PROJECT SUMMARY The loss of a functional limb due to amputation, stroke, or spinal cord injury has devastating consequences for quality of life. Brain-machine interfaces (BMIs) present a means to restore lost functionality by providing patients with voluntary control over a prosthetic limb. However, most such BMIs lack somatosensory feedback, which has severely limited their efficacy. A major reason somatosensory feedback remains absent from neural prostheses is that we have yet to understand the relationship between neural activity in sensory cortex and behavior. One approach to relating neural activity with behavior has been to study choice-related activity in sensory cortex. Choice-related activity is neural activity that can be used to predict animals’ behavioral choices and has been identified in numerous sensory areas as animals perform a variety of behavioral tasks. However, because of technological limitations, it remains unclear how choice-related activity in sensory cortex changes across learning and whether this activity is causally related to behavior. Identifying the dynamics and behavioral role of choice-predictive neurons would be a step towards linking neural activity with behavior and developing more effective BMIs. Here, I propose a series of experiments that overcome prior technological limitations and seek to clarify the role of choice-related activity in sensory cortex. Using two-photon calcium imaging, transgenic animals, and cellular-resolution gain- and loss-of-function perturbations, I will test two hypotheses: (1) that training on an optical microstimulation task drives the formation of a stable population of choice-predictive neurons in mouse somatosensory cortex and (2) that perturbation of choice-predictive neurons in this task will perturb behavior. In Aim 1, I will develop a combined LED photostimulation and two-photon imaging setup and use it to train mice to perform a discrimination task using activity evoked by the LED in sensory cortex. As animals learn the task, I will monitor neural activity in the stimulated population with cellular resolution and characterize how choice-predictive neurons change across sessions. In Aim 2, I will apply cellular-resolution, gain- and loss- of-function perturbations to choice-predictive neurons and assess how these perturbations affect task performance. These experiments will enhance our understanding of choice-related activity in sensory cortex and provide necessary insight into the link between neural activity and behavior.

PROJECT NARRATIVE Neurons in sensory cortex display activity related to animals’ choices, but it is unclear how this activity changes over learning and whether it is causally related to behavior. This project aims to expand our understanding of choice-related activity by assessing the dynamics and behavioral role of choice-predictive neurons in mouse somatosensory cortex. By linking neural activity in sensory cortex with behavior, this study may advance the development of effective brain-machine interfaces, which promise improvements in quality-of-life for patients with debilitating neurological injuries and sensorimotor deficits.