Modeled changes of cerebellar activity in mutant mice are predictive of their learning impairments

Translating neuronal activity to measurable behavioral changes has been a long-standing goal of systems neuroscience. Recently, we have developed a model of phase-reversal learning of the vestibulo-ocular reflex, a well-established, cerebellar-dependent task. The model, comprising both the cerebellar cortex and vestibular nuclei, reproduces behavioral data and accounts for the changes in neural activity during learning in wild type mice. Here, we used our model to predict Purkinje cell spiking as well as behavior before and after learning of five different lines of mutant mice with distinct cell-specific alterations of the cerebellar cortical circuitry. We tested these predictions by obtaining electrophysiological data depicting changes in neuronal spiking. We show that our data is largely consistent with the model predictions for simple spike modulation of Purkinje cells and concomitant behavioral learning in four of the mutants. In addition, our model accurately predicts a shift in simple spike activity in a mutant mouse with a brainstem specific mutation. This combination of electrophysiological and computational techniques opens a possibility of predicting behavioral impairments from neural activity

Spatial navigation impairment in mice lacking cerebellar LTD: a motor adaptation deficit?

L7-PKCI transgenic mice, having a specific lack of parallel fiber-Purkinje cell LTD, were tested with two different mazes to dissociate the relative importance of declarative and procedural components of spatial navigation. Our data bring evidence for a deficit of L7-PKCI mice in the acquisition of an adapted goal-oriented behavior, i.e. in the procedural component of the task. This finding supports the hypothesis that cerebellar LTD may subserve a general sensory-motor adaptation process shared by motor and spatial learning functions

Climbing Fiber Burst Size and Olivary Sub-threshold Oscillations in a Network Setting

The inferior olivary nucleus provides one of the two main inputs to the cerebellum: the so-called climbing fibers. Activation of climbing fibers is generally believed to be related to timing of motor commands and/or motor learning. Climbing fiber spikes lead to large all-or-none action potentials in cerebellar Purkinje cells, overriding any other ongoing activity and silencing these cells for a brief period of time afterwards. Empirical evidence shows that the climbing fiber can transmit a short burst of spikes as a result of an olivary cell somatic spike, potentially increasing the information being transferred to the cerebellum per climbing fiber activation. Previously reported results from in vitro studies suggested that the information encoded in the climbing fiber burst is related to the occurrence of the spike relative to the ongoing sub-threshold membrane potential oscillation of the olivary cell, i.e. that the phase of the oscillation is reflected in the size of the climbing fiber burst. We used a detailed three-compartmental model of an inferior olivary cell to further investigate the possible factors determining the size of the climbing fiber burst. Our findings suggest that the phase-dependency of the burst size is present but limited and that charge flow between soma and dendrite is a major determinant of the climbing fiber burst. From our findings it follows that phenomena such as cell ensemble synchrony can have a big effect on the climbing fiber burst size through dendrodendritic gap-junctional coupling between olivary cells

The generation of phase differences and frequency changes in a network model of inferior olive subthreshold oscillations

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedicationIt is commonly accepted that the Inferior Olive (IO) provides a timing signal to the cerebellum. Stable subthreshold oscillations in the IO can facilitate accurate timing by phase-locking spikes to the peaks of the oscillation. Several theoretical models accounting for the synchronized subthreshold oscillations have been proposed, however, two experimental observations remain an enigma. The first is the observation of frequent alterations in the frequency of the oscillations. The second is the observation of constant phase differences between simultaneously recorded neurons. In order to account for these two observations we constructed a canonical network model based on anatomical and physiological data from the IO. The constructed network is characterized by clustering of neurons with similar conductance densities, and by electrical coupling between neurons. Neurons inside a cluster are densely connected with weak strengths, while neurons belonging to different clusters are sparsely connected with stronger connections. We found that this type of network can robustly display stable subthreshold oscillations. The overall frequency of the network changes with the strength of the inter-cluster connections, and phase differences occur between neurons of different clusters. Moreover, the phase differences provide a mechanistic explanation for the experimentally observed propagating waves of activity in the IO. We conclude that the architecture of the network of electrically coupled neurons in combination with modulation of the inter-cluster coupling strengths can account for the experimentally observed frequency changes and the phase differences.Peer reviewedFinal Published versio

Purkinje cell input to cerebellar nuclei in tottering: Ultrastructure and physiology

Homozygous tottering mice are spontaneous ataxic mutants, which carry a mutation in the gene encoding the ion pore of the P/Q-type voltage-gated calcium channels. P/Q-type calcium channels are prominently expressed in Purkinje cell terminals, but it is unknown to what extent these inhibitory terminals in tottering mice are affected at the morphological and electrophysiological level. Here, we investigated the distribution and ultrastructure of their Purkinje cell terminals in the cerebellar nuclei as well as the activities of their target neurons. The densities of Purkinje cell terminals and their synapses were not significantly affected in the mutants. However, the Purkinje cell terminals were enlarged and had an increased number of vacuoles, whorled bodies, and mitochondria. These differences started to occur between 3 and 5 weeks of age and persisted throughout adulthood. Stimulation of Purkinje cells in adult tottering mice resulted in inhibition at normal latencies, but the activities of their postsynaptic neurons in the cerebellar nuclei were abnormal in that the frequency and irregularity of their spiking patterns were enhanced. Thus, although the number of their terminals and their synaptic contacts appear quantitatively intact, Purkinje cells in tottering mice show several signs of axonal damage that may contribute to altered postsynaptic activities in the cerebellar nuclei

