Cerebellar granule cells, which constitute half the brain’s neurons, supply Purkinje cells with contextual information necessary for motor learning, but how they encode this information is unknown. Here we show, using two-photon microscopy to track neural activity over multiple days of cerebellum-dependent eyeblink conditioning in mice, that granule cell populations acquire a dense representation of the anticipatory eyelid movement. Initially, granule cells responded to neutral visual and somatosensory stimuli as well as periorbital airpuffs used for training. As learning progressed, two-thirds of monitored granule cells acquired a conditional response whose timing matched or preceded the learned eyelid movements. Granule cell activity covaried trial by trial to form a redundant code. Many granule cells were also active during movements of nearby body structures. Thus, a predictive signal about the upcoming movement is widely available at the input stage of the cerebellar cortex, as required by forward models of cerebellar control.
The inferior olive projects climbing fiber axons to cerebellar Purkinje neurons, where they trigger calcium-based dendritic spikes. These responses dynamically shape the immediate spike output of Purkinje cells as well as provide an instructive signal to guide long-term plasticity. Climbing fibers typically fire approximately once a second, and the instructive role is distributed over many such firing events. However, transmission of salient information on an immediate basis needs to occur on a shorter timescale during which a Purkinje cell would typically be activated by a climbing fiber only once. Here we show using in vivo calcium imaging in anesthetized mice and rats that sensory events are rapidly and reliably represented by momentary, simultaneous coactivation of microbands of adjacent Purkinje cells. Microbands were sagittally oriented and spanned up to 100 m mediolaterally, representing hundreds of Purkinje cells distributed over multiple folia. Spontaneous and sensory-evoked microbands followed boundaries that were close or identical to one another and were desynchronized by olivary injection of the gap junction blocker mefloquine, indicating that excitation to the olive is converted to synchronized firing by electrical coupling. One-time activation of microbands could distinguish a sensory response from spontaneous activity with up to 98% accuracy. Given the anatomy of the olivocerebellar system, microband synchrony may shape the output of neurons in the cerebellar nuclei either via powerful inhibition by Purkinje cells or by direct monosynaptic excitation from the inferior olive.
In vivo multiphoton fluorescence microscopy allows imaging of cellular structures in brain tissue to depths of hundreds of micrometers and, when combined with the use of activity-dependent indicator dyes, opens the possibility of observing intact, functioning neural circuitry. We have developed tools for analyzing in vivo multiphoton data sets to identify responding structures and events in single cells as well as patterns of activity within the neural ensemble. Data were analyzed from populations of cerebellar Purkinje cell dendrites, which generate calcium-based complex action potentials. For image segmentation, active dendrites were identified using a correlation-based method to group covarying pixels. Firing events were extracted from dendritic fluorescence signals with a 95% detection rate and an 8% false-positive rate. Because an event that begins in one movie frame is sometimes not detected until the next frame, detection delays were compensated using a likelihood-based correction procedure. To identify groups of dendrites that tended to fire synchronously, a k-means-based procedure was developed to analyze pairwise correlations across the population. Because repeated runs of k-means often generated dissimilar clusterings, the runs were combined to determine a consensus cluster number and composition. This procedure, termed meta-k-means, gave clusterings as good as individual runs of k-means, was independent of random initial seeding, and allowed the exclusion of outliers. Our methods should be generally useful for analyzing multicellular activity recordings in a variety of brain structures.
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