Periodic attention operates faster during more complex visual search.

Attention has been found to sample visual information periodically, in a wide range of frequencies below 20 Hz. This periodicity may be supported by brain oscillations at corresponding frequencies. We propose that part of the discrepancy in periodic frequencies observed in the literature is due to differences in attentional demands, resulting from heterogeneity in tasks performed. To test this hypothesis, we used visual search and manipulated task complexity, i.e., target discriminability (high, medium, low) and number of distractors (set size), while electro-encephalography was simultaneously recorded. We replicated previous results showing that the phase of pre-stimulus low-frequency oscillations predicts search performance. Crucially, such effects were observed at increasing frequencies within the theta-alpha range (6-18 Hz) for decreasing target discriminability. In medium and low discriminability conditions, correct responses were further associated with higher post-stimulus phase-locking than incorrect ones, in increasing frequency and latency. Finally, the larger the set size, the later the post-stimulus effect peaked. Together, these results suggest that increased complexity (lower discriminability or larger set size) requires more attentional cycles to perform the task, partially explaining discrepancies between reports of attentional sampling. Low-frequency oscillations structure the temporal dynamics of neural activity and aid top-down, attentional control for efficient visual processing.

Postdiction: When Temporal Regularity Drives Space Perception through Prestimulus Alpha Oscillations.

In postdiction, the last stimulus of a sequence changes the perception of the preceding stimuli. Postdiction has been reported in all sensory modalities, but its neural underpinnings remain poorly understood. In the rabbit illusion, a sequence of nonequidistant stimuli presented isochronously is perceived as equidistantly spaced. This illusion might be driven by an internal prior favoring a constant-speed motion. Here, we hypothesized that prestimulus alpha oscillations (8-12 Hz), known to correlate with perceptual expectations and biases, would reflect the degree to which perceptual reports are influenced by a constant-speed prior. Human participants were presented with ambiguous visual sequences while being recorded simultaneously with MEG and EEG: the same sequences yielded an illusory perception in about half the trials, allowing contrasting brain responses elicited by identical sequences causing distinct percepts. As a proxy of an individual's prior, we used the percentage of perceived illusion and the detection criterion, assuming that a strong constant-speed prior would result in a higher rate of illusory percepts. We found that high frontoparietal alpha power was associated with perceiving the sequence according to the individual's prior: participants with high susceptibility to the illusion would report the illusion, while participants with low susceptibility would report the veridical sequence. Additionally, we found that prestimulus alpha phase in occipitoparietal regions dissociated illusion from no-illusion trials. We interpret our results as suggesting that alpha power reflects an individual's constant-speed prior, whereas alpha phase modulates sensory uncertainty.

Alpha Activity Reflects the Magnitude of an Individual Bias in Human Perception.

Biases in sensory perception can arise from both experimental manipulations and personal trait-like features. These idiosyncratic biases and their neural underpinnings are often overlooked in studies on the physiology underlying perception. A potential candidate mechanism reflecting such idiosyncratic biases could be spontaneous alpha band activity, a prominent brain rhythm known to influence perceptual reports in general. Using a temporal order judgment task, we here tested the hypothesis that alpha power reflects the overcoming of an idiosyncratic bias. Importantly, to understand the interplay between idiosyncratic biases and contextual (temporary) biases induced by experimental manipulations, we quantified this relation before and after temporal recalibration. Using EEG recordings in human participants (male and female), we find that prestimulus frontal alpha power correlates with the tendency to respond relative to an own idiosyncratic bias, with stronger α leading to responses matching the bias. In contrast, alpha power does not predict response correctness. These results also hold after temporal recalibration and are specific to the alpha band, suggesting that alpha band activity reflects, directly or indirectly, processes that help to overcome an individual's momentary bias in perception. We propose that combined with established roles of parietal α in the encoding of sensory information frontal α reflects complementary mechanisms influencing perceptual decisions.SIGNIFICANCE STATEMENT The brain is a biased organ, frequently generating systematically distorted percepts of the world, leading each of us to evolve in our own subjective reality. However, such biases are often overlooked or considered noise when studying the neural mechanisms underlying perception. We show that spontaneous alpha band activity predicts the degree of biasedness of human choices in a time perception task, suggesting that alpha activity indexes processes needed to overcome an individual's idiosyncratic bias. This result provides a window onto the neural underpinnings of subjective perception, and offers the possibility to quantify or manipulate such priors in future studies.

The Strength of Alpha-Beta Oscillatory Coupling Predicts Motor Timing Precision.

