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J A Perrone

Publications and source records attributed to J A Perrone.

13 recordsLinked to original sources
PubMed1998

Emulating the visual receptive-field properties of MST neurons with a template model of heading estimation.

We have proposed previously a computational neural-network model by which the complex patterns of retinal image motion generated during locomotion (optic flow) can be processed by specialized detectors acting as templates for specific instances of self-motion. The detectors in this template model respond to global optic flow by sampling image motion over a large portion of the visual field through networks of local motion sensors with properties similar to those of neurons found in the middle temporal (MT) area of primate extrastriate visual cortex. These detectors, arranged within cortical-like maps, were designed to extract self-translation (heading) and self-rotation, as well as the scene layout (relative distances) ahead of a moving observer. We then postulated that heading from optic flow is directly encoded by individual neurons acting as heading detectors within the medial superior temporal (MST) area. Others have questioned whether individual MST neurons can perform this function because some of their receptive-field properties seem inconsistent with this role. To resolve this issue, we systematically compared MST responses with those of detectors from two different configurations of the model under matched stimulus conditions. We found that the characteristic physiological properties of MST neurons can be explained by the template model. We conclude that MST neurons are well suited to support self-motion estimation via a direct encoding of heading and that the template model provides an explicit set of testable hypotheses that can guide future exploration of MST and adjacent areas within the superior temporal sulcus.

Head Movements↗
PubMed1997

Human heading estimation during visually simulated curvilinear motion.

Recent studies have suggested that humans cannot estimate their direction of forward translation (heading) from the resulting retinal motion (flow field) alone when rotation rates are higher than approximately 1 deg/sec. It has been argued that either oculomotor or static depth cues are necessary to disambiguate the rotational and translational components of the flow field and, thus, to support accurate heading estimation. We have re-examined this issue using visually simulated motion along a curved path towards a layout of random points as the stimulus. Our data show that, in this curvilinear motion paradigm, five of six observers could estimate their heading relatively accurately and precisely (error and uncertainty < approximately 4 deg), even for rotation rates as high as 16 deg/sec, without the benefit of either oculomotor or static depth cues signaling rotation rate. Such performance is inconsistent with models of human self-motion estimation that require rotation information from sources other than the flow field to cancel the rotational flow.

Adult↗
PubMed1994

A model of self-motion estimation within primate extrastriate visual cortex.

Perrone [(1992) Journal of the Optical Society of America A, 9, 177-194] recently proposed a template-based model of self-motion estimation which uses direction- and speed-tuned input sensors similar to neurons in area MT of primate visual cortex. Such an approach would generally require an unrealistically large number of templates (five continuous dimensions). However, because primates, including humans, have a number of oculomotor mechanisms which stabilize gaze during locomotion, we can greatly reduce the number of templates required (two continuous dimensions and one compressed and bounded dimension). We therefore refined the model to deal with the gaze-stabilization case and extended it to extract heading and relative depth simultaneously. The new model is consistent with previous human psychophysics and has the emergent property that its output detectors have similar response properties to neurons in area MST.

Depth Perception↗
PubMed1992

Model for the computation of self-motion in biological systems.

I present a method by which direction- and speed-tuned cells, such as those commonly found in the middle temporal area of the primate brain, can be used to analyze the patterns of retinal image motion that are generated during observer movement through the environment. For pure translation, the retinal image motion is radial in nature and expands out from a point that corresponds to the direction of heading. This heading direction can be found by the use of translation detectors that act as templates for the radial image motion. Each translation detector sums the outputs of direction- and speed-tuned motion sensors arranged such that their preferred direction of motion lies along the radial direction out from the detector center. The most active detector signifies the heading direction. Rotation detectors can be constructed in a similar fashion to detect areas of uniform image speed and direction in the motion field produced by observer rotation. A model consisting of both detector types can determine the heading direction independently of any rotational motion of the observer. The model can achieve this from the outputs of the two-dimensional motion sensors directly and does not assume the existence of accurate estimates of image speed and direction. It is robust to the aperture problem and is biologically realistic. The basic elements of the model have been shown to exist in the primate visual cortex.

Animals↗
PubMed1984

Visual slant misperception and the 'black-hole' landing situation.

A theory is presented which explains the often quoted tendency for dangerously low approaches during night-landing situations. The two-dimensional information at the pilot's eye contains sufficient information for the visual system to estimate correctly the angle of slant of the runway relative to the approach path. An algorithm is developed which can perform this angle estimation. It is dependent upon perspective information being available a certain lateral distance out from the aimpoint, to either side of the runway edgelights. However, under 'black-hole' landing conditions this information is not available, and it is proposed that the visual system uses instead the only available information--namely the perspective gradient of the runway edgelights. An equation is developed which predicts what the perceived approach angle will be when this incorrect perspective is used. The predictions are in close agreement with existing experimental data.

Aviation↗
PubMed1982

Visual slant underestimation: a general model.

A general model of visual slant underestimation is presented. It is based on the idea that two specific types of perceptual error occur in the evaluation of the slant angle by the observer. The reason for these errors occurring is postulated to be that reduced viewing conditions result in the deviation of the observer's perceived straight-ahead direction from the true direction. Specifically this deviation is postulated to be in the direction of the nearest part of the surface in accord with conditions that exist in our everyday environment. In the case of a slanted rectangle correct registration of the projected length of half of the surface and the correct registration of the appropriate angle of convergence will result in perception being veridical. A mechanism is outlined which indicates how both of these factors can be in error, and an equation is developed which enables the predicted slant estimates to be calculated given the dimensions of the rectangle and its distance from the eye. Equations for the case of slanted surfaces viewed through apertures are also developed. The model is assessed in relation to past slant-perception experiments and is found to be a good predictor of the large amount of previously unexplained underestimation that occurred in these studies.

Humans↗
PubMed1980

Slant underestimation: a model based on the size of the viewing aperture.

By analyzing the projection plane in terms of the projected size of different elements on a surface, it is shown how the direction of the perpendicular, from the station point to the surface, is an important variable in the derivation of the slant angle. It is also shown that the test surfaces used in traditional slant-perception experiments contain no information about this direction. A model is proposed which is based on the idea that the direction of the line from the eye to one edge of the viewing aperture is mistaken for the perpendicular, and two options are derived to show how the information in the optical array could be interpreted on the basis of the perpendicular lying in this new direction. It is shown that both of these options are dependent upon the size of the field of view of the test surface and both are underestimations as long as half of the angle measuring the field of view is less than the actual slant of the surface. The model is tested against some data from previously reported experiments and is found to provide a close fit.

Form Perception↗