Optogenetic dissection of motor cortex dynamics an.. (OptoMotorPath)
Optogenetic dissection of motor cortex dynamics and pathways
(OptoMotorPath)
Start date: Nov 1, 2014,
End date: Oct 31, 2019
PROJECT
FINISHED
Within a densely interconnected network, selective communication can be achieved only if neuronal inputs and outputs are functionally segmented and if only one segment is selected for a given time and neural population. We focus here on this process in the primary motor cortex (M1) which projects to a variety of brain structures involved in motor generation and suppression as well as somatosensory perception. We propose to investigate what kind of information is sent to two of M1’s main target brain areas – the striatum and the somatosensory cortex by separate or partially overlapping neural subpopulations. To dissect the two pathways we will apply new optogenetic projection and stimulation strategies and combine them with controlled behavior and electrophysiological recordings conducted with advanced optoelectronic probes. The goal is to neurophysiologically characterize the two populations in a specially designed Go/NoGo task with sensorimotor component and understand their functional relevance for motor behavior. For causally defining the optimal stimulation frequencies for a specific task period, we will make use of real-time feedback by measuring ongoing oscillatory patterns and enhance or phase shift the synchronized activity in motor cortex and its targets. In particular, we will focus on beta and gamma band oscillations. While beta band activity has been mainly associated with the suppression of movements and with postural maintenance as well as sensorimotor integration and planning, elevated gamma band activity has been reported often during movement initiation and attention. We hypothesize that the best suited resonance frequencies differ between the two communication paths to S1 and striatum and that they might change across trial phases. Apart from the impact on basic science, finding out about the details of sensorimotor integration and the role of synchronization may lead to a better understanding of motor disorders, e.g. Parkinson’s disease.
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