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.
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.