Computational Neuroscience InitiativeMichele Insanally
Department of Otolaryngology
Department of Neurobiology
University of Pittsburgh
Contributions of diverse cortical neuron responses to auditory perceptual learning
Flexible responses to sensory cues in dynamic environments are essential for adaptive auditory-guided behaviors such as navigation and communication. How do neural circuits flexibly gate sensory information to select appropriate behavioral strategies based on sensory input and context? Auditory neural responses during behavior are diverse, ranging from highly-reliable ‘classical’ responses (i.e. robust, frequency-tuned cells) to irregular or seemingly random ‘non-classically responsive’ firing patterns (i.e., nominally non-responsive cells) that fail to demonstrate any significant trial-averaged responses to sensory inputs or other behavioral factors. While classically responsive cells have been extensively studied for decades, the contribution of non-classically responsive cells to behavior has remained underexplored despite their prevalence. Using a single-trial, spike-timing-dependent Bayesian decoder we’ve shown that non-classically responsive cells in auditory cortex (AC) and secondary motor cortex (M2) contain significant stimulus and choice information and encode flexible task rules. Moreover, in a spiking recurrent neural network model both classically and non-classically responsive units are essential for asymptotic task performance, however their role during learning is unknown. To address this, we explored how diverse cortical responses emerge and evolve during flexible behavior. Strikingly, we found that the proportion of task-encoding non-classically responsive neurons significantly increased during late learning when the largest behavioral improvements occur demonstrating that non-classically responsive neurons are preferentially recruited during learning. To identify the role of top-down feedback on AC circuits during key learning phases we optogenetically silenced M2→AC projection neurons while recording AC spiking responses. Remarkably, silencing M2 inputs selectively modulated non-classically responsive cells and impaired behavioral performance during post-reversal learning. Our findings demonstrate that task-encoding non-classically responsive cells are preferentially recruited during learning by top-down inputs enabling neural and behavioral flexibility.
A pizza lunch willl be served.