Individual alpha frequency increases during a task but is unchanged by alpha-band flicker

Spectral tuning and after-effects in neural entrainment

Neural entrainment has become a popular technique to non-invasively manipulate brain rhythms via external, periodic stimulation. However, there is still debate regarding its underlying mechanisms and effects on brain activity. Here, we used EEG recordings during a visual entrainment paradigm to assess characteristic changes in the spectral content of EEG signals due to entrainment. Our results demonstrate that entrainment not only increases synchrony between neural oscillations and the entraining stimulus but also elicits previously unreported spectral tuning effects and long-lasting after-effects. These findings offer compelling evidence for the presence of dedicated, flexible, and adaptive mechanisms for neural entrainment, which may have key roles in adjusting the sensitivity and dynamic range of brain oscillators in response to environmental temporal structures.

Investigating the synergistic neuromodulation effect of bilateral rTMS and VR brain-computer interfaces training in chronic stroke patients

Objective.Stroke is a major cause of adult disability worldwide, resulting in motor impairments. To regain motor function, patients undergo rehabilitation, typically involving repetitive movement training. For those who lack volitional movement, novel technology-based approaches have emerged that directly involve the central nervous system, through neuromodulation techniques such as transcranial magnetic stimulation (TMS), and closed-loop neurofeedback like brain-computer interfaces (BCIs). This, can be augmented through proprioceptive feedback delivered many times by embodied virtual reality (VR). Nonetheless, despite a growing body of research demonstrating the individual efficacy of each technique, there is limited information on their combined effects.Approach.In this study, we analyzed the Electroencephalographic (EEG) signals acquired from 10 patients with more than 4 months since stroke during a longitudinal intervention with repetitive TMS followed by VR-BCI training. From the EEG, the event related desynchronization (ERD) and individual alpha frequency (IAF) were extracted, evaluated over time and correlated with clinical outcome.Main results.Every patient's clinical outcome improved after treatment, and ERD magnitude increased during simultaneous rTMS and VR-BCI. Additionally, IAF values showed a significant correlation with clinical outcome, nonetheless, no relationship was found between differences in ERD pre- post- intervention with the clinical improvement.Significance.This study furnishes empirical evidence supporting the efficacy of the joint action of rTMS and VR-BCI in enhancing patient recovery. It also suggests a relationship between IAF and rehabilitation outcomes, that could potentially serve as a retrievable biomarker for stroke recovery.

A Role for Bottom-Up Alpha Oscillations in Temporal Integration

Neural oscillations in the 8-12 Hz alpha band are thought to represent top-down inhibitory control and to influence temporal resolution: Individuals with faster peak frequencies segregate stimuli appearing closer in time. Recently, this theory has been challenged. Here, we investigate a special case in which alpha does not correlate with temporal resolution: when stimuli are presented amidst strong visual drive. Based on findings regarding alpha rhythmogenesis and wave spatial propagation, we suggest that stimulus-induced, bottom-up alpha oscillations play a role in temporal integration. We propose a theoretical model, informed by visual persistence, lateral inhibition, and network refractory periods, and simulate physiologically plausible scenarios of the interaction between bottom-up alpha and the temporal segregation. Our simulations reveal that different features of oscillations, including frequency, phase, and power, can influence temporal perception and provide a theoretically informed starting point for future empirical studies.

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.

