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Tactile frequency discrimination is enhanced by circumventing neocortical adaptation


Neocortical responses typically adapt to repeated sensory stimulation, improving sensitivity to stimulus changes, but possibly also imposing limitations on perception. For example, it is unclear whether information about stimulus frequency is perturbed by adaptation or encoded by precise response timing. We addressed this question in rat barrel cortex by comparing performance in behavioral tasks with either whisker stimulation, which causes frequency-dependent adaptation, or optical activation of cortically expressed channelrhodopsin-2, which elicits non-adapting neural responses. Circumventing adaption by optical activation substantially improved cross-hemispheric discrimination of stimulus frequency. This improvement persisted when temporal precision of optically evoked spikes was reduced. We were able to replicate whisker-driven behavior only by applying adaptation rules mimicking sensory-evoked responses to optical stimuli. Conversely, in a change-detection task, animals performed better with whisker than optical stimulation. Our results directly demonstrate that sensory adaptation critically governs the perception of stimulus patterns, decreasing fidelity under steady-state conditions in favor of change detection.

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Figure 1: Whisker-evoked cortical responses show frequency-dependent adaption that affects performance in detection and discrimination tasks.
Figure 2: A model for repetition frequency discrimination based on neural response probabilities.
Figure 3: Optogenetic stimulation induces adaptation-free responses that result in increased detection and discrimination performance.
Figure 4: Adapting light stimulation reproduces whisker-evoked repetition frequency discrimination performance.
Figure 5: Adapting light is comparable to whisker stimulation.
Figure 6: Sensory adaptation facilitates deviant detection.


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We thank A. Saab, D. Margolis and B. Kampa for critically reading the manuscript, S. Weber for technical assistance, M. Durmaz for help with histological preparation, and Medartis AG for providing cortical screws. This work was supported by the EU-FP7 program (BRAIN-I-NETS project 243914 and BrainScales project 269921 to F. Haiss and F. Helmchen), the Swiss National Science Foundation (grant PP00B-110751/1 to B.W.), (project 2008/2011-Neurochoice to F. Helmchen and B.W.) and the Interdisciplinary Center for Clinical Research (IZKF Aachen) in the Faculty of Medicine at the RWTH Aachen University (to F. Haiss).

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S.M., W.v.d.B., J.M.M., F. Helmchen, B.W. and F. Haiss designed the study. S.M. and W.v.d.B. carried out experiments in the laboratory of B.W. J.M.M. and S.M. performed data analysis. F. Haiss and W.v.d.B. performed surgeries. F. Haiss, F. Helmchen, B.W. and S.M. wrote the paper.

Corresponding author

Correspondence to Simon Musall.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Distribution of recording depth during whisker stimulation

a, Left: Adaptation index of all recording sites against their respective depth in cortex during 40Hz whisker stimulation in passive animals. Right: Mean adaptation index of every cortical layer. No systematic differences were observed between different cortical layers. b, Same as in a but for recordings in task-engaged animals. Error bars show s.e.m.

Supplementary Figure 2 Illustrations of behavioral paradigms

a, Behavioral paradigm for stimulus detection and discrimination. For stimulus detection, uniform whisker deflection sequences were applied to a single C1 whisker (Target, green) and a reward was given if the animal correctly responded to the target side. For stimulus discrimination, a distractor sequence (black) was simultaneously applied to the C1 whisker on the opposing side. b, Same paradigm as in a but using direct stimulation of the C1-barrels. c, Same paradigm as in a but distractor sequences were replaced by direct stimulation of the C1-barrels. d, Behavioral paradigm for deviant detection. Two 20-Hz sequences were concomitantly presented on both sides of the animal. The target sequence additionally contained a deviant stimulus, occurring 1.5 s after sequence onset. We used either sequences of whisker deflections (red) or light pulses (blue) and presented either 1, 4 or 10 deviants in one target sequence.

Supplementary Figure 3 Model threshold calibration.

a, Detection threshold α was determined by tuning the model with neural responses to single whisker deflections. b, The threshold that achieved the highest similarity index between modeled (red) and scaled animal (blue) single pulse detection performance was used for further analysis. As a result model achieved higher absolute detection performance as the animals (green) but sensitivity to single deflections, defined by the inflection curve of the tuning curves (M50), was highly comparable.

Supplementary Figure 4 Histological analyses of ChR2 expression

a, Macroscopic image of ChR2-YFP fluorescence (green) of a bilaterally injected rat brain with equal expression in BC of both hemispheres. b, Coronal brain section, stained with DAPI (blue) showing the middle of the injection site. c, Examples of ChR2 expression in all three animals that were used for behavioral assessment with light stimulation. The spatial profile of ChR2 expression was highly comparable across animals and injection sites. d, Theoretical estimates for changes in light irradiance with distance from the fiber tip. e, Overview of ChR2 expression site in the right BC. The illustration shows the glass fiber (blue square) on the brain surface and a rough estimation of the cortical area that is affected by blue light stimulation (blue cone). f, Magnified view on local projections of ChR2+ neurons in cortex. White arrow denotes a localized accumulation of ChR2-YFP, indicating occurrence of a local axonal swelling. These local changes in morphology were observed repeatedly in all animals and might be due to long-term expression of ChR257. No other signs of cellular damage from ChR2 expression were observed. g, ChR2-YFP labeled projections from cortex to the ventral posteromedial nucleus (VPM) in thalamus. Nuclei of thalamic cells (identified by DAPI staining in blue) showed no overlap with ChR2-YFP fluorescence and were surrounded by non-fluorescent areas (dotted white circles) that are presumably cell bodies. This indicates that thalamic neurons were not retrogradely labeled with ChR2-YFP. Similar results were also seen in cortical area S2 (not shown).

