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...
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| Format: | Article |
| Language: | English |
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Hindawi Publishing Corporation
2015
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| Online Access: | http://hdl.handle.net/1721.1/96120 |
| _version_ | 1826201417017196544 |
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| author | Chen, Zhe |
| author2 | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences |
| author_facet | Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Chen, Zhe |
| author_sort | Chen, Zhe |
| collection | MIT |
| description | 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 tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed. |
| first_indexed | 2024-09-23T11:51:16Z |
| format | Article |
| id | mit-1721.1/96120 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T11:51:16Z |
| publishDate | 2015 |
| publisher | Hindawi Publishing Corporation |
| record_format | dspace |
| spelling | mit-1721.1/961202022-09-27T22:22:12Z An Overview of Bayesian Methods for Neural Spike Train Analysis Chen, Zhe Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Picower Institute for Learning and Memory Chen, Zhe 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 tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed. Mathematical Biosciences Institute at the Ohio State University (Early Career Award) National Science Foundation (U.S.) (NSF-IIS CRCNS (Collaborative Research in Computational Neuroscience) Grant 1307645) 2015-03-20T15:29:08Z 2015-03-20T15:29:08Z 2013 2013-09 2015-03-19T11:34:54Z Article http://purl.org/eprint/type/JournalArticle 1687-5265 1687-5273 http://hdl.handle.net/1721.1/96120 Chen, Zhe. “An Overview of Bayesian Methods for Neural Spike Train Analysis.” Computational Intelligence and Neuroscience 2013 (2013): 1–17. en http://dx.doi.org/10.1155/2013/251905 Computational Intelligence and Neuroscience Creative Commons Attribution http://creativecommons.org/licenses/by/2.0 Copyright © 2013 Zhe Chen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. application/pdf Hindawi Publishing Corporation Hindawi Publishing Corporation |
| spellingShingle | Chen, Zhe An Overview of Bayesian Methods for Neural Spike Train Analysis |
| title | An Overview of Bayesian Methods for Neural Spike Train Analysis |
| title_full | An Overview of Bayesian Methods for Neural Spike Train Analysis |
| title_fullStr | An Overview of Bayesian Methods for Neural Spike Train Analysis |
| title_full_unstemmed | An Overview of Bayesian Methods for Neural Spike Train Analysis |
| title_short | An Overview of Bayesian Methods for Neural Spike Train Analysis |
| title_sort | overview of bayesian methods for neural spike train analysis |
| url | http://hdl.handle.net/1721.1/96120 |
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