Sensory Drive Modifies Brain Dynamics and the Temporal Integration Window

Perception is suggested to occur in discrete temporal windows, clocked by cycles of neural oscillations. An important testable prediction of this theory is that individuals' peak frequencies of oscillations should correlate with their ability to segregate the appearance of two successive stimuli. An influential study tested this prediction and showed that individual peak frequency of spontaneously occurring alpha (8-12 Hz) correlated with the temporal segregation threshold between two successive flashes of light [Samaha, J., & Postle, B. R. The speed of alpha-band oscillations predicts the temporal resolution of visual perception. Current Biology, 25, 2985-2990, 2015]. However, these findings were recently challenged [Buergers, S., & Noppeney, U. The role of alpha oscillations in temporal binding within and across the senses. Nature Human Behaviour, 6, 732-742, 2022]. To advance our understanding of the link between oscillations and temporal segregation, we devised a novel experimental approach. Rather than relying entirely on spontaneous brain dynamics, we presented a visual grating before the flash stimuli that is known to induce continuous oscillations in the gamma band (45-65 Hz). By manipulating the contrast of the grating, we found that high contrast induces a stronger gamma response and a shorter temporal segregation threshold, compared to low-contrast trials. In addition, we used a novel tool to characterize sustained oscillations and found that, for half of the participants, both the low- and high-contrast gratings were accompanied by a sustained and phase-locked alpha oscillation. These participants tended to have longer temporal segregation thresholds. Our results suggest that visual stimulus drive, reflected by oscillations in specific bands, is related to the temporal resolution of visual perception.

Alpha-band Brain Dynamics and Temporal Processing: An Introduction to the Special Focus

For decades, the intriguing connection between the human alpha rhythm (an 8- to 13-Hz oscillation maximal over posterior cortex) and temporal processes in perception has furnished a rich landscape of proposals. The past decade, however, has seen a surge in interest in the topic, bringing new theoretical, analytic, and methodological developments alongside fresh controversies. This Special Focus on alpha-band dynamics and temporal processing provides an up-to-date snapshot of the playing field, with contributions from leading researchers in the field spanning original perspectives, new evidence, comprehensive reviews and meta-analyses, as well as discussion of ongoing controversies and paths forward. We hope that the perspectives captured here will help catalyze future research and shape the pathways toward a theoretically grounded and mechanistic account of the link between alpha dynamics and temporal properties of perception.

Perceptual Training as Means to Assess the Effect of Alpha Frequency on Temporal Binding Window

For decades, it has been shown that alpha frequency is related to temporal binding window, and currently, such is the mainstream viewpoint [Noguchi, Y. Individual differences in beta frequency correlate with the audio-visual fusion illusion. Psychophysiology, 59, e14041, 2022; Gray, M. J., & Emmanouil, T. A. Individual alpha frequency increases during a task but is unchanged by alpha-band flicker. Psychophysiology, 57, e13480, 2020; Hirst, R. J., McGovern, D. P., Setti, A., Shams, L., & Newell, F. N. What you see is what you hear: Twenty years of research using the sound-induced flash illusion. Neuroscience & Biobehavioral Reviews, 118, 759-774, 2020; Keil, J. Double flash illusions: Current findings and future directions. Frontiers in Neuroscience, 14, 298, 2020; Migliorati, D., Zappasodi, F., Perrucci, M. G., Donno, B., Northoff, G., Romei, V., & Costantini, M. Individual alpha frequency predicts perceived visuotactile simultaneity. Journal of Cognitive Neuroscience, 32, 1-11, 2020; Keil, J., & Senkowski, D. Individual alpha frequency relates to the sound-induced flash illusion. Multisensory Research, 30, 565-578, 2017; Minami, S., & Amano, K. Illusory jitter perceived at the frequency of alpha oscillations. Current Biology, 27, 2344-2351, 2017; Cecere, R., Rees, G., & Romei, V. Individual differences in alpha frequency drive crossmodal illusory perception. Current Biology, 25, 231-235, 2015]. However, recently, this stance has been challenged [Buergers, S., & Noppeney, U. The role of alpha oscillations in temporal binding within and across the senses. Nature Human Behaviour, 6, 732-742, 2022]. Moreover, both stances appear to have their limitations regarding the reliability of results. Therefore, it is of paramount importance to develop new methodology to gain more reliable results. Perceptual training seems to be such a method that also offers significant practical implications.

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.

