Low-Frequency Neural Oscillations Support Dynamic Attending in Temporal Context

Abstract

Behaviorally relevant environmental stimuli are often characterized by some degree of temporal regularity. Dynamic attending theory provides a framework for explaining how perception of stimulus events is affected by the temporal context within which they occur. However, the precise neural implementation of dynamic attending remains unclear. Here, we provide a suggestion for a potential neural implementation of dynamic attending by appealing to low-frequency neural oscillations. The current review will familiarize the reader with the basic theoretical tenets of dynamic attending theory, and review empirical work supporting predictions derived from the theory. The potential neural implementation of dynamic attending theory with respect to low-frequency neural oscillations will be outlined, covering stimulus processing in regular and irregular contexts. Finally, we will provide some more speculative connections between dynamic attending and neural oscillations, and suggest further avenues for future research.

Entrained neural oscillations in multiple frequency bands comodulate behavior

“…In recent years, increasing scientific attention has been devoted to the hypothesis that entrainment of low-frequency neural oscillations by the temporal structure of time-varying stimuli supports perception through alignment of an oscillation's excitable phase with predictable, and thus important, portions of the signal (1,2,16,26). A limitation of these studies, however, is related to their exclusive focus on entrained neural phase in a single frequency band (7-10, 12, 14, 27).…”

“…However, in the absence of rhythmic stimulation, that is, during continuous-mode processing (16,17,58), neural phase effects are likely to be much more complex than can be revealed by a singular focus on individual frequency bands. We suggest that the perspective adopted here (i.e., allowing for the possibility that complex interactions among frequency bands support perception and cognition) will in turn allow for a better understanding of these dynamics in potentially more complicated nonrhythmic situations.…”

“…The result is that the probability that a (near-threshold) stimulus will elicit a neuronal response is not a uniform function of time but, instead, depends on the phase of the neural oscillation into which the stimulation falls. Indeed, the dependence of behavioral performance on neural oscillatory phase has been demonstrated in the visual (7-11) and auditory (12-15) domains.The role of neural oscillatory phase in perception is suggested to be of particular importance when stimuli possess temporal regularity (1,11,16,17). Precise alignment of neural oscillations with rhythmic stimuli is accomplished via entrainment, which is a process by which two oscillations become synchronized, or phaselocked, through phase and/or period adjustments (18).…”

“…The role of neural oscillatory phase in perception is suggested to be of particular importance when stimuli possess temporal regularity (1,11,16,17). Precise alignment of neural oscillations with rhythmic stimuli is accomplished via entrainment, which is a process by which two oscillations become synchronized, or phaselocked, through phase and/or period adjustments (18).…”

Subjective Duration as a Signature of Coding Efficiency: Emerging Links Among Stimulus Repetition, Predictive Coding, and Cortical GABA Levels

“…In the case of sub-second intervals, the RS and GABA-related effects observed in the cortex are presumably produced by "additive" as opposed to "multiplicative" effects, i.e., changes in the threshold manifold (Mitry et al, 2013) required to initiate timing of the "to-be-timed" stimulus as opposed to the oscillation frequency of the putative clock during the course of the entire stimulus duration (see Cheng et al, 2007;Lake et al, 2014;Lake & Meck, 2013;Matthews, 2011a, b). Future work should be aimed at separating threshold dynamics from speed effects for suband supra-second durations in order to better understand the dynamics of temporal processing and how satellite (i.e., local/peripheral) and core interval-timing mechanisms are integrated with circadian clocks and more general cognitive processes (e.g., Agostino et al, 2011;Boehm, Van Maanen, Forstmann, & Van Rijn, 2014;Bausenhart et al, 2010;Buhusi & Meck, 2005;Gu et al, in press b;Henry & Hermann, 2014;Matthews & Meck, 2014, submitted;Meck et al, 2012;Méndez et al, 2014;Merchant et al, 2013;Polyn & Sederberg, 2014;Shi et al, 2013;Taatgen, Van Rijn & Anderson, 2007;Tucci et al, 2014;Van Rijn et al, 2011, in press). Figure 1.…”