Generative Phenomenology of form perception: Perceptograms and cortical models for amblyopic phantom percepts

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Abstract

We introduce Generative Phenomenology: making viewable images of people’s perceptions (Perceptograms) and generating the images from neural models, as a powerful technique for understanding the neural bases of perception. Amblyopia, a disorder of spatial vision, provides a perfect case because signals from the two eyes go through partly different cortical neurons, and many amblyopes report phantom forms when viewing sinusoidal gratings through their amblyopic eye (AE) but not through the fellow eye (FE). Using a dichoptic display, we acquired high-fidelity perceptograms for 24 gratings shown to AE while sums-of-gratings plaids were shown to FE with contrast, frequency, phase, and orientation of the plaid gratings adjusted to match the two percepts exactly. Plaids provided exact matches to 92.6% of distortions. A formal equation that the signals generated in visual cortex by the test gratings seen through AE match the signals generated by their matched perceptograms seen through FE for each observer, was used to analytically derive cortical filters processing AE signals as linear transforms of standard steerable filters modeling normal V1 neurons for FE. Passing gratings through AE filters accurately generated the measured perceptograms. The filter transformations reflected complex changes in V1 receptive fields and possibly in cross-correlations. The AE filters also explained amblyopic deficits in perceiving sinusoidally modulated circular contours and were consistent with orientation perceptive fields estimated from reverse-correlation experiments. Changes in neuronal receptive fields thus have profound effects on perception, to the extent that observers can see more features than are present in the viewed stimulus.

SIGNIFICANCE STATEMENT

What we see is generated by our cortical neurons processing sensory input. With their amblyopic eye, whose signals are processed by deficiently developed cortical cells, many amblyopes see phantom forms that contain more features than the viewed stimulus, providing a perfect case for studying the neural generation of percepts (Generative Phenomenolog)y). We acquired computer aided perceptograms (viewable records of perceived images) of the phantom forms and then derived a cortical model that accurately generated the perceptograms by using linear transforms of normal V1 receptive fields. The modifications also explained amblyopic deficits at discerning departures from circularity and were validated with reverse-correlation experiments. These results show that small changes in cortical neuronal properties can cause major differences in what people perceive.

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