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Gamma-range synchronization of fast-spiking interneurons can enhance detection of tactile stimuli

Nature Neuroscience volume 17, pages 1371–1379 (2014)Cite this article

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Abstract

We tested the sensory impact of repeated synchronization of fast-spiking interneurons (FS), an activity pattern thought to underlie neocortical gamma oscillations. We optogenetically drove 'FS-gamma' while mice detected naturalistic vibrissal stimuli and found enhanced detection of less salient stimuli and impaired detection of more salient ones. Prior studies have predicted that the benefit of FS-gamma is generated when sensory neocortical excitation arrives in a specific temporal window 20–25 ms after FS synchronization. To systematically test this prediction, we aligned periodic tactile and optogenetic stimulation. We found that the detection of less salient stimuli was improved only when peripheral drive led to the arrival of excitation 20–25 ms after synchronization and that other temporal alignments either had no effects or impaired detection. These results provide causal evidence that FS-gamma can enhance processing of less salient stimuli, those that benefit from the allocation of attention.

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Figure 1: Task structure.
Figure 2: Gamma is expressed in distinct bouts of activity in the LFP, associated with enhanced phase locking of spiking activity.
Figure 3: Optogenetic stimulation to emulate FS-gamma.
Figure 4: Generation and characterization of naturalistic vibrissal stimuli.
Figure 5: Endogenous and entrained FS-gamma predict enhanced detection of less salient naturalistic stimuli.
Figure 6: Entrained FS-gamma enhances detection of less salient periodic stimuli at a specific optimal temporal offset between FS synchronization and sensory drive.
Figure 7: Interaction between optogenetically entrained gamma and the response to vibrissal deflections.

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Acknowledgements

We thank R. Clary, J. Feather, H. Farrow, R. Lichtin, S. Bechek, J. Klee, N. Padilla and C. Burley for help running experiments, J. Cardin, U. Knoblich, M. Halassa, J. Ritt, J. Voigts, C. Deister, B. Higashikuibo, D. Meletis and M. Carlén, and members of the Moore laboratory, M. Wilson, M. Andermann, R. Haslinger, N. Kopell, C. Börgers, R. Sekuler and D. Sheinberg for their comments on the manuscript. This study was supported by a grant from the US National Institutes of Health to C.I.M., a National Research Service Award Fellowship to D.L.P., and a National Defense and Science & Engineering Graduate Fellowship and a National Research Service Award Fellowship to J.H.S.

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Author notes

  1. Dominique L Pritchett

    Present address: Present address: Champalimaud Centre for the Unknown, Lisbon, Portugal.,

  2. Joshua H Siegle and Dominique L Pritchett: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Neuroscience and Institute for Brain Science, Brown University, Providence, Rhode Island, USA

    Joshua H Siegle, Dominique L Pritchett & Christopher I Moore

  2. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Joshua H Siegle & Dominique L Pritchett

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Contributions

J.H.S., D.L.P. and C.I.M. designed the experiments. J.H.S. designed the implants and performed the viral injections. D.L.P. and J.H.S. designed the behavioral rig and oversaw training. J.H.S. and D.L.P. analyzed the data. J.H.S., D.L.P. and C.I.M. made the figures and wrote the manuscript.

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Correspondence to Christopher I Moore.

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Integrated supplementary information

Supplementary Figure 1 Quantifying gamma events.

a, An example of a gamma event in the local field potential (bottom), wavelet power spectrum and spectrogram (top left), and Fourier transform power spectrum and spectrogram (top right). Note that the highlighted peak in the spectrogram is associated with a clearly visible 40 Hz oscillation in the raw voltage trace. The 30–80 Hz range for event centroids is shown in white. Similar events were observed in all animals, with an average rate of occurrence of 0.89 Hz during periods in which the animals were not licking. b, Examples of spontaneously arising gamma oscillations during the pre-stimulus period (similar to Figure 2b in the main text). Mouse 1 is the same subject used in Figure 2b. Gamma events also occurred on “miss” trials, but at a lower frequency. Mouse 1: 1.430 events/trial on hits vs. 1.407 events/trial on misses; Mouse 2: 1.309 events/trial on hits vs. 1.272 events/trial on misses; Mouse 3: 1.245 events/trial on hits vs. 1.205 events/trial on misses.

Supplementary Figure 2 AAV and histology.

a, Schematic of the viral vector, which interacts with Cre in parvalbumin-positive cells to induce expression of ChR2-mCherry. b, Example histological section, showing viral expression primarily in the upper layers of barrel cortex. Expression was typically distributed over 1–3 barrel columns (300–500 μm medial–lateral spread, 500–1000 μm anterior–posterior spread). Blue = DAPI stain, red = mCherry fluorescence. Viral expression was confirmed in all experimental animals.

Supplementary Figure 3 Naturalistic stimuli.

a, The 17 motion sequences of an ex vivo B2 vibrissa contacting a rotating drum covered in sandpaper that were used for natural stimulus presentation in the detection task. b, Impact of optical stimulation in a control (Cre-negative littermate) animal on the natural scenes task. This mouse was injected with ChR2 and subjected to the same training protocol as all other mice. In contrast with the four Cre-positive animals, no significant modulation by the laser was observed (R2 = 0.073, P = 0.30).

