Biomedical subjects

M A Georgeson

Publications and source records attributed to M A Georgeson.

At least 19 recordsLinked to original sources

PubMed2000

The temporal properties of first- and second-order vision.

Vision is sensitive to first-order modulations of luminance and second-order modulations of image contrast. There is now a body of evidence that the two types of modulation are detected by separate mechanisms. Some previous experiments on motion detection have suggested that the second-order system is quite sluggish compared to the first-order system. Here we derive temporal properties of first- and second-order vision at threshold from studies of temporal integration and two-pulse summation. Three types of modulation were tested: luminance gratings alone, luminance modulations added to dynamic visual noise, and contrast modulations of dynamic noise. Data from the two-pulse summation experiment were used to derive impulse response functions for the three types of stimulus. These were then used to predict performance in the temporal integration experiment. Temporal frequency response functions were obtained as the Fourier transform of impulse responses derived from data averaged across two observers. The response to noise-free luminance gratings of 2 c/deg was bi-phasic and transient in the time domain, and bandpass in the frequency domain. The addition of dynamic noise caused the response to become mono-phasic, sustained and low-pass. The response to contrast modulated noise (second-order) was also mono-phasic, sustained and low-pass, with only a slightly longer integration time than in the first-order case. The ultimate roll-off at high frequencies was about the same as for the first-order case. We conclude that second-order vision may not be as sluggish as previously thought.

Contrast Sensitivity↗

PubMed2000

Spatial resolution and receptive field height of motion sensors in human vision.

We estimated the length of motion-detecting receptive fields in human vision by measuring direction discrimination for three novel stimuli. The motion sequences contained either (i) alternate frames of two differently oriented sinusoidal gratings; (ii) alternate frames of vertical grating and plaid stimuli or (iii) a vertical grating divided into horizontal strips of equal height, where alternate strips moved leftward and rightward. All three stimulus sequences had a similar appearance (of moving strips) and the task was to identify the direction of the central strip. For sequences (ii) and (iii), performance fell as the strip height decreased. Threshold height fell with increasing contrast up to about 20%, then levelled off at the critical strip height. Temporal frequency (1. 9-15 Hz) had no effect on the critical strip height. We argue that the receptive field length corresponds to twice this critical height. The length estimates were strikingly short, ranging from about 0.4 cycles at 3.0 cpd to 0.1 cycles at 0.1 cpd. These lengths agree well with the estimates derived at threshold by Anderson and Burr (1991, J. Opt. Soc. Am. A8, 1330-1339), and imply that the motion-sensing filters have very broad orientation tuning. These and other results are interpreted within the framework of a Gaussian derivative model for motion filtering. The sensitivity of motion filters to a broad range of orientations suggests a simpler view of how coherent plaid motion is processed.

Humans↗

PubMed1999

Feature matching and segmentation in motion perception.

We examined the role of feature matching in motion perception. The stimulus sequence was constructed from a vertical, 1 cycle deg-1 sinusoidal grating divided into horizontal strips of equal height, where alternate strips moved leftward and rightward. The initial relative phase of adjacent strips was either 0 degree (aligned) or 90 degrees (non-aligned) and the motion was sampled at 90 degrees phase steps. A blank interstimulus interval (ISI) of 0-117 ms was introduced between each 33 ms presentation of the stimulus frames. The observers had to identify the direction of motion of the central strip. Motion was perceived correctly at short ISIs, but at longer ISIs performance was much better for the non-aligned sequence than the aligned sequence. This difference in performance may reflect a role for feature correspondence and grouping of features in motion perception at longer ISIs. In the aligned sequence half the frames consisted of a single coherent vertical grating, while the interleaved frames contained short strips. We argue that to achieve feature matching over time, the long edge and bar features must be broken up perceptually (segmented) into shorter elements before these short segments can appear to move in opposite directions. This idea correctly predicted that overlaying narrow, stationary, black horizontal lines at the junctions of the grating strips would improve performance in the aligned condition. The results support the view that, in addition to motion energy, feature analysis and feature tracking play an important role in motion perception.

Humans↗

PubMed1999

Sensitivity to modulations of luminance and contrast in visual white noise: separate mechanisms with similar behaviour.

