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The neuroconnectionist research programme.
Doerig, Adrien; Sommers, Rowan P; Seeliger, Katja; Richards, Blake; Ismael, Jenann; Lindsay, Grace W; Kording, Konrad P; Konkle, Talia; van Gerven, Marcel A J; Kriegeskorte, Nikolaus; Kietzmann, Tim C.
Afiliação
  • Doerig A; Institute of Cognitive Science, University of Osnabrück, Osnabrück, Germany. adoerig@uni-osnabrueck.de.
  • Sommers RP; Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands. adoerig@uni-osnabrueck.de.
  • Seeliger K; Department of Neurobiology of Language, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.
  • Richards B; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
  • Ismael J; Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada.
  • Lindsay GW; School of Computer Science, McGill University, Montréal, QC, Canada.
  • Kording KP; Mila, Montréal, QC, Canada.
  • Konkle T; Montréal Neurological Institute, Montréal, QC, Canada.
  • van Gerven MAJ; Learning in Machines and Brains Program, CIFAR, Toronto, ON, Canada.
  • Kriegeskorte N; Johns Hopkins University, Baltimore, MD, USA.
  • Kietzmann TC; New York University, New York, NY, USA.
Nat Rev Neurosci ; 24(7): 431-450, 2023 07.
Article em En | MEDLINE | ID: mdl-37253949
Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have been not only lauded as the current best models of information processing in the brain but also criticized for failing to account for basic cognitive functions. In this Perspective article, we propose that arguing about the successes and failures of a restricted set of current ANNs is the wrong approach to assess the promise of neuroconnectionism for brain science. Instead, we take inspiration from the philosophy of science, and in particular from Lakatos, who showed that the core of a scientific research programme is often not directly falsifiable but should be assessed by its capacity to generate novel insights. Following this view, we present neuroconnectionism as a general research programme centred around ANNs as a computational language for expressing falsifiable theories about brain computation. We describe the core of the programme, the underlying computational framework and its tools for testing specific neuroscientific hypotheses and deriving novel understanding. Taking a longitudinal view, we review past and present neuroconnectionist projects and their responses to challenges and argue that the research programme is highly progressive, generating new and otherwise unreachable insights into the workings of the brain.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Encéfalo / Redes Neurais de Computação Limite: Humans Idioma: En Revista: Nat Rev Neurosci Assunto da revista: NEUROLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Encéfalo / Redes Neurais de Computação Limite: Humans Idioma: En Revista: Nat Rev Neurosci Assunto da revista: NEUROLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha