Interindividual variability of learning in stereoacuity

Schmitt, Christina; Kromeier, Miriam; Bach, Michael; Kommerell, Guntram

doi:10.1007/s00417-002-0458-y

Cited by 18 publications

(17 citation statements)

References 25 publications

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“…The behavioral component identified by the factor analysis (i.e., PC1) combined aspects of initial performance (i.e., predisposition), the rate of performance improvement, and the quantity of practice required to reach criterion. Our observers were highly variable in their initial performance, a finding concordant with previous studies of complex visual tasks (1) as well as perceptual learning (2)(3)(4)6). Interestingly, task fitness was positively correlated with initial performance, and negatively correlated with the rate of learning and the number of blocks to criterion.…”

Section: Discussionsupporting

confidence: 89%

Individual variability in functional connectivity predicts performance of a perceptual task

Baldassarre

Lewis

Committeri

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

252

177

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People differ in their ability to perform novel perceptual tasks, both during initial exposure and in the rate of improvement with practice. It is also known that regions of the brain recruited by particular tasks change their activity during learning. Here we investigate neural signals predictive of individual variability in performance. We used resting-state functional MRI to assess functional connectivity before training on a novel visual discrimination task. Subsequent task performance was related to functional connectivity measures within portions of visual cortex and between visual cortex and prefrontal association areas. Our results indicate that individual differences in performing novel perceptual tasks can be related to individual differences in spontaneous cortical activity

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Section: Discussionsupporting

confidence: 89%

Individual variability in functional connectivity predicts performance of a perceptual task

Baldassarre

Lewis

Committeri

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

252

177

View full text Add to dashboard Cite

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“…These values are 3168 ± 384 for the sparse stereograms and 3771 ± 795 for the dense stereograms, which are consistent with other studies of perceptual learning of depth discrimination using RDSs (Gantz, Chung & Harwerth, 2007a, Westheimer, 2001). The high variability obtained in the group data for the critical number of training trials (see also the individual functions shown in Figure 2) is consistent with the large inter-individual variability of perceptual learning that is reported by others (Schmitt, Kromeier, Bach & Kommerell, 2002). …”

Section: Resultssupporting

confidence: 90%

Transfer of perceptual learning of depth discrimination between local and global stereograms

Gantz

Bedell

2010

Vision Research

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Several previous studies reported differences when stereothresholds are assessed with local-contour stereograms vs. complex random-dot stereograms (RDSs). Dissimilar thresholds may be due to differences in the properties of the stereograms (e.g., spatial frequency content, contrast, inter-element separation, area) or to different underlying processing mechanisms. This study examined the transfer of perceptual learning of depth discrimination between local and global RDSs with similar properties, and vice versa. If global and local stereograms are processed by separate neural mechanisms, then the magnitude and rate of training for the two types of stimuli are likely to differ, and the transfer of training from one stimulus type to the other should be minimal. Based on previous results, we chose RDSs with element densities of 0.17% and 28.3% to serve as the local and global stereograms, respectively. Fourteen inexperienced subjects with normal binocular vision were randomly assigned to either a local- or global- RDS training group. Stereothresholds for both stimulus types were measured before and after 7700 training trials distributed over 10 sessions. Stereothresholds for the trained condition improve for approximately 3000 trials, by an average of 0.36 ± 0.08 for local and 0.29 ± 0.10 for global RDSs, and level off thereafter. Neither the rate nor the magnitude of improvement differ statistically between the local- and global-training groups. Further, no significant difference exists in the amount of improvement on the trained vs. the untrained targets for either training group. These results are consistent with the operation of a single mechanism to process both local and global stereograms.

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“…Several studies have reported considerable intersubject variability in both the occurrence and magnitude of perceptual learning (Fahle et al, 1995; Fahle & Henke-Fahle, 1996; Mukai et al, 2007; Schmitt, Kromeier, Bach, & Kommerell, 2002). Attention has been implicated in both psychophysical and electrophysiological studies as playing a key role in explaining this variability (Ahissar & Hochstein, 1993; Crist, Li, & Gilbert, 2001; Fahle, 2004; Li, Piech, & Gilbert, 2004; Shiu & Pashler, 1992).…”

Section: Introductionmentioning

confidence: 99%

Exogenous and endogenous attention during perceptual learning differentially affect post-training target thresholds

et al. 2011

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There is conflicting evidence in the literature regarding the role played by attention in perceptual learning. To further examine this issue, we independently manipulated exogenous and endogenous attention and measured the rate of perceptual learning of oriented Gabor patches presented in different quadrants of the visual field. In this way, we could track learning at attended, divided-attended, and unattended locations. We also measured contrast thresholds of the Gabor patches before and after training. Our results showed that, for both exogenous and endogenous attention, accuracy in performing the orientation discrimination improved to a greater extent at attended than at unattended locations. Importantly, however, only exogenous attention resulted in improved contrast thresholds. These findings suggest that both exogenous and endogenous attention facilitate perceptual learning, but that these two types of attention may be mediated by different neural mechanisms.

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Interindividual variability of learning in stereoacuity

Cited by 18 publications

References 25 publications

Individual variability in functional connectivity predicts performance of a perceptual task

Individual variability in functional connectivity predicts performance of a perceptual task

Transfer of perceptual learning of depth discrimination between local and global stereograms

Exogenous and endogenous attention during perceptual learning differentially affect post-training target thresholds

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