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.

A Simple Method to Simultaneously Detect and Identify Spikes from Raw Extracellular Recordings.

PubMed

Petrantonakis, Panagiotis C; Poirazi, Panayiota

2015-01-01

The ability to track when and which neurons fire in the vicinity of an electrode, in an efficient and reliable manner can revolutionize the neuroscience field. The current bottleneck lies in spike sorting algorithms; existing methods for detecting and discriminating the activity of multiple neurons rely on inefficient, multi-step processing of extracellular recordings. In this work, we show that a single-step processing of raw (unfiltered) extracellular signals is sufficient for both the detection and identification of active neurons, thus greatly simplifying and optimizing the spike sorting approach. The efficiency and reliability of our method is demonstrated in both real and simulated data.

Frequency domain beamforming of magnetoencephalographic beta band activity in epilepsy patients with focal cortical dysplasia.

PubMed

Heers, Marcel; Hirschmann, Jan; Jacobs, Julia; Dümpelmann, Matthias; Butz, Markus; von Lehe, Marec; Elger, Christian E; Schnitzler, Alfons; Wellmer, Jörg

2014-09-01

Spike-based magnetoencephalography (MEG) source localization is an established method in the presurgical evaluation of epilepsy patients. Focal cortical dysplasias (FCDs) are associated with focal epileptic discharges of variable morphologies in the beta frequency band in addition to single epileptic spikes. Therefore, we investigated the potential diagnostic value of MEG-based localization of spike-independent beta band (12-30Hz) activity generated by epileptogenic lesions. Five patients with FCD IIB underwent MEG. In one patient, invasive EEG (iEEG) was recorded simultaneously with MEG. In two patients, iEEG succeeded MEG, and two patients had MEG only. MEG and iEEG were evaluated for epileptic spikes. Two minutes of iEEG data and MEG epochs with no spikes as well as MEG epochs with epileptic spikes were analyzed in the frequency domain. MEG oscillatory beta band activity was localized using Dynamic Imaging of Coherent Sources. Intralesional beta band activity was coherent between simultaneous MEG and iEEG recordings. Continuous 14Hz beta band power correlated with the rate of interictal epileptic discharges detected in iEEG. In cases where visual MEG evaluation revealed epileptic spikes, the sources of beta band activity localized within <2cm of the epileptogenic lesion as shown on magnetic resonance imaging. This result held even when visually marked epileptic spikes were deselected. When epileptic spikes were detectable in iEEG but not MEG, MEG beta band activity source localization failed. Source localization of beta band activity has the potential to contribute to the identification of epileptic foci in addition to source localization of visually marked epileptic spikes. Thus, this technique may assist in the localization of epileptic foci in patients with suspected FCD. Copyright © 2014 Elsevier B.V. All rights reserved.

ViSAPy: a Python tool for biophysics-based generation of virtual spiking activity for evaluation of spike-sorting algorithms.

PubMed

Hagen, Espen; Ness, Torbjørn V; Khosrowshahi, Amir; Sørensen, Christina; Fyhn, Marianne; Hafting, Torkel; Franke, Felix; Einevoll, Gaute T

2015-04-30

New, silicon-based multielectrodes comprising hundreds or more electrode contacts offer the possibility to record spike trains from thousands of neurons simultaneously. This potential cannot be realized unless accurate, reliable automated methods for spike sorting are developed, in turn requiring benchmarking data sets with known ground-truth spike times. We here present a general simulation tool for computing benchmarking data for evaluation of spike-sorting algorithms entitled ViSAPy (Virtual Spiking Activity in Python). The tool is based on a well-established biophysical forward-modeling scheme and is implemented as a Python package built on top of the neuronal simulator NEURON and the Python tool LFPy. ViSAPy allows for arbitrary combinations of multicompartmental neuron models and geometries of recording multielectrodes. Three example benchmarking data sets are generated, i.e., tetrode and polytrode data mimicking in vivo cortical recordings and microelectrode array (MEA) recordings of in vitro activity in salamander retinas. The synthesized example benchmarking data mimics salient features of typical experimental recordings, for example, spike waveforms depending on interspike interval. ViSAPy goes beyond existing methods as it includes biologically realistic model noise, synaptic activation by recurrent spiking networks, finite-sized electrode contacts, and allows for inhomogeneous electrical conductivities. ViSAPy is optimized to allow for generation of long time series of benchmarking data, spanning minutes of biological time, by parallel execution on multi-core computers. ViSAPy is an open-ended tool as it can be generalized to produce benchmarking data or arbitrary recording-electrode geometries and with various levels of complexity. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Real-time separation of multineuron recordings with a DSP32C signal processor.

PubMed

Gädicke, R; Albus, K

1995-04-01

We have developed a hardware and software package for real-time discrimination of multiple-unit activities recorded simultaneously from multiple microelectrodes using a VME-Bus system. Compared with other systems cited in literature or commercially available, our system has the following advantages. (1) Each electrode is served by its own preprocessor (DSP32C); (2) On-line spike discrimination is performed independently for each electrode. (3) The VME-bus allows processing of data received from 16 electrodes. The digitized (62.5 kHz) spike form is itself used as the model spike; the algorithm allows for comparing and sorting complete wave forms in real time into 8 different models per electrode.

Past, present and future of spike sorting techniques

PubMed Central

Rey, Hernan Gonzalo; Pedreira, Carlos; Quian Quiroga, Rodrigo

2015-01-01

Spike sorting is a crucial step to extract information from extracellular recordings. With new recording opportunities provided by the development of new electrodes that allow monitoring hundreds of neurons simultaneously, the scenario for the new generation of algorithms is both exciting and challenging. However, this will require a new approach to the problem and the development of a common reference framework to quickly assess the performance of new algorithms. In this work, we review the basic concepts of spike sorting, including the requirements for different applications, together with the problems faced by presently available algorithms. We conclude by proposing a roadmap stressing the crucial points to be addressed to support the neuroscientific research of the near future. PMID:25931392

Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains.

PubMed

Onken, Arno; Liu, Jian K; Karunasekara, P P Chamanthi R; Delis, Ioannis; Gollisch, Tim; Panzeri, Stefano

2016-11-01

Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding.

Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains

PubMed Central

Onken, Arno; Liu, Jian K.; Karunasekara, P. P. Chamanthi R.; Delis, Ioannis; Gollisch, Tim; Panzeri, Stefano

2016-01-01

Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding. PMID:27814363

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.

Computational solution of spike overlapping using data-based subtraction algorithms to resolve synchronous sympathetic nerve discharge

PubMed Central

Su, Chun-Kuei; Chiang, Chia-Hsun; Lee, Chia-Ming; Fan, Yu-Pei; Ho, Chiu-Ming; Shyu, Liang-Yu

2013-01-01

Sympathetic nerves conveying central commands to regulate visceral functions often display activities in synchronous bursts. To understand how individual fibers fire synchronously, we establish “oligofiber recording techniques” to record “several” nerve fiber activities simultaneously, using in vitro splanchnic sympathetic nerve–thoracic spinal cord preparations of neonatal rats as experimental models. While distinct spike potentials were easily recorded from collagenase-dissociated sympathetic fibers, a problem arising from synchronous nerve discharges is a higher incidence of complex waveforms resulted from spike overlapping. Because commercial softwares do not provide an explicit solution for spike overlapping, a series of custom-made LabVIEW programs incorporated with MATLAB scripts was therefore written for spike sorting. Spikes were represented as data points after waveform feature extraction and automatically grouped by k-means clustering followed by principal component analysis (PCA) to verify their waveform homogeneity. For dissimilar waveforms with exceeding Hotelling's T2 distances from the cluster centroids, a unique data-based subtraction algorithm (SA) was used to determine if they were the complex waveforms resulted from superimposing a spike pattern close to the cluster centroid with the other signals that could be observed in original recordings. In comparisons with commercial software, higher accuracy was achieved by analyses using our algorithms for the synthetic data that contained synchronous spiking and complex waveforms. Moreover, both T2-selected and SA-retrieved spikes were combined as unit activities. Quantitative analyses were performed to evaluate if unit activities truly originated from single fibers. We conclude that applications of our programs can help to resolve synchronous sympathetic nerve discharges (SND). PMID:24198782

Exact computation of the maximum-entropy potential of spiking neural-network models.

PubMed

Cofré, R; Cessac, B

2014-05-01

Understanding how stimuli and synaptic connectivity influence the statistics of spike patterns in neural networks is a central question in computational neuroscience. The maximum-entropy approach has been successfully used to characterize the statistical response of simultaneously recorded spiking neurons responding to stimuli. However, in spite of good performance in terms of prediction, the fitting parameters do not explain the underlying mechanistic causes of the observed correlations. On the other hand, mathematical models of spiking neurons (neuromimetic models) provide a probabilistic mapping between the stimulus, network architecture, and spike patterns in terms of conditional probabilities. In this paper we build an exact analytical mapping between neuromimetic and maximum-entropy models.

Stimulus encoding and feature extraction by multiple sensory neurons.

PubMed

Krahe, Rüdiger; Kreiman, Gabriel; Gabbiani, Fabrizio; Koch, Christof; Metzner, Walter

2002-03-15

Neighboring cells in topographical sensory maps may transmit similar information to the next higher level of processing. How information transmission by groups of nearby neurons compares with the performance of single cells is a very important question for understanding the functioning of the nervous system. To tackle this problem, we quantified stimulus-encoding and feature extraction performance by pairs of simultaneously recorded electrosensory pyramidal cells in the hindbrain of weakly electric fish. These cells constitute the output neurons of the first central nervous stage of electrosensory processing. Using random amplitude modulations (RAMs) of a mimic of the fish's own electric field within behaviorally relevant frequency bands, we found that pyramidal cells with overlapping receptive fields exhibit strong stimulus-induced correlations. To quantify the encoding of the RAM time course, we estimated the stimuli from simultaneously recorded spike trains and found significant improvements over single spike trains. The quality of stimulus reconstruction, however, was still inferior to the one measured for single primary sensory afferents. In an analysis of feature extraction, we found that spikes of pyramidal cell pairs coinciding within a time window of a few milliseconds performed significantly better at detecting upstrokes and downstrokes of the stimulus compared with isolated spikes and even spike bursts of single cells. Coincident spikes can thus be considered "distributed bursts." Our results suggest that stimulus encoding by primary sensory afferents is transformed into feature extraction at the next processing stage. There, stimulus-induced coincident activity can improve the extraction of behaviorally relevant features from the stimulus.

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.

[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.

[Functional organization and structure of the serotonergic neuronal network of terrestrial snail].

PubMed

Nikitin, E S; Balaban, P M

2011-01-01

The extension of knowledge how the brain works requires permanent improvement of methods of recording of neuronal activity and increase in the number of neurons recorded simultaneously to better understand the collective work of neuronal networks and assemblies. Conventional methods allow simultaneous intracellular recording up to 2-5 neurons and their membrane potentials, currents or monosynaptic connections or observation of spiking of neuronal groups with subsequent discrimination of individual spikes with loss of details of the dynamics of membrane potential. We recorded activity of a compact group of serotonergic neurons (up to 56 simultaneously) in the ganglion of a terrestrial mollusk using the method of optical recording of membrane potential that allowed to record individual action potentials in details with action potential parameters and to reveal morphology of the neurons rcorded. We demonstrated clear clustering in the group in relation with the dynamics of action potentials and phasic or tonic components in the neuronal responses to external electrophysiological and tactile stimuli. Also, we showed that identified neuron Pd2 could induce activation of a significant number of neurons in the group whereas neuron Pd4 did not induce any activation. However, its activation is delayed with regard to activation of the reacting group of neurons. Our data strongly support the concept of possible delegation of the integrative function by the network to a single neuron.

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

Past, present and future of spike sorting techniques.

PubMed

Rey, Hernan Gonzalo; Pedreira, Carlos; Quian Quiroga, Rodrigo

2015-10-01

Spike sorting is a crucial step to extract information from extracellular recordings. With new recording opportunities provided by the development of new electrodes that allow monitoring hundreds of neurons simultaneously, the scenario for the new generation of algorithms is both exciting and challenging. However, this will require a new approach to the problem and the development of a common reference framework to quickly assess the performance of new algorithms. In this work, we review the basic concepts of spike sorting, including the requirements for different applications, together with the problems faced by presently available algorithms. We conclude by proposing a roadmap stressing the crucial points to be addressed to support the neuroscientific research of the near future. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Unsupervised neural spike sorting for high-density microelectrode arrays with convolutive independent component analysis.

PubMed

Leibig, Christian; Wachtler, Thomas; Zeck, Günther

2016-09-15

Unsupervised identification of action potentials in multi-channel extracellular recordings, in particular from high-density microelectrode arrays with thousands of sensors, is an unresolved problem. While independent component analysis (ICA) achieves rapid unsupervised sorting, it ignores the convolutive structure of extracellular data, thus limiting the unmixing to a subset of neurons. Here we present a spike sorting algorithm based on convolutive ICA (cICA) to retrieve a larger number of accurately sorted neurons than with instantaneous ICA while accounting for signal overlaps. Spike sorting was applied to datasets with varying signal-to-noise ratios (SNR: 3-12) and 27% spike overlaps, sampled at either 11.5 or 23kHz on 4365 electrodes. We demonstrate how the instantaneity assumption in ICA-based algorithms has to be relaxed in order to improve the spike sorting performance for high-density microelectrode array recordings. Reformulating the convolutive mixture as an instantaneous mixture by modeling several delayed samples jointly is necessary to increase signal-to-noise ratio. Our results emphasize that different cICA algorithms are not equivalent. Spike sorting performance was assessed with ground-truth data generated from experimentally derived templates. The presented spike sorter was able to extract ≈90% of the true spike trains with an error rate below 2%. It was superior to two alternative (c)ICA methods (≈80% accurately sorted neurons) and comparable to a supervised sorting. Our new algorithm represents a fast solution to overcome the current bottleneck in spike sorting of large datasets generated by simultaneous recording with thousands of electrodes. Copyright © 2016 Elsevier B.V. All rights reserved.

Flexible multielectrodes can resolve multiple muscles in an insect appendage.

PubMed

Spence, Andrew J; Neeves, Keith B; Murphy, Devon; Sponberg, Simon; Land, Bruce R; Hoy, Ronald R; Isaacson, Michael S

2007-01-15

Research into the neuromechanical basis of behavior, either in biomechanics, neuroethology, or neuroscience, is frequently limited by methods of data collection. Two of the most pressing needs are for methods with which to (1) record from multiple neurons or muscles simultaneously and (2) perform this recording in intact, behaving animals. In this paper we present the fabrication and testing of flexible multielectrode arrays (fMEAs) that move us significantly towards these goals. The fMEAs were used to record the activity of several distinct units in the coxa of the cockroach Blaberus discoidalis. The devices fabricated here address the first goal in two ways: (1) their flexibility allows them to be inserted into an animal and guided through internal tissues in order to access distinct groups of neurons and muscles and (2) their recording site geometry has been tuned to suit the anatomy under study, yielding multichannel spike waveforms that are easily separable under conditions of spike overlap. The flexible nature of the devices simultaneously addresses the second goal, in that it is less likely to interfere with the natural movement of the animal.

Effects of high-frequency stimulation of the internal pallidal segment on neuronal activity in the thalamus in parkinsonian monkeys

PubMed Central

Kammermeier, Stefan; Pittard, Damien; Hamada, Ikuma

2016-01-01

Deep brain stimulation of the internal globus pallidus (GPi) is a major treatment for advanced Parkinson's disease. The effects of this intervention on electrical activity patterns in targets of GPi output, specifically in the thalamus, are poorly understood. The experiments described here examined these effects using electrophysiological recordings in two Rhesus monkeys rendered moderately parkinsonian through treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), after sampling control data in the same animals. Analysis of spontaneous spiking activity of neurons in the basal ganglia-receiving areas of the ventral thalamus showed that MPTP-induced parkinsonism is associated with a reduction of firing rates of segments of the data that contained neither bursts nor decelerations, and with increased burst firing. Spectral analyses revealed an increase of power in the 3- to 13-Hz band and a reduction in the γ-range in the spiking activity of these neurons. Electrical stimulation of the ventrolateral motor territory of GPi with macroelectrodes, mimicking deep brain stimulation in parkinsonian patients (bipolar electrodes, 0.5 mm intercontact distance, biphasic stimuli, 120 Hz, 100 μs/phase, 200 μA), had antiparkinsonian effects. The stimulation markedly reduced oscillations in thalamic firing in the 13- to 30-Hz range and uncoupled the spiking activity of recorded neurons from simultaneously recorded local field potential (LFP) activity. These results confirm that oscillatory and nonoscillatory characteristics of spontaneous activity in the basal ganglia receiving ventral thalamus are altered in MPTP-induced parkinsonism. Electrical stimulation of GPi did not entrain thalamic activity but changed oscillatory activity in the ventral thalamus and altered the relationship between spikes and simultaneously recorded LFPs. PMID:27683881

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 Simple Deep Learning Method for Neuronal Spike Sorting

NASA Astrophysics Data System (ADS)

Yang, Kai; Wu, Haifeng; Zeng, Yu

2017-10-01

Spike sorting is one of key technique to understand brain activity. With the development of modern electrophysiology technology, some recent multi-electrode technologies have been able to record the activity of thousands of neuronal spikes simultaneously. The spike sorting in this case will increase the computational complexity of conventional sorting algorithms. In this paper, we will focus spike sorting on how to reduce the complexity, and introduce a deep learning algorithm, principal component analysis network (PCANet) to spike sorting. The introduced method starts from a conventional model and establish a Toeplitz matrix. Through the column vectors in the matrix, we trains a PCANet, where some eigenvalue vectors of spikes could be extracted. Finally, support vector machine (SVM) is used to sort spikes. In experiments, we choose two groups of simulated data from public databases availably and compare this introduced method with conventional methods. The results indicate that the introduced method indeed has lower complexity with the same sorting errors as the conventional methods.

Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays

PubMed Central

Grosberg, Lauren E.; Madugula, Sasidhar; Litke, Alan; Cunningham, John; Chichilnisky, E. J.; Paninski, Liam

2017-01-01

Simultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these measurements is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is greatly complicated by electrical stimulation artifacts across the array, which can exhibit complex and nonlinear waveforms, and overlap temporarily with evoked spikes. Here we develop a scalable algorithm based on a structured Gaussian Process model to estimate the artifact and identify evoked spikes. The effectiveness of our methods is demonstrated in both real and simulated 512-electrode recordings in the peripheral primate retina with single-electrode and several types of multi-electrode stimulation. We establish small error rates in the identification of evoked spikes, with a computational complexity that is compatible with real-time data analysis. This technology may be helpful in the design of future high-resolution sensory prostheses based on tailored stimulation (e.g., retinal prostheses), and for closed-loop neural stimulation at a much larger scale than currently possible. PMID:29131818

Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays.

PubMed

Mena, Gonzalo E; Grosberg, Lauren E; Madugula, Sasidhar; Hottowy, Paweł; Litke, Alan; Cunningham, John; Chichilnisky, E J; Paninski, Liam

2017-11-01

Simultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these measurements is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is greatly complicated by electrical stimulation artifacts across the array, which can exhibit complex and nonlinear waveforms, and overlap temporarily with evoked spikes. Here we develop a scalable algorithm based on a structured Gaussian Process model to estimate the artifact and identify evoked spikes. The effectiveness of our methods is demonstrated in both real and simulated 512-electrode recordings in the peripheral primate retina with single-electrode and several types of multi-electrode stimulation. We establish small error rates in the identification of evoked spikes, with a computational complexity that is compatible with real-time data analysis. This technology may be helpful in the design of future high-resolution sensory prostheses based on tailored stimulation (e.g., retinal prostheses), and for closed-loop neural stimulation at a much larger scale than currently possible.

Detection of Bursts and Pauses in Spike Trains

PubMed Central

Ko, D.; Wilson, C. J.; Lobb, C. J.; Paladini, C. A.

2012-01-01

Midbrain dopaminergic neurons in vivo exhibit a wide range of firing patterns. They normally fire constantly at a low rate, and speed up, firing a phasic burst when reward exceeds prediction, or pause when an expected reward does not occur. Therefore, the detection of bursts and pauses from spike train data is a critical problem when studying the role of phasic dopamine (DA) in reward related learning, and other DA dependent behaviors. However, few statistical methods have been developed that can identify bursts and pauses simultaneously. We propose a new statistical method, the Robust Gaussian Surprise (RGS) method, which performs an exhaustive search of bursts and pauses in spike trains simultaneously. We found that the RGS method is adaptable to various patterns of spike trains recorded in vivo, and is not influenced by baseline firing rate, making it applicable to all in vivo spike trains where baseline firing rates vary over time. We compare the performance of the RGS method to other methods of detecting bursts, such as the Poisson Surprise (PS), Rank Surprise (RS), and Template methods. Analysis of data using the RGS method reveals potential mechanisms underlying how bursts and pauses are controlled in DA neurons. PMID:22939922

Cerebellar Purkinje Cells Generate Highly Correlated Spontaneous Slow-Rate Fluctuations.

PubMed

Cao, Ying; Liu, Yu; Jaeger, Dieter; Heck, Detlef H

2017-01-01

Cerebellar Purkinje cells (PC) fire action potentials at high, sustained rates. Changes in spike rate that last a few tens of milliseconds encode sensory and behavioral events. Here we investigated spontaneous fluctuations of PC simple spike rate at a slow time scale of the order of 1 s. Simultaneous recordings from pairs of PCs that were aligned either along the sagittal or transversal axis of the cerebellar cortex revealed that simple spike rate fluctuations at the 1 s time scale were highly correlated. Each pair of PCs had either a predominantly positive or negative slow-rate correlation, with negative correlations observed only in PC pairs aligned along the transversal axis. Slow-rate correlations were independent of faster rate changes that were correlated with fluid licking behavior. Simultaneous recordings from PCs and cerebellar nuclear (CN) neurons showed that slow-rate fluctuations in PC and CN activity were also highly correlated, but their correlations continually alternated between periods of positive and negative correlation. The functional significance of this new aspect of cerebellar spike activity remains to be determined. Correlated slow-rate fluctuations seem too slow to be involved in the real-time control of ongoing behavior. However, slow-rate fluctuations of PCs converging on the same CN neuron are likely to modulate the excitability of the CN neuron, thus introduce a possible slow modulation of cerebellar output activity.

Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex

PubMed Central

Logiaco, Laureline; Quilodran, René; Procyk, Emmanuel; Arleo, Angelo

2015-01-01

The frontal cortex controls behavioral adaptation in environments governed by complex rules. Many studies have established the relevance of firing rate modulation after informative events signaling whether and how to update the behavioral policy. However, whether the spatiotemporal features of these neuronal activities contribute to encoding imminent behavioral updates remains unclear. We investigated this issue in the dorsal anterior cingulate cortex (dACC) of monkeys while they adapted their behavior based on their memory of feedback from past choices. We analyzed spike trains of both single units and pairs of simultaneously recorded neurons using an algorithm that emulates different biologically plausible decoding circuits. This method permits the assessment of the performance of both spike-count and spike-timing sensitive decoders. In response to the feedback, single neurons emitted stereotypical spike trains whose temporal structure identified informative events with higher accuracy than mere spike count. The optimal decoding time scale was in the range of 70–200 ms, which is significantly shorter than the memory time scale required by the behavioral task. Importantly, the temporal spiking patterns of single units were predictive of the monkeys’ behavioral response time. Furthermore, some features of these spiking patterns often varied between jointly recorded neurons. All together, our results suggest that dACC drives behavioral adaptation through complex spatiotemporal spike coding. They also indicate that downstream networks, which decode dACC feedback signals, are unlikely to act as mere neural integrators. PMID:26266537

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.

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

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

Synaptic input correlations leading to membrane potential decorrelation of spontaneous activity in cortex.

PubMed

Graupner, Michael; Reyes, Alex D

2013-09-18

Correlations in the spiking activity of neurons have been found in many regions of the cortex under multiple experimental conditions and are postulated to have important consequences for neural population coding. While there is a large body of extracellular data reporting correlations of various strengths, the subthreshold events underlying the origin and magnitude of signal-independent correlations (called noise or spike count correlations) are unknown. Here we investigate, using intracellular recordings, how synaptic input correlations from shared presynaptic neurons translate into membrane potential and spike-output correlations. Using a pharmacologically activated thalamocortical slice preparation, we perform simultaneous recordings from pairs of layer IV neurons in the auditory cortex of mice and measure synaptic potentials/currents, membrane potentials, and spiking outputs. We calculate cross-correlations between excitatory and inhibitory inputs to investigate correlations emerging from the network. We furthermore evaluate membrane potential correlations near resting potential to study how excitation and inhibition combine and affect spike-output correlations. We demonstrate directly that excitation is correlated with inhibition thereby partially canceling each other and resulting in weak membrane potential and spiking correlations between neurons. Our data suggest that cortical networks are set up to partially cancel correlations emerging from the connections between neurons. This active decorrelation is achieved because excitation and inhibition closely track each other. Our results suggest that the numerous shared presynaptic inputs do not automatically lead to increased spiking correlations.

Surface-modified CMOS IC electrochemical sensor array targeting single chromaffin cells for highly parallel amperometry measurements.

PubMed

Huang, Meng; Delacruz, Joannalyn B; Ruelas, John C; Rathore, Shailendra S; Lindau, Manfred

2018-01-01

Amperometry is a powerful method to record quantal release events from chromaffin cells and is widely used to assess how specific drugs modify quantal size, kinetics of release, and early fusion pore properties. Surface-modified CMOS-based electrochemical sensor arrays allow simultaneous recordings from multiple cells. A reliable, low-cost technique is presented here for efficient targeting of single cells specifically to the electrode sites. An SU-8 microwell structure is patterned on the chip surface to provide insulation for the circuitry as well as cell trapping at the electrode sites. A shifted electrode design is also incorporated to increase the flexibility of the dimension and shape of the microwells. The sensitivity of the electrodes is validated by a dopamine injection experiment. Microwells with dimensions slightly larger than the cells to be trapped ensure excellent single-cell targeting efficiency, increasing the reliability and efficiency for on-chip single-cell amperometry measurements. The surface-modified device was validated with parallel recordings of live chromaffin cells trapped in the microwells. Rapid amperometric spikes with no diffusional broadening were observed, indicating that the trapped and recorded cells were in very close contact with the electrodes. The live cell recording confirms in a single experiment that spike parameters vary significantly from cell to cell but the large number of cells recorded simultaneously provides the statistical significance.

[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.

Information theoretic analysis of proprioceptive encoding during finger flexion in the monkey sensorimotor system.

PubMed

Witham, Claire L; Baker, Stuart N

2015-01-01

There is considerable debate over whether the brain codes information using neural firing rate or the fine-grained structure of spike timing. We investigated this issue in spike discharge recorded from single units in the sensorimotor cortex, deep cerebellar nuclei, and dorsal root ganglia in macaque monkeys trained to perform a finger flexion task. The task required flexion to four different displacements against two opposing torques; the eight possible conditions were randomly interleaved. We used information theory to assess coding of task condition in spike rate, discharge irregularity, and spectral power in the 15- to 25-Hz band during the period of steady holding. All three measures coded task information in all areas tested. Information coding was most often independent between irregularity and 15-25 Hz power (60% of units), moderately redundant between spike rate and irregularity (56% of units redundant), and highly redundant between spike rate and power (93%). Most simultaneously recorded unit pairs coded using the same measure independently (86%). Knowledge of two measures often provided extra information about task, compared with knowledge of only one alone. We conclude that sensorimotor systems use both rate and temporal codes to represent information about a finger movement task. As well as offering insights into neural coding, this work suggests that incorporating spike irregularity into algorithms used for brain-machine interfaces could improve decoding accuracy. Copyright © 2015 the American Physiological Society.

Copula Regression Analysis of Simultaneously Recorded Frontal Eye Field and Inferotemporal Spiking Activity during Object-Based Working Memory

PubMed Central

Hu, Meng; Clark, Kelsey L.; Gong, Xiajing; Noudoost, Behrad; Li, Mingyao; Moore, Tirin

2015-01-01

Inferotemporal (IT) neurons are known to exhibit persistent, stimulus-selective activity during the delay period of object-based working memory tasks. Frontal eye field (FEF) neurons show robust, spatially selective delay period activity during memory-guided saccade tasks. We present a copula regression paradigm to examine neural interaction of these two types of signals between areas IT and FEF of the monkey during a working memory task. This paradigm is based on copula models that can account for both marginal distribution over spiking activity of individual neurons within each area and joint distribution over ensemble activity of neurons between areas. Considering the popular GLMs as marginal models, we developed a general and flexible likelihood framework that uses the copula to integrate separate GLMs into a joint regression analysis. Such joint analysis essentially leads to a multivariate analog of the marginal GLM theory and hence efficient model estimation. In addition, we show that Granger causality between spike trains can be readily assessed via the likelihood ratio statistic. The performance of this method is validated by extensive simulations, and compared favorably to the widely used GLMs. When applied to spiking activity of simultaneously recorded FEF and IT neurons during working memory task, we observed significant Granger causality influence from FEF to IT, but not in the opposite direction, suggesting the role of the FEF in the selection and retention of visual information during working memory. The copula model has the potential to provide unique neurophysiological insights about network properties of the brain. PMID:26063909

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 theoretical framework for analyzing coupled neuronal networks: Application to the olfactory system.

PubMed

Barreiro, Andrea K; Gautam, Shree Hari; Shew, Woodrow L; Ly, Cheng

2017-10-01

Determining how synaptic coupling within and between regions is modulated during sensory processing is an important topic in neuroscience. Electrophysiological recordings provide detailed information about neural spiking but have traditionally been confined to a particular region or layer of cortex. Here we develop new theoretical methods to study interactions between and within two brain regions, based on experimental measurements of spiking activity simultaneously recorded from the two regions. By systematically comparing experimentally-obtained spiking statistics to (efficiently computed) model spike rate statistics, we identify regions in model parameter space that are consistent with the experimental data. We apply our new technique to dual micro-electrode array in vivo recordings from two distinct regions: olfactory bulb (OB) and anterior piriform cortex (PC). Our analysis predicts that: i) inhibition within the afferent region (OB) has to be weaker than the inhibition within PC, ii) excitation from PC to OB is generally stronger than excitation from OB to PC, iii) excitation from PC to OB and inhibition within PC have to both be relatively strong compared to presynaptic inputs from OB. These predictions are validated in a spiking neural network model of the OB-PC pathway that satisfies the many constraints from our experimental data. We find when the derived relationships are violated, the spiking statistics no longer satisfy the constraints from the data. In principle this modeling framework can be adapted to other systems and be used to investigate relationships between other neural attributes besides network connection strengths. Thus, this work can serve as a guide to further investigations into the relationships of various neural attributes within and across different regions during sensory processing.

[A cross-correlational analysis of the background neuronal pulse trains in surviving slices of the guinea pig neocortex].

PubMed

Bortnik, A T; Iakupova, L P

1991-01-01

Cross-correlation analysis of interdependence of the background spike activity was carried out for pairs of adjacent neurons simultaneously recorded in the incubated slices of the neocortex of guinea-pig. Statistical correlation of spike discharges was detected in 16 out of 26 recorded pairs of the neurons. Significant correlation was observed mainly in the range of +/- 100 ms from the null point. Cross-correlation had symmetric or asymmetric maxima up to 150 ms long and negative shifts up to 200 ms long. More complex positive-negative types of cross-correlations were also obtained. The data were compared to those known from other authors for the intact brain. The contribution of intrinsic intracortical interactions and extrinsic afferent influences in these correlations of activity is discussed.

Joint time-frequency analysis of EEG signals based on a phase-space interpretation of the recording process

NASA Astrophysics Data System (ADS)

Testorf, M. E.; Jobst, B. C.; Kleen, J. K.; Titiz, A.; Guillory, S.; Scott, R.; Bujarski, K. A.; Roberts, D. W.; Holmes, G. L.; Lenck-Santini, P.-P.

2012-10-01

Time-frequency transforms are used to identify events in clinical EEG data. Data are recorded as part of a study for correlating the performance of human subjects during a memory task with pathological events in the EEG, called spikes. The spectrogram and the scalogram are reviewed as tools for evaluating spike activity. A statistical evaluation of the continuous wavelet transform across trials is used to quantify phase-locking events. For simultaneously improving the time and frequency resolution, and for representing the EEG of several channels or trials in a single time-frequency plane, a multichannel matching pursuit algorithm is used. Fundamental properties of the algorithm are discussed as well as preliminary results, which were obtained with clinical EEG data.

Multi-neuron intracellular recording in vivo via interacting autopatching robots

PubMed Central

Holst, Gregory L; Singer, Annabelle C; Han, Xue; Brown, Emery N

2018-01-01

The activities of groups of neurons in a circuit or brain region are important for neuronal computations that contribute to behaviors and disease states. Traditional extracellular recordings have been powerful and scalable, but much less is known about the intracellular processes that lead to spiking activity. We present a robotic system, the multipatcher, capable of automatically obtaining blind whole-cell patch clamp recordings from multiple neurons simultaneously. The multipatcher significantly extends automated patch clamping, or 'autopatching’, to guide four interacting electrodes in a coordinated fashion, avoiding mechanical coupling in the brain. We demonstrate its performance in the cortex of anesthetized and awake mice. A multipatcher with four electrodes took an average of 10 min to obtain dual or triple recordings in 29% of trials in anesthetized mice, and in 18% of the trials in awake mice, thus illustrating practical yield and throughput to obtain multiple, simultaneous whole-cell recordings in vivo. PMID:29297466

Validation of neural spike sorting algorithms without ground-truth information.

PubMed

Barnett, Alex H; Magland, Jeremy F; Greengard, Leslie F

2016-05-01

The throughput of electrophysiological recording is growing rapidly, allowing thousands of simultaneous channels, and there is a growing variety of spike sorting algorithms designed to extract neural firing events from such data. This creates an urgent need for standardized, automatic evaluation of the quality of neural units output by such algorithms. We introduce a suite of validation metrics that assess the credibility of a given automatic spike sorting algorithm applied to a given dataset. By rerunning the spike sorter two or more times, the metrics measure stability under various perturbations consistent with variations in the data itself, making no assumptions about the internal workings of the algorithm, and minimal assumptions about the noise. We illustrate the new metrics on standard sorting algorithms applied to both in vivo and ex vivo recordings, including a time series with overlapping spikes. We compare the metrics to existing quality measures, and to ground-truth accuracy in simulated time series. We provide a software implementation. Metrics have until now relied on ground-truth, simulated data, internal algorithm variables (e.g. cluster separation), or refractory violations. By contrast, by standardizing the interface, our metrics assess the reliability of any automatic algorithm without reference to internal variables (e.g. feature space) or physiological criteria. Stability is a prerequisite for reproducibility of results. Such metrics could reduce the significant human labor currently spent on validation, and should form an essential part of large-scale automated spike sorting and systematic benchmarking of algorithms. Copyright © 2016 Elsevier B.V. All rights reserved.

Discriminative Learning of Receptive Fields from Responses to Non-Gaussian Stimulus Ensembles

PubMed Central

Meyer, Arne F.; Diepenbrock, Jan-Philipp; Happel, Max F. K.; Ohl, Frank W.; Anemüller, Jörn

2014-01-01

Analysis of sensory neurons' processing characteristics requires simultaneous measurement of presented stimuli and concurrent spike responses. The functional transformation from high-dimensional stimulus space to the binary space of spike and non-spike responses is commonly described with linear-nonlinear models, whose linear filter component describes the neuron's receptive field. From a machine learning perspective, this corresponds to the binary classification problem of discriminating spike-eliciting from non-spike-eliciting stimulus examples. The classification-based receptive field (CbRF) estimation method proposed here adapts a linear large-margin classifier to optimally predict experimental stimulus-response data and subsequently interprets learned classifier weights as the neuron's receptive field filter. Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa) is minimized. Efficacy of the CbRF method is validated with simulations and for auditory spectro-temporal receptive field (STRF) estimation from experimental recordings in the auditory midbrain of Mongolian gerbils. Acoustic stimulation is performed with frequency-modulated tone complexes that mimic properties of natural stimuli, specifically non-Gaussian amplitude distribution and higher-order correlations. Results demonstrate that the proposed approach successfully identifies correct underlying STRFs, even in cases where second-order methods based on the spike-triggered average (STA) do not. Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. Thus, CbRF estimation may prove useful for investigation of neuronal processes in response to natural stimuli and in settings where rapid adaptation is induced by experimental design. PMID:24699631

Discriminative learning of receptive fields from responses to non-Gaussian stimulus ensembles.

PubMed

Meyer, Arne F; Diepenbrock, Jan-Philipp; Happel, Max F K; Ohl, Frank W; Anemüller, Jörn

2014-01-01

Analysis of sensory neurons' processing characteristics requires simultaneous measurement of presented stimuli and concurrent spike responses. The functional transformation from high-dimensional stimulus space to the binary space of spike and non-spike responses is commonly described with linear-nonlinear models, whose linear filter component describes the neuron's receptive field. From a machine learning perspective, this corresponds to the binary classification problem of discriminating spike-eliciting from non-spike-eliciting stimulus examples. The classification-based receptive field (CbRF) estimation method proposed here adapts a linear large-margin classifier to optimally predict experimental stimulus-response data and subsequently interprets learned classifier weights as the neuron's receptive field filter. Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa) is minimized. Efficacy of the CbRF method is validated with simulations and for auditory spectro-temporal receptive field (STRF) estimation from experimental recordings in the auditory midbrain of Mongolian gerbils. Acoustic stimulation is performed with frequency-modulated tone complexes that mimic properties of natural stimuli, specifically non-Gaussian amplitude distribution and higher-order correlations. Results demonstrate that the proposed approach successfully identifies correct underlying STRFs, even in cases where second-order methods based on the spike-triggered average (STA) do not. Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. Thus, CbRF estimation may prove useful for investigation of neuronal processes in response to natural stimuli and in settings where rapid adaptation is induced by experimental design.

Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades.

PubMed

Orchard, Garrick; Jayawant, Ajinkya; Cohen, Gregory K; Thakor, Nitish

2015-01-01

Creating datasets for Neuromorphic Vision is a challenging task. A lack of available recordings from Neuromorphic Vision sensors means that data must typically be recorded specifically for dataset creation rather than collecting and labeling existing data. The task is further complicated by a desire to simultaneously provide traditional frame-based recordings to allow for direct comparison with traditional Computer Vision algorithms. Here we propose a method for converting existing Computer Vision static image datasets into Neuromorphic Vision datasets using an actuated pan-tilt camera platform. Moving the sensor rather than the scene or image is a more biologically realistic approach to sensing and eliminates timing artifacts introduced by monitor updates when simulating motion on a computer monitor. We present conversion of two popular image datasets (MNIST and Caltech101) which have played important roles in the development of Computer Vision, and we provide performance metrics on these datasets using spike-based recognition algorithms. This work contributes datasets for future use in the field, as well as results from spike-based algorithms against which future works can compare. Furthermore, by converting datasets already popular in Computer Vision, we enable more direct comparison with frame-based approaches.

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

Encoding of Both Reaching and Grasping Kinematics in Dorsal and Ventral Premotor Cortices

PubMed Central

Best, Matthew D.

2017-01-01

Classically, it has been hypothesized that reach-to-grasp movements arise from two discrete parietofrontal cortical networks. As part of these networks, the dorsal premotor cortex (PMd) has been implicated in the control of reaching movements of the arm, whereas the ventral premotor cortex (PMv) has been associated with the control of grasping movements of the hand. Recent studies have shown that such a strict delineation of function along anatomical boundaries is unlikely, partly because reaching to different locations can alter distal hand kinematics and grasping different objects can affect kinematics of the proximal arm. Here, we used chronically implanted multielectrode arrays to record unit-spiking activity in both PMd and PMv simultaneously while rhesus macaques engaged in a reach-to-grasp task. Generalized linear models were used to predict the spiking activity of cells in both areas as a function of different kinematic parameters, as well as spike history. To account for the influence of reaching on hand kinematics and vice versa, we applied demixed principal components analysis to define kinematics synergies that maximized variance across either different object locations or grip types. We found that single cells in both PMd and PMv encode the kinematics of both reaching and grasping synergies, suggesting that this classical division of reach and grasp in PMd and PMv, respectively, does not accurately reflect the encoding preferences of cells in those areas. SIGNIFICANCE STATEMENT For reach-to-grasp movements, the dorsal premotor cortex (PMd) has been implicated in the control of reaching movements of the arm, whereas the ventral premotor cortex (PMv) has been associated with the control of grasping movements of the hand. We recorded unit-spiking activity in PMd and PMv simultaneously while macaques performed a reach-to-grasp task. We modeled the spiking activity of neurons as a function of kinematic parameters and spike history. We applied demixed principal components analysis to define kinematics synergies. We found that single units in both PMd and PMv encode the kinematics of both reaching and grasping synergies, suggesting that the division of reach and grasp in PMd and PMv, respectively, cannot be made based on their encoding properties. PMID:28077725

A Wireless Headstage for Combined Optogenetics and Multichannel Electrophysiological Recording.

PubMed

Gagnon-Turcotte, Gabriel; LeChasseur, Yoan; Bories, Cyril; Messaddeq, Younes; De Koninck, Yves; Gosselin, Benoit

2017-02-01

This paper presents a wireless headstage with real-time spike detection and data compression for combined optogenetics and multichannel electrophysiological recording. The proposed headstage, which is intended to perform both optical stimulation and electrophysiological recordings simultaneously in freely moving transgenic rodents, is entirely built with commercial off-the-shelf components, and includes 32 recording channels and 32 optical stimulation channels. It can detect, compress and transmit full action potential waveforms over 32 channels in parallel and in real time using an embedded digital signal processor based on a low-power field programmable gate array and a Microblaze microprocessor softcore. Such a processor implements a complete digital spike detector featuring a novel adaptive threshold based on a Sigma-delta control loop, and a wavelet data compression module using a new dynamic coefficient re-quantization technique achieving large compression ratios with higher signal quality. Simultaneous optical stimulation and recording have been performed in-vivo using an optrode featuring 8 microelectrodes and 1 implantable fiber coupled to a 465-nm LED, in the somatosensory cortex and the Hippocampus of a transgenic mouse expressing ChannelRhodospin (Thy1::ChR2-YFP line 4) under anesthetized conditions. Experimental results show that the proposed headstage can trigger neuron activity while collecting, detecting and compressing single cell microvolt amplitude activity from multiple channels in parallel while achieving overall compression ratios above 500. This is the first reported high-channel count wireless optogenetic device providing simultaneous optical stimulation and recording. Measured characteristics show that the proposed headstage can achieve up to 100% of true positive detection rate for signal-to-noise ratio (SNR) down to 15 dB, while achieving up to 97.28% at SNR as low as 5 dB. The implemented prototype features a lifespan of up to 105 minutes, and uses a lightweight (2.8 g) and compact [Formula: see text] rigid-flex printed circuit board.

Recording from two neurons: second-order stimulus reconstruction from spike trains and population coding.

PubMed

Fernandes, N M; Pinto, B D L; Almeida, L O B; Slaets, J F W; Köberle, R

2010-10-01

We study the reconstruction of visual stimuli from spike trains, representing the reconstructed stimulus by a Volterra series up to second order. We illustrate this procedure in a prominent example of spiking neurons, recording simultaneously from the two H1 neurons located in the lobula plate of the fly Chrysomya megacephala. The fly views two types of stimuli, corresponding to rotational and translational displacements. Second-order reconstructions require the manipulation of potentially very large matrices, which obstructs the use of this approach when there are many neurons. We avoid the computation and inversion of these matrices using a convenient set of basis functions to expand our variables in. This requires approximating the spike train four-point functions by combinations of two-point functions similar to relations, which would be true for gaussian stochastic processes. In our test case, this approximation does not reduce the quality of the reconstruction. The overall contribution to stimulus reconstruction of the second-order kernels, measured by the mean squared error, is only about 5% of the first-order contribution. Yet at specific stimulus-dependent instants, the addition of second-order kernels represents up to 100% improvement, but only for rotational stimuli. We present a perturbative scheme to facilitate the application of our method to weakly correlated neurons.

A Fully Automated Approach to Spike Sorting.

PubMed

Chung, Jason E; Magland, Jeremy F; Barnett, Alex H; Tolosa, Vanessa M; Tooker, Angela C; Lee, Kye Y; Shah, Kedar G; Felix, Sarah H; Frank, Loren M; Greengard, Leslie F

2017-09-13

Understanding the detailed dynamics of neuronal networks will require the simultaneous measurement of spike trains from hundreds of neurons (or more). Currently, approaches to extracting spike times and labels from raw data are time consuming, lack standardization, and involve manual intervention, making it difficult to maintain data provenance and assess the quality of scientific results. Here, we describe an automated clustering approach and associated software package that addresses these problems and provides novel cluster quality metrics. We show that our approach has accuracy comparable to or exceeding that achieved using manual or semi-manual techniques with desktop central processing unit (CPU) runtimes faster than acquisition time for up to hundreds of electrodes. Moreover, a single choice of parameters in the algorithm is effective for a variety of electrode geometries and across multiple brain regions. This algorithm has the potential to enable reproducible and automated spike sorting of larger scale recordings than is currently possible. Copyright © 2017 Elsevier Inc. All rights reserved.

Correlates of a single cortical action potential in the epidural EEG

PubMed Central

Teleńczuk, Bartosz; Baker, Stuart N; Kempter, Richard; Curio, Gabriel

2015-01-01

To identify the correlates of a single cortical action potential in surface EEG, we recorded simultaneously epidural EEG and single-unit activity in the primary somatosensory cortex of awake macaque monkeys. By averaging over EEG segments coincident with more than hundred thousand single spikes, we found short-lived (≈ 0.5 ms) triphasic EEG deflections dominated by high-frequency components > 800 Hz. The peak-to-peak amplitude of the grand-averaged spike correlate was 80 nV, which matched theoretical predictions, while single-neuron amplitudes ranged from 12 to 966 nV. Combining these estimates with post-stimulus-time histograms of single-unit responses to median-nerve stimulation allowed us to predict the shape of the evoked epidural EEG response and to estimate the number of contributing neurons. These findings establish spiking activity of cortical neurons as a primary building block of high-frequency epidural EEG, which thus can serve as a quantitative macroscopic marker of neuronal spikes. PMID:25554430

A 16-Channel Nonparametric Spike Detection ASIC Based on EC-PC Decomposition.

PubMed

Wu, Tong; Xu, Jian; Lian, Yong; Khalili, Azam; Rastegarnia, Amir; Guan, Cuntai; Yang, Zhi

2016-02-01

In extracellular neural recording experiments, detecting neural spikes is an important step for reliable information decoding. A successful implementation in integrated circuits can achieve substantial data volume reduction, potentially enabling a wireless operation and closed-loop system. In this paper, we report a 16-channel neural spike detection chip based on a customized spike detection method named as exponential component-polynomial component (EC-PC) algorithm. This algorithm features a reliable prediction of spikes by applying a probability threshold. The chip takes raw data as input and outputs three data streams simultaneously: field potentials, band-pass filtered neural data, and spiking probability maps. The algorithm parameters are on-chip configured automatically based on input data, which avoids manual parameter tuning. The chip has been tested with both in vivo experiments for functional verification and bench-top experiments for quantitative performance assessment. The system has a total power consumption of 1.36 mW and occupies an area of 6.71 mm (2) for 16 channels. When tested on synthesized datasets with spikes and noise segments extracted from in vivo preparations and scaled according to required precisions, the chip outperforms other detectors. A credit card sized prototype board is developed to provide power and data management through a USB port.

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.

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.

A Bit-Encoding Based New Data Structure for Time and Memory Efficient Handling of Spike Times in an Electrophysiological Setup.

PubMed

Ljungquist, Bengt; Petersson, Per; Johansson, Anders J; Schouenborg, Jens; Garwicz, Martin

2018-04-01

Recent neuroscientific and technical developments of brain machine interfaces have put increasing demands on neuroinformatic databases and data handling software, especially when managing data in real time from large numbers of neurons. Extrapolating these developments we here set out to construct a scalable software architecture that would enable near-future massive parallel recording, organization and analysis of neurophysiological data on a standard computer. To this end we combined, for the first time in the present context, bit-encoding of spike data with a specific communication format for real time transfer and storage of neuronal data, synchronized by a common time base across all unit sources. We demonstrate that our architecture can simultaneously handle data from more than one million neurons and provide, in real time (< 25 ms), feedback based on analysis of previously recorded data. In addition to managing recordings from very large numbers of neurons in real time, it also has the capacity to handle the extensive periods of recording time necessary in certain scientific and clinical applications. Furthermore, the bit-encoding proposed has the additional advantage of allowing an extremely fast analysis of spatiotemporal spike patterns in a large number of neurons. Thus, we conclude that this architecture is well suited to support current and near-future Brain Machine Interface requirements.

The detection of intestinal spike activity on surface electroenterograms

NASA Astrophysics Data System (ADS)

Ye-Lin, Y.; Garcia-Casado, J.; Martinez-de-Juan, J. L.; Prats-Boluda, G.; Ponce, J. L.

2010-02-01

Myoelectrical recording could provide an alternative technique for assessing intestinal motility, which is a topic of great interest in gastroenterology since many gastrointestinal disorders are associated with intestinal dysmotility. The pacemaker activity (slow wave, SW) of the electroenterogram (EEnG) has been detected in abdominal surface recordings, although the activity related to bowel contractions (spike bursts, SB) has to date only been detected in experimental models with artificially favored electrical conductivity. The aim of the present work was to assess the possibility of detecting SB activity in abdominal surface recordings under physiological conditions. For this purpose, 11 recording sessions of simultaneous internal and external myolectrical signals were conducted on conscious dogs. Signal analysis was carried out in the spectral domain. The results show that in periods of intestinal contractile activity, high-frequency components of EEnG signals can be detected on the abdominal surface in addition to SW activity. The energy between 2 and 20 Hz of the surface myoelectrical recording presented good correlation with the internal intestinal motility index (0.64 ± 0.10 for channel 1 and 0.57 ± 0.11 for channel 2). This suggests that SB activity can also be detected in canine surface EEnG recording.

Rank Order Coding: a Retinal Information Decoding Strategy Revealed by Large-Scale Multielectrode Array Retinal Recordings.

PubMed

Portelli, Geoffrey; Barrett, John M; Hilgen, Gerrit; Masquelier, Timothée; Maccione, Alessandro; Di Marco, Stefano; Berdondini, Luca; Kornprobst, Pierre; Sernagor, Evelyne

2016-01-01

How a population of retinal ganglion cells (RGCs) encodes the visual scene remains an open question. Going beyond individual RGC coding strategies, results in salamander suggest that the relative latencies of a RGC pair encode spatial information. Thus, a population code based on this concerted spiking could be a powerful mechanism to transmit visual information rapidly and efficiently. Here, we tested this hypothesis in mouse by recording simultaneous light-evoked responses from hundreds of RGCs, at pan-retinal level, using a new generation of large-scale, high-density multielectrode array consisting of 4096 electrodes. Interestingly, we did not find any RGCs exhibiting a clear latency tuning to the stimuli, suggesting that in mouse, individual RGC pairs may not provide sufficient information. We show that a significant amount of information is encoded synergistically in the concerted spiking of large RGC populations. Thus, the RGC population response described with relative activities, or ranks, provides more relevant information than classical independent spike count- or latency- based codes. In particular, we report for the first time that when considering the relative activities across the whole population, the wave of first stimulus-evoked spikes is an accurate indicator of stimulus content. We show that this coding strategy coexists with classical neural codes, and that it is more efficient and faster. Overall, these novel observations suggest that already at the level of the retina, concerted spiking provides a reliable and fast strategy to rapidly transmit new visual scenes.

The mechanics of state dependent neural correlations

PubMed Central

Doiron, Brent; Litwin-Kumar, Ashok; Rosenbaum, Robert; Ocker, Gabriel K.; Josić, Krešimir

2016-01-01

Simultaneous recordings from large neural populations are becoming increasingly common. An important feature of the population activity are the trial-to-trial correlated fluctuations of the spike train outputs of recorded neuron pairs. Like the firing rate of single neurons, correlated activity can be modulated by a number of factors, from changes in arousal and attentional state to learning and task engagement. However, the network mechanisms that underlie these changes are not fully understood. We review recent theoretical results that identify three separate biophysical mechanisms that modulate spike train correlations: changes in input correlations, internal fluctuations, and the transfer function of single neurons. We first examine these mechanisms in feedforward pathways, and then show how the same approach can explain the modulation of correlations in recurrent networks. Such mechanistic constraints on the modulation of population activity will be important in statistical analyses of high dimensional neural data. PMID:26906505

Function of identified motoneurones and co-ordination of primary and secondary motor systems during zebra fish swimming.

PubMed Central

Liu, D W; Westerfield, M

1988-01-01

1. The activity of the two classes of motoneurones, primary and secondary, which innervate myotomal muscle fibres in the zebra fish, was monitored with electromyographic and intracellular techniques. 2. Simultaneous EMG and intracellular recordings from muscle fibres showed that the activity of the two motor systems and of individual primary motoneurones can be distinguished by recording EMG spikes during swimming. 3. Measurements of EMG spikes demonstrated that primary and secondary motoneurones are co-ordinately activated over a wide range of conditions during normal swimming. 4. During swimming the primary motoneurones within a given segment are usually co-activated although they sometimes fire independently. 5. When different primary motoneurones within a given segment are co-activated, they fire nearly synchronously. 6. We conclude that the primary motoneurones are used principally, although not exclusively, during fast swimming, struggling and the startle response, whereas secondary motoneurones function primarily during slower swimming. PMID:3253426

Acute in vivo testing of a conformal polymer microelectrode array for multi-region hippocampal recordings

NASA Astrophysics Data System (ADS)

Xu, Huijing; Weltman Hirschberg, Ahuva; Scholten, Kee; Berger, Theodore William; Song, Dong; Meng, Ellis

2018-02-01

Objective. The success of a cortical prosthetic device relies upon its ability to attain resolvable spikes from many neurons in particular neural networks over long periods of time. Traditionally, lifetimes of neural recordings are greatly limited by the body’s immune response against the foreign implant which causes neuronal death and glial scarring. This immune reaction is posited to be exacerbated by micromotion between the implant, which is often rigid, and the surrounding, soft brain tissue, and attenuates the quality of recordings over time. Approach. In an attempt to minimize the foreign body response to a penetrating neural array that records from multiple brain regions, Parylene C, a flexible, biocompatible polymer was used as the substrate material for a functional, proof-of-concept neural array with a reduced elastic modulus. This probe array was designed and fabricated to have 64 electrodes positioned to match the anatomy of the rat hippocampus and allow for simultaneous recordings between two cell-body layers of interest. A dissolvable brace was used for deep-brain penetration of the flexible array. Main results. Arrays were electrochemically characterized at the benchtop, and a novel insertion technique that restricts acute insertion injury enabled accurate target placement of four, bare, flexible arrays to greater than 4 mm deep into the rat brain. Arrays were tested acutely and in vivo recordings taken intra-operatively reveal spikes in both targeted regions of the hippocampus with spike amplitudes and noise levels similar to those recorded with microwires. Histological staining of a sham array implanted for one month reveals limited astrocytic scarring and neuronal death around the implant. Significance. This work represents one of the first examples of a penetrating polymer probe array that records from individual neurons in structures that lie deep within the brain.

Action potential propagation recorded from single axonal arbors using multi-electrode arrays.

PubMed

Tovar, Kenneth R; Bridges, Daniel C; Wu, Bian; Randall, Connor; Audouard, Morgane; Jang, Jiwon; Hansma, Paul K; Kosik, Kenneth S

2018-04-11

We report the presence of co-occurring extracellular action potentials (eAPs) from cultured mouse hippocampal neurons among groups of planar electrodes on multi-electrode arrays (MEAs). The invariant sequences of eAPs among co-active electrode groups, repeated co-occurrences and short inter-electrode latencies are consistent with action potential propagation in unmyelinated axons. Repeated eAP co-detection by multiple electrodes was widespread in all our data records. Co-detection of eAPs confirms they result from the same neuron and allows these eAPs to be isolated from all other spikes independently of spike sorting algorithms. We averaged co-occurring events and revealed additional electrodes with eAPs that would otherwise be below detection threshold. We used these eAP cohorts to explore the temperature sensitivity of action potential propagation and the relationship between voltage-gated sodium channel density and propagation velocity. The sequence of eAPs among co-active electrodes 'fingerprints' neurons giving rise to these events and identifies them within neuronal ensembles. We used this property and the non-invasive nature of extracellular recording to monitor changes in excitability at multiple points in single axonal arbors simultaneously over several hours, demonstrating independence of axonal segments. Over several weeks, we recorded changes in inter-electrode propagation latencies and ongoing changes in excitability in different regions of single axonal arbors. Our work illustrates how repeated eAP co-occurrences can be used to extract physiological data from single axons with low electrode density MEAs. However, repeated eAP co-occurrences leads to over-sampling spikes from single neurons and thus can confound traditional spike-train analysis.

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

Cortical Action Potential Backpropagation Explains Spike Threshold Variability and Rapid-Onset Kinetics

PubMed Central

Yu, Yuguo; Shu, Yousheng; McCormick, David A.

2008-01-01

Neocortical action potential responses in vivo are characterized by considerable threshold variability, and thus timing and rate variability, even under seemingly identical conditions. This finding suggests that cortical ensembles are required for accurate sensorimotor integration and processing. Intracellularly, trial-to-trial variability results not only from variation in synaptic activities, but also in the transformation of these into patterns of action potentials. Through simultaneous axonal and somatic recordings and computational simulations, we demonstrate that the initiation of action potentials in the axon initial segment followed by backpropagation of these spikes throughout the neuron results in a distortion of the relationship between the timing of synaptic and action potential events. In addition, this backpropagation also results in an unusually high rate of rise of membrane potential at the foot of the action potential. The distortion of the relationship between the amplitude time course of synaptic inputs and action potential output caused by spike back-propagation results in the appearance of high spike threshold variability at the level of the soma. At the point of spike initiation, the axon initial segment, threshold variability is considerably less. Our results indicate that spike generation in cortical neurons is largely as expected by Hodgkin—Huxley theory and is more precise than previously thought. PMID:18632930

Simultaneous multi-patch-clamp and extracellular-array recordings: Single neuron reflects network activity

NASA Astrophysics Data System (ADS)

Vardi, Roni; Goldental, Amir; Sardi, Shira; Sheinin, Anton; Kanter, Ido

2016-11-01

The increasing number of recording electrodes enhances the capability of capturing the network’s cooperative activity, however, using too many monitors might alter the properties of the measured neural network and induce noise. Using a technique that merges simultaneous multi-patch-clamp and multi-electrode array recordings of neural networks in-vitro, we show that the membrane potential of a single neuron is a reliable and super-sensitive probe for monitoring such cooperative activities and their detailed rhythms. Specifically, the membrane potential and the spiking activity of a single neuron are either highly correlated or highly anti-correlated with the time-dependent macroscopic activity of the entire network. This surprising observation also sheds light on the cooperative origin of neuronal burst in cultured networks. Our findings present an alternative flexible approach to the technique based on a massive tiling of networks by large-scale arrays of electrodes to monitor their activity.

Simultaneous multi-patch-clamp and extracellular-array recordings: Single neuron reflects network activity.

PubMed

Vardi, Roni; Goldental, Amir; Sardi, Shira; Sheinin, Anton; Kanter, Ido

2016-11-08

The increasing number of recording electrodes enhances the capability of capturing the network's cooperative activity, however, using too many monitors might alter the properties of the measured neural network and induce noise. Using a technique that merges simultaneous multi-patch-clamp and multi-electrode array recordings of neural networks in-vitro, we show that the membrane potential of a single neuron is a reliable and super-sensitive probe for monitoring such cooperative activities and their detailed rhythms. Specifically, the membrane potential and the spiking activity of a single neuron are either highly correlated or highly anti-correlated with the time-dependent macroscopic activity of the entire network. This surprising observation also sheds light on the cooperative origin of neuronal burst in cultured networks. Our findings present an alternative flexible approach to the technique based on a massive tiling of networks by large-scale arrays of electrodes to monitor their activity.

Simultaneous multi-patch-clamp and extracellular-array recordings: Single neuron reflects network activity

PubMed Central

Vardi, Roni; Goldental, Amir; Sardi, Shira; Sheinin, Anton; Kanter, Ido

2016-01-01

The increasing number of recording electrodes enhances the capability of capturing the network’s cooperative activity, however, using too many monitors might alter the properties of the measured neural network and induce noise. Using a technique that merges simultaneous multi-patch-clamp and multi-electrode array recordings of neural networks in-vitro, we show that the membrane potential of a single neuron is a reliable and super-sensitive probe for monitoring such cooperative activities and their detailed rhythms. Specifically, the membrane potential and the spiking activity of a single neuron are either highly correlated or highly anti-correlated with the time-dependent macroscopic activity of the entire network. This surprising observation also sheds light on the cooperative origin of neuronal burst in cultured networks. Our findings present an alternative flexible approach to the technique based on a massive tiling of networks by large-scale arrays of electrodes to monitor their activity. PMID:27824075

Propagating Neural Source Revealed by Doppler Shift of Population Spiking Frequency

PubMed Central

Zhang, Mingming; Shivacharan, Rajat S.; Chiang, Chia-Chu; Gonzalez-Reyes, Luis E.

2016-01-01

Electrical activity in the brain during normal and abnormal function is associated with propagating waves of various speeds and directions. It is unclear how both fast and slow traveling waves with sometime opposite directions can coexist in the same neural tissue. By recording population spikes simultaneously throughout the unfolded rodent hippocampus with a penetrating microelectrode array, we have shown that fast and slow waves are causally related, so a slowly moving neural source generates fast-propagating waves at ∼0.12 m/s. The source of the fast population spikes is limited in space and moving at ∼0.016 m/s based on both direct and Doppler measurements among 36 different spiking trains among eight different hippocampi. The fact that the source is itself moving can account for the surprising direction reversal of the wave. Therefore, these results indicate that a small neural focus can move and that this phenomenon could explain the apparent wave reflection at tissue edges or multiple foci observed at different locations in neural tissue. SIGNIFICANCE STATEMENT The use of novel techniques with an unfolded hippocampus and penetrating microelectrode array to record and analyze neural activity has revealed the existence of a source of neural signals that propagates throughout the hippocampus. The source itself is electrically silent, but its location can be inferred by building isochrone maps of population spikes that the source generates. The movement of the source can also be tracked by observing the Doppler frequency shift of these spikes. These results have general implications for how neural signals are generated and propagated in the hippocampus; moreover, they have important implications for the understanding of seizure generation and foci localization. PMID:27013678

Electromagnetic Emissions from a Modular Low Voltage Electro-Impulse De-Icing System

DTIC Science & Technology

1989-03-01

composite wing section employed in these tests. Cy O’Young of the Boeing Commercial Airplance Company is thanked for his many he-pful suggestions during this...a voltage spike which occurred simultaneous wi’h the discharge of the coil. A 2.2 volt spike would be adequate to create a transmission error on a...signal was a voltage spike which occurs simultaneous with discharge of the coil. A 2.2 volt spike would be adequate to create an error on a digital

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.

