Investigating the complex integration processing of input patterns in the cerebellar cortex using HD - MEA and computational tools

The cerebellum is a remarkable structure with a well-organized cytoarchitecture that allows it to perform parallel operations and process information in a few milliseconds to retransmit them to different brain areas. The main functions of the cerebellum perform are posture control, gait, motor coordination, and learning. In recent decades, the study of the cerebellum has also focused on other functions besides motor functions: emotional and cognitive functions, corroborating the idea that this structure, although highly organized, is capable to perform complex functions. The presence of numerous and different cell types performing excitatory or inhibitory functions and the presence of feedback and feedforward loops, make the cerebellum an interesting object of study on multiple scales of resolution, from the microscale to the macroscale. At the microscale level, I focused on studying the biophysical aspect of the Golgi cell, one of the main interneurons of the granular layer that plays a key role in the control of information integration. In fact, the Golgi cell is involved in the spatiotemporal organization of inputs and regulates the transmission of the excitatory signal between mossy fibers and granules. The presence of apical and basal dendrites makes the Golgi cell able to perform a dendritic integration and a process of synaptic plasticity called spike-timing-dependent plasticity (STDP). These predictive properties were identified through the construction of a detailed computational model of a single neuron, used here to make up for the lack of experimental information on Golgi cell connectivity and dynamics. The computational model made it possible to provide a prediction about the interplay of basal and apical dendrites, whose functioning is modulated by different patterns of excitation and inhibition regulated by synaptic NMDA and AMPA receptors. STDP may be controlled by information provided by parallel fiber and integrated into apical dendrites, supporting the fact that spike timing is important to control synaptic plasticity at the input stage. At the mesoscale level, I focused on the ex vivo spatiotemporal study of the cerebellar cortex circuit, and how the signal from the mossy fibers is transmitted and integrated at the level of the granular layer and the Purkinje cell layer, the only output of the cerebellar cortex. The focus has been on how the circuit manages to integrate information at different input frequencies by stimulating the mossy fibers electrically. We recorded the extracellular signals of the neuronal population using the HD – MEA (high-density multielectrode array), a new technology that allows high spatial and temporal resolution, especially in terms of a population study. The spatiotemporal profile of the extracellular responses of granules and Purkinje cells was then analyzed by applying a Lempel - Ziv compression algorithm that allowed us to identify all significant activations of cells after each last pulse of the stimulation train across trials, at different input frequencies (0.1Hz, 6Hz, 20Hz, 50Hz, 100Hz). Subsequently, we calculated the Perturbational Complexity Index (PCI) an index, mainly used to investigate the different complexity states of the cerebral cortex, here applied to an ex vivo condition, to define the state of integration and segregation that determines the connectivity of cerebellar neurons and the complexity of information transmission.