Microglia sense the changes in their environment. How microglia actively translate these changes into suitable cues to adapt brain physiology is unknown. We reveal an activity-dependent regulation of cortical inhibitory synapses plasticity by microglia, driven by purinergic signaling acting on P2RX7 and mediated by microglia-derived TNFα. We demonstrate that sleep induces this microglia-dependent inhibitory plasticity by promoting synaptic enrichment of GABAARs. We further show that in turn, microglia-specific depletion of TNFα alters slow waves during NREM sleep and blunts sleep-dependent memory consolidation. Together, our results reveal that microglia orchestrate sleep-intrinsic plasticity of inhibitory synapses, ultimately sculpting sleep slow waves and memory.
Chronic Levodopa therapy, the gold-standard treatment for Parkinson’s Disease (PD), leads to the emergence of involuntary movements, called levodopa-induced dyskinesia (LID). Cerebellar stimulation has been shown to decrease LID severity in PD patients. Here, in order to determine how cerebellar stimulation induces LID alleviation, we performed daily short trains of optogenetic stimulations of Purkinje cells (PC) in freely moving LID mice. We demonstrated that these stimulations are sufficient to suppress LID or even prevent their development. This symptomatic relief is accompanied by the normalization of aberrant neuronal discharge in the cerebellar nuclei, the motor cortex and the parafascicular thalamus. Inhibition of the cerebello-parafascicular pathway counteracted the beneficial effects of cerebellar stimulation. Moreover, cerebellar stimulation reversed plasticity in D1 striatal neurons and normalized the overexpression of FosB, a transcription factor causally linked to LID. These findings demonstrate LID alleviation and prevention by daily PC stimulations, which restore the function of a wide motor network, and may be valuable for LID treatment.
Perception generates time-invariant objects and categories from time-varying streams of information. However, individual neuron responses, even in cortex, are not time-invariant as they usually track the temporal variations of the input. Here we show that representations of time-varying sounds remain decodable even after time-averaging at the level of neuronal populations in the mouse auditory cortex. This population-scale, time-invariant property is absent in subcortical auditory regions. By implanting light-sculpted artificial representations in the cortex with optogenetics, we show that robustness to time-averaging is a necessary property for rapid association of neural representations with behavioral output. Moreover, deep neural networks which perform sound recognition and categorization tasks generate population representations that become robust to time-averaging in their deeper layers. Hence, the auditory cortex implements a generic transformation that replicates temporal information into time-independent neural population dimensions and makes it available for learning and classification.
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