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Multi-area functional modules mediate feedforward and recurrent processing in visual cortical hierarchy
[article]
2020
bioRxiv
pre-print
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Here, we characterize spiking interactions in populations of neurons from six interconnected areas along the visual hierarchy in awake mice. ...
The visual cortex is organized hierarchically, but extensive recurrent pathways make it challenging to decipher the flow of information with single neuron resolution. ...
First, we constructed a co-clustering association matrix by running k-means with different initial conditions 100 times (reached stable co-clustering). ...
doi:10.1101/2020.08.30.272948
fatcat:aal7fi6ding7dmwzrtd2shsx7e
High-frequency broadband modulation of electroencephalographic spectra
2009
Frontiers in Human Neuroscience
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may be differentially associated with brain sources and cognitive activities. ...
Thus, contrary to prevalent assumption, unitary modes of spectral modulation of frequencies encompassing the beta, gamma, and high gamma frequency ranges can be isolated from scalp-recorded EEG data and ...
Value-sorted time course correlations of all within-subject IM pairs for each pair of IM clusters. ...
doi:10.3389/neuro.09.061.2009
pmid:20076775
pmcid:PMC2806183
fatcat:gbugnbcnhbhz5e3alo2hpejbd4
Frontal midline EEG dynamics during working memory
2005
NeuroImage
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The process accounting for the fmQ increase during working memory was separated from 71-channel data by clustering on time/frequency transforms of components returned by independent component analysis ...
Dipole models of fmQ component scalp maps were consistent with their generation in or near dorsal anterior cingulate cortex. ...
Component clustering To identify clusters of similar independent EEG components based on similarity of their dominant activity patterns, the positive-valued single-trial weights for each component in each ...
doi:10.1016/j.neuroimage.2005.04.014
pmid:15927487
fatcat:3l2zakhxgbbihe53d4whoe6uqu
Identifying Functional Connectivity in Large-Scale Neural Ensemble Recordings: A Multiscale Data Mining Approach
2009
Neural Computation
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We then use a probabilistic spectral clustering algorithm to cluster the neurons in the graph by solving a minimum graph cut optimization problem. ...
This letter suggests a new approach to identify functional connectivity between neuronal elements from their simultaneously recorded spike trains. ...
A sample undirected graph with four objects and arbitrary edge weights for which the spectral clustering algorithm clusters objects with strong similarity (a small edge weight indicates stronger similarity ...
doi:10.1162/neco.2008.09-07-606
pmid:19431266
pmcid:PMC2808693
fatcat:n7x6w6x2inehjc3qtnr4zxxs6i
Spectrotemporal Structure of Receptive Fields in Areas AI and AAF of Mouse Auditory Cortex
2003
Journal of Neurophysiology
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Spectral properties of AI and AAF receptive fields were more similar, although STRF bandwidths were slightly broader in AI than in AAF. ...
Both analyses revealed temporal differences between AI and AAF responses: peak latencies and receptive-field durations for STRFs and first-spike latencies for responses to tone bursts were significantly ...
Kvale for helpful comments on the manuscript and for the use of spike-sorting user interface software, and B. Bonham for the use of frequency-intensity tuning curve analysis software. J. F. ...
doi:10.1152/jn.00751.2002
pmid:12815016
fatcat:gosr353nijecrgp3o7y2fancwq
Phase-specific pooling of sparse assembly activity by respiration-related brain oscillations
[article]
2021
bioRxiv
pre-print
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The spike train matrix z was constructed by convolving each neuron's spike train with a Gaussian kernel (standard deviation 7.2 ms). ...
The association of interneurons with assembly patterns was tested by first z-scoring the convolved interneuron spike trains. ...
doi:10.1101/2021.06.09.447658
fatcat:zzectveienha5a3grq37kvdqga
A review on cluster estimation methods and their application to neural spike data
2018
Journal of Neural Engineering
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Lai et al (2011) used single linkage clustering based on grey relational grade (GRG) to sort spike data. ...
Chah et al (2011) used the PBM index to obtain the optimum number of clusters for their automatics spike sorting methods based on feature extraction of Laplacian eigenmaps with k-means clustering. ...
doi:10.1088/1741-2552/aab385
pmid:29498353
fatcat:vx32ydpw4nezxcnuvydk6gxvfu
A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas
2018
PLoS Computational Biology
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Activity propagates down the visual hierarchy, similar to experimental results associated with visual imagery. ...
We present a multi-scale spiking network model of all vision-related areas of macaque cortex that represents each area by a full-scale microcircuit with area-specific architecture. ...
