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Awareness as inference in a higher-order state space.

Stephen M Fleming1

  • 1Wellcome Centre for Human Neuroimaging, Institute of Neurology, 12 Queen Square, London WC1N 3AR, UK.

Neuroscience of Consciousness
|March 20, 2020
PubMed
Summary

This study proposes a computational framework for awareness reports, viewing them as metacognitive decisions. The model explains how simple, abstract internal states support subjective experience reports, aligning with brain imaging findings.

Keywords:
computational modelingconsciousnessmetacognitiontheories and models

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Area of Science:

  • Cognitive Neuroscience
  • Computational Psychiatry

Background:

  • Human subjective experience reporting is crucial but decision processes are poorly understood.
  • Existing models lack a comprehensive framework for awareness report generation.

Purpose of the Study:

  • To propose a computational framework for awareness reports.
  • To characterize awareness reports as metacognitive decisions within a generative model of perception.

Main Methods:

  • Developed a computational framework based on hierarchical state spaces and metacognitive inference.
  • Simulated a model with asymmetric internal states for awareness reports.
  • Compared model predictions with brain imaging data on global ignition.

Main Results:

  • Awareness reports are modeled as metacognitive decisions about a generative perceptual model.
  • Internal states for awareness are simple, abstract, and vary on a 1D continuum.
  • The proposed asymmetric architecture explains 'global ignition' phenomena in brain imaging.

Conclusions:

  • The framework provides a novel computational account of awareness reporting.
  • Metacognitive inference over generative models offers insights into subjective experience.
  • The model's asymmetry is key to understanding neural correlates of awareness.