Whole brain modelling for simulating pharmacological interventions on patients with disorders of consciousness.
I Mindlin, R Herzog, L Belloli, D Manasova, M Monge-Asensio, J Vohryzek, A Escrichs, N Alnagger, P Núñez, O Gosseries, M L Kringelbach, G Deco, E Tagliazucchi, L Naccache, B Rohaut, J D Sitt, Y Sanz Perl
Communications biology September 19, 2024 DOI: 10.1038/s42003-024-06852-9 via PubMed
Summary
AI-generated from the abstractCombining whole-brain models with deep learning, researchers mapped the low-dimensional space of patients with disorders of consciousness and simulated pharmacological interventions by altering neuromodulatory levels. Serotonergic and opioid receptor activation shifted the models toward brain dynamics seen in healthier states, with improvements correlating with the mean density of activated receptors across the brain. This approach provides a way to explore therapeutic potential of psychedelic drugs within ethical and methodological constraints, marking progress toward treatments for disorders of consciousness and other brain diseases.
Study at a glance
| Characteristics | Computational modeling study Peer reviewed |
|---|---|
| Population | Biologically plausible whole-brain models of patients with disorders of consciousness |
| Citations | 18 |
| Key finding | Simulated activation of serotonergic and opioid receptors shifted whole-brain models of disorders of consciousness toward dynamics associated with healthier states, with improvements correlated to mean receptor density. |
Abstract
Disorders of consciousness (DoC) represent a challenging and complex group of neurological conditions characterised by profound disturbances in consciousness. The current range of treatments for DoC is limited. This has sparked growing interest in developing new treatments, including the use of psychedelic drugs. Nevertheless, clinical investigations and the mechanisms behind them are methodologically and ethically constrained. To tackle these limitations, we combined biologically plausible whole-brain models with deep learning techniques to characterise the low-dimensional space of DoC patients. We investigated the effects of model pharmacological interventions by including the whole-brain dynamical consequences of the enhanced neuromodulatory level of different neurotransmitters, and providing geometrical interpretation in the low-dimensional space. Our findings show that serotonergic and opioid receptors effectively shifted the DoC models towards a dynamical behaviour associated with a healthier state, and that these improvements correlated with the mean density of the activated receptors throughout the brain. These findings mark an important step towards the development of treatments not only for DoC but also for a broader spectrum of brain diseases. Our method offers a promising avenue for exploring the therapeutic potential of pharmacological interventions within the ethical and methodological confines of clinical research.