（add new sections reversed phi illusion/ phi phenomenon and beta phenomenon/ Hassenstein-Reichardt detector model)
Reverse Phi Illusion edit
As apparent phi movement is perceived by human’s visual system with two stationary and similar optical stimuli presented next to each other exposing successively with high frequency, there is also a reversed version of this motion, which is reversed phi illusion[1]. Reverse phi illusion is the kind of phi phenomenon that fades or dissolves from its positive direction to the displaced negative, so that the apparent motion human perceive is opposite to the actual physical displacement. Reverse phi illusion is often followed by black and white patterns.
It is believed that reverse phi illusion is indeed brightness effects, that it occurs when brightness-reversing picture moving across our retina[1][2]. It can be explained by mechanisms of visual receptive field model, where visual stimuli are summated spatially (a process that is reverse to spatial differentiation). This spacial summation blurs the contour to a small extent, and thus changes the brightness perceived. Four predictions are confirmed from this receptive field model. First, foveal reverse-phi should be broken down when the displacement is greater than the width of foveal receptive fields. Second, reverse phi illusion exists in the peripheral retina for greater displacements than in the fovea, for receptive fields are greater in the peripheral retina. Third, the spacial summation by the receptive fields could be increased by the visual blurring of the reversed phi illusion projected on a screen with defocus lens. Fourth, the amount of reversed phi illusion should be increasing with the decrease of displacement between positive and negative pictures.
Indeed, our visual system processes forward and reversed phi phenomenon in the same way. Our visual system perceives phi phenomenon between individual points of corresponding brightness in successive frames, and phi movement is determined on a local, point-for-point basis mediated by brightness instead of on a global basis.[2]
Neural Mechanism underlying sensitivity to reversed phi phenomenon[3] edit
- T4 and T5 motion detectors cells are necessary and sufficient for reversed phi behavior, and there is no other pathways to produce turning responses for reversed phi motion
- Tangential cells show partial voltage response with the stimulation of reversed phi motion
- Hassenstein-Reichardt detector model
- There is substantial responses for reversed-phi in T4 dendrites, and marginal responses in T5 dendrites
Phi Phenomenon and Beta Movement edit
Phi phenomenon has long been confused with beta movement; however, the founder of Gestalt School of Psychology, Max Wertheimer, has distinguished the difference between them in 1912. Phi phenomenon and Beta movement are quite distinct indeed.
Firstly, the difference is on neuroanatomical level. Visual information is processed in two pathways, one processes position and motion, and the other one processes form and color. If an object is moving or changing position, it would be likely to stimulate both pathways and result in a percept of beta movement. Whereas if the object changes position too rapidly, it might result in a percept of pure movement such as phi phenomenon.
Secondly, phi phenomenon and beta movement are also different perceptually. For phi phenomenon, two stimuli A and B are presented successively, what you perceive is some motion passing over A and B; while for beta movement, still with two stimuli A and B presented in succession, what you perceive would be an object actually passing from position A to position B.
The difference also lies on cognitive level, about how our visual system interprets movement, which is based on the assumption that visual system solves an inverse problem of perceptual interpretation. For neighboring stimuli produced by an object, the visual system has to infer the object since the neighboring stimuli do not give the complete picture of the reality. There are more than one way for our visual system to interpret. Therefore, our visual system needs to put constraints to multiple interpretations in order to acquire the unique and authentic one. Principles employed by our visual system to set the constraints are often relevant to simplicity and likelihood. [4]
Hassenstein-Reichardt Detector Model edit
Hassenstein-Reichardt detector model is considered to be the first mathematical model to propose that our visual system estimates motion by detecting a temporal cross-correlation of light intensities from two neighboring points, in short a theoretical neural circuit for how our visual system track motion. This model can explain and predict phi phenomenon and its reversed version.[3] [5]This model consists two locations and two visual inputs, that if one input at one location is detected, the signal would be sent to the other location. Two visual inputs would be asymmetrically filtered in time, then the visual contrast at one location is multiplied with the time-delayed contrast from the other location. Finally, the multiplication result would be subtracted to obtain an output.