Supplementary Figure 5 Light-sensitivity, cortical distribution and adaptation of individual ChR2-expressing neurons

a, Neurometric tuning curves of all single neurons, recorded under anesthesia. Circles denote firing probability after stimulating with 50 pulses at 10 Hz repetition rate. b, Recording depth of all recorded neurons against their respective M50 value. We observed no clear relation between recording depth and sensitivity to light. c, Distribution of adaptation indices in response to 40-Hz stimulation over all recorded neurons. Color-coding in all panels refers to cellular identity.

Supplementary Figure 6 Neural responses to optical stimulation in the awake animal

a, Extracellular recording in L5 BC upon 40-Hz stimulation with blue light pulses. Only the initial and last four responses are shown. Bottom panel shows a PSTH with spike rates (SR) normalized to the initial response. b, Normalized SR per light pulse at 20- and 40-Hz stimulation over all recorded neurons. Dashed lines show AI levels. c, Adaptation index of all recording sites against their respective depth in cortex during 40-Hz light stimulation.

Supplementary Figure 7 Behavioral effects of optical stimulation with low light power

a, Repetition frequency discrimination with 40-Hz target sequences, using optical stimulation with either low (M5 of single pulse detection, black) or high (M100 of single pulse detection, red) light power. Performance is plotted against normalized distractor frequencies (distractor divided by target frequency). b, Detection of optical stimulus sequences at low light power with different repetition frequencies. When using low light power, animals were unable to reliably detect sequences at repetition frequencies below 40-Hz. Error bars, 95% CIs

Supplementary Figure 8 Neural responses to light ramp stimulation

a, Normalized PSTHs in response to different stimulus types. PSTHs were constructed after combining spike data from all recorded neurons into one dataset, thus showing differences in response behavior over the whole neural population. b, Normalized population PSTHs for 20-Hz (left panel) and 40-Hz (right panel) light ramp stimulation. Shown are the first and last 100 ms of the stimulus sequence. c, Normalized SR per light ramp stimulation at different repetition frequencies over all recorded neurons. Dashed lines show AI levels.

Supplementary Figure 9 Adaptation of deviant stimuli with repeated stimulation

PSTHs of BC neurons in response to a 2-s long whisker sequence with either four or ten deviant pulses after 1.5 s. To remain comparability to Fig. 6a, PSTHs were smoothed with a 25-ms moving average.

Supplementary Figure 10 Illustration of whisker stimuli and single-trial timing

a, To change whisker stimulus velocity, we adjusted the amplitude of the 120 Hz cosine prototype pulse (left). To change repetition frequency, the interval between two prototype pulses was varied (right). b, Illustration of the behavioral setup, showing the piezo bending actuators used for whisker stimulation and LEDs that were connected via glass fibers for optical stimulation. Animals received a water reward when licking on the water spout that corresponded to the target side. c, Temporal organization of a single trial during behavioral testing.

Supplementary Figure 11 Long-term stability of optical stimulation.

a Psychometric curves for detection of single light pulses at different time points after ChR2 expression. b, M50 values for all animals and hemispheres over the course of up to seven months after initial ChR2 expression. Although we observed some changes in required irradiance over time M50 values where mostly stable, indicating that our approach for cortical stimulation was suited for stable long-term application. Error bars show estimated 95% confidence intervals.

Supplementary Figure 12 Overview of behavioral paradigms

Schematic overview of the time course for training and data acquisition, using different behavioral paradigms. Time point zero remarks the surgery for injection of the viral construct.

Supplementary Figure 13 Whisker movements during optical stimulation

a, Single trial example for velocity of the C1 whisker during 40 Hz stimulation of its corresponding barrel in S1. Gray square indicates changes in velocity due to whisking activity. b, Root-mean-squared (RMS) whisker velocity, either 25 or 1000 ms before (baseline) and after (stimulation) light pulse presentation. In both cases, we did not observe any significant difference between the two conditions.

Supplementary Figure 14 Differences in response latency between whisker and optical stimulation

a, Distribution of response latencies for 21000 trials of either whisker or optical stimulation. Bin size is 5 ms. For visual purposes only, distributions were cut after 1550 ms. b, Median response latencies were significantly different (Rank-sum test, p = 1.4×10-8) with 332 ms during light and 345 ms during whisker stimulation.

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Musall, S., von der Behrens, W., Mayrhofer, J. et al. Tactile frequency discrimination is enhanced by circumventing neocortical adaptation. Nat Neurosci 17, 1567–1573 (2014).

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