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Neural codes for perceptual discrimination in primary somatosensory cortex

Nature Neuroscience volume 8, pages 1210–1219 (2005)Cite this article

Abstract

We sought to determine the neural code(s) for frequency discrimination of vibrotactile stimuli. We tested five possible candidate codes by analyzing the responses of single neurons recorded in primary somatosensory cortex of trained monkeys while they discriminated between two consecutive vibrotactile stimuli. Differences in the frequency of two stimuli could be discriminated using information from (i) time intervals between spikes, (ii) average spiking rate during each stimulus, (iii) absolute number of spikes elicited by each stimulus, (iv) average rate of bursts of spikes or (v) absolute number of spike bursts elicited by each stimulus. However, only a spike count code, in which spikes are integrated over a time window that has most of its mass in the first 250 ms of each stimulus period, covaried with behavior on a trial-by-trial basis, was consistent with psychophysical biases induced by manipulation of stimulus duration, and produced neurometric discrimination thresholds similar to behavioral psychophysical thresholds.

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Figure 1: Discrimination task.
Figure 2: Psychophysical performance during the manipulation of the duration of one of the two stimuli.
Figure 3: Responses of S1 neurons as a function of time during the stimulus period.
Figure 4: Responses of an area 1 neuron during the discrimination of the periodic stimulus set in Figure 2c.
Figure 5: Individual neurons' neurometric functions, using different measures, while monkeys performed the discrimination task using the stimulus sets in Figure 2.
Figure 6: An integration time window, for event-number codes, that produces neurometric biases consistent with the psychophysical biases induced by stimulus lengthening and shortening.
Figure 7: Weighted counts of spikes covary with behavior on a trial-by-trial basis, but weighted counts of bursts do not.

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References

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

    Article  CAS  Google Scholar 

  2. Romo, R., Hernández, A., Zainos, A., Brody, C. & Lemus, L. Sensing without touching: psychophysical performance based on cortical microstimulation. Neuron 26, 273–278 (2000).

    Article  CAS  Google Scholar 

  3. Mountcastle, V.B., Steinmetz, M.A. & Romo, R. Frequency discrimination in the sense of flutter: psychophysical measurements correlated with postcentral events in behaving monkeys. J. Neurosci. 10, 3032–3044 (1990).

    Article  CAS  Google Scholar 

  4. Recanzone, G.H., Merzenich, M.M. & Schreiner, C.E. Changes in the distributed temporal response properties of S1 cortical neurons reflect improvements in performance on a temporally based tactile discrimination task. J. Neurophysiol. 67, 1071–1091 (1992).

    Article  CAS  Google Scholar 

  5. Salinas, E., Hernández, A., Zainos, A. & Romo, R. Periodicity and firing rate as candidate neural codes for the frequency of vibrotactile stimuli. J. Neurosci. 20, 5503–5515 (2000).

    Article  CAS  Google Scholar 

  6. Hernández, A., Zainos, A. & Romo, R. Neuronal correlates of sensory discrimination in the somatosensory cortex. Proc. Natl. Acad. Sci. USA 97, 6191–6196 (2000).

    Article  Google Scholar 

  7. Romo, R. & Salinas, E. Touch and go: decision-making mechanisms in somatosensation. Annu. Rev. Neurosci. 24, 107–137 (2001).

    Article  CAS  Google Scholar 

  8. Romo, R. & Salinas, E. Flutter discrimination: Neural codes, perception, memory and decision making. Nat. Rev. Neurosci. 4, 203–218 (2003).

    Article  CAS  Google Scholar 

  9. Reinagel, P., Godwin, D., Sherman, M. & Koch, C. Encoding of visual information by LGN bursts. J. Neurophysiol. 81, 2558–2569 (1999).

    Article  CAS  Google Scholar 

  10. Martínez-Conde, S., Macknik, S.L. & Hubel, D.H. The function of bursts of spikes during visual fixation in the awake primate lateral geniculate nucleus and primary visual cortex. Proc. Natl. Acad. Sci. USA 99, 13920–13925 (2000).

