The brain is like a complex network, with neurons and synapses communicating and shaping our thoughts and actions. Neurodegenerative diseases, such as Alzheimer’s Disease and Amyotrophic Lateral Sclerosis, disrupt this delicate balance, leading to cognitive decline and motor dysfunction. Using advanced simulations on The Virtual Brain platform, scientists have gained insights into the impact of excitation/inhibition profiles on these diseases. By modeling the brain’s structural connections and the excitatory/inhibitory balance in individual patients, they discovered unique signatures for each clinical condition. These biophysical parameters not only contributed to explaining variations in cognitive performance but also improved the ability to distinguish between different disease states. Furthermore, the integration of cerebro-cerebellar loops in the simulations strengthened the predictive power of The Virtual Brain, highlighting the role of the cerebellum in neurodegeneration. This groundbreaking research holds promise for personalized diagnosis and therapy for neurodegenerative diseases. To delve deeper into the fascinating world of brain dynamics and functional states, check out the full article!

Brain pathologies are characterized by microscopic changes in neurons and synapses that reverberate into large scale networks altering brain dynamics and functional states. An important yet unresolved issue concerns the impact of patients’ excitation/inhibition profiles on neurodegenerative diseases including Alzheimer’s Disease, Frontotemporal Dementia, and Amyotrophic Lateral Sclerosis. In this work, we used The Virtual Brain (TVB) simulation platform to simulate brain dynamics in healthy and neurodegenerative conditions and to extract information about the excitatory/inhibitory balance in single subjects. The brain structural and functional connectomes were extracted from 3T-MRI (Magnetic Resonance Imaging) scans and TVB nodes were represented by a Wong-Wang neural mass model endowing an explicit representation of the excitatory/inhibitory balance. Simulations were performed including both cerebral and cerebellar nodes and their structural connections to explore cerebellar impact on brain dynamics generation. The potential for clinical translation of TVB derived biophysical parameters was assessed by exploring their association with patients’ cognitive performance and testing their discriminative power between clinical conditions. Our results showed that TVB biophysical parameters differed between clinical phenotypes, predicting higher global coupling and inhibition in Alzheimer’s Disease and stronger N-methyl-D-aspartate (NMDA) receptor-dependent excitation in Amyotrophic Lateral Sclerosis. These physio-pathological parameters allowed us to perform an advanced analysis of patients’ conditions. In backward regressions, TVB-derived parameters significantly contributed to explain the variation of neuropsychological scores and, in discriminant analysis, the combination of TVB parameters and neuropsychological scores significantly improved the discriminative power between clinical conditions. Moreover, cluster analysis provided a unique description of the excitatory/inhibitory balance in individual patients. Importantly, the integration of cerebro-cerebellar loops in simulations improved TVB predictive power, i.e., the correlation between experimental and simulated functional connectivity in all pathological conditions supporting the cerebellar role in brain function disrupted by neurodegeneration. Overall, TVB simulations reveal differences in the excitatory/inhibitory balance of individual patients that, combined with cognitive assessment, can promote the personalized diagnosis and therapy of neurodegenerative diseases.

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