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Information Theory in Neural Coding and Decoding

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 620

Special Issue Editor

Institute of Cognitive Science and Technologies (ISTC), National Research Council (CNR) of Italy, Via Martiri della Libertà 2, 35137 Padova, Italy
Interests: neurocomputational modeling; machine learning; neural networks; active inference; visual perception; executive functions; spatial navigation; sensorimotor control; neural coding and decoding
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The hypothesis that the brain performs Bayesian inferential predictive processing to perceive the environment and conduct motor control by minimizing prediction errors is gaining an increasing popularity. In this view, perception continuously adds incoming sensory evidence to improve its estimate of the latent states of the world, reducing state-prediction errors. In turn, actions minimize prediction errors at the proprioceptive and at the external sensory level and further reduce latent-state uncertainty through exploration. This principle view about neural processing is embraced in several theories about perception and action - such as Predictive Coding and Active Inference - and makes strong predictions about the type of information content in the brain and its localization.

The special issue aims to aggregate novel theoretical and experimental research investigating this issue, critical reviews of theories, novel analyses of published data, and practical applications, with focus on information coding and decoding in the brain at the neural- and at the population level.

The topic is gaining growing popularity especially following the recent massive advance in machine learning that allowed empirical granular verification of such neural coding theories. Neural decoding receives recent strong attention also from practical point of view, with aims to further improve Brain Computer Interface systems and Artificial Intelligence agents.

Dr. Ivilin Peev Stoianov
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Computational Neuroscience
  • Cognitive Neuroscience
  • Predictive Coding
  • Active Inference
  • Information Theory methods
  • Dynamic inference
  • Deep Networks
  • Neural decoding
  • Brain Computer Interface
  • Artificial Intelligence

Published Papers

There is no accepted submissions to this special issue at this moment.
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