Whole-brain models to explore altered states of consciousness from the bottom up

TL;DR

This paper proposes a bottom-up modeling approach using whole-brain models to understand the neural mechanisms underlying altered states of consciousness, linking large-scale connectivity with local neural dynamics.

Contribution

It introduces a research framework that bridges generative models of brain activity with consciousness signatures, advancing the understanding of altered states from a biophysical perspective.

Findings

Highlights the role of large-scale connectivity in altered consciousness

Proposes a systematic bottom-up modeling approach

Discusses potential insights into neural underpinnings of consciousness

Abstract

The scope of human consciousness includes states departing from what most of us experience as ordinary wakefulness. These altered states of consciousness constitute a prime opportunity to study how global changes in brain activity relate to different varieties of subjective experience. We consider the problem of explaining how global signatures of altered consciousness arise from the interplay between large-scale connectivity and local dynamical rules that can be traced to known properties of neural tissue. For this purpose, we advocate a research program aimed at bridging the gap between bottom-up generative models of whole-brain activity and the top-down signatures proposed by theories of consciousness. Throughout this paper, we define altered states of consciousness, discuss relevant signatures of consciousness observed in brain activity, and introduce whole-brain models to explore the mechanisms of altered consciousness from the bottom-up. We discuss the potential of our proposal in view of the current state of the art, give specific examples of how this research agenda might play out, and emphasise how a systematic investigation of altered states of consciousness via bottom-up modelling may help us better understand the biophysical, informational, and dynamical underpinnings of consciousness.