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. 2018 May 22;12(5):4086-4095.
doi: 10.1021/acsnano.8b02758. Epub 2018 May 4.

Nongenetic Optical Methods for Measuring and Modulating Neuronal Response

Free PMC article

Nongenetic Optical Methods for Measuring and Modulating Neuronal Response

John F Zimmerman et al. ACS Nano. .
Free PMC article


The ability to probe and modulate electrical signals sensitively at cellular length scales is a key challenge in the field of electrophysiology. Electrical signals play integral roles in regulating cellular behavior and in controlling biological function. From cardiac arrhythmias to neurodegenerative disorders, maladaptive phenotypes in electrophysiology can result in serious and potentially deadly medical conditions. Understanding how to monitor and to control these behaviors precisely and noninvasively represents an important step in developing next-generation therapeutic devices. As we develop a deeper understanding of neural network formation, electrophysiology has the potential to offer fundamental insights into the inner working of the brain. In this Perspective, we explore traditional methods for examining neural function, discuss recent genetic advances in electrophysiology, and then focus on the latest innovations in optical sensing and stimulation of action potentials in neurons. We emphasize nongenetic optical methods, as these provide high spatiotemporal resolution and can be achieved with minimal invasiveness.


Figure 1.
Figure 1.. Soliton Waves Induce Membrane Displacement During Neuron Action Potential Firing.
(a) Illustration of a soliton action wave (AW) traveling through an axon during an action potential (AP), showing membrane displacement accompanying voltage propagation. (b) Predicted circumferential (i), 2Dρ (ro. x), and lateral (ii.), Dz(ro. x), membrane displacement as a function of axon radius, ro, and AP propagation speed, CAP such that x = z -CAPt, where z is the longitudinal direction and t is time. Corresponding voltage (iii), V(x), and mechanical force waves (iv), F(x), giving rise to the observed displacement. (c) Scanning electron micrograph of an experimental setup using piezoelectrical (PZT) nanoribbons to measure membrane displacement during action potential propagation, with (right) and without (left) neurons present (scale bars, 15 µm). (d) Calibrated PZT force response of neurons compared to membrane potential. Experimental data (red) is shown compared to predicted displacement (blue). Inset: Measured PZT nanoribbon response (green) showing lateral membrane displacement induced by spontaneous depolarization (blue). Inset: optical image showing the experimental patch clamp setup (scale bar, 12 µm). (e) DIC micrograph of a neuron (top) with corresponding differential imaging (upper middle) and calibrated displacement map (lower middle), indicating a shift in membrane position during axon firing (lower) (scale bars, 15 µm). Modified and reproduced with permission from A. Hady et al (a&b), T. Nguyen et al (c&d), and Y. Yang et al(e). Copyright 2015 & 2012 Springer Nature, and 2018 American Chemical Society respectively.
Figure 2.
Figure 2.. Nanomaterial Based Photothermal Stimulation of Neurons.
(a) Schematic diagram of a gold nanoparticle locally heating the cell membrane, changing the membrane’s capacitance, Cm, and inducing a depolarization event. (b) Equivalent circuit diagram, showing the net surface potential (Vs), capacitive current (Ic), membrane resistance (Rm), reversal potential (Vr) and ionic current (Ii) respectively. (c) Predicted time derivatives of capacitive current for varying laser pulse powers (high to low power, from top to bottom), indicating that Ic is maximized with higher intensity lasers at the time of pulse initiation (d) Corresponding experimentally measured photothermally induced neuronal action potential (25 × 95 gold nanorod, 785 nm, 5 mW, 1 ms laser pulse). (e) Transmission Electron Microscope (TEM) micrograph of hexagonally packed silicon nanowires, with the mesoporous structure enabling rapid localized heating (scale bar 100nm). (f) Membrane potential recordings of DRG neurons photothermally stimulated using mesoporous silicon, at different frequencies (Left, 5.32 µJ), with corresponding normalized Fast-Fourier Transforms (right). Green ticks indicate the time of delivery for the laser pulse. F and F0 are the output and input frequencies receptively. Modified and reproduced with permission from J. Carvalho-de-Souza et al. (b-d) and Y. Jiang et al. . (e-f). Copyright 2017 Elsevier and 2016 Springer Nature respectively.
Figure 3.
Figure 3.. Silicon Nanowire Photoelectrochemical Stimulation of Neurons.
(a) Scanning electron micrograph of a coaxial photovoltaic PIN-SiNW (scale bar 100 nm) (b) Schematic diagram showing DRG uptake of surface modified silicon nanowires, with corresponding time-lapse confocal fluorescent micrograph cross-sections of the process (Red-plasma membrane, Alexa 594) (Green – SiNW, Alexa 555). (c) Schematic of photoelectrochemical stimulation of neurons upon light stimulation using PIN-SiNWs. (d) Scanning electron micrograph of a DRG neuron interfacing with a PIN-SiNW. (e) Current-clamp trace of membrane voltage in a DRG neuron stimulated by injected current (blue) and laser-pulsed PIN-SiNW (green), showing comparable action potentials. Modified and reproduced with permission from B. Tian et. al. (a), J. Lee, A. Zhang S. You & C. Lieber (b). and R. Parameswaran et. al. (c-e). Copyright 2007 Springer Nature, 2016 American Chemical Society, and 2018 Springer Nature respectively.
Figure 4.
Figure 4.. Optically Enabled Feedback Networks in 2D ‘Brain’ Culture.
Human brains form complex interactions across three dimensional interconnected networks which are difficult to replicate in two dimensional in-vitro cultures. As optical probes and stimulators become more stable, researchers can imagine using these devices to mimic complex spatial interconnects, using self-contained feedback loops to artificially link disparate regions in space.

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