Human vision can detect spatiotemporal information conveyed by first-order modulations of luminance and by second-order, non-Fourier modulations of image contrast. Models for second-order motion have suggested two filtering stages separated by a rectifying nonlinearity. We explore here the encoding of stationary first-order and second-order gratings, and their interaction. Stimuli consisted of 2-D binary, broad-band, static, visual noise sinusoidally modulated in luminance (LM, first-order) or contrast (CM, second-order). Modulation thresholds were measured in a two-interval forced-choice staircase procedure. Sensitivity curves for LM and CM had similar shape as a function of spatial frequency, and as a function of the size of a circular Gaussian blob of modulation. Weak background gratings present in both intervals produced order-specific facilitation: LM background facilitated LM detection (the dipper function) and CM facilitated CM detection. LM did not facilitate CM, nor vice-versa, neither in-phase nor out-of-phase, and this is strong evidence that LM and CM are detected via separate mechanisms. This conclusion was further supported by an experiment on the detection of LM/CM mixtures. From a general mathematical model and a specific computer simulation we conclude that a single mechanism sensitive to both LM and CM cannot predict the pattern of results for mixtures, while a model containing separate pathways for LM and CM, followed by energy summation, does so successfully and is quantitatively consistent with the finding of order-specific facilitation.

Contrast Sensitivity↗

PubMed1999

Does early non-linearity account for second-order motion?

A contrast-modulated (CM) pattern is formed when a modulating or envelope function imposes local contrast variations on a higher-frequency carrier. Motion may be seen when the envelope drifts across a stationary carrier and this has been attributed to a second-order pathway for motion. However, an early compressive response to luminance (e.g. in the photoreceptors) would introduce a distortion product at the modulating frequency. We used a nulling method to measure the distortion product, and then asked whether this early distortion could account for perception of second-order motion. The first stimulus sequence consisted of alternate frames of CM (100% modulation) and luminance-modulated (LM) patterns. Carriers were either 2-D binary noise (4 x 4 min arc dots) or a 4 c/deg grating, both modulated at 0.6 c/deg. The carrier was stationary while the phase of the modulating signal (LM alternating with CM) stepped successively through 90 degrees to the left or right. Motion was seen in a direction opposite to the phase stepping, consistent with early compressive distortion that induces an out-of-phase LM component into the CM stimulus. We measured distortion amplitude by adding LM to the CM frames to null the perceived motion. Distortion increased as the square of carrier contrast, as predicted by the compressive transducer. It also increased with modulation drift rate, implying that the transducer is time-dependent, not static. Thus early compressive non-linearity does induce first-order artefacts into second-order stimuli. Nevertheless this does not account for second-order motion, since perceived motion of second-order sequences (CM in every frame) could in general not be nulled by adding LM components. We conclude that two pathways for motion do exist.

Contrast Sensitivity↗

PubMed1999

Motion contrast: a new metric for direction discrimination.

The Adelson-Bergen energy model (Adelson, E. H., & Bergen, J. R. (1985). Spatiotemporal energy models for the perception of motion. Journal of the Optical Society of America A, 2, 284-299) is a standard framework for understanding first-order motion processing. The opponent energy for a given input is calculated by subtracting one directional energy measure (EL) from its opposite (ER), and its sign indicates the direction of motion of the input. Our observers viewed a dynamic sequence of gratings (1 c/deg) equivalent to the sum of two gratings moving in opposite directions with different contrasts. The ratio of contrasts was varied across trials. We found that opponent energy was a very poor predictor of direction discrimination performance. Heeger (1992). Normalization of cell responses in cat striate cortex. Visual Neuroscience, 9, 181-197) has suggested that divisive inhibition amongst striate cells requires a contrast gain control in the energy model. A new metric can be formulated in the spirit of Heeger's model by normalising the opponent energy (EL - ER) with flicker energy, the sum of the directional motion energies (EL + ER). This new measure, motion contrast (EL - ER)/(EL + ER), was found to be a good predictor of direction discrimination performance over a wide range of contrast levels, but opponent energy was not. Discrimination thresholds expressed as motion contrast were around 0.5 +/- 0.1 for the sampled drifting gratings used in our experiments. We show that the dependence on motion contrast, and the threshold of about 0.5, can be predicted by a modified opponent energy model based on current knowledge of the response functions and response variance of cortical cells.

