Temporal Windows in Visual Processing: “Prestimulus Brain State” and “Poststimulus Phase Reset” Segregate Visual Transients on Different Temporal Scales

Abstract

Dynamic vision requires both stability of the current perceptual representation and sensitivity to the accumulation of sensory evidence over time. Here we study the electrophysiological signatures of this intricate balance between temporal segregation and integration in vision. Within a forward masking paradigm with short and long stimulus onset asynchronies (SOA), we manipulated the temporal overlap of the visual persistence of two successive transients. Human observers enumerated the items presented in the second target display as a measure of the informational capacity read-out from this partly temporally integrated visual percept. We observed higher ␤-power immediately before mask display onset in incorrect trials, in which enumeration failed due to stronger integration of mask and target visual information. This effect was timescale specific, distinguishing between segregation and integration of visual transients that were distant in time (long SOA). Conversely, for short SOA trials, mask onset evoked a stronger visual response when mask and targets were correctly segregated in time. Examination of the target-related response profile revealed the importance of an evoked ␣-phase reset for the segregation of those rapid visual transients. Investigating this precise mapping of the temporal relationships of visual signals onto electrophysiological responses highlights how the stream of visual information is carved up into discrete temporal windows that mediate between segregated and integrated percepts. Fragmenting the stream of visual information provides a means to stabilize perceptual events within one instant in time.

The edge of awareness: Mask spatial density, but not color, determines optimal temporal frequency for continuous flash suppression

“…This frequency range has been implicated in detection of nearthreshold stimuli (particularly oscillations in the alpha range: Busch, Dubois, & VanRullen, 2009;Mathewson, Beck, Fabiani, Ro, & Gratton, 2011;VanRullen, Busch, Drewes, & Dubois, 2011), in oscillations in spatial attention (low alpha or high theta: Fiebelkorn et al, 2011;Fiebelkorn, Saalmann, & Kastner, 2013;Landau & Fries, 2012;Song, Meng, Chen, Zhou, & Luo, 2014), and in recurrent processing (theta: Drewes, Zhu, Wutz, & Melcher, 2015;Wutz, Muschter, van Koningsbruggen, & Melcher, 2014;Wutz, Weisz, Braun, & Melcher, 2014). On the one hand, theta (5-7 Hz) has been implicated in many tasks involving image categorization or binding features to specific objects or locations (Drewes et al, 2015;Wutz, Weisz, et al, 2014;. Higher frequencies, in the alpha band, have been implicated in the temporal resolution of perception (Cecere, Rees, & Romei, 2015;Cravo et al, 2015;Gho & Varela, 1988;Milton & Pleydell, 2016;Samaha & Postle, 2015;Varela et al, 1981).…”

The temporal window of individuation limits visual capacity

“…Segregating sensory changes exceeding this critical time frame (long SOA trials) instead depends on slower beta power modulations prior to stimulus onset (Wutz et al, 2014). The time course of the alpha phase synchrony reset (≈100 ms; ≈one alpha cycle) is consistent with the perceptual effects of integration masking (Enns and Di Lollo, 2000; Breitmeyer and Öğmen, 2006; Wutz et al, 2012).…”

Frequency modulation of neural oscillations according to visual task demands

“…visual perception | temporal integration | alpha oscillations | oscillation frequency | top-down control V isual perception is tasked both with constructing stable representations over time as well as maximizing sensitivity to transient changes. A large body of work has shown that neural oscillations in the alpha band (8)(9)(10)(11)(12) are partially responsible for determining the temporal resolution of perception, such that when discrete events occur within the same oscillatory cycle they can become perceptually integrated (1)(2)(3)(4)(5)(6)(7)(8). For instance, individuals with higher peak alpha frequencies have perception with higher temporal resolution (2,9), indicating that lower peak frequencies correspond to integration over longer time windows.…”