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. 2016 Feb 1;115(2):1043-62.
doi: 10.1152/jn.00960.2015. Epub 2015 Dec 2.

Optogenetic Spatial and Temporal Control of Cortical Circuits on a Columnar Scale

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Free PMC article

Optogenetic Spatial and Temporal Control of Cortical Circuits on a Columnar Scale

Arani Roy et al. J Neurophysiol. .
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Abstract

Many circuits in the mammalian brain are organized in a topographic or columnar manner. These circuits could be activated-in ways that reveal circuit function or restore function after disease-by an artificial stimulation system that is capable of independently driving local groups of neurons. Here we present a simple custom microscope called ProjectorScope 1 that incorporates off-the-shelf parts and a liquid crystal display (LCD) projector to stimulate surface brain regions that express channelrhodopsin-2 (ChR2). In principle, local optogenetic stimulation of the brain surface with optical projection systems might not produce local activation of a highly interconnected network like the cortex, because of potential stimulation of axons of passage or extended dendritic trees. However, here we demonstrate that the combination of virally mediated ChR2 expression levels and the light intensity of ProjectorScope 1 is capable of producing local spatial activation with a resolution of ∼200-300 μm. We use the system to examine the role of cortical activity in the experience-dependent emergence of motion selectivity in immature ferret visual cortex. We find that optogenetic cortical activation alone-without visual stimulation-is sufficient to produce increases in motion selectivity, suggesting the presence of a sharpening mechanism that does not require precise spatiotemporal activation of the visual system. These results demonstrate that optogenetic stimulation can sculpt the developing brain.

Keywords: activity-dependent plasticity; direction selectivity; optogenetics.

