Grounding brain mechanisms in the spatiotemporal properties of cerebral and behavioral networks

Field: Neuroscience (Life Sciences)

The spatiotemporal properties of the cerebral and behavioral networks are key elements to understand normal brain functioning and their breakdowns. This dissertation focuses on the cerebral networks of the brain regions’ co-activation patterns over the brain, as well as the behavioral networks of the bidirectional exchanges of information within the body-brain-environment nexus. Recent investigations revealed that the genetic etiological landscape of Autism Spectrum Disorder (ASD) could reflect the spectral diversity observed in clinical behaviors and resting-state spatiotemporal connectivity profiles. However, the exact neural mechanism behind a sub-type of ASD as defined by resting-state fMRI (rs-fMRI) overconnectivity remains elusive. In Chapter 2, we test whether Chd8 haploinsufficient mutation (Chd8+/−) supports a theoretical model in which inter-areal functional overconnectivity could reflect an increased excitation/inhibition (E/I) ratio mediated by a decrease in the integration of inhibitory input. Our results suggest that locally reducing the synaptic interneurons couplings over the whole brain, proportionally to the brain area's excitatory drives, theoretically results in large-scale oversynchronization and E/I imbalance in Chd8+/− rs-fMRI mouse model. This study shows that the experimentally observed dynamical connectopathy in response to the Chd8+/− genetic mutation could be retrieved via in silico mouse rs-fMRI whole-brain modeling, suggesting an underlying dynamical synaptopathy within the E/I balance. Furthermore, spatiotemporal impairments of large-scale resting-state networks are noticed in brain diseases, as observed in stroke. However, the effects of a stroke on the functional connectivity network time properties remain elusive in mouse models. In Chapter 3, we explore the impact of a stroke and motor rehabilitation on brain connectivity reorganization. To do so, we use the leading eigenvectors of the dynamical functional connectivity from a longitudinal rs-fluorescence GCaMP6f mouse model in k-means clustering. Our results show that the time properties of the functional connectivity states interplay between the peripheral and core stroke regions were altered as revealed in the state's probability of occurrence, duration, and switching transition after a stroke and reset to the pre-stroke condition after motor-rehabilitation training. Finally, the congruency of behavioral spatiotemporal patterns influences complex mental constructs as observed in the concept of the experience of the body as belonging to oneself called body ownership. However, the effect of the congruency of spatiotemporal components which pertain to the external world within an ongoing action is an element of the behavioral network and yet remains underexplored. In Chapter 4, we build a Virtual-Reality game to investigate the role of top-down cognitive processes in the sense of body ownership. Our results suggest that when action-driven and task-relevant visuoauditory feedback of goal-oriented movements do not match sensory predictions in terms of space and time, motor performances along with the sense of body ownership are negatively impacted. In a multidisciplinary attempt that combines model-based along with neural and behavioral data-driven analyses, this dissertation intends to shed light on the impact of the cerebral and behavioral network spatiotemporal properties on brain mechanisms.