![]() ![]() ![]() ![]() In the next two sections, we review the overall project to naturalize phenomenology. The structure of this paper is as follows. More precisely, we propose a model that maps phenomenological constitution onto the notion of inference, as it is used in generative modelling to infer the (causal) structure of the process generating some data or, more simply, making sense of data. We present a specific application of computational phenomenology to what phenomenological philosophers have called ‘constitution’, see Sokolowski ( 1964). Our approach represents a distinctive formulation of computational phenomenology because it applies methods from computational modelling directly to phenomenology. 1999 Varela 1997), based on methodological innovations that have emerged recently under the rubric of generative modelling (Friston 2019 Hesp et al. Specifically, we propose a new version of neurophenomenology as ‘generative passages’ (Lutz 2002 Roy et al. In this paper, we pursue the naturalization of phenomenology using modelling techniques developed in computational neuroscience and biology. 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. We conclude by discussing how our approach differs from previous attempts to use generative modelling to help understand consciousness. The final section presents our approach in detail. The third section reviews the generative modelling framework. The second section presents and evaluates philosophical objections to that project and situates our version of computational phenomenology with respect to these projects. The first section presents a brief review of the overall project to naturalize phenomenology. 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.). This paper presents a version of neurophenomenology based on generative modelling techniques developed in computational neuroscience and biology. ![]()
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