Alpha Oscillations and Temporal Binding Windows in Perception-A Critical Review and Best Practice Guidelines

An intriguing question in cognitive neuroscience is whether alpha oscillations shape how the brain transforms the continuous sensory inputs into distinct percepts. According to the alpha temporal resolution hypothesis, sensory signals arriving within a single alpha cycle are integrated, whereas those in separate cycles are segregated. Consequently, shorter alpha cycles should be associated with smaller temporal binding windows and higher temporal resolution. However, the evidence supporting this hypothesis is contentious, and the neural mechanisms remain unclear. In this review, we first elucidate the alpha temporal resolution hypothesis and the neural circuitries that generate alpha oscillations. We then critically evaluate study designs, experimental paradigms, psychophysics, and neurophysiological analyses that have been employed to investigate the role of alpha frequency in temporal binding. Through the lens of this methodological framework, we then review evidence from between-subject, within-subject, and causal perturbation studies. Our review highlights the inherent interpretational ambiguities posed by previous study designs and experimental paradigms and the extensive variability in analysis choices across studies. We also suggest best practice recommendations that may help to guide future research. To establish a mechanistic role of alpha frequency in temporal parsing, future research is needed that demonstrates its causal effects on the temporal binding window with consistent, experimenter-independent methods.

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.

The role of alpha oscillations in temporal binding within and across the senses

An intriguing notion in cognitive neuroscience posits that alpha oscillations mould how the brain parses the constant influx of sensory signals into discrete perceptual events. Yet, the evidence is controversial and the underlying neural mechanism unclear. Further, it is unknown whether alpha oscillations influence observers’ perceptual sensitivity (i.e. temporal resolution) or their top-down biases to bind signals within and across the senses. Combining EEG, psychophysics and signal detection theory, this multi-day study rigorously assessed the impact of alpha frequency on temporal binding of signals within and across the senses. In a series of two-flash discrimination experiments twenty human observers were presented with one or two flashes together with none, one or two sounds. Our results provide robust evidence that pre-stimulus alpha frequency as a dynamic neural state and an individual’s trait index does not influence observers’ perceptual sensitivity or bias for two-flash discrimination in any of the three sensory contexts. These results challenge the notion that alpha oscillations have a profound impact on how observers parse sensory inputs into discrete perceptual events.

Occipital alpha-band brain waves when the eyes are closed are shaped by ongoing visual processes

One of the seminal findings of cognitive neuroscience is that the power of occipital alpha-band (~ 10 Hz) brain waves is increased when peoples' eyes are closed, rather than open. This has encouraged the view that alpha oscillations are a default dynamic, to which the visual brain returns in the absence of input. Accordingly, we might be unable to increase the power of alpha oscillations when the eyes are closed, above the level that would normally ensue when people close their eyes. Here we report counter evidence. We used electroencephalography (EEG) to record brain activity when people had their eyes open and closed, both before and after they had adapted to radial motion. The increase in alpha power when people closed their eyes was increased by prior adaptation to a broad range of radial motion speeds. This effect was greatest for 10 Hz motion, but robust for other frequencies (and especially 7.5 Hz). This discredits a persistent entrainment of activity at the adaptation frequency as an explanation for our findings. Our data show that the power of occipital alpha-band brain waves can be increased by motion sensitive visual processes that persist when the eyes are closed. Consequently, we suggest that the power of these brain waves is, at least in part, an index of the degree to which visual brain activity is being subjected to inhibition. This is increased when people close their eyes, but can be even further increased by pre-adaptation to radial motion.

