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

Abstract

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.

Mechanisms underlying vestibulo‐cerebellar motor learning in mice depend on movement direction

“…In line with that previously shown in sinusoidal training paradigms (Raymond & Lisberger, ; Badura et al . ), the SSs showed a substantial increase in firing rate during the initial segments of the individual training cycles, during which the eyes moved into the n–t direction (Fig. B ).…”

“…; Badura et al . ; Titley and Hansel, ). Based on previous studies in mutants in which various forms of plasticity and/or parts of the cerebellar cortical network are affected (Schonewille et al .…”

“…; Badura et al . , ). Hence, we hypothesize that gain–increase and gain–decrease trainings can both be optimally executed during contraversive head movements and that the levels of increase and decrease of both SS and eye movement gain depend on the level of concomitant climbing fibre activity, with low climbing fibre activity leading to gain–increases and vice versa because of the windows of opportunity set by the synergistic forms of plasticity (Gao et al .…”

Nonspecific synaptic plasticity improves the recognition of sparse patterns degraded by local noise

“…S5), and, consequently, increased the number of patterns the PC could store with an s/n ratio >4 (from ~200 with simple LTD to more than 800 with combined LTP and nsLTD). This importance of LTP-induced weight homeostasis may explain the observed need for LTP in motor learning424344.…”

Homeostatic cerebellar compensation of age-related changes of vestibulo-ocular reflex adaptation: a computational epidemiology study

“…Computationally, (i.e., tonic firing mode, see Luque et al, 2019). PCs also integrated the error-related 8 LTD) modulated PF-PC and MF-MVN synapses (Clopath et al, 2014, Badura et al, 2016, whereas the remaining synaptic connections in the model were either non plastic or electrical, as between IO cells ( Fig. 1C; see Methods).…”