The matrix elements are sorted according to simulated clusters determined with the Louvain algorithm [112] (see Materials and methods). ...
doi:10.1371/journal.pcbi.1006359
pmid:30335761
pmcid:PMC6193609
fatcat:ltzaf6lohvejxk4ukkll5u7qay
Properties of Correlated Neural Activity Clusters in Cat Auditory Cortex Resemble Those of Neural Assemblies
2006
Journal of Neurophysiology
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Common-spike STRFs had higher signal-to-noise ratio than all-spike STRFs and showed generally spectral and temporal sharpening. ...
The pair-wise crosscorrelation matrix was constructed for the peak values of the correlograms. Hierarchical clustering was performed on the crosscorrelation matrix for six stimulus conditions. ...
This was also the case (P ϭ 0.0001) for the average number of inter-area R C based clusters (0.1 Ϯ 0.3) compared with weighted overlap based clusters (0.4 Ϯ 0.7). ...
doi:10.1152/jn.00059.2006
pmid:16835364
fatcat:o7mh2cy6czeijlpxbfalst32ca
Wavelet analysis in neurodynamics
2012
Physics Uspekhi
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Results obtained using continuous and discrete wavelet transforms as applied to problems in neurodynamics are reviewed, with the emphasis on the potential of wavelet analysis for decoding signal information ...
The detection and classification of various oscillatory patterns of brain electrical activity and the development of continuous wavelet-based brain activity monitoring systems are also discussed as possibilities ...
The weight (or scaling) factors S i are used as characteristics in spike sorting. ...
doi:10.3367/ufne.0182.201209a.0905
fatcat:nbxzthms5fggtbovzdbbp7gluu
Hidden Markov Models in the Neurosciences
[chapter]
2011
Hidden Markov Models, Theory and Applications
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By using stimulus-dependent clustering based on their measures, they determine how well the different classes of spike trains can be separated. ...
There is no need for preprocessing, such as spike identification, feature extraction or even manual inspection, all of which are error prone. HMM-based spike sorting is permissive to spike overlaps. ...
doi:10.5772/14183
fatcat:ukg5thd35zenblrpoiwvuqbumy
Using Local Spectral Methods to Robustify Graph-Based Learning Algorithms
2015
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15
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This is demonstrated by a study with predicting product categories from an Amazon co-purchasing network. ...
and densifying the graph through a matrix polynomial. ...
Let B be the unweighted edge-node incidence matrix, and let C be the corresponding diagonal matrix of weights associated with each edge. Thus, L = B T CB. ...
doi:10.1145/2783258.2783376
dblp:conf/kdd/GleichM15
fatcat:zuwb7yoao5dk3gqocynlpyaolq
Entrainment of Neocortical Neurons and Gamma Oscillations by the Hippocampal Theta Rhythm
2008
Neuron
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coordination of neocortical gamma oscillators by hippocampal theta is a mechanism by which information contained in spatially widespread neocortical assemblies can be synchronously transferred to the associative ...
Laminar analysis of neocortical gamma bursts revealed multiple gamma oscillators of varying frequency and location, which were spatially confined and synchronized local groups of neurons. ...
Variations in the sample size and contamination of spike train, and therefore a bias on the estimates of R, could arise from imperfect spike sorting. ...
doi:10.1016/j.neuron.2008.09.014
pmid:19038224
pmcid:PMC2640228
fatcat:gmz7e4szebbq7bqcr2b32phnqu
Local community detection based on network motifs
2019
Tsinghua Science and Technology
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Local community detection aims to find a cluster of nodes by exploring a small region of the network. ...
LCD-Motif adopts the local expansion of a seed set to identify the local community with minimal motif conductance, representing a generalization of the conductance metric for network motifs. ...
This is based on forcedirected embedding with motif-based weighting. (6) MAPPR [11] . ...
doi:10.26599/tst.2018.9010106
fatcat:aot32ypqtzg6tgp6mkoecvh2vq
An investigation of Hebbian phase sequences as assembly graphs
2014
Frontiers in Neural Circuits
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The results are compatible with a role for phase sequences in behavior and cognition. ...
Our findings agree with Hebb's view that assemblies correspond to primitive building blocks of representation, nearly unchanged in the adult, while phase sequences are labile across behavioral states and ...
Top panel shows the spike matrix (white circles mark co-activations of assembly neurons). ...
doi:10.3389/fncir.2014.00034
pmid:24782715
pmcid:PMC3986516
fatcat:u7rasdypzvfjxm4bon4ht24cpi
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