Skip to main content
SpringerLink
Log in

Neural encoding schemes of tactile information in afferent activity of the vibrissal system

  • Published:
Journal of Computational Neuroscience Aims and scope Submit manuscript

Abstract

When rats acquire sensory information by actively moving their vibrissae, a neural code is manifested at different levels of the sensory system. Behavioral studies in tactile discrimination agree that rats can distinguish different roughness surfaces by whisking their vibrissae. The present study explores the existence of neural encoding in the afferent activity of one vibrissal nerve. Two neural encoding schemes based on “events” were proposed (cumulative event count and median inter-event time). The events were detected by using an event detection algorithm based on multiscale decomposition of the signal (Continuous Wavelet Transform). The encoding schemes were quantitatively evaluated through the maximum amount of information which was obtained by the Shannon’s mutual information formula. Moreover, the effect of difference distances between rat snout and swept surfaces on the information values was also studied. We found that roughness information was encoded by events of 0.8 ms duration in the cumulative event count and event of 1.0 to 1.6 ms duration in the median inter-event count. It was also observed that an extreme decrease of the distance between rat snout and swept surfaces significantly reduces the information values and the capacity to discriminate among the sweep situations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Albarracín, A. L., Farfán, F. D., Felice, C. J., & Décima, E. E. (2006). Texture discrimination and multi-unit recording in the rat vibrissal nerve. BMC Neuroscience, 7, 42.

    Article  PubMed  Google Scholar 

  • Albarracín, A. L. (2008). Estudio fisiológico y anatómico del control motor de las vibrisas de la rata. PhD Thesis.

  • Arabzadeh, E., Panzeri, S., & Diamond, M. E. (2006). Deciphering the spike train of a sensory neuron: counts and temporal patterns in the rat whisker pathway. The Journal of Neuroscience, 26(36), 9216–9226.

    Article  PubMed  CAS  Google Scholar 

  • Arabzadeh, E., Zorzin, E., & Diamond, M. E. (2005). Neuronal encoding of texture in the whisker sensory pathway. PLoS Biology, 3, e17.

    Article  PubMed  Google Scholar 

  • Berg, R. W., & Kleinfeld, D. (2003). Rhythmic whisking by rat: retraction as well protraction of the vibrissae is under active muscular control. Journal of Neurophysiology, 89, 104–117.

    Article  PubMed  Google Scholar 

  • Calvin, W. H. (1975). Generation of spike trains in CNS neurons. Brain Research, 84, 1–22.

    Article  PubMed  CAS  Google Scholar 

  • Carvell, G. E., & Simons, D. J. (1990). Biometric analyses of vibrissal tactile discrimination in the rat. Journal of Neuroscience, 10, 2638–2648.

    PubMed  CAS  Google Scholar 

  • Cover, T. M., & Thomas, J. A. (1991). Elements of information theory. New York: Wiley.

    Book  Google Scholar 

  • Daubechies, I. (1992). Ten lectures on wavelets. Philadelphia: SIAM.

    Book  Google Scholar 

  • Diamond, M. E., von Heimendahl, M., & Arabzadeh, E. (2008). Whisker-mediated texture discrimination. PLoS Biol, 6(8), e220.

    Article  PubMed  Google Scholar 

  • Donoho, D. L. (1994). Nonlinear wavelet methods for recovery of signals, densities, and spectra from indirect and noisy data. Proc Sympos Appl Math. 173–205.

  • Dürig, F., Albarracín, A. L., Farfán, F. D., & Felice, C. J. (2009). Design and construction of a photoresistive sensor for monitoring the rat vibrissal displacement. Journal of Neuroscience Methods, 80(1), 71–76.

    Article  Google Scholar 

  • Farfán, F. D., Albarracín, A. L., & Felice, C. J. (2011). Electrophysiological characterization of texture information slip-resistance dependent in the rat vibrissal nerve. BMC Neuroscience, 12, 32.

    Article  PubMed  Google Scholar 

  • Golomb, D., Hertz, J., Panzeri, S., Treves, A., & Richmond, B. (1997). How well can we estimate the information carried in neuronal responses from limited samples? Neural Computation, 9, 649–665.

    Article  PubMed  CAS  Google Scholar 

  • Hartmann, M. J., Johnson, N. J., Towal, R. B., & Assad, C. (2003). Mechanical characteristics of rat vibrissae: resonant frequencies and damping in isolated whiskers and in the awake behaving animal. J Neuroscience, 23(16), 6510–6519.