Supplementary Figure 4 d′ as an indicator of detection performance.

a, Illustration of how d′ converts hit rate and false alarm rate into a single measure of perceptual acuity. b, Performance of one animal over the course of 4407 trials from 11 sessions. Top plot shows lick times on individual trials (black dots), bottom plot shows change in d′ for blocks of 50 trials. The animal transitioned between periods of constant licking, accurately licking to the stimulus, and no licking. Only blocks of trials in which d′ was above a threshold of 1.25 (green lines) were included in further analysis.

Supplementary Figure 5 Propagation of signals from the periphery to barrel cortex.

a, Schematic showing three synapses between the periphery and the cortex. PrV = principal trigeminal nucleus; VPM = ventral posterior medial nucleus; SI = primary somatosensory cortex. Evoked responses initiated in the periphery take, on average, 8–10 ms to propagate to barrel cortex. b, Raw voltage trace recorded during a single trial. A sharp transient in LFP traces from single trials is apparent ∼8 ms after the onset of stimulation, indicating the arrival of excitatory EPSPs from the thalamus. c, Average peri-stimulus spike histogram for N = 48 RS and FS cells, showing the ∼8 ms delay between deflecting the vibrissae (T = 0 ms) and the onset of spike activity in barrel cortex.

Supplementary Figure 6 Comparing d′ and hit rate.

a, Average d′ as a function of the temporal offset between sensory stimulus and entrained gamma for “threshold” trials with periodic stimulus presentation (same as Figure 6a in the main text). b, Average d′ as a function of temporal offset between sensory stimulus and entrained gamma for “max” trials (same as Figure 6b in the main text). c, Average hit rate as a function of temporal offset between sensory stimulus and entrained gamma for “threshold” trials. d, Average hit rate as a function of temporal offset between sensory stimulus and entrained gamma for “max” trials. All panels are for the same N = 8 animals as in Figure 6. Error bars indicate s.e.m.

Supplementary Figure 7 Electrophysiological methods.

a, Diagram of the fiber-optic–electrode implant used to record single unit activity in barrel cortex. b, Example projection plots for waveforms recorded on the same electrode over the course of a month. Spikes from the same cell are color-coded across days. c, Assertions of cell identity, used to minimize chances of double-counting the same cells across days, were analyzed with a waveform similarity metric. Orange dots indicate distance between waveforms identified as coming from the same cell; blue dots indicate distance between waveforms identified as coming from different cells. Distance from the origin indicates degree of waveform similarity. d, Measures used to identify cells as FS (fast-spiking) or RS (regular spiking). Cells in the present sample were separated into two groups based on peak–trough ratio and peak–trough separation.

Supplementary Figure 8 Additional spike quantification.

a, Mean PSTH of multi-unit activity from 15 electrodes during the peri-stimulus period (black lines = baseline condition). The condition with a 12.5 ms temporal offset (Figure 6a) is visibly more entrained to the 40 Hz stimulus. b, Wavelet transform of the mean PSTH for each temporal offset (colors map to plots in a). c, Power at 40 Hz for each of 5 temporal offsets, taken from the plot in panel b. d, Mean rate and peak rate for 0–25 ms and 30–150 ms, relative to baseline (N = 35 well-isolated RS cells).

Supplementary Figure 9 FS-gamma enhances perception when peripheral sensory drive arrives in neocortex during a beneficial window 20–25 milliseconds after FS synchronization.

Prior computational and experimental studies have predicted that FS-gamma may create an optimal window 20-25 milliseconds after FS synchronization, benefitting sensory relay when inputs arrive during this period. The conceptual diagram shows the timing of potential spikes generated by high-velocity vibrissae micro-motions (filled triangles) relative to the laser pulses that define the FS-gamma cycle (blue rectangles). In the naturalistic stimulation condition (top), stochastic vibrissal deflections at 180–200 Hz generated many high velocity micro-motions within a 25 ms cycle. As shown in Figure 4, these events had no systematic relationship to the FS-gamma cycle, and afferent spikes generated by these stimuli should arrive during the beneficial window. In the periodic stimulation condition (bottom), only one temporal offset (green, 12.5 ms) was predicted to generate stimulus-driven spikes inside the beneficial window, given the predicted lag of 8–10 milliseconds between peripheral drive and arrival in neocortex.

Supplementary Figure 10 Proposed schema of gamma’s effects on evoked spiking in pyramidal cells.

In this example, high-velocity deflections arrive while the cortex is in one of two “states,” one in which low synchrony among FS leads to generalized inhibition of firing and desynchronized firing in pyramidal cells (left), and one in which high FS synchrony creates a localized gamma oscillation (right). In the former state, disorganized but high rates of FS activity create a persistent state of inhibitory tone, diminishing the probability of spiking. In contrast, FS synchronization creates a greater transient depth of inhibition, but recovery from this hyperpolarization creates a window in which a host of excitatory currents are more readily recruited. This relief from synchronized inhibition concentrates firing of local neurons to this period. Motion patterns (bottom) measured from an ex vivo vibrissa; FS spike times and pyramidal cell membrane potential are simulated.

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Siegle, J., Pritchett, D. & Moore, C. Gamma-range synchronization of fast-spiking interneurons can enhance detection of tactile stimuli. Nat Neurosci 17, 1371–1379 (2014). https://doi.org/10.1038/nn.3797

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