo, M J; Gieselmann, M A; Vuksanovic, V; Hunter, D; Sun, L; Chen, X; Delicato, L S; Thiele, A

2011-01-01

The functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent (BOLD) signal is regularly used to assign neuronal activity to cognitive function. Recent analyses have shown that the local field potential (LFP) gamma power is a better predictor of the fMRI BOLD signal than spiking activity. However, LFP gamma power and spiking activity are usually correlated, clouding the analysis of the neural basis of the BOLD signal. We show that changes in LFP gamma power and spiking activity in the primary visual cortex (V1) of the awake primate can be dissociated by using grating and plaid pattern stimuli, which differentially engage surround suppression and cross-orientation inhibition/facilitation within and between cortical columns. Grating presentation yielded substantial V1 LFP gamma frequency oscillations and significant multi-unit activity. Plaid pattern presentation significantly reduced the LFP gamma power while increasing population multi-unit activity. The fMRI BOLD activity followed the LFP gamma power changes, not the multi-unit activity. Inference of neuronal activity from the fMRI BOLD signal thus requires detailed a priori knowledge of how different stimuli or tasks activate the cortical network. PMID:22081989

Computation of interaural time difference in the owl's coincidence detector neurons.

PubMed

Funabiki, Kazuo; Ashida, Go; Konishi, Masakazu

2011-10-26

Both the mammalian and avian auditory systems localize sound sources by computing the interaural time difference (ITD) with submillisecond accuracy. The neural circuits for this computation in birds consist of axonal delay lines and coincidence detector neurons. Here, we report the first in vivo intracellular recordings from coincidence detectors in the nucleus laminaris of barn owls. Binaural tonal stimuli induced sustained depolarizations (DC) and oscillating potentials whose waveforms reflected the stimulus. The amplitude of this sound analog potential (SAP) varied with ITD, whereas DC potentials did not. The amplitude of the SAP was correlated with firing rate in a linear fashion. Spike shape, synaptic noise, the amplitude of SAP, and responsiveness to current pulses differed between cells at different frequencies, suggesting an optimization strategy for sensing sound signals in neurons tuned to different frequencies.

Background levels of methane in Mars’ atmosphere show strong seasonal variations

NASA Astrophysics Data System (ADS)

Webster, Christopher R.; Mahaffy, Paul R.; Atreya, Sushil K.; Moores, John E.; Flesch, Gregory J.; Malespin, Charles; McKay, Christopher P.; Martinez, German; Smith, Christina L.; Martin-Torres, Javier; Gomez-Elvira, Javier; Zorzano, Maria-Paz; Wong, Michael H.; Trainer, Melissa G.; Steele, Andrew; Archer, Doug; Sutter, Brad; Coll, Patrice J.; Freissinet, Caroline; Meslin, Pierre-Yves; Gough, Raina V.; House, Christopher H.; Pavlov, Alexander; Eigenbrode, Jennifer L.; Glavin, Daniel P.; Pearson, John C.; Keymeulen, Didier; Christensen, Lance E.; Schwenzer, Susanne P.; Navarro-Gonzalez, Rafael; Pla-García, Jorge; Rafkin, Scot C. R.; Vicente-Retortillo, Álvaro; Kahanpää, Henrik; Viudez-Moreiras, Daniel; Smith, Michael D.; Harri, Ari-Matti; Genzer, Maria; Hassler, Donald M.; Lemmon, Mark; Crisp, Joy; Sander, Stanley P.; Zurek, Richard W.; Vasavada, Ashwin R.

2018-06-01

Variable levels of methane in the martian atmosphere have eluded explanation partly because the measurements are not repeatable in time or location. We report in situ measurements at Gale crater made over a 5-year period by the Tunable Laser Spectrometer on the Curiosity rover. The background levels of methane have a mean value 0.41 ± 0.16 parts per billion by volume (ppbv) (95% confidence interval) and exhibit a strong, repeatable seasonal variation (0.24 to 0.65 ppbv). This variation is greater than that predicted from either ultraviolet degradation of impact-delivered organics on the surface or from the annual surface pressure cycle. The large seasonal variation in the background and occurrences of higher temporary spikes (~7 ppbv) are consistent with small localized sources of methane released from martian surface or subsurface reservoirs.

SPIKE – a database, visualization and analysis tool of cellular signaling pathways

PubMed Central

Elkon, Ran; Vesterman, Rita; Amit, Nira; Ulitsky, Igor; Zohar, Idan; Weisz, Mali; Mass, Gilad; Orlev, Nir; Sternberg, Giora; Blekhman, Ran; Assa, Jackie; Shiloh, Yosef; Shamir, Ron

2008-01-01

Background Biological signaling pathways that govern cellular physiology form an intricate web of tightly regulated interlocking processes. Data on these regulatory networks are accumulating at an unprecedented pace. The assimilation, visualization and interpretation of these data have become a major challenge in biological research, and once met, will greatly boost our ability to understand cell functioning on a systems level. Results To cope with this challenge, we are developing the SPIKE knowledge-base of signaling pathways. SPIKE contains three main software components: 1) A database (DB) of biological signaling pathways. Carefully curated information from the literature and data from large public sources constitute distinct tiers of the DB. 2) A visualization package that allows interactive graphic representations of regulatory interactions stored in the DB and superposition of functional genomic and proteomic data on the maps. 3) An algorithmic inference engine that analyzes the networks for novel functional interplays between network components. SPIKE is designed and implemented as a community tool and therefore provides a user-friendly interface that allows registered users to upload data to SPIKE DB. Our vision is that the DB will be populated by a distributed and highly collaborative effort undertaken by multiple groups in the research community, where each group contributes data in its field of expertise. Conclusion The integrated capabilities of SPIKE make it a powerful platform for the analysis of signaling networks and the integration of knowledge on such networks with omics data. PMID:18289391

Reflex reading epilepsy: effect of linguistic characteristics on spike frequency.

PubMed

Safi, Dima; Lassonde, Maryse; Nguyen, Dang Khoa; Denault, Carole; Macoir, Joël; Rouleau, Isabelle; Béland, Renée

2011-04-01

Reading epilepsy is a rare reflex epilepsy in which seizures are provoked by reading. Several cases have been described in the literature, but the pathophysiological processes vary widely and remain unclear. We describe a 42-year-old male patient with reading epilepsy evaluated using clinical assessments and continuous video/EEG recordings. We administered verbal, nonverbal, and reading tasks to determine factors precipitating seizures. Linguistic characteristics of the words were manipulated. Results indicated that reading-induced seizures were significantly more numerous than those observed during verbal and nonverbal tasks. In reading tasks, spike frequency significantly increased with involvement of the phonological reading route. Spikes were recorded predominantly in left parasagittal regions. Future cerebral imaging studies will enable us to visualize the spatial localization and temporal course of reading-induced seizures and brain activity involved in reading. A better understanding of reading epilepsy is crucial for reading rehabilitation in these patients. Copyright © 2011 Elsevier Inc. All rights reserved.

Biomorphic networks: approach to invariant feature extraction and segmentation for ATR

NASA Astrophysics Data System (ADS)

Baek, Andrew; Farhat, Nabil H.

1998-10-01

Invariant features in two dimensional binary images are extracted in a single layer network of locally coupled spiking (pulsating) model neurons with prescribed synapto-dendritic response. The feature vector for an image is represented as invariant structure in the aggregate histogram of interspike intervals obtained by computing time intervals between successive spikes produced from each neuron over a given period of time and combining such intervals from all neurons in the network into a histogram. Simulation results show that the feature vectors are more pattern-specific and invariant under translation, rotation, and change in scale or intensity than achieved in earlier work. We also describe an application of such networks to segmentation of line (edge-enhanced or silhouette) images. The biomorphic spiking network's capabilities in segmentation and invariant feature extraction may prove to be, when they are combined, valuable in Automated Target Recognition (ATR) and other automated object recognition systems.

Rapid learning in visual cortical networks.

PubMed

Wang, Ye; Dragoi, Valentin

2015-08-26

Although changes in brain activity during learning have been extensively examined at the single neuron level, the coding strategies employed by cell populations remain mysterious. We examined cell populations in macaque area V4 during a rapid form of perceptual learning that emerges within tens of minutes. Multiple single units and LFP responses were recorded as monkeys improved their performance in an image discrimination task. We show that the increase in behavioral performance during learning is predicted by a tight coordination of spike timing with local population activity. More spike-LFP theta synchronization is correlated with higher learning performance, while high-frequency synchronization is unrelated with changes in performance, but these changes were absent once learning had stabilized and stimuli became familiar, or in the absence of learning. These findings reveal a novel mechanism of plasticity in visual cortex by which elevated low-frequency synchronization between individual neurons and local population activity accompanies the improvement in performance during learning.

Pyramidal cell-interneuron interactions underlie hippocampal ripple oscillations.

PubMed

Stark, Eran; Roux, Lisa; Eichler, Ronny; Senzai, Yuta; Royer, Sebastien; Buzsáki, György

2014-07-16

High-frequency ripple oscillations, observed most prominently in the hippocampal CA1 pyramidal layer, are associated with memory consolidation. The cellular and network mechanisms underlying the generation, frequency control, and spatial coherence of the rhythm are poorly understood. Using multisite optogenetic manipulations in freely behaving rodents, we found that depolarization of a small group of nearby pyramidal cells was sufficient to induce high-frequency oscillations, whereas closed-loop silencing of pyramidal cells or activation of parvalbumin- (PV) or somatostatin-immunoreactive interneurons aborted spontaneously occurring ripples. Focal pharmacological blockade of GABAA receptors abolished ripples. Localized PV interneuron activation paced ensemble spiking, and simultaneous induction of high-frequency oscillations at multiple locations resulted in a temporally coherent pattern mediated by phase-locked interneuron spiking. These results constrain competing models of ripple generation and indicate that temporally precise local interactions between excitatory and inhibitory neurons support ripple generation in the intact hippocampus. Copyright © 2014 Elsevier Inc. All rights reserved.

Pyramidal Cell-Interneuron Interactions Underlie Hippocampal Ripple Oscillations

PubMed Central

Stark, Eran; Roux, Lisa; Eichler, Ronny; Senzai, Yuta; Royer, Sebastien; Buzsáki, György

2015-01-01

SUMMARY High-frequency ripple oscillations, observed most prominently in the hippocampal CA1 pyramidal layer, are associated with memory consolidation. The cellular and network mechanisms underlying the generation, frequency control, and spatial coherence of the rhythm are poorly understood. Using multisite optogenetic manipulations in freely behaving rodents, we found that depolarization of a small group of nearby pyramidal cells was sufficient to induce high-frequency oscillations, whereas closed-loop silencing of pyramidal cells or activation of parvalbumin-(PV) or somatostatin-immunoreactive interneurons aborted spontaneously occurring ripples. Focal pharmacological blockade of GABAA receptors abolished ripples. Localized PV inter-neuron activation paced ensemble spiking, and simultaneous induction of high-frequency oscillations at multiple locations resulted in a temporally coherent pattern mediated by phase-locked inter-neuron spiking. These results constrain competing models of ripple generation and indicate that temporally precise local interactions between excitatory and inhibitory neurons support ripple generation in the intact hippocampus. PMID:25033186

Survey of the plasma electron environment of Jupiter: A view from Voyager

NASA Technical Reports Server (NTRS)

Scudder, J. D.; Sittler, E. C., Jr.; Bridge, H. S.

1980-01-01

The plasma environment within Jupiter's bow shock is considered in terms of the in situ, calibrated electron plasma measurements made between 10 eV and 5.95 keV by the Voyager plasma science experiment (PLS). Measurements were analyzed and corrected for spacecraft potential variations; the data were reduced to nearly model independent macroscopic parameters of the local electron density and temperature. It is tentatively concluded that the radial temperature profile within the plasma sheet is caused by the intermixing of two different electron populations that probably have different temporal histories and spatial paths to their local observation. The cool plasma source of the plasma sheet and spikes is probably the Io plasma torus and arrives in the plasma sheet as a result of flux tube interchange motions or other generalized transport which can be accomplished without diverting the plasma from the centrifugal equator. The hot suprathermal populations in the plasma sheet have most recently come from the sparse, hot mid-latitude "bath" of electrons which were directly observed juxtaposed to the plasma sheet.

Associative spike timing-dependent potentiation of the basal dendritic excitatory synapses in the hippocampus in vivo

PubMed Central

Fung, Thomas K.; Law, Clayton S.

2016-01-01

Spike timing-dependent plasticity in the hippocampus has rarely been studied in vivo. Using extracellular potential and current source density analysis in urethane-anesthetized adult rats, we studied synaptic plasticity at the basal dendritic excitatory synapse in CA1 after excitation-spike (ES) pairing; E was a weak basal dendritic excitation evoked by stratum oriens stimulation, and S was a population spike evoked by stratum radiatum apical dendritic excitation. We hypothesize that positive ES pairing—generating synaptic excitation before a spike—results in long-term potentiation (LTP) while negative ES pairing results in long-term depression (LTD). Pairing (50 pairs at 5 Hz) at ES intervals of −10 to 0 ms resulted in significant input-specific LTP of the basal dendritic excitatory sink, lasting 60–120 min. Pairing at +10- to +20-ms ES intervals, or unpaired 5-Hz stimulation, did not induce significant basal dendritic or apical dendritic LTP or LTD. No basal dendritic LTD was found after stimulation of stratum oriens with 200 pairs of high-intensity pulses at 25-ms interval. Pairing-induced LTP was abolished by pretreatment with an N-methyl-d-aspartate receptor antagonist, 3-(2-carboxypiperazin-4-yl)-propyl-1-phosphonic acid (CPP), which also reduced spike bursting during 5-Hz pairing. Pairing at 0.5 Hz did not induce spike bursts or basal dendritic LTP. In conclusion, ES pairing at 5 Hz resulted in input-specific basal dendritic LTP at ES intervals of −10 ms to 0 ms but no LTD at ES intervals of −20 to +20 ms. Associative LTP likely occurred because of theta-rhythmic coincidence of subthreshold excitation with a backpropagated spike burst, which are conditions that can occur naturally in the hippocampus. PMID:27052581

Isolated terawatt attosecond hard X-ray pulse generated from single current spike.

PubMed

Shim, Chi Hyun; Parc, Yong Woon; Kumar, Sandeep; Ko, In Soo; Kim, Dong Eon

2018-05-10

Isolated terawatt (TW) attosecond (as) hard X-ray pulse is greatly desired for four-dimensional investigations of natural phenomena with picometer spatial and attosecond temporal resolutions. Since the demand for such sources is continuously increasing, the possibility of generating such pulse by a single current spike without the use of optical or electron delay units in an undulator line is addressed. The conditions of a current spike (width and height) and a modulation laser pulse (wavelength and power) is also discussed. We demonstrate that an isolated TW-level as a hard X-ray can be produced by a properly chosen single current spike in an electron bunch with simulation results. By using realistic specifications of an electron bunch of the Pohang Accelerator Laboratory X-ray Free-Electron Laser (PAL-XFEL), we show that an isolated, >1.0 TW and ~36 as X-ray pulse at 12.4 keV can be generated in an optimized-tapered undulator line. This result opens a new vista for current XFEL operation: the attosecond XFEL.

Relationship between cortical state and spiking activity in the lateral geniculate nucleus of marmosets

PubMed Central

Pietersen, Alexander N.J.; Cheong, Soon Keen; Munn, Brandon; Gong, Pulin; Solomon, Samuel G.

2017-01-01

Key points How parallel are the primate visual pathways? In the present study, we demonstrate that parallel visual pathways in the dorsal lateral geniculate nucleus (LGN) show distinct patterns of interaction with rhythmic activity in the primary visual cortex (V1).In the V1 of anaesthetized marmosets, the EEG frequency spectrum undergoes transient changes that are characterized by fluctuations in delta‐band EEG power.We show that, on multisecond timescales, spiking activity in an evolutionary primitive (koniocellular) LGN pathway is specifically linked to these slow EEG spectrum changes. By contrast, on subsecond (delta frequency) timescales, cortical oscillations can entrain spiking activity throughout the entire LGN.Our results are consistent with the hypothesis that, in waking animals, the koniocellular pathway selectively participates in brain circuits controlling vigilance and attention. Abstract The major afferent cortical pathway in the visual system passes through the dorsal lateral geniculate nucleus (LGN), where nerve signals originating in the eye can first interact with brain circuits regulating visual processing, vigilance and attention. In the present study, we investigated how ongoing and visually driven activity in magnocellular (M), parvocellular (P) and koniocellular (K) layers of the LGN are related to cortical state. We recorded extracellular spiking activity in the LGN simultaneously with local field potentials (LFP) in primary visual cortex, in sufentanil‐anaesthetized marmoset monkeys. We found that asynchronous cortical states (marked by low power in delta‐band LFPs) are linked to high spike rates in K cells (but not P cells or M cells), on multisecond timescales. Cortical asynchrony precedes the increases in K cell spike rates by 1–3 s, implying causality. At subsecond timescales, the spiking activity in many cells of all (M, P and K) classes is phase‐locked to delta waves in the cortical LFP, and more cells are phase‐locked during synchronous cortical states than during asynchronous cortical states. The switch from low‐to‐high spike rates in K cells does not degrade their visual signalling capacity. By contrast, during asynchronous cortical states, the fidelity of visual signals transmitted by K cells is improved, probably because K cell responses become less rectified. Overall, the data show that slow fluctuations in cortical state are selectively linked to K pathway spiking activity, whereas delta‐frequency cortical oscillations entrain spiking activity throughout the entire LGN, in anaesthetized marmosets. PMID:28116750

Molecular dynamics simulations of damage production by thermal spikes in Ge

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

Lopez, Pedro; Pelaz, Lourdes; Santos, Ivan

2012-02-01

Molecular dynamics simulation techniques are used to analyze damage production in Ge by the thermal spike process and to compare the results to those obtained for Si. As simulation results are sensitive to the choice of the inter-atomic potential, several potentials are compared in terms of material properties relevant for damage generation, and the most suitable potentials for this kind of analysis are identified. A simplified simulation scheme is used to characterize, in a controlled way, the damage generation through the local melting of regions in which energy is deposited. Our results show the outstanding role of thermal spikes inmore » Ge, since the lower melting temperature and thermal conductivity of Ge make this process much more efficient in terms of damage generation than in Si. The study is extended to the modeling of full implant cascades, in which both collision events and thermal spikes coexist. Our simulations reveal the existence of bigger damaged or amorphous regions in Ge than in Si, which may be formed by the melting and successive quenching induced by thermal spikes. In the particular case of heavy ion implantation, defect structures in Ge are not only bigger, but they also present a larger net content in vacancies than in Si, which may act as precursors for the growth of voids and the subsequent formation of honeycomb-like structures.« less

Phenotypic and genome-wide association analysis of spike ethylene in diverse wheat genotypes under heat stress.

PubMed

Valluru, Ravi; Reynolds, Matthew P; Davies, William J; Sukumaran, Sivakumar

2017-04-01

The gaseous phytohormone ethylene plays an important role in spike development in wheat (Triticum aestivum). However, the genotypic variation and the genomic regions governing spike ethylene (SET) production in wheat under long-term heat stress remain unexplored. We investigated genotypic variation in the production of SET and its relationship with spike dry weight (SDW) in 130 diverse wheat elite lines and landraces under heat-stressed field conditions. We employed an Illumina iSelect 90K single nucleotide polymorphism (SNP) genotyping array to identify the genetic loci for SET and SDW through a genome-wide association study (GWAS) in a subset of the Wheat Association Mapping Initiative (WAMI) panel. The SET and SDW exhibited appreciable genotypic variation among wheat genotypes at the anthesis stage. There was a strong negative correlation between SET and SDW. The GWAS uncovered five and 32 significant SNPs for SET, and 22 and 142 significant SNPs for SDW, in glasshouse and field conditions, respectively. Some of these SNPs closely localized to the SNPs for plant height, suggesting close associations between plant height and spike-related traits. The phenotypic and genetic elucidation of SET and its relationship with SDW supports future efforts toward gene discovery and breeding wheat cultivars with reduced ethylene effects on yield under heat stress. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Bio-amplifier with Driven Shield Inputs to Reduce Electrical Noise and its Application to Laboratory Teaching of Electrophysiology

PubMed Central

Matsuzaka, Yoshiya; Ichihara, Toshiaki; Abe, Toshihiko; Mushiake, Hajime

2012-01-01

We describe a custom-designed bio-amplifier and its use in teaching neurophysiology to undergraduate students. The amplifier has the following features: 1) differential amplification with driven shield inputs, which makes it workable even in electrically unshielded environments, 2) high input impedance to allow recordings of small signals through high signal source impedance, 3) dual fixed frequency bandpass filters (1–340Hz for surface EMG, EEG, local field potential etc and 320Hz – 3.4kHz for neuronal action potential recording) and independent gain controllers (up to x107,000) to allow the recording of different signals from the same source (e.g., local field potential and spiking activity of neurons), and 4) printed circuit board technology for easy replication with consistent quality. We compared its performance with a commercial amplifier in an electrically noisy environment. Even without any electrostatic shield, it recorded clear electromyographic activity with little interference from other electric appliances. In contrast, the commercial amplifier’s performance severely deteriorated under the same condition. We used this amplifier to build a computer-controlled stimulation and measurement system for electroencephalographic recordings by undergraduate students. The students successfully recorded various sensory evoked potentials with clarity that otherwise would have required costly instruments. This amplifier is a low-cost yet reliable instrument for electro-physiological recording both in education and research. PMID:23504543

Field portable low temperature porous layer open tubular cryoadsorption headspace sampling and analysis part II: Applications.

PubMed

Harries, Megan; Bukovsky-Reyes, Santiago; Bruno, Thomas J

2016-01-15

This paper details the sampling methods used with the field portable porous layer open tubular cryoadsorption (PLOT-cryo) approach, described in Part I of this two-part series, applied to several analytes of interest. We conducted tests with coumarin and 2,4,6-trinitrotoluene (two solutes that were used in initial development of PLOT-cryo technology), naphthalene, aviation turbine kerosene, and diesel fuel, on a variety of matrices and test beds. We demonstrated that these analytes can be easily detected and reliably identified using the portable unit for analyte collection. By leveraging efficiency-boosting temperature control and the high flow rate multiple capillary wafer, very short collection times (as low as 3s) yielded accurate detection. For diesel fuel spiked on glass beads, we determined a method detection limit below 1 ppm. We observed greater variability among separate samples analyzed with the portable unit than previously documented in work using the laboratory-based PLOT-cryo technology. We identify three likely sources that may help explain the additional variation: the use of a compressed air source to generate suction, matrix geometry, and variability in the local vapor concentration around the sampling probe as solute depletion occurs both locally around the probe and in the test bed as a whole. This field-portable adaptation of the PLOT-cryo approach has numerous and diverse potential applications. Published by Elsevier B.V.

Field Portable Low Temperature Porous Layer Open Tubular Cryoadsorption Headspace Sampling and Analysis Part II: Applications*

PubMed Central

Harries, Megan; Bukovsky-Reyes, Santiago; Bruno, Thomas J.

2016-01-01

This paper details the sampling methods used with the field portable porous layer open tubular cryoadsorption (PLOT-cryo) approach, described in Part I of this two-part series, applied to several analytes of interest. We conducted tests with coumarin and 2,4,6-trinitrotoluene (two solutes that were used in initial development of PLOT-cryo technology), naphthalene, aviation turbine kerosene, and diesel fuel, on a variety of matrices and test beds. We demonstrated that these analytes can be easily detected and reliably identified using the portable unit for analyte collection. By leveraging efficiency-boosting temperature control and the high flow rate multiple capillary wafer, very short collection times (as low as 3 s) yielded accurate detection. For diesel fuel spiked on glass beads, we determined a method detection limit below 1 ppm. We observed greater variability among separate samples analyzed with the portable unit than previously documented in work using the laboratory-based PLOT-cryo technology. We identify three likely sources that may help explain the additional variation: the use of a compressed air source to generate suction, matrix geometry, and variability in the local vapor concentration around the sampling probe as solute depletion occurs both locally around the probe and in the test bed as a whole. This field-portable adaptation of the PLOT-cryo approach has numerous and diverse potential applications. PMID:26726934

State-Dependent Spike and Local Field Synchronization between Motor Cortex and Substantia Nigra in Hemiparkinsonian Rats

PubMed Central

Brazhnik, Elena; Cruz, Ana V.; Avila, Irene; Wahba, Marian I.; Novikov, Nikolay; Ilieva, Neda M.; McCoy, Alex J.; Gerber, Colin; Walters, Judith. R.

2012-01-01

Excessive beta frequency oscillatory and synchronized activity has been reported in the basal ganglia of Parkinsonian patients and animal models of the disease. To gain insight into processes underlying this activity, this study explores relationships between oscillatory activity in motor cortex and basal ganglia output in behaving rats after dopamine cell lesion. During inattentive rest, seven days after lesion, increases in motor cortex-substantia nigra pars reticulata (SNpr) coherence emerged in the 8–25 Hz range, with significant increases in local field potential (LFP) power in SNpr but not motor cortex. In contrast, during treadmill walking, marked increases in both motor cortex and SNpr LFP power, as well as coherence, emerged in the 25–40 Hz band with a peak frequency at 30–35 Hz. Spike-triggered waveform averages showed that 77% of SNpr neurons, 77% of putative cortical interneurons and 44% of putative pyramidal neurons were significantly phase-locked to the increased cortical LFP activity in the 25–40 Hz range. Although the mean lag between cortical and SNpr LFPs fluctuated around zero, SNpr neurons phase-locked to cortical LFP oscillations fired, on average, 17 ms after synchronized spiking in motor cortex. High coherence between LFP oscillations in cortex and SNpr supports the view that cortical activity facilitates entrainment and synchronization of activity in basal ganglia after loss of dopamine. However, the dramatic increases in cortical power and relative timing of phase-locked spiking in these areas suggest that additional processes help shape the frequency-specific tuning of the basal ganglia-thalamocortical network during ongoing motor activity. PMID:22674263

Sensory Regulation of Network Components Underlying Ciliary Locomotion in Hermissenda

PubMed Central

Crow, Terry; Tian, Lian-Ming

2008-01-01

Ciliary locomotion in the nudibranch mollusk Hermissenda is modulated by the visual and graviceptive systems. Components of the neural network mediating ciliary locomotion have been identified including aggregates of polysensory interneurons that receive monosynaptic input from identified photoreceptors and efferent neurons that activate cilia. Illumination produces an inhibition of type Ii (off-cell) spike activity, excitation of type Ie (on-cell) spike activity, decreased spike activity in type IIIi inhibitory interneurons, and increased spike activity of ciliary efferent neurons. Here we show that pairs of type Ii interneurons and pairs of type Ie interneurons are electrically coupled. Neither electrical coupling or synaptic connections were observed between Ie and Ii interneurons. Coupling is effective in synchronizing dark-adapted spontaneous firing between pairs of Ie and pairs of Ii interneurons. Out-of-phase burst activity, occasionally observed in dark-adapted and light-adapted pairs of Ie and Ii interneurons, suggests that they receive synaptic input from a common presynaptic source or sources. Rhythmic activity is typically not a characteristic of dark-adapted, light-adapted, or light-evoked firing of type I interneurons. However, burst activity in Ie and Ii interneurons may be elicited by electrical stimulation of pedal nerves or generated at the offset of light. Our results indicate that type I interneurons can support the generation of both rhythmic activity and changes in tonic firing depending on sensory input. This suggests that the neural network supporting ciliary locomotion may be multifunctional. However, consistent with the nonmuscular and nonrhythmic characteristics of visually modulated ciliary locomotion, type I interneurons exhibit changes in tonic activity evoked by illumination. PMID:18768639

Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity

PubMed Central

Bennett, James E. M.; Bair, Wyeth

2015-01-01

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli. PMID:26308406

Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity.

PubMed

Bennett, James E M; Bair, Wyeth

2015-08-01

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli.

Bursting as a source of non-linear determinism in the firing patterns of nigral dopamine neurons

PubMed Central

Jeong, Jaeseung; Shi, Wei-Xing; Hoffman, Ralph; Oh, Jihoon; Gore, John C.; Bunney, Benjamin S.; Peterson, Bradley S.

2012-01-01

Nigral dopamine (DA) neurons in vivo exhibit complex firing patterns consisting of tonic single-spikes and phasic bursts that encode information for certain types of reward-related learning and behavior. Non-linear dynamical analysis has previously demonstrated the presence of a non-linear deterministic structure in complex firing patterns of DA neurons, yet the origin of this non-linear determinism remains unknown. In this study, we hypothesized that bursting activity is the primary source of non-linear determinism in the firing patterns of DA neurons. To test this hypothesis, we investigated the dimension complexity of inter-spike interval data recorded in vivo from bursting and non-bursting DA neurons in the chloral hydrate-anesthetized rat substantia nigra. We found that bursting DA neurons exhibited non-linear determinism in their firing patterns, whereas non-bursting DA neurons showed truly stochastic firing patterns. Determinism was also detected in the isolated burst and inter-burst interval data extracted from firing patterns of bursting neurons. Moreover, less bursting DA neurons in halothane-anesthetized rats exhibited higher dimensional spiking dynamics than do more bursting DA neurons in chloral hydrate-anesthetized rats. These results strongly indicate that bursting activity is the main source of low-dimensional, non-linear determinism in the firing patterns of DA neurons. This finding furthermore suggests that bursts are the likely carriers of meaningful information in the firing activities of DA neurons. PMID:22831464

Electrical Interaction of Paired Ganglion Cells in the Leech

PubMed Central

Eckert, Roger

1963-01-01

The two paired giant ganglion cells (PGC's) found in each ganglion of the leech central nervous system fire synchronously in response to certain sensory input. Polarizing current passed into either of these cells is seen to displace the membrane potentials of both cells, the voltage attenuation between the two somata ranging from 2 to 5 times. This attenuation factor remains unchanged when the direction of the polarizing current is reversed, and remains about the same when the other cell of the pair is directly polarized. When one of the PGC's is partially depolarized with outward current, a repetitive train of impulses is generated. Each spike is followed by a spike in the other cell. Occasionally, a small subspike potential is seen in place of a follower spike. This potential appears to differ in shape and time course from synaptic potentials elicited by afferent input to these cells, and appears rather to be an electrotonic potential derived from the prejunctional impulse in the stimulated PGC. It is proposed that transmission between these cells is electrical, being accomplished by a flow of local circuit current across a non-rectifying junction or connection to the spike-initiating region of the other PGC. PMID:19873553

Memristive neural network for on-line learning and tracking with brain-inspired spike timing dependent plasticity.

PubMed

Pedretti, G; Milo, V; Ambrogio, S; Carboni, R; Bianchi, S; Calderoni, A; Ramaswamy, N; Spinelli, A S; Ielmini, D

2017-07-13

Brain-inspired computation can revolutionize information technology by introducing machines capable of recognizing patterns (images, speech, video) and interacting with the external world in a cognitive, humanlike way. Achieving this goal requires first to gain a detailed understanding of the brain operation, and second to identify a scalable microelectronic technology capable of reproducing some of the inherent functions of the human brain, such as the high synaptic connectivity (~10 4 ) and the peculiar time-dependent synaptic plasticity. Here we demonstrate unsupervised learning and tracking in a spiking neural network with memristive synapses, where synaptic weights are updated via brain-inspired spike timing dependent plasticity (STDP). The synaptic conductance is updated by the local time-dependent superposition of pre- and post-synaptic spikes within a hybrid one-transistor/one-resistor (1T1R) memristive synapse. Only 2 synaptic states, namely the low resistance state (LRS) and the high resistance state (HRS), are sufficient to learn and recognize patterns. Unsupervised learning of a static pattern and tracking of a dynamic pattern of up to 4 × 4 pixels are demonstrated, paving the way for intelligent hardware technology with up-scaled memristive neural networks.

A hidden Markov model for decoding and the analysis of replay in spike trains.

PubMed

Box, Marc; Jones, Matt W; Whiteley, Nick

2016-12-01

We present a hidden Markov model that describes variation in an animal's position associated with varying levels of activity in action potential spike trains of individual place cell neurons. The model incorporates a coarse-graining of position, which we find to be a more parsimonious description of the system than other models. We use a sequential Monte Carlo algorithm for Bayesian inference of model parameters, including the state space dimension, and we explain how to estimate position from spike train observations (decoding). We obtain greater accuracy over other methods in the conditions of high temporal resolution and small neuronal sample size. We also present a novel, model-based approach to the study of replay: the expression of spike train activity related to behaviour during times of motionlessness or sleep, thought to be integral to the consolidation of long-term memories. We demonstrate how we can detect the time, information content and compression rate of replay events in simulated and real hippocampal data recorded from rats in two different environments, and verify the correlation between the times of detected replay events and of sharp wave/ripples in the local field potential.

Influence of food, aquatic humus, and alkalinity on methylmercury uptake by Daphnia magna

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

Monson, B.A.; Brezonik, P.L.

Six-day-old Daphnia magna were exposed to low concentrations of methylmercury (MeHg) in synthetic freshwater and synthetic food. Uptake kinetics were determined in 24- to 72-h experiments, measuring both the loss of Hg from water and accumulation in D. magna. Dose-uptake response was linear for MeHg concentrations up to 4.0 ng/L; an initial concentration of 2.0 ng/L was used when other factors were varied. Concentrations of total Hg and MeHg in water and D. magna were measured in treatments with varied hardness and alkalinity, aquatic humus (AH), and food spiked with MeHg versus water spiked with MeHg. Uptake rate coefficients weremore » derived from two versions of a first-order, two-compartment model. The first version assumed constant MeHg concentration; the second accounted for changing MeHg concentration in water over time. Both models accounted for a nonzero starting concentration of MeHg in plankton. Fitted rate coefficients were higher for the second model than the first: the uptake coefficient (k{sub u}) was nine times higher; the depuration coefficient (k{sub d}) was twice as high. Assuming a constant MeHg concentration for a one-time spike thus underestimated the rate coefficient. The source of MeHg was compared by exposing D. magna for 48 h to MeHg at 2 ng/L in food or water. Daphnia magna accumulated significantly more inorganic Hg (i.e., Hg{sup 2+}) from spiked food than from spiked water, but accumulation of MeHg was the same from both sources. A similar response was found when D. magna were exposed to a lake water extraction of AH at concentrations of C at 3 and 10 mg/L. At the higher AH concentration, total Hg in daphnids was higher, but MeHg was lower, suggesting that AH was a source of inorganic Hg but reduced the bioavailability of MeHg. Exposure of D. magna to MeHg at 2 ng/L in hard or soft water adjusted to pH 6.7 showed no significant difference in MeHg uptake, supporting an argument that hardness and alkalinity per se do not affect MeHg uptake by daphnids.« less

The impact of short term synaptic depression and stochastic vesicle dynamics on neuronal variability

PubMed Central

Reich, Steven

2014-01-01

Neuronal variability plays a central role in neural coding and impacts the dynamics of neuronal networks. Unreliability of synaptic transmission is a major source of neural variability: synaptic neurotransmitter vesicles are released probabilistically in response to presynaptic action potentials and are recovered stochastically in time. The dynamics of this process of vesicle release and recovery interacts with variability in the arrival times of presynaptic spikes to shape the variability of the postsynaptic response. We use continuous time Markov chain methods to analyze a model of short term synaptic depression with stochastic vesicle dynamics coupled with three different models of presynaptic spiking: one model in which the timing of presynaptic action potentials are modeled as a Poisson process, one in which action potentials occur more regularly than a Poisson process (sub-Poisson) and one in which action potentials occur more irregularly (super-Poisson). We use this analysis to investigate how variability in a presynaptic spike train is transformed by short term depression and stochastic vesicle dynamics to determine the variability of the postsynaptic response. We find that sub-Poisson presynaptic spiking increases the average rate at which vesicles are released, that the number of vesicles released over a time window is more variable for smaller time windows than larger time windows and that fast presynaptic spiking gives rise to Poisson-like variability of the postsynaptic response even when presynaptic spike times are non-Poisson. Our results complement and extend previously reported theoretical results and provide possible explanations for some trends observed in recorded data. PMID:23354693

Current-horn suppression for reduced coherent-synchrotron-radiation-induced emittance growth in strong bunch compression

NASA Astrophysics Data System (ADS)

Charles, T. K.; Paganin, D. M.; Latina, A.; Boland, M. J.; Dowd, R. T.

2017-03-01

Control of coherent synchrotron radiation (CSR)-induced emittance growth is essential in linear accelerators designed to deliver very high brightness electron beams. Extreme current values at the head and tail of the electron bunch, resulting from strong bunch compression, are responsible for large CSR production leading to significant transverse projected emittance growth. The Linac Coherent Light Source (LCLS) truncates the head and tail current spikes which greatly improves free electron laser (FEL) performance. Here we consider the underlying dynamics that lead to formation of current spikes (also referred to as current horns), which has been identified as caustics forming in electron trajectories. We present a method to analytically determine conditions required to avoid the caustic formation and therefore prevent the current spikes from forming. These required conditions can be easily met, without increasing the transverse slice emittance, through inclusion of an octupole magnet in the middle of a bunch compressor.

Power feasibility of implantable digital spike sorting circuits for neural prosthetic systems.

