Pezzulo, Giovanni;
D'Amato, Leo;
Mannella, Francesco;
Priorelli, Matteo;
Van de Maele, Toon;
Stoianov, Ivilin Peev;
Friston, Karl;
(2024)
Neural representation in active inference: Using generative models to interact with-and understand-the lived world.
Annals of the New York Academy of Sciences
, 1534
(1)
pp. 45-68.
10.1111/nyas.15118.
Preview |
Text
Friston_Neural representation in active inference.pdf Download (1MB) | Preview |
Abstract
This paper considers neural representation through the lens of active inference, a normative framework for understanding brain function. It delves into how living organisms employ generative models to minimize the discrepancy between predictions and observations (as scored with variational free energy). The ensuing analysis suggests that the brain learns generative models to navigate the world adaptively, not (or not solely) to understand it. Different living organisms may possess an array of generative models, spanning from those that support action-perception cycles to those that underwrite planning and imagination; namely, from explicit models that entail variables for predicting concurrent sensations, like objects, faces, or people-to action-oriented models that predict action outcomes. It then elucidates how generative models and belief dynamics might link to neural representation and the implications of different types of generative models for understanding an agent's cognitive capabilities in relation to its ecological niche. The paper concludes with open questions regarding the evolution of generative models and the development of advanced cognitive abilities-and the gradual transition from pragmatic to detached neural representations. The analysis on offer foregrounds the diverse roles that generative models play in cognitive processes and the evolution of neural representation.
| Type: | Article |
|---|---|
| Title: | Neural representation in active inference: Using generative models to interact with-and understand-the lived world |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1111/nyas.15118 |
| Publisher version: | http://dx.doi.org/10.1111/nyas.15118 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | action‐oriented models, active inference, explicit models, generative model, neural representation, predictive coding |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10191719 |
Archive Staff Only
 |
View Item |
