No evidence for a single oscillator underlying discrete visual percepts

Theoretical and Technical Issues Concerning the Measurement of Alpha Frequency and the Application of Signal Detection Theory: Comment on Buergers and Noppeney (2022)

Classical and recent evidence has suggested that alpha oscillations play a critical role in temporally discriminating or binding successively presented items. Challenging this view, Buergers and Noppeney [Buergers, S., & Noppeney, U. The role of alpha oscillations in temporal binding within and across the senses. Nature Human Behaviour, 6, 732-742, 2022] found that by combining EEG, psychophysics, and signal detection theory, neither prestimulus nor resting-state alpha frequency influences perceptual sensitivity and bias in the temporal binding task. We propose the following four points that should be considered when interpreting the role of alpha oscillations, and especially their frequency, on perceptual temporal binding: (1) Multiple alpha components can be contaminated in conventional EEG analysis; (2) the effect of alpha frequency on perception will interact with alpha power; (3) prestimulus and resting-state alpha frequency can be different from poststimulus alpha frequency, which is the frequency during temporal binding and should be more directly related to temporal binding; and (4) when applying signal detection theory under the assumption of equal variance, the assumption is often incomplete and can be problematic (e.g., the magnitude relationships between individuals in parametric sensitivity may change when converted into nonparametric sensitivity). Future directions, including solutions to each of the issues, are discussed.

Alpha-Band Frequency and Temporal Windows in Perception: A Review and Living Meta-analysis of 27 Experiments (and Counting)

Temporal windows in perception refer to windows of time within which distinct stimuli interact to influence perception. A simple example is two temporally proximal stimuli fusing into a single percept. It has long been hypothesized that the human alpha rhythm (an 8- to 13-Hz neural oscillation maximal over posterior cortex) is linked to temporal windows, with higher frequencies corresponding to shorter windows and finer-grained temporal resolution. This hypothesis has garnered support from studies demonstrating a correlation between individual differences in alpha-band frequency (IAF) and behavioral measures of temporal processing. However, nonsignificant effects have also been reported. Here, we review and meta-analyze 27 experiments correlating IAF with measures of visual and audiovisual temporal processing. Our results estimate the true correlation in the population to be between .39 and .53, a medium-to-large effect. The effect held when considering visual or audiovisual experiments separately, when examining different IAF estimation protocols (i.e., eyes open and eyes closed), and when using analysis choices that favor a null result. Our review shows that (1) effects have been internally and independently replicated, (2) several positive effects are based on larger sample sizes than the null effects, and (3) many reported null effects are actually in the direction predicted by the hypothesis. A free interactive web app was developed to allow users to replicate our meta-analysis and change or update the study selection at will, making this a "living" meta-analysis (randfxmeta.streamlit.app). We discuss possible factors underlying null reports, design recommendations, and open questions for future research.

Alerting attention is sufficient to induce a phase-dependent behavior that can be predicted by frontal EEG

Recent studies suggest that attention is rhythmic. Whether that rhythmicity can be explained by the phase of ongoing neural oscillations, however, is still debated. We contemplate that a step toward untangling the relationship between attention and phase stems from employing simple behavioral tasks that isolate attention from other cognitive functions (perception/decision-making) and by localized monitoring of neural activity with high spatiotemporal resolution over the brain regions associated with the attentional network. In this study, we investigated whether the phase of electroencephalography (EEG) oscillations predicts alerting attention. We isolated the alerting mechanism of attention using the Psychomotor Vigilance Task, which does not involve a perceptual component, and collected high resolution EEG using novel high-density dry EEG arrays at the frontal region of the scalp. We identified that alerting attention alone is sufficient to induce a phase-dependent modulation of behavior at EEG frequencies of 3, 6, and 8 Hz throughout the frontal region, and we quantified the phase that predicts the high and low attention states in our cohort. Our findings disambiguate the relationship between EEG phase and alerting attention.

Individual alpha frequency appears unrelated to the latency of early visual responses

A large body of work has linked neural oscillations in the alpha-band (8-13 Hz) to visual perceptual outcomes. In particular, studies have found that alpha phase prior to stimulus onset predicts stimulus detection, and sensory responses and that the frequency of alpha can predict temporal properties of perception. These findings have bolstered the idea that alpha-band oscillations reflect rhythmic sampling of visual information, however the mechanisms of this are unclear. Recently two contrasting hypotheses have been proposed. According to the rhythmic perception account, alpha oscillations impose phasic inhibition on perceptual processing and primarily modulate the amplitude or strength of visual responses and thus the likelihood of stimulus detection. On the other hand, the discrete perception account proposes that alpha activity discretizes perceptual inputs thereby reorganizing the timing (not only the strength) of perceptual and neural processes. In this paper, we sought neural evidence for the discrete perception account by assessing the correlation between individual alpha frequencies (IAF) and the latency of early visual evoked event-related potential (ERP) components. If alpha cycles were responsible for shifting neural events in time, then we may expect higher alpha frequencies to be associated with earlier afferent visual ERPs. Participants viewed large checkerboard stimuli presented to either the upper or lower visual field that were designed to elicit a large C1 ERP response (thought to index feedforward primary visual cortex activation). We found no reliable correlation between IAF and the C1 latency, or subsequent ERP component latencies, suggesting that the timing of these visual-evoked potentials was not modulated by alpha frequency. Our results thus fail to find evidence for discrete perception at the level of early visual responses but leave open the possibility of rhythmic perception.

Quantifying rhythmicity in perceptual reports

Several recent studies investigated the rhythmic nature of cognitive processes that lead to perception and behavioral report. These studies used different methods, and there has not yet been an agreement on a general standard. Here, we present a way to test and quantitatively compare these methods. We simulated behavioral data from a typical experiment and analyzed these data with several methods. We applied the main methods found in the literature, namely sine-wave fitting, the discrete Fourier transform (DFT) and the least square spectrum (LSS). DFT and LSS can be applied both on the average accuracy time course and on single trials. LSS is mathematically equivalent to DFT in the case of regular, but not irregular sampling - which is more common. LSS additionally offers the possibility to take into account a weighting factor which affects the strength of the rhythm, such as arousal. Statistical inferences were done either on the investigated sample (fixed-effects) or on the population (random-effects) of simulated participants. Multiple comparisons across frequencies were corrected using False Discovery Rate, Bonferroni, or the Max-Based approach. To perform a quantitative comparison, we calculated sensitivity, specificity and D-prime of the investigated analysis methods and statistical approaches. Within the investigated parameter range, single-trial methods had higher sensitivity and D-prime than the methods based on the average accuracy time course. This effect was further increased for a simulated rhythm of higher frequency. If an additional (observable) factor influenced detection performance, adding this factor as weight in the LSS further improved sensitivity and D-prime. For multiple comparison correction, the Max-Based approach provided the highest specificity and D-prime, closely followed by the Bonferroni approach. Given a fixed total amount of trials, the random-effects approach had higher D-prime when trials were distributed over a larger number of participants, even though this gave less trials per participant. Finally, we present the idea of using a dampened sinusoidal oscillator instead of a simple sinusoidal function, to further improve the fit to behavioral rhythmicity observed after a reset event.

When Average is Over: Small N but Many Trials

Rouder & Haaf (2021) provide a valuable recipe for testing whether there are qualitative differences. This should hasten the day when psychologists routine consider individual participant data, rather than just the average of the participants' data. Work remains to be done, however, on how to approach the issue of individual differences with the small-N, many-trials tradition that dates back to the beginning of experimental psychology and continues today in some areas, particularly cognitive modelling and perception.