Publications by authors named "Bruce Cumming"

Neurons throughout the brain modulate their firing rate lawfully in response to sensory input. Theories of neural computation posit that these modulations reflect the outcome of a constrained optimization in which neurons aim to robustly and efficiently represent sensory information. Our understanding of how this optimization varies across different areas in the brain, however, is still in its infancy.

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Neurons throughout the brain modulate their firing rate lawfully in response to changes in sensory input. Theories of neural computation posit that these modulations reflect the outcome of a constrained optimization: neurons aim to efficiently and robustly represent sensory information under resource limitations. Our understanding of how this optimization varies across the brain, however, is still in its infancy.

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Natural images are typically broadband, whereas detectors in early visual processing are selective for narrow ranges of spatial frequency. White noise patterns are widely used in laboratory settings to investigate how responses are derived from Fourier components in the image. Here, we report disparity vergence responses (DVRs) to white noise stimuli in human subjects and compare these with responses to white noise patterns filtered with bandpass filters and notch filters and to sinusoidal gratings.

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Ocular following eye movements have provided insights into how the visual system of humans and monkeys processes motion. Recently, it has been shown that they also reliably reveal stereoanomalies, and, thus, might have clinical applications. Their translation from research to clinical setting has however been hindered by their small size, which makes them difficult to record, and by a lack of data about their properties in sizable populations.

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Direction selective neurons in macaque primary visual cortex are narrowly tuned for orientation, and are thus afflicted by the aperture problem. At the next stage of motion processing, in the middle temporal (MT) area, some cells appear to solve this problem, responding to the pattern motion direction of plaids. Models have been proposed to account for this computation, but they do not replicate the diversity of responses observed in MT.

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Statistical models are increasingly being used to understand the complexity of stimulus selectivity in primary visual cortex (V1) in the context of complex time-varying stimuli, replacing averaging responses to simple parametric stimuli. Although such models often can more accurately reflect the computations performed by V1 neurons in more natural visual environments, they do not by themselves provide insight into V1 neural selectivity to basic stimulus features such as receptive field size, spatial frequency tuning, and phase invariance. Here, we present a battery of analyses that can be directly applied to encoding models to link complex encoding models to more interpretable aspects of stimulus selectivity.

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Neuronal and psychophysical responses to a visual stimulus are known to depend on the preceding history of visual stimulation, but the effect of stimulation history on reflexive eye movements has received less attention. Here, we quantify these effects using short-latency ocular following responses (OFRs), a valuable tool for studying early motion processing. We recorded, in human subjects, the horizontal OFRs induced by drifting vertical 1D pink noise.

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We recorded horizontal ocular-following responses to pairs of superimposed vertical sine wave gratings moving in opposite directions in human subjects. This configuration elicits a nonlinear interaction: when the relative contrast of the gratings is changed, the response transitions abruptly between the responses elicited by either grating alone. We explore this interaction in pairs of gratings that differ in spatial and temporal frequency and show that all cases can be described as a weighted sum of the responses to each grating presented alone, where the weights are a nonlinear function of stimulus contrast: a nonlinear weighed summation model.

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From a mathematical point of view, extracting motion and disparity signals from a binocular visual stream requires very similar operations, applied over time for motion and across eyes for disparity. This similarity is reflected in the theories that have been proposed to describe the neural mechanisms used by the brain to extract these signals. At the behavioral level there are, however, several differences in how humans react to these stimuli, which presumably reflect differences in how these signals are processed by the brain.

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Early vision proceeds through distinct ON and OFF channels, which encode luminance increments and decrements respectively. It has been argued that these channels also contribute separately to stereoscopic vision. This is based on the fact that observers perform better on a noisy disparity discrimination task when the stimulus is a random-dot pattern consisting of equal numbers of black and white dots (a "mixed-polarity stimulus," argued to activate both ON and OFF stereo channels), than when it consists of all-white or all-black dots ("same-polarity," argued to activate only one).

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Purpose: Stereoscopic vision, by detecting interocular correlations, enhances depth perception. Stereodeficiencies often emerge during the first months of life, and left untreated can lead to severe loss of visual acuity in one eye and/or strabismus. Early treatment results in much better outcomes, yet diagnostic tests for infants are cumbersome and not widely available.

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Vergence is defined as a binocular eye movement during which the two eyes move in opposite directions to align to a target in depth. In adults, fine vergence control is driven primarily by interocular retinal image disparity. Although infants have not typically been shown to respond to disparity until 3 to 5 months postpartum, they have been shown to align their eyes from hours after birth.

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Psychophysical studies and our own subjective experience suggest that, in natural viewing conditions (i.e., at medium to high contrasts), monocularly and binocularly viewed scenes appear very similar, with the exception of the improved depth perception provided by stereopsis.

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The variable responses of sensory neurons tend to be weakly correlated (spike-count correlation, r). This is widely thought to reflect noise in shared afferents, in which case r can limit the reliability of sensory coding. However, it could also be due to feedback from higher-order brain regions.

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Sensory neurons are activated by a range of stimuli to which they are said to be tuned. Usually, they are also suppressed by another set of stimuli that have little effect when presented in isolation. The interactions between preferred and suppressive stimuli are often quite complex and vary across neurons, even within a single area, making it difficult to infer their collective effect on behavioral responses mediated by activity across populations of neurons.

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When light falls within a neuronal visual receptive field (RF) the resulting activity is referred to as the visual response. Recent work suggests this activity is in response to both the visual stimulation and the abrupt appearance, or salience, of the presentation. Here we present a novel method for distinguishing the two, based on the timing of random and nonrandom presentations.

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How does our brain use differences between the images in our two eyes, binocular disparities, to generate depth perception? New work shows that a type of neural network trained on natural binocular images can learn parameters that match key properties of visual cortex. Most information is conveyed by cells which sense differences between the two eyes' images.

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The motion energy model is the standard account of motion detection in animals from beetles to humans. Despite this common basis, we show here that a difference in the early stages of visual processing between mammals and insects leads this model to make radically different behavioural predictions. In insects, early filtering is spatially lowpass, which makes the surprising prediction that motion detection can be impaired by "invisible" noise, i.

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At least under some conditions, plaid stimuli are processed by combining information first extracted in orientation and scale-selective channels. The rules that govern this combination across channels are only partially understood. Although the available data suggests that only components having similar spatial frequency and contrast are combined, the extent to which this holds has not been firmly established.

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Unlabelled: Fine judgments of stereoscopic depth rely mainly on relative judgments of depth (relative binocular disparity) between objects, rather than judgments of the distance to where the eyes are fixating (absolute disparity). In macaques, visual area V2 is the earliest site in the visual processing hierarchy for which neurons selective for relative disparity have been observed (Thomas et al., 2002).

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Unlabelled: Human stereopsis can operate in dense "cyclopean" images containing no monocular objects. This is believed to depend on the computation of binocular correlation by neurons in primary visual cortex (V1). The observation that humans perceive depth in half-matched random-dot stereograms, although these stimuli have no net correlation, has led to the proposition that human depth perception in these stimuli depends on a distinct "matching" computation possibly performed in extrastriate cortex.

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Unlabelled: The ability to distinguish between elements of a sensory neuron's activity that are stimulus independent versus driven by the stimulus is critical for addressing many questions in systems neuroscience. This is typically accomplished by measuring neural responses to repeated presentations of identical stimuli and identifying the trial-variable components of the response as noise. In awake primates, however, small "fixational" eye movements (FEMs) introduce uncontrolled trial-to-trial differences in the visual stimulus itself, potentially confounding this distinction.

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The first step in binocular stereopsis is to match features on the left retina with the correct features on the right retina, discarding 'false' matches. The physiological processing of these signals starts in the primary visual cortex, where the binocular energy model has been a powerful framework for understanding the underlying computation. For this reason, it is often used when thinking about how binocular matching might be performed beyond striate cortex.

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In order to extract retinal disparity from a visual scene, the brain must match corresponding points in the left and right retinae. This computationally demanding task is known as the stereo correspondence problem. The initial stage of the solution to the correspondence problem is generally thought to consist of a correlation-based computation.

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Unlabelled: Since the discovery of neurons selective for pattern motion direction in primate middle temporal area MT (Albright, 1984; Movshon et al., 1985), the neural computation of this signal has been the subject of intense study. The bulk of this work has explored responses to plaids obtained by summing two drifting sinusoidal gratings.

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