Discrimination, Psychological↗

PubMed1999

Adaptive filtering in spatial vision: evidence from feature marking in plaids.

Much evidence shows that early vision employs an array of spatial filters tuned for different spatial frequencies and orientations. We suggest that for moderately low spatial frequencies these preliminary filters are not treated independently, but are used to perform grouping and segmentation in the patchwise Fourier domain. For example, consider a stationary plaid made from two superimposed sinusoidal gratings of the same contrast and spatial frequency oriented +/- 45 degrees from vertical. Most of the energy in a wavelet-like (e.g. simple-cell) transform of this stimulus is in the oblique orientations, but typically it looks like a compound structure containing blurred vertical and horizontal edges. This checkerboard structure corresponds with the locations of zero crossings in the output of an isotropic (circular) filter, synthesised from the linear sum of a set of oriented basis-filters (Georgeson, 1992 Proceedings of the Royal Society of London, Series B 249 235-245). However, the addition of a third harmonic in square-wave phase causes almost complete perceptual segmentation of the plaid into two overlapping oblique gratings. Here we confirm this result psychophysically using a feature-marking technique, and argue that this perceptual segmentation cannot be understood in terms of the zero crossings marked in the output of any static linear filter that is sensitive to all of the plaid's components. If it is assumed that zero crossings or similar are an appropriate feature-primitive in human vision, our results require a flexible process that combines and segments early basis-filters according to prevailing image conditions. Thus, we suggest that combination and segmentation of spatial filters in the patchwise Fourier domain underpins the perceptual segmentation observed in our experiments. Under this kind of image-processing scheme, registration across spatial scales occurs at the level of spatial filters, before features are extracted. This contrasts with many previous schemes where feature correspondence is required between spatial edge-maps at different spatial scales.

Adaptation, Psychological↗

PubMed1998

Motion blur and motion sharpening: temporal smear and local contrast non-linearity.

Blurred images may appear sharper when drifting than when stationary. But, paradoxically, moving sharp edges may appear more blurred. To resolve this paradox, the perceived sharpness of drifting, blurred, square wave gratings was compared with that of their static analogues over a range of speeds, blurs and spatial frequencies. Both motion blur and motion sharpening occurred, depending upon the physical blur of the patterns. For large extents of blur (> 10 min arc) moving patterns always appeared sharper than their static analogues, but for small blurs (< 10 min arc) moving edges appeared more blurred than stationary ones. We present a quantitative model for the distortion of waveforms in motion based on two factors: (i) visual temporal integration that smears moving images, and (ii) a local contrast non-linearity that increasingly sharpens the effective profile of edges as speed and contrast increase. We suggest that a plausible account of the speed-dependent non-linearity is the differential recruitment of M and P cells at different speeds.

Contrast Sensitivity↗

PubMed1997

Perceived location of bars and edges in one-dimensional images: computational models and human vision.

Observers used a cursor to mark the location and polarity of all the bar and edge features seen in compound (f + 3f) gratings of moderate frequency and contrast. They almost always reported six bars and six edges per cycle of the fundamental frequency (f = 0.4 c/deg, contrast 32%), for all phases of the third harmonic (3f = 1.2 c/deg, contrast 10.7%). This general pattern of features was predicted by the positions of peaks and troughs in the outputs of even and odd filters applied to the stimulus waveform, but not by peaks of "local energy" since there were only two energy peaks per cycle. We considered a family of filters whose amplitude spectrum has slope p on a log-log plot. The best-fitting filter slope was determined for bars (even filter) and edges (odd filter) in conjunction with a classification rule in which all peaks and troughs in the response profile are counted as features. If bars were seen at luminance peaks, and edges seen at gradient peaks (zero-crossings in the second derivative) we should have found p = 0 for bars and p = 1 for edges. In fact, for both bars and edges the best-fitting slope was about p = 0.5. For edges, this is consistent with the use of a smoothed (Gaussian) derivative operator. The filters form a quadrature pair, as in the energy model, but features are not constrained to lie at energy peaks. A compressive transducer preceding the filters improved the goodness-of-fit for predicted edge locations, but did not affect the estimate of filter slopes, nor the goodness-of-fit for bar locations. In an experiment with single blurred edges we confirmed that the perceived location of edges is shifted towards the darker side of the edge in direct proportion to the contrast of the edge. This was well predicted by adding a compressive transducer to the filter model.

