Paper on a New Framework (V1SH-Bottleneck-CPD framework) to understand vision from the perspective of the primary visual cortex

Zhaoping, L. (2019) A new framework for understanding vision from the perspective of the primary visual cortex , Current Opinion in Neurobiology, volume 58, pages 1-10.

Physiological/Neural data confirming, or consistent with, the prediction that top-down feedback mainly target central visual field in ventral stream

Morales-Gregorio et al 2024 Neural manifolds in V1 change with top-down signals from V4 targeting the foveal region , Cell reports, 2024

Sims et al 2021 Frontal cortical regions associated with attention connect more strongly to central than peripheral V1 , NeuroImage, 2021.

Behavioral data demonstrating, supporting, or confirming predictions of, the Dichotomy between central and peripheral vision

Zhaoping, L. (2025) Testing the top-down feedback in the central visual field using the reversed depth illusion iScience, Volume 28, Issue 4, 112223

Zhaoping, L. (2024) Looking with or without seeing in an individual with age-related macular degeneration impairing central vision i-Perception, 15(4), 1-5, https://doi.org/10.1177/20416695241265821

Zhaoping, L. (2024) Peripheral vision is mainly for looking rather than seeing Neuroscience Research https://doi.org/10.1016/j.neures.2023.11.006

Zhaoping, L. (2023) Peripheral and central sensation: Multisensory orienting and recognition across species Trends for Cognitive Sciences, Vol 27, issue 6, page 539-552.

Zhaoping, L. (2021) Seeing reversed depth in contrast-reversed random-dot stereograms in central vision 43rd European Conference on Visual Perception (ECVP 2021)

Zhaoping, L. (2021) Contrast-reversed binocular dot-pairs in random-dot stereograms for depth perception in central visual field: Probing the dynamics of feedforward-feedback processes in visual inference, Vision Research, vol. 186, pages 124-139.

Zhaoping, L. (2020) The flip tilt illusion: visible in peripheral vision as predicted by the Central-Peripheral Dichotomy (CPD). i-Perception, 11(4), 1--5. https://doi.org/10.1177/2041669520938408

Zhaoping L. and Ackermann J. (2018) Reversed Depth in Anticorrelated Random-Dot Stereograms and the Central-Peripheral Difference in Visual Inference Perception, 47(5) 531-539, https://doi.org/10.1177/0301006618758571

Zhaoping L. (2017) Feedback from higher to lower visual areas for visual recognition may be weaker in the periphery: glimpses from the perception of brief dichoptic stimuli. Vision Research, 136: 32--49.

Nuthmann A. (2014) How do the regions of the visual field contribute to object search in real-world scenes? Evidence from eye movements. Journal of Experimental Psychology: Human Perception and Performance, 40(1), 342-360. This paper shows dissociation between looking by peripheral vision and seeing by central vision, supporting the central-peripheral dichotomy.

a quick glimpse from this 2024 video on the V1SH-Bottleneck-CPD framework

this 9 minute video

Lectures and Presentations

"Recurrence through bottleneck: theory-driven experiments on the central-peripheral dichotomy", presentation in Redwood Institute, UC Berkeley, May 2024

"Looking and seeing in human vision in light of a severe attentional processing bottleneck in the brain", presentation in Redwood Institute, UC Berkeley, July 2023

keynote speech at CNS*2020: A new computational framework for understanding vision in our brain

keynote speech at CNS*2020: A new computational framework for understanding vision in our brain

From V1SH to CPD: feedforward, feedback, and the attentional bottleneck in vision". a seminar talk in June 2021 at Neurospin

seminar at UCSD, Oct. 2020 " "From V1SH to CPD in a new framework for understanding vision"

The central-peripheral dichotomy in visual decoding A lecture for a summer school 2019.

A 2021 video is this talk in June 2021

A Lecture at KITP in UCSB, Sep. 2018

You may also see Zhaoping, L. (2014) Understanding Vision: theory, models, and data , published by Oxford Unviersity Press, 2014

Click here to go back to Li Zhaoping's webpage