Biomedical subjects

Mark E McCourt

Publications and source records attributed to Mark E McCourt.

7 recordsLinked to original sources

PubMed2005

Oriented multiscale spatial filtering and contrast normalization: a parsimonious model of brightness induction in a continuum of stimuli including White, Howe and simultaneous brightness contrast.

The White effect [Perception 8 (1979) 413] cannot be simply explained as due to either brightness contrast or brightness assimilation because the direction of the induced brightness change does not correlate with the amount of black or white border in contact with the gray test patch. This has led some investigators to abandon spatial filtering explanations not only for the White effect but for brightness perception in general. Offered instead are explanations based on a variety of junction analyses and/or perceptual organization schemes which in the case of the White effect are usually based on T-junctions. Recently, Howe [Perception 30 (2001) 1023] challenged T-junction based explanations with a novel variation of White's effect in which the T-junctions were constant while the brightness effect was eliminated or reversed, and proposed an alternative explanation in terms of illusory contours. The present study argues that an analysis at the level of illusory contours is not necessary and that a much simpler spatial filtering based explanation is sufficient. Brightness induction was measured in a set of stimuli chosen to illustrate the relationship between the Howe stimulus [Perception 30 (2001) 1023], the White stimulus [Perception 8 (1979) 413] and the classical simultaneous brightness contrast (SBC) stimulus. The White stimulus and the SBC stimulus occupy opposite ends of a continuum of stimuli in which the Howe stimulus is the mid-point. The psychophysical measurements were compared with the predictions of the oriented difference-of-Gaussians (ODOG) computational model of Blakeslee and McCourt [Vision Research 39 (1999) 4361]. The ODOG model parsimoniously accounted for both the direction and relative magnitude of the brightness effects suggesting that more complex mechanisms are not required to explain them.

Contrast Sensitivity↗

PubMed2005

Unilateral visual cueing and asymmetric line geometry share a common attentional origin in the modulation of pseudoneglect.

Numerous factors influence the leftward bias (pseudoneglect) in perceived line midpoint of normal subjects in line bisection tasks. Cues are a potent factor; left and right cues promote shifts in perceived midpoint to the left and right, respectively. Trapezoidal lines have recently been shown to influence perceived line midpoint, displacing it toward the larger side. The present experiments test the hypothesis that the effect of line geometry, like that of unilateral cues, results from an exogenous recruitment of spatial attention. Normal right-handed subjects (N = 60) participated in two experiments employing a tachistoscopic forced-choice line bisection task. Experiment 1 crossed the effect of cue position and cue contrast, and confirmed that a significant interaction could be obtained. Experiment 2 crossed the effect of line geometry and cue position, revealing that line geometry and cue location both significantly influence perceived line midpoint, and produce a significant interaction. According to Additive Factors Logic the finding that spatial cueing interacts with line geometry suggests that both types of stimuli modulate spatial attention at a common site of processing, supporting the conclusion that the effect of line geometry itself derives from asymmetric cueing. An explanation for the interaction is offered that is based on the existence of a hypothesized compressive nonlinearity that maps attentional bias to perceptual error.

Adolescent↗

PubMed2005

A multiscale filtering explanation of gradient induction and remote brightness induction effects: a reply to Logvinenko (2003).

Grating induction is a brightness effect in which a counterphase spatial brightness variation (a grating) is induced in a homogeneous test strip that is surrounded by an inducing luminance grating (McCourt, 1982 Vision Research 22 119-134). Moulden and Kingdom (1991 Vision Research 31 1999-2008) introduced an interesting variant of grating induction (sometimes referred to as gradient induction) in which multiple strips of either a linear luminance ramp or a sine-wave grating were interlaced with strips of homogeneous luminance. We (Blakeslee and McCourt, 1999 Vision Research 39 4361-4377) demonstrated that a simple multiscale filtering explanation could account for grating induction. Recently, however, Logvinenko (2003 Perception 32 621-626) presented several arguments impugning the adequacy of spatial filtering approaches to understanding brightness induction in gradient induction stimuli. We propose that Logvinenko's arguments apply only to a limited class of filtering models, specifically those which employ only a single spatial filter. To test this hypothesis we modeled gradient induction stimuli as a function of inducing contrast, as well as Logvinenko's (2003) remote induction stimulus, using our multiscale oriented difference-of-Gaussians (ODOG) model (Blakeslee and McCourt 1999). The ODOG model successfully predicts the appearance of the inducing strips and the homogeneous test strips in the gradient induction stimuli and the appearance of the test patches in the remote induction stimuli. These results refute Logvinenko's (2003) claims, and we interpret them as providing strong evidence for a multiscale filtering approach to understanding both gradient induction and remote brightness induction effects.

Computational Biology↗

PubMed2005

Comparing the spatial-frequency response of first-order and second-order lateral visual interactions: grating induction and contrast-contrast.

