Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

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.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

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.


  1. Stüttgen, M.C. & Schwarz, C. Integration of vibrotactile signals for whisker-related perception in rats is governed by short time constants: comparison of neurometric and psychometric detection performance. J. Neurosci. 30, 2060–2069 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Adibi, M. & Arabzadeh, E. A Comparison of neuronal and behavioral detection and discrimination performances in rat whisker system. J. Neurophysiol. 105, 356–365 (2011).

    Article  PubMed  Google Scholar 

  3. Mayrhofer, J.M. et al. Novel two-alternative forced choice paradigm for bilateral vibrotactile whisker frequency discrimination in head-fixed mice and rats. J. Neurophysiol. 109, 273–284 (2013).

    Article  PubMed  Google Scholar 

  4. Romo, R., Hernández, A., Zainos, A. & Salinas, E. Somatosensory discrimination based on cortical microstimulation. Nature 392, 387–390 (1998).

    Article  CAS  PubMed  Google Scholar 

  5. Sachidhanandam, S., Sreenivasan, V., Kyriakatos, A., Kremer, Y. & Petersen, C.C.H. Membrane potential correlates of sensory perception in mouse barrel cortex. Nat. Neurosci. 16, 1671–1677 (2013).

    Article  CAS  PubMed  Google Scholar 

  6. Huber, D. et al. Sparse optical microstimulation in barrel cortex drives learned behaviour in freely moving mice. Nature 451, 61–64 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Fanselow, E.E. & Nicolelis, M.A.L. Behavioral modulation of tactile responses in the rat somatosensory system. J. Neurosci. 19, 7603–7616 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Castro-Alamancos, M.A. Absence of rapid sensory adaptation in neocortex during information processing states. Neuron 41, 455–464 (2004).

    Article  CAS  PubMed  Google Scholar 

  9. Hentschke, H., Haiss, F. & Schwarz, C. Central signals rapidly switch tactile processing in rat barrel cortex during whisker movements. Cereb. Cortex 16, 1142–1156 (2006).

    Article  PubMed  Google Scholar 

  10. Ulanovsky, N., Las, L., Farkas, D. & Nelken, I. Multiple time scales of adaptation in auditory cortex neurons. J. Neurosci. 24, 10440–10453 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Khatri, V., Hartings, J.A. & Simons, D.J. Adaptation in thalamic barreloid and cortical barrel neurons to periodic whisker deflections varying in frequency and velocity. J. Neurophysiol. 92, 3244–3254 (2004).

    Article  CAS  PubMed  Google Scholar 

  12. Ohzawa, I., Sclar, G. & Freeman, R.D. Contrast gain control in the cat visual cortex. Nature 298, 266–268 (1982).

    Article  CAS  PubMed  Google Scholar 

  13. Fraser, G., Hartings, J.A. & Simons, D.J. Adaptation of trigeminal ganglion cells to periodic whisker deflections. Somatosens. Mot. Res. 23, 111–118 (2006).

    Article  PubMed  Google Scholar 

  14. Minnery, B.S. & Simons, D.J. Response properties of whisker-associated trigeminothalamic neurons in rat nucleus principalis. J. Neurophysiol. 89, 40–56 (2003).

    Article  PubMed  Google Scholar 

  15. Chung, S., Li, X. & Nelson, S.B. Short-term depression at thalamocortical synapses contributes to rapid adaptation of cortical sensory responses in vivo. Neuron 34, 437–446 (2002).

    Article  CAS  PubMed  Google Scholar 

  16. Hartings, J.A. & Simons, D.J. Inhibition suppresses transmission of tonic vibrissa-evoked activity in the rat ventrobasal thalamus. J. Neurosci. 20, RC100 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Hirata, A., Aguilar, J. & Castro-Alamancos, M.A. Influence of subcortical inhibition on barrel cortex receptive fields. J. Neurophysiol. 102, 437–450 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Hawken, M.J., Shapley, R.M. & Grosof, D.H. Temporal-frequency selectivity in monkey visual cortex. Vis. Neurosci. 13, 477–492 (1996).

    Article  CAS  PubMed  Google Scholar 

  19. Ulanovsky, N., Las, L. & Nelken, I. Processing of low-probability sounds by cortical neurons. Nat. Neurosci. 6, 391–398 (2003).

