Kernel density compression for real-time Bayesian encoding/decoding of unsorted hippocampal spikes-Reference-Cited by-同舟云学术

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Kernel density compression for real-time Bayesian encoding/decoding of unsorted hippocampal spikes

Published:2016-02 Issue: Volume:94 Page:1-12
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Sodkomkham Danaipat,Ciliberti Davide,Wilson Matthew A.,Fukui Ken-ichi,Moriyama Koichi,Numao Masayuki,Kloosterman Fabian

Funder

National Institute of Mental Health

Office of Naval Research MURI

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference46 articles.

1. A statistical paradigm for neural spike train decoding applied to position prediction from ensemble firing patterns of rat hippocampal place cells;Brown;J. Neurosci.,1998

2. Interpreting neuronal population activity by reconstruction: unified framework with application to hippocampal place cells;Zhang;J. Neurophysiol.,1998

3. Statistical models for neural encoding, decoding, and optimal stimulus design;Paninski;Progr. Brain Res.,2007

4. Predicting movement from multiunit activity;Stark;J. Neurosci.,2007

5. Spike train decoding without spike sorting;Ventura;Neural Comput.,2008

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