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From generative models to generative passages: a computational approach to (Neuro) phenomenology

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Version 2 2023-06-12, 07:47
Version 1 2023-06-10, 03:16
journal contribution
posted on 2023-06-12, 07:47 authored by Maxwell J D Ramstead, Anil SethAnil Seth, Casper Hesp, Lars Sandved-Smith, Jonas Mago, Michael Lifshitz, Giuseppe Pagnoni, Ryan Smith, Guillaume Dumas, Antoine Lutz, Karl Friston, Axel Constant
This paper presents a version of neurophenomenology based on generative modelling techniques developed in computational neuroscience and biology. Our approach can be described as computational phenomenology because it applies methods originally developed in computational modelling to provide a formal model of the descriptions of lived experience in the phenomenological tradition of philosophy (e.g., the work of Edmund Husserl, Maurice Merleau-Ponty, etc.). The first section presents a brief review of the overall project to naturalize phenomenology. The second section presents and evaluates philosophical objections to that project and situates our version of computational phenomenology with respect to these projects. The third section reviews the generative modelling framework. The final section presents our approach in detail. We conclude by discussing how our approach differs from previous attempts to use generative modelling to help understand consciousness. In summary, we describe a version of computational phenomenology which uses generative modelling to construct a computational model of the inferential or interpretive processes that best explain this or that kind of lived experience.

History

Publication status

  • Published

File Version

  • Published version

Journal

Review of Philosophy and Psychology

ISSN

1878-5158

Publisher

Springer

Department affiliated with

  • Informatics Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2022-04-29

First Open Access (FOA) Date

2022-04-29

First Compliant Deposit (FCD) Date

2022-04-29

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