Memory consolidation in the cerebellar cortex

Several forms of learning, including classical conditioning of the eyeblink, depend upon the cerebellum. In examining mechanisms of eyeblink conditioning in rabbits, reversible inactivations of the control circuitry have begun to dissociate aspects of cerebellar cortical and nuclear function in memory consolidation. It was previously shown that post-training cerebellar cortical, but not nuclear, inactivations with the GABA(A) agonist muscimol prevented consolidation but these findings left open the question as to how final memory storage was partitioned across cortical and nuclear levels. Memory consolidation might be essentially cortical and directly disturbed by actions of the muscimol, or it might be nuclear, and sensitive to the raised excitability of the nuclear neurons following the loss of cortical inhibition. To resolve this question, we simultaneously inactivated cerebellar cortical lobule HVI and the anterior interpositus nucleus of rabbits during the post-training period, so protecting the nuclei from disinhibitory effects of cortical inactivation. Consolidation was impaired by these simultaneous inactivations. Because direct application of muscimol to the nuclei alone has no impact upon consolidation, we can conclude that post-training, consolidation processes and memory storage for eyeblink conditioning have critical cerebellar cortical components. The findings are consistent with a recent model that suggests the distribution of learning-related plasticity across cortical and nuclear levels is task-dependent. There can be transfer to nuclear or brainstem levels for control of high-frequency responses but learning with lower frequency response components, such as in eyeblink conditioning, remains mainly dependent upon cortical memory storage

Visuomotor Cerebellum in Human and Nonhuman Primates

In this paper, we will review the anatomical components of the visuomotor cerebellum in human and, where possible, in non-human primates and discuss their function in relation to those of extracerebellar visuomotor regions with which they are connected. The floccular lobe, the dorsal paraflocculus, the oculomotor vermis, the uvula–nodulus, and the ansiform lobule are more or less independent components of the visuomotor cerebellum that are involved in different corticocerebellar and/or brain stem olivocerebellar loops. The floccular lobe and the oculomotor vermis share different mossy fiber inputs from the brain stem; the dorsal paraflocculus and the ansiform lobule receive corticopontine mossy fibers from postrolandic visual areas and the frontal eye fields, respectively. Of the visuomotor functions of the cerebellum, the vestibulo-ocular reflex is controlled by the floccular lobe; saccadic eye movements are controlled by the oculomotor vermis and ansiform lobule, while control of smooth pursuit involves all these cerebellar visuomotor regions. Functional imaging studies in humans further emphasize cerebellar involvement in visual reflexive eye movements and are discussed

GlyT2+ Neurons in the Lateral Cerebellar Nucleus

The deep cerebellar nuclei (DCN) are a major hub in the cerebellar circuitry but the functional classification of their neurons is incomplete. We have previously characterized three cell groups in the lateral cerebellar nucleus: large non-GABAergic neurons and two groups of smaller neurons, one of which express green fluorescence protein (GFP) in a GAD67/GFP mouse line and is therefore GABAergic. However, as a substantial number of glycinergic and glycine/GABA co-expressing neurons have been described in the DCN, this classification needed to be refined by considering glycinergic neurons. To this end we took advantage of a glycine transporter isoform 2 (GlyT2)-eGFP mouse line that allows identification of GlyT2-expressing, presumably glycinergic neurons in living cerebellar slices and compared their electrophysiological properties with previously described DCN neuron populations. We found two electrophysiologically and morphologically distinct sets of GlyT2-expressing neurons in the lateral cerebellar nucleus. One of them showed electrophysiological similarity to the previously characterized GABAergic cell group. The second GlyT2+ cell population, however, differed from all other so far described neuron types in DCN in that the cells (1) are intrinsically silent in slices and only fire action potentials upon depolarizing current injection and (2) have a projecting axon that was often seen to leave the DCN and project in the direction of the cerebellar cortex. Presence of this so far undescribed DCN neuron population in the lateral nucleus suggests a direct inhibitory pathway from the DCN to the cerebellar cortex

The Optokinetic Reflex as a Tool for Quantitative Analyses of Nervous System Function in Mice: Application to Genetic and Drug-Induced Variation

The optokinetic reflex (OKR), which serves to stabilize a moving image on the retina, is a behavioral response that has many favorable attributes as a test of CNS function. The OKR requires no training, assesses the function of diverse CNS circuits, can be induced repeatedly with minimal fatigue or adaptation, and produces an electronic record that is readily and objectively quantifiable