PubMed

Zumsteg, Zachary S; Kemere, Caleb; O'Driscoll, Stephen; Santhanam, Gopal; Ahmed, Rizwan E; Shenoy, Krishna V; Meng, Teresa H

2005-09-01

A new class of neural prosthetic systems aims to assist disabled patients by translating cortical neural activity into control signals for prosthetic devices. Based on the success of proof-of-concept systems in the laboratory, there is now considerable interest in increasing system performance and creating implantable electronics for use in clinical systems. A critical question that impacts system performance and the overall architecture of these systems is whether it is possible to identify the neural source of each action potential (spike sorting) in real-time and with low power. Low power is essential both for power supply considerations and heat dissipation in the brain. In this paper we report that state-of-the-art spike sorting algorithms are not only feasible using modern complementary metal oxide semiconductor very large scale integration processes, but may represent the best option for extracting large amounts of data in implantable neural prosthetic interfaces.

Large short-term deviations from dipolar field during the Levantine Iron Age Geomagnetic Anomaly ca. 1050-700 BCE

NASA Astrophysics Data System (ADS)

Shaar, R.; Tauxe, L.; Ebert, Y.

2017-12-01

Continuous decadal-resolution paleomagnetic data from archaeological and sedimentary sources in the Levant revealed the existence a local high-field anomaly, which spanned the first 350 years of the first millennium BCE. This so-called "the Levantine Iron Age geomagnetic Anomaly" (LIAA) was characterized by a high averaged geomagnetic field (virtual axial dipole moments, VADM > 140 Z Am2, nearly twice of today's field), short decadal-scale geomagnetic spikes (VADM of 160-185 Z Am2), fast directional and intensity variations, and substantial deviation (20°-25°) from dipole field direction. Similar high field values in the time frame of LIAA have been observed north, and northeast to the Levant: Eastern Anatolia, Turkmenistan, and Georgia. West of the Levant, in the Balkans, field values in the same time are moderate to low. The overall data suggest that the LIAA is a manifestation of a local positive geomagnetic field anomaly similar in magnitude and scale to the presently active negative South Atlantic Anomaly. In this presentation we review the overall archaeomagnetic and sedimentary evidences supporting the local anomaly hypothesis, and compare these observations with today's IGRF field. We analyze the global data during the first two millennia BCE, which suggest some unexpected large deviations from a simple dipolar geomagnetic structure.

Impact of adaptation currents on synchronization of coupled exponential integrate-and-fire neurons.

PubMed

Ladenbauer, Josef; Augustin, Moritz; Shiau, LieJune; Obermayer, Klaus

2012-01-01

The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC) and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experimentally. Here we use the adaptive exponential integrate-and-fire (aEIF) neuron model to determine how subthreshold and spike-triggered slow adaptation currents shape the PRC. Based on that, we predict how synchrony and phase locked states of coupled neurons change in presence of synaptic delays and unequal coupling strengths. We find that increased subthreshold adaptation currents cause a transition of the PRC from only phase advances to phase advances and delays in response to excitatory perturbations. Increased spike-triggered adaptation currents on the other hand predominantly skew the PRC to the right. Both adaptation induced changes of the PRC are modulated by spike frequency, being more prominent at lower frequencies. Applying phase reduction theory, we show that subthreshold adaptation stabilizes synchrony for pairs of coupled excitatory neurons, while spike-triggered adaptation causes locking with a small phase difference, as long as synaptic heterogeneities are negligible. For inhibitory pairs synchrony is stable and robust against conduction delays, and adaptation can mediate bistability of in-phase and anti-phase locking. We further demonstrate that stable synchrony and bistable in/anti-phase locking of pairs carry over to synchronization and clustering of larger networks. The effects of adaptation in aEIF neurons on PRCs and network dynamics qualitatively reflect those of biophysical adaptation currents in detailed Hodgkin-Huxley-based neurons, which underscores the utility of the aEIF model for investigating the dynamical behavior of networks. Our results suggest neuronal spike frequency adaptation as a mechanism synchronizing low frequency oscillations in local excitatory networks, but indicate that inhibition rather than excitation generates coherent rhythms at higher frequencies.

Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons

PubMed Central

Ladenbauer, Josef; Augustin, Moritz; Shiau, LieJune; Obermayer, Klaus

2012-01-01

The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC) and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experimentally. Here we use the adaptive exponential integrate-and-fire (aEIF) neuron model to determine how subthreshold and spike-triggered slow adaptation currents shape the PRC. Based on that, we predict how synchrony and phase locked states of coupled neurons change in presence of synaptic delays and unequal coupling strengths. We find that increased subthreshold adaptation currents cause a transition of the PRC from only phase advances to phase advances and delays in response to excitatory perturbations. Increased spike-triggered adaptation currents on the other hand predominantly skew the PRC to the right. Both adaptation induced changes of the PRC are modulated by spike frequency, being more prominent at lower frequencies. Applying phase reduction theory, we show that subthreshold adaptation stabilizes synchrony for pairs of coupled excitatory neurons, while spike-triggered adaptation causes locking with a small phase difference, as long as synaptic heterogeneities are negligible. For inhibitory pairs synchrony is stable and robust against conduction delays, and adaptation can mediate bistability of in-phase and anti-phase locking. We further demonstrate that stable synchrony and bistable in/anti-phase locking of pairs carry over to synchronization and clustering of larger networks. The effects of adaptation in aEIF neurons on PRCs and network dynamics qualitatively reflect those of biophysical adaptation currents in detailed Hodgkin-Huxley-based neurons, which underscores the utility of the aEIF model for investigating the dynamical behavior of networks. Our results suggest neuronal spike frequency adaptation as a mechanism synchronizing low frequency oscillations in local excitatory networks, but indicate that inhibition rather than excitation generates coherent rhythms at higher frequencies. PMID:22511861

Evaluation of two spike-and-recovery controls for assessment of extraction efficiency in microbial source tracking studies

USGS Publications Warehouse

Stoeckel, D.M.; Stelzer, E.A.; Dick, L.K.

2009-01-01

Quantitative PCR (qPCR), applied to complex environmental samples such as water, wastewater, and feces, is susceptible to methodological and sample related biases. In this study, we evaluated two exogenous DNA spike-and-recovery controls as proxies for recovery efficiency of Bacteroidales 16S rDNA gene sequences (AllBac and qHF183) that are used for microbial source tracking (MST) in river water. Two controls-(1) the plant pathogen Pantoea stewartii, carrying the chromosomal target gene cpsD, and (2) Escherichia coli, carrying the plasmid-borne target gene DsRed2-were added to raw water samples immediately prior to concentration and DNA extraction for qPCR. When applied to samples processed in replicate, recovery of each control was positively correlated with the observed concentration of each MST marker. Adjustment of MST marker concentrations according to recovery efficiency reduced variability in replicate analyses when consistent processing and extraction methodologies were applied. Although the effects of this procedure on accuracy could not be tested due to uncertainties in control DNA concentrations, the observed reduction in variability should improve the strength of statistical comparisons. These findings suggest that either of the tested spike-and-recovery controls can be useful to measure efficiency of extraction and recovery in routine laboratory processing. ?? 2009 Elsevier Ltd.

Phase-locking of bursting neuronal firing to dominant LFP frequency components.

PubMed

Constantinou, Maria; Elijah, Daniel H; Squirrell, Daniel; Gigg, John; Montemurro, Marcelo A

2015-10-01

Neuronal firing in the hippocampal formation relative to the phase of local field potentials (LFP) has a key role in memory processing and spatial navigation. Firing can be in either tonic or burst mode. Although bursting neurons are common in the hippocampal formation, the characteristics of their locking to LFP phase are not completely understood. We investigated phase-locking properties of bursting neurons using simulations generated by a dual compartmental model of a pyramidal neuron adapted to match the bursting activity in the subiculum of a rat. The model was driven with stochastic input signals containing a power spectral profile consistent with physiologically relevant frequencies observed in LFP. The single spikes and spike bursts fired by the model were locked to a preferred phase of the predominant frequency band where there was a peak in the power of the driving signal. Moreover, the preferred phase of locking shifted with increasing burst size, providing evidence that LFP phase can be encoded by burst size. We also provide initial support for the model results by analysing example data of spontaneous LFP and spiking activity recorded from the subiculum of a single urethane-anaesthetised rat. Subicular neurons fired single spikes, two-spike bursts and larger bursts that locked to a preferred phase of either dominant slow oscillations or theta rhythms within the LFP, according to the model prediction. Both power-modulated phase-locking and gradual shift in the preferred phase of locking as a function of burst size suggest that neurons can use bursts to encode timing information contained in LFP phase into a spike-count code. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Molecular Architecture of the Cleavage-Dependent Mannose Patch on a Soluble HIV-1 Envelope Glycoprotein Trimer

PubMed Central

Behrens, Anna-Janina; Harvey, David J.; Milne, Emilia; Cupo, Albert; Kumar, Abhinav; Zitzmann, Nicole; Struwe, Weston B.; Moore, John P.

2016-01-01

ABSTRACT The formation of a correctly folded and natively glycosylated HIV-1 viral spike is dependent on protease cleavage of the gp160 precursor protein in the Golgi apparatus. Cleavage induces a compact structure which not only renders the spike capable of fusion but also limits further maturation of its extensive glycosylation. The redirection of the glycosylation pathway to preserve underprocessed oligomannose-type glycans is an important feature in immunogen design, as glycans contribute to or influence the epitopes of numerous broadly neutralizing antibodies. Here we present a quantitative site-specific analysis of a recombinant, trimeric mimic of the native HIV-1 viral spike (BG505 SOSIP.664) compared to the corresponding uncleaved pseudotrimer and the matched gp120 monomer. We present a detailed molecular map of a trimer-associated glycan remodeling that forms a localized subdomain of the native mannose patch. The formation of native trimers is a critical design feature in shaping the glycan epitopes presented on recombinant vaccine candidates. IMPORTANCE The envelope spike of human immunodeficiency virus type 1 (HIV-1) is a target for antibody-based neutralization. For some patients infected with HIV-1, highly potent antibodies have been isolated that can neutralize a wide range of circulating viruses. It is a goal of HIV-1 vaccine research to elicit these antibodies by immunization with recombinant mimics of the viral spike. These antibodies have evolved to recognize the dense array of glycans that coat the surface of the viral molecule. We show how the structure of these glycans is shaped by steric constraints imposed upon them by the native folding of the viral spike. This information is important in guiding the development of vaccine candidates. PMID:27807235

Photospheric Current Spikes as Possible Predictors of Flares

NASA Technical Reports Server (NTRS)

Goodman, Michael L.; Kwan, Chiman; Ayhan, Bulent; Shang, Eric L.

2016-01-01

Flares involve generation of the largest current densities in the solar atmosphere. This suggests the hypothesis that prior to a large (M,X) flare there are related time dependent changes in the photospheric current distribution, and hence in the resistive heating rate in neutral line regions (NLRs). If this is true, these changes might be useful predictors of flares. Preliminary evidence supporting this hypothesis is presented. Results from a data driven, near photospheric, 3D magnetohydrodynamic type model suggest the model might be useful for predicting M and X flares several hours to several days in advance. The model takes as input the photospheric magnetic field observed by the Helioseismic and Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO) satellite. The model computes quantities in every active region (AR) pixel for 14 ARs, with spurious Doppler periods due to SDO orbital motion filtered out of the time series of the magnetic field for each pixel. Spikes in the NLR resistive heating rate Q, appearing as increases by orders of magnitude above background values in the time series of Q are found to occur, and appear to be correlated with the occurrence of M or X flares a few hours to a few days later. The subset of spikes analyzed at the pixel level are found to occur on HMI and granulation scales of 1 arcsec and 12 minutes. Spikes are found in NLRs with and without M or X flares, and outside as well as inside NLRs, but the largest spikes are localized in the NLRs of ARs with M or X flares, and associated with horizontal magnetic field strengths approximately several hG, and vertical magnetic field strengths several orders of magnitude smaller. The spikes may be signatures of horizontal current sheets associated with emerging magnetic flux.

Photospheric Current Spikes as Possible Predictors of Flares

NASA Technical Reports Server (NTRS)

Goodman, Michael L.; Kwan, Chiman; Ayhan, Bulent; Shang, Eric L.

2016-01-01

Flares involve generation of the largest current densities in the solar atmosphere. This suggests the hypothesis that prior to a large (M,X) flare there are related time dependent changes in the photospheric current distribution, and hence in the resistive heating rate in neutral line regions (NLRs). If this is true, these changes might be useful predictors of flares. Evidence supporting this hypothesis is presented. Results from a data driven, near photospheric, 3D magnetohydrodynamic type model suggest the model might be useful for predicting M and X flares several hours to several days in advance. The model takes as input the photospheric magnetic field observed by the Helioseismic & Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO) satellite. The model computes quantities in every active region (AR) pixel for 14 ARs, with spurious Doppler periods due to SDO orbital motion filtered out of the time series of the magnetic field for each pixel. Spikes in the NLR resistive heating rate Q, appearing as increases by orders of magnitude above background values in the time series of Q are found to occur, and appear to be correlated with the occurrence of M or X flares a few hours to a few days later. The subset of spikes analyzed at the pixel level are found to occur on HMI and granulation scales of 1 arcsec and 12 minutes. Spikes are found in NLRs with and without M or X flares, and outside as well as inside NLRs, but the largest spikes are localized in the NLRs of ARs with M or X flares, and associated with horizontal magnetic field strengths several hG, and vertical magnetic field strengths several orders of magnitude smaller, suggesting that the spikes are associated with current sheets.

State-based decoding of hand and finger kinematics using neuronal ensemble and LFP activity during dexterous reach-to-grasp movements

PubMed Central

Mollazadeh, Mohsen; Davidson, Adam G.; Schieber, Marc H.; Thakor, Nitish V.

2013-01-01

The performance of brain-machine interfaces (BMIs) that continuously control upper limb neuroprostheses may benefit from distinguishing periods of posture and movement so as to prevent inappropriate movement of the prosthesis. Few studies, however, have investigated how decoding behavioral states and detecting the transitions between posture and movement could be used autonomously to trigger a kinematic decoder. We recorded simultaneous neuronal ensemble and local field potential (LFP) activity from microelectrode arrays in primary motor cortex (M1) and dorsal (PMd) and ventral (PMv) premotor areas of two male rhesus monkeys performing a center-out reach-and-grasp task, while upper limb kinematics were tracked with a motion capture system with markers on the dorsal aspect of the forearm, hand, and fingers. A state decoder was trained to distinguish four behavioral states (baseline, reaction, movement, hold), while a kinematic decoder was trained to continuously decode hand end point position and 18 joint angles of the wrist and fingers. LFP amplitude most accurately predicted transition into the reaction (62%) and movement (73%) states, while spikes most accurately decoded arm, hand, and finger kinematics during movement. Using an LFP-based state decoder to trigger a spike-based kinematic decoder [r = 0.72, root mean squared error (RMSE) = 0.15] significantly improved decoding of reach-to-grasp movements from baseline to final hold, compared with either a spike-based state decoder combined with a spike-based kinematic decoder (r = 0.70, RMSE = 0.17) or a spike-based kinematic decoder alone (r = 0.67, RMSE = 0.17). Combining LFP-based state decoding with spike-based kinematic decoding may be a valuable step toward the realization of BMI control of a multifingered neuroprosthesis performing dexterous manipulation. PMID:23536714

From individual spiking neurons to population behavior: Systematic elimination of short-wavelength spatial modes

NASA Astrophysics Data System (ADS)

Steyn-Ross, Moira L.; Steyn-Ross, D. A.

2016-02-01

Mean-field models of the brain approximate spiking dynamics by assuming that each neuron responds to its neighbors via a naive spatial average that neglects local fluctuations and correlations in firing activity. In this paper we address this issue by introducing a rigorous formalism to enable spatial coarse-graining of spiking dynamics, scaling from the microscopic level of a single type 1 (integrator) neuron to a macroscopic assembly of spiking neurons that are interconnected by chemical synapses and nearest-neighbor gap junctions. Spiking behavior at the single-neuron scale ℓ ≈10 μ m is described by Wilson's two-variable conductance-based equations [H. R. Wilson, J. Theor. Biol. 200, 375 (1999), 10.1006/jtbi.1999.1002], driven by fields of incoming neural activity from neighboring neurons. We map these equations to a coarser spatial resolution of grid length B ℓ , with B ≫1 being the blocking ratio linking micro and macro scales. Our method systematically eliminates high-frequency (short-wavelength) spatial modes q ⃗ in favor of low-frequency spatial modes Q ⃗ using an adiabatic elimination procedure that has been shown to be equivalent to the path-integral coarse graining applied to renormalization group theory of critical phenomena. This bottom-up neural regridding allows us to track the percolation of synaptic and ion-channel noise from the single neuron up to the scale of macroscopic population-average variables. Anticipated applications of neural regridding include extraction of the current-to-firing-rate transfer function, investigation of fluctuation criticality near phase-transition tipping points, determination of spatial scaling laws for avalanche events, and prediction of the spatial extent of self-organized macrocolumnar structures. As a first-order exemplar of the method, we recover nonlinear corrections for a coarse-grained Wilson spiking neuron embedded in a network of identical diffusively coupled neurons whose chemical synapses have been disabled. Intriguingly, we find that reblocking transforms the original type 1 Wilson integrator into a type 2 resonator whose spike-rate transfer function exhibits abrupt spiking onset with near-vertical takeoff and chaotic dynamics just above threshold.

Definitions of state variables and state space for brain-computer interface : Part 2. Extraction and classification of feature vectors.

PubMed

Freeman, Walter J

2007-06-01

The hypothesis is proposed that the central dynamics of the action-perception cycle has five steps: emergence from an existing macroscopic brain state of a pattern that predicts a future goal state; selection of a mesoscopic frame for action control; execution of a limb trajectory by microscopic spike activity; modification of microscopic cortical spike activity by sensory inputs; construction of mesoscopic perceptual patterns; and integration of a new macroscopic brain state. The basis is the circular causality between microscopic entities (neurons) and the mesoscopic and macroscopic entities (populations) self-organized by axosynaptic interactions. Self-organization of neural activity is bidirectional in all cortices. Upwardly the organization of mesoscopic percepts from microscopic spike input predominates in primary sensory areas. Downwardly the organization of spike outputs that direct specific limb movements is by mesoscopic fields constituting plans to achieve predicted goals. The mesoscopic fields in sensory and motor cortices emerge as frames within macroscopic activity. Part 1 describes the action-perception cycle and its derivative reflex arc qualitatively. Part 2 describes the perceptual limb of the arc from microscopic MSA to mesoscopic wave packets, and from these to macroscopic EEG and global ECoG fields that express experience-dependent knowledge in successive states. These macroscopic states are conceived to embed and control mesoscopic frames in premotor and motor cortices that are observed in local ECoG and LFP of frontoparietal areas. The fields sampled by ECoG and LFP are conceived as local patterns of neural activity in which trajectories of multiple spike activities (MSA) emerge that control limb movements. Mesoscopic frames are located by use of the analytic signal from the Hilbert transform after band pass filtering. The state variables in frames are measured to construct feature vectors by which to describe and classify frame patterns. Evidence is cited to justify use of linear analysis. The aim of the review is to enable researchers to conceive and identify goal-oriented states in brain activity for use as commands, in order to relegate the details of execution to adaptive control devices outside the brain.

Method of analysis of local neuronal circuits in the vertebrate central nervous system.

PubMed

Reinis, S; Weiss, D S; McGaraughty, S; Tsoukatos, J

1992-06-01

Although a considerable amount of knowledge has been accumulated about the activity of individual nerve cells in the brain, little is known about their mutual interactions at the local level. The method presented in this paper allows the reconstruction of functional relations within a group of neurons as recorded by a single microelectrode. Data are sampled at 10 or 13 kHz. Prominent spikes produced by one or more single cells are selected and sorted by K-means cluster analysis. The activities of single cells are then related to the background firing of neurons in their vicinity. Auto-correlograms of the leading cells, auto-correlograms of the background cells (mass correlograms) and cross-correlograms between these two levels of firing are computed and evaluated. The statistical probability of mutual interactions is determined, and the statistically significant, most common interspike intervals are stored and attributed to real pairs of spikes in the original record. Selected pairs of spikes, characterized by statistically significant intervals between them, are then assembled into a working model of the system. This method has revealed substantial differences between the information processing in the visual cortex, the inferior colliculus, the rostral ventromedial medulla and the ventrobasal complex of the thalamus. Even short 1-s records of the multiple neuronal activity may provide meaningful and statistically significant results.

Origins of correlated spiking in the mammalian olfactory bulb

PubMed Central

Gerkin, Richard C.; Tripathy, Shreejoy J.; Urban, Nathaniel N.

2013-01-01

Mitral/tufted (M/T) cells of the main olfactory bulb transmit odorant information to higher brain structures. The relative timing of action potentials across M/T cells has been proposed to encode this information and to be critical for the activation of downstream neurons. Using ensemble recordings from the mouse olfactory bulb in vivo, we measured how correlations between cells are shaped by stimulus (odor) identity, common respiratory drive, and other cells’ activity. The shared respiration cycle is the largest source of correlated firing, but even after accounting for all observable factors a residual positive noise correlation was observed. Noise correlation was maximal on a ∼100-ms timescale and was seen only in cells separated by <200 µm. This correlation is explained primarily by common activity in groups of nearby cells. Thus, M/T-cell correlation principally reflects respiratory modulation and sparse, local network connectivity, with odor identity accounting for a minor component. PMID:24082089

Implementing Signature Neural Networks with Spiking Neurons

PubMed Central

Carrillo-Medina, José Luis; Latorre, Roberto

2016-01-01

Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm—i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data—to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence of inhibitory connections. These parameters also modulate the memory capabilities of the network. The dynamical modes observed in the different informational dimensions in a given moment are independent and they only depend on the parameters shaping the information processing in this dimension. In view of these results, we argue that plasticity mechanisms inside individual cells and multicoding strategies can provide additional computational properties to spiking neural networks, which could enhance their capacity and performance in a wide variety of real-world tasks. PMID:28066221

Implementing Signature Neural Networks with Spiking Neurons.

PubMed

Carrillo-Medina, José Luis; Latorre, Roberto

2016-01-01

Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm-i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data-to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence of inhibitory connections. These parameters also modulate the memory capabilities of the network. The dynamical modes observed in the different informational dimensions in a given moment are independent and they only depend on the parameters shaping the information processing in this dimension. In view of these results, we argue that plasticity mechanisms inside individual cells and multicoding strategies can provide additional computational properties to spiking neural networks, which could enhance their capacity and performance in a wide variety of real-world tasks.

40 CFR Appendix A to Part 63 - Test Methods Pollutant Measurement Methods From Various Waste Media

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 15 2013-07-01 2013-07-01 false Test Methods Pollutant Measurement... POLLUTANTS FOR SOURCE CATEGORIES (CONTINUED) Pt. 63, App. A Appendix A to Part 63—Test Methods Pollutant... analyte spiking? 13.0How do I conduct tests at similar sources? Optional Requirements 14.0How do I use and...

40 CFR Appendix A to Part 63 - Test Methods Pollutant Measurement Methods From Various Waste Media

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 15 2014-07-01 2014-07-01 false Test Methods Pollutant Measurement... POLLUTANTS FOR SOURCE CATEGORIES (CONTINUED) Pt. 63, App. A Appendix A to Part 63—Test Methods Pollutant... analyte spiking? 13.0How do I conduct tests at similar sources? Optional Requirements 14.0How do I use and...

40 CFR Appendix A to Part 63 - Test Methods Pollutant Measurement Methods From Various Waste Media

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 14 2011-07-01 2011-07-01 false Test Methods Pollutant Measurement... POLLUTANTS FOR SOURCE CATEGORIES (CONTINUED) Pt. 63, App. A Appendix A to Part 63—Test Methods Pollutant... analyte spiking? 13.0How do I conduct tests at similar sources? Optional Requirements 14.0How do I use and...

40 CFR Appendix A to Part 63 - Test Methods Pollutant Measurement Methods From Various Waste Media

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 15 2012-07-01 2012-07-01 false Test Methods Pollutant Measurement... POLLUTANTS FOR SOURCE CATEGORIES (CONTINUED) Pt. 63, App. A Appendix A to Part 63—Test Methods Pollutant... analyte spiking? 13.0How do I conduct tests at similar sources? Optional Requirements 14.0How do I use and...

Clathrate hydrates as possible source of episodic methane releases on Mars

NASA Astrophysics Data System (ADS)

Karatekin, Özgür; Gloesener, Elodie; Temel, Orkun

2017-04-01

Methane has been shown to vary with location and time in the Martian atmosphere, with abundances of up to tens of parts-per-billion by volume (ppbv). Since methane is short-lived on geological time scales, its presence implies the existence of an active, current source of methane that is yet to be understood. In this study we investigate the destabilization of subsurface reservoirs of clathrate hydrates as a possible geological source of methane. Clathrate hydrates are crystalline compounds constituted by cages of hydrogen-bonded water molecules, inside of which guest gas molecules are trapped. We show the present-day maps of methane clathrate stability zones, in particular in the vicinity of Gale Crater where the Sample Analysis at Mars (SAM) suite on the Curiosity rover has made in situ measurements of atmospheric methane, during more than 3 years. Curiosity has observed spikes of elevated methane levels of 7 ppbv on four sequential observations over a 2-month period. The possibility of episodic releases consistent with curiosity observations from a subsurface clathrate source, is investigated using a gas transport through porous Martian regolith considering different depths of reservoirs. Transport of the released methane spike into the atmosphere is simulated using the PlanetWRF model.

Climate Change Effect on Thermal Power Cooling in the U.S.

EPA Science Inventory

Maintaining reasonable surface-water temperatures is paramount for aquatic ecosystem health. Thermal pollution from power plant effluent can result in unnatural river temperature spikes locally, as well as cause damaging breaches to river temperature. The threat of a nonstationar...

The Relationship between Respiration-Related Membrane Potential Slow Oscillations and Discharge Patterns in Mitral/Tufted Cells: What Are the Rules?

PubMed Central

Briffaud, Virginie; Fourcaud-Trocmé, Nicolas; Messaoudi, Belkacem; Buonviso, Nathalie; Amat, Corine

2012-01-01

Background A slow respiration-related rhythm strongly shapes the activity of the olfactory bulb. This rhythm appears as a slow oscillation that is detectable in the membrane potential, the respiration-related spike discharge of the mitral/tufted cells and the bulbar local field potential. Here, we investigated the rules that govern the manifestation of membrane potential slow oscillations (MPSOs) and respiration-related discharge activities under various afferent input conditions and cellular excitability states. Methodology and Principal Findings We recorded the intracellular membrane potential signals in the mitral/tufted cells of freely breathing anesthetized rats. We first demonstrated the existence of multiple types of MPSOs, which were influenced by odor stimulation and discharge activity patterns. Complementary studies using changes in the intracellular excitability state and a computational model of the mitral cell demonstrated that slow oscillations in the mitral/tufted cell membrane potential were also modulated by the intracellular excitability state, whereas the respiration-related spike activity primarily reflected the afferent input. Based on our data regarding MPSOs and spike patterns, we found that cells exhibiting an unsynchronized discharge pattern never exhibited an MPSO. In contrast, cells with a respiration-synchronized discharge pattern always exhibited an MPSO. In addition, we demonstrated that the association between spike patterns and MPSO types appeared complex. Conclusion We propose that both the intracellular excitability state and input strength underlie specific MPSOs, which, in turn, constrain the types of spike patterns exhibited. PMID:22952828

Overexpression of cypin alters dendrite morphology, single neuron activity, and network properties via distinct mechanisms

NASA Astrophysics Data System (ADS)

Rodríguez, Ana R.; O'Neill, Kate M.; Swiatkowski, Przemyslaw; Patel, Mihir V.; Firestein, Bonnie L.

2018-02-01

Objective. This study investigates the effect that overexpression of cytosolic PSD-95 interactor (cypin), a regulator of synaptic PSD-95 protein localization and a core regulator of dendrite branching, exerts on the electrical activity of rat hippocampal neurons and networks. Approach. We cultured rat hippocampal neurons and used lipid-mediated transfection and lentiviral gene transfer to achieve high levels of cypin or cypin mutant (cypinΔPDZ PSD-95 non-binding) expression cellularly and network-wide, respectively. Main results. Our analysis revealed that although overexpression of cypin and cypinΔPDZ increase dendrite numbers and decrease spine density, cypin and cypinΔPDZ distinctly regulate neuronal activity. At the single cell level, cypin promotes decreases in bursting activity while cypinΔPDZ reduces sEPSC frequency and further decreases bursting compared to cypin. At the network level, by using the Fano factor as a measure of spike count variability, cypin overexpression results in an increase in variability of spike count, and this effect is abolished when cypin cannot bind PSD-95. This variability is also dependent on baseline activity levels and on mean spike rate over time. Finally, our spike sorting data show that overexpression of cypin results in a more complex distribution of spike waveforms and that binding to PSD-95 is essential for this complexity. Significance. Our data suggest that dendrite morphology does not play a major role in cypin action on electrical activity.

Six-rowed barley originated from a mutation in a homeodomain-leucine zipper I-class homeobox gene

PubMed Central

Komatsuda, Takao; Pourkheirandish, Mohammad; He, Congfen; Azhaguvel, Perumal; Kanamori, Hiroyuki; Perovic, Dragan; Stein, Nils; Graner, Andreas; Wicker, Thomas; Tagiri, Akemi; Lundqvist, Udda; Fujimura, Tatsuhito; Matsuoka, Makoto; Matsumoto, Takashi; Yano, Masahiro

2007-01-01

Increased seed production has been a common goal during the domestication of cereal crops, and early cultivators of barley (Hordeum vulgare ssp. vulgare) selected a phenotype with a six-rowed spike that stably produced three times the usual grain number. This improved yield established barley as a founder crop for the Near Eastern Neolithic civilization. The barley spike has one central and two lateral spikelets at each rachis node. The wild-type progenitor (H. vulgare ssp. spontaneum) has a two-rowed phenotype, with additional, strictly rudimentary, lateral rows; this natural adaptation is advantageous for seed dispersal after shattering. Until recently, the origin of the six-rowed phenotype remained unknown. In the present study, we isolated vrs1 (six-rowed spike 1), the gene responsible for the six-rowed spike in barley, by means of positional cloning. The wild-type Vrs1 allele (for two-rowed barley) encodes a transcription factor that includes a homeodomain with a closely linked leucine zipper motif. Expression of Vrs1 was strictly localized in the lateral-spikelet primordia of immature spikes, suggesting that the VRS1 protein suppresses development of the lateral rows. Loss of function of Vrs1 resulted in complete conversion of the rudimentary lateral spikelets in two-rowed barley into fully developed fertile spikelets in the six-rowed phenotype. Phylogenetic analysis demonstrated that the six-rowed phenotype originated repeatedly, at different times and in different regions, through independent mutations of Vrs1. PMID:17220272

Electrical activity of the cingulate cortex. II. Cholinergic modulation.

PubMed

Borst, J G; Leung, L W; MacFabe, D F

1987-03-24

The role of the cholinergic innervation in the modulation of cingulate electrical activity was studied by means of pharmacological manipulations and brain lesions. In the normal rat, an irregular slow activity (ISA) accompanied with EEG-spikes was recorded in the cingulate cortex during immobility as compared to walking. Atropine sulfate, but not atropine methyl nitrate, increased ISA and the frequency of cingulate EEG-spikes. Pilocarpine suppressed ISA and EEG-spikes during immobility, and induced a slow (4-7 Hz) theta rhythm. Unilateral or bilateral lesions of the substantia innominata and ventral globus pallidus area using kainic acid did not significantly change the cingulate EEG or its relation to behavior. Large electrolytic lesions of the medial septal nuclei and vertical limbs of the diagonal band generally decreased or abolished all theta activity in the cingulate cortex and the hippocampus. However, in 5 rats the cingulate theta rhythm increased while the hippocampal theta disappeared after a medial septal lesion. The large, postlesion cingulate theta, accompanied by sharp EEG-spikes during its negative phase, is an unequivocal demonstration of the existence of a theta rhythm in the cingulate cortex, independent of the hippocampal rhythm. Cholinergic afferents from the medial septum and diagonal band nuclei are inferred to be responsible for the behavioral suppression of cingulate EEG-spikes and ISA, and partially for the generation of a local cingulate theta rhythm. However, an atropine-resistant pathway and a theta-suppressing pathway, possibly coming from the medial septum or the hippocampus, may also be important in cingulate theta generation.

Adjustment of pesticide concentrations for temporal changes in analytical recovery, 1992–2010

USGS Publications Warehouse

Martin, Jeffrey D.; Eberle, Michael

2011-01-01

Recovery is the proportion of a target analyte that is quantified by an analytical method and is a primary indicator of the analytical bias of a measurement. Recovery is measured by analysis of quality-control (QC) water samples that have known amounts of target analytes added ("spiked" QC samples). For pesticides, recovery is the measured amount of pesticide in the spiked QC sample expressed as a percentage of the amount spiked, ideally 100 percent. Temporal changes in recovery have the potential to adversely affect time-trend analysis of pesticide concentrations by introducing trends in apparent environmental concentrations that are caused by trends in performance of the analytical method rather than by trends in pesticide use or other environmental conditions. This report presents data and models related to the recovery of 44 pesticides and 8 pesticide degradates (hereafter referred to as "pesticides") that were selected for a national analysis of time trends in pesticide concentrations in streams. Water samples were analyzed for these pesticides from 1992 through 2010 by gas chromatography/mass spectrometry. Recovery was measured by analysis of pesticide-spiked QC water samples. Models of recovery, based on robust, locally weighted scatterplot smooths (lowess smooths) of matrix spikes, were developed separately for groundwater and stream-water samples. The models of recovery can be used to adjust concentrations of pesticides measured in groundwater or stream-water samples to 100 percent recovery to compensate for temporal changes in the performance (bias) of the analytical method.

Coordinated neuronal activity enhances corticocortical communication

PubMed Central

Zandvakili, Amin; Kohn, Adam

2015-01-01

Summary Relaying neural signals between cortical areas is central to cognition and sensory processing. The temporal coordination of activity in a source population has been suggested to determine corticocortical signaling efficacy, but others have argued that coordination is functionally irrelevant. We reasoned that if coordination significantly influenced signaling, spiking in downstream networks should be preceded by transiently elevated coordination in a source population. We developed a metric to quantify network coordination in brief epochs, and applied it to simultaneous recordings of neuronal populations in cortical areas V1 and V2 of the macaque monkey. Spiking in the input layers of V2 was preceded by brief epochs of elevated V1 coordination, but this was not the case in other layers of V2. Our results indicate that V1 coordination influences its signaling to direct downstream targets, but that coordinated V1 epochs do not propagate through multiple downstream networks as in some corticocortical signaling schemes. PMID:26291164

Bottom-up and Top-down Input Augment the Variability of Cortical Neurons

PubMed Central

Nassi, Jonathan J.; Kreiman, Gabriel; Born, Richard T.

2016-01-01

SUMMARY Neurons in the cerebral cortex respond inconsistently to a repeated sensory stimulus, yet they underlie our stable sensory experiences. Although the nature of this variability is unknown, its ubiquity has encouraged the general view that each cell produces random spike patterns that noisily represent its response rate. In contrast, here we show that reversibly inactivating distant sources of either bottom-up or top-down input to cortical visual areas in the alert primate reduces both the spike train irregularity and the trial-to-trial variability of single neurons. A simple model in which a fraction of the pre-synaptic input is silenced can reproduce this reduction in variability, provided that there exist temporal correlations primarily within, but not between, excitatory and inhibitory input pools. A large component of the variability of cortical neurons may therefore arise from synchronous input produced by signals arriving from multiple sources. PMID:27427459

Systematic analysis of the contributions of stochastic voltage gated channels to neuronal noise

PubMed Central

O'Donnell, Cian; van Rossum, Mark C. W.

2014-01-01

Electrical signaling in neurons is mediated by the opening and closing of large numbers of individual ion channels. The ion channels' state transitions are stochastic and introduce fluctuations in the macroscopic current through ion channel populations. This creates an unavoidable source of intrinsic electrical noise for the neuron, leading to fluctuations in the membrane potential and spontaneous spikes. While this effect is well known, the impact of channel noise on single neuron dynamics remains poorly understood. Most results are based on numerical simulations. There is no agreement, even in theoretical studies, on which ion channel type is the dominant noise source, nor how inclusion of additional ion channel types affects voltage noise. Here we describe a framework to calculate voltage noise directly from an arbitrary set of ion channel models, and discuss how this can be use to estimate spontaneous spike rates. PMID:25360105

Anchoring historical sequences using a new source of astro-chronological tie-points

NASA Astrophysics Data System (ADS)

Dee, Michael W.; Pope, Benjamin J. S.

2016-08-01

The discovery of past spikes in atmospheric radiocarbon activity, caused by major solar energetic particle events, has opened up new possibilities for high-precision chronometry. The two spikes, or Miyake Events, have now been widely identified in tree-rings that grew in the years 775 and 994 CE. Furthermore, all other plant material that grew in these years would also have incorporated the anomalously high concentrations of radiocarbon. Crucially, some plant-based artefacts, such as papyrus documents, timber beams and linen garments, can also be allocated to specific positions within long, currently unfixed, historical sequences. Thus, Miyake Events represent a new source of tie-points that could provide the means for anchoring early chronologies to the absolute timescale. Here, we explore this possibility, outlining the most expeditious approaches, the current challenges and obstacles, and how they might best be overcome.

Characterization of long-range functional connectivity in epileptic networks by neuronal spike-triggered local field potentials

NASA Astrophysics Data System (ADS)

Lopour, Beth A.; Staba, Richard J.; Stern, John M.; Fried, Itzhak; Ringach, Dario L.

