Linearity and Gain Control in V1 Simple Cells

Carandini, Matteo; Heeger, David J.; Movshon, J. Anthony

doi:10.1007/978-1-4615-4903-1_7

Cited by 77 publications

(86 citation statements)

References 169 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The scaling and time shifting of the temporal response profiles with contrast and the dramatic changes in shape of the temporal response profiles with luminance presumably result from a mixture of rapid luminance and contrast gain-control mechanisms that may occur in the retina (Shapley and Victor, 1979;Shapley and Enroth-Cugell, 1984;Baccus and Meister, 2002) or in the cortex (Carandini et al, 1999;Albrecht et al, 2003;Tucker and Fitzpatrick, 2006) (see also supplemental Fig. 5, available at www.jneurosci.org as supplemental material).…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies of contrast responses in cat and monkey have made measurements under conditions where the local luminance is held constant at the mean value for the display (for review, see Carandini et al, 1999;Albrecht et al, 2003). The relatively fewer previous studies of luminance responses in the primary visual cortex have measured responses to large field modulations without parametric variation of contrast (Bartlett and Doty, 1974;Maguire and Baizer, 1982;Rossi et al, 1996, Rossi andParadiso, 1999;Peng and Van Essen, 2005;Tucker and Fitzpatrick, 2006).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Responses of Neurons in Primary Visual Cortex to Transient Changes in Local Contrast and Luminance

Geisler¹,

Albrecht²,

Crane³

2007

J. Neurosci.

View full text Add to dashboard Cite

During normal saccadic inspection of natural images, the receptive fields of cortical neurons are bombarded with frequent simultaneous changes in local mean luminance and contrast, yet there have been no systematic studies of how cortical neurons respond to such stimulation. The responses of single neurons in the primary visual cortex of the cat were measured for 200 ms presentations of sine-wave gratings confined to the conventional receptive field. Both local mean luminance and contrast were parametrically and randomly varied over the 1-1.5 log unit ranges that are typical of natural images. We find that responses are strongly modulated by both the local mean luminance and contrast, but in an approximately separable manner: the contrast response function is approximately invariant except for a scale factor that depends on the local mean luminance. The shape of the temporal response profiles were found to be approximately invariant with contrast, but were strongly affected by the local mean luminance. The results suggest that most, if not all, cortical neurons carry substantial local luminance information.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Responses of Neurons in Primary Visual Cortex to Transient Changes in Local Contrast and Luminance

Geisler¹,

Albrecht²,

Crane³

2007

J. Neurosci.

View full text Add to dashboard Cite

show abstract

“…Energy-based models can predict many of the physiological and psychophysical responses to various image features, including orientation, motion, texture, and stereoscopic depth (e.g., Adelson & Bergen, 1985;Anzai, Ohzawa, & Freeman, 1999;Bergen & Landy, 1991;Carandini, Heeger, & Movshon, 1999;Emerson, Bergen, & Adelson, 1992;Heeger, 1992;Malik & Perona, 1990;Morrone & Burr, 1988;Ohzawa, DeAngelis, & Freeman, 1990;Pollen & Ronner, 1983;Watson & Ahumada, 1985). The quadrature phase relationship between the four linear filters used in the model is adopted from an energy model of the complex cell in V1 (e.g., DeAngelis & Anzai, 2004;Heeger, 1992).…”

Section: Outline Of the Orientation Energy Modelmentioning

confidence: 99%

The effect of eccentricity and the adapting level on the café wall illusion

Takeuchi

2005

Perception & Psychophysics

View full text Add to dashboard Cite

“…In comparison, the spatial frequency bandwidth for neurons in the LGN ranges from 3 to Ͼ5 octaves (e.g., Croner and Kaplan 1995;Derrington and Lennie 1984;Hicks et al 1983;Irvin et al 1993;Kaplan and Shapley 1982;Rodieck and Stone 1965;So and Shapley 1981;Troy 1983a,b;Xu et al 2002). Although it is unknown exactly how this transformation in the selectivity, from the LGN to the cortex, is produced, several different classes of models have been proposed (e.g., Anderson et al 2000a,b;Carandini and Ringach 1997;Carandini et al 1999;Chance et al 1998;Douglas et al 1995;Gilbert et al 1990;Hubel and Wiesel 1962;Troyer et al 1998; for recent reviews, see Albrecht et al 2002Albrecht et al , 2003Ferster and Miller 2000).…”

Section: Introductionmentioning

confidence: 99%

Visual Cortex Neurons of Monkeys and Cats: Temporal Dynamics of the Spatial Frequency Response Function

Frazor

Albrecht

Geisler

et al. 2004

Journal of Neurophysiology

View full text Add to dashboard Cite

Crane. Visual cortex neurons of monkeys and cats: temporal dynamics of the spatial frequency response function. J Neurophysiol 91: 2607Neurophysiol 91: -2627Neurophysiol 91: , 2004 10.1152/jn.00858.2003. We measured the responses of striate cortex neurons as a function of spatial frequency on a fine time scale, over the course of an interval that is comparable to the duration of a single fixation (200 ms). Stationary gratings were flashed on for 200 ms and then off for 300 ms; the responses were analyzed at sequential 1-ms intervals. We found that 1) the preferred spatial frequency shifts through time from low frequencies to high frequencies, 2) the latency of the response increases as a function of spatial frequency, and 3) the poststimulus time histograms (PSTHs) are relatively shape-invariant across spatial frequency. The dynamic shifts in preferred spatial frequency appear to be a simple consequence of the latency shifts and the transient nature of the PSTH. The effects of these dynamic shifts on the coding of spatial frequency information are examined within the context of several different temporal integration strategies, and pattern-detection performance is determined as a function of the interval of integration, following response onset. The findings are considered within the context of related investigations as well as a number of functional issues: motion selectivity in depth, "coarse-to-fine" processing, direction selectivity, latency as a code for stimulus attributes, and behavioral response latency. Finally, we demonstrate that the results are qualitatively consistent with a simple feedforward model, similar to the one originally proposed in 1962 by Hubel and Wiesel, that incorporates measured differences in the response latencies and the receptive field sizes of different lateral geniculate nucleus inputs.

show abstract

Linearity and Gain Control in V1 Simple Cells

Cited by 77 publications

References 169 publications

Responses of Neurons in Primary Visual Cortex to Transient Changes in Local Contrast and Luminance

Responses of Neurons in Primary Visual Cortex to Transient Changes in Local Contrast and Luminance

The effect of eccentricity and the adapting level on the café wall illusion

Visual Cortex Neurons of Monkeys and Cats: Temporal Dynamics of the Spatial Frequency Response Function

Contact Info

Product

Resources

About