Internal Models in the Cerebellum: A Coupling Scheme for Online and Offline Learning in Procedural Tasks

The cerebellum plays a major role in motor control. It is thought to mediate the acquisition of forward and inverse internal models of the bodyenvironment interaction [1]. In this study, the main processing components of the cerebellar microcomplex are modelled as a network of spiking neural populations. The model cerebellar circuit is shown to be suitable for learning both forward and inverse models. A new coupling scheme is put forth to optimise online adaptation and support offline learning. The proposed model is validated on two procedural tasks and the simulation results are consistent with data from human experiments on adaptive motor control and sleep-dependent consolidation [2, 3]. This work corroborates the hypothesis that both forward and inverse internal models can be learnt and stored by the same cerebellar circuit, and that their coupling favours online and offline learning of procedural memories

Contribution of Cerebellar Sensorimotor Adaptation to Hippocampal Spatial Memory

Complementing its primary role in motor control, cerebellar learning has also a bottom-up influence on cognitive functions, where high-level representations build up from elementary sensorimotor memories. In this paper we examine the cerebellar contribution to both procedural and declarative components of spatial cognition. To do so, we model a functional interplay between the cerebellum and the hippocampal formation during goal-oriented navigation. We reinterpret and complete existing genetic behavioural observations by means of quantitative accounts that cross-link synaptic plasticity mechanisms, single cell and population coding properties, and behavioural responses. In contrast to earlier hypotheses positing only a purely procedural impact of cerebellar adaptation deficits, our results suggest a cerebellar involvement in high-level aspects of behaviour. In particular, we propose that cerebellar learning mechanisms may influence hippocampal place fields, by contributing to the path integration process. Our simulations predict differences in place-cell discharge properties between normal mice and L7-PKCI mutant mice lacking long-term depression at cerebellar parallel fibre-Purkinje cell synapses. On the behavioural level, these results suggest that, by influencing the accuracy of hippocampal spatial codes, cerebellar deficits may impact the exploration-exploitation balance during spatial navigation

Role of the cerebellum in adaptative voluntary movements and spatial cognition (a neurocomputational study)

Ma thèse a pour objectif de mettre en évidence les propriétés computationnelles ainsi que les processus d adaptation du cervelet communs aux apprentissages moteurs et à la cognition spatiale. Dans la première partie, nous nous intéressons aux mécanismes d apprentissage procédural lors de l'adaptation de mouvements volontaires. Nous proposons un nouveau schéma de couplage de modèles internes du cervelet. Le microcomplexe cérébelleux est modélisé en utilisant un réseau de neurones formels impulsionnels reproduisant les éléments fondamentaux de la cytoarchitecture cérébelleuse. Le modèle est testé sur une tâche d'adaptation de rotation. Les résultats obtenus sur une version simulée de ce paradigme montrent que seul le modèle d apprentissage est capable de reproduire les résultats expérimentaux dont la consolidation post-sommeil. Dans la seconde partie, nous inscrivons notre modèle de microcomplexe cérébelleux dans une architecture neurale plus étendue afin d étudier le rôle du cervelet dans la composante procédurale et déclarative de la cognition spatiale. Nos résultats de simulation suggèrent que le cervelet serait impliqué à la fois dans l'optimisation locale d'une trajectoire et aussi dans la mise en place de procédures adaptées à la réalisation d'une tache, i.e. la composante locale et globale de la mémoire procédurale. Finalement, nos résultats suggèrent que le cervelet serait aussi impliqué dans l'intégration des informations idiothétiques, ce qui affecterait indirectement la mise en place d'une représentation stable de l'environnement au niveau des cellules de lieu hippocampiques, et par conséquent l acquisition de mémoires à caractère déclaratif.PARIS-BIUSJ-Biologie recherche (751052107) / SudocSudocFranceF

Multipeak place fields occur with higher probability in simulated L7-PKCI than in control mice.

