Abstract
This paper proposes an account of neurocognitive activity without leveraging the notion of neural representation. Neural representation is a concept that results from assuming that the properties of the models used in computational cognitive neuroscience (e.g., information, representation, etc.) must literally exist the system being modelled (e.g., the brain). Computational models are important tools to test a theory about how the collected data (e.g., behavioural or neuroimaging) has been generated. While the usefulness of computational models is unquestionable, it does not follow that neurocognitive activity should literally entail the properties construed in the model (e.g., information, representation). While this is an assumption present in computationalist accounts, it is not held across the board in neuroscience. In the last section, the paper offers a dynamical account of neurocognitive activity with Dynamical Causal Modelling (DCM) that combines dynamical systems theory (DST) mathematical formalisms with the theoretical contextualisation provided by Embodied and Enactive Cognitive Science (EECS).
Highlights
In his seminal paper in 1995, Van Gelder (1995) asked, ‘what might cognition be, if not computation’
This paper rejected the analogy between neurocognitive activity and a computer
It was shown that the analogy results from assuming that the properties of the models used in computational cognitive neuroscience must exist in the system being modelled
Summary
In his seminal paper in 1995, Van Gelder (1995) asked, ‘what might cognition be, if not computation’. While the two main modelling techniques are motivated by different theoretical assumptions, they set off completely different paradigms tackling different questions (how vs why processes occur), subject matters (topology vs causes), and elucidation goals (description vs explanation), respectively Both models, aim to solve a common problem: to explain how the data has been generated. Cognitive scientists applied this form of computing to explain the nervous system (and linked cognitive activity) in a model called Parallel Distributed Processing (PDP) (McClelland and Rumelhart, 1986).7 These were the early days of neural networks (Cowan, 1990). P3: The system maintains itself by being congruent with the medium
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