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

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.

Cortical membrane potential signature of optimal states for sensory signal detection

PubMed Central

McGinley, Matthew J.; David, Stephen V.; McCormick, David A.

2015-01-01

The neural correlates of optimal states for signal detection task performance are largely unknown. One hypothesis holds that optimal states exhibit tonically depolarized cortical neurons with enhanced spiking activity, such as occur during movement. We recorded membrane potentials of auditory cortical neurons in mice trained on a challenging tone-in-noise detection task while assessing arousal with simultaneous pupillometry and hippocampal recordings. Arousal measures accurately predicted multiple modes of membrane potential activity, including: rhythmic slow oscillations at low arousal, stable hyperpolarization at intermediate arousal, and depolarization during phasic or tonic periods of hyper-arousal. Walking always occurred during hyper-arousal. Optimal signal detection behavior and sound-evoked responses, at both sub-threshold and spiking levels, occurred at intermediate arousal when pre-decision membrane potentials were stably hyperpolarized. These results reveal a cortical physiological signature of the classically-observed inverted-U relationship between task performance and arousal, and that optimal detection exhibits enhanced sensory-evoked responses and reduced background synaptic activity. PMID:26074005

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

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.

Integration of cortical and pallidal inputs in the basal ganglia-recipient thalamus of singing birds

PubMed Central

Goldberg, Jesse H.; Farries, Michael A.

2012-01-01

The basal ganglia-recipient thalamus receives inhibitory inputs from the pallidum and excitatory inputs from cortex, but it is unclear how these inputs interact during behavior. We recorded simultaneously from thalamic neurons and their putative synaptically connected pallidal inputs in singing zebra finches. We find, first, that each pallidal spike produces an extremely brief (∼5 ms) pulse of inhibition that completely suppresses thalamic spiking. As a result, thalamic spikes are entrained to pallidal spikes with submillisecond precision. Second, we find that the number of thalamic spikes that discharge within a single pallidal interspike interval (ISI) depends linearly on the duration of that interval but does not depend on pallidal activity prior to the interval. In a detailed biophysical model, our results were not easily explained by the postinhibitory “rebound” mechanism previously observed in anesthetized birds and in brain slices, nor could most of our data be characterized as “gating” of excitatory transmission by inhibitory pallidal input. Instead, we propose a novel “entrainment” mechanism of pallidothalamic transmission that highlights the importance of an excitatory conductance that drives spiking, interacting with brief pulses of pallidal inhibition. Building on our recent finding that cortical inputs can drive syllable-locked rate modulations in thalamic neurons during singing, we report here that excitatory inputs affect thalamic spiking in two ways: by shortening the latency of a thalamic spike after a pallidal spike and by increasing thalamic firing rates within individual pallidal ISIs. We present a unifying biophysical model that can reproduce all known modes of pallidothalamic transmission—rebound, gating, and entrainment—depending on the amount of excitation the thalamic neuron receives. PMID:22673333

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

Visual stimulation synchronizes or desynchronizes the activity of neuron pairs between the caudate nucleus and the posterior thalamus.

PubMed

Rokszin, Alice; Gombköto, Péter; Berényi, Antal; Márkus, Zita; Braunitzer, Gábor; Benedek, György; Nagy, Attila

2011-10-18

Recent morphological and physiological studies have suggested a strong relationship between the suprageniculate nucleus (Sg) of the posterior thalamus and the input structure of the basal ganglia, the caudate nucleus (CN) of the feline brain. Accordingly, to clarify if there is a real functional relationship between Sg and CN during visual information processing, we investigated the temporal relations of simultaneously recorded neuronal spike trains of these two structures, looking for any significant cross-correlation between the spiking of the simultaneously recorded neurons. For the purposes of statistical analysis, we used the shuffle and jittering resampling methods. Of the recorded 288 Sg-CN neuron pairs, 26 (9.2%) showed significantly correlated spontaneous activity. Nineteen pairs (6.7%) showed correlated activity during stationary visual stimulation, while 21 (7.4%) pairs during stimulus movement. There was no overlap between the neuron pairs that showed cross-correlated spontaneous activity and the pairs that synchronized their activity during visual stimulation. Thus visual stimulation seems to have been able to synchronize, and also, by other neuron pairs, desynchronize the activity of CN and Sg. In about half of the cases, the activation of Sg preceded the activation of CN by a few milliseconds, while in the other half, CN was activated earlier. Our results provide the first piece of evidence for the existence of a functional cooperation between Sg and CN. We argue that either a monosynaptic bidirectional direct connection should exist between these structures, or a common input comprising of parallel pathways synchronizing them. Copyright © 2011 Elsevier B.V. All rights reserved.

Shade-Induced Action Potentials in Helianthus annuus L. Originate Primarily from the Epicotyl

PubMed Central

Stephens, Nicholas R; Cleland, Robert E; Van Volkenburgh, Elizabeth

2006-01-01

Repeated observations that shading (a drastic reduction in illumination rate) increased the generation of spikes (rapidly reversed depolarizations) in leaves and stems of many cucumber and sunflower plants suggests a phenomenon widespread among plant organs and species. Although shaded leaves occasionally generate spikes and have been suggested to trigger systemic action potentials (APs) in sunflower stems, we never found leaf-generated spikes to propagate out of the leaf and into the stem. On the contrary, our data consistently implicate the epicotyl as the location where most spikes and APs (propagating spikes) originate. Microelectrode studies of light and shading responses in mesophyll cells of leaf strips and in epidermis/cortex cells of epicotyl segments confirm this conclusion and show that spike induction is not confined to intact plants. 90% of the epicotyl-generated APs undergo basipetal propagation to the lower epicotyl, hypocotyl and root. They propagate with an average rate of 2 ± 0.3 mm s−1 and always undergo a large decrement from the hypocotyl to the root. The few epicotyl-derived APs that can be tracked to leaf blades (< 10%) undergo either a large decrement or fail to be transmitted at all. Occasionally (5% of the observations) spikes were be generated in hypocotyl and lower epicotyl that moved towards the upper epicotyl unaltered, decremented, or amplified. This study confirms that plant APs arise to natural, nontraumatic changes. In simultaneous recordings with epicotyl growth, AP generation was found to parallel the acceleration of stem growth under shade. The possible relatedness of both processes must be further investigated. PMID:19521471

A unified approach to the study of temporal, correlational, and rate coding.

PubMed

Panzeri, S; Schultz, S R

2001-06-01

We demonstrate that the information contained in the spike occurrence times of a population of neurons can be broken up into a series of terms, each reflecting something about potential coding mechanisms. This is possible in the coding regime in which few spikes are emitted in the relevant time window. This approach allows us to study the additional information contributed by spike timing beyond that present in the spike counts and to examine the contributions to the whole information of different statistical properties of spike trains, such as firing rates and correlation functions. It thus forms the basis for a new quantitative procedure for analyzing simultaneous multiple neuron recordings and provides theoretical constraints on neural coding strategies. We find a transition between two coding regimes, depending on the size of the relevant observation timescale. For time windows shorter than the timescale of the stimulus-induced response fluctuations, there exists a spike count coding phase, in which the purely temporal information is of third order in time. For time windows much longer than the characteristic timescale, there can be additional timing information of first order, leading to a temporal coding phase in which timing information may affect the instantaneous information rate. In this new framework, we study the relative contributions of the dynamic firing rate and correlation variables to the full temporal information, the interaction of signal and noise correlations in temporal coding, synergy between spikes and between cells, and the effect of refractoriness. We illustrate the utility of the technique by analyzing a few cells from the rat barrel cortex.

Dynamic balance of excitation and inhibition rapidly modulates spike probability and precision in feed-forward hippocampal circuits

PubMed Central

Wahlstrom-Helgren, Sarah

2016-01-01

Feed-forward inhibitory (FFI) circuits are important for many information-processing functions. FFI circuit operations critically depend on the balance and timing between the excitatory and inhibitory components, which undergo rapid dynamic changes during neural activity due to short-term plasticity (STP) of both components. How dynamic changes in excitation/inhibition (E/I) balance during spike trains influence FFI circuit operations remains poorly understood. In the current study we examined the role of STP in the FFI circuit functions in the mouse hippocampus. Using a coincidence detection paradigm with simultaneous activation of two Schaffer collateral inputs, we found that the spiking probability in the target CA1 neuron was increased while spike precision concomitantly decreased during high-frequency bursts compared with a single spike. Blocking inhibitory synaptic transmission revealed that dynamics of inhibition predominately modulates the spike precision but not the changes in spiking probability, whereas the latter is modulated by the dynamics of excitation. Further analyses combining whole cell recordings and simulations of the FFI circuit suggested that dynamics of the inhibitory circuit component may influence spiking behavior during bursts by broadening the width of excitatory postsynaptic responses and that the strength of this modulation depends on the basal E/I ratio. We verified these predictions using a mouse model of fragile X syndrome, which has an elevated E/I ratio, and found a strongly reduced modulation of postsynaptic response width during bursts. Our results suggest that changes in the dynamics of excitatory and inhibitory circuit components due to STP play important yet distinct roles in modulating the properties of FFI circuits. PMID:27605532

Neural noise and movement-related codes in the macaque supplementary motor area.

PubMed

Averbeck, Bruno B; Lee, Daeyeol

2003-08-20

We analyzed the variability of spike counts and the coding capacity of simultaneously recorded pairs of neurons in the macaque supplementary motor area (SMA). We analyzed the mean-variance functions for single neurons, as well as signal and noise correlations between pairs of neurons. All three statistics showed a strong dependence on the bin width chosen for analysis. Changes in the correlation structure of single neuron spike trains over different bin sizes affected the mean-variance function, and signal and noise correlations between pairs of neurons were much smaller at small bin widths, increasing monotonically with the width of the bin. Analyses in the frequency domain showed that the noise between pairs of neurons, on average, was most strongly correlated at low frequencies, which explained the increase in noise correlation with increasing bin width. The coding performance was analyzed to determine whether the temporal precision of spike arrival times and the interactions within and between neurons could improve the prediction of the upcoming movement. We found that in approximately 62% of neuron pairs, the arrival times of spikes at a resolution between 66 and 40 msec carried more information than spike counts in a 200 msec bin. In addition, in 19% of neuron pairs, inclusion of within (11%)- or between-neuron (8%) correlations in spike trains improved decoding accuracy. These results suggest that in some SMA neurons elements of the spatiotemporal pattern of activity may be relevant for neural coding.

Head direction cells in the postsubiculum do not show replay of prior waking sequences during sleep

PubMed Central

Brandon, Mark P.; Bogaard, Andrew; Andrews, Chris M.; Hasselmo, Michael E.

2011-01-01

During slow-wave sleep and REM sleep, hippocampal place cells in the rat show replay of sequences previously observed during waking. We tested the hypothesis from computational modelling that the temporal structure of REM sleep replay could arise from an interplay of place cells with head direction cells in the postsubiculum. Physiological single-unit recording was performed simultaneously from five or more head direction or place by head direction cells in the postsubiculum during running on a circular track allowing sampling of a full range of head directions, and during sleep periods before and after running on the circular track. Data analysis compared the spiking activity during individual REM periods with waking as in previous analysis procedures for REM sleep. We also used a new procedure comparing groups of similar runs during waking with REM sleep periods. There was no consistent evidence for a statistically significant correlation of the temporal structure of spiking during REM sleep with spiking during waking running periods. Thus, the spiking activity of head direction cells during REM sleep does not show replay of head direction cell activity occurring during a previous waking period of running on the task. In addition, we compared the spiking of postsubiculum neurons during hippocampal sharp wave ripple events. We show that head direction cells are not activated during sharp wave ripples, while neurons responsive to place in the postsubiculum show reliable spiking at ripple events. PMID:21509854

A data variance technique for automated despiking of magnetotelluric data with a remote reference

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

Kappler, K.

2011-02-15

The magnetotelluric method employs co-located surface measurements of electric and magnetic fields to infer the local electrical structure of the earth. The frequency-dependent 'apparent resistivity' curves can be inaccurate at long periods if input data are contaminated - even when robust remote reference techniques are employed. Data despiking prior to processing can result in significantly more reliable estimates of long period apparent resistivities. This paper outlines a two-step method of automatic identification and replacement for spike-like contamination of magnetotelluric data; based on the simultaneity of natural electric and magnetic field variations at distant sites. This simultaneity is exploited both tomore » identify windows in time when the array data are compromised, and to generate synthetic data that replace observed transient noise spikes. In the first step, windows in data time series containing spikes are identified via intersite comparison of channel 'activity' - such as the variance of differenced data within each window. In the second step, plausible data for replacement of flagged windows is calculated by Wiener filtering coincident data in clean channels. The Wiener filters - which express the time-domain relationship between various array channels - are computed using an uncontaminated segment of array training data. Examples are shown where the algorithm is applied to artificially contaminated data, and to real field data. In both cases all spikes are successfully identified. In the case of implanted artificial noise, the synthetic replacement time series are very similar to the original recording. In all cases, apparent resistivity and phase curves obtained by processing the despiked data are much improved over curves obtained from raw data.« less

Unique Configurations of Compression and Truncation of Neuronal Activity Underlie l-DOPA-Induced Selection of Motor Patterns in Aplysia.

PubMed

Neveu, Curtis L; Costa, Renan M; Homma, Ryota; Nagayama, Shin; Baxter, Douglas A; Byrne, John H

2017-01-01

A key issue in neuroscience is understanding the ways in which neuromodulators such as dopamine modify neuronal activity to mediate selection of distinct motor patterns. We addressed this issue by applying either low or high concentrations of l-DOPA (40 or 250 μM) and then monitoring activity of up to 130 neurons simultaneously in the feeding circuitry of Aplysia using a voltage-sensitive dye (RH-155). l-DOPA selected one of two distinct buccal motor patterns (BMPs): intermediate (low l-DOPA) or bite (high l-DOPA) patterns. The selection of intermediate BMPs was associated with shortening of the second phase of the BMP (retraction), whereas the selection of bite BMPs was associated with shortening of both phases of the BMP (protraction and retraction). Selection of intermediate BMPs was also associated with truncation of individual neuron spike activity (decreased burst duration but no change in spike frequency or burst latency) in neurons active during retraction. In contrast, selection of bite BMPs was associated with compression of spike activity (decreased burst latency and duration and increased spike frequency) in neurons projecting through specific nerves, as well as increased spike frequency of protraction neurons. Finally, large-scale voltage-sensitive dye recordings delineated the spatial distribution of neurons active during BMPs and the modification of that distribution by the two concentrations of l-DOPA.

Unique Configurations of Compression and Truncation of Neuronal Activity Underlie l-DOPA–Induced Selection of Motor Patterns in Aplysia

PubMed Central

Homma, Ryota; Nagayama, Shin; Baxter, Douglas A.

2017-01-01

A key issue in neuroscience is understanding the ways in which neuromodulators such as dopamine modify neuronal activity to mediate selection of distinct motor patterns. We addressed this issue by applying either low or high concentrations of l-DOPA (40 or 250 μM) and then monitoring activity of up to 130 neurons simultaneously in the feeding circuitry of Aplysia using a voltage-sensitive dye (RH-155). l-DOPA selected one of two distinct buccal motor patterns (BMPs): intermediate (low l-DOPA) or bite (high l-DOPA) patterns. The selection of intermediate BMPs was associated with shortening of the second phase of the BMP (retraction), whereas the selection of bite BMPs was associated with shortening of both phases of the BMP (protraction and retraction). Selection of intermediate BMPs was also associated with truncation of individual neuron spike activity (decreased burst duration but no change in spike frequency or burst latency) in neurons active during retraction. In contrast, selection of bite BMPs was associated with compression of spike activity (decreased burst latency and duration and increased spike frequency) in neurons projecting through specific nerves, as well as increased spike frequency of protraction neurons. Finally, large-scale voltage-sensitive dye recordings delineated the spatial distribution of neurons active during BMPs and the modification of that distribution by the two concentrations of l-DOPA. PMID:29071298

Neurite-specific Ca2+ dynamics underlying sound processing in an auditory interneurone.

PubMed

Baden, T; Hedwig, B

2007-01-01

Concepts on neuronal signal processing and integration at a cellular and subcellular level are driven by recording techniques and model systems available. The cricket CNS with the omega-1-neurone (ON1) provides a model system for auditory pattern recognition and directional processing. Exploiting ON1's planar structure we simultaneously imaged free intracellular Ca(2+) at both input and output neurites and recorded the membrane potential in vivo during acoustic stimulation. In response to a single sound pulse the rate of Ca(2+) rise followed the onset spike rate of ON1, while the final Ca(2+) level depended on the mean spike rate. Ca(2+) rapidly increased in both dendritic and axonal arborizations and only gradually in the axon and the cell body. Ca(2+) levels were particularly high at the spike-generating zone. Through the activation of a Ca(2+)-sensitive K(+) current this may exhibit a specific control over the cell's electrical response properties. In all cellular compartments presentation of species-specific calling song caused distinct oscillations of the Ca(2+) level in the chirp rhythm, but not the faster syllable rhythm. The Ca(2+)-mediated hyperpolarization of ON1 suppressed background spike activity between chirps, acting as a noise filter. During directional auditory processing, the functional interaction of Ca(2+)-mediated inhibition and contralateral synaptic inhibition was demonstrated. Upon stimulation with different sound frequencies, the dendrites, but not the axonal arborizations, demonstrated a tonotopic response profile. This mirrored the dominance of the species-specific carrier frequency and resulted in spatial filtering of high frequency auditory inputs. (c) 2006 Wiley Periodicals, Inc.

Applying the multivariate time-rescaling theorem to neural population models

PubMed Central

Gerhard, Felipe; Haslinger, Robert; Pipa, Gordon

2011-01-01

Statistical models of neural activity are integral to modern neuroscience. Recently, interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on neural information processing. However any statistical model must be validated by an appropriate goodness-of-fit test. Kolmogorov-Smirnov tests based upon the time-rescaling theorem have proven to be useful for evaluating point-process-based statistical models of single-neuron spike trains. Here we discuss the extension of the time-rescaling theorem to the multivariate (neural population) case. We show that even in the presence of strong correlations between spike trains, models which neglect couplings between neurons can be erroneously passed by the univariate time-rescaling test. We present the multivariate version of the time-rescaling theorem, and provide a practical step-by-step procedure for applying it towards testing the sufficiency of neural population models. Using several simple analytically tractable models and also more complex simulated and real data sets, we demonstrate that important features of the population activity can only be detected using the multivariate extension of the test. PMID:21395436

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.

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.

Interictal spike detection comparing subdural and depth electrodes during electrocorticography.

PubMed

Privitera, M D; Quinlan, J G; Yeh, H S

1990-11-01

We compared the ability of subdural and depth electrodes to detect and localize interictal epileptiform discharges (IEDs) in the temporal lobe. Sixteen patients had simultaneous intraoperative recordings with depth and subdural electrodes while undergoing anterior temporal lobe resections under local anesthesia for medically intractable seizures. IEDs that were focal (detected at just 1 or 2 electrode contacts) typically registered at the nearest contact, regardless of type. IEDs that were regional (engaging more than 2 electrode contacts) typically appeared simultaneously at both electrode types. Neither method was better able to indicate whether an IED was mesial or lateral, posterior or anterior. Subdural and depth electrodes seem to provide complementary information on the location of IEDs within the temporal lobe.

A review on cluster estimation methods and their application to neural spike data.

PubMed

Zhang, James; Nguyen, Thanh; Cogill, Steven; Bhatti, Asim; Luo, Lingkun; Yang, Samuel; Nahavandi, Saeid

2018-06-01

The extracellular action potentials recorded on an electrode result from the collective simultaneous electrophysiological activity of an unknown number of neurons. Identifying and assigning these action potentials to their firing neurons-'spike sorting'-is an indispensable step in studying the function and the response of an individual or ensemble of neurons to certain stimuli. Given the task of neural spike sorting, the determination of the number of clusters (neurons) is arguably the most difficult and challenging issue, due to the existence of background noise and the overlap and interactions among neurons in neighbouring regions. It is not surprising that some researchers still rely on visual inspection by experts to estimate the number of clusters in neural spike sorting. Manual inspection, however, is not suitable to processing the vast, ever-growing amount of neural data. To address this pressing need, in this paper, thirty-three clustering validity indices have been comprehensively reviewed and implemented to determine the number of clusters in neural datasets. To gauge the suitability of the indices to neural spike data, and inform the selection process, we then calculated the indices by applying k-means clustering to twenty widely used synthetic neural datasets and one empirical dataset, and compared the performance of these indices against pre-existing ground truth labels. The results showed that the top five validity indices work consistently well across variations in noise level, both for the synthetic datasets and the real dataset. Using these top performing indices provides strong support for the determination of the number of neural clusters, which is essential in the spike sorting process.

A review on cluster estimation methods and their application to neural spike data

NASA Astrophysics Data System (ADS)

Zhang, James; Nguyen, Thanh; Cogill, Steven; Bhatti, Asim; Luo, Lingkun; Yang, Samuel; Nahavandi, Saeid

2018-06-01

The extracellular action potentials recorded on an electrode result from the collective simultaneous electrophysiological activity of an unknown number of neurons. Identifying and assigning these action potentials to their firing neurons—‘spike sorting’—is an indispensable step in studying the function and the response of an individual or ensemble of neurons to certain stimuli. Given the task of neural spike sorting, the determination of the number of clusters (neurons) is arguably the most difficult and challenging issue, due to the existence of background noise and the overlap and interactions among neurons in neighbouring regions. It is not surprising that some researchers still rely on visual inspection by experts to estimate the number of clusters in neural spike sorting. Manual inspection, however, is not suitable to processing the vast, ever-growing amount of neural data. To address this pressing need, in this paper, thirty-three clustering validity indices have been comprehensively reviewed and implemented to determine the number of clusters in neural datasets. To gauge the suitability of the indices to neural spike data, and inform the selection process, we then calculated the indices by applying k-means clustering to twenty widely used synthetic neural datasets and one empirical dataset, and compared the performance of these indices against pre-existing ground truth labels. The results showed that the top five validity indices work consistently well across variations in noise level, both for the synthetic datasets and the real dataset. Using these top performing indices provides strong support for the determination of the number of neural clusters, which is essential in the spike sorting process.

Parallel multipoint recording of aligned and cultured neurons on corresponding Micro Channel Array toward on-chip cell analysis.

PubMed

Tonomura, W; Moriguchi, H; Jimbo, Y; Konishi, S

2008-01-01

This paper describes an advanced Micro Channel Array (MCA) so as to record neuronal network at multiple points simultaneously. Developed MCA is designed for neuronal network analysis which has been studied by co-authors using MEA (Micro Electrode Arrays) system. The MCA employs the principle of the extracellular recording. Presented MCA has the following advantages. First of all, the electrodes integrated around individual micro channels are electrically isolated for parallel multipoint recording. Sucking and clamping of cells through micro channels is expected to improve the cellular selectivity and S/N ratio. In this study, hippocampal neurons were cultured on the developed MCA. As a result, the spontaneous and evoked spike potential could be recorded by sucking and clamping the cells at multiple points. Herein, we describe the successful experimental results together with the design and fabrication of the advanced MCA toward on-chip analysis of neuronal network.

A simple white noise analysis of neuronal light responses.

PubMed

Chichilnisky, E J

2001-05-01

A white noise technique is presented for estimating the response properties of spiking visual system neurons. The technique is simple, robust, efficient and well suited to simultaneous recordings from multiple neurons. It provides a complete and easily interpretable model of light responses even for neurons that display a common form of response nonlinearity that precludes classical linear systems analysis. A theoretical justification of the technique is presented that relies only on elementary linear algebra and statistics. Implementation is described with examples. The technique and the underlying model of neural responses are validated using recordings from retinal ganglion cells, and in principle are applicable to other neurons. Advantages and disadvantages of the technique relative to classical approaches are discussed.

Application of Savitzky-Golay differentiation filters and Fourier functions to simultaneous determination of cefepime and the co-administered drug, levofloxacin, in spiked human plasma

NASA Astrophysics Data System (ADS)

Abdel-Aziz, Omar; Abdel-Ghany, Maha F.; Nagi, Reham; Abdel-Fattah, Laila

2015-03-01

The present work is concerned with simultaneous determination of cefepime (CEF) and the co-administered drug, levofloxacin (LEV), in spiked human plasma by applying a new approach, Savitzky-Golay differentiation filters, and combined trigonometric Fourier functions to their ratio spectra. The different parameters associated with the calculation of Savitzky-Golay and Fourier coefficients were optimized. The proposed methods were validated and applied for determination of the two drugs in laboratory prepared mixtures and spiked human plasma. The results were statistically compared with reported HPLC methods and were found accurate and precise.

Kinetic Assessment of Golf Shoe Outer Sole Design Features

PubMed Central

Smith, Neal A.; Dyson, Rosemary J.

2009-01-01

This study assessed human kinetics in relation to golf shoe outer sole design features during the golf swing using a driver club by measuring both within the shoe, and beneath the shoe at the natural grass interface. Three different shoes were assessed: metal 7- spike shoe, alternative 7-spike shoe, and a flat soled shoe. In-shoe plantar pressure data were recorded using Footscan RS International pressure insoles and sampling at 500 Hz. Simultaneously ground reaction force at the shoe outer sole was measured using 2 natural grass covered Kistler force platforms and 1000 Hz data acquisition. Video recording of the 18 right-handed golfers at 200 Hz was undertaken while the golfer performed 5 golf shots with his own driver in each type of shoe. Front foot (nearest to shot direction) maximum vertical force and torque were greater than at the back foot, and there was no significant difference related to the shoe type. Wearing the metal spike shoe when using a driver was associated with more torque generation at the back foot (p < 0. 05) than when the flat soled shoe was worn. Within shoe regional pressures differed significantly with golf shoe outer sole design features (p < 0.05). Comparison of the metal spike and alternative spike shoe results provided indications of the quality of regional traction on the outer sole. Potential golf shoe outer sole design features and traction were presented in relation to phases of the golf swing movement. Application of two kinetic measurement methods identified that moderated (adapted) muscular control of foot and body movement may be induced by golf shoe outer sole design features. Ground reaction force measures inform comparisons of overall shoe functional performance, and insole pressure measurements inform comparisons of the underfoot conditions induced by specific regions of the golf shoe outer sole. Key points Assessments of within golf shoe pressures and beneath shoe forces at the natural grass interface were conducted during golf shots with a driver. Application of two kinetic measurement methods simultaneously identified that moderated (adapted) muscular control of the foot and body movement may be induced by golf shoe outer sole localised design features. Ground force measures inform overall shoe kinetic functional performance. Insole pressure measurement informs of underfoot conditions induced by localised specific regions of the golf outer sole. Significant differences in ground-shoe torque generation and insole regional pressures were identified when different golf shoes were worn. PMID:24149603

A novel high electrode count spike recording array using an 81,920 pixel transimpedance amplifier-based imaging chip.

PubMed

Johnson, Lee J; Cohen, Ethan; Ilg, Doug; Klein, Richard; Skeath, Perry; Scribner, Dean A

2012-04-15

Microelectrode recording arrays of 60-100 electrodes are commonly used to record neuronal biopotentials, and these have aided our understanding of brain function, development and pathology. However, higher density microelectrode recording arrays of larger area are needed to study neuronal function over broader brain regions such as in cerebral cortex or hippocampal slices. Here, we present a novel design of a high electrode count picocurrent imaging array (PIA), based on an 81,920 pixel Indigo ISC9809 readout integrated circuit camera chip. While originally developed for interfacing to infrared photodetector arrays, we have adapted the chip for neuron recording by bonding it to microwire glass resulting in an array with an inter-electrode pixel spacing of 30 μm. In a high density electrode array, the ability to selectively record neural regions at high speed and with good signal to noise ratio are both functionally important. A critical feature of our PIA is that each pixel contains a dedicated low noise transimpedance amplifier (∼0.32 pA rms) which allows recording high signal to noise ratio biocurrents comparable to single electrode voltage amplifier recordings. Using selective sampling of 256 pixel subarray regions, we recorded the extracellular biocurrents of rabbit retinal ganglion cell spikes at sampling rates up to 7.2 kHz. Full array local electroretinogram currents could also be recorded at frame rates up to 100 Hz. A PIA with a full complement of 4 readout circuits would span 1cm and could acquire simultaneous data from selected regions of 1024 electrodes at sampling rates up to 9.3 kHz. Published by Elsevier B.V.

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

Network Oscillations Drive Correlated Spiking of ON and OFF Ganglion Cells in the rd1 Mouse Model of Retinal Degeneration

PubMed Central

Margolis, David J.; Gartland, Andrew J.; Singer, Joshua H.; Detwiler, Peter B.

2014-01-01

Following photoreceptor degeneration, ON and OFF retinal ganglion cells (RGCs) in the rd-1/rd-1 mouse receive rhythmic synaptic input that elicits bursts of action potentials at ∼10 Hz. To characterize the properties of this activity, RGCs were targeted for paired recording and morphological classification as either ON alpha, OFF alpha or non-alpha RGCs using two-photon imaging. Identified cell types exhibited rhythmic spike activity. Cross-correlation of spike trains recorded simultaneously from pairs of RGCs revealed that activity was correlated more strongly between alpha RGCs than between alpha and non-alpha cell pairs. Bursts of action potentials in alpha RGC pairs of the same type, i.e. two ON or two OFF cells, were in phase, while bursts in dissimilar alpha cell types, i.e. an ON and an OFF RGC, were 180 degrees out of phase. This result is consistent with RGC activity being driven by an input that provides correlated excitation to ON cells and inhibition to OFF cells. A2 amacrine cells were investigated as a candidate cellular mechanism and found to display 10 Hz oscillations in membrane voltage and current that persisted in the presence of antagonists of fast synaptic transmission and were eliminated by tetrodotoxin. Results support the conclusion that the rhythmic RGC activity originates in a presynaptic network of electrically coupled cells including A2s via a Na+-channel dependent mechanism. Network activity drives out of phase oscillations in ON and OFF cone bipolar cells, entraining similar frequency fluctuations in RGC spike activity over an area of retina that migrates with changes in the spatial locus of the cellular oscillator. PMID:24489706

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

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

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.

Action Potential Waveform Variability Limits Multi-Unit Separation in Freely Behaving Rats

PubMed Central

Stratton, Peter; Cheung, Allen; Wiles, Janet; Kiyatkin, Eugene; Sah, Pankaj; Windels, François

2012-01-01

Extracellular multi-unit recording is a widely used technique to study spontaneous and evoked neuronal activity in awake behaving animals. These recordings are done using either single-wire or mulitwire electrodes such as tetrodes. In this study we have tested the ability of single-wire electrodes to discriminate activity from multiple neurons under conditions of varying noise and neuronal cell density. Using extracellular single-unit recording, coupled with iontophoresis to drive cell activity across a wide dynamic range, we studied spike waveform variability, and explored systematic differences in single-unit spike waveform within and between brain regions as well as the influence of signal-to-noise ratio (SNR) on the similarity of spike waveforms. We also modelled spike misclassification for a range of cell densities based on neuronal recordings obtained at different SNRs. Modelling predictions were confirmed by classifying spike waveforms from multiple cells with various SNRs using a leading commercial spike-sorting system. Our results show that for single-wire recordings, multiple units can only be reliably distinguished under conditions of high recording SNR (≥4) and low neuronal density (≈20,000/ mm3). Physiological and behavioural changes, as well as technical limitations typical of awake animal preparations, reduce the accuracy of single-channel spike classification, resulting in serious classification errors. For SNR <4, the probability of misclassifying spikes approaches 100% in many cases. Our results suggest that in studies where the SNR is low or neuronal density is high, separation of distinct units needs to be evaluated with great caution. PMID:22719894

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

Application of Savitzky-Golay differentiation filters and Fourier functions to simultaneous determination of cefepime and the co-administered drug, levofloxacin, in spiked human plasma.

PubMed

Abdel-Aziz, Omar; Abdel-Ghany, Maha F; Nagi, Reham; Abdel-Fattah, Laila

2015-03-15

The present work is concerned with simultaneous determination of cefepime (CEF) and the co-administered drug, levofloxacin (LEV), in spiked human plasma by applying a new approach, Savitzky-Golay differentiation filters, and combined trigonometric Fourier functions to their ratio spectra. The different parameters associated with the calculation of Savitzky-Golay and Fourier coefficients were optimized. The proposed methods were validated and applied for determination of the two drugs in laboratory prepared mixtures and spiked human plasma. The results were statistically compared with reported HPLC methods and were found accurate and precise. Copyright © 2014 Elsevier B.V. All rights reserved.

Neural dynamics and information representation in microcircuits of motor cortex.

PubMed

Tsubo, Yasuhiro; Isomura, Yoshikazu; Fukai, Tomoki

2013-01-01

The brain has to analyze and respond to external events that can change rapidly from time to time, suggesting that information processing by the brain may be essentially dynamic rather than static. The dynamical features of neural computation are of significant importance in motor cortex that governs the process of movement generation and learning. In this paper, we discuss these features based primarily on our recent findings on neural dynamics and information coding in the microcircuit of rat motor cortex. In fact, cortical neurons show a variety of dynamical behavior from rhythmic activity in various frequency bands to highly irregular spike firing. Of particular interest are the similarity and dissimilarity of the neuronal response properties in different layers of motor cortex. By conducting electrophysiological recordings in slice preparation, we report the phase response curves (PRCs) of neurons in different cortical layers to demonstrate their layer-dependent synchronization properties. We then study how motor cortex recruits task-related neurons in different layers for voluntary arm movements by simultaneous juxtacellular and multiunit recordings from behaving rats. The results suggest an interesting difference in the spectrum of functional activity between the superficial and deep layers. Furthermore, the task-related activities recorded from various layers exhibited power law distributions of inter-spike intervals (ISIs), in contrast to a general belief that ISIs obey Poisson or Gamma distributions in cortical neurons. We present a theoretical argument that this power law of in vivo neurons may represent the maximization of the entropy of firing rate with limited energy consumption of spike generation. Though further studies are required to fully clarify the functional implications of this coding principle, it may shed new light on information representations by neurons and circuits in motor cortex.

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.

Millisecond-timescale local network coding in the rat primary somatosensory cortex.

PubMed

Eldawlatly, Seif; Oweiss, Karim G

2011-01-01

Correlation among neocortical neurons is thought to play an indispensable role in mediating sensory processing of external stimuli. The role of temporal precision in this correlation has been hypothesized to enhance information flow along sensory pathways. Its role in mediating the integration of information at the output of these pathways, however, remains poorly understood. Here, we examined spike timing correlation between simultaneously recorded layer V neurons within and across columns of the primary somatosensory cortex of anesthetized rats during unilateral whisker stimulation. We used bayesian statistics and information theory to quantify the causal influence between the recorded cells with millisecond precision. For each stimulated whisker, we inferred stable, whisker-specific, dynamic bayesian networks over many repeated trials, with network similarity of 83.3±6% within whisker, compared to only 50.3±18% across whiskers. These networks further provided information about whisker identity that was approximately 6 times higher than what was provided by the latency to first spike and 13 times higher than what was provided by the spike count of individual neurons examined separately. Furthermore, prediction of individual neurons' precise firing conditioned on knowledge of putative pre-synaptic cell firing was 3 times higher than predictions conditioned on stimulus onset alone. Taken together, these results suggest the presence of a temporally precise network coding mechanism that integrates information across neighboring columns within layer V about vibrissa position and whisking kinetics to mediate whisker movement by motor areas innervated by layer V.

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

ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains

PubMed Central

Canova, Carlos; Denker, Michael; Gerstein, George; Helias, Moritz

2016-01-01

With the ability to observe the activity from large numbers of neurons simultaneously using modern recording technologies, the chance to identify sub-networks involved in coordinated processing increases. Sequences of synchronous spike events (SSEs) constitute one type of such coordinated spiking that propagates activity in a temporally precise manner. The synfire chain was proposed as one potential model for such network processing. Previous work introduced a method for visualization of SSEs in massively parallel spike trains, based on an intersection matrix that contains in each entry the degree of overlap of active neurons in two corresponding time bins. Repeated SSEs are reflected in the matrix as diagonal structures of high overlap values. The method as such, however, leaves the task of identifying these diagonal structures to visual inspection rather than to a quantitative analysis. Here we present ASSET (Analysis of Sequences of Synchronous EvenTs), an improved, fully automated method which determines diagonal structures in the intersection matrix by a robust mathematical procedure. The method consists of a sequence of steps that i) assess which entries in the matrix potentially belong to a diagonal structure, ii) cluster these entries into individual diagonal structures and iii) determine the neurons composing the associated SSEs. We employ parallel point processes generated by stochastic simulations as test data to demonstrate the performance of the method under a wide range of realistic scenarios, including different types of non-stationarity of the spiking activity and different correlation structures. Finally, the ability of the method to discover SSEs is demonstrated on complex data from large network simulations with embedded synfire chains. Thus, ASSET represents an effective and efficient tool to analyze massively parallel spike data for temporal sequences of synchronous activity. PMID:27420734

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

Selective fatigue of fast motor units after electrically elicited muscle contractions.

PubMed

Hamada, Taku; Kimura, Tetsuya; Moritani, Toshio

2004-10-01

The aim of the present study was to elucidate the electrophysiological manifestations of selective fast motor unit (MU) activation by electrical stimulation (ES) of knee extensor muscles. In six male subjects, test contraction measurement at 40% maximal voluntary contraction (MVC) was performed before and at every 5 min (5, 10, 15 and 20 min) during 20-min low intensity intermittent exercise of either ES or voluntary contractions (VC) at 10% MVC (5-s isometric contraction and 5-s rest cycles). Both isolated intramuscular MU spikes obtained from three sets of bipolar fine-wire electrodes and surface electromyogram (EMG) were simultaneously recorded and were analyzed by means of a computer-aided intramuscular spike amplitude-frequency analysis and frequency power spectral analysis, respectively. Results indicated that mean MU spike amplitude, particularly those MUs with relatively large amplitude, was significantly reduced while those MUs with small spike amplitude increased their firing rate during the 40% MVC test contraction after the ES. This was accompanied by the increased amplitude of surface EMG (rmsEMG). However, no such significant changes in the intramuscular and surface EMGs were observed after VC. These findings indicated differential MU activation patterns in terms of MU recruitment and rate coding characteristics during ES and VC, respectively. Our data strongly suggest the possibility of "an inverse size principle" of MU recruitment during ES.

Population decoding of motor cortical activity using a generalized linear model with hidden states.

PubMed

Lawhern, Vernon; Wu, Wei; Hatsopoulos, Nicholas; Paninski, Liam

2010-06-15

Generalized linear models (GLMs) have been developed for modeling and decoding population neuronal spiking activity in the motor cortex. These models provide reasonable characterizations between neural activity and motor behavior. However, they lack a description of movement-related terms which are not observed directly in these experiments, such as muscular activation, the subject's level of attention, and other internal or external states. Here we propose to include a multi-dimensional hidden state to address these states in a GLM framework where the spike count at each time is described as a function of the hand state (position, velocity, and acceleration), truncated spike history, and the hidden state. The model can be identified by an Expectation-Maximization algorithm. We tested this new method in two datasets where spikes were simultaneously recorded using a multi-electrode array in the primary motor cortex of two monkeys. It was found that this method significantly improves the model-fitting over the classical GLM, for hidden dimensions varying from 1 to 4. This method also provides more accurate decoding of hand state (reducing the mean square error by up to 29% in some cases), while retaining real-time computational efficiency. These improvements on representation and decoding over the classical GLM model suggest that this new approach could contribute as a useful tool to motor cortical decoding and prosthetic applications. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Population Decoding of Motor Cortical Activity using a Generalized Linear Model with Hidden States

PubMed Central

Lawhern, Vernon; Wu, Wei; Hatsopoulos, Nicholas G.; Paninski, Liam

2010-01-01

Generalized linear models (GLMs) have been developed for modeling and decoding population neuronal spiking activity in the motor cortex. These models provide reasonable characterizations between neural activity and motor behavior. However, they lack a description of movement-related terms which are not observed directly in these experiments, such as muscular activation, the subject's level of attention, and other internal or external states. Here we propose to include a multi-dimensional hidden state to address these states in a GLM framework where the spike count at each time is described as a function of the hand state (position, velocity, and acceleration), truncated spike history, and the hidden state. The model can be identified by an Expectation-Maximization algorithm. We tested this new method in two datasets where spikes were simultaneously recorded using a multi-electrode array in the primary motor cortex of two monkeys. It was found that this method significantly improves the model-fitting over the classical GLM, for hidden dimensions varying from 1 to 4. This method also provides more accurate decoding of hand state (lowering the Mean Square Error by up to 29% in some cases), while retaining real-time computational efficiency. These improvements on representation and decoding over the classical GLM model suggest that this new approach could contribute as a useful tool to motor cortical decoding and prosthetic applications. PMID:20359500

Binaural electric-acoustic interactions recorded from the inferior colliculus of Guinea pigs: the effect of masking observed in the central nucleus of the inferior colliculus.

PubMed

Noh, Heil; Lee, Dong-Hee

2012-09-01

To investigate the electric-acoustic interactions within the inferior colliculus of guinea pigs and to observe how central masking appears in invasive neural recordings of the inferior colliculus (IC). A platinum-iridium wire was inserted to scala tympani through cochleostomy with a depth no greater than 1 mm for intracochlear stimulation of electric pulse train. A 5 mm 100 µm, single-shank, thin-film, penetrating recording probe was inserted perpendicularly to the surface of the IC in the coronal plane at an angle of 30-40° off the parasagittal plane with a depth of 2.0-2.5 mm. The peripheral and central masking effects were compared using electric pulse trains to the left ear and acoustic noise to the left ear (ipsilateral) and to the right ear (contralateral). Binaural acoustic stimuli were presented with different time delays and compared with combined electric and acoustic stimuli. The averaged evoked potentials and total spike numbers were measured using thin-film electrodes inserted into the central nucleus of the IC. Ipsilateral noise had more obvious effects on the electric response than did contralateral noise. Contralateral noise decreased slightly the response amplitude to the electric pulse train stimuli. Immediately after the onset of acoustic noise, the response pattern changed transiently with shorter response intervals. The effects of contralateral noise were evident at the beginning of the continuous noise. The total spike number decreased when the binaural stimuli reached the IC most simultaneously. These results suggest that central masking is quite different from peripheral masking and occurs within the binaural auditory system, and this study showed that the effect of masking could be observed in the IC recording. These effects are more evident and consistent with the psychophysical data from spike number analyses than with the previously reported gross potential data.

Micropower CMOS Integrated Low-Noise Amplification, Filtering, and Digitization of Multimodal Neuropotentials

PubMed Central

Mollazadeh, Mohsen; Murari, Kartikeya; Cauwenberghs, Gert; Thakor, Nitish

2009-01-01

Electrical activity in the brain spans a wide range of spatial and temporal scales, requiring simultaneous recording of multiple modalities of neurophysiological signals in order to capture various aspects of brain state dynamics. Here, we present a 16-channel neural interface integrated circuit fabricated in a 0.5 μm 3M2P CMOS process for selective digital acquisition of biopotentials across the spectrum of neural signal modalities in the brain, ranging from single spike action potentials to local field potentials (LFP), electrocorticograms (ECoG), and electroencephalograms (EEG). Each channel is composed of a tunable bandwidth, fixed gain front-end amplifier and a programmable gain/resolution continuous-time incremental ΔΣ analog-to-digital converter (ADC). A two-stage topology for the front-end voltage amplifier with capacitive feedback offers independent tuning of the amplifier bandpass frequency corners, and attains a noise efficiency factor (NEF) of 2.9 at 8.2 kHz bandwidth for spike recording, and a NEF of 3.2 at 140 Hz bandwidth for EEG recording. The amplifier has a measured midband gain of 39.6 dB, frequency response from 0.2 Hz to 8.2 kHz, and an input-referred noise of 1.94 μVrms while drawing 12.2 μA of current from a 3.3 V supply. The lower and higher cutoff frequencies of the bandpass filter are adjustable from 0.2 to 94 Hz and 140 Hz to 8.2 kHz, respectively. At 10-bit resolution, the ADC has an SNDR of 56 dB while consuming 76 μW power. Time-modulation feedback in the ADC offers programmable digital gain (1–4096) for auto-ranging, further improving the dynamic range and linearity of the ADC. Experimental recordings with the system show spike signals in rat somatosensory cortex as well as alpha EEG activity in a human subject. PMID:20046962

Short- and medium-term plasticity associated with augmenting responses in cortical slabs and spindles in intact cortex of cats in vivo

PubMed Central

Timofeev, Igor; Grenier, François; Bazhenov, Maxim; Houweling, Arthur R; Sejnowski, Terrence J; Steriade, Mircea

2002-01-01

Plastic changes in the synaptic responsiveness of neocortical neurones, which occur after rhythmic stimuli within the frequency range of sleep spindles (10 Hz), were investigated in isolated neocortical slabs and intact cortex of anaesthetized cats by means of single, dual and triple simultaneous intracellular recordings in conjunction with recordings of local field potential responses. In isolated cortical slabs (10 mm long, 6 mm wide and 4–5 mm deep), augmenting responses to pulse-trains at 10 Hz (responses with growing amplitudes from the second stimulus in a train) were elicited only by relatively high-intensity stimuli. At low intensities, responses were decremental. The largest augmenting responses were evoked in neurones located close to the stimulation site. Quantitative analyses of the number of action potentials and the amplitude and area of depolarization during augmenting responses in a population of neurones recorded from slabs showed that the most dramatic increases in the number of spikes with successive stimuli, and the greatest increase in depolarization amplitude, were found in conventional fast-spiking (FS) neurones. The largest increase in the area of depolarization was found in regular-spiking (RS) neurones. Dual intracellular recordings from a pair of FS and RS neurones in the slab revealed more action potentials in the FS neurone during augmenting responses and a significant increase in the depolarization area of the RS neurone that was dependent on the firing of the FS neurone. Self-sustained seizures could occur in the slab after rhythmic stimuli at 10 Hz. In the intact cortex, repeated sequences of stimuli generating augmenting responses or spontaneous spindles could induce an increased synaptic responsiveness to single stimuli, which lasted for several minutes. A similar time course of increased responsiveness was obtained with induction of cellular plasticity. These data suggest that augmenting responses elicited by stimulation, as well as spontaneously occurring spindles, may induce short- and medium-term plasticity of neuronal responses. PMID:12122155

Fully integrated silicon probes for high-density recording of neural activity.

PubMed

Jun, James J; Steinmetz, Nicholas A; Siegle, Joshua H; Denman, Daniel J; Bauza, Marius; Barbarits, Brian; Lee, Albert K; Anastassiou, Costas A; Andrei, Alexandru; Aydın, Çağatay; Barbic, Mladen; Blanche, Timothy J; Bonin, Vincent; Couto, João; Dutta, Barundeb; Gratiy, Sergey L; Gutnisky, Diego A; Häusser, Michael; Karsh, Bill; Ledochowitsch, Peter; Lopez, Carolina Mora; Mitelut, Catalin; Musa, Silke; Okun, Michael; Pachitariu, Marius; Putzeys, Jan; Rich, P Dylan; Rossant, Cyrille; Sun, Wei-Lung; Svoboda, Karel; Carandini, Matteo; Harris, Kenneth D; Koch, Christof; O'Keefe, John; Harris, Timothy D

2017-11-08

Sensory, motor and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution, but from only a few dozen neurons per shank. Optical Ca 2+ imaging offers more coverage but lacks the temporal resolution needed to distinguish individual spikes reliably and does not measure local field potentials. Until now, no technology compatible with use in unrestrained animals has combined high spatiotemporal resolution with large volume coverage. Here we design, fabricate and test a new silicon probe known as Neuropixels to meet this need. Each probe has 384 recording channels that can programmably address 960 complementary metal-oxide-semiconductor (CMOS) processing-compatible low-impedance TiN sites that tile a single 10-mm long, 70 × 20-μm cross-section shank. The 6 × 9-mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed and digitized on the base, allowing the direct transmission of noise-free digital data from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were recorded simultaneously from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed large populations of neurons from several brain structures to be recorded in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens a path towards recording of brain-wide neural activity during behaviour.

Fully Integrated Silicon Probes for High-Density Recording of Neural Activity

PubMed Central

Jun, James J.; Steinmetz, Nicholas A.; Siegle, Joshua H.; Denman, Daniel J.; Bauza, Marius; Barbarits, Brian; Lee, Albert K.; Anastassiou, Costas A.; Andrei, Alexandru; Aydın, Çağatay; Barbic, Mladen; Blanche, Timothy J.; Bonin, Vincent; Couto, João; Dutta, Barundeb; Gratiy, Sergey L.; Gutnisky, Diego A.; Häusser, Michael; Karsh, Bill; Ledochowitsch, Peter; Lopez, Carolina Mora; Mitelut, Catalin; Musa, Silke; Okun, Michael; Pachitariu, Marius; Putzeys, Jan; Rich, P. Dylan; Rossant, Cyrille; Sun, Wei-lung; Svoboda, Karel; Carandini, Matteo; Harris, Kenneth D.; Koch, Christof; O'Keefe, John; Harris, Timothy D.

2018-01-01

Summary Paragraph Sensory, motor, and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures1,2. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution but from only a few dozen neurons per shank. Optical Ca2+ imaging3–5 offers more coverage but lacks the temporal resolution to reliably distinguish individual spikes and does not measure local field potentials. To date, no technology compatible with unrestrained animals has combined high spatiotemporal resolution with large volume coverage. To satisfy this need, we designed, fabricated, and tested a new silicon probe called Neuropixels. Each probe has 384 recording channels that can programmably address 960 CMOS processing-compatible low-impedance TiN6 sites that tile a single 10 mm long, 70x20 µm cross section shank. The 6x9 mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed, and digitized on the base, allowing noise-free digital data transmission directly from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were simultaneously recorded from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed recording large populations of neurons from multiple brain structures in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens the path to record brain-wide neural activity during behavior. PMID:29120427

Cortical light scattering during interictal epileptic spikes in frontal lobe epilepsy in children: A fast optical signal and electroencephalographic study.

PubMed

Manoochehri, Mana; Mahmoudzadeh, Mahdi; Bourel-Ponchel, Emilie; Wallois, Fabrice

2017-12-01

Interictal epileptic spikes (IES) represent a signature of the transient synchronous and excessive discharge of a large ensemble of cortical heterogeneous neurons. Epilepsy cannot be reduced to a hypersynchronous activation of neurons whose functioning is impaired, resulting on electroencephalogram (EEG) in epileptic seizures or IES. The complex pathophysiological mechanisms require a global approach to the interactions between neural synaptic and nonsynaptic, vascular, and metabolic systems. In the present study, we focused on the interaction between synaptic and nonsynaptic mechanisms through the simultaneous noninvasive multimodal multiscale recording of high-density EEG (HD-EEG; synaptic) and fast optical signal (FOS; nonsynaptic), which evaluate rapid changes in light scattering related to changes in membrane configuration occurring during neuronal activation of IES. To evaluate changes in light scattering occurring around IES, three children with frontal IES were simultaneously recorded with HD-EEG and FOS. To evaluate change in synchronization, time-frequency representation analysis of the HD-EEG was performed simultaneously around the IES. To independently evaluate our multimodal method, a control experiment with somatosensory stimuli was designed and applied to five healthy volunteers. Alternating increase-decrease-increase in optical signals occurred 200 ms before to 180 ms after the IES peak. These changes started before any changes in EEG signal. In addition, time-frequency domain EEG analysis revealed alternating decrease-increase-decrease in the EEG spectral power concomitantly with changes in the optical signal during IES. These results suggest a relationship between (de)synchronization and neuronal volume changes in frontal lobe epilepsy during IES. These changes in the neuronal environment around IES in frontal lobe epilepsy observed in children, as they have been in rats, raise new questions about the synaptic/nonsynaptic mechanisms that propel the neurons to hypersynchronization, as occurs during IES. We further demonstrate that this noninvasive multiscale multimodal approach is suitable for studying the pathophysiology of the IES in patients. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

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

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.

Parallel multipoint recording of aligned and cultured neurons on micro channel array toward cellular network analysis.

PubMed

Tonomura, Wataru; Moriguchi, Hiroyuki; Jimbo, Yasuhiko; Konishi, Satoshi

2010-08-01

This paper describes an advanced Micro Channel Array (MCA) for recording electrophysiological signals of neuronal networks at multiple points simultaneously. The developed MCA is designed for neuronal network analysis which has been studied by the co-authors using the Micro Electrode Arrays (MEA) system, and employs the principles of extracellular recordings. A prerequisite for extracellular recordings with good signal-to-noise ratio is a tight contact between cells and electrodes. The MCA described herein has the following advantages. The electrodes integrated around individual micro channels are electrically isolated to enable parallel multipoint recording. Reliable clamping of a targeted cell through micro channels is expected to improve the cellular selectivity and the attachment between the cell and the electrode toward steady electrophysiological recordings. We cultured hippocampal neurons on the developed MCA. As a result, the spontaneous and evoked spike potentials could be recorded by sucking and clamping the cells at multiple points. In this paper, we describe the design and fabrication of the MCA and the successful electrophysiological recordings leading to the development of an effective cellular network analysis device.

Accuracy assessment of a surface electromyogram decomposition system in human first dorsal interosseus muscle

NASA Astrophysics Data System (ADS)

Hu, Xiaogang; Rymer, William Z.; Suresh, Nina L.

2014-04-01

Objective. The aim of this study is to assess the accuracy of a surface electromyogram (sEMG) motor unit (MU) decomposition algorithm during low levels of muscle contraction. Approach. A two-source method was used to verify the accuracy of the sEMG decomposition system, by utilizing simultaneous intramuscular and surface EMG recordings from the human first dorsal interosseous muscle recorded during isometric trapezoidal force contractions. Spike trains from each recording type were decomposed independently utilizing two different algorithms, EMGlab and dEMG decomposition algorithms. The degree of agreement of the decomposed spike timings was assessed for three different segments of the EMG signals, corresponding to specified regions in the force task. A regression analysis was performed to examine whether certain properties of the sEMG and force signal can predict the decomposition accuracy. Main results. The average accuracy of successful decomposition among the 119 MUs that were common to both intramuscular and surface records was approximately 95%, and the accuracy was comparable between the different segments of the sEMG signals (i.e., force ramp-up versus steady state force versus combined). The regression function between the accuracy and properties of sEMG and force signals revealed that the signal-to-noise ratio of the action potential and stability in the action potential records were significant predictors of the surface decomposition accuracy. Significance. The outcomes of our study confirm the accuracy of the sEMG decomposition algorithm during low muscle contraction levels and provide confidence in the overall validity of the surface dEMG decomposition algorithm.

Mapping slow waves and spikes in chronically instrumented conscious dogs: implantation techniques and recordings.

PubMed

Ver Donck, L; Lammers, W J E P; Moreaux, B; Smets, D; Voeten, J; Vekemans, J; Schuurkes, J A J; Coulie, B

2006-03-01

Myoelectric recordings from the intestines in conscious animals have been limited to a few electrode sites with relatively large inter-electrode distances. The aim of this project was to increase the number of recording sites to allow high-resolution reconstruction of the propagation of myoelectrical signals. Sets of six unipolar electrodes, positioned in a 3x2 array, were constructed. A silver ring close to each set served as the reference electrodes. Inter-electrode distances varied from 4 to 8 mm. Electrode sets, to a maximum of 4, were implanted in various configurations allowing recording from 24 sites simultaneously. Four sets of 6 electrodes each were implanted successfully in 11 female Beagles. Implantation sites evaluated were the upper small intestine (n=10), the lower small intestine (n=4) and the stomach (n=3). The implants remained functional for 7.2 months (median; range 1.4-27.3 months). Recorded signals showed slow waves at regular intervals and spike potentials. In addition, when the sets were positioned close together, it was possible to re-construct the propagation of individual slow waves, to determine their direction of propagation and to calculate their propagation velocity. No signs or symptoms of interference with normal GI-function were observed in the tested animals. With this approach, it is possible to implant 24 extracellular electrodes on the serosal surface of the intestines without interfering with its normal physiology. This approach makes it possible to study the electrical activities of the GI system at high resolution in vivo in the conscious animal.

Short-Term Depression of Axonal Spikes at the Mouse Hippocampal Mossy Fibers and Sodium Channel-Dependent Modulation

PubMed Central

Ohura, Shunsuke

2018-01-01

Axonal spike is an important upstream process of transmitter release, which directly impacts on release probability from the presynaptic terminals. Despite the functional significance, possible activity-dependent modulation of axonal spikes has not been studied extensively, partly due to inaccessibility of the small structures of axons for electrophysiological recordings. In this study, we tested the possibility of use-dependent changes in axonal spikes at the hippocampal mossy fibers, where direct recordings from the axon terminals are readily feasible. Hippocampal slices were made from mice of either sex, and loose-patch clamp recordings were obtained from the visually identified giant mossy fiber boutons located in the stratum lucidum of the CA3 region. Stimulation of the granule cell layer of the dentate gyrus elicited axonal spikes at the single bouton which occurred in all or none fashion. Unexpected from the digital nature of spike signaling, the peak amplitude of the second spikes in response to paired stimuli at a 50-ms interval was slightly but reproducibly smaller than the first spikes. Repetitive stimuli at 20 or 100 Hz also caused progressive use-dependent depression during the train. Notably, veratridine, an inhibitor of inactivation of sodium channels, significantly accelerated the depression with minimal effect on the initial spikes. These results suggest that sodium channels contribute to use-dependent depression of axonal spikes at the hippocampal mossy fibers, possibly by shaping the afterdepolarization (ADP) following axonal spikes. Prolonged depolarization during ADP may inactivate a fraction of sodium channels and thereby suppresses the subsequent spikes at the hippocampal mossy fibers. PMID:29468192

Axonal propagation of simple and complex spikes in cerebellar Purkinje neurons.

PubMed

Khaliq, Zayd M; Raman, Indira M

2005-01-12

In cerebellar Purkinje neurons, the reliability of propagation of high-frequency simple spikes and spikelets of complex spikes is likely to regulate inhibition of Purkinje target neurons. To test the extent to which a one-to-one correspondence exists between somatic and axonal spikes, we made dual somatic and axonal recordings from Purkinje neurons in mouse cerebellar slices. Somatic action potentials were recorded with a whole-cell pipette, and the corresponding axonal signals were recorded extracellularly with a loose-patch pipette. Propagation of spontaneous and evoked simple spikes was highly reliable. At somatic firing rates of approximately 200 spikes/sec, <10% of spikes failed to propagate, with failures becoming more frequent only at maximal somatic firing rates (approximately 260 spikes/sec). Complex spikes were elicited by climbing fiber stimulation, and their somatic waveforms were modulated by tonic current injection, as well as by paired stimulation to depress the underlying EPSCs. Across conditions, the mean number of propagating action potentials remained just above two spikes per climbing fiber stimulation, but the instantaneous frequency of the propagating spikes changed, from approximately 375 Hz during somatic hyperpolarizations that silenced spontaneous firing to approximately 150 Hz during spontaneous activity. The probability of propagation of individual spikelets could be described quantitatively as a saturating function of spikelet amplitude, rate of rise, or preceding interspike interval. The results suggest that ion channels of Purkinje axons are adapted to produce extremely short refractory periods and that brief bursts of forward-propagating action potentials generated by complex spikes may contribute transiently to inhibition of postsynaptic neurons.

A cortical integrate-and-fire neural network model for blind decoding of visual prosthetic stimulation.

PubMed

Eiber, Calvin D; Morley, John W; Lovell, Nigel H; Suaning, Gregg J

2014-01-01

We present a computational model of the optic pathway which has been adapted to simulate cortical responses to visual-prosthetic stimulation. This model reproduces the statistically observed distributions of spikes for cortical recordings of sham and maximum-intensity stimuli, while simultaneously generating cellular receptive fields consistent with those observed using traditional visual neuroscience methods. By inverting this model to generate candidate phosphenes which could generate the responses observed to novel stimulation strategies, we hope to aid the development of said strategies in-vivo before being deployed in clinical settings.

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

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'.

PubMed

Swindale, Nicholas V; Mitelut, Catalin; Murphy, Timothy H; Spacek, Martin A

2017-02-10

Few stand-alone software applications are available for sorting spikes from recordings made with multi-electrode arrays. Ideally, an application should be user friendly with a graphical user interface, able to read data files in a variety of formats, and provide users with a flexible set of tools giving them the ability to detect and sort extracellular voltage waveforms from different units with some degree of reliability. Previously published spike sorting methods are now available in a software program, SpikeSorter, intended to provide electrophysiologists with a complete set of tools for sorting, starting from raw recorded data file and ending with the export of sorted spikes times. Procedures are automated to the extent this is currently possible. The article explains and illustrates the use of the program. A representative data file is opened, extracellular traces are filtered, events are detected and then clustered. A number of problems that commonly occur during sorting are illustrated, including the artefactual over-splitting of units due to the tendency of some units to fire spikes in pairs where the second spike is significantly smaller than the first, and over-splitting caused by slow variation in spike height over time encountered in some units. The accuracy of SpikeSorter's performance has been tested with surrogate ground truth data and found to be comparable to that of other algorithms in current development.