The magnitudes of two suprathreshold lateral spatial-interaction effects--grating induction and contrast--contrast--were compared with regard to their dependence upon inducing-grating spatial frequency. Both effects cause the contrast of target stimuli embedded in surrounding patterns to be matched nonveridically. The magnitudes of each effect were measured in a common unit that indexed the degree of nonveridical contrast matching across a large range of target-grating contrasts (+/- 0.80). Grating induction was a low-pass effect with respect to spatial frequency, whereas contrast-contrast was bandpass, peaking at approximately 4.0 cycles deg(-1). The magnitude of grating induction exceeded that of contrast--contrast, both overall and at their optimal frequencies (0.03125 and 4.0 cycles deg(-1), respectively); the two effects are equipotent at an inducing-grating spatial frequency of 1.0 cycle deg(-1). A significant negative correlation between the magnitudes of the two effects suggests a link whereby activation of second-order normalization mechanisms may inhibit first-order mechanisms.

Contrast Sensitivity↗

PubMed2004

Brightening prospects for early cortical coding of perceived luminance: a high-density electrical mapping study.

Establishing the computational rules and neural substrates of brightness coding is a topic of both historical and contemporary interest. Two major classes of explanations for brightness illusions, such as brightness contrast, can be traced to Hering and Helmholtz. Hering's legacy is a low-level account in which brightness contrast results from obligatory lateral inhibitory interactions occurring at some level(s) in the visual system. Helmholtz offered a high-level account, positing a causal role for factors such as perceptual grouping, inferred illumination, and the extraction of surface properties such as orientation and reflectance. The tension between these theoretical viewpoints persists unabated to date. Intracranial electrophysiological recordings have revealed that brightness is represented in the firing rates of striate neurons, a fact consistent with low-level explanations. However, since the time-course of brightness-related responses relative to the onset of striate activity is undisclosed, it remains possible that striate activation might be temporally and causally secondary to higher-level computational processes. Knowledge of the timing of brightness-related neural activity is thus crucial to both constrain and adjudicate between these competing theories. We utilize high-density electrophysiological recording and a tachistoscopic brightness discrimination task to measure the time-course and scalp topography of brightness-related electrical potentials in human observers. Brightness perception is correlated with electrical activity at the earliest stages of visual cortical processing. These findings are interpreted to support Hering's low-level account of brightness for White's effect, and the results are discussed in the context of current theories of brightness perception.

Adult↗

PubMed2004

A unified theory of brightness contrast and assimilation incorporating oriented multiscale spatial filtering and contrast normalization.

Brightness induction includes both contrast and assimilations effects. Brightness contrast occurs when the brightness of a test region shifts away from the brightness of adjacent regions. Brightness assimilation refers to the opposite situation in which the brightness of the test region shifts toward that of the surrounding regions. Interestingly, in the White effect [Perception 8 (1979) 413] the direction of the induced brightness change does not correlate with the amount of black or white border in contact with the gray test patch. This has led some investigators to reject spatial filtering explanations not only for the White effect but for brightness perception in general. Instead, these investigators have offered explanations based on a variety of junction analyses and/or perceptual organization schemes. Here, these approaches are challenged with a critical set of new psychophysical measurements that determined the magnitude of the White effect, the shifted White effect [Perception 10 (1981) 215] and the checkerboard illusion [R.L. DeValois, K.K. DeValois, Spatial Vision, Oxford University Press, NY, 1988] as a function of inducing pattern spatial frequency and test patch height. The oriented difference-of-Gaussians (ODOG) computational model of Blakeslee and McCourt [Vision Res. 39 (1999) 4361] parsimoniously accounts for the psychophysical data, and illustrates that mechanisms based on junction analysis or perceptual inference are not required to explain them. According to the ODOG model, brightness induction results from linear spatial filtering with an incomplete basis set (the finite array of spatial filters in the human visual system). In addition, orientation selectivity of the filters and contrast normalization across orientation channels are critical for explaining some brightness effects, such as the White effect.

Computational Biology↗

PubMed2003

Right hemisphere control of visuospatial attention: line-bisection judgments evaluated with high-density electrical mapping and source analysis.

The "line-bisection" task has proven an especially useful clinical tool for assessment of spatial neglect syndrome in neurological patients. Here, we investigated the neural processes involved in performing this task by recording high-density event-related potentials from 128 scalp electrodes in normal observers. We characterized a robust net negative potential from 170-400 ms poststimulus presentation that correlates with line-bisection judgments. Topographic mapping shows three distinct phases to this negativity. The first phase (approximately 170-190 ms) has a scalp distribution exclusively over the right parieto-occipital and lateral occipital scalp, consistent with generators in the region of the right temporo-parietal junction and right lateral occipital cortices. The second phase (approximately 190-240 ms) sees the emergence of a second negative focus over the right central parietal scalp, consistent with subsequent involvement of right superior parietal cortices. In the third phase (approximately 240-400 ms), the topography becomes dominated by this right central parietal negativity. Inverse source modeling confirmed that right hemisphere lateral occipital, inferior parietal, and superior parietal regions were the likeliest generators of the bulk of the activity associated with this effect. The line stimuli were also presented at three contrast levels (3, 25, and 100%) in order to manipulate both the latency of stimulus processing and the relative contributions from magnocellular and parvocellular inputs. Through this manipulation, we show that the line-bisection effect systematically tracks/follows the latency of the N1 component, which is considered a temporal marker for object processing in the ventral visual stream. This pattern of effects suggests that this task invokes an allocentric (object-based) form of visuospatial attention. Further, at 3% contrast, the line-bisection effect was equivalent to the effects seen at higher contrast levels, suggesting that parvocellular inputs are not necessary for successful performance of this task.

Adult↗