The deep cerebellar nuclei (DCN) function as output gates for a large majority of the Purkinje cells of the cerebellar cortex and thereby determine how the cerebellum influences the rest of the brain and body. In my PhD programme I have investigated how the DCN process two kinds of input patterns received from Purkinje cells: irregularity of spike intervals and pauses in Purkinje cell activity resulting from the recognition of patterns received at the synapses with the upstream parallel fibres (PFs). To that objective I have created a network system of biophysically realistic Purkinje cell and DCN neuron models that enables the exploration of a wide range of network structure and cell physiology parameters. With this system I have performed simulations that show how the DCN neuron changes the information modality of its input, consisting of varying regularity in Purkinje cell spike intervals, to varying spike rates in its output to the nervous system outside of the cerebellum. This was confirmed in simulations where I exchanged the artificial Purkinje cell trains for those received from experimental collaborators. In pattern recognition simulations I have found that the morphological arrangement present in the cerebellum, where multiple Purkinje cells connect to each DCN neuron, has the effect of amplifying pattern recognition already performed in the Purkinje cells. Using the metric of signal-to-noise ratio I show that PF patterns previously encountered and stored in PF - Purkinje cell synapses are most clearly distinguished from those novel to the system by a 10-20 ms shortened burst firing of the DCN neuron. This result suggests that the effect on downstream targets of these excitatory projection neurons is a decreased excitation when a stored as opposed to novel pattern is received. My work has contributed to a better understanding of information processing in the cerebellum, with implications for human motor control as well as the increasingly recognised non-motor functions of the cerebellum.

Le cervelet permet l’apprentissage moteur et la coordination des mouvements fins. Pour ce faire, il intègre les informations sensorielles provenant de l’ensemble du corps ainsi que les commandes motrices émises par d’autres structures du système nerveux central. Les noyaux cérébelleux profonds (DCN) constituent la sortie du cervelet et intègre les informations provenant des cellules de Purkinje (PC), des fibres moussues et des fibres grimpantes. Nous avons étudié les connexions fonctionnelles entres les PC et les DNC in vivo, grâce à une stimulation optogénétique des lobules IV/V du cortex cérébelleux et à l’enregistrement multi unitaire du noyau médian. Nous avons ainsi identifié deux groupes de cellules au sein des DCN, présentant des caractéristiques propres au niveau de leur fréquence de décharge et de la forme des potentiels d’action, en accord avec la dichotomie établie par une précédente étude in vitro permettant de séparer les neurones GABAergiques des autres neurones. Nos résultats suggèrent que les PC contrôlent la sotie du cervelet d’un point de vue temporel. De plus, la ciruiterie interne des DCN conforte ce résultat de part le fait que les cellules GABAergiques ne produisent pas d’effet temporel au travers de l’inhibition locale. / The cerebellum integrates motor commands with somatosensory, vestibular, visual and auditory information for motor learning and coordination functions. The deep cerebellar nuclei (DCN) generates the final output by processing inputs from Purkinje cells (PC), mossy and climbing fibers. We investigated the properties of PC connections to DCN cells using optogenetic stimulation in L7-ChR2 mice with in vivo multi electrode extracellular recordings in lobule IV/V of the cerebellar cortex and in the medial nuclei. DCN cells discharged phase locked to local field potentials in the beta, gamma and high frequency bands. We identified two groups of DCN cells with significant differences in action potential waveforms and firing rates, matching previously discriminated in vitro properties of GABAergic and non-GABAergic cells. PCs inhibited the two group of cells gradually (rate coding), however spike times were controlled for only non-GABAergic cells. Our results suggest that PC inputs temporally control the output of cerebellum and the internal DCN circuitry supports this phenomenon since GABAergic cells do not induce a temporal effect through local inhibition.