2016-04-01

Objective. Quantifying the relationship between microelectrode-recorded multi-unit activity (MUA) and local field potentials (LFPs) in distinct brain regions can provide detailed information on the extent of functional connectivity in spatially widespread networks. These methods are common in studies of cognition using non-human animal models, but are rare in humans. Here we applied a neuronal spike-triggered impulse response to electrophysiological recordings from the human epileptic brain for the first time, and we evaluate functional connectivity in relation to brain areas supporting the generation of seizures. Approach. Broadband interictal electrophysiological data were recorded from microwires adapted to clinical depth electrodes that were implanted bilaterally using stereotactic techniques in six presurgical patients with medically refractory epilepsy. MUA and LFPs were isolated in each microwire, and we calculated the impulse response between the MUA on one microwire and the LFPs on a second microwire for all possible MUA/LFP pairs. Results were compared to clinical seizure localization, including sites of seizure onset and interictal epileptiform discharges. Main results. We detected significant interictal long-range functional connections in each subject, in some cases across hemispheres. Results were consistent between two independent datasets, and the timing and location of significant impulse responses reflected anatomical connectivity. However, within individual subjects, the spatial distribution of impulse responses was unique. In two subjects with clear seizure localization and successful surgery, the epileptogenic zone was associated with significant impulse responses. Significance. The results suggest that the spike-triggered impulse response can provide valuable information about the neuronal networks that contribute to seizures using only interictal data. This technique will enable testing of specific hypotheses regarding functional connectivity in epilepsy and the relationship between functional properties and imaging findings. Beyond epilepsy, we expect that the impulse response could be more broadly applied as a measure of long-range functional connectivity in studies of cognition.

Decoding 3D reach and grasp from hybrid signals in motor and premotor cortices: spikes, multiunit activity, and local field potentials.

PubMed

Bansal, Arjun K; Truccolo, Wilson; Vargas-Irwin, Carlos E; Donoghue, John P

2012-03-01

Neural activity in motor cortex during reach and grasp movements shows modulations in a broad range of signals from single-neuron spiking activity (SA) to various frequency bands in broadband local field potentials (LFPs). In particular, spatiotemporal patterns in multiband LFPs are thought to reflect dendritic integration of local and interareal synaptic inputs, attentional and preparatory processes, and multiunit activity (MUA) related to movement representation in the local motor area. Nevertheless, the relationship between multiband LFPs and SA, and their relationship to movement parameters and their relative value as brain-computer interface (BCI) control signals, remain poorly understood. Also, although this broad range of signals may provide complementary information channels in primary (MI) and ventral premotor (PMv) areas, areal differences in information have not been systematically examined. Here, for the first time, the amount of information in SA and multiband LFPs was compared for MI and PMv by recording from dual 96-multielectrode arrays while monkeys made naturalistic reach and grasp actions. Information was assessed as decoding accuracy for 3D arm end point and grip aperture kinematics based on SA or LFPs in MI and PMv, or combinations of signal types across areas. In contrast with previous studies with ≤16 simultaneous electrodes, here ensembles of >16 units (on average) carried more information than multiband, multichannel LFPs. Furthermore, reach and grasp information added by various LFP frequency bands was not independent from that in SA ensembles but rather typically less than and primarily contained within the latter. Notably, MI and PMv did not show a particular bias toward reach or grasp for this task or for a broad range of signal types. For BCIs, our results indicate that neuronal ensemble spiking is the preferred signal for decoding, while LFPs and combined signals from PMv and MI can add robustness to BCI control.

Decoding 3D reach and grasp from hybrid signals in motor and premotor cortices: spikes, multiunit activity, and local field potentials

PubMed Central

Truccolo, Wilson; Vargas-Irwin, Carlos E.; Donoghue, John P.

2012-01-01

Neural activity in motor cortex during reach and grasp movements shows modulations in a broad range of signals from single-neuron spiking activity (SA) to various frequency bands in broadband local field potentials (LFPs). In particular, spatiotemporal patterns in multiband LFPs are thought to reflect dendritic integration of local and interareal synaptic inputs, attentional and preparatory processes, and multiunit activity (MUA) related to movement representation in the local motor area. Nevertheless, the relationship between multiband LFPs and SA, and their relationship to movement parameters and their relative value as brain-computer interface (BCI) control signals, remain poorly understood. Also, although this broad range of signals may provide complementary information channels in primary (MI) and ventral premotor (PMv) areas, areal differences in information have not been systematically examined. Here, for the first time, the amount of information in SA and multiband LFPs was compared for MI and PMv by recording from dual 96-multielectrode arrays while monkeys made naturalistic reach and grasp actions. Information was assessed as decoding accuracy for 3D arm end point and grip aperture kinematics based on SA or LFPs in MI and PMv, or combinations of signal types across areas. In contrast with previous studies with ≤16 simultaneous electrodes, here ensembles of >16 units (on average) carried more information than multiband, multichannel LFPs. Furthermore, reach and grasp information added by various LFP frequency bands was not independent from that in SA ensembles but rather typically less than and primarily contained within the latter. Notably, MI and PMv did not show a particular bias toward reach or grasp for this task or for a broad range of signal types. For BCIs, our results indicate that neuronal ensemble spiking is the preferred signal for decoding, while LFPs and combined signals from PMv and MI can add robustness to BCI control. PMID:22157115

Characterization of long-range functional connectivity in epileptic networks by neuronal spike-triggered local field potentials

PubMed Central

Lopour, Beth A; Staba, Richard J; Stern, John M; Fried, Itzhak; Ringach, Dario L

2017-01-01

Objective Quantifying the relationship between microelectrode-recorded multi-unit activity (MUA) and local field potentials (LFPs) in distinct brain regions can provide detailed information on the extent of functional connectivity in spatially widespread networks. These methods are common in studies of cognition using non-human animal models, but are rare in humans. Here we applied a neuronal spike-triggered impulse response to electrophysiological recordings from the human epileptic brain for the first time, and we evaluate functional connectivity in relation to brain areas supporting the generation of seizures. Approach Broadband interictal electrophysiological data were recorded from microwires adapted to clinical depth electrodes that were implanted bilaterally using stereotactic techniques in six presurgical patients with medically refractory epilepsy. MUA and LFPs were isolated in each microwire, and we calculated the impulse response between the MUA on one microwire and the LFPs on a second microwire for all possible MUA/LFP pairs. Results were compared to clinical seizure localization, including sites of seizure onset and interictal epileptiform discharges. Main results We detected significant interictal long-range functional connections in each subject, in some cases across hemispheres. Results were consistent between two independent datasets, and the timing and location of significant impulse responses reflected anatomical connectivity. However, within individual subjects, the spatial distribution of impulse responses was unique. In two subjects with clear seizure localization and successful surgery, the epileptogenic zone was associated with significant impulse responses. Significance The results suggest that the spike-triggered impulse response can provide valuable information about the neuronal networks that contribute to seizures using only interictal data. This technique will enable testing of specific hypotheses regarding functional connectivity in epilepsy and the relationship between functional properties and imaging findings. Beyond epilepsy, we expect that the impulse response could be more broadly applied as a measure of long-range functional connectivity in studies of cognition. PMID:26975603

Recording human cortical population spikes non-invasively--An EEG tutorial.

PubMed

Waterstraat, Gunnar; Fedele, Tommaso; Burghoff, Martin; Scheer, Hans-Jürgen; Curio, Gabriel

2015-07-30

Non-invasively recorded somatosensory high-frequency oscillations (sHFOs) evoked by electric nerve stimulation are markers of human cortical population spikes. Previously, their analysis was based on massive averaging of EEG responses. Advanced neurotechnology and optimized off-line analysis can enhance the signal-to-noise ratio of sHFOs, eventually enabling single-trial analysis. The rationale for developing dedicated low-noise EEG technology for sHFOs is unfolded. Detailed recording procedures and tailored analysis principles are explained step-by-step. Source codes in Matlab and Python are provided as supplementary material online. Combining synergistic hardware and analysis improvements, evoked sHFOs at around 600 Hz ('σ-bursts') can be studied in single-trials. Additionally, optimized spatial filters increase the signal-to-noise ratio of components at about 1 kHz ('κ-bursts') enabling their detection in non-invasive surface EEG. sHFOs offer a unique possibility to record evoked human cortical population spikes non-invasively. The experimental approaches and algorithms presented here enable also non-specialized EEG laboratories to combine measurements of conventional low-frequency EEG with the analysis of concomitant cortical population spike responses. Copyright © 2014 Elsevier B.V. All rights reserved.

Cell-Type and State-Dependent Synchronization among Rodent Somatosensory, Visual, Perirhinal Cortex, and Hippocampus CA1

PubMed Central

Vinck, Martin; Bos, Jeroen J.; Van Mourik-Donga, Laura A.; Oplaat, Krista T.; Klein, Gerbrand A.; Jackson, Jadin C.; Gentet, Luc J.; Pennartz, Cyriel M. A.

2016-01-01

Beta and gamma rhythms have been hypothesized to be involved in global and local coordination of neuronal activity, respectively. Here, we investigated how cells in rodent area S1BF are entrained by rhythmic fluctuations at various frequencies within the local area and in connected areas, and how this depends on behavioral state and cell type. We performed simultaneous extracellular field and unit recordings in four connected areas of the freely moving rat (S1BF, V1M, perirhinal cortex, CA1). S1BF spiking activity was strongly entrained by both beta and gamma S1BF oscillations, which were associated with deactivations and activations, respectively. We identified multiple classes of fast spiking and excitatory cells in S1BF, which showed prominent differences in rhythmic entrainment and in the extent to which phase locking was modulated by behavioral state. Using an additional dataset acquired by whole-cell recordings in head-fixed mice, these cell classes could be compared with identified phenotypes showing gamma rhythmicity in their membrane potential. We next examined how S1BF cells were entrained by rhythmic fluctuations in connected brain areas. Gamma-synchronization was detected in all four areas, however we did not detect significant gamma coherence among these areas. Instead, we only found long-range coherence in the theta-beta range among these areas. In contrast to local S1BF synchronization, we found long-range S1BF-spike to CA1–LFP synchronization to be homogeneous across inhibitory and excitatory cell types. These findings suggest distinct, cell-type contributions of low and high-frequency synchronization to intra- and inter-areal neuronal interactions. PMID:26834582

Selective control of cortical axonal spikes by a slowly inactivating K+ current

PubMed Central

Shu, Yousheng; Yu, Yuguo; Yang, Jing; McCormick, David A.

2007-01-01

Neurons are flexible electrophysiological entities in which the distribution and properties of ionic channels control their behaviors. Through simultaneous somatic and axonal whole-cell recording of layer 5 pyramidal cells, we demonstrate a remarkable differential expression of slowly inactivating K+ currents. Depolarizing the axon, but not the soma, rapidly activated a low-threshold, slowly inactivating, outward current that was potently blocked by low doses of 4-aminopyridine, α-dendrotoxin, and rTityustoxin-Kα. Block of this slowly inactivating current caused a large increase in spike duration in the axon but only a small increase in the soma and could result in distal axons generating repetitive discharge in response to local current injection. Importantly, this current was also responsible for slow changes in the axonal spike duration that are observed after somatic membrane potential change. These data indicate that low-threshold, slowly inactivating K+ currents, containing Kv1.2 α subunits, play a key role in the flexible properties of intracortical axons and may contribute significantly to intracortical processing. PMID:17581873

A Primary Role for Nucleus Accumbens and Related Limbic Network in Vocal Tics.

PubMed

McCairn, Kevin W; Nagai, Yuji; Hori, Yukiko; Ninomiya, Taihei; Kikuchi, Erika; Lee, Ju-Young; Suhara, Tetsuya; Iriki, Atsushi; Minamimoto, Takafumi; Takada, Masahiko; Isoda, Masaki; Matsumoto, Masayuki

2016-01-20

Inappropriate vocal expressions, e.g., vocal tics in Tourette syndrome, severely impact quality of life. Neural mechanisms underlying vocal tics remain unexplored because no established animal model representing the condition exists. We report that unilateral disinhibition of the nucleus accumbens (NAc) generates vocal tics in monkeys. Whole-brain PET imaging identified prominent, bilateral limbic cortico-subcortical activation. Local field potentials (LFPs) developed abnormal spikes in the NAc and the anterior cingulate cortex (ACC). Vocalization could occur without obvious LFP spikes, however, when phase-phase coupling of alpha oscillations were accentuated between the NAc, ACC, and the primary motor cortex. These findings contrasted with myoclonic motor tics induced by disinhibition of the dorsolateral putamen, where PET activity was confined to the ipsilateral sensorimotor system and LFP spikes always preceded motor tics. We propose that vocal tics emerge as a consequence of dysrhythmic alpha coupling between critical nodes in the limbic and motor networks. VIDEO ABSTRACT. Copyright © 2016 Elsevier Inc. All rights reserved.

Electrocardiograms with pacemakers: accuracy of computer reading.

PubMed

Guglin, Maya E; Datwani, Neeta

2007-04-01

We analyzed the accuracy with which a computer algorithm reads electrocardiograms (ECGs) with electronic pacemakers (PMs). Electrocardiograms were screened for the presence of electronic pacing spikes. Computer-derived interpretations were compared with cardiologists' readings. Computer-drawn interpretations required revision by cardiologists in 61.3% of cases. In 18.4% of cases, the ECG reading algorithm failed to recognize the presence of a PM. The misinterpretation of paced beats as intrinsic beats led to multiple secondary errors, including myocardial infarctions in varying localization. The most common error in computer reading was the failure to identify an underlying rhythm. This error caused frequent misidentification of the PM type, especially when the presence of normal sinus rhythm was not recognized in a tracing with a DDD PM tracking the atrial activity. The increasing number of pacing devices, and the resulting number of ECGs with pacing spikes, mandates the refining of ECG reading algorithms. Improvement is especially needed in the recognition of the underlying rhythm, pacing spikes, and mode of pacing.

A Streaming PCA VLSI Chip for Neural Data Compression.

PubMed

Wu, Tong; Zhao, Wenfeng; Guo, Hongsun; Lim, Hubert H; Yang, Zhi

2017-12-01

Neural recording system miniaturization and integration with low-power wireless technologies require compressing neural data before transmission. Feature extraction is a procedure to represent data in a low-dimensional space; its integration into a recording chip can be an efficient approach to compress neural data. In this paper, we propose a streaming principal component analysis algorithm and its microchip implementation to compress multichannel local field potential (LFP) and spike data. The circuits have been designed in a 65-nm CMOS technology and occupy a silicon area of 0.06 mm. Throughout the experiments, the chip compresses LFPs by 10 at the expense of as low as 1% reconstruction errors and 144-nW/channel power consumption; for spikes, the achieved compression ratio is 25 with 8% reconstruction errors and 3.05-W/channel power consumption. In addition, the algorithm and its hardware architecture can swiftly adapt to nonstationary spiking activities, which enables efficient hardware sharing among multiple channels to support a high-channel count recorder.

Synchronous beta rhythms of frontoparietal networks support only behaviorally relevant representations

PubMed Central

Antzoulatos, Evan G; Miller, Earl K

2016-01-01

Categorization has been associated with distributed networks of the primate brain, including the prefrontal cortex (PFC) and posterior parietal cortex (PPC). Although category-selective spiking in PFC and PPC has been established, the frequency-dependent dynamic interactions of frontoparietal networks are largely unexplored. We trained monkeys to perform a delayed-match-to-spatial-category task while recording spikes and local field potentials from the PFC and PPC with multiple electrodes. We found category-selective beta- and delta-band synchrony between and within the areas. However, in addition to the categories, delta synchrony and spiking activity also reflected irrelevant stimulus dimensions. By contrast, beta synchrony only conveyed information about the task-relevant categories. Further, category-selective PFC neurons were synchronized with PPC beta oscillations, while neurons that carried irrelevant information were not. These results suggest that long-range beta-band synchrony could act as a filter that only supports neural representations of the variables relevant to the task at hand. DOI: http://dx.doi.org/10.7554/eLife.17822.001 PMID:27841747

nSTAT: Open-Source Neural Spike Train Analysis Toolbox for Matlab

PubMed Central

Cajigas, I.; Malik, W.Q.; Brown, E.N.

2012-01-01

Over the last decade there has been a tremendous advance in the analytical tools available to neuroscientists to understand and model neural function. In particular, the point process - Generalized Linear Model (PPGLM) framework has been applied successfully to problems ranging from neuro-endocrine physiology to neural decoding. However, the lack of freely distributed software implementations of published PP-GLM algorithms together with problem-specific modifications required for their use, limit wide application of these techniques. In an effort to make existing PP-GLM methods more accessible to the neuroscience community, we have developed nSTAT – an open source neural spike train analysis toolbox for Matlab®. By adopting an Object-Oriented Programming (OOP) approach, nSTAT allows users to easily manipulate data by performing operations on objects that have an intuitive connection to the experiment (spike trains, covariates, etc.), rather than by dealing with data in vector/matrix form. The algorithms implemented within nSTAT address a number of common problems including computation of peri-stimulus time histograms, quantification of the temporal response properties of neurons, and characterization of neural plasticity within and across trials. nSTAT provides a starting point for exploratory data analysis, allows for simple and systematic building and testing of point process models, and for decoding of stimulus variables based on point process models of neural function. By providing an open-source toolbox, we hope to establish a platform that can be easily used, modified, and extended by the scientific community to address limitations of current techniques and to extend available techniques to more complex problems. PMID:22981419

Bursting as a source of non-linear determinism in the firing patterns of nigral dopamine neurons.

PubMed

Jeong, Jaeseung; Shi, Wei-Xing; Hoffman, Ralph; Oh, Jihoon; Gore, John C; Bunney, Benjamin S; Peterson, Bradley S

2012-11-01

Nigral dopamine (DA) neurons in vivo exhibit complex firing patterns consisting of tonic single-spikes and phasic bursts that encode information for certain types of reward-related learning and behavior. Non-linear dynamical analysis has previously demonstrated the presence of a non-linear deterministic structure in complex firing patterns of DA neurons, yet the origin of this non-linear determinism remains unknown. In this study, we hypothesized that bursting activity is the primary source of non-linear determinism in the firing patterns of DA neurons. To test this hypothesis, we investigated the dimension complexity of inter-spike interval data recorded in vivo from bursting and non-bursting DA neurons in the chloral hydrate-anesthetized rat substantia nigra. We found that bursting DA neurons exhibited non-linear determinism in their firing patterns, whereas non-bursting DA neurons showed truly stochastic firing patterns. Determinism was also detected in the isolated burst and inter-burst interval data extracted from firing patterns of bursting neurons. Moreover, less bursting DA neurons in halothane-anesthetized rats exhibited higher dimensional spiking dynamics than do more bursting DA neurons in chloral hydrate-anesthetized rats. These results strongly indicate that bursting activity is the main source of low-dimensional, non-linear determinism in the firing patterns of DA neurons. This finding furthermore suggests that bursts are the likely carriers of meaningful information in the firing activities of DA neurons. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Use of a deuterated internal standard with pyrolysis-GC/MS dimeric marker analysis to quantify tire tread particles in the environment.

PubMed

Unice, Kenneth M; Kreider, Marisa L; Panko, Julie M

2012-11-08

Pyrolysis(pyr)-GC/MS analysis of characteristic thermal decomposition fragments has been previously used for qualitative fingerprinting of organic sources in environmental samples. A quantitative pyr-GC/MS method based on characteristic tire polymer pyrolysis products was developed for tread particle quantification in environmental matrices including soil, sediment, and air. The feasibility of quantitative pyr-GC/MS analysis of tread was confirmed in a method evaluation study using artificial soil spiked with known amounts of cryogenically generated tread. Tread concentration determined by blinded analyses was highly correlated (r2 ≥ 0.88) with the known tread spike concentration. Two critical refinements to the initial pyrolysis protocol were identified including use of an internal standard and quantification by the dimeric markers vinylcyclohexene and dipentene, which have good specificity for rubber polymer with no other appreciable environmental sources. A novel use of deuterated internal standards of similar polymeric structure was developed to correct the variable analyte recovery caused by sample size, matrix effects, and ion source variability. The resultant quantitative pyr-GC/MS protocol is reliable and transferable between laboratories.

Local excitation-inhibition ratio for synfire chain propagation in feed-forward neuronal networks

NASA Astrophysics Data System (ADS)

Guo, Xinmeng; Yu, Haitao; Wang, Jiang; Liu, Jing; Cao, Yibin; Deng, Bin

2017-09-01

A leading hypothesis holds that spiking activity propagates along neuronal sub-populations which are connected in a feed-forward manner, and the propagation efficiency would be affected by the dynamics of sub-populations. In this paper, how the interaction between local excitation and inhibition effects on synfire chain propagation in feed-forward network (FFN) is investigated. The simulation results show that there is an appropriate excitation-inhibition (EI) ratio maximizing the performance of synfire chain propagation. The optimal EI ratio can significantly enhance the selectivity of FFN to synchronous signals, which thereby increases the stability to background noise. Moreover, the effect of network topology on synfire chain propagation is also investigated. It is found that synfire chain propagation can be maximized by an optimal interlayer linking probability. We also find that external noise is detrimental to synchrony propagation by inducing spiking jitter. The results presented in this paper may provide insights into the effects of network dynamics on neuronal computations.

Theory of population coupling and applications to describe high order correlations in large populations of interacting neurons

NASA Astrophysics Data System (ADS)

Huang, Haiping

2017-03-01

To understand the collective spiking activity in neuronal populations, it is essential to reveal basic circuit variables responsible for these emergent functional states. Here, I develop a mean field theory for the population coupling recently proposed in the studies of the visual cortex of mouse and monkey, relating the individual neuron activity to the population activity, and extend the original form to the second order, relating neuron-pair’s activity to the population activity, to explain the high order correlations observed in the neural data. I test the computational framework on the salamander retinal data and the cortical spiking data of behaving rats. For the retinal data, the original form of population coupling and its advanced form can explain a significant fraction of two-cell correlations and three-cell correlations, respectively. For the cortical data, the performance becomes much better, and the second order population coupling reveals non-local effects in local cortical circuits.

Interaural Level Difference Dependent Gain Control and Synaptic Scaling Underlying Binaural Computation

PubMed Central

Xiong, Xiaorui R.; Liang, Feixue; Li, Haifu; Mesik, Lukas; Zhang, Ke K.; Polley, Daniel B.; Tao, Huizhong W.; Xiao, Zhongju; Zhang, Li I.

2013-01-01

Binaural integration in the central nucleus of inferior colliculus (ICC) plays a critical role in sound localization. However, its arithmetic nature and underlying synaptic mechanisms remain unclear. Here, we showed in mouse ICC neurons that the contralateral dominance is created by a “push-pull”-like mechanism, with contralaterally dominant excitation and more bilaterally balanced inhibition. Importantly, binaural spiking response is generated apparently from an ipsilaterally-mediated scaling of contralateral response, leaving frequency tuning unchanged. This scaling effect is attributed to a divisive attenuation of contralaterally-evoked synaptic excitation onto ICC neurons with their inhibition largely unaffected. Thus, a gain control mediates the linear transformation from monaural to binaural spike responses. The gain value is modulated by interaural level difference (ILD) primarily through scaling excitation to different levels. The ILD-dependent synaptic scaling and gain adjustment allow ICC neurons to dynamically encode interaural sound localization cues while maintaining an invariant representation of other independent sound attributes. PMID:23972599

No nitrate spikes detectable in several polar ice cores following the largest known solar events

NASA Astrophysics Data System (ADS)

Mekhaldi, Florian; McConnell, Joseph R.; Adolphi, Florian; Arienzo, Monica; Chellman, Nathan J.; Maselli, Olivia; Sigl, Michael; Muscheler, Raimund

2017-04-01

Solar energetic particle (SEP) events are a genuine and recognized threat to our modern society which is increasingly relying on satellites and technological infrastructures. However, knowledge on the frequency and on the upper limit of the intensity of major solar storms is largely limited by the relatively short direct observation period. In an effort to extend the observation period and because atmospheric ionization induced by solar particles can lead to the production of odd nitrogen, spikes in the nitrate content of ice cores have been tentatively used to reconstruct both the occurrence and intensity of past SEP events. Yet the reliability of its use as such a proxy has been long debated. This is partly due to differing chemistry-climate model outputs, equivocal detection of nitrate spikes in single ice cores for single events, and possible alternative sources to explain nitrate spikes in ice cores. Here we present nitrate measurements from several Antarctic and Greenland ice cores for time periods covering the largest known solar events. More specifically, we use new highly-resolved nitrate and biomass burning proxy species data (e.g. black carbon) from continuous flow analysis following the largest known solar events from the paleo record - the SEP events of 775 and 994 AD. We also consider the historical Carrington event of 1859 as well as contemporary events from the past 60 years which were observed by satellites. Doing so we show that i) there are no reproducible nitrate spikes in Greenland and Antarctic ice cores following any of these major events and that ii) most nitrate spikes found in ice cores are related to biomass burning plumes. Our analysis thus suggests that ice-core nitrate data is not a reliable proxy for atmospheric ionization by SEP events. In light of our results, we advocate that nitrate spikes so far identified from single ice cores should not be used to assess the intensity and occurrence rate of extreme solar events.

Investigation of uptake and retention of atmospheric Hg(II) by boreal forest plants using stable Hg isotopes

USGS Publications Warehouse

Graydon, J.A.; St. Louis, V.L.; Hintelmann, H.; Lindberg, S.E.; Sandilands, K.A.; Rudd, J.W.M.; Kelly, C.A.; Tate, M.T.; Krabbenhoft, D.P.; Lehnherr, I.

2009-01-01

Although there is now a general consensus among mercury (Hg) biogeochemists that increased atmospheric inputs of inorganic Hg(II) to lakes and watersheds can result in increased methylmercury (MeHg) concentrations in fish, researchers still lack kinetic data describing the movement of Hg from the atmosphere, through watershed and lake ecosystems, and into fish. The use of isotopically enriched Hg species in environmental studies now allows experimentally applied new Hg to be distinguished from ambient Hg naturally present in the system. Four different enriched stable Hg(II) isotope "spikes" were applied sequentially over four years to the ground vegetation of a microcatchment at the Experimental Lakes Area (ELA) in the remote boreal forest of Canada to examine retention of Hg(II) following deposition. Areal masses of the spikes and ambient THg (all forms of Hg in a sample) were monitored for eight years, and the pattern of spike retention was used to estimate retention of newly deposited ambient Hg within the ground vegetation pool. Fifty to eighty percent of applied spike Hg was initially retained by ground vegetation. The areal mass of spike Hg declined exponentially over time and was best described by a first-order process with constants (k) ranging between 9.7 ?? 10-4 day -1 and 11.6 ?? 10-4 day-1. Average half-life (t1/2) of spike Hg within the ground vegetation pool (??S.D.) was 704 ?? 52 days. This retention of new atmospheric Hg(II) by vegetation delays movement of new Hg(II) into soil, runoff, and finally into adjacent lakes. Ground-applied Hg(II) spikes were not detected in tree foliage and litterfall, indicating that stomatal and/or root uptake of previously deposited Hg (i.e., "recycled" from ground vegetation or soil Hg pools) were likely not large sources of foliar Hg under these experimental conditions. ?? 2009 American Chemical Society.

Self-consistent determination of the spike-train power spectrum in a neural network with sparse connectivity.

PubMed

Dummer, Benjamin; Wieland, Stefan; Lindner, Benjamin

2014-01-01

A major source of random variability in cortical networks is the quasi-random arrival of presynaptic action potentials from many other cells. In network studies as well as in the study of the response properties of single cells embedded in a network, synaptic background input is often approximated by Poissonian spike trains. However, the output statistics of the cells is in most cases far from being Poisson. This is inconsistent with the assumption of similar spike-train statistics for pre- and postsynaptic cells in a recurrent network. Here we tackle this problem for the popular class of integrate-and-fire neurons and study a self-consistent statistics of input and output spectra of neural spike trains. Instead of actually using a large network, we use an iterative scheme, in which we simulate a single neuron over several generations. In each of these generations, the neuron is stimulated with surrogate stochastic input that has a similar statistics as the output of the previous generation. For the surrogate input, we employ two distinct approximations: (i) a superposition of renewal spike trains with the same interspike interval density as observed in the previous generation and (ii) a Gaussian current with a power spectrum proportional to that observed in the previous generation. For input parameters that correspond to balanced input in the network, both the renewal and the Gaussian iteration procedure converge quickly and yield comparable results for the self-consistent spike-train power spectrum. We compare our results to large-scale simulations of a random sparsely connected network of leaky integrate-and-fire neurons (Brunel, 2000) and show that in the asynchronous regime close to a state of balanced synaptic input from the network, our iterative schemes provide an excellent approximations to the autocorrelation of spike trains in the recurrent network.

Selectivity of Local Field Potentials in Macaque Inferior Temporal Cortex

DTIC Science & Technology

2004-09-01

Selectivity of Local Field Potentials in Macaque Inferior Temporal Cortex Gabriel Kreiman , Chou Hung, Tomaso Poggio and James DiCarlo AI Memo 2004...IT. Note: Gabriel Kreiman and Chou Hung contributed equally to this work This report describes research done within the Center for Biological...separate the neuronal components of the MUA by using spike sorting algorithms (Quiroga et al., 2004; Yu and Kreiman , 1999). It will be interesting to

Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation.

PubMed

Augustin, Moritz; Ladenbauer, Josef; Baumann, Fabian; Obermayer, Klaus

2017-06-01

The spiking activity of single neurons can be well described by a nonlinear integrate-and-fire model that includes somatic adaptation. When exposed to fluctuating inputs sparsely coupled populations of these model neurons exhibit stochastic collective dynamics that can be effectively characterized using the Fokker-Planck equation. This approach, however, leads to a model with an infinite-dimensional state space and non-standard boundary conditions. Here we derive from that description four simple models for the spike rate dynamics in terms of low-dimensional ordinary differential equations using two different reduction techniques: one uses the spectral decomposition of the Fokker-Planck operator, the other is based on a cascade of two linear filters and a nonlinearity, which are determined from the Fokker-Planck equation and semi-analytically approximated. We evaluate the reduced models for a wide range of biologically plausible input statistics and find that both approximation approaches lead to spike rate models that accurately reproduce the spiking behavior of the underlying adaptive integrate-and-fire population. Particularly the cascade-based models are overall most accurate and robust, especially in the sensitive region of rapidly changing input. For the mean-driven regime, when input fluctuations are not too strong and fast, however, the best performing model is based on the spectral decomposition. The low-dimensional models also well reproduce stable oscillatory spike rate dynamics that are generated either by recurrent synaptic excitation and neuronal adaptation or through delayed inhibitory synaptic feedback. The computational demands of the reduced models are very low but the implementation complexity differs between the different model variants. Therefore we have made available implementations that allow to numerically integrate the low-dimensional spike rate models as well as the Fokker-Planck partial differential equation in efficient ways for arbitrary model parametrizations as open source software. The derived spike rate descriptions retain a direct link to the properties of single neurons, allow for convenient mathematical analyses of network states, and are well suited for application in neural mass/mean-field based brain network models.

Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation

PubMed Central

Baumann, Fabian; Obermayer, Klaus

2017-01-01

The spiking activity of single neurons can be well described by a nonlinear integrate-and-fire model that includes somatic adaptation. When exposed to fluctuating inputs sparsely coupled populations of these model neurons exhibit stochastic collective dynamics that can be effectively characterized using the Fokker-Planck equation. This approach, however, leads to a model with an infinite-dimensional state space and non-standard boundary conditions. Here we derive from that description four simple models for the spike rate dynamics in terms of low-dimensional ordinary differential equations using two different reduction techniques: one uses the spectral decomposition of the Fokker-Planck operator, the other is based on a cascade of two linear filters and a nonlinearity, which are determined from the Fokker-Planck equation and semi-analytically approximated. We evaluate the reduced models for a wide range of biologically plausible input statistics and find that both approximation approaches lead to spike rate models that accurately reproduce the spiking behavior of the underlying adaptive integrate-and-fire population. Particularly the cascade-based models are overall most accurate and robust, especially in the sensitive region of rapidly changing input. For the mean-driven regime, when input fluctuations are not too strong and fast, however, the best performing model is based on the spectral decomposition. The low-dimensional models also well reproduce stable oscillatory spike rate dynamics that are generated either by recurrent synaptic excitation and neuronal adaptation or through delayed inhibitory synaptic feedback. The computational demands of the reduced models are very low but the implementation complexity differs between the different model variants. Therefore we have made available implementations that allow to numerically integrate the low-dimensional spike rate models as well as the Fokker-Planck partial differential equation in efficient ways for arbitrary model parametrizations as open source software. The derived spike rate descriptions retain a direct link to the properties of single neurons, allow for convenient mathematical analyses of network states, and are well suited for application in neural mass/mean-field based brain network models. PMID:28644841

Characterization of Gladiolus Germplasm Using Morphological, Physiological, and Molecular Markers.

PubMed

Singh, Niraj; Pal, Ashish K; Roy, R K; Tewari, S K; Tamta, Sushma; Rana, T S

2018-04-01

Estimation of variability and genetic relationships among breeding materials is one of the important strategies in crop improvement programs. Morphological (plant height, spike length, a number of florets/spike), physiological (chlorophyll content, chlorophyll fluorescence, and rapid light curve parameters) and Directed amplification of minisatellite DNA (DAMD) markers were used to investigate the relationships among 50 Gladiolus cultivars. Cluster analysis based on morphological data, physiological characteristics, molecular markers, and cumulative data discriminated all cultivars into seven, five, seven, and six clusters in the unweighted pair-group method using arithmetic mean (UPGMA) dendrogram, respectively. The results of the principal coordinate analysis (PCoA) also supported UPGMA clustering. Variations among the Gladiolus cultivars at phenotypic level could be due to the changes in physiology, environmental conditions, and genetic variability. DAMD analysis using 10 primers produced 120 polymorphic bands with 80% polymorphism showing polymorphic information content (PIC = 0.28), Marker index (MI = 3.37), Nei's gene diversity (h = 0.267), and Shannon's information index (I = 0.407). Plant height showed a positive significant correlation with Spike length and Number of florets/spike (r = 0.729, p < 0.001 and r = 0.448, p = 0.001 respectively). Whereas, Spike length showed positive significant correlation with Number of florets/spike (r = 0.688, p < 0.001) and Chlorophyll content showed positive significant correlation with Electron transport rate (r = 0.863, p < 0.001). Based on significant morphological variations, high physiological performance, high genetic variability, and genetic distances between cultivars, we have been able to identify diverse cultivars of Gladiolus that could be the potential source as breeding material for further genetic improvement in this ornamental crop.

Electrical excitability: a spectrum of properties in the progeny of a single embryonic neuroblast.

PubMed Central

Goodman, C S; Pearson, K G; Spitzer, N C

1980-01-01

We have examined the range of some properties of the progeny of a single embryonic precursor cell in the grasshopper. The approximately 100 progeny of this single neuroblast share certain features such as their transmitter and some aspects of their morphology; at the same time, however, they demonstrate a broad spectrum of electrical properties, from spiking to non-spiking neurons. The first-born progeny are spiking neurons with peripheral axons. Many of the progeny, including all of the last-born, do not generate action potentials. The nonspiking progeny are local intraganglionic neurons and appear to compose a major proportion of the progeny of this neuroblast. All of the nonspiking neurons have calcium inward current channels and can make action potentials when outward current channels are blocked. We propose a model for grasshopper neurogenesis based on cell lineage such that (i) certain features (e.g., transmitter) are shared by the progeny of all cell divisions from a single neuroblast, and (ii) other features (e.g., electrical properties) are shared by the progeny of a given birth position (e.g., first versus last born) from all of the neuroblasts. According to this model, the first-born progeny from all neuroblasts are spiking neurons, whereas the last-born are nonspiking. Images PMID:6246499

Hard X-Ray Burst Detected From Caltech Plasma Jet Experiment Magnetic Reconnection Event

NASA Astrophysics Data System (ADS)

Marshall, Ryan S.; Bellan, Paul M.

2016-10-01

In the Caltech plasma jet experiment a 100 kA MHD driven jet becomes kink unstable leading to a Rayleigh-Taylor instability that quickly causes a magnetic reconnection event. Movies show that the Rayleigh-Taylor instability is simultaneous with voltage spikes across the electrodes that provide the current that drives the jet. Hard x-rays between 4 keV and 9 keV have now been observed using an x-ray scintillator detector mounted just outside of a kapton window on the vacuum chamber. Preliminary results indicate that the timing of the x-ray burst coincides with a voltage spike on the electrodes occurring in association with the Rayleigh-Taylor event. The x-ray signal accompanies the voltage spike and Rayleigh-Taylor event in approximately 50% of the shots. A possible explanation for why the x-ray signal is sometimes missing is that the magnetic reconnection event may be localized to a specific region of the plasma outside the line of sight of the scintillator. The x-ray signal has also been seen accompanying the voltage spike when no Rayleigh-Taylor is observed. This may be due to the interframe timing on the camera being longer than the very short duration of the Rayleigh-Taylor instability.

The Stereo Electron Spikes and the Interplanetary Magnetic Field

NASA Astrophysics Data System (ADS)

Jokipii, J. R.; Sheeley, N. R., Jr.; Wang, Y. M.; Giacalone, J.

