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From V1SH to CPD: feedforward, feedback, and the attentional bottleneck in vision

From 6/28/2021 to 6/28/2021

Li ZHAOPING (Tübingen MPI, Germany) will give a talk on Zoom on June 28th.

(1) Zhaoping, L. (2019) A new framework for understanding vision from the perspective of the primary visual cortex Current Opinion in Neurobiology, volume 58, page 1-10.
(2)  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.
(3)  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.

Short abstract:

V1SH is the V1 Saliency Hypothesis, and CPD is the Central-Peripheral Dichotomy.
I will explain how they motivate a new framework: Visual attention selects only a tiny fraction of visual input information for further processing.  Selection starts in the primary visual cortex (V1),  which creates a bottom-up saliency map (V1SH) to guide the fovea to selected visual locations via gaze shifts.
This motivates a new framework that  views vision as consisting of encoding, selection, and decoding stages, placing selection on center stage.  It suggests a massive loss of non-selected information from V1 downstream along the visual pathway.  Hence, feedback from downstream visual cortical areas to V1 for better decoding (recognition), through analysis-by- synthesis, should query for additional information  and be mainly directed at the foveal region (CPD).  Accordingly, non-foveal vision is not only poorer in spatial resolution, but also more susceptible to many illusions.  I will show  some illusions arising from V1's feedforward inputs limited by the attentional bottleneck, and use random-dot stereograms to illustrate how top-down feedback constructively utilizes the feedforward inputs in some visual inferences and vetoes feedforward inputs in other cases, depending on the nature of the feedforward inputs

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