INTRODUCTION
The question of whether perception is discrete, continuous or a combination of both has been a subject of ongoing debate in the fields of sensory neuroscience, psychology and philosophy for many years (VanRullen & Koch, 2003; Herzog et al., 2016; Ruzzoli et al., 2019). Many different “flash fusion” paradigms have been developed based on the notion that our sensory system may sample information in discrete time windows: if two sensory stimuli, usually visual and/or auditory, are quickly flashed within the same time window, they are fused to form a single percept. If one of the stimuli falls outside of the window, they are segregated and two separate percepts are formed.
The rhythmic nature of brain activity is often proposed as a possible mechanism to support the idea of discrete sampling and is theorized to be a driving factor behind the integration and segregation of sensory information (Schroeder & Lakatos, 2009; Keitel et al., 2022; VanRullen & Koch, 2003). More specifically, the phase and frequency of neural oscillations are thought to determine the size of the temporal sampling window.
Neural oscillations are generally grouped into five distinct bands: delta (1 – 4 Hz), theta (5 – 8 Hz), alpha (8 – 13), beta (13 – 30) and gamma (30+ Hz) (Başar et al., 2001; Ward, 2003; Keil & Senkowski, 2018). As alpha band oscillations are the dominant oscillations in the brain, they have been studied extensively and have been found to be affected by the activity of the visual system in multiple ways, with one of the most basic findings being that alpha power is high when eyes are closed, but suppressed when eyes are open (Adrian & Matthews, 1934; Klimesch, 2012). One popular theory is that alpha-band oscillations may play a role in the modulation of visual stimulus detection (Ergenoglu et al., 2004; Hanslmayr et al., 2005; Morrow & Samaha, 2022; Mathewson et al., 2009). Some studies have found that the phase and frequency of alpha oscillations may affect whether or not a near-threshold stimulus is perceived, with higher frequency alpha oscillations being correlated with a more finely tuned capacity to segregate visual asynchronous stimuli (Busch et al., 2009; Mathewson et al., 2009; Samaha & Postle, 2015). Other studies however, failed to replicate this effect (Buergers & Noppeney, 2022; Ruzzoli et al., 2019). It is unclear whether this failure to replicate is due to the absence of a true relationship or because the previously mentioned studies all differed in their task paradigms and analysis methods. As pointed out by Keitel et al. (2022), the lack of direct replications is one of the main issues this field suffers from, along with small effect sizes and low statistical power.
To address this issue, we carried out a replication of a visual perception experiment conducted by Samaha & Postle in 2015. In this experiment, a two-flash fusion task was used to investigate how alpha-band oscillations may affect the perception of near-threshold visual stimuli. The study found that both pre-stimulus and eyes-closed peak alpha frequency correlated with flash/fusion thresholds between subjects. Moreover, the study found that within subjects, instantaneous peak alpha was correlated with perceptual accuracy.
In the current study, we employed the two-alternative-forced choice gap detection task (hereafter: flash-fusion task) used by Samaha & Postle with a larger sample size for a higher statistical power, and carried out similar EEG-data analyses to compare flash-fusion thresholds in relation with peak alpha frequency for resting-state and pre-stimulus scenarios. We also replicated within-participant analyses to investigate potential correlations between instantaneous alpha frequency and perceptual accuracy, using methods developed by Cohen (2014).
We additionally hypothesized that, if natural variation in peak alpha frequency is indeed indicative of an individual’s visual temporal resolution, it should correlate with different behavioural measures of visual perception speed. We therefore expanded the original study by also including a second visual perception speed task: the critical flicker fusion threshold task (hereafter: CFF task), which utilizes a continuously flickering stimulus to estimate individual temporal resolution thresholds.