Contrast Sensitivity↗

PubMed1997

Perception of stationary plaids: the role of spatial filters in edge analysis.

Orientation-tuned spatial filters in visual cortex are widely held to act as "orientation detectors", but our experiments on the perception of stationary two-dimensional (2-D) plaids require a new view. When two sinusoidal gratings at different orientations (say 1 c/deg, +/- 45 deg from vertical) are superimposed to form a standard plaid they do not, in general, look like two sets of oblique contours (diamonds) but more like a blurred checkerboard (squares) with vertical and horizontal edges, although the Fourier components are oblique. The pattern of edges seen in this plaid and others corresponds to the zero-crossings (ZCs) in the output of a circular filter, but adaptation and masking experiments suggest that oriented filters are being summed to emulate circular filtering, before ZC analysis. At low contrasts or after adaptation to an intermediate orientation, the combining of filters can fail or be "broken", and the diamond structure of the components is seen instead. Adding a low contrast third harmonic to one component in square-wave phase also changed the plaid's appearance from squares to diamonds, but adapting to the third harmonic enhanced the square appearance. Filters can evidently switch from combining across orientation to combining across spatial frequency. The combination stage of edge detection may involve variably weighted summing of oriented filters in monocular pathways, followed by a process that makes explicit the locations and orientations of features.

Adaptation, Ocular↗

PubMed1996

The tilt aftereffect in plaids and gratings: channel codes, local signs and "patchwise" transforms.

The perceived structure of a suprathreshold plaid made from two sinusoidal gratings tilted +/- 45 deg from vertical usually resembles a blurred checkerboard. Physically increasing the tilt of the components away from vertical elongates the pattern horizontally, yielding rectangular checks. We asked whether illusory tilt of the components induced by adaptation to a vertical grating would also give apparent elongation of the checks. Using a staircase method, we found that after adaptation the component orientations had to be set 3-4 deg closer to vertical to maintain a square, checkerboard-like appearance, implying that the +/- 45 deg plaid did appear elongated. This result suggests that the tilt aftereffect adaptation not only distorts the orientation of 1-D patterns but can also change the relative location of features, even when their orientation is not altered. This is not easy to explain within filter models that (often implicitly) assume each receptive field carries a fixed "local sign" indicating its position within the retinal array. We consider a representation in which localized patches of the image are encoded by the coefficients of a 2-D Fourier-like transform. With a simple subtractive model of adaptation, we show that the spatial information carried by each patch would be distorted in just the way observed for plaids and gratings. The fact that perceived structure is both distorted and coherent, not fragmented, after adaptation suggests an additional, more global process whereby local patches are combined to form a coherent, composite "neural image". We offer a simple principle that could establish this coherence. If the positions of local patches are adjusted so as to maximize the contrast energy of the composite image, then the spatial distortions of the patches (induced by selective adaptation) are carried through to the global structure of the composite. Thus, the conflict between channel codes and local signs is resolved, but perceptual distortion is the result.

Adaptation, Ocular↗

PubMed1996

Sub-pixel accuracy: psychophysical validation of an algorithm for fine positioning and movement of dots on visual displays.

Many visual experiments call for visual displays in which dots are plotted with very fine positional accuracy. Spatial hyperacuities and motion displacement thresholds can be as low as 5 sec arc. On computer graphics displays small angular displacements of a pixel can be obtained only with long viewing distances which impose a small field of view. To overcome this problem, we describe a method for positioning the centroid of a quadrel (a 2 x 2 block of pixels) with very high accuracy, equivalent to 0.4% of a pixel width. This enables dot displays to be plotted with high positional accuracy at short viewing distances with larger fields of view. We show psychophysically that hyperacuities can be measured with sub-pixel accuracy in quadrel displays. Motion displacement thresholds of 16 sec arc were measured in multiple-dot and single-dot displays even though the pixel spacing was 1.2 min arc. Quadrel displays may be especially useful in studies of optic flow and structure-from-motion which demand a fairly large field of view along with fine positional accuracy.

