How brain network architecture, disease, and neurotransmitter systems control transitions between cognitive states

To support the diversity of human cognitive functions, brain regions flexibly form and dissolve coalitions on the fly. How is the brain’s capacity to transition between different functional configurations shaped by brain network architecture? This talk will argue that a powerful approach is to use engineering principles of network control to simulate transitions between behaviourally-derived brain states, guided by the anatomical connectivity of the human brain as reconstructed from diffusion tractography. We identified >100 cognitively relevant brain states in a data-driven manner, corresponding to meta-analytic activation patterns aggregated over 14,000 fMRI studies from the NeuroSynth database. We discovered that the network architecture of the human connectome enables transitions between brain states at lower energetic cost than alternative wiring schemes - even after accounting for geometric constraints. These computational predictions were then validated with in-scanner task performance. We then systematically modelled how transitions could be impacted by changes in cortical thickness associated with 11 neurological, psychiatric and neurodevelopmental disorders from 17,000 patients in the ENIGMA database. We found systematic relationships between cortical abnormality and transitions towards brain states supporting memory and language, providing a mechanistic link between anatomical changes and cognitive symptoms. Finally, we leveraged the largest available database of neurotransmitter receptor expression in the human brain in vivo (18 receptor and transporter maps from >1,200 PET scans) to predict the effects of pharmacological interventions. Dopamine transporters and D1 receptors emerged as well positioned to facilitate many desired brain transitions - consistent with their engagement by drugs used to treat attention deficit such as modafinil and methylphenidate. Crucially, our model also highlighted other receptors such as Mu and H3 as suitable targets to achieve specific brain states (Luppi et al 2024, Nature Biomedical Engineering).

Up to this point, we lacked a comprehensive ‘look-up table’ charting how brain network organization and chemoarchitecture interact to manifest cognitively relevant brain states. By jointly leveraging large-scale databases of network structure, functional activation and neurotransmitter systems, the present work provides an integrative framework for the systematic exploration of the full range of possible transitions between experimentally defined brain states. This systematic approach allowed us to discover the key role of the brain’s wiring diagram in supporting flexible transitions with high energetic efficiency, and how this efficiency can be disrupted by disease and restored by targeted pharmacology. The predictions generated by our model highlight numerous potential clinical and non-clinical applications. We anticipate that future work will combine different facets of our computational framework to evaluate in silico which potential pharmacological treatments may best address the specific cognitive difficulties associated with a given disorder or brain tissue lesion. Altogether, we established a principled foundation for interrogating transitions between specific configurations of brain activity, and designing interventions that promote selective transitions between cognitive states.