Figures

Fig. 1.
Fig. 1.
ProjectorScope 1. A: schematic. Projector path (dashed cyan lines): the image of a liquid crystal display (LCD) projector is brought into focus on the surface of the brain by a pair of lenses (L1 and L2) and a ×4 or ×10 objective (OBJ). A dichroic mirror (DM) reflects light of certain wavelengths while permitting light of other wavelengths to be imaged at the CCD camera (CCD) via a tube lens (TL). When the projector was driven at its maximum luminance on the blue channel, the irradiance measured at the objective ranged from 8 to 11 mW/mm2. Brightfield path (solid yellow lines): external light (LIGHT) is provided to permit brightfield imaging of the brain surface. Epifluorescence path (short-dashed green and yellow lines): for epifluorescence imaging, the projector dichroic mirror is removed, and a new epifluorescence dichroic mirror is installed (DM, gray). A halide light source (via a liquid light guide, LLG) is used along with excitation (EX) and emission (EM) filters to perform epifluorescence microscopy. B: test image (Boston Red Sox logo) (using a half-mirror for DM) on a US dime, illustrating minification of the projector image. C: epifluorescence yellow fluorescent protein (YFP) image of the brain surface, showing area with strong channelrhodopsin-2 (ChR2)-YFP expression, for guiding electrode placement. D: images of surface stimulation. Left: brightfield image of brain surface under thin layer of agarose, with superimposed outline of target stimulation site. Right: activation of stimulation site, as viewed by CCD camera. E, left: average optogenetically evoked response rates with a full-field flash stimulus (solid lines) or a grating stimulus (spatial frequency = 2.5 cycles/mm, dashed lines), using full spectral illumination (black lines) or blue channel only illumination (cyan lines), for 2 animals. Right: lack of optogenetically driven responses in 7 animals without ChR2. This shows that the bright optogenetic stimulus on the brain did not drive visual cortex through the eyes via reflection or via some other process. F: histogram of the maximum response rates evoked by optogenetic stimulation for all single-unit recordings and multiunit sites (N = 117) in ChR2 animals. On average, 28 spikes/s were evoked. Visually evoked responses at this age range from 3 to 10 Hz (Clemens et al. 2012; Van Hooser et al. 2014), so, on average, we are able to evoke stronger responses optogenetically than with visual stimuli. Optogenetic stimulus intensity can be reduced to match visually evoked rates.
Fig. 2.
Fig. 2.
Optogenetically driven surface receptive zones indicate local control of cortical circuits with ProjectorScope 1. A: optogenetic receptive zones (ORZs) for 4 recording sites. False color: average response to flashed circles of 90-μm diameter, with maximum response noted at bottom. Black line, fit of full width at half-height (FWHH) of a Gaussian surface receptive field fit with a Naka-Rushton summation response to light pulses of several sizes (see methods). B: fits of ORZ for several cells recorded on the same multichannel electrode from the same animal, showing locations of ORZ locations across the cortical surface. Color indicates electrode pad (key at right). C: average FWHH for 2 animals and with 2 light levels for 1 animal (∼30 mW/mm2 and 15 mW/mm2). FWHH is shown for each axis (major and minor) of the elliptical ORZ fit. ORZs are typically smaller than 200–300 μm in diameter and are smaller when lower light intensity is used. D: fraction of sites that exhibited a significant response as a function of spot size. E: maximum firing rate of response to increasing spot sizes. F: coefficient of variation (CV) of responses to increasing spot sizes. As spot size increases, the variability of the response is reduced.
Fig. 3.
Fig. 3.
Temporal modulation of cortical neurons with trains of optogenetic full-field pulses. A and B: responses of 2 example neurons to a train of 10 pulses of 500-ms duration (A; 500 ms ON/500 ms OFF) or 33.4-ms duration (B; 33.4 ms ON/33.4 ms OFF). C: fraction of pulses that resulted in at least 1 spike (“success rate”) for different pulse durations. D: average 1st pulse firing rate of sites (N = 95) for different pulse durations; responses are the number of spikes divided by the duration of the stimulation (spikes/s). E: adaptation of firing rate response as a function of pulse number within a train. F and G: distribution across recording sites of response latencies (F) and 1st spike jitter (G) for all 60 pulses within the 500 ms ON/500 ms OFF train. The projector light response, which depends on the liquid crystal reaction time, is superimposed in blue in F. H–K: response resonances. H: raster and peristimulus time histogram (PSTH) of responses to all 60 pulses in the 500 ms ON/500 ms OFF case. I: autocorrelograms (ACH) of same sites. Yellow lines indicate smoothed ACH for oscillation score (Muresan et al. 2008). J: peak frequency of smoothed ACH for each site. K: oscillation scores indicate substantial resonance.
Fig. 4.
Fig. 4.
Temporal modulation of cortical neurons with optogenetic sinusoidal gratings. A: responses of a single neuron to sinusoidal gratings at different temporal frequencies (TFs). In each case, the neuron responds at a consistent phase at the stimulus temporal frequency. Firing rates are shown by PSTHs with bin size equal to 1/TF/10. B: average modulation at the stimulus temporal frequency (F1 component) for a range of stimulus temporal frequencies. Higher modulation rates at higher temporal frequencies reflect precise spike timing at those higher temporal frequencies. C: log-log plot of the average Fourier amplitude coefficients of spike responses to 2-Hz stimulation, which was commonly employed in optogenetic training experiments. There is a clear peak at the stimulus temporal frequency (2 Hz) and weak modulation at ∼35 Hz. D: average Fourier amplitude coefficients of responses to several stimulus temporal frequencies. Each column is the spectrum for a different stimulus temporal frequency. Shading indicates coefficient value (white is 0, black is maximum for each column). In each case, the largest modulation component (darkest bar) is at the stimulus temporal frequency.
Fig. 5.
Fig. 5.