Algorithms↗

PubMed1996

Spatial filter combination in human pattern vision: channel interactions revealed by adaptation.

Above threshold, two superimposed sinusoidal gratings of the same spatial frequency (eg 1 cycle deg-1), of equal moderate contrast (eg C1 = C2 = 6%), and with orientations of +/- 45 degrees, usually look like a compound structure containing vertical and horizontal edges (ie a blurred checkerboard). These feature orientations are very different from the dominant filter orientations in a wavelet-type (eg simple-cell) transform of the stimulus, and so present a serious challenge to conventional models of orientation coding based on labelled linear filters. Previous experiments on perceived structure in static plaids have led to the view that the outputs of tuned spatial filters are combined in a stimulus-dependent way, before features such as edges are extracted. Here an adaptation paradigm was used to investigate the cross-channel interactions that appear to underlie the spatial-filter-combination process. Reported are two aftereffects of selective adaptation: (i) adaptation to a 1 cycle deg-1 plaid whose component orientations are intermediate to those in a 1 cycle deg-1 test plaid 'breaks' perceptual combination of the components in the test plaid; (ii) adapting to a 3 cycles deg-1 plaid whose component orientations match those in a 1 cycle deg-1 test plaid facilitates perceptual combination of the components in the test plaid. The results are taken as evidence that spatial channels remote from those most responsive to a test plaid play a crucial role in determining whether the test plaid segments or coheres perceptually.

Adaptation, Ocular↗

PubMed1994

From filters to features: location, orientation, contrast and blur.

Consider three main ideas about spatial filtering and feature coding in human spatial vision. (1) Computational theory: the representation of local luminance features--bars and edges--is a crucial step in human vision, forming the basis for many decisions in pattern discrimination. (2) Algorithm: features may be located and characterized in terms of polarity, blur and contrast by comparison of 1st, 2nd and 3rd spatial derivatives taken at a common point. Edges in compound (f + 3f) gratings are seen at or close to peaks of gradient magnitude. More tentatively, bars may be located at peaks of the 2nd derivative or at peaks in the Hilbert transform of the 1st derivative. Peaks of contrast energy do not predict all the features seen. An algorithm for recovering the blur of edges is derived as the square-root of the ratio of 1st to 3rd derivatives at the edge location. This successfully predicts blur matching between Gaussian edges and a variety of other test waveforms, including sine waves. Blur matching is (nearly) contrast invariant, as predicted by this ratio rule. (3) IMPLEMENTATION: experiments on the perception and discrimination of plaids imply that the outputs of tuned filters are combined before feature coding. The adaptive, weighted summation of bandpass filters may serve to synthesize the derivative operators while facilitating the segmentation of overlapping features and preventing the representation from being swamped by noise.

Animals↗

PubMed1994

Perceived contrast of gratings and plaids: non-linear summation across oriented filters.

Plaids composed of two orthogonal sine-wave gratings appeared to be of lower contrast than single gratings of the same Michelson luminance contrast. This effect for plaids was obtained at all spatial frequencies (1-16 c/deg) and contrast levels (2-32%). Contrast-matching data plotted as a function of the angle between plaid components (0-90 deg) and as a function of spatial frequency and standard contrast level were consistent with a model in which the response of each orientation-tuned spatial frequency channel is a threshold-corrected power function of contrast, and is followed by quadratic summation of responses across all channels. The best-fitting contrast-response exponent in the main experiment was 0.63. Analysis of several other data-sets suggested a slightly higher value, 0.80. The same model gave a good account of contrast-matching between simple and compound (two-component) one dimensional gratings, accounting in particular for the apparent increase in contrast summation exponent at low contrasts reported by Quick, Hamerly and Reichert [(1976) Vision Research, 16, 351-355]. The model can, with one further assumption, account for the finding that contrast-matching between sine-wave and square-wave gratings depended only on the amplitude at the fundamental frequency. Comparison with contrast discrimination studies suggests that internal noise (variance of a channel's contrast-response) is not constant, but increases approximately in proportion to the mean response.

Contrast Sensitivity↗

PubMed1992

Human vision combines oriented filters to compute edges.

