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The statistical reliability of signals in single neurons in cat and monkey visual cortex
Abstract
The variability of the discharge of visual cortical neurons in cats and macaque monkeys limits the reliability with which such neurons can relay signals about weak visual stimuli. In general, the variance of a neuron's firing rate is directly proportional to its mean firing rate. The probability that a neuron will fire a criterion number of impulses on a stimulus trial grows monotonically with the contrast of a sinusoidal grating stimulus. Neural probability functions prepared either by computing the probability of criterion response or by integrating receiver operating characteristics to yield the probability of correct choice in a two-alternative forced-choice situation resemble psychometric functions obtained in psychophysical and behavioral experiments on humans and animals, but are shallower in slope. The slopes of neuronal probability functions are slightly higher when they are estimated over short time periods, but even so do not equal the slopes measured psychophysically in human and monkey observers. This discrepancy in slope could be explained if the whole observer responded only when about four neurons were active together.
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“We implemented a simple simulation based on Poisson responses (which are a reasonable approximation to neural firing71) that are either independent or shared across neurons.”
From Sampling bias corrections for discrete and Gaussian partial information decompositions (2026) · cites this paper as [71]
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Cites
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
Hubel, D. H., & Wiesel, T. N. (1962) · The Journal of Physiology · doi:10.1113/jphysiol.1962.sp006837 · Cited by 13,680
Effects of sleep and arousal on the processing of visual information in the cat
Livingstone, M. S., & Hubel, D. H. (1981) · Nature · doi:10.1038/291554a0 · Cited by 583
Research works printed but not linked: 39
- Bamber, 1975, The area above the ordinal dominance graph and the area below the receiver operating characteristic graph, J. Math. Psychol., 12, 387, 10.1016/0022-2496(75)90001-2 · DOI
- Barlow, 1969, Three factors affecting the reliable detection of light by retinal ganglion cells of the cat, J. Physiol., Lond., 200, 1, 10.1113/jphysiol.1969.sp008679 · DOI
- Barlow, 1971, Responses to single quanta of light in retinal ganglion cells of the cat, Vision Res., 87, 10.1016/0042-6989(71)90033-2 · DOI
- Bisti, 1974, Behavioural contrast sensitivity of the cat in various visual meridians, J. Physiol., Lond., 241, 201, 10.1113/jphysiol.1974.sp010649 · DOI
- Coenen, 1972, Determination of the transfer ratio of cat's geniculate neurones through quasi-intracellular recordings and the relation with level of alertness, Expl Brain Res., 14, 227, 10.1007/BF00816160 · DOI
- Dean, 1981, The relationship between response amplitude and contrast for cat striate cortical neurones, J. Physiol., Lond., 318, 413, 10.1113/jphysiol.1981.sp013875 · DOI
- Dean, 1981, The variability of discharge of simple cells in the cat striate cortex, Expl Brain Res., 44, 437, 10.1007/BF00238837 · DOI
- De Valois, 1974, Psychophysical tests of monkey vision III. Spatial luminance contrast tests of macaque and human observers, Vision Res., 14, 75, 10.1016/0042-6989(74)90118-7 · DOI
- Gilbert, 1977, Laminar differences in receptive field properties in cat primary visual cortex, J. Physiol., Lond., 268, 391, 10.1113/jphysiol.1977.sp011863 · DOI
- Hallett, 1969, The variations in visual threshold measurement, J. Physiol., Lond., 220, 403, 10.1113/jphysiol.1969.sp008818 · DOI
- Henry, 1973, Orientation specificity and response variability of cells in the striate cortex, Vision Res., 13, 1771, 10.1016/0042-6989(73)90094-1 · DOI
- Hess, 1980, Effects of luminance on contrast coding in cat visual cortex, J. Physiol., Lond., 300, 56
- Hubel, 1968, Receptive fields and functional architecture of monkey striate cortex, J. Physiol., Lond., 195, 215, 10.1113/jphysiol.1968.sp008455 · DOI
