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. 2019 Aug 9;365(6453):eaaw5202.
doi: 10.1126/science.aaw5202. Epub 2019 Jul 18.

Cortical layer-specific critical dynamics triggering perception

Affiliations

Cortical layer-specific critical dynamics triggering perception

James H Marshel et al. Science. .

Abstract

Perceptual experiences may arise from neuronal activity patterns in mammalian neocortex. We probed mouse neocortex during visual discrimination using a red-shifted channelrhodopsin (ChRmine, discovered through structure-guided genome mining) alongside multiplexed multiphoton-holography (MultiSLM), achieving control of individually specified neurons spanning large cortical volumes with millisecond precision. Stimulating a critical number of stimulus-orientation-selective neurons drove widespread recruitment of functionally related neurons, a process enhanced by (but not requiring) orientation-discrimination task learning. Optogenetic targeting of orientation-selective ensembles elicited correct behavioral discrimination. Cortical layer-specific dynamics were apparent, as emergent neuronal activity asymmetrically propagated from layer 2/3 to layer 5, and smaller layer 5 ensembles were as effective as larger layer 2/3 ensembles in eliciting orientation discrimination behavior. Population dynamics emerging after optogenetic stimulation both correctly predicted behavior and resembled natural internal representations of visual stimuli at cellular resolution over volumes of cortex.

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Conflict of interest statement

Competing interests: The MultiSLM and ChRmine methods are covered in pending patent application material; all methods, protocols, clones, and sequences are freely available to nonprofit institutions and investigators. At the conclusion of the study, J.H.M. became a member of the scientific advisory board for Bruker Fluorescence Microscopy. J.C.S. and D.J.M. are employees of BNS, manufacturer of the MacroSLM device.

