Understanding how cortical circuits give rise to perception-allowing us, for example, to hear and see the world-remains a central challenge in neuroscience. The application of concepts from cognitive science, such as Representational Similarity Analysis, has proven valuable for interpreting large-scale neuronal recordings, including in rodent models. In this work, I present recent efforts from our laboratory to characterize the structure of auditory representations in the mouse cortex and demonstrate how these representations can be used to predict behavioral phenomena such as stimulus generalization and perceptual choice biases. Moreover, leveraging neuronal activity recordings at single-cell resolution, I describe our findings on the circuit mechanisms that organize sound-evoked activity into structured representational maps and maintain their integrity in the face of perturbations, including synaptic volatility and neuronal loss.
