Next-generation interfaces for studying neural function.

James A Frank, Marc-Joseph Antonini, Polina Anikeeva
Author Information
  1. James A Frank: Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
  2. Marc-Joseph Antonini: Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
  3. Polina Anikeeva: Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA. anikeeva@mit.edu. ORCID

Abstract

Monitoring and modulating the diversity of signals used by neurons and glia in a closed-loop fashion is necessary to establish causative links between biochemical processes within the nervous system and observed behaviors. As developments in neural-interface hardware strive to keep pace with rapid progress in genetically encoded and synthetic reporters and modulators of neural activity, the integration of multiple functional features becomes a key requirement and a pressing challenge in the field of neural engineering. Electrical, optical and chemical approaches have been used to manipulate and record neuronal activity in vivo, with a recent focus on technologies that both integrate multiple modes of interaction with neurons into a single device and enable bidirectional communication with neural circuits with enhanced spatiotemporal precision. These technologies not only are facilitating a greater understanding of the brain, spinal cord and peripheral circuits in the context of health and disease, but also are informing the development of future closed-loop therapies for neurological, neuro-immune and neuroendocrine conditions.

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Grants

  1. R01 MH111872/NIMH NIH HHS
  2. R01 NS086804/NINDS NIH HHS

MeSH Term

Brain
Diagnostic Techniques, Neurological
Electric Stimulation
Humans
Nerve Net
Neurons

Word Cloud

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