Thesis title: The causality of complexity: understanding higher human cognitive functions through dynamic interactions among brain regions
The human brain may be considered as a complex system composed of regions interacting with each other in a way as to form a network of connections. As a set of elements, the brain regions are ordered in a specific way so that the position in the structure predicts the degree of connectivity with the other areas. Despite an apparent static architecture, which is the brain anatomy, the functional abilities of the human brain are massive. Indeed, to respond to the outside world demands, the brain flexibly adapts and behaves as a coherent whole network. Concurrently, although the structural architecture and the functional profiles of brain regions are quite stable, the dynamic interactions among brain areas are not fully understood. For instance, different tasks such as visual perception and visual imagery recruit partially overlapping circuits but the interplays among regions involved in these tasks are noteworthy. This is also the case of motor execution and motor imagery. These pieces of evidence lead to the understanding of how neuronal activity in a region affects the activity in another region, and thus to figure out the direction and the strength of the brain signal. In other words, which is the effect, in terms of excitation and inhibition, of a brain region on another especially during higher cognitive functions? In my doctoral work, I addressed these questions by studying the causal influence, termed effective connectivity, among regions involved in perceptual tasks, such as during visual perception and motor execution, and during imagery tasks. I took advantage of the newest techniques that allow assessing the connectivity in terms of inhibition and excitation starting from brain activation detected using functional Magnetic Resonance Imaging (fMRI). The overall results presented in this work support the idea that preferred signal routes branch off in the human brain and these pathways are strictly dependent on both the task performed and the intrinsic individual variability.