scholarly journals Corrigendum to “Limited transfer of visual skill in orientation discrimination to locations treated by pre-testing and subliminal exposure” [Vis. Res. 143 (2018) 103–116]

2018 ◽  
Vol 146-147 ◽  
pp. 48
Author(s):  
Gesa Lange ◽  
Peter De Weerd
Keyword(s):  
Orientation Discrimination ◽  
Visual Skill

Orienting and Focusing in Voluntary and Involuntary Visuospatial Attention Conditions

2010 ◽  
Vol 24 (3) ◽  
pp. 198-209 ◽  
Author(s):  
Yan Wang ◽  
Jianhui Wu ◽  
Shimin Fu ◽  
Yuejia Luo
Keyword(s):  
Gain Control ◽  
Event Related Potentials ◽  
Stimulus Onset ◽  
Orientation Discrimination ◽  
Involuntary Attention ◽  
Attention Condition ◽  
Voluntary Attention ◽  
Visual Spatial ◽  
Related Potentials ◽  
Underlying Mechanisms

In the present study, we used event-related potentials (ERPs) and behavioral measurements in a peripherally cued line-orientation discrimination task to investigate the underlying mechanisms of orienting and focusing in voluntary and involuntary attention conditions. Informative peripheral cue (75% valid) with long stimulus onset asynchrony (SOA) was used in the voluntary attention condition; uninformative peripheral cue (50% valid) with short SOA was used in the involuntary attention condition. Both orienting and focusing were affected by attention type. Results for attention orienting in the voluntary attention condition confirmed the “sensory gain control theory,” as attention enhanced the amplitude of the early ERP components, P1 and N1, without latency changes. In the involuntary attention condition, compared with invalid trials, targets in the valid trials elicited larger and later contralateral P1 components, and smaller and later contralateral N1 components. Furthermore, but only in the voluntary attention condition, targets in the valid trials elicited larger N2 and P3 components than in the invalid trials. Attention focusing in the involuntary attention condition resulted in larger P1 components elicited by targets in small-cue trials compared to large-cue trials, whereas in the voluntary attention condition, larger P1 components were elicited by targets in large-cue trials than in small-cue trials. There was no interaction between orienting and focusing. These results suggest that orienting and focusing of visual-spatial attention are deployed independently regardless of attention type. In addition, the present results provide evidence of dissociation between voluntary and involuntary attention during the same task.

scholarly journals The Impact of Shape-Based Cue Discriminability on Attentional Performance

Vision ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 18
Author(s):  
Olga Lukashova-Sanz ◽  
Siegfried Wahl ◽  
Thomas S. A. Wallis ◽  
Katharina Rifai
Keyword(s):  
Temporal Processing ◽  
Visual Cues ◽  
Human Performance ◽  
Covert Attention ◽  
Orientation Discrimination ◽  
Know How ◽  
Processing Times ◽  
Attentional Performance ◽  
Cue Processing ◽  
The Impact

With rapidly developing technology, visual cues became a powerful tool for deliberate guiding of attention and affecting human performance. Using cues to manipulate attention introduces a trade-off between increased performance in cued, and decreased in not cued, locations. For higher efficacy of visual cues designed to purposely direct user’s attention, it is important to know how manipulation of cue properties affects attention. In this verification study, we addressed how varying cue complexity impacts the allocation of spatial endogenous covert attention in space and time. To gradually vary cue complexity, the discriminability of the cue was systematically modulated using a shape-based design. Performance was compared in attended and unattended locations in an orientation-discrimination task. We evaluated additional temporal costs due to processing of a more complex cue by comparing performance at two different inter-stimulus intervals. From preliminary data, attention scaled with cue discriminability, even for supra-threshold cue discriminability. Furthermore, individual cue processing times partly impacted performance for the most complex, but not simpler cues. We conclude that, first, cue complexity expressed by discriminability modulates endogenous covert attention at supra-threshold cue discriminability levels, with increasing benefits and decreasing costs; second, it is important to consider the temporal processing costs of complex visual cues.

scholarly journals Qualitative speed-accuracy tradeoff effects can be explained by a diffusion/fast-guess mixture model

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Roger Ratcliff ◽  
Inhan Kang
Keyword(s):  
Mixture Model ◽  
Diffusion Model ◽  
Response Times ◽  
Model Fit ◽  
Orientation Discrimination ◽  
Model Parameters ◽  
Stimulus Contrast ◽  
Accuracy Stress ◽  
Speed Accuracy ◽  
Selective Influence

AbstractRafiei and Rahnev (2021) presented an analysis of an experiment in which they manipulated speed-accuracy stress and stimulus contrast in an orientation discrimination task. They argued that the standard diffusion model could not account for the patterns of data their experiment produced. However, their experiment encouraged and produced fast guesses in the higher speed-stress conditions. These fast guesses are responses with chance accuracy and response times (RTs) less than 300 ms. We developed a simple mixture model in which fast guesses were represented by a simple normal distribution with fixed mean and standard deviation and other responses by the standard diffusion process. The model fit the whole pattern of accuracy and RTs as a function of speed/accuracy stress and stimulus contrast, including the sometimes bimodal shapes of RT distributions. In the model, speed-accuracy stress affected some model parameters while stimulus contrast affected a different one showing selective influence. Rafiei and Rahnev’s failure to fit the diffusion model was the result of driving subjects to fast guess in their experiment.

scholarly journals Tactile orientation perception: an ideal observer analysis of human psychophysical performance in relation to macaque area 3b receptive fields

2015 ◽  
Vol 114 (6) ◽  
pp. 3076-3096 ◽  
Author(s):  
Ryan M. Peters ◽  
Phillip Staibano ◽  
Daniel Goldreich
Keyword(s):  
Cortical Neurons ◽  
Human Performance ◽  
Spatial Perception ◽  
Receptive Fields ◽  
Human Perception ◽  
Ideal Observer ◽  
Orientation Discrimination ◽  
Orientation Perception ◽  
Area 3B ◽  
The Ideal

The ability to resolve the orientation of edges is crucial to daily tactile and sensorimotor function, yet the means by which edge perception occurs is not well understood. Primate cortical area 3b neurons have diverse receptive field (RF) spatial structures that may participate in edge orientation perception. We evaluated five candidate RF models for macaque area 3b neurons, previously recorded while an oriented bar contacted the monkey's fingertip. We used a Bayesian classifier to assign each neuron a best-fit RF structure. We generated predictions for human performance by implementing an ideal observer that optimally decoded stimulus-evoked spike counts in the model neurons. The ideal observer predicted a saturating reduction in bar orientation discrimination threshold with increasing bar length. We tested 24 humans on an automated, precision-controlled bar orientation discrimination task and observed performance consistent with that predicted. We next queried the ideal observer to discover the RF structure and number of cortical neurons that best matched each participant's performance. Human perception was matched with a median of 24 model neurons firing throughout a 1-s period. The 10 lowest-performing participants were fit with RFs lacking inhibitory sidebands, whereas 12 of the 14 higher-performing participants were fit with RFs containing inhibitory sidebands. Participants whose discrimination improved as bar length increased to 10 mm were fit with longer RFs; those who performed well on the 2-mm bar, with narrower RFs. These results suggest plausible RF features and computational strategies underlying tactile spatial perception and may have implications for perceptual learning.

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