High-density multi-fiber photometry for studying large-scale brain circuit dynamics


Animal behavior originates from neuronal activity distributed across brain-wide networks. However, techniques available to assess large-scale neural dynamics in behaving animals remain limited. Here we present compact, chronically implantable, high-density arrays of optical fibers that enable multi-fiber photometry and optogenetic perturbations across many regions in the mammalian brain. In mice engaged in a texture discrimination task, we achieved simultaneous photometric calcium recordings from networks of 12–48 brain regions, including striatal, thalamic, hippocampal and cortical areas. Furthermore, we optically perturbed subsets of regions in VGAT-ChR2 mice by targeting specific fiber channels with a spatial light modulator. Perturbation of ventral thalamic nuclei caused distributed network modulation and behavioral deficits. Finally, we demonstrate multi-fiber photometry in freely moving animals, including simultaneous recordings from two mice during social interaction. High-density multi-fiber arrays are versatile tools for the investigation of large-scale brain dynamics during behavior.

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Fig. 1: Optical setup for multi-site photometry using high-density multi-fiber arrays.
Fig. 2: Large-scale network dynamics across multiple brain regions during texture discrimination behavior.
Fig. 3: Simultaneous 48-channel multi-fiber photometry during texture discrimination.
Fig. 4: Combining multi-fiber photometry with optogenetic perturbation.
Fig. 5: Multi-fiber photometry in freely moving mice.

Data availability

The data that support the findings of this study are available from the corresponding authors upon reasonable request.

Code availability

Custom-written software code for data acquisition (LABView) and data analysis (MATLAB) is available upon reasonable request.


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We would like to thank H. Kasper, M. Wieckhorst and S. Giger for technical assistance; J. L. Alatorre Warren for the registration of histology sections to the Allen Brain Atlas and fiber shaft tracking; A. Jovalekic for help with electrophysiological recordings and spike sorting; and A. Ayaz, L. Egolf and C. Lewis for comments on the manuscript. This work was supported by grants to F.H. from the Swiss National Science Foundation (No. 310030B_170269) and the European Research Council (ERC Advanced Grant, project No. 670757, BRAINCOMPATH), by a Transfer Project and an IPhD Project from SystemsX.ch (Nos. 51TP-0_145729 and 51PHP0_157359, respectively) and through a Roche Joint Collaborative Project.

Author information




Y.S. and F.H. designed the experiments. Y.S. conducted the experiments and analyzed the data. M.C. assisted in fiber-optic experiments. L.S. performed brain histology. Y.S. and F.H. wrote the paper.

Corresponding authors

Correspondence to Yaroslav Sych or Fritjof Helmchen.

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The authors declare no competing interests.

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Integrated supplementary information

Supplementary Figure 1 Glial response in mouse brain tissue 1 month after implantation of a UM22-100 multi-fiber array.

(a) Left: Confocal image of astrocytes stained for GFAP (yellow) surrounding an optical fiber shaft in S1 cortex. A moderate astroglial scar formation is detected near the optical fiber. Right: Confocal image of microglia in S1 cortex (EGFP-expressing in a CX3CR1 mouse, green, and co-stained against Iba1, yellow). Note that microglia density is not markedly changed close to the fiber shaft as compared to more distant tissue areas. (b) Left: Confocal image of astrocytes surrounding the fiber shaft in the hippocampal CA1 region (yellow). The CA1 pyramidal layer is marked by dense band of DAPI-stained nuclei (blue). Right: Similar image with EGFP-stained microglia in the CX3CR1-EGFP mouse line. A moderate astroglial scar formation is detected near the optical fiber. Microglia density is not markedly changed, except for corpus callosum above CA1. (a, b) Experiment was repeated in 2 mice with similar results.

Supplementary Figure 2 Construction of a 12-fiber array front piece.

