Monitoring Communication in Neuronal Networks in Real Time and at Single Cell Resolution

2018 Seed Grant
Andre Berndt, Ph.D.
University of Washington

Visualizing the flow of information through the complex and intertwined networks of the brain is a long‐sought goal of neuroscience. Genetically encoded proteins such as the fluorescent calcium sensor GCaMP provide tremendous advantages for analyzing neuronal activity. Protein expression can be restricted to specific neuronal subtypes enabling us to probe their function in isolation from surrounding cells in real time and with single cell resolution. Consequently, we could dissect brain function in even more detail by visualizing crucial signals such as action potentials or neurotransmitter release. However, the number of sensors that provide applicable readout capabilities is limited, and new designs depend on slow and iterative engineering cycles. We have built one of the fastest platforms for functional screening of voltage and ligand‐activated sensors. We hypothesize that the significant increase in testing throughput will allow us to generate a new generation of applicable tools at unprecedented speeds. We propose to rapidly develop novel fluorescent protein sensors for quantifying the excitatory and inhibitory activity of neuronal networks. We will utilize these new sensors in much faster timeframes and directly monitor the impaired excitatory and inhibitory activity in mouse models with severe autistic and epileptic phenotypes. Monitoring impaired network dynamics in real time and at large scale will close critical knowledge gaps in our understanding of the physiology underlying neuronal dysfunction. These insights will be crucial for developing therapies and interventions which could significantly improve the outcome of patients and their caregivers.

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Erin M. Gibson, Ph.D., Stanford University
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Byoung Il Bae, Ph.D., University of Connecticut
Unique Vulnerability of Developing Human Cerebral Cortex to Loss of Centrosomal Protein
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