    Article  Google Scholar 

  11. Kepecs, A., Wang, X.J. & Lisman, J. Bursting neurons signal input slope. J. Neurosci. 22, 9053–9062 (2002).

    Article  CAS  Google Scholar 

  12. Krahe, R. & Gabbiani, F. Burst firing in sensory systems. Nat. Rev. Neurosci. 5, 13–24 (2004).

    Article  CAS  Google Scholar 

  13. Hernández, A., Salinas, E., García, R. & Romo, R. Discrimination in the sense of flutter: new psychophysical measurements in monkeys. J. Neurosci. 17, 6391–6400 (1997).

    Article  Google Scholar 

  14. Siegel, S. & Castellan, N.J. Nonparametric Statistics for the Behavioral Science (McGraw-Hill, New York, 1988).

    Google Scholar 

  15. Connors, B.W. & Gutnik, M.J. Intrinsic firing patterns of diverse neocortical neurons. Trends Neurosci. 13, 99–104 (1990).

    Article  CAS  Google Scholar 

  16. Carandini, M. Visual cortex: fatigue and adaptation. Curr. Biol. 10, R605–R607 (2000).

    Article  CAS  Google Scholar 

  17. Nowak, L.G., Azouz, R., Sánchez-Vives, M., Gray, C.M. & McCormick, D.A. Electrophysiological classes of cat primary visual cortical neurons in vivo as revealed by quantitative analyses. J. Neurophysiol. 89, 1541–1566 (2003).

    Article  Google Scholar 

  18. Kohn, A. & Movshon, J.A. Neuronal adaptation to visual motion in area MT of the macaque. Neuron 39, 681–691 (2003).

    Article  CAS  Google Scholar 

  19. Parker, A.J. & Newsome, W.T. Sense and the single neuron: probing the physiology of perception. Annu. Rev. Neurosci. 21, 227–277 (1998).

    Article  CAS  Google Scholar 

  20. Britten, K.H., Newsome, W.T., Shadlen, M.N., Celebrini, S. & Movshon, J.A. A relationship between behavioral choice and the visual responses of neurons in macaque MT. Vis. Neurosci. 13, 87–100 (1996).

    Article  CAS  Google Scholar 

  21. Romo, R., Hernández, A., Zainos, A., Lemus, L. & Brody, C.D. Neuronal correlates of decision-making in secondary somatosensory cortex. Nat. Neurosci. 5, 1217–1225 (2002).

    Article  CAS  Google Scholar 

  22. Romo, R., Hernández, A., Zainos, A. & Salinas, E. Correlated neuronal discharges that increase coding efficiency during perceptual discrimination. Neuron 38, 649–657 (2003).

    Article  CAS  Google Scholar 

  23. Romo, R., Hernández, A. & Zainos, A. Neuronal correlates of a perceptual decision in ventral premotor cortex. Neuron 41, 165–173 (2004).

    Article  CAS  Google Scholar 

  24. Hernández, A., Zainos, A. & Romo, R. Temporal evolution of a decision-making process in medial premotor cortex. Neuron 33, 959–972 (2002).

    Article  Google Scholar 

  25. Romo, R., Brody, C.D., Hernández, A. & Lemus, L. Neuronal correlates of parametric working memory in the prefrontal cortex. Nature 399, 470–473 (1999).

    Article  CAS  Google Scholar 

  26. Brody, C.D., Hernández, A., Zainos, A. & Romo, R. Timing and neural encoding of somatosensory parametric working memory in macaque prefrontal cortex. Cereb. Cortex 13, 1196–1207 (2003).

    Article  Google Scholar 

  27. Gescheider, G.A., Berryhill, M.E., Verrillo, R.T. & Bolanowski, S.J. Vibrotactile temporal summation: probability summation or neural intergration? Somatosens. Mot. Res. 16, 229–242 (1999).

