Improve P300-Speller performance by online adaptive tuning Stimulus Onset Asynchrony (SOA)

Author(s):  
Pin Gao ◽  
Yihao Huang ◽  
Feng He ◽  
Hongzhi Qi
1975 ◽  
Vol 41 (3) ◽  
pp. 791-796 ◽  
Author(s):  
Johannes Abresch ◽  
Viktor Sarris

Perceptual contrast effect was studied from two points of view, as a special anchor effect and as a special figural aftereffect. Two experiments were conducted to investigate the influence of stimulus onset asynchrony on contrast and assimilation effects, induced and measured by different psychophysical methods. Stimuli were circular beams of light projected on screens (Delboef type of illusion). When anchor and series stimuli were shown and the latter were judged by means of a rating scale, stimulus onset asychrony had no substantial influence on the contrast effect (Exp. I). When the constant method was applied, however, the asynchrony altered the shape of the contrast effect considerably (Exp. II).


1986 ◽  
Vol 61 (1) ◽  
pp. 17-36 ◽  
Author(s):  
Annette M.B. de Groot ◽  
Arnold J.W.M. Thomassen ◽  
Patrick T.W. Hudson

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251117
Author(s):  
Andrea Polzien ◽  
Iris Güldenpenning ◽  
Matthias Weigelt

In many kinds of sports, deceptive actions are frequently used to hamper the anticipation of an opponent. The head fake in basketball is often applied to deceive an observer regarding the direction of a pass. To perform a head fake, a basketball player turns the head in one direction, but passes the ball to the opposite direction. Several studies showed that reactions to passes with head fakes are slower and more error-prone than to passes without head fakes (head-fake effect). The aim of a basketball player is to produce a head-fake effect for as large as possible in the opponent. The question if the timing of the deceptive action influences the size of the head-fake effect has not yet been examined systematically. The present study investigated if the head-fake effect depends on the temporal lag between the head turn and the passing movement. To this end, the stimulus onset asynchrony between head turn, and pass was varied between 0 and 800 ms. The results showed the largest effect when the head turn precedes the pass by 300 ms. This result can be explained better by facilitating the processing of passes without head fake than by making it more difficult to process passes with a head fake. This result is discussed regarding practical implications and conclusions about the underlying mechanism of the head–fake effect in basketball are drawn.


Perception ◽  
10.1068/p5844 ◽  
2007 ◽  
Vol 36 (10) ◽  
pp. 1455-1464 ◽  
Author(s):  
Vanessa Harrar ◽  
Laurence R Harris

Gestalt rules that describe how visual stimuli are grouped also apply to sounds, but it is unknown if the Gestalt rules also apply to tactile or uniquely multimodal stimuli. To investigate these rules, we used lights, touches, and a combination of lights and touches, arranged in a classic Ternus configuration. Three stimuli (A, B, C) were arranged in a row across three fingers. A and B were presented for 50 ms and, after a delay, B and C were presented for 50 ms. Subjects were asked whether they perceived AB moving to BC (group motion) or A moving to C (element motion). For all three types of stimuli, at short delays, A to C dominated, while at longer delays AB to BC dominated. The critical delay, where perception changed from group to element motion, was significantly different for the visual Ternus (3 lights, 162 ms) and the tactile Ternus (3 touches, 195 ms). The critical delay for the multimodal Ternus (3 light – touch pairs, 161 ms) was not different from the visual or tactile Ternus effects. In a second experiment, subjects were exposed to 2.5 min of visual group motion (stimulus onset asynchrony = 300 ms). The exposure caused a shift in the critical delay of the visual Ternus, a trend in the same direction for the multimodal Ternus, but no shift in the tactile Ternus. These results suggest separate but similar grouping rules for visual, tactile, and multimodal stimuli.


1992 ◽  
Vol 43 ◽  
pp. 27-38
Author(s):  
Ton Dijkstra

Two divided attention experiments investigated whether graphemes and phonemes can mutually activate each other during bimodal sublexical processing. Dutch subjects reacted to target letters and/or speech sounds in single-channel and bimodal stimuli. In some bimodal conditions, the visual and auditory targets were congruent (e.g., visual A, auditory /a:/), in others they were not (e.g., visual U, auditory /a:/). Temporal aspects of cross-modal activation were examined by varying the stimulus onset asynchrony (SOA) of visual and auditory stimulus components. Processing differences among stimuli (e.g., the letters A and U) were accounted for by correcting the obtained bimodal reaction times by means of the predictions of an independent race-model. Comparing the results of the adapted congruent and incongruent conditions for each SOA, it can be concluded that (a) cross-modal activation takes place in this task situation; (b) it is bidirectional, i.e. it spreads from grapheme to phoneme and vice versa; and (c) it occurs very rapidly.


2020 ◽  
Vol 74 (1) ◽  
pp. 199-217
Author(s):  
Ulrike Senftleben ◽  
Martin Schoemann ◽  
Matthias Rudolf ◽  
Stefan Scherbaum

In real life, decisions are often naturally embedded in decision sequences. In contrast, in the laboratory, decisions are oftentimes analysed in isolation. Here, we investigated the influence of decision sequences in value-based decision making and whether the stability of such effects can be modulated. In our decision task, participants needed to collect rewards in a virtual two-dimensional world. We presented a series of two reward options that were either quick to collect but were smaller in value or took longer to collect but were larger in value. The subjective value of each option was driven by the options’ value and how quickly they could be reached. We manipulated the subjective values of the options so that one option became gradually less valuable over the course of a sequence, which allowed us to measure choice perseveration (i.e., how long participants stick to this option). In two experiments, we further manipulated the time interval between two trials (inter-trial interval), and the time delay between the onsets of both reward options (stimulus onset asynchrony). We predicted how these manipulations would affect choice perseveration using a computational attractor model. Our results indicate that both the inter-trial interval and the stimulus onset asynchrony modulate choice perseveration as predicted by the model. We discuss how our findings extend to research on cognitive stability and flexibility.


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