Computational methods to study information processing in neural circuits
The brain is an information processing machine and thus naturally lends itself to be studied using computational tools based on the principles of information theory. For this reason, computational methods based on or inspired by information theory have been a cornerstone of practical and conceptual...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-01-01
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| Series: | Computational and Structural Biotechnology Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037023000119 |
| _version_ | 1797384147132481536 |
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| author | Veronika Koren Giulio Bondanelli Stefano Panzeri |
| author_facet | Veronika Koren Giulio Bondanelli Stefano Panzeri |
| author_sort | Veronika Koren |
| collection | DOAJ |
| description | The brain is an information processing machine and thus naturally lends itself to be studied using computational tools based on the principles of information theory. For this reason, computational methods based on or inspired by information theory have been a cornerstone of practical and conceptual progress in neuroscience. In this Review, we address how concepts and computational tools related to information theory are spurring the development of principled theories of information processing in neural circuits and the development of influential mathematical methods for the analyses of neural population recordings. We review how these computational approaches reveal mechanisms of essential functions performed by neural circuits. These functions include efficiently encoding sensory information and facilitating the transmission of information to downstream brain areas to inform and guide behavior. Finally, we discuss how further progress and insights can be achieved, in particular by studying how competing requirements of neural encoding and readout may be optimally traded off to optimize neural information processing. |
| first_indexed | 2024-03-08T21:31:17Z |
| format | Article |
| id | doaj.art-7613b79f770d418e8bd667676a1adfcc |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-03-08T21:31:17Z |
| publishDate | 2023-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-7613b79f770d418e8bd667676a1adfcc2023-12-21T07:30:45ZengElsevierComputational and Structural Biotechnology Journal2001-03702023-01-0121910922Computational methods to study information processing in neural circuitsVeronika Koren0Giulio Bondanelli1Stefano Panzeri2Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Falkenried 94, Hamburg 20251, GermanyIstituto Italiano di Tecnologia, Via Melen 83, Genova 16152, ItalyDepartment of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Falkenried 94, Hamburg 20251, Germany; Istituto Italiano di Tecnologia, Via Melen 83, Genova 16152, Italy; Corresponding author at: Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Falkenried 94, Hamburg 20251, Germany.The brain is an information processing machine and thus naturally lends itself to be studied using computational tools based on the principles of information theory. For this reason, computational methods based on or inspired by information theory have been a cornerstone of practical and conceptual progress in neuroscience. In this Review, we address how concepts and computational tools related to information theory are spurring the development of principled theories of information processing in neural circuits and the development of influential mathematical methods for the analyses of neural population recordings. We review how these computational approaches reveal mechanisms of essential functions performed by neural circuits. These functions include efficiently encoding sensory information and facilitating the transmission of information to downstream brain areas to inform and guide behavior. Finally, we discuss how further progress and insights can be achieved, in particular by studying how competing requirements of neural encoding and readout may be optimally traded off to optimize neural information processing.http://www.sciencedirect.com/science/article/pii/S2001037023000119Information theoryEfficient codingNoise correlationsInformation encodingInformation transmissionComputational tools |
| spellingShingle | Veronika Koren Giulio Bondanelli Stefano Panzeri Computational methods to study information processing in neural circuits Computational and Structural Biotechnology Journal Information theory Efficient coding Noise correlations Information encoding Information transmission Computational tools |
| title | Computational methods to study information processing in neural circuits |
| title_full | Computational methods to study information processing in neural circuits |
| title_fullStr | Computational methods to study information processing in neural circuits |
| title_full_unstemmed | Computational methods to study information processing in neural circuits |
| title_short | Computational methods to study information processing in neural circuits |
| title_sort | computational methods to study information processing in neural circuits |
| topic | Information theory Efficient coding Noise correlations Information encoding Information transmission Computational tools |
| url | http://www.sciencedirect.com/science/article/pii/S2001037023000119 |
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