2016-12-01

A recent paper (Klassen etal, 2015) discussed observations of a spike event of 55-65 keV electrons which occurred very nearly simultaneously at STEREO A and STEREO B, which at the time were separated in longitude by 38 degrees. The authors associated the spikes with a flare at the Sun near the footpoint of the nominal Archimedean spiral magnetic field line passing through STEREO A. The spike at STEREO A was delayed by 2.2 minutes from that at STEREOB. We discuss the observations in terms of a model in which the electrons, accelerated at the flare, propagate without significant scattering along magnetic field lines which separate or diverge as a function of radial distance from the Sun. The near simultaneity of the spikes at the two spacecraft is a natural consequence of this model. We interpret the divergence of the magnetic field lines as a consequence of field-line random walk and flux-tube expansion. We show that the field-line random walk in the absence of flux-tube expansion produces an rms spread of field lines significantly less than that which is required to produce to observed divergence. We find that observations of the solar wind and its source region at the time of the event can account for the observations in terms of propagation along interplanetary magnetic field-lines. Klassen, A., Dresing, N., Gomez-Herrero, R, and Heber, B., A&A 580, A115 (2015) Financial support for NS and YMW was provided by NASA and CNR.

Modeling the impact of common noise inputs on the network activity of retinal ganglion cells

PubMed Central

Ahmadian, Yashar; Shlens, Jonathon; Pillow, Jonathan W.; Kulkarni, Jayant; Litke, Alan M.; Chichilnisky, E. J.; Simoncelli, Eero; Paninski, Liam

2013-01-01

Synchronized spontaneous firing among retinal ganglion cells (RGCs), on timescales faster than visual responses, has been reported in many studies. Two candidate mechanisms of synchronized firing include direct coupling and shared noisy inputs. In neighboring parasol cells of primate retina, which exhibit rapid synchronized firing that has been studied extensively, recent experimental work indicates that direct electrical or synaptic coupling is weak, but shared synaptic input in the absence of modulated stimuli is strong. However, previous modeling efforts have not accounted for this aspect of firing in the parasol cell population. Here we develop a new model that incorporates the effects of common noise, and apply it to analyze the light responses and synchronized firing of a large, densely-sampled network of over 250 simultaneously recorded parasol cells. We use a generalized linear model in which the spike rate in each cell is determined by the linear combination of the spatio-temporally filtered visual input, the temporally filtered prior spikes of that cell, and unobserved sources representing common noise. The model accurately captures the statistical structure of the spike trains and the encoding of the visual stimulus, without the direct coupling assumption present in previous modeling work. Finally, we examined the problem of decoding the visual stimulus from the spike train given the estimated parameters. The common-noise model produces Bayesian decoding performance as accurate as that of a model with direct coupling, but with significantly more robustness to spike timing perturbations. PMID:22203465

Viterbi sparse spike detection and a compositional origin to ultralow-velocity zones

NASA Astrophysics Data System (ADS)

Brown, Samuel Paul

Accurate interpretation of seismic travel times and amplitudes in both the exploration and global scales is complicated by the band-limited nature of seismic data. We present a stochastic method, Viterbi sparse spike detection (VSSD), to reduce a seismic waveform into a most probable constituent spike train. Model waveforms are constructed from a set of candidate spike trains convolved with a source wavelet estimate. For each model waveform, a profile hidden Markov model (HMM) is constructed to represent the waveform as a stochastic generative model with a linear topology corresponding to a sequence of samples. The Viterbi algorithm is employed to simultaneously find the optimal nonlinear alignment between a model waveform and the seismic data, and to assign a score to each candidate spike train. The most probable travel times and amplitudes are inferred from the alignments of the highest scoring models. Our analyses show that the method can resolve closely spaced arrivals below traditional resolution limits and that travel time estimates are robust in the presence of random noise and source wavelet errors. We applied the VSSD method to constrain the elastic properties of a ultralow- velocity zone (ULVZ) at the core-mantle boundary beneath the Coral Sea. We analyzed vertical component short period ScP waveforms for 16 earthquakes occurring in the Tonga-Fiji trench recorded at the Alice Springs Array (ASAR) in central Australia. These waveforms show strong pre and postcursory seismic arrivals consistent with ULVZ layering. We used the VSSD method to measure differential travel-times and amplitudes of the post-cursor arrival ScSP and the precursor arrival SPcP relative to ScP. We compare our measurements to a database of approximately 340,000 synthetic seismograms finding that these data are best fit by a ULVZ model with an S-wave velocity reduction of 24%, a P-wave velocity reduction of 23%, a thickness of 8.5 km, and a density increase of 6%. We simultaneously constrain both P- and S-wave velocity reductions as a 1:1 ratio inside this ULVZ. This 1:1 ratio is not consistent with a partial melt origin to ULVZs. Rather, we demonstrate that a compositional origin is more likely.

Potassium conductance dynamics confer robust spike-time precision in a neuromorphic model of the auditory brain stem

PubMed Central

Boahen, Kwabena

2013-01-01

A fundamental question in neuroscience is how neurons perform precise operations despite inherent variability. This question also applies to neuromorphic engineering, where low-power microchips emulate the brain using large populations of diverse silicon neurons. Biological neurons in the auditory pathway display precise spike timing, critical for sound localization and interpretation of complex waveforms such as speech, even though they are a heterogeneous population. Silicon neurons are also heterogeneous, due to a key design constraint in neuromorphic engineering: smaller transistors offer lower power consumption and more neurons per unit area of silicon, but also more variability between transistors and thus between silicon neurons. Utilizing this variability in a neuromorphic model of the auditory brain stem with 1,080 silicon neurons, we found that a low-voltage-activated potassium conductance (gKL) enables precise spike timing via two mechanisms: statically reducing the resting membrane time constant and dynamically suppressing late synaptic inputs. The relative contribution of these two mechanisms is unknown because blocking gKL in vitro eliminates dynamic adaptation but also lengthens the membrane time constant. We replaced gKL with a static leak in silico to recover the short membrane time constant and found that silicon neurons could mimic the spike-time precision of their biological counterparts, but only over a narrow range of stimulus intensities and biophysical parameters. The dynamics of gKL were required for precise spike timing robust to stimulus variation across a heterogeneous population of silicon neurons, thus explaining how neural and neuromorphic systems may perform precise operations despite inherent variability. PMID:23554436

Energy-efficient STDP-based learning circuits with memristor synapses

NASA Astrophysics Data System (ADS)

Wu, Xinyu; Saxena, Vishal; Campbell, Kristy A.

2014-05-01

It is now accepted that the traditional von Neumann architecture, with processor and memory separation, is ill suited to process parallel data streams which a mammalian brain can efficiently handle. Moreover, researchers now envision computing architectures which enable cognitive processing of massive amounts of data by identifying spatio-temporal relationships in real-time and solving complex pattern recognition problems. Memristor cross-point arrays, integrated with standard CMOS technology, are expected to result in massively parallel and low-power Neuromorphic computing architectures. Recently, significant progress has been made in spiking neural networks (SNN) which emulate data processing in the cortical brain. These architectures comprise of a dense network of neurons and the synapses formed between the axons and dendrites. Further, unsupervised or supervised competitive learning schemes are being investigated for global training of the network. In contrast to a software implementation, hardware realization of these networks requires massive circuit overhead for addressing and individually updating network weights. Instead, we employ bio-inspired learning rules such as the spike-timing-dependent plasticity (STDP) to efficiently update the network weights locally. To realize SNNs on a chip, we propose to use densely integrating mixed-signal integrate-andfire neurons (IFNs) and cross-point arrays of memristors in back-end-of-the-line (BEOL) of CMOS chips. Novel IFN circuits have been designed to drive memristive synapses in parallel while maintaining overall power efficiency (<1 pJ/spike/synapse), even at spike rate greater than 10 MHz. We present circuit design details and simulation results of the IFN with memristor synapses, its response to incoming spike trains and STDP learning characterization.

Computational Modeling of Distinct Neocortical Oscillations Driven by Cell-Type Selective Optogenetic Drive: Separable Resonant Circuits Controlled by Low-Threshold Spiking and Fast-Spiking Interneurons

PubMed Central

Vierling-Claassen, Dorea; Cardin, Jessica A.; Moore, Christopher I.; Jones, Stephanie R.

2010-01-01

Selective optogenetic drive of fast-spiking (FS) interneurons (INs) leads to enhanced local field potential (LFP) power across the traditional “gamma” frequency band (20–80 Hz; Cardin et al., 2009). In contrast, drive to regular-spiking (RS) pyramidal cells enhances power at lower frequencies, with a peak at 8 Hz. The first result is consistent with previous computational studies emphasizing the role of FS and the time constant of GABAA synaptic inhibition in gamma rhythmicity. However, the same theoretical models do not typically predict low-frequency LFP enhancement with RS drive. To develop hypotheses as to how the same network can support these contrasting behaviors, we constructed a biophysically principled network model of primary somatosensory neocortex containing FS, RS, and low-threshold spiking (LTS) INs. Cells were modeled with detailed cell anatomy and physiology, multiple dendritic compartments, and included active somatic and dendritic ionic currents. Consistent with prior studies, the model demonstrated gamma resonance during FS drive, dependent on the time constant of GABAA inhibition induced by synchronous FS activity. Lower-frequency enhancement during RS drive was replicated only on inclusion of an inhibitory LTS population, whose activation was critically dependent on RS synchrony and evoked longer-lasting inhibition. Our results predict that differential recruitment of FS and LTS inhibitory populations is essential to the observed cortical dynamics and may provide a means for amplifying the natural expression of distinct oscillations in normal cortical processing. PMID:21152338

Stimulus-dependent spiking relationships with the EEG

PubMed Central

Snyder, Adam C.

2015-01-01

The development and refinement of noninvasive techniques for imaging neural activity is of paramount importance for human neuroscience. Currently, the most accessible and popular technique is electroencephalography (EEG). However, nearly all of what we know about the neural events that underlie EEG signals is based on inference, because of the dearth of studies that have simultaneously paired EEG recordings with direct recordings of single neurons. From the perspective of electrophysiologists there is growing interest in understanding how spiking activity coordinates with large-scale cortical networks. Evidence from recordings at both scales highlights that sensory neurons operate in very distinct states during spontaneous and visually evoked activity, which appear to form extremes in a continuum of coordination in neural networks. We hypothesized that individual neurons have idiosyncratic relationships to large-scale network activity indexed by EEG signals, owing to the neurons' distinct computational roles within the local circuitry. We tested this by recording neuronal populations in visual area V4 of rhesus macaques while we simultaneously recorded EEG. We found substantial heterogeneity in the timing and strength of spike-EEG relationships and that these relationships became more diverse during visual stimulation compared with the spontaneous state. The visual stimulus apparently shifts V4 neurons from a state in which they are relatively uniformly embedded in large-scale network activity to a state in which their distinct roles within the local population are more prominent, suggesting that the specific way in which individual neurons relate to EEG signals may hold clues regarding their computational roles. PMID:26108954

Rupture characteristics of the three M ∼ 4.7 (1992-1994) Parkfield earthquakes

USGS Publications Warehouse

Fletcher, Jon Peter B.; Spudich, Paul A.

1998-01-01

Slip on the San Andreas fault was determined for three M ∼ 4.7 earthquakes using a tomographic inverse system [Beroza and Spudich, 1988] to invert seismic source time functions (STFs) from S waves. STFs were obtained by deconvolving mainshock accelerograms by those from collocated smaller earthquakes. Accelerograms were from the U.S. Geological Survey Parkfield Small Aperture Array (UPSAR) and from a distributed array of digital accelerometer stations at Parkfield. Eight or nine STFs are used in each of the three inversions. STFs are typically symmetrical pulses with a duration of about 0.3–0.5 s. In the inversion, mainshock rise time was set to 0.05 s, and we allowed the rupture time to vary slightly from a constant rupture velocity of approximately 0.85β. Rupture for all three events, which are located in or close to the Middle Mountain preparation zone or box (MMB), quickly reaches a local maximum in slip and then propagates outward to peaks, ridges, or plateaus in the slip distribution. Slip for the October 20, 1992, event (located just inside the southern edge of the MMB) propagates from an initial spike north and updip along a curving ridge for about 2 km. The initial spike continued to grow in the November 14, 1993, event (located north of the October 20, 1992, event just beneath the hypocenter of the 1966 Parkfield earthquake), which shows little directivity, although there is a smaller patch of slip updip and to the south. In contrast, rupture for the December 20, 1994, event (located just south of the October 20, 1992, event) propagated north and slightly updip, creating a rough plateau in slip a few kilometers wide on a side. Directivity for this event also is to the north. Directivity for all three events points in the approximate direction of the 1966 hypocenter. Small pulses, which comprise a coda, are found on the STFs for several seconds after the initial impulsive event. Several tests based on the assumption that the average of all STFs from UPSAR for each event is an estimate of the true slip at the source suggest that the codas in the STFs are S waves from a long-duration source rather than uncorrected site response. An initiation phase is found on the array average for the November 14, 1993, and December 20, 1994, events. These precursory phases are the result of a spike in slip at the hypocenter. A value of 2.4–4 mm is obtained for Dc, the slip-weakening distance, by interpreting the initial spike as a critical patch. The few aftershocks for the October 20, 1992, event are distributed to the north and updip of the mainshock, but the November 14, 1993, event had a strong burst of aftershock activity that propagated to the north of its hypocenter at roughly the same depth. Aftershocks of the December 20, 1994, event are mostly updip. The November 14, 1993, event had the simplest slip distribution, appeared to be the most impulsive, and had the most active aftershock sequence and the greatest depth. If the eventual Parkfield earthquake initiates near the 1966 hypocenter, then the directivity of the three events studied here will have pointed to it. However, it is certainly possible that both the initiation of characteristic Parkfield shocks and the directivity of smaller events are controlled by fault properties on a larger scale such as by fault bends or jogs.

Anisotropic connectivity implements motion-based prediction in a spiking neural network.

PubMed

Kaplan, Bernhard A; Lansner, Anders; Masson, Guillaume S; Perrinet, Laurent U

2013-01-01

Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the world. Although it is becoming generally accepted, it is not clear on which level spiking neural networks may implement predictive coding and what function their connectivity may have. We present a network model of conductance-based integrate-and-fire neurons inspired by the architecture of retinotopic cortical areas that assumes predictive coding is implemented through network connectivity, namely in the connection delays and in selectiveness for the tuning properties of source and target cells. We show that the applied connection pattern leads to motion-based prediction in an experiment tracking a moving dot. In contrast to our proposed model, a network with random or isotropic connectivity fails to predict the path when the moving dot disappears. Furthermore, we show that a simple linear decoding approach is sufficient to transform neuronal spiking activity into a probabilistic estimate for reading out the target trajectory.

Community-based benchmarking improves spike rate inference from two-photon calcium imaging data.

PubMed

Berens, Philipp; Freeman, Jeremy; Deneux, Thomas; Chenkov, Nikolay; McColgan, Thomas; Speiser, Artur; Macke, Jakob H; Turaga, Srinivas C; Mineault, Patrick; Rupprecht, Peter; Gerhard, Stephan; Friedrich, Rainer W; Friedrich, Johannes; Paninski, Liam; Pachitariu, Marius; Harris, Kenneth D; Bolte, Ben; Machado, Timothy A; Ringach, Dario; Stone, Jasmine; Rogerson, Luke E; Sofroniew, Nicolas J; Reimer, Jacob; Froudarakis, Emmanouil; Euler, Thomas; Román Rosón, Miroslav; Theis, Lucas; Tolias, Andreas S; Bethge, Matthias

2018-05-01

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.

Neurobehavioral consequences of continuous spike and waves during slow sleep (CSWS) in a pediatric population: A pattern of developmental hindrance.

PubMed

De Giorgis, Valentina; Filippini, Melissa; Macasaet, Joyce Ann; Masnada, Silvia; Veggiotti, Pierangelo

2017-09-01

Continuous spike and waves during slow sleep (CSWS) is a typical EEG pattern defined as diffuse, bilateral and recently also unilateral or focal localization spike-wave occurring in slow sleep or non-rapid eye movement sleep. Literature results so far point out a progressive deterioration and decline of intellectual functioning in CSWS patients, i.e. a loss of previously normally acquired skills, as well as persistent neurobehavioral disorders, beyond seizure and EEG control. The objective of this study was to shed light on the neurobehavioral impact of CSWS and to identify the potential clinical risk factors for development. We conducted a retrospective study involving a series of 16 CSWS idiopathic patients age 3-16years, considering the entire duration of epilepsy from the onset to the outcome, i.e. remission of CSWS pattern. All patients were longitudinally assessed taking into account clinical (sex, age at onset, lateralization and localization of epileptiform abnormalities, spike wave index, number of antiepileptic drugs) and behavioral features. Intelligent Quotient (IQ) was measured in the whole sample, whereas visuo-spatial attention, visuo-motor skills, short term memory and academic abilities (reading and writing) were tested in 6 out of 16 patients. Our results showed that the most vulnerable from an intellectual point of view were those children who had an early-onset of CSWS whereas those with later onset resulted less affected (p=0.004). Neuropsychological outcome was better than the behavioral one and the lexical-semantic route in reading and writing resulted more severely affected compared to the phonological route. Cognitive deterioration is one but not the only consequence of CSWS. Especially with respect to verbal skills, CSWS is responsible of a pattern of consequences in terms of developmental hindrance, including slowing of development and stagnation, whereas deterioration is rare. Behavioral and academic problems tend to persist beyond epilepsy resolution. Copyright © 2017 Elsevier Inc. All rights reserved.

The Sustainable Energy Utility (SEU) Model for Energy Service Delivery

ERIC Educational Resources Information Center

Houck, Jason; Rickerson, Wilson

2009-01-01

Climate change, energy price spikes, and concerns about energy security have reignited interest in state and local efforts to promote end-use energy efficiency, customer-sited renewable energy, and energy conservation. Government agencies and utilities have historically designed and administered such demand-side measures, but innovative…

Gold nanoparticle induced vasculature damage in radiotherapy: Comparing protons, megavoltage photons, and kilovoltage photons

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

Lin, Yuting, E-mail: yutingl188@gmail.com; Paganetti, Harald; Schuemann, Jan

2015-10-15

Purpose: The purpose of this work is to investigate the radiosensitizing effect of gold nanoparticle (GNP) induced vasculature damage for proton, megavoltage (MV) photon, and kilovoltage (kV) photon irradiation. Methods: Monte Carlo simulations were carried out using tool for particle simulation (TOPAS) to obtain the spatial dose distribution in close proximity up to 20 μm from the GNPs. The spatial dose distribution from GNPs was used as an input to calculate the dose deposited to the blood vessels. GNP induced vasculature damage was evaluated for three particle sources (a clinical spread out Bragg peak proton beam, a 6 MV photonmore » beam, and two kV photon beams). For each particle source, various depths in tissue, GNP sizes (2, 10, and 20 nm diameter), and vessel diameters (8, 14, and 20 μm) were investigated. Two GNP distributions in lumen were considered, either homogeneously distributed in the vessel or attached to the inner wall of the vessel. Doses of 30 Gy and 2 Gy were considered, representing typical in vivo enhancement studies and conventional clinical fractionation, respectively. Results: These simulations showed that for 20 Au-mg/g GNP blood concentration homogeneously distributed in the vessel, the additional dose at the inner vascular wall encircling the lumen was 43% of the prescribed dose at the depth of treatment for the 250 kVp photon source, 1% for the 6 MV photon source, and 0.1% for the proton beam. For kV photons, GNPs caused 15% more dose in the vascular wall for 150 kVp source than for 250 kVp. For 6 MV photons, GNPs caused 0.2% more dose in the vascular wall at 20 cm depth in water as compared to at depth of maximum dose (Dmax). For proton therapy, GNPs caused the same dose in the vascular wall for all depths across the spread out Bragg peak with 12.7 cm range and 7 cm modulation. For the same weight of GNPs in the vessel, 2 nm diameter GNPs caused three times more damage to the vessel than 20 nm diameter GNPs. When the GNPs were attached to the inner vascular wall, the damage to the inner vascular wall can be up to 207% of the prescribed dose for the 250 kVp photon source, 4% for the 6 MV photon source, and 2% for the proton beam. Even though the average dose increase from the proton beam and MV photon beam was not large, there were high dose spikes that elevate the local dose of the parts of the blood vessel to be higher than 15 Gy even for 2 Gy prescribed dose, especially when the GNPs can be actively targeted to the endothelial cells. Conclusions: GNPs can potentially be used to enhance radiation therapy by causing vasculature damage through high dose spikes caused by the addition of GNPs especially for hypofractionated treatment. If GNPs are designed to actively accumulate at the tumor vasculature walls, vasculature damage can be increased significantly. The largest enhancement is seen using kilovoltage photons due to the photoelectric effect. Although no significant average dose enhancement was observed for the whole vasculature structure for both MV photons and protons, they can cause high local dose escalation (>15 Gy) to areas of the blood vessel that can potentially contribute to the disruption of the functionality of the blood vessels in the tumor.« less

Gold nanoparticle induced vasculature damage in radiotherapy: Comparing protons, megavoltage photons, and kilovoltage photons.

PubMed

Lin, Yuting; Paganetti, Harald; McMahon, Stephen J; Schuemann, Jan

2015-10-01

The purpose of this work is to investigate the radiosensitizing effect of gold nanoparticle (GNP) induced vasculature damage for proton, megavoltage (MV) photon, and kilovoltage (kV) photon irradiation. Monte Carlo simulations were carried out using tool for particle simulation (TOPAS) to obtain the spatial dose distribution in close proximity up to 20 μm from the GNPs. The spatial dose distribution from GNPs was used as an input to calculate the dose deposited to the blood vessels. GNP induced vasculature damage was evaluated for three particle sources (a clinical spread out Bragg peak proton beam, a 6 MV photon beam, and two kV photon beams). For each particle source, various depths in tissue, GNP sizes (2, 10, and 20 nm diameter), and vessel diameters (8, 14, and 20 μm) were investigated. Two GNP distributions in lumen were considered, either homogeneously distributed in the vessel or attached to the inner wall of the vessel. Doses of 30 Gy and 2 Gy were considered, representing typical in vivo enhancement studies and conventional clinical fractionation, respectively. These simulations showed that for 20 Au-mg/g GNP blood concentration homogeneously distributed in the vessel, the additional dose at the inner vascular wall encircling the lumen was 43% of the prescribed dose at the depth of treatment for the 250 kVp photon source, 1% for the 6 MV photon source, and 0.1% for the proton beam. For kV photons, GNPs caused 15% more dose in the vascular wall for 150 kVp source than for 250 kVp. For 6 MV photons, GNPs caused 0.2% more dose in the vascular wall at 20 cm depth in water as compared to at depth of maximum dose (Dmax). For proton therapy, GNPs caused the same dose in the vascular wall for all depths across the spread out Bragg peak with 12.7 cm range and 7 cm modulation. For the same weight of GNPs in the vessel, 2 nm diameter GNPs caused three times more damage to the vessel than 20 nm diameter GNPs. When the GNPs were attached to the inner vascular wall, the damage to the inner vascular wall can be up to 207% of the prescribed dose for the 250 kVp photon source, 4% for the 6 MV photon source, and 2% for the proton beam. Even though the average dose increase from the proton beam and MV photon beam was not large, there were high dose spikes that elevate the local dose of the parts of the blood vessel to be higher than 15 Gy even for 2 Gy prescribed dose, especially when the GNPs can be actively targeted to the endothelial cells. GNPs can potentially be used to enhance radiation therapy by causing vasculature damage through high dose spikes caused by the addition of GNPs especially for hypofractionated treatment. If GNPs are designed to actively accumulate at the tumor vasculature walls, vasculature damage can be increased significantly. The largest enhancement is seen using kilovoltage photons due to the photoelectric effect. Although no significant average dose enhancement was observed for the whole vasculature structure for both MV photons and protons, they can cause high local dose escalation (>15 Gy) to areas of the blood vessel that can potentially contribute to the disruption of the functionality of the blood vessels in the tumor.

Gold nanoparticle induced vasculature damage in radiotherapy: Comparing protons, megavoltage photons, and kilovoltage photons

PubMed Central

Lin, Yuting; Paganetti, Harald; McMahon, Stephen J.; Schuemann, Jan

2015-01-01

Purpose: The purpose of this work is to investigate the radiosensitizing effect of gold nanoparticle (GNP) induced vasculature damage for proton, megavoltage (MV) photon, and kilovoltage (kV) photon irradiation. Methods: Monte Carlo simulations were carried out using tool for particle simulation (TOPAS) to obtain the spatial dose distribution in close proximity up to 20 μm from the GNPs. The spatial dose distribution from GNPs was used as an input to calculate the dose deposited to the blood vessels. GNP induced vasculature damage was evaluated for three particle sources (a clinical spread out Bragg peak proton beam, a 6 MV photon beam, and two kV photon beams). For each particle source, various depths in tissue, GNP sizes (2, 10, and 20 nm diameter), and vessel diameters (8, 14, and 20 μm) were investigated. Two GNP distributions in lumen were considered, either homogeneously distributed in the vessel or attached to the inner wall of the vessel. Doses of 30 Gy and 2 Gy were considered, representing typical in vivo enhancement studies and conventional clinical fractionation, respectively. Results: These simulations showed that for 20 Au-mg/g GNP blood concentration homogeneously distributed in the vessel, the additional dose at the inner vascular wall encircling the lumen was 43% of the prescribed dose at the depth of treatment for the 250 kVp photon source, 1% for the 6 MV photon source, and 0.1% for the proton beam. For kV photons, GNPs caused 15% more dose in the vascular wall for 150 kVp source than for 250 kVp. For 6 MV photons, GNPs caused 0.2% more dose in the vascular wall at 20 cm depth in water as compared to at depth of maximum dose (Dmax). For proton therapy, GNPs caused the same dose in the vascular wall for all depths across the spread out Bragg peak with 12.7 cm range and 7 cm modulation. For the same weight of GNPs in the vessel, 2 nm diameter GNPs caused three times more damage to the vessel than 20 nm diameter GNPs. When the GNPs were attached to the inner vascular wall, the damage to the inner vascular wall can be up to 207% of the prescribed dose for the 250 kVp photon source, 4% for the 6 MV photon source, and 2% for the proton beam. Even though the average dose increase from the proton beam and MV photon beam was not large, there were high dose spikes that elevate the local dose of the parts of the blood vessel to be higher than 15 Gy even for 2 Gy prescribed dose, especially when the GNPs can be actively targeted to the endothelial cells. Conclusions: GNPs can potentially be used to enhance radiation therapy by causing vasculature damage through high dose spikes caused by the addition of GNPs especially for hypofractionated treatment. If GNPs are designed to actively accumulate at the tumor vasculature walls, vasculature damage can be increased significantly. The largest enhancement is seen using kilovoltage photons due to the photoelectric effect. Although no significant average dose enhancement was observed for the whole vasculature structure for both MV photons and protons, they can cause high local dose escalation (>15 Gy) to areas of the blood vessel that can potentially contribute to the disruption of the functionality of the blood vessels in the tumor. PMID:26429263

Lessons learned in preparing method 29 filters for compliance testing audits.

PubMed

Martz, R F; McCartney, J E; Bursey, J T; Riley, C E

2000-01-01

Companies conducting compliance testing are required to analyze audit samples at the time they collect and analyze the stack samples if audit samples are available. Eastern Research Group (ERG) provides technical support to the EPA's Emission Measurements Center's Stationary Source Audit Program (SSAP) for developing, preparing, and distributing performance evaluation samples and audit materials. These audit samples are requested via the regulatory Agency and include spiked audit materials for EPA Method 29-Metals Emissions from Stationary Sources, as well as other methods. To provide appropriate audit materials to federal, state, tribal, and local governments, as well as agencies performing environmental activities and conducting emission compliance tests, ERG has recently performed testing of blank filter materials and preparation of spiked filters for EPA Method 29. For sampling stationary sources using an EPA Method 29 sampling train, the use of filters without organic binders containing less than 1.3 microg/in.2 of each of the metals to be measured is required. Risk Assessment testing imposes even stricter requirements for clean filter background levels. Three vendor sources of quartz fiber filters were evaluated for background contamination to ensure that audit samples would be prepared using filters with the lowest metal background levels. A procedure was developed to test new filters, and a cleaning procedure was evaluated to see if a greater level of cleanliness could be achieved using an acid rinse with new filters. Background levels for filters supplied by different vendors and within lots of filters from the same vendor showed a wide variation, confirmed through contact with several analytical laboratories that frequently perform EPA Method 29 analyses. It has been necessary to repeat more than one compliance test because of suspect metals background contamination levels. An acid cleaning step produced improvement in contamination level, but the difference was not significant for most of the Method 29 target metals. As a result of our studies, we conclude: Filters for Method 29 testing should be purchased in lots as large as possible. Testing firms should pre-screen new boxes and/or new lots of filters used for Method 29 testing. Random analysis of three filters (top, middle, bottom of the box) from a new box of vendor filters before allowing them to be used in field tests is a prudent approach. A box of filters from a given vendor should be screened, and filters from this screened box should be used both for testing and as field blanks in each test scenario to provide the level of quality assurance required for stationary source testing.

Volatile organic compound emissions from the oil and natural gas industry in the Uinta Basin, Utah: point sources compared to ambient air composition

NASA Astrophysics Data System (ADS)

Warneke, C.; Geiger, F.; Edwards, P. M.; Dube, W.; Pétron, G.; Kofler, J.; Zahn, A.; Brown, S. S.; Graus, M.; Gilman, J.; Lerner, B.; Peischl, J.; Ryerson, T. B.; de Gouw, J. A.; Roberts, J. M.

2014-05-01

The emissions of volatile organic compounds (VOCs) associated with oil and natural gas production in the Uinta Basin, Utah were measured at a ground site in Horse Pool and from a NOAA mobile laboratory with PTR-MS instruments. The VOC compositions in the vicinity of individual gas and oil wells and other point sources such as evaporation ponds, compressor stations and injection wells are compared to the measurements at Horse Pool. High mixing ratios of aromatics, alkanes, cycloalkanes and methanol were observed for extended periods of time and short-term spikes caused by local point sources. The mixing ratios during the time the mobile laboratory spent on the well pads were averaged. High mixing ratios were found close to all point sources, but gas wells using dry-gas collection, which means dehydration happens at the well, were clearly associated with higher mixing ratios than other wells. Another large source was the flowback pond near a recently hydraulically re-fractured gas well. The comparison of the VOC composition of the emissions from the oil and natural gas wells showed that wet gas collection wells compared well with the majority of the data at Horse Pool and that oil wells compared well with the rest of the ground site data. Oil wells on average emit heavier compounds than gas wells. The mobile laboratory measurements confirm the results from an emissions inventory: the main VOC source categories from individual point sources are dehydrators, oil and condensate tank flashing and pneumatic devices and pumps. Raw natural gas is emitted from the pneumatic devices and pumps and heavier VOC mixes from the tank flashings.

Passive dendrites enable single neurons to compute linearly non-separable functions.

PubMed

Cazé, Romain Daniel; Humphries, Mark; Gutkin, Boris

2013-01-01

Local supra-linear summation of excitatory inputs occurring in pyramidal cell dendrites, the so-called dendritic spikes, results in independent spiking dendritic sub-units, which turn pyramidal neurons into two-layer neural networks capable of computing linearly non-separable functions, such as the exclusive OR. Other neuron classes, such as interneurons, may possess only a few independent dendritic sub-units, or only passive dendrites where input summation is purely sub-linear, and where dendritic sub-units are only saturating. To determine if such neurons can also compute linearly non-separable functions, we enumerate, for a given parameter range, the Boolean functions implementable by a binary neuron model with a linear sub-unit and either a single spiking or a saturating dendritic sub-unit. We then analytically generalize these numerical results to an arbitrary number of non-linear sub-units. First, we show that a single non-linear dendritic sub-unit, in addition to the somatic non-linearity, is sufficient to compute linearly non-separable functions. Second, we analytically prove that, with a sufficient number of saturating dendritic sub-units, a neuron can compute all functions computable with purely excitatory inputs. Third, we show that these linearly non-separable functions can be implemented with at least two strategies: one where a dendritic sub-unit is sufficient to trigger a somatic spike; another where somatic spiking requires the cooperation of multiple dendritic sub-units. We formally prove that implementing the latter architecture is possible with both types of dendritic sub-units whereas the former is only possible with spiking dendrites. Finally, we show how linearly non-separable functions can be computed by a generic two-compartment biophysical model and a realistic neuron model of the cerebellar stellate cell interneuron. Taken together our results demonstrate that passive dendrites are sufficient to enable neurons to compute linearly non-separable functions.

Passive Dendrites Enable Single Neurons to Compute Linearly Non-separable Functions

PubMed Central

Cazé, Romain Daniel; Humphries, Mark; Gutkin, Boris

2013-01-01

Local supra-linear summation of excitatory inputs occurring in pyramidal cell dendrites, the so-called dendritic spikes, results in independent spiking dendritic sub-units, which turn pyramidal neurons into two-layer neural networks capable of computing linearly non-separable functions, such as the exclusive OR. Other neuron classes, such as interneurons, may possess only a few independent dendritic sub-units, or only passive dendrites where input summation is purely sub-linear, and where dendritic sub-units are only saturating. To determine if such neurons can also compute linearly non-separable functions, we enumerate, for a given parameter range, the Boolean functions implementable by a binary neuron model with a linear sub-unit and either a single spiking or a saturating dendritic sub-unit. We then analytically generalize these numerical results to an arbitrary number of non-linear sub-units. First, we show that a single non-linear dendritic sub-unit, in addition to the somatic non-linearity, is sufficient to compute linearly non-separable functions. Second, we analytically prove that, with a sufficient number of saturating dendritic sub-units, a neuron can compute all functions computable with purely excitatory inputs. Third, we show that these linearly non-separable functions can be implemented with at least two strategies: one where a dendritic sub-unit is sufficient to trigger a somatic spike; another where somatic spiking requires the cooperation of multiple dendritic sub-units. We formally prove that implementing the latter architecture is possible with both types of dendritic sub-units whereas the former is only possible with spiking dendrites. Finally, we show how linearly non-separable functions can be computed by a generic two-compartment biophysical model and a realistic neuron model of the cerebellar stellate cell interneuron. Taken together our results demonstrate that passive dendrites are sufficient to enable neurons to compute linearly non-separable functions. PMID:23468600

Topographic prominence discriminator for the detection of short-latency spikes of retinal ganglion cells

NASA Astrophysics Data System (ADS)

Choi, Myoung-Hwan; Ahn, Jungryul; Park, Dae Jin; Lee, Sang Min; Kim, Kwangsoo; Cho, Dong-il Dan; Senok, Solomon S.; Koo, Kyo-in; Goo, Yong Sook

2017-02-01

Objective. Direct stimulation of retinal ganglion cells in degenerate retinas by implanting epi-retinal prostheses is a recognized strategy for restoration of visual perception in patients with retinitis pigmentosa or age-related macular degeneration. Elucidating the best stimulus-response paradigms in the laboratory using multielectrode arrays (MEA) is complicated by the fact that the short-latency spikes (within 10 ms) elicited by direct retinal ganglion cell (RGC) stimulation are obscured by the stimulus artifact which is generated by the electrical stimulator. Approach. We developed an artifact subtraction algorithm based on topographic prominence discrimination, wherein the duration of prominences within the stimulus artifact is used as a strategy for identifying the artifact for subtraction and clarifying the obfuscated spikes which are then quantified using standard thresholding. Main results. We found that the prominence discrimination based filters perform creditably in simulation conditions by successfully isolating randomly inserted spikes in the presence of simple and even complex residual artifacts. We also show that the algorithm successfully isolated short-latency spikes in an MEA-based recording from degenerate mouse retinas, where the amplitude and frequency characteristics of the stimulus artifact vary according to the distance of the recording electrode from the stimulating electrode. By ROC analysis of false positive and false negative first spike detection rates in a dataset of one hundred and eight RGCs from four retinal patches, we found that the performance of our algorithm is comparable to that of a generally-used artifact subtraction filter algorithm which uses a strategy of local polynomial approximation (SALPA). Significance. We conclude that the application of topographic prominence discrimination is a valid and useful method for subtraction of stimulation artifacts with variable amplitudes and shapes. We propose that our algorithm may be used as stand-alone or supplementary to other artifact subtraction algorithms like SALPA.

Enhanced Burst-Suppression and Disruption of Local Field Potential Synchrony in a Mouse Model of Focal Cortical Dysplasia Exhibiting Spike-Wave Seizures.

PubMed

Williams, Anthony J; Zhou, Chen; Sun, Qian-Quan

2016-01-01

Focal cortical dysplasias (FCDs) are a common cause of brain seizures and are often associated with intractable epilepsy. Here we evaluated aberrant brain neurophysiology in an in vivo mouse model of FCD induced by neonatal freeze lesions (FLs) to the right cortical hemisphere (near S1). Linear multi-electrode arrays were used to record extracellular potentials from cortical and subcortical brain regions near the FL in anesthetized mice (5-13 months old) followed by 24 h cortical electroencephalogram (EEG) recordings. Results indicated that FL animals exhibit a high prevalence of spontaneous spike-wave discharges (SWDs), predominately during sleep (EEG), and an increase in the incidence of hyper-excitable burst/suppression activity under general anesthesia (extracellular recordings, 0.5%-3.0% isoflurane). Brief periods of burst activity in the local field potential (LFP) typically presented as an arrhythmic pattern of increased theta-alpha spectral peaks (4-12 Hz) on a background of low-amplitude delta activity (1-4 Hz), were associated with an increase in spontaneous spiking of cortical neurons, and were highly synchronized in control animals across recording sites in both cortical and subcortical layers (average cross-correlation values ranging from +0.73 to +1.0) with minimal phase shift between electrodes. However, in FL animals, cortical vs. subcortical burst activity was strongly out of phase with significantly lower cross-correlation values compared to controls (average values of -0.1 to +0.5, P < 0.05 between groups). In particular, a marked reduction in the level of synchronous burst activity was observed, the closer the recording electrodes were to the malformation (Pearson's Correlation = 0.525, P < 0.05). In a subset of FL animals (3/9), burst activity also included a spike or spike-wave pattern similar to the SWDs observed in unanesthetized animals. In summary, neonatal FLs increased the hyperexcitable pattern of burst activity induced by anesthesia and disrupted field potential synchrony between cortical and subcortical brain regions near the site of the cortical malformation. Monitoring the altered electrophysiology of burst activity under general anesthesia with multi-dimensional micro-electrode arrays may serve to define distinct neurophysiological biomarkers of epileptogenesis in human brain and improve techniques for surgical resection of epileptogenic malformed brain tissue.

