Going with the Flow: The Neural Mechanisms Underlying Illusions of Complex-Flow Motion

Abstract

Studying the mismatch between perception and reality helps us better understand the constructive nature of the visual brain. The Pinna-Brelstaff motion illusion is a compelling example illustrating how a complex moving pattern can generate an illusory motion perception. When an observer moves toward (expansion) or away (contraction) from the Pinna-Brelstaff figure, the figure appears to rotate. The neural mechanisms underlying the illusory complex-flow motion of rotation, expansion, and contraction remain unknown. We studied this question at both perceptual and neuronal levels in behaving male macaques by using carefully parametrized Pinna-Brelstaff figures that induce the above motion illusions. We first demonstrate that macaques perceive illusory motion in a manner similar to that of human observers. Neurophysiological recordings were subsequently performed in the middle temporal area (MT) and the dorsal portion of the medial superior temporal area (MSTd). We find that subgroups of MSTd neurons encoding a particular global pattern of real complex-flow motion (rotation, expansion, contraction) also represent illusory motion patterns of the same class. They require an extra 15 ms to reliably discriminate the illusion. In contrast, MT neurons encode both real and illusory local motions with similar temporal delays. These findings reveal that illusory complex-flow motion is first represented in MSTd by the same neurons that normally encode real complex-flow motion. However, the extraction of global illusory motion in MSTd from other classes of real complex-flow motion requires extra processing time. Our study illustrates a cascaded integration mechanism from MT to MSTd underlying the transformation from external physical to internal nonveridical flow-motion perception.

Optic flow parsing in the macaque monkey

“…Neurons in MT are strongly selective for motion direction ( Albright, 1989 ; Albright et al, 1984 ; DeAngelis & Uka, 2003 ; Desimone & Ungerleider, 1986 ; Maunsell & Van Essen, 1983 ; Van Essen et al, 1981 ; Zeki, 1974 ) and speed ( DeAngelis & Newsome, 1999 ; Liu & Newsome, 2003 ; Maunsell & Van Essen, 1983 ). MT activity reflects perceived motion direction ( Britten, Newsome, Shadlen, Celebrini, & Movshon, 1996 ; Purushothaman & Bradley, 2005 ), even when the perceived motion does not correspond with retinal image motion ( Krekelberg, Dannenberg, Hoffmann, Bremmer, & Ross, 2003 ; Luo et al, 2019 ; Rodman & Albright, 1989 ; Stoner & Albright, 1992 ). If MT represents the result of flow parsing, the observed biases in perceived object direction should correspond to a shift in MT's population response profile, when plotted as a function of direction preferences.…”

Primate extrastriate cortical area MST: a gateway between sensation and cognition

“…The relation between RF eccentricity and RF size in the MST is weaker (24,31,34,38,51,52) than that found in the neurons of lower areas [see, e.g., Fig. 1 of Freeman and Simoncelli (53)].…”

The Serpentine Illusion: A Visual Motion Illusion Induced by Phase-Shifted Line Gratings

“…It is also worth noting that for both-motions optimized stimuli, there was no "additive" effect for combining diagonal and lateral illusory motion together. We do not wish to suggest that we can infer directly from single unit responses to global illusory perception, but previous work has shown that biases present in neurons in early visual areas can be combined downstream in MT and MST to form global perceptions of illusory motion (Luo et al, 2019).…”

“…We used control stimuli whose illusory contours are orthogonal to the line patterns ( Supplementary Figure 5 top row), where only the physical direction of line pattern motion should be observed in the direction tuning curve of modeled neurons. For stimuli that contain a single tilt (Supplementary Figure 5 middle row), if the energy model is consistent with illusory perception, we predict that the tuning curves will shift clockwise or anti-clockwise depending on the combination of tilt and physical motion direction (for details of how predictions are made please refer to Luo et al, 2019). For the zigzag patterns ( Supplementary Figure 5 bottom row), both clockwise and anti-clockwise relative illusory motions are present and should therefore cause an increase in bandwidth without an overall shift in preferred direction.…”

“…The motion energy model is a simplified linear summation model (Baker and Issa, 2005;Mante and Carandini, 2005), best at predicting response properties in the earliest motion processing stages (Reid et al, 1987;Carandini et al, 1997). Complex cells in primary visual cortex and neurons in downstream visual areas like MT and MST have more nonlinear response properties (Emerson et al, 1992;Simoncelli and Heeger, 1998;Pack et al, 2006), and they contribute significantly to the neural representation and perception of illusory motions (Luo et al, 2019). Future studies should explore compare both linear and non-linear coding components and hierarchical population responses (mirroring the hierarchical spatiotemporal integration of motion information), as these may better predict the cortical responses to Serpentine and other illusory motion patterns.…”