Different categories of model circuits and plasticity mechanisms that could, in principle, underlie the development of direction selectivity. A: example of a circuit that becomes direction selective on the basis of changes in synaptic weights from feedforward lateral geniculate nucleus (LGN) connections (Blais et al. 2000; Feidler et al. 1997). After sufficient exposure, weights from LGN cells at specific latencies and spatial positions become strengthened, and the cortical cell exhibits direction selectivity. Under this circuit, activation of the cortex itself would not produce direction selectivity. B: example of a circuit that becomes direction selective on the basis of sharpening of initial biases within cortical circuits. The model depicted here undergoes activity-dependent increases in intracortical inhibition (see Garkun and Maffei 2014; Van Hooser et al. 2014), which would increase any difference between suprathreshold responses to preferred and null directions that existed initially. Under this circuit, activating cortex by itself should cause increases in direction selectivity; however, the spatiotemporal characteristics of the cortical activation should not influence the direction preference that emerges. C: example of a circuit that develops direction selectivity on the basis of space-specific strengthening and weakening of horizontal connections (Shon et al. 2004; Wenisch et al. 2005). In the initial circuit, horizontal connections have moderate strengths. With stimulation in 1 direction, say rightward, spike-timing-dependent plasticity at the horizontal connections causes an asymmetric strengthening of connections from cells whose receptive fields are opposite the preferred direction (to the left here) and a commensurate weakening of connections from cells whose receptive fields are in the preferred direction (to the right here). These altered connections cause an amplification of responses in the preferred direction and a reduction of responses in the null direction, producing increased direction selectivity. Under this circuit, activating cortex with drifting sinusoidal waves should cause an increase in direction selectivity, and the direction preference that is acquired should match the sweep direction. Spatially broad activation of the cortex should not cause an increase in direction selectivity in this class of circuit models.
Fig. 6.
Fig. 6.
Prolonged optogenetic stimulation experiment. A: schematic of the experiment. B: simplified diagram of the mapping of retinal space onto the surface of primary visual cortex in the ferret (Law et al. 1988). C and D: schematic drawings of the optogenetic constant stimulus (C), which was a full-field stimulus 1 s in duration, and the optogenetic motion stimulus (D), which was a drifting sinusoidal grating moving across the cortical surface.
Fig. 7.
Fig. 7.
Direct surface stimulation of the immature visual cortex causes a rapid increase in direction selectivity. A–C: visually driven direction tuning curves measured before and after several hours of training with an optogenetic motion stimulus. The estimated direction, in retinal coordinates, of the optical motion stimulus is shown in gray. Time indicates time since initial recording; ∼1.5 h of surface training was provided during each 3-h recording interval. DI, direction index; ΔDIs, change in signed DI. The signed DI is the absolute DI multiplied by +1 if the empirically measured direction preference of the cell is within 90° of the training direction (in retinal coordinates) and −1 if the measured direction preference differs by >90°. Some cells increased DI without switching their empirical direction preference (A); other cells reversed to match the training direction (B), while others reversed to be opposite the training direction (C). D: DI measurements at each recording site vs. time for optogenetic constant training stimuli (i), optogenetic motion training stimuli (ii), and optogenetic motion training stimuli delivered to control animals that lacked ChR2 (iii). Left: scatterplots. Right: histograms of mean values that were obtained over indicated time intervals (error bars are SE; individual points are shown on right of each bar). Animals with ChR2 that were provided optogenetic motion or optogenetic constant training exhibited robust increases in direction selectivity (regression slope > 0 with P < 0.001 for both cases), but no significant increase was observed in animals that lacked ChR2 (slope not different from 0, P = 0.13). While the regression slopes in Di and Dii were highly significant, other factors would be needed to more completely describe the variation in the data around the mean (r2 = 0.14, 0.10, 0.09, for Di–Diii, respectively). *Significant relationships in means over intervals (ANOVA, P < 0.05). E: changes in DI at individual sites for optogenetic motion stimulation (red) and optogenetic constant stimulation (green). Individual sites are linked by lines. Data are separated into sites with initial DI < 0.5 (left) and those with initial DI ≥ 0.5 (right). Sites with weak initial DI values tended to exhibit increases in DI, while sites with strong initial DI values tended to maintain those values, indicating that the increases in Di and Dii are due to increases in DI at individual sites, and not due to a loss of visual responsiveness of weakly selective sites.
Fig. 8.
Fig. 8.
No evidence of a relationship between the optogenetic surface motion training direction and the final visual direction preference. A: signed DI of the initial and final measurement of each site. Positive DI indicates that the visual direction preference was within 180° of the estimated corresponding retinal direction of the optogenetic surface motion training; negative DI indicates that the visual direction preference differed from the estimated corresponding retinal direction by >180°. Cells from individual animals are indicated in different colors; the mean for each animal is indicated by an X. Some cells switched sign to match the corresponding retinal training direction (top left quadrant) while others switched sign to differ from the corresponding retinal training direction (bottom right quadrant), and many cells kept the same sign, regardless of whether they initially matched (positive signs, top right quadrant) or differed from (negative signs, bottom left quadrant) the corresponding retinal training direction. So while direction selectivity increased overall, visual direction preference was not related to the corresponding retinal training direction. B: relationship between the initial visual orientation preference of neurons (rotated so the training orientation is 0) and the increase in direction selectivity. Left: for brain surface training with ProjectorScope 1, there was no relationship between the visual orientation preference and the increase in direction selectivity (P = 0.8220). Right: for visual motion training stimulation through the eyes, there was a strong relationship (P < 0.001); cells whose orientation preferences match the visual training orientation tend to show much stronger increases in direction selectivity after training. This indicates that the increases in direction selectivity with brain surface training were nonspecific and were not influenced by the direction of the stimulus for brain surface motion training.
