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Reflections on Simplicity and Complexity in Computational Neuroscience

Rajan K.
•
Treves A.
•
Gaudenzi R.
2025
  • journal article

Periodico
HUMAN ARENAS
Abstract
This double interview with two distinguished researchers in computational neuroscience, Kanaka Rajan and Alessandro Treves, aims to capture a part of their talks and discussions that emerged during a workshop on physical modelling of thought, held in Berlin in January 2023. The topic is the fascinating all-round intersection of physics and neuroscience through the perspectives of the interviewees. The dialogue traverses the complex terrain of modelling thought processes, shedding light on the trade-off between simplicity and complexity that defines the field of computational neuroscience. From the early days of physics-inspired brain models to the cutting-edge advancements in large language models, the interviewees share their journey, challenges, and insights into the modelling of physical and biological systems; they recount their experience with computational neuroscience, explore the impact of large language models on our understanding of human language and cognition, and speculate on the future directions of physics-inspired computational neuroscience, emphasising the importance of interdisciplinary collaboration and a deeper integration of complexity and detail in modelling the brain and its functions.
DOI
10.1007/s42087-024-00423-4
WOS
WOS:001251330600001
Archivio
https://hdl.handle.net/20.500.11767/141370
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85196396908
Diritti
open access
license:creative commons
license uri:http://creativecommons.org/licenses/by/4.0/
Soggetti
  • Modelling practices i...

  • Computational neurosc...

  • Physics modelling of ...

  • Large language models...

  • Settore PSIC-01/B - N...

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