Effects of grain species and cultivar, thermal processing, and enzymatic hydrolysis on gluten quantitation.

PubMed

Pahlavan, Autusa; Sharma, Girdhari M; Pereira, Marion; Williams, Kristina M

2016-10-01

Gluten from wheat, rye, and barley can trigger IgE-mediated allergy or Celiac disease in sensitive individuals. Gluten-free labeled foods are available as a safe alternative. Immunoassays such as the enzyme-linked immunosorbent assay (ELISA) are commonly used to quantify gluten in foods. However, various non-assay related factors can affect gluten quantitation. The effect of gluten-containing grain cultivars, thermal processing, and enzymatic hydrolysis on gluten quantitation by various ELISA kits was evaluated. The ELISA kits exhibited variations in gluten quantitation depending on the gluten-containing grain and their cultivars. Acceptable gluten recoveries were obtained in 200mg/kg wheat, rye, and barley-spiked corn flour thermally processed at various conditions. However, depending on the enzyme, gluten grain source, and ELISA kit used, measured gluten content was significantly reduced in corn flour spiked with 200mg/kg hydrolyzed wheat, rye, and barley flour. Thus, the gluten grain source and processing conditions should be considered for accurate gluten analysis. Published by Elsevier Ltd.

Receptive field optimisation and supervision of a fuzzy spiking neural network.

PubMed

Glackin, Cornelius; Maguire, Liam; McDaid, Liam; Sayers, Heather

2011-04-01

This paper presents a supervised training algorithm that implements fuzzy reasoning on a spiking neural network. Neuron selectivity is facilitated using receptive fields that enable individual neurons to be responsive to certain spike train firing rates and behave in a similar manner as fuzzy membership functions. The connectivity of the hidden and output layers in the fuzzy spiking neural network (FSNN) is representative of a fuzzy rule base. Fuzzy C-Means clustering is utilised to produce clusters that represent the antecedent part of the fuzzy rule base that aid classification of the feature data. Suitable cluster widths are determined using two strategies; subjective thresholding and evolutionary thresholding respectively. The former technique typically results in compact solutions in terms of the number of neurons, and is shown to be particularly suited to small data sets. In the latter technique a pool of cluster candidates is generated using Fuzzy C-Means clustering and then a genetic algorithm is employed to select the most suitable clusters and to specify cluster widths. In both scenarios, the network is supervised but learning only occurs locally as in the biological case. The advantages and disadvantages of the network topology for the Fisher Iris and Wisconsin Breast Cancer benchmark classification tasks are demonstrated and directions of current and future work are discussed. Copyright © 2010 Elsevier Ltd. All rights reserved.

The inverse problem in electroencephalography using the bidomain model of electrical activity.

PubMed

Lopez Rincon, Alejandro; Shimoda, Shingo

2016-12-01

Acquiring information about the distribution of electrical sources in the brain from electroencephalography (EEG) data remains a significant challenge. An accurate solution would provide an understanding of the inner mechanisms of the electrical activity in the brain and information about damaged tissue. In this paper, we present a methodology for reconstructing brain electrical activity from EEG data by using the bidomain formulation. The bidomain model considers continuous active neural tissue coupled with a nonlinear cell model. Using this technique, we aim to find the brain sources that give rise to the scalp potential recorded by EEG measurements taking into account a non-static reconstruction. We simulate electrical sources in the brain volume and compare the reconstruction to the minimum norm estimates (MNEs) and low resolution electrical tomography (LORETA) results. Then, with the EEG dataset from the EEG Motor Movement/Imagery Database of the Physiobank, we identify the reaction to visual stimuli by calculating the time between stimulus presentation and the spike in electrical activity. Finally, we compare the activation in the brain with the registered activation using the LinkRbrain platform. Our methodology shows an improved reconstruction of the electrical activity and source localization in comparison with MNE and LORETA. For the Motor Movement/Imagery Database, the reconstruction is consistent with the expected position and time delay generated by the stimuli. Thus, this methodology is a suitable option for continuously reconstructing brain potentials. Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.

Subthalamic, not striatal, activity correlates with basal ganglia downstream activity in normal and parkinsonian monkeys

PubMed Central

Deffains, Marc; Iskhakova, Liliya; Katabi, Shiran; Haber, Suzanne N; Israel, Zvi; Bergman, Hagai

2016-01-01

The striatum and the subthalamic nucleus (STN) constitute the input stage of the basal ganglia (BG) network and together innervate BG downstream structures using GABA and glutamate, respectively. Comparison of the neuronal activity in BG input and downstream structures reveals that subthalamic, not striatal, activity fluctuations correlate with modulations in the increase/decrease discharge balance of BG downstream neurons during temporal discounting classical condition task. After induction of parkinsonism with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), abnormal low beta (8-15 Hz) spiking and local field potential (LFP) oscillations resonate across the BG network. Nevertheless, LFP beta oscillations entrain spiking activity of STN, striatal cholinergic interneurons and BG downstream structures, but do not entrain spiking activity of striatal projection neurons. Our results highlight the pivotal role of STN divergent projections in BG physiology and pathophysiology and may explain why STN is such an effective site for invasive treatment of advanced Parkinson's disease and other BG-related disorders. DOI: http://dx.doi.org/10.7554/eLife.16443.001 PMID:27552049

Neural Correlation Is Stimulus Modulated by Feedforward Inhibitory Circuitry

PubMed Central

Middleton, Jason W.; Omar, Cyrus; Doiron, Brent; Simons, Daniel J.

2012-01-01

Correlated variability of neural spiking activity has important consequences for signal processing. How incoming sensory signals shape correlations of population responses remains unclear. Cross-correlations between spiking of different neurons may be particularly consequential in sparsely firing neural populations such as those found in layer 2/3 of sensory cortex. In rat whisker barrel cortex, we found that pairs of excitatory layer 2/3 neurons exhibit similarly low levels of spike count correlation during both spontaneous and sensory-evoked states. The spontaneous activity of excitatory–inhibitory neuron pairs is positively correlated, while sensory stimuli actively decorrelate joint responses. Computational modeling shows how threshold nonlinearities and local inhibition form the basis of a general decorrelating mechanism. We show that inhibitory population activity maintains low correlations in excitatory populations, especially during periods of sensory-evoked coactivation. The role of feedforward inhibition has been previously described in the context of trial-averaged phenomena. Our findings reveal a novel role for inhibition to shape correlations of neural variability and thereby prevent excessive correlations in the face of feedforward sensory-evoked activation. PMID:22238086

Use of a Deuterated Internal Standard with Pyrolysis-GC/MS Dimeric Marker Analysis to Quantify Tire Tread Particles in the Environment

PubMed Central

Unice, Kenneth M.; Kreider, Marisa L.; Panko, Julie M.

2012-01-01

Pyrolysis(pyr)-GC/MS analysis of characteristic thermal decomposition fragments has been previously used for qualitative fingerprinting of organic sources in environmental samples. A quantitative pyr-GC/MS method based on characteristic tire polymer pyrolysis products was developed for tread particle quantification in environmental matrices including soil, sediment, and air. The feasibility of quantitative pyr-GC/MS analysis of tread was confirmed in a method evaluation study using artificial soil spiked with known amounts of cryogenically generated tread. Tread concentration determined by blinded analyses was highly correlated (r2 ≥ 0.88) with the known tread spike concentration. Two critical refinements to the initial pyrolysis protocol were identified including use of an internal standard and quantification by the dimeric markers vinylcyclohexene and dipentene, which have good specificity for rubber polymer with no other appreciable environmental sources. A novel use of deuterated internal standards of similar polymeric structure was developed to correct the variable analyte recovery caused by sample size, matrix effects, and ion source variability. The resultant quantitative pyr-GC/MS protocol is reliable and transferable between laboratories. PMID:23202830

How to generate a sound-localization map in fish

NASA Astrophysics Data System (ADS)

van Hemmen, J. Leo

2015-03-01

How sound localization is represented in the fish brain is a research field largely unbiased by theoretical analysis and computational modeling. Yet, there is experimental evidence that the axes of particle acceleration due to underwater sound are represented through a map in the midbrain of fish, e.g., in the torus semicircularis of the rainbow trout (Wubbels et al. 1997). How does such a map arise? Fish perceive pressure gradients by their three otolithic organs, each of which comprises a dense, calcareous, stone that is bathed in endolymph and attached to a sensory epithelium. In rainbow trout, the sensory epithelia of left and right utricle lie in the horizontal plane and consist of hair cells with equally distributed preferred orientations. We model the neuronal response of this system on the basis of Schuijf's vector detection hypothesis (Schuijf et al. 1975) and introduce a temporal spike code of sound direction, where optimality of hair cell orientation θj with respect to the acceleration direction θs is mapped onto spike phases via a von-Mises distribution. By learning to tune in to the earliest synchronized activity, nerve cells in the midbrain generate a map under the supervision of a locally excitatory, yet globally inhibitory visual teacher. Work done in collaboration with Daniel Begovic. Partially supported by BCCN - Munich.

The electrophysiological "delayed effect" of focal interictal epileptiform discharges. A low resolution electromagnetic tomography (LORETA) study.

PubMed

Clemens, Béla; Piros, Pálma; Bessenyei, Mónika; Varga, Edit; Puskás, Szilvia; Fekete, István

2009-08-01

Collating the findings regarding the role of focal interictal epileptiform discharges (IEDs) on CNS functions raises the possibility that IEDs might have negative impact that outlasts the duration of the spike-and-wave complexes. The aim of this study was the electrophysiological demonstration of the "delayed effect" of the IEDs. 19-channel, linked-ears referenced, digital waking EEG records of 11 children (aged 6-14 years, eight with idiopathic, three with cryptogenic focal epilepsy, showing a single spike focus) were retrospectively selected from our database. A minimum of 20 (preferably, 30), 2-s epochs containing a single focal spike-and-wave complex were selected (Spike epochs). Thereafter, Postspike-1 (Ps1), Postspike-2 (Ps2) and Postspike-3 (Ps3) epochs were selected, representing the first and second seconds (Ps1), the third and fourth seconds (Ps2) and the fifth and sixth seconds (Ps3) after the Spike epoch, respectively. Interspike epochs (Is) were selected at a distance at least 10s after the Spike epoch. Individual analysis: the frequency of interest (FOI=the individual frequency of the wave component of the IEDs), and the region of interest (ROI=the site of the IEDs) were identified by reading the raw EEG waveform and the instant power spectrum. Very narrow band LORETA (low resolution electromagnetic tomography) analysis at the FOI and ROI was carried out. Age-adjusted, Z-transformed LORETA "activity" (=current source density, amperes/meters squared) was compared in the Spike, Ps1, Ps2, Ps3 and Is epochs. the greatest (uppermost pathological) Z-scores and the greatest spatial extension of the LORETA-abnormality were always found in the Spike epochs, followed by the gradual decrease of activity in terms of severity and spatial extension in the Ps1, Ps2, Ps3 epochs. The lowest (baseline) level and extension of the abnormality was found in the Is epochs. Group analysis: average values of activity across the patients were computed for the temporal decrease of the abnormality. a clear tendency for the decrease of abnormality was demonstrated. the "delayed effect" of the IEDs was demonstrated electrophysiologically and quantified. The method may be utilized in the individual assessment of the effect of IEDs on cortical activity, the degree and temporo-spatial extension of the abnormality.

In Canada: Litigating Literacy

ERIC Educational Resources Information Center

Robertson, Heather-jane

2004-01-01

While Canadians tend to consider the American system to be overly litigious, they are catching up fast. Their own domestic set of plaintiffs is suing the agents of obesity and pollution, but actions pertaining to education seem to be spiking as well. A few of these cases are trivial. This morning's local newspaper reports that a judge has ruled…

76 FR 68699 - Approval and Promulgation of Air Quality Implementation Plans; Pennsylvania; Adoption of the...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-07

... river basin with spikes in localized PM 2.5 concentrations that coincide with temperature inversions... an inversion break, the monitor returns to a level comparable to, and sometimes less than, the... often occur within the Liberty-Clairton Area during periods of strong nocturnal inversions. When this...

Feature extraction across individual time series observations with spikes using wavelet principal component analysis.

PubMed

Røislien, Jo; Winje, Brita

2013-09-20

Clinical studies frequently include repeated measurements of individuals, often for long periods. We present a methodology for extracting common temporal features across a set of individual time series observations. In particular, the methodology explores extreme observations within the time series, such as spikes, as a possible common temporal phenomenon. Wavelet basis functions are attractive in this sense, as they are localized in both time and frequency domains simultaneously, allowing for localized feature extraction from a time-varying signal. We apply wavelet basis function decomposition of individual time series, with corresponding wavelet shrinkage to remove noise. We then extract common temporal features using linear principal component analysis on the wavelet coefficients, before inverse transformation back to the time domain for clinical interpretation. We demonstrate the methodology on a subset of a large fetal activity study aiming to identify temporal patterns in fetal movement (FM) count data in order to explore formal FM counting as a screening tool for identifying fetal compromise and thus preventing adverse birth outcomes. Copyright © 2013 John Wiley & Sons, Ltd.

On-chip photonic transistor based on the spike synchronization in circuit QED

NASA Astrophysics Data System (ADS)

Gül, Yusuf

2018-03-01

We consider the single photon transistor in coupled cavity system of resonators interacting with multilevel superconducting artificial atom simultaneously. Effective single mode transformation is used for the diagonalization of the Hamiltonian and impedance matching in terms of the normal modes. Storage and transmission of the incident field are described by the interactions between the cavities controlling the atomic transitions of lowest lying states. Rabi splitting of vacuum-induced multiphoton transitions is considered in input/output relations by the quadrature operators in the absence of the input field. Second-order coherence functions are employed to investigate the photon blockade and delocalization-localization transitions of cavity fields. Spontaneous virtual photon conversion into real photons is investigated in localized and oscillating regimes. Reflection and transmission of cavity output fields are investigated in the presence of the multilevel transitions. Accumulation and firing of the reflected and transmitted fields are used to investigate the synchronization of the bunching spike train of transmitted field and population imbalance of cavity fields. In the presence of single photon gate field, gain enhancement is explained for transmitted regime.

Synaptic and nonsynaptic plasticity approximating probabilistic inference

PubMed Central

Tully, Philip J.; Hennig, Matthias H.; Lansner, Anders

2014-01-01

Learning and memory operations in neural circuits are believed to involve molecular cascades of synaptic and nonsynaptic changes that lead to a diverse repertoire of dynamical phenomena at higher levels of processing. Hebbian and homeostatic plasticity, neuromodulation, and intrinsic excitability all conspire to form and maintain memories. But it is still unclear how these seemingly redundant mechanisms could jointly orchestrate learning in a more unified system. To this end, a Hebbian learning rule for spiking neurons inspired by Bayesian statistics is proposed. In this model, synaptic weights and intrinsic currents are adapted on-line upon arrival of single spikes, which initiate a cascade of temporally interacting memory traces that locally estimate probabilities associated with relative neuronal activation levels. Trace dynamics enable synaptic learning to readily demonstrate a spike-timing dependence, stably return to a set-point over long time scales, and remain competitive despite this stability. Beyond unsupervised learning, linking the traces with an external plasticity-modulating signal enables spike-based reinforcement learning. At the postsynaptic neuron, the traces are represented by an activity-dependent ion channel that is shown to regulate the input received by a postsynaptic cell and generate intrinsic graded persistent firing levels. We show how spike-based Hebbian-Bayesian learning can be performed in a simulated inference task using integrate-and-fire (IAF) neurons that are Poisson-firing and background-driven, similar to the preferred regime of cortical neurons. Our results support the view that neurons can represent information in the form of probability distributions, and that probabilistic inference could be a functional by-product of coupled synaptic and nonsynaptic mechanisms operating over several timescales. The model provides a biophysical realization of Bayesian computation by reconciling several observed neural phenomena whose functional effects are only partially understood in concert. PMID:24782758

Spike propagation through the dorsal root ganglia in an unmyelinated sensory neuron: a modeling study

PubMed Central

Sundt, Danielle; Gamper, Nikita

2015-01-01

Unmyelinated C-fibers are a major type of sensory neurons conveying pain information. Action potential conduction is regulated by the bifurcation (T-junction) of sensory neuron axons within the dorsal root ganglia (DRG). Understanding how C-fiber signaling is influenced by the morphology of the T-junction and the local expression of ion channels is important for understanding pain signaling. In this study we used biophysical computer modeling to investigate the influence of axon morphology within the DRG and various membrane conductances on the reliability of spike propagation. As expected, calculated input impedance and the amplitude of propagating action potentials were both lowest at the T-junction. Propagation reliability for single spikes was highly sensitive to the diameter of the stem axon and the density of voltage-gated Na+ channels. A model containing only fast voltage-gated Na+ and delayed-rectifier K+ channels conducted trains of spikes up to frequencies of 110 Hz. The addition of slowly activating KCNQ channels (i.e., KV7 or M-channels) to the model reduced the following frequency to 30 Hz. Hyperpolarization produced by addition of a much slower conductance, such as a Ca2+-dependent K+ current, was needed to reduce the following frequency to 6 Hz. Attenuation of driving force due to ion accumulation or hyperpolarization produced by a Na+-K+ pump had no effect on following frequency but could influence the reliability of spike propagation mutually with the voltage shift generated by a Ca2+-dependent K+ current. These simulations suggest how specific ion channels within the DRG may contribute toward therapeutic treatments for chronic pain. PMID:26334005

Action potential processing in a detailed Purkinje cell model reveals a critical role for axonal compartmentalization

PubMed Central

Masoli, Stefano; Solinas, Sergio; D'Angelo, Egidio

2015-01-01

The Purkinje cell (PC) is among the most complex neurons in the brain and plays a critical role for cerebellar functioning. PCs operate as fast pacemakers modulated by synaptic inputs but can switch from simple spikes to complex bursts and, in some conditions, show bistability. In contrast to original works emphasizing dendritic Ca-dependent mechanisms, recent experiments have supported a primary role for axonal Na-dependent processing, which could effectively regulate spike generation and transmission to deep cerebellar nuclei (DCN). In order to account for the numerous ionic mechanisms involved (at present including Nav1.6, Cav2.1, Cav3.1, Cav3.2, Cav3.3, Kv1.1, Kv1.5, Kv3.3, Kv3.4, Kv4.3, KCa1.1, KCa2.2, KCa3.1, Kir2.x, HCN1), we have elaborated a multicompartmental model incorporating available knowledge on localization and gating of PC ionic channels. The axon, including initial segment (AIS) and Ranvier nodes (RNs), proved critical to obtain appropriate pacemaking and firing frequency modulation. Simple spikes initiated in the AIS and protracted discharges were stabilized in the soma through Na-dependent mechanisms, while somato-dendritic Ca channels contributed to sustain pacemaking and to generate complex bursting at high discharge regimes. Bistability occurred only following Na and Ca channel down-regulation. In addition, specific properties in RNs K currents were required to limit spike transmission frequency along the axon. The model showed how organized electroresponsive functions could emerge from the molecular complexity of PCs and showed that the axon is fundamental to complement ionic channel compartmentalization enabling action potential processing and transmission of specific spike patterns to DCN. PMID:25759640

Archeomagnetic intensity spikes: global or regional geomagnetic field features?

NASA Astrophysics Data System (ADS)

Korte, Monika; Constable, Catherine G.

2018-03-01

Variations of the geomagnetic field prior to direct observations are inferred from archeo- and paleomagnetic experiments. Seemingly unusual variations not seen in the present day and historical field are of particular interest to constrain the full range of core dynamics. Recently, archeomagnetic intensity spikes, characterised by very high field values that appear to be associated with rapid secular variation rates, have been reported from several parts of the world. They were first noted in data from the Levant at around 900 BCE. A recent re-assessment of previous and new Levantine data, involving a rigorous quality assessment, interprets the observations as an extreme local geomagnetic high with at least two intensity spikes between the 11^{th} and 8^{th} centuries BCE. Subsequent reports of similar features from Asia, the Canary Islands and Texas raise the question of whether such features might be common occurrences, or whether they might even be part of a global magnetic field feature. Here we use spherical harmonic modelling to test two hypotheses: firstly, whether the Levantine and other potential spikes might be associated with higher dipole field intensity than shown by existing global field models around 1000 BCE, and secondly, whether the observations from different parts of the world are compatible with a westward drifting intense flux patch. Our results suggest that the spikes originate from intense flux patches growing and decaying mostly in situ, combined with stronger and more variable dipole moment than shown by previous global field models. Axial dipole variations no more than 60% higher than observed in the present field, probably within the range of normal geodynamo behaviour, seem sufficient to explain the observations.

Graded, Dynamically Routable Information Processing with Synfire-Gated Synfire Chains.

PubMed

Wang, Zhuo; Sornborger, Andrew T; Tao, Louis

2016-06-01

Coherent neural spiking and local field potentials are believed to be signatures of the binding and transfer of information in the brain. Coherent activity has now been measured experimentally in many regions of mammalian cortex. Recently experimental evidence has been presented suggesting that neural information is encoded and transferred in packets, i.e., in stereotypical, correlated spiking patterns of neural activity. Due to their relevance to coherent spiking, synfire chains are one of the main theoretical constructs that have been appealed to in order to describe coherent spiking and information transfer phenomena. However, for some time, it has been known that synchronous activity in feedforward networks asymptotically either approaches an attractor with fixed waveform and amplitude, or fails to propagate. This has limited the classical synfire chain's ability to explain graded neuronal responses. Recently, we have shown that pulse-gated synfire chains are capable of propagating graded information coded in mean population current or firing rate amplitudes. In particular, we showed that it is possible to use one synfire chain to provide gating pulses and a second, pulse-gated synfire chain to propagate graded information. We called these circuits synfire-gated synfire chains (SGSCs). Here, we present SGSCs in which graded information can rapidly cascade through a neural circuit, and show a correspondence between this type of transfer and a mean-field model in which gating pulses overlap in time. We show that SGSCs are robust in the presence of variability in population size, pulse timing and synaptic strength. Finally, we demonstrate the computational capabilities of SGSC-based information coding by implementing a self-contained, spike-based, modular neural circuit that is triggered by streaming input, processes the input, then makes a decision based on the processed information and shuts itself down.

On the origin of the extracellular field potential in the nucleus laminaris of the barn owl (Tyto alba).

PubMed

Kuokkanen, Paula T; Wagner, Hermann; Ashida, Go; Carr, Catherine E; Kempter, Richard

2010-10-01

The neurophonic is a sound-evoked, frequency-following potential that can be recorded extracellularly in nucleus laminaris of the barn owl. The origin of the neurophonic, and thus the mechanisms that give rise to its exceptional temporal precision, has not yet been identified. Putative generators of the neurophonic are the activity of afferent axons, synaptic activation of laminaris neurons, or action potentials in laminaris neurons. To identify the generators, we analyzed the neurophonic in the high-frequency (>2.5 kHz) region of nucleus laminaris in response to monaural pure-tone stimulation. The amplitude of the neurophonic is typically in the millivolt range. The signal-to-noise ratio reaches values beyond 30 dB. To assess which generators could give rise to these large, synchronous extracellular potentials, we developed a computational model. Spike trains were produced by an inhomogeneous Poisson process and convolved with a spike waveform. The model explained the dependence of the simulated neurophonic on parameters such as the mean rate, the vector strength of phase locking, the number of statistically independent sources, and why the signal-to-noise ratio is independent of the spike waveform and subsequent filtering of the signal. We found that several hundred sources are needed to reach the observed signal-to-noise ratio. The summed coherent signal from the densely packed afferent axons and activation of their synapses on laminaris neurons are alone sufficient to explain the measured properties of the neurophonic.

Transgenerational isotopic marking of carp Cyprinus carpio, L. using a 86Sr /84Sr double spike

NASA Astrophysics Data System (ADS)

Zitek, Andreas; Cervicek, Magdalena; Irrgeher, Johanna; Horsky, Monika; Kletzl, Manfred; Weismann, Thomas; Prohaska, Thomas

2013-04-01

Transgenerational isotopic marking has been recognized recently as an effective tool for mass marking and tracking of individual fish to their original source. Compared to other conventional marking techniques, transgenerational marking offers several advantages. Most importantly, it is possible to mark all offspring of one individual female without the necessity of handling eggs or larval fish. Furthermore it is possible to vary the concentrations of individual isotopes to obtain specific marks for individual female fish. An enriched isotopic spike solution is usually applied to gravid female spawners by injection into the body cavity for transgenerational marking. The isotope is then incorporated into the central otolith region of the offspring which is known to be built up by maternally derived material. Within this study transgenerational marking of a typical cyprinid fish species, Cyprinus carpio, L., was tested using a 86Sr /84Sr double spike. Buffered solutions with different isotopic composition and concentrations were administered to 4 female individuals by intraperitoneal injection 5 days before spawning, while one female was injected a blank solution. After spawning, otoliths (Lapilli) from juvenile fish were sampled at the age of about 5 months at fish sizes between 3 and 4 cm and analyzed for their isotopic composition by LA-ICPMS applying cross sectional line scans. Central otolith regions of the progeny showed a shift in the natural isotope ratios for the administered isotopes. Deconvolution of the blank corrected measurement data of the Sr isotopes was done to trace back the original spike ratio. The different spike ratios could be well distinguished reflecting the original composition of the spike solution. This study proved that it is possible to create batch-specific unique transgenerational marks in otolith cores by varying the concentrations of two naturally occurring Sr isotopes. This method has high potential to reduce the marking effort for any application in aquaculture and ecological research and management where the tracking of high numbers of offspring is needed.

Intra-day signal instabilities affect decoding performance in an intracortical neural interface system.

PubMed

Perge, János A; Homer, Mark L; Malik, Wasim Q; Cash, Sydney; Eskandar, Emad; Friehs, Gerhard; Donoghue, John P; Hochberg, Leigh R

2013-06-01

Motor neural interface systems (NIS) aim to convert neural signals into motor prosthetic or assistive device control, allowing people with paralysis to regain movement or control over their immediate environment. Effector or prosthetic control can degrade if the relationship between recorded neural signals and intended motor behavior changes. Therefore, characterizing both biological and technological sources of signal variability is important for a reliable NIS. To address the frequency and causes of neural signal variability in a spike-based NIS, we analyzed within-day fluctuations in spiking activity and action potential amplitude recorded with silicon microelectrode arrays implanted in the motor cortex of three people with tetraplegia (BrainGate pilot clinical trial, IDE). 84% of the recorded units showed a statistically significant change in apparent firing rate (3.8 ± 8.71 Hz or 49% of the mean rate) across several-minute epochs of tasks performed on a single session, and 74% of the units showed a significant change in spike amplitude (3.7 ± 6.5 µV or 5.5% of mean spike amplitude). 40% of the recording sessions showed a significant correlation in the occurrence of amplitude changes across electrodes, suggesting array micro-movement. Despite the relatively frequent amplitude changes, only 15% of the observed within-day rate changes originated from recording artifacts such as spike amplitude change or electrical noise, while 85% of the rate changes most likely emerged from physiological mechanisms. Computer simulations confirmed that systematic rate changes of individual neurons could produce a directional 'bias' in the decoded neural cursor movements. Instability in apparent neuronal spike rates indeed yielded a directional bias in 56% of all performance assessments in participant cursor control (n = 2 participants, 108 and 20 assessments over two years), resulting in suboptimal performance in these sessions. We anticipate that signal acquisition and decoding methods that can adapt to the reported instabilities will further improve the performance of intracortically-based NISs.

Local Wavelet-Based Filtering of Electromyographic Signals to Eliminate the Electrocardiographic-Induced Artifacts in Patients with Spinal Cord Injury

PubMed Central

Nitzken, Matthew; Bajaj, Nihit; Aslan, Sevda; Gimel’farb, Georgy; Ovechkin, Alexander

2013-01-01

Surface Electromyography (EMG) is a standard method used in clinical practice and research to assess motor function in order to help with the diagnosis of neuromuscular pathology in human and animal models. EMG recorded from trunk muscles involved in the activity of breathing can be used as a direct measure of respiratory motor function in patients with spinal cord injury (SCI) or other disorders associated with motor control deficits. However, EMG potentials recorded from these muscles are often contaminated with heart-induced electrocardiographic (ECG) signals. Elimination of these artifacts plays a critical role in the precise measure of the respiratory muscle electrical activity. This study was undertaken to find an optimal approach to eliminate the ECG artifacts from EMG recordings. Conventional global filtering can be used to decrease the ECG-induced artifact. However, this method can alter the EMG signal and changes physiologically relevant information. We hypothesize that, unlike global filtering, localized removal of ECG artifacts will not change the original EMG signals. We develop an approach to remove the ECG artifacts without altering the amplitude and frequency components of the EMG signal by using an externally recorded ECG signal as a mask to locate areas of the ECG spikes within EMG data. These segments containing ECG spikes were decomposed into 128 sub-wavelets by a custom-scaled Morlet Wavelet Transform. The ECG-related sub-wavelets at the ECG spike location were removed and a de-noised EMG signal was reconstructed. Validity of the proposed method was proven using mathematical simulated synthetic signals and EMG obtained from SCI patients. We compare the Root-mean Square Error and the Relative Change in Variance between this method, global, notch and adaptive filters. The results show that the localized wavelet-based filtering has the benefit of not introducing error in the native EMG signal and accurately removing ECG artifacts from EMG signals. PMID:24307920

Local Wavelet-Based Filtering of Electromyographic Signals to Eliminate the Electrocardiographic-Induced Artifacts in Patients with Spinal Cord Injury.

PubMed

Nitzken, Matthew; Bajaj, Nihit; Aslan, Sevda; Gimel'farb, Georgy; El-Baz, Ayman; Ovechkin, Alexander

2013-07-18

Surface Electromyography (EMG) is a standard method used in clinical practice and research to assess motor function in order to help with the diagnosis of neuromuscular pathology in human and animal models. EMG recorded from trunk muscles involved in the activity of breathing can be used as a direct measure of respiratory motor function in patients with spinal cord injury (SCI) or other disorders associated with motor control deficits. However, EMG potentials recorded from these muscles are often contaminated with heart-induced electrocardiographic (ECG) signals. Elimination of these artifacts plays a critical role in the precise measure of the respiratory muscle electrical activity. This study was undertaken to find an optimal approach to eliminate the ECG artifacts from EMG recordings. Conventional global filtering can be used to decrease the ECG-induced artifact. However, this method can alter the EMG signal and changes physiologically relevant information. We hypothesize that, unlike global filtering, localized removal of ECG artifacts will not change the original EMG signals. We develop an approach to remove the ECG artifacts without altering the amplitude and frequency components of the EMG signal by using an externally recorded ECG signal as a mask to locate areas of the ECG spikes within EMG data. These segments containing ECG spikes were decomposed into 128 sub-wavelets by a custom-scaled Morlet Wavelet Transform. The ECG-related sub-wavelets at the ECG spike location were removed and a de-noised EMG signal was reconstructed. Validity of the proposed method was proven using mathematical simulated synthetic signals and EMG obtained from SCI patients. We compare the Root-mean Square Error and the Relative Change in Variance between this method, global, notch and adaptive filters. The results show that the localized wavelet-based filtering has the benefit of not introducing error in the native EMG signal and accurately removing ECG artifacts from EMG signals.

Stimulus dependence of local field potential spectra: experiment versus theory.

PubMed

Barbieri, Francesca; Mazzoni, Alberto; Logothetis, Nikos K; Panzeri, Stefano; Brunel, Nicolas

2014-10-29

The local field potential (LFP) captures different neural processes, including integrative synaptic dynamics that cannot be observed by measuring only the spiking activity of small populations. Therefore, investigating how LFP power is modulated by external stimuli can offer important insights into sensory neural representations. However, gaining such insight requires developing data-driven computational models that can identify and disambiguate the neural contributions to the LFP. Here, we investigated how networks of excitatory and inhibitory integrate-and-fire neurons responding to time-dependent inputs can be used to interpret sensory modulations of LFP spectra. We computed analytically from such models the LFP spectra and the information that they convey about input and used these analytical expressions to fit the model to LFPs recorded in V1 of anesthetized macaques (Macaca mulatta) during the presentation of color movies. Our expressions explain 60%-98% of the variance of the LFP spectrum shape and its dependency upon movie scenes and we achieved this with realistic values for the best-fit parameters. In particular, synaptic best-fit parameters were compatible with experimental measurements and the predictions of firing rates, based only on the fit of LFP data, correlated with the multiunit spike rate recorded from the same location. Moreover, the parameters characterizing the input to the network across different movie scenes correlated with cross-scene changes of several image features. Our findings suggest that analytical descriptions of spiking neuron networks may become a crucial tool for the interpretation of field recordings. Copyright © 2014 the authors 0270-6474/14/3414589-17$15.00/0.

TRPC6-mediated ERK1/2 Activation Regulates Neuronal Excitability via Subcellular Kv4.3 Localization in the Rat Hippocampus

PubMed Central

Kim, Ji-Eun; Park, Jin-Young; Kang, Tae-Cheon

2017-01-01

Recently, we have reported that transient receptor potential channel-6 (TRPC6) plays an important role in the regulation of neuronal excitability and synchronization of spiking activity in the dentate granule cells (DGC). However, the underlying mechanisms of TRPC6 in these phenomena have been still unclear. In the present study, we investigated the role of TRPC6 in subcellular localization of Kv4.3 and its relevance to neuronal excitability in the rat hippocampus. TRPC6 knockdown increased excitability and inhibitory transmission in the DGC and the CA1 neurons in response to a paired-pulse stimulus. However, TRPC6 knockdown impaired γ-aminobutyric acid (GABA)ergic inhibition in the hippocampus during and after high-frequency stimulation (HFS). TRPC6 knockdown reduced the Kv4.3 clusters in membrane fractions and its dendritic localization on DGC and GABAergic interneurons. TRPC6 knockdown also decreased extracellular signal-regulated kinase 1/2 (ERK1/2) phosphorylation and the efficacy of 4-aminopyridine (4-AP) in neuronal excitability. An ERK1/2 inhibitor generated multiple population spikes in response to a paired-pulse stimulus, concomitant with reduced membrane Kv4.3 translocation. A TRPC6 activator (hyperforin) reversed the effects of TRPC knockdown, except paired-pulse inhibition. These findings provide valuable clues indicating that TRPC6-mediated ERK1/2 activation may regulate subcellular Kv4.3 localization in DGC and interneurons, which is cause-effect relationship between neuronal excitability and seizure susceptibility. PMID:29326557

Impact of local traffic exclusion on near-road air quality: findings from the New York City "Summer Streets" campaign.

PubMed

Whitlow, Thomas H; Hall, Andrew; Zhang, K Max; Anguita, Juan

2011-01-01

We monitored curbside airborne particulate matter (PM) concentrations and its proinflammatory capacity during 3 weekends when vehicle traffic was excluded from Park. Ave., New York City. Fine PM concentration peaked in the morning regardless of traffic while ultrafine PM was 58% lower during mornings without traffic. Ultrafine PM concentration varied linearly with traffic flow, while fine PM spiked sharply in response to random traffic events that were weakly correlated with the traffic signal cycle. Ultrafine PM concentrations decayed exponentially with distance from a cross street with unrestricted traffic flow, reaching background levels within 100 m of the source. IL-6 induction was typically highest on Friday afternoons but showed no clear relationship to the presence of traffic. The coarse fraction (>2.5 μm) had the greatest intrinsic inflammatory capacity, suggesting that coarse PM still warrants attention even as the research focus is shifting to nano-particles. Copyright © 2011 Elsevier Ltd. All rights reserved.

Background levels of methane in Mars' atmosphere show strong seasonal variations.