Risk of punishment influences discrete and coordinated encoding of reward-guided actions by prefrontal cortex and VTA neurons

PubMed Central

Park, Junchol

2017-01-01

Actions motivated by rewards are often associated with risk of punishment. Little is known about the neural representation of punishment risk during reward-seeking behavior. We modeled this circumstance in rats by designing a task where actions were consistently rewarded but probabilistically punished. Spike activity and local field potentials were recorded during task performance simultaneously from VTA and mPFC, two reciprocally connected regions implicated in reward-seeking and aversive behaviors. At the single unit level, we found that ensembles of putative dopamine and non-dopamine VTA neurons and mPFC neurons encode the relationship between action and punishment. At the network level, we found that coherent theta oscillations synchronize VTA and mPFC in a bottom-up direction, effectively phase-modulating the neuronal spike activity in the two regions during punishment-free actions. This synchrony declined as a function of punishment probability, suggesting that during reward-seeking actions, risk of punishment diminishes VTA-driven neural synchrony between the two regions. PMID:29058673

Multiplexing of Motor Information in the Discharge of a Collision Detecting Neuron during Escape Behaviors

PubMed Central

Fotowat, Haleh; Harrison, Reid R; Gabbiani, Fabrizio

2010-01-01

Locusts possess an identified neuron, the descending contralateral movement detector (DCMD), conveying visual information about impending collision from the brain to thoracic motor centers. We built a telemetry system to simultaneously record, in freely behaving animals, the activity of the DCMD and of motoneurons involved in jump execution. Co-contraction of antagonistic leg muscles, a required preparatory phase, was triggered after the DCMD firing rate crossed a threshold. Thereafter, the number of DCMD spikes predicted precisely motoneuron activity and jump occurrence. Additionally, the time of DCMD peak firing rate predicted that of jump. Ablation experiments suggest that the DCMD, together with a nearly identical ipsilateral descending neuron, is responsible for the timely execution of the escape. Thus, three distinct features that are multiplexed in a single neuron’s sensory response to impending collision – firing rate threshold, peak firing time, and spike count – likely control three distinct motor aspects of escape behaviors. PMID:21220105

A closed-loop compressive-sensing-based neural recording system.

PubMed

Zhang, Jie; Mitra, Srinjoy; Suo, Yuanming; Cheng, Andrew; Xiong, Tao; Michon, Frederic; Welkenhuysen, Marleen; Kloosterman, Fabian; Chin, Peter S; Hsiao, Steven; Tran, Trac D; Yazicioglu, Firat; Etienne-Cummings, Ralph

2015-06-01

This paper describes a low power closed-loop compressive sensing (CS) based neural recording system. This system provides an efficient method to reduce data transmission bandwidth for implantable neural recording devices. By doing so, this technique reduces a majority of system power consumption which is dissipated at data readout interface. The design of the system is scalable and is a viable option for large scale integration of electrodes or recording sites onto a single device. The entire system consists of an application-specific integrated circuit (ASIC) with 4 recording readout channels with CS circuits, a real time off-chip CS recovery block and a recovery quality evaluation block that provides a closed feedback to adaptively adjust compression rate. Since CS performance is strongly signal dependent, the ASIC has been tested in vivo and with standard public neural databases. Implemented using efficient digital circuit, this system is able to achieve >10 times data compression on the entire neural spike band (500-6KHz) while consuming only 0.83uW (0.53 V voltage supply) additional digital power per electrode. When only the spikes are desired, the system is able to further compress the detected spikes by around 16 times. Unlike other similar systems, the characteristic spikes and inter-spike data can both be recovered which guarantes a >95% spike classification success rate. The compression circuit occupied 0.11mm(2)/electrode in a 180nm CMOS process. The complete signal processing circuit consumes <16uW/electrode. Power and area efficiency demonstrated by the system make it an ideal candidate for integration into large recording arrays containing thousands of electrode. Closed-loop recording and reconstruction performance evaluation further improves the robustness of the compression method, thus making the system more practical for long term recording.

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.

Detection of dependence patterns with delay.

PubMed

Chevallier, Julien; Laloë, Thomas

2015-11-01

The Unitary Events (UE) method is a popular and efficient method used this last decade to detect dependence patterns of joint spike activity among simultaneously recorded neurons. The first introduced method is based on binned coincidence count (Grün, 1996) and can be applied on two or more simultaneously recorded neurons. Among the improvements of the methods, a transposition to the continuous framework has recently been proposed by Muiño and Borgelt (2014) and fully investigated by Tuleau-Malot et al. (2014) for two neurons. The goal of the present paper is to extend this study to more than two neurons. The main result is the determination of the limit distribution of the coincidence count. This leads to the construction of an independence test between L≥2 neurons. Finally, we propose a multiple test procedure via a Benjamini and Hochberg approach (Benjamini and Hochberg, 1995). All the theoretical results are illustrated by a simulation study, and compared to the UE method proposed by Grün et al. (2002). Furthermore our method is applied on real data. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

When the Ostrich-Algorithm Fails: Blanking Method Affects Spike Train Statistics.

PubMed

Joseph, Kevin; Mottaghi, Soheil; Christ, Olaf; Feuerstein, Thomas J; Hofmann, Ulrich G

2018-01-01

Modern electroceuticals are bound to employ the usage of electrical high frequency (130-180 Hz) stimulation carried out under closed loop control, most prominent in the case of movement disorders. However, particular challenges are faced when electrical recordings of neuronal tissue are carried out during high frequency electrical stimulation, both in-vivo and in-vitro . This stimulation produces undesired artifacts and can render the recorded signal only partially useful. The extent of these artifacts is often reduced by temporarily grounding the recording input during stimulation pulses. In the following study, we quantify the effects of this method, "blanking," on the spike count and spike train statistics. Starting from a theoretical standpoint, we calculate a loss in the absolute number of action potentials, depending on: width of the blanking window, frequency of stimulation, and intrinsic neuronal activity. These calculations were then corroborated by actual high signal to noise ratio (SNR) single cell recordings. We state that, for clinically relevant frequencies of 130 Hz (used for movement disorders) and realistic blanking windows of 2 ms, up to 27% of actual existing spikes are lost. We strongly advice cautioned use of the blanking method when spike rate quantification is attempted. Blanking (artifact removal by temporarily grounding input), depending on recording parameters, can lead to significant spike loss. Very careful use of blanking circuits is advised.

When the Ostrich-Algorithm Fails: Blanking Method Affects Spike Train Statistics

PubMed Central

Joseph, Kevin; Mottaghi, Soheil; Christ, Olaf; Feuerstein, Thomas J.; Hofmann, Ulrich G.

2018-01-01

Modern electroceuticals are bound to employ the usage of electrical high frequency (130–180 Hz) stimulation carried out under closed loop control, most prominent in the case of movement disorders. However, particular challenges are faced when electrical recordings of neuronal tissue are carried out during high frequency electrical stimulation, both in-vivo and in-vitro. This stimulation produces undesired artifacts and can render the recorded signal only partially useful. The extent of these artifacts is often reduced by temporarily grounding the recording input during stimulation pulses. In the following study, we quantify the effects of this method, “blanking,” on the spike count and spike train statistics. Starting from a theoretical standpoint, we calculate a loss in the absolute number of action potentials, depending on: width of the blanking window, frequency of stimulation, and intrinsic neuronal activity. These calculations were then corroborated by actual high signal to noise ratio (SNR) single cell recordings. We state that, for clinically relevant frequencies of 130 Hz (used for movement disorders) and realistic blanking windows of 2 ms, up to 27% of actual existing spikes are lost. We strongly advice cautioned use of the blanking method when spike rate quantification is attempted. Impact statement Blanking (artifact removal by temporarily grounding input), depending on recording parameters, can lead to significant spike loss. Very careful use of blanking circuits is advised. PMID:29780301

BIOLOGICAL RESPONSE TO VARIATION OF ACID-VOLATILE SULFIDES AND METALS IN FIELD-EXPOSED SPIKED SEDIMENTS

EPA Science Inventory

Vertical and temporal variations of acid-volatile sulfides (AVS) and simultaneously extracted metals (SEM) in sediment can control biological impacts of metals. To assess the significance of these variations in field sediments, sediments spiked with cadmium, copper, lead, nickel ...

Brain plasticity and functionality explored by nonlinear optical microscopy

NASA Astrophysics Data System (ADS)

Sacconi, L.; Allegra, L.; Buffelli, M.; Cesare, P.; D'Angelo, E.; Gandolfi, D.; Grasselli, G.; Lotti, J.; Mapelli, J.; Strata, P.; Pavone, F. S.

2010-02-01

In combination with fluorescent protein (XFP) expression techniques, two-photon microscopy has become an indispensable tool to image cortical plasticity in living mice. In parallel to its application in imaging, multi-photon absorption has also been used as a tool for the dissection of single neurites with submicrometric precision without causing any visible collateral damage to the surrounding neuronal structures. In this work, multi-photon nanosurgery is applied to dissect single climbing fibers expressing GFP in the cerebellar cortex. The morphological consequences are then characterized with time lapse 3-dimensional two-photon imaging over a period of minutes to days after the procedure. Preliminary investigations show that the laser induced fiber dissection recalls a regenerative process in the fiber itself over a period of days. These results show the possibility of this innovative technique to investigate regenerative processes in adult brain. In parallel with imaging and manipulation technique, non-linear microscopy offers the opportunity to optically record electrical activity in intact neuronal networks. In this work, we combined the advantages of second-harmonic generation (SHG) with a random access (RA) excitation scheme to realize a new microscope (RASH) capable of optically recording fast membrane potential events occurring in a wide-field of view. The RASH microscope, in combination with bulk loading of tissue with FM4-64 dye, was used to simultaneously record electrical activity from clusters of Purkinje cells in acute cerebellar slices. Complex spikes, both synchronous and asynchronous, were optically recorded simultaneously across a given population of neurons. Spontaneous electrical activity was also monitored simultaneously in pairs of neurons, where action potentials were recorded without averaging across trials. These results show the strength of this technique in describing the temporal dynamics of neuronal assemblies, opening promising perspectives in understanding the computations of neuronal networks.

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

Fast inference of interactions in assemblies of stochastic integrate-and-fire neurons from spike recordings.

PubMed

Monasson, Remi; Cocco, Simona

2011-10-01

We present two Bayesian procedures to infer the interactions and external currents in an assembly of stochastic integrate-and-fire neurons from the recording of their spiking activity. The first procedure is based on the exact calculation of the most likely time courses of the neuron membrane potentials conditioned by the recorded spikes, and is exact for a vanishing noise variance and for an instantaneous synaptic integration. The second procedure takes into account the presence of fluctuations around the most likely time courses of the potentials, and can deal with moderate noise levels. The running time of both procedures is proportional to the number S of spikes multiplied by the squared number N of neurons. The algorithms are validated on synthetic data generated by networks with known couplings and currents. We also reanalyze previously published recordings of the activity of the salamander retina (including from 32 to 40 neurons, and from 65,000 to 170,000 spikes). We study the dependence of the inferred interactions on the membrane leaking time; the differences and similarities with the classical cross-correlation analysis are discussed.

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.

A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data.

PubMed

Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

2017-06-01

Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

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.

Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data

PubMed Central

Pnevmatikakis, Eftychios A.; Soudry, Daniel; Gao, Yuanjun; Machado, Timothy A.; Merel, Josh; Pfau, David; Reardon, Thomas; Mu, Yu; Lacefield, Clay; Yang, Weijian; Ahrens, Misha; Bruno, Randy; Jessell, Thomas M.; Peterka, Darcy S.; Yuste, Rafael; Paninski, Liam

2016-01-01

SUMMARY We present a modular approach for analyzing calcium imaging recordings of large neuronal ensembles. Our goal is to simultaneously identify the locations of the neurons, demix spatially overlapping components, and denoise and deconvolve the spiking activity from the slow dynamics of the calcium indicator. Our approach relies on a constrained nonnegative matrix factorization that expresses the spatiotemporal fluorescence activity as the product of a spatial matrix that encodes the spatial footprint of each neuron in the optical field and a temporal matrix that characterizes the calcium concentration of each neuron over time. This framework is combined with a novel constrained deconvolution approach that extracts estimates of neural activity from fluorescence traces, to create a spatiotemporal processing algorithm that requires minimal parameter tuning. We demonstrate the general applicability of our method by applying it to in vitro and in vivo multineuronal imaging data, whole-brain light-sheet imaging data, and dendritic imaging data. PMID:26774160

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.).

Dynamics of neurons controlling movements of a locust hind leg. III. Extensor tibiae motor neurons.

PubMed

Newland, P L; Kondoh, Y

1997-06-01

Imposed movements of the apodeme of the femoral chordotonal organ (FeCO) of the locust hind leg elicit resistance reflexes in extensor and flexor tibiae motor neurons. The synaptic responses of the fast and slow extensor tibiae motor neurons (FETi and SETi, respectively) and the spike responses of SETi were analyzed with the use of the Wiener kernel white noise method to determine their response properties. The first-order Wiener kernels computed from soma recordings were essentially monophasic, or low passed, indicating that the motor neurons were primarily sensitive to the position of the tibia about the femorotibial joint. The responses of both extensor motor neurons had large nonlinear components. The second-order kernels of the synaptic responses of FETi and SETi had large on-diagonal peaks with two small off-diagonal valleys. That of SETi had an additional elongated valley on the diagonal, which was accompanied by two off-diagonal depolarizing peaks at a cutoff frequency of 58 Hz. These second-order components represent a half-wave rectification of the position-sensitive depolarizing response in FETi and SETi, and a delayed inhibitory input to SETi, indicating that both motor neurons were directionally sensitive. Model predictions of the responses of the motor neurons showed that the first-order (linear) characterization poorly predicted the actual responses of FETi and SETi to FeCO stimulation, whereas the addition of the second-order (nonlinear) term markedly improved the performance of the model. Simultaneous recordings from the soma and a neuropilar process of FETi showed that its synaptic responses to FeCO stimulation were phase delayed by about -30 degrees at 20 Hz, and reduced in amplitude by 30-40% when recorded in the soma. Similar configurations of the first and second-order kernels indicated that the primary process of FETi acted as a low-pass filter. Cross-correlation between a white noise stimulus and a unitized spike discharge of SETi again produced well-defined first- and second-order kernels that showed that the SETi spike response was also dependent on positional inputs. An elongated negative valley on the diagonal, characteristic of the second-order kernel of the synaptic response in SETi, was absent in the kernel from the spike component, suggesting that information is lost in the spike production process. The functional significance of these results is discussed in relation to the behavior of the locust.

Forced normalisation precipitated by lamotrigine.

PubMed

Clemens, Béla

2005-10-01

To report two patients with lamotrigine-induced forced normalization (FN). Evaluation of the patient files, EEG, and video-EEG records, with special reference to the parallel clinical and EEG changes before, during, and after FN. This is the first documented report of lamotrigine-induced FN. The two epileptic patients (one of them was a 10-year-old girl) were successfully treated with lamotrigine. Their seizures ceased and interictal epileptiform events disappeared from the EEG record. Simultaneously, the patients displayed de novo occurrence of psychopathologic manifestations and disturbed behaviour. Reduction of the daily dose of LTG led to disappearance of the psychopathological symptoms and reappearance of the spikes but not the seizures. Lamotrigine may precipitate FN in adults and children. Analysis of the cases showed that lamotrigine-induced FN is a dose-dependent phenomenon and can be treated by reduction of the daily dose of the drug.

A stationary wavelet transform and a time-frequency based spike detection algorithm for extracellular recorded data

NASA Astrophysics Data System (ADS)

Lieb, Florian; Stark, Hans-Georg; Thielemann, Christiane

2017-06-01

Objective. Spike detection from extracellular recordings is a crucial preprocessing step when analyzing neuronal activity. The decision whether a specific part of the signal is a spike or not is important for any kind of other subsequent preprocessing steps, like spike sorting or burst detection in order to reduce the classification of erroneously identified spikes. Many spike detection algorithms have already been suggested, all working reasonably well whenever the signal-to-noise ratio is large enough. When the noise level is high, however, these algorithms have a poor performance. Approach. In this paper we present two new spike detection algorithms. The first is based on a stationary wavelet energy operator and the second is based on the time-frequency representation of spikes. Both algorithms are more reliable than all of the most commonly used methods. Main results. The performance of the algorithms is confirmed by using simulated data, resembling original data recorded from cortical neurons with multielectrode arrays. In order to demonstrate that the performance of the algorithms is not restricted to only one specific set of data, we also verify the performance using a simulated publicly available data set. We show that both proposed algorithms have the best performance under all tested methods, regardless of the signal-to-noise ratio in both data sets. Significance. This contribution will redound to the benefit of electrophysiological investigations of human cells. Especially the spatial and temporal analysis of neural network communications is improved by using the proposed spike detection algorithms.

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

Principal components of hand kinematics and neurophysiological signals in motor cortex during reach to grasp movements

PubMed Central

Aggarwal, Vikram; Thakor, Nitish V.; Schieber, Marc H.

2014-01-01

A few kinematic synergies identified by principal component analysis (PCA) account for most of the variance in the coordinated joint rotations of the fingers and wrist used for a wide variety of hand movements. To examine the possibility that motor cortex might control the hand through such synergies, we collected simultaneous kinematic and neurophysiological data from monkeys performing a reach-to-grasp task. We used PCA, jPCA and isomap to extract kinematic synergies from 18 joint angles in the fingers and wrist and analyzed the relationships of both single-unit and multiunit spike recordings, as well as local field potentials (LFPs), to these synergies. For most spike recordings, the maximal absolute cross-correlations of firing rates were somewhat stronger with an individual joint angle than with any principal component (PC), any jPC or any isomap dimension. In decoding analyses, where spikes and LFP power in the 100- to 170-Hz band each provided better decoding than other LFP-based signals, the first PC was decoded as well as the best decoded joint angle. But the remaining PCs and jPCs were predicted with lower accuracy than individual joint angles. Although PCs, jPCs or isomap dimensions might provide a more parsimonious description of kinematics, our findings indicate that the kinematic synergies identified with these techniques are not represented in motor cortex more strongly than the original joint angles. We suggest that the motor cortex might act to sculpt the synergies generated by subcortical centers, superimposing an ability to individuate finger movements and adapt the hand to grasp a wide variety of objects. PMID:24990564

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

Minimum Requirements for Accurate and Efficient Real-Time On-Chip Spike Sorting

PubMed Central

Navajas, Joaquin; Barsakcioglu, Deren Y.; Eftekhar, Amir; Jackson, Andrew; Constandinou, Timothy G.; Quiroga, Rodrigo Quian

2014-01-01

Background Extracellular recordings are performed by inserting electrodes in the brain, relaying the signals to external power-demanding devices, where spikes are detected and sorted in order to identify the firing activity of different putative neurons. A main caveat of these recordings is the necessity of wires passing through the scalp and skin in order to connect intracortical electrodes to external amplifiers. The aim of this paper is to evaluate the feasibility of an implantable platform (i.e. a chip) with the capability to wirelessly transmit the neural signals and perform real-time on-site spike sorting. New Method We computationally modelled a two-stage implementation for online, robust, and efficient spike sorting. In the first stage, spikes are detected on-chip and streamed to an external computer where mean templates are created and sent back to the chip. In the second stage, spikes are sorted in real-time through template matching. Results We evaluated this procedure using realistic simulations of extracellular recordings and describe a set of specifications that optimise performance while keeping to a minimum the signal requirements and the complexity of the calculations. Comparison with Existing Methods A key bottleneck for the development of long-term BMIs is to find an inexpensive method for real-time spike sorting. Here, we simulated a solution to this problem that uses both offline and online processing of the data. Conclusions Hardware implementations of this method therefore enable low-power long-term wireless transmission of multiple site extracellular recordings, with application to wireless BMIs or closed-loop stimulation designs. PMID:24769170

Information recall using relative spike timing in a spiking neural network.

PubMed

Sterne, Philip

2012-08-01

We present a neural network that is capable of completing and correcting a spiking pattern given only a partial, noisy version. It operates in continuous time and represents information using the relative timing of individual spikes. The network is capable of correcting and recalling multiple patterns simultaneously. We analyze the network's performance in terms of information recall. We explore two measures of the capacity of the network: one that values the accurate recall of individual spike times and another that values only the presence or absence of complete patterns. Both measures of information are found to scale linearly in both the number of neurons and the period of the patterns, suggesting these are natural measures of network information. We show a smooth transition from encodings that provide precise spike times to flexible encodings that can encode many scenes. This makes it plausible that many diverse tasks could be learned with such an encoding.

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

With or without spikes: localization of focal epileptic activity by simultaneous electroencephalography and functional magnetic resonance imaging

PubMed Central

Grouiller, Frédéric; Thornton, Rachel C.; Groening, Kristina; Spinelli, Laurent; Duncan, John S.; Schaller, Karl; Siniatchkin, Michael; Lemieux, Louis; Seeck, Margitta; Michel, Christoph M.

2011-01-01

In patients with medically refractory focal epilepsy who are candidates for epilepsy surgery, concordant non-invasive neuroimaging data are useful to guide invasive electroencephalographic recordings or surgical resection. Simultaneous electroencephalography and functional magnetic resonance imaging recordings can reveal regions of haemodynamic fluctuations related to epileptic activity and help localize its generators. However, many of these studies (40–70%) remain inconclusive, principally due to the absence of interictal epileptiform discharges during simultaneous recordings, or lack of haemodynamic changes correlated to interictal epileptiform discharges. We investigated whether the presence of epilepsy-specific voltage maps on scalp electroencephalography correlated with haemodynamic changes and could help localize the epileptic focus. In 23 patients with focal epilepsy, we built epilepsy-specific electroencephalographic voltage maps using averaged interictal epileptiform discharges recorded during long-term clinical monitoring outside the scanner and computed the correlation of this map with the electroencephalographic recordings in the scanner for each time frame. The time course of this correlation coefficient was used as a regressor for functional magnetic resonance imaging analysis to map haemodynamic changes related to these epilepsy-specific maps (topography-related haemodynamic changes). The method was first validated in five patients with significant haemodynamic changes correlated to interictal epileptiform discharges on conventional analysis. We then applied the method to 18 patients who had inconclusive simultaneous electroencephalography and functional magnetic resonance imaging studies due to the absence of interictal epileptiform discharges or absence of significant correlated haemodynamic changes. The concordance of the results with subsequent intracranial electroencephalography and/or resection area in patients who were seizure free after surgery was assessed. In the validation group, haemodynamic changes correlated to voltage maps were similar to those obtained with conventional analysis in 5/5 patients. In 14/18 patients (78%) with previously inconclusive studies, scalp maps related to epileptic activity had haemodynamic correlates even when no interictal epileptiform discharges were detected during simultaneous recordings. Haemodynamic changes correlated to voltage maps were spatially concordant with intracranial electroencephalography or with the resection area. We found better concordance in patients with lateral temporal and extratemporal neocortical epilepsy compared to medial/polar temporal lobe epilepsy, probably due to the fact that electroencephalographic voltage maps specific to lateral temporal and extratemporal epileptic activity are more dissimilar to maps of physiological activity. Our approach significantly increases the yield of simultaneous electroencephalography and functional magnetic resonance imaging to localize the epileptic focus non-invasively, allowing better targeting for surgical resection or implantation of intracranial electrode arrays. PMID:21752790

A Novel and Simple Spike Sorting Implementation.

PubMed

Petrantonakis, Panagiotis C; Poirazi, Panayiota

2017-04-01

Monitoring the activity of multiple, individual neurons that fire spikes in the vicinity of an electrode, namely perform a Spike Sorting (SS) procedure, comprises one of the most important tools for contemporary neuroscience in order to reverse-engineer the brain. As recording electrodes' technology rabidly evolves by integrating thousands of electrodes in a confined spatial setting, the algorithms that are used to monitor individual neurons from recorded signals have to become even more reliable and computationally efficient. In this work, we propose a novel framework of the SS approach in which a single-step processing of the raw (unfiltered) extracellular signal is sufficient for both the detection and sorting of the activity of individual neurons. Despite its simplicity, the proposed approach exhibits comparable performance with state-of-the-art approaches, especially for spike detection in noisy signals, and paves the way for a new family of SS algorithms with the potential for multi-recording, fast, on-chip implementations.

Origins of correlated activity in an olfactory circuit.

PubMed

Kazama, Hokto; Wilson, Rachel I

2009-09-01

Multineuronal recordings often reveal synchronized spikes in different neurons. The manner in which correlated spike timing affects neural codes depends on the statistics of correlations, which in turn reflects the connectivity that gives rise to correlations. However, determining the connectivity of neurons recorded in vivo can be difficult. We investigated the origins of correlated activity in genetically labeled neurons of the Drosophila antennal lobe. Dual recordings showed synchronized spontaneous spikes in projection neurons (PNs) postsynaptic to the same type of olfactory receptor neuron (ORN). Odors increased these correlations. The primary origin of correlations lies in the divergence of each ORN onto every PN in its glomerulus. Reciprocal PN-PN connections make a smaller contribution to correlations and PN spike trains in different glomeruli were only weakly correlated. PN axons from the same glomerulus reconverge in the lateral horn, where pooling redundant signals may allow lateral horn neurons to average out noise that arises independently in these PNs.

Detection of changes of high-frequency activity by statistical time-frequency analysis in epileptic spikes

PubMed Central

Kobayashi, Katsuhiro; Jacobs, Julia; Gotman, Jean

2013-01-01

Objective A novel type of statistical time-frequency analysis was developed to elucidate changes of high-frequency EEG activity associated with epileptic spikes. Methods The method uses the Gabor Transform and detects changes of power in comparison to background activity using t-statistics that are controlled by the false discovery rate (FDR) to correct type I error of multiple testing. The analysis was applied to EEGs recorded at 2000 Hz from three patients with mesial temporal lobe epilepsy. Results Spike-related increase of high-frequency oscillations (HFOs) was clearly shown in the FDR-controlled t-spectra: it was most dramatic in spikes recorded from the hippocampus when the hippocampus was the seizure onset zone (SOZ). Depression of fast activity was observed immediately after the spikes, especially consistently in the discharges from the hippocampal SOZ. It corresponded to the slow wave part in case of spike-and-slow-wave complexes, but it was noted even in spikes without apparent slow waves. In one patient, a gradual increase of power above 200 Hz preceded spikes. Conclusions FDR-controlled t-spectra clearly detected the spike-related changes of HFOs that were unclear in standard power spectra. Significance We developed a promising tool to study the HFOs that may be closely linked to the pathophysiology of epileptogenesis. PMID:19394892

Comparison of Classifier Architectures for Online Neural Spike Sorting.

PubMed

Saeed, Maryam; Khan, Amir Ali; Kamboh, Awais Mehmood

2017-04-01

High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce the data transmission and power requirements, on-chip real-time processing is becoming very popular. However, high computational resources are required for classifiers in on-chip spike-sorters, making scalability a great challenge. In this review paper, we analyze several popular classifiers to propose five new hardware architectures using the off-chip training with on-chip classification approach. These include support vector classification, fuzzy C-means classification, self-organizing maps classification, moving-centroid K-means classification, and Cosine distance classification. The performance of these architectures is analyzed in terms of accuracy and resource requirement. We establish that the neural networks based Self-Organizing Maps classifier offers the most viable solution. A spike sorter based on the Self-Organizing Maps classifier, requires only 7.83% of computational resources of the best-reported spike sorter, hierarchical adaptive means, while offering a 3% better accuracy at 7 dB SNR.

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.

Automatic Fitting of Spiking Neuron Models to Electrophysiological Recordings

PubMed Central

Rossant, Cyrille; Goodman, Dan F. M.; Platkiewicz, Jonathan; Brette, Romain

2010-01-01

Spiking models can accurately predict the spike trains produced by cortical neurons in response to somatically injected currents. Since the specific characteristics of the model depend on the neuron, a computational method is required to fit models to electrophysiological recordings. The fitting procedure can be very time consuming both in terms of computer simulations and in terms of code writing. We present algorithms to fit spiking models to electrophysiological data (time-varying input and spike trains) that can run in parallel on graphics processing units (GPUs). The model fitting library is interfaced with Brian, a neural network simulator in Python. If a GPU is present it uses just-in-time compilation to translate model equations into optimized code. Arbitrary models can then be defined at script level and run on the graphics card. This tool can be used to obtain empirically validated spiking models of neurons in various systems. We demonstrate its use on public data from the INCF Quantitative Single-Neuron Modeling 2009 competition by comparing the performance of a number of neuron spiking models. PMID:20224819

Human Subthalamic Nucleus Theta and Beta Oscillations Entrain Neuronal Firing During Sensorimotor Conflict

PubMed Central

Zavala, Baltazar; Damera, Srikanth; Dong, Jian Wilson; Lungu, Codrin; Brown, Peter; Zaghloul, Kareem A.

2017-01-01

Recent evidence has suggested that prefrontal cortical structures may inhibit impulsive actions during conflict through activation of the subthalamic nucleus (STN). Consistent with this hypothesis, deep brain stimulation to the STN has been associated with altered prefrontal cortical activity and impaired response inhibition. The interactions between oscillatory activity in the STN and its presumably antikinetic neuronal spiking, however, remain poorly understood. Here, we simultaneously recorded intraoperative local field potential and spiking activity from the human STN as participants performed a sensorimotor action selection task involving conflict. We identified several STN neuronal response types that exhibited different temporal dynamics during the task. Some neurons showed early, cue-related firing rate increases that remained elevated longer during high conflict trials, whereas other neurons showed late, movement-related firing rate increases. Notably, the high conflict trials were associated with an entrainment of individual neurons by theta- and beta-band oscillations, both of which have been observed in cortical structures involved in response inhibition. Our data suggest that frequency-specific activity in the beta and theta bands influence STN firing to inhibit impulsivity during conflict. PMID:26494798

Identification of Linear and Nonlinear Sensory Processing Circuits from Spiking Neuron Data.

PubMed

Florescu, Dorian; Coca, Daniel

2018-03-01

Inferring mathematical models of sensory processing systems directly from input-output observations, while making the fewest assumptions about the model equations and the types of measurements available, is still a major issue in computational neuroscience. This letter introduces two new approaches for identifying sensory circuit models consisting of linear and nonlinear filters in series with spiking neuron models, based only on the sampled analog input to the filter and the recorded spike train output of the spiking neuron. For an ideal integrate-and-fire neuron model, the first algorithm can identify the spiking neuron parameters as well as the structure and parameters of an arbitrary nonlinear filter connected to it. The second algorithm can identify the parameters of the more general leaky integrate-and-fire spiking neuron model, as well as the parameters of an arbitrary linear filter connected to it. Numerical studies involving simulated and real experimental recordings are used to demonstrate the applicability and evaluate the performance of the proposed algorithms.

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

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.

Exact distinction of excitatory and inhibitory neurons in neural networks: a study with GFP-GAD67 neurons optically and electrophysiologically recognized on multielectrode arrays

PubMed Central

Becchetti, Andrea; Gullo, Francesca; Bruno, Giuseppe; Dossi, Elena; Lecchi, Marzia; Wanke, Enzo

2012-01-01

Distinguishing excitatory from inhibitory neurons with multielectrode array (MEA) recordings is a serious experimental challenge. The current methods, developed in vitro, mostly rely on spike waveform analysis. These however often display poor resolution and may produce errors caused by the variability of spike amplitudes and neuron shapes. Recent recordings in human brain suggest that the spike waveform features correlate with time-domain statistics such as spiking rate, autocorrelation, and coefficient of variation. However, no precise criteria are available to exactly assign identified units to specific neuronal types, either in vivo or in vitro. To solve this problem, we combined MEA recording with fluorescence imaging of neocortical cultures from mice expressing green fluorescent protein (GFP) in GABAergic cells. In this way, we could sort out “authentic excitatory neurons” (AENs) and “authentic inhibitory neurons” (AINs). We thus characterized 1275 units (from 405 electrodes, n = 10 experiments), based on autocorrelation, burst length, spike number (SN), spiking rate, squared coefficient of variation, and Fano factor (FF) (the ratio between spike-count variance and mean). These metrics differed by about one order of magnitude between AINs and AENs. In particular, the FF turned out to provide a firing code which exactly (no overlap) recognizes excitatory and inhibitory units. The difference in FF between all of the identified AEN and AIN groups was highly significant (p < 10−8, ANOVA post-hoc Tukey test). Our results indicate a statistical metric-based approach to distinguish excitatory from inhibitory neurons independently from the spike width. PMID:22973197

Synchronicity and Rhythmicity of Purkinje Cell Firing during Generalized Spike-and-Wave Discharges in a Natural Mouse Model of Absence Epilepsy

PubMed Central

Kros, Lieke; Lindeman, Sander; Eelkman Rooda, Oscar H. J.; Murugesan, Pavithra; Bina, Lorenzo; Bosman, Laurens W. J.; De Zeeuw, Chris I.; Hoebeek, Freek E.

2017-01-01

Absence epilepsy is characterized by the occurrence of generalized spike and wave discharges (GSWDs) in electrocorticographical (ECoG) recordings representing oscillatory activity in thalamocortical networks. The oscillatory nature of GSWDs has been shown to be reflected in the simple spike activity of cerebellar Purkinje cells and in the activity of their target neurons in the cerebellar nuclei, but it is unclear to what extent complex spike activity is implicated in generalized epilepsy. Purkinje cell complex spike firing is elicited by climbing fiber activation and reflects action potential firing in the inferior olive. Here, we investigated to what extent modulation of complex spike firing is reflected in the temporal patterns of seizures. Extracellular single-unit recordings in awake, head-restrained homozygous tottering mice, which suffer from a mutation in the voltage-gated CaV2.1 calcium channel, revealed that a substantial proportion of Purkinje cells (26%) showed increased complex spike activity and rhythmicity during GSWDs. Moreover, Purkinje cells, recorded either electrophysiologically or by using Ca2+-imaging, showed a significant increase in complex spike synchronicity for both adjacent and remote Purkinje cells during ictal events. These seizure-related changes in firing frequency, rhythmicity and synchronicity were most prominent in the lateral cerebellum, a region known to receive cerebral input via the inferior olive. These data indicate profound and widespread changes in olivary firing that are most likely induced by seizure-related activity changes in the thalamocortical network, thereby highlighting the possibility that olivary neurons can compensate for pathological brain-state changes by dampening oscillations. PMID:29163057

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.

Variable Action Potential Backpropagation during Tonic Firing and Low-Threshold Spike Bursts in Thalamocortical But Not Thalamic Reticular Nucleus Neurons.

PubMed

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

2017-05-24

Backpropagating action potentials (bAPs) are indispensable in dendritic signaling. Conflicting Ca 2+ -imaging data and an absence of dendritic recording data means that the extent of backpropagation in thalamocortical (TC) and thalamic reticular nucleus (TRN) neurons remains unknown. Because TRN neurons signal electrically through dendrodendritic gap junctions and possibly via chemical dendritic GABAergic synapses, as well as classical axonal GABA release, this lack of knowledge is problematic. To address this issue, we made two-photon targeted patch-clamp recordings from rat TC and TRN neuron dendrites to measure bAPs directly. These recordings reveal that "tonic"' and low-threshold-spike (LTS) "burst" APs in both cell types are always recorded first at the soma before backpropagating into the dendrites while undergoing substantial distance-dependent dendritic amplitude attenuation. In TC neurons, bAP attenuation strength varies according to firing mode. During LTS bursts, somatic AP half-width increases progressively with increasing spike number, allowing late-burst spikes to propagate more efficiently into the dendritic tree compared with spikes occurring at burst onset. Tonic spikes have similar somatic half-widths to late burst spikes and undergo similar dendritic attenuation. In contrast, in TRN neurons, AP properties are unchanged between LTS bursts and tonic firing and, as a result, distance-dependent dendritic attenuation remains consistent across different firing modes. Therefore, unlike LTS-associated global electrical and calcium signals, the spatial influence of bAP signaling in TC and TRN neurons is more restricted, with potentially important behavioral-state-dependent consequences for synaptic integration and plasticity in thalamic neurons. SIGNIFICANCE STATEMENT In most neurons, action potentials (APs) initiate in the axosomatic region and propagate into the dendritic tree to provide a retrograde signal that conveys information about the level of cellular output to the locations that receive most input: the dendrites. In thalamocortical and thalamic reticular nucleus neurons, the site of AP generation and the true extent of backpropagation remain unknown. Using patch-clamp recordings, this study measures dendritic propagation of APs directly in these neurons. In either cell type, high-frequency low-threshold spike burst or lower-frequency tonic APs undergo substantial voltage attenuation as they spread into the dendritic tree. Therefore, backpropagating spikes in these cells can only influence signaling in the proximal part of the dendritic tree. Copyright © 2017 Connelly et al.

Maturation of Spontaneous Firing Properties after Hearing Onset in Rat Auditory Nerve Fibers: Spontaneous Rates, Refractoriness, and Interfiber Correlations

PubMed Central

Wu, Jingjing Sherry; Young, Eric D.

2016-01-01

Auditory nerve fibers (ANFs) exhibit a range of spontaneous firing rates (SRs) that are inversely correlated with threshold for sounds. To probe the underlying mechanisms and time course of SR differentiation during cochlear maturation, loose-patch extracellular recordings were made from ANF dendrites using acutely excised rat cochlear preparations of different ages after hearing onset. Diversification of SRs occurred mostly between the second and the third postnatal week. Statistical properties of ANF spike trains showed developmental changes that approach adult-like features in older preparations. Comparison with intracellularly recorded EPSCs revealed that most properties of ANF spike trains derive from the characteristics of presynaptic transmitter release. Pharmacological tests and waveform analysis showed that endogenous firing produces some fraction of ANF spikes, accounting for their unusual properties; the endogenous firing diminishes gradually during maturation. Paired recordings showed that ANFs contacting the same inner hair cell could have different SRs, with no correlation in their spike timing. SIGNIFICANCE STATEMENT The inner hair cell (IHC)/auditory nerve fiber (ANF) synapse is the first synapse of the auditory pathway. Remarkably, each IHC is the sole partner of 10–30 ANFs with a range of spontaneous firing rates (SRs). Low and high SR ANFs respond to sound differently, and both are important for encoding sound information across varying acoustical environments. Here we demonstrate SR diversification after hearing onset by afferent recordings in acutely excised rat cochlear preparations. We describe developmental changes in spike train statistics and endogenous firing in immature ANFs. Dual afferent recordings provide the first direct evidence that fibers with different SRs contact the same IHCs and do not show correlated spike timing at rest. These results lay the groundwork for understanding the differential sensitivity of ANFs to acoustic trauma. PMID:27733610

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

Relationship between focal penicillin spikes and cortical spindles in the cerveau isolé cat.

PubMed

McLachlan, R S; Kaibara, M; Girvin, J P

1983-01-01

Using the unanesthetized, cerveau isolé preparation in the cat, the association between artificially induced penicillin (PCN) spikes and spontaneously occurring electrocorticographic (ECoG) spindles was investigated. Spikes were elicited by surface application of small pledgets of PCN. After the application of PCN, there was a decrease in spindle amplitude but no change in frequency, duration, or spindle wave frequency in the area of the focus. Examination of the times of occurrence of the spikes and spindles disclosed that in the majority of cases, within a few minutes of the initiation of the foci, there was very high simultaneity, usually 100% between the occurrences of these two events. Examination of the times of occurrence of the spikes within the ECoG spindles failed to disclose any compelling evidence which would favor either the hypothesis that spikes "trigger" spindles or the hypothesis that spindles predispose to focal spikes. Thus, whether spikes trigger spindles, or spikes simply occur in a nonspecific manner during the occurrence of the spindle, or whether it is a combination of both these explanations, must remain an open question on the basis of the data available.

Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering

PubMed Central

2012-01-01

Background Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Results Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize: (i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com) using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike sorting algorithms. Conclusions This new software provides neuroscience laboratories with a new tool for fast and robust online classification of single neuron activity. This feature could become crucial in situations when online spike detection from multiple electrodes is paramount, such as in human clinical recordings or in brain-computer interfaces. PMID:22871125

Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering.

PubMed

Oliynyk, Andriy; Bonifazzi, Claudio; Montani, Fernando; Fadiga, Luciano

2012-08-08

Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize: (i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com) using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike sorting algorithms. This new software provides neuroscience laboratories with a new tool for fast and robust online classification of single neuron activity. This feature could become crucial in situations when online spike detection from multiple electrodes is paramount, such as in human clinical recordings or in brain-computer interfaces.

Differential Covariance: A New Class of Methods to Estimate Sparse Connectivity from Neural Recordings

PubMed Central

Lin, Tiger W.; Das, Anup; Krishnan, Giri P.; Bazhenov, Maxim; Sejnowski, Terrence J.

2017-01-01

With our ability to record more neurons simultaneously, making sense of these data is a challenge. Functional connectivity is one popular way to study the relationship of multiple neural signals. Correlation-based methods are a set of currently well-used techniques for functional connectivity estimation. However, due to explaining away and unobserved common inputs (Stevenson, Rebesco, Miller, & Körding, 2008), they produce spurious connections. The general linear model (GLM), which models spike trains as Poisson processes (Okatan, Wilson, & Brown, 2005; Truccolo, Eden, Fellows, Donoghue, & Brown, 2005; Pillow et al., 2008), avoids these confounds. We develop here a new class of methods by using differential signals based on simulated intracellular voltage recordings. It is equivalent to a regularized AR(2) model. We also expand the method to simulated local field potential recordings and calcium imaging. In all of our simulated data, the differential covariance-based methods achieved performance better than or similar to the GLM method and required fewer data samples. This new class of methods provides alternative ways to analyze neural signals. PMID:28777719

Differential Covariance: A New Class of Methods to Estimate Sparse Connectivity from Neural Recordings.

PubMed

Lin, Tiger W; Das, Anup; Krishnan, Giri P; Bazhenov, Maxim; Sejnowski, Terrence J

2017-10-01

With our ability to record more neurons simultaneously, making sense of these data is a challenge. Functional connectivity is one popular way to study the relationship of multiple neural signals. Correlation-based methods are a set of currently well-used techniques for functional connectivity estimation. However, due to explaining away and unobserved common inputs (Stevenson, Rebesco, Miller, & Körding, 2008 ), they produce spurious connections. The general linear model (GLM), which models spike trains as Poisson processes (Okatan, Wilson, & Brown, 2005 ; Truccolo, Eden, Fellows, Donoghue, & Brown, 2005 ; Pillow et al., 2008 ), avoids these confounds. We develop here a new class of methods by using differential signals based on simulated intracellular voltage recordings. It is equivalent to a regularized AR(2) model. We also expand the method to simulated local field potential recordings and calcium imaging. In all of our simulated data, the differential covariance-based methods achieved performance better than or similar to the GLM method and required fewer data samples. This new class of methods provides alternative ways to analyze neural signals.

Klusters, NeuroScope, NDManager: a free software suite for neurophysiological data processing and visualization.

PubMed

Hazan, Lynn; Zugaro, Michaël; Buzsáki, György

2006-09-15

Recent technological advances now allow for simultaneous recording of large populations of anatomically distributed neurons in behaving animals. The free software package described here was designed to help neurophysiologists process and view recorded data in an efficient and user-friendly manner. This package consists of several well-integrated applications, including NeuroScope (http://neuroscope.sourceforce.net), an advanced viewer for electrophysiological and behavioral data with limited editing capabilities, Klusters (http://klusters.sourceforge.net), a graphical cluster cutting application for manual and semi-automatic spike sorting, NDManager (GPL,see http://www.gnu.org/licenses/gpl.html), an experimental parameter and data processing manager. All of these programs are distributed under the GNU General Public License (GPL, see ), which gives its users legal permission to copy, distribute and/or modify the software. Also included are extensive user manuals and sample data, as well as source code and documentation.

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.

How many neurons can we see with current spike sorting algorithms?

PubMed Central

Pedreira, Carlos; Martinez, Juan; Ison, Matias J.; Quian Quiroga, Rodrigo

2012-01-01

Recent studies highlighted the disagreement between the typical number of neurons observed with extracellular recordings and the ones to be expected based on anatomical and physiological considerations. This disagreement has been mainly attributed to the presence of sparsely firing neurons. However, it is also possible that this is due to limitations of the spike sorting algorithms used to process the data. To address this issue, we used realistic simulations of extracellular recordings and found a relatively poor spike sorting performance for simulations containing a large number of neurons. In fact, the number of correctly identified neurons for single-channel recordings showed an asymptotic behavior saturating at about 8–10 units, when up to 20 units were present in the data. This performance was significantly poorer for neurons with low firing rates, as these units were twice more likely to be missed than the ones with high firing rates in simulations containing many neurons. These results uncover one of the main reasons for the relatively low number of neurons found in extracellular recording and also stress the importance of further developments of spike sorting algorithms. PMID:22841630

Fitting neuron models to spike trains.

PubMed

Rossant, Cyrille; Goodman, Dan F M; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K; Brette, Romain

2011-01-01

Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input-output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model.

Decoding Speech With Integrated Hybrid Signals Recorded From the Human Ventral Motor Cortex.

PubMed

Ibayashi, Kenji; Kunii, Naoto; Matsuo, Takeshi; Ishishita, Yohei; Shimada, Seijiro; Kawai, Kensuke; Saito, Nobuhito

2018-01-01

Restoration of speech communication for locked-in patients by means of brain computer interfaces (BCIs) is currently an important area of active research. Among the neural signals obtained from intracranial recordings, single/multi-unit activity (SUA/MUA), local field potential (LFP), and electrocorticography (ECoG) are good candidates for an input signal for BCIs. However, the question of which signal or which combination of the three signal modalities is best suited for decoding speech production remains unverified. In order to record SUA, LFP, and ECoG simultaneously from a highly localized area of human ventral sensorimotor cortex (vSMC), we fabricated an electrode the size of which was 7 by 13 mm containing sparsely arranged microneedle and conventional macro contacts. We determined which signal modality is the most capable of decoding speech production, and tested if the combination of these signals could improve the decoding accuracy of spoken phonemes. Feature vectors were constructed from spike frequency obtained from SUAs and event-related spectral perturbation derived from ECoG and LFP signals, then input to the decoder. The results showed that the decoding accuracy for five spoken vowels was highest when features from multiple signals were combined and optimized for each subject, and reached 59% when averaged across all six subjects. This result suggests that multi-scale signals convey complementary information for speech articulation. The current study demonstrated that simultaneous recording of multi-scale neuronal activities could raise decoding accuracy even though the recording area is limited to a small portion of cortex, which is advantageous for future implementation of speech-assisting BCIs.

Decoding Speech With Integrated Hybrid Signals Recorded From the Human Ventral Motor Cortex

PubMed Central

Ibayashi, Kenji; Kunii, Naoto; Matsuo, Takeshi; Ishishita, Yohei; Shimada, Seijiro; Kawai, Kensuke; Saito, Nobuhito

2018-01-01

Restoration of speech communication for locked-in patients by means of brain computer interfaces (BCIs) is currently an important area of active research. Among the neural signals obtained from intracranial recordings, single/multi-unit activity (SUA/MUA), local field potential (LFP), and electrocorticography (ECoG) are good candidates for an input signal for BCIs. However, the question of which signal or which combination of the three signal modalities is best suited for decoding speech production remains unverified. In order to record SUA, LFP, and ECoG simultaneously from a highly localized area of human ventral sensorimotor cortex (vSMC), we fabricated an electrode the size of which was 7 by 13 mm containing sparsely arranged microneedle and conventional macro contacts. We determined which signal modality is the most capable of decoding speech production, and tested if the combination of these signals could improve the decoding accuracy of spoken phonemes. Feature vectors were constructed from spike frequency obtained from SUAs and event-related spectral perturbation derived from ECoG and LFP signals, then input to the decoder. The results showed that the decoding accuracy for five spoken vowels was highest when features from multiple signals were combined and optimized for each subject, and reached 59% when averaged across all six subjects. This result suggests that multi-scale signals convey complementary information for speech articulation. The current study demonstrated that simultaneous recording of multi-scale neuronal activities could raise decoding accuracy even though the recording area is limited to a small portion of cortex, which is advantageous for future implementation of speech-assisting BCIs. PMID:29674950

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

Reliable Analysis of Single-Unit Recordings from the Human Brain under Noisy Conditions: Tracking Neurons over Hours

PubMed Central

Boström, Jan; Elger, Christian E.; Mormann, Florian

2016-01-01

Recording extracellulary from neurons in the brains of animals in vivo is among the most established experimental techniques in neuroscience, and has recently become feasible in humans. Many interesting scientific questions can be addressed only when extracellular recordings last several hours, and when individual neurons are tracked throughout the entire recording. Such questions regard, for example, neuronal mechanisms of learning and memory consolidation, and the generation of epileptic seizures. Several difficulties have so far limited the use of extracellular multi-hour recordings in neuroscience: Datasets become huge, and data are necessarily noisy in clinical recording environments. No methods for spike sorting of such recordings have been available. Spike sorting refers to the process of identifying the contributions of several neurons to the signal recorded in one electrode. To overcome these difficulties, we developed Combinato: a complete data-analysis framework for spike sorting in noisy recordings lasting twelve hours or more. Our framework includes software for artifact rejection, automatic spike sorting, manual optimization, and efficient visualization of results. Our completely automatic framework excels at two tasks: It outperforms existing methods when tested on simulated and real data, and it enables researchers to analyze multi-hour recordings. We evaluated our methods on both short and multi-hour simulated datasets. To evaluate the performance of our methods in an actual neuroscientific experiment, we used data from from neurosurgical patients, recorded in order to identify visually responsive neurons in the medial temporal lobe. These neurons responded to the semantic content, rather than to visual features, of a given stimulus. To test our methods with multi-hour recordings, we made use of neurons in the human medial temporal lobe that respond selectively to the same stimulus in the evening and next morning. PMID:27930664

Mapping the spatio-temporal structure of motor cortical LFP and spiking activities during reach-to-grasp movements

PubMed Central

Riehle, Alexa; Wirtssohn, Sarah; Grün, Sonja; Brochier, Thomas

2013-01-01

Grasping an object involves shaping the hand and fingers in relation to the object’s physical properties. Following object contact, it also requires a fine adjustment of grasp forces for secure manipulation. Earlier studies suggest that the control of hand shaping and grasp force involve partially segregated motor cortical networks. However, it is still unclear how information originating from these networks is processed and integrated. We addressed this issue by analyzing massively parallel signals from population measures (local field potentials, LFPs) and single neuron spiking activities recorded simultaneously during a delayed reach-to-grasp task, by using a 100-electrode array chronically implanted in monkey motor cortex. Motor cortical LFPs exhibit a large multi-component movement-related potential (MRP) around movement onset. Here, we show that the peak amplitude of each MRP component and its latency with respect to movement onset vary along the cortical surface covered by the array. Using a comparative mapping approach, we suggest that the spatio-temporal structure of the MRP reflects the complex physical properties of the reach-to-grasp movement. In addition, we explored how the spatio-temporal structure of the MRP relates to two other measures of neuronal activity: the temporal profile of single neuron spiking activity at each electrode site and the somatosensory receptive field properties of single neuron activities. We observe that the spatial representations of LFP and spiking activities overlap extensively and relate to the spatial distribution of proximal and distal representations of the upper limb. Altogether, these data show that, in motor cortex, a precise spatio-temporal pattern of activation is involved for the control of reach-to-grasp movements and provide some new insight about the functional organization of motor cortex during reaching and object manipulation. PMID:23543888

Burst firing and modulation of functional connectivity in cat striate cortex.

PubMed

Snider, R K; Kabara, J F; Roig, B R; Bonds, A B

1998-08-01

We studied the influences of the temporal firing patterns of presynaptic cat visual cortical cells on spike generation by postsynaptic cells. Multiunit recordings were dissected into the activity of individual neurons within the recorded group. Cross-correlation analysis was then used to identify directly coupled neuron pairs. The 22 multiunit groups recorded typically showed activity from two to six neurons, each containing between 1 and 15 neuron pairs. From a total of 241 neuron pairs, 91 (38%) had a shifted cross-correlation peak, which indicated a possible direct connection. Only two multiunit groups contained no shifted peaks. Burst activity, defined by groups of two or more spikes with intervals of

Unsupervised spike sorting based on discriminative subspace learning.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2014-01-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.

Mouse EEG spike detection based on the adapted continuous wavelet transform

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Kharatishvili, Irina; Chen, Min; Reutens, David C.

2016-04-01

Objective. Electroencephalography (EEG) is an important tool in the diagnosis of epilepsy. Interictal spikes on EEG are used to monitor the development of epilepsy and the effects of drug therapy. EEG recordings are generally long and the data voluminous. Thus developing a sensitive and reliable automated algorithm for analyzing EEG data is necessary. Approach. A new algorithm for detecting and classifying interictal spikes in mouse EEG recordings is proposed, based on the adapted continuous wavelet transform (CWT). The construction of the adapted mother wavelet is founded on a template obtained from a sample comprising the first few minutes of an EEG data set. Main Result. The algorithm was tested with EEG data from a mouse model of epilepsy and experimental results showed that the algorithm could distinguish EEG spikes from other transient waveforms with a high degree of sensitivity and specificity. Significance. Differing from existing approaches, the proposed approach combines wavelet denoising, to isolate transient signals, with adapted CWT-based template matching, to detect true interictal spikes. Using the adapted wavelet constructed from a predefined template, the adapted CWT is calculated on small EEG segments to fit dynamical changes in the EEG recording.

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.

Temporal coordination of olfactory cortex sharp-wave activity with up- and downstates in the orbitofrontal cortex during slow-wave sleep.

PubMed

Onisawa, Naomi; Manabe, Hiroyuki; Mori, Kensaku

2017-01-01

During slow-wave sleep, interareal communications via coordinated, slow oscillatory activities occur in the large-scale networks of the mammalian neocortex. Because olfactory cortex (OC) areas, which belong to paleocortex, show characteristic sharp-wave (SPW) activity during slow-wave sleep, we examined whether OC SPWs in freely behaving rats occur in temporal coordination with up- and downstates of the orbitofrontal cortex (OFC) slow oscillation. Simultaneous recordings of local field potentials and spike activities in the OC and OFC showed that during the downstate in the OFC, the OC also exhibited downstate with greatly reduced neuronal activity and suppression of SPW generation. OC SPWs occurred during two distinct phases of the upstate of the OFC: early-phase SPWs occurred at the start of upstate shortly after the down-to-up transition in the OFC, whereas late-phase SPWs were generated at the end of upstate shortly before the up-to-down transition. Such temporal coordination between neocortical up- and downstates and olfactory system SPWs was observed between the prefrontal cortex areas (OFC and medial prefrontal cortex) and the OC areas (anterior piriform cortex and posterior piriform cortex). These results suggest that during slow-wave sleep, OC and OFC areas communicate preferentially in specific time windows shortly after the down-to-up transition and shortly before the up-to-down transition. Simultaneous recordings of local field potentials and spike activities in the anterior piriform cortex (APC) and orbitofrontal cortex (OFC) during slow-wave sleep showed that APC sharp waves tended to occur during two distinct phases of OFC upstate: early phase, shortly after the down-to-up transition, and late phase, shortly before the up-to-down transition, suggesting that during slow-wave sleep, olfactory cortex and OFC areas communicate preferentially in the specific time windows. Copyright © 2017 the American Physiological Society.

Temporal coordination of olfactory cortex sharp-wave activity with up- and downstates in the orbitofrontal cortex during slow-wave sleep

PubMed Central

Onisawa, Naomi; Mori, Kensaku

2016-01-01

During slow-wave sleep, interareal communications via coordinated, slow oscillatory activities occur in the large-scale networks of the mammalian neocortex. Because olfactory cortex (OC) areas, which belong to paleocortex, show characteristic sharp-wave (SPW) activity during slow-wave sleep, we examined whether OC SPWs in freely behaving rats occur in temporal coordination with up- and downstates of the orbitofrontal cortex (OFC) slow oscillation. Simultaneous recordings of local field potentials and spike activities in the OC and OFC showed that during the downstate in the OFC, the OC also exhibited downstate with greatly reduced neuronal activity and suppression of SPW generation. OC SPWs occurred during two distinct phases of the upstate of the OFC: early-phase SPWs occurred at the start of upstate shortly after the down-to-up transition in the OFC, whereas late-phase SPWs were generated at the end of upstate shortly before the up-to-down transition. Such temporal coordination between neocortical up- and downstates and olfactory system SPWs was observed between the prefrontal cortex areas (OFC and medial prefrontal cortex) and the OC areas (anterior piriform cortex and posterior piriform cortex). These results suggest that during slow-wave sleep, OC and OFC areas communicate preferentially in specific time windows shortly after the down-to-up transition and shortly before the up-to-down transition. NEW & NOTEWORTHY Simultaneous recordings of local field potentials and spike activities in the anterior piriform cortex (APC) and orbitofrontal cortex (OFC) during slow-wave sleep showed that APC sharp waves tended to occur during two distinct phases of OFC upstate: early phase, shortly after the down-to-up transition, and late phase, shortly before the up-to-down transition, suggesting that during slow-wave sleep, olfactory cortex and OFC areas communicate preferentially in the specific time windows. PMID:27733591

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

NASA Astrophysics Data System (ADS)

Gupta, Isha; Serb, Alexantrou; Khiat, Ali; Zeitler, Ralf; Vassanelli, Stefano; Prodromakis, Themistoklis

2016-09-01

Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real-time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multi-electrode array, demonstrating the technology's potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces.

Real-time encoding and compression of neuronal spikes by metal-oxide memristors

PubMed Central

Gupta, Isha; Serb, Alexantrou; Khiat, Ali; Zeitler, Ralf; Vassanelli, Stefano; Prodromakis, Themistoklis

2016-01-01

Advanced brain-chip interfaces with numerous recording sites bear great potential for investigation of neuroprosthetic applications. The bottleneck towards achieving an efficient bio-electronic link is the real-time processing of neuronal signals, which imposes excessive requirements on bandwidth, energy and computation capacity. Here we present a unique concept where the intrinsic properties of memristive devices are exploited to compress information on neural spikes in real-time. We demonstrate that the inherent voltage thresholds of metal-oxide memristors can be used for discriminating recorded spiking events from background activity and without resorting to computationally heavy off-line processing. We prove that information on spike amplitude and frequency can be transduced and stored in single devices as non-volatile resistive state transitions. Finally, we show that a memristive device array allows for efficient data compression of signals recorded by a multi-electrode array, demonstrating the technology's potential for building scalable, yet energy-efficient on-node processors for brain-chip interfaces. PMID:27666698

Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events.

PubMed

Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

2016-01-01

Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate.

Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events

PubMed Central

Shahi, Mina; van Vreeswijk, Carl; Pipa, Gordon

2016-01-01

Detecting the existence of temporally coordinated spiking activity, and its role in information processing in the cortex, has remained a major challenge for neuroscience research. Different methods and approaches have been suggested to test whether the observed synchronized events are significantly different from those expected by chance. To analyze the simultaneous spike trains for precise spike correlation, these methods typically model the spike trains as a Poisson process implying that the generation of each spike is independent of all the other spikes. However, studies have shown that neural spike trains exhibit dependence among spike sequences, such as the absolute and relative refractory periods which govern the spike probability of the oncoming action potential based on the time of the last spike, or the bursting behavior, which is characterized by short epochs of rapid action potentials, followed by longer episodes of silence. Here we investigate non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons. For that, we use the Monte Carlo method to estimate the full shape of the coincidence count distribution and to generate false positives for coincidence detection. The results show that compared to the distributions based on homogeneous Poisson processes, and also non-Poisson processes, the width of the distribution of joint spike events changes. Non-renewal processes can lead to both heavy tailed or narrow coincidence distribution. We conclude that small differences in the exact autostructure of the point process can cause large differences in the width of a coincidence distribution. Therefore, manipulations of the autostructure for the estimation of significance of joint spike events seem to be inadequate. PMID:28066225

Nonlinear Modeling of Causal Interrelationships in Neuronal Ensembles

PubMed Central

Zanos, Theodoros P.; Courellis, Spiros H.; Berger, Theodore W.; Hampson, Robert E.; Deadwyler, Sam A.; Marmarelis, Vasilis Z.

2009-01-01

The increasing availability of multiunit recordings gives new urgency to the need for effective analysis of “multidimensional” time-series data that are derived from the recorded activity of neuronal ensembles in the form of multiple sequences of action potentials—treated mathematically as point-processes and computationally as spike-trains. Whether in conditions of spontaneous activity or under conditions of external stimulation, the objective is the identification and quantification of possible causal links among the neurons generating the observed binary signals. A multiple-input/multiple-output (MIMO) modeling methodology is presented that can be used to quantify the neuronal dynamics of causal interrelationships in neuronal ensembles using spike-train data recorded from individual neurons. These causal interrelationships are modeled as transformations of spike-trains recorded from a set of neurons designated as the “inputs” into spike-trains recorded from another set of neurons designated as the “outputs.” The MIMO model is composed of a set of multiinput/single-output (MISO) modules, one for each output. Each module is the cascade of a MISO Volterra model and a threshold operator generating the output spikes. The Laguerre expansion approach is used to estimate the Volterra kernels of each MISO module from the respective input–output data using the least-squares method. The predictive performance of the model is evaluated with the use of the receiver operating characteristic (ROC) curve, from which the optimum threshold is also selected. The Mann–Whitney statistic is used to select the significant inputs for each output by examining the statistical significance of improvements in the predictive accuracy of the model when the respective inputs is included. Illustrative examples are presented for a simulated system and for an actual application using multiunit data recordings from the hippocampus of a behaving rat. PMID:18701382

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.

Feasibility Study of Extended-Gate-Type Silicon Nanowire Field-Effect Transistors for Neural Recording

PubMed Central

Kang, Hongki; Kim, Jee-Yeon; Choi, Yang-Kyu; Nam, Yoonkey

2017-01-01

In this research, a high performance silicon nanowire field-effect transistor (transconductance as high as 34 µS and sensitivity as 84 nS/mV) is extensively studied and directly compared with planar passive microelectrode arrays for neural recording application. Electrical and electrochemical characteristics are carefully characterized in a very well-controlled manner. We especially focused on the signal amplification capability and intrinsic noise of the transistors. A neural recording system using both silicon nanowire field-effect transistor-based active-type microelectrode array and platinum black microelectrode-based passive-type microelectrode array are implemented and compared. An artificial neural spike signal is supplied as input to both arrays through a buffer solution and recorded simultaneously. Recorded signal intensity by the silicon nanowire transistor was precisely determined by an electrical characteristic of the transistor, transconductance. Signal-to-noise ratio was found to be strongly dependent upon the intrinsic 1/f noise of the silicon nanowire transistor. We found how signal strength is determined and how intrinsic noise of the transistor determines signal-to-noise ratio of the recorded neural signals. This study provides in-depth understanding of the overall neural recording mechanism using silicon nanowire transistors and solid design guideline for further improvement and development. PMID:28350370

Feasibility Study of Extended-Gate-Type Silicon Nanowire Field-Effect Transistors for Neural Recording.

