From Neurons to Microcircuits of Hippocampus: A Computational Model Based on Experimental Findings
Abstract
Network oscillations of different frequencies, durations and amplitudes are hypothesized to coordinate information processing and transfer across brain areas. Understanding the mechanisms and microcircuits involved in information processing can open up new opportunities towards scalable, efficient and brain-like cognitive skills for computation systems. This enhanced computational capability can assist soldiers for challenging warfare situations. Hippocampal sharp wave-ripples (SPW-Rs) are the most synchronous population pattern recorded in the mammalian brain. Such synchronous population patterns have beensuggested to be essential for information transfer from the hippocampus to down-stream cortical structures. To date, most of the knowledge about SPW-Rs comes from experimental studies averaging responses from a small number of neurons monitored by conventional microelectrodes with limited number of channels. On the other hand, most of the computational modelling workfor SPW-Rs has focused on small scale networks based on assumptions on connectivity to replicate or validate experimental findings. In this proposed work, we will pursue the opposite approach: utilizing experimental findings to construct a realistic biophysical model. Ourobjectives in this study are (1) to understand emergence and propagation of SPW-Rs in hippocampal microcircuits and to elucidate a complete picture of neuronal participation in SPWRs, and (2) to construct a biophysical model coupling microcircuits of the hippocampus to cortical structures to study information transfer for long term storage.The major challenge facing detailed experimental studies of SPW-Rs is the lack of a technology to monitor large number of neurons and simultaneously record responses generated by microcircuits at multiple spatial scales across the entire hippocampus. In response to that unmet need, we have developed a novel optically transparent graphene array technology. Transparency of graphene allows penetration of light for combining multiphoton imaging and optogenetic stimulation with electrophysiology. The transparent electrode technology will be a key enabler for imaging activities of large number of neurons while recording field potentialsgenerated by microcircuits with high spatio-temporal resolution. For the first time, we will obtain a dynamic map of hippocampus with cellular level spatial resolution, spike level temporal resolution, and field potentials measured at multiple scales across the entirehippocampus. This unique experimental capability will enable us to study how SPW-Rs emerge and propagate across neuronal microcircuits and how information is encoded in neuronal spikes and field potentials. In this proposal, we will pioneer an interdisciplinary approach, taking advantage of this unique neurotechnology to develop microcircuit models for different hippocampal regions based on experimental findings. In our computational model, we aim to implement functionally connected microcircuits coupled to cortical structures to investigate information transfer for learning and memory during SPW-Rs. The biophysical computational model we will develop during the course of this proposal will lead to new discoveries about how neuronal microcircuits function and how information is transferred and processed in the brain.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 23, 2016
- Source ID
- N000141612531
Entities
People
- Duygu Kuzum
Organizations
- Office of Naval Research
- United States Navy
- University of California, San Diego