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Published on: August 12, 2018
Whole brain modelling for simulating pharmacological interventions on patients with disorders of consciousness
I Mindlin1, R Herzog2, L Belloli2,3
1Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, Sorbonne Université, Paris, 75013, France. ivan.mindlin@icm-institute.org.
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.
Insights
New research uses brain models and AI to explore treatments for disorders of consciousness (DoC). Serotonin and opioid receptor activation showed potential for improving brain dynamics in DoC models.
Area of Science:
- Neuroscience
- Computational Psychiatry
- Pharmacology
Background:
- Disorders of consciousness (DoC) present significant challenges in diagnosis and treatment.
- Current therapeutic options for DoC are limited, necessitating novel approaches.
- Ethical and methodological constraints hinder direct clinical investigation of new treatments for DoC.
Purpose of the Study:
- To develop and validate a computational framework for studying DoC.
- To investigate the potential of pharmacological interventions for DoC using computational models.
- To explore the mechanisms underlying consciousness disorders and potential therapeutic targets.
Main Methods:
- Utilized biologically plausible whole-brain models integrated with deep learning techniques.
- Characterized the low-dimensional dynamical space of patients with disorders of consciousness.
- Simulated pharmacological interventions by modeling the effects of enhanced neurotransmitter levels on brain dynamics.
Main Results:
- Serotonergic and opioid receptor activation shifted DoC models towards healthier dynamical states.
- Improvements in DoC models correlated with the density of activated receptors.
- The study identified specific receptor pathways with therapeutic potential for DoC.
Conclusions:
- Computational modeling offers a viable method to explore DoC treatments within ethical and methodological boundaries.
- Pharmacological interventions targeting serotonergic and opioid systems show promise for DoC.
- This approach could advance treatments for a range of brain disorders beyond DoC.