PubMed

Kang, Hongki; Kim, Jee-Yeon; Choi, Yang-Kyu; Nam, Yoonkey

2017-03-28

In this research, a high performance silicon nanowire field-effect transistor (transconductance as high as 34 µS and sensitivity as 84 nS/mV) is extensively studied and directly compared with planar passive microelectrode arrays for neural recording application. Electrical and electrochemical characteristics are carefully characterized in a very well-controlled manner. We especially focused on the signal amplification capability and intrinsic noise of the transistors. A neural recording system using both silicon nanowire field-effect transistor-based active-type microelectrode array and platinum black microelectrode-based passive-type microelectrode array are implemented and compared. An artificial neural spike signal is supplied as input to both arrays through a buffer solution and recorded simultaneously. Recorded signal intensity by the silicon nanowire transistor was precisely determined by an electrical characteristic of the transistor, transconductance. Signal-to-noise ratio was found to be strongly dependent upon the intrinsic 1/f noise of the silicon nanowire transistor. We found how signal strength is determined and how intrinsic noise of the transistor determines signal-to-noise ratio of the recorded neural signals. This study provides in-depth understanding of the overall neural recording mechanism using silicon nanowire transistors and solid design guideline for further improvement and development.

Ripples on spikes show increased phase-amplitude coupling in mesial temporal lobe epilepsy seizure onset zones

PubMed Central

Weiss, Shennan A; Orosz, Iren; Salamon, Noriko; Moy, Stephanie; Wei, Linqing; Van ’t Klooster, Maryse A; Knight, Robert T; Harper, Ronald M; Bragin, Anatol; Fried, Itzhak; Engel, Jerome; Staba, Richard J

2016-01-01

Objective Ripples (80–150 Hz) recorded from clinical macroelectrodes have been shown to be an accurate biomarker of epileptogenic brain tissue. We investigated coupling between epileptiform spike phase and ripple amplitude to better understand the mechanisms that generate this type of pathological ripple (pRipple) event. Methods We quantified phase amplitude coupling (PAC) between epileptiform EEG spike phase and ripple amplitude recorded from intracranial depth macroelectrodes during episodes of sleep in 12 patients with mesial temporal lobe epilepsy. PAC was determined by 1) a phasor transform that corresponds to the strength and rate of ripples coupled with spikes, and a 2) ripple-triggered average to measure the strength, morphology, and spectral frequency of the modulating and modulated signals. Coupling strength was evaluated in relation to recording sites within and outside the seizure onset zone (SOZ). Results Both the phasor transform and ripple-triggered averaging methods showed ripple amplitude was often robustly coupled with epileptiform EEG spike phase. Coupling was more regularly found inside than outside the SOZ, and coupling strength correlated with the likelihood a macroelectrode’s location was within the SOZ (p<0.01). The ratio of the rate of ripples coupled with EEG spikes inside the SOZ to rates of coupled ripples in non-SOZ was greater than the ratio of rates of ripples on spikes detected irrespective of coupling (p<0.05). Coupling strength correlated with an increase in mean normalized ripple amplitude (p<0.01), and a decrease in mean ripple spectral frequency (p<0.05). Significance Generation of low-frequency (80–150 Hz) pRipples in the SOZ involves coupling between epileptiform spike phase and ripple amplitude. The changes in excitability reflected as epileptiform spikes may also cause clusters of pathologically interconnected bursting neurons to grow and synchronize into aberrantly large neuronal assemblies. PMID:27723936

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.

A digitally assisted, signal folding neural recording amplifier.

PubMed

Chen, Yi; Basu, Arindam; Liu, Lei; Zou, Xiaodan; Rajkumar, Ramamoorthy; Dawe, Gavin Stewart; Je, Minkyu

2014-08-01

A novel signal folding and reconstruction scheme for neural recording applications that exploits the 1/f(n) characteristics of neural signals is described in this paper. The amplified output is 'folded' into a predefined range of voltages by using comparison and reset circuits along with the core amplifier. After this output signal is digitized and transmitted, a reconstruction algorithm can be applied in the digital domain to recover the amplified signal from the folded waveform. This scheme enables the use of an analog-to-digital convertor with less number of bits for the same effective dynamic range. It also reduces the transmission data rate of the recording chip. Both of these features allow power and area savings at the system level. Other advantages of the proposed topology are increased reliability due to the removal of pseudo-resistors, lower harmonic distortion and low-voltage operation. An analysis of the reconstruction error introduced by this scheme is presented along with a behavioral model to provide a quick estimate of the post reconstruction dynamic range. Measurement results from two different core amplifier designs in 65 nm and 180 nm CMOS processes are presented to prove the generality of the proposed scheme in the neural recording applications. Operating from a 1 V power supply, the amplifier in 180 nm CMOS has a gain of 54.2 dB, bandwidth of 5.7 kHz, input referred noise of 3.8 μVrms and power dissipation of 2.52 μW leading to a NEF of 3.1 in spike band. It exhibits a dynamic range of 66 dB and maximum SNDR of 43 dB in LFP band. It also reduces system level power (by reducing the number of bits in the ADC by 2) as well as data rate to 80% of a conventional design. In vivo measurements validate the ability of this amplifier to simultaneously record spike and LFP signals.

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.

How many neurons can we see with current spike sorting algorithms?

PubMed

Pedreira, Carlos; Martinez, Juan; Ison, Matias J; Quian Quiroga, Rodrigo

2012-10-15

Recent studies highlighted the disagreement between the typical number of neurons observed with extracellular recordings and the ones to be expected based on anatomical and physiological considerations. This disagreement has been mainly attributed to the presence of sparsely firing neurons. However, it is also possible that this is due to limitations of the spike sorting algorithms used to process the data. To address this issue, we used realistic simulations of extracellular recordings and found a relatively poor spike sorting performance for simulations containing a large number of neurons. In fact, the number of correctly identified neurons for single-channel recordings showed an asymptotic behavior saturating at about 8-10 units, when up to 20 units were present in the data. This performance was significantly poorer for neurons with low firing rates, as these units were twice more likely to be missed than the ones with high firing rates in simulations containing many neurons. These results uncover one of the main reasons for the relatively low number of neurons found in extracellular recording and also stress the importance of further developments of spike sorting algorithms. Copyright © 2012 Elsevier B.V. All rights reserved.

A case-control study of wicket spikes using video-EEG monitoring.

PubMed

Vallabhaneni, Maya; Baldassari, Laura E; Scribner, James T; Cho, Yong Won; Motamedi, Gholam K

2013-01-01

To investigate clinical characteristics associated with wicket spikes in patients undergoing long-term video-EEG monitoring. A case-control study was performed in 479 patients undergoing video-EEG monitoring, with 3 age- (±3 years) and gender-matched controls per patient with wicket spikes. Logistic regression was utilized to investigate the association between wicket spikes and other factors, including conditions that have been previously associated with wicket spikes. Wicket spikes were recorded in 48 patients. There was a significantly higher prevalence of dizziness/vertigo (p=0.002), headaches (p=0.005), migraine (p=0.015), and seizures (p=0.016) in patients with wickets. The majority of patients with wicket spikes did not exhibit epileptiform activity on EEG; however, patients with history of seizures were more likely to have wickets (p=0.017). There was no significant difference in the prevalence of psychogenic non-epileptic seizures between the groups. Wickets were more common on the left, during sleep, and more likely to be first recorded on day 1-2 of monitoring. Patients with wicket spikes are more likely to have dizziness/vertigo, headaches, migraine, and seizures. Patients with history of seizures are more likely to have wickets. The prevalence of psychogenic non-epileptic seizures is not significantly higher in patients with wickets. Copyright © 2012 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

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.

The spike generator in the labellar taste receptors of the blowfly is differently affected by 4-aminopyridine and 5-hydroxytryptamine.

PubMed

Sollai, Giorgia; Solari, Paolo; Corda, Valentina; Masala, Carla; Crnjar, Roberto

2012-12-01

In taste chemoreception of invertebrates the interaction of taste stimuli with specific membrane receptors and/or ion channels located in the apical membrane of taste receptor cells results in the generation of a receptor potential which, in turn, activates the 'encoder' region to produce action potentials which propagate to the CNS. This study investigates, in the labellar chemosensilla of the blowfly, Protophormia terraenovae, the voltage-gated K(+) currents involved in the action potential repolarization and repetitive firing of the neurons by way of the K(v) channel inhibitors, 4-aminopyridine and 5-hydroxytryptamine. The receptor potential and the spike activity were simultaneously recorded from the 'salt', 'sugar' and 'deterrent' cells, by means of the extracellular side-wall technique, in response to 150 mM NaCl, 100 mM sucrose and 1 mM quinine HCl, before, 0÷10 min after apical administration of 4-AP (0.01-10 mM) or 5-HT (0.1-100 mM). The results show that the receptor potential in all three cells is neither affected by 4-AP nor by 5-HT. Instead, spike activity is significantly decreased, by way of blocking different K(v) channel types: an inactivating A-type K(+) current (KA) modulating repetitive firing of the cells and responsible for the after hyperpolarization, and a sustained K(+) current that resembles the delayed rectifier (DKR) and contributes to action potential repolarization. Copyright © 2012 Elsevier Ltd. All rights reserved.

Different correlation patterns of cholinergic and GABAergic interneurons with striatal projection neurons

PubMed Central

Adler, Avital; Katabi, Shiran; Finkes, Inna; Prut, Yifat; Bergman, Hagai

2013-01-01

The striatum is populated by a single projection neuron group, the medium spiny neurons (MSNs), and several groups of interneurons. Two of the electrophysiologically well-characterized striatal interneuron groups are the tonically active neurons (TANs), which are presumably cholinergic interneurons, and the fast spiking interneurons (FSIs), presumably parvalbumin (PV) expressing GABAergic interneurons. To better understand striatal processing it is thus crucial to define the functional relationship between MSNs and these interneurons in the awake and behaving animal. We used multiple electrodes and standard physiological methods to simultaneously record MSN spiking activity and the activity of TANs or FSIs from monkeys engaged in a classical conditioning paradigm. All three cell populations were highly responsive to the behavioral task. However, they displayed different average response profiles and a different degree of response synchronization (signal correlation). TANs displayed the most transient and synchronized response, MSNs the most diverse and sustained response and FSIs were in between on both parameters. We did not find evidence for direct monosynaptic connectivity between the MSNs and either the TANs or the FSIs. However, while the cross correlation histograms of TAN to MSN pairs were flat, those of FSI to MSN displayed positive asymmetrical broad peaks. The FSI-MSN correlogram profile implies that the spikes of MSNs follow those of FSIs and both are driven by a common, most likely cortical, input. Thus, the two populations of striatal interneurons are probably driven by different afferents and play complementary functional roles in the physiology of the striatal microcircuit. PMID:24027501

Intracellular activity of cortical and thalamic neurones during high-voltage rhythmic spike discharge in Long-Evans rats in vivo

PubMed Central

Polack, Pierre-Olivier; Charpier, Stéphane

2006-01-01

Spontaneous high-voltage rhythmic spike (HVRS) discharges at 6–12 Hz have been widely described in the electrocorticogram (EcoG) of Long-Evans rats. These ECoG oscillations have been proposed to reflect a state of attentive immobility allowing the optimization of sensory integration within the corticothalamic pathway. This hypothesis has been challenged by recent studies emphasizing similarities between HVRS discharges and spike-and-wave discharges (SWDs) in well-established rat genetic models of absence epilepsy. Here, we made in vivo intracellular recordings to determine, for the first time, the cellular mechanisms responsible for the synchronized oscillations in the corticothalamic loop during HVRS discharges in the Long-Evans rats. We show that HVRS discharges are associated in corticothalamic neurones with rhythmic suprathreshold synaptic depolarizations superimposed on a tonic hyperpolarization, likely due to a process of synaptic disfacilitation. Simultaneously, thalamocortical neurones exhibit a large-amplitude ‘croissant’-shaped membrane hyperpolarization with a voltage sensitivity suggesting a potassium-dependent mechanism. This thalamic hyperpolarizing envelope was associated with a membrane oscillation resulting from interactions between excitatory synaptic inputs, a chloride-dependent inhibitory conductance and voltage-gated intrinsic currents. These cortical and thalamic cellular mechanisms underlying HVRS activity in Long-Evans rats are remarkably similar to those previously described in the thalamocortical networks during SWDs. Thus, the present study provides an additional support to the hypothesis that HVRS activity in Long-Evans rats is an absence-like seizure activity. PMID:16410284

Fitting Neuron Models to Spike Trains

PubMed Central

Rossant, Cyrille; Goodman, Dan F. M.; Fontaine, Bertrand; Platkiewicz, Jonathan; Magnusson, Anna K.; Brette, Romain

2011-01-01

Computational modeling is increasingly used to understand the function of neural circuits in systems neuroscience. These studies require models of individual neurons with realistic input–output properties. Recently, it was found that spiking models can accurately predict the precisely timed spike trains produced by cortical neurons in response to somatically injected currents, if properly fitted. This requires fitting techniques that are efficient and flexible enough to easily test different candidate models. We present a generic solution, based on the Brian simulator (a neural network simulator in Python), which allows the user to define and fit arbitrary neuron models to electrophysiological recordings. It relies on vectorization and parallel computing techniques to achieve efficiency. We demonstrate its use on neural recordings in the barrel cortex and in the auditory brainstem, and confirm that simple adaptive spiking models can accurately predict the response of cortical neurons. Finally, we show how a complex multicompartmental model can be reduced to a simple effective spiking model. PMID:21415925

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.

Multiscale analysis of neural spike trains.

PubMed

Ramezan, Reza; Marriott, Paul; Chenouri, Shojaeddin

2014-01-30

This paper studies the multiscale analysis of neural spike trains, through both graphical and Poisson process approaches. We introduce the interspike interval plot, which simultaneously visualizes characteristics of neural spiking activity at different time scales. Using an inhomogeneous Poisson process framework, we discuss multiscale estimates of the intensity functions of spike trains. We also introduce the windowing effect for two multiscale methods. Using quasi-likelihood, we develop bootstrap confidence intervals for the multiscale intensity function. We provide a cross-validation scheme, to choose the tuning parameters, and study its unbiasedness. Studying the relationship between the spike rate and the stimulus signal, we observe that adjusting for the first spike latency is important in cross-validation. We show, through examples, that the correlation between spike trains and spike count variability can be multiscale phenomena. Furthermore, we address the modeling of the periodicity of the spike trains caused by a stimulus signal or by brain rhythms. Within the multiscale framework, we introduce intensity functions for spike trains with multiplicative and additive periodic components. Analyzing a dataset from the retinogeniculate synapse, we compare the fit of these models with the Bayesian adaptive regression splines method and discuss the limitations of the methodology. Computational efficiency, which is usually a challenge in the analysis of spike trains, is one of the highlights of these new models. In an example, we show that the reconstruction quality of a complex intensity function demonstrates the ability of the multiscale methodology to crack the neural code. Copyright © 2013 John Wiley & Sons, Ltd.

Should spikes on post-resection ECoG guide pediatric epilepsy surgery?

PubMed

Greiner, Hansel M; Horn, Paul S; Tenney, Jeffrey R; Arya, Ravindra; Jain, Sejal V; Holland, Katherine D; Leach, James L; Miles, Lili; Rose, Douglas F; Fujiwara, Hisako; Mangano, Francesco T

2016-05-01

There is wide variation in clinical practice regarding the role of electrocorticography immediately after resection (post-resection ECoG) for pediatric epilepsy surgery. Results can guide further resection of potentially epileptogenic tissue. We hypothesized that post-resection ECoG spiking represents a biomarker of the epileptogenic zone and predicts seizure outcome in children undergoing epilepsy surgery. We retrospectively identified 124 children with post-resection ECoG performed on the margins of resection. ECoG records were scored in a blinded fashion based on presence of frequent spiking. For patients identified as having additional resection based on clinical post-resection ECoG interpretation, these "second-look" ECoG results were re-reviewed for ongoing discharges or completeness of resection. Frequent spike populations were grouped using a standard scoring system into three ranges: 0.1-0.5Hz, 0.5-1Hz, >1Hz. Seizure outcomes were determined at minimum 12-month followup. Of 124 patients who met inclusion criteria, 60 (48%) had an identified spike population on post-resection ECoG. Thirty (50%) of these had further resection based on clinical interpretation. Overall, good outcome (ILAE 1) was seen in 56/124 (45%). Completeness of resection of spiking (absence of spiking on initial post-resection ECoG or resolution of spiking after further resection) showed a trend toward good outcome (OR 2.03, p=0.099). Patients with completeness of resection had good outcome in 41/80 (51%) of cases; patients with continued spikes had good outcome in 15/44 (35%) of cases. Post-resection ECoG identifies residual epileptogenic tissue in a significant number of children. Lower frequency or absence of discharges on initial recording showed a trend toward good outcome. Completeness of resection demonstrated on final ECoG recording did not show a significant difference in outcome. This suggests that post-resection discharges represent a prognostic marker rather than a remediable biomarker of the epileptogenic zone in all patients. Resecting residual spike-generating cortex may be beneficial in selected patients, including children with tumors. Copyright © 2016 Elsevier B.V. All rights reserved.

A Novel Nonparametric Approach for Neural Encoding and Decoding Models of Multimodal Receptive Fields.

PubMed

Agarwal, Rahul; Chen, Zhe; Kloosterman, Fabian; Wilson, Matthew A; Sarma, Sridevi V

2016-07-01

Pyramidal neurons recorded from the rat hippocampus and entorhinal cortex, such as place and grid cells, have diverse receptive fields, which are either unimodal or multimodal. Spiking activity from these cells encodes information about the spatial position of a freely foraging rat. At fine timescales, a neuron's spike activity also depends significantly on its own spike history. However, due to limitations of current parametric modeling approaches, it remains a challenge to estimate complex, multimodal neuronal receptive fields while incorporating spike history dependence. Furthermore, efforts to decode the rat's trajectory in one- or two-dimensional space from hippocampal ensemble spiking activity have mainly focused on spike history-independent neuronal encoding models. In this letter, we address these two important issues by extending a recently introduced nonparametric neural encoding framework that allows modeling both complex spatial receptive fields and spike history dependencies. Using this extended nonparametric approach, we develop novel algorithms for decoding a rat's trajectory based on recordings of hippocampal place cells and entorhinal grid cells. Results show that both encoding and decoding models derived from our new method performed significantly better than state-of-the-art encoding and decoding models on 6 minutes of test data. In addition, our model's performance remains invariant to the apparent modality of the neuron's receptive field.

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.

Application of the SP algorithm to the INTERMAGNET magnetograms of the disturbed geomagnetic field

NASA Astrophysics Data System (ADS)

Sidorov, R. V.; Soloviev, A. A.; Bogoutdinov, Sh. R.

2012-05-01

The algorithmic system developed in the Laboratory of Geoinformatics at the Geophysical Center, Russian Academy of Sciences, which is intended for recognizing spikes on the magnetograms from the global network INTERMAGNET provides the possibility to carry out retrospective analysis of the magnetograms from the World Data Centers. Application of this system to the analysis of the magnetograms allows automating the job of the experts-interpreters on identifying the artificial spikes in the INTERMAGNET data. The present paper is focused on the SP algorithm (abbreviated from SPIKE) which recognizes artificial spikes on the records of the geomagnetic field. Initially, this algorithm was trained on the magnetograms of 2007 and 2008, which recorded the quiet geomagnetic field. The results of training and testing showed that the algorithm is quite efficient. Applying this method to the problem of recognizing spikes on the data for periods of enhanced geomagnetic activity is a separate task. In this short communication, we present the results of applying the SP algorithm trained on the data of 2007 to the INTERMAGNET magnetograms for 2003 and 2005 sampled every minute. This analysis shows that the SP algorithm does not exhibit a worse performance if applied to the records of a disturbed geomagnetic field.

Complex effusive events at Kilauea as documented by the GOES satellite and remote video cameras

USGS Publications Warehouse

Harris, A.J.L.; Thornber, C.R.

1999-01-01

GOES provides thermal data for all of the Hawaiian volcanoes once every 15 min. We show how volcanic radiance time series produced from this data stream can be used as a simple measure of effusive activity. Two types of radiance trends in these time series can be used to monitor effusive activity: (a) Gradual variations in radiance reveal steady flow-field extension and tube development. (b) Discrete spikes correlate with short bursts of activity, such as lava fountaining or lava-lake overflows. We are confident that any effusive event covering more than 10,000 m2 of ground in less than 60 min will be unambiguously detectable using this approach. We demonstrate this capability using GOES, video camera and ground-based observational data for the current eruption of Kilauea volcano (Hawai'i). A GOES radiance time series was constructed from 3987 images between 19 June and 12 August 1997. This time series displayed 24 radiance spikes elevated more than two standard deviations above the mean; 19 of these are correlated with video-recorded short-burst effusive events. Less ambiguous events are interpreted, assessed and related to specific volcanic events by simultaneous use of permanently recording video camera data and ground-observer reports. The GOES radiance time series are automatically processed on data reception and made available in near-real-time, so such time series can contribute to three main monitoring functions: (a) automatically alerting major effusive events; (b) event confirmation and assessment; and (c) establishing effusive event chronology.

Role of a looming-sensitive neuron in triggering the defense behavior of the praying mantis Tenodera aridifolia.

PubMed

Sato, Keiichiro; Yamawaki, Yoshifumi

2014-08-01

In responses to looming objects, the praying mantis shows a defense behavior, which consists of retracting forelegs under the prothorax. The role of a looming-sensitive neuron in triggering this behavior was investigated by simultaneously recording the activity and behavioral responses of the neuron. The mantis initiated the defense behavior earlier in response to larger and slower looming stimuli. The time remaining to collision at defense initiation was linearly correlated with the ratio of the half-size of an approaching object to its speed (l/|v|), suggesting that the defense behavior occurred a fixed delay after the stimuli had reached a fixed angular threshold. Furthermore, the results suggested that high-frequency spikes of the looming-sensitive neuron were involved in triggering the defense behavior: the distribution of maximum firing rate for trials with defense was shifted to larger rates compared with trials without defense; the firing rate of the neuron exceeded 150 Hz ∼100 ms before the defense initiation regardless of stimulus parameters; when a looming stimulus ceased approach prematurely, high-frequency spikes were removed, and the occurrence of defense was reduced. Copyright © 2014 the American Physiological Society.

Three-dimensional structure and function of the Paramecium bursaria chlorella virus capsid.

PubMed

Zhang, Xinzheng; Xiang, Ye; Dunigan, David D; Klose, Thomas; Chipman, Paul R; Van Etten, James L; Rossmann, Michael G

2011-09-06

A cryoelectron microscopy 8.5 Å resolution map of the 1,900 Å diameter, icosahedral, internally enveloped Paramecium bursaria chlorella virus was used to interpret structures of the virus at initial stages of cell infection. A fivefold averaged map demonstrated that two minor capsid proteins involved in stabilizing the capsid are missing in the vicinity of the unique vertex. Reconstruction of the virus in the presence of host chlorella cell walls established that the spike at the unique vertex initiates binding to the cell wall, which results in the enveloped nucleocapsid moving closer to the cell. This process is concurrent with the release of the internal viral membrane that was linked to the capsid by many copies of a viral membrane protein in the mature infectous virus. Simultaneously, part of the trisymmetrons around the unique vertex disassemble, probably in part because two minor capsid proteins are absent, causing Paramecium bursaria chlorella virus and the cellular contents to merge, possibly as a result of enzyme(s) within the spike assembly. This may be one of only a few recordings of successive stages of a virus while infecting a eukaryotic host in pseudoatomic detail in three dimensions.

Three-dimensional structure and function of the Paramecium bursaria chlorella virus capsid

PubMed Central

Zhang, Xinzheng; Xiang, Ye; Dunigan, David D.; Klose, Thomas; Chipman, Paul R.; Van Etten, James L.; Rossmann, Michael G.

2011-01-01

A cryoelectron microscopy 8.5 Å resolution map of the 1,900 Å diameter, icosahedral, internally enveloped Paramecium bursaria chlorella virus was used to interpret structures of the virus at initial stages of cell infection. A fivefold averaged map demonstrated that two minor capsid proteins involved in stabilizing the capsid are missing in the vicinity of the unique vertex. Reconstruction of the virus in the presence of host chlorella cell walls established that the spike at the unique vertex initiates binding to the cell wall, which results in the enveloped nucleocapsid moving closer to the cell. This process is concurrent with the release of the internal viral membrane that was linked to the capsid by many copies of a viral membrane protein in the mature infectous virus. Simultaneously, part of the trisymmetrons around the unique vertex disassemble, probably in part because two minor capsid proteins are absent, causing Paramecium bursaria chlorella virus and the cellular contents to merge, possibly as a result of enzyme(s) within the spike assembly. This may be one of only a few recordings of successive stages of a virus while infecting a eukaryotic host in pseudoatomic detail in three dimensions. PMID:21873222

Synchronization Dynamics in Response to Plaid Stimuli in Monkey V1

PubMed Central

Lima, Bruss; Singer, Wolf; Chen, Nan-Hui

2010-01-01

Gamma synchronization has generally been associated with grouping processes in the visual system. Here, we examine in monkey V1 whether gamma oscillations play a functional role in segmenting surfaces of plaid stimuli. Local field potentials (LFPs) and spiking activity were recorded simultaneously from multiple sites in the opercular and calcarine regions while the monkeys were presented with sequences of single and superimposed components of plaid stimuli. In accord with the previous studies, responses to the single components (gratings) exhibited strong and sustained gamma-band oscillations (30–65 Hz). The superposition of the second component, however, led to profound changes in the temporal structure of the responses, characterized by a drastic reduction of gamma oscillations in the spiking activity and systematic shifts to higher frequencies in the LFP (∼10% increase). Comparisons between cerebral hemispheres and across monkeys revealed robust subject-specific spectral signatures. A possible interpretation of our results may be that single gratings induce strong cooperative interactions among populations of cells that share similar response properties, whereas plaids lead to competition. Overall, our results suggest that the functional architecture of the cortex is a major determinant of the neuronal synchronization dynamics in V1. PMID:19812238

The extraction of neural information from the surface EMG for the control of upper-limb prostheses: emerging avenues and challenges.

PubMed

Farina, Dario; Jiang, Ning; Rehbaum, Hubertus; Holobar, Aleš; Graimann, Bernhard; Dietl, Hans; Aszmann, Oskar C

2014-07-01

Despite not recording directly from neural cells, the surface electromyogram (EMG) signal contains information on the neural drive to muscles, i.e., the spike trains of motor neurons. Using this property, myoelectric control consists of the recording of EMG signals for extracting control signals to command external devices, such as hand prostheses. In commercial control systems, the intensity of muscle activity is extracted from the EMG and used for single degrees of freedom activation (direct control). Over the past 60 years, academic research has progressed to more sophisticated approaches but, surprisingly, none of these academic achievements has been implemented in commercial systems so far. We provide an overview of both commercial and academic myoelectric control systems and we analyze their performance with respect to the characteristics of the ideal myocontroller. Classic and relatively novel academic methods are described, including techniques for simultaneous and proportional control of multiple degrees of freedom and the use of individual motor neuron spike trains for direct control. The conclusion is that the gap between industry and academia is due to the relatively small functional improvement in daily situations that academic systems offer, despite the promising laboratory results, at the expense of a substantial reduction in robustness. None of the systems so far proposed in the literature fulfills all the important criteria needed for widespread acceptance by the patients, i.e. intuitive, closed-loop, adaptive, and robust real-time ( 200 ms delay) control, minimal number of recording electrodes with low sensitivity to repositioning, minimal training, limited complexity and low consumption. Nonetheless, in recent years, important efforts have been invested in matching these criteria, with relevant steps forwards.

Data-Driven Significance Estimation for Precise Spike Correlation

PubMed Central

Grün, Sonja

2009-01-01

The mechanisms underlying neuronal coding and, in particular, the role of temporal spike coordination are hotly debated. However, this debate is often confounded by an implicit discussion about the use of appropriate analysis methods. To avoid incorrect interpretation of data, the analysis of simultaneous spike trains for precise spike correlation needs to be properly adjusted to the features of the experimental spike trains. In particular, nonstationarity of the firing of individual neurons in time or across trials, a spike train structure deviating from Poisson, or a co-occurrence of such features in parallel spike trains are potent generators of false positives. Problems can be avoided by including these features in the null hypothesis of the significance test. In this context, the use of surrogate data becomes increasingly important, because the complexity of the data typically prevents analytical solutions. This review provides an overview of the potential obstacles in the correlation analysis of parallel spike data and possible routes to overcome them. The discussion is illustrated at every stage of the argument by referring to a specific analysis tool (the Unitary Events method). The conclusions, however, are of a general nature and hold for other analysis techniques. Thorough testing and calibration of analysis tools and the impact of potentially erroneous preprocessing stages are emphasized. PMID:19129298

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

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.

Rat globus pallidus neurons: functional classification and effects of dopamine depletion.

PubMed

Karain, Brad; Xu, Dan; Bellone, John A; Hartman, Richard E; Shi, Wei-Xing

2015-01-01

The rat globus pallidus (GP) is homologous to the primate GP externus. Studies with injectable anesthetics suggest that GP neurons can be classified into Type-I and Type-II cells based on extracellularly recorded spike shape, or positively coupled (PC), negatively coupled (NC), and uncoupled (UC) cells based on functional connectivity with the cortex. In this study, we examined the electrophysiology of rat GP neurons using the inhalational anesthetic isoflurane which offers more constant and easily regulated levels of anesthesia than injectable anesthetics. In 130 GP neurons recorded using small-tip glass electrodes (<1 μm), all but one fired Type-II spikes (positive/negative waveform). Type-I cells were unlikely to be inhibited by isoflurane since all GP neurons also fired Type-II spikes under ketamine-induced anesthesia. When recorded with large-tip electrodes (∼2 μm), however, over 70% of GP neurons exhibited Type-I spikes (negative/positive waveform). These results suggest that the spike shape, recorded extracellularly, varies depending on the electrode used and is not reliable in distinguishing Type-I and Type-II neurons. Using dual-site recording, 40% of GP neurons were identified as PC cells, 17.5% NC cells, and 42.5% UC cells. The three subtypes also differed significantly in firing rate and pattern. Lesions of dopamine neurons increased the number of NC cells, decreased that of UC cells, and significantly shifted the phase relationship between PC cells and the cortex. These results support the presence of GP neuron subtypes and suggest that each subtype plays a different role in the pathophysiology of Parkinson's disease. Synapse 69:41-51, 2015. © 2014 Wiley Periodicals, Inc. © 2014 Wiley Periodicals, Inc.

The magnetic field of gastrointestinal smooth muscle activity

NASA Astrophysics Data System (ADS)

Bradshaw, Alan; Ladipo, Jk; Richards, William; Wikswo, John

1997-11-01

The gastrointestinal (GI) tract controls the absorption and transport of ingested materials. Its function is determined largely by the electrical activity of the smooth muscle that lines the GI tract. GI electrical activity consists of an omnipresent slowly oscillating wave known as the basic electrical rhythm (BER) that modulates a higher-frequency spiking activity associated with muscle contraction. The BER has been shown to be a reliable indicator of intestinal viability, and thus, recording of smooth muscle activity may have clinical value. The BER is difficult to measure with cutaneous electrodes because layers of low-conductivity fat between the GI tract and the abdominal surface attenuate the potential. On the other hand, the magnetic field associated with GI electrical activity is mostly unaffected by intervening fat layers. We recorded the magnetic fields from GI activity in 12 volunteers using a multichannel Superconducting QUantum Interference Device (SQUID) magnetometer. Characteristics typical of gastric and intestinal BER were apparent in the data. Channels near the epigastrium recorded gastric BER, and channels in intestinal areas recorded small bowel BER. These results suggest that a single multichannel SQUID magnetometer is able to measure gastrointestinal electrical activity from multiple locations around the abdomen simultaneously.

Deep brain optical measurements of cell type-specific neural activity in behaving mice.

PubMed

Cui, Guohong; Jun, Sang Beom; Jin, Xin; Luo, Guoxiang; Pham, Michael D; Lovinger, David M; Vogel, Steven S; Costa, Rui M

2014-01-01

Recent advances in genetically encoded fluorescent sensors enable the monitoring of cellular events from genetically defined groups of neurons in vivo. In this protocol, we describe how to use a time-correlated single-photon counting (TCSPC)-based fiber optics system to measure the intensity, emission spectra and lifetime of fluorescent biosensors expressed in deep brain structures in freely moving mice. When combined with Cre-dependent selective expression of genetically encoded Ca(2+) indicators (GECIs), this system can be used to measure the average neural activity from a specific population of cells in mice performing complex behavioral tasks. As an example, we used viral expression of GCaMPs in striatal projection neurons (SPNs) and recorded the fluorescence changes associated with calcium spikes from mice performing a lever-pressing operant task. The whole procedure, consisting of virus injection, behavior training and optical recording, takes 3-4 weeks to complete. With minor adaptations, this protocol can also be applied to recording cellular events from other cell types in deep brain regions, such as dopaminergic neurons in the ventral tegmental area. The simultaneously recorded fluorescence signals and behavior events can be used to explore the relationship between the neural activity of specific brain circuits and behavior.

System-Level Design of a 64-Channel Low Power Neural Spike Recording Sensor.

PubMed

Delgado-Restituto, Manuel; Rodriguez-Perez, Alberto; Darie, Angela; Soto-Sanchez, Cristina; Fernandez-Jover, Eduardo; Rodriguez-Vazquez, Angel

2017-04-01

This paper reports an integrated 64-channel neural spike recording sensor, together with all the circuitry to process and configure the channels, process the neural data, transmit via a wireless link the information and receive the required instructions. Neural signals are acquired, filtered, digitized and compressed in the channels. Additionally, each channel implements an auto-calibration algorithm which individually configures the transfer characteristics of the recording site. The system has two transmission modes; in one case the information captured by the channels is sent as uncompressed raw data; in the other, feature vectors extracted from the detected neural spikes are released. Data streams coming from the channels are serialized by the embedded digital processor. Experimental results, including in vivo measurements, show that the power consumption of the complete system is lower than 330 μW.

Simultaneous determination of the quantity and isotopic ratios of uranium in individual micro-particles by isotope dilution thermal ionization mass spectrometry (ID-TIMS).

PubMed

Park, Jong-Ho; Choi, Eun-Ju

2016-11-01

A method to determine the quantity and isotopic ratios of uranium in individual micro-particles simultaneously by isotope dilution thermal ionization mass spectrometry (ID-TIMS) has been developed. This method consists of sequential sample and spike loading, ID-TIMS for isotopic measurement, and application of a series of mathematical procedures to remove the contribution of uranium in the spike. The homogeneity of evaporation and ionization of uranium content was confirmed by the consistent ratio of n((233)U)/n((238)U) determined by TIMS measurements. Verification of the method was performed using U030 solution droplets and U030 particles. Good agreements of resulting uranium quantity, n((235)U)/n((238)U), and n((236)U)/n((238)U) with the estimated or certified values showed the validity of this newly developed method for particle analysis when simultaneous determination of the quantity and isotopic ratios of uranium is required. Copyright © 2016 Elsevier B.V. All rights reserved.

Variability of acute extracellular action potential measurements with multisite silicon probes

PubMed Central

Scott, Kimberly M.; Du, Jiangang; Lester, Henry A.; Masmanidis, Sotiris C.

2012-01-01

Device miniaturization technologies have led to significant advances in sensors for extracellular measurements of electrical activity in the brain. Multisite, silicon-based probes containing implantable electrode arrays afford greater coverage of neuronal activity than single electrodes and therefore potentially offer a more complete view of how neuronal ensembles encode information. However, scaling up the number of sites is not sufficient to ensure capture of multiple neurons, as action potential signals from extracellular electrodes may vary due to numerous factors. In order to understand the large-scale recording capabilities and potential limitations of multisite probes, it is important to quantify this variability, and to determine whether certain key device parameters influence the recordings. Here we investigate the effect of four parameters, namely, electrode surface, width of the structural support shafts, shaft number, and position of the recording site relative to the shaft tip. This study employs acutely implanted silicon probes containing up to 64 recording sites, whose performance is evaluated by the metrics of noise, spike amplitude, and spike detection probability. On average, we find no significant effect of device geometry on spike amplitude and detection probability but we find significant differences among individual experiments, with the likelihood of detecting spikes varying by a factor of approximately three across trials. PMID:22971352

Antigravity posture for analysis of motor unit recruitment: the "45 degree test".

PubMed

Petajan, J H

1990-04-01

The maximum number of different motor unit action potentials (MUAPs), their firing rates, and total MUAP spikes/second recorded by monopolar needle electrode were determined for the biceps brachii muscle during 45-degree elbow flexion. There were 4.2 +/- 1.6 different MUAPs exceeding 100 microV. Mean firing rate was 10.0 +/- 1.7 Hz, and total MUAP spikes/second were 40.3 +/- 18. Recordings from 16 patients with neurogenic atrophy (NA) and just detectable weakness revealed corresponding values of 3.1 +/- 1.7 different MUAPs, a mean rate of 10.2 +/- 1.5 Hz and 30.6 +/- 19 total MUAP spikes/second, not different from normal. In these patients, increased force of muscle contraction was required to activate high threshold motor units firing at high rates. In each of 4 patients just able to hold the arm against gravity, 1 or 2 "overdriven" motor units firing at a mean rate greater than 20 Hz were recorded. In 8 patients with myopathy and just detectable weakness, greater than 100 total MUAP spikes/second were recorded. Antigravity posture as a reference level of innervation has the advantage that motor unit firing rate is set about that of physiologic tremor (10-13 Hz). Its application was helpful in quantifying recruitment.

Scalable, Lightweight, Integrated and Quick-to-Assemble (SLIQ) Hyperdrives for Functional Circuit Dissection.

PubMed

Liang, Li; Oline, Stefan N; Kirk, Justin C; Schmitt, Lukas Ian; Komorowski, Robert W; Remondes, Miguel; Halassa, Michael M

2017-01-01

Independently adjustable multielectrode arrays are routinely used to interrogate neuronal circuit function, enabling chronic in vivo monitoring of neuronal ensembles in freely behaving animals at a single-cell, single spike resolution. Despite the importance of this approach, its widespread use is limited by highly specialized design and fabrication methods. To address this, we have developed a Scalable, Lightweight, Integrated and Quick-to-assemble multielectrode array platform. This platform additionally integrates optical fibers with independently adjustable electrodes to allow simultaneous single unit recordings and circuit-specific optogenetic targeting and/or manipulation. In current designs, the fully assembled platforms are scalable from 2 to 32 microdrives, and yet range 1-3 g, light enough for small animals. Here, we describe the design process starting from intent in computer-aided design, parameter testing through finite element analysis and experimental means, and implementation of various applications across mice and rats. Combined, our methods may expand the utility of multielectrode recordings and their continued integration with other tools enabling functional dissection of intact neural circuits.

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.

Wiener Filtering of Surface EMG with a priori SNR Estimation Toward Myoelectric Control for Neurological Injury Patients

PubMed Central

Liu, Jie; Ying, Dongwen; Zhou, Ping

2014-01-01

Voluntary surface electromyogram (EMG) signals from neurological injury patients are often corrupted by involuntary background interference or spikes, imposing difficulties for myoelectric control. We present a novel framework to suppress involuntary background spikes during voluntary surface EMG recordings. The framework applies a Wiener filter to restore voluntary surface EMG signals based on tracking a priori signal to noise ratio (SNR) by using the decision-directed method. Semi-synthetic surface EMG signals contaminated by different levels of involuntary background spikes were constructed from a database of surface EMG recordings in a group of spinal cord injury subjects. After the processing, the onset detection of voluntary muscle activity was significantly improved against involuntary background spikes. The magnitude of voluntary surface EMG signals can also be reliably estimated for myoelectric control purpose. Compared with the previous sample entropy analysis for suppressing involuntary background spikes, the proposed framework is characterized by quick and simple implementation, making it more suitable for application in a myoelectric control system toward neurological injury rehabilitation. PMID:25443536

Leaders and followers: quantifying consistency in spatio-temporal propagation patterns

NASA Astrophysics Data System (ADS)

Kreuz, Thomas; Satuvuori, Eero; Pofahl, Martin; Mulansky, Mario

2017-04-01

Repetitive spatio-temporal propagation patterns are encountered in fields as wide-ranging as climatology, social communication and network science. In neuroscience, perfectly consistent repetitions of the same global propagation pattern are called a synfire pattern. For any recording of sequences of discrete events (in neuroscience terminology: sets of spike trains) the questions arise how closely it resembles such a synfire pattern and which are the spike trains that lead/follow. Here we address these questions and introduce an algorithm built on two new indicators, termed SPIKE-order and spike train order, that define the synfire indicator value, which allows to sort multiple spike trains from leader to follower and to quantify the consistency of the temporal leader-follower relationships for both the original and the optimized sorting. We demonstrate our new approach using artificially generated datasets before we apply it to analyze the consistency of propagation patterns in two real datasets from neuroscience (giant depolarized potentials in mice slices) and climatology (El Niño sea surface temperature recordings). The new algorithm is distinguished by conceptual and practical simplicity, low computational cost, as well as flexibility and universality.

Decoding grating orientation from microelectrode array recordings in monkey cortical area V4.

PubMed

Manyakov, Nikolay V; Van Hulle, Marc M

2010-04-01

We propose an invasive brain-machine interface (BMI) that decodes the orientation of a visual grating from spike train recordings made with a 96 microelectrodes array chronically implanted into the prelunate gyrus (area V4) of a rhesus monkey. The orientation is decoded irrespective of the grating's spatial frequency. Since pyramidal cells are less prominent in visual areas, compared to (pre)motor areas, the recordings contain spikes with smaller amplitudes, compared to the noise level. Hence, rather than performing spike decoding, feature selection algorithms are applied to extract the required information for the decoder. Two types of feature selection procedures are compared, filter and wrapper. The wrapper is combined with a linear discriminant analysis classifier, and the filter is followed by a radial-basis function support vector machine classifier. In addition, since we have a multiclass classification problen, different methods for combining pairwise classifiers are compared.

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.

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

A case for spiking neural network simulation based on configurable multiple-FPGA systems.

PubMed

Yang, Shufan; Wu, Qiang; Li, Renfa

2011-09-01

Recent neuropsychological research has begun to reveal that neurons encode information in the timing of spikes. Spiking neural network simulations are a flexible and powerful method for investigating the behaviour of neuronal systems. Simulation of the spiking neural networks in software is unable to rapidly generate output spikes in large-scale of neural network. An alternative approach, hardware implementation of such system, provides the possibility to generate independent spikes precisely and simultaneously output spike waves in real time, under the premise that spiking neural network can take full advantage of hardware inherent parallelism. We introduce a configurable FPGA-oriented hardware platform for spiking neural network simulation in this work. We aim to use this platform to combine the speed of dedicated hardware with the programmability of software so that it might allow neuroscientists to put together sophisticated computation experiments of their own model. A feed-forward hierarchy network is developed as a case study to describe the operation of biological neural systems (such as orientation selectivity of visual cortex) and computational models of such systems. This model demonstrates how a feed-forward neural network constructs the circuitry required for orientation selectivity and provides platform for reaching a deeper understanding of the primate visual system. In the future, larger scale models based on this framework can be used to replicate the actual architecture in visual cortex, leading to more detailed predictions and insights into visual perception phenomenon.

Classification of EEG abnormalities in partial epilepsy with simultaneous EEG-fMRI recordings.

PubMed

Pedreira, C; Vaudano, A E; Thornton, R C; Chaudhary, U J; Vulliemoz, S; Laufs, H; Rodionov, R; Carmichael, D W; Lhatoo, S D; Guye, M; Quian Quiroga, R; Lemieux, L

2014-10-01

Scalp EEG recordings and the classification of interictal epileptiform discharges (IED) in patients with epilepsy provide valuable information about the epileptogenic network, particularly by defining the boundaries of the "irritative zone" (IZ), and hence are helpful during pre-surgical evaluation of patients with severe refractory epilepsies. The current detection and classification of epileptiform signals essentially rely on expert observers. This is a very time-consuming procedure, which also leads to inter-observer variability. Here, we propose a novel approach to automatically classify epileptic activity and show how this method provides critical and reliable information related to the IZ localization beyond the one provided by previous approaches. We applied Wave_clus, an automatic spike sorting algorithm, for the classification of IED visually identified from pre-surgical simultaneous Electroencephalogram-functional Magnetic Resonance Imagining (EEG-fMRI) recordings in 8 patients affected by refractory partial epilepsy candidate for surgery. For each patient, two fMRI analyses were performed: one based on the visual classification and one based on the algorithmic sorting. This novel approach successfully identified a total of 29 IED classes (compared to 26 for visual identification). The general concordance between methods was good, providing a full match of EEG patterns in 2 cases, additional EEG information in 2 other cases and, in general, covering EEG patterns of the same areas as expert classification in 7 of the 8 cases. Most notably, evaluation of the method with EEG-fMRI data analysis showed hemodynamic maps related to the majority of IED classes representing improved performance than the visual IED classification-based analysis (72% versus 50%). Furthermore, the IED-related BOLD changes revealed by using the algorithm were localized within the presumed IZ for a larger number of IED classes (9) in a greater number of patients than the expert classification (7 and 5, respectively). In contrast, in only one case presented the new algorithm resulted in fewer classes and activation areas. We propose that the use of automated spike sorting algorithms to classify IED provides an efficient tool for mapping IED-related fMRI changes and increases the EEG-fMRI clinical value for the pre-surgical assessment of patients with severe epilepsy. Copyright © 2014 Elsevier Inc. All rights reserved.

Kv1.1 channelopathy abolishes presynaptic spike width modulation by subthreshold somatic depolarization

PubMed Central

Vivekananda, Umesh; Novak, Pavel; Bello, Oscar D.; Korchev, Yuri E.; Krishnakumar, Shyam S.; Volynski, Kirill E.; Kullmann, Dimitri M.

2017-01-01

Although action potentials propagate along axons in an all-or-none manner, subthreshold membrane potential fluctuations at the soma affect neurotransmitter release from synaptic boutons. An important mechanism underlying analog–digital modulation is depolarization-mediated inactivation of presynaptic Kv1-family potassium channels, leading to action potential broadening and increased calcium influx. Previous studies have relied heavily on recordings from blebs formed after axon transection, which may exaggerate the passive propagation of somatic depolarization. We recorded instead from small boutons supplied by intact axons identified with scanning ion conductance microscopy in primary hippocampal cultures and asked how distinct potassium channels interact in determining the basal spike width and its modulation by subthreshold somatic depolarization. Pharmacological or genetic deletion of Kv1.1 broadened presynaptic spikes without preventing further prolongation by brief depolarizing somatic prepulses. A heterozygous mouse model of episodic ataxia type 1 harboring a dominant Kv1.1 mutation had a similar broadening effect on basal spike shape as deletion of Kv1.1; however, spike modulation by somatic prepulses was abolished. These results argue that the Kv1.1 subunit is not necessary for subthreshold modulation of spike width. However, a disease-associated mutant subunit prevents the interplay of analog and digital transmission, possibly by disrupting the normal stoichiometry of presynaptic potassium channels. PMID:28193892

On the robustness of EC-PC spike detection method for online neural recording.

PubMed

Zhou, Yin; Wu, Tong; Rastegarnia, Amir; Guan, Cuntai; Keefer, Edward; Yang, Zhi

2014-09-30

Online spike detection is an important step to compress neural data and perform real-time neural information decoding. An unsupervised, automatic, yet robust signal processing is strongly desired, thus it can support a wide range of applications. We have developed a novel spike detection algorithm called "exponential component-polynomial component" (EC-PC) spike detection. We firstly evaluate the robustness of the EC-PC spike detector under different firing rates and SNRs. Secondly, we show that the detection Precision can be quantitatively derived without requiring additional user input parameters. We have realized the algorithm (including training) into a 0.13 μm CMOS chip, where an unsupervised, nonparametric operation has been demonstrated. Both simulated data and real data are used to evaluate the method under different firing rates (FRs), SNRs. The results show that the EC-PC spike detector is the most robust in comparison with some popular detectors. Moreover, the EC-PC detector can track changes in the background noise due to the ability to re-estimate the neural data distribution. Both real and synthesized data have been used for testing the proposed algorithm in comparison with other methods, including the absolute thresholding detector (AT), median absolute deviation detector (MAD), nonlinear energy operator detector (NEO), and continuous wavelet detector (CWD). Comparative testing results reveals that the EP-PC detection algorithm performs better than the other algorithms regardless of recording conditions. The EC-PC spike detector can be considered as an unsupervised and robust online spike detection. It is also suitable for hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

Effects of changing the ionic environment on passive and active membrane properties of pregnant rat uterus

PubMed Central

Abe, Y.

1971-01-01

1. In pregnant rat myometrium electrotonic potentials, produced by externally applied current, were recorded intracellularly. 2. The space constant, λ, was 1·8 mm, the time constant, τm, 120 msec. The values obtained on the 7th day and on the 20th day of pregnancy were the same. 3. The magnitude of the electrotonic potential and the time constant of the membrane were increased in the absence of potassium from the external solution and decreased by excess potassium. 4. The magnitude of the electrotonic potential and the time constant of the membrane were increased by the replacement of chloride with C6H5SO3- or SO42-, and decreased with NO3- or I- replacement. 5. When the sodium chloride was replaced with sucrose (16·7 mM sodium remaining in the buffers) the spontaneous spikes deteriorated and activity stopped within 30 min. However, for periods up to 4 hr, a spike of larger amplitude and faster rate of rise than in normal solution could be evoked when a depolarizing current was applied. 6. When the external calcium concentration was raised (5 and 10 mM) the amplitude and the rate of rise of the evoked spike were increased. They were decreased by reducing calcium. In zero calcium spontaneous activity stopped within 15 min. 7. The effects of calcium deficiency were much less marked and slower in onset when, simultaneously, the sodium concentration was reduced to 16·7 mM. 8. When calcium was replaced with strontium (2·5 mM), the membrane was depolarized and the duration of the spontaneous and evoked action potential was prolonged, mainly due to a slowed rate of repolarization. When the concentration of strontium was raised to 7·5 or 12·5 mM the membrane was hyperpolarized, the duration of the action potential became short and the amplitude of the spike was increased. 9. Addition of barium or the replacement of calcium with barium caused depolarization and oscillatory membrane activity. However, a spike could be evoked by applying conditioning hyperpolarization. 10. Manganese abolished the spontaneous and evoked spike. Tetrodotoxin had no effect. 11. The results show that rat uterus has cable-like properties. The action potential may be due to calcium entry, while sodium, by influencing the membrane potential in competition with calcium, may be involved in the spontaneous spike generation and the spread of excitation. PMID:5103422

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.

Input-output relation and energy efficiency in the neuron with different spike threshold dynamics.

PubMed

Yi, Guo-Sheng; Wang, Jiang; Tsang, Kai-Ming; Wei, Xi-Le; Deng, Bin

2015-01-01

Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt) preceding a spike. Identifying the metabolic energy involved in neural coding and their relationship to threshold dynamic is critical to understanding neuronal function and evolution. Here, we use a modified Morris-Lecar model to investigate neuronal input-output property and energy efficiency associated with different spike threshold dynamics. We find that the neurons with dynamic threshold sensitive to dV/dt generate discontinuous frequency-current curve and type II phase response curve (PRC) through Hopf bifurcation, and weak noise could prohibit spiking when bifurcation just occurs. The threshold that is insensitive to dV/dt, instead, results in a continuous frequency-current curve, a type I PRC and a saddle-node on invariant circle bifurcation, and simultaneously weak noise cannot inhibit spiking. It is also shown that the bifurcation, frequency-current curve and PRC type associated with different threshold dynamics arise from the distinct subthreshold interactions of membrane currents. Further, we observe that the energy consumption of the neuron is related to its firing characteristics. The depolarization of spike threshold improves neuronal energy efficiency by reducing the overlap of Na(+) and K(+) currents during an action potential. The high energy efficiency is achieved at more depolarized spike threshold and high stimulus current. These results provide a fundamental biophysical connection that links spike threshold dynamics, input-output relation, energetics and spike initiation, which could contribute to uncover neural encoding mechanism.

Input-output relation and energy efficiency in the neuron with different spike threshold dynamics

PubMed Central

Yi, Guo-Sheng; Wang, Jiang; Tsang, Kai-Ming; Wei, Xi-Le; Deng, Bin

2015-01-01

Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt) preceding a spike. Identifying the metabolic energy involved in neural coding and their relationship to threshold dynamic is critical to understanding neuronal function and evolution. Here, we use a modified Morris-Lecar model to investigate neuronal input-output property and energy efficiency associated with different spike threshold dynamics. We find that the neurons with dynamic threshold sensitive to dV/dt generate discontinuous frequency-current curve and type II phase response curve (PRC) through Hopf bifurcation, and weak noise could prohibit spiking when bifurcation just occurs. The threshold that is insensitive to dV/dt, instead, results in a continuous frequency-current curve, a type I PRC and a saddle-node on invariant circle bifurcation, and simultaneously weak noise cannot inhibit spiking. It is also shown that the bifurcation, frequency-current curve and PRC type associated with different threshold dynamics arise from the distinct subthreshold interactions of membrane currents. Further, we observe that the energy consumption of the neuron is related to its firing characteristics. The depolarization of spike threshold improves neuronal energy efficiency by reducing the overlap of Na+ and K+ currents during an action potential. The high energy efficiency is achieved at more depolarized spike threshold and high stimulus current. These results provide a fundamental biophysical connection that links spike threshold dynamics, input-output relation, energetics and spike initiation, which could contribute to uncover neural encoding mechanism. PMID:26074810

Simultaneous video analysis of the kinematics of opercular movement and electromyographic activity during agonistic display in Siamese fighting fish.

PubMed

Polnau, D G; Ma, P M

2001-12-01

Neuroethology seeks to uncover the neural mechanisms underlying natural behaviour. One of the major challenges in this field is the need to correlate directly neural activity and behavioural output. In most cases, recording of neural activity in freely moving animals is extremely difficult. However, electromyographic recording can often be used in lieu of neural recording to gain an understanding of the motor output program underlying a well-defined behaviour. Electromyographic recording is less invasive than most other recording methods, and does not impede the performance of most natural tasks. Using the opercular display of the Siamese fighting fish as a model, we developed a protocol for correlating directly electromyographic activity and kinematics of opercular movement: electromyographic activity was recorded in the audio channel of a video cassette recorder while video taping the display behaviour. By combining computer-assisted, quantitative video analysis and spike analysis, the kinematics of opercular movement are linked to the motor output program. Since the muscle that mediates opercular abduction in this fish, the dilator operculi, is a relatively small muscle with several subdivisions, we also describe methods for recording from small muscles and marking the precise recording site with electrolytic corrosion. The protocol described here is applicable to studies of a variety of natural behaviour that can be performed in a relatively confined space. It is also useful for analyzing complex or rapidly changing behaviour in which a precise correlation between kinematics and electromyography is required.

Spike-Threshold Adaptation Predicted by Membrane Potential Dynamics In Vivo

PubMed Central

Fontaine, Bertrand; Peña, José Luis; Brette, Romain

2014-01-01

Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo. PMID:24722397

Burst and Principal Components Analyses of MEA Data Separates Chemicals by Class

EPA Science Inventory

Microelectrode arrays (MEAs) detect drug and chemical induced changes in action potential "spikes" in neuronal networks and can be used to screen chemicals for neurotoxicity. Analytical "fingerprinting," using Principal Components Analysis (PCA) on spike trains recorded from prim...

High-frequency oscillations mirror disease activity in patients with epilepsy.

PubMed

Zijlmans, M; Jacobs, J; Zelmann, R; Dubeau, F; Gotman, J

2009-03-17

High-frequency oscillations (HFOs) can be recorded in epileptic patients with clinical intracranial EEG. HFOs have been associated with seizure genesis because they occur in the seizure focus and during seizure onset. HFOs are also found interictally, partly co-occurring with epileptic spikes. We studied how HFOs are influenced by antiepileptic medication and seizure occurrence, to improve understanding of the pathophysiology and clinical meaning of HFOs. Intracerebral depth EEG was partly sampled at 2,000 Hz in 42 patients with intractable focal epilepsy. Patients with five or more usable nights of recording were selected. A sample of slow-wave sleep from each night was analyzed, and HFOs (ripples: 80-250 Hz, fast ripples: 250-500 Hz) and spikes were identified on all artifact-free channels. The HFOs and spikes were compared before and after seizures with stable medication dose and during medication reduction with no intervening seizures. Twelve patients with five to eight nights were included. After seizures, there was an increase in spikes, whereas HFO rates remained the same. Medication reduction was followed by an increase in HFO rates and mean duration. Contrary to spikes, high-frequency oscillations (HFOs) do not increase after seizures, but do so after medication reduction, similarly to seizures. This implies that spikes and HFOs have different pathophysiologic mechanisms and that HFOs are more tightly linked to seizures than spikes. HFOs seem to play an important role in seizure genesis and can be a useful clinical marker for disease activity.

Non-causal spike filtering improves decoding of movement intention for intracortical BCIs

PubMed Central

Masse, Nicolas Y.; Jarosiewicz, Beata; Simeral, John D.; Bacher, Daniel; Stavisky, Sergey D.; Cash, Sydney S.; Oakley, Erin M.; Berhanu, Etsub; Eskandar, Emad; Friehs, Gerhard; Hochberg, Leigh R.; Donoghue, John P.

2014-01-01

Background Multiple types of neural signals are available for controlling assistive devices through brain-computer interfaces (BCIs). Intracortically-recorded spiking neural signals are attractive for BCIs because they can in principle provide greater fidelity of encoded information compared to electrocorticographic (ECoG) signals and electroencephalograms (EEGs). Recent reports show that the information content of these spiking neural signals can be reliably extracted simply by causally band-pass filtering the recorded extracellular voltage signals and then applying a spike detection threshold, without relying on “sorting” action potentials. New method We show that replacing the causal filter with an equivalent non-causal filter increases the information content extracted from the extracellular spiking signal and improves decoding of intended movement direction. This method can be used for real-time BCI applications by using a 4 ms lag between recording and filtering neural signals. Results Across 18 sessions from two people with tetraplegia enrolled in the BrainGate2 pilot clinical trial, we found that threshold crossing events extracted using this non-causal filtering method were significantly more informative of each participant’s intended cursor kinematics compared to threshold crossing events derived from causally filtered signals. This new method decreased the mean angular error between the intended and decoded cursor direction by 9.7° for participant S3, who was implanted 5.4 years prior to this study, and by 3.5° for participant T2, who was implanted 3 months prior to this study. Conclusions Non-causally filtering neural signals prior to extracting threshold crossing events may be a simple yet effective way to condition intracortically recorded neural activity for direct control of external devices through BCIs. PMID:25128256

Stimuli Reduce the Dimensionality of Cortical Activity

PubMed Central

Mazzucato, Luca; Fontanini, Alfredo; La Camera, Giancarlo

2016-01-01

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models. PMID:26924968

Stimuli Reduce the Dimensionality of Cortical Activity.

PubMed

Mazzucato, Luca; Fontanini, Alfredo; La Camera, Giancarlo

2016-01-01

The activity of ensembles of simultaneously recorded neurons can be represented as a set of points in the space of firing rates. Even though the dimension of this space is equal to the ensemble size, neural activity can be effectively localized on smaller subspaces. The dimensionality of the neural space is an important determinant of the computational tasks supported by the neural activity. Here, we investigate the dimensionality of neural ensembles from the sensory cortex of alert rats during periods of ongoing (inter-trial) and stimulus-evoked activity. We find that dimensionality grows linearly with ensemble size, and grows significantly faster during ongoing activity compared to evoked activity. We explain these results using a spiking network model based on a clustered architecture. The model captures the difference in growth rate between ongoing and evoked activity and predicts a characteristic scaling with ensemble size that could be tested in high-density multi-electrode recordings. Moreover, we present a simple theory that predicts the existence of an upper bound on dimensionality. This upper bound is inversely proportional to the amount of pair-wise correlations and, compared to a homogeneous network without clusters, it is larger by a factor equal to the number of clusters. The empirical estimation of such bounds depends on the number and duration of trials and is well predicted by the theory. Together, these results provide a framework to analyze neural dimensionality in alert animals, its behavior under stimulus presentation, and its theoretical dependence on ensemble size, number of clusters, and correlations in spiking network models.

Robust spike classification based on frequency domain neural waveform features.

PubMed

Yang, Chenhui; Yuan, Yuan; Si, Jennie

2013-12-01

We introduce a new spike classification algorithm based on frequency domain features of the spike snippets. The goal for the algorithm is to provide high classification accuracy, low false misclassification, ease of implementation, robustness to signal degradation, and objectivity in classification outcomes. In this paper, we propose a spike classification algorithm based on frequency domain features (CFDF). It makes use of frequency domain contents of the recorded neural waveforms for spike classification. The self-organizing map (SOM) is used as a tool to determine the cluster number intuitively and directly by viewing the SOM output map. After that, spike classification can be easily performed using clustering algorithms such as the k-Means. In conjunction with our previously developed multiscale correlation of wavelet coefficient (MCWC) spike detection algorithm, we show that the MCWC and CFDF detection and classification system is robust when tested on several sets of artificial and real neural waveforms. The CFDF is comparable to or outperforms some popular automatic spike classification algorithms with artificial and real neural data. The detection and classification of neural action potentials or neural spikes is an important step in single-unit-based neuroscientific studies and applications. After the detection of neural snippets potentially containing neural spikes, a robust classification algorithm is applied for the analysis of the snippets to (1) extract similar waveforms into one class for them to be considered coming from one unit, and to (2) remove noise snippets if they do not contain any features of an action potential. Usually, a snippet is a small 2 or 3 ms segment of the recorded waveform, and differences in neural action potentials can be subtle from one unit to another. Therefore, a robust, high performance classification system like the CFDF is necessary. In addition, the proposed algorithm does not require any assumptions on statistical properties of the noise and proves to be robust under noise contamination.

Revealing degree distribution of bursting neuron networks.

PubMed

Shen, Yu; Hou, Zhonghuai; Xin, Houwen

2010-03-01

We present a method to infer the degree distribution of a bursting neuron network from its dynamics. Burst synchronization (BS) of coupled Morris-Lecar neurons has been studied under the weak coupling condition. In the BS state, all the neurons start and end bursting almost simultaneously, while the spikes inside the burst are incoherent among the neurons. Interestingly, we find that the spike amplitude of a given neuron shows an excellent linear relationship with its degree, which makes it possible to estimate the degree distribution of the network by simple statistics of the spike amplitudes. We demonstrate the validity of this scheme on scale-free as well as small-world networks. The underlying mechanism of such a method is also briefly discussed.

