An Overview of Bayesian Methods for Neural Spike Train Analysis
Neural spike train analysis is an important task in computational neuroscience which aims to understand neural mechanisms and gain insights into neural circuits. With the advancement of multielectrode recording and imaging technologies, it has become increasingly demanding to develop statistical too...
Main Author: | Chen, Zhe |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences |
Format: | Article |
Language: | English |
Published: |
Hindawi Publishing Corporation
2015
|
Online Access: | http://hdl.handle.net/1721.1/96120 |
Similar Items
-
Variational bayesian inference for point process generalized linear models in neural spike trains analysis
by: Chen, Zhe, et al.
Published: (2012) -
Signal Processing for Neural Spike Trains
by: Berger, Theodore W., et al.
Published: (2011) -
State-Space Analysis of Time-Varying Higher-Order Spike Correlation for Multiple Neural Spike Train Data
by: Shimazaki, Hideaki, et al.
Published: (2012) -
nSTAT: Open-source neural spike train analysis toolbox for Matlab
by: Cajigas, Iahn, et al.
Published: (2016) -
The Computational Structure of Spike Trains
by: Haslinger, Robert Heinz, et al.
Published: (2010)