Photons and neurons

Abstract

Methods to control neural activity by light have been introduced to the field of neuroscience. During the last decade, several techniques have been established, including optogenetics, thermogenetics, and infrared neural stimulation. The techniques allow investigators to turn-on or turn-off neural activity. This review is an attempt to show the importance of the techniques for the auditory field and provide insight in the similarities, overlap, and differences of the techniques. Discussing the mechanism of each of the techniques will shed light on the abilities and challenges for each of the techniques. The field has been grown tremendously and a review cannot be complete. However, efforts are made to summarize the important points and to refer the reader to excellent papers and reviews to specific topics. This article is part of a Special Issue entitled <Annual Reviews 2014>.

Figure 1

The plot shows the penetration depth for radiation of different wavelength into water. The data were obtained from Hale 1973. Colored sections reflect the wavelength used for the different optical methods described. Green represents the range of radiation wavelengths used for optogenetics, red for thermogenetics, optoacoustics and INS. For the red dotted line it has been shown in the rat sciatic nerve that stimulation can be achieved. However, at present, it is not possible to deliver the radiation with optical fibers.

Figure 2

Images are sections through a 3D map of light intensity along the axis of an illuminating fiber. Contour maps of the image data show iso-intensity lines at 50%, 10%, 5%, and 1% of maximum. A shows the plots for saline solution and B for rat gray matter obtained for two different radiation wavelengths, 473 nm or yellow and 594 nm or blue. Scatter in brain tissue reduces the penetration depth significantly when compared with saline solution. Also, blue light has a longer penetration depth. C–D are reproduced from Thompson et al., 2012. C–D shows an example of a Monte Carlo simulation. In the model an optical fiber is positioned 500 μm from the center of a nerve layer C. For the modeling the following parameters are assumed: λ = 1850 nm, 200 μm optical fiber, NA = 0.22, n_photons = 10¹¹, radiant energy = 25 μJ/pulse). E shows the result form the modulation and indicate little effect by the tissue on the photon distribution. D is the same as E but scaled to the plots A and B. A and B are plots reproduced from Yizhar et al. 2011.

Figure 3

The top, left panel shows an acoustic spatial tuning curve (STC) recorded on the 16-channel, penetrating electrode array inserted into the inferior colliculus. The curve gives a relative measure of the area of the cochlea activated by the acoustic tones. The inferior colliculus retains the tonotopic map of the cochlea, with high frequencies encoded at the deep layers of the IC (electrode 1) and low frequencies encoded more superficially (electrode 16). The top, right panel shows an optical spatial tuning curve for cochlear INS. The bottom, left panel shows the widths of many acoustic and optical STCs. The widths of optical STCs overlap entirely with the acoustic STCs. A smaller width indicates a more spatially selective stimulus. The bottom, right panel gives a comparison of widths (mean±s.d.) measured in our study and STC widths measured by Snyder et al. (2004) for various electrical stimulation configurations. Note that the reference values of acoustic STC widths are identical between the two studies. Panels of the figure 3 are modified figures from Richter et al. (2011).