    CAS  Google Scholar 

  • Ito, M. (1985). Processing of vibrissa sensory information within the rat neocortex. Journal of Neurophysiology, 54, 479–490.

    PubMed  CAS  Google Scholar 

  • Magri, C., Whittingstall, K., Singh, V., Logothetis, N. K., & Panzeri, S. (2009). A toolbox for the fast information analysis of multiple-site LFP, EEG and spike train recordings. BMC Neuroscience, 10(1), 81.

    Article  PubMed  Google Scholar 

  • Mallat, S., & Hwang, W. L. (1992). Singularity detection and processing with wavelets. IEEE Trans Inform Theory, 38(2), 617–643.

    Article  Google Scholar 

  • McDonnell, M. D., Ikeda, S., & Manton, J. H. (2011). An introductory review of information theory in the context of computational neuroscience. Biological Cybernetics, 105, 55–70.

    Article  PubMed  Google Scholar 

  • Mehta, S. B., & Kleinfeld, D. (2004). Frisking the whiskers: patterned sensory input in the rat vibrissae system. Neuron, 41, 181–184.

    Article  PubMed  CAS  Google Scholar 

  • Mehta, S. B., Whitmer, D., Figueroa, R., Williams, B. A., & Kleinfeld, D. (2007). Active spatial perception in the vibrissa scanning sensorimotor system. PLoS Biology, 5(2), e15. doi:10.1371/journal.pbio.0050015.

    Article  PubMed  Google Scholar 

  • Mitchinson, B., Gurney, K. N., Redgrave, P., Melhuish, C., Pipe, A. G., Pearson, M., Gilhespy, I., & Prescott, T. J. (2004). Empirically inspired simulated electromechanical model of the rat mystacial follicle-sinus complex. Proceedings of the Royal Society of London, 271, 2509–2516.

    Article  Google Scholar 

  • Nemenman, I., Bialek, W., & van Steveninck, R. (2004). Entropy and information in neural spike trains: progree on the sampling problem. Physical Review E, 69, 056111.

    Google Scholar 

  • Nenadic, Z., & Burdick, J. W. (2005). Spike detection the continuous wavelet transform. IEEE Transactions on Biomedical Engineering, 52(1), 74–87.

    Article  PubMed  Google Scholar 

  • Optican, L. M., Gawne, T. J., Richmond, B. J., & Joseph, P. J. (1991). Unbiased measures of transmitted information and channel capacity from multivariate neuronal data. Biological Cybernetics, 65, 305–310.

    Article  PubMed  CAS  Google Scholar 

  • Paninski, L. (2003). Convergence properties of three spike-triggered analysis techniques. Network, 14, 437–464.

    Article  PubMed  Google Scholar 

  • Panzeri, S., & Diamond, M. E. (2010). Information carried by population spike times in the whisker sensory cortex can be decoded without knowledge of stimulus time. Frontiers in Synaptic Neuroscience, 2(17).

  • Panzeri, S., Petersen, R. S., Schultz, S., Lebedev, M., & Diamond, M. E. (2001). The role of spike timing in the coding of stimulus location in rat somatosensory cortex. Neuron, 29, 769–777.

    Article  PubMed  CAS  Google Scholar 

  • Panzeri, S., & Treves, A. (1996). Analytical estimates of limited sampling biases in different information measures. Network, 7, 87–107.

    Article  Google Scholar 

  • Petersen, R. S., Panzeri, S., & Diamond, M. E. (2001). Population coding of stimulus location in rat somatosensory cortex. Neuron, 32, 503–514.

    Article  PubMed  CAS  Google Scholar 

  • Petersen, R. S., Panzeri, S., & Diamond, M. E. (2002). Population coding in somatosensory cortex. Current Opinion in Neurobiology, 12, 441–447.

    Article  PubMed  CAS  Google Scholar 

  • Petersen, R. S., Panzeri, S., & Maravall, M. (2009). Neural coding and contextual influences in the whisker system. Biological Cybernetics, 100(6), 427–446.

    Article  PubMed  Google Scholar 

  • Rieke, F., Warland, D., Ruyter, D., van Steveninck, R., & Bialek, W. (1997). Spikes: exploring the neural code. Cambridge: MIT Press.

    Google Scholar 

  • Rogers, R. F., Runyan, J. D., Vaidyanathan, G., & Schwaber, J. S. (2001). Information theoretic analysis of pulmonary stretch receptor spike trains. Journal of Neurophysiology, 85, 448–461.

