Resolving and manipulating neuronal networks in the mammalian brain - from correlative to causal analysis; Project: Causative Mechanisms of Mesoscopic Activity Patterns in Auditory Category Discrimination
The formation of categories is a fundamental element of cognition, and has been studied extensively to probe the functional basis of cognition. However, the circuit mechanisms of category formation, especially at the mesoscopic scale bridging single neuron activity to organismal behavior, remain largely unknown. While most previous work on category discrimination has focused on unit activity reflecting category selectivity in higher cortical areas, recent work has started to focus on such mesoscopic circuit mechanisms, especially the emergence of selectivity much earlier in the sensory processing stream, particularly within the primary auditory cortex. We have established a robust model of auditory category discrimination learning in the Mongolian gerbil, using frequency modulated (FM)-sweeps and a go/no-go shuttlebox paradigm. We have shown that mesoscopic spatial patterns of neural population activity as measured by surface ECoG arrays can accurately predict the animals behavioral/cognitive decision. In this proposal, we explore the causative mechanisms leading to such mesoscopic neural activity patterns and their behavioral outcome. In particular, we aim to first demonstrate formal neurophysiological causality by testing for both the necessity and sufficiency of the mesoscopic activity for behavioral output, and second, to investigate the single-neuronal circuit mechanisms underlying these mesoscopic patterns, using a combination of behavioral, electrophysiological and optogenetic techniques. We thereby hope to offer an important mesoscopic link between (A) the firing patterns of single neurons and resultant local oscillations, and (B) the total behavioral output of the brain as an organ.