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Giulio Ruffini

17 papers in the library · 154 citations · publishing 2017-2026

Papers

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Formas persistentes: de Pitágoras a la Teoría de Kolmogorov

Zenodo (CERN European Organization for Nuclear Research) July 12, 2026 Giulio Ruffini

This work presents a structured theoretical framework for understanding mind, agency, and experience through the lens of algorithmic information theory, tracing a philosophical lineage from Pythagoras and Aristotle through Kant and Turing to Kolmogorov. The framework, designated KT-ESP, proposes that an agent can be modeled as an algorithmic entity that receives information, constructs...

Art as a Neuroplastogen

Zenodo (CERN European Organization for Nuclear Research) June 28, 2026 Giulio Ruffini, Francesca Castaldo

Pharmacological neuroplastogens---psilocybin, LSD, MDMA, ketamine---open transient windows of enhanced neural plasticity that can catalyze therapeutic change in mood disorders. Their mechanism, in the language of predictive processing, is to flatten high-level priors so that bottom-up prediction errors propagate freely and remodel the agent's generative model. We have argued, from first...

Consistency constraints on mathematical theories of phenomenal consciousness

Zenodo (CERN European Organization for Nuclear Research) June 28, 2026 Giulio Ruffini

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...

Art as Neuroplastogens

Zenodo (CERN European Organization for Nuclear Research) June 28, 2026 Giulio Ruffini, Francesca Castaldo

Pharmacological neuroplastogens---psychedelics, ketamine, MDMA---open transient windows of enhanced neural plasticity that can catalyze therapeutic change in mood disorders and beyond. Their clinical promise, however, is constrained by safety concerns, regulatory barriers, and unsuitability for vulnerable populations such as adolescents. Here we argue, from first principles within the...

An algorithmic agent model of pure awareness and minimal experiences

Philosophy and the Mind Sciences May 27, 2026 Edmundo Lopez-Sola, Roser Sanchez-Todo, Jakub Vohryzek et al. 1 citation

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...

Brain Dynamics of Classical Psychedelics Show Paradoxical Hierarchical Flattening With Increased Complexity

SSRN Electronic Journal 2026 Jakub Vohryzek, Elvira Garcia Guzman, Morten L. Kringelbach et al. 1 citation

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...

Whole-Brain Models of Advanced Concentrative Absorption Meditation: Approaching Critical Dynamics through Jhāna

bioRxiv September 25, 2025 Jakub Vohryzek, Edmundo Lopez-Sola, Winson F.z. Yang et al. preprint

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...

Cross-Frequency Coupling as a Neural Substrate for Prediction Error Evaluation: A Laminar Neural Mass Modeling Approach

bioRxiv (Cold Spring Harbor Laboratory) March 19, 2025 Giulio Ruffini, Edmundo Lopez-Sola, Raul P. Aristides et al. 8 citations preprint

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...

Structured Dynamics in the Algorithmic Agent.

Entropy (Basel, Switzerland) January 19, 2025 Giulio Ruffini, Francesca Castaldo, Jakub Vohryzek 6 citations

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...

Restoring Oscillatory Dynamics in Alzheimer’s Disease: A Laminar Whole-Brain Model of Serotonergic Psychedelic Effects

bioRxiv (Cold Spring Harbor Laboratory) December 16, 2024 Jan C. Gendra, Edmundo Lopez-Sola, Francesca Castaldo et al. 7 citations preprint

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...

The Algorithmic Agent Perspective and Computational Neuropsychiatry: From Etiology to Advanced Therapy in Major Depressive Disorder

Entropy November 6, 2024 Giulio Ruffini, Francesca Castaldo, Edmundo Lopez-Sola et al. 10 citations

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...

Neural Geometrodynamics, Complexity, and Plasticity: A Psychedelics Perspective

Entropy January 22, 2024 Giulio Ruffini, Edmundo Lopez-Sola, Jakub Vohryzek et al. 15 citations

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...

LSD-induced increase of Ising temperature and algorithmic complexity of brain dynamics.

PLoS Computational Biology February 1, 2023 Giulio Ruffini, Giada Damiani, Diego Lozano-Soldevilla et al. 28 citations

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...

Algorithmic structure of experience and the unfolding argument

August 30, 2022 Giulio Ruffini, Edmundo Lopez-Sola, Jakub Vohryzek 3 citations preprint

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...

Probing the circuits of conscious perception with magnetophosphenes.

Journal of Neural Engineering July 3, 2020 Julien Modolo, Mahmoud Hassan, Giulio Ruffini et al.

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...

Evaluating Complexity of Fetal MEG Signals: A Comparison of Different Metrics and Their Applicability.

Frontiers in Systems Neuroscience 2019 Julia Moser, Siouar Bensaid, Eleni Kroupi et al.

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...

An algorithmic information theory of consciousness

Neuroscience of Consciousness 2017 Giulio Ruffini 75 citations

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...