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.