Lan Zhang

Bio: Lan Zhang is an academic researcher from Syracuse University. The author has an hindex of 2, co-authored 2 publications receiving 527 citations.

The Psychophysics Toolbox.

Abstract: The Psychophysics Toolbox is a software package that supports visual psychophysics. Its routines provide an interface between a high-level interpreted language (MATLAB on the Macintosh) and the video display hardware. A set of example programs is included with the Toolbox distribution.

Attention alters appearance

Abstract: At any given moment, our visual system is confronted with far more information than it can process effectively. The high energy cost of neuronal activity involved in cortical computation severely limits our capacity to process this information 1 .V isual attention serves as a mediating mechanism, enabling us to selectively grant priority of processing to certain aspects of the visual scene. One means of granting priority is to direct one’s gaze towards the relevant location. However, many situations call for one to attend to an area in the periphery without actually directing gaze toward it. For example, when driving it is generally best to keep your eyes on the road ahead while covertly monitoring the periphery for cars, pedestrians and potential road hazards. The impact of covert attention 2 on visual performance is well-documented across a range of perceptual tasks, such as visual search 3‐6 ,l etter identification 7,8 ,c ontrast sensitivity 9‐12 and spatial resolution 13‐16 .S everal studies that used single-cell recording 17‐22 ,e vent-related potentials 23,24 and functional magnetic resonance imaging (fMRI) 25‐27 indicate that attentional modulation

Controlling low-level image properties: the SHINE toolbox.

Abstract: Visual perception can be influenced by top-down processes related to the observer’s goals and expectations, as well as by bottom-up processes related to low-level stimulus attributes, such as luminance, contrast, and spatial frequency. When using different physical stimuli across psychological conditions, one faces the problem of disentangling the contributions of low- and high-level factors. Here, we make available the SHINE (spectrum, histogram, and intensity normalization and equalization) toolbox for MATLAB, which we have found useful for controlling a number of image properties separately or simultaneously. The toolbox features functions for specifying the (rotational average of the) Fourier amplitude spectra, for normalizing and scaling mean luminance and contrast, and for exact histogram specification optimized for perceptual visual quality. SHINE can thus be employed for parametrically modifying a number of image properties or for equating them across stimuli to minimize potential low-level confounds in studies on higher level processes.

Compulsory averaging of crowded orientation signals in human vision

Abstract: A shape can be more difficult to identify when other shapes are near it. For example, when several grating patches are viewed parafoveally, observers are unable to report the orientation of the central patch. This phenomenon, known as 'crowding,' has historically been confused with lateral masking, in which one stimulus attenuates signals generated by another stimulus. Here we show that despite their inability to report the orientation of an individual patch, observers can reliably estimate the average orientation, demonstrating that the local orientation signals are combined rather than lost. Our results imply that crowding is distinct from ordinary masking, and is perhaps related to texture perception. Under crowded conditions, the orientation signals in primary visual cortex are pooled before they reach consciousness.

Crowding is unlike ordinary masking: Distinguishing feature integration from detection

Abstract: A letter in the peripheral visual field is much harder to identify in the presence of nearby letters. This is “crowding.” Both crowding and ordinary masking are special cases of “masking,” which, in general, refers to any effect of a “mask” pattern on the discriminability of a signal. Here we characterize crowding, and propose a diagnostic test to distinguish it from ordinary masking. In ordinary masking, the signal disappears. In crowding, it remains visible, but is ambiguous, jumbled with its neighbors. Masks are usually effective only if they overlap the signal, but the crowding effect extends over a large region. The width of that region is proportional to signal eccentricity from the fovea and independent of signal size, mask size, mask contrast, signal and mask font, and number of masks. At 4 deg eccentricity, the threshold contrast for identification of a 0.32 deg signal letter is elevated (up to six-fold) by mask letters anywhere in a 2.3 deg region, 7 times wider than the signal. In ordinary masking, threshold contrast rises as a power function of mask contrast, with a shallow log-log slope of 0.5 to 1, whereas, in crowding, threshold is a sigmoidal function of mask contrast, with a steep log-log slope of 2 at close spacing. Most remarkably, although the threshold elevation decreases exponentially with spacing, the threshold and saturation contrasts of crowding are independent of spacing. Finally, ordinary masking is similar for detection and identification, but crowding occurs only for identification, not detection. More precisely, crowding occurs only in tasks that cannot be done based on a single detection by coarsely coded feature detectors. These results (and observers’ introspections) suggest that ordinary masking blocks feature detection, so the signal disappears, while crowding (like “illusory conjunction”) is excessive feature integration — detected features are integrated over an inappropriately large area because there are no smaller integration fields — so the integrated signal is ambiguous, jumbled with the mask. In illusory conjunction, observers see an object that is not there made up of features that are. A survey of the illusory conjunction literature finds that most of the illusory conjunction results are consistent with the spatial crowding described here, which depends on spatial proximity, independent of time pressure. The rest seem to arise through a distinct phenomenon that one might call “temporal crowding,” which depends on time pressure (“overloading attention”), independent of spatial proximity.