Power spectrum slope confounds estimation of instantaneous oscillatory frequency

Oscillatory neural dynamics are highly non-stationary and require methods capable of quantifying time-resolved changes in oscillatory activity in order to understand neural function. Recently, a method termed 'frequency sliding' was introduced to estimate the instantaneous frequency of oscillatory activity, providing a means of tracking temporal changes in the dominant frequency within a sub-band of field potential recordings. Here, the ability of frequency sliding to recover ground-truth oscillatory frequency in simulated data is tested while the exponent (slope) of the 1/f^x component of the signal power spectrum is systematically varied, mimicking real electrophysiological data. The results show that 1) in the presence of 1/f activity, frequency sliding systematically underestimates the true frequency of the signal, 2) the magnitude of underestimation is correlated with the steepness of the slope, suggesting that, if unaccounted for, slope changes could be misinterpreted as frequency changes, 3) the impact of slope on frequency estimates interacts with oscillation amplitude, indicating that changes in oscillation amplitude alone may also influence instantaneous frequency estimates in the presence of strong 1/f activity; and 4) analysis parameters such as filter bandwidth and location also mediate the influence of slope on estimated frequency, indicating that these settings should be considered when interpreting estimates obtained via frequency sliding. The origin of these biases resides in the output of the filtering step of frequency sliding, whose energy is biased towards lower frequencies precisely because of the 1/f structure of the data. We discuss several strategies to mitigate these biases and provide a proof-of-principle for a 1/f normalization strategy.

Transcranial magnetic stimulation entrains alpha oscillatory activity in occipital cortex

Parieto-occipital alpha rhythms (8-12 Hz) underlie cortical excitability and influence visual performance. Whether the synchrony of intrinsic alpha rhythms in the occipital cortex can be entrained by transcranial magnetic stimulation (TMS) is an open question. We applied 4-pulse, 10-Hz rhythmic TMS to entrain intrinsic alpha oscillators targeting right V1/V2, and tested four predictions with concurrent electroencephalogram (EEG): (1) progressive enhancement of entrainment across time windows, (2) output frequency specificity, (3) dependence on the intrinsic oscillation phase, and (4) input frequency specificity to individual alpha frequency (IAF) in the neural signatures. Two control conditions with an equal number of pulses and duration were arrhythmic-active and rhythmic-sham stimulation. The results confirmed the first three predictions. Rhythmic TMS bursts significantly entrained local neural activity. Near the stimulation site, evoked oscillation amplitude and inter-trial phase coherence (ITPC) were increased for 2 and 3 cycles, respectively, after the last TMS pulse. Critically, ITPC following entrainment positively correlated with IAF rather than with the degree of similarity between IAF and the input frequency (10 Hz). Thus, we entrained alpha-band activity in occipital cortex for ~ 3 cycles (~ 300 ms), and IAF predicts the strength of entrained occipital alpha phase synchrony indexed by ITPC.

Calibrating rhythmic stimulation parameters to individual EEG markers: the consistency of individual alpha frequency in practical lab settings

Rhythmic stimulation can be applied to modulate neuronal oscillations. Such 'entrainment' is optimized when stimulation frequency is individually-calibrated based on magneto/encephalography markers. It remains unknown how consistent such individual markers are across days/sessions, within a session, or across cognitive states, hemispheres, and estimation methods, especially in a realistic, practical, lab setting. We here estimated individual alpha frequency (IAF) repeatedly from short EEG measurements at rest or during an attention task (cognitive state), using single parieto-occipital electrodes in 24 participants on four days (between-sessions), with multiple measurements over an hour on one day (within-session). First, we introduce an algorithm to automatically reject power spectra without a sufficiently clear peak to ensure unbiased IAF estimations. Then we estimated IAF via the traditional 'maximum' method and a 'Gaussian fit' method. IAF was reliable within- and between-sessions for both cognitive states and hemispheres, though task-IAF estimates tended to be more variable. Overall, the 'Gaussian fit' method was more reliable than the 'maximum' method. Furthermore, we evaluated how far from an approximated 'true' task-related IAF the selected 'stimulation frequency' was, when calibrating this frequency based on a short rest-EEG, a short task-EEG, or simply selecting 10Hertz for all participants. For the 'maximum' method, rest-EEG calibration was best, followed by task-EEG, and then 10 Hertz. For the 'Gaussian fit' method, rest-EEG and task-EEG-based calibration were similarly accurate, and better than 10 Hertz. These results lead to concrete recommendations about valid, and automated, estimation of individual oscillation markers in experimental and clinical settings.