- Ikeda, 1974, Sensitivity of neurones in visual cortex (area 17) under different levels of anesthesia, Expl Brain Res., 20, 417, 10.1007/BF00238014 · DOI
- Knight, 1972, Dynamics of encoding in a population of neurons, J. gen. Physiol., 59, 734, 10.1085/jgp.59.6.734 · DOI
- Lee, 1945, Periodic fluctuations in the dark-adapted threshold, Am. J. Physiol., 143, 6, 10.1152/ajplegacy.1945.143.1.6 · DOI
- Levick, 1972, Another tungsten microelectrode, Med. Biol. Engng, 10, 510, 10.1007/BF02474199 · DOI
- Maffei, 1965, Effects of synchronized sleep on the response of lateral geniculate units to flashes of light, Archs Ital. Biol., 103, 609
- Merrill, 1972, Glass-coated platinum-plated microelectrodes, Med. Biol. Engng, 10, 662, 10.1007/BF02476084 · DOI
- Movshon, 1978, Spatial summation in the receptive fields of simple cells in the cat striate cortex, J. Physiol., Lond., 283, 53, 10.1113/jphysiol.1978.sp012488 · DOI · Paper page
- Movshon, 1978, Receptive field organization of complex cells in the cat striate cortex, J. Physiol., Lond., 283, 79, 10.1113/jphysiol.1978.sp012489 · DOI
- Movshon, 1978, Spatial and temporal contrast sensitivity of neurones in areas 17 and 18 of the cat's visual cortex, J. Physiol. Lond., 283, 101, 10.1113/jphysiol.1978.sp012490 · DOI
- Movshon, 1982, How many neurons are involved in perceptual decisions?, Infest. Ophthal. visual Sci., 22
- Nachmias, 1981, On the psychometric function for contrast detection, Vision Res., 21, 215, 10.1016/0042-6989(81)90115-2 · DOI
- Noda, 1970, Firing variability in cat association cortex during sleep and vvakefulness, Brain Res., 54, 243, 10.1016/0006-8993(73)90047-4 · DOI
- Noda, 1973, Neuronal activity in the association cortex of the cat during sleep, wakefulness and anesthesia, Brain Res., 54, 243, 10.1016/0006-8993(73)90047-4 · DOI
- Pasternak, 1981, The luminance dependence of spatial vision in the cat, Vision Res., 21, 1333, 10.1016/0042-6989(81)90240-6 · DOI
- Quick, 1974, A vector magnitude model of contrast detection, Kybernetik, 16, 65, 10.1007/BF00271628 · DOI
- Robson, 1981, Probability summation and regional variation in contrast sensitivity across the visual field, Vision Res., 21, 409, 10.1016/0042-6989(81)90169-3 · DOI
- Rose, 1979, An analysis of the variability of unit activity in the cat's visual cortex, Expl Brain Res., 37, 595, 10.1007/BF00236826 · DOI
- Semenoff, 1941, Sensitivity of the dark adapted eye during prolonged periods of observation, Nature, Lond., 147, 454, 10.1038/147454a0 · DOI
- Smith, 1965, A statistical analysis of the continual activity of single cortical neurons in the cat unanesthetized isolated forebrain, Biophys. J., 5, 47, 10.1016/S0006-3495(65)86702-9 · DOI
- Tanner, 1954, A decision-making theory of visual detection, Psychol. Rev., 61, 401, 10.1037/h0058700 · DOI
- Tolhurst, 1981, The dependence of response amplitude and variance of cat visual cortical neurones on stimulus contrast, Expl Brain Res., 41, 414, 10.1007/BF00238900 · DOI
- Tomko, 1974, Neuronal variability: non-stationary responses to identical visual stimuli, Brain Res., 79, 405, 10.1016/0006-8993(74)90438-7 · DOI
- Toyama, 1981, Crosscorrelation analysis of interneuronal connectivity in cat visual cortex, J. Neurophysiol., 46, 191, 10.1152/jn.1981.46.2.191 · DOI
- Toyama, 1981, Organization of cat visual cortex as investigated by cross-correlation technique, J. Neurophysiol., 46, 202, 10.1152/jn.1981.46.2.202 · DOI
- Watson, 1979, Probability summation over time, Vision Res., 19, 515, 10.1016/0042-6989(79)90136-6 · DOI
- Werner, 1963, The variability of central neural activity in a sensory system, and its implications for the central reflection of sensory events, J. Neurophysiol., 26, 958, 10.1152/jn.1963.26.6.958 · DOI
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Metadata
- Authors
- Tolhurst, D. J., Movshon, J. A., & Dean, A. F.
- Venue
- Vision Research
- Publisher
- Elsevier BV
- Published
- 1983-01
- Volume
- 23
- Issue
- 8
- Pages
- 775-785
- ISSN
- 0042-6989
- Cited by
- 829
- References
- 2
- Language
- en
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