Structure-from-motion: dissociating perception, neural persistence, and sensory memory of illusory depth and illusory rotation

Abstract

In the structure-from-motion paradigm, physical motion on a screen produces the vivid illusion of an object rotating in depth. Here, we show how to dissociate illusory depth and illusory rotation in a structure-from-motion stimulus using a rotationally asymmetric shape and reversals of physical motion. Reversals of physical motion create a conflict between the original illusory states and the new physical motion: Either illusory depth remains constant and illusory rotation reverses, or illusory rotation stays the same and illusory depth reverses. When physical motion reverses after the interruption in presentation, we find that illusory rotation tends to remain constant for long blank durations (T blank ≥ 0.5 s), but illusory depth is stabilized if interruptions are short (T blank ≤ 0.1 s). The stability of illusory depth over brief interruptions is consistent with the effect of neural persistence. When this is curtailed using a mask, stability of ambiguous vision (for either illusory depth or illusory rotation) is disrupted. We also examined the selectivity of the neural persistence of illusory depth. We found that it relies on a static representation of an interpolated illusory object, since changes to low-level display properties had little detrimental effect. We discuss our findings with respect to other types of history dependence in multistable displays (sensory stabilization memory, neural fatigue, etc.). Our results suggest that when brief interruptions are used during the presentation of multistable displays, switches in perception are likely to rely on the same neural mechanisms as spontaneous switches, rather than switches due to the initial percept choice at the stimulus onset.

Sensory memory of structure-from-motion is shape-specific

“…In ambiguous displays, object shape is comparatively persistent in that reversals of apparent shape are prohibited even when prompted by stimulus transients (Pastukhov & Braun, 2013;Pastukhov, Vonau, & Braun, 2012). By comparison, object rotation is far more "flexible" in that reversals of apparent rotation are readily prompted by stimulus transients Stonkute, Braun, & Pastukhov, 2012).…”

Transformation priming helps to disambiguate sudden changes of sensory inputs

“…Whereas in the present experiments priming lasted for seconds, other effects induced by recent experience, which may be linked to perception of transformations, retain their influence over far longer time-scales (Klink, Brascamp, Blake, & van Wezel, 2010;Pastukhov & Braun, 2013a;Suzuki & Grabowecky, 2007). Moreover, priming of perceptual states exhibits both facilitatory (Leopold et al, 2002;Orbach, Ehrlich, & Heath, 1963;Pastukhov & Braun, 2013b;Pastukhov, Füllekrug, et al, 2013;Pastukhov, Lissner, Füllekrug, et al, 2014) and inhibitory effects (Pastukhov & Braun, 2011, 2013b operating concurrently on different time-scales. Similarly diverging effects may also exist for priming of transformations.…”

“…For example, perceptual adaptation is thought to prioritize perceptual sensitivity (Kohn, 2007;Pastukhov, García-Rodríguez, et al, 2013;Theodoni, Kovács, Greenlee, & Deco, 2011;Webster, 2011). Conversely, neural persistence (Coltheart, 1980;Loftus & Irwin, 1998;Pastukhov & Braun, 2013b) and a rolling average over a longer period of perceptual history are thought to be used to minimize influence of neural noise and ensure perceptual constancy Cicchini et al, 2014;Fischer & Whitney, 2014). Finally, several mechanisms work as predictive memories trying to optimize target selection and processing (Chopin & Mamassian, 2012;Grill-Spector, Henson, & Martin, 2006;Kristjánsson & Campana, 2010;Maljkovic & Nakayama, 1994, 2000Schacter, Dobbins, & Schnyer, 2004).…”

“…In turn, observer's reports on her/his perception, allow experimenter to infer corresponding changes to these hidden internal variables. This approach is particularly fruitful when studying changes of internal variables over time (Leopold, Wilke, Maier, & Logothetis, 2002;Nawrot & Blake, 1991;Pastukhov & Braun, 2008, 2013a, 2013bPastukhov, Lissner, Füllekrug, & Braun, 2014).…”

“…It is the ubiquity of these events that raises the question of how the visual system resolves their dynamic ambiguity. The general answer to the problem is to gather and exploit prior knowledge (Friston, Breakspear, & Deco, 2012;Gregory, 2009;Metzger, 2009;Yuille & Kersten, 2006), and this process has been well studied from both behavioral (Kristjánsson http & Campana, 2010;Pastukhov & Braun, 2011, 2013b and theoretical (Friston et al, 2012;Pastukhov, García-Rodríguez, et al, 2013) perspectives, even though the neural implementations are still poorly understood (Daw, O'Doherty, Dayan, Seymour, & Dolan, 2006). The main focus of prior research was the knowledge about physical states (Hansen, Olkkonen, Walter, & Gegenfurtner, 2006;Weiss, Simoncelli, & Adelson, 2002;Yang & Purves, 2003;Yuille & Kersten, 2006), however this type of knowledge serves only as a weak constraint because the number of transformations by far outstrips the number of states.…”