    Article  CAS  PubMed  Google Scholar 

  20. Katz, Y., Heiss, J.E. & Lampl, I. Cross-whisker adaptation of neurons in the rat barrel cortex. J. Neurosci. 26, 13363–13372 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Adibi, M., McDonald, J.S., Clifford, C.W.G. & Arabzadeh, E. Adaptation improves neural coding efficiency despite increasing correlations in variability. J. Neurosci. 33, 2108–2120 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Maravall, M., Petersen, R.S., Fairhall, A.L., Arabzadeh, E. & Diamond, M.E. Shifts in coding properties and maintenance of information transmission during adaptation in barrel cortex. PLoS Biol. 5, e19 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. von der Behrens, W., Bäuerle, P., Kössl, M. & Gaese, B.H. Correlating stimulus-specific adaptation of cortical neurons and local field potentials in the awake rat. J. Neurosci. 29, 13837–13849 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Tannan, V., Simons, S., Dennis, R.G. & Tommerdahl, M. Effects of adaptation on the capacity to differentiate simultaneously delivered dual-site vibrotactile stimuli. Brain Res. 1186, 164–170 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Goble, A.K. & Hollins, M. Vibrotactile adaptation enhances amplitude discrimination. J. Acoust. Soc. Am. 93, 418–424 (1993).

    Article  CAS  PubMed  Google Scholar 

  26. Garcia-Lazaro, J.A., Ho, S.S.M., Nair, A. & Schnupp, J.W.H. Shifting and scaling adaptation to dynamic stimuli in somatosensory cortex. Eur. J. Neurosci. 26, 2359–2368 (2007).

    Article  CAS  PubMed  Google Scholar 

  27. Gescheider, G.A., Santoro, K.E., Makous, J.C. & Bolanowski, S.J. Vibrotactile forward masking: effects of the amplitude and duration of the masking stimulus. J. Acoust. Soc. Am. 98, 3188–3194 (1995).

    Article  CAS  PubMed  Google Scholar 

  28. Laskin, S.E. & Spencer, W.A. Cutaneous masking. I. Psychophysical observations on interactions of multipoint stimuli in man. J. Neurophysiol. 42, 1048–1060 (1979).

    Article  CAS  PubMed  Google Scholar 

  29. Gerdjikov, T.V., Bergner, C.G., Stüttgen, M.C., Waiblinger, C. & Schwarz, C. Discrimination of vibrotactile stimuli in the rat whisker system: behavior and neurometrics. Neuron 65, 530–540 (2010).

    Article  CAS  PubMed  Google Scholar 

  30. Waiblinger, C., Brugger, D. & Schwarz, C. Vibrotactile discrimination in the rat whisker system is based on neuronal coding of instantaneous kinematic cues. Cereb. Cortex published online 10.1093/cercor/bht305 (29 October 2013).

  31. Luna, R., Hernández, A., Brody, C.D. & Romo, R. Neural codes for perceptual discrimination in primary somatosensory cortex. Nat. Neurosci. 8, 1210–1219 (2005).

    Article  CAS  PubMed  Google Scholar 

  32. Harvey, M.A., Saal, H.P., Dammann, J.F. III & Bensmaia, S.J. Multiplexing stimulus information through rate and temporal codes in primate somatosensory cortex. PLoS Biol. 11, e1001558 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Ewert, T.A.S., Vahle-Hinz, C. & Engel, A.K. High-frequency whisker vibration is encoded by phase-locked responses of neurons in the rat's barrel cortex. J. Neurosci. 28, 5359–5368 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Boyden, E.S., Zhang, F., Bamberg, E., Nagel, G. & Deisseroth, K. Millisecond-timescale, genetically targeted optical control of neural activity. Nat. Neurosci. 8, 1263–1268 (2005).

    Article  CAS  PubMed  Google Scholar 

  35. Butovas, S. & Schwarz, C. Detection psychophysics of intracortical microstimulation in rat primary somatosensory cortex. Eur. J. Neurosci. 25, 2161–2169 (2007).

    Article  PubMed  Google Scholar 

  36. Wang, Q., Webber, R.M. & Stanley, G.B. Thalamic synchrony and the adaptive gating of information flow to cortex. Nat. Neurosci. 13, 1534–1541 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Pellicano, E., Jeffery, L., Burr, D. & Rhodes, G. Abnormal adaptive face-coding mechanisms in children with autism spectrum disorder. Curr. Biol. 17, 1508–1512 (2007).

