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Data-driven multiscale computational models of cortical and subcortical regions

Lookup NU author(s): Dr Srikanth RamaswamyORCiD

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Abstract

© 2024 Elsevier Ltd. Data-driven computational models of neurons, synapses, microcircuits, and mesocircuits have become essential tools in modern brain research. The goal of these multiscale models is to integrate and synthesize information from different levels of brain organization, from cellular properties, dendritic excitability, and synaptic dynamics to microcircuits, mesocircuits, and ultimately behavior. This article surveys recent advances in the genesis of data-driven computational models of mammalian neural networks in cortical and subcortical areas. I discuss the challenges and opportunities in developing data-driven multiscale models, including the need for interdisciplinary collaborations, the importance of model validation and comparison, and the potential impact on basic and translational neuroscience research. Finally, I highlight future directions and emerging technologies that will enable more comprehensive and predictive data-driven models of brain function and dysfunction.

Publication metadata

Author(s): Ramaswamy S

Publication type: Review

Publication status: Published

Journal: Current Opinion in Neurobiology

Year: 2024

Volume: 85

Print publication date: 01/04/2024

Online publication date: 05/02/2024

Acceptance date: 02/04/2018

ISSN (print): 0959-4388

ISSN (electronic): 1873-6882

Publisher: Elsevier Ltd

URL: https://doi.org/10.1016/j.conb.2024.102842

DOI: 10.1016/j.conb.2024.102842

PubMed id: 38320453

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