PubMed

Webster, Christopher R; Mahaffy, Paul R; Atreya, Sushil K; Moores, John E; Flesch, Gregory J; Malespin, Charles; McKay, Christopher P; Martinez, German; Smith, Christina L; Martin-Torres, Javier; Gomez-Elvira, Javier; Zorzano, Maria-Paz; Wong, Michael H; Trainer, Melissa G; Steele, Andrew; Archer, Doug; Sutter, Brad; Coll, Patrice J; Freissinet, Caroline; Meslin, Pierre-Yves; Gough, Raina V; House, Christopher H; Pavlov, Alexander; Eigenbrode, Jennifer L; Glavin, Daniel P; Pearson, John C; Keymeulen, Didier; Christensen, Lance E; Schwenzer, Susanne P; Navarro-Gonzalez, Rafael; Pla-García, Jorge; Rafkin, Scot C R; Vicente-Retortillo, Álvaro; Kahanpää, Henrik; Viudez-Moreiras, Daniel; Smith, Michael D; Harri, Ari-Matti; Genzer, Maria; Hassler, Donald M; Lemmon, Mark; Crisp, Joy; Sander, Stanley P; Zurek, Richard W; Vasavada, Ashwin R

2018-06-08

Variable levels of methane in the martian atmosphere have eluded explanation partly because the measurements are not repeatable in time or location. We report in situ measurements at Gale crater made over a 5-year period by the Tunable Laser Spectrometer on the Curiosity rover. The background levels of methane have a mean value 0.41 ± 0.16 parts per billion by volume (ppbv) (95% confidence interval) and exhibit a strong, repeatable seasonal variation (0.24 to 0.65 ppbv). This variation is greater than that predicted from either ultraviolet degradation of impact-delivered organics on the surface or from the annual surface pressure cycle. The large seasonal variation in the background and occurrences of higher temporary spikes (~7 ppbv) are consistent with small localized sources of methane released from martian surface or subsurface reservoirs. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Prefrontal Parvalbumin Neurons in Control of Attention

PubMed Central

Kim, Hoseok; Ährlund-Richter, Sofie; Wang, Xinming; Deisseroth, Karl; Carlén, Marie

2016-01-01

Summary While signatures of attention have been extensively studied in sensory systems, the neural sources and computations responsible for top-down control of attention are largely unknown. Using chronic recordings in mice, we found that fast-spiking parvalbumin (FS-PV) interneurons in medial prefrontal cortex (mPFC) uniformly show increased and sustained firing during goal-driven attentional processing, correlating to the level of attention. Elevated activity of FS-PV neurons on the timescale of seconds predicted successful execution of behavior. Successful allocation of attention was characterized by strong synchronization of FS-PV neurons, increased gamma oscillations, and phase locking of pyramidal firing. Phase-locked pyramidal neurons showed gamma-phase-dependent rate modulation during successful attentional processing. Optogenetic silencing of FS-PV neurons deteriorated attentional processing, while optogenetic synchronization of FS-PV neurons at gamma frequencies had pro-cognitive effects and improved goal-directed behavior. FS-PV neurons thus act as a functional unit coordinating the activity in the local mPFC circuit during goal-driven attentional processing. PMID:26771492

Visually Evoked Spiking Evolves While Spontaneous Ongoing Dynamics Persist

PubMed Central

Huys, Raoul; Jirsa, Viktor K.; Darokhan, Ziauddin; Valentiniene, Sonata; Roland, Per E.

2016-01-01

Neurons in the primary visual cortex spontaneously spike even when there are no visual stimuli. It is unknown whether the spiking evoked by visual stimuli is just a modification of the spontaneous ongoing cortical spiking dynamics or whether the spontaneous spiking state disappears and is replaced by evoked spiking. This study of laminar recordings of spontaneous spiking and visually evoked spiking of neurons in the ferret primary visual cortex shows that the spiking dynamics does not change: the spontaneous spiking as well as evoked spiking is controlled by a stable and persisting fixed point attractor. Its existence guarantees that evoked spiking return to the spontaneous state. However, the spontaneous ongoing spiking state and the visual evoked spiking states are qualitatively different and are separated by a threshold (separatrix). The functional advantage of this organization is that it avoids the need for a system reorganization following visual stimulation, and impedes the transition of spontaneous spiking to evoked spiking and the propagation of spontaneous spiking from layer 4 to layers 2–3. PMID:26778982

Uncovering Neuronal Networks Defined by Consistent Between-Neuron Spike Timing from Neuronal Spike Recordings

PubMed Central

2018-01-01

Abstract It is widely assumed that distributed neuronal networks are fundamental to the functioning of the brain. Consistent spike timing between neurons is thought to be one of the key principles for the formation of these networks. This can involve synchronous spiking or spiking with time delays, forming spike sequences when the order of spiking is consistent. Finding networks defined by their sequence of time-shifted spikes, denoted here as spike timing networks, is a tremendous challenge. As neurons can participate in multiple spike sequences at multiple between-spike time delays, the possible complexity of networks is prohibitively large. We present a novel approach that is capable of (1) extracting spike timing networks regardless of their sequence complexity, and (2) that describes their spiking sequences with high temporal precision. We achieve this by decomposing frequency-transformed neuronal spiking into separate networks, characterizing each network’s spike sequence by a time delay per neuron, forming a spike sequence timeline. These networks provide a detailed template for an investigation of the experimental relevance of their spike sequences. Using simulated spike timing networks, we show network extraction is robust to spiking noise, spike timing jitter, and partial occurrences of the involved spike sequences. Using rat multineuron recordings, we demonstrate the approach is capable of revealing real spike timing networks with sub-millisecond temporal precision. By uncovering spike timing networks, the prevalence, structure, and function of complex spike sequences can be investigated in greater detail, allowing us to gain a better understanding of their role in neuronal functioning. PMID:29789811

Laboratory study of PCB transport from primary sources to settled dust

EPA Science Inventory

Transport of house dust and Arizona Test Dust on polychlorinated biphenyl (PCB)-containing panels and PCB-free panels was investigated in a 30-m3 stainless steel chamber. The PCB-containing panels were aluminum sheets coated with a PCB-spiked, oil-based primer or two-part polysul...

A protozoal-associated epizootic impacting marine wildlife: Mass-mortality of southern sea otters (Enhydra lutris nereis) due to Sarcocystis neurona infection

PubMed Central

Conrad, Patricia A.; Harris, Michael; Hatfield, Brian; Langlois, Gregg; Jessup, David A.; Magargal, Spencer L.; Packham, Andrea E.; Toy-Choutka, Sharon; Melli, Ann C.; Murray, Michael A.; Gulland, Frances M.; Grigg, Michael E.

2016-01-01

During April, 2004, 40 sick and dead southern sea otters (Enhydra lutris nereis) were recovered over 18 km of coastline near Morro Bay, California. This event represented the single largest monthly spike in mortality ever recorded during 30 years of southern sea otter stranding data collection. Because of the point-source nature of the event and clinical signs consistent with severe, acute neurological disease, exposure to a chemical or marine toxin was initially considered. However, detailed postmortem examinations revealed lesions consistent with an infectious etiology, and further investigation confirmed the protozoan parasite Sarcocystis neurona as the underlying cause. Tissues from 94% of examined otters were PCR-positive for S. neurona, based on DNA amplification and sequencing at the ITS-1 locus, and 100% of tested animals (n = 14) had elevated IgM and IgG titers to S. neurona. Evidence to support the point-source character of this event include the striking spatial and temporal clustering of cases and detection of high concentrations of anti-S. neurona IgM in serum of stranded animals. Concurrent exposure to the marine biotoxin domoic acid may have enhanced susceptibility of affected otters to S. neurona and exacerbated the neurological signs exhibited by stranded animals. Other factors that may have contributed to the severity of this epizootic include a large rainstorm that preceded the event and an abundance of razor clams near local beaches, attracting numerous otters close to shore within the affected area. This is the first report of a localized epizootic in marine wildlife caused by apicomplexan protozoa. PMID:20615616

A protozoal-associated epizootic impacting marine wildlife: mass-mortality of southern sea otters (Enhydra lutris nereis) due to Sarcocystis neurona infection.

PubMed

Miller, Melissa A; Conrad, Patricia A; Harris, Michael; Hatfield, Brian; Langlois, Gregg; Jessup, David A; Magargal, Spencer L; Packham, Andrea E; Toy-Choutka, Sharon; Melli, Ann C; Murray, Michael A; Gulland, Frances M; Grigg, Michael E

2010-09-20

During April 2004, 40 sick and dead southern sea otters (Enhydra lutris nereis) were recovered over 18km of coastline near Morro Bay, California. This event represented the single largest monthly spike in mortality ever recorded during 30 years of southern sea otter stranding data collection. Because of the point-source nature of the event and clinical signs consistent with severe, acute neurological disease, exposure to a chemical or marine toxin was initially considered. However, detailed postmortem examinations revealed lesions consistent with an infectious etiology, and further investigation confirmed the protozoan parasite Sarcocystis neurona as the underlying cause. Tissues from 94% of examined otters were PCR-positive for S. neurona, based on DNA amplification and sequencing at the ITS-1 locus, and 100% of tested animals (n=14) had elevated IgM and IgG titers to S. neurona. Evidence to support the point-source character of this event include the striking spatial and temporal clustering of cases and detection of high concentrations of anti-S. neurona IgM in serum of stranded animals. Concurrent exposure to the marine biotoxin domoic acid may have enhanced susceptibility of affected otters to S. neurona and exacerbated the neurological signs exhibited by stranded animals. Other factors that may have contributed to the severity of this epizootic include a large rainstorm that preceded the event and an abundance of razor clams near local beaches, attracting numerous otters close to shore within the affected area. This is the first report of a localized epizootic in marine wildlife caused by apicomplexan protozoa.

Using computer simulations to determine the limitations of dynamic clamp stimuli applied at the soma in mimicking distributed conductance sources.

PubMed

Lin, Risa J; Jaeger, Dieter

2011-05-01

In previous studies we used the technique of dynamic clamp to study how temporal modulation of inhibitory and excitatory inputs control the frequency and precise timing of spikes in neurons of the deep cerebellar nuclei (DCN). Although this technique is now widely used, it is limited to interpreting conductance inputs as being location independent; i.e., all inputs that are biologically distributed across the dendritic tree are applied to the soma. We used computer simulations of a morphologically realistic model of DCN neurons to compare the effects of purely somatic vs. distributed dendritic inputs in this cell type. We applied the same conductance stimuli used in our published experiments to the model. To simulate variability in neuronal responses to repeated stimuli, we added a somatic white current noise to reproduce subthreshold fluctuations in the membrane potential. We were able to replicate our dynamic clamp results with respect to spike rates and spike precision for different patterns of background synaptic activity. We found only minor differences in the spike pattern generation between focal or distributed input in this cell type even when strong inhibitory or excitatory bursts were applied. However, the location dependence of dynamic clamp stimuli is likely to be different for each cell type examined, and the simulation approach developed in the present study will allow a careful assessment of location dependence in all cell types.

Laboratory study of PCB transport from primary sources to ...

EPA Pesticide Factsheets

Transport of house dust and Arizona Test Dust on polychlorinated biphenyl (PCB)-containing panels and PCB-free panels was investigated in a 30-m3 stainless steel chamber. The PCB-containing panels were aluminum sheets coated with a PCB-spiked, oil-based primer or two-part polysulfide caulk. The PCB-free panels were coated with the same materials but they were not spiked with PCBs. The dust was weighed and spread on the panels as evenly as possible. The dust on each panel was collected at different times to determine its PCB content. The dust data collected from the PCB panels were used to evaluate the PCB migration from the source to the dust through direct contact, and the data from the PCB-free panels were used to evaluate the sorption of PCBs through the dust/air partition. Settled dust can adsorb PCBs from air. The sorption concentration was dependent on the congener concentration in the air and favored less volatile congeners. When the house dust was in direct contact with a primary source, PCBs migrated into the dust at a much faster rate than the PCB transfer rate due to the dust/air partition. Unlike the dust/air partition, the dust/source partition was not significantly affected by the volatility of the congener. This research is important to decision makers, environmental engineers, and researchers who are concerned with risk assessment and risk management for PCB contamination.

Nitrate Deposition to Surface Snow at Summit, Greenland, Following the 9 November 2000 Solar Proton Event

NASA Technical Reports Server (NTRS)

Duderstadt, Katharine A.; Dibb, Jack E.; Schwadron, Nathan A.; Spence, Harlan E.; Jackman, Charles Herbert; Randall, Cora E.; Solomon, Stanley C.; Mills, Michael J.

2014-01-01

This study considers whether spurious peaks in nitrate ions in snow sampled at Summit, Greenland from August 2000 to August 2002 are related to solar proton events. After identifying tropospheric sources of nitrate on the basis of correlations with sulfate, ammonium, sodium, and calcium, we use the three-dimensional global Whole Atmosphere Community Climate Model (WACCM) to examine unaccounted for nitrate spikes. Model calculations confirm that solar proton events significantly impact HOx, NOx, and O3 levels in the mesosphere and stratosphere during the weeks and months following the major 9 November 2000 solar proton event. However, SPE-enhanced NOy calculated within the atmospheric column is too small to account for the observed nitrate ion peaks in surface snow. Instead, our WACCM results suggest that nitrate spikes not readily accounted for by measurement correlations are likely of anthropogenic origin. These results, consistent with other recent studies, imply that nitrate spikes in ice cores are not suitable proxies for individual SPEs and motivate the need to identify alternative proxies.

Two Coincidence Detectors for Spike Timing-Dependent Plasticity in Somatosensory Cortex

PubMed Central

Bender, Vanessa A.; Bender, Kevin J.; Brasier, Daniel J.; Feldman, Daniel E.

2011-01-01

Many cortical synapses exhibit spike timing-dependent plasticity (STDP) in which the precise timing of presynaptic and postsynaptic spikes induces synaptic strengthening [long-term potentiation (LTP)] or weakening [long-term depression (LTD)]. Standard models posit a single, postsynaptic, NMDA receptor-based coincidence detector for LTP and LTD components of STDP. We show instead that STDP at layer 4 to layer 2/3 synapses in somatosensory (S1) cortex involves separate calcium sources and coincidence detection mechanisms for LTP and LTD. LTP showed classical NMDA receptor dependence. LTD was independent of postsynaptic NMDA receptors and instead required group I metabotropic glutamate receptors and calcium from voltage-sensitive channels and IP3 receptor-gated stores. Downstream of postsynaptic calcium, LTD required retrograde endocannabinoid signaling, leading to presynaptic LTD expression, and also required activation of apparently presynaptic NMDA receptors. These LTP and LTD mechanisms detected firing coincidence on ~25 and ~125 ms time scales, respectively, and combined to implement the overall STDP rule. These findings indicate that STDP is not a unitary process and suggest that endocannabinoid-dependent LTD may be relevant to cortical map plasticity. PMID:16624937

On the origin of multiply-impulsive emission from solar flares. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Karpen, J. T.

1980-01-01

A set of solar hard X-ray bursts observed with the hard X-ray burst spectrometer on board the OSO-5 satellite was analyzed. The multiply-impulsive two stage events were selected on the basis of both morphological characteristics and association with appropriate phenomena at other wavelengths. Coincident radio, soft X-ray, H-alpha interplanetary particle, and magnetographic data were obtained from several observatories, to aid in developing a comprehensive picture of the physical processes underlying these complex bursts. Two classes of multiply impulsive bursts were identified: events whose components spikes apparently originate in one location, and events in which groups of spikes appear to come from separate regions which flare sequentially. The origin of multiplicity in the case of a single source region remains unidentified. Purely impulsive emissions show no sign of betatron acceleration, thus eliminating this mechanisn as a candidate for inducing multiply spiked structure. The majority of the two stage bursts, however, exhibited spectral behavior consistent with the betatron model, for the first few minutes of the second stage. Betatron acceleration thus has been identified as a common second stage phenomenon.

Methodological considerations for detection of terrestrial small-body salamander eDNA and implications for biodiversity conservation

USGS Publications Warehouse

Walker, Donald M.; Leys, Jacob E.; Dunham, Kelly E.; Oliver, Joshua C.; Schiller, Emily E.; Stephenson, Kelsey S.; Kimrey, John T.; Wooten, Jessica; Rogers, Mark W.

2017-01-01

Environmental DNA (eDNA) can be used as an assessment tool to detect populations of threatened species and provide fine-scale data required to make management decisions. The objectives of this project were to use quantitative PCR (qPCR) to: (i) detect spiked salamander DNA in soil, (ii) quantify eDNA degradation over time, (iii) determine detectability of salamander eDNA in a terrestrial environment using soil, faeces, and skin swabs, (iv) detect salamander eDNA in a mesocosm experiment. Salamander eDNA was positively detected in 100% of skin swabs and 66% of faecal samples and concentrations did not differ between the two sources. However, eDNA was not detected in soil samples collected from directly underneath wild-caught living salamanders. Salamander genomic DNA (gDNA) was detected in all qPCR reactions when spiked into soil at 10.0, 5.0, and 1.0 ng/g soil and spike concentration had a significant effect on detected concentrations. Only 33% of samples showed recoverable eDNA when spiked with 0.25 ng/g soil, which was the low end of eDNA detection. To determine the rate of eDNA degradation, gDNA (1 ng/g soil) was spiked into soil and quantified over seven days. Salamander eDNA concentrations decreased across days, but eDNA was still amplifiable at day 7. Salamander eDNA was detected in two of 182 mesocosm soil samples over 12 weeks (n = 52 control samples; n = 65 presence samples; n = 65 eviction samples). The discrepancy in detection success between experiments indicates the potential challenges for this method to be used as a monitoring technique for small-bodied wild terrestrial salamander populations.

Methodological considerations for detection of terrestrial small-body salamander eDNA and implications for biodiversity conservation.

PubMed

Walker, Donald M; Leys, Jacob E; Dunham, Kelly E; Oliver, Joshua C; Schiller, Emily E; Stephenson, Kelsey S; Kimrey, John T; Wooten, Jessica; Rogers, Mark W

2017-11-01

Environmental DNA (eDNA) can be used as an assessment tool to detect populations of threatened species and provide fine-scale data required to make management decisions. The objectives of this project were to use quantitative PCR (qPCR) to: (i) detect spiked salamander DNA in soil, (ii) quantify eDNA degradation over time, (iii) determine detectability of salamander eDNA in a terrestrial environment using soil, faeces, and skin swabs, (iv) detect salamander eDNA in a mesocosm experiment. Salamander eDNA was positively detected in 100% of skin swabs and 66% of faecal samples and concentrations did not differ between the two sources. However, eDNA was not detected in soil samples collected from directly underneath wild-caught living salamanders. Salamander genomic DNA (gDNA) was detected in all qPCR reactions when spiked into soil at 10.0, 5.0, and 1.0 ng/g soil and spike concentration had a significant effect on detected concentrations. Only 33% of samples showed recoverable eDNA when spiked with 0.25 ng/g soil, which was the low end of eDNA detection. To determine the rate of eDNA degradation, gDNA (1 ng/g soil) was spiked into soil and quantified over seven days. Salamander eDNA concentrations decreased across days, but eDNA was still amplifiable at day 7. Salamander eDNA was detected in two of 182 mesocosm soil samples over 12 weeks (n = 52 control samples; n = 65 presence samples; n = 65 eviction samples). The discrepancy in detection success between experiments indicates the potential challenges for this method to be used as a monitoring technique for small-bodied wild terrestrial salamander populations. © 2017 John Wiley & Sons Ltd.

An in-situ assessment of low-density polyethylene and silicone rubber passive samplers using methods with and without performance reference compounds in the context of investigation of polychlorinated biphenyl sources in rivers.

PubMed

Estoppey, Nicolas; Schopfer, Adrien; Fong, Camille; Delémont, Olivier; De Alencastro, Luiz F; Esseiva, Pierre

2016-12-01

This study firstly aims to assess the field performances of low density polyethylene (LDPE) and silicone rubber (SR) samplers for the monitoring of polychlorinated biphenyls (PCBs) in water regarding the uptake, the sampling rate (R S ) estimated by using performance reference compounds (PRCs) and the time-weighted average (TWA) concentrations. The second aim is to evaluate the efficiency of these samplers to investigate PCB sources (localization and imputation steps) using methods with and without PRCs to correct for the impact of water velocity on the uptake. Samplers spiked with PRCs were deployed in the outfalls of two PCB sources and at 8 river sites situated upstream and downstream of the outfalls. After 6weeks, the uptake of PCBs in the linear phase was equivalent in LDPE and SR but 5 times lower in LDPE for PCBs approaching equilibrium. PRC-based R S and water velocity (0.08 to 1.21ms -1 ) were well correlated in river (LDPE: R 2 =0.91, SR: R 2 =0.96) but not in outfalls (higher turbulences and potential release of PRCs to air). TWA concentrations obtained with SR were slightly higher than those obtained with LDPE (factor 1.4 to 2.6 in river) likely because of uncertainty in sampler-water partition coefficient values. Concentrations obtained through filtration and extraction of water samples (203L) were 1.6 and 5.1 times higher than TWA concentrations obtained with SR and LDPE samplers, respectively. PCB sources could efficiently be localized when PRCs were used (increases of PCB loads in river) but the impact of high differences of water velocity was overcorrected (leading sometimes to false positives and negatives). Increases of PCB loads in the river could not be entirely imputed to the investigated sources (underestimation of PCBs contributing to the load increases). A method without PRCs (relationship between uptake and water velocity) appeared to be a good complementary method for LDPE. Copyright © 2016. Published by Elsevier B.V.

Time domain structures in a colliding magnetic flux rope experiment

NASA Astrophysics Data System (ADS)

Tang, Shawn Wenjie; Gekelman, Walter; Dehaas, Timothy; Vincena, Steve; Pribyl, Patrick

2017-10-01

Electron phase-space holes, regions of positive potential on the scale of the Debye length, have been observed in auroras as well as in laboratory experiments. These potential structures, also known as Time Domain Structures (TDS), are packets of intense electric field spikes that have significant components parallel to the local magnetic field. In an ongoing investigation at UCLA, TDS were observed on the surface of two magnetized flux ropes produced within the Large Plasma Device (LAPD). A barium oxide (BaO) cathode was used to produce an 18 m long magnetized plasma column and a lanthanum hexaboride (LaB6) source was used to create 11 m long kink unstable flux ropes. Using two probes capable of measuring the local electric and magnetic fields, correlation analysis was performed on tens of thousands of these structures and their propagation velocities, probability distribution function and spatial distribution were determined. The TDS became abundant as the flux ropes collided and appear to emanate from the reconnection region in between them. In addition, a preliminary analysis of the permutation entropy and statistical complexity of the data suggests that the TDS signals may be chaotic in nature. Work done at the Basic Plasma Science Facility (BaPSF) at UCLA which is supported by DOE and NSF.

Sound Rhythms Are Encoded by Postinhibitory Rebound Spiking in the Superior Paraolivary Nucleus

PubMed Central

Felix, Richard A.; Fridberger, Anders; Leijon, Sara; Berrebi, Albert S.; Magnusson, Anna K.

2013-01-01

The superior paraolivary nucleus (SPON) is a prominent structure in the auditory brainstem. In contrast to the principal superior olivary nuclei with identified roles in processing binaural sound localization cues, the role of the SPON in hearing is not well understood. A combined in vitro and in vivo approach was used to investigate the cellular properties of SPON neurons in the mouse. Patch-clamp recordings in brain slices revealed that brief and well timed postinhibitory rebound spiking, generated by the interaction of two subthreshold-activated ion currents, is a hallmark of SPON neurons. The Ih current determines the timing of the rebound, whereas the T-type Ca2+ current boosts the rebound to spike threshold. This precisely timed rebound spiking provides a physiological explanation for the sensitivity of SPON neurons to sinusoidally amplitude-modulated (SAM) tones in vivo, where peaks in the sound envelope drive inhibitory inputs and SPON neurons fire action potentials during the waveform troughs. Consistent with this notion, SPON neurons display intrinsic tuning to frequency-modulated sinusoidal currents (1–15Hz) in vitro and discharge with strong synchrony to SAMs with modulation frequencies between 1 and 20 Hz in vivo. The results of this study suggest that the SPON is particularly well suited to encode rhythmic sound patterns. Such temporal periodicity information is likely important for detection of communication cues, such as the acoustic envelopes of animal vocalizations and speech signals. PMID:21880918

Sound rhythms are encoded by postinhibitory rebound spiking in the superior paraolivary nucleus.

PubMed

Felix, Richard A; Fridberger, Anders; Leijon, Sara; Berrebi, Albert S; Magnusson, Anna K

2011-08-31

The superior paraolivary nucleus (SPON) is a prominent structure in the auditory brainstem. In contrast to the principal superior olivary nuclei with identified roles in processing binaural sound localization cues, the role of the SPON in hearing is not well understood. A combined in vitro and in vivo approach was used to investigate the cellular properties of SPON neurons in the mouse. Patch-clamp recordings in brain slices revealed that brief and well timed postinhibitory rebound spiking, generated by the interaction of two subthreshold-activated ion currents, is a hallmark of SPON neurons. The I(h) current determines the timing of the rebound, whereas the T-type Ca(2+) current boosts the rebound to spike threshold. This precisely timed rebound spiking provides a physiological explanation for the sensitivity of SPON neurons to sinusoidally amplitude-modulated (SAM) tones in vivo, where peaks in the sound envelope drive inhibitory inputs and SPON neurons fire action potentials during the waveform troughs. Consistent with this notion, SPON neurons display intrinsic tuning to frequency-modulated sinusoidal currents (1-15Hz) in vitro and discharge with strong synchrony to SAMs with modulation frequencies between 1 and 20 Hz in vivo. The results of this study suggest that the SPON is particularly well suited to encode rhythmic sound patterns. Such temporal periodicity information is likely important for detection of communication cues, such as the acoustic envelopes of animal vocalizations and speech signals.

Emergence of band-pass filtering through adaptive spiking in the owl's cochlear nucleus

PubMed Central

MacLeod, Katrina M.; Lubejko, Susan T.; Steinberg, Louisa J.; Köppl, Christine; Peña, Jose L.

2014-01-01

In the visual, auditory, and electrosensory modalities, stimuli are defined by first- and second-order attributes. The fast time-pressure signal of a sound, a first-order attribute, is important, for instance, in sound localization and pitch perception, while its slow amplitude-modulated envelope, a second-order attribute, can be used for sound recognition. Ascending the auditory pathway from ear to midbrain, neurons increasingly show a preference for the envelope and are most sensitive to particular envelope modulation frequencies, a tuning considered important for encoding sound identity. The level at which this tuning property emerges along the pathway varies across species, and the mechanism of how this occurs is a matter of debate. In this paper, we target the transition between auditory nerve fibers and the cochlear nucleus angularis (NA). While the owl's auditory nerve fibers simultaneously encode the fast and slow attributes of a sound, one synapse further, NA neurons encode the envelope more efficiently than the auditory nerve. Using in vivo and in vitro electrophysiology and computational analysis, we show that a single-cell mechanism inducing spike threshold adaptation can explain the difference in neural filtering between the two areas. We show that spike threshold adaptation can explain the increased selectivity to modulation frequency, as input level increases in NA. These results demonstrate that a spike generation nonlinearity can modulate the tuning to second-order stimulus features, without invoking network or synaptic mechanisms. PMID:24790170

The dynamic relationship between cerebellar Purkinje cell simple spikes and the spikelet number of complex spikes

PubMed Central

Burroughs, Amelia; Wise, Andrew K.; Xiao, Jianqiang; Houghton, Conor; Tang, Tianyu; Suh, Colleen Y.; Lang, Eric J.

2016-01-01

Key points Purkinje cells are the sole output of the cerebellar cortex and fire two distinct types of action potential: simple spikes and complex spikes.Previous studies have mainly considered complex spikes as unitary events, even though the waveform is composed of varying numbers of spikelets.The extent to which differences in spikelet number affect simple spike activity (and vice versa) remains unclear.We found that complex spikes with greater numbers of spikelets are preceded by higher simple spike firing rates but, following the complex spike, simple spikes are reduced in a manner that is graded with spikelet number.This dynamic interaction has important implications for cerebellar information processing, and suggests that complex spike spikelet number may maintain Purkinje cells within their operational range. Abstract Purkinje cells are central to cerebellar function because they form the sole output of the cerebellar cortex. They exhibit two distinct types of action potential: simple spikes and complex spikes. It is widely accepted that interaction between these two types of impulse is central to cerebellar cortical information processing. Previous investigations of the interactions between simple spikes and complex spikes have mainly considered complex spikes as unitary events. However, complex spikes are composed of an initial large spike followed by a number of secondary components, termed spikelets. The number of spikelets within individual complex spikes is highly variable and the extent to which differences in complex spike spikelet number affects simple spike activity (and vice versa) remains poorly understood. In anaesthetized adult rats, we have found that Purkinje cells recorded from the posterior lobe vermis and hemisphere have high simple spike firing frequencies that precede complex spikes with greater numbers of spikelets. This finding was also evident in a small sample of Purkinje cells recorded from the posterior lobe hemisphere in awake cats. In addition, complex spikes with a greater number of spikelets were associated with a subsequent reduction in simple spike firing rate. We therefore suggest that one important function of spikelets is the modulation of Purkinje cell simple spike firing frequency, which has implications for controlling cerebellar cortical output and motor learning. PMID:27265808

Emergence of Adaptive Computation by Single Neurons in the Developing Cortex

PubMed Central

Famulare, Michael; Gjorgjieva, Julijana; Moody, William J.

2013-01-01

Adaptation is a fundamental computational motif in neural processing. To maintain stable perception in the face of rapidly shifting input, neural systems must extract relevant information from background fluctuations under many different contexts. Many neural systems are able to adjust their input–output properties such that an input's ability to trigger a response depends on the size of that input relative to its local statistical context. This “gain-scaling” strategy has been shown to be an efficient coding strategy. We report here that this property emerges during early development as an intrinsic property of single neurons in mouse sensorimotor cortex, coinciding with the disappearance of spontaneous waves of network activity, and can be modulated by changing the balance of spike-generating currents. Simultaneously, developing neurons move toward a common intrinsic operating point and a stable ratio of spike-generating currents. This developmental trajectory occurs in the absence of sensory input or spontaneous network activity. Through a combination of electrophysiology and modeling, we demonstrate that developing cortical neurons develop the ability to perform nearly perfect gain scaling by virtue of the maturing spike-generating currents alone. We use reduced single neuron models to identify the conditions for this property to hold. PMID:23884925

Preventing food crises using a food policy approach.

PubMed

Timmer, C Peter

2010-01-01

A food crisis occurs when rates of hunger and malnutrition rise sharply at local, national, or global levels. This definition distinguishes a food crisis from chronic hunger, although food crises are far more likely among populations already suffering from prolonged hunger and malnutrition. A food crisis is usually set off by a shock to either supply or demand for food and often involves a sudden spike in food prices. It is important to remember that in a market economy, food prices measure the scarcity of food, not its value in any nutritional sense. Except in rare circumstances, the straightforward way to prevent a food crisis is to have rapidly rising labor productivity through economic growth and keep food prices stable while maintaining access by the poor. The formula is easier to state than to implement, especially on a global scale, but it is good to have both the objective, reducing short-run spikes in hunger, and the deep mechanisms, pro-poor economic growth and stable food prices, clearly in mind. A coherent food policy seeks to use these mechanisms, and others, to achieve a sustained reduction in chronic hunger over the long run while preventing spikes in hunger in the short run.

Primordial black holes from polynomial potentials in single field inflation

NASA Astrophysics Data System (ADS)

Hertzberg, Mark P.; Yamada, Masaki

2018-04-01

Within canonical single field inflation models, we provide a method to reverse engineer and reconstruct the inflaton potential from a given power spectrum. This is not only a useful tool to find a potential from observational constraints, but also gives insight into how to generate a large amplitude spike in density perturbations, especially those that may lead to primordial black holes (PBHs). In accord with other works, we find that the usual slow-roll conditions need to be violated in order to generate a significant spike in the spectrum. We find that a way to achieve a very large amplitude spike in single field models is for the classical roll of the inflaton to overshoot a local minimum during inflation. We provide an example of a quintic polynomial potential that implements this idea and leads to the observed spectral index, observed amplitude of fluctuations on large scales, significant PBH formation on small scales, and is compatible with other observational constraints. We quantify how much fine-tuning is required to achieve this in a family of random polynomial potentials, which may be useful to estimate the probability of PBH formation in the string landscape.

Calcium spikes, waves and oscillations in a large, patterned epithelial tissue

PubMed Central

Balaji, Ramya; Bielmeier, Christina; Harz, Hartmann; Bates, Jack; Stadler, Cornelia; Hildebrand, Alexander; Classen, Anne-Kathrin

2017-01-01

While calcium signaling in excitable cells, such as muscle or neurons, is extensively characterized, calcium signaling in epithelial tissues is little understood. Specifically, the range of intercellular calcium signaling patterns elicited by tightly coupled epithelial cells and their function in the regulation of epithelial characteristics are little explored. We found that in Drosophila imaginal discs, a widely studied epithelial model organ, complex spatiotemporal calcium dynamics occur. We describe patterns that include intercellular waves traversing large tissue domains in striking oscillatory patterns as well as spikes confined to local domains of neighboring cells. The spatiotemporal characteristics of intercellular waves and oscillations arise as emergent properties of calcium mobilization within a sheet of gap-junction coupled cells and are influenced by cell size and environmental history. While the in vivo function of spikes, waves and oscillations requires further characterization, our genetic experiments suggest that core calcium signaling components guide actomyosin organization. Our study thus suggests a possible role for calcium signaling in epithelia but importantly, introduces a model epithelium enabling the dissection of cellular mechanisms supporting the initiation, transmission and regeneration of long-range intercellular calcium waves and the emergence of oscillations in a highly coupled multicellular sheet. PMID:28218282

Common time-frequency analysis of local field potential and pyramidal cell activity in seizure-like events of the rat hippocampus

NASA Astrophysics Data System (ADS)

Cotic, M.; Chiu, A. W. L.; Jahromi, S. S.; Carlen, P. L.; Bardakjian, B. L.

2011-08-01

To study cell-field dynamics, physiologists simultaneously record local field potentials and the activity of individual cells from animals performing cognitive tasks, during various brain states or under pathological conditions. However, apart from spike shape and spike timing analyses, few studies have focused on elucidating the common time-frequency structure of local field activity relative to surrounding cells across different periods of phenomena. We have used two algorithms, multi-window time frequency analysis and wavelet phase coherence (WPC), to study common intracellular-extracellular (I-E) spectral features in spontaneous seizure-like events (SLEs) from rat hippocampal slices in a low magnesium epilepsy model. Both algorithms were applied to 'pairs' of simultaneously observed I-E signals from slices in the CA1 hippocampal region. Analyses were performed over a frequency range of 1-100 Hz. I-E spectral commonality varied in frequency and time. Higher commonality was observed from 1 to 15 Hz, and lower commonality was observed in the 15-100 Hz frequency range. WPC was lower in the non-SLE region compared to SLE activity; however, there was no statistical difference in the 30-45 Hz band between SLE and non-SLE modes. This work provides evidence of strong commonality in various frequency bands of I-E SLEs in the rat hippocampus, not only during SLEs but also immediately before and after.

Selective neuronal lapses precede human cognitive lapses following sleep deprivation.

PubMed

Nir, Yuval; Andrillon, Thomas; Marmelshtein, Amit; Suthana, Nanthia; Cirelli, Chiara; Tononi, Giulio; Fried, Itzhak

2017-12-01

Sleep deprivation is a major source of morbidity with widespread health effects, including increased risk of hypertension, diabetes, obesity, heart attack, and stroke. Moreover, sleep deprivation brings about vehicle accidents and medical errors and is therefore an urgent topic of investigation. During sleep deprivation, homeostatic and circadian processes interact to build up sleep pressure, which results in slow behavioral performance (cognitive lapses) typically attributed to attentional thalamic and frontoparietal circuits, but the underlying mechanisms remain unclear. Recently, through study of electroencephalograms (EEGs) in humans and local field potentials (LFPs) in nonhuman primates and rodents it was found that, during sleep deprivation, regional 'sleep-like' slow and theta (slow/theta) waves co-occur with impaired behavioral performance during wakefulness. Here we used intracranial electrodes to record single-neuron activities and LFPs in human neurosurgical patients performing a face/nonface categorization psychomotor vigilance task (PVT) over multiple experimental sessions, including a session after full-night sleep deprivation. We find that, just before cognitive lapses, the selective spiking responses of individual neurons in the medial temporal lobe (MTL) are attenuated, delayed, and lengthened. These 'neuronal lapses' are evident on a trial-by-trial basis when comparing the slowest behavioral PVT reaction times to the fastest. Furthermore, during cognitive lapses, LFPs exhibit a relative local increase in slow/theta activity that is correlated with degraded single-neuron responses and with baseline theta activity. Our results show that cognitive lapses involve local state-dependent changes in neuronal activity already present in the MTL.

MEA-Tools: an open source toolbox for the analysis of multi-electrode data with MATLAB.

PubMed

Egert, U; Knott, Th; Schwarz, C; Nawrot, M; Brandt, A; Rotter, S; Diesmann, M

2002-05-30

Recent advances in electrophysiological techniques have created new tools for the acquisition and storage of neuronal activity recorded simultaneously with numerous electrodes. These techniques support the analysis of the function as well as the structure of individual electrogenic cells in the context of surrounding neuronal or cardiac network. Commercially available tools for the analysis of such data, however, cannot be easily adapted to newly emerging requirements for data analysis and visualization, and cross compatibility between them is limited. In this report we introduce a free open source toolbox called microelectrode array tools (MEA-Tools) for the analysis of multi-electrode data based on the common data analysis environment MATLAB (version 5.3-6.1, The Mathworks, Natick, MA). The toolbox itself is platform independent. The file interface currently supports files recorded with MCRack (Multi Channel Systems, Reutlingen, Germany) under Microsoft Windows 95, 98, NT, and 2000, but can be adapted to other data acquisition systems. Functions are controlled via command line input and graphical user interfaces, and support common requirements for the analysis of local field potentials, extracellular spike activity, and continuous recordings, in addition to supplementary data acquired by additional instruments, e.g. intracellular amplifiers. Data may be processed as continuous recordings or time windows triggered to some event.

A Brain-Machine-Brain Interface for Rewiring of Cortical Circuitry after Traumatic Brain Injury

DTIC Science & Technology

2011-09-01

cerebral cortex of a rat’s brain. The flow chart for spike discrimination algorithm is also shown. Negative threshold level (not shown in bottom left...portion of the transistor drain current can flow into its bulk due to impact ionization effect [40], greatly degrading the output impedance of the...current source. This can be solved by connecting the bulk and source of together, as also seen in Fig. 4, allowing its drain-bulk current to also flow

EFFECTS OF RESIDUAL ORGANIC MATTER ON ELEMENTAL ANALYSES BY SPARK SOURCE MASS SPECTROGRAPHY (SSMS)

EPA Science Inventory

The report gives results of research to define the effect of organics in SSMS and to evaluate several sample preparation methods for their removal. Samples of known organic content were fabricated by diluting NBS SRM 1633 fly ash (spiked with several trace elements) with a mixtur...

