Size and distribution of movement fields in the monkey superior colliculus

Sparks, David L.; Holland, Richard A.; Guthrie, Barton L.

doi:10.1016/0006-8993(76)90003-2

Cited by 311 publications

(186 citation statements)

References 22 publications

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“…Bisley and Goldberg (2003) reported that attention for a particular location could be known only by considering the firing rates of LIP cells representing two task-relevant locations, not just by the activity of LIP cells representing the target location alone. The premotor theory of visual attention suggests that covert attention is closely related to overt eye movements (Rizzolatti et al, 1987), which have been shown to depend on the distribution of activity across entire neural maps (Sparks et al, 1976;Lee et al, 1988). Furthermore, frontal eye field lesions cause conjugate eye deviation (Pedersen and Troost, 1981;Tijssen et al, 1991;Singer et al, 2006), consistent with eye movements being driven by the difference in activity between portions of FEF representing different portions of space.…”

Section: Spatial Attention As Moment-to-moment Asymmetries Across Cormentioning

confidence: 93%

Asymmetry of Anticipatory Activity in Visual Cortex Predicts the Locus of Attention and Perception

et al. 2007

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Humans can use advance information to direct spatial attention before stimulus presentation and respond more accurately to stimuli at the attended location compared with unattended locations. Likewise, spatially directed attention is associated with anticipatory activity in the portion of visual cortex representing the attended location. It is unknown, however, whether and how anticipatory signals predict the locus of spatial attention and perception. Here, we show that prestimulus, preparatory activity is highly correlated across regions representing attended and unattended locations. Comparing activity representing attended versus unattended locations, rather than measuring activity for only one location, dramatically improves the accuracy with which preparatory signals predict the locus of attention, largely by removing this positive correlation common across locations. In V3A, moreover, only the difference in activity between attended and unattended locations predicts whether upcoming visual stimuli will be accurately perceived. These results suggest that the locus of attention is coded in visual cortex by an asymmetry of anticipatory activity between attended and unattended locations and that this asymmetry predicts the accuracy of perception. This coding strategy may bias activity in downstream brain regions to represent the stimulus at the attended location.

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Section: Spatial Attention As Moment-to-moment Asymmetries Across Cormentioning

confidence: 93%

Asymmetry of Anticipatory Activity in Visual Cortex Predicts the Locus of Attention and Perception

et al. 2007

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“…Saccade-related neurons (SN) are located in the more caudal parts of the SC. SN pause firing during fixations while producing bursts of spikes prior to and during saccades directed to their response field (Sparks et al 1976;Wurtz and Goldberg 1972;Munoz and Wurtz 1995a). Converging data from microstimulation studies (Gandhi and Keller 1999;Robinson 1972) and single cell recordings (Krauzlis et al 1997;Wurtz 1993a, 1995b) reveal that FN like SN still possess a movement field, i.e., activity of FN is associated with small contraversive saccades.…”

Section: Prolongation Of Saccade Latencies Following Microsaccadesmentioning

confidence: 99%

Shortening and prolongation of saccade latencies following microsaccades

2005

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When the eyes fixate at a point in a visual scene, small saccades rapidly shift the image on the retina. The effect of these microsaccades on the latency of subsequent large-scale saccades may be twofold. First, microsaccades are associated with an enhancement of visual perception.Their occurrence during saccade target perception should, thus, decrease saccade latencies. On the other hand, microsaccades likely indicate activity in fixation-related oculomotor neurons. These represent competitors to saccade-related cells in the interplay of gaze holding and shifting.Consequently, an increase in saccade latencies after microsaccades would be expected. Here, we present evidence for both aspects of microsaccadic impact on saccade latency. In a delayed response task, participants made saccades to visible or memorized targets. First, microsaccade occurrence up to 50 ms before target disappearance correlated with 18 ms (or 8%) faster saccades to memorized targets. Second, if microsaccades occurred shortly (i.e., < 150 ms) before a saccade was required, saccadic reaction times in visual and memory trials were increased by about 40 ms (or 16%). Hence, microsaccades can have opposite consequences for saccade latencies, pointing at a differential role of these fixational eye movements in preparation of motor programs.

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“…Second, Churchland and Lisberger (2001) also included in the denominator of their reconstruction equation, but to achieve noise immunity in the speed estimation rather than to account for a fundamental feature of their data. A related model has been used to describe the effect of microstimulation in the superior colliculus on saccadic eye movements (Sparks et al, 1976;Stanford et al, 1996) and a neurally plausible way of implementing Equation 6 has been tested by (Groh, 2001).…”

Section: Estimating Target Speed From the Population Responsementioning

confidence: 99%

Estimating Target Speed from the Population Response in Visual Area MT

Priebe¹,

Lisberger²

2004

J. Neurosci.

116

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To guide behavior, perceptual and motor systems must estimate properties of the sensory environment from the responses of populations of cortical neurons. In the domain of visual motion, estimates of target speed are derived from the responses of motion-sensitive neurons in the middle temporal (MT) area of the extrastriate visual cortex and are used to drive smooth pursuit eye movements and perceptual judgments of speed. We have asked how these behavioral systems estimate target speed from the population response in area MT. We found that increasing the spatial frequency of a sine wave grating caused decreases in the target speed estimated by both pursuit and perception and commensurate changes in the identity of the active neurons in area MT. Decreasing the contrast of a sine wave grating caused decreases in the target speed estimated by both pursuit and perception, while altering only the response amplitude of MT neurons and not the identity of the active neurons. Applying a modified vector-averaging computation to the population response measured in area MT allowed us to predict the effects of both spatial frequency and contrast on speed estimation for both perception and pursuit. The modification biased the speed estimation toward low target speeds when responses across the population of neurons were small.

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Size and distribution of movement fields in the monkey superior colliculus

Cited by 311 publications

References 22 publications

Asymmetry of Anticipatory Activity in Visual Cortex Predicts the Locus of Attention and Perception

Asymmetry of Anticipatory Activity in Visual Cortex Predicts the Locus of Attention and Perception

Shortening and prolongation of saccade latencies following microsaccades

Estimating Target Speed from the Population Response in Visual Area MT

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