Serial dependence in visual perception

Abstract

Visual input often arrives in a noisy and discontinuous stream, owing to head and eye movements, occlusion, lighting changes, and many other factors. Yet the physical world is generally stable—objects and physical characteristics rarely change spontaneously. How then does the human visual system capitalize on continuity in the physical environment over time? Here we show that visual perception is serially dependent, using both prior and present input to inform perception at the present moment. Using an orientation judgment task, we found that even when visual input changes randomly over time, perceived orientation is strongly and systematically biased toward recently seen stimuli. Further, the strength of this bias is modulated by attention and tuned to the spatial and temporal proximity of successive stimuli. These results reveal a serial dependence in perception characterized by a spatiotemporally tuned, orientation-selective operator—which we call a continuity field—that may promote visual stability over time.

Divided spatial attention and feature-mixing errors

“…Similar attractive shifts have also been reported for items held serially (Fischer & Whitney, 2014;Huang & Sekuler, 2010) or simultaneously in visual working memory (Brady & Alvarez, 2011). For example, Brady and Alvarez had subjects remember the sizes of a set of circles; when subjects were asked to report the size of a single circle, their reports were biased toward the mean size of the set.…”

Serial Dependence in the Perception of Faces

“…The mechanism by which the visual system accomplishes this object continuity remains elusive. Recent results have demonstrated that the perception of low-level stimulus features such as orientation and numerosity is systematically biased (i.e., pulled) toward visual input from the recent past [1, 2]. The spatial region over which current orientations are pulled by previous orientations is known as the continuity field, which is temporally tuned for the past 10–15 s [1].…”

Transformation priming helps to disambiguate sudden changes of sensory inputs

“…5B-D), priming for match pairs t(8) = 7, p = 0.0001; for mismatch pairs t(8) = 7.3, p < 0.0001; the difference in priming strength was not significant t(8) = 1.9, p = 0.09. Therefore, we conclude that although priming of perceptual states can stabilize perception Cicchini et al, 2014;Fischer & Whitney, 2014), prior knowledge about physical transformations is gathered in addition to and independent of it.…”

“…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).…”

“…Specifically, we wanted to confirm that prior knowledge about physical transformations is gathered in addition to and independent of the similar information on physical states Cicchini, Anobile, & Burr, 2014;Fischer & Whitney, 2014).…”