No changes in parieto-occipital alpha during neural phase locking to visual quasi-periodic theta-, alpha-, and beta-band stimulation

Recent studies have probed the role of the parieto‐occipital alpha rhythm (8 – 12 Hz) in human visual perception through attempts to drive its neural generators. To that end, paradigms have used high‐intensity strictly‐periodic visual stimulation that created strong predictions about future stimulus occurrences and repeatedly demonstrated perceptual consequences in line with an entrainment of parieto‐occipital alpha. Our study, in turn, examined the case of alpha entrainment by non‐predictive low‐intensity quasi‐periodic visual stimulation within theta‐ (4 – 7 Hz), alpha‐ (8 – 13 Hz) and beta (14 – 20 Hz) frequency bands, i.e. a class of stimuli that resemble the temporal characteristics of naturally occurring visual input more closely. We have previously reported substantial neural phase‐locking in EEG recording during all three stimulation conditions. Here, we studied to what extent this phase‐locking reflected an entrainment of intrinsic alpha rhythms in the same dataset. Specifically, we tested whether quasi‐periodic visual stimulation affected several properties of parieto‐occipital alpha generators. Speaking against an entrainment of intrinsic alpha rhythms by non‐predictive low‐intensity quasi‐periodic visual stimulation, we found none of these properties to show differences between stimulation frequency bands. In particular, alpha band generators did not show increased sensitivity to alpha band stimulation and Bayesian inference corroborated evidence against an influence of stimulation frequency. Our results set boundary conditions for when and how to expect effects of entrainment of alpha generators and suggest that the parieto‐occipital alpha rhythm may be more inert to external influences than previously thought

Rhythmic entrainment source separation: Optimizing analyses of neural responses to rhythmic sensory stimulation

Contains fulltext : 169813.pdf (preprint version ) (Open Access)Steady-state evoked potentials (SSEPs) are rhythmic brain responses to rhythmic sensory stimulation, and are often used to study perceptual and attentional processes. We present a data analysis method for maximizing the signal-to-noise ratio of the narrow-band steady-state response in the frequency and time-frequency domains. The method, termed rhythmic entrainment source separation (RESS), is based on denoising source separation approaches that take advantage of the simultaneous but differential projection of neural activity to multiple electrodes or sensors. Our approach is a combination and extension of existing multivariate source separation methods. We demonstrate that RESS performs well on both simulated and empirical data, and outperforms conventional SSEP analysis methods based on selecting electrodes with the strongest SSEP response, as well as several other linear spatial filters. We also discuss the potential confound of overfitting, whereby the filter captures noise in absence of a signal. Matlab scripts are available to replicate and extend our simulations and methods. We conclude with some practical advice for optimizing SSEP data analyses and interpreting the results.14 p

Five methodological