Cochlear spike synchronization and neuron coincidence detection model

NASA Astrophysics Data System (ADS)

Bader, Rolf

2018-02-01

Coincidence detection of a spike pattern fed from the cochlea into a single neuron is investigated using a physical Finite-Difference model of the cochlea and a physiologically motivated neuron model. Previous studies have shown experimental evidence of increased spike synchronization in the nucleus cochlearis and the trapezoid body [Joris et al., J. Neurophysiol. 71(3), 1022-1036 and 1037-1051 (1994)] and models show tone partial phase synchronization at the transition from mechanical waves on the basilar membrane into spike patterns [Ch. F. Babbs, J. Biophys. 2011, 435135]. Still the traveling speed of waves on the basilar membrane cause a frequency-dependent time delay of simultaneously incoming sound wavefronts up to 10 ms. The present model shows nearly perfect synchronization of multiple spike inputs as neuron outputs with interspike intervals (ISI) at the periodicity of the incoming sound for frequencies from about 30 to 300 Hz for two different amounts of afferent nerve fiber neuron inputs. Coincidence detection serves here as a fusion of multiple inputs into one single event enhancing pitch periodicity detection for low frequencies, impulse detection, or increased sound or speech intelligibility due to dereverberation.

Reprint of “Non-causal spike filtering improves decoding of movement intention for intracortical BCIs”☆

PubMed Central

Masse, Nicolas Y.; Jarosiewicz, Beata; Simeral, John D.; Bacher, Daniel; Stavisky, Sergey D.; Cash, Sydney S.; Oakley, Erin M.; Berhanu, Etsub; Eskandar, Emad; Friehs, Gerhard; Hochberg, Leigh R.; Donoghue, John P.

2015-01-01

Background Multiple types of neural signals are available for controlling assistive devices through brain–computer interfaces (BCIs). Intracortically recorded spiking neural signals are attractive for BCIs because they can in principle provide greater fidelity of encoded information compared to electrocorticographic (ECoG) signals and electroencephalograms (EEGs). Recent reports show that the information content of these spiking neural signals can be reliably extracted simply by causally band-pass filtering the recorded extracellular voltage signals and then applying a spike detection threshold, without relying on “sorting” action potentials. New method We show that replacing the causal filter with an equivalent non-causal filter increases the information content extracted from the extracellular spiking signal and improves decoding of intended movement direction. This method can be used for real-time BCI applications by using a 4 ms lag between recording and filtering neural signals. Results Across 18 sessions from two people with tetraplegia enrolled in the BrainGate2 pilot clinical trial, we found that threshold crossing events extracted using this non-causal filtering method were significantly more informative of each participant’s intended cursor kinematics compared to threshold crossing events derived from causally filtered signals. This new method decreased the mean angular error between the intended and decoded cursor direction by 9.7° for participant S3, who was implanted 5.4 years prior to this study, and by 3.5° for participant T2, who was implanted 3 months prior to this study. PMID:25681017

Prospective Identification of Oligoclonal/Abnormal Band of the Same Immunoglobulin Type as the Malignant Clone by Differential Location of M-Spike and Oligoclonal Band.

PubMed

Vyas, Shikhar G; Singh, Gurmukh

2017-10-01

Serum and urine protein electrophoreses and immunofixation electrophoreses are the gold standards in diagnosing monoclonal gammopathy. Identification of oligoclonal bands in post-treatment patients has emerged as an important issue and recording the location of the malignant monoclonal peak may facilitate prospective identification of a new "monoclonal" spike as being distinct from the malignant peak. We recorded the locations of monoclonal spikes in descriptive terms, such as being in the cathodal region, mid-gamma region, anodal region, and beta region. The location of monoclonal or restricted heterogeneity bands in subsequent protein electrophoreses was compared to the location of the original malignant spike. In a patient with plasma cell myeloma, the original monoclonal IgG kappa band was located at the anodal end of gamma region. Post-treatment, an IgG kappa band was noted in mid-gamma region and the primary malignant clone was not detectable by serum protein immunofixation electrophoresis (SIFE) in post-treatment sample. Even though the κ/λ ratio remained abnormal, we were able to recognize stringent complete response by noting the different location of the new IgG kappa band as a benign regenerative process. Recording the location of the malignant monoclonal spike facilitates the identification of post-treatment oligoclonal bands, prospectively. Recognizing the regenerative, benign, bands in post-transplant patients facilitates the determination of stringent complete response despite an abnormal κ/λ ratio.

Bidirectional control of spike timing by GABA(A) receptor-mediated inhibition during theta oscillation in CA1 pyramidal neurons.

PubMed

Kwag, Jeehyun; Paulsen, Ole

2009-08-26

Precisely controlled spike times relative to theta-frequency network oscillations play an important role in hippocampal memory processing. Here we study how inhibitory synaptic input during theta oscillation contributes to the control of spike timing. Using whole-cell patch-clamp recordings from CA1 pyramidal cells in vitro with dynamic clamp to simulate theta-frequency oscillation (5 Hz), we show that gamma-aminobutyric acid-A (GABA(A)) receptor-mediated inhibitory postsynaptic potentials (IPSPs) can not only delay but also advance the postsynaptic spike depending on the timing of the inhibition relative to the oscillation. Spike time advancement with IPSP was abolished by the h-channel blocker ZD7288 (10 microM), suggesting that IPSPs can interact with intrinsic membrane conductances to yield bidirectional control of spike timing.

An Unsupervised Online Spike-Sorting Framework.

PubMed

Knieling, Simeon; Sridharan, Kousik S; Belardinelli, Paolo; Naros, Georgios; Weiss, Daniel; Mormann, Florian; Gharabaghi, Alireza

2016-08-01

Extracellular neuronal microelectrode recordings can include action potentials from multiple neurons. To separate spikes from different neurons, they can be sorted according to their shape, a procedure referred to as spike-sorting. Several algorithms have been reported to solve this task. However, when clustering outcomes are unsatisfactory, most of them are difficult to adjust to achieve the desired results. We present an online spike-sorting framework that uses feature normalization and weighting to maximize the distinctiveness between different spike shapes. Furthermore, multiple criteria are applied to either facilitate or prevent cluster fusion, thereby enabling experimenters to fine-tune the sorting process. We compare our method to established unsupervised offline (Wave_Clus (WC)) and online (OSort (OS)) algorithms by examining their performance in sorting various test datasets using two different scoring systems (AMI and the Adamos metric). Furthermore, we evaluate sorting capabilities on intra-operative recordings using established quality metrics. Compared to WC and OS, our algorithm achieved comparable or higher scores on average and produced more convincing sorting results for intra-operative datasets. Thus, the presented framework is suitable for both online and offline analysis and could substantially improve the quality of microelectrode-based data evaluation for research and clinical application.

Scene segmentation by spike synchronization in reciprocally connected visual areas. I. Local effects of cortical feedback.

PubMed

Knoblauch, Andreas; Palm, Günther

2002-09-01

To investigate scene segmentation in the visual system we present a model of two reciprocally connected visual areas using spiking neurons. Area P corresponds to the orientation-selective subsystem of the primary visual cortex, while the central visual area C is modeled as associative memory representing stimulus objects according to Hebbian learning. Without feedback from area C, a single stimulus results in relatively slow and irregular activity, synchronized only for neighboring patches (slow state), while in the complete model activity is faster with an enlarged synchronization range (fast state). When presenting a superposition of several stimulus objects, scene segmentation happens on a time scale of hundreds of milliseconds by alternating epochs of the slow and fast states, where neurons representing the same object are simultaneously in the fast state. Correlation analysis reveals synchronization on different time scales as found in experiments (designated as tower, castle, and hill peaks). On the fast time scale (tower peaks, gamma frequency range), recordings from two sites coding either different or the same object lead to correlograms that are either flat or exhibit oscillatory modulations with a central peak. This is in agreement with experimental findings, whereas standard phase-coding models would predict shifted peaks in the case of different objects.

A 1.5-to-5 V converter for a battery-powered activity-dependent intracortical microstimulation SoC.

PubMed

Azin, Meysam; Mohseni, Pedram

2012-01-01

This paper reports on the design, analysis, implementation, and testing of a 1.5-to-5 V converter as part of a battery-powered activity-dependent intracortical microstimulation (ICMS) system-on-chip (SoC) that converts extracellular neural spikes recorded from one cortical area to electrical stimuli delivered to another cortical area in real time. The highly integrated voltage converter is intended to generate a 5-V supply for the stimulating back-end on the SoC from a miniature primary battery that powers the entire system. It is implemented in AMS 0.35 µm two-poly four-metal (2P/4M) complementary metal-oxide-semiconductor (CMOS) technology, employs only one external capacitor (1 µF) for storage, and delivers a maximum dc load current of ~88 µA with power efficiency of 31% with its output voltage adjusted to 5.05 V. This current drive capability affords simultaneous stimulation on all eight channels of the SoC with current amplitude up to ~100 µA and average stimulus rate >500 Hz, which is comfortably higher than firing rate of cortical neurons (<150 spikes per second). The measurement results also agree favorably with theoretical derivations from the analysis of converter operation.

Human Subthalamic Nucleus Theta and Beta Oscillations Entrain Neuronal Firing During Sensorimotor Conflict.

PubMed

Zavala, Baltazar; Damera, Srikanth; Dong, Jian Wilson; Lungu, Codrin; Brown, Peter; Zaghloul, Kareem A

2017-01-01

Recent evidence has suggested that prefrontal cortical structures may inhibit impulsive actions during conflict through activation of the subthalamic nucleus (STN). Consistent with this hypothesis, deep brain stimulation to the STN has been associated with altered prefrontal cortical activity and impaired response inhibition. The interactions between oscillatory activity in the STN and its presumably antikinetic neuronal spiking, however, remain poorly understood. Here, we simultaneously recorded intraoperative local field potential and spiking activity from the human STN as participants performed a sensorimotor action selection task involving conflict. We identified several STN neuronal response types that exhibited different temporal dynamics during the task. Some neurons showed early, cue-related firing rate increases that remained elevated longer during high conflict trials, whereas other neurons showed late, movement-related firing rate increases. Notably, the high conflict trials were associated with an entrainment of individual neurons by theta- and beta-band oscillations, both of which have been observed in cortical structures involved in response inhibition. Our data suggest that frequency-specific activity in the beta and theta bands influence STN firing to inhibit impulsivity during conflict. Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Deconstruction of spatial integrity in visual stimulus detected by modulation of synchronized activity in cat visual cortex.

PubMed

Zhou, Zhiyi; Bernard, Melanie R; Bonds, A B

2008-04-02

Spatiotemporal relationships among contour segments can influence synchronization of neural responses in the primary visual cortex. We performed a systematic study to dissociate the impact of spatial and temporal factors in the signaling of contour integration via synchrony. In addition, we characterized the temporal evolution of this process to clarify potential underlying mechanisms. With a 10 x 10 microelectrode array, we recorded the simultaneous activity of multiple cells in the cat primary visual cortex while stimulating with drifting sine-wave gratings. We preserved temporal integrity and systematically degraded spatial integrity of the sine-wave gratings by adding spatial noise. Neural synchronization was analyzed in the time and frequency domains by conducting cross-correlation and coherence analyses. The general association between neural spike trains depends strongly on spatial integrity, with coherence in the gamma band (35-70 Hz) showing greater sensitivity to the change of spatial structure than other frequency bands. Analysis of the temporal dynamics of synchronization in both time and frequency domains suggests that spike timing synchronization is triggered nearly instantaneously by coherent structure in the stimuli, whereas frequency-specific oscillatory components develop more slowly, presumably through network interactions. Our results suggest that, whereas temporal integrity is required for the generation of synchrony, spatial integrity is critical in triggering subsequent gamma band synchronization.

Dynamic Alignment Models for Neural Coding

PubMed Central

Kollmorgen, Sepp; Hahnloser, Richard H. R.

2014-01-01

Recently, there have been remarkable advances in modeling the relationships between the sensory environment, neuronal responses, and behavior. However, most models cannot encompass variable stimulus-response relationships such as varying response latencies and state or context dependence of the neural code. Here, we consider response modeling as a dynamic alignment problem and model stimulus and response jointly by a mixed pair hidden Markov model (MPH). In MPHs, multiple stimulus-response relationships (e.g., receptive fields) are represented by different states or groups of states in a Markov chain. Each stimulus-response relationship features temporal flexibility, allowing modeling of variable response latencies, including noisy ones. We derive algorithms for learning of MPH parameters and for inference of spike response probabilities. We show that some linear-nonlinear Poisson cascade (LNP) models are a special case of MPHs. We demonstrate the efficiency and usefulness of MPHs in simulations of both jittered and switching spike responses to white noise and natural stimuli. Furthermore, we apply MPHs to extracellular single and multi-unit data recorded in cortical brain areas of singing birds to showcase a novel method for estimating response lag distributions. MPHs allow simultaneous estimation of receptive fields, latency statistics, and hidden state dynamics and so can help to uncover complex stimulus response relationships that are subject to variable timing and involve diverse neural codes. PMID:24625448

Sample preparation combined with electroanalysis to improve simultaneous determination of antibiotics in animal derived food samples.

PubMed

da Silva, Wesley Pereira; de Oliveira, Luiz Henrique; Santos, André Luiz Dos; Ferreira, Valdir Souza; Trindade, Magno Aparecido Gonçalves

2018-06-01

A procedure based on liquid-liquid extraction (LLE) and phase separation using magnetically stirred salt-induced high-temperature liquid-liquid extraction (PS-MSSI-HT-LLE) was developed to extract and pre-concentrate ciprofloxacin (CIPRO) and enrofloxacin (ENRO) from animal food samples before electroanalysis. Firstly, simple LLE was used to extract the fluoroquinolones (FQs) from animal food samples, in which dilution was performed to reduce interference effects to below a tolerable threshold. Then, adapted PS-MSSI-HT-LLE protocols allowed re-extraction and further pre-concentration of target analytes in the diluted acid samples for simultaneous electrochemical quantification at low concentration levels. To improve the peak separation, in simultaneous detection, a baseline-corrected second-order derivative approach was processed. These approaches allowed quantification of target FQs from animal food samples spiked at levels of 0.80 to 2.00 µmol L -1 in chicken meat, with recovery values always higher than 80.5%, as well as in milk samples spiked at 4.00 µmol L -1 , with recovery values close to 70.0%. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparative study of six sequential spectrophotometric methods for quantification and separation of ribavirin, sofosbuvir and daclatasvir: An application on Laboratory prepared mixture, pharmaceutical preparations, spiked human urine, spiked human plasma, and dissolution test.

PubMed

Hassan, Wafaa S; Elmasry, Manal S; Elsayed, Heba M; Zidan, Dalia W

2018-09-05

In accordance with International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) guidelines, six novel, simple and precise sequential spectrophotometric methods were developed and validated for the simultaneous analysis of Ribavirin (RIB), Sofosbuvir (SOF), and Daclatasvir (DAC) in their mixture without prior separation steps. These drugs are described as co-administered for treatment of Hepatitis C virus (HCV). HCV is the cause of hepatitis C and some cancers such as liver cancer (hepatocellular carcinoma) and lymphomas in humans. These techniques consisted of several sequential steps using zero, ratio and/or derivative spectra. DAC was first determined through direct spectrophotometry at 313.7 nm without any interference of the other two drugs while RIB and SOF can be determined after ratio subtraction through five methods; Ratio difference spectrophotometric method, successive derivative ratio method, constant center, isoabsorptive method at 238.8 nm, and mean centering of the ratio spectra (MCR) at 224 nm and 258 nm for RIB and SOF, respectively. The calibration curve is linear over the concentration ranges of (6-42), (10-70) and (4-16) μg/mL for RIB, SOF, and DAC, respectively. This method was successfully applied to commercial pharmaceutical preparation of the drugs, spiked human urine, and spiked human plasma. The above methods are very simple methods that were developed for the simultaneous determination of binary and ternary mixtures and so enhance signal-to-noise ratio. The method has been successfully applied to the simultaneous analysis of RIB, SOF, and DAC in laboratory prepared mixtures. The obtained results are statistically compared with those obtained by the official or reported methods, showing no significant difference with respect to accuracy and precision at p = 0.05. Copyright © 2018 Elsevier B.V. All rights reserved.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE.

PubMed

Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M; Grün, Sonja

2017-01-01

Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

PubMed Central

Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M.; Grün, Sonja

2017-01-01

Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis. PMID:28596729

A method for decoding the neurophysiological spike-response transform.

PubMed

Stern, Estee; García-Crescioni, Keyla; Miller, Mark W; Peskin, Charles S; Brezina, Vladimir

2009-11-15

Many physiological responses elicited by neuronal spikes-intracellular calcium transients, synaptic potentials, muscle contractions-are built up of discrete, elementary responses to each spike. However, the spikes occur in trains of arbitrary temporal complexity, and each elementary response not only sums with previous ones, but can itself be modified by the previous history of the activity. A basic goal in system identification is to characterize the spike-response transform in terms of a small number of functions-the elementary response kernel and additional kernels or functions that describe the dependence on previous history-that will predict the response to any arbitrary spike train. Here we do this by developing further and generalizing the "synaptic decoding" approach of Sen et al. (1996). Given the spike times in a train and the observed overall response, we use least-squares minimization to construct the best estimated response and at the same time best estimates of the elementary response kernel and the other functions that characterize the spike-response transform. We avoid the need for any specific initial assumptions about these functions by using techniques of mathematical analysis and linear algebra that allow us to solve simultaneously for all of the numerical function values treated as independent parameters. The functions are such that they may be interpreted mechanistically. We examine the performance of the method as applied to synthetic data. We then use the method to decode real synaptic and muscle contraction transforms.

Neuron-Type-Specific Utility in a Brain-Machine Interface: a Pilot Study.

PubMed

Garcia-Garcia, Martha G; Bergquist, Austin J; Vargas-Perez, Hector; Nagai, Mary K; Zariffa, Jose; Marquez-Chin, Cesar; Popovic, Milos R

2017-11-01

Firing rates of single cortical neurons can be volitionally modulated through biofeedback (i.e. operant conditioning), and this information can be transformed to control external devices (i.e. brain-machine interfaces; BMIs). However, not all neurons respond to operant conditioning in BMI implementation. Establishing criteria that predict neuron utility will assist translation of BMI research to clinical applications. Single cortical neurons (n=7) were recorded extracellularly from primary motor cortex of a Long-Evans rat. Recordings were incorporated into a BMI involving up-regulation of firing rate to control the brightness of a light-emitting-diode and subsequent reward. Neurons were classified as 'fast-spiking', 'bursting' or 'regular-spiking' according to waveform-width and intrinsic firing patterns. Fast-spiking and bursting neurons were found to up-regulate firing rate by a factor of 2.43±1.16, demonstrating high utility, while regular-spiking neurons decreased firing rates on average by a factor of 0.73±0.23, demonstrating low utility. The ability to select neurons with high utility will be important to minimize training times and maximize information yield in future clinical BMI applications. The highly contrasting utility observed between fast-spiking and bursting neurons versus regular-spiking neurons allows for the hypothesis to be advanced that intrinsic electrophysiological properties may be useful criteria that predict neuron utility in BMI implementation.

Spatiotemporal Mapping of Interictal Spike Propagation: A Novel Methodology Applied to Pediatric Intracranial EEG Recordings

PubMed Central

Tomlinson, Samuel B.; Bermudez, Camilo; Conley, Chiara; Brown, Merritt W.; Porter, Brenda E.; Marsh, Eric D.

2016-01-01

Synchronized cortical activity is implicated in both normative cognitive functioning and many neurologic disorders. For epilepsy patients with intractable seizures, irregular synchronization within the epileptogenic zone (EZ) is believed to provide the network substrate through which seizures initiate and propagate. Mapping the EZ prior to epilepsy surgery is critical for detecting seizure networks in order to achieve postsurgical seizure control. However, automated techniques for characterizing epileptic networks have yet to gain traction in the clinical setting. Recent advances in signal processing and spike detection have made it possible to examine the spatiotemporal propagation of interictal spike discharges across the epileptic cortex. In this study, we present a novel methodology for detecting, extracting, and visualizing spike propagation and demonstrate its potential utility as a biomarker for the EZ. Eighteen presurgical intracranial EEG recordings were obtained from pediatric patients ultimately experiencing favorable (i.e., seizure-free, n = 9) or unfavorable (i.e., seizure-persistent, n = 9) surgical outcomes. Novel algorithms were applied to extract multichannel spike discharges and visualize their spatiotemporal propagation. Quantitative analysis of spike propagation was performed using trajectory clustering and spatial autocorrelation techniques. Comparison of interictal propagation patterns revealed an increase in trajectory organization (i.e., spatial autocorrelation) among Sz-Free patients compared with Sz-Persist patients. The pathophysiological basis and clinical implications of these findings are considered. PMID:28066315

Intracortical microstimulation induced changes in spectral and temporal response properties in cat auditory cortex.

PubMed

Valentine, Pamela A; Eggermont, Jos J

2003-09-01

Intracortical microstimulation (ICMS), consisting of a 40 ms burst (rate 300 Hz) of 10 microA pulses, repetitively administered once per second, for a total duration of 1 h, induced cortical reorganization in the primary auditory cortical field of the anesthetized cat. Multiple single-unit activity was simultaneously recorded from three to nine microelectrodes. Spiking activity was recorded from the same units prior to and following the application of ICMS in conjunction with tone pips at the characteristic frequency (CF) of the stimulus electrode. ICMS produced a significant increase in the mean firing rate, and in the occurrence of burst activity. There was an increase in the cross-correlation coefficient (R) for unit pairs recorded from sites distant from the ICMS site, and a decrease in R for unit pairs that were recorded at the stimulation site. ICMS induced a shift in the CF, dependent on the difference between the baseline CF and the ICMS-paired tone pip frequency. ICMS also resulted in broader tuning curves, increased driven peak firing rate and reduced response latency. This suggests a lasting reduction in inhibition in a small region surrounding the ICMS site that allows expansion of the frequency range normally represented in the vicinity of the stimulation electrode.

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 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.

EMG prediction from Motor Cortical Recordings via a Non-Negative Point Process Filter

PubMed Central

Nazarpour, Kianoush; Ethier, Christian; Paninski, Liam; Rebesco, James M.; Miall, R. Chris; Miller, Lee E.

2012-01-01

A constrained point process filtering mechanism for prediction of electromyogram (EMG) signals from multi-channel neural spike recordings is proposed here. Filters from the Kalman family are inherently sub-optimal in dealing with non-Gaussian observations, or a state evolution that deviates from the Gaussianity assumption. To address these limitations, we modeled the non-Gaussian neural spike train observations by using a generalized linear model (GLM) that encapsulates covariates of neural activity, including the neurons’ own spiking history, concurrent ensemble activity, and extrinsic covariates (EMG signals). In order to predict the envelopes of EMGs, we reformulated the Kalman filter (KF) in an optimization framework and utilized a non-negativity constraint. This structure characterizes the non-linear correspondence between neural activity and EMG signals reasonably. The EMGs were recorded from twelve forearm and hand muscles of a behaving monkey during a grip-force task. For the case of limited training data, the constrained point process filter improved the prediction accuracy when compared to a conventional Wiener cascade filter (a linear causal filter followed by a static non-linearity) for different bin sizes and delays between input spikes and EMG output. For longer training data sets, results of the proposed filter and that of the Wiener cascade filter were comparable. PMID:21659018

Distinct responses of Purkinje neurons and roles of simple spikes during associative motor learning in larval zebrafish

PubMed Central

Harmon, Thomas C; Magaram, Uri; McLean, David L; Raman, Indira M

2017-01-01

To study cerebellar activity during learning, we made whole-cell recordings from larval zebrafish Purkinje cells while monitoring fictive swimming during associative conditioning. Fish learned to swim in response to visual stimulation preceding tactile stimulation of the tail. Learning was abolished by cerebellar ablation. All Purkinje cells showed task-related activity. Based on how many complex spikes emerged during learned swimming, they were classified as multiple, single, or zero complex spike (MCS, SCS, ZCS) cells. With learning, MCS and ZCS cells developed increased climbing fiber (MCS) or parallel fiber (ZCS) input during visual stimulation; SCS cells fired complex spikes associated with learned swimming episodes. The categories correlated with location. Optogenetically suppressing simple spikes only during visual stimulation demonstrated that simple spikes are required for acquisition and early stages of expression of learned responses, but not their maintenance, consistent with a transient, instructive role for simple spikes during cerebellar learning in larval zebrafish. DOI: http://dx.doi.org/10.7554/eLife.22537.001 PMID:28541889

Hierarchical Adaptive Means (HAM) clustering for hardware-efficient, unsupervised and real-time spike sorting.

PubMed

Paraskevopoulou, Sivylla E; Wu, Di; Eftekhar, Amir; Constandinou, Timothy G

2014-09-30

This work presents a novel unsupervised algorithm for real-time adaptive clustering of neural spike data (spike sorting). The proposed Hierarchical Adaptive Means (HAM) clustering method combines centroid-based clustering with hierarchical cluster connectivity to classify incoming spikes using groups of clusters. It is described how the proposed method can adaptively track the incoming spike data without requiring any past history, iteration or training and autonomously determines the number of spike classes. Its performance (classification accuracy) has been tested using multiple datasets (both simulated and recorded) achieving a near-identical accuracy compared to k-means (using 10-iterations and provided with the number of spike classes). Also, its robustness in applying to different feature extraction methods has been demonstrated by achieving classification accuracies above 80% across multiple datasets. Last but crucially, its low complexity, that has been quantified through both memory and computation requirements makes this method hugely attractive for future hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Simultaneous Thermal Analysis of Remediated Nitrate Salt Surrogates

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

Wayne, David Matthew

The actinide engineering and science group (MET-1) have completed simultaneous thermal analysis and offgas analysis by mass spectrometry (STA-MS) of remediated nitrate salt (RNS) surrogates formulated by the high explosives science and technology group (M-7). The 1.0 to 1.5g surrogate samples were first analyzed as received, then a new set was analyzed with 100-200mL 10M HNO 3 +0.3 MHF added, and a third set was analyzed after 200 mL of a concentrated Pu-AM spike (in 10M HNO 3 +0.3 MHF) was added. The acid and spike solutions were formulated by the actinide analytical chemistry group (C-AAC) using reagent-grade HNO 3more » and HF, which was also used to dissolve a small quantity of mixed, high-fired PuO 2/ AmO 2 oxide.« less

Spatiotemporal dynamics of neocortical excitation and inhibition during human sleep.

PubMed

Peyrache, Adrien; Dehghani, Nima; Eskandar, Emad N; Madsen, Joseph R; Anderson, William S; Donoghue, Jacob A; Hochberg, Leigh R; Halgren, Eric; Cash, Sydney S; Destexhe, Alain

2012-01-31

Intracranial recording is an important diagnostic method routinely used in a number of neurological monitoring scenarios. In recent years, advancements in such recordings have been extended to include unit activity of an ensemble of neurons. However, a detailed functional characterization of excitatory and inhibitory cells has not been attempted in human neocortex, particularly during the sleep state. Here, we report that such feature discrimination is possible from high-density recordings in the neocortex by using 2D multielectrode arrays. Successful separation of regular-spiking neurons (or bursting cells) from fast-spiking cells resulted in well-defined clusters that each showed unique intrinsic firing properties. The high density of the array, which allowed recording from a large number of cells (up to 90), helped us to identify apparent monosynaptic connections, confirming the excitatory and inhibitory nature of regular-spiking and fast-spiking cells, thus categorized as putative pyramidal cells and interneurons, respectively. Finally, we investigated the dynamics of correlations within each class. A marked exponential decay with distance was observed in the case of excitatory but not for inhibitory cells. Although the amplitude of that decline depended on the timescale at which the correlations were computed, the spatial constant did not. Furthermore, this spatial constant is compatible with the typical size of human columnar organization. These findings provide a detailed characterization of neuronal activity, functional connectivity at the microcircuit level, and the interplay of excitation and inhibition in the human neocortex.

Single unit action potentials in humans and the effect of seizure activity

PubMed Central

Merricks, Edward M.; Smith, Elliot H.; McKhann, Guy M.; Goodman, Robert R.; Bateman, Lisa M.; Emerson, Ronald G.

2015-01-01

Spike-sorting algorithms have been used to identify the firing patterns of isolated neurons (‘single units’) from implanted electrode recordings in patients undergoing assessment for epilepsy surgery, but we do not know their potential for providing helpful clinical information. It is important therefore to characterize both the stability of these recordings and also their context. A critical consideration is where the units are located with respect to the focus of the pathology. Recent analyses of neuronal spiking activity, recorded over extended spatial areas using microelectrode arrays, have demonstrated the importance of considering seizure activity in terms of two distinct spatial territories: the ictal core and penumbral territories. The pathological information in these two areas, however, is likely to be very different. We investigated, therefore, whether units could be followed reliably over prolonged periods of times in these two areas, including during seizure epochs. We isolated unit recordings from several hundred neurons from four patients undergoing video-telemetry monitoring for surgical evaluation of focal neocortical epilepsies. Unit stability could last in excess of 40 h, and across multiple seizures. A key finding was that in the penumbra, spike stereotypy was maintained even during the seizure. There was a net tendency towards increased penumbral firing during the seizure, although only a minority of units (10–20%) showed significant changes over the baseline period, and notably, these also included neurons showing significant reductions in firing. In contrast, within the ictal core territories, regions characterized by intense hypersynchronous multi-unit firing, our spike sorting algorithms failed as the units were incorporated into the seizure activity. No spike sorting was possible from that moment until the end of the seizure, but recovery of the spike shape was rapid following seizure termination: some units reappeared within tens of seconds of the end of the seizure, and over 80% reappeared within 3 min (τrecov = 104 ± 22 s). The recovery of the mean firing rate was close to pre-ictal levels also within this time frame, suggesting that the more protracted post-ictal state cannot be explained by persistent cellular neurophysiological dysfunction in either the penumbral or the core territories. These studies lay the foundation for future investigations of how these recordings may inform clinical practice. See Kimchi and Cash (doi:10.1093/awv264) for a scientific commentary on this article. PMID:26187332

Clusterless Decoding of Position From Multiunit Activity Using A Marked Point Process Filter

PubMed Central

Deng, Xinyi; Liu, Daniel F.; Kay, Kenneth; Frank, Loren M.; Eden, Uri T.

2016-01-01

Point process filters have been applied successfully to decode neural signals and track neural dynamics. Traditionally, these methods assume that multiunit spiking activity has already been correctly spike-sorted. As a result, these methods are not appropriate for situations where sorting cannot be performed with high precision such as real-time decoding for brain-computer interfaces. As the unsupervised spike-sorting problem remains unsolved, we took an alternative approach that takes advantage of recent insights about clusterless decoding. Here we present a new point process decoding algorithm that does not require multiunit signals to be sorted into individual units. We use the theory of marked point processes to construct a function that characterizes the relationship between a covariate of interest (in this case, the location of a rat on a track) and features of the spike waveforms. In our example, we use tetrode recordings, and the marks represent a four-dimensional vector of the maximum amplitudes of the spike waveform on each of the four electrodes. In general, the marks may represent any features of the spike waveform. We then use Bayes’ rule to estimate spatial location from hippocampal neural activity. We validate our approach with a simulation study and with experimental data recorded in the hippocampus of a rat moving through a linear environment. Our decoding algorithm accurately reconstructs the rat’s position from unsorted multiunit spiking activity. We then compare the quality of our decoding algorithm to that of a traditional spike-sorting and decoding algorithm. Our analyses show that the proposed decoding algorithm performs equivalently or better than algorithms based on sorted single-unit activity. These results provide a path toward accurate real-time decoding of spiking patterns that could be used to carry out content-specific manipulations of population activity in hippocampus or elsewhere in the brain. PMID:25973549

Temporal Correlations and Neural Spike Train Entropy

NASA Astrophysics Data System (ADS)

Schultz, Simon R.; Panzeri, Stefano

2001-06-01

Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limited samples of data. This approach also yields insight to the role of correlations between spikes in temporal coding mechanisms. The method, when applied to recordings from complex cells of the monkey primary visual cortex, results in lower rms error information estimates in comparison to a ``brute force'' approach.

Reconstruction of audio waveforms from spike trains of artificial cochlea models

PubMed Central

Zai, Anja T.; Bhargava, Saurabh; Mesgarani, Nima; Liu, Shih-Chii

2015-01-01

Spiking cochlea models describe the analog processing and spike generation process within the biological cochlea. Reconstructing the audio input from the artificial cochlea spikes is therefore useful for understanding the fidelity of the information preserved in the spikes. The reconstruction process is challenging particularly for spikes from the mixed signal (analog/digital) integrated circuit (IC) cochleas because of multiple non-linearities in the model and the additional variance caused by random transistor mismatch. This work proposes an offline method for reconstructing the audio input from spike responses of both a particular spike-based hardware model called the AEREAR2 cochlea and an equivalent software cochlea model. This method was previously used to reconstruct the auditory stimulus based on the peri-stimulus histogram of spike responses recorded in the ferret auditory cortex. The reconstructed audio from the hardware cochlea is evaluated against an analogous software model using objective measures of speech quality and intelligibility; and further tested in a word recognition task. The reconstructed audio under low signal-to-noise (SNR) conditions (SNR < –5 dB) gives a better classification performance than the original SNR input in this word recognition task. PMID:26528113

Population interactions between parietal and primary motor cortices during reach

PubMed Central

Rao, Naveen G.; Bondy, Adrian; Truccolo, Wilson; Donoghue, John P.

2014-01-01

Neural interactions between parietal area 2/5 and primary motor cortex (M1) were examined to determine the timing and behavioral correlates of cortico-cortical interactions. Neural activity in areas 2/5 and M1 was simultaneously recorded with 96-channel microelectrode arrays in three rhesus monkeys performing a center-out reach task. We introduce a new method to reveal parietal-motor interactions at a population level using partial spike-field coherence (PSFC) between ensembles of neurons in one area and a local field potential (LFP) in another. PSFC reflects the extent of phase locking between spike times and LFP, after removing the coherence between LFPs in the two areas. Spectral analysis of M1 LFP revealed three bands: low, medium, and high, differing in power between movement preparation and performance. We focus on PSFC in the 1–10 Hz band, in which coherence was strongest. PSFC was also present in the 10–40 Hz band during movement preparation in many channels but generally nonsignificant in the 60–200 Hz band. Ensemble PSFC revealed stronger interactions than single cell-LFP pairings. PSFC of area 2/5 ensembles with M1 LFP typically rose around movement onset and peaked ∼500 ms afterward. PSFC was typically stronger for subsets of area 2/5 neurons and M1 LFPs with similar directional bias than for those with opposite bias, indicating that area 2/5 contributes movement direction information. Together with linear prediction of M1 LFP by area 2/5 spiking, the ensemble-LFP pairing approach reveals interactions missed by single neuron-LFP pairing, demonstrating that cortico-cortical communication can be more readily observed at the ensemble level. PMID:25210154

Spiking Neural Networks Based on OxRAM Synapses for Real-Time Unsupervised Spike Sorting.

PubMed

Werner, Thilo; Vianello, Elisa; Bichler, Olivier; Garbin, Daniele; Cattaert, Daniel; Yvert, Blaise; De Salvo, Barbara; Perniola, Luca

2016-01-01

In this paper, we present an alternative approach to perform spike sorting of complex brain signals based on spiking neural networks (SNN). The proposed architecture is suitable for hardware implementation by using resistive random access memory (RRAM) technology for the implementation of synapses whose low latency (<1μs) enables real-time spike sorting. This offers promising advantages to conventional spike sorting techniques for brain-computer interfaces (BCI) and neural prosthesis applications. Moreover, the ultra-low power consumption of the RRAM synapses of the spiking neural network (nW range) may enable the design of autonomous implantable devices for rehabilitation purposes. We demonstrate an original methodology to use Oxide based RRAM (OxRAM) as easy to program and low energy (<75 pJ) synapses. Synaptic weights are modulated through the application of an online learning strategy inspired by biological Spike Timing Dependent Plasticity. Real spiking data have been recorded both intra- and extracellularly from an in-vitro preparation of the Crayfish sensory-motor system and used for validation of the proposed OxRAM based SNN. This artificial SNN is able to identify, learn, recognize and distinguish between different spike shapes in the input signal with a recognition rate about 90% without any supervision.

A spiking neural integrator model of the adaptive control of action by the medial prefrontal cortex.

PubMed

Bekolay, Trevor; Laubach, Mark; Eliasmith, Chris

2014-01-29

Subjects performing simple reaction-time tasks can improve reaction times by learning the expected timing of action-imperative stimuli and preparing movements in advance. Success or failure on the previous trial is often an important factor for determining whether a subject will attempt to time the stimulus or wait for it to occur before initiating action. The medial prefrontal cortex (mPFC) has been implicated in enabling the top-down control of action depending on the outcome of the previous trial. Analysis of spike activity from the rat mPFC suggests that neural integration is a key mechanism for adaptive control in precisely timed tasks. We show through simulation that a spiking neural network consisting of coupled neural integrators captures the neural dynamics of the experimentally recorded mPFC. Errors lead to deviations in the normal dynamics of the system, a process that could enable learning from past mistakes. We expand on this coupled integrator network to construct a spiking neural network that performs a reaction-time task by following either a cue-response or timing strategy, and show that it performs the task with similar reaction times as experimental subjects while maintaining the same spiking dynamics as the experimentally recorded mPFC.

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

Intracranial evaluation and laser ablation for epilepsy with periventricular nodular heterotopia.

PubMed

Thompson, Stephen A; Kalamangalam, Giridhar P; Tandon, Nitin

2016-10-01

Surgical treatment of focal epilepsy in the presence of periventricular nodular heterotopia (PVNH) poses a challenge, as the relative roles of the nodular tissue and the overlying cortex in the generation of seizures can be complex and variable. Here, we review the literature on chronic invasive EEG recordings in humans with this substrate and present two illustrative cases from our practice. We found that while inter-ictal spiking from nodules is common, clinical seizures rarely arise solely from nodular tissue. More typically, ictal onset is simultaneous with overlying neocortex or mesial temporal structures. Surgical outcome is more favorable in cases with unilateral (as opposed to bilateral) PVNH, and when a substantial or complete ablation of PVNH is performed. In rare cases, nodular ablation alone may be sufficient, as may be completed by MRI-guided laser interstitial thermal therapy. The mechanism(s) by which PNVH interacts with overlying cortex are not fully understood, but we suggest that PVNH either orchestrates or amplifies local network epileptogenicity. At present, invasive recordings with penetrating depth electrodes are required prior to surgical therapy, as illustrated in our cases. Published by Elsevier Ltd.

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding

PubMed Central

Resnik, Andrey; Celikel, Tansu; Englitz, Bernhard

2016-01-01

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information. PMID:27304526

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding.

PubMed

Huang, Chao; Resnik, Andrey; Celikel, Tansu; Englitz, Bernhard

2016-06-01

Neural processing rests on the intracellular transformation of information as synaptic inputs are translated into action potentials. This transformation is governed by the spike threshold, which depends on the history of the membrane potential on many temporal scales. While the adaptation of the threshold after spiking activity has been addressed before both theoretically and experimentally, it has only recently been demonstrated that the subthreshold membrane state also influences the effective spike threshold. The consequences for neural computation are not well understood yet. We address this question here using neural simulations and whole cell intracellular recordings in combination with information theoretic analysis. We show that an adaptive spike threshold leads to better stimulus discrimination for tight input correlations than would be achieved otherwise, independent from whether the stimulus is encoded in the rate or pattern of action potentials. The time scales of input selectivity are jointly governed by membrane and threshold dynamics. Encoding information using adaptive thresholds further ensures robust information transmission across cortical states i.e. decoding from different states is less state dependent in the adaptive threshold case, if the decoding is performed in reference to the timing of the population response. Results from in vitro neural recordings were consistent with simulations from adaptive threshold neurons. In summary, the adaptive spike threshold reduces information loss during intracellular information transfer, improves stimulus discriminability and ensures robust decoding across membrane states in a regime of highly correlated inputs, similar to those seen in sensory nuclei during the encoding of sensory information.

Feature Representations for Neuromorphic Audio Spike Streams.

PubMed

Anumula, Jithendar; Neil, Daniel; Delbruck, Tobi; Liu, Shih-Chii

2018-01-01

Event-driven neuromorphic spiking sensors such as the silicon retina and the silicon cochlea encode the external sensory stimuli as asynchronous streams of spikes across different channels or pixels. Combining state-of-art deep neural networks with the asynchronous outputs of these sensors has produced encouraging results on some datasets but remains challenging. While the lack of effective spiking networks to process the spike streams is one reason, the other reason is that the pre-processing methods required to convert the spike streams to frame-based features needed for the deep networks still require further investigation. This work investigates the effectiveness of synchronous and asynchronous frame-based features generated using spike count and constant event binning in combination with the use of a recurrent neural network for solving a classification task using N-TIDIGITS18 dataset. This spike-based dataset consists of recordings from the Dynamic Audio Sensor, a spiking silicon cochlea sensor, in response to the TIDIGITS audio dataset. We also propose a new pre-processing method which applies an exponential kernel on the output cochlea spikes so that the interspike timing information is better preserved. The results from the N-TIDIGITS18 dataset show that the exponential features perform better than the spike count features, with over 91% accuracy on the digit classification task. This accuracy corresponds to an improvement of at least 2.5% over the use of spike count features, establishing a new state of the art for this dataset.

Feature Representations for Neuromorphic Audio Spike Streams

PubMed Central

Anumula, Jithendar; Neil, Daniel; Delbruck, Tobi; Liu, Shih-Chii

2018-01-01

Event-driven neuromorphic spiking sensors such as the silicon retina and the silicon cochlea encode the external sensory stimuli as asynchronous streams of spikes across different channels or pixels. Combining state-of-art deep neural networks with the asynchronous outputs of these sensors has produced encouraging results on some datasets but remains challenging. While the lack of effective spiking networks to process the spike streams is one reason, the other reason is that the pre-processing methods required to convert the spike streams to frame-based features needed for the deep networks still require further investigation. This work investigates the effectiveness of synchronous and asynchronous frame-based features generated using spike count and constant event binning in combination with the use of a recurrent neural network for solving a classification task using N-TIDIGITS18 dataset. This spike-based dataset consists of recordings from the Dynamic Audio Sensor, a spiking silicon cochlea sensor, in response to the TIDIGITS audio dataset. We also propose a new pre-processing method which applies an exponential kernel on the output cochlea spikes so that the interspike timing information is better preserved. The results from the N-TIDIGITS18 dataset show that the exponential features perform better than the spike count features, with over 91% accuracy on the digit classification task. This accuracy corresponds to an improvement of at least 2.5% over the use of spike count features, establishing a new state of the art for this dataset. PMID:29479300

A method for decoding the neurophysiological spike-response transform

PubMed Central

Stern, Estee; García-Crescioni, Keyla; Miller, Mark W.; Peskin, Charles S.; Brezina, Vladimir

2009-01-01

Many physiological responses elicited by neuronal spikes—intracellular calcium transients, synaptic potentials, muscle contractions—are built up of discrete, elementary responses to each spike. However, the spikes occur in trains of arbitrary temporal complexity, and each elementary response not only sums with previous ones, but can itself be modified by the previous history of the activity. A basic goal in system identification is to characterize the spike-response transform in terms of a small number of functions—the elementary response kernel and additional kernels or functions that describe the dependence on previous history—that will predict the response to any arbitrary spike train. Here we do this by developing further and generalizing the “synaptic decoding” approach of Sen et al. (J Neurosci 16:6307-6318, 1996). Given the spike times in a train and the observed overall response, we use least-squares minimization to construct the best estimated response and at the same time best estimates of the elementary response kernel and the other functions that characterize the spike-response transform. We avoid the need for any specific initial assumptions about these functions by using techniques of mathematical analysis and linear algebra that allow us to solve simultaneously for all of the numerical function values treated as independent parameters. The functions are such that they may be interpreted mechanistically. We examine the performance of the method as applied to synthetic data. We then use the method to decode real synaptic and muscle contraction transforms. PMID:19695289

+Gz-induced post-cholecystectomy syndrome in rabbit model by using a telemetric method

PubMed Central

Kong, Yalin; Zhao, Gang; Li, Yifeng; Wen, Dongqing; Zhang, Hui; He, Xiaojun; Zhen, Yuying; Zhang, Hongyi

2015-01-01

Aviation-related mechanism may exist in the post-cholecystectomy syndrome (PCS) of aircrew patients. The aim of this study was to test this hypothesis on vivo rabbit model and to explore the mechanism by using a novel telemetric method. We constructed a bile duct-to-intestinal bridge bypass on 30 rabbits, with a telemetry implant attached to the Oddi’s sphincter. Then a telemetric recording system was used to record the biliary pressure fluctuation through the subcutaneous bridge and the changes of electromyography of the Oddi’s sphincter under different +Gz acceleration. Self-control comparison was made before and after cholecystectomy. The fully implantable device was very well accepted by rabbits and the data could reflect the real experimental environment simultaneously. Biliary pressure in common bile duct increased accordingly with +Gz acceleration increased, but bile secretion didn’t change. Although +Gz acceleration could increase the frequency of burst of spike potentials in the Oddi’s sphincter, the frequency didn’t change with the +Gz acceleration increased, and the spike activity didn’t change obviously before cholecystectomy. After cholecystectomy, the biliary pressure in common bile duct remained high in 12 rabbits (40%) under +Gz exposure, and the pressure value didn’t change as the +Gz acceleration increased. The long-time changes in electromyography of the Oddi’s sphincter were observed in the same 12 rabbits, with symptoms of PCS developed in 9 of them. +Gz exposure is an important external factor leading to the biliary physiology disorder, and it may induce PCS in some aircrew patients with individual susceptibility, which means gallbladder maybe a dominant factor in regulating the biliary physiology in theses aircrew patients. PMID:26064268

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

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

Long-term follow-up of cognitive functions in patients with continuous spike-waves during sleep (CSWS).

PubMed

Maltoni, Lucia; Posar, Annio; Parmeggiani, Antonia

2016-07-01

Continuous spike-waves during sleep (CSWS) are associated with several cognitive, neurological, and psychiatric disorders, which sometimes persist after CSWS disappearance. The purpose of this retrospective study was to investigate the correlation between general (clinical and instrumental) and neuropsychological findings in CSWS, to identify variables that predispose patients to a poorer long-term neuropsychological outcome. Patients with spikes and waves during sleep with a frequency ≥25/min (spikes and waves frequency index - SWFI) were enrolled. There were patients presenting abnormal EEG activity corresponding to the classic CSWS and patients with paroxysmal abnormalities during sleep <85% with SWFI ≥25/min that was defined as excessive spike-waves during sleep (ESWS). Clinical and instrumental features and neuropsychological findings during and after the spike and wave active phase period were considered. A statistical analysis was performed utilizing the Spearman correlation test and multivariate analysis. The study included 61 patients; the mean follow-up (i.e., the period between SWFI ≥25 first recording and last observation) was 7years and 4months. The SWFI correlated inversely with full and performance IQ during CSWS/ESWS. Longer-lasting SWFI ≥25 was related to worse results in verbal IQ and performance IQ after CSWS/ESWS disappearance. Other variables may influence the neuropsychological outcome, like age at SWFI ≥25 first recording, perinatal distress, pathologic neurologic examination, and antiepileptic drug resistance. This confirms that CSWS/ESWS are a complex pathology and that many variables contribute to its outcome. The SWFI value above all during CSWS/ESWS and long-lasting SWFI ≥25 after CSWS/ESWS disappearance are the most significant indexes that appear mostly to determine cognitive evolution. This finding underscores the importance of EEG recordings during sleep in children with a developmental disorder, even if seizures are not reported, as well as the importance of using therapy with an early efficacy. Copyright © 2016 Elsevier Inc. All rights reserved.

Neural signal processing and closed-loop control algorithm design for an implanted neural recording and stimulation system.

PubMed

Hamilton, Lei; McConley, Marc; Angermueller, Kai; Goldberg, David; Corba, Massimiliano; Kim, Louis; Moran, James; Parks, Philip D; Sang Chin; Widge, Alik S; Dougherty, Darin D; Eskandar, Emad N

2015-08-01

A fully autonomous intracranial device is built to continually record neural activities in different parts of the brain, process these sampled signals, decode features that correlate to behaviors and neuropsychiatric states, and use these features to deliver brain stimulation in a closed-loop fashion. In this paper, we describe the sampling and stimulation aspects of such a device. We first describe the signal processing algorithms of two unsupervised spike sorting methods. Next, we describe the LFP time-frequency analysis and feature derivation from the two spike sorting methods. Spike sorting includes a novel approach to constructing a dictionary learning algorithm in a Compressed Sensing (CS) framework. We present a joint prediction scheme to determine the class of neural spikes in the dictionary learning framework; and, the second approach is a modified OSort algorithm which is implemented in a distributed system optimized for power efficiency. Furthermore, sorted spikes and time-frequency analysis of LFP signals can be used to generate derived features (including cross-frequency coupling, spike-field coupling). We then show how these derived features can be used in the design and development of novel decode and closed-loop control algorithms that are optimized to apply deep brain stimulation based on a patient's neuropsychiatric state. For the control algorithm, we define the state vector as representative of a patient's impulsivity, avoidance, inhibition, etc. Controller parameters are optimized to apply stimulation based on the state vector's current state as well as its historical values. The overall algorithm and software design for our implantable neural recording and stimulation system uses an innovative, adaptable, and reprogrammable architecture that enables advancement of the state-of-the-art in closed-loop neural control while also meeting the challenges of system power constraints and concurrent development with ongoing scientific research designed to define brain network connectivity and neural network dynamics that vary at the individual patient level and vary over time.

Classification of epileptiform and wicket spike of EEG pattern using backpropagation neural network

NASA Astrophysics Data System (ADS)

Puspita, Juni Wijayanti; Jaya, Agus Indra; Gunadharma, Suryani

2017-03-01

Epilepsy is characterized by recurrent seizures that is resulted by permanent brain abnormalities. One of tools to support the diagnosis of epilepsy is Electroencephalograph (EEG), which describes the recording of brain electrical activity. Abnormal EEG patterns in epilepsy patients consist of Spike and Sharp waves. While both waves, there is a normal pattern that sometimes misinterpreted as epileptiform by electroenchepalographer (EEGer), namely Wicket Spike. The main difference of the three waves are on the time duration that related to the frequency. In this study, we proposed a method to classify a EEG wave into Sharp wave, Spike wave or Wicket spike group using Backpropagation Neural Network based on the frequency and amplitude of each wave. The results show that the proposed method can classifies the three group of waves with good accuracy.

Behavior related pauses in simple spike activity of mouse Purkinje cells are linked to spike rate modulation

PubMed Central

Cao, Ying; Maran, Selva K.; Dhamala, Mukesh; Jaeger, Dieter; Heck, Detlef H.

2012-01-01

Purkinje cells (PCs) in the mammalian cerebellum express high frequency spontaneous activity with average spike rates between 30 and 200 Hz. Cerebellar nuclear (CN) neurons receive converging input from many PCs resulting in a continuous barrage of inhibitory inputs. It has been hypothesized that pauses in PC activity trigger increases in CN spiking activity. A prediction derived from this hypothesis is that pauses in PC simple spike activity represent relevant behavioral or sensory events. Here we asked whether pauses in the simple spike activity of PCs related to either fluid licking or respiration, play a special role in representing information about behavior. Both behaviors are widely represented in cerebellar PC simple spike activity. We recorded PC activity in the vermis and lobus simplex of head fixed mice while monitoring licking and respiratory behavior. Using cross correlation and Granger causality analysis we examined whether short ISIs had a different temporal relation to behavior than long ISIs or pauses. Behavior related simple spike pauses occurred during low-rate simple spike activity in both licking and breathing related PCs. Granger causality analysis revealed causal relationships between simple spike pauses and behavior. However, the same results were obtained from an analysis of surrogate spike trains with gamma ISI distributions constructed to match rate modulations of behavior related Purkinje cells. Our results therefore suggest that the occurrence of pauses in simple spike activity does not represent additional information about behavioral or sensory events that goes beyond the simple spike rate modulations. PMID:22723707

Differences in reward processing between putative cell types in primate prefrontal cortex

PubMed Central

Fan, Hongwei; Wang, Rubin; Sakagami, Masamichi

2017-01-01

Single-unit studies in monkeys have demonstrated that neurons in the prefrontal cortex predict the reward type, reward amount or reward availability associated with a stimulus. To examine contributions of pyramidal cells and interneurons in reward processing, single-unit activity was extracellularly recorded in prefrontal cortices of four monkeys performing a reward prediction task. Based on their shapes of spike waveforms, prefrontal neurons were classified into broad-spike and narrow-spike units that represented putative pyramidal cells and interneurons, respectively. We mainly observed that narrow-spike neurons showed higher firing rates but less bursty discharges than did broad-spike neurons. Both narrow-spike and broad-spike cells selectively responded to the stimulus, reward and their interaction, and the proportions of each type of selective neurons were similar between the two cell classes. Moreover, the two types of cells displayed equal reliability of reward or stimulus discrimination. Furthermore, we found that broad-spike and narrow-spike cells showed distinct mechanisms for encoding reward or stimulus information. Broad-spike neurons raised their firing rate relative to the baseline rate to represent the preferred reward or stimulus information, whereas narrow-spike neurons inhibited their firing rate lower than the baseline rate to encode the non-preferred reward or stimulus information. Our results suggest that narrow-spike and broad-spike cells were equally involved in reward and stimulus processing in the prefrontal cortex. They utilized a binary strategy to complementarily represent reward or stimulus information, which was consistent with the task structure in which the monkeys were required to remember two reward conditions and two visual stimuli. PMID:29261734

Differences in reward processing between putative cell types in primate prefrontal cortex.

PubMed

Fan, Hongwei; Pan, Xiaochuan; Wang, Rubin; Sakagami, Masamichi

2017-01-01

Single-unit studies in monkeys have demonstrated that neurons in the prefrontal cortex predict the reward type, reward amount or reward availability associated with a stimulus. To examine contributions of pyramidal cells and interneurons in reward processing, single-unit activity was extracellularly recorded in prefrontal cortices of four monkeys performing a reward prediction task. Based on their shapes of spike waveforms, prefrontal neurons were classified into broad-spike and narrow-spike units that represented putative pyramidal cells and interneurons, respectively. We mainly observed that narrow-spike neurons showed higher firing rates but less bursty discharges than did broad-spike neurons. Both narrow-spike and broad-spike cells selectively responded to the stimulus, reward and their interaction, and the proportions of each type of selective neurons were similar between the two cell classes. Moreover, the two types of cells displayed equal reliability of reward or stimulus discrimination. Furthermore, we found that broad-spike and narrow-spike cells showed distinct mechanisms for encoding reward or stimulus information. Broad-spike neurons raised their firing rate relative to the baseline rate to represent the preferred reward or stimulus information, whereas narrow-spike neurons inhibited their firing rate lower than the baseline rate to encode the non-preferred reward or stimulus information. Our results suggest that narrow-spike and broad-spike cells were equally involved in reward and stimulus processing in the prefrontal cortex. They utilized a binary strategy to complementarily represent reward or stimulus information, which was consistent with the task structure in which the monkeys were required to remember two reward conditions and two visual stimuli.

Dysregulated corticostriatal activity in open-field behavior and the head-twitch response induced by the hallucinogen 2,5-dimethoxy-4-iodoamphetamine.

PubMed

Rangel-Barajas, Claudia; Estrada-Sánchez, Ana María; Barton, Scott J; Luedtke, Robert R; Rebec, George V

2017-02-01

The substituted amphetamine, 2,5-dimethoxy-4-iodoamphetamine (DOI), is a hallucinogen that has been used to model a variety of psychiatric conditions. Here, we studied the effect of DOI on neural activity recorded simultaneously in the primary motor cortex (M1) and dorsal striatum of freely behaving FvB/N mice. DOI significantly decreased the firing rate of individually isolated neurons in M1 and dorsal striatum relative to pre-drug baseline. It also induced a bursting pattern of activity by increasing both the number of spikes within a burst and burst duration. In addition, DOI increased coincident firing between simultaneously recorded neuron pairs within the striatum and between M1 and dorsal striatum. Local field potential (LFP) activity also increased in coherence between M1 and dorsal striatum after DOI in the low frequency gamma band (30-50 Hz), while corticostriatal coherence in delta, theta, alpha, and beta activity decreased. We also assessed corticostriatal LFP activity in relation to the DOI-induced head-twitch response (HTR), a readily identifiable behavior used to assess potential treatments for the conditions it models. The HTR was associated with increased delta and decreased theta power in both M1 and dorsal striatum. Together, our results suggest that DOI dysregulates corticostriatal communication and that the HTR is associated with this dysregulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chronic multiunit recordings in behaving animals: advantages and limitations.

PubMed

Supèr, Hans; Roelfsema, Pieter R

2005-01-01

By simultaneous recording from neural responses at many different loci at the same time, we can understand the interaction between neurons, and thereby gain insight into the network properties of neural processing, instead of the functioning of individual neurons. Here we will discuss a method for recording in behaving animals that uses chronically implanted micro-electrodes that allow one to track neural responses over a long period of time. In a majority of cases, multiunit activity, which is the aggregate spiking activity of a number of neurons in the vicinity of an electrode tip, is recorded through these electrodes, and occasionally single neurons can be isolated. Here we compare the properties of multiunit responses to the responses of single neurons in the primary visual cortex. We also discuss the advantages and disadvantages of the multiunit signal as opposed to a signal of single neurons. We demonstrate that multiunit recording provides a reliable and useful technique in cases where the neurons at the electrodes have similar response properties. Multiunit recording is therefore especially valuable when task variables have an effect that is consistent across the population of neurons. In the primary visual cortex, this is the case for figure-ground segregation and visual attention. Multiunit recording also has clear advantages for cross-correlation analysis. We show that the cross-correlation function between multiunit signals gives a reliable estimate of the average single-unit cross-correlation function. By the use of multiunit recording, it becomes much easier to detect relatively weak interactions between neurons at different cortical locations.

Spatial dynamics of action potentials estimated by dendritic Ca(2+) signals in insect projection neurons.

PubMed

Ogawa, Hiroto; Mitani, Ruriko

2015-11-13

The spatial dynamics of action potentials, including their propagation and the location of spike initiation zone (SIZ), are crucial for the computation of a single neuron. Compared with mammalian central neurons, the spike dynamics of invertebrate neurons remain relatively unknown. Thus, we examined the spike dynamics based on single spike-induced Ca(2+) signals in the dendrites of cricket mechanosensory projection neurons, known as giant interneurons (GIs). The Ca(2+) transients induced by a synaptically evoked single spike were larger than those induced by an antidromic spike, whereas subthreshold synaptic potentials caused no elevation of Ca(2+). These results indicate that synaptic activity enhances the dendritic Ca(2+) influx through voltage-gated Ca(2+) channels. Stimulation of the presynaptic sensory afferents ipsilateral to the recording site evoked a dendritic spike with higher amplitude than contralateral stimulation, thereby suggesting that alteration of the spike waveform resulted in synaptic enhancement of the dendritic Ca(2+) transients. The SIZ estimated from the spatial distribution of the difference in the Ca(2+) amplitude was distributed throughout the right and left dendritic branches across the primary neurite connecting them in GIs. Copyright © 2015 Elsevier Inc. All rights reserved.

Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface.

PubMed

Lajoie, Guillaume; Krouchev, Nedialko I; Kalaska, John F; Fairhall, Adrienne L; Fetz, Eberhard E

2017-02-01

Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites eventually strengthen. It was also found that effective spike-stimulus delays are consistent with experimentally derived spike-timing-dependent plasticity (STDP) rules, suggesting that STDP is key to drive these changes. However, the impact of STDP at the level of circuits, and the mechanisms governing its modification with neural implants remain poorly understood. The present work describes a recurrent neural network model with probabilistic spiking mechanisms and plastic synapses capable of capturing both neural and synaptic activity statistics relevant to BBCI conditioning protocols. Our model successfully reproduces key experimental results, both established and new, and offers mechanistic insights into spike-triggered conditioning. Using analytical calculations and numerical simulations, we derive optimal operational regimes for BBCIs, and formulate predictions concerning the efficacy of spike-triggered conditioning in different regimes of cortical activity.

Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface

PubMed Central

Lajoie, Guillaume; Kalaska, John F.; Fairhall, Adrienne L.; Fetz, Eberhard E.

2017-01-01

Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites eventually strengthen. It was also found that effective spike-stimulus delays are consistent with experimentally derived spike-timing-dependent plasticity (STDP) rules, suggesting that STDP is key to drive these changes. However, the impact of STDP at the level of circuits, and the mechanisms governing its modification with neural implants remain poorly understood. The present work describes a recurrent neural network model with probabilistic spiking mechanisms and plastic synapses capable of capturing both neural and synaptic activity statistics relevant to BBCI conditioning protocols. Our model successfully reproduces key experimental results, both established and new, and offers mechanistic insights into spike-triggered conditioning. Using analytical calculations and numerical simulations, we derive optimal operational regimes for BBCIs, and formulate predictions concerning the efficacy of spike-triggered conditioning in different regimes of cortical activity. PMID:28151957

Excitation and inhibition compete to control spiking during hippocampal ripples: intracellular study in behaving mice.

PubMed

English, Daniel F; Peyrache, Adrien; Stark, Eran; Roux, Lisa; Vallentin, Daniela; Long, Michael A; Buzsáki, György

2014-12-03

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 of the rhythm and the recruitment of spikes from pyramidal neurons are still poorly understood. Using intracellular, sharp electrode recordings in freely moving, drug-free mice, we observed consistent large depolarizations in CA1 pyramidal cells during sharp wave ripples, which are associated with ripple frequency fluctuation of the membrane potential ("intracellular ripple"). Despite consistent depolarization, often exceeding pre-ripple spike threshold values, current pulse-induced spikes were strongly suppressed, indicating that spiking was under the control of concurrent shunting inhibition. Ripple events were followed by a prominent afterhyperpolarization and spike suppression. Action potentials during and outside ripples were orthodromic, arguing against ectopic spike generation, which has been postulated by computational models of ripple generation. These findings indicate that dendritic excitation of pyramidal neurons during ripples is countered by shunting of the membrane and postripple silence is mediated by hyperpolarizing inhibition. Copyright © 2014 the authors 0270-6474/14/3316509-09$15.00/0.

Characterizing neural activities evoked by manual acupuncture through spiking irregularity measures

NASA Astrophysics Data System (ADS)

Xue, Ming; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Yu, Hai-Tao; Chen, Ying-Yuan

2013-09-01

The neural system characterizes information in external stimulations by different spiking patterns. In order to examine how neural spiking patterns are related to acupuncture manipulations, experiments are designed in such a way that different types of manual acupuncture (MA) manipulations are taken at the ‘Zusanli’ point of experimental rats, and the induced electrical signals in the spinal dorsal root ganglion are detected and recorded. The interspike interval (ISI) statistical histogram is fitted by the gamma distribution, which has two parameters: one is the time-dependent firing rate and the other is a shape parameter characterizing the spiking irregularities. The shape parameter is the measure of spiking irregularities and can be used to identify the type of MA manipulations. The coefficient of variation is mostly used to measure the spike time irregularity, but it overestimates the irregularity in the case of pronounced firing rate changes. However, experiments show that each acupuncture manipulation will lead to changes in the firing rate. So we combine four relatively rate-independent measures to study the irregularity of spike trains evoked by different types of MA manipulations. Results suggest that the MA manipulations possess unique spiking statistics and characteristics and can be distinguished according to the spiking irregularity measures. These studies have offered new insights into the coding processes and information transfer of acupuncture.

