Dynamics of spatial summation in primary visual cortex of alert monkeys.

By M. Kapadia, G. Westheimer, Charles D. Gilbert. 1999

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Citations in the corpus

Normalization as a canonical neural computation (2011, background): “A neuron's responses to stimuli inside the summation field can be suppressed by placing additional stimuli in the surrounding regio”
Structure and function of visual area MT. (2005, background): “A similar effect of contrast on surround effects has been observed in both V1 (Levitt & Lund 1997, Polat et al. 1998, Kapadia et al. 1999, Sceniak et al. 1999) and the LGN (Solomon et al. 2002), so this strategy may be general.”
LFP and oscillations—what do they tell us? (2015, methodology): “Using invasive electrophysiological responses from awake-behaving monkeys several mechanisms were compared [31 ]: candidate DCMs allowed for contrast-dependent changes in the strength of recurrent local connections [6], the strength of horizontal connections [33] or the spatial extent of horizontal ”
Circuits for Local and Global Signal Integration in Primary Visual Cortex (2002, background): “Furthermore, V1 RFs show dynamic spatial properties, changing in size depending on stimulus contrast (Kapadia et al., 1999; Sceniak et al., 1999).”
On the nature of the BOLD fMRI contrast mechanism. (2004, background): “Modulation of contextual effects, possibly through the feedback connections, may also be the mechanism by which attention affects the response of V1 cells [9].”
Edge co-occurrence in natural images predicts contour grouping performance. (2001, unknown): “During the past decade, a number of psychophysical (Kellman & Shipley, 1991; Field, Hayes, & Hess, 1993; McIlhagga & Mullen, 1996; Dakin & Hess, 1998), neurophysiological (Bosking, Zhang, Schofield, & Fitzpatrick, 1997; Kapadia, Westheimer, & Gilbert, 1999 ), and computational (Sha’ashua & Ullman, ”
Natural signal statistics and sensory gain control (2001, background): “However, the shapes of physiologically measured tuning curves for some parameters exhibit substantial dependence on input level in both audition [16] and vision [17, 18].”
The Normalization Model of Attention (2009, result): “Normalization of visual cortical responses is analogous to earlier models of retinal light adaptation (Sperling and Sondhi, 1968) and to models of contrast gain control in the retina and LGN (Baccus and Meister, 2002; Bonin et al., 2005; Kaplan et al., 1987; Mante et al., 2005; Shapley and Victor, 1”
Integration of local features into global shapes: monkey and human FMRI studies. (2003, unknown): “…neurons have larger RF size than central V1 (i.e., the range for the RF size in peripheral V1 is 1.5 –2 and in central V2 is 0.05 –2.5 ), and as a result enhanced responses to collinear patterns are observed (Kapadia et al., 1995, 1999; Zipser et al., 1996; Lamme et al., 1998; Polat et al., 1998).”
Temporal properties of surround suppression in cat primary visual cortex (2007, background): “Because V1 neurons are more selective for stimulus size at high contrast than at low contrast ~Jagadeesh & Ferster, 1990; Kapadia et al., 1999; Sceniak et al., 1999, 2001; Cavanaugh et al., 2002a!, their responses saturate at higher contrasts for small stimuli than for large stimuli.”
Time Course and Time-Distance Relationships for Surround Suppression in Macaque V1 Neurons (2003, methodology): “However, we used high-contrast stimuli, which minimize the apparent size of the CRF (Kapadia et al., 1999; Sceniak et al., 1999; Cavanaugh et al., 2002), and therefore have tested as close to the CRF as our methods allow.”