No evidence for a single oscillator underlying discrete visual percepts

Theories of perception based on discrete sampling posit that visual consciousness is reconstructed based on snapshot-like perceptual moments, as opposed to being updated continuously. According to a model proposed by Schneider (2018), discrete sampling can explain both the flash-lag and the Fröhlich illusion, whereby a lag in the conscious updating of a moving stimulus alters its perceived spatial location in comparison to stationary stimulus. The alpha-band frequency, which is associated with phasic modulation of stimulus detection and the temporal resolution of perception, has been proposed to reflect the duration of perceptual moments. The goal of this study was to determine whether a single oscillator (e.g., alpha) is underlying the duration of perceptual moments, which would predict that the point of subjective equality (PSE) in the flash-lag and Fröhlich illusions are positively correlated across individuals. Although our displays induced robust flash-lag and Fröhlich effects, virtually zero correlation was seen between the PSE in the two illusions, indicating that the illusion magnitudes are unrelated across observers. These findings suggest that, if discrete sampling theory is true, these illusory percepts either rely on different oscillatory frequencies or not on oscillations at all. Alternatively, discrete sampling may not be the mechanism underlying these two motion illusions or our methods were ill-suited to test the theory.

Experimental increase of blood glucose alters resting state EEG measures of excitation-inhibition balance

NEW FINDINGS

What is the central question of this study? Glucose is the dominant energy source for the brain. However, little is known about how glucose metabolism impacts the coordination of network activity in the brain in healthy adults. What is the main finding and its importance? We demonstrate that both α oscillations and the aperiodic signal components of the resting EEG are modulated by experimentally elevated blood glucose concentrations. Our findings suggest that glucose increases measures associated with excitation-inhibition (E:I) balance, but that the effect on α oscillations might plateau. Understanding the relationship between glucose consumption and E:I balance is crucial to developing our understanding of how metabolism shapes human brain activity.

ABSTRACT

Brain network oscillations can be divided broadly into periodic and aperiodic signal components, which are sensitive to state-dependent changes in network coordination and excitation-inhibition (E:I) balance. We sought to address whether the dominant energy source of the brain, glucose, is implicated in the regulation of network activity and excitability. We conducted an experimenter-blind, crossover study of the effect of blood glucose level (BGL) on the resting EEG frequency spectrum. Participants consumed a glucose drink (75 g glucose) or an equivalent volume of water on two separate visits. EEG data were sampled before and ≤3 h after the drink. We found that the experimentally induced changes in BGL exhibited an inverted U-shaped relationship, with changes in the individual α frequency peak, whereas the slope of the aperiodic signal component of the frequency spectrum showed a positive linear association suggestive of greater excitation. In contrast, peak α power, which is typically associated with top-down inhibitory processes, was negatively associated with changes in BGL. Collectively, these results suggest that high BGL alters brain network coordination in the form of α oscillations and measures associated with E:I balance.

Shifts in broadband power and alpha peak frequency observed during long-term isolation

Prolonged periods of social isolation and spatial confinement do not only represent an issue that needs to be faced by a few astronauts during space missions, but can affect all of us as recently shown during pandemic situations. The fundamental question, how the brain adapts to periods of sensory deprivation and re-adapts to normality, has only received little attention. Here, we use eyes closed and eyes open resting-state electroencephalographic (EEG) recordings to investigate how neural activity is altered during 120 days of isolation in a spatially confined, space-analogue environment. After disentangling oscillatory patterns from 1/f activity, we show that isolation leads to a reduction in broadband power and a flattening of the 1/f spectral slope. Beyond that, we observed a reduction in alpha peak frequency during isolation, but did not find strong evidence for isolation-induced changes that are of oscillatory nature. Critically, all effects reversed upon release from isolation. These findings suggest that isolation and concomitant sensory deprivation lead to an enhanced cortical deactivation which might be explained by a reduction in the mean neuronal population firing rate.