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Dive into the research topics where Peter Lennie is active.

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Featured researches published by Peter Lennie.


Vision Research | 1990

Coding of image contrast in central visual pathways of the macaque monkey.

Gary Sclar; John H. R. Maunsell; Peter Lennie

Measurements of contrast sensitivity were obtained from isolated neurons in the lateral geniculate nucleus, striate cortex, and middle temporal visual area of macaque monkeys. Between the lateral geniculate nucleus and the middle temporal area contrast sensitivity functions become progressively steeper. Furthermore, many neurons in the middle temporal area are more sensitive than any cell encountered in early stages. Measurements made with stimuli of different sizes show that this high sensitivity depends on areal summation across the receptive field.


Current Biology | 2003

The Cost of Cortical Computation

Peter Lennie

Electrophysiological recordings show that individual neurons in cortex are strongly activated when engaged in appropriate tasks, but they tell us little about how many neurons might be engaged by a task, which is important to know if we are to understand how cortex encodes information. For human cortex, I estimate the cost of individual spikes, then, from the known energy consumption of cortex, I establish how many neurons can be active concurrently. The cost of a single spike is high, and this severely limits, possibly to fewer than 1%, the number of neurons that can be substantially active concurrently. The high cost of spikes requires the brain not only to use representational codes that rely on very few active neurons, but also to allocate its energy resources flexibly among cortical regions according to task demand. The latter constraint explains the investment in local control of hemodynamics, exploited by functional magnetic resonance imaging, and the need for mechanisms of selective attention.


Journal of The Optical Society of America A-optics Image Science and Vision | 1986

Mechanisms of color constancy

Michael D'Zmura; Peter Lennie

We develop a model of how the visual system finds the colors of objects that have unknown shapes and positions. The model relies on mechanisms of light adaptation, coupled with eye movements, to recover three descriptors of surface reflectance that are represented in the signals of an achromatic mechanism and two color-opponent mechanisms. These descriptors are transformed to yield estimates of hue, the dimension of surface color that is independent of object shape and viewing geometry.


Perception | 1998

Single Units and Visual Cortical Organization

Peter Lennie

The visual system has a parallel and hierarchical organization, evident at every stage from the retina onwards. Although the general benefits of parallel and hierarchical organization in the visual system are easily understood, it has not been easy to discern the function of the visual cortical modules. I explore the view that striate cortex segregates information about different attributes of the image, and dispatches it for analysis to different extrastriate areas. I argue that visual cortex does not undertake multiple relatively independent analyses of the image from which it assembles a unified representation that can be interrogated about the what and where of the world. Instead, occipital cortex is organized so that perceptually relevant information can be recovered at every level in the hierarchy, that information used in making decisions at one level is not passed on to the next level, and, with one rather special exception (area MT), through all stages of analysis all dimensions of the image remain intimately coupled in a retinotopic map. I then offer some explicit suggestions about the analyses undertaken by visual areas in occipital cortex, and conclude by examining some objections to the proposals.


Neuron | 2004

Profound Contrast Adaptation Early in the Visual Pathway

Samuel G. Solomon; Jonathan W. Peirce; Neel T. Dhruv; Peter Lennie

Prior exposure to a moving grating of high contrast led to a substantial and persistent reduction in the contrast sensitivity of neurons in the lateral geniculate nucleus (LGN) of macaque. This slow contrast adaptation was potent in all magnocellular (M) cells but essentially absent in parvocellular (P) cells and neurons that received input from S cones. Simultaneous recordings of M cells and the potentials of ganglion cells driving them showed that adaptation originated in ganglion cells. As expected from the spatiotemporal tuning of M cells, adaptation was broadly tuned for spatial frequency and lacked orientation selectivity. Adaptation could be induced by high temporal frequencies to which cortical neurons do not respond, but not by low temporal frequencies that can strongly adapt cortical neurons. Our observations confirm that contrast adaptation occurs at multiple levels in the visual system, and they provide a new way to reveal the function and perceptual significance of the M pathway.


