Abstract
The brain shows a complex multiscale organization that prevents a direct understanding of how structure, function and dynamics are correlated. To date, advances in neural modeling offer a unique opportunity for simulating global brain dynamics by embedding empirical data on different scales in a mathematical framework. The Virtual Brain (TVB) is an advanced data-driven model allowing to simulate brain dynamics starting from individual subjects’ structural and functional connectivity obtained, for example, from magnetic resonance imaging (MRI). The use of TVB has been limited so far to cerebral connectivity but here, for the first time, we have introduced cerebellar nodes and interconnecting tracts to demonstrate the impact of cerebro-cerebellar loops on brain dynamics. Indeed, the matching between the empirical and simulated functional connectome was significantly improved when including the cerebro-cerebellar loops. This positive result should be considered as a first step, since issues remain open about the best strategy to reconstruct effective structural connectivity and the nature of the neural mass or mean-field models generating local activity in the nodes. For example, signal processing is known to differ remarkably between cortical and cerebellar microcircuits. Tackling these challenges is expected to further improve the predictive power of functional brain activity simulations, using TVB or other similar tools, in explaining not just global brain dynamics but also the role of cerebellum in determining brain states in physiological conditions and in the numerous pathologies affecting the cerebro-cerebellar loops.
Highlights
The brain is made of several interconnected networks that differently contribute to generate its global activity
The use of The Virtual Brain (TVB) has been limited so far to cerebral connectivity but here, for the first time, we have introduced cerebellar nodes and interconnecting tracts to demonstrate the impact of cerebro-cerebellar loops on brain dynamics
The microscale concerns local neuronal microcircuits, the mesoscale is a collection of local microcircuits possibly of different nature, while the macroscale refers to large-scale circuits
Summary
The brain is made of several interconnected networks that differently contribute to generate its global activity. To improve the understanding of mechanisms that subtend physiological and pathological dynamics, these networks need to be investigated at different organization scales. The relationship between brain structure, function and dynamics can be investigated using appropriate experimental and modeling approaches. The microscale concerns local neuronal microcircuits (e.g., a cerebral cortical microcolumn or a cerebellar cortical microzone), the mesoscale is a collection of local microcircuits possibly of different nature (e.g. a cortical area connected to the corresponding thalamic nucleus or a cerebellar microcomplex including multiple microzones and the connected deep cerebellar nuclei neurons), while the macroscale refers to large-scale circuits (e.g., the cerebral cortical and subcortical circuits forming cerebro-cerebellar loops). Microscale and mesoscale data have been made available for the rodent brain and are being used to implement detailed computational models and simulate the underlying physiological processes and computational rules (Markram et al, 2015; D’Angelo et al, 2016; Casali et al, 2019). Non-invasive functional macroscale data, in humans in vivo, can be acquired using electroencephalography (EEG) or magnetoencephalography (MEG), but magnetic resonance imaging (MRI) is the most widely used techniques for its great versatility
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
