Brain ResearchSeptember 7, 2026Eleni Kroupi, Helena Araujo, Cas Oosterveld et al.
N,N-Dimethyltryptamine (DMT), a potent serotonin-2A receptor agonist, elicits intense psychedelic experiences and has become a focus of interest in neuroscience and mental health research. While EEG studies of psychedelics typically report reduced alpha power, increased delta power, and enhanced signal complexity-primarily assessed using Lempel-Ziv complexity (LZc)-less is known about DMT's...
We state clean consistency constraints on any descriptive (structural) mathematical theory of phenomenal consciousness. Let the configuration space \(U\) of physically realizable systems be connected (under admissible deformations) and let a descriptive theory deliver a symmetry\-invariant scalar \(p:U [0,1]\) (a ``phenomenality score'') together with an optional crisp classifier \(P= {1}\{p...
The phenomenon of “pure awareness”, central to many contemplative traditions, has recently attracted scientific interest for its relevance to the study of consciousness. In this paper, we investigate pure awareness through the algorithmic agent model, a computational framework with roots in algorithmic information theory. This framework proposes that agents build compressive models of the...
This document provides a self-contained overview of the Kolmogorov Theory (KT) of consciousness---a research program spanning over two decades (2000--2026) that grounds the study of cognition, agency, and structured experience in Algorithmic Information Theory (AIT). KT proposes that brains and, more generally, algorithmic agents build and run compressive models of the world, and that the...
Despite divergent behavioral and phenomenological profiles, both psychedelic states and reduced states of consciousness have been associated with a flattening of the brain's functional hierarchy. To address this apparent paradox, we developed a more specific definition of hierarchy based on the proximity of the brain to thermodynamic equilibrium and then applied it to investigate the changes to...
Advanced meditation offers a powerful lens for investigating consciousness and for understanding how sustained training may contribute to human flourishing. In the spirit of neurophenomenology, we combine first-person reports with model-free empirical analyses and formal whole-brain modeling to investigate the mechanisms underlying advanced meditative states and minimal phenomenal experience...
The Complexity of Consciousness and Orch OR Orch OR states that phenomena such as the discrete perception of time unfolding, the subjective wholeness of perception, spatio-temporal binding, causal free will [28], mechanisms of anesthesia, and the so-called "hard problem" are explainable aspects of consciousness. It organizes these phenomena within a systematic framework capable of explaining...
Abstract Predictive coding frameworks suggest that neural computations rely on hierarchical error minimization, where sensory signals are evaluated against internal model predictions. However, the neural implementation of this inference process remains unclear. We propose that cross-frequency coupling (CFC) furnishes a fundamental mechanism for this form of inference. We first demonstrate that...
In the Kolmogorov Theory of Consciousness, algorithmic agents utilize inferred compressive models to track coarse-grained data produced by simplified world models, capturing regularities that structure subjective experience and guide action planning. Here, we study the dynamical aspects of this framework by examining how the requirement of tracking natural data drives the structural and...
Abstract Classical serotonergic psychedelics show promise in addressing neurodegenerative disorders such as Alzheimer’s disease by modulating pathological brain dynamics. However, the precise neurobiological mechanisms underlying their effects remain elusive. This study introduces a personalized whole-brain model built upon a laminar neural mass framework to elucidate these effects. Using...
Major Depressive Disorder (MDD) is a complex, heterogeneous condition affecting millions worldwide. Computational neuropsychiatry offers potential breakthroughs through the mechanistic modeling of this disorder. Using the Kolmogorov theory (KT) of consciousness, we developed a foundational model where algorithmic agents interact with the world to maximize an Objective Function evaluating...
We explore the intersection of neural dynamics and the effects of psychedelics in light of distinct timescales in a framework integrating concepts from dynamics, complexity, and plasticity. We call this framework neural geometrodynamics for its parallels with general relativity’s description of the interplay of spacetime and matter. The geometry of trajectories within the dynamical landscape of...
A topic of growing interest in computational neuroscience is the discovery of fundamental principles underlying global dynamics and the self-organization of the brain. In particular, the notion that the brain operates near criticality has gained considerable support, and recent work has shown that the dynamics of different brain states may be modeled by pairwise maximum entropy Ising models at...
Here we discuss the impact of issues recently raised about theories of consciousness in light of the so-called "unfolding argument" and the more general falsification requirements on causal structure theories of consciousness. These arguments potentially affect the algorithmic information theory of consciousness (KT), where the structure of a computational system is seen to shape subjective...
We present a unifying framework to study consciousness based on algorithmic information theory (AIT). We take as a premise that ``there is experience'' and focus on the requirements for structured experience (S)--- the spatial, temporal, and conceptual organization of our first-person experience of the world and of ourselves as agents in it. Our starting point is the insight that access to good...
We aimed at characterizing, in non-invasive human brain recordings, the large-scale, coordinated activation of distant brain regions thought to occur during conscious perception. This process is termed ignition in the Global Workspace Theory, and integration in Integrated Information Theory, which are two of the major theories of consciousness. Here, we provide evidence for this process in...
In this work, we aim to investigate whether information based metrics of neural activity are a useful tool for the quantification of consciousness before and shortly after birth. Neural activity is measured using fetal magnetoencephalography (fMEG) in human fetuses and neonates. Based on recent theories on consciousness, information-based metrics are established to measure brain complexity and...
Providing objective metrics of conscious state is of great interest across multiple research and clinical fields-from neurology to artificial intelligence. Here we approach this challenge by proposing plausible mechanisms for the phenomenon of structured experience. In earlier work, we argued that the experience we call reality is a mental construct derived from information compression. Here we...