A Platform for Spatiotemporal “Matrix” Stimulation in Brain Networks Reveals Novel Forms of Circuit Plasticity - Wilson, Nathan R.; Wang, Forea L.; Chen, Naiyan; Yan, Sherry X.; Daitch, Amy L.; Shi, Bo; Sharma, Samvaran; Sur, Mriganka (Frontiers in Neural Circuits, 2022)
Here we demonstrate a facile method by which to deliver complex spatiotemporal stimulation to neural networks in fast patterns, to trigger interesting forms of circuit-level plasticity in cortical areas. We present a complete platform by which patterns of electricity can be arbitrarily defined and distributed across a brain circuit, either simultaneously, asynchronously, or in complex patterns that can be easily designed and orchestrated with precise timing. Interfacing with acute slices of mouse cortex, we show that our system can be used to activate neurons at many locations and drive synaptic transmission in distributed patterns, and that this elicits new forms of plasticity that may not be observable via traditional methods, including interesting measurements of associational and sequence plasticity. Finally, we introduce an automated "network assay" for imaging activation and plasticity across a circuit. Spatiotemporal stimulation opens the door for high-throughput explorations of plasticity at the circuit level, and may provide a basis for new types of adaptive neural prosthetics.