Vitaly Chicherov

Crowding, grouping, and object recognition: A matter of appearance

In crowding, the perception of a target strongly deteriorates when neighboring elements are presented. Crowding is usually assumed to have the following characteristics. (a) Crowding is determined only by nearby elements within a restricted region around the target (Boumas law). (b) Increasing the number of flankers can only deteriorate performance. (c) Target-flanker interference is feature-specific. These characteristics are usually explained by pooling models, which are well in the spirit of classic models of object recognition. In this review, we summarize recent findings showing that crowding is not determined by the above characteristics, thus, challenging most models of crowding. We propose that the spatial configuration across the entire visual field determines crowding. Only when one understands how all elements of a visual scene group with each other, can one determine crowding strength. We put forward the hypothesis that appearance (i.e., how stimuli look) is a good predictor for crowding, because both crowding and appearance reflect the output of recurrent processing rather than interactions during the initial phase of visual processing.

Neural correlates of visual crowding

In visual crowding, target discrimination strongly deteriorates when flanking elements are added. We have recently shown that crowding cannot be explained by simple low-level interactions and that grouping is a key component instead. We presented a vernier flanked by arrays of vertical lines. When the flankers had the same lengths as the vernier, offset discrimination was strongly impaired. When longer flankers were presented, crowding was weaker. We proposed that crowding is strong when the flankers group with the target (equal length flankers). When the target segregates from the flankers, crowding is weaker (long flankers). To understand the neurophysiological mechanisms of grouping in crowding, here, we adapted the above vernier paradigm to a high-density EEG study. The P1 component reflected basic stimulus characteristics (flanker length) but not crowding. Crowding emerged slowly and manifested as a suppression of the N1 component (after 180ms). Using inverse solutions, we found that the N1 suppression was caused by reduced neural activity in high-level visual areas such as the lateral occipital cortex. Our results suggest that crowding occurs when elements are grouped into wholes, a process reflected by the N1 component.

Targets but not flankers are suppressed in crowding as revealed by EEG frequency tagging

Perception of a visual target can strongly deteriorate in the presence of flanking elements (crowding). For example, adding lines next to a vernier makes vernier offset discrimination difficult. Crowding is often considered a bottleneck of low-level vision, determined by the unavoidable limitations of the early visual system. In accordance with this proposal, neural processing of the flankers should be impaired in crowding as much as that of the target. To test this prediction, we used steady-state visually evoked potentials (ssVEPs) to separate target responses from flanker responses. We presented a vernier target either alone or flanked by lines, which had the same color as the vernier or a different color. Crowding by same-color flankers was stronger than by different-color flankers. Mirroring the behavioral results, ssVEP amplitudes corresponding to the target were higher for different-color flankers than for same-color flankers. Flanker related ssVEPs, however, did not depend on crowding strength. It seems that target, but not flanker processing, is susceptible to crowding. In line with previous results, we suggest that crowding is not caused by low-level interferences but is linked to target-flanker grouping instead.

An automatic pre-processing pipeline for EEG analysis (APP) based on robust statistics

OBJECTIVE With the advent of high-density EEG and studies of large numbers of participants, yielding increasingly greater amounts of data, supervised methods for artifact rejection have become excessively time consuming. Here, we propose a novel automatic pipeline (APP) for pre-processing and artifact rejection of EEG data, which innovates relative to existing methods by not only following state-of-the-art guidelines but also further employing robust statistics. METHODS APP was tested on event-related potential (ERP) data from healthy participants and schizophrenia patients, and resting-state (RS) data from healthy participants. Its performance was compared with that of existing automatic methods (FASTER for ERP data, TAPEEG and Prep pipeline for RS data) and supervised pre-processing by experts. RESULTS APP rejected fewer bad channels and bad epochs than the other methods. In the ERP study, it produced significantly higher amplitudes than FASTER, which were consistent with the supervised scheme. In the RS study, it produced spectral measures that correlated well with the automatic alternatives and the supervised scheme. CONCLUSION APP effectively removed EEG artifacts, performing similarly to the supervised scheme and outperforming existing automatic alternatives. SIGNIFICANCE The proposed automatic pipeline provides a reliable and efficient tool for pre-processing large datasets of both evoked and resting-state EEG.

What crowds in crowding

Keywords: crowding ; masking ; object recognition ; reading Reference EPFL-ARTICLE-223306doi:10.1167/16.11.25View record in Web of Science Record created on 2016-11-21, modified on 2016-11-27

Electrophysiological signatures of crowding are similar in foveal and peripheral vision

Flankers can strongly deteriorate performance on a visual target (crowding). For example, vernier offset discrimination strongly deteriorates when neighbouring flankers are presented. Interestingly, performance for longer and shorter flankers is better than performance for flankers of the same length as the vernier. Based on these findings, we proposed that crowding is strongest when the vernier and the flankers group (same length flankers) and weaker when the vernier ungroups from the flankers (shorter or longer flankers). These effects were observed both in foveal and peripheral vision. Here, using high-density EEG, we show that electrophysiological signatures of crowding are also similar in foveal and peripheral vision. In both foveal and peripheral (3.9°) vision, the N1 wave correlated well with performance levels and, hence, with crowding. Amplitudes were highest for the long flankers, intermediate for the short flankers and lowest for the equal length flankers. This effect was observed neither at earlier stages of processing, nor in control conditions matched for stimulus energy. Effects are more pronounced in the fovea than in the periphery. These similarities are evidence for a common mechanism of crowding in both foveal and peripheral vision.