Modeling spiking behavior of neurons with time-dependent Poisson processes.

PubMed

Shinomoto, S; Tsubo, Y

2001-10-01

Three kinds of interval statistics, as represented by the coefficient of variation, the skewness coefficient, and the correlation coefficient of consecutive intervals, are evaluated for three kinds of time-dependent Poisson processes: pulse regulated, sinusoidally regulated, and doubly stochastic. Among these three processes, the sinusoidally regulated and doubly stochastic Poisson processes, in the case when the spike rate varies slowly compared with the mean interval between spikes, are found to be consistent with the three statistical coefficients exhibited by data recorded from neurons in the prefrontal cortex of monkeys.

Network activity influences the subthreshold and spiking visual responses of pyramidal neurons in the three-layer turtle cortex.

PubMed

Wright, Nathaniel C; Wessel, Ralf

2017-10-01

A primary goal of systems neuroscience is to understand cortical function, typically by studying spontaneous and stimulus-modulated cortical activity. Mounting evidence suggests a strong and complex relationship exists between the ongoing and stimulus-modulated cortical state. To date, most work in this area has been based on spiking in populations of neurons. While advantageous in many respects, this approach is limited in scope: it records the activity of a minority of neurons and gives no direct indication of the underlying subthreshold dynamics. Membrane potential recordings can fill these gaps in our understanding, but stable recordings are difficult to obtain in vivo. Here, we recorded subthreshold cortical visual responses in the ex vivo turtle eye-attached whole brain preparation, which is ideally suited for such a study. We found that, in the absence of visual stimulation, the network was "synchronous"; neurons displayed network-mediated transitions between hyperpolarized (Down) and depolarized (Up) membrane potential states. The prevalence of these slow-wave transitions varied across turtles and recording sessions. Visual stimulation evoked similar Up states, which were on average larger and less reliable when the ongoing state was more synchronous. Responses were muted when immediately preceded by large, spontaneous Up states. Evoked spiking was sparse, highly variable across trials, and mediated by concerted synaptic inputs that were, in general, only very weakly correlated with inputs to nearby neurons. Together, these results highlight the multiplexed influence of the cortical network on the spontaneous and sensory-evoked activity of individual cortical neurons. NEW & NOTEWORTHY Most studies of cortical activity focus on spikes. Subthreshold membrane potential recordings can provide complementary insight, but stable recordings are difficult to obtain in vivo. Here, we recorded the membrane potentials of cortical neurons during ongoing and visually evoked activity. We observed a strong relationship between network and single-neuron evoked activity spanning multiple temporal scales. The membrane potential perspective of cortical dynamics thus highlights the influence of intrinsic network properties on visual processing. Copyright © 2017 the American Physiological Society.

Recovery cycle times of inferior colliculus neurons in the awake bat measured with spike counts and latencies

PubMed Central

Sayegh, Riziq; Aubie, Brandon; Fazel-Pour, Siavosh; Faure, Paul A.

2012-01-01

Neural responses in the mammalian auditory midbrain (inferior colliculus; IC) arise from complex interactions of synaptic excitation, inhibition, and intrinsic properties of the cell. Temporally selective duration-tuned neurons (DTNs) in the IC are hypothesized to arise through the convergence of excitatory and inhibitory synaptic inputs offset in time. Synaptic inhibition can be inferred from extracellular recordings by presenting pairs of pulses (paired tone stimulation) and comparing the evoked responses of the cell to each pulse. We obtained single unit recordings from the IC of the awake big brown bat (Eptesicus fuscus) and used paired tone stimulation to measure the recovery cycle times of DTNs and non-temporally selective auditory neurons. By systematically varying the interpulse interval (IPI) of the paired tone stimulus, we determined the minimum IPI required for a neuron's spike count or its spike latency (first- or last-spike latency) in response to the second tone to recover to within ≥50% of the cell's baseline count or to within 1 SD of it's baseline latency in response to the first tone. Recovery times of shortpass DTNs were significantly shorter than those of bandpass DTNs, and recovery times of bandpass DTNs were longer than allpass neurons not selective for stimulus duration. Recovery times measured with spike counts were positively correlated with those measured with spike latencies. Recovery times were also correlated with first-spike latency (FSL). These findings, combined with previous studies on duration tuning in the IC, suggest that persistent inhibition is a defining characteristic of DTNs. Herein, we discuss measuring recovery times of neurons with spike counts and latencies. We also highlight how persistent inhibition could determine neural recovery times and serve as a potential mechanism underlying the precedence effect in humans. Finally, we explore implications of recovery times for DTNs in the context of bat hearing and echolocation. PMID:22933992

Millisecond Microwave Spikes: Statistical Study and Application for Plasma Diagnostics

NASA Astrophysics Data System (ADS)

Rozhansky, I. V.; Fleishman, G. D.; Huang, G.-L.

2008-07-01

We analyze a dense cluster of solar radio spikes registered at 4.5-6 GHz by the Purple Mountain Observatory spectrometer (Nanjing, China), operating in the 4.5-7.5 GHz range with 5 ms temporal resolution. To handle the data from the spectrometer, we developed a new technique that uses a nonlinear multi-Gaussian spectral fit based on χ2 criteria to extract individual spikes from the originally recorded spectra. Applying this method to the experimental raw data, we eventually identified about 3000 spikes for this event, which allows us to make a detailed statistical analysis. Various statistical characteristics of the spikes have been evaluated, including the intensity distributions, the spectral bandwidth distributions, and the distribution of the spike mean frequencies. The most striking finding of this analysis is the distributions of the spike bandwidth, which are remarkably asymmetric. To reveal the underlaying microphysics, we explore the local-trap model with the renormalized theory of spectral profiles of the electron cyclotron maser (ECM) emission peak in a source with random magnetic irregularities. The distribution of the solar spike relative bandwidths calculated within the local-trap model represents an excellent fit to the experimental data. Accordingly, the developed technique may offer a new tool with which to study very low levels of magnetic turbulence in the spike sources, when the ECM mechanism of the spike cluster is confirmed.

Information transmission in hippocampal CA1 neuron models in the presence of poisson shot noise: the case of periodic sub-threshold spike trains.

PubMed

Kawaguchi, Minato; Mino, Hiroyuki; Durand, Dominique M

2006-01-01

This article presents an analysis of the information transmission of periodic sub-threshold spike trains in a hippocampal CA1 neuron model in the presence of a homogeneous Poisson shot noise. In the computer simulation, periodic sub-threshold spike trains were presented repeatedly to the midpoint of the main apical branch, while the homogeneous Poisson shot noise was applied to the mid-point of a basal dendrite in the CA1 neuron model consisting of the soma with one sodium, one calcium, and five potassium channels. From spike firing times recorded at the soma, the inter spike intervals were generated and then the probability, p(T), of the inter-spike interval histogram corresponding to the spike interval, r, of the periodic input spike trains was estimated to obtain an index of information transmission. In the present article, it is shown that at a specific amplitude of the homogeneous Poisson shot noise, p(T) was found to be maximized, as well as the possibility to encode the periodic sub-threshold spike trains became greater. It was implied that setting the amplitude of the homogeneous Poisson shot noise to the specific values which maximize the information transmission might contribute to efficiently encoding the periodic sub-threshold spike trains by utilizing the stochastic resonance.

Different Timescales for the Neural Coding of Consonant and Vowel Sounds

PubMed Central

Perez, Claudia A.; Engineer, Crystal T.; Jakkamsetti, Vikram; Carraway, Ryan S.; Perry, Matthew S.

2013-01-01

Psychophysical, clinical, and imaging evidence suggests that consonant and vowel sounds have distinct neural representations. This study tests the hypothesis that consonant and vowel sounds are represented on different timescales within the same population of neurons by comparing behavioral discrimination with neural discrimination based on activity recorded in rat inferior colliculus and primary auditory cortex. Performance on 9 vowel discrimination tasks was highly correlated with neural discrimination based on spike count and was not correlated when spike timing was preserved. In contrast, performance on 11 consonant discrimination tasks was highly correlated with neural discrimination when spike timing was preserved and not when spike timing was eliminated. These results suggest that in the early stages of auditory processing, spike count encodes vowel sounds and spike timing encodes consonant sounds. These distinct coding strategies likely contribute to the robust nature of speech sound representations and may help explain some aspects of developmental and acquired speech processing disorders. PMID:22426334

Bayesian decoding using unsorted spikes in the rat hippocampus

PubMed Central

Layton, Stuart P.; Chen, Zhe; Wilson, Matthew A.

2013-01-01

A fundamental task in neuroscience is to understand how neural ensembles represent information. Population decoding is a useful tool to extract information from neuronal populations based on the ensemble spiking activity. We propose a novel Bayesian decoding paradigm to decode unsorted spikes in the rat hippocampus. Our approach uses a direct mapping between spike waveform features and covariates of interest and avoids accumulation of spike sorting errors. Our decoding paradigm is nonparametric, encoding model-free for representing stimuli, and extracts information from all available spikes and their waveform features. We apply the proposed Bayesian decoding algorithm to a position reconstruction task for freely behaving rats based on tetrode recordings of rat hippocampal neuronal activity. Our detailed decoding analyses demonstrate that our approach is efficient and better utilizes the available information in the nonsortable hash than the standard sorting-based decoding algorithm. Our approach can be adapted to an online encoding/decoding framework for applications that require real-time decoding, such as brain-machine interfaces. PMID:24089403

Screening for Developmental Neurotoxicants using In Vitro "Brain on a Chip" Cultures

EPA Science Inventory

Currently there are thousands of chemicals in the environment that have not been screened for their potential to cause developmental neurotoxicity (DNT). The use of microelectrode array (MEA) technology allows for simultaneous extracellular measurement of action potential (spike)...

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.

Therapeutic deep brain stimulation in Parkinsonian rats directly influences motor cortex.

PubMed

Li, Qian; Ke, Ya; Chan, Danny C W; Qian, Zhong-Ming; Yung, Ken K L; Ko, Ho; Arbuthnott, Gordon W; Yung, Wing-Ho

2012-12-06

Much recent discussion about the origin of Parkinsonian symptoms has centered around the idea that they arise with the increase of beta frequency waves in the EEG. This activity may be closely related to an oscillation between subthalamic nucleus (STN) and globus pallidus. Since STN is the target of deep brain stimulation, it had been assumed that its action is on the nucleus itself. By means of simultaneous recordings of the firing activities from populations of neurons and the local field potentials in the motor cortex of freely moving Parkinsonian rats, this study casts doubt on this assumption. Instead, we found evidence that the corrective action is upon the cortex, where stochastic antidromic spikes originating from the STN directly modify the firing probability of the corticofugal projection neurons, destroy the dominance of beta rhythm, and thus restore motor control to the subjects, be they patients or rodents. Copyright © 2012 Elsevier Inc. All rights reserved.

Simultaneous recording of mouse retinal ganglion cells during epiretinal or subretinal stimulation

PubMed Central

Sim, S.L.; Szalewski, R.J.; Johnson, L.J.; Akah, L.E.; Shoemaker, L.E.; Thoreson, W.B.; Margalit, E.

2015-01-01

We compared response patterns and electrical receptive fields (ERF) of retinal ganglion cells (RGCs) during epiretinal and subretinal electrical stimulation of isolated mouse retina. Retinas were stimulated with an array of 3200 independently controllable electrodes. Four response patterns were observed: a burst of activity immediately after stimulation (Type I cells, Vision Research (2008), 48, 1562–1568), delayed bursts beginning >25 ms after stimulation (Type II), a combination of both (Type III), and inhibition of ongoing spike activity. Type I responses were produced more often by epiretinal than subretinal stimulation whereas delayed and inhibitory responses were evoked more frequently by subretinal stimulation. Response latencies were significantly shorter with epiretinal than subretinal stimulation. These data suggest that subretinal stimulation is more effective at activating intraretinal circuits than epiretinal stimulation. There was no significant difference in charge threshold between subretinal and epiretinal configurations. ERFs were defined by the stimulating array surface area that successfully stimulated spikes in an RGC. ERFs were complex in shape, similar to receptive fields mapped with light. ERF areas were significantly smaller with subretinal than epiretinal stimulation. This may reflect the greater distance between stimulating electrodes and RGCs in the subretinal configuration. ERFs for immediate and delayed responses mapped within the same Type III cells differed in shape and size, consistent with different sites and mechanisms for generating these two response types. PMID:24863584

Detecting higher-order interactions among the spiking events in a group of neurons.

PubMed

Martignon, L; Von Hasseln, H; Grün, S; Aertsen, A; Palm, G

1995-06-01

We propose a formal framework for the description of interactions among groups of neurons. This framework is not restricted to the common case of pair interactions, but also incorporates higher-order interactions, which cannot be reduced to lower-order ones. We derive quantitative measures to detect the presence of such interactions in experimental data, by statistical analysis of the frequency distribution of higher-order correlations in multiple neuron spike train data. Our first step is to represent a frequency distribution as a Markov field on the minimal graph it induces. We then show the invariance of this graph with regard to changes of state. Clearly, only linear Markov fields can be adequately represented by graphs. Higher-order interdependencies, which are reflected by the energy expansion of the distribution, require more complex graphical schemes, like constellations or assembly diagrams, which we introduce and discuss. The coefficients of the energy expansion not only point to the interactions among neurons but are also a measure of their strength. We investigate the statistical meaning of detected interactions in an information theoretic sense and propose minimum relative entropy approximations as null hypotheses for significance tests. We demonstrate the various steps of our method in the situation of an empirical frequency distribution on six neurons, extracted from data on simultaneous multineuron recordings from the frontal cortex of a behaving monkey and close with a brief outlook on future work.

Brain-state dependent astrocytic Ca2+ signals are coupled to both positive and negative BOLD-fMRI signals.

PubMed

Wang, Maosen; He, Yi; Sejnowski, Terrence J; Yu, Xin

2018-02-13

Astrocytic Ca 2+ -mediated gliovascular interactions regulate the neurovascular network in situ and in vivo. However, it is difficult to measure directly both the astrocytic activity and fMRI to relate the various forms of blood-oxygen-level-dependent (BOLD) signaling to brain states under normal and pathological conditions. In this study, fMRI and GCaMP-mediated Ca 2+ optical fiber recordings revealed distinct evoked astrocytic Ca 2+ signals that were coupled with positive BOLD signals and intrinsic astrocytic Ca 2+ signals that were coupled with negative BOLD signals. Both evoked and intrinsic astrocytic calcium signal could occur concurrently or respectively during stimulation. The intrinsic astrocytic calcium signal can be detected globally in multiple cortical sites in contrast to the evoked astrocytic calcium signal only detected at the activated cortical region. Unlike propagating Ca 2+ waves in spreading depolarization/depression, the intrinsic Ca 2+ spikes occurred simultaneously in both hemispheres and were initiated upon the activation of the central thalamus and midbrain reticular formation. The occurrence of the intrinsic astrocytic calcium signal is strongly coincident with an increased EEG power level of the brain resting-state fluctuation. These results demonstrate highly correlated astrocytic Ca 2+ spikes with bidirectional fMRI signals based on the thalamic regulation of cortical states, depicting a brain-state dependency of both astrocytic Ca 2+ and BOLD fMRI signals.

Rebound spiking in layer II medial entorhinal cortex stellate cells: Possible mechanism of grid cell function

PubMed Central

Shay, Christopher F.; Ferrante, Michele; Chapman, G. William; Hasselmo, Michael E.

2015-01-01

Rebound spiking properties of medial entorhinal cortex (mEC) stellate cells induced by inhibition may underlie their functional properties in awake behaving rats, including the temporal phase separation of distinct grid cells and differences in grid cell firing properties. We investigated rebound spiking properties using whole cell patch recording in entorhinal slices, holding cells near spiking threshold and delivering sinusoidal inputs, superimposed with realistic inhibitory synaptic inputs to test the capacity of cells to selectively respond to specific phases of inhibitory input. Stellate cells showed a specific phase range of hyperpolarizing inputs that elicited spiking, but non-stellate cells did not show phase specificity. In both cell types, the phase range of spiking output occurred between the peak and subsequent descending zero crossing of the sinusoid. The phases of inhibitory inputs that induced spikes shifted earlier as the baseline sinusoid frequency increased, while spiking output shifted to later phases. Increases in magnitude of the inhibitory inputs shifted the spiking output to earlier phases. Pharmacological blockade of h-current abolished the phase selectivity of hyperpolarizing inputs eliciting spikes. A network computational model using cells possessing similar rebound properties as found in vitro produces spatially periodic firing properties resembling grid cell firing when a simulated animal moves along a linear track. These results suggest that the ability of mEC stellate cells to fire rebound spikes in response to a specific range of phases of inhibition could support complex attractor dynamics that provide completion and separation to maintain spiking activity of specific grid cell populations. PMID:26385258

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.

Seismology and Earthquake Ground Motions of the August 24, 2014 M6 South Napa Earthquake

NASA Astrophysics Data System (ADS)

Kishida, T.; Wang, S.; Mazzoni, S.; Markam, C.; Lu, Y.; Bozorgnia, Y.; Mahin, S.; Bray, J.; Panagiotou, M.; Stewart, J. P.; Darragh, R. B.; Abrahamson, N. A.; Hollenback, J. C.; Gutierrez, C.; Chiou, B.; Muin, S.; Dreger, D. S.

2014-12-01

The M6.0 South Napa earthquake produced strong ground motions in the northern San Francisco Bay area. A total of 214 three-component uncorrected digital accelerograms were downloaded from the CESMD website and processed following the PEER standard procedure (Ancheta et al. 2014). Intense ground motions were recorded in the heavily damaged area of Napa with peak acceleration greater than 0.3 g. Pulse-like waveforms were observed in several of the velocity time series at the near-fault stations. Near-fault velocity time series were rotated into fault normal and fault parallel directions and then characterized as pulse-like or non pulse-like according to previous studies by Hayden et al. (2014), Shahi (2013), and Lu and Panagiotou (2014). The near-fault velocity time series at five stations contained pulses with periods within the expected range of 0.7 s to 2.0 s for soil sites (Bray et al. 2009). However, they also contained longer period pulses than the expected range. High-frequency spikes were recorded at Carquinez Bridge Geotechnical Array #1 (CBGA1) of approximately 1.0 g on the NS component. These spikes were in the S-wave portion and were consistently observed in the downhole arrays and several other sites along the same azimuth from the source. The spikes increase in amplitude both from the Hwy 37/Napa River East Geotechnical Array to CBGA1 and from a depth below 100 m to the surface. This suggests that the spikes could be a result of path effects and site amplification through the surficial soft soil deposits. However, these observations do not exclude the possibility of soil-structure interaction effects on the measured recordings. The 5% damped pseudo-spectral accelerations (PSA) from the recorded ground motions compared well to those estimated from the recent NGA-West2 GMPEs. The exceptions are that PSA is under predicted from 1 to 3 seconds at several near fault records due to the velocity pulses and for short periods at Carquinez Bridge where the large high-frequency spikes in acceleration were recorded. The PSA of the recorded ground motions are compared to ASCE 7-10 design spectra and USGS uniform hazard spectra (UHS). The PSA exceeded the MCE spectra and the 2475-year UHS within the range of 1 to 2 s at two Napa stations, and short periods at CBGA1.

Spike processing with a graphene excitable laser

PubMed Central

Shastri, Bhavin J.; Nahmias, Mitchell A.; Tait, Alexander N.; Rodriguez, Alejandro W.; Wu, Ben; Prucnal, Paul R.

2016-01-01

Novel materials and devices in photonics have the potential to revolutionize optical information processing, beyond conventional binary-logic approaches. Laser systems offer a rich repertoire of useful dynamical behaviors, including the excitable dynamics also found in the time-resolved “spiking” of neurons. Spiking reconciles the expressiveness and efficiency of analog processing with the robustness and scalability of digital processing. We demonstrate a unified platform for spike processing with a graphene-coupled laser system. We show that this platform can simultaneously exhibit logic-level restoration, cascadability and input-output isolation—fundamental challenges in optical information processing. We also implement low-level spike-processing tasks that are critical for higher level processing: temporal pattern detection and stable recurrent memory. We study these properties in the context of a fiber laser system and also propose and simulate an analogous integrated device. The addition of graphene leads to a number of advantages which stem from its unique properties, including high absorption and fast carrier relaxation. These could lead to significant speed and efficiency improvements in unconventional laser processing devices, and ongoing research on graphene microfabrication promises compatibility with integrated laser platforms. PMID:26753897

Using 13C-labeled benzene and Raman gas spectroscopy to investigate respiration and biodegradation kinetics following soil contamination

NASA Astrophysics Data System (ADS)

Jochum, Tobias; Popp, Juergen; Frosch, Torsten

2016-04-01

Soil and groundwater contamination with benzene can cause serious environmental damages. However, many soil microorganisms are capable to adapt and known to strongly control the fate of organic contamination. Cavity enhanced Raman gas spectroscopy (CERS) was applied to investigate the short-term response of indigenous soil bacteria to a sudden surface contamination with benzene regarding the temporal variations of gas products and their exchange rates with the adjacent atmosphere. 13C-labeled benzene was spiked on a silty-loamy soil column (sampled from Hainich National Park, Germany) in order to track and separate the changes in heterotrophic soil respiration - involving 12CO2 and O2 - from the microbial process of benzene degradation, which ultimately forms 13CO2.1 The respiratory quotient (RQ) of 0.98 decreased significantly after the spiking and increased again within 33 hours to a value of 0.72. This coincided with maximum 13CO2 concentration rates (0.63 μ mol m-2 s-1), indicating highest benzene degradation at 33 hours after the spiking event. The diffusion of benzene in the headspace and the biodegradation into 13CO2 were simultaneously monitored and 12 days after the benzene spiking no measurable degradation was detected anymore.1 The RQ finally returned to a value of 0.96 demonstrating the reestablished aerobic respiration. In summary, this study shows the potential of combining Raman gas spectroscopy and stable isotopes to follow soil microbial biodegradation dynamics while simultaneously monitoring the underlying respiration behavior. Support by the Collaborative Research Center 1076 Aqua Diva is kindly acknowledged. We thank Beate Michalzik for soil analysis and discussion. 1. T. Jochum, B. Michalzik, A. Bachmann, J. Popp and T. Frosch, Analyst, 2015, 140, 3143-3149.

[Determination of phthalate plasticizers in foods by high performance liquid chromatography with gel permeation chromatographic clean-up].

PubMed

Zhang, Chunyu; Wang, Hui; Zhang, Xiaohui; Ma, Zhongqiang; Deng, Wanmei; Hu, Ke; Ding, Mingyu

2011-12-01

A method of gel permeation chromatography-high performance liquid chromatography (GPC-HPLC) was established for the simultaneous determination of 5 main phthalate plasticizers in foods (edible oil, instant noodles, fried pastries, Saqima, etc.). The samples were extracted with petroleum ether in an ultrasonator, purified by a GPC column, and analyzed by HPLC. The chromatographic separation was achieved on a Labtech-C18 column (250 mm x 4.6 mm, 5 microm) using acetonitrile and water mixture as the mobile phases in a gradient elution mode. The developed method exhibited a linear correlation coefficient of more than 0.997 and the detection limits of 3.25 - 13.4 microg/L. The spike recoveries were between 70.4% and 113.6% with the relative standard deviations (RSDs, n = 3) of 0.3% - 5.8% at the spiked level of 50 mg/L. This method is simple, rapid and practical, and can be used for the simultaneous determination of PAEs in grease food samples.

Simultaneous Detection of Four Foodborne Viruses in Food Samples Using a One-Step Multiplex Reverse Transcription PCR.

PubMed

Lee, Shin-Young; Kim, Mi-Ju; Kim, Hyun-Joong; Jeong, KwangCheol Casey; Kim, Hae-Yeong

2018-02-28

A one-step multiplex reverse transcription PCR (RT-PCR) method comprising six primer sets (for the detection of norovirus GI and GII, hepatitis A virus, rotavirus, and astrovirus) was developed to simultaneously detect four kinds of pathogenic viruses. The size of the PCR products for norovirus GI and GII, hepatitis A virus (VP3/VP1 and P2A regions), rotavirus, and astrovirus were 330, 164, 244, 198, 629, and 449 bp, respectively. The RT-PCR with the six primer sets showed specificity for the pathogenic viruses. The detection limit of the developed multiplex RT-PCR, as evaluated using serially diluted viral RNAs, was comparable to that of one-step single RT-PCR. Moreover, this multiplex RT-PCR was evaluated using food samples such as water, oysters, lettuce, and vegetable product. These food samples were artificially spiked with the four kinds of viruses in diverse combinations, and the spiked viruses in all food samples were detected successfully.

Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively

PubMed Central

Shimamoto, Shoichi; Waldman, Zachary J.; Orosz, Iren; Song, Inkyung; Bragin, Anatol; Fried, Itzhak; Engel, Jerome; Staba, Richard; Sharan, Ashwini; Wu, Chengyuan; Sperling, Michael R.; Weiss, Shennan A.

2018-01-01

Objective To develop and validate a detector that identifies ripple (80–200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence of detected ripples and the seizure onset zone (SOZ). Methods iEEG recordings from 16 patients were first band-pass filtered (80–600 Hz) and Infomax ICA was next applied to derive the first independent component (IC1). IC1 was subsequently pruned, and an artifact index was derived to reduce the identification of high-frequency events introduced by the reference electrode signal. A Hilbert detector identified ripple events in the processed iEEG recordings using amplitude and duration criteria. The identified ripple events were further classified and characterized as true or false ripple on spikes, or ripples on oscillations by utilizing a topographical analysis to their time-frequency plot, and confirmed by visual inspection. Results The signal to noise ratio was improved by pruning IC1. The precision of the detector for ripple events was 91.27 ± 4.3%, and the sensitivity of the detector was 79.4 ± 3.0% (N = 16 patients, 5842 ripple events). The sensitivity and precision of the detector was equivalent in iEEG recordings obtained during sleep or intra-operatively. Across all the patients, true ripple on spike rates and also the rates of false ripple on spikes, that were generated due to filter ringing, classified the seizure onset zone (SOZ) with an area under the receiver operating curve (AUROC) of >76%. The magnitude and spectral content of true ripple on spikes generated in the SOZ was distinct as compared with the ripples generated in the NSOZ (p < .001). Conclusions Utilizing ICA to analyze iEEG recordings in referential montage provides many benefits to the study of high-frequency oscillations. The ripple rates and properties defined using this approach may accurately delineate the seizure onset zone. Significance Strategies to improve the spatial resolution of intracranial EEG and reduce artifact can help improve the clinical utility of HFO biomarkers. PMID:29113719

Statistical properties of superimposed stationary spike trains.

PubMed

Deger, Moritz; Helias, Moritz; Boucsein, Clemens; Rotter, Stefan

2012-06-01

The Poisson process is an often employed model for the activity of neuronal populations. It is known, though, that superpositions of realistic, non- Poisson spike trains are not in general Poisson processes, not even for large numbers of superimposed processes. Here we construct superimposed spike trains from intracellular in vivo recordings from rat neocortex neurons and compare their statistics to specific point process models. The constructed superimposed spike trains reveal strong deviations from the Poisson model. We find that superpositions of model spike trains that take the effective refractoriness of the neurons into account yield a much better description. A minimal model of this kind is the Poisson process with dead-time (PPD). For this process, and for superpositions thereof, we obtain analytical expressions for some second-order statistical quantities-like the count variability, inter-spike interval (ISI) variability and ISI correlations-and demonstrate the match with the in vivo data. We conclude that effective refractoriness is the key property that shapes the statistical properties of the superposition spike trains. We present new, efficient algorithms to generate superpositions of PPDs and of gamma processes that can be used to provide more realistic background input in simulations of networks of spiking neurons. Using these generators, we show in simulations that neurons which receive superimposed spike trains as input are highly sensitive for the statistical effects induced by neuronal refractoriness.

Functional Neuroimaging of Spike-Wave Seizures

PubMed Central

Motelow, Joshua E.; Blumenfeld, Hal

2013-01-01

Generalized spike-wave seizures are typically brief events associated with dynamic changes in brain physiology, metabolism, and behavior. Functional magnetic resonance imaging (fMRI) provides a relatively high spatio-temporal resolution method for imaging cortical-subcortical network activity during spike-wave seizures. Patients with spike-wave seizures often have episodes of staring and unresponsiveness which interfere with normal behavior. Results from human fMRI studies suggest that spike-wave seizures disrupt specific networks in the thalamus and fronto-parietal association cortex which are critical for normal attentive consciousness. However, the neuronal activity underlying imaging changes seen during fMRI is not well understood, particularly in abnormal conditions such as seizures. Animal models have begun to provide important fundamental insights into the neuronal basis for fMRI changes during spike-wave activity. Work from these models including both fMRI and direct neuronal recordings suggest that, like in humans, specific cortical-subcortical networks are involved in spike-wave, while other regions are spared. Regions showing fMRI increases demonstrate correlated increases in neuronal activity in animal models. The mechanisms of fMRI decreases in spike-wave will require further investigation. A better understanding of the specific brain regions involved in generating spike-wave seizures may help guide efforts to develop targeted therapies aimed at preventing or reversing abnormal excitability in these brain regions, ultimately leading to a cure for this disorder. PMID:18839093

Dynamical estimation of neuron and network properties III: network analysis using neuron spike times.

PubMed

Knowlton, Chris; Meliza, C Daniel; Margoliash, Daniel; Abarbanel, Henry D I

2014-06-01

Estimating the behavior of a network of neurons requires accurate models of the individual neurons along with accurate characterizations of the connections among them. Whereas for a single cell, measurements of the intracellular voltage are technically feasible and sufficient to characterize a useful model of its behavior, making sufficient numbers of simultaneous intracellular measurements to characterize even small networks is infeasible. This paper builds on prior work on single neurons to explore whether knowledge of the time of spiking of neurons in a network, once the nodes (neurons) have been characterized biophysically, can provide enough information to usefully constrain the functional architecture of the network: the existence of synaptic links among neurons and their strength. Using standardized voltage and synaptic gating variable waveforms associated with a spike, we demonstrate that the functional architecture of a small network of model neurons can be established.

Interlaboratory comparison of measurements of acid-volatile sulfide and simultaneously extracted nickel in spiked sediments

USGS Publications Warehouse

Brumbaugh, William G.; Hammerschmidt, Chad R.; Zanella, Luciana; Rogevich, Emily; Salata, Gregory; Bolek, Radoslaw

2011-01-01

An interlaboratory comparison of acid-volatile sulfide (AVS) and simultaneously extracted nickel (SEM_Ni) measurements of sediments was conducted among five independent laboratories. Relative standard deviations for the seven test samples ranged from 5.6 to 71% (mean = 25%) for AVS and from 5.5 to 15% (mean = 10%) for SEM_Ni. These results are in stark contrast to a recently published study that indicated AVS and SEM analyses were highly variable among laboratories.

In vivo analysis of Purkinje cell firing properties during postnatal mouse development

PubMed Central

Arancillo, Marife; White, Joshua J.; Lin, Tao; Stay, Trace L.

2014-01-01

Purkinje cell activity is essential for controlling motor behavior. During motor behavior Purkinje cells fire two types of action potentials: simple spikes that are generated intrinsically and complex spikes that are induced by climbing fiber inputs. Although the functions of these spikes are becoming clear, how they are established is still poorly understood. Here, we used in vivo electrophysiology approaches conducted in anesthetized and awake mice to record Purkinje cell activity starting from the second postnatal week of development through to adulthood. We found that the rate of complex spike firing increases sharply at 3 wk of age whereas the rate of simple spike firing gradually increases until 4 wk of age. We also found that compared with adult, the pattern of simple spike firing during development is more irregular as the cells tend to fire in bursts that are interrupted by long pauses. The regularity in simple spike firing only reached maturity at 4 wk of age. In contrast, the adult complex spike pattern was already evident by the second week of life, remaining consistent across all ages. Analyses of Purkinje cells in alert behaving mice suggested that the adult patterns are attained more than a week after the completion of key morphogenetic processes such as migration, lamination, and foliation. Purkinje cell activity is therefore dynamically sculpted throughout postnatal development, traversing several critical events that are required for circuit formation. Overall, we show that simple spike and complex spike firing develop with unique developmental trajectories. PMID:25355961

Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

PubMed

Tam, Wing-Kin; Yang, Zhi

2018-05-01

Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

A Cross-Correlated Delay Shift Supervised Learning Method for Spiking Neurons with Application to Interictal Spike Detection in Epilepsy.

PubMed

Guo, Lilin; Wang, Zhenzhong; Cabrerizo, Mercedes; Adjouadi, Malek

2017-05-01

This study introduces a novel learning algorithm for spiking neurons, called CCDS, which is able to learn and reproduce arbitrary spike patterns in a supervised fashion allowing the processing of spatiotemporal information encoded in the precise timing of spikes. Unlike the Remote Supervised Method (ReSuMe), synapse delays and axonal delays in CCDS are variants which are modulated together with weights during learning. The CCDS rule is both biologically plausible and computationally efficient. The properties of this learning rule are investigated extensively through experimental evaluations in terms of reliability, adaptive learning performance, generality to different neuron models, learning in the presence of noise, effects of its learning parameters and classification performance. Results presented show that the CCDS learning method achieves learning accuracy and learning speed comparable with ReSuMe, but improves classification accuracy when compared to both the Spike Pattern Association Neuron (SPAN) learning rule and the Tempotron learning rule. The merit of CCDS rule is further validated on a practical example involving the automated detection of interictal spikes in EEG records of patients with epilepsy. Results again show that with proper encoding, the CCDS rule achieves good recognition performance.

Regular Patterns in Cerebellar Purkinje Cell Simple Spike Trains

PubMed Central

Shin, Soon-Lim; Hoebeek, Freek E.; Schonewille, Martijn; De Zeeuw, Chris I.; Aertsen, Ad; De Schutter, Erik

2007-01-01

Background Cerebellar Purkinje cells (PC) in vivo are commonly reported to generate irregular spike trains, documented by high coefficients of variation of interspike-intervals (ISI). In strong contrast, they fire very regularly in the in vitro slice preparation. We studied the nature of this difference in firing properties by focusing on short-term variability and its dependence on behavioral state. Methodology/Principal Findings Using an analysis based on CV2 values, we could isolate precise regular spiking patterns, lasting up to hundreds of milliseconds, in PC simple spike trains recorded in both anesthetized and awake rodents. Regular spike patterns, defined by low variability of successive ISIs, comprised over half of the spikes, showed a wide range of mean ISIs, and were affected by behavioral state and tactile stimulation. Interestingly, regular patterns often coincided in nearby Purkinje cells without precise synchronization of individual spikes. Regular patterns exclusively appeared during the up state of the PC membrane potential, while single ISIs occurred both during up and down states. Possible functional consequences of regular spike patterns were investigated by modeling the synaptic conductance in neurons of the deep cerebellar nuclei (DCN). Simulations showed that these regular patterns caused epochs of relatively constant synaptic conductance in DCN neurons. Conclusions/Significance Our findings indicate that the apparent irregularity in cerebellar PC simple spike trains in vivo is most likely caused by mixing of different regular spike patterns, separated by single long intervals, over time. We propose that PCs may signal information, at least in part, in regular spike patterns to downstream DCN neurons. PMID:17534435

Changes in Purkinje cell simple spike encoding of reach kinematics during adaption to a mechanical perturbation.

PubMed

Hewitt, Angela L; Popa, Laurentiu S; Ebner, Timothy J

2015-01-21

The cerebellum is essential in motor learning. At the cellular level, changes occur in both the simple spike and complex spike firing of Purkinje cells. Because simple spike discharge reflects the main output of the cerebellar cortex, changes in simple spike firing likely reflect the contribution of the cerebellum to the adapted behavior. Therefore, we investigated in Rhesus monkeys how the representation of arm kinematics in Purkinje cell simple spike discharge changed during adaptation to mechanical perturbations of reach movements. Monkeys rapidly adapted to a novel assistive or resistive perturbation along the direction of the reach. Adaptation consisted of matching the amplitude and timing of the perturbation to minimize its effect on the reach. In a majority of Purkinje cells, simple spike firing recorded before and during adaptation demonstrated significant changes in position, velocity, and acceleration sensitivity. The timing of the simple spike representations change within individual cells, including shifts in predictive versus feedback signals. At the population level, feedback-based encoding of position increases early in learning and velocity decreases. Both timing changes reverse later in learning. The complex spike discharge was only weakly modulated by the perturbations, demonstrating that the changes in simple spike firing can be independent of climbing fiber input. In summary, we observed extensive alterations in individual Purkinje cell encoding of reach kinematics, although the movements were nearly identical in the baseline and adapted states. Therefore, adaption to mechanical perturbation of a reaching movement is accompanied by widespread modifications in the simple spike encoding. Copyright © 2015 the authors 0270-6474/15/351106-19$15.00/0.

Changes in Purkinje Cell Simple Spike Encoding of Reach Kinematics during Adaption to a Mechanical Perturbation

PubMed Central

Hewitt, Angela L.; Popa, Laurentiu S.

2015-01-01

The cerebellum is essential in motor learning. At the cellular level, changes occur in both the simple spike and complex spike firing of Purkinje cells. Because simple spike discharge reflects the main output of the cerebellar cortex, changes in simple spike firing likely reflect the contribution of the cerebellum to the adapted behavior. Therefore, we investigated in Rhesus monkeys how the representation of arm kinematics in Purkinje cell simple spike discharge changed during adaptation to mechanical perturbations of reach movements. Monkeys rapidly adapted to a novel assistive or resistive perturbation along the direction of the reach. Adaptation consisted of matching the amplitude and timing of the perturbation to minimize its effect on the reach. In a majority of Purkinje cells, simple spike firing recorded before and during adaptation demonstrated significant changes in position, velocity, and acceleration sensitivity. The timing of the simple spike representations change within individual cells, including shifts in predictive versus feedback signals. At the population level, feedback-based encoding of position increases early in learning and velocity decreases. Both timing changes reverse later in learning. The complex spike discharge was only weakly modulated by the perturbations, demonstrating that the changes in simple spike firing can be independent of climbing fiber input. In summary, we observed extensive alterations in individual Purkinje cell encoding of reach kinematics, although the movements were nearly identical in the baseline and adapted states. Therefore, adaption to mechanical perturbation of a reaching movement is accompanied by widespread modifications in the simple spike encoding. PMID:25609626

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.

A model of metastable dynamics during ongoing and evoked cortical activity

NASA Astrophysics Data System (ADS)

La Camera, Giancarlo

The dynamics of simultaneously recorded spike trains in alert animals often evolve through temporal sequences of metastable states. Little is known about the network mechanisms responsible for the genesis of such sequences, or their potential role in neural coding. In the gustatory cortex of alert rates, state sequences can be observed also in the absence of overt sensory stimulation, and thus form the basis of the so-called `ongoing activity'. This activity is characterized by a partial degree of coordination among neurons, sharp transitions among states, and multi-stability of single neurons' firing rates. A recurrent spiking network model with clustered topology can account for both the spontaneous generation of state sequences and the (network-generated) multi-stability. In the model, each network state results from the activation of specific neural clusters with potentiated intra-cluster connections. A mean field solution of the model shows a large number of stable states, each characterized by a subset of simultaneously active clusters. The firing rate in each cluster during ongoing activity depends on the number of active clusters, so that the same neuron can have different firing rates depending on the state of the network. Because of dense intra-cluster connectivity and recurrent inhibition, in finite networks the stable states lose stability due to finite size effects. Simulations of the dynamics show that the model ensemble activity continuously hops among the different states, reproducing the ongoing dynamics observed in the data. Moreover, when probed with external stimuli, the model correctly predicts the quenching of single neuron multi-stability into bi-stability, the reduction of dimensionality of the population activity, the reduction of trial-to-trial variability, and a potential role for metastable states in the anticipation of expected events. Altogether, these results provide a unified mechanistic model of ongoing and evoked cortical dynamics. NSF IIS-1161852, NIDCD K25-DC013557, NIDCD R01-DC010389.

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.

Temporally coordinated spiking activity of human induced pluripotent stem cell-derived neurons co-cultured with astrocytes.

PubMed

Kayama, Tasuku; Suzuki, Ikuro; Odawara, Aoi; Sasaki, Takuya; Ikegaya, Yuji

2018-01-01

In culture conditions, human induced-pluripotent stem cells (hiPSC)-derived neurons form synaptic connections with other cells and establish neuronal networks, which are expected to be an in vitro model system for drug discovery screening and toxicity testing. While early studies demonstrated effects of co-culture of hiPSC-derived neurons with astroglial cells on survival and maturation of hiPSC-derived neurons, the population spiking patterns of such hiPSC-derived neurons have not been fully characterized. In this study, we analyzed temporal spiking patterns of hiPSC-derived neurons recorded by a multi-electrode array system. We discovered that specific sets of hiPSC-derived neurons co-cultured with astrocytes showed more frequent and highly coherent non-random synchronized spike trains and more dynamic changes in overall spike patterns over time. These temporally coordinated spiking patterns are physiological signs of organized circuits of hiPSC-derived neurons and suggest benefits of co-culture of hiPSC-derived neurons with astrocytes. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of spike-wave discharges in rats using discrete wavelet transform.

PubMed

Ubeyli, Elif Derya; Ilbay, Gül; Sahin, Deniz; Ateş, Nurbay

2009-03-01

A feature is a distinctive or characteristic measurement, transform, structural component extracted from a segment of a pattern. Features are used to represent patterns with the goal of minimizing the loss of important information. The discrete wavelet transform (DWT) as a feature extraction method was used in representing the spike-wave discharges (SWDs) records of Wistar Albino Glaxo/Rijswijk (WAG/Rij) rats. The SWD records of WAG/Rij rats were decomposed into time-frequency representations using the DWT and the statistical features were calculated to depict their distribution. The obtained wavelet coefficients were used to identify characteristics of the signal that were not apparent from the original time domain signal. The present study demonstrates that the wavelet coefficients are useful in determining the dynamics in the time-frequency domain of SWD records.

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.

Axonal recordings from medial superior olive neurons obtained from the lateral lemniscus of the chinchilla (Chinchilla laniger).

PubMed

Bremen, Peter; Joris, Philip X

2013-10-30

Interaural time differences (ITDs) are a major cue for localizing low-frequency (<1.5 kHz) sounds. Sensitivity to this cue first occurs in the medial superior olive (MSO), which is thought to perform a coincidence analysis on its monaural inputs. Extracellular single-neuron recordings in MSO are difficult to obtain because (1) MSO action potentials are small and (2) a large field potential locked to the stimulus waveform hampers spike isolation. Consequently, only a limited number of studies report MSO data, and even in these studies data are limited in the variety of stimuli used, in the number of neurons studied, and in spike isolation. More high-quality data are needed to better understand the mechanisms underlying neuronal ITD-sensitivity. We circumvented these difficulties by recording from the axons of MSO neurons in the lateral lemniscus (LL) of the chinchilla, a species with pronounced low-frequency sensitivity. Employing sharp glass electrodes we successfully recorded from neurons with ITD sensitivity: the location, response properties, latency, and spike shape were consistent with an MSO axonal origin. The main difficulty encountered was mechanical stability. We obtained responses to binaural beats and dichotic noise bursts to characterize the best delay versus characteristic frequency distribution, and compared the data to recordings we obtained in the inferior colliculus (IC). In contrast to most reports in other rodents, many best delays were close to zero ITD, both in MSO and IC, with a majority of the neurons recorded in the LL firing maximally within the presumed ethological ITD range.

Estimating the Information Extracted by a Single Spiking Neuron from a Continuous Input Time Series.

PubMed

Zeldenrust, Fleur; de Knecht, Sicco; Wadman, Wytse J; Denève, Sophie; Gutkin, Boris

2017-01-01

Understanding the relation between (sensory) stimuli and the activity of neurons (i.e., "the neural code") lies at heart of understanding the computational properties of the brain. However, quantifying the information between a stimulus and a spike train has proven to be challenging. We propose a new ( in vitro ) method to measure how much information a single neuron transfers from the input it receives to its output spike train. The input is generated by an artificial neural network that responds to a randomly appearing and disappearing "sensory stimulus": the hidden state. The sum of this network activity is injected as current input into the neuron under investigation. The mutual information between the hidden state on the one hand and spike trains of the artificial network or the recorded spike train on the other hand can easily be estimated due to the binary shape of the hidden state. The characteristics of the input current, such as the time constant as a result of the (dis)appearance rate of the hidden state or the amplitude of the input current (the firing frequency of the neurons in the artificial network), can independently be varied. As an example, we apply this method to pyramidal neurons in the CA1 of mouse hippocampi and compare the recorded spike trains to the optimal response of the "Bayesian neuron" (BN). We conclude that like in the BN, information transfer in hippocampal pyramidal cells is non-linear and amplifying: the information loss between the artificial input and the output spike train is high if the input to the neuron (the firing of the artificial network) is not very informative about the hidden state. If the input to the neuron does contain a lot of information about the hidden state, the information loss is low. Moreover, neurons increase their firing rates in case the (dis)appearance rate is high, so that the (relative) amount of transferred information stays constant.

Single-unit muscle sympathetic nervous activity and its relation to cardiac noradrenaline spillover

PubMed Central

Lambert, Elisabeth A; Schlaich, Markus P; Dawood, Tye; Sari, Carolina; Chopra, Reena; Barton, David A; Kaye, David M; Elam, Mikael; Esler, Murray D; Lambert, Gavin W

2011-01-01

Abstract Recent work using single-unit sympathetic nerve recording techniques has demonstrated aberrations in the firing pattern of sympathetic nerves in a variety of patient groups. We sought to examine whether nerve firing pattern is associated with increased noradrenaline release. Using single-unit muscle sympathetic nerve recording techniques coupled with direct cardiac catheterisation and noradrenaline isotope dilution methodology we examined the relationship between single-unit firing patterns and cardiac and whole body noradrenaline spillover to plasma. Participants comprised patients with hypertension (n = 6), depression (n = 7) and panic disorder (n = 9) who were drawn from our ongoing studies. The patient groups examined did not differ in their single-unit muscle sympathetic nerve firing characteristics nor in the rate of spillover of noradrenaline to plasma from the heart. The median incidence of multiple spikes per beat was 9%. Patients were stratified according to the firing pattern: low level of incidence (less than 9% incidence of multiple spikes per beat) and high level of incidence (greater than 9% incidence of multiple spikes per beat). High incidence of multiple spikes within a cardiac cycle was associated with higher firing rates (P < 0.0001) and increased probability of firing (P < 0.0001). Whole body noradrenaline spillover to plasma and (multi-unit) muscle sympathetic nerve activity in subjects with low incidence of multiple spikes was not different to that of those with high incidence of multiple spikes. In those with high incidence of multiple spikes there occurred a parallel activation of the sympathetic outflow to the heart, with cardiac noradrenaline spillover to plasma being two times that of subjects with low nerve firing rates (11.0 ± 1.5 vs. 22.0 ± 4.5 ng min−1, P < 0.05). This study indicates that multiple within-burst firing and increased single-unit firing rates of the sympathetic outflow to the skeletal muscle vasculature is associated with high cardiac noradrenaline spillover. PMID:21486790

β-Adrenergic enhancement of neuronal excitability in the lateral amygdala is developmentally gated.

PubMed

Fink, Ann E; LeDoux, Joseph E

2018-05-01

Noradrenergic signaling in the amygdala is important for processing threats and other emotionally salient stimuli, and β-adrenergic receptor activation is known to enhance neuronal spiking in the lateral amygdala (LA) of juvenile animals. Nevertheless, intracellular recordings have not yet been conducted to determine the effect of β-adrenergic receptor activation on spike properties in the adult LA, despite the potential significance of developmental changes between adolescence and adulthood. Here we demonstrate that the β-adrenergic agonist isoproterenol (15 μM) enhances spike frequency in dorsal LA principal neurons of juvenile male C57BL/6 mice and fails to do so in strain- and sex-matched adults. Furthermore, we find that the age-dependent effect of isoproterenol on spike frequency is occluded by the GABA A receptor blocker picrotoxin (75 μM), suggesting that β-adrenergic receptors downregulate tonic inhibition specifically in juvenile animals. These findings indicate a significant shift during adolescence in the cellular mechanisms of β-adrenergic modulation in the amygdala. NEW & NOTEWORTHY β-Adrenergic receptors (β-ARs) in amygdala are important in processing emotionally salient stimuli. Most cellular recordings have examined juvenile animals, while behavioral data are often obtained from adults. We replicate findings showing that β-ARs enhance spiking of principal cells in the lateral amygdala of juveniles, but we fail to find this in adults. These findings have notable scientific and clinical implications regarding the noradrenergic modulation of threat processing, alterations of which underlie fear and anxiety disorders.

A Comparison of Golf Shoe Designs Highlights Greater Ground Reaction Forces with Shorter Irons

PubMed Central

Worsfold, Paul; Smith, Neal A.; Dyson, Rosemary J.

2007-01-01

In an effort to reduce golf turf damage the traditional metal spike golf shoe has been redesigned, but shoe-ground biomechanical evaluations have utilised artificial grass surfaces. Twenty-four golfers wore three different golf shoe traction designs (traditional metal spikes, alternative spikes, and a flat-soled shoe with no additional traction) when performing shots with a driver, 3 iron and 7 iron. Ground action forces were measured beneath the feet by two natural grass covered force platforms. The maximum vertical force recorded at the back foot with the 3 iron and 7 iron was 0.82 BW (body weight) and at the front foot 1.1 BW approximately in both the metal spike and alternative spike golf shoe designs. When using the driver these maximal vertical values were 0.49 BW at the back foot and 0.84 BW at the front foot. Furthermore, as performance of the backswing and then downswing necessitates a change in movement direction the range of force generated during the complete swing was calculated. In the metal spike shoe the vertical force generated at the back foot with both irons was 0.67 BW and at the front foot 0.96 BW with the 3 iron and 0.92 BW with the 7 iron. The back foot vertical force generated with the driver was 0.33 BW and at the front foot 0.83 BW wearing the metal spike shoe. Results indicated the greater force generation with the irons. When using the driver the more horizontal swing plane associated with the longer club reduced vertical forces at the back and front foot. However, the mediolateral force generated across each foot in the metal and alternative spike shoes when using the driver was greater than when the irons were used. The coefficient of friction was 0. 62 at the back and front foot whichever shoe was worn or club used. Key pointsDuring the golf swing ground reaction forces at the golf shoe to natural grass turf interface were greater with irons than with the longer driver.In the golf swing maximal vertical forces were greater at the front (left) foot in the than at the back foot for a right handed golfer.Similar maximum vertical ground reaction forces were recorded with each club when a 8 mm metal spike golf shoe or an alternative spike golf shoe were worn.Force generation and coefficients of friction were similar for the alternative spike design and traditional metal seven spike golf shoe on natural grass turf.Data collection possible due to application of technical developments to golf from work on other natural turf based sports. PMID:24149482

Recording single neurons' action potentials from freely moving pigeons across three stages of learning.

PubMed

Starosta, Sarah; Stüttgen, Maik C; Güntürkün, Onur

2014-06-02

While the subject of learning has attracted immense interest from both behavioral and neural scientists, only relatively few investigators have observed single-neuron activity while animals are acquiring an operantly conditioned response, or when that response is extinguished. But even in these cases, observation periods usually encompass only a single stage of learning, i.e. acquisition or extinction, but not both (exceptions include protocols employing reversal learning; see Bingman et al.(1) for an example). However, acquisition and extinction entail different learning mechanisms and are therefore expected to be accompanied by different types and/or loci of neural plasticity. Accordingly, we developed a behavioral paradigm which institutes three stages of learning in a single behavioral session and which is well suited for the simultaneous recording of single neurons' action potentials. Animals are trained on a single-interval forced choice task which requires mapping each of two possible choice responses to the presentation of different novel visual stimuli (acquisition). After having reached a predefined performance criterion, one of the two choice responses is no longer reinforced (extinction). Following a certain decrement in performance level, correct responses are reinforced again (reacquisition). By using a new set of stimuli in every session, animals can undergo the acquisition-extinction-reacquisition process repeatedly. Because all three stages of learning occur in a single behavioral session, the paradigm is ideal for the simultaneous observation of the spiking output of multiple single neurons. We use pigeons as model systems, but the task can easily be adapted to any other species capable of conditioned discrimination learning.

Medial prefrontal cortex neuronal circuits in fear behavior.

PubMed

Courtin, J; Bienvenu, T C M; Einarsson, E Ö; Herry, C

2013-06-14

The medial prefrontal cortex (mPFC) has emerged as a key structure involved in the modulation of fear behavior over the past few decades. Anatomical, functional and electrophysiological studies have begun to shed light on the precise mechanisms by which different prefrontal regions regulate the expression and inhibition of fear behavior. These studies have established a canonical view of mPFC functions during fear behavior with dorsal regions selectively involved in the expression of fear behavior and ventral regions linked to the inhibition of fear behavior. Although numerous reports support this view, recent data have refined this model and suggested that dorsal prefrontal regions might also play an important role in the encoding of fear behavior itself. The recent development of sophisticated approaches such as large scale neuronal recordings, simultaneous multisite recordings of spiking activity and local field potentials (LFPs) along with optogenetic approaches will facilitate the testing of these new hypotheses in the near future. Here we provide an extensive review of the literature on the role of mPFC in fear behavior and propose further directions to dissect the contribution of specific prefrontal neuronal elements and circuits in the regulation of fear behavior. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Investigation of mercury exchange between forest canopy vegetation and the atmosphere using a new dynamic chamber

USGS Publications Warehouse

Graydon, J.A.; St. Louis, V.L.; Lindberg, S.E.; Hintelmann, H.; Krabbenhoft, D.P.

2006-01-01

This paper presents the design of a dynamic chamber system that allows full transmission of PAR and UV radiation and permits enclosed intact foliage to maintain normal physiological function while Hg(0) flux rates are quantified in the field. Black spruce and jack pine foliage both emitted and absorbed Hg(0), exhibiting compensation points near atmospheric Hg(0) concentrations of ???2-3 ng m-3. Using enriched stable Hg isotope spikes, patterns of spike Hg(II) retention on foliage were investigated. Hg(0) evasion rates from foliage were simultaneously measured using the chamber to determine if the decline of foliar spike Hg(II) concentrations overtime could be explained by the photoreduction and re-emission of spike Hg to the atmosphere. This mass balance approach suggested that spike Hg(0) fluxes alone could not account for the measured decrease in spike Hg(II) on foliage following application, implying that either the chamber underestimates the true photoreduction of Hg(II) to Hg(0) on foliage, or other mechanisms of Hg(II) loss from foliage, such as cuticle weathering, are in effect. The radiation spectrum responsible for the photoreduction of newly deposited Hg(II) on foliage was also investigated. Our spike experiments suggest that some of the Hg(II) in wet deposition retained by the forest canopy may be rapidly photoreduced to Hg(0) and re-emitted back to the atmosphere, while another portion may be retained by foliage at the end of the growing season, with some being deposited in litterfall. This finding has implications for the estimation of Hg dry deposition based on throughfall and litterfall fluxes. ?? 2006 American Chemical Society.

Stimulus Size Dependence of Information Transfer from Retina to Thalamus

PubMed Central

Uglesich, Robert; Casti, Alex; Hayot, Fernand; Kaplan, Ehud

2009-01-01

Relay cells in the mammalian lateral geniculate nucleus (LGN) are driven primarily by single retinal ganglion cells (RGCs). However, an LGN cell responds typically to less than half of the spikes it receives from the RGC that drives it, and without retinal drive the LGN is silent (Kaplan and Shapley, 1984). Recent studies, which used stimuli restricted to the receptive field (RF) center, show that despite the great loss of spikes, more than half of the information carried by the RGC discharge is typically preserved in the LGN discharge (Sincich et al., 2009), suggesting that the retinal spikes that are deleted by the LGN carry less information than those that are transmitted to the cortex. To determine how LGN relay neurons decide which retinal spikes to respond to, we recorded extracellularly from the cat LGN relay cell spikes together with the slow synaptic (‘S’) potentials that signal the firing of retinal spikes. We investigated the influence of the inhibitory surround of the LGN RF by stimulating the eyes with spots of various sizes, the largest of which covered the center and surround of the LGN relay cell's RF. We found that for stimuli that activated mostly the RF center, each LGN spike delivered more information than the retinal spike, but this difference was reduced as stimulus size increased to cover the RF surround. To evaluate the optimality of the LGN editing of retinal spikes, we created artificial spike trains from the retinal ones by various deletion schemes. We found that single LGN cells transmitted less information than an optimal detector could. PMID:19838326

Spike-train communities: finding groups of similar spike trains.

PubMed

Humphries, Mark D

2011-02-09

Identifying similar spike-train patterns is a key element in understanding neural coding and computation. For single neurons, similar spike patterns evoked by stimuli are evidence of common coding. Across multiple neurons, similar spike trains indicate potential cell assemblies. As recording technology advances, so does the urgent need for grouping methods to make sense of large-scale datasets of spike trains. Existing methods require specifying the number of groups in advance, limiting their use in exploratory analyses. I derive a new method from network theory that solves this key difficulty: it self-determines the maximum number of groups in any set of spike trains, and groups them to maximize intragroup similarity. This method brings us revealing new insights into the encoding of aversive stimuli by dopaminergic neurons, and the organization of spontaneous neural activity in cortex. I show that the characteristic pause response of a rat's dopaminergic neuron depends on the state of the superior colliculus: when it is inactive, aversive stimuli invoke a single pattern of dopaminergic neuron spiking; when active, multiple patterns occur, yet the spike timing in each is reliable. In spontaneous multineuron activity from the cortex of anesthetized cat, I show the existence of neural ensembles that evolve in membership and characteristic timescale of organization during global slow oscillations. I validate these findings by showing that the method both is remarkably reliable at detecting known groups and can detect large-scale organization of dynamics in a model of the striatum.

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

Network rhythms influence the relationship between spike-triggered local field potential and functional connectivity

PubMed Central

Maunsell, John H.R.

2012-01-01

Characterizing the functional connectivity between neurons is key for understanding brain function. We recorded spikes and local field potentials (LFP) from multi-electrode arrays implanted in monkey visual cortex to test the hypotheses that spikes generated outward traveling LFP waves and the strength of functional connectivity depended on stimulus contrast, as described recently. These hypotheses were proposed based on the observation that the latency of the peak negativity of the spike-triggered LFP average (STA) increased with distance between the spike and LFP electrodes, and the magnitude of the STA negativity and the distance over which it was observed decreased with increasing stimulus contrast. Detailed analysis of the shape of the STA, however, revealed contributions from two distinct sources – a transient negativity in the LFP locked to the spike (∼0 ms) that attenuated rapidly with distance, and a low frequency rhythm with peak negativity ∼25 ms after the spike that attenuated slowly with distance. The overall negative peak of the LFP, which combined both these components, shifted from ∼0 to ∼25 ms going from electrodes near the spike to electrodes far from the spike, giving an impression of a traveling wave, although the shift was fully explained by changing contributions from the two fixed components. The low frequency rhythm was attenuated during stimulus presentations, decreasing the overall magnitude of the STA. These results highlight the importance of accounting for the network activity while using STAs to determine functional connectivity. PMID:21880928

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.

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.

Frequency-dependent response of SI RA-class neurons to vibrotactile stimulation of the receptive field.

PubMed

Whitsel, B L; Kelly, E F; Xu, M; Tommerdahl, M; Quibrera, M

2001-01-01

Three types of experiment were carried out on anesthetized monkeys and cats. In the first, spike discharge activity of rapidly adapting (RA) SI neurons was recorded extracellularly during the application of different frequencies of vibrotactile stimulation to the receptive field (RF). The second used the same stimulus conditions to study the response of RA-I (RA) cutaneous mechanoreceptive afferents. The third used optical intrinsic signal (OIS) imaging and extracellular neurophysiological recording methods together, in the same sessions, to evaluate the relationship between the SI optical and RA neuron spike train responses to low- vs high-frequency stimulation of the same skin site. RA afferent entrainment was high at all frequencies of stimulation. In contrast, SI RA neuron entrainment was much lower on average, and was strongly frequency-dependent, declining in near-linear fashion from 6 to 200 Hz. Even at 200 Hz, however, unambiguous frequency-following responses were present in the spike train activity of som

The role of BK-type Ca2+-dependent K+ channels in spike broadening during repetitive firing in rat hippocampal pyramidal cells

PubMed Central

Shao, Li-Rong; Halvorsrud, Ragnhild; Borg-Graham, Lyle; Storm, Johan F

1999-01-01

The role of large-conductance Ca2+-dependent K+ channels (BK-channels; also known as maxi-K- or slo-channels) in spike broadening during repetitive firing was studied in CA1 pyramidal cells, using sharp electrode intracellular recordings in rat hippocampal slices, and computer modelling. Trains of action potentials elicited by depolarizing current pulses showed a progressive, frequency-dependent spike broadening, reflecting a reduced rate of repolarization. During a 50 ms long 5 spike train, the spike duration increased by 63·6 ± 3·4% from the 1st to the 3rd spike. The amplitude of the fast after-hyperpolarization (fAHP) also rapidly declined during each train. Suppression of BK-channel activity with (a) the selective BK-channel blocker iberiotoxin (IbTX, 60 nM), (b) the non-peptidergic BK-channel blocker paxilline (2–10 μM), or (c) calcium-free medium, broadened the 1st spike to a similar degree (≈60%). BK-channel suppression also caused a similar change in spike waveform as observed during repetitive firing, and eliminated (occluded) most of the spike broadening during repetitive firing. Computer simulations using a reduced compartmental model with transient BK-channel current and 10 other active ionic currents, produced an activity-dependent spike broadening that was strongly reduced when the BK-channel inactivation mechanism was removed. These results, which are supported by recent voltage-clamp data, strongly suggest that in CA1 pyramidal cells, fast inactivation of a transient BK-channel current (ICT), substantially contributes to frequency-dependent spike broadening during repetitive firing. PMID:10562340

Localization of MEG pathologic gamma oscillations in adult epilepsy patients with focal cortical dysplasia☆

PubMed Central

Jeong, Woorim; Kim, June Sic; Chung, Chun Kee

2013-01-01

We aimed to evaluate the clinical value of gamma oscillations in MEG for intractable neocortical epilepsy patients with cortical dysplasia by comparing gamma and interictal spike events. A retrospective analysis of MEG recordings of 30 adult neocortical epilepsy patients was performed. Gamma (30–70 Hz) and interictal spike events were independently identified, their independent or concurrent presence determined, and their source localization rates compared. Of 30 patients, gamma activities were detected in 28 patients and interictal spikes in 24 patients. Gamma events alone appeared in 5 patients, interictal spikes alone in 1 patient, and no events in 1 patient. Gamma co-occurred with interictal spikes in 20.1 ± 22.1% and interictal spikes co-occurred with gamma in 15.0 ± 19.2%. Rates of event localization within the resection cavity were significantly different (p = 0.042) between gamma (63.3 ± 32.6%) and interictal spike (47.0 ± 41.3%) events. In 4 of the 5 gamma-only patients the mean localization rate was 42.5%. Compared with the interictal spike localization rate, 4 of 9 seizure-free patients had higher gamma localization rates, 4 had the same rate, and 1 had a lower rate. Individual gamma events can be detected independently from interictal spike presence. Gamma can be localized to the resection cavity at least comparably to or more frequently than that from interictal spikes. Even when interictal spikes were undetected, gamma sources were localized to the resection cavity. Gamma oscillations may be a useful indicator of epileptogenic focus. PMID:24273733

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

Low power and high accuracy spike sorting microprocessor with on-line interpolation and re-alignment in 90 nm CMOS process.

