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Computational Approaches and Modeling in Neuroscience

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Entropy and Biology".

Deadline for manuscript submissions: closed (15 November 2023) | Viewed by 6303

Special Issue Editors


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Guest Editor
Faculty of Natural Sciences, University of Stirling, Stirling FK9 4AL, UK
Interests: computational neuroscience; neuroinformatics; early auditory processing; artificial intelligence

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Guest Editor
Ecole Normale Superieure, Paris and Churchill College, University of Cambridge, Trinity Ln, Cambridge CB2 1TN, UK
Interests: computational neuroscience; modeling; biophysics; computational molecular and cellular biology; data modeling; analysis of cellular microdomains; stochastic simulations; analysis of large amount of time-series and single particle trajectories; super-resolution data analysis; reconstruction of chromatin organization from large matrices; analysis of long-time series of electrophysiological recordings and deconvolution of fluorescent indicators in neurons; predictive medicine algorithms: anoxic coma; EEG analysis; monitoring and short-term anesthesia prediction

Special Issue Information

Dear Colleagues,

Modelling neural systems using mathematics takes many forms, from programming systems to differential equations to discrete models. What is being modelled can vary from the molecular (modelling interactions between neurochemicals) to the microscopic (modelling ion channels or patches of membrane) to the cellular (modelling small numbers of neurons, or neural circuits) to larger scale (modelling large numbers of neurons) to full-scale brain modelling (modelling the interactions between brain areas). Furthermore, interest in models that bring together multiple levels is increasing.

The aims of these models can be just as varied. For example, the interest may be in modelling the system to better understand it (perhaps by modelling ground truth, where such data exist, or attempting to connect the model to existing mathematics such as information theory), or it may be in modelling the effect of a neurochemical; interest may also be clinical (for example, better understanding recalcitrant or refractory epilepsy or Parkinsonism, or modelling psychiatric effects).

The main topics of this Special Issue include (but are not limited to):

-mathematical and computational models of neural systems

-multi-level models of neural systems

-confirming neural models with ground truth data

Prof. Dr. Leslie S. Smith
Dr. David Holcman
Guest Editors

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.

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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

  • synapse/membrane/neural models
  • neural circuit models
  • brain modelling
  • discrete neural models
  • differential equation neural models
  • multi-level neural model
  • applications of neural models

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Published Papers (1 paper)

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Research

20 pages, 3391 KiB  
Article
From Black Holes Entropy to Consciousness: The Dimensions of the Brain Connectome
by Denis Le Bihan
Entropy 2023, 25(12), 1645; https://doi.org/10.3390/e25121645 - 11 Dec 2023
Cited by 1 | Viewed by 5947
Abstract
It has been shown that the theory of relativity can be applied physically to the functioning brain, so that the brain connectome should be considered as a four-dimensional spacetime entity curved by brain activity, just as gravity curves the four-dimensional spacetime of the [...] Read more.
It has been shown that the theory of relativity can be applied physically to the functioning brain, so that the brain connectome should be considered as a four-dimensional spacetime entity curved by brain activity, just as gravity curves the four-dimensional spacetime of the physical world. Following the most recent developments in modern theoretical physics (black hole entropy, holographic principle, AdS/CFT duality), we conjecture that consciousness can naturally emerge from this four-dimensional brain connectome when a fifth dimension is considered, in the same way that gravity emerges from a ‘flat’ four-dimensional quantum world, without gravitation, present at the boundaries of a five-dimensional spacetime. This vision makes it possible to envisage quantitative signatures of consciousness based on the entropy of the connectome and the curvature of spacetime estimated from data obtained by fMRI in the resting state (nodal activity and functional connectivity) and constrained by the anatomical connectivity derived from diffusion tensor imaging. Full article
(This article belongs to the Special Issue Computational Approaches and Modeling in Neuroscience)
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