Nature Reviews Neuroscience | 2007

The machinery of colour vision

Samuel G. Solomon; Peter Lennie

Some fundamental principles of colour vision, deduced from perceptual studies, have been understood for a long time. Physiological studies have confirmed the existence of three classes of cone photoreceptors, and of colour-opponent neurons that compare the signals from cones, but modern work has drawn attention to unexpected complexities of early organization: the proportions of cones of different types vary widely among individuals, without great effect on colour vision; the arrangement of different types of cones in the mosaic seems to be random, making it hard to optimize the connections to colour-opponent mechanisms; and new forms of colour-opponent mechanisms have recently been discovered. At a higher level, in the primary visual cortex, recent studies have revealed a simpler organization than had earlier been supposed, and in some respects have made it easier to reconcile physiological and perceptual findings.


Vision Research | 1989

Contrast adaptation in striate cortex of macaque

Gary Sclar; Peter Lennie; Derryl D. DePriest

We have characterized the contrast-response relationships for simple and complex cells in striate cortex of macaque monkey, before and during adaptation to high-contrast sinusoidal gratings of the optimal spatial-frequency and orientation. Adaptation brings about systematic changes in the steepness of contrast-response curves and in the effective contrast of stimuli. Adaptation reduces the detectability of low-contrast gratings by almost a factor of three, but by extending the operating range of most cells it appears to improve the discriminability of high-contrast stimuli that previously gave rise to responses of saturating amplitude.


The Journal of Neuroscience | 2005

Early and Late Mechanisms of Surround Suppression in Striate Cortex of Macaque

Ben S. Webb; Neel T. Dhruv; Samuel G. Solomon; Chris Tailby; Peter Lennie

The response of a neuron in striate cortex to an optimally configured visual stimulus is generally reduced when the stimulus is enlarged to encroach on a suppressive region that surrounds its classical receptive field (CRF). To characterize the mechanism that gives rise to this suppression, we measured its spatiotemporal tuning, its susceptibility to contrast adaptation, and its capacity for interocular transfer. Responses to an optimally configured grating confined to the CRF were strongly suppressed by annular surrounding gratings drifting at a wide range of temporal and spatial frequencies (including spatially uniform fields) that extended from well below to well above the range that drives most cortical neurons. Suppression from gratings capable of driving cortical CRFs was profoundly reduced by contrast adaptation and showed substantial interocular transfer. Suppression from stimuli that lay outside the spatiotemporal passband of most cortical CRFs was relatively stronger when the stimulus on the CRF was of low contrast, was generally insusceptible to contrast adaptation, and showed little interocular transfer. Our findings point to the existence of two mechanisms of surround suppression: one that is prominent when high-contrast stimuli drive the CRF, is orientation selective, has relatively sharp spatiotemporal tuning, is binocularly driven, and can be substantially desensitized by adaptation; the other is relatively more prominent when low-contrast stimuli drive the CRF, has very broad spatiotemporal tuning, is monocularly driven, and is insusceptible to adaptation. Its character suggests an origin in the input layers of primary visual cortex, or earlier.


Vision Research | 2001

Packing arrangement of the three cone classes in primate retina

Austin Roorda; Andrew B. Metha; Peter Lennie; David R. Williams

We describe a detailed analysis of the spatial arrangement of L, M and S cones in the living eyes of two humans and one monkey. We analyze the cone mosaics near 1 degrees eccentricity using statistical methods that characterize the arrangement of each type of cone in the mosaic of photoreceptors. In all eyes, the M and L cones are arranged randomly. This gives rise to patches containing cones of a single type. In human, but not in monkey, the arrangement of S-cones cannot be distinguished from random.


Journal of The Optical Society of America A-optics Image Science and Vision | 2005

Coding of color and form in the geniculostriate visual pathway (invited review).

Peter Lennie; J. Anthony Movshon

We review how neurons in the principal pathway connecting the retina to the visual cortex represent information about the chromatic and spatial characteristics of the retinal image. Our examination focuses particularly on individual neurons: what are their visual properties, how might these properties arise, what do these properties tell us about visual signal transformations, and how might these properties be expressed in perception? Our discussion is inclined toward studies on old-world monkeys and where possible emphasizes quantitative work that has led to or illuminates models of visual signal processing.

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John Krauskopf

Center for Neural Science

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Chris Tailby

Florey Institute of Neuroscience and Mental Health

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Neel T. Dhruv

Center for Neural Science

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