Localization of Epileptogenic Zone With the Correction of Pathological Networks.

PubMed

Yang, Chuanzuo; Luan, Guoming; Wang, Qian; Liu, Zhao; Zhai, Feng; Wang, Qingyun

2018-01-01

Patients with focal drug-resistant epilepsy are potential candidates for surgery. Stereo-electroencephalograph (SEEG) is often considered as the "gold standard" to identify the epileptogenic zone (EZ) that accounts for the onset and propagation of epileptiform discharges. However, visual analysis of SEEG still prevails in clinical practice. In addition, epilepsy is increasingly understood to be the result of network disorder, but the specific organization of the epileptic network is still unclear. Therefore, it is necessary to quantitatively localize the EZ and investigate the nature of epileptogenic networks. In this study, intracranial recordings from 10 patients were analyzed through adaptive directed transfer function, and the out-degree of effective network was selected as the principal indicator to localize the epileptogenic area. Furthermore, a coupled neuronal population model was used to qualitatively simulate electrical activity in the brain. By removing individual populations, virtual surgery adjusting the network organization could be performed. Results suggested that the accuracy and detection rate of the EZ localization were 82.86 and 85.29%, respectively. In addition, the same stage shared a relatively stable connectivity pattern, while the patterns changed with transition to different processes. Meanwhile, eight cases of simulations indicated that networks in the ictal stage were more likely to generate rhythmic spikes. This indicated the existence of epileptogenic networks, which could enhance local excitability and facilitate synchronization. The removal of the EZ could correct these pathological networks and reduce the amount of spikes by at least 75%. This might be one reason why accurate resection could reduce or even suppress seizures. This study provides novel insights into epilepsy and surgical treatments from the network perspective.

Spiking irregularity and frequency modulate the behavioral report of single-neuron stimulation.

PubMed

Doron, Guy; von Heimendahl, Moritz; Schlattmann, Peter; Houweling, Arthur R; Brecht, Michael

2014-02-05

The action potential activity of single cortical neurons can evoke measurable sensory effects, but it is not known how spiking parameters and neuronal subtypes affect the evoked sensations. Here, we examined the effects of spike train irregularity, spike frequency, and spike number on the detectability of single-neuron stimulation in rat somatosensory cortex. For regular-spiking, putative excitatory neurons, detectability increased with spike train irregularity and decreasing spike frequencies but was not affected by spike number. Stimulation of single, fast-spiking, putative inhibitory neurons led to a larger sensory effect compared to regular-spiking neurons, and the effect size depended only on spike irregularity. An ideal-observer analysis suggests that, under our experimental conditions, rats were using integration windows of a few hundred milliseconds or more. Our data imply that the behaving animal is sensitive to single neurons' spikes and even to their temporal patterning. Copyright © 2014 Elsevier Inc. All rights reserved.

Numerical analysis of buoyancy effects during the dissolution and transport of oxygenated gasoline in groundwater

NASA Astrophysics Data System (ADS)

Molson, J.; Mocanu, M.; Barker, J.

2008-07-01

Dissolution of oxygenated gasoline, as well as buoyancy-driven groundwater flow and transport of the multicomponent dissolved phase plumes, is simulated numerically in three dimensions. The simulations are based on a field experiment described by Mocanu (2007) in which three oxygenated gasoline sources were emplaced as nonaqueous phase liquids (NAPLs) below the water table of the shallow sand aquifer at Canadian Forces Base Borden, Ontario. The sources were composed of an ethanol-free gasoline mixture spiked with 9.8% methyl tert-butyl ether and 0.2% tert-butyl alcohol (GMT-E0), a gasoline with 10% ethanol (E10), and a source with 95% ethanol (E95). The numerical model includes dissolution of gasoline as a NAPL, density-dependent groundwater flow, advective-dispersive transport of the dissolved components, and ethanol cosolvency and degradation. Buoyancy effects in the dissolved plumes were compared under a homogeneous hydraulic conductivity field as well as with five realizations of spatially correlated random fields representing the Borden aquifer. The simulations showed that buoyancy was most significant in the E95 source plumes within the homogeneous system, having induced after 150 days a net upward displacement of the local peak concentrations for all but the least soluble component of approximately 1.5 m. The peak rise in ethanol from the GMT-E0 and E10 plumes was about 0.6 m. The results highlight the importance of shallow monitoring wells when monitoring high oxygenate fraction gasoline spills in groundwater and have implications for assessing mass fluxes and biodegradation rates.

The dynamic relationship between cerebellar Purkinje cell simple spikes and the spikelet number of complex spikes.

PubMed

Burroughs, Amelia; Wise, Andrew K; Xiao, Jianqiang; Houghton, Conor; Tang, Tianyu; Suh, Colleen Y; Lang, Eric J; Apps, Richard; Cerminara, Nadia L

2017-01-01

Purkinje cells are the sole output of the cerebellar cortex and fire two distinct types of action potential: simple spikes and complex spikes. Previous studies have mainly considered complex spikes as unitary events, even though the waveform is composed of varying numbers of spikelets. The extent to which differences in spikelet number affect simple spike activity (and vice versa) remains unclear. We found that complex spikes with greater numbers of spikelets are preceded by higher simple spike firing rates but, following the complex spike, simple spikes are reduced in a manner that is graded with spikelet number. This dynamic interaction has important implications for cerebellar information processing, and suggests that complex spike spikelet number may maintain Purkinje cells within their operational range. Purkinje cells are central to cerebellar function because they form the sole output of the cerebellar cortex. They exhibit two distinct types of action potential: simple spikes and complex spikes. It is widely accepted that interaction between these two types of impulse is central to cerebellar cortical information processing. Previous investigations of the interactions between simple spikes and complex spikes have mainly considered complex spikes as unitary events. However, complex spikes are composed of an initial large spike followed by a number of secondary components, termed spikelets. The number of spikelets within individual complex spikes is highly variable and the extent to which differences in complex spike spikelet number affects simple spike activity (and vice versa) remains poorly understood. In anaesthetized adult rats, we have found that Purkinje cells recorded from the posterior lobe vermis and hemisphere have high simple spike firing frequencies that precede complex spikes with greater numbers of spikelets. This finding was also evident in a small sample of Purkinje cells recorded from the posterior lobe hemisphere in awake cats. In addition, complex spikes with a greater number of spikelets were associated with a subsequent reduction in simple spike firing rate. We therefore suggest that one important function of spikelets is the modulation of Purkinje cell simple spike firing frequency, which has implications for controlling cerebellar cortical output and motor learning. © 2016 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.

Volatile organic compound emissions from the oil and natural gas industry in the Uintah Basin, Utah: oil and gas well pad emissions compared to ambient air composition

NASA Astrophysics Data System (ADS)

Warneke, C.; Geiger, F.; Edwards, P. M.; Dube, W.; Pétron, G.; Kofler, J.; Zahn, A.; Brown, S. S.; Graus, M.; Gilman, J. B.; Lerner, B. M.; Peischl, J.; Ryerson, T. B.; de Gouw, J. A.; Roberts, J. M.

2014-10-01

Emissions of volatile organic compounds (VOCs) associated with oil and natural gas production in the Uintah Basin, Utah were measured at a ground site in Horse Pool and from a NOAA mobile laboratory with PTR-MS instruments. The VOC compositions in the vicinity of individual gas and oil wells and other point sources such as evaporation ponds, compressor stations and injection wells are compared to the measurements at Horse Pool. High mixing ratios of aromatics, alkanes, cycloalkanes and methanol were observed for extended periods of time and for short-term spikes caused by local point sources. The mixing ratios during the time the mobile laboratory spent on the well pads were averaged. High mixing ratios were found close to all point sources, but gas well pads with collection and dehydration on the well pad were clearly associated with higher mixing ratios than other wells. The comparison of the VOC composition of the emissions from the oil and natural gas well pads showed that gas well pads without dehydration on the well pad compared well with the majority of the data at Horse Pool, and that oil well pads compared well with the rest of the ground site data. Oil well pads on average emit heavier compounds than gas well pads. The mobile laboratory measurements confirm the results from an emissions inventory: the main VOC source categories from individual point sources are dehydrators, oil and condensate tank flashing and pneumatic devices and pumps. Raw natural gas is emitted from the pneumatic devices and pumps and heavier VOC mixes from the tank flashings.

Hypotheses for Near-Surface Exchange of Methane on Mars.

PubMed

Hu, Renyu; Bloom, A Anthony; Gao, Peter; Miller, Charles E; Yung, Yuk L

2016-07-01

The Curiosity rover recently detected a background of 0.7 ppb and spikes of 7 ppb of methane on Mars. This in situ measurement reorients our understanding of the martian environment and its potential for life, as the current theories do not entail any geological source or sink of methane that varies sub-annually. In particular, the 10-fold elevation during the southern winter indicates episodic sources of methane that are yet to be discovered. Here we suggest a near-surface reservoir could explain this variability. Using the temperature and humidity measurements from the rover, we find that perchlorate salts in the regolith deliquesce to form liquid solutions, and deliquescence progresses to deeper subsurface in the season of the methane spikes. We therefore formulate the following three testable hypotheses. The first scenario is that the regolith in Gale Crater adsorbs methane when dry and releases this methane to the atmosphere upon deliquescence. The adsorption energy needs to be 36 kJ mol(-1) to explain the magnitude of the methane spikes, higher than existing laboratory measurements. The second scenario is that microorganisms convert organic matter in the soil to methane when they are in liquid solutions. This scenario does not require regolith adsorption but entails extant life on Mars. The third scenario is that deep subsurface aquifers produce the bursts of methane. Continued in situ measurements of methane and water, as well as laboratory studies of adsorption and deliquescence, will test these hypotheses and inform the existence of the near-surface reservoir and its exchange with the atmosphere. Mars-Methane-Astrobiology-Regolith. Astrobiology 16, 539-550.

Hypotheses for a Near-Surface Reservoir of Methane and Its Release on Mars

NASA Astrophysics Data System (ADS)

Hu, R.; Bloom, A. A.; Gao, P.; Miller, C. E.; Yung, Y. L.

2015-12-01

The Curiosity rover recently detected a background of 0.7 ppb and spikes of 7 ppb of methane on Mars. This in situ measurement reorients our understanding of the Martian environment and its potential for life, as the current theories do not entail any active source or sink of methane. In particular, the 10-fold elevation during the southern winter indicates episodic sources of methane that are yet to be discovered. Using the temperature and humidity measurements from the rover, we find that perchlorate salts in the regolith deliquesce to form liquid solutions, and deliquescence progresses to deeper subsurface in the season of the methane spikes. We therefore formulate the following three testable hypotheses as an attempt to explain the apparent variability of the atmospheric methane abundance. The first scenario is that the regolith in Gale Crater adsorbs methane when dry and releases this methane to the atmosphere upon deliquescence. The adsorption energy needs to be 36 kJ mol-1 to explain the magnitude of the methane spikes, higher than laboratory measurements. The second scenario is that microorganisms exist and convert organic matter in the soil to methane when they are in liquid solutions. This scenario does not require regolith adsorption. The third scenario is that deep subsurface aquifers sealed by ice or clathrate produce bursts of methane as a result of freezing and thawing of the permafrost, as the terrestrial arctic tundra. Continued monitoring of methane by Curiosity will test the existence of the near-surface reservoir and its exchange with the atmosphere.

Hypotheses for Near-Surface Exchange of Methane on Mars

NASA Astrophysics Data System (ADS)

Hu, Renyu; Bloom, A. Anthony; Gao, Peter; Miller, Charles E.; Yung, Yuk L.

2016-07-01

The Curiosity rover recently detected a background of 0.7 ppb and spikes of 7 ppb of methane on Mars. This in situ measurement reorients our understanding of the martian environment and its potential for life, as the current theories do not entail any geological source or sink of methane that varies sub-annually. In particular, the 10-fold elevation during the southern winter indicates episodic sources of methane that are yet to be discovered. Here we suggest a near-surface reservoir could explain this variability. Using the temperature and humidity measurements from the rover, we find that perchlorate salts in the regolith deliquesce to form liquid solutions, and deliquescence progresses to deeper subsurface in the season of the methane spikes. We therefore formulate the following three testable hypotheses. The first scenario is that the regolith in Gale Crater adsorbs methane when dry and releases this methane to the atmosphere upon deliquescence. The adsorption energy needs to be 36 kJ mol-1 to explain the magnitude of the methane spikes, higher than existing laboratory measurements. The second scenario is that microorganisms convert organic matter in the soil to methane when they are in liquid solutions. This scenario does not require regolith adsorption but entails extant life on Mars. The third scenario is that deep subsurface aquifers produce the bursts of methane. Continued in situ measurements of methane and water, as well as laboratory studies of adsorption and deliquescence, will test these hypotheses and inform the existence of the near-surface reservoir and its exchange with the atmosphere.

TEF-7A, a transcript elongation factor gene, influences yield-related traits in bread wheat (Triticum aestivum L.)

PubMed Central

Zheng, Jun; Liu, Hong; Wang, Yuquan; Wang, Lanfen; Chang, Xiaoping; Jing, Ruilian; Hao, Chenyang; Zhang, Xueyong

2014-01-01

In this study, TaTEF-7A, a member of the transcript elongation factor gene family, and its flanking sequences were isolated. TaTEF-7A was located on chromosome 7A and was flanked by markers Xwmc83 and XP3156.3. Subcellular localization revealed that TaTEF-7A protein was localized in the nucleus. This gene was expressed in all organs, but the highest expression occurred in young spikes and developing seeds. Overexpression of TaTEF-7A in Arabidopsis thaliana produced pleiotropic effects on vegetative and reproductive development that enhanced grain length, silique number, and silique length. No diversity was found in the coding region of TaTEF-7A, but 16 single nucleotide polymorphisms and Indels were detected in the promoter regions of different cultivars. Markers based on sequence variations in the promoter regions (InDel-629 and InDel-604) were developed, and three haplotypes were identified based on those markers. Haplotype–trait association analysis of the Chinese wheat mini core collection revealed that TaTEF-7A was significantly associated with grain number per spike. Phenotyping of near-isogenic lines (NILs) confirmed that TaTEF-7A increases potential grain yield and yield-related traits. Frequency changes in favoured haplotypes gradually increased in cultivars released in China from the 1940s. Geographic distributions of favoured haplotypes were characterized in six major wheat production regions worldwide. The presence of Hap-7A-3, the favoured haplotype, showed a positive correlation with yield in a global set of breeding lines. These results suggest that TaTEF-7A is a functional regulatory factor for grain number per spike and provide a basis for marker-assisted selection. PMID:25056774

Estrogen receptor 1 and 2 mRNA expression and protein localization in the porcine endometrium during the estrous cycle and early pregnancy

USDA-ARS?s Scientific Manuscript database

Between d 10 and 12 of gestation, the pig embryo undergoes elongation and produces estrogen, which serves as the key molecule for maternal recognition of pregnancy. Around d 15 of gestation, the embryo begins its superficial implantation with the endometrium and a second spike in estrogen occurs fro...

The Brain as an Efficient and Robust Adaptive Learner.

PubMed

Denève, Sophie; Alemi, Alireza; Bourdoukan, Ralph

2017-06-07

Understanding how the brain learns to compute functions reliably, efficiently, and robustly with noisy spiking activity is a fundamental challenge in neuroscience. Most sensory and motor tasks can be described as dynamical systems and could presumably be learned by adjusting connection weights in a recurrent biological neural network. However, this is greatly complicated by the credit assignment problem for learning in recurrent networks, e.g., the contribution of each connection to the global output error cannot be determined based only on locally accessible quantities to the synapse. Combining tools from adaptive control theory and efficient coding theories, we propose that neural circuits can indeed learn complex dynamic tasks with local synaptic plasticity rules as long as they associate two experimentally established neural mechanisms. First, they should receive top-down feedbacks driving both their activity and their synaptic plasticity. Second, inhibitory interneurons should maintain a tight balance between excitation and inhibition in the circuit. The resulting networks could learn arbitrary dynamical systems and produce irregular spike trains as variable as those observed experimentally. Yet, this variability in single neurons may hide an extremely efficient and robust computation at the population level. Copyright © 2017 Elsevier Inc. All rights reserved.

Phase unwrapping in digital holography based on non-subsampled contourlet transform

NASA Astrophysics Data System (ADS)

Zhang, Xiaolei; Zhang, Xiangchao; Xu, Min; Zhang, Hao; Jiang, Xiangqian

2018-01-01

In the digital holographic measurement of complex surfaces, phase unwrapping is a critical step for accurate reconstruction. The phases of the complex amplitudes calculated from interferometric holograms are disturbed by speckle noise, thus reliable unwrapping results are difficult to be obtained. Most of existing unwrapping algorithms implement denoising operations first to obtain noise-free phases and then conduct phase unwrapping pixel by pixel. This approach is sensitive to spikes and prone to unreliable results in practice. In this paper, a robust unwrapping algorithm based on the non-subsampled contourlet transform (NSCT) is developed. The multiscale and directional decomposition of NSCT enhances the boundary between adjacent phase levels and henceforth the influence of local noise can be eliminated in the transform domain. The wrapped phase map is segmented into several regions corresponding to different phase levels. Finally, an unwrapped phase map is obtained by elevating the phases of a whole segment instead of individual pixels to avoid unwrapping errors caused by local spikes. This algorithm is suitable for dealing with complex and noisy wavefronts. Its universality and superiority in the digital holographic interferometry have been demonstrated by both numerical analysis and practical experiments.

Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor

PubMed Central

Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei

2016-01-01

Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation. PMID:27649190

Spiking Cortical Model Based Multimodal Medical Image Fusion by Combining Entropy Information with Weber Local Descriptor.

PubMed

Zhang, Xuming; Ren, Jinxia; Huang, Zhiwen; Zhu, Fei

2016-09-15

Multimodal medical image fusion (MIF) plays an important role in clinical diagnosis and therapy. Existing MIF methods tend to introduce artifacts, lead to loss of image details or produce low-contrast fused images. To address these problems, a novel spiking cortical model (SCM) based MIF method has been proposed in this paper. The proposed method can generate high-quality fused images using the weighting fusion strategy based on the firing times of the SCM. In the weighting fusion scheme, the weight is determined by combining the entropy information of pulse outputs of the SCM with the Weber local descriptor operating on the firing mapping images produced from the pulse outputs. The extensive experiments on multimodal medical images show that compared with the numerous state-of-the-art MIF methods, the proposed method can preserve image details very well and avoid the introduction of artifacts effectively, and thus it significantly improves the quality of fused images in terms of human vision and objective evaluation criteria such as mutual information, edge preservation index, structural similarity based metric, fusion quality index, fusion similarity metric and standard deviation.

Tools for probing local circuits: high-density silicon probes combined with optogenetics

PubMed Central

Buzsáki, György; Stark, Eran; Berényi, Antal; Khodagholy, Dion; Kipke, Daryl R.; Yoon, Euisik; Wise, Kensall

2015-01-01

To understand how function arises from the interactions between neurons, it is necessary to use methods that allow the monitoring of brain activity at the single-neuron, single-spike level and the targeted manipulation of the diverse neuron types selectively in a closed-loop manner. Large-scale recordings of neuronal spiking combined with optogenetic perturbation of identified individual neurons has emerged as a suitable method for such tasks in behaving animals. To fully exploit the potential power of these methods, multiple steps of technical innovation are needed. We highlight the current state-of-the-art in electrophysiological recording methods, combined with optogenetics, and discuss directions for progress. In addition, we point to areas where rapid development is in progress and discuss topics where near-term improvements are possible and needed. PMID:25856489

The role of cortical oscillations in a spiking neural network model of the basal ganglia.

PubMed

Fountas, Zafeirios; Shanahan, Murray

2017-01-01

Although brain oscillations involving the basal ganglia (BG) have been the target of extensive research, the main focus lies disproportionally on oscillations generated within the BG circuit rather than other sources, such as cortical areas. We remedy this here by investigating the influence of various cortical frequency bands on the intrinsic effective connectivity of the BG, as well as the role of the latter in regulating cortical behaviour. To do this, we construct a detailed neural model of the complete BG circuit based on fine-tuned spiking neurons, with both electrical and chemical synapses as well as short-term plasticity between structures. As a measure of effective connectivity, we estimate information transfer between nuclei by means of transfer entropy. Our model successfully reproduces firing and oscillatory behaviour found in both the healthy and Parkinsonian BG. We found that, indeed, effective connectivity changes dramatically for different cortical frequency bands and phase offsets, which are able to modulate (or even block) information flow in the three major BG pathways. In particular, alpha (8-12Hz) and beta (13-30Hz) oscillations activate the direct BG pathway, and favour the modulation of the indirect and hyper-direct pathways via the subthalamic nucleus-globus pallidus loop. In contrast, gamma (30-90Hz) frequencies block the information flow from the cortex completely through activation of the indirect pathway. Finally, below alpha, all pathways decay gradually and the system gives rise to spontaneous activity generated in the globus pallidus. Our results indicate the existence of a multimodal gating mechanism at the level of the BG that can be entirely controlled by cortical oscillations, and provide evidence for the hypothesis of cortically-entrained but locally-generated subthalamic beta activity. These two findings suggest new insights into the pathophysiology of specific BG disorders.

Integrate-and-fire vs Poisson models of LGN input to V1 cortex: noisier inputs reduce orientation selectivity

PubMed Central

Lin, I-Chun; Xing, Dajun; Shapley, Robert

2014-01-01

One of the reasons the visual cortex has attracted the interest of computational neuroscience is that it has well-defined inputs. The lateral geniculate nucleus (LGN) of the thalamus is the source of visual signals to the primary visual cortex (V1). Most large-scale cortical network models approximate the spike trains of LGN neurons as simple Poisson point processes. However, many studies have shown that neurons in the early visual pathway are capable of spiking with high temporal precision and their discharges are not Poisson-like. To gain an understanding of how response variability in the LGN influences the behavior of V1, we study response properties of model V1 neurons that receive purely feedforward inputs from LGN cells modeled either as noisy leaky integrate-and-fire (NLIF) neurons or as inhomogeneous Poisson processes. We first demonstrate that the NLIF model is capable of reproducing many experimentally observed statistical properties of LGN neurons. Then we show that a V1 model in which the LGN input to a V1 neuron is modeled as a group of NLIF neurons produces higher orientation selectivity than the one with Poisson LGN input. The second result implies that statistical characteristics of LGN spike trains are important for V1's function. We conclude that physiologically motivated models of V1 need to include more realistic LGN spike trains that are less noisy than inhomogeneous Poisson processes. PMID:22684587

Integrate-and-fire vs Poisson models of LGN input to V1 cortex: noisier inputs reduce orientation selectivity.

PubMed

Lin, I-Chun; Xing, Dajun; Shapley, Robert

2012-12-01

One of the reasons the visual cortex has attracted the interest of computational neuroscience is that it has well-defined inputs. The lateral geniculate nucleus (LGN) of the thalamus is the source of visual signals to the primary visual cortex (V1). Most large-scale cortical network models approximate the spike trains of LGN neurons as simple Poisson point processes. However, many studies have shown that neurons in the early visual pathway are capable of spiking with high temporal precision and their discharges are not Poisson-like. To gain an understanding of how response variability in the LGN influences the behavior of V1, we study response properties of model V1 neurons that receive purely feedforward inputs from LGN cells modeled either as noisy leaky integrate-and-fire (NLIF) neurons or as inhomogeneous Poisson processes. We first demonstrate that the NLIF model is capable of reproducing many experimentally observed statistical properties of LGN neurons. Then we show that a V1 model in which the LGN input to a V1 neuron is modeled as a group of NLIF neurons produces higher orientation selectivity than the one with Poisson LGN input. The second result implies that statistical characteristics of LGN spike trains are important for V1's function. We conclude that physiologically motivated models of V1 need to include more realistic LGN spike trains that are less noisy than inhomogeneous Poisson processes.

Feedback Inhibition Shapes Emergent Computational Properties of Cortical Microcircuit Motifs.

PubMed

Jonke, Zeno; Legenstein, Robert; Habenschuss, Stefan; Maass, Wolfgang

2017-08-30

Cortical microcircuits are very complex networks, but they are composed of a relatively small number of stereotypical motifs. Hence, one strategy for throwing light on the computational function of cortical microcircuits is to analyze emergent computational properties of these stereotypical microcircuit motifs. We are addressing here the question how spike timing-dependent plasticity shapes the computational properties of one motif that has frequently been studied experimentally: interconnected populations of pyramidal cells and parvalbumin-positive inhibitory cells in layer 2/3. Experimental studies suggest that these inhibitory neurons exert some form of divisive inhibition on the pyramidal cells. We show that this data-based form of feedback inhibition, which is softer than that of winner-take-all models that are commonly considered in theoretical analyses, contributes to the emergence of an important computational function through spike timing-dependent plasticity: The capability to disentangle superimposed firing patterns in upstream networks, and to represent their information content through a sparse assembly code. SIGNIFICANCE STATEMENT We analyze emergent computational properties of a ubiquitous cortical microcircuit motif: populations of pyramidal cells that are densely interconnected with inhibitory neurons. Simulations of this model predict that sparse assembly codes emerge in this microcircuit motif under spike timing-dependent plasticity. Furthermore, we show that different assemblies will represent different hidden sources of upstream firing activity. Hence, we propose that spike timing-dependent plasticity enables this microcircuit motif to perform a fundamental computational operation on neural activity patterns. Copyright © 2017 the authors 0270-6474/17/378511-13$15.00/0.

Organic electronics for high-resolution electrocorticography of the human brain.

PubMed

Khodagholy, Dion; Gelinas, Jennifer N; Zhao, Zifang; Yeh, Malcolm; Long, Michael; Greenlee, Jeremy D; Doyle, Werner; Devinsky, Orrin; Buzsáki, György

2016-11-01

Localizing neuronal patterns that generate pathological brain signals may assist with tissue resection and intervention strategies in patients with neurological diseases. Precise localization requires high spatiotemporal recording from populations of neurons while minimizing invasiveness and adverse events. We describe a large-scale, high-density, organic material-based, conformable neural interface device ("NeuroGrid") capable of simultaneously recording local field potentials (LFPs) and action potentials from the cortical surface. We demonstrate the feasibility and safety of intraoperative recording with NeuroGrids in anesthetized and awake subjects. Highly localized and propagating physiological and pathological LFP patterns were recorded, and correlated neural firing provided evidence about their local generation. Application of NeuroGrids to brain disorders, such as epilepsy, may improve diagnostic precision and therapeutic outcomes while reducing complications associated with invasive electrodes conventionally used to acquire high-resolution and spiking data.

SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

PubMed

Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

2017-01-01

This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

Automatic spike sorting using tuning information.

PubMed

Ventura, Valérie

2009-09-01

Current spike sorting methods focus on clustering neurons' characteristic spike waveforms. The resulting spike-sorted data are typically used to estimate how covariates of interest modulate the firing rates of neurons. However, when these covariates do modulate the firing rates, they provide information about spikes' identities, which thus far have been ignored for the purpose of spike sorting. This letter describes a novel approach to spike sorting, which incorporates both waveform information and tuning information obtained from the modulation of firing rates. Because it efficiently uses all the available information, this spike sorter yields lower spike misclassification rates than traditional automatic spike sorters. This theoretical result is verified empirically on several examples. The proposed method does not require additional assumptions; only its implementation is different. It essentially consists of performing spike sorting and tuning estimation simultaneously rather than sequentially, as is currently done. We used an expectation-maximization maximum likelihood algorithm to implement the new spike sorter. We present the general form of this algorithm and provide a detailed implementable version under the assumptions that neurons are independent and spike according to Poisson processes. Finally, we uncover a systematic flaw of spike sorting based on waveform information only.

Intra-day signal instabilities affect decoding performance in an intracortical neural interface system

PubMed Central

Perge, János A.; Homer, Mark L.; Malik, Wasim Q.; Cash, Sydney; Eskandar, Emad; Friehs, Gerhard; Donoghue, John P.; Hochberg, Leigh R.

2013-01-01

Objective Motor Neural Interface Systems (NIS) aim to convert neural signals into motor prosthetic or assistive device control, allowing people with paralysis to regain movement or control over their immediate environment. Effector or prosthetic control can degrade if the relationship between recorded neural signals and intended motor behavior changes. Therefore, characterizing both biological and technological sources of signal variability is important for a reliable NIS. Approach To address the frequency and causes of neural signal variability in a spike-based NIS, we analyzed within-day fluctuations in spiking activity and action potential amplitude recorded with silicon microelectrode arrays implanted in the motor cortex of three people with tetraplegia (BrainGate pilot clinical trial, IDE). Main results Eighty-four percent of the recorded units showed a statistically significant change in apparent firing rate (3.8±8.71Hz or 49% of the mean rate) across several-minute epochs of tasks performed on a single session, and seventy-four percent of the units showed a significant change in spike amplitude (3.7±6.5μV or 5.5% of mean spike amplitude). Forty percent of the recording sessions showed a significant correlation in the occurrence of amplitude changes across electrodes, suggesting array micro-movement. Despite the relatively frequent amplitude changes, only 15% of the observed within-day rate changes originated from recording artifacts such as spike amplitude change or electrical noise, while 85% of the rate changes most likely emerged from physiological mechanisms. Computer simulations confirmed that systematic rate changes of individual neurons could produce a directional “bias” in the decoded neural cursor movements. Instability in apparent neuronal spike rates indeed yielded a directional bias in fifty-six percent of all performance assessments in participant cursor control (n=2 participants, 108 and 20 assessments over two years), resulting in suboptimal performance in these sessions. Significance We anticipate that signal acquisition and decoding methods that can adapt to the reported instabilities will further improve the performance of intracortically-based NISs. PMID:23574741

Point process modeling and estimation: Advances in the analysis of dynamic neural spiking data

NASA Astrophysics Data System (ADS)

Deng, Xinyi

2016-08-01

A common interest of scientists in many fields is to understand the relationship between the dynamics of a physical system and the occurrences of discrete events within such physical system. Seismologists study the connection between mechanical vibrations of the Earth and the occurrences of earthquakes so that future earthquakes can be better predicted. Astrophysicists study the association between the oscillating energy of celestial regions and the emission of photons to learn the Universe's various objects and their interactions. Neuroscientists study the link between behavior and the millisecond-timescale spike patterns of neurons to understand higher brain functions. Such relationships can often be formulated within the framework of state-space models with point process observations. The basic idea is that the dynamics of the physical systems are driven by the dynamics of some stochastic state variables and the discrete events we observe in an interval are noisy observations with distributions determined by the state variables. This thesis proposes several new methodological developments that advance the framework of state-space models with point process observations at the intersection of statistics and neuroscience. In particular, we develop new methods 1) to characterize the rhythmic spiking activity using history-dependent structure, 2) to model population spike activity using marked point process models, 3) to allow for real-time decision making, and 4) to take into account the need for dimensionality reduction for high-dimensional state and observation processes. We applied these methods to a novel problem of tracking rhythmic dynamics in the spiking of neurons in the subthalamic nucleus of Parkinson's patients with the goal of optimizing placement of deep brain stimulation electrodes. We developed a decoding algorithm that can make decision in real-time (for example, to stimulate the neurons or not) based on various sources of information present in population spiking data. Lastly, we proposed a general three-step paradigm that allows us to relate behavioral outcomes of various tasks to simultaneously recorded neural activity across multiple brain areas, which is a step towards closed-loop therapies for psychological diseases using real-time neural stimulation. These methods are suitable for real-time implementation for content-based feedback experiments.

Interaction between synaptic inhibition and glial-potassium dynamics leads to diverse seizure transition modes in biophysical models of human focal seizures.

PubMed

Y Ho, E C; Truccolo, Wilson

2016-10-01

How focal seizures initiate and evolve in human neocortex remains a fundamental problem in neuroscience. Here, we use biophysical neuronal network models of neocortical patches to study how the interaction between inhibition and extracellular potassium ([K (+)] o ) dynamics may contribute to different types of focal seizures. Three main types of propagated focal seizures observed in recent intracortical microelectrode recordings in humans were modelled: seizures characterized by sustained (∼30-60 Hz) gamma local field potential (LFP) oscillations; seizures where the onset in the propagated site consisted of LFP spikes that later evolved into rhythmic (∼2-3 Hz) spike-wave complexes (SWCs); and seizures where a brief stage of low-amplitude fast-oscillation (∼10-20 Hz) LFPs preceded the SWC activity. Our findings are fourfold: (1) The interaction between elevated [K (+)] o (due to abnormal potassium buffering by glial cells) and the strength of synaptic inhibition plays a predominant role in shaping these three types of seizures. (2) Strengthening of inhibition leads to the onset of sustained narrowband gamma seizures. (3) Transition into SWC seizures is obtained either by the weakening of inhibitory synapses, or by a transient strengthening followed by an inhibitory breakdown (e.g. GABA depletion). This reduction or breakdown of inhibition among fast-spiking (FS) inhibitory interneurons increases their spiking activity and leads them eventually into depolarization block. Ictal spike-wave discharges in the model are then sustained solely by pyramidal neurons. (4) FS cell dynamics are also critical for seizures where the evolution into SWC activity is preceded by low-amplitude fast oscillations. Different levels of elevated [K (+)] o were important for transitions into and maintenance of sustained gamma oscillations and SWC discharges. Overall, our modelling study predicts that the interaction between inhibitory interneurons and [K (+)] o glial buffering under abnormal conditions may explain different types of ictal transitions and dynamics during propagated seizures in human focal epilepsy.

Molecular dynamics simulations of bubble nucleation in dark matter detectors.

PubMed

Denzel, Philipp; Diemand, Jürg; Angélil, Raymond

2016-01-01

Bubble chambers and droplet detectors used in dosimetry and dark matter particle search experiments use a superheated metastable liquid in which nuclear recoils trigger bubble nucleation. This process is described by the classical heat spike model of F. Seitz [Phys. Fluids (1958-1988) 1, 2 (1958)PFLDAS0031-917110.1063/1.1724333], which uses classical nucleation theory to estimate the amount and the localization of the deposited energy required for bubble formation. Here we report on direct molecular dynamics simulations of heat-spike-induced bubble formation. They allow us to test the nanoscale process described in the classical heat spike model. 40 simulations were performed, each containing about 20 million atoms, which interact by a truncated force-shifted Lennard-Jones potential. We find that the energy per length unit needed for bubble nucleation agrees quite well with theoretical predictions, but the allowed spike length and the required total energy are about twice as large as predicted. This could be explained by the rapid energy diffusion measured in the simulation: contrary to the assumption in the classical model, we observe significantly faster heat diffusion than the bubble formation time scale. Finally we examine α-particle tracks, which are much longer than those of neutrons and potential dark matter particles. Empirically, α events were recently found to result in louder acoustic signals than neutron events. This distinction is crucial for the background rejection in dark matter searches. We show that a large number of individual bubbles can form along an α track, which explains the observed larger acoustic amplitudes.

A New and Fast Method for Smoothing Spectral Imaging Data

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Liu, Ming; Davis, Curtiss O.

1998-01-01

The Airborne Visible Infrared Imaging Spectrometer (AVIRIS) acquires spectral imaging data covering the 0.4 - 2.5 micron wavelength range in 224 10-nm-wide channels from a NASA ER-2 aircraft at 20 km. More than half of the spectral region is affected by atmospheric gaseous absorption. Over the past decade, several techniques have been used to remove atmospheric effects from AVIRIS data for the derivation of surface reflectance spectra. An operational atmosphere removal algorithm (ATREM), which is based on theoretical modeling of atmospheric absorption and scattering effects, has been developed and updated for deriving surface reflectance spectra from AVIRIS data. Due to small errors in assumed wavelengths and errors in line parameters compiled on the HITRAN database, small spikes (particularly near the centers of the 0.94- and 1.14-micron water vapor bands) are present in this spectrum. Similar small spikes are systematically present in entire ATREM output cubes. These spikes have distracted geologists who are interested in studying surface mineral features. A method based on the "global" fitting of spectra with low order polynomials or other functions for removing these weak spikes has recently been developed by Boardman (this volume). In this paper, we describe another technique, which fits spectra "locally" based on cubic spline smoothing, for quick post processing of ATREM apparent reflectance spectra derived from AVIRIS data. Results from our analysis of AVIRIS data acquired over Cuprite mining district in Nevada in June of 1995 are given. Comparisons between our smoothed spectra and those derived with the empirical line method are presented.

CLUSTERING OF INTERICTAL SPIKES BY DYNAMIC TIME WARPING AND AFFINITY PROPAGATION

PubMed Central

Thomas, John; Jin, Jing; Dauwels, Justin; Cash, Sydney S.; Westover, M. Brandon

2018-01-01

Epilepsy is often associated with the presence of spikes in electroencephalograms (EEGs). The spike waveforms vary vastly among epilepsy patients, and also for the same patient across time. In order to develop semi-automated and automated methods for detecting spikes, it is crucial to obtain a better understanding of the various spike shapes. In this paper, we develop several approaches to extract exemplars of spikes. We generate spike exemplars by applying clustering algorithms to a database of spikes from 12 patients. As similarity measures for clustering, we consider the Euclidean distance and Dynamic Time Warping (DTW). We assess two clustering algorithms, namely, K-means clustering and affinity propagation. The clustering methods are compared based on the mean squared error, and the similarity measures are assessed based on the number of generated spike clusters. Affinity propagation with DTW is shown to be the best combination for clustering epileptic spikes, since it generates fewer spike templates and does not require to pre-specify the number of spike templates. PMID:29527130

Training Spiking Neural Models Using Artificial Bee Colony

PubMed Central

Vazquez, Roberto A.; Garro, Beatriz A.