Fig. A1.
Fig. A1.
ProjectorScope 1 technical diagram (see text).
Fig. A2.
Fig. A2.
Photographs of ProjectorScope 1. Left: the base of the ProjectorScope 1, removed from the rig and projector. Right: the ProjectorScope 1 in place with the projector.
Fig. A3.
Fig. A3.
Modulation transfer function: the empirical brightness of alternating black and white bars passed through the ProjectorScope 1 alone (blue ○) and through ∼1.5 mm of agarose (red ×) toward a target (a glass slide). Brightness was examined on the opposite side of the slide with a second camera (IDS u-Eye) through a ×4 lens, such that the light only passed through the agarose once. Fits are 3rd-order polynomial fits of the data points.
Fig. A4.
Fig. A4.
Conversion from cortical space to visual space. We used the visuotopic map of Law et al. (1988) to produce a rough projection between retinotopic space and cortical space. Colors indicate directions in visual and cortical space. That is, the green arrow indicates that medial-to-lateral travel in cortical space corresponds to movement in an upward direction in visual space. Degree numbers on visual space panel indicate the transformation between visual space and the coordinate frame of our visual stimulus monitor (that is, 0° stimulus on visual stimulus monitor corresponds to upward motion). Degree numbers in cortex panel indicate the transformation between the cortical directions and the projector (empirically determined from the rotation of the image of the projector on the cortical surface). That is, a 0° stimulus sweeps in posterior-medial direction on the cortical surface, whereas a 120° stimulus sweeps in medial-to-lateral motion that corresponds to upward motion in visual space.
Fig. A5.
Fig. A5.
A: adeno-associated viruses (AAVs) caused widespread expression of ChR2 over several millimeters and across all cortical layers. Left: anti-green fluorescent protein (GFP) (ChR2) staining (in magenta) shown in a horizontal section through the expression zone in V1 (×4 magnification). A-P axis is anterior-posterior axis; M-L axis is medial-lateral axis. Right: anti-NeuN (all cells, in green) and anti-GFP (only ChR2-expressing cells, in blue) staining are shown at higher magnification (×10) from the same section at location indicated by yellow arrow. Inset, right: higher-magnification view (×20). High-resolution images of neurons stained for both NeuN and YFP indicated that virtually all cells that were positive for NeuN also expressed ChR2, suggesting wide staining of both excitatory and inhibitory neurons, as documented previously for high-titer, high-volume injections (Nathanson et al. 2009). B: normalized fluorescence intensity measured along a path across each slice (see yellow line in A), averaged from several slices from each of 4 animals.
Fig. A6.
Fig. A6.
Within-train adaptation for all stimulus ON and OFF times. For moderate and long stimulus ON times, neurons exhibited modest adaptation. For very short stimulus ON times, neurons exhibited some weak facilitation. These adaptation data indicate that there are limits to the action potential trains that can be produced in the cortex through the ProjectorScope 1. FR, firing rate.
Fig. A7.
Fig. A7.
Example extracellular recording data from 1 multiunit site. Top: before cortical stimulation. Bottom: after 6 h of stimulation. In each panel, single-trial raw voltage trace and spike rasters for 5 trials for visual responses to 2 opposite direction angles 90 and 270 are shown on left. On right, the individual spike waveforms (black) and average spike waveforms are shown. While responses to the 2 opposite directions were similar before cortical stimulation, after prolonged stimulation the responses to angle 90 were stronger in this case. These data show an example of spiking activity that remained robust over time.
Fig. A8.
Fig. A8.
Direction selectivity and orientation selectivity as assessed by circular variance methods. Several studies have indicated that selectivity indexes that are based on circular variance are more robust than those based purely on a preferred-to-null ratio (Grabska-Barwinska et al. 2012; Mazurek et al. 2014; Ringach et al. 2002). A: direction selectivity of neurons in the 3 experimental groups as assessed by 1-direction circular variance (1-DCV). The statistically significant differences are identical to those reported for the direction index DI that was used in Fig. 7D. B: orientation selectivity in the 3 experimental groups measured over time. There were no differences in orientation selectivity across time in the optical motion stimulation case (ANOVA, P = 0.87) or the optical constant stimulation case (ANOVA, P = 0.73), but we did observe an increase in orientation selectivity in the control case, where we performed optical motion stimulation without ChR2 (ANOVA, P < 0.001).
Fig. A9.
Fig. A9.
Changes in responsiveness over time. A: raw responses tended to decline throughout the duration of the experiment in all conditions. B: normalized response magnitude across conditions and time. Declines were similar across conditions, except that neurons exposed to optical constant stimulation exhibited slightly higher responses in the time interval 1–4 h than the other conditions (ANOVA, Tukey-Kramer post hoc test, P < 0.05). C: fraction of electrodes with neurons that exhibited a significant degree of orientation tuning via an ANOVA test across responses and blank (with P < 0.05). No statistically significant differences were found across the 3 experimental conditions (P = 0.06). D: a small amount of the increase in direction selectivity over time in the optical motion stimulation and optical constant stimulation cases can be explained by an overall reduction in firing rate in the neurons across time. The slope of the correlation is significant (P < 0.001), but the amount of variance explained by response magnitude is relatively small (r2 = 0.12).

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