Precise timing makes the difference between harmony and cacophony, but how the brain achieves precision during timing is unknown. In this study, human participants (7 females, 5 males) generated a time interval while being recorded with magnetoencephalography. Building on the proposal that the coupling of neural oscillations provides a temporal code for information processing in the brain, we tested whether the strength of oscillatory coupling was sensitive to self-generated temporal precision. On a per individual basis, we show the presence of alpha-beta phase-amplitude coupling whose strength was associated with the temporal precision of self-generated time intervals, not with their absolute duration. Our results provide evidence that active oscillatory coupling engages α oscillations in maintaining the precision of an endogenous temporal motor goal encoded in ß power; the when of self-timed actions. We propose that oscillatory coupling indexes the variance of neuronal computations, which translates into the precision of an individual's behavioral performance.SIGNIFICANCE STATEMENT Which neural mechanisms enable precise volitional timing in the brain is unknown, yet accurate and precise timing is essential in every realm of life. In this study, we build on the hypothesis that neural oscillations, and their coupling across time scales, are essential for the coding and for the transmission of information in the brain. We show the presence of alpha-beta phase-amplitude coupling (α-ß PAC) whose strength was associated with the temporal precision of self-generated time intervals, not with their absolute duration. α-ß PAC indexes the temporal precision with which information is represented in an individual's brain. Our results link large-scale neuronal variability on the one hand, and individuals' timing precision, on the other.

Non-linear auto-regressive models for cross-frequency coupling in neural time series.

We address the issue of reliably detecting and quantifying cross-frequency coupling (CFC) in neural time series. Based on non-linear auto-regressive models, the proposed method provides a generative and parametric model of the time-varying spectral content of the signals. As this method models the entire spectrum simultaneously, it avoids the pitfalls related to incorrect filtering or the use of the Hilbert transform on wide-band signals. As the model is probabilistic, it also provides a score of the model "goodness of fit" via the likelihood, enabling easy and legitimate model selection and parameter comparison; this data-driven feature is unique to our model-based approach. Using three datasets obtained with invasive neurophysiological recordings in humans and rodents, we demonstrate that these models are able to replicate previous results obtained with other metrics, but also reveal new insights such as the influence of the amplitude of the slow oscillation. Using simulations, we demonstrate that our parametric method can reveal neural couplings with shorter signals than non-parametric methods. We also show how the likelihood can be used to find optimal filtering parameters, suggesting new properties on the spectrum of the driving signal, but also to estimate the optimal delay between the coupled signals, enabling a directionality estimation in the coupling.

Prestimulus Alpha Oscillations and the Temporal Sequencing of Audiovisual Events.

Perceiving the temporal order of sensory events typically depends on participants' attentional state, thus likely on the endogenous fluctuations of brain activity. Using magnetoencephalography, we sought to determine whether spontaneous brain oscillations could disambiguate the perceived order of auditory and visual events presented in close temporal proximity, that is, at the individual's perceptual order threshold (Point of Subjective Simultaneity [PSS]). Two neural responses were found to index an individual's temporal order perception when contrasting brain activity as a function of perceived order (i.e., perceiving the sound first vs. perceiving the visual event first) given the same physical audiovisual sequence. First, average differences in prestimulus auditory alpha power indicated perceiving the correct ordering of audiovisual events irrespective of which sensory modality came first: a relatively low alpha power indicated perceiving auditory or visual first as a function of the actual sequence order. Additionally, the relative changes in the amplitude of the auditory (but not visual) evoked responses were correlated with participant's correct performance. Crucially, the sign of the magnitude difference in prestimulus alpha power and evoked responses between perceived audiovisual orders correlated with an individual's PSS. Taken together, our results suggest that spontaneous oscillatory activity cannot disambiguate subjective temporal order without prior knowledge of the individual's bias toward perceiving one or the other sensory modality first. Altogether, our results suggest that, under high perceptual uncertainty, the magnitude of prestimulus alpha (de)synchronization indicates the amount of compensation needed to overcome an individual's prior in the serial ordering and temporal sequencing of information.

Time Order as Psychological Bias.

Incorrectly perceiving the chronology of events can fundamentally alter people's understanding of the causal structure of the world. For example, when astronomers used the "eye and ear" method to locate stars, they showed systematic interindividual errors. In the current study, we showed that temporal-order perception may be considered a psychological bias that attention can modulate but not fully eradicate. According to Titchener's law of prior entry, attention prioritizes the perception of an event and thus can help compensate for possible interindividual differences in the perceived timing of an event by normalizing perception in time. In a longitudinal study, we tested the stability of participants' temporal-order perception across and within sensory modalities, together with the magnitude of the participants' prior-entry effect. All measurements showed the persistence of stable interindividual variability. Crucially, the magnitude of the prior-entry effect was insufficient to compensate for interindividual variability: Conscious time order was systematically subjective, and therefore traceable on an individual basis.