    Article  CAS  PubMed  Google Scholar 

  38. Tannan, V., Holden, J.K., Zhang, Z., Baranek, G.T. & Tommerdahl, M.A. Perceptual metrics of individuals with autism provide evidence for disinhibition. Autism Res. 1, 223–230 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Umbricht, D. & Krljes, S. Mismatch negativity in schizophrenia: a meta-analysis. Schizophr. Res. 76, 1–23 (2005).

    Article  PubMed  Google Scholar 

  40. O'Connor, D.H. et al. Neural coding during active somatosensation revealed using illusory touch. Nat. Neurosci. 16, 958–965 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Brunton, B.W., Botvinick, M.M. & Brody, C.D. Rats and humans can optimally accumulate evidence for decision-making. Science 340, 95–98 (2013).

    Article  CAS  PubMed  Google Scholar 

  42. Abbott, L.F., Varela, J.A., Sen, K. & Nelson, S.B. Synaptic depression and cortical gain control. Science 275, 220–224 (1997).

    Article  CAS  PubMed  Google Scholar 

  43. Gil, Z., Connors, B.W. & Amitai, Y. Efficacy of thalamocortical and intracortical synaptic connections: quanta, innervation, and reliability. Neuron 23, 385–397 (1999).

    Article  CAS  PubMed  Google Scholar 

  44. Bruno, R.M. & Sakmann, B. Cortex is driven by weak but synchronously active thalamocortical synapses. Science 312, 1622–1627 (2006).

    Article  CAS  PubMed  Google Scholar 

  45. Temereanca, S., Brown, E.N. & Simons, D.J. Rapid changes in thalamic firing synchrony during repetitive whisker stimulation. J. Neurosci. 28, 11153–11164 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Ritt, J.T., Andermann, M.L. & Moore, C.I. Embodied information processing: vibrissa mechanics and texture features shape micromotions in actively sensing rats. Neuron 57, 599–613 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Wolfe, J. et al. Texture coding in the rat whisker system: slip-stick versus differential resonance. PLoS Biol. 6, e215 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. von Heimendahl, M., Itskov, P.M., Arabzadeh, E. & Diamond, M.E. Neuronal activity in rat barrel cortex underlying texture discrimination. PLoS Biol. 5, e305 (2007).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Jadhav, S.P., Wolfe, J. & Feldman, D.E. Sparse temporal coding of elementary tactile features during active whisker sensation. Nat. Neurosci. 12, 792–800 (2009).

    Article  CAS  PubMed  Google Scholar 

  50. Lak, A., Arabzadeh, E., Harris, J.A. & Diamond, M.E. Correlated physiological and perceptual effects of noise in a tactile stimulus. Proc. Natl. Acad. Sci. USA 107, 7981–7986 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Grinvald, A., Lieke, E., Frostig, R.D., Gilbert, C.D. & Wiesel, T.N. Functional architecture of cortex revealed by optical imaging of intrinsic signals. Nature 324, 361–364 (1986).

    Article  CAS  PubMed  Google Scholar 

  52. Aravanis, A.M. et al. An optical neural interface: in vivo control of rodent motor cortex with integrated fiberoptic and optogenetic technology. J. Neural Eng. 4, S143–S156 (2007).

    Article  PubMed  Google Scholar 

  53. Guo, Z.V. et al. Flow of cortical activity underlying a tactile decision in mice. Neuron 81, 179–194 (2014).

    Article  CAS  PubMed  Google Scholar 

  54. Miyashita, T., Shao, Y.R., Chung, J., Pourzia, O. & Feldman, D.E. Long-term channelrhodopsin-2 (ChR2) expression can induce abnormal axonal morphology and targeting in cerebral cortex. Front. Neural Circuits 7, 8 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Cardin, J.A. et al. Targeted optogenetic stimulation and recording of neurons in vivo using cell type–specific expression of Channelrhodopsin-2. Nat. Protoc. 5, 247–254 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Wichmann, F.A. & Hill, N.J. The psychometric function. I. Fitting, sampling, and goodness of fit. Percept. Psychophys. 63, 1293–1313 (2001).

    Article  CAS  PubMed  Google Scholar 

  57. Trevelyan, A.J. & Jack, J. Detailed passive cable models of layer 2/3 pyramidal cells in rat visual cortex at different temperatures. J. Physiol. (Lond.) 539, 623–636 (2002).

    Article  CAS  Google Scholar 

Download references


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).

Author information

Authors and Affiliations



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.

Ethics declarations

Competing interests

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.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

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).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing