Investigating reciprocal interactions between circuit and synaptic function

PROJECT SUMMARY/ABSTRACT The patterns of connectivity across the neural networks of the brain play a critical role in determining how those networks function. However, the mechanisms through which the architecture of a circuit supports information encoding or storage remain unclear. In addition, circuit-level activity patterns drive changes in the strength of synapses across that circuit, which in turn necessarily alters how the circuit behaves. While considerable work has elucidated many cellular and molecular components of synaptic plasticity, the precise reciprocal interaction between in vivo activity patterns, synaptic plasticity, and circuit level function remains unclear. The brain expresses several distinct types of internally generated sequences of neuronal activity independent of external sensory stimuli, and such temporally precise, self-organized sequences play a crucial role in information processing and memory formation/retrieval. Due to their independence from external inputs, internally generated sequences serve as a powerful model to explore the fundamental relationship between the connectome and network function. The hippocampus, a brain area critical for the formation of many types of memory, generates a well-defined type of neuronal sequence, sharp-wave/ripple (SWR)-associated replay, which is observed during “offline” states such as rest or sleep. The central objectives of this proposal are to identify the in vivo connectome architecture of the hippocampal network, quantify how these connection patterns regulate activity across the circuit during active “online” encoding and during “offline” SWR sequences, measure how in vivo activity patterns across this neural network change the weights of synaptic connections, and establish how those synaptic changes in turn impact circuit function. Supported by considerable preliminary data, these ambitious aims will be achieved through a combination of ultra-high density, large-scale in vivo electrophysiology followed by in-depth computational analysis of the resulting data, and rapid in vivo optical labeling of active neural populations followed by ex vivo physiological quantification of synaptic function. In Aim 1, we will directly test two models with differing predictions regarding the impact of local hippocampal connectivity on place field distribution and activity patterns during SWRs. In Aim 2, we will test the hypothesis that coordinated activity of synaptically connected neuron pairs during behavior (e.g., overlapping place fields) potentiates their synaptic connections, which in turn impacts the content of subsequent SWRs. In Aim 3, we will directly quantify the synaptic consequences of in vivo activity via whole cell electrophysiology performed in neurons which were either active or silent in an immediately prior experience. Together, this study is expected to meaningfully advance our understanding of circuit-level brain function by revealing the fundamental principles which allow precise patterns of activity to be dynamically generated and propagated throughout the hippocampal network in support of learning.