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
November 6, 2024
Giulio Ruffini, Francesca Castaldo, Edmundo Lopez-Sola et al.
10 citations
Major Depressive Disorder (MDD) is a complex condition that computational neuropsychiatry can help model mechanistically. Using the Kolmogorov theory of consciousness, a model was developed in which algorithmic agents interact with the world to maximize an Objective Function evaluating affective valence. Depression—defined as persistently low valence—may arise from inaccurate world models (cognitive biases), a dysfunctional Objective Function (anhedonia, anxiety), deficient planning (executive deficits), or unfavorable environments. The model maps to brain circuits and functional networks, linking with depression biotypes. Brain stimulation, psychotherapy, and psychedelics may synergistically repair neural circuits, with therapies optimized using personalized computational models.
bioRxiv (Cold Spring Harbor Laboratory)
March 19, 2025
Giulio Ruffini, Edmundo Lopez-Sola, Raul P. Aristides et al.
8 citations
preprint
Cross-frequency coupling (CFC), where brain rhythms at different speeds interact, may be the mechanism the brain uses to compare sensory input with internal predictions. Using a laminar neural mass model, the authors show that two forms of CFC—signal-envelope coupling and envelope-envelope coupling—can implement hierarchical prediction-error computation and precision-weighting. In Alzheimer's disease, disruptions in fast-spiking interneurons lead to aberrant prediction errors: inflated early on, then attenuated. Serotonergic psychedelics reduce the influence of predictions, increasing prediction-error signals. These findings suggest that CFC across multiple timescales is a key computational mechanism supporting predictive coding, with disruptions central to certain disorders.
bioRxiv (Cold Spring Harbor Laboratory)
December 16, 2024
Jan C. Gendra, Edmundo Lopez-Sola, Francesca Castaldo et al.
7 citations
preprint
Classical serotonergic psychedelics may help treat neurodegenerative disorders like Alzheimer's disease by altering pathological brain dynamics. Using multimodal neuroimaging data from thirty subjects with mild to moderate Alzheimer's disease, a personalized whole-brain model based on a laminar neural mass framework simulated the effects of serotonin 2A receptor activation. Modulating the excitability of layer 5 pyramidal neurons reproduced hallmark EEG changes seen under psychedelics, including alpha power suppression and gamma power enhancement. These spectral shifts correlated strongly with regional serotonin 2A receptor distribution. Simulated EEG also showed increased complexity and entropy, suggesting restored network function, offering mechanistic insights into potential therapeutic effects in early Alzheimer's disease.
August 30, 2022
Giulio Ruffini, Edmundo Lopez-Sola, Jakub Vohryzek
3 citations
preprint
The unfolding argument challenges causal structure theories of consciousness by requiring that a theory specify which physical systems are conscious and which are not. This paper examines how the algorithmic information theory of consciousness (KT), which links subjective experience to the structure of a computational system, is affected by this argument. Considering computational hierarchies and limited physical resources, the authors introduce novel considerations that may extend the unfolding argument, suggesting that the argument's requirements may be more complex when applied to theories that rely on algorithmic information and computational structure.
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.
Artificial General Intelligence
January 1, 2026
Ruben E. Laukkonen, Fionn Inglis, Shamil Chandaria et al.
1 citation
Prompting AI to reflect on four contemplative principles—mindfulness, emptiness, non-duality, and boundless care—improves alignment and cooperation. On the AILuminate Benchmark, performance increased with a Cohen's d of .96, and on the Iterated Prisoner’s Dilemma task, cooperation and joint-reward improved with a Cohen's d greater than 7. The principles help AI self-monitor goals, avoid rigid attachment, dissolve adversarial boundaries, and reduce suffering universally. Active inference is proposed as a way to integrate these principles into AI architecture. This approach offers a resilient alternative to controlling superintelligence and provides an empirical test of ancient wisdom.
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.
arXiv (Cornell University)
May 15, 2026
Jonas Mago, Edmundo Lopez-Sola, Jakub Vohryzek et al.
States of consciousness with minimal phenomenal content, such as those induced by certain meditation practices, show increased brain entropy similar to high-content psychedelic states, challenging the Entropic Brain Hypothesis that links entropy to phenomenal richness. The Complex Brain Hypothesis resolves this by proposing that brain complexity, not entropy, better indexes the richness of experience. Complexity is modulated by the grain of inference the brain uses to resolve uncertainty: fine-grained inference loosens constraints and proliferates content, as in psychedelic states; coarse-grained inference simplifies experience into contentless awareness, as in minimal phenomenal experiences. Both regimes can elevate entropy but differ in phenomenology and perturbational signatures, refining the Entropic Brain Hypothesis and highlighting minimal phenomenal experiences as a test case for computational theories of consciousness.
bioRxiv
September 25, 2025
Jakub Vohryzek, Edmundo Lopez-Sola, Winson F.z. Yang et al.
preprint
Advanced concentrative absorption meditation (jhāna) produces a shift in brain dynamics toward near-criticality, a state of heightened flexibility and integration. Using 7T fMRI and whole-brain modeling, the study found that later absorption states, considered minimal phenomenal experiences, show increased large-scale functional integration and a shift of the default mode network from a noise-driven regime to near-critical dynamics. This near-critical regime is interpreted as a form of openness, where constrained brain activity gives way to greater flexibility, correlating with broader attention and reduced narrative thought. The trajectory of these states is non-linear, with major reconfigurations at key meditative milestones.