Topic: patterned perturbations

Higher cortical areas carry a wide range of sensory, cognitive, and motor signals supporting complex goal-directed behavior. These signals mix in heterogeneous responses of single neurons, making it difficult to untangle underlying mechanisms. I will present two approaches for revealing interpretable circuit mechanisms from heterogeneous neural responses during cognitive tasks. First, I will show a flexible nonparametric framework for simultaneously inferring population dynamics on single trials and tuning functions of individual neurons to the latent population state. When applied to recordin

Targeted photostimulation optogenetics offers unprecedented precision in perturbing neural circuits in action. However, due to the complexity of neural responses, perturbing neurons chosen randomly or based on their task selectivity often produces weak or counter-intuitive effects. Recurrent neural networks (RNNs) trained to replicate neural activity and task behavior hold promise for guiding the design of targeted perturbations. Yet, it remains uncertain whether low-dimensional neural responses during cognitive tasks sufficiently constrain high-dimensional models to predict outcomes of patter