Therefore, two positive or two negative signals would generate a positive output; but if the inputs are one positive and one negative, the output would be negative. This corresponds to the multiplication rule mathematically.
For phi phenomenon, motion detector would develop to detect a change in light intensities at one point on the retina, then our visual system would compute a correlation of that change with a change in light intensities of a neighboring point on the retina, with a short delay.[6]
Reichardt Model edit
The Reichardt Model[5] is a more complex form of the simplest Hassenstein-Reichardt detector model, which is considered to be a pairwise model with a common quadratic nonlinearity. As Fourier method is considered to be linear method, Reichardt Model introduces multiplicative nonlinearity when our visual responses to luminance changes at different element locations are combined[7]. In this model, one photoreceptor input would be delayed by a filter to be compared by the multiplication with the other input from a neighboring location. The input would be filtered two times in a mirror-symmetrical manner, one before the multiplication and one after the multiplication, which gives a second-order motion estimation. [5][8]This generalized Reichardt model allows arbitrary filters before the multiplicative nonlinearity as well as filters post-nonlinearity. [5] Phi Phenomenon is often regarded as first-order motion, but reversed phi could be both first-order and second-order, according to this model. [9]
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- ^ a b Anstis, Stuart M.; Rogers, Brian J. (1975-08-01). "Illusory reversal of visual depth and movement during changes of contrast". Vision Research. 15 (8): 957–IN6. doi:10.1016/0042-6989(75)90236-9. ISSN 0042-6989.
- ^ a b Anstis, S. M. (1970-12-01). "Phi movement as a subtraction process". Vision Research. 10 (12): 1411–IN5. doi:10.1016/0042-6989(70)90092-1. ISSN 0042-6989.
- ^ a b Leonhardt, Aljoscha; Meier, Matthias; Serbe, Etienne; Eichner, Hubert; Borst, Alexander (2017). "Neural mechanisms underlying sensitivity to reverse-phi motion in the fly". PloS One. 12 (12): e0189019. doi:10.1371/journal.pone.0189019. ISSN 1932-6203. PMC 5737883. PMID 29261684.
{{cite journal}}: CS1 maint: unflagged free DOI (link) - ^ Steinman, Robert M.; Pizlo, Zygmunt; Pizlo, Filip J. (2000-08-01). "Phi is not beta, and why Wertheimer's discovery launched the Gestalt revolution". Vision Research. 40 (17): 2257–2264. doi:10.1016/S0042-6989(00)00086-9. ISSN 0042-6989.
- ^ a b c d Fitzgerald, James E.; Katsov, Alexander Y.; Clandinin, Thomas R.; Schnitzer, Mark J. (2011-08-02). "Symmetries in stimulus statistics shape the form of visual motion estimators". Proceedings of the National Academy of Sciences. 108 (31): 12909–12914. doi:10.1073/pnas.1015680108. ISSN 0027-8424. PMID 21768376.
- ^ Werner, Reichardt. Autocorrelation, a Principle for the Evaluation of Sensory Information by the Central Nervous System. The MIT Press. doi:10.7551/mitpress/9780262518420.001.0001/upso-9780262518420-chapter-17. ISBN 978-0-262-31421-3.
- ^ Gilroy, Lee A.; Hock, Howard S. (2004-08-01). "Multiplicative nonlinearity in the perception of apparent motion". Vision Research. 44 (17): 2001–2007. doi:10.1016/j.visres.2004.03.028. ISSN 0042-6989.
- ^ Borst, Alexander (2000-11). "Models of motion detection". Nature Neuroscience. 3 (11): 1168–1168. doi:10.1038/81435. ISSN 1546-1726.
{{cite journal}}: Check date values in:|date=(help) - ^ Wehrhahn, Christian (2006-08-01). "Reversed phi revisited". Journal of Vision. 6 (10): 2–2. doi:10.1167/6.10.2. ISSN 1534-7362.