PubMed

Chen, Tung-Chien; Ma, Tsung-Chuan; Chen, Yun-Yu; Chen, Liang-Gee

2012-01-01

Accurate spike sorting is an important issue for neuroscientific and neuroprosthetic applications. The sorting of spikes depends on the features extracted from the neural waveforms, and a better sorting performance usually comes with a higher sampling rate (SR). However for the long duration experiments on free-moving subjects, the miniaturized and wireless neural recording ICs are the current trend, and the compromise on sorting accuracy is usually made by a lower SR for the lower power consumption. In this paper, we implement an on-chip spike sorting processor with integrated interpolation hardware in order to improve the performance in terms of power versus accuracy. According to the fabrication results in 90nm process, if the interpolation is appropriately performed during the spike sorting, the system operated at the SR of 12.5 k samples per second (sps) can outperform the one not having interpolation at 25 ksps on both accuracy and power.

The influence of single bursts vs. single spikes at excitatory dendrodendritic synapses

PubMed Central

Masurkar, Arjun V.; Chen, Wei R.

2015-01-01

The synchronization of neuronal activity is thought to enhance information processing. There is much evidence supporting rhythmically bursting external tufted cells (ETCs) of the rodent olfactory bulb glomeruli coordinating the activation of glomerular interneurons and mitral cells via dendrodendritic excitation. However, as bursting has variable significance at axodendritic cortical synapses, it is not clear if ETC bursting imparts a specific functional advantage over the preliminary spike in dendrodendritic synaptic networks. To answer this question, we investigated the influence of single ETC bursts and spikes with the in-vitro rat olfactory bulb preparation at different levels of processing, via calcium imaging of presynaptic ETC dendrites, dual electrical recording of ETC–interneuron synaptic pairs, and multicellular calcium imaging of ETC-induced population activity. Our findings supported single ETC bursts, vs. single spikes, driving robust presynaptic calcium signaling, which in turn was associated with profound extension of the initial monosynaptic spike-driven dendrodendritic excitatory postsynaptic potential. This extension could be driven by either the spike-dependent or spike-independent components of the burst. At the population level, burst-induced excitation was more widespread and reliable compared with single spikes. This further supports the ETC network, in part due to a functional advantage of bursting at excitatory dendrodendritic synapses, coordinating synchronous activity at behaviorally relevant frequencies related to odor processing in vivo. PMID:22277089

Quality control considerations for the determination of acid-volatile sulfide and simultaneously extracted metals in sediments

USGS Publications Warehouse

Brumbaugh, William G.; Arms, Jesse W.

1996-01-01

The determination of acid-volatile sulfide (AVS) and simultaneously extracted metals (SEMs) in sediment by treatment with dilute HCl shows promise as a tool for predicting the potential for metal toxicity to sediment-dwelling organisms. Effective quality control measures must be developed if this method is to become a reliable procedure and to ensure comparability of data. However, establishing quality control measures that assess procedural errors for an operationally defined method can be problematic. For example, preextraction spikes added for assessing the accuracy of AVS and SEMs may be poorly recovered due to adsorption or reaction with sediment constituents. For a variety of sediment types, we found preextraction spikes of sulfide, mercury, and copper to be prone to variable recoveries for the AVS/SEM procedure; recoveries averaged 76.3% (SD, 20.9) for sulfide, 61.9% (39.6) for Hg, and 90.1% (12.7) for Cu. The average recovery was near 100% for preextraction spikes of sediments for Cd, Ni, Pb, and Zn, and the recoveries of preextraction blank spikes for all analytes were consistently 95 to 105%. Binding of Cu or Hg with sulfides is sufficiently strong that 1 N hydrochloric acid will not necessarily keep the spiked metal in the dissolved state. This does not mean that the SEM procedure is invalid for these metals, only that the quality control of procedural error is difficult to assess. However, Hg will generally not be detected when measured as an SEM because of its tendency to adsorb onto sulfide minerals even at extremely low pH. Some reference sediments may be useful for assessing consistency of AVS determinations; we measured 5.97 ± 0.65 μmol/g in National Institute of Standards and Technology (NIST) 1645 and 1.34 ± 0.14 μmol/g in NIST 2704 for repeated determinations conducted over the past 3 years. Apparently, some sediments may contain an oxidation-resistant sulfide component that can release low to moderate AVS when treated with dilute HCl.

Arcuate hypothalamic AgRP and putative POMC neurons show opposite changes in spiking across multiple timescales

PubMed Central

Mandelblat-Cerf, Yael; Ramesh, Rohan N; Burgess, Christian R; Patella, Paola; Yang, Zongfang; Lowell, Bradford B; Andermann, Mark L

2015-01-01

Agouti-related-peptide (AgRP) neurons—interoceptive neurons in the arcuate nucleus of the hypothalamus (ARC)—are both necessary and sufficient for driving feeding behavior. To better understand the functional roles of AgRP neurons, we performed optetrode electrophysiological recordings from AgRP neurons in awake, behaving AgRP-IRES-Cre mice. In free-feeding mice, we observed a fivefold increase in AgRP neuron firing with mounting caloric deficit in afternoon vs morning recordings. In food-restricted mice, as food became available, AgRP neuron firing dropped, yet remained elevated as compared to firing in sated mice. The rapid drop in spiking activity of AgRP neurons at meal onset may reflect a termination of the drive to find food, while residual, persistent spiking may reflect a sustained drive to consume food. Moreover, nearby neurons inhibited by AgRP neuron photostimulation, likely including satiety-promoting pro-opiomelanocortin (POMC) neurons, demonstrated opposite changes in spiking. Finally, firing of ARC neurons was also rapidly modulated within seconds of individual licks for liquid food. These findings suggest novel roles for antagonistic AgRP and POMC neurons in the regulation of feeding behaviors across multiple timescales. DOI: http://dx.doi.org/10.7554/eLife.07122.001 PMID:26159614

Preserving information in neural transmission.

PubMed

Sincich, Lawrence C; Horton, Jonathan C; Sharpee, Tatyana O

2009-05-13

Along most neural pathways, the spike trains transmitted from one neuron to the next are altered. In the process, neurons can either achieve a more efficient stimulus representation, or extract some biologically important stimulus parameter, or succeed at both. We recorded the inputs from single retinal ganglion cells and the outputs from connected lateral geniculate neurons in the macaque to examine how visual signals are relayed from retina to cortex. We found that geniculate neurons re-encoded multiple temporal stimulus features to yield output spikes that carried more information about stimuli than was available in each input spike. The coding transformation of some relay neurons occurred with no decrement in information rate, despite output spike rates that averaged half the input spike rates. This preservation of transmitted information was achieved by the short-term summation of inputs that geniculate neurons require to spike. A reduced model of the retinal and geniculate visual responses, based on two stimulus features and their associated nonlinearities, could account for >85% of the total information available in the spike trains and the preserved information transmission. These results apply to neurons operating on a single time-varying input, suggesting that synaptic temporal integration can alter the temporal receptive field properties to create a more efficient representation of visual signals in the thalamus than the retina.

Seasonal Plasticity of Precise Spike Timing in the Avian Auditory System

PubMed Central

Sen, Kamal; Rubel, Edwin W; Brenowitz, Eliot A.

2015-01-01

Vertebrate audition is a dynamic process, capable of exhibiting both short- and long-term adaptations to varying listening conditions. Precise spike timing has long been known to play an important role in auditory encoding, but its role in sensory plasticity remains largely unexplored. We addressed this issue in Gambel's white-crowned sparrow (Zonotrichia leucophrys gambelii), a songbird that shows pronounced seasonal fluctuations in circulating levels of sex-steroid hormones, which are known to be potent neuromodulators of auditory function. We recorded extracellular single-unit activity in the auditory forebrain of males and females under different breeding conditions and used a computational approach to explore two potential strategies for the neural discrimination of sound level: one based on spike counts and one based on spike timing reliability. We report that breeding condition has robust sex-specific effects on spike timing. Specifically, in females, breeding condition increases the proportion of cells that rely solely on spike timing information and increases the temporal resolution required for optimal intensity encoding. Furthermore, in a functionally distinct subset of cells that are particularly well suited for amplitude encoding, female breeding condition enhances spike timing-based discrimination accuracy. No effects of breeding condition were observed in males. Our results suggest that high-resolution temporal discharge patterns may provide a plastic neural substrate for sensory coding. PMID:25716843

In vivo mouse inferior olive neurons exhibit heterogeneous subthreshold oscillations and spiking patterns

PubMed Central

Khosrovani, S.; Van Der Giessen, R. S.; De Zeeuw, C. I.; De Jeu, M. T. G.

2007-01-01

In vitro whole-cell recordings of the inferior olive have demonstrated that its neurons are electrotonically coupled and have a tendency to oscillate. However, it remains to be shown to what extent subthreshold oscillations do indeed occur in the inferior olive in vivo and whether its spatiotemporal firing pattern may be dynamically generated by including or excluding different types of oscillatory neurons. Here, we did whole-cell recordings of olivary neurons in vivo to investigate the relation between their subthreshold activities and their spiking behavior in an intact brain. The vast majority of neurons (85%) showed subthreshold oscillatory activities. The frequencies of these subthreshold oscillations were used to distinguish four main olivary subtypes by statistical means. Type I showed both sinusoidal subthreshold oscillations (SSTOs) and low-threshold Ca2+ oscillations (LTOs) (16%); type II showed only sinusoidal subthreshold oscillations (13%); type III showed only low-threshold Ca2+ oscillations (56%); and type IV did not reveal any subthreshold oscillations (15%). These subthreshold oscillation frequencies were strongly correlated with the frequencies of preferred spiking. The frequency characteristics of the subthreshold oscillations and spiking behavior of virtually all olivary neurons were stable throughout the recordings. However, the occurrence of spontaneous or evoked action potentials modified the subthreshold oscillation by resetting the phase of its peak toward 90°. Together, these findings indicate that the inferior olive in intact mammals offers a rich repertoire of different neurons with relatively stable frequency settings, which can be used to generate and reset temporal firing patterns in a dynamically coupled ensemble. PMID:17895389

Inherent characteristics of sawtooth cycles can explain different glacial periodicities

NASA Astrophysics Data System (ADS)

Omta, Anne Willem; Kooi, Bob W.; van Voorn, George A. K.; Rickaby, Rosalind E. M.; Follows, Michael J.

2016-01-01

At the Mid-Pleistocene Transition about 1 Ma, the dominant periodicity of the glacial-interglacial cycles shifted from 40 to 100 kyr. Here, we use a previously developed mathematical model to investigate the possible dynamical origin of these different periodicities. The model has two variables, one of which exhibits sawtooth oscillations, resembling the glacial-interglacial cycles, whereas the other variable exhibits spikes at the rapid transitions. When applying a sinusoidal forcing with a fixed period, there emerges a rich variety of cycles with different periodicities, each being a multiple of the forcing period. Furthermore, the dominant periodicity of the system can change, while the forcing periodicity remains fixed, due to either random variations or different frequency components of the orbital forcing. Two key relationships stand out as predictions to be tested against observations: (1) the amplitude and the periodicity of the cycles are approximately linearly proportional to each other, a relationship that is also found in the δ ^{18}O temperature proxy. (2) The magnitude of the spikes increases with increasing periodicity and amplitude of the sawtooth. This prediction could be used to identify one or more currently hidden spiking variables driving the glacial-interglacial transitions. Essentially, the quest would be for any proxy record, concurrent with a dynamical model prediction, that exhibits deglacial spikes which increase at times when the amplitude/periodicity of the glacial cycles increases. In the specific context of our calcifier-alkalinity mechanism, the records of interest would be calcifier productivity and calcite accumulation. We believe that such a falsifiable hypothesis should provide a strong motivation for the collection of further records.

Systematic Regional Variations in Purkinje Cell Spiking Patterns

PubMed Central

Xiao, Jianqiang; Cerminara, Nadia L.; Kotsurovskyy, Yuriy; Aoki, Hanako; Burroughs, Amelia; Wise, Andrew K.; Luo, Yuanjun; Marshall, Sarah P.; Sugihara, Izumi; Apps, Richard; Lang, Eric J.

2014-01-01

In contrast to the uniform anatomy of the cerebellar cortex, molecular and physiological studies indicate that significant differences exist between cortical regions, suggesting that the spiking activity of Purkinje cells (PCs) in different regions could also show distinct characteristics. To investigate this possibility we obtained extracellular recordings from PCs in different zebrin bands in crus IIa and vermis lobules VIII and IX in anesthetized rats in order to compare PC firing characteristics between zebrin positive (Z+) and negative (Z−) bands. In addition, we analyzed recordings from PCs in the A2 and C1 zones of several lobules in the posterior lobe, which largely contain Z+ and Z− PCs, respectively. In both datasets significant differences in simple spike (SS) activity were observed between cortical regions. Specifically, Z− and C1 PCs had higher SS firing rates than Z+ and A2 PCs, respectively. The irregularity of SS firing (as assessed by measures of interspike interval distribution) was greater in Z+ bands in both absolute and relative terms. The results regarding systematic variations in complex spike (CS) activity were less consistent, suggesting that while real differences can exist, they may be sensitive to other factors than the cortical location of the PC. However, differences in the interactions between SSs and CSs, including the post-CS pause in SSs and post-pause modulation of SSs, were also consistently observed between bands. Similar, though less strong trends were observed in the zonal recordings. These systematic variations in spontaneous firing characteristics of PCs between zebrin bands in vivo, raises the possibility that fundamental differences in information encoding exist between cerebellar cortical regions. PMID:25144311

A low-power current-reuse dual-band analog front-end for multi-channel neural signal recording.

PubMed

Sepehrian, H; Gosselin, B

2014-01-01

Thoroughly studying the brain activity of freely moving subjects requires miniature data acquisition systems to measure and wirelessly transmit neural signals in real time. In this application, it is mandatory to simultaneously record the bioelectrical activity of a large number of neurons to gain a better knowledge of brain functions. However, due to limitations in transferring the entire raw data to a remote base station, employing dedicated data reduction techniques to extract the relevant part of neural signals is critical to decrease the amount of data to transfer. In this work, we present a new dual-band neural amplifier to separate the neuronal spike signals (SPK) and the local field potential (LFP) simultaneously in the analog domain, immediately after the pre-amplification stage. By separating these two bands right after the pre-amplification stage, it is possible to process LFP and SPK separately. As a result, the required dynamic range of the entire channel, which is determined by the signal-to-noise ratio of the SPK signal of larger bandwidth, can be relaxed. In this design, a new current-reuse low-power low-noise amplifier and a new dual-band filter that separates SPK and LFP while saving capacitors and pseudo resistors. A four-channel dual-band (SPK, LFP) analog front-end capable of simultaneously separating SPK and LFP is implemented in a TSMC 0.18 μm technology. Simulation results present a total power consumption per channel of 3.1 μw for an input referred noise of 3.28 μV and a NEF for 2.07. The cutoff frequency of the LFP band is fc=280 Hz, and fL=725 Hz and fL=11.2 KHz for SPK, with 36 dB gain for LFP band 46 dB gain for SPK band.

Mercury methylation and reduction potentials in marine water: An improved methodology using 197Hg radiotracer.

PubMed

Koron, Neža; Bratkič, Arne; Ribeiro Guevara, Sergio; Vahčič, Mitja; Horvat, Milena

2012-01-01

A highly sensitive laboratory methodology for simultaneous determination of methylation and reduction of spiked inorganic mercury (Hg(2+)) in marine water labelled with high specific activity radiotracer ((197)Hg prepared from enriched (196)Hg stable isotope) was developed. A conventional extraction protocol for methylmercury (CH(3)Hg(+)) was modified in order to significantly reduce the partitioning of interfering labelled Hg(2+) into the final extract, thus allowing the detection of as little as 0.1% of the Hg(2+) spike transformed to labelled CH(3)Hg(+). The efficiency of the modified CH(3)Hg(+) extraction procedure was assessed by radiolabelled CH(3)Hg(+) spikes corresponding to concentrations of methylmercury between 0.05 and 4ngL(-1). The recoveries were 73.0±6.0% and 77.5±3.9% for marine and MilliQ water, respectively. The reduction potential was assessed by purging and trapping the radiolabelled elemental Hg in a permanganate solution. The method allows detection of the reduction of as little as 0.001% of labelled Hg(2+) spiked to natural waters. To our knowledge, the optimised methodology is among the most sensitive available to study the Hg methylation and reduction potential, therefore allowing experiments to be done at spikes close to natural levels (1-10ngL(-1)). Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

Presynaptic membrane potential affects transmitter release in an identified neuron in Aplysia by modulating the Ca2+ and K+ currents.

PubMed

Shapiro, E; Castellucci, V F; Kandel, E R

1980-01-01

We have examined the relationships between the modulation of transmitter release and of specific ionic currents by membrane potential in the cholinergic interneuron L10 of the abdominal ganglion of Aplysia californica. The presynaptic cell body was voltage-clamped under various pharmacological conditions and transmitter release from the terminals was assayed simultaneously by recording the synaptic potentials in the postsynaptic cell. When cell L10 was voltage-clamped from a holding potential of -60 mV in the presence of tetrodotoxin, graded transmitter release was evoked by depolarizing command pulses in the membrane voltage range (-35 mV to + 10 mV) in which the Ca(2+) current was also increasing. Depolarizing the holding potential of L10 results in increased transmitter output. Two ionic mechanisms contribute to this form of plasticity. First, depolarization inactivates some K(+) channels so that depolarizing command pulses recruit a smaller K(+) current. In unclamped cells the decreased K(+) conductance causes spike-broadening and increased influx of Ca(2+) during each spike. Second, small depolarizations around resting potential (-55 mV to -35 mV) activate a steady-state Ca(2+) current that also contributes to the modulation of transmitter release, because, even with most presynaptic K(+) currents blocked pharmacologically, depolarizing the holding potential still increases transmitter release. In contrast to the steady-state Ca(2+) current, the transient inward Ca(2+) current evoked by depolarizing clamp steps is relatively unchanged from various holding potentials.

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

A 1024-Channel CMOS Microelectrode Array With 26,400 Electrodes for Recording and Stimulation of Electrogenic Cells In Vitro

PubMed Central

Ballini, Marco; Müller, Jan; Livi, Paolo; Chen, Yihui; Frey, Urs; Stettler, Alexander; Shadmani, Amir; Viswam, Vijay; Jones, Ian Lloyd; Jäckel, David; Radivojevic, Milos; Lewandowska, Marta K.; Gong, Wei; Fiscella, Michele; Bakkum, Douglas J.; Heer, Flavio; Hierlemann, Andreas

2017-01-01

To advance our understanding of the functioning of neuronal ensembles, systems are needed to enable simultaneous recording from a large number of individual neurons at high spatiotemporal resolution and good signal-to-noise ratio. Moreover, stimulation capability is highly desirable for investigating, for example, plasticity and learning processes. Here, we present a microelectrode array (MEA) system on a single CMOS die for in vitro recording and stimulation. The system incorporates 26,400 platinum electrodes, fabricated by in-house post-processing, over a large sensing area (3.85 × 2.10 mm2) with sub-cellular spatial resolution (pitch of 17.5 μm). Owing to an area and power efficient implementation, we were able to integrate 1024 readout channels on chip to record extracellular signals from a user-specified selection of electrodes. These channels feature noise values of 2.4 μVrms in the action-potential band (300 Hz–10 kHz) and 5.4 μVrms in the local-field-potential band (1 Hz–300 Hz), and provide programmable gain (up to 78 dB) to accommodate various biological preparations. Amplified and filtered signals are digitized by 10 bit parallel single-slope ADCs at 20 kSamples/s. The system also includes 32 stimulation units, which can elicit neural spikes through either current or voltage pulses. The chip consumes only 75 mW in total, which obviates the need of active cooling even for sensitive cell cultures. PMID:28502989

A fully integrated mixed-signal neural processor for implantable multichannel cortical recording.

PubMed

Sodagar, Amir M; Wise, Kensall D; Najafi, Khalil

2007-06-01

A 64-channel neural processor has been developed for use in an implantable neural recording microsystem. In the Scan Mode, the processor is capable of detecting neural spikes by programmable positive, negative, or window thresholding. Spikes are tagged with their associated channel addresses and formed into 18-bit data words that are sent serially to the external host. In the Monitor Mode, two channels can be selected and viewed at high resolution for studies where the entire signal is of interest. The processor runs from a 3-V supply and a 2-MHz clock, with a channel scan rate of 64 kS/s and an output bit rate of 2 Mbps.

Chronic toxicity of nickel-spiked freshwater sediments: variation in toxicity among eight invertebrate taxa and eight sediments

USGS Publications Warehouse

Besser, John M.; Brumbaugh, William G.; Ingersoll, Christopher G.; Ivey, Chris D.; Kunz, James L.; Kemble, Nile E.; Schlekat, Christian E.; Garman, Emily R.

2013-01-01

This study evaluated the chronic toxicity of Ni-spiked freshwater sediments to benthic invertebrates. A 2-step spiking procedure (spiking and sediment dilution) and a 2-stage equilibration period (10 wk anaerobic and 1 wk aerobic) were used to spike 8 freshwater sediments with wide ranges of acid-volatile sulfide (AVS; 0.94–38 µmol/g) and total organic carbon (TOC; 0.42–10%). Chronic sediment toxicity tests were conducted with 8 invertebrates (Hyalella azteca, Gammarus pseudolimnaeus, Chironomus riparius, Chironomus dilutus, Hexagenia sp., Lumbriculus variegatus, Tubifex tubifex, and Lampsilis siliquoidea) in 2 spiked sediments. Nickel toxicity thresholds estimated from species-sensitivity distributions were 97 µg/g and 752 µg/g (total recoverable Ni; dry wt basis) for sediments with low and high concentrations of AVS and TOC, respectively. Sensitive species were tested with 6 additional sediments. The 20% effect concentrations (EC20s) for Hyalella and Gammarus, but not Hexagenia, were consistent with US Environmental Protection Agency benchmarks based on Ni in porewater and in simultaneously extracted metals (SEM) normalized to AVS and TOC. For Hexagenia, sediment EC20s increased at less than an equimolar basis with increased AVS, and toxicity occurred in several sediments with Ni concentrations in SEM less than AVS. The authors hypothesize that circulation of oxygenated water by Hexagenia led to oxidation of AVS in burrows, creating microenvironments with high Ni exposure. Despite these unexpected results, a strong relationship between Hexagenia EC20s and AVS could provide a basis for conservative site-specific sediment quality guidelines for Ni.

Spatial representation and cognitive modulation of response variability in the lateral intraparietal area priority map.

PubMed

Falkner, Annegret L; Goldberg, Michael E; Krishna, B Suresh

2013-10-09

The lateral intraparietal area (LIP) in the macaque contains a priority-based representation of the visual scene. We previously showed that the mean spike rate of LIP neurons is strongly influenced by spatially wide-ranging surround suppression in a manner that effectively sharpens the priority map. Reducing response variability can also improve the precision of LIP's priority map. We show that when a monkey plans a visually guided delayed saccade with an intervening distractor, variability (measured by the Fano factor) decreases both for neurons representing the saccade goal and for neurons representing the broad spatial surround. The reduction in Fano factor is maximal for neurons representing the saccade goal and steadily decreases for neurons representing more distant locations. LIP Fano factor changes are behaviorally significant: increasing expected reward leads to lower variability for the LIP representation of both the target and distractor locations, and trials with shorter latency saccades are associated with lower Fano factors in neurons representing the surround. Thus, the LIP Fano factor reflects both stimulus and behavioral engagement. Quantitative modeling shows that the interaction between mean spike count and target-receptive field (RF) distance in the surround during the predistractor epoch is multiplicative: the Fano factor increases more steeply with mean spike count further away from the RF. A negative-binomial model for LIP spike counts captures these findings quantitatively, suggests underlying mechanisms based on trial-by-trial variations in mean spike rate or burst-firing patterns, and potentially provides a principled framework to account simultaneously for the previously observed unsystematic relationships between spike rate and variability in different brain areas.

Chronic toxicity of nickel-spiked freshwater sediments: variation in toxicity among eight invertebrate taxa and eight sediments.

PubMed

Besser, John M; Brumbaugh, William G; Ingersoll, Christopher G; Ivey, Chris D; Kunz, James L; Kemble, Nile E; Schlekat, Christian E; Garman, Emily Rogevich

2013-11-01

This study evaluated the chronic toxicity of Ni-spiked freshwater sediments to benthic invertebrates. A 2-step spiking procedure (spiking and sediment dilution) and a 2-stage equilibration period (10 wk anaerobic and 1 wk aerobic) were used to spike 8 freshwater sediments with wide ranges of acid-volatile sulfide (AVS; 0.94-38 µmol/g) and total organic carbon (TOC; 0.42-10%). Chronic sediment toxicity tests were conducted with 8 invertebrates (Hyalella azteca, Gammarus pseudolimnaeus, Chironomus riparius, Chironomus dilutus, Hexagenia sp., Lumbriculus variegatus, Tubifex tubifex, and Lampsilis siliquoidea) in 2 spiked sediments. Nickel toxicity thresholds estimated from species-sensitivity distributions were 97 µg/g and 752 µg/g (total recoverable Ni; dry wt basis) for sediments with low and high concentrations of AVS and TOC, respectively. Sensitive species were tested with 6 additional sediments. The 20% effect concentrations (EC20s) for Hyalella and Gammarus, but not Hexagenia, were consistent with US Environmental Protection Agency benchmarks based on Ni in porewater and in simultaneously extracted metals (SEM) normalized to AVS and TOC. For Hexagenia, sediment EC20s increased at less than an equimolar basis with increased AVS, and toxicity occurred in several sediments with Ni concentrations in SEM less than AVS. The authors hypothesize that circulation of oxygenated water by Hexagenia led to oxidation of AVS in burrows, creating microenvironments with high Ni exposure. Despite these unexpected results, a strong relationship between Hexagenia EC20s and AVS could provide a basis for conservative site-specific sediment quality guidelines for Ni. © 2013 SETAC.

Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively.

PubMed

Shimamoto, Shoichi; Waldman, Zachary J; Orosz, Iren; Song, Inkyung; Bragin, Anatol; Fried, Itzhak; Engel, Jerome; Staba, Richard; Sharan, Ashwini; Wu, Chengyuan; Sperling, Michael R; Weiss, Shennan A

2018-01-01

To develop and validate a detector that identifies ripple (80-200 Hz) events in intracranial EEG (iEEG) recordings in a referential montage and utilizes independent component analysis (ICA) to eliminate or reduce high-frequency artifact contamination. Also, investigate the correspondence of detected ripples and the seizure onset zone (SOZ). iEEG recordings from 16 patients were first band-pass filtered (80-600 Hz) and Infomax ICA was next applied to derive the first independent component (IC1). IC1 was subsequently pruned, and an artifact index was derived to reduce the identification of high-frequency events introduced by the reference electrode signal. A Hilbert detector identified ripple events in the processed iEEG recordings using amplitude and duration criteria. The identified ripple events were further classified and characterized as true or false ripple on spikes, or ripples on oscillations by utilizing a topographical analysis to their time-frequency plot, and confirmed by visual inspection. The signal to noise ratio was improved by pruning IC1. The precision of the detector for ripple events was 91.27 ± 4.3%, and the sensitivity of the detector was 79.4 ± 3.0% (N = 16 patients, 5842 ripple events). The sensitivity and precision of the detector was equivalent in iEEG recordings obtained during sleep or intra-operatively. Across all the patients, true ripple on spike rates and also the rates of false ripple on spikes, that were generated due to filter ringing, classified the seizure onset zone (SOZ) with an area under the receiver operating curve (AUROC) of >76%. The magnitude and spectral content of true ripple on spikes generated in the SOZ was distinct as compared with the ripples generated in the NSOZ (p < .001). Utilizing ICA to analyze iEEG recordings in referential montage provides many benefits to the study of high-frequency oscillations. The ripple rates and properties defined using this approach may accurately delineate the seizure onset zone. Strategies to improve the spatial resolution of intracranial EEG and reduce artifact can help improve the clinical utility of HFO biomarkers. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

In vivo performance of a microelectrode neural probe with integrated drug delivery

PubMed Central

Rohatgi, Pratik; Langhals, Nicholas B.; Kipke, Daryl R.; Patil, Parag G.

2014-01-01

Object The availability of sophisticated neural probes is a key prerequisite in the development of future brain machine interfaces (BMI). In this study, we developed and validated a neural probe design capable of simultaneous drug delivery and electrophysiology recordings in vivo. Focal drug delivery has promise to dramatically extend the recording lives of neural probes, a limiting factor to clinical adoption of BMI technology. Methods To form the multifunctional neural probe, we affixed a 16-channel microfabricated silicon electrode array to a fused silica catheter. Three experiments were conducted to characterize the performance of the device. Experiment 1 examines cellular damage from probe insertion and the drug distribution in tissue. Experiment 2 measures the effects of saline infusions delivered through the probe on concurrent electrophysiology. Experiment 3 demonstrates that a physiologically relevant amount of drug can be delivered in a controlled fashion. For these experiments, Hoechst and propidium iodide were used to assess insertion trauma and the tissue distribution of the infusate. Artificial cerebral spinal fluid and tetrodotoxin were injected to determine the efficacy of drug delivery. Results The newly developed multifunctional neural probes were successfully inserted into rat cortex and were able to deliver fluids and drugs that resulted in the expected electrophysiological and histological responses. The damage from insertion of the device into brain tissue was substantially less than the volume of drug dispersion in tissue. Electrophysiological activity, including both individual spikes as well as local field potentials, was successfully recorded with this device during real-time drug delivery. No significant changes were seen in response to delivery of artificial cerebral spinal fluid as a control experiment, whereas delivery of tetrodotoxin produced the expected result of suppressing all spiking activity in the vicinity of the catheter outlet. Conclusions Multifunctional neural probes such as the ones developed and validated within this study have great potential to help further understand the design space and criteria for the next generation of neural probe technology. By incorporating integrated drug delivery functionality into the probes, new treatment options for neurological disorders and regenerative neural interfaces utilizing localized and feedback controlled delivery of drugs can be realized in the near future. PMID:19569896

Thermal and Electrical Conductivity Probe for Phoenix Mars Lander

NASA Technical Reports Server (NTRS)

2007-01-01

NASA's Phoenix Mars Lander will assess how heat and electricity move through Martian soil from one spike or needle to another of a four-spike electronic fork that will be pushed into the soil at different stages of digging by the lander's Robotic Arm.

The four-spike tool, called the thermal and electrical conductivity probe, is in the middle-right of this photo, mounted near the end of the arm near the lander's scoop (upper left).

In one type of experiment with this tool, a pulse of heat will be put into one spike, and the rate at which the temperature rises on the nearby spike will be recorded, along with the rate at which the heated spike cools. A little bit of ice can make a big difference in how well soil conducts heat. Similarly, soil's electrical conductivity -- also tested with this tool -- is a sensitive

indicator of moisture in the soil. This device adapts technology used in soil-moisture gauges for irrigation-control systems. The conductivity probe has an additional role besides soil analysis. It will serve as a hunidity sensor when held in the air.

In Vivo Neural Recording and Electrochemical Performance of Microelectrode Arrays Modified by Rough-Surfaced AuPt Alloy Nanoparticles with Nanoporosity

PubMed Central

Zhao, Zongya; Gong, Ruxue; Zheng, Liang; Wang, Jue

2016-01-01

In order to reduce the impedance and improve in vivo neural recording performance of our developed Michigan type silicon electrodes, rough-surfaced AuPt alloy nanoparticles with nanoporosity were deposited on gold microelectrode sites through electro-co-deposition of Au-Pt-Cu alloy nanoparticles, followed by chemical dealloying Cu. The AuPt alloy nanoparticles modified gold microelectrode sites were characterized by scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and in vivo neural recording experiment. The SEM images showed that the prepared AuPt alloy nanoparticles exhibited cauliflower-like shapes and possessed very rough surfaces with many different sizes of pores. Average impedance of rough-surfaced AuPt alloy nanoparticles modified sites was 0.23 MΩ at 1 kHz, which was only 4.7% of that of bare gold microelectrode sites (4.9 MΩ), and corresponding in vitro background noise in the range of 1 Hz to 7500 Hz decreased to 7.5 μVrms from 34.1 μVrms at bare gold microelectrode sites. Spontaneous spike signal recording was used to evaluate in vivo neural recording performance of modified microelectrode sites, and results showed that rough-surfaced AuPt alloy nanoparticles modified microelectrode sites exhibited higher average spike signal-to-noise ratio (SNR) of 4.8 in lateral globus pallidus (GPe) due to lower background noise compared to control microelectrodes. Electro-co-deposition of Au-Pt-Cu alloy nanoparticles combined with chemical dealloying Cu was a convenient way for increasing the effective surface area of microelectrode sites, which could reduce electrode impedance and improve the quality of in vivo spike signal recording. PMID:27827893

Bomb-produced radiocarbon in the western tropical Pacific Ocean: Guam coral reveals operation-specific signals from the Pacific Proving Grounds

NASA Astrophysics Data System (ADS)

Andrews, Allen H.; Asami, Ryuji; Iryu, Yasufumi; Kobayashi, Donald R.; Camacho, Frank

2016-08-01

High-resolution radiocarbon (14C) analyses on a coral core extracted from Guam, a western tropical Pacific island, revealed a series of early bomb-produced 14C spikes. The typical marine bomb 14C signal—phase lagged and attenuated relative to atmospheric records—is present in the coral and is consistent with other regional coral records. However, 14C levels well above what can be attributed to air-sea diffusion alone punctuate this pattern. This anomaly was observed in other Indo-Pacific coral records, but the Guam record is unmatched in magnitude and temporal resolution. The Guam coral Δ14C record provided three spikes in 1954-1955, 1956-1957, and 1958-1959 that are superimposed on a normal 14C record. Relative to mean prebomb levels, the first peak rises an incredible ˜700‰ and remained elevated for ˜1.2 years. A follow up assay with finer resolution increased the peak by ˜300‰. Subsequent spikes were less intense with a rise of ˜35 and ˜70‰. Each can be linked to thermonuclear testing in the Pacific Proving Grounds at Bikini and Enewetak atolls in Operations Castle (1954), Redwing (1956), and Hardtack I (1958). These 14C signals can be explained by vaporization of coral reef material in the nuclear fireball, coupled with neutron activation of atmospheric nitrogen (14C production), and subsequent absorption of 14CO2 to form particulate carbonates of close-in fallout. The lag time in reaching Guam and other coral records abroad was tied to ocean surface currents and modeling provided validation of 14C arrival observations.

Green Pharmaceutical Analysis of Drugs Coformulated with Highly Different Concentrations Using Spiking and Manipulation of Their Ratio Spectra.

PubMed

Ayoub, Bassam M

2017-07-01

Introducing green analysis to pharmaceutical products is considered a significant approach to preserving the environment. This method can be an environmentally friendly alternative to the existing methods, accompanied by a validated automated procedure for the analysis of a drug with the lowest possible number of samples. Different simple spectrophotometric methods were developed for the simultaneous determination of empagliflozin (EG) and metformin (MT) by manipulating their ratio spectra in their application on a recently approved pharmaceutical combination, Synjardy tablets. A spiking technique was used to increase the concentration of EG in samples prepared from the tablets to allow for the simultaneous determination of EG with MT without prior separation. Validation parameters according to International Conference on Harmonization guidelines were acceptable over a concentration range of 2-12 μg/mL for both drugs using derivative ratio and ratio subtraction coupled with extended ratio subtraction. The optimized methods were compared using one-way analysis of variance and proved to be suitable as ecofriendly approaches for industrial QC laboratories.

A single extraction and HPLC procedure for simultaneous analysis of phytosterols, tocopherols and lutein in soybeans.

PubMed

Slavin, Margaret; Yu, Liangli Lucy

2012-12-15

A saponification/extraction procedure and high performance liquid chromatography (HPLC) analysis method were developed and validated for simultaneous analysis of phytosterols, tocopherols and lutein (a carotenoid) in soybeans. Separation was achieved on a phenyl column with a ternary, isocratic solvent system of acetonitrile, methanol and water (48:22.5:29.5, v/v/v). Evaporative light scattering detection (ELSD) was used to quantify β-sitosterol, stigmasterol, campesterol, and α-, δ- and γ-tocopherols, while lutein was quantified with visible light absorption at 450 nm. Peak identification was verified by retention times and spikes with external standards. Standard curves were constructed (R(2)>0.99) to allow for sample quantification. Recovery of the saponification and extraction was demonstrated via analysis of spiked samples. Also, the accuracy of results of four soybeans using the described saponification and HPLC analytical method was validated against existing methods. This method offers a more efficient alternative to individual methods for quantifying lutein, tocopherols and sterols in soybeans. Copyright © 2012 Elsevier Ltd. 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.

Membrane Potentials of the Lobster Giant Axon Obtained by Use of the Sucrose-Gap Technique

PubMed Central

Julian, Fred J.; Moore, John W.; Goldman, David E.

1962-01-01

A method similar to the sucrose-gap technique introduced be Stäpfli is described for measuring membrane potential and current in singly lobster giant axons (diameter about 100 micra). The isotonic sucrose solution used to perfuse the gaps raises the external leakage resistance so that the recorded potential is only about 5 per cent less than the actual membrane potential. However, the resting potential of an axon in the sucrose-gap arrangement is increased 20 to 60 mv over that recorded by a conventional micropipette electrode when the entire axon is bathed in sea water. A complete explanation for this effect has not been discovered. The relation between resting potential and external potassium and sodium ion concentrations shows that potassium carries most of the current in a depolarized axon in the sucrose-gap arrangement, but that near the resting potential other ions make significant contributions. Lowering the external chloride concentration decreases the resting potential. Varying the concentration of the sucrose solution has little effect. A study of the impedance changes associated with the action potential shows that the membrane resistance decreases to a minimum at the peak of the spike and returns to near its initial value before repolarization is complete (a normal lobster giant axon action potential does not have an undershoot). Action potentials recorded simultaneously by the sucrose-gap technique and by micropipette electrodes are practically superposable. PMID:14452759

Linear and quadratic models of point process systems: contributions of patterned input to output.

PubMed

Lindsay, K A; Rosenberg, J R

2012-08-01

In the 1880's Volterra characterised a nonlinear system using a functional series connecting continuous input and continuous output. Norbert Wiener, in the 1940's, circumvented problems associated with the application of Volterra series to physical problems by deriving from it a new series of terms that are mutually uncorrelated with respect to Gaussian processes. Subsequently, Brillinger, in the 1970's, introduced a point-process analogue of Volterra's series connecting point-process inputs to the instantaneous rate of point-process output. We derive here a new series from this analogue in which its terms are mutually uncorrelated with respect to Poisson processes. This new series expresses how patterned input in a spike train, represented by third-order cross-cumulants, is converted into the instantaneous rate of an output point-process. Given experimental records of suitable duration, the contribution of arbitrary patterned input to an output process can, in principle, be determined. Solutions for linear and quadratic point-process models with one and two inputs and a single output are investigated. Our theoretical results are applied to isolated muscle spindle data in which the spike trains from the primary and secondary endings from the same muscle spindle are recorded in response to stimulation of one and then two static fusimotor axons in the absence and presence of a random length change imposed on the parent muscle. For a fixed mean rate of input spikes, the analysis of the experimental data makes explicit which patterns of two input spikes contribute to an output spike. Copyright © 2012 Elsevier Ltd. All rights reserved.

A comparison of take-off dynamics during three different spikes, block and counter-movement jump in female volleyball players.

PubMed

Kabacinski, Jaroslae; Dworak, Lecholslaw B; Murawa, Michal; Ostarello, John; Rzepnicka, Agata; Maczynski, Jacek

2016-12-01

The purpose of the study was to compare the take-off dynamics in counter-movement jump (CMJ), volleyball block and spikes. Twelve professional female players, representing the highest volleyball league in Poland, participated in the laboratory tests. A force platform was used to record ground reaction force (GRF) during take-off phase in CMJ test, block from a run-up and spikes: front row attack, slide attack, back row attack. Vertical (v) GRF (peak: Rmax and integral mean: ), impulse of vGRF (J) and mechanical power (peak: Pmax and integral mean:

) were analyzed. Significant differences (P<0.05) of values of the dynamic parameters (Rmax, , J, Pmax, and

) were found between CMJ, block from a run-up and three different technique spikes. The highest values were recorded during take-off in the back row attack: peak vGRF (2.93±0.05 BW), integral mean vGRF (1.90±0.08 BW), impulse of vGRF (354±40 Ns), peak power (5320±918 W) and integral mean power (3604±683 W). Peak power (2608±217 W) and integral mean power (1417±94 W) were determined in CMJ test to evaluate the force-velocity capabilities of the players. In terms of GRF and the mechanical power, high level of dynamics in take-off influences positively the jumping height and significantly increases the effectiveness of attacks during spike of the ball over the block of the opponent.

Cortical Plasticity Induced by Spike-Triggered Microstimulation in Primate Somatosensory Cortex

PubMed Central

Song, Weiguo; Kerr, Cliff C.; Lytton, William W.; Francis, Joseph T.

2013-01-01

Electrical stimulation of the nervous system for therapeutic purposes, such as deep brain stimulation in the treatment of Parkinson’s disease, has been used for decades. Recently, increased attention has focused on using microstimulation to restore functions as diverse as somatosensation and memory. However, how microstimulation changes the neural substrate is still not fully understood. Microstimulation may cause cortical changes that could either compete with or complement natural neural processes, and could result in neuroplastic changes rendering the region dysfunctional or even epileptic. As part of our efforts to produce neuroprosthetic devices and to further study the effects of microstimulation on the cortex, we stimulated and recorded from microelectrode arrays in the hand area of the primary somatosensory cortex (area 1) in two awake macaque monkeys. We applied a simple neuroprosthetic microstimulation protocol to a pair of electrodes in the area 1 array, using either random pulses or pulses time-locked to the recorded spiking activity of a reference neuron. This setup was replicated using a computer model of the thalamocortical system, which consisted of 1980 spiking neurons distributed among six cortical layers and two thalamic nuclei. Experimentally, we found that spike-triggered microstimulation induced cortical plasticity, as shown by increased unit-pair mutual information, while random microstimulation did not. In addition, there was an increased response to touch following spike-triggered microstimulation, along with decreased neural variability. The computer model successfully reproduced both qualitative and quantitative aspects of the experimental findings. The physiological findings of this study suggest that even simple microstimulation protocols can be used to increase somatosensory information flow. PMID:23472086

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

Mental arithmetic leads to multiple discrete changes from baseline in the firing patterns of human thalamic neurons.

PubMed

Kim, J H; Ohara, S; Lenz, F A

2009-04-01

Primate thalamic action potential bursts associated with low-threshold spikes (LTS) occur during waking sensory and motor activity. We now test the hypothesis that different firing and LTS burst characteristics occur during quiet wakefulness (spontaneous condition) versus mental arithmetic (counting condition). This hypothesis was tested by thalamic recordings during the surgical treatment of tremor. Across all neurons and epochs, preburst interspike intervals (ISIs) were bimodal at median values, consistent with the duration of type A and type B gamma-aminobutyric acid inhibitory postsynaptic potentials. Neuronal spike trains (117 neurons) were categorized by joint ISI distributions into those firing as LTS bursts (G, grouped), firing as single spikes (NG, nongrouped), or firing as single spikes with sporadic LTS bursting (I, intermediate). During the spontaneous condition (46 neurons) only I spike trains changed category. Overall, burst rates (BRs) were lower and firing rates (FRs) were higher during the counting versus the spontaneous condition. Spike trains in the G category sometimes changed to I and NG categories at the transition from the spontaneous to the counting condition, whereas those in the I category often changed to NG. Among spike trains that did not change category by condition, G spike trains had lower BRs during counting, whereas NG spike trains had higher FRs. BRs were significantly greater than zero for G and I categories during wakefulness (both conditions). The changes between the spontaneous and counting conditions are most pronounced for the I category, which may be a transitional firing pattern between the bursting (G) and relay modes of thalamic firing (NG).

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.

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

Performance evaluation of PCA-based spike sorting algorithms.

PubMed

Adamos, Dimitrios A; Kosmidis, Efstratios K; Theophilidis, George

2008-09-01

Deciphering the electrical activity of individual neurons from multi-unit noisy recordings is critical for understanding complex neural systems. A widely used spike sorting algorithm is being evaluated for single-electrode nerve trunk recordings. The algorithm is based on principal component analysis (PCA) for spike feature extraction. In the neuroscience literature it is generally assumed that the use of the first two or most commonly three principal components is sufficient. We estimate the optimum PCA-based feature space by evaluating the algorithm's performance on simulated series of action potentials. A number of modifications are made to the open source nev2lkit software to enable systematic investigation of the parameter space. We introduce a new metric to define clustering error considering over-clustering more favorable than under-clustering as proposed by experimentalists for our data. Both the program patch and the metric are available online. Correlated and white Gaussian noise processes are superimposed to account for biological and artificial jitter in the recordings. We report that the employment of more than three principal components is in general beneficial for all noise cases considered. Finally, we apply our results to experimental data and verify that the sorting process with four principal components is in agreement with a panel of electrophysiology experts.

NeuroCa: integrated framework for systematic analysis of spatiotemporal neuronal activity patterns from large-scale optical recording data

PubMed Central

Jang, Min Jee; Nam, Yoonkey

2015-01-01

Abstract. Optical recording facilitates monitoring the activity of a large neural network at the cellular scale, but the analysis and interpretation of the collected data remain challenging. Here, we present a MATLAB-based toolbox, named NeuroCa, for the automated processing and quantitative analysis of large-scale calcium imaging data. Our tool includes several computational algorithms to extract the calcium spike trains of individual neurons from the calcium imaging data in an automatic fashion. Two algorithms were developed to decompose the imaging data into the activity of individual cells and subsequently detect calcium spikes from each neuronal signal. Applying our method to dense networks in dissociated cultures, we were able to obtain the calcium spike trains of ∼1000 neurons in a few minutes. Further analyses using these data permitted the quantification of neuronal responses to chemical stimuli as well as functional mapping of spatiotemporal patterns in neuronal firing within the spontaneous, synchronous activity of a large network. These results demonstrate that our method not only automates time-consuming, labor-intensive tasks in the analysis of neural data obtained using optical recording techniques but also provides a systematic way to visualize and quantify the collective dynamics of a network in terms of its cellular elements. PMID:26229973

Simultaneous extraction of polycyclic aromatic hydrocarbons through the complete dissolution of solid biological samples in sodium hydroxide/urea/thiourea aqueous solution.

PubMed

Mohammad, Sedigheh Ale; Ghanemi, Kamal; Larki, Arash

2016-12-09

In order to precisely and simultaneously extract polycyclic aromatic hydrocarbons (PAHs) for measurement using a high performance liquid chromatography-fluorescence detector (HPLC-FL), a novel sample preparation method was developed. This method is based on the complete and fast dissolution of biological samples in a new non-alcoholic alkaline medium. A solution composed of NaOH/urea/thiourea at an optimized ratio was used for complete dissolution of approximately 0.25g dried fish samples within 20min. The proposed method was conducted at 10°C and under atmospheric pressure to obtain a stable and highly homogeneous solution, without the need for microwaves or any other apparatus. This process operates at considerably lower temperature than conventional methods and provides an opportunity to simultaneously extract the target analytes from their matrices by adding the extracting solvent in the initial steps of the dissolution; this process greatly reduced the time of analysis and the loss of analytes via vaporization. Several key parameters were identified and their effects on precision and extraction recoveries were investigated. Linearity over a calibration range of 1.0-100 and 2.5-100ngg -1 was achieved, with high coefficients of determination (r 2 ) ranging between 0.9987 and 0.9998. Based on relative standard deviations (n=5), the intra-day and inter-day precisions of the spiked PAHs were found to be better than 3.1% and 3.2%, respectively, at a concentration level of 25ngg -1 . The recoveries of PAH from spiked marine fish tissues and shrimp samples were in the range of 90.6%-100.4%. The spiked samples were also treated with the alcoholic alkaline and Soxhlet extraction methods in order to provide a comparison. Copyright © 2016 Elsevier B.V. All rights reserved.

Membrane potential dynamics of grid cells

PubMed Central

Domnisoru, Cristina; Kinkhabwala, Amina A.; Tank, David W.

2014-01-01

During navigation, grid cells increase their spike rates in firing fields arranged on a strikingly regular triangular lattice, while their spike timing is often modulated by theta oscillations. Oscillatory interference models of grid cells predict theta amplitude modulations of membrane potential during firing field traversals, while competing attractor network models predict slow depolarizing ramps. Here, using in-vivo whole-cell recordings, we tested these models by directly measuring grid cell intracellular potentials in mice running along linear tracks in virtual reality. Grid cells had large and reproducible ramps of membrane potential depolarization that were the characteristic signature tightly correlated with firing fields. Grid cells also exhibited intracellular theta oscillations that influenced their spike timing. However, the properties of theta amplitude modulations were not consistent with the view that they determine firing field locations. Our results support cellular and network mechanisms in which grid fields are produced by slow ramps, as in attractor models, while theta oscillations control spike timing. PMID:23395984

Spike shape analysis of electromyography for parkinsonian tremor evaluation.

PubMed

Marusiak, Jarosław; Andrzejewska, Renata; Świercz, Dominika; Kisiel-Sajewicz, Katarzyna; Jaskólska, Anna; Jaskólski, Artur

2015-12-01

Standard electromyography (EMG) parameters have limited utility for evaluation of Parkinson disease (PD) tremor. Spike shape analysis (SSA) EMG parameters are more sensitive than standard EMG parameters for studying motor control mechanisms in healthy subjects. SSA of EMG has not been used to assess parkinsonian tremor. This study assessed the utility of SSA and standard time and frequency analysis for electromyographic evaluation of PD-related resting tremor. We analyzed 1-s periods of EMG recordings to detect nontremor and tremor signals in relaxed biceps brachii muscle of seven mild to moderate PD patients. SSA revealed higher mean spike amplitude, duration, and slope and lower mean spike frequency in tremor signals than in nontremor signals. Standard EMG parameters (root mean square, median, and mean frequency) did not show differences between the tremor and nontremor signals. SSA of EMG data is a sensitive method for parkinsonian tremor evaluation. © 2015 Wiley Periodicals, Inc.

State-space receptive fields of semicircular canal afferent neurons in the bullfrog

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

2001-01-01

Receptive fields are commonly used to describe spatial characteristics of sensory neuron responses. They can be extended to characterize temporal or dynamical aspects by mapping neural responses in dynamical state spaces. The state-space receptive field of a neuron is the probability distribution of the dynamical state of the stimulus-generating system conditioned upon the occurrence of a spike. We have computed state-space receptive fields for semicircular canal afferent neurons in the bullfrog (Rana catesbeiana). We recorded spike times during broad-band Gaussian noise rotational velocity stimuli, computed the frequency distribution of head states at spike times, and normalized these to obtain conditional pdfs for the state. These state-space receptive fields quantify what the brain can deduce about the dynamical state of the head when a single spike arrives from the periphery. c2001 Elsevier Science B.V. All rights reserved.

Development and Validation of a Spike Detection and Classification Algorithm Aimed at Implementation on Hardware Devices

PubMed Central

Biffi, E.; Ghezzi, D.; Pedrocchi, A.; Ferrigno, G.

2010-01-01

Neurons cultured in vitro on MicroElectrode Array (MEA) devices connect to each other, forming a network. To study electrophysiological activity and long term plasticity effects, long period recording and spike sorter methods are needed. Therefore, on-line and real time analysis, optimization of memory use and data transmission rate improvement become necessary. We developed an algorithm for amplitude-threshold spikes detection, whose performances were verified with (a) statistical analysis on both simulated and real signal and (b) Big O Notation. Moreover, we developed a PCA-hierarchical classifier, evaluated on simulated and real signal. Finally we proposed a spike detection hardware design on FPGA, whose feasibility was verified in terms of CLBs number, memory occupation and temporal requirements; once realized, it will be able to execute on-line detection and real time waveform analysis, reducing data storage problems. PMID:20300592

Changes in complex spike activity during classical conditioning

PubMed Central

Rasmussen, Anders; Jirenhed, Dan-Anders; Wetmore, Daniel Z.; Hesslow, Germund

2014-01-01

The cerebellar cortex is necessary for adaptively timed conditioned responses (CRs) in eyeblink conditioning. During conditioning, Purkinje cells acquire pause responses or “Purkinje cell CRs” to the conditioned stimuli (CS), resulting in disinhibition of the cerebellar nuclei (CN), allowing them to activate motor nuclei that control eyeblinks. This disinhibition also causes inhibition of the inferior olive (IO), via the nucleo-olivary pathway (N-O). Activation of the IO, which relays the unconditional stimulus (US) to the cortex, elicits characteristic complex spikes in Purkinje cells. Although Purkinje cell activity, as well as stimulation of the CN, is known to influence IO activity, much remains to be learned about the way that learned changes in simple spike firing affects the IO. In the present study, we analyzed changes in simple and complex spike firing, in extracellular Purkinje cell records, from the C3 zone, in decerebrate ferrets undergoing training in a conditioning paradigm. In agreement with the N-O feedback hypothesis, acquisition resulted in a gradual decrease in complex spike activity during the conditioned stimulus, with a delay that is consistent with the long N-O latency. Also supporting the feedback hypothesis, training with a short interstimulus interval (ISI), which does not lead to acquisition of a Purkinje cell CR, did not cause a suppression of complex spike activity. In contrast, observations that extinction did not lead to a recovery in complex spike activity and the irregular patterns of simple and complex spike activity after the conditioned stimulus are less conclusive. PMID:25140129

The influence of single bursts versus single spikes at excitatory dendrodendritic synapses.

PubMed

Masurkar, Arjun V; Chen, Wei R

2012-02-01

The synchronization of neuronal activity is thought to enhance information processing. There is much evidence supporting rhythmically bursting external tufted cells (ETCs) of the rodent olfactory bulb glomeruli coordinating the activation of glomerular interneurons and mitral cells via dendrodendritic excitation. However, as bursting has variable significance at axodendritic cortical synapses, it is not clear if ETC bursting imparts a specific functional advantage over the preliminary spike in dendrodendritic synaptic networks. To answer this question, we investigated the influence of single ETC bursts and spikes with the in vitro rat olfactory bulb preparation at different levels of processing, via calcium imaging of presynaptic ETC dendrites, dual electrical recording of ETC -interneuron synaptic pairs, and multicellular calcium imaging of ETC-induced population activity. Our findings supported single ETC bursts, versus single spikes, driving robust presynaptic calcium signaling, which in turn was associated with profound extension of the initial monosynaptic spike-driven dendrodendritic excitatory postsynaptic potential. This extension could be driven by either the spike-dependent or spike-independent components of the burst. At the population level, burst-induced excitation was more widespread and reliable compared with single spikes. This further supports the ETC network, in part due to a functional advantage of bursting at excitatory dendrodendritic synapses, coordinating synchronous activity at behaviorally relevant frequencies related to odor processing in vivo. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

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.

Polarity of cortical electrical stimulation differentially affects neuronal activity of deep and superficial layers of rat motor cortex.

PubMed

Yazdan-Shahmorad, Azadeh; Kipke, Daryl R; Lehmkuhle, Mark J

2011-10-01

Cortical electrical stimulation (CES) techniques are practical tools in neurorehabilitation that are currently being used to test models of functional recovery after neurologic injury. However, the mechanisms by which CES has therapeutic effects, are not fully understood. In this study, we investigated the effects of CES on unit activity of different neuronal elements in layers of rat primary motor cortex after the offset of stimulation. We evaluated the effects of monopolar CES pulse polarity (anodic-first versus cathodic-first) using various stimulation frequencies and amplitudes on unit activity after stimulation. A penetrating single shank silicon microelectrode array enabled us to span the entirety of six layer motor cortex allowing simultaneous electrophysiologic recordings from different depths after monopolar CES. Neural spiking activity before the onset and after the offset of CES was modeled using point processes fit to capture neural spiking dynamics as a function of extrinsic stimuli based on generalized linear model methods. We found that neurons in lower layers have a higher probability of being excited after anodic CES. Conversely, neurons located in upper cortical layers have a higher probability of being excited after cathodic stimulation. The opposing effects observed following anodic versus cathodic stimulation in upper and lower layers were frequency- and amplitude-dependent. The data demonstrates that the poststimulus changes in neural activity after manipulation of CES parameters changes according to the location (depth) of the recorded units in rat primary motor cortex. The most effective pulse polarity for eliciting action potentials after stimulation in lower layers was not as effective in upper layers. Likewise, lower amplitudes and frequencies of CES were more effective than higher amplitudes and frequencies for eliciting action potentials. These results have important implications in the context of maximizing efficacy of CES for neurorehabilitation and neuroprosthetic applications. Copyright © 2011 Elsevier Inc. All rights reserved.

A two-channel action-potential generator for testing neurophysiologic data acquisition/analysis systems.

PubMed

Lisiecki, R S; Voigt, H F

1995-08-01

A 2-channel action-potential generator system was designed for use in testing neurophysiologic data acquisition/analysis systems. The system consists of a personal computer controlling an external hardware unit. This system is capable of generating 2 channels of simulated action potential (AP) waveshapes. The AP waveforms are generated from the linear combination of 2 principal-component template functions. Each channel generates randomly occurring APs with a specified rate ranging from 1 to 200 events per second. The 2 trains may be independent of one another or the second channel may be made to be excited or inhibited by the events from the first channel with user-specified probabilities. A third internal channel may be made to excite or inhibit events in both of the 2 output channels with user-specified rate parameters and probabilities. The system produces voltage waveforms that may be used to test neurophysiologic data acquisition systems for recording from 2 spike trains simultaneously and for testing multispike-train analysis (e.g., cross-correlation) software.

Complementary theta resonance filtering by two spatially segregated mechanisms in CA1 hippocampal pyramidal neurons.

PubMed

Hu, Hua; Vervaeke, Koen; Graham, Lyle J; Storm, Johan F

2009-11-18

Synaptic input to a neuron may undergo various filtering steps, both locally and during transmission to the soma. Using simultaneous whole-cell recordings from soma and apical dendrites from rat CA1 hippocampal pyramidal cells, and biophysically detailed modeling, we found two complementary resonance (bandpass) filters of subthreshold voltage signals. Both filters favor signals in the theta (3-12 Hz) frequency range, but have opposite location, direction, and voltage dependencies: (1) dendritic H-resonance, caused by h/HCN-channels, filters signals propagating from soma to dendrite when the membrane potential is close to rest; and (2) somatic M-resonance, caused by M/Kv7/KCNQ and persistent Na(+) (NaP) channels, filters signals propagating from dendrite to soma when the membrane potential approaches spike threshold. Hippocampal pyramidal cells participate in theta network oscillations during behavior, and we suggest that that these dual, polarized theta resonance mechanisms may convey voltage-dependent tuning of theta-mediated neural coding in the entorhinal/hippocampal system during locomotion, spatial navigation, memory, and sleep.

A comparison of optimal MIMO linear and nonlinear models for brain machine interfaces

NASA Astrophysics Data System (ADS)

Kim, S.-P.; Sanchez, J. C.; Rao, Y. N.; Erdogmus, D.; Carmena, J. M.; Lebedev, M. A.; Nicolelis, M. A. L.; Principe, J. C.

2006-06-01

The field of brain-machine interfaces requires the estimation of a mapping from spike trains collected in motor cortex areas to the hand kinematics of the behaving animal. This paper presents a systematic investigation of several linear (Wiener filter, LMS adaptive filters, gamma filter, subspace Wiener filters) and nonlinear models (time-delay neural network and local linear switching models) applied to datasets from two experiments in monkeys performing motor tasks (reaching for food and target hitting). Ensembles of 100-200 cortical neurons were simultaneously recorded in these experiments, and even larger neuronal samples are anticipated in the future. Due to the large size of the models (thousands of parameters), the major issue studied was the generalization performance. Every parameter of the models (not only the weights) was selected optimally using signal processing and machine learning techniques. The models were also compared statistically with respect to the Wiener filter as the baseline. Each of the optimization procedures produced improvements over that baseline for either one of the two datasets or both.

A comparison of optimal MIMO linear and nonlinear models for brain-machine interfaces.

PubMed

Kim, S-P; Sanchez, J C; Rao, Y N; Erdogmus, D; Carmena, J M; Lebedev, M A; Nicolelis, M A L; Principe, J C

2006-06-01

The field of brain-machine interfaces requires the estimation of a mapping from spike trains collected in motor cortex areas to the hand kinematics of the behaving animal. This paper presents a systematic investigation of several linear (Wiener filter, LMS adaptive filters, gamma filter, subspace Wiener filters) and nonlinear models (time-delay neural network and local linear switching models) applied to datasets from two experiments in monkeys performing motor tasks (reaching for food and target hitting). Ensembles of 100-200 cortical neurons were simultaneously recorded in these experiments, and even larger neuronal samples are anticipated in the future. Due to the large size of the models (thousands of parameters), the major issue studied was the generalization performance. Every parameter of the models (not only the weights) was selected optimally using signal processing and machine learning techniques. The models were also compared statistically with respect to the Wiener filter as the baseline. Each of the optimization procedures produced improvements over that baseline for either one of the two datasets or both.