<p><b>A.</b> Samples of receptive fields of simulated place cells from control (top) and mutant (bottom) simulated animals. Each plot shows the mean discharge of the recorded neuron as a function of the animal position in the MWM (red and blue denote peak and baseline firing rates, respectively). The unimodality property of firing distributions is statistically assessed by a Hartigan DIP test ( indicates a multipeak receptive field). <b>B.</b> Percentage of unimodal and multimodal place fields in simulated controls and mutants. <b>C.</b> Mean number of peaks per hippocampal place field in both groups of simulated animals.</p

The hypothesis of a cerebellar influence on path integration, and hence on hippocampal place coding, accounts for all L7-PKCIs' spatial navigation impairments observed experimentally.

<p>Occupancy maps in the MWM. Three-dimensional diagrams of the mean time spent by control and mutant mice at each location of the maze at different training phases (days, 1, 3, 5, 7 and 10). A grid of resolution 31 × 31 (each grid cell is 5 × 5 cm) samples spatial locations. The value associated to each grid cell is the normalised time spent in the cell region with respect to the duration of each trial, averaged over all day trials and over all animals of a group.</p

Population place coding is suboptimal in simulated L7-PKCI mice compared to controls.

<p><b>A.</b> Information content of the spatial code encoded by the population of hippocampal place cells in controls and mutants. <b>B.</b> Redundancy of the hippocampal spatial code in both simulated groups. <b>C.</b> Spatial density of hippocampal place fields in both groups. <b>Unitary hippocampal place fields in simulated L7-PKCI mice are not impaired, relative to controls, in terms of size, spatial coherence and information content. D.</b> Mean size of place fields in simulated controls and mutants. <b>E.</b> Mean spatial coherence (local smoothness) of place fields in both groups. <b>F.</b> Mean spatial information content of unitary place fields in both groups.</p

The hypothesis of a cerebellar influence on path integration, and hence on hippocampal place coding, accounts for all L7-PKCIs' spatial navigation impairments observed experimentally.

<p><b>Results in the MWM: </b><b>A.</b> Mean escape latency over training (left y-axis) and score (right y-axis) of simulated controls and mutants. <b>B.</b> Correlation between searching score and escape latency for control (top) and mutant (bottom) simulated mice. <b>C.</b> Mean angular deviation between ideal and actual trajectory to the goal. <b>D.</b> Ratio between the time spent in the platform quadrant and the total duration of a trial. <b>E.</b> Mean distance of the simulated mouse to the platform. <b>F.</b> Mean circling time. <b>Results in the Starmaze: </b><b>G.</b> Mean number of visited alleys. <b>H.</b> Mean distance swum in the Starmaze.</p

Cerebellar microcomplex model.

<p><b>A.</b> A simplified scheme of the cerebellar microcomplex (adapted from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032560#pone.0032560-Medina2" target="_blank">[114]</a>). Information enters the cerebellum via two neural pathways: the mossy fibres convey multimodal sensorimotor signals, whereas climbing fibres are assumed to convey error-related information. Granule cells process and transmit sensorimotor inputs to Purkinje cells. Error-related signals also converge onto Purkinje cell synapses, which undergo long-term modifications (i.e. long-term potentiation, LTP, and depression, LTD). <b>B.</b> Model cerebellar microcomplex circuit. Each box indicates a population of spiking neurons. The same cerebellar circuit implements both forward (dark gray inputs) and inverse (white inputs) internal models.</p

Model architecture and simulated navigation protocols.

<p><b>A.</b> Overview of the connectionist model implementing a functional coupling between cerebellar and hippocampal networks. Note that arrows indicate functional projections, which do not necessarily correspond to direct anatomical pathways. <b>B.</b> The simulated Morris watermaze <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032560#pone.0032560-Morris1" target="_blank">[26]</a> consists of a circular maze of cm in diameter. <b>C.</b> The simulated Starmaze <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032560#pone.0032560-RondiReig2" target="_blank">[54]</a> is also a circular maze ( cm in diameter) but it contains alleys ( cm in width) forming a central pentagonal ring with radiating arms from each vertex. Both tasks require simulated animals to reach an escape platform ( cm in diameter) hidden below the surface of opaque water at a fixed location (black dashed cylinder). At each trial, animals start from one location that is randomly drawn from four possible starting locations (black stars). In both tasks animals can use available visual landmarks (coloured stars) as well as self-motion cues to learn allocentric spatial representations.</p