The N1 wave amplitude reflects perceptual grouping and correlates with crowding

In crowding, flanking elements strongly deteriorate performance. For example, vernier offset discrimination is strongly affected by neighboring flankers. Performance is worst when the flankers have the same length as the vernier. Surprisingly, performance improves for longer and shorter flankers [Malania et al., 2007, Journal of Vision, 7(2):1, 1-7]. We proposed that crowding is strongest when the vernier and the flankers group (same length flankers) and weaker when they ungroup (shorter or longer flankers). Here, we used high density EEG to investigate the time course of crowding. First we replicated previous findings. Performance was best in the long flankers condition, intermediate in the short flankers condition, and worst in the medium flankers condition. The P1 wave amplitude correlated with flanker length being highest in the long flankers condition, intermediate in the medium flankers condition, and lowest in the short flankers condition. The N1 wave amplitude correlated well with performance being highest in the long flankers condition, intermediate in the short flankers condition, and lowest in the medium flankers condition. Our study shows that the N1 wave is a good predictor for perceptual grouping and hence crowding. These processes seem to occur after the P1 wave, i.e. after basic feature extraction.

Dominant men are faster in decision-making situations and exhibit a distinct neural signal for promptness

Abstract Social dominance, the main organizing principle of social hierarchies, facilitates priority access to resources by dominant individuals. Throughout taxa, individuals are more likely to become dominant if they act first in social situations and acting fast may provide evolutionary advantage; yet whether fast decision‐making is a behavioral predisposition of dominant persons outside of social contexts is not known. Following characterization of participants for social dominance motivation, we found that, indeed, men high in social dominance respond faster‐without loss of accuracy‐than those low in dominance across a variety of decision‐making tasks. Both groups did not differ in a simple reaction task. Then, we selected a decision‐making task and applied high‐density electroencephalography (EEG) to assess temporal dynamics of brain activation through event related potentials. We found that promptness to respond in the choice task in dominant individuals is related to a strikingly amplified brain signal at approximately 240 ms post‐stimulus presentation. Source imaging analyses identified higher activity in the left insula and in the cingulate, right inferior temporal and right angular gyri in high than in low dominance participants. Our findings suggest that promptness to respond in choice situations, regardless of social context, is a biomarker for social disposition.

Crowding, grouping, timing

In crowding, target perception is deteriorated by flanking elements. For example, when a vernier is flanked by two lines of the same length, vernier offset discrimination strongly deteriorates. Interestingly, changing the color of the flankers can reduce crowding (uncrowding). Similarly, when the flanking lines are part of a cube, i.e., a good Gestalt, crowding is weak. Conversely, however, scrambling the lines of the cubes, i.e., a “bad” Gestalt, leads to strong crowding. We proposed that crowding is strong when target and flankers group (two-lines, scrambled cubes). Crowding is weak when the target ungroups from the flankers (two flanking lines with different color, cubes). Here, we show, first, that when target and flankers group (strong crowding), crowding is unaffected by stimulus duration. Two same-length flankers presented for 20 ms lead to similar performance as when presented for 150 ms. Second, in uncrowding with flankers of different color (and other basic feature differences), performance is again unaffected by stimulus duration. Third, in uncrowding with cubes, duration matters. For short durations (20 ms), crowding is strong and only for longer stimulus durations (from 120 ms on) does crowding decrease. We suggest that, for short durations, the brain cannot process the good Gestalt of the cubes. The representation of the cube’s lines is “unstructured”, as in the scrambled cubes, and hence crowding is strong. Interestingly, a short preview (20 ms duration) of only the cubes strongly reduces crowding, even when the preview is presented one second before the “crowded” stimulus. Our results suggest that uncrowding emerges in a slow, recurrent manner, with iconic memory playing an important role.

EEG frequency tagging dissociates target and flanker processing in crowding

Flankers can strongly deteriorate performance on a target (crowding). The neural mechanisms of crowding are largely unknown. We have recently shown that the N1 component of the EEG is suppressed during crowding. Because it is difficult to disentangle the neural correlates of target and flanker processing with standard visually evoked potentials, here, we used a frequency-tagging technique to analyze EEG responses separately for flankers and target. Subjects discriminated the offset direction of a vernier that was slowly increasing in size either to the left or right. The vernier and the flankers were either green or red and flickered at two different frequencies. Flankers of the same color as the vernier (green-green or red-red) crowded more strongly than flankers of a different color (green-red or red-green) because the former, as we propose, grouped with the vernier. EEG responses to the vernier were suppressed during crowding (same color flankers) compared to uncrowding (different color flankers). EEG responses to the flankers were slightly larger when the flankers grouped with the target compared to when they ungrouped from the target. Hence, EEG frequency tagging dissociates target and flanker processing. Our results suggest that, in crowding, the target is suppressed when it groups with the flankers while flanker-related activity increases or stays constant.