The experiments examined the perceived spatial structure of plaid patterns, composed of two or three sinusoidal gratings of the same spatial frequency, superimposed at different orientations. Perceived structure corresponded well with the pattern of zero crossings in the output of a circular spatial filter applied to the image. This lends some support to Marr & Hildreth's (Proc. R. Soc. Lond. B 207, 187 (1980)) theory of edge detection as a model for human vision, but with a very different implementation. The perceived structure of two-component plaids was distorted by prior exposure to a masking or adapting grating, in a way that was perceptually equivalent to reducing the contrast of one of the plaid components. This was confirmed by finding that the plaid distortion could be nulled by increasing the contrast of the masked or adapted component. A corresponding reduction of perceived contrast for single gratings was observed after adaptation and in some masking conditions. I propose the outlines of a model for edge finding in human vision. The plaid components are processed through cortical, orientation-selective filters that are subject to attenuation by forward masking and adaptation. The outputs of these oriented filters are then linearly summed to emulate circular filtering, and zero crossings (zcs) in the combined output are used to determine edge locations. Masking or adapting to a grating attenuates some oriented filters more than others, and although this changes only the effective contrast of the components, it results in a geometric distortion at the zc level after different filters have been combined. The orientation of zcs may not correspond at all with the orientation of Fourier components, but they are correctly predicted by this two-stage model. The oriented filters are not 'orientation detectors', but are precursors to a more subtle stage that locates and represents spatial features.

Adaptation, Ocular↗

PubMed1992

No evidence for dichoptic motion sensing: a reply to Carney and Shadlen.

Georgeson and Shackleton (1989, Vision Research, 29, 1511-1523) confirmed the existence of dichoptic apparent motion (AM), but argued that its basis was the spatio-temporal correspondence of visible features ("feature tracking"), not early motion sensors. Direction selectivity in motion sensors was probably purely monocular. The key evidence came from AM of missing-fundamental (MF) gratings. Monocular MF motion was always reversed, implying motion sensors responding to the third harmonic (3f) component. Dichoptic MF motion was in the correct direction at the higher contrasts and lower drift rates, and overall was highly correlated with judgements of pattern structure, suggesting feature-tracking. Carney and Shadlen (1992, Vision Research, 32, 187-191) criticized some of our methodology and the theoretical interpretation. Their central argument was that dichoptic AM for sine-waves did reflect dichoptic motion sensing, but was less reliable at higher contrasts. Hence forward motion of the dichoptic MF pattern should occur only where sine-wave (3f) motion-sensing declines. We discuss their critique, and find little support for it. We also present additional data on dichoptic AM for 3f and 5f gratings, showing that Carney and Shadlen's predictions were not upheld. Feature tracking remains the most plausible account of dichoptic AM.

Contrast Sensitivity↗

PubMed1991

The time course of adaptation to spatial contrast.

We explored the buildup and decay of threshold elevation during and after adaptation to sinewave gratings in a series of experiments investigating the effects of adapting time, adapting contrast, spatial frequency and retinal eccentricity. Contrast thresholds for vertical sinewave gratings truncated in space by a one-dimensional Gaussian envelope were measured before and after adaptation to a full-field suprathreshold grating of the same spatial frequency and orientation. Thresholds were measured intermittently after adaptation in a "seen/not-seen" single presentation procedure until these thresholds returned to baseline values. The first test grating was presented 300 msec after the offset of the adapting stimulus, and thereafter at regular intervals. At different times after adaptation, contrast thresholds were estimated by off-line analysis of the data using the QUEST algorithm. Adapting time was either 1, 10, 100 or 1000 sec and adapting contrast was either 9, 19, 29 or 39 dB (re. 1%). The test gratings were presented centered either at the fixation point or at 5 and 10 deg eccentricity along the horizontal meridian. The results suggest that up to the saturation level the buildup and the decay of adaptation to contrast is well described by a power function of time. The slope of the best fitting line on log-log axes is fairly constant for the adaptation times tested. As reported earlier, thresholds increased with adapting contrast and these contrast-dependent differences were evident 300 msec after the termination of adaptation. Adaptation at 10 deg eccentricity yielded slightly higher threshold elevations than for central vision. Based on these results, a description is given of the dynamic response of the underlying neural mechanisms.

Adaptation, Ocular↗