(a) Insertion of the optical fibers into a 12-fiber connector ferrule. (b) Alignment of the fiber ends to a printed template of the intended pattern of fiber lengths. The ferrule is fixated with tape on the printout of the pattern. (c) Application of glue on both ends. (d) Cut of the fibers at the proximal side. (e) Polishing with the help of a custom-designed bare ferrule polishing puck and polishing sheets of 30, 6, 3 and 1 µm grit size. (f) Fitting of the guiding pins. (g) Addition of a magnet housing. (h) Optional magnet housing for additional fixation of the multi-fiber implant and the fiber bundle. (i) Full assembly of a 12-fiber front piece. The same procedures as described here apply for the design of the 12-fiber array connectors at the end of fiber bundles as well as for the 24- and 48-fiber array front pieces and connectors.

Supplementary Figure 3 Simultaneous fiber photometry and single-unit recording during texture discrimination.

(a) Schematic of our custom-designed optotetrode drive for simultaneous fiber photometry and electrophysiological recording. Bottom: Cross section of optotetrode tip comprising the UM22-100 fiber surrounded by four tetrodes. (b) Examples of three single units displaying selective spike rate changes in Hit versus CR trials. (c) Least-squares fit of the fiber-optic bulk calcium signal using the weighted spike rates of 364 single units that were recorded in the vicinity of the fiber tip, convolved with an exponential curve to account for the calcium indicator characteristics. The mean calcium signals for Hit trials (averaged over 187, 257, 251, 306 and 112 trials for day 1 to day 24, respectively) and CR trials (averaged over 181, 227, 237, 298 and 120 CR trials for day 1 to day 24, respectively) are plotted in as blue and red solid traces and the fitted curve is plotted as dashed black trace. (d) The amplitude contribution (in %ΔF/F, left axes) of 143 and 70 single units (for 112 Hit and 120 CR trials respectively) to the fit of the trial related ΔF/F from one example session, sorted in descending order. Left: Hit trials; Right: CR trials. The orange solid line shows cumulative R2 (explained variance) for the sorted single units. (e) Comparison of the number of single units required to explain 90% of the variance in fiber-optic calcium signal for Hit and CR trials (mean ± standard deviation, 9 sessions from 2 mice).

Supplementary Figure 4 Comparison of fiber photometry and two-photon calcium imaging.

(a) Schematic of the experiment combining a fiber-optic recording under a 16x microscope objective and two-photon calcium imaging. A piggyback stimulation electrode allowed for local electrical stimulation. (b) Two-photon fluorescence image capturing the neuronal ensemble activated by a 50-ms, 20-µA stimulation pulse as detected by the standard photomultiplier in the two-photo microscope detection path The tip of the UM22-100 fiber is shown in red. (c) Two-photon fluorescence image upon the same stimulation pulse as collected through the UM22-100 fiber and detected in the photometry setup. Note the neuron that apparently is not ‘seen’ by the fiber tip (marked as circle). (d) Comparison of stimulus-evoked ΔF/F calcium transients averaged over the entire field-of-view for the two-photon microscope collected through the objective (green), using scanned two-photon excitation but light collection through the fiber (red), and using single-photon excitation at 473 nm and fluorescence collection by the photometry system (blue). (e) Mean ± SEM ΔF/F amplitudes evoked for stimulation pulses of 5, 10, 20 (3 stimulation pulses per condition) and 30 µA (4 stimulation pulses) and measured with fiber photometry. Scatter plot shows data points for every stimulation pulse. (b - e) Experiment was conducted in one mouse.

Supplementary Figure 5 Assessment of potential cross-talk between different fiber channels.

(a) Schematic illustrating the sequential coupling of excitation light into individual fiber channels. To estimate cross talk we coupled excitation light into each fiber separately while measuring fluorescence from all 12 channels. (b) Two measures of cross talk. Left: The percentwise contamination was estimated from the median value of the fluorescence recorded in each channel F1..n normalized by Fb, the median value of fluorescence excited by direct illumination of the respective channel. Right: A second measure is based on evaluating the variance of the fluorescence signal induced by excitation in F1..n normalized by Fb. (c) Median estimation of cross talk for GCaMP6m and R-CaMP1.07 sorted by the distance between the tips of the excited and recorded fiber (mean ± standard deviation across channels), shown separately for the cases when the recorded fiber is in front or in the back of the excited fiber. Fluorescence signals were pooled across several channels of the 12-fiber array according to the distance binned by 250 µm and the depth of adjacent fibers with respect to the illuminated fiber channel (i.e. below or above) for 2 mice (GCaMP6m and R-CaMP 1.07).

