Next-generation interfaces for studying neural function


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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Fig. 1: Overview of neuronal communication.

Debbie Maizels/Springer Nature

Fig. 2: Probes for electrical stimulation and recording of neural activity.

Debbie Maizels/Springer Nature

Fig. 3: Optical neural stimulation and recording via genetic or non-genetic tools; sensitivity, orthogonality and requirements for hardware.

Debbie Maizels/Springer Nature

Fig. 4: Chemical sensing with voltammetry and microdialysis.

Debbie Maizels/Springer Nature

Fig. 5: Technologies for chemical modulation and delivery.

Debbie Maizels/Springer Nature

Fig. 6: Multimodal integration.

Debbie Maizels/Springer Nature


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This work was supported in part by the National Institute of Neurological Disorders and Stroke (5R01NS086804), the National Institutes of Health BRAIN Initiative (1R01MH111872), the National Science Foundation through the Center for Materials Science and Engineering (DMR-1419807) and the Center for Neurotechnology (EEC-1028725), and by the McGovern Institute for Brain Research at MIT.

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J.A.F. and M.-J.A. researched data for the article. J.A.F., M.-J.A. and P.A. discussed the article scope and wrote the manuscript.

Correspondence to Polina Anikeeva.

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