Publication 4099

Allen M. & Friston K. (2016) From cognitivism to autopoiesis: Towards a computational framework for the embodied mind. Synthese : First Online. Fulltext at
Predictive processing (PP) approaches to the mind are increasingly popular in the cognitive sciences. This surge of interest is accompanied by a proliferation of philosophical arguments, which seek to either extend or oppose various aspects of the emerging framework. In particular, the question of how to position predictive processing with respect to enactive and embodied cognition has become a topic of intense debate. While these arguments are certainly of valuable scientific and philosophical merit, they risk underestimating the variety of approaches gathered under the predictive label. Here, we first present a basic review of neuroscientific, cognitive, and philosophical approaches to PP, to illustrate how these range from solidly cognitivist applications – with a firm commitment to modular, internalistic mental representation – to more moderate views emphasizing the importance of ‘body-representations’, and finally to those which fit comfortably with radically enactive, embodied, and dynamic theories of mind. Any nascent predictive processing theory (e.g., of attention or consciousness) must take into account this continuum of views, and associated theoretical commitments. As a final point, we illustrate how the Free Energy Principle (FEP) attempts to dissolve tension between internalist and externalist accounts of cognition, by providing a formal synthetic account of how internal ‘representations’ arise from autopoietic self-organization. The FEP thus furnishes empirically productive process theories (e.g., predictive processing) by which to guide discovery through the formal modelling of the embodied mind.


The publication is not yet part of any reading list

You cannot add this publication to a reading list because you are not member of any » Log in to create one.

There are currently no annotations

To add an annotation you need to log in first
Export bibliographic details as: CF Format · APA · BibTex · EndNote · Harvard · MLA · Nature · RIS · Science