Supplementary Figure 6 Across-mice comparison of the session-averaged calcium dynamics.

(a) Example calcium signals recorded from 12 brain regions during Hit trials for day 1 and day 14 (blue curves are mean ΔF/F traces averaged over 303 and 315 Hit trials, respectively; example traces of individual trials are shown in grey; note that some individual traces are truncated). (b) Top: average ΔF/F traces for the 6 mice with 12-fiber implants. Bottom: across-mice average of the z-scored ΔF/F traces (mean ± SEM, solid black line and a shaded area respectively). In some mice we missed the target region; therefore less than 6 traces are shown.

Supplementary Figure 7 Viral strategies to separate the contribution of axonal afferents and local neurons to regional fluorescence signals.

(a) Left: To specifically label the CPu→GP pathway we combined injection of Cre-dependent virus encoding GCaMP6m in CPu with injection of a retrograde AAV driving Cre expression in GP in one mouse. A 12-fiber array was implanted such that dorso-lateral fibers targeted CPu and ventro-medial fibers targeted GP. Right: Likewise, to specifically label the GP→VL pathway with GCaMP6m virus we combined injection of Cre-dependent GCaMP6m virus in GP with injection retrograde promoter injected in VL in another mouse. A 12-fiber array was implanted such that ventro-lateral fibers targeted GP and dorso-medial fibers targeted VL. (b) Fiber-optic calcium signals from these two mice were measured from the respective region pairs while mice collected water reward upon texture presentation (see trial structure at bottom: black lines indicate auditory tone cues; grey bar represents texture presentation time; yellow bar shows reward period). Calcium signals for Hit and Miss trials (mean ± SEM shaded area) displayed distinct temporal profiles for the CPu→GP pathway (left; 30 Hit and 132 Miss trials) and the GP→VL pathway (right; 69 Hit and 33 Miss trials) but were consistent for the somatic and axonal components for each of the two pathways. For both pathways ΔF/F signals discriminated between Hit and Miss trials (licking vs. not-licking) in a late reward period window (grey bar): CPu→GP, p = 3.2·10-4 in CPu and p = 4.8·10-4 in GP; GP→VL, p = 0.016 in GP and p = 1.8·10-4 in VL; two-sided Wilcoxon rank sum test).

Supplementary Figure 8 Example of trial-related brain activity during the texture discrimination task measured by 48-fiber photometry.

(a) Example of a Hit trial. Top: a horizontal bar plot shows the Hit trial structure (black lines indicate time onsets for auditory tones signalling texture approach (starting at 1 s), report decision (at 5 s); grey bar represents texture presentation time; yellow bar marks reward period). ΔF/F fluorescence signal is plotted for every channel. Whisking angle and lick events are repeated for each block of 24-channels on the bottom of panels a and b, respectively. (b) Example of a CR trial. Top: a horizontal bar plot shows the CR trial structure (no lick and reward-related events).

Supplementary Figure 9 Comparison of 48-fiber photometry across three mice during expert performance in the texture discrimination task.

(a) Examples of normalized and sorted mean calcium responses for Hit and CR trials. AI (agranular insular cortex), mM1 (primary motor cortex), and BLA (basolateral amygdaloid nucleus) were consistently activated during the licking/reward collection period in all mice. Mouse m1 is the same as shown in Figure 3. (b) Adjacency matrices of correlation coefficients for each mouse thresholded at three standard deviations above the mean of the respective correlation coefficient calculated from shuffled trials. (c) Adjacency matrix of correlation coefficients averaged across three animals, thresholded at three standard deviations above the mean calculated across mice. In b and c regions are ordered according to fiber channels. Two clusters of anatomically defined regions are recruited: an anterior cluster consisting of VO, Cg1, PrL, MO and a medial cluster consisting of VM, VPM, VPL, RT, CPu, GP, functionally connecting to anterior MO, Cg1, VO, AOD, AOL via VM. These functional clusters are outlined as dashed rectangles in c.

Supplementary Figure 10 Non-local effects of optogenetic perturbation in VGAT mice.

