Dataset Information

Dissociable prior influences of signal probability and relevance on visual contrast sensitivity.

ABSTRACT: According to signal detection theoretical analyses, visual signals occurring at a cued location are detected more accurately, whereas frequently occurring ones are reported more often but are not better distinguished from noise. However, conventional analyses that estimate sensitivity and bias by comparing true- and false-positive rates offer limited insights into the mechanisms responsible for these effects. Here, we reassessed the prior influences of signal probability and relevance on visual contrast detection using a reverse-correlation technique that quantifies how signal-like fluctuations in noise predict trial-to-trial variability in choice discarded by conventional analyses. This approach allowed us to estimate separately the sensitivity of true and false positives to parametric changes in signal energy. We found that signal probability and relevance both increased energy sensitivity, but in dissociable ways. Cues predicting the relevant location increased primarily the sensitivity of true positives by suppressing internal noise during signal processing, whereas cues predicting greater signal probability increased both the frequency and the sensitivity of false positives by biasing the baseline activity of signal-selective units. We interpret these findings in light of "predictive-coding" models of perception, which propose separable top-down influences of expectation (probability driven) and attention (relevance driven) on bottom-up sensory processing.

SUBMITTER: Wyart V

PROVIDER: S-EPMC3295248 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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Dissociable prior influences of signal probability and relevance on visual contrast sensitivity.

Wyart Valentin V Nobre Anna Christina AC Summerfield Christopher C

Proceedings of the National Academy of Sciences of the United States of America 20120213 9

According to signal detection theoretical analyses, visual signals occurring at a cued location are detected more accurately, whereas frequently occurring ones are reported more often but are not better distinguished from noise. However, conventional analyses that estimate sensitivity and bias by comparing true- and false-positive rates offer limited insights into the mechanisms responsible for these effects. Here, we reassessed the prior influences of signal probability and relevance on visual ...[more]

PMID: 22331901

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Project description:Current clinical evaluation, which focuses on central vision, could be improved through characterization of residual vision with peripheral testing of visual acuity, contrast sensitivity, color vision, crowding, and reading speed. Assessing visual functions in addition to light sensitivity, a comprehensive visual field map (VFM) would be valuable for detecting and managing eye diseases. In a previous study, we developed a Bayesian adaptive qVFM method that combines a global module for preliminary assessment of the VFM's shape and a local module for assessment at individual retinal locations. The method was validated in measuring the light sensitivity VFM. In this study, we extended the qVFM method to measure contrast sensitivity across the visual field. In both simulations and psychophysics, we sampled 64 visual field locations (48 x 48 deg) and compared the qVFM method with a procedure that tested each retinal location independently (qFC; Lesmes et al., 2015). In each trial, subjects were required to identify a single optotype (size: 2.5 x 2.5 deg), one of 10 filtered Sloan letters. To compare the accuracy and precision of the two methods, three simulated eyes were tested in 1,280 trials with each method. In addition, data were collected from 10 eyes (5 OS, 5 OD) of five normal observers. For simulations, the average RMSE of the estimated contrast sensitivity with the qVFM and qFC methods were 0.057 and 0.100 after 320 trials, and 0.037 and 0.041 after 1,280 trials [all in log10 units, represent as log(sensitivity)], respectively. The average SD of the qVFM and qFC estimates were 0.054 and 0.096 after 320 trials, and 0.032 and 0.041 after 1,280 trials, respectively. The within-run variability (68.2% HWCIs) were comparable to the cross-run variability (SD). In the psychophysics experiment, the average HWCI of the estimated contrast sensitivity from the qVFM and qFC methods across the visual field decreased from 0.33 on the first trial to 0.072 and 0.16 after 160, and to 0.060 and 0.10 after 320 trials. The RMSE between the qVFM and qFC estimates started at 0.26, decreased to 0.12 after 160 and to 0.11 after 320 qVFM trials. The qVFM provides an accurate, precise, and efficient mapping of contrast sensitivity across the entire visual field. The method might find potential clinical applications in monitoring vision loss, evaluating therapeutic interventions, and developing effective rehabilitation for visual diseases.

Dataset Information

Dissociable prior influences of signal probability and relevance on visual contrast sensitivity.

Publications

Dissociable prior influences of signal probability and relevance on visual contrast sensitivity.

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