2015-01-01

Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, the lack of learning strategies for training these models do not allow to use them in several pattern recognition problems. On the other hand, several bioinspired algorithms have been proposed in the last years for solving a broad range of optimization problems, including those related to the field of artificial neural networks (ANNs). Artificial bee colony (ABC) is a novel algorithm based on the behavior of bees in the task of exploring their environment to find a food source. In this paper, we describe how the ABC algorithm can be used as a learning strategy to train a spiking neuron aiming to solve pattern recognition problems. Finally, the proposed approach is tested on several pattern recognition problems. It is important to remark that to realize the powerfulness of this type of model only one neuron will be used. In addition, we analyze how the performance of these models is improved using this kind of learning strategy. PMID:25709644

Intrinsic and synaptic properties of vertical cells of the mouse dorsal cochlear nucleus

PubMed Central

Kuo, Sidney P.; Lu, Hsin-Wei

2012-01-01

Multiple classes of inhibitory interneurons shape the activity of principal neurons of the dorsal cochlear nucleus (DCN), a primary target of auditory nerve fibers in the mammalian brain stem. Feedforward inhibition mediated by glycinergic vertical cells (also termed tuberculoventral or corn cells) is thought to contribute importantly to the sound-evoked response properties of principal neurons, but the cellular and synaptic properties that determine how vertical cells function are unclear. We used transgenic mice in which glycinergic neurons express green fluorescent protein (GFP) to target vertical cells for whole cell patch-clamp recordings in acute slices of DCN. We found that vertical cells express diverse intrinsic spiking properties and could fire action potentials at high, sustained spiking rates. Using paired recordings, we directly examined synapses made by vertical cells onto fusiform cells, a primary DCN principal cell type. Vertical cell synapses produced unexpectedly small-amplitude unitary currents in fusiform cells, and additional experiments indicated that multiple vertical cells must be simultaneously active to inhibit fusiform cell spike output. Paired recordings also revealed that a major source of inhibition to vertical cells comes from other vertical cells. PMID:22572947

A protozoal-associated epizootic impacting marine wildlife: Mass-mortality of southern sea otters (Enhydra lutris nereis) due to Sarcocystis neurona infection

USGS Publications Warehouse

Miller, M.A.; Conrad, P.A.; Harris, M.; Hatfield, B.; Langlois, G.; Jessup, David A.; Magargal, S.L.; Packham, A.E.; Toy-Choutka, S.; Melli, A.C.; Murray, M.A.; Gulland, F.M.; Grigg, M.E.

2010-01-01

During April 2004, 40 sick and dead southern sea otters (Enhydra lutris nereis) were recovered over 18 km of coastline near Morro Bay, California. This event represented the single largest monthly spike in mortality ever recorded during 30 years of southern sea otter stranding data collection. Because of the point-source nature of the event and clinical signs consistent with severe, acute neurological disease, exposure to a chemical or marine toxin was initially considered. However, detailed postmortem examinations revealed lesions consistent with an infectious etiology, and further investigation confirmed the protozoan parasite Sarcocystis neurona as the underlying cause. Tissues from 94% of examined otters were PCR-positive for S. neurona, based on DNA amplification and sequencing at the ITS-1 locus, and 100% of tested animals (n= 14) had elevated IgM and IgG titers to S. neurona. Evidence to support the point-source character of this event include the striking spatial and temporal clustering of cases and detection of high concentrations of anti- S. neurona IgM in serum of stranded animals. Concurrent exposure to the marine biotoxin domoic acid may have enhanced susceptibility of affected otters to S. neurona and exacerbated the neurological signs exhibited by stranded animals. Other factors that may have contributed to the severity of this epizootic include a large rainstorm that preceded the event and an abundance of razor clams near local beaches, attracting numerous otters close to shore within the affected area. This is the first report of a localized epizootic in marine wildlife caused by apicomplexan protozoa. ?? 2010 Elsevier B.V.

Large‐scale analysis reveals populational contributions of cortical spike rate and synchrony to behavioural functions

PubMed Central

Saiki, Akiko; Fujiwara‐Tsukamoto, Yoko; Sakai, Yutaka; Isomura, Yoshikazu

2016-01-01

Key points There have been few systematic population‐wide analyses of relationships between spike synchrony within a period of several milliseconds and behavioural functions.In this study, we obtained a large amount of spike data from > 23,000 neuron pairs by multiple single‐unit recording from deep layer neurons in motor cortical areas in rats performing a forelimb movement task.The temporal changes of spike synchrony in the whole neuron pairs were statistically independent of behavioural changes during the task performance, although some neuron pairs exhibited correlated changes in spike synchrony.Mutual information analyses revealed that spike synchrony made a smaller contribution than spike rate to behavioural functions.The strength of spike synchrony between two neurons was statistically independent of the spike rate‐based preferences of the pair for behavioural functions. Abstract Spike synchrony within a period of several milliseconds in presynaptic neurons enables effective integration of functional information in the postsynaptic neuron. However, few studies have systematically analysed the population‐wide relationships between spike synchrony and behavioural functions. Here we obtained a sufficiently large amount of spike data among regular‐spiking (putatively excitatory) and fast‐spiking (putatively inhibitory) neuron subtypes (> 23,000 pairs) by multiple single‐unit recording from deep layers in motor cortical areas (caudal forelimb area, rostral forelimb area) in rats performing a forelimb movement task. After holding a lever, rats pulled the lever either in response to a cue tone (external‐trigger trials) or spontaneously without any cue (internal‐trigger trials). Many neurons exhibited functional spike activity in association with forelimb movements, and the preference of regular‐spiking neurons in the rostral forelimb area was more biased toward externally triggered movement than that in the caudal forelimb area. We found that a population of neuron pairs with spike synchrony does exist, and that some neuron pairs exhibit a dependence on movement phase during task performance. However, the population‐wide analysis revealed that spike synchrony was statistically independent of the movement phase and the spike rate‐based preferences of the pair for behavioural functions, whereas spike rates were clearly dependent on the movement phase. In fact, mutual information analyses revealed that the contribution of spike synchrony to the behavioural functions was small relative to the contribution of spike rate. Our large‐scale analysis revealed that cortical spike rate, rather than spike synchrony, contributes to population coding for movement. PMID:27488936

Large-scale analysis reveals populational contributions of cortical spike rate and synchrony to behavioural functions.

PubMed

Kimura, Rie; Saiki, Akiko; Fujiwara-Tsukamoto, Yoko; Sakai, Yutaka; Isomura, Yoshikazu

2017-01-01

There have been few systematic population-wide analyses of relationships between spike synchrony within a period of several milliseconds and behavioural functions. In this study, we obtained a large amount of spike data from > 23,000 neuron pairs by multiple single-unit recording from deep layer neurons in motor cortical areas in rats performing a forelimb movement task. The temporal changes of spike synchrony in the whole neuron pairs were statistically independent of behavioural changes during the task performance, although some neuron pairs exhibited correlated changes in spike synchrony. Mutual information analyses revealed that spike synchrony made a smaller contribution than spike rate to behavioural functions. The strength of spike synchrony between two neurons was statistically independent of the spike rate-based preferences of the pair for behavioural functions. Spike synchrony within a period of several milliseconds in presynaptic neurons enables effective integration of functional information in the postsynaptic neuron. However, few studies have systematically analysed the population-wide relationships between spike synchrony and behavioural functions. Here we obtained a sufficiently large amount of spike data among regular-spiking (putatively excitatory) and fast-spiking (putatively inhibitory) neuron subtypes (> 23,000 pairs) by multiple single-unit recording from deep layers in motor cortical areas (caudal forelimb area, rostral forelimb area) in rats performing a forelimb movement task. After holding a lever, rats pulled the lever either in response to a cue tone (external-trigger trials) or spontaneously without any cue (internal-trigger trials). Many neurons exhibited functional spike activity in association with forelimb movements, and the preference of regular-spiking neurons in the rostral forelimb area was more biased toward externally triggered movement than that in the caudal forelimb area. We found that a population of neuron pairs with spike synchrony does exist, and that some neuron pairs exhibit a dependence on movement phase during task performance. However, the population-wide analysis revealed that spike synchrony was statistically independent of the movement phase and the spike rate-based preferences of the pair for behavioural functions, whereas spike rates were clearly dependent on the movement phase. In fact, mutual information analyses revealed that the contribution of spike synchrony to the behavioural functions was small relative to the contribution of spike rate. Our large-scale analysis revealed that cortical spike rate, rather than spike synchrony, contributes to population coding for movement. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

Spike persistence and normalization in benign epilepsy with centrotemporal spikes - Implications for management.

PubMed

Kim, Hunmin; Kim, Soo Yeon; Lim, Byung Chan; Hwang, Hee; Chae, Jong-Hee; Choi, Jieun; Kim, Ki Joong; Dlugos, Dennis J

2018-05-10

This study was performed 1) to determine the timing of spike normalization in patients with benign epilepsy with centrotemporal spikes (BECTS); 2) to identify relationships between age of seizure onset, age of spike normalization, years of spike persistence and treatment; and 3) to assess final outcomes between groups of patients with or without spikes at the time of medication tapering. Retrospective analysis of BECTS patients confirmed by clinical data, including age of onset, seizure semiology and serial electroencephalography (EEG) from diagnosis to remission. Age at spike normalization, years of spike persistence, and time of treatment onset to spike normalization were assessed. Final seizure and EEG outcome were compared between the groups with or without spikes at the time of AED tapering. One hundred and thirty-four patients were included. Mean age at seizure onset was 7.52 ± 2.11 years. Mean age at spike normalization was 11.89 ± 2.11 (range: 6.3-16.8) years. Mean time of treatment onset to spike normalization was 4.11 ± 2.13 (range: 0.24-10.08) years. Younger age of seizure onset was correlated with longer duration of spike persistence (r = -0.41, p < 0.001). In treated patients, spikes persisted for 4.1 ± 1.95 years, compared with 2.9 ± 1.97 years in untreated patients. No patients had recurrent seizures after AED was discontinued, regardless of the presence/absence of spikes at time of AED tapering. Years of spike persistence was longer in early onset BECTS patients. Treatment with AEDs did not shorten years of spike persistence. Persistence of spikes at time of treatment withdrawal was not associated with seizure recurrence. Copyright © 2018 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Detection of infectious bronchitis virus strains similar to Japan in Taiwan.

PubMed

Tsai, Cheng-Ta; Tsai, Hsin-Fu; Wang, Ching-Ho

2016-06-01

A total of 1,320 tracheal samples from 66 broiler flocks sent to slaughterhouses and 42 tracheal samples from 42 flocks of local chickens in the field were collected for infectious bronchitis virus (IBV) gene detection by reverse transcription polymerase chain reaction using nucleocapsid-specific primers and spike-specific primers. Prevalence in broiler flocks was 39.4% (26/66) and in local chicken flocks was 11.9% (5/42). Several IBVs similar to Japan were detected in Taiwan. One-direction neutralization revealed that the reference antisera did not offer protection against the IBVs similar to those from Japan.

Prevention of Ca(2+)-mediated action potentials in GABAergic local circuit neurones of rat thalamus by a transient K+ current.

PubMed Central

Pape, H C; Budde, T; Mager, R; Kisvárday, Z F

1994-01-01

1. Neurones enzymatically dissociated from the rat dorsal lateral geniculate nucleus (LGN) were identified as GABAergic local circuit interneurones and geniculocortical relay cells, based upon quantitative analysis of soma profiles, immunohistochemical detection of GABA or glutamic acid decarboxylase, and basic electrogenic behaviour. 2. During whole-cell current-clamp recording, isolated LGN neurones generated firing patterns resembling those in intact tissue, with the most striking difference relating to the presence in relay cells of a Ca2+ action potential with a low threshold of activation, capable of triggering fast spikes, and the absence of a regenerative Ca2+ response with a low threshold of activation in local circuit cells. 3. Whole-cell voltage-clamp experiments demonstrated that both classes of LGN neurones possess at least two voltage-dependent membrane currents which operate in a range of membrane potentials negative to the threshold for generation of Na(+)-K(+)-mediated spikes: the T-type Ca2+ current (IT) and an A-type K+ current (IA). Taking into account the differences in membrane surface area, the average size of IT was similar in the two types of neurones, and interneurones possessed a slightly larger A-conductance. 4. In local circuit neurones, the ranges of steady-state inactivation and activation of IT and IA were largely overlapping (VH = 81.1 vs. -82.8 mV), both currents activated at around -70 mV, and they rapidly increased in amplitude with further depolarization. In relay cells, the inactivation curve of IT was negatively shifted along the voltage axis by about 20 mV compared with that of IA (Vh = -86.1 vs. -69.2 mV), and the activation threshold for IT (at -80 mV) was 20 mV more negative than that for IA. In interneurones, the activation range of IT was shifted to values more positive than that in relay cells (Vh = -54.9 vs. -64.5 mV), whereas the activation range of IA was more negative (Vh = -25.2 vs. -14.5 mV). 5. Under whole-cell voltage-clamp conditions that allowed the combined activation of Ca2+ and K+ currents, depolarizing voltage steps from -110 mV evoked inward currents resembling IT in relay cells and small outward currents indicative of IA in local circuit neurones. After blockade of IA with 4-aminopyridine (4-AP), the same pulse protocol produced IT in both types of neurones. Under current clamp, 4-AP unmasked a regenerative membrane depolarization with a low threshold of activation capable of triggering fast spikes in local circuit neurones.(ABSTRACT TRUNCATED AT 400 WORDS) Images Figure 1 PMID:7965855

Revisiting the thermal-spike concept in ion-surface interactions

NASA Astrophysics Data System (ADS)

Miotello, Antonio; Kelly, Roger

1997-02-01

In recent years many groups have advocated a thermal-spike model to explain a variety of experimental results in ion-irradiation of solids, as for example sputtering, mixing, compositional change, structural change, and track formation. The latter include crystal-to-amorphous transitions as well as track formation due to MeV/u particles. In this paper we reconsider the phenomena occurring during ion impact of solids looking at the time scale generally indicated as relevant for thermal-spike effects, namely a picosecond scale as shown by molecular dynamics. Sputtering, mixing, and track formation, however, will be analyzed in more detail. We consider first ion-beam sputtering and reiterate (as is already well-known) that yields which increase with the bulk temperature most often indicate merely the onset of normal vaporization. Indeed, only simulations appear to be capable of giving insight even if the information is sometimes tentative. In mixing, ballistic transport is important but not dominant. It is often argued that the additional transport is provided by thermal spikes but it is noted that such an assumption is normally not required by the experimental results. What is more relevant is a role for residual defects such that the total diffusion flux includes (if the defects are chemically guided) a modified Darken factor, or (if the defects are not chemically guided) simply an increased diffusivity. The time scale (min), distances (well beyond the collision cascade), temperature sensitivity (changes of as little as 75 K are relevant), and correlation with vacancy properties (thence with the solid rather than liquid state) which are relevant to these residual defects are not understandable in terms of thermal spikes. We finally consider track formation. Recent work claiming that track formation in solids, irradiated with heavy ions, may be understood in terms of thermal spikes is reconsidered to show that the thermal-spike model is utilized without considering all the relevant phenomena included in irradiation-induced heating and phase transitions. For example, a comparison of fs-laser pulse irradiation of Si with swift heavy-ion irradiation, shows that melting is possible in the first case since the excited electrons have a low and more or less restricted energy while in the case of swift ion-irradiation, the motion of the excited electrons includes a ballistic component which does not favour the localization of the thermal energy necessary to induce lattice melting. It is concluded that track formation is better understandable in a more general framework of defect-induced processes in solids.

Automatic Spike Sorting Using Tuning Information

PubMed Central

Ventura, Valérie

2011-01-01

Current spike sorting methods focus on clustering neurons’ characteristic spike waveforms. The resulting spike-sorted data are typically used to estimate how covariates of interest modulate the firing rates of neurons. However, when these covariates do modulate the firing rates, they provide information about spikes’ identities, which thus far have been ignored for the purpose of spike sorting. This letter describes a novel approach to spike sorting, which incorporates both waveform information and tuning information obtained from the modulation of firing rates. Because it efficiently uses all the available information, this spike sorter yields lower spike misclassification rates than traditional automatic spike sorters. This theoretical result is verified empirically on several examples. The proposed method does not require additional assumptions; only its implementation is different. It essentially consists of performing spike sorting and tuning estimation simultaneously rather than sequentially, as is currently done. We used an expectation-maximization maximum likelihood algorithm to implement the new spike sorter. We present the general form of this algorithm and provide a detailed implementable version under the assumptions that neurons are independent and spike according to Poisson processes. Finally, we uncover a systematic flaw of spike sorting based on waveform information only. PMID:19548802

Enhanced Removal of Nutrients and Trace Organics from Urban Runoff with Novel Capture, Treatment, and Recharge Systems

NASA Astrophysics Data System (ADS)

Ashoori, N.; Planes, M. T.; Lefevre, G.; Sedlak, D.; Luthy, R. G.

2017-12-01

Rapid population growth, urban sprawl and impact of climate change are forcing water-stressed areas to rely on new local sources of water supply. Under this scenario, reclamation of stormwater runoff has emerged as a source for irrigation and replenishing drinking-water groundwater reservoirs. However, urban stormwater can be a significant source of pollutants, including nutrients and organic compounds. In order to overcome the stormwater treatment system limitations, this project has developed a pilot-scale column system for passive treatment of infiltrated water using low-cost, low-energy geomedia. The objective was to provide guidance on the design and operation of systems for controlling nutrient and trace organic contaminant releases to surface waters. The work comprised of replicate column studies in the field to test stormwater treatment modules with various media, such as woodchips and biochar, using urban runoff from a watershed in Sonoma, California. Woodchip bioreactors host an endemic population of microorganisms that can be harnessed to biologically degrade nitrate. The columns amended with biochar enhance removal of organic pollutants present in stormwater through physicochemical processes (i.e., adsorption onto biochar) and biodegradation in the column through increasing retention time. The field columns were conditioned with stormwater for eight months before being spiked weekly with 50 ppb of representative trace organics. The key finding was the successful field demonstration of a novel treatment system for both the removal of nitrate and trace organics. Nitrogen removal was successful in all columns for the thirteen month experiment due to the woodchips being an effective source of carbon for denitrifying microorganisms to convert nitrate to nitrogen gases. As for the trace organics experiments, the results highlight an overall attenuation of the studied trace organic compounds by the columns containing woodchip and biochar throughout the five months of contaminant dosing. By developing a fundamental understanding of the mechanisms of contaminant removal in the laboratory and testing system performance at the test-bed scale, the project advances efforts to improve water quality and augment local water supplies through distributed capture, treatment, and recharge systems.

Spikes and matter inhomogeneities in massless scalar field models

NASA Astrophysics Data System (ADS)

Coley, A. A.; Lim, W. C.

2016-01-01

We shall discuss the general relativistic generation of spikes in a massless scalar field or stiff perfect fluid model. We first investigate orthogonally transitive (OT) G 2 stiff fluid spike models both heuristically and numerically, and give a new exact OT G 2 stiff fluid spike solution. We then present a new two-parameter family of non-OT G 2 stiff fluid spike solutions, obtained by the generalization of non-OT G 2 vacuum spike solutions to the stiff fluid case by applying Geroch's transformation on a Jacobs seed. The dynamics of these new stiff fluid spike solutions is qualitatively different from that of the vacuum spike solutions in that the matter (stiff fluid) feels the spike directly and the stiff fluid spike solution can end up with a permanent spike. We then derive the evolution equations of non-OT G 2 stiff fluid models, including a second perfect fluid, in full generality, and briefly discuss some of their qualitative properties and their potential numerical analysis. Finally, we discuss how a fluid, and especially a stiff fluid or massless scalar field, affects the physics of the generation of spikes.

Supervised Learning Based on Temporal Coding in Spiking Neural Networks.

PubMed

Mostafa, Hesham

2017-08-01

Gradient descent training techniques are remarkably successful in training analog-valued artificial neural networks (ANNs). Such training techniques, however, do not transfer easily to spiking networks due to the spike generation hard nonlinearity and the discrete nature of spike communication. We show that in a feedforward spiking network that uses a temporal coding scheme where information is encoded in spike times instead of spike rates, the network input-output relation is differentiable almost everywhere. Moreover, this relation is piecewise linear after a transformation of variables. Methods for training ANNs thus carry directly to the training of such spiking networks as we show when training on the permutation invariant MNIST task. In contrast to rate-based spiking networks that are often used to approximate the behavior of ANNs, the networks we present spike much more sparsely and their behavior cannot be directly approximated by conventional ANNs. Our results highlight a new approach for controlling the behavior of spiking networks with realistic temporal dynamics, opening up the potential for using these networks to process spike patterns with complex temporal information.

A model-based spike sorting algorithm for removing correlation artifacts in multi-neuron recordings.

PubMed

Pillow, Jonathan W; Shlens, Jonathon; Chichilnisky, E J; Simoncelli, Eero P

2013-01-01

We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call "binary pursuit". The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth.

A Model-Based Spike Sorting Algorithm for Removing Correlation Artifacts in Multi-Neuron Recordings

PubMed Central

Chichilnisky, E. J.; Simoncelli, Eero P.

2013-01-01

We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call “binary pursuit”. The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth. PMID:23671583

Frequency-dependent reliability of spike propagation is function of axonal voltage-gated sodium channels in cerebellar Purkinje cells.

PubMed

Yang, Zhilai; Wang, Jin-Hui

2013-12-01

The spike propagation on nerve axons, like synaptic transmission, is essential to ensure neuronal communication. The secure propagation of sequential spikes toward axonal terminals has been challenged in the neurons with a high firing rate, such as cerebellar Purkinje cells. The shortfall of spike propagation makes some digital spikes disappearing at axonal terminals, such that the elucidation of the mechanisms underlying spike propagation reliability is crucial to find the strategy of preventing loss of neuronal codes. As the spike propagation failure is influenced by the membrane potentials, this process is likely caused by altering the functional status of voltage-gated sodium channels (VGSC). We examined this hypothesis in Purkinje cells by using pair-recordings at their somata and axonal blebs in cerebellar slices. The reliability of spike propagation was deteriorated by elevating spike frequency. The frequency-dependent reliability of spike propagation was attenuated by inactivating VGSCs and improved by removing their inactivation. Thus, the functional status of axonal VGSCs influences the reliability of spike propagation.

Dynamical transition, hydrophobic interface, and the temperature dependence of electrostatic fluctuations in proteins.

PubMed

Lebard, David N; Matyushov, Dmitry V

2008-12-01

Molecular dynamics simulations have revealed a dramatic increase, with increasing temperature, of the amplitude of electrostatic fluctuations caused by water at the active site of metalloprotein plastocyanin. The increased breadth of electrostatic fluctuations, expressed in terms of the reorganization energy of changing the redox state of the protein, is related to the formation of the hydrophobic protein-water interface, allowing large-amplitude collective fluctuations of the water density in the protein's first solvation shell. On top of the monotonic increase of the reorganization energy with increasing temperature, we have observed a spike at approximately 220 K also accompanied by a significant slowing of the exponential collective Stokes shift dynamics. In contrast to the local density fluctuations of the hydration-shell waters, these spikes might be related to the global property of the water solvent crossing the Widom line or undergoing a weak first-order transition.

Signal, noise, and variation in neural and sensory-motor latency

PubMed Central

Lee, Joonyeol; Joshua, Mati; Medina, Javier F.; Lisberger, Stephen G.

2016-01-01

Analysis of the neural code for sensory-motor latency in smooth pursuit eye movements reveals general principles of neural variation and the specific origin of motor latency. The trial-by-trial variation in neural latency in MT comprises: a shared component expressed as neuron-neuron latency correlations; and an independent component that is local to each neuron. The independent component arises heavily from fluctuations in the underlying probability of spiking with an unexpectedly small contribution from the stochastic nature of spiking itself. The shared component causes the latency of single neuron responses in MT to be weakly predictive of the behavioral latency of pursuit. Neural latency deeper in the motor system is more strongly predictive of behavioral latency. A model reproduces both the variance of behavioral latency and the neuron-behavior latency correlations in MT if it includes realistic neural latency variation, neuron-neuron latency correlations in MT, and noisy gain control downstream from MT. PMID:26971946

Pattern Formation in Keller-Segel Chemotaxis Models with Logistic Growth

NASA Astrophysics Data System (ADS)

Jin, Ling; Wang, Qi; Zhang, Zengyan

In this paper, we investigate pattern formation in Keller-Segel chemotaxis models over a multidimensional bounded domain subject to homogeneous Neumann boundary conditions. It is shown that the positive homogeneous steady state loses its stability as chemoattraction rate χ increases. Then using Crandall-Rabinowitz local theory with χ being the bifurcation parameter, we obtain the existence of nonhomogeneous steady states of the system which bifurcate from this homogeneous steady state. Stability of the bifurcating solutions is also established through rigorous and detailed calculations. Our results provide a selection mechanism of stable wavemode which states that the only stable bifurcation branch must have a wavemode number that minimizes the bifurcation value. Finally, we perform extensive numerical simulations on the formation of stable steady states with striking structures such as boundary spikes, interior spikes, stripes, etc. These nontrivial patterns can model cellular aggregation that develop through chemotactic movements in biological systems.

Spike-Timing of Orbitofrontal Neurons Is Synchronized With Breathing.

PubMed

Kőszeghy, Áron; Lasztóczi, Bálint; Forro, Thomas; Klausberger, Thomas

2018-01-01

The orbitofrontal cortex (OFC) has been implicated in a multiplicity of complex brain functions, including representations of expected outcome properties, post-decision confidence, momentary food-reward values, complex flavors and odors. As breathing rhythm has an influence on odor processing at primary olfactory areas, we tested the hypothesis that it may also influence neuronal activity in the OFC, a prefrontal area involved also in higher order processing of odors. We recorded spike timing of orbitofrontal neurons as well as local field potentials (LFPs) in awake, head-fixed mice, together with the breathing rhythm. We observed that a large majority of orbitofrontal neurons showed robust phase-coupling to breathing during immobility and running. The phase coupling of action potentials to breathing was significantly stronger in orbitofrontal neurons compared to cells in the medial prefrontal cortex. The characteristic synchronization of orbitofrontal neurons with breathing might provide a temporal framework for multi-variable processing of olfactory, gustatory and reward-value relationships.

Joint statistics of strongly correlated neurons via dimensionality reduction

NASA Astrophysics Data System (ADS)

Deniz, Taşkın; Rotter, Stefan

2017-06-01

The relative timing of action potentials in neurons recorded from local cortical networks often shows a non-trivial dependence, which is then quantified by cross-correlation functions. Theoretical models emphasize that such spike train correlations are an inevitable consequence of two neurons being part of the same network and sharing some synaptic input. For non-linear neuron models, however, explicit correlation functions are difficult to compute analytically, and perturbative methods work only for weak shared input. In order to treat strong correlations, we suggest here an alternative non-perturbative method. Specifically, we study the case of two leaky integrate-and-fire neurons with strong shared input. Correlation functions derived from simulated spike trains fit our theoretical predictions very accurately. Using our method, we computed the non-linear correlation transfer as well as correlation functions that are asymmetric due to inhomogeneous intrinsic parameters or unequal input.

A case study of air quality above an urban roof top vegetable farm.

PubMed

Tong, Zheming; Whitlow, Thomas H; Landers, Andrew; Flanner, Benjamin

2016-01-01

The effect of elevation and rooftop configuration on local air quality was investigated at the Brooklyn Grange rooftop farm during a short-term observational campaign. Using multiple particle counters and sonic anemometers deployed along vertical gradients, we found that PM2.5 concentration decayed with height above the street. Samples adjacent to the street had the highest average PM2.5 concentration and frequent stochastic spikes above background. Rooftop observations 26 m above ground showed 7-33% reductions in average PM2.5 concentration compared with the curbside and had far fewer spikes. A relationship between the vertical extinction rate of PM2.5 and atmospheric stability was found whereby less unstable atmosphere and greater wind shear led to greater PM2.5 extinction due to damped vertical motion of air. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spiking Neural P Systems with Communication on Request.

PubMed

Pan, Linqiang; Păun, Gheorghe; Zhang, Gexiang; Neri, Ferrante

2017-12-01

Spiking Neural [Formula: see text] Systems are Neural System models characterized by the fact that each neuron mimics a biological cell and the communication between neurons is based on spikes. In the Spiking Neural [Formula: see text] systems investigated so far, the application of evolution rules depends on the contents of a neuron (checked by means of a regular expression). In these [Formula: see text] systems, a specified number of spikes are consumed and a specified number of spikes are produced, and then sent to each of the neurons linked by a synapse to the evolving neuron. [Formula: see text]In the present work, a novel communication strategy among neurons of Spiking Neural [Formula: see text] Systems is proposed. In the resulting models, called Spiking Neural [Formula: see text] Systems with Communication on Request, the spikes are requested from neighboring neurons, depending on the contents of the neuron (still checked by means of a regular expression). Unlike the traditional Spiking Neural [Formula: see text] systems, no spikes are consumed or created: the spikes are only moved along synapses and replicated (when two or more neurons request the contents of the same neuron). [Formula: see text]The Spiking Neural [Formula: see text] Systems with Communication on Request are proved to be computationally universal, that is, equivalent with Turing machines as long as two types of spikes are used. Following this work, further research questions are listed to be open problems.

The relationship between seizures, interictal spikes and antiepileptic drugs.

PubMed

Goncharova, Irina I; Alkawadri, Rafeed; Gaspard, Nicolas; Duckrow, Robert B; Spencer, Dennis D; Hirsch, Lawrence J; Spencer, Susan S; Zaveri, Hitten P

2016-09-01

A considerable decrease in spike rate accompanies antiepileptic drug (AED) taper during intracranial EEG (icEEG) monitoring. Since spike rate during icEEG monitoring can be influenced by surgery to place intracranial electrodes, we studied spike rate during long-term scalp EEG monitoring to further test this observation. We analyzed spike rate, seizure occurrence and AED taper in 130 consecutive patients over an average of 8.9days (range 5-17days). We observed a significant relationship between time to the first seizure, spike rate, AED taper and seizure occurrence (F (3,126)=19.77, p<0.0001). A high spike rate was related to a longer time to the first seizure. Further, in a subset of 79 patients who experienced seizures on or after day 4 of monitoring, spike rate decreased initially from an on- to off-AEDs epoch (from 505.0 to 382.3 spikes per hour, p<0.00001), and increased thereafter with the occurrence of seizures. There is an interplay between seizures, spikes and AEDs such that spike rate decreases with AED taper and increases after seizure occurrence. The direct relationship between spike rate and AEDs and between spike rate and time to the first seizure suggests that spikes are a marker of inhibition rather than excitation. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

An integrated system for multichannel neuronal recording with spike/LFP separation, integrated A/D conversion and threshold detection.

PubMed

Perelman, Yevgeny; Ginosar, Ran

2007-01-01

A mixed-signal front-end processor for multichannel neuronal recording is described. It receives 12 differential-input channels of implanted recording electrodes. A programmable cutoff High Pass Filter (HPF) blocks dc and low-frequency input drift at about 1 Hz. The signals are band-split at about 200 Hz to low-frequency Local Field Potential (LFP) and high-frequency spike data (SPK), which is band limited by a programmable-cutoff LPF, in a range of 8-13 kHz. Amplifier offsets are compensated by 5-bit calibration digital-to-analog converters (DACs). The SPK and LFP channels provide variable amplification rates of up to 5000 and 500, respectively. The analog signals are converted into 10-bit digital form, and streamed out over a serial digital bus at up to 8 Mbps. A threshold filter suppresses inactive portions of the signal and emits only spike segments of programmable length. A prototype has been fabricated on a 0.35-microm CMOS process and tested successfully, demonstrating a 3-microV noise level. Special interface system incorporating an embedded CPU core in a programmable logic device accompanied by real-time software has been developed to allow connectivity to a computer host.

Configurable hardware integrate and fire neurons for sparse approximation.

PubMed

Shapero, Samuel; Rozell, Christopher; Hasler, Paul

2013-09-01

Sparse approximation is an important optimization problem in signal and image processing applications. A Hopfield-Network-like system of integrate and fire (IF) neurons is proposed as a solution, using the Locally Competitive Algorithm (LCA) to solve an overcomplete L1 sparse approximation problem. A scalable system architecture is described, including IF neurons with a nonlinear firing function, and current-based synapses to provide linear computation. A network of 18 neurons with 12 inputs is implemented on the RASP 2.9v chip, a Field Programmable Analog Array (FPAA) with directly programmable floating gate elements. Said system uses over 1400 floating gates, the largest system programmed on a FPAA to date. The circuit successfully reproduced the outputs of a digital optimization program, converging to within 4.8% RMS, and an objective cost only 1.7% higher on average. The active circuit consumed 559 μA of current at 2.4 V and converges on solutions in 25 μs, with measurement of the converged spike rate taking an additional 1 ms. Extrapolating the scaling trends to a N=1000 node system, the spiking LCA compares favorably with state-of-the-art digital solutions, and analog solutions using a non-spiking approach. Copyright © 2013 Elsevier Ltd. All rights reserved.

Cortical circuitry implementing graphical models.

PubMed

Litvak, Shai; Ullman, Shimon

2009-11-01

In this letter, we develop and simulate a large-scale network of spiking neurons that approximates the inference computations performed by graphical models. Unlike previous related schemes, which used sum and product operations in either the log or linear domains, the current model uses an inference scheme based on the sum and maximization operations in the log domain. Simulations show that using these operations, a large-scale circuit, which combines populations of spiking neurons as basic building blocks, is capable of finding close approximations to the full mathematical computations performed by graphical models within a few hundred milliseconds. The circuit is general in the sense that it can be wired for any graph structure, it supports multistate variables, and it uses standard leaky integrate-and-fire neuronal units. Following previous work, which proposed relations between graphical models and the large-scale cortical anatomy, we focus on the cortical microcircuitry and propose how anatomical and physiological aspects of the local circuitry may map onto elements of the graphical model implementation. We discuss in particular the roles of three major types of inhibitory neurons (small fast-spiking basket cells, large layer 2/3 basket cells, and double-bouquet neurons), subpopulations of strongly interconnected neurons with their unique connectivity patterns in different cortical layers, and the possible role of minicolumns in the realization of the population-based maximum operation.

Immunoaffinity column cleanup with liquid chromatography using postcolumn bromination for the determination of aflatoxins in black and white sesame seed: single-laboratory validation.

PubMed

Liu, Guihua; Zhu, Zhou; Cheng, Jinquan; Senyuva, Hamide Z

2012-01-01

A single-laboratory validation was conducted to establish the effectiveness of an immunoaffinity column cleanup procedure followed by LC with fluorescence detection for the determination of aflatoxins B1, B2, G1, and G2 in sesame seeds. The sample is homogenized with 50% water (w/w) to form a slurry, then the test portion is extracted with methanol-water (60 + 40, v/v) using a high-speed blender. The sample extract is filtered, diluted with 15% Tween 20 in phosphate-buffered saline solution, and applied to an immunoaffinity column. Aflatoxins are removed with neat methanol, then directly determined by RP-LC with fluorescence detection using postcolumn bromination (Kobra cell). Test portions of blank white sesame seed slurry were spiked with a mixture of aflatoxins to give total levels of 4 and 10 microg/kg. Recoveries for individual and total aflatoxins ranged from 92.7 to 110.3% for spiked samples. Based on results for spiked sesame paste (triplicates at two levels), the RSD for repeatability (RSD(r)) averaged 1.1% for total aflatoxins and 1.4% for aflatoxin B1. The method was demonstrated to be applicable to naturally contaminated samples of black and white sesame seeds obtained from local markets in China.

Probing HeII Reionization at z>3.5 with Resolved HeII Lyman Alpha Forest Spectra

NASA Astrophysics Data System (ADS)

Worseck, Gabor

2017-08-01

The advent of GALEX and COS have revolutionized our view of HeII reionization, the final major phase transition of the intergalactic medium. COS spectra of the HeII Lyman alpha forest have confirmed with high confidence the high HeII transmission that signifies the completion of HeII reionization at z 2.7. However, the handful of z>3.5 quasars observed to date show a set of HeII transmission 'spikes' and larger regions with non-zero transmission that suggest HeII reionization was well underway by z=4. This is in striking conflict with predictions from state-of-the-art radiative transfer simulations of a HeII reionization driven by bright quasars. Explaining these measurements may require either faint quasars or more exotic sources of hard photons at z>4, with concomitant implications for HI reionization. However, many of the observed spikes are unresolved in G140L spectra and are significantly impacted by Poisson noise. Current data cannot reliably probe the ionization state of helium at z>3.5.We request 41 orbits to obtain science-grade G130M spectra of the two UV-brightest HeII-transmitting QSOs at z>3.5 to confirm and resolve their HeII transmission spikes as an unequivocal test of early HeII reionization. These spectra are complemented by recently obtained data from 8m telescopes: (1) Echelle spectra of the coeval HI Lya forest to map the underlying density field that modulates the HeII absorption, and (2) Our dedicated survey for foreground QSOs that may source the HeII transmission. Our recent HST programs revealed the only two viable targets to resolve the z>3.5 HeII Lyman alpha forest, and to conclusively solve this riddle.