(a) Left: schematic of the experiment. We combined multi-site electrode recordings (‘ephys’ E16+R-100-S1-L6NT probe, Atlas Neuroengineering) with optical perturbation in two VGAT mice under anesthesia (1% isoflurane). The optical fiber was targeted to anterior VL, delivering 473-nm excitation light for ChR2 excitation. The electrode was repeatedly inserted into VL and RT. Air-puff stimulation of the whiskers was applied with and without simultaneous light stimulation. Right: mean multi-unit activity (Spike Rate, 24 trials) in VL without (blue) and with (black) optogenetic perturbation. (b) Left: schematic of the experiment. Right: mean multi-unit activity (Spike Rate, 24 trials) in RT without (blue) and with (black) optogenetic perturbation. (a, b) Arrow shows the onset of the whisker stimulation and the optogenetic light. Grey bar above outlines the period of 400 ms after the stimulation onset for a two-sided Wilcoxon rank sum test.

Supplementary Figure 11 Fluorescence tail after a brief (50-ms) illumination by 473 nm in C57BL/6 mice expressing only R-CaMP1.07.

(a) Averaged ΔF/F activity (mean ± SEM) without perturbation laser for 134 Hit trials is plotted with solid blue line. Averaged ΔF/F activity (mean ± SEM) with perturbation laser pulse of 50ms during Hit 88 trials is plotted with dashed black and grey respectively. Both traces were measured at the R-CaMP1.07 emission band. 473 nm laser pulse was coupled to iGP channel only. Bottom (for every channel): black bars indicate significant time samples (p<0.01, one-way ANOVA) for Hit trials with and without perturbation compared. (b) Example of a trial with a 473 nm laser pulse and a least squares exponential fit.

Supplementary Figure 12 Perturbation of ventral thalamus during a texture discrimination task caused changes in a mesoscale network and behavioral variables.

(a) Identified fiber tip positions for all mice. Several fibers were implanted into ventral thalamus (m3 s1 and s2, m4 s1 and s2, m5 s1, m8 s1 and s2). Light at 473-nm was coupled into individual fiber. (b) Distribution of mean calcium dynamics across channels compared for Light Off vs Light On conditions. Distribution contains 20 sessions from 3 mice (median is shown with red circle, mean black line, bottom and top notches show 25th and 75th percentile respectively). Top and bottom rows show comparison for Hit and CR trials; p and z values are given for two-sided Wilcoxon signed rank test. (c) Changes in whisking and licking for a full trial duration. Behavioral variables for the perturbed/unperturbed trials are plotted in solid/dashed line respectively. Whisking and licking were reduced during optogenetic perturbation. Black bar below each plot shows p<0.01 one-way ANOVA tested for every time sample across the trial (Number of Hit, CR, FA trials without/with optogenetic perturbation 204,196,14/ 78,14,83 for m4; 52,59,5/ 9,23,- for m3; 84,90,7/ 31,24,4 for m5 respectively).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–12, Supplementary Note 1 and Supplementary Table 1

Reporting Summary

Supplementary Video 1

Example of 48-channel multi-fiber photometry.: Left column: example Hit trial; right column: example CR trial. Top row: raw fluorescence movie of the 48-channel multi-fiber array as recorded by the camera; middle row: background-corrected and normalized ΔF/F movie; bottom row: movie of the behaving mouse. The texture approaches from the left and the water spout is visible, too. Video was taken with IR illumination and is shown in real time

Supplementary Video 2

Example of simultaneous multi-fiber photometry in two freely moving mice during social interaction.: Top and middle rows: normalized ΔF/F fluorescence traces from the fiber array implants: anterior 12-fiber array implanted in mouse 2 (M2); medial 24-fiber array implanted in M2 (medial a and b); medial 12-fiber array implanted in mouse 1 (M1). Bottom: simultaneously recorded movie (top view) of behaving mice. Video is shown in real time

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Sych, Y., Chernysheva, M., Sumanovski, L.T. et al. High-density multi-fiber photometry for studying large-scale brain circuit dynamics. Nat Methods 16, 553–560 (2019). https://doi.org/10.1038/s41592-019-0400-4

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