For animals to execute complicated behaviors, successful motor planning and execution is essential. Moreover, the sequence of events leading to successful goal-based behavior takes place over a wide range of timescales. For example, when walking from home to work, one must first make an abstract, long-timescale decision to go to work, which much then be translated into a sequence of shorter-timescale right-left turning decisions, which are translated into the finely fluctuating electrical patterns that control the muscles. How motor planning and execution occur simultaneously over many timescales in populations of motor cortex neurons is not well understood. Much work in humans and nonhuman primates have shown that visual and auditory stimuli integrate over multiple timescales. This work has shown that early sensory regions, like primary visual cortex, respond to fast fluctuations in the environment. This information is integrated to longer-timescale information in secondary cortical regions, with the longest- timescale information in frontal and association areas. We therefore hypothesize that secondary motor cortex (M2) neurons control behavior over longer timescales than primary motor cortex (M1) neurons. To study this phenomenon, I have built a setup in which head-fixed mice navigate in virtual reality to a rewarded location. In this setup, I can record video from all sides of the animal for high spatiotemporal resolution measurement of motor behaviors. I have developed machine learning algorithms to extract 3D pose data from these videos.
In Aim 1, I will use calcium imaging to record large numbers of neurons in mouse M1 and M2 to correlate the activity of individual neurons and populations to the animal?s ongoing pose kinematics. We will supplement with targeted silicon probe recordings to capture fast neural responses.
In Aim 2, I will compare the calcium dynamics in populations of M1 and M2 neurons in mice trained to perform a virtual motor planning task versus mice that have not been trained. We hypothesize that training to plan motor actions increases the timescale of M1/M2 neural activity.
In Aim 3, we will use optogenetic silencing in specific regions of cortex to perturb the animal?s motor behavior. We hypothesize that the duration of the perturbed movements will be longer when M2 is perturbed than M1. In this way, we will study how different cortical regions relate to behavior over many timescales. This proposal will broaden our knowledge of cortical processing in general, and motor planning and execution in particular. Patients with mental illness, such as ADHD, autism, and Asperger?s disorder show impaired ability to plan upcoming movements. The first step to successfully treating these illnesses is to better understand how motor planning occurs in general.
This proposal will elucidate how motor planning and execution take place simultaneously, over many timescales, and across brain regions. Better understanding motor planning will help generate new treatments for diseases that affect motor planning, like attention deficit hyperactivity disorder and autism.
