Healthy and pathological cerebellar Spiking Neural Networks in Vestibulo-Ocular Reflex

Localization of long-term synaptic plasticity defects in cerebellar circuits using optokinetic reflex learning profile

Objective.Functional maps of the central nervous system attribute the coordination and control of many body movements directly or indirectly to the cerebellum. Despite this general picture, there is little information on the function of cerebellar neural components at the circuit level. The presence of multiple synaptic junctions and the synergistic action of different types of plasticity make it virtually difficult to determine the distinct contribution of cerebellar neural processes to behavioral manifestations. In this study, investigating the effect of long-term synaptic changes on cerebellar motor learning, we intend to provide quantitative criteria for localizing defects in the major forms of synaptic plasticity in the cerebellum.Approach.To this end, we develop a firing rate model of the cerebellar circuits to simulate learning of optokinetic reflex (OKR), one of the most well-known cerebellar-dependent motor tasks. In the following, by comparing the simulated OKR learning profile for normal and pathosynaptic conditions, we extract the learning features affected by long-term plasticity disorders. Next, conducting simulation with different massed (continuous with no rest) and spaced (interleaved with rest periods) learning paradigms, we estimate the detrimental impact of plasticity defects at corticonuclear synapses on short- and long-term motor memory.Main results.Our computational approach predicts a correlation between location and grade of the defect with some learning factors such as the rate of formation and retention of motor memory, baseline performance, and even cerebellar motor reserve capacity. Further, spacing analysis reveal the dependence of learning paradigm efficiency on the spatiotemporal characteristic of defect in the network. Indeed, defects in cortical memory formation and nuclear memory consolidation mainly harm massed and spaced learning, respectively. This result is used to design a differential assay for identifying the faulty phases of cerebellar learning.Significance.The proposed computational framework can help develop neural-screening systems and prepare meso-scale functional maps of the cerebellar circuits.

Robotic set-up to quantify hand-eye behavior in motor execution and learning of children with autism spectrum disorder

Autism spectrum disorder (ASD) is a multifaceted neurodevelopmental disorder characterized by a persistence of social and communication impairment, and restricted and repetitive behaviors. However, motor disorders have also been described, but not objectively assessed. Most studies showed inefficient eye-hand coordination and motor learning in children with ASD; in other experiments, mechanisms of acquisition of internal models in self-generated movements appeared to be normal in autism. In this framework, we have developed a robotic protocol, recording gaze and hand data during upper limb tasks, in which a haptic pen-like handle is moved along specific trajectories displayed on the screen. The protocol includes trials of reaching under a perturbing force field and catching moving targets, with or without visual availability of the whole path. We acquired 16 typically-developing scholar-age children and one child with ASD as a case study. Speed-accuracy tradeoff, motor performance, and gaze-hand spatial coordination have been evaluated. Compared to typically developing peers, in the force field sequence, the child with ASD showed an intact but delayed learning, and more variable gazehand patterns. In the catching trials, he showed less efficient movements, but an intact capability of exploiting the available a-priori plan. The proposed protocol represents a powerful tool, easily tunable, for quantitative (longitudinal) assessment, and for subject-tailored training in ASD.