Neuroscience of Consciousness
January 1, 2017
Giulio Ruffini
75 citations
Conscious experience can be understood as a mental construct arising from information compression. Using algorithmic information theory, specifically Kolmogorov complexity, provides a natural framework to quantify consciousness from brain data, assuming the brain's primary role is information processing. The theory hypothesizes that compressive models in cognitive systems, such as biological recurrent neural networks, enable structured phenomenal experience, with self-awareness emerging naturally as part of a better model in systems interacting bidirectionally with the world. This approach, called KT theory, is compared to other information-centric theories, and methods are described for studying brain complexity as a correlate of conscious state through input probing, spontaneous activity analysis, perturbation, and behavioral quantification.
PLoS computational biology
February 1, 2023
Giulio Ruffini, Giada Damiani, Diego Lozano-Soldevilla et al.
28 citations
Brain dynamics under LSD become more disordered and complex, moving further from the critical point that characterizes healthy brain function. Using Ising spin models fitted to fMRI data from fifteen participants, the authors show that LSD reduces interhemispheric connectivity, especially between corresponding regions in opposite hemispheres. Ising temperatures were significantly higher under LSD than placebo, indicating a shift into a more disordered (paramagnetic) state. Algorithmic complexity of brain activity, measured by block decomposition, correlated with both Ising temperature and condition, supporting the entropic brain hypothesis that psychedelics increase neural disorder.
Entropy
January 22, 2024
Giulio Ruffini, Edmundo Lopez-Sola, Jakub Vohryzek et al.
15 citations
A framework called neural geometrodynamics, inspired by general relativity, describes how neural dynamics unfold at three timescales: fast (momentary activity), slow (synaptic plasticity), and ultraslow (metaplasticity). Psychedelics flatten the neural landscape, increasing entropy and complexity of fast dynamics, which disrupts functional integration. This destabilization counteracts pathological, rigid neural patterns by promoting fluid, adaptable states. The plasticity-enhancing effects of psychedelics amplify this shift, leading to acute systemic disorder and potentially longer-lasting increases in complexity that affect both short-term dynamics and long-term plastic processes, offering a holistic view of psychedelics' acute and lasting impacts.
Entropy (Basel, Switzerland)
January 19, 2025
Giulio Ruffini, Francesca Castaldo, Jakub Vohryzek
6 citations
Tracking natural data forces an agent to mirror the symmetry properties of the generative world model, enforcing a hierarchical organization in the agent's neural network consistent with the manifold hypothesis. Using Lie pseudogroups to formalize invariance in natural data and drawing parallels to Noether's theorem, the study shows that data tracking constrains both the agent's constitutive parameters and dynamical repertoire. This bridges algorithmic information theory, symmetry, and dynamics, offering insights into neural correlates of agenthood and structured experience, as well as AI and brain model design.
Philosophy and the Mind Sciences
May 27, 2026
Edmundo Lopez-Sola, Roser Sanchez-Todo, Jakub Vohryzek et al.
1 citation
A computational framework rooted in algorithmic information theory, the algorithmic agent model, is used to investigate the phenomenon of pure awareness central to contemplative traditions. The framework proposes that agents build compressive models of the world, and structured experience arises from running such models. Pure awareness may correspond to experiences with minimal structure achieved through meditation, psychedelics, or other deconstructive practices, such as jhāna meditation. A key hypothesis is that the phenomenology of pure awareness arises from the agent's model of its own modeling process, and this recognition can occur alongside other phenomenal content, as in non-dual awareness. These ideas can be explored through whole-brain computational models based on predictive processing, grounded in meditation and psychedelic research.
bioRxiv (Cold Spring Harbor Laboratory)
December 22, 2024
Jakub Vohryzek, Morten L. Kringelbach, Edmundo Lopez-Sola et al.
1 citation
preprint
Both psychedelic states and reduced states of consciousness flatten the brain's functional hierarchy, yet their behavioral and phenomenological profiles differ. To resolve this paradox, researchers defined hierarchy by the brain's proximity to thermodynamic equilibrium and examined changes induced by three serotonergic psychedelics: psilocybin, LSD, and DMT. All three consistently reduced the functional hierarchy globally. Unlike loss of consciousness, psychedelics moved the brain toward equilibrium while increasing neural activity complexity, indicating a distinct mechanism involving altered configuration and differentiation of resting-state networks. This work demonstrates how statistical mechanics metrics can characterize different global brain states, advancing understanding of consciousness as an emergent collective process.
Zenodo (CERN European Organization for Nuclear Research)
June 28, 2026
Giulio Ruffini, Francesca Castaldo
Pharmacological neuroplastogens like psilocybin and LSD enhance neural plasticity by flattening high-level priors, allowing bottom-up prediction errors to remodel the brain's generative model. The same computational regime can be achieved non-pharmacologically through immersive algorithmic art held in a Goldilocks zone of compressibility. This approach is operationalized in a closed-loop digital therapeutic for adolescent depression. The argument extends to music, where harmonic tension serves as a prediction-error scaffold, and live performance with a chaos-harmony narrative arc. All three modalities sustain structured prediction error in the Goldilocks zone, transiently flatten the dynamical landscape, and push subjective phenomenology into territory typically associated with psychedelics like MDA, psilocybin, and LSD, as measured by altered states of consciousness and mystical experience instruments.
Zenodo (CERN European Organization for Nuclear Research)
June 28, 2026
Giulio Ruffini, Francesca Castaldo
Immersive algorithmic art may enhance neural plasticity through the same computational mechanism as psychedelics: sustained, structured prediction-error signaling. The brain's modeling engine generates predictions of sensory input; mismatches drive model updating via synaptic plasticity. Algorithmic art maximizes these errors while keeping stimuli in a compressible, emotionally rewarding "Goldilocks zone," creating a self-reinforcing loop of engagement, prediction error, plasticity, model updating, and positive valence. The hypothesis is formalized within Kolmogorov Theory, connected to the REBUS model, and supported by convergent evidence from psychedelic neuroimaging and predictive-coding electrophysiology. A translational pathway combining closed-loop EEG-driven algorithmic art with cognitive behavioral therapy for adolescent depression is outlined.
Zenodo (CERN European Organization for Nuclear Research)
June 28, 2026
Giulio Ruffini
A mathematical theory that assigns a continuous 'phenomenality score' to physical systems cannot produce a sharp yes/no classification of consciousness without a discontinuity somewhere. Any such scoring function that varies smoothly must take on intermediate values between zero and a positive threshold. Under certain smoothness conditions, the extreme scores of 0 and 1 are impossible to achieve. These results show that descriptive mathematical models of consciousness can identify boundaries but cannot explain why or how consciousness arises, consistent with the idea of an explanatory gap.