LSD-induced increase of Ising temperature and algorithmic complexity of brain dynamics
Using pairwise maximum-entropy (Ising) models and algorithmic-complexity measures on fMRI from 15 subjects, the study shows that LSD raises individualized Ising temperatures, shifting brain dynamics further into an above-critical, more disordered (paramagnetic) regime. This shift is accompanied by reduced homotopic interhemispheric connectivity and increased algorithmic complexity (notably BDM), and the derived Ising archetypes correlate strongly with a structural connectome template (r ≈ 0.6).
Authors
- Fernando Rosas
- Robin Carhart-Harris
- Morten Kringelbach
Published
Abstract
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 various distances from a phase transition, i.e., from criticality. Here we aim to characterize two brain states (psychedelics-induced and placebo) as captured by functional magnetic resonance imaging (fMRI), with features derived from the Ising spin model formalism (system temperature, critical point, susceptibility) and from algorithmic complexity. We hypothesized, along the lines of the entropic brain hypothesis, that psychedelics drive brain dynamics into a more disordered state at a higher Ising temperature and increased complexity. We analyze resting state blood-oxygen-level-dependent (BOLD) fMRI data collected in an earlier study from fifteen subjects in a control condition (placebo) and during ingestion of lysergic acid diethylamide (LSD). Working with the automated anatomical labeling (AAL) brain parcellation, we first create “archetype” Ising models representative of the entire dataset (global) and of the data in each condition. Remarkably, we find that such archetypes exhibit a strong correlation with an average structural connectome template obtained from dMRI ( r = 0.6). We compare the archetypes from the two conditions and find that the Ising connectivity in the LSD condition is lower than in the placebo one, especially in homotopic links (interhemispheric connectivity), reflecting a significant decrease of homotopic functional connectivity in the LSD condition. The global archetype is then personalized for each individual and condition by adjusting the system temperature. The resulting temperatures are all near but above the critical point of the model in the paramagnetic (disordered) phase. The individualized Ising temperatures are higher in the LSD condition than in the placebo condition ( p = 9 × 10 −5 ). Next, we estimate the Lempel-Ziv-Welch (LZW) complexity of the binarized BOLD data and the synthetic data generated with the individualized model using the Metropolis algorithm for each participant and condition. The LZW complexity computed from experimental data reveals a weak statistical relationship with condition ( p = 0.04 one-tailed Wilcoxon test) and none with Ising temperature ( r (13) = 0.13, p = 0.65), presumably because of the limited length of the BOLD time series. Similarly, we explore complexity using the block decomposition method (BDM), a more advanced method for estimating algorithmic complexity. The BDM complexity of the experimental data displays a significant correlation with Ising temperature ( r (13) = 0.56, p = 0.03) and a weak but significant correlation with condition ( p = 0.04, one-tailed Wilcoxon test). This study suggests that the effects of LSD increase the complexity of brain dynamics by loosening interhemispheric connectivity—especially homotopic links. In agreement with earlier work using the Ising formalism with BOLD data, we find the brain state in the placebo condition is already above the critical point, with LSD resulting in a shift further away from criticality into a more disordered state.
Research Summary of 'LSD-induced increase of Ising temperature and algorithmic complexity of brain dynamics'
Introduction
Ruffini and colleagues situate this study within a tradition of applying statistical physics to brain activity, arguing that large-scale neural dynamics can be meaningfully described in terms of phase transitions and critical phenomena. Previous work has suggested that healthy brains may operate near critical points where a balance of order and disorder affords rich, multiscale correlations and computational advantages, and that pharmacological perturbations—such as psychedelics—alter the repertoire and entropy of spontaneous brain activity. The authors note that LSD in particular has been associated in prior functional neuroimaging studies with increased signal diversity, weakened canonical functional configurations, and greater global integration and flexibility. Building on these ideas, the study aims to characterise how LSD affects whole-brain dynamics using pairwise maximum-entropy (Ising) models and measures of algorithmic complexity. Specifically, the investigators construct a group-level "archetype" Ising model from resting-state fMRI BOLD data, then personalise that archetype for each subject and condition by fitting a single temperature parameter that controls randomness and distance from the model's critical point. They also estimate signal complexity using Lempel–Ziv–Welch (LZW) compression and the Block Decomposition Method (BDM) on both empirical and model-generated (synthetic) binary time series, testing the hypothesis that complexity metrics will correlate with fitted Ising temperature and distinguish LSD from placebo.
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Study Details
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- APA Citation
Ruffini, G., Damiani, G., Lozano-Soldevilla, D., Deco, N., Rosas, F. E., Kiani, N. A., Ponce-Alvarez, A., Kringelbach, M. L., Carhart-Harris, R., & Deco, G. (2023). LSD-induced increase of Ising temperature and algorithmic complexity of brain dynamics. PLOS Computational Biology, 19(2), e1010811. https://doi.org/10.1371/journal.pcbi.1010811
References (20)
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Atasoy, S., Leor, R., Kaelen, M. et al. · Scientific Reports (2017)
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Carhart-Harris, R. L. · Neuropharmacology (2018)
Carhart-Harris, R. L., Erritzoe, D., Williams, T. et al. · PNAS (2012)
Carhart-Harris, R. L., Leech, R., Shanahan, M. et al. · Frontiers in Human Neuroscience (2014)
Carhart-Harris, R. L., Muthukumaraswamy, S., Roseman, L. et al. · PNAS (2016)
Deco, G., Cruzat, J., Cabral, J. et al. · Current Biology (2018)
Kirchner, K. · Journal of Psychopharmacology (2014)
Geyer, M. A., Vollenweider, F. X. · Trends in Pharmacological Sciences (2008)
Johnson, M. W., Hendricks, P. S., Barrett, F. S. et al. · Pharmacology and Therapeutics (2019)
Show all 20 referencesShow fewer
Krebs, T. S., Johansen, P. Ø. · Journal of Psychopharmacology (2012)
McCulloch, D. E-W., Knudsen, G. M., Barrett, F. S. et al. · Neuroscience and Biobehavioral Reviews (2022)
Lenz, C., Dolder, P. C., Lang, U. E. et al. · Acta Psychiatrica Scandinavica (2017)
Nutt, D. J., Erritzoe, D., Carhart-Harris, R. L. · Cell (2020)
Passie, T., Halpern, J. H., Stichtenoth, D. O. et al. · CNS Neuroscience and Therapeutics (2008)
Preller, K. H., Burt, J. B., Adkinson, B. et al. · eLife (2018)
Preller, K. H., Razi, A., Zeidman, P. et al. · PNAS (2019)
Schartner, M., Carhart-Harris, R. L., Barrett, A. B. et al. · Scientific Reports (2017)
Tagliazucchi, E., Roseman, L., Kaelen, M. et al. · Current Biology (2016)
Varley, T. F., Carhart-Harris, R., Roseman, L. et al. · NeuroImage (2020)
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Shinozuka, K., Tewarie, P. K. B., Luppi, A. et al. · Biorxiv (2024)
Carhart-Harris, R. L., Chandaria, S., Erritzoe, D. E. et al. · Neuropharmacology (2023)
Girn, M., Roseman, L., Bernhardt, B. et al. · Biorxiv (2020)
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