The Dynamics and Behavioral Role of Choice-Predictive Neurons in Sensory Cortex - 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.
