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Oweiss, K.

Publications and source records attributed to Oweiss, K..

2 recordsLinked to original sources

High-throughput in vivo synaptic connectivity mapping of neuronal micro-circuits using two-photon holographic optogenetics and compressive sensing

Understanding the intricate synaptic connectivity in living neural circuits is crucial for unraveling the relationship between network structure and function, as well as its evolution during development, learning, and recovery from injury. However, current methodologies for identifying connected neurons in vivo suffer from limitations, particularly with regards to their throughput. In this study, we introduce a groundbreaking framework for in vivo connectivity mapping that combines two-photon holographic optogenetics for activating single or multiple potential presynaptic neurons, whole-cell recording of postsynaptic responses, and a compressive sensing strategy for efficiently retrieving individual postsynaptic neurons responses when multiple potential presynaptic neurons are simultaneously activated. The approach was validated in the layer 2/3 of the visual cortex in anesthetized mice, enabling rapid probing of up to 100 cells in approximately 5 minutes. By identifying tens of synaptic pairs, including their connection strength, kinetics, and spatial distribution, this method showcases its potential to significantly advance circuit reconstruction in large neuronal networks with minimal invasiveness. Moreover, through simultaneous multi-cell stimulation and compressive sensing, we demonstrate up to a three-fold reduction in the number of required measurements to infer connectivity with limited loss in accuracy, thereby enabling high-throughput connectivity mapping in vivo. These results pave the way for a more efficient and rapid investigation of neuronal circuits, leading to deeper insights into brain function and plasticity.

neuroscience↗

Compressive sensing of neuronal connectivity maps from subsampled, cell-targeted optogenetic stimulation of a network model

Mapping functional connectivity between neurons is an essential step towards probing the neural computations mediating behavior. The ability to consistently and robustly determine synaptic connectivity maps in large populations of interconnected neurons is a significant challenge in terms of yield, accuracy and experimental time. Here we developed a compressive sensing approach to reconstruct synaptic connectivity maps based on random two photon (2p) cell-targeted optogenetic stimulation and membrane voltage readout of many putative postsynaptic neurons. Using a biophysical network model of interconnected populations of excitatory and inhibitory neurons, we found that the mapping can be achieved with far fewer measurements than the standard pairwise sequential approach. We characterized the recall and precision probabilities as a function of network observability, sparsity, number of neurons stimulated per trial, off-target stimulation, synaptic reliability, propagation latency and network topology. We found that that network sparsity and synaptic reliability were primary determinants of the performance. In particular, in a network with 10% probability of neuronal connectivity, functional connections were recovered with >85% recall and >80% precision in half the trials that would be required for single cell stimulation. Our results suggest a rapid and efficient method to reconstruct functional connectivity of brain networks where sparsity is predominantly present.

neuroscience↗