    CAS  Google Scholar 

  28. Talbot, W.H., Darian-Smith, I., Kornhuber, H.H. & Mountcastle, W.T. The sense of flutter-vibration: comparison of human capacity with response patterns of mechanoreceptors afferents from the monkey hand. J. Neurophysiol. 31, 301–334 (1968).

    Article  CAS  Google Scholar 

  29. Mountcastle, V.B., Talbot, W.H., Sakata, H. & Hyvarinen, J. Cortical neuronal mechanisms in flutter vibration studied in unanesthetized monkeys. J. Neurophysiol. 32, 452–484 (1969).

    Article  CAS  Google Scholar 

  30. Shadlen, M.N. & Newsome, W.T. Noise, neural codes and cortical organization. Curr. Opin. Neurobiol. 4, 569–579 (1994).

    Article  CAS  Google Scholar 

  31. Shadlen, M.N. & Newsome, W.T. The variable discharges of cortical neurons: Implications for connectivity, computation, and information coding. J. Neurosci. 18, 3870–3896 (1998).

    Article  CAS  Google Scholar 

  32. Ahissar, E., Sosnik, R. & Haidarliu, S. Transformation from temporal to rate coding in a somatosensory thalamocortical pathway. Nature 406, 302–306 (2000).

    Article  CAS  Google Scholar 

  33. Poggio, G.F. & Viernstein, L.J. Time series analysis of impulse sequences of thalamic somatic sensory neurons. J. Neurophysiol. 27, 517–545 (1964).

    Article  CAS  Google Scholar 

  34. Abeles, M. Corticonics (Cambridge Univ. Press, Cambridge, 1990).

    Google Scholar 

  35. Bialek, W., Rieke, F., Vansteveninck, R.R.D. & Warland, D. Reading a neural code. Science 252, 1854–1857 (1991).

    Article  CAS  Google Scholar 

  36. Bair, W., Koch, C., Newsome, W.T. & Britten, K. Power spectrum analysis of bursting cells in area MT in the behaving monkey. J. Neurosci. 14, 2870–2892 (1994).

    Article  CAS  Google Scholar 

  37. deCharms, R.C. & Zador, A. Neural representation and the cortical code. Annu. Rev. Neurosci. 23, 613–647 (2000).

    Article  CAS  Google Scholar 

  38. Draper, N. & Smith, H. Applied Regression Analysis 2nd edn.(Wiley, New York, 1966).

    Google Scholar 

  39. Press, W.H., Flannery, B.P., Teukolsky, S.A. & Vetterling, W.T. Numerical Recipes in C 2nd edn. (Cambridge Univ. Press, Cambridge, 1992).

    Google Scholar 

  40. Green, D.M. & Swets, J.A. Signal Detection Theory and Psychophysics (Wiley, New York, 1966).

    Google Scholar 

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Acknowledgements

The research of R.R. was supported by an International Research Scholars Award from the Howard Hughes Medical Institute and grants from Consejo Nacional de Ciencia y Tecnología and Dirección del Personal Académico of the Universidad Nacional Autónoma de México. C.D.B. is supported in part by the US National Institutes of Health (grant R01-MH067991).

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Authors and Affiliations

  1. Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, 04510 México, D.F., México

    Rogelio Luna, Adrián Hernández & Ranulfo Romo

  2. Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, 11724, USA

    Carlos D Brody

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  1. Rogelio Luna
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  2. Adrián Hernández
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  3. Carlos D Brody
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  4. Ranulfo Romo
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Correspondence to Ranulfo Romo.

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Supplementary information

Supplementary Fig. 1

Example rasters from a neuron that responded to each stimulus cycle with a burst of spikes. (PDF 104 kb)

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Luna, R., Hernández, A., Brody, C. et al. Neural codes for perceptual discrimination in primary somatosensory cortex. Nat Neurosci 8, 1210–1219 (2005). https://doi.org/10.1038/nn1513

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