Multiple neural spike train data analysis: state-of-the-art and future challenges
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Erythropoietin enhances hippocampal long-term potentiation and memoryA Granger causality measure for point process models of ensemble neural spiking activityLarge-scale recording of neuronal ensemblesEffects of random external background stimulation on network synaptic stability after tetanization: a modeling studyTheta rhythms coordinate hippocampal-prefrontal interactions in a spatial memory taskProcessing and Analysis of Multichannel Extracellular Neuronal Signals: State-of-the-Art and ChallengesA neural network model of reliably optimized spike transmissionThe BRAIN Initiative: developing technology to catalyse neuroscience discovery.Encoding of both analog- and digital-like behavioral outputs by one C. elegans interneuronAttracting dynamics of frontal cortex ensembles during memory-guided decision-makingAutonomous head-mounted electrophysiology systems for freely behaving primates.A method for selecting the bin size of a time histogramData-driven inference of network connectivity for modeling the dynamics of neural codes in the insect antennal lobeThe neural decoding toolboxMultiplexed, high density electrophysiology with nanofabricated neural probesState-space analysis of time-varying higher-order spike correlation for multiple neural spike train dataModels of Neuronal Stimulus-Response Functions: Elaboration, Estimation, and Evaluation.Interpreting neurodynamics: concepts and facts.Analysis of complex neural circuits with nonlinear multidimensional hidden state models.Automatic online spike sorting with singular value decomposition and fuzzy C-mean clusteringTransient neuronal correlations underlying goal selection and maintenance in prefrontal cortex.A toolbox for the fast information analysis of multiple-site LFP, EEG and spike train recordings.Region-specific network plasticity in simulated and living cortical networks: comparison of the center of activity trajectory (CAT) with other statistics.Subspace projection approaches to classification and visualization of neural network-level encoding patternsGibbs distribution analysis of temporal correlations structure in retina ganglion cells.Algorithms for the analysis of ensemble neural spiking activity using simultaneous-event multivariate point-process modelsDetermining the role of correlated firing in large populations of neurons using white noise and natural scene stimuliStatistical issues in the analysis of neuronal data.Data-robust tight lower bounds to the information carried by spike times of a neuronal population.A Framework for the Comparative Assessment of Neuronal Spike Sorting Algorithms towards More Accurate Off-Line and On-Line Microelectrode Arrays Data AnalysisArmed-conflict risks enhanced by climate-related disasters in ethnically fractionalized countriesImproving data quality in neuronal population recordings.Common-input models for multiple neural spike-train data.Robust Estimation of Sparse Narrowband Spectra from Binary Neuronal Spiking Data.Data-driven significance estimation for precise spike correlationA new look at state-space models for neural data.Hierarchical Bayesian modeling and Markov chain Monte Carlo sampling for tuning-curve analysis.Methods for implantation of micro-wire bundles and optimization of single/multi-unit recordings from human mesial temporal lobe.Inferring eye position from populations of lateral intraparietal neurons.Statistical inference for assessing functional connectivity of neuronal ensembles with sparse spiking data.
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P2860
Multiple neural spike train data analysis: state-of-the-art and future challenges
description
2004 nî lūn-bûn
@nan
2004 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2004 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2004年の論文
@ja
2004年論文
@yue
2004年論文
@zh-hant
2004年論文
@zh-hk
2004年論文
@zh-mo
2004年論文
@zh-tw
2004年论文
@wuu
name
Multiple neural spike train data analysis: state-of-the-art and future challenges
@ast
Multiple neural spike train data analysis: state-of-the-art and future challenges
@en
Multiple neural spike train data analysis: state-of-the-art and future challenges
@en-gb
Multiple neural spike train data analysis: state-of-the-art and future challenges
@nl
type
label
Multiple neural spike train data analysis: state-of-the-art and future challenges
@ast
Multiple neural spike train data analysis: state-of-the-art and future challenges
@en
Multiple neural spike train data analysis: state-of-the-art and future challenges
@en-gb
Multiple neural spike train data analysis: state-of-the-art and future challenges
@nl
prefLabel
Multiple neural spike train data analysis: state-of-the-art and future challenges
@ast
Multiple neural spike train data analysis: state-of-the-art and future challenges
@en
Multiple neural spike train data analysis: state-of-the-art and future challenges
@en-gb
Multiple neural spike train data analysis: state-of-the-art and future challenges
@nl
P2860
P3181
P356
P1433
P1476
Multiple neural spike train data analysis: state-of-the-art and future challenges
@en
P2093
Robert E Kass
P2860
P2888
P304
P3181
P356
10.1038/NN1228
P407
P577
2004-05-01T00:00:00Z
P5875
P6179
1028259697