Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-10T14:51:34.699Z Has data issue: false hasContentIssue false
  • English
  • Français

Video-rate and continuous visual stimuli do not produce equivalent response timings in visual cortical neurons

Published online by Cambridge University Press:  22 January 2004

TIMOTHY J. GAWNE  and
JILL M. WOODS
TIMOTHY J. GAWNE
Affiliation:
Department of Physiological Optics, University of Alabama at Birmingham, Birmingham
JILL M. WOODS
Affiliation:
Department of Physiological Optics, University of Alabama at Birmingham, Birmingham
Get access Rights & Permissions [Opens in a new window]

Abstract

Video cathode ray tube (CRT) technology has proven to be extremely valuable for performing research in the visual system. However, the image on a CRT monitor is not constant, but consists of a series of brief pulses. This has implications for any study that explores the responses of neurons in the visual system on short time scales. In particular, there is no unambiguous time point at which a visual stimulus presented via CRT may be said to have ended. Recordings from single units in visual cortical area V1 of an awake primate demonstrate that, when studying changes in response timing on the order of 10 ms or less, stimuli delivered at video frame rates do not duplicate the effects seen with stimuli that have continuous functions of luminance versus time. Additionally, there does not seem to be any clear method of comparing the results obtained with video-rate stimuli with results obtained with continuous-time stimuli that holds for all conditions. These effects are especially critical when exploring the time course of the neuronal responses to the ending of a visual stimulus (off-response). Our findings cast doubt upon the recently reported result that off-responses have consistently shorter latencies than on-responses.

Keywords

V1Visual cortexTemporal dynamicsCRTOff-responseTiming
Type
Research Article
Information
Visual Neuroscience , Volume 20 , Issue 5 , September 2003 , pp. 495 - 500
Copyright
2003 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Abeles, M. & Goldstein, M.H. (1977). Multispike train analysis. Proceedings of the IEEE 65, 762–773.CrossRefGoogle Scholar
Bair, W., Cavanaugh, J.R., Smith, M.A., & Movshon, J.A. (2002). The timing of response onset and offset in macaque visual neurons. Journal of Neuroscience 22, 3189–3205.Google Scholar
Gawne, T.J., Richmond, B.J., & Optican, L.M. (1991). Interactive effects among several stimulus parameters on the responses of striate cortical complex cells. Journal of Neurophysiology 66, 379–389.Google Scholar
Gawne, T.J., Kjaer, T.W., & Richmond, B.J. (1996). Latency: Another potential code for feature binding in striate cortex. Journal of Neurophysiology 76, 1356–1360.Google Scholar
Heller, J., Hertz, J.A., Kjaer, T.W., & Richmond, B.J. (1995). Information flow and temporal coding in primate pattern vision. Journal of Computational Neuroscience 2, 175–193.CrossRefGoogle Scholar
Judge, S.J., Richmond, B.J., & Chu, F.C. (1980). Implantation of magnetic search coils for measurement of eye position: An improved method. Vision Research 20, 535–538.CrossRefGoogle Scholar
Lee, B.B., Pokorny, J., Smith, V.C., & Kremers, J. (1994). Responses to pulses and sinusoids in macaque ganglion cells. Vision Research 34, 3081–3096.CrossRefGoogle Scholar
Robinson, D.A. (1963). A method of measuring eye movement using a scleral search coil in a magnetic field. IEEE Transactions in Biomedical Engineering 10, 137–145.Google Scholar
Silverman, B.W. (1986). Density Estimation for Statistics and Data Analysis. New York: Chapman & Hall.CrossRef