Attentional Enhancement via Selection and Pooling of Early Sensory Responses in Human Visual Cortex
Open accessAbstract
The computational processes by which attention improves behavioral performance were characterized by measuring visual cortical activity with functional magnetic resonance imaging as humans performed a contrast-discrimination task with focal and distributed attention. Focal attention yielded robust improvements in behavioral performance accompanied by increases in cortical responses. Quantitative analysis revealed that if performance were limited only by the sensitivity of the measured sensory signals, the improvements in behavioral performance would have corresponded to an unrealistically large reduction in response variability. Instead, behavioral performance was well characterized by a pooling and selection process for which the largest sensory responses, those most strongly modulated by attention, dominated the perceptual decision. This characterization predicts that high-contrast distracters that evoke large responses should negatively impact behavioral performance. We tested and confirmed this prediction. We conclude that attention enhanced behavioral performance predominantly by enabling efficient selection of the behaviorally relevant sensory signals.
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In detection and coarse discrimination tasks, Lau, Rahnev, and colleagues report that subjects overestimate their confidence in the periphery and for unattended stimuli.
“In detection and coarse discrimination tasks, Lau, Rahnev, and colleagues report that subjects overestimate their confidence in the periphery and for unattended stimuli.”
From Comparing Bayesian and non-Bayesian accounts of human confidence reports (2018) · cites this paper as [61]
The Results section on psychophysical contrast-discrimination functions reports lower thresholds with focal than distributed cues, but does not report confidence judgments. Searches for Lau, Rahnev, peripheral confidence, and confidence overestimation found no passage addressing the attributed finding. Page numbers were not available in our copy. (LLM, conf=0.77)
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Comparing Bayesian and non-Bayesian accounts of human confidence reports
Adler, W. T., & Ma, W. J. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006572 · Cited by 118 · see citing works
- Authors
- Pestilli, F., Carrasco, M., Heeger, D. J., & Gardner, J. L.
- Affiliations
- RIKEN Center for Brain Science (JP)
- New York University (US)
- Corresponding author
- Pestilli, Franco
- Gardner, Justin L.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2011-12
- Volume
- 72
- Issue
- 5
- Pages
- 832-846
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC3264681
- OpenAlex
- W1967985907
- Cited by
- 190
- References
- 5
- Citations by year
- 2026: 4 · 2025: 12 · 2024: 8 · 2023: 9 · 2022: 12 · 2021: 14 · 2020: 12 · 2019: 13 · 2018: 12 · 2017: 13 · 2016: 15 · 2015: 16 · 2014: 18 · 2013: 12 · 2012: 17
- FWCI
- 7.80
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 594 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Israel National Road Safety Authority
- National Institutes of Health (R01-EY016200, R01-EY019693, R01-MH069880)
- RIKEN Brain Science Institute
- National Institute of Mental Health (T32-EY1393309, T32-MH05174)
- National Eye Institute (F32-EY016260)
- Italian Academy for Advanced Studies in America, Columbia University
- Burroughs Wellcome Fund
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- visual attention, focal attention, distributed attention, contrast discrimination, early visual cortex, response variability, perceptual decision making, distractors, behavioral performance
- MeSH terms
- Adult, Attention, Brain Mapping, Choice Behavior, Cues, Discrimination, Psychological, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Neuropsychological Tests, Oxygen, Photic Stimulation, Psychophysics, Reaction Time, Visual Cortex, Models, Statistical, Contrast Sensitivity
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