    PubMed  CAS  Google Scholar 

  • Sachdev, R. N. S., Berg, R. W., Champney, G., Kleinfeld, D., & Ebner, F. F. (2003). Unilateral vibrissa contact: changes in amplitude but not timing of rhythmic whisking. Somatosensory & Motor Research, 20, 163–169.

    Article  Google Scholar 

  • Shoykhet, M., Doherty, D., & Simons, D. (2000). Coding of deflection velocity and amplitude by whisker primary afferent neurons: implications for higher level processing. Somatosens Motor Res, 17, 171–180.

    Article  CAS  Google Scholar 

  • Shoham, S., Fellows, M. R., & Normann, R. A. (2003). Robust, automatic spike sorting using mixtures of multivariate t-distributions. Journal of Neuroscience Methods, 127, 111–122.

    Google Scholar 

  • Smith, L. S., & Mtetwa, N. (2007). A tool for synthesizing spike trains with realistic interference. Journal of Neuroscience Methods, 159(1), 170–180.

    Article  PubMed  Google Scholar 

  • Strong, S. P., Koberle, R., van Steveninck, R., & Bialek, W. (1998). Entropy and information in neural spike trains. Physical Review Letters, 80, 197–200.

    Google Scholar 

  • Szwed, M., Bagdasarian, K., & Ahissar, E. (2003). Encoding of vibrissal active touch. Neuron, 40(3), 621–630.

    Article  PubMed  CAS  Google Scholar 

  • Victor, J. D. (2000). Asymptotic bias in information estimates and the exponential (Bell) polynomials. Neural Computation, 12, 2797–2804.

    Article  PubMed  CAS  Google Scholar 

  • Vincent, S. B. (1912). The function of the vibrissae in the behavior of the white rat. Behav Monog, 1, 1–181.

    Google Scholar 

  • Wang, Z., & Willett, P. K. (2001). All-purpose plug-in power-law detectors for transients signals. IEEE Trans Signal Processing, 49(11), 2454–2466.

    Article  Google Scholar 

  • Wolfe, J., Hill, D. N., Pahlavan, S., Drew, P. J., Kleinfeld, D., et al. (2008). Texture coding in the rat whisker system: slip-stick versus differential resonance. PLoS Biology, 6(8), e215.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This work has been supported by grants from Agencia Nacional de Promoción Científica y Tecnológica (ANPCYT); Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), and Consejo de Investigaciones de la Universidad Nacional de Tucumán (CIUNT), as well as with Institutional funds from Instituto Superior de Investigaciones Biológicas (INSIBIO).

Author information

Authors and Affiliations

  1. Laboratorio de Medios e Interfases (LAMEIN), Facultad de Ciencias Exactas y Tecnología (FACET), Universidad Nacional de Tucumán (UNT), Tucumán, Argentina

    Fernando D. Farfán & Carmelo J. Felice

  2. Instituto Superior de Investigaciones Biológicas (INSIBIO), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina

    Fernando D. Farfán & Carmelo J. Felice

  3. Laboratorio de Neurociencia, Facultad de Medicina (FM), Universidad Nacional de Tucumán (UNT), Tucumán, Argentina

    Ana L. Albarracín

Authors
  1. Fernando D. Farfán
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ana L. Albarracín
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Carmelo J. Felice
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fernando D. Farfán.

Additional information

Action Editor: Simon R Schultz

Electronic supplementary material

Below is the link to the electronic supplementary material.

Additional File 1

Information values versus window length where the cumulative event count is done. The information values were obtained considering the all possible pairwise comparisons. The events depicted in these figures were of 0.8, 1.0, 1.2 and 1.4 ms durations. These results were obtained at slip-resistance level 1. (EMF 150 kb)

Additional File 2

Idem to Additional File 1 but at slip-resistance level 2. (EMF 172 kb)

Additional File 3

Idem to Additional File 1 but at slip-resistance level 3. (EMF 173 kb)

Additional File 4

Information values obtained for all stimulus pairwise at different slip-resistance levels. Event duration considered for these calculations were of 0.6 to 2.0 ms. The remaining event durations showed no significant information values. (EMF 102 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Farfán, F.D., Albarracín, A.L. & Felice, C.J. Neural encoding schemes of tactile information in afferent activity of the vibrissal system. J Comput Neurosci 34, 89–101 (2013). https://doi.org/10.1007/s10827-012-0408-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10827-012-0408-6

Keywords

Search

Navigation