Figures

Fig. 1.
Fig. 1.. ChRmine: Discovery from a marine environment of a class of opsin suitable for high-fidelity read-write experiments.
(A) Genome mining procedure. (B) Left: type-I opsin genes. Right: opsin subfamilies (scale bar denotes fractional change in amino acid sequence). (C) Left: voltage-clamp traces of red-shifted ChRs responding to 1 s of orange light (585 nm, 0.7 mW/mm2) or red light (650 nm, 0.7 mW/mm2) in cultured neurons. Right: action spectra in cultured neurons (0.7 mW/mm2; n = 5 to 7 cells/condition, one-way ANOVA with Tukey correction). (D) ChR I-V curves, −70 mV to +60 mV, in HEK cells (n = 5 to 7 cells/condition). (E) Spike probability versus light-pulse width (at 5 Hz for 2 s, 0.7 mW/mm2; n =5 to 7 cells/condition, one-way ANOVA, Tukey correction). (F) Spike probability versus light intensity (at 5 Hz for 2 s, pulse width 5 ms; n = 5 to 7 cells/ condition, one-way ANOVA, Tukey correction). (G) Top: current-clamp traces. Bottom: ChRmine spike fidelity in response to orange or blue (438 nm) light (n = 5 cells). (H) Orange light stimulation (ticks) in cultured neurons expressing GCaMP6m and ChRmine (left), CsChrimson (middle), or bReaChES (right) at pHext = 7.4. Light-pulse width varied as shown in blue shades. (I) Peak GCaMP6m responses to light pulses of varied duration [585 nm light, as in (H)]. (J) Trial-averaged kinetics of three opsins (n = 5 to 7 cells/condition, one-way ANOVA, Tukey correction). (K) Two-photon power spectrum of ChRmine across 0 to 30 mW at λ = 1035 nm. (L) Two-photon action spectrum of ChRmine (n = 6 cells, 20 mW, 12 rotations/spiral, 25-mm diameter spirals, 4-ms duration, 80-MHz laser repetition rate). (M) Left: current-clamp trace showing spike fidelity versus laser pulse frequency at λ = 1035 nm. Right: spike fidelity versus laser pulse frequency at λ = 920 nm (2.8 Hz/frame). (N) Summary of (M), n =6 cells for stimulation and n = 5 for imaging. (O) Jitter across 10 overlaid 2P-elicited ChRmine spikes (aligned to 2P stimulus timing; λ = 1035 nm, 20 mW, 12 rotations, 4-ms exposure). All plots show mean ± SEM unless otherwise noted. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.
Fig. 2.
Fig. 2.. MultiSLM: Large-volume, temporally precise all-optical microscope.
(A) Custom multi-photon 3D imaging and optogenetic stimulation microscope (MultiSLM). Inset: large field-of-view spatial light modulator (MacroSLM). See materials and methods for abbreviation definitions. (B) Neurons expressing both GCaMP6m and ChRmine from a single bicistronic virus (green: anti-GFP; magenta: anti-HA, as HA is conjugated to ChRmine-TS-Kv2.1; co-expression observed in 610 of 610 soma across nine 40-µm V1 sections from n = 3 mice). (C) Simultaneous imaging and photoexcitation across a 1mm2 field-of-view (160 total targets in six groups of neurons, 90 stimulation pulses at 29 Hz, 20 to 30 mW per target, 10 mm diameter, five revolutions). (D) Photostimulation of two cells (identified as C1 and C2, mean ± SD), separated by 1.164 mm. (E) Temporal interleaving paradigm for high-speed photostimulation of multiple neural ensembles. (F) Six nonoverlapping ensembles of 25 to 27 neurons stimulated every 1 ms, in a 1 kHz sequence (in total, 124 of 160 cells were successfully targeted at this speed in 5.2 ms, success criteria: µstim − µbaseline > 2σbaseline). (G) Targeting precision; a single neuron (target iv) can be stimulated in isolation (middle column), or in an ensemble targeted in other trials (right column). Images share common colorscale, and activity traces are mean ± SD. (H) 3D imaging with simultaneous optogenetic control across cortical layers; cellular region of interest labels are enlarged for visualization. (I) Simultaneous excitation of 27 of 30 total targets located across cortical layers 2/3 and 5 in V1 (30 total targets, 90 stimulation pulses at 30 Hz, 10 to 20 mW/target, single 0.63-ms exposure, 15-mm diameter spiral, eight revolutions). (F) and (I) on common z-score scale.
Fig. 3.
Fig. 3.. Selective visual network recruitment by functionally defined–ensemble stimulation.
(A) Schematic of experimental apparatus. (B) Top row: visual stimuli. Bottom two rows: neural responses to visual stimuli were used to define tuned ensembles for optogenetic stimulation. (C) Spatial location of neuronal ensembles identified for stimulation. There are two tuned ensembles (green, 0° cells; red, 90° cells) and size-matched random ensembles (magenta, “0°” cells; cyan, “90°” cells). (D) After ensemble identification, each group was stimulated without a visual stimulus present (0% contrast). Ensemble stimulation trials were randomly interleaved alongside visual stimulus trials without optogenetic stimulation. (E) Mean normalized Ca2+ responses for all neurons within each selective or random ensemble during optogenetic stimulation trials (colored horizontal bars indicate stimulation time). (F) Locations of tuned neurons stimulated and recruited for one experimental session overlaid on average images from each imaging plane in the volume. (G) Classifier and neural trajectory analysis scheme. (H) Unstimulated neurons from different experimental conditions (visual-only, tuned-optogenetic only, random-optogenetic only, or no stimulation) projected into PC space defined on visual-only data. Black dots, trial start; red and blue dots, first frame after visual or optogenetic stimulus onset. (I) Top two rows: mean 0° and 90° fluorescence responses in unstimulated neurons, for one mouse. Left column shows classifier weight of each neuron. Third row: first row (0° trials) − second row (90° trials). (J) Top row: mean fluorescence response of all neurons included in the classifier analysis during 0° (lighter lines) and 90° (darker lines) conditions multiplied by their classifier weights. Error bars indicate SEM. Bottom row: weighted mean responses for four mice. Vertical lines indicate the time interval for training the classifier. (K) Percent correct prediction performance of classifiers trained on visual data. ***P < 0.001, ****P < 0.0001; ns, not significant.
Fig. 4.
Fig. 4.. Eliciting a specific visual percept through targeting of individually identified neurons.
(A) Experimental apparatus with reward port. (B) Mice learn to discriminate vertical versus horizontal gratings in a Go/No-Go task. (C) Visual discrimination performance of one mouse (with ≥12% contrast, P < 0.05 Fisher’s exact tests, Target versus Distractor conditions for each session). (D) Chosen neural ensembles were stimulated alone and/or with visual stimuli. (E and F) Top row: normalized mean visual responses (50% contrast) for Target (0°) and Distractor (90°) selective ensembles. Bottom two rows: optogenetic responses for neurons within tuned (E) and random ensembles (F). (G) Discrimination performance during visual stimuli alone (black), paired with stimulation of random ensembles (blue) or with tuned ensembles (red) (P < 0.05, two-way ANOVA, main effect of stimulation type, P < 0.01 tuned and visual stimulation versus visual only, Tukey post hoc test, n = 6 mice). Logit fits are for visualization purposes only. (H) Discrimination performance of tuned ensembles before and after the contrast ramp, the following day (day 2; or third session for mouse that did not go through the ramp), and to new ensembles (P > 0.05 all unmarked pairwise comparisons, ANOVA Tukey post hoc test; data from n = 7 mice included for each condition on the basis of availability of data in each mouse). (I) Format matches (H) for random ensembles [P > 0.05 all unmarked pairwise comparisons; dotted lines indicate chance; tuned, random, and no-stimulation trials were randomly interleaved within each session; the same no-stimulation data were used in both (H) and (I)]. (J and K) Recruitment in held-out populations during optogenetic-only stimulation before contrast ramp training (tuned ensemble stimulation: P < 0.05, χ2 two tailed test, n = 6 sessions in five mice; random: P > 0.1, χ2 two-tailed test, n = 6 sessions in five mice). (L and M) Held-out recruitment during optogenetic stimulation after contrast ramp training (tuned: P < 0.0001, iso versus orthogonally tuned, χ2 two-tailed test, n = 15 sessions in five mice; random: P < 0.0001, χ2 two-tailed test, n = 13 sessions in five mice). (N) Held-out iso-tuned recruitment during optogenetic stimulation after versus before contrast ramp for tuned and random ensembles (P < 0.0001, all χ2 two-tailed). *P < 0.05, **P < 0.01, ****P < 0.0001, error bars indicate mean ± SEM in (G).
Fig. 5.
Fig. 5.. Dynamics of tuned and behaviorally potent visual ensembles.
(A) Discrimination performance during visual-only stimulation (black) and tuned-ensemble stimulation (red) over several weeks (mean ± SEM for up to five mice per time point). (B) Discrimination performance for tuned-ensemble stimulation versus visual trials (12% visual contrast behavior shown, left, P > 0.1 paired t test, two-tailed, n = 112 sessions across five mice; error bars indicate SD). (C) Locations of tuned neurons stimulated and held-out recruited neurons for one experimental session (scale bars, 100 µm). (D) Recruitment in held-out populations during optogenetic-only stimulation across all experimental days (iso-versus ortho-tuned, P < 0.0001, χ2 two- tailed test; n = 58 sessions in five mice; mice are different colored dots). (E) Recruitment in held-out populations as differently sized ensembles were stimulated (n = 232 data points from 58 sessions in five mice; iso-tuned in green, mean ± SEM, Spearman’s ρ = 0.34, P < 0.001, n = 116 data points; ortho-tuned in magenta, mean ± SEM, Spearman’s ρ = −0.24, P < 0.01, n = 116 data points). (F) Unstimulated neurons from different experimental conditions (visual-only, tuned-optogenetic only, random-optogenetic only, or no stimulation) projected into PC space defined on visual-only data. Black dots, trial start; red and blue dots, first frame after visual or optogenetic stimulus onset. Dark, bold trajectories denote conditions with erroneous licking behavior on average. (G) Top two rows: Mean target (0°) and distractor (90°) fluorescence responses in unstimulated neurons, for one mouse. Left column shows classifier weight of each neuron. Third row: first row (target trials) − second row (distractor trials). Bottom row: results from another mouse. (H) Top row: mean fluorescence response of all neurons included in the classifier analysis during 0° (lighter lines) and 90° (darker lines) conditions multiplied by their classifier weights. Error bars indicate SEM. Bottom row: weighted mean responses for all five mice. Vertical lines indicate time interval for training the classifier. (I) Behavioral performance versus decoding performance of classifiers trained on visual-only data. Error bars indicate SEM across sessions.
Fig. 6.
Fig. 6.. Circuit architecture underlying layer-specific perceptual thresholds.
(A) Recruitment in held-out populations during optogenetic stimulation of only tuned layer 2/3 neurons (χ2 two-tailed test results shown). (B) Recruitment in held-out iso-tuned populations as a function of the number of layer 2/3 neurons stimulated (Spearman’s ρ = 0.46, P < 0.001 for layer 2/3; Spearman’s ρ = 0.51, P < 0.0001 for layer 5; n = 46 experiments in five mice, P > 0.1, Fisher’s z transformation comparing ρ values; logit fits for visualization only). (C and D) Format matches (A) and (B) but during stimulation of only tuned layer 5 neurons. (E and G) Psychometric functions fit to predictions derived from classifiers trained on either neural or behavioral data pooled over five mice. (F and H) Data from panels (E) and (G) re-plotted for ensemble sizes used to compute two-way ANOVA results, where comparable numbers of neurons were stimulated (P < 0.01 for classifier data, P = 0.023 for behavioral data, main effect of layer). *P < 0.05, **P < 0.01, ****P < 0.0001.

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