Practical approximation method for firing-rate models of coupled neural networks with correlated inputs

NASA Astrophysics Data System (ADS)

Barreiro, Andrea K.; Ly, Cheng

2017-08-01

Rapid experimental advances now enable simultaneous electrophysiological recording of neural activity at single-cell resolution across large regions of the nervous system. Models of this neural network activity will necessarily increase in size and complexity, thus increasing the computational cost of simulating them and the challenge of analyzing them. Here we present a method to approximate the activity and firing statistics of a general firing rate network model (of the Wilson-Cowan type) subject to noisy correlated background inputs. The method requires solving a system of transcendental equations and is fast compared to Monte Carlo simulations of coupled stochastic differential equations. We implement the method with several examples of coupled neural networks and show that the results are quantitatively accurate even with moderate coupling strengths and an appreciable amount of heterogeneity in many parameters. This work should be useful for investigating how various neural attributes qualitatively affect the spiking statistics of coupled neural networks.

Voluntary control of intracortical oscillations for reconfiguration of network activity

PubMed Central

Corlier, Juliana; Valderrama, Mario; Navarrete, Miguel; Lehongre, Katia; Hasboun, Dominique; Adam, Claude; Belaid, Hayat; Clémenceau, Stéphane; Baulac, Michel; Charpier, Stéphane; Navarro, Vincent; Le Van Quyen, Michel

2016-01-01

Voluntary control of oscillatory activity represents a key target in the self-regulation of brain function. Using a real-time closed-loop paradigm and simultaneous macro- and micro-electrode recordings, we studied the effects of self-induced intracortical oscillatory activity (4–8 Hz) in seven neurosurgical patients. Subjects learned to robustly and specifically induce oscillations in the target frequency, confirmed by increased oscillatory event density. We have found that the session-to-session variability in performance was explained by the functional long-range decoupling of the target area suggesting a training-induced network reorganization. Downstream effects on more local activities included progressive cross-frequency-coupling with gamma oscillations (30–120 Hz), and the dynamic modulation of neuronal firing rates and spike timing, indicating an improved temporal coordination of local circuits. These findings suggest that effects of voluntary control of intracortical oscillations can be exploited to specifically target plasticity processes to reconfigure network activity, with a particular relevance for memory function or skill acquisition. PMID:27808225

Relaxation oscillator-realized artificial electronic neurons, their responses, and noise

NASA Astrophysics Data System (ADS)

Lim, Hyungkwang; Ahn, Hyung-Woo; Kornijcuk, Vladimir; Kim, Guhyun; Seok, Jun Yeong; Kim, Inho; Hwang, Cheol Seong; Jeong, Doo Seok

2016-05-01

A proof-of-concept relaxation oscillator-based leaky integrate-and-fire (ROLIF) neuron circuit is realized by using an amorphous chalcogenide-based threshold switch and non-ideal operational amplifier (op-amp). The proposed ROLIF neuron offers biologically plausible features such as analog-type encoding, signal amplification, unidirectional synaptic transmission, and Poisson noise. The synaptic transmission between pre- and postsynaptic neurons is achieved through a passive synapse (simple resistor). The synaptic resistor coupled to the non-ideal op-amp realizes excitatory postsynaptic potential (EPSP) evolution that evokes postsynaptic neuron spiking. In an attempt to generalize our proposed model, we theoretically examine ROLIF neuron circuits adopting different non-ideal op-amps having different gains and slew rates. The simulation results indicate the importance of gain in postsynaptic neuron spiking, irrespective of the slew rate (as long as the rate exceeds a particular value), providing the basis for the ROLIF neuron circuit design. Eventually, the behavior of a postsynaptic neuron in connection to multiple presynaptic neurons via synapses is highlighted in terms of EPSP evolution amid simultaneously incident asynchronous presynaptic spikes, which in fact reveals an important role of the random noise in spatial integration.A proof-of-concept relaxation oscillator-based leaky integrate-and-fire (ROLIF) neuron circuit is realized by using an amorphous chalcogenide-based threshold switch and non-ideal operational amplifier (op-amp). The proposed ROLIF neuron offers biologically plausible features such as analog-type encoding, signal amplification, unidirectional synaptic transmission, and Poisson noise. The synaptic transmission between pre- and postsynaptic neurons is achieved through a passive synapse (simple resistor). The synaptic resistor coupled to the non-ideal op-amp realizes excitatory postsynaptic potential (EPSP) evolution that evokes postsynaptic neuron spiking. In an attempt to generalize our proposed model, we theoretically examine ROLIF neuron circuits adopting different non-ideal op-amps having different gains and slew rates. The simulation results indicate the importance of gain in postsynaptic neuron spiking, irrespective of the slew rate (as long as the rate exceeds a particular value), providing the basis for the ROLIF neuron circuit design. Eventually, the behavior of a postsynaptic neuron in connection to multiple presynaptic neurons via synapses is highlighted in terms of EPSP evolution amid simultaneously incident asynchronous presynaptic spikes, which in fact reveals an important role of the random noise in spatial integration. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr01278g

Solar microwave millisecond spike at 2.84 GHz

NASA Technical Reports Server (NTRS)

Fu, Qi-Jun; Jin, Sheng-Zhen; Zhao, Ren-Yang; Zheng, Le-Ping; Liu, Yu-Ying; Li, Xiao-Cong; Wang, Shu-Lan; Chen, Zhi-Jun; Hu, Chu-Min

1986-01-01

Using the high time resolution of 1 ms, the data of solar microwave millisecond spike (MMS) event was recorded more than two hundred times at the frequency of 2.84 GHz at Beijing (Peking) Observatory since May 1981. A preliminary analysis was made. It can be seen from the data that the MMS-events have a variety of the fast activities such as the dispersed and isolated spikes, the clusters of the crowded spikes, the weak spikes superimposed on the noise background, and the phenomena of absorption. The marked differences from that observed with lower time resolution are presented. Using the data, a valuable statistical analysis was made. There are close correlations between MMS-events and hard X-ray bursts, and fast drifting bursts. The MMS events are highly dependent on the type of active regions and the magnetic field configuration. It seems to be crucial to find out the accurate positions on the active region where the MMS-events happen and to make co-operative observations at different bands during the special period when specific active regions appear on the solar disk.

A computationally efficient method for incorporating spike waveform information into decoding algorithms.

PubMed

Ventura, Valérie; Todorova, Sonia

2015-05-01

Spike-based brain-computer interfaces (BCIs) have the potential to restore motor ability to people with paralysis and amputation, and have shown impressive performance in the lab. To transition BCI devices from the lab to the clinic, decoding must proceed automatically and in real time, which prohibits the use of algorithms that are computationally intensive or require manual tweaking. A common choice is to avoid spike sorting and treat the signal on each electrode as if it came from a single neuron, which is fast, easy, and therefore desirable for clinical use. But this approach ignores the kinematic information provided by individual neurons recorded on the same electrode. The contribution of this letter is a linear decoding model that extracts kinematic information from individual neurons without spike-sorting the electrode signals. The method relies on modeling sample averages of waveform features as functions of kinematics, which is automatic and requires minimal data storage and computation. In offline reconstruction of arm trajectories of a nonhuman primate performing reaching tasks, the proposed method performs as well as decoders based on expertly manually and automatically sorted spikes.

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.

Strategies for mapping synaptic inputs on dendrites in vivo by combining two-photon microscopy, sharp intracellular recording, and pharmacology

PubMed Central

Levy, Manuel; Schramm, Adrien E.; Kara, Prakash

2012-01-01

Uncovering the functional properties of individual synaptic inputs on single neurons is critical for understanding the computational role of synapses and dendrites. Previous studies combined whole-cell patch recording to load neurons with a fluorescent calcium indicator and two-photon imaging to map subcellular changes in fluorescence upon sensory stimulation. By hyperpolarizing the neuron below spike threshold, the patch electrode ensured that changes in fluorescence associated with synaptic events were isolated from those caused by back-propagating action potentials. This technique holds promise for determining whether the existence of unique cortical feature maps across different species may be associated with distinct wiring diagrams. However, the use of whole-cell patch for mapping inputs on dendrites is challenging in large mammals, due to brain pulsations and the accumulation of fluorescent dye in the extracellular milieu. Alternatively, sharp intracellular electrodes have been used to label neurons with fluorescent dyes, but the current passing capabilities of these high impedance electrodes may be insufficient to prevent spiking. In this study, we tested whether sharp electrode recording is suitable for mapping functional inputs on dendrites in the cat visual cortex. We compared three different strategies for suppressing visually evoked spikes: (1) hyperpolarization by intracellular current injection, (2) pharmacological blockade of voltage-gated sodium channels by intracellular QX-314, and (3) GABA iontophoresis from a perisomatic electrode glued to the intracellular electrode. We found that functional inputs on dendrites could be successfully imaged using all three strategies. However, the best method for preventing spikes was GABA iontophoresis with low currents (5–10 nA), which minimally affected the local circuit. Our methods advance the possibility of determining functional connectivity in preparations where whole-cell patch may be impractical. PMID:23248588

Spatiotemporal source analysis in scalp EEG vs. intracerebral EEG and SPECT: a case study in a 2-year-old child.

PubMed

Aarabi, A; Grebe, R; Berquin, P; Bourel Ponchel, E; Jalin, C; Fohlen, M; Bulteau, C; Delalande, O; Gondry, C; Héberlé, C; Moullart, V; Wallois, F

2012-06-01

This case study aims to demonstrate that spatiotemporal spike discrimination and source analysis are effective to monitor the development of sources of epileptic activity in time and space. Therefore, they can provide clinically useful information allowing a better understanding of the pathophysiology of individual seizures with time- and space-resolved characteristics of successive epileptic states, including interictal, preictal, postictal, and ictal states. High spatial resolution scalp EEGs (HR-EEG) were acquired from a 2-year-old girl with refractory central epilepsy and single-focus seizures as confirmed by intracerebral EEG recordings and ictal single-photon emission computed tomography (SPECT). Evaluation of HR-EEG consists of the following three global steps: (1) creation of the initial head model, (2) automatic spike and seizure detection, and finally (3) source localization. During the source localization phase, epileptic states are determined to allow state-based spike detection and localization of underlying sources for each spike. In a final cluster analysis, localization results are integrated to determine the possible sources of epileptic activity. The results were compared with the cerebral locations identified by intracerebral EEG recordings and SPECT. The results obtained with this approach were concordant with those of MRI, SPECT and distribution of intracerebral potentials. Dipole cluster centres found for spikes in interictal, preictal, ictal and postictal states were situated an average of 6.3mm from the intracerebral contacts with the highest voltage. Both amplitude and shape of spikes change between states. Dispersion of the dipoles was higher in the preictal state than in the postictal state. Two clusters of spikes were identified. The centres of these clusters changed position periodically during the various epileptic states. High-resolution surface EEG evaluated by an advanced algorithmic approach can be used to investigate the spatiotemporal characteristics of sources located in the epileptic focus. The results were validated by standard methods, ensuring good spatial resolution by MRI and SPECT and optimal temporal resolution by intracerebral EEG. Surface EEG can be used to identify different spike clusters and sources of the successive epileptic states. The method that was used in this study will provide physicians with a better understanding of the pathophysiological characteristics of epileptic activities. In particular, this method may be useful for more effective positioning of implantable intracerebral electrodes. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Dissociation between sustained single-neuron spiking and transient β-LFP oscillations in primate motor cortex

PubMed Central

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

2017-01-01

Determining the relationship between single-neuron spiking and transient (20 Hz) β-local field potential (β-LFP) oscillations is an important step for understanding the role of these oscillations in motor cortex. We show that whereas motor cortex firing rates and beta spiking rhythmicity remain sustained during steady-state movement preparation periods, β-LFP oscillations emerge, in contrast, as short transient events. Single-neuron mean firing rates within and outside transient β-LFP events showed no differences, and no consistent correlation was found between the beta oscillation amplitude and firing rates, as was the case for movement- and visual cue-related β-LFP suppression. Importantly, well-isolated single units featuring beta-rhythmic spiking (43%, 125/292) showed no apparent or only weak phase coupling with the transient β-LFP oscillations. Similar results were obtained for the population spiking. These findings were common in triple microelectrode array recordings from primary motor (M1), ventral (PMv), and dorsal premotor (PMd) cortices in nonhuman primates during movement preparation. Although beta spiking rhythmicity indicates strong membrane potential fluctuations in the beta band, it does not imply strong phase coupling with β-LFP oscillations. The observed dissociation points to two different sources of variation in motor cortex β-LFPs: one that impacts single-neuron spiking dynamics and another related to the generation of mesoscopic β-LFP signals. Furthermore, our findings indicate that rhythmic spiking and diverse neuronal firing rates, which encode planned actions during movement preparation, may naturally limit the ability of different neuronal populations to strongly phase-couple to a single dominant oscillation frequency, leading to the observed spiking and β-LFP dissociation. NEW & NOTEWORTHY We show that whereas motor cortex spiking rates and beta (~20 Hz) spiking rhythmicity remain sustained during steady-state movement preparation periods, β-local field potential (β-LFP) oscillations emerge, in contrast, as transient events. Furthermore, the β-LFP phase at which neurons spike drifts: phase coupling is typically weak or absent. This dissociation points to two sources of variation in the level of motor cortex beta: one that impacts single-neuron spiking and another related to the generation of measured mesoscopic β-LFPs. PMID:28100654

Comparative sensitivity of commercially available aPTT reagents to mulga snake (Pseudechis australis) venom.

PubMed

Lincz, Lisa F; Scorgie, Fiona E; Johnston, Christopher I; O'Leary, Margaret; Prasad, Ritam; Seldon, Michael; Favaloro, Emmanuel; Isbister, Geoffrey K

2014-08-01

This study aimed to determine the relative sensitivity of activated partial thromboplastin time (aPTT) reagents to the anticoagulant effects of phospholipases in mulga snake (Pseudechis australis) venom.Twenty-one haematology laboratories participating in the Royal College of Pathologists of Australasia Quality Assurance Programs were sent human plasma samples spiked with mulga venom (n=25 total results). Results for 17 patients with mulga snake envenoming were available through the Australian Snakebite Project.Only 12 of 25 venom spiked samples returned an abnormally prolonged aPTT. Tests performed with Dade Actin FS (n=7) did not identify any of the spiked samples as abnormal. Although clotting times were significantly prolonged using the lupus anticoagulant sensitive Actin FSL (n=5, p=0.043), only one was reported as abnormal. Only laboratories using TriniCLOT aPTT S (n=6), HemosIL APTT SP (n=2) and Stago PTT-A (n=1) consistently recorded the spiked sample as being above the upper normal reference interval. Abnormally prolonged aPTTs were recorded for four of eight patients whose tests were performed with Actin FSL, five of eight patients with TriniCLOT aPTT HS, and three of three patients using TriniCLOT aPTT S.We conclude that some reagents used for routine aPTT testing are relatively insensitive to the anticoagulant effects of mulga snake venom. Tests performed with these reagents should be interpreted with caution.

Visual Receptive Field Structure of Cortical Inhibitory Neurons Revealed by Two-Photon Imaging Guided Recording

PubMed Central

Liu, Bao-hua; Li, Pingyang; Li, Ya-tang; Sun, Yujiao J.; Yanagawa, Yuchio; Obata, Kunihiko; Zhang, Li I.; Tao, Huizhong W.

2009-01-01

Synaptic inhibition plays an important role in shaping receptive field (RF) properties in the visual cortex. However, the underlying mechanisms remain not well understood, partly due to difficulties in systematically studying functional properties of cortical inhibitory neurons in vivo. Here, we established two-photon imaging guided cell-attached recordings from genetically labelled inhibitory neurons and nearby “shadowed” excitatory neurons in the primary visual cortex of adult mice. Our results revealed that in layer 2/3, the majority of excitatory neurons exhibited both On and Off spike subfields, with their spatial arrangement varying from being completely segregated to overlapped. On the other hand, most layer 4 excitatory neurons exhibited only one discernable subfield. Interestingly, no RF structure with significantly segregated On and Off subfields was observed for layer 2/3 inhibitory neurons of either the fast-spike or regular-spike type. They predominantly possessed overlapped On and Off subfields with a significantly larger size than the excitatory neurons, and exhibited much weaker orientation tuning. These results from the mouse visual cortex suggest that different from the push-pull model proposed for simple cells, layer 2/3 simple-type neurons with segregated spike On and Off subfields likely receive spatially overlapped inhibitory On and Off inputs. We propose that the phase-insensitive inhibition can enhance the spatial distinctiveness of On and Off subfields through a gain control mechanism. PMID:19710305

Stream-based Hebbian eigenfilter for real-time neuronal spike discrimination

PubMed Central

2012-01-01

Background Principal component analysis (PCA) has been widely employed for automatic neuronal spike sorting. Calculating principal components (PCs) is computationally expensive, and requires complex numerical operations and large memory resources. Substantial hardware resources are therefore needed for hardware implementations of PCA. General Hebbian algorithm (GHA) has been proposed for calculating PCs of neuronal spikes in our previous work, which eliminates the needs of computationally expensive covariance analysis and eigenvalue decomposition in conventional PCA algorithms. However, large memory resources are still inherently required for storing a large volume of aligned spikes for training PCs. The large size memory will consume large hardware resources and contribute significant power dissipation, which make GHA difficult to be implemented in portable or implantable multi-channel recording micro-systems. Method In this paper, we present a new algorithm for PCA-based spike sorting based on GHA, namely stream-based Hebbian eigenfilter, which eliminates the inherent memory requirements of GHA while keeping the accuracy of spike sorting by utilizing the pseudo-stationarity of neuronal spikes. Because of the reduction of large hardware storage requirements, the proposed algorithm can lead to ultra-low hardware resources and power consumption of hardware implementations, which is critical for the future multi-channel micro-systems. Both clinical and synthetic neural recording data sets were employed for evaluating the accuracy of the stream-based Hebbian eigenfilter. The performance of spike sorting using stream-based eigenfilter and the computational complexity of the eigenfilter were rigorously evaluated and compared with conventional PCA algorithms. Field programmable logic arrays (FPGAs) were employed to implement the proposed algorithm, evaluate the hardware implementations and demonstrate the reduction in both power consumption and hardware memories achieved by the streaming computing Results and discussion Results demonstrate that the stream-based eigenfilter can achieve the same accuracy and is 10 times more computationally efficient when compared with conventional PCA algorithms. Hardware evaluations show that 90.3% logic resources, 95.1% power consumption and 86.8% computing latency can be reduced by the stream-based eigenfilter when compared with PCA hardware. By utilizing the streaming method, 92% memory resources and 67% power consumption can be saved when compared with the direct implementation of GHA. Conclusion Stream-based Hebbian eigenfilter presents a novel approach to enable real-time spike sorting with reduced computational complexity and hardware costs. This new design can be further utilized for multi-channel neuro-physiological experiments or chronic implants. PMID:22490725

Extending Transfer Entropy Improves Identification of Effective Connectivity in a Spiking Cortical Network Model

PubMed Central

Ito, Shinya; Hansen, Michael E.; Heiland, Randy; Lumsdaine, Andrew; Litke, Alan M.; Beggs, John M.

2011-01-01

Transfer entropy (TE) is an information-theoretic measure which has received recent attention in neuroscience for its potential to identify effective connectivity between neurons. Calculating TE for large ensembles of spiking neurons is computationally intensive, and has caused most investigators to probe neural interactions at only a single time delay and at a message length of only a single time bin. This is problematic, as synaptic delays between cortical neurons, for example, range from one to tens of milliseconds. In addition, neurons produce bursts of spikes spanning multiple time bins. To address these issues, here we introduce a free software package that allows TE to be measured at multiple delays and message lengths. To assess performance, we applied these extensions of TE to a spiking cortical network model (Izhikevich, 2006) with known connectivity and a range of synaptic delays. For comparison, we also investigated single-delay TE, at a message length of one bin (D1TE), and cross-correlation (CC) methods. We found that D1TE could identify 36% of true connections when evaluated at a false positive rate of 1%. For extended versions of TE, this dramatically improved to 73% of true connections. In addition, the connections correctly identified by extended versions of TE accounted for 85% of the total synaptic weight in the network. Cross correlation methods generally performed more poorly than extended TE, but were useful when data length was short. A computational performance analysis demonstrated that the algorithm for extended TE, when used on currently available desktop computers, could extract effective connectivity from 1 hr recordings containing 200 neurons in ∼5 min. We conclude that extending TE to multiple delays and message lengths improves its ability to assess effective connectivity between spiking neurons. These extensions to TE soon could become practical tools for experimentalists who record hundreds of spiking neurons. PMID:22102894

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.

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

Modeling continuous covariates with a "spike" at zero: Bivariate approaches.

PubMed

Jenkner, Carolin; Lorenz, Eva; Becher, Heiko; Sauerbrei, Willi

2016-07-01

In epidemiology and clinical research, predictors often take value zero for a large amount of observations while the distribution of the remaining observations is continuous. These predictors are called variables with a spike at zero. Examples include smoking or alcohol consumption. Recently, an extension of the fractional polynomial (FP) procedure, a technique for modeling nonlinear relationships, was proposed to deal with such situations. To indicate whether or not a value is zero, a binary variable is added to the model. In a two stage procedure, called FP-spike, the necessity of the binary variable and/or the continuous FP function for the positive part are assessed for a suitable fit. In univariate analyses, the FP-spike procedure usually leads to functional relationships that are easy to interpret. This paper introduces four approaches for dealing with two variables with a spike at zero (SAZ). The methods depend on the bivariate distribution of zero and nonzero values. Bi-Sep is the simplest of the four bivariate approaches. It uses the univariate FP-spike procedure separately for the two SAZ variables. In Bi-D3, Bi-D1, and Bi-Sub, proportions of zeros in both variables are considered simultaneously in the binary indicators. Therefore, these strategies can account for correlated variables. The methods can be used for arbitrary distributions of the covariates. For illustration and comparison of results, data from a case-control study on laryngeal cancer, with smoking and alcohol intake as two SAZ variables, is considered. In addition, a possible extension to three or more SAZ variables is outlined. A combination of log-linear models for the analysis of the correlation in combination with the bivariate approaches is proposed. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fast EEG spike detection via eigenvalue analysis and clustering of spatial amplitude distribution

NASA Astrophysics Data System (ADS)

Fukami, Tadanori; Shimada, Takamasa; Ishikawa, Bunnoshin

2018-06-01

Objective. In the current study, we tested a proposed method for fast spike detection in electroencephalography (EEG). Approach. We performed eigenvalue analysis in two-dimensional space spanned by gradients calculated from two neighboring samples to detect high-amplitude negative peaks. We extracted the spike candidates by imposing restrictions on parameters regarding spike shape and eigenvalues reflecting detection characteristics of individual medical doctors. We subsequently performed clustering, classifying detected peaks by considering the amplitude distribution at 19 scalp electrodes. Clusters with a small number of candidates were excluded. We then defined a score for eliminating spike candidates for which the pattern of detected electrodes differed from the overall pattern in a cluster. Spikes were detected by setting the score threshold. Main results. Based on visual inspection by a psychiatrist experienced in EEG, we evaluated the proposed method using two statistical measures of precision and recall with respect to detection performance. We found that precision and recall exhibited a trade-off relationship. The average recall value was 0.708 in eight subjects with the score threshold that maximized the F-measure, with 58.6  ±  36.2 spikes per subject. Under this condition, the average precision was 0.390, corresponding to a false positive rate 2.09 times higher than the true positive rate. Analysis of the required processing time revealed that, using a general-purpose computer, our method could be used to perform spike detection in 12.1% of the recording time. The process of narrowing down spike candidates based on shape occupied most of the processing time. Significance. Although the average recall value was comparable with that of other studies, the proposed method significantly shortened the processing time.

Integrated low noise low power interface for neural bio-potentials recording and conditioning

NASA Astrophysics Data System (ADS)

Bottino, Emanuele; Martinoia, Sergio; Valle, Maurizio

2005-06-01

The recent progress in both neurobiology and microelectronics suggests the creation of new, powerful tools to investigate the basic mechanisms of brain functionality. In particular, a lot of efforts are spent by scientific community to define new frameworks devoted to the analysis of in-vitro cultured neurons. One possible approach is recording their spiking activity to monitor the coordinated cellular behaviour and get insights about neural plasticity. Due to the nature of neurons action-potentials, when considering the design of an integrated microelectronic-based recording system, a number of problems arise. First, one would desire to have a high number of recording sites (i.e. several hundreds): this poses constraints on silicon area and power consumption. In this regard, our aim is to integrate-through on-chip post-processing techniques-hundreds of bio-compatible microsensors together with CMOS standard-process low-power (i.e. some tenths of uW per channel) conditioning electronics. Each recording channel is provided with sampling electronics to insure synchronous recording so that, for example, cross-correlation between signals coming from different sites can be performed. Extra-cellular potentials are in the range of [50-150] uV, so a comparison in terms of noise-efficiency was carried out among different architectures and very low-noise pre-amplification electronics (i.e. less than 5 uVrms) was designed. As spikes measurements are made with respect to the voltage of a reference electrode, we opted for an AC-coupled differential-input preamplifier provided with band-pass filtering capability. To achieve this, we implemented large time-constant (up to seconds) integrated components in the preamp feedback path. Thus, we got rid also of random slow-drifting DC-offsets and common mode signals. The paper will present our achievements in the design and implementation of a fully integrated bio-abio interface to record neural spiking activity. In particular, preliminary results will be reported.

Influence of enrichment broths on multiplex PCR detection of total coliform bacteria, Escherichia coli and Clostridium perfringens, in spiked water samples.

PubMed

Worakhunpiset, S; Tharnpoophasiam, P

2009-07-01

Although multiplex PCR amplification condition for simultaneous detection of total coliform bacteria, Escherichia coli and Clostridium perfringens in water sample has been developed, results with high sensitivity are obtained when amplifying purified DNA, but the sensitivity is low when applied to spiked water samples. An enrichment broth culture prior PCR analysis increases sensitivity of the test but the specific nature of enrichment broth can affect the PCR results. Three enrichment broths, lactose broth, reinforced clostridial medium and fluid thioglycollate broth, were compared for their influence on sensitivity and on time required with multiplex PCR assay. Fluid thioglycollate broth was the most effective with shortest enrichment time and lowest detection limit.

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.

A fast BK-type KCa current acts as a postsynaptic modulator of temporal selectivity for communication signals.

PubMed

Kohashi, Tsunehiko; Carlson, Bruce A

2014-01-01

Temporal patterns of spiking often convey behaviorally relevant information. Various synaptic mechanisms and intrinsic membrane properties can influence neuronal selectivity to temporal patterns of input. However, little is known about how synaptic mechanisms and intrinsic properties together determine the temporal selectivity of neuronal output. We tackled this question by recording from midbrain electrosensory neurons in mormyrid fish, in which the processing of temporal intervals between communication signals can be studied in a reduced in vitro preparation. Mormyrids communicate by varying interpulse intervals (IPIs) between electric pulses. Within the midbrain posterior exterolateral nucleus (ELp), the temporal patterns of afferent spike trains are filtered to establish single-neuron IPI tuning. We performed whole-cell recording from ELp neurons in a whole-brain preparation and examined the relationship between intrinsic excitability and IPI tuning. We found that spike frequency adaptation of ELp neurons was highly variable. Postsynaptic potentials (PSPs) of strongly adapting (phasic) neurons were more sharply tuned to IPIs than weakly adapting (tonic) neurons. Further, the synaptic filtering of IPIs by tonic neurons was more faithfully converted into variation in spiking output, particularly at short IPIs. Pharmacological manipulation under current- and voltage-clamp revealed that tonic firing is mediated by a fast, large-conductance Ca(2+)-activated K(+) (KCa) current (BK) that speeds up action potential repolarization. These results suggest that BK currents can shape the temporal filtering of sensory inputs by modifying both synaptic responses and PSP-to-spike conversion. Slow SK-type KCa currents have previously been implicated in temporal processing. Thus, both fast and slow KCa currents can fine-tune temporal selectivity.

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

An ambulatory recording system for the assessment of autonomic changes across multiple days

NASA Astrophysics Data System (ADS)

Sollers, John J., III; Yonezawa, Yoshiharu; Silver, Rebecca A.; Merritt, Marcellus M.; Thayer, Julian F.

2005-05-01

Recent evidence indicates that poor autonomic regulation, indexed by decreased heart period variability (HPV), is associated with decreased working memory. HPV analyses are computed on the interbeat interval time series derived from the electrocardiogram (EKG). Unfortunately, the duration of the data collection and the issue of the size of ambulatory monitors with sufficient storage capacity for multi-day records is somewhat problematic. In the present paper we describe a system that allows for the collection of large amounts of high quality data using a small data collection device. The recording system consists of a miniature, single-module electrocardiogram-recording device. This module consists of an integrated three-electrode device that is attached to the chest of the subject. A low power 8-bit micro-controller detects the R-spike and stores the time between R-spikes in milliseconds on a 512 KB EEPROM. This system can record continuously for over four days. This system will allow the recording of cardio-dynamics in the field and provide highly reliable data across multiple days. The use of this device to assess physiological function in military operations would allow researchers to examine longer data records across several contexts and to understand the role of changes in autonomic function as they relate to performance.

Goulds Belt, Interstellar Clouds, and the Eocene-Oligocene Helium-3 Spike

NASA Technical Reports Server (NTRS)

Rubincam, David Parry

2015-01-01

Drag from hydrogen in the interstellar cloud which formed Gould's Belt may have sent small meteoroids with embedded helium to the Earth, perhaps explaining part or all of the (sup 3) He spike seen in the sedimentary record at the Eocene-Oligocene transition. Assuming the Solar System passed through part of the cloud, meteoroids in the asteroid belt up to centimeter size may have been dragged to the resonances, where their orbital eccentricities were pumped up into Earth-crossing orbits.

Effective Synchronization of EEG and EMG for Mobile Brain/Body Imaging in Clinical Settings.

PubMed

Artoni, Fiorenzo; Barsotti, Annalisa; Guanziroli, Eleonora; Micera, Silvestro; Landi, Alberto; Molteni, Franco

2017-01-01

Mobile Brain/Body Imaging (MoBI) is rapidly gaining traction as a new imaging modality to study how cognitive processes support locomotion. Electroencephalogram (EEG) and electromyogram (EMG), due to their time resolution, non-invasiveness and portability are the techniques of choice for MoBI, but synchronization requirements among others restrict its use to high-end research facilities. Here we test the effectiveness of a technique that enables us to achieve MoBI-grade synchronization of EEG and EMG, even when other strategies (such as Lab Streaming Layer (LSL)) cannot be used e.g., due to the unavailability of proprietary Application Programming Interfaces (APIs), which is often the case in clinical settings. The proposed strategy is that of aligning several spikes at the beginning and end of the session. We delivered a train of spikes to the EEG amplifier and EMG electrodes every 2 s over a 10-min time period. We selected a variable number of spikes (from 1 to 10) both at the beginning and end of the time series and linearly resampled the data so as to align them. We then compared the misalignment of the "middle" spikes over the whole recording to test for jitter and synchronization drifts, highlighting possible nonlinearities (due to hardware filters) and estimated the maximum length of the recording to achieve a [-5 to 5] ms misalignment range. We demonstrate that MoBI-grade synchronization can be achieved within 10-min recordings with a 1.7 ms jitter and [-5 5] ms misalignment range. We show that repeated spike delivery can be used to test online synchronization options and to troubleshoot synchronization issues over EEG and EMG. We also show that synchronization cannot rely only on the equipment sampling rate advertised by manufacturers. The synchronization strategy described can be used virtually in every clinical environment, and may increase the interest among a broader spectrum of clinicians and researchers in the MoBI framework, ultimately leading to a better understanding of the brain processes underlying locomotion control and the development of more effective rehabilitation approaches.

Constructing Precisely Computing Networks with Biophysical Spiking Neurons.

PubMed

Schwemmer, Michael A; Fairhall, Adrienne L; Denéve, Sophie; Shea-Brown, Eric T

2015-07-15

While spike timing has been shown to carry detailed stimulus information at the sensory periphery, its possible role in network computation is less clear. Most models of computation by neural networks are based on population firing rates. In equivalent spiking implementations, firing is assumed to be random such that averaging across populations of neurons recovers the rate-based approach. Recently, however, Denéve and colleagues have suggested that the spiking behavior of neurons may be fundamental to how neuronal networks compute, with precise spike timing determined by each neuron's contribution to producing the desired output (Boerlin and Denéve, 2011; Boerlin et al., 2013). By postulating that each neuron fires to reduce the error in the network's output, it was demonstrated that linear computations can be performed by networks of integrate-and-fire neurons that communicate through instantaneous synapses. This left open, however, the possibility that realistic networks, with conductance-based neurons with subthreshold nonlinearity and the slower timescales of biophysical synapses, may not fit into this framework. Here, we show how the spike-based approach can be extended to biophysically plausible networks. We then show that our network reproduces a number of key features of cortical networks including irregular and Poisson-like spike times and a tight balance between excitation and inhibition. Lastly, we discuss how the behavior of our model scales with network size or with the number of neurons "recorded" from a larger computing network. These results significantly increase the biological plausibility of the spike-based approach to network computation. We derive a network of neurons with standard spike-generating currents and synapses with realistic timescales that computes based upon the principle that the precise timing of each spike is important for the computation. We then show that our network reproduces a number of key features of cortical networks including irregular, Poisson-like spike times, and a tight balance between excitation and inhibition. These results significantly increase the biological plausibility of the spike-based approach to network computation, and uncover how several components of biological networks may work together to efficiently carry out computation. Copyright © 2015 the authors 0270-6474/15/3510112-23$15.00/0.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

PubMed

Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

2018-04-24

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

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.

Self-control with spiking and non-spiking neural networks playing games.

PubMed

Christodoulou, Chris; Banfield, Gaye; Cleanthous, Aristodemos

2010-01-01

Self-control can be defined as choosing a large delayed reward over a small immediate reward, while precommitment is the making of a choice with the specific aim of denying oneself future choices. Humans recognise that they have self-control problems and attempt to overcome them by applying precommitment. Problems in exercising self-control, suggest a conflict between cognition and motivation, which has been linked to competition between higher and lower brain functions (representing the frontal lobes and the limbic system respectively). This premise of an internal process conflict, lead to a behavioural model being proposed, based on which, we implemented a computational model for studying and explaining self-control through precommitment behaviour. Our model consists of two neural networks, initially non-spiking and then spiking ones, representing the higher and lower brain systems viewed as cooperating for the benefit of the organism. The non-spiking neural networks are of simple feed forward multilayer type with reinforcement learning, one with selective bootstrap weight update rule, which is seen as myopic, representing the lower brain and the other with the temporal difference weight update rule, which is seen as far-sighted, representing the higher brain. The spiking neural networks are implemented with leaky integrate-and-fire neurons with learning based on stochastic synaptic transmission. The differentiating element between the two brain centres in this implementation is based on the memory of past actions determined by an eligibility trace time constant. As the structure of the self-control problem can be likened to the Iterated Prisoner's Dilemma (IPD) game in that cooperation is to defection what self-control is to impulsiveness or what compromising is to insisting, we implemented the neural networks as two players, learning simultaneously but independently, competing in the IPD game. With a technique resembling the precommitment effect, whereby the payoffs for the dilemma cases in the IPD payoff matrix are differentially biased (increased or decreased), it is shown that increasing the precommitment effect (through increasing the differential bias) increases the probability of cooperating with oneself in the future, irrespective of whether the implementation is with spiking or non-spiking neural networks. Copyright (c) 2009 Elsevier Ltd. All rights reserved.

Training Deep Spiking Neural Networks Using Backpropagation.

PubMed

Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael

2016-01-01

Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy efficiency of deep neural networks through data-driven event-based computation. However, training such networks is difficult due to the non-differentiable nature of spike events. In this paper, we introduce a novel technique, which treats the membrane potentials of spiking neurons as differentiable signals, where discontinuities at spike times are considered as noise. This enables an error backpropagation mechanism for deep SNNs that follows the same principles as in conventional deep networks, but works directly on spike signals and membrane potentials. Compared with previous methods relying on indirect training and conversion, our technique has the potential to capture the statistics of spikes more precisely. We evaluate the proposed framework on artificially generated events from the original MNIST handwritten digit benchmark, and also on the N-MNIST benchmark recorded with an event-based dynamic vision sensor, in which the proposed method reduces the error rate by a factor of more than three compared to the best previous SNN, and also achieves a higher accuracy than a conventional convolutional neural network (CNN) trained and tested on the same data. We demonstrate in the context of the MNIST task that thanks to their event-driven operation, deep SNNs (both fully connected and convolutional) trained with our method achieve accuracy equivalent with conventional neural networks. In the N-MNIST example, equivalent accuracy is achieved with about five times fewer computational operations.

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.

Analyzing large data sets acquired through telemetry from rats exposed to organophosphorous compounds: an EEG study.

PubMed

de Araujo Furtado, Marcio; Zheng, Andy; Sedigh-Sarvestani, Madineh; Lumley, Lucille; Lichtenstein, Spencer; Yourick, Debra

2009-10-30

The organophosphorous compound soman is an acetylcholinesterase inhibitor that causes damage to the brain. Exposure to soman causes neuropathology as a result of prolonged and recurrent seizures. In the present study, long-term recordings of cortical EEG were used to develop an unbiased means to quantify measures of seizure activity in a large data set while excluding other signal types. Rats were implanted with telemetry transmitters and exposed to soman followed by treatment with therapeutics similar to those administered in the field after nerve agent exposure. EEG, activity and temperature were recorded continuously for a minimum of 2 days pre-exposure and 15 days post-exposure. A set of automatic MATLAB algorithms have been developed to remove artifacts and measure the characteristics of long-term EEG recordings. The algorithms use short-time Fourier transforms to compute the power spectrum of the signal for 2-s intervals. The spectrum is then divided into the delta, theta, alpha, and beta frequency bands. A linear fit to the power spectrum is used to distinguish normal EEG activity from artifacts and high amplitude spike wave activity. Changes in time spent in seizure over a prolonged period are a powerful indicator of the effects of novel therapeutics against seizures. A graphical user interface has been created that simultaneously plots the raw EEG in the time domain, the power spectrum, and the wavelet transform. Motor activity and temperature are associated with EEG changes. The accuracy of this algorithm is also verified against visual inspection of video recordings up to 3 days after exposure.

Crossed motor innervation of the base of human tongue

PubMed Central

Jordan, Amy S.; Nicholas, Christian L.; Cori, Jennifer M.; Semmler, John G.; Trinder, John

2015-01-01

Muscle fibers of the genioglossus (GG) form the bulk of the muscle mass at the base of the tongue. The motor control of the tongue is critical for vocalization, feeding, and breathing. Our goal was to assess the patterns of motor innervation of GG single motor units (SMUs) in humans. Simultaneous monopolar recordings were obtained from four sites in the base of the tongue bilaterally at two antero-posterior levels from 16 resting, awake, healthy adult males, who wore a face mask with airway pressure and airflow sensors. We analyzed 69 data segments in which at least one lead contained large action potentials generated by an SMU. Such potentials served as triggers for spike-triggered averaging (STA) of signals recorded from the other three sites. Spontaneous activity of the SMUs was classified as inspiratory modulated, expiratory modulated, or tonic. Consistent with the antero-posterior orientation of GG fibers, 44 STAs (77%) recorded ipsilateral to the trigger yielded sharp action potentials with a median amplitude of 52 μV [interquartile range (IQR): 25–190] that were time shifted relative to the trigger by about 1 ms. Notably, 48% of recordings on the side opposite to the trigger also yielded sharp action potentials. Of those, 17 (29%) had a median amplitude of 63 μV (IQR: 39–96), and most were generated by tonic SMUs. Thus a considerable proportion of GG muscle fibers receive a crossed motor innervation. Crossed innervation may help ensure symmetry and stability of tongue position and movements under normal conditions and following injury or degenerative changes affecting the tongue. PMID:25855691

Subcortical neuronal ensembles: an analysis of motor task association, tremor, oscillations, and synchrony in human patients.

PubMed

Hanson, Timothy L; Fuller, Andrew M; Lebedev, Mikhail A; Turner, Dennis A; Nicolelis, Miguel A L

2012-06-20

Deep brain stimulation (DBS) has expanded as an effective treatment for motor disorders, providing a valuable opportunity for intraoperative recording of the spiking activity of subcortical neurons. The properties of these neurons and their potential utility in neuroprosthetic applications are not completely understood. During DBS surgeries in 25 human patients with either essential tremor or Parkinson's disease, we acutely recorded the single-unit activity of 274 ventral intermediate/ventral oralis posterior motor thalamus (Vim/Vop) neurons and 123 subthalamic nucleus (STN) neurons. These subcortical neuronal ensembles (up to 23 neurons sampled simultaneously) were recorded while the patients performed a target-tracking motor task using a cursor controlled by a haptic glove. We observed that modulations in firing rate of a substantial number of neurons in both Vim/Vop and STN represented target onset, movement onset/direction, and hand tremor. Neurons in both areas exhibited rhythmic oscillations and pairwise synchrony. Notably, all tremor-associated neurons exhibited synchrony within the ensemble. The data further indicate that oscillatory (likely pathological) neurons and behaviorally tuned neurons are not distinct but rather form overlapping sets. Whereas previous studies have reported a linear relationship between power spectra of neuronal oscillations and hand tremor, we report a nonlinear relationship suggestive of complex encoding schemes. Even in the presence of this pathological activity, linear models were able to extract motor parameters from ensemble discharges. Based on these findings, we propose that chronic multielectrode recordings from Vim/Vop and STN could prove useful for further studying, monitoring, and even treating motor disorders.

Nonlinear computations shaping temporal processing of precortical vision.

PubMed

Butts, Daniel A; Cui, Yuwei; Casti, Alexander R R

2016-09-01

Computations performed by the visual pathway are constructed by neural circuits distributed over multiple stages of processing, and thus it is challenging to determine how different stages contribute on the basis of recordings from single areas. In the current article, we address this problem in the lateral geniculate nucleus (LGN), using experiments combined with nonlinear modeling capable of isolating various circuit contributions. We recorded cat LGN neurons presented with temporally modulated spots of various sizes, which drove temporally precise LGN responses. We utilized simultaneously recorded S-potentials, corresponding to the primary retinal ganglion cell (RGC) input to each LGN cell, to distinguish the computations underlying temporal precision in the retina from those in the LGN. Nonlinear models with excitatory and delayed suppressive terms were sufficient to explain temporal precision in the LGN, and we found that models of the S-potentials were nearly identical, although with a lower threshold. To determine whether additional influences shaped the response at the level of the LGN, we extended this model to use the S-potential input in combination with stimulus-driven terms to predict the LGN response. We found that the S-potential input "explained away" the major excitatory and delayed suppressive terms responsible for temporal patterning of LGN spike trains but revealed additional contributions, largely PULL suppression, to the LGN response. Using this novel combination of recordings and modeling, we were thus able to dissect multiple circuit contributions to LGN temporal responses across retina and LGN, and set the foundation for targeted study of each stage. Copyright © 2016 the American Physiological Society.

Bio-electrochemical microelectrode arrays for glutamate and electrophysiology detection in hippocampus of temporal lobe epileptic rats.

PubMed

Li, Ziyue; Song, Yilin; Xiao, Guihua; Gao, Fei; Xu, Shengwei; Wang, Mixia; Zhang, Yu; Guo, Fengru; Liu, Jie; Xia, Yang; Cai, Xinxia

2018-06-01

Temporal Lobe Epilepsy (TLE) is a chronic neurological disorder, characterized by sudden, repeated and transient central nervous system dysfunction. For better understanding of TLE, bio-nanomodified microelectrode arrays (MEA) are designed, for the achievement of high-quality simultaneous detection of glutamate signals (Glu) and multi-channel electrophysiological signals including action potentials (spikes) and local field potentials (LFPs). The MEA was fabricated by Micro-Electro-Mechanical System fabrication technology and all recording sites were modified with platinum black nano-particles, the average impedance decreased by nearly 90 times. Additionally, glutamate oxidase was also modified for the detection of Glu. The average sensitivity of the electrode in Glu solution was 1.999 ± 0.032 × 10 -2 pA/μM·μm 2 (n = 3) and linearity was R = 0.9986, with a good selectivity of 97.82% for glutamate and effective blocking of other interferents. In the in-vivo experiments, the MEA was subjected in hippocampus to electrophysiology and Glu concentration detection. During seizures, the fire rate of spikes increases, and the interspike interval is concentrated within 30 ms. The amplitude of LFPs increases by 3 times and the power increases. The Glu level (4.22 μM, n = 4) was obviously higher than normal rats (2.24 μM, n = 4). The MEA probe provides an advanced tool for the detection of dual-mode signals in the research of neurological diseases. Copyright © 2018 Elsevier Inc. All rights reserved.

Microscopic mild focal cortical dysplasia in temporal lobe dual pathology: an electrocorticography study.

PubMed

Morales Chacón, L; Estupiñán, B; Lorigados Pedre, L; Trápaga Quincoses, O; García Maeso, I; Sanchez, A; Bender del Busto, J; Garcia, M E; Baez Martin, M; Zaldivar, M; Gómez, A; Orozco, S; Rocha Arrieta, L

2009-10-01

Associations between electrophysiological and histological findings might provide an insight into the epileptogenicity of mild focal cortical dysplasia (FCD) in patients with temporal lobe epilepsy (TLE) and a dual pathology. A total of 22 patients with pharmacoresistant TLE were included in the study, 16 of them with histologically confirmed hippocampal sclerosis (HS) associated with neocortical temporal mild Palmini Type-I FCD subtypes and 6 with HS. Intraoperative electrocorticography (ECoG) recordings were analysed for epileptiform discharge frequency and morphology. Associations between histological, and electrocorticography pattern findings in these patients were analysed. Electroclinical outcomes in these patients were also evaluated. Neocortical areas with mild Palmini Type-I FCD showed a significantly higher spike frequency (SF) recorded in the inferior temporal gyrus than those neocortical areas in patients with HS. There was a tendency to higher spike frequency and lower amplitude in neocortical areas with histopathologic subtype IB FCD in relation with IA during intraoperative ECoG. Post-SF excision and amplitude were significantly lower during neocortical post-excision intraoperative ECoG than during neocortical pre-excision recording. There was no difference found in the clinical outcome between patients with and without FCD. Intraoperative electrocorticographic interictal spike frequency recorded in the neocortical inferior temporal gyrus may help to characterize the histopathologic subtypes of mild Palmini Type-I FCD in patients with temporal lobe epilepsy (TLE) and a dual pathology. Our data support the epileptogenicity of neocortical mild FCD in TLE and assessments of ECoG patterns are relevant to determine the extent of the resection in these patients which can influence the electroclinical outcome.

The Research Laboratory of Electronics Progress Report Number 132: January 1-December 31, 1989

DTIC Science & Technology

1990-01-01

between Binaural Hearing and Brainstem Auditory Evoked Potentials in Humans...fem- tosecond excitation pulses. This gives rise to the characteristic " beating " pattern which contains sum and difference frequencies. The "spike...vibrational modes whose through a simple optical network consisting simultaneous oscillations yield the " beating " of only two lenses, two gratings

A wireless neural recording system with a precision motorized microdrive for freely behaving animals

PubMed Central

Hasegawa, Taku; Fujimoto, Hisataka; Tashiro, Koichiro; Nonomura, Mayu; Tsuchiya, Akira; Watanabe, Dai

2015-01-01

The brain is composed of many different types of neurons. Therefore, analysis of brain activity with single-cell resolution could provide fundamental insights into brain mechanisms. However, the electrical signal of an individual neuron is very small, and precise isolation of single neuronal activity from moving subjects is still challenging. To measure single-unit signals in actively behaving states, establishment of technologies that enable fine control of electrode positioning and strict spike sorting is essential. To further apply such a single-cell recording approach to small brain areas in naturally behaving animals in large spaces or during social interaction, we developed a compact wireless recording system with a motorized microdrive. Wireless control of electrode placement facilitates the exploration of single neuronal activity without affecting animal behaviors. Because the system is equipped with a newly developed data-encoding program, the recorded data are readily compressed almost to theoretical limits and securely transmitted to a host computer. Brain activity can thereby be stably monitored in real time and further analyzed using online or offline spike sorting. Our wireless recording approach using a precision motorized microdrive will become a powerful tool for studying brain mechanisms underlying natural or social behaviors. PMID:25597933

Reduced spike-timing reliability correlates with the emergence of fast ripples in the rat epileptic hippocampus.

PubMed

Foffani, Guglielmo; Uzcategui, Yoryani G; Gal, Beatriz; Menendez de la Prida, Liset

2007-09-20

Ripples are sharp-wave-associated field oscillations (100-300 Hz) recorded in the hippocampus during behavioral immobility and slow-wave sleep. In epileptic rats and humans, a different and faster oscillation (200-600 Hz), termed fast ripples, has been described. However, the basic mechanisms are unknown. Here, we propose that fast ripples emerge from a disorganized ripple pattern caused by unreliable firing in the epileptic hippocampus. Enhanced synaptic activity is responsible for the irregular bursting of CA3 pyramidal cells due to large membrane potential fluctuations. Lower field interactions and a reduced spike-timing reliability concur with decreased spatial synchronization and the emergence of fast ripples. Reducing synaptically driven membrane potential fluctuations improves both spike-timing reliability and spatial synchronization and restores ripples in the epileptic hippocampus. Conversely, a lower spike-timing reliability, with reduced potassium currents, is associated with ripple shuffling in normal hippocampus. Therefore, fast ripples may reflect a pathological desynchronization of the normal ripple pattern.

Automated spike sorting algorithm based on Laplacian eigenmaps and k-means clustering.

PubMed

Chah, E; Hok, V; Della-Chiesa, A; Miller, J J H; O'Mara, S M; Reilly, R B

2011-02-01

This study presents a new automatic spike sorting method based on feature extraction by Laplacian eigenmaps combined with k-means clustering. The performance of the proposed method was compared against previously reported algorithms such as principal component analysis (PCA) and amplitude-based feature extraction. Two types of classifier (namely k-means and classification expectation-maximization) were incorporated within the spike sorting algorithms, in order to find a suitable classifier for the feature sets. Simulated data sets and in-vivo tetrode multichannel recordings were employed to assess the performance of the spike sorting algorithms. The results show that the proposed algorithm yields significantly improved performance with mean sorting accuracy of 73% and sorting error of 10% compared to PCA which combined with k-means had a sorting accuracy of 58% and sorting error of 10%.A correction was made to this article on 22 February 2011. The spacing of the title was amended on the abstract page. No changes were made to the article PDF and the print version was unaffected.

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

Determinants of spikes in ultrafine particle concentration whilst commuting by bus

NASA Astrophysics Data System (ADS)

Lim, Shanon; Dirks, Kim N.; Salmond, Jennifer A.; Xie, Shanju

2015-07-01

This paper examines concentration of ultrafine particles (UFPs) based on data collected using high-resolution UFP monitors whilst travelling by bus during rush hour along three different urban routes in Auckland, New Zealand. The factors influencing in-bus UFP concentration were assessed using a combination of spatial, statistical and GIS analysis techniques to determine both spatial and temporal variability. Results from 68 bus trips showed that concentrations varied more within a route than between on a given day, despite differences in urban morphology, land use and traffic densities between routes. A number of trips were characterised by periods of very rapid increases in UFPs (concentration 'spikes'), followed by slow declines. Trips which recorded at least one spike (an increase of greater than 10,000 pt/cm3) resulted in significantly higher mean concentrations. Spikes in UFPs were significantly more likely to occur when travelling at low speeds and when passengers were alighting and boarding at bus stops close to traffic light intersections.

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.

Input-output mapping reconstruction of spike trains at dorsal horn evoked by manual acupuncture

NASA Astrophysics Data System (ADS)

Wei, Xile; Shi, Dingtian; Yu, Haitao; Deng, Bin; Lu, Meili; Han, Chunxiao; Wang, Jiang

2016-12-01

In this study, a generalized linear model (GLM) is used to reconstruct mapping from acupuncture stimulation to spike trains driven by action potential data. The electrical signals are recorded in spinal dorsal horn after manual acupuncture (MA) manipulations with different frequencies being taken at the “Zusanli” point of experiment rats. Maximum-likelihood method is adopted to estimate the parameters of GLM and the quantified value of assumed model input. Through validating the accuracy of firings generated from the established GLM, it is found that the input-output mapping of spike trains evoked by acupuncture can be successfully reconstructed for different frequencies. Furthermore, via comparing the performance of several GLMs based on distinct inputs, it suggests that input with the form of half-sine with noise can well describe the generator potential induced by acupuncture mechanical action. Particularly, the comparison of reproducing the experiment spikes for five selected inputs is in accordance with the phenomenon found in Hudgkin-Huxley (H-H) model simulation, which indicates the mapping from half-sine with noise input to experiment spikes meets the real encoding scheme to some extent. These studies provide us a new insight into coding processes and information transfer of acupuncture.

Effect of Soil Aging on the Phytoremediation Potential of Zea mays in Chromium and Benzo[a]Pyrene Contaminated Soils.

PubMed

Chigbo, Chibuike

2015-06-01

This study compared the phytoremediation potential of Zea mays in soil either aged or freshly amended with chromium (Cr) and benzo[a]pyrene (B[a]P). Z. mays showed increased shoot biomass in aged soils than in freshly spiked soils. The shoot biomass in contaminated soils increased by over 50% in aged soil when compared to freshly amended soils, and over 29% more Cr was accumulated in the shoot of Z. mays in aged soil than in freshly amended soil. Planting Z. mays in aged soil helped in the dissipation of more than 31% B[a]P than in freshly spiked soil, but in the absence of plants, there seemed to be no difference between the dissipation rates of B[a]P in freshly and aged co-contaminated soil. Z. mays seemed to enhance the simultaneous removal of Cr and B[a]P in aged soil than in freshly spiked soil and hence can be a good plant choice for phytoremediation of co-contaminated soils.

Detection of Salmonella enterica Serovar Typhimurium by Using a Rapid, Array-Based Immunosensor

PubMed Central

Taitt, Chris Rowe; Shubin, Yura S.; Angel, Roselina; Ligler, Frances S.

2004-01-01

The multianalyte array biosensor (MAAB) is a rapid analysis instrument capable of detecting multiple analytes simultaneously. Rapid (15-min), single-analyte sandwich immunoassays were developed for the detection of Salmonella enterica serovar Typhimurium, with a detection limit of 8 × 104 CFU/ml; the limit of detection was improved 10-fold by lengthening the assay protocol to 1 h. S. enterica serovar Typhimurium was also detected in the following spiked foodstuffs, with minimal sample preparation: sausage, cantaloupe, whole liquid egg, alfalfa sprouts, and chicken carcass rinse. Cross-reactivity tests were performed with Escherichia coli and Campylobacter jejuni. To determine whether the MAAB has potential as a screening tool for the diagnosis of asymptomatic Salmonella infection of poultry, chicken excretal samples from a private, noncommercial farm and from university poultry facilities were tested. While the private farm excreta gave rise to signals significantly above the buffer blanks, none of the university samples tested positive for S. enterica serovar Typhimurium without spiking; dose-response curves of spiked excretal samples from university-raised poultry gave limits of detection of 8 × 103 CFU/g. PMID:14711637

Cortical activity patterns predict robust speech discrimination ability in noise

PubMed Central

Shetake, Jai A.; Wolf, Jordan T.; Cheung, Ryan J.; Engineer, Crystal T.; Ram, Satyananda K.; Kilgard, Michael P.

2012-01-01

The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds. We tested speech sound discrimination in rats and recorded primary auditory cortex (A1) responses to speech sounds in background noise of different intensities and spectral compositions. Our behavioral results indicate that rats, like humans, are able to accurately discriminate consonant sounds even in the presence of background noise that is as loud as the speech signal. Our neural recordings confirm that speech sounds evoke degraded but detectable responses in noise. Finally, we developed a novel neural classifier that mimics behavioral discrimination. The classifier discriminates between speech sounds by comparing the A1 spatiotemporal activity patterns evoked on single trials with the average spatiotemporal patterns evoked by known sounds. Unlike classifiers in most previous studies, this classifier is not provided with the stimulus onset time. Neural activity analyzed with the use of relative spike timing was well correlated with behavioral speech discrimination in quiet and in noise. Spike timing information integrated over longer intervals was required to accurately predict rat behavioral speech discrimination in noisy conditions. The similarity of neural and behavioral discrimination of speech in noise suggests that humans and rats may employ similar brain mechanisms to solve this problem. PMID:22098331

Performance comparison of extracellular spike sorting algorithms for single-channel recordings.

PubMed

Wild, Jiri; Prekopcsak, Zoltan; Sieger, Tomas; Novak, Daniel; Jech, Robert

2012-01-30

Proper classification of action potentials from extracellular recordings is essential for making an accurate study of neuronal behavior. Many spike sorting algorithms have been presented in the technical literature. However, no comparative analysis has hitherto been performed. In our study, three widely-used publicly-available spike sorting algorithms (WaveClus, KlustaKwik, OSort) were compared with regard to their parameter settings. The algorithms were evaluated using 112 artificial signals (publicly available online) with 2-9 different neurons and varying noise levels between 0.00 and 0.60. An optimization technique based on Adjusted Mutual Information was employed to find near-optimal parameter settings for a given artificial signal and algorithm. All three algorithms performed significantly better (p<0.01) with optimized parameters than with the default ones. WaveClus was the most accurate spike sorting algorithm, receiving the best evaluation score for 60% of all signals. OSort operated at almost five times the speed of the other algorithms. In terms of accuracy, OSort performed significantly less well (p<0.01) than WaveClus for signals with a noise level in the range 0.15-0.30. KlustaKwik achieved similar scores to WaveClus for signals with low noise level 0.00-0.15 and was worse otherwise. In conclusion, none of the three compared algorithms was optimal in general. The accuracy of the algorithms depended on proper choice of the algorithm parameters and also on specific properties of the examined signal. Copyright © 2011 Elsevier B.V. All rights reserved.

Levetiracetam reduces the frequency of interictal epileptiform discharges during NREM sleep in children with ADHD.

PubMed

Bakke, Kristin A; Larsson, Pål G; Eriksson, Ann-Sofie; Eeg-Olofsson, Orvar

2011-11-01

Symptoms of attention deficit hyperactivity disorder (ADHD) are more common in children with epilepsy than in the general paediatric population. Epileptiform discharges in EEG may be seen in children with ADHD also in those without seizure disorders. Sleep enhances these discharges which may be suppressed by levetiracetam. To assess the effect of levetiracetam on focal epileptiform discharges during sleep in children with ADHD. In this retrospective study a new semi-automatic quantitative method based on the calculation of spike index in 24-h ambulatory EEG recordings was applied. Thirty-five ADHD children, 17 with focal epilepsy, one with generalised epilepsy, and 17 with no seizure disorder were evaluated. Follow-up 24-h EEG recordings were performed after a median time of four months. Mean spike index was 50 prior to levetiracetam treatment and 21 during treatment. Seventeen children had no focal interictal epileptiform discharges in EEG at follow-up. Five children had a more than 50% reduction in spike index. Thus, a more than 50% reduction in spike index was found in 22/35 children (63%). Out of these an improved behaviour was noticed in 13 children (59%). This study shows that treatment with levetiracetam reduces interictal epileptiform discharges in children with ADHD. There is a complex relationship between epilepsy, ADHD and epileptiform activity, why it is a need for prospective studies in larger sample sizes, also to ascertain clinical benefits. Copyright © 2011 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

Nonlinear Dynamic Modeling of Neuron Action Potential Threshold During Synaptically Driven Broadband Intracellular Activity

PubMed Central

Roach, Shane M.; Song, Dong; Berger, Theodore W.

2012-01-01

Activity-dependent variation of neuronal thresholds for action potential (AP) generation is one of the key determinants of spike-train temporal-pattern transformations from presynaptic to postsynaptic spike trains. In this study, we model the nonlinear dynamics of the threshold variation during synaptically driven broadband intracellular activity. First, membrane potentials of single CA1 pyramidal cells were recorded under physiologically plausible broadband stimulation conditions. Second, a method was developed to measure AP thresholds from the continuous recordings of membrane potentials. It involves measuring the turning points of APs by analyzing the third-order derivatives of the membrane potentials. Four stimulation paradigms with different temporal patterns were applied to validate this method by comparing the measured AP turning points and the actual AP thresholds estimated with varying stimulation intensities. Results show that the AP turning points provide consistent measurement of the AP thresholds, except for a constant offset. It indicates that 1) the variation of AP turning points represents the nonlinearities of threshold dynamics; and 2) an optimization of the constant offset is required to achieve accurate spike prediction. Third, a nonlinear dynamical third-order Volterra model was built to describe the relations between the threshold dynamics and the AP activities. Results show that the model can predict threshold accurately based on the preceding APs. Finally, the dynamic threshold model was integrated into a previously developed single neuron model and resulted in a 33% improvement in spike prediction. PMID:22156947

[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.

Importance of equilibration time in the partitioning and toxicity of zinc in spiked sediment bioassays

USGS Publications Warehouse

Lee, J.-S.; Lee, B.-G.; Luoma, S.N.; Yoo, H.

2004-01-01

The influences of spiked Zn concentrations (1-40 ??mol/g) and equilibration time (???95 d) on the partitioning of Zn between pore water (PW) and sediment were evaluated with estuarine sediments containing two levels (5 and 15 ??mol/g) of acid volatile sulfides (AVS). Their influence on Zn bioavailability was also evaluated by a parallel, 10-d amphipod (Leptocheirus plumulosus) mortality test at 5, 20, and 85 d of equilibration. During the equilibration, AVS increased (up to twofold) with spiked Zn concentration ([Zn]), whereas Zn-simultaneously extracted metals ([SEM]; Zn with AVS) remained relatively constant. Concentrations of Zn in PW decreased most rapidly during the initial 30 d and by 11- to 23-fold during the whole 95-d equilibration period. The apparent partitioning coefficient (Kpw, ratio of [Zn] in SEM to PW) increased by 10- to 20-fold with time and decreased with spiked [Zn] in sediments. The decrease of PW [Zn] could be explained by a combination of changes in AVS and redistribution of Zn into more insoluble phases as the sediment aged. Amphipod mortality decreased significantly with the equilibration time, consistent with decrease in dissolved [Zn]. The median lethal concentration (LC50) value (33 ??M) in the second bioassay, conducted after 20 d of equilibration, was twofold the LC50 in the initial bioassay at 5 d of equilibration, probably because of the change of dissolved Zn speciation. Sediment bioassay protocols employing a short equilibration time and high spiked metal concentrations could accentuate partitioning of metals to the dissolved phase and shift the pathway for metal exposure toward the dissolved phase.