Mr. Xiaoxiao Hou Profile

Xiaoxiao Hou

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Proceedings Article | 29 August 2017 Paper

Toward multi-area distributed network of implanted neural interrogators

Marc Powell, Xiaoxiao Hou, Craig Galligan, Jeffrey Ashe, David Borton

Proceedings Volume 10352, 103520H (2017) https://doi.org/10.1117/12.2276046

KEYWORDS: Neurons, Brain, Interfaces, Sensory processes, Electroencephalography, Neural networks, Electrophysiology, Nervous system, Temporal resolution, Microfabrication

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As we aim to improve our understanding of the brain, it is critical that researchers have simultaneous multi-area, large-scale access to the brain. Information processing in the brain occurs through close and distant coupling of functional sub-domains, as opposed to within isolated single neurons. However, commercially available neural interfaces capable of sensing electrophysiology of single neurons, currently allow access to only a small, mm3 volume of cortical cells, are not scalable to recording from orders of magnitude more neurons, and leverage bulky, skull mounted hardware and cabling sensitive to relative movements of the skull and brain. In this work, we propose a system capable of recording from many individual distributed neural interrogator nodes, untethered from any external electronics. Using an array of epidural inductive coils to wirelessly power the implanted electronics, the system is intended to be agnostic to the surgical placement of any individual node. Here, we demonstrate the ability to transmit nearly 15mW of power with greater than 50% power transfer eﬃciency, benchtop testing of individual subcircuit system components showing successful digitization of neural signals, and wireless transmission currently supporting a data rate of 3.84Mbps. We leverage a software deﬁned radio based RF receiver to demodulate the data which can be stored in memory for later retrieval. Finally, we introduce a packaging technology capable of isolating active electronics from the surrounding tissue while providing capability for electrical feed-through assemblies for external neural interfacing. We expect, based on the presented preliminary ﬁndings, that the system can be integrated into a platform technology for the study of the intricate interactions between cortical domains.

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