Unveiling the Neural Code: computing intentions in V6A

The title of this thesis, Unveiling the Neural Code: Computing Intentions in V6A, reflects the overarching objective of elucidating the brain’s processing of motor intentions during spatial target perception, with a specific focus on the V6A parietal cortical area. The primary focus of this thesis is revealing the computations occurring within V6A in motor intentions related to spatial target perception. The findings herein highlight V6A’s crucial role in translating sensory inputs into actionable motor plans, bridging perception and action within the brain’s sensorimotor circuitry. The second major contribution of this work proposes advanced methods for analysis of the neural activity inspired by biological processes. The brain-inspired decoding approach is grounded in the concept of predictive coding, a fundamental principle in brain function. In particular, the framework of active inference, suggests that the brain continuously predicts sensory inputs and motor outcomes, refining its actions through feedback. This bio-inspired model not only aligns with the current understanding of predictive coding but also offers a novel perspective on how motor intentions are formed and executed. The transferability of this model across different neural datasets is demonstrated. In collaboration with the Spanish research center Tecnalia, neural data recorded from a human patient with a motor cortex (M1) lesion following a stroke were analyzed. This dataset allowed for testing the robustness of the model and exploring its applicability beyond V6A, providing insights into neural recovery and compensation mechanisms in damaged cortical areas. This research thesis elucidates the neural code underlying motor intentions and offer models that can potentially inform the design of future neural interfaces and rehabilitation strategies.