ReviewAnnual review of vision science2018
Linking V1 Activity to Behavior.
Review in Annual review of vision science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
15 citing papers in PubMed.
- Fluctuating internal states mediate neural-behavioral covariations in V1.Nature neuroscience · 2026Article
- Discretized representations in V1 predict suboptimal orientation discrimination.Nature communications · 2025Article
- Body-Related Visual Biasing Affects Accuracy of Reaching.Brain sciences · 2024Article
- Disparate nonlinear neural dynamics measured with different techniques in macaque and human V1.Scientific reports · 2024Article
- How does V1 population activity inform perceptual certainty?Journal of vision · 2024Article
- Article
- Mesoscopic calcium imaging in a head-unrestrained male non-human primate using a lensless microscope.Nature communications · 2024Article
- NEURAL CORRELATES OF PERCEPTUAL SIMILARITY MASKING IN PRIMATE V1.bioRxiv : the preprint server for biology · 2023Article
- Distributed context-dependent choice information in mouse posterior cortex.Nature communications · 2023Article
- Suppression of top-down influence decreases both behavioral and V1 neuronal response sensitivity to stimulus orientations in cats.Frontiers in behavioral neuroscience · 2023Article
- Perceptual enhancement and suppression correlate with V1 neural activity during active sensing.Current biology : CB · 2022Article
- Effects of top-down influence suppression on behavioral and V1 neuronal contrast sensitivity functions in cats.iScience · 2022Article
- Decision Signals in the Local Field Potentials of Early and Mid-Level Macaque Visual Cortex.Cerebral cortex (New York, N.Y. : 1991) · 2021Article
- Predicting Perceptual Decisions Using Visual Cortical Population Responses and Choice History.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2019Article
- Decision-variable correlation.Journal of vision · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
A long-term goal of visual neuroscience is to develop and test quantitative models that account for the moment-by-moment relationship between neural responses in early visual cortex and human performance in natural visual tasks. This review focuses on efforts to address this goal by measuring and perturbing the activity of primary visual cortex (V1) neurons while nonhuman primates perform demanding, well-controlled visual tasks. We start by describing a conceptual approach-the decoder linking model (DLM) framework-in which candidate decoding models take neural responses as input and generate predicted behavior as output. The ultimate goal in this framework is to find the actual decoder-the model that best predicts behavior from neural responses. We discuss key relevant properties of primate V1 and review current literature from the DLM perspective. We conclude by discussing major technological and theoretical advances that are likely to accelerate our understanding of the link between V1 activity and behavior.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.