Situated Neural Representations: Solving the Problems of Content.
Frontiers in neurorobotics January 1, 2022 Peer reviewed DOI: 10.3389/fnbot.2022.846979 via PubMed
Summary
Situated approaches to cognition emphasize that thinking is embodied, embedded, enactive, and affective, often contrasting with computational and representational views. This work argues that situatedness and neural representation are deeply intertwined rather than opposites. A neurocomputational account of cognition is introduced that relies on neural representations but requires embodiment, embeddedness, enaction, and affect at its core.
Study at a glance
| Design | theoretical or philosophical paper |
|---|---|
| Key finding | Situatedness is needed for a satisfactory account of neural representation, enabling original semantic content, coordinated processing, causal efficacy, determinate content, distal representation, and misrepresentation. |
Abstract
Situated approaches to cognition maintain that cognition is embodied, embedded, enactive, and affective (and extended, but that is not relevant here). Situated approaches are often pitched as alternatives to computational and representational approaches, according to which cognition is computation over representations. I argue that, far from being opposites, situatedness and neural representation are more deeply intertwined than anyone suspected. To show this, I introduce a neurocomputational account of cognition that relies on neural representations. I argue not only that this account is compatible with (non-question-begging) situated approaches, but also that it requires embodiment, embeddedness, enaction, and affect at its very core. That is, constructing neural representations and their semantic content, and learning computational processes appropriate for their content, requires a tight dynamic interaction between nervous system, body, and environment. Most importantly, I argue that situatedness is needed to give a satisfactory account of neural representation: neurocognitive systems that are embodied, embedded, affective, dynamically interact with their environment, and use feedback from their interaction to shape their own representations and computations (1) can construct neural representations with original semantic content, (2) their neural vehicles and the way they are processed are automatically coordinated with their content, (3) such content is causally efficacious, (4) is determinate enough for the system's purposes, (5) represents the distal stimulus, and (6) can misrepresent. This proposal hints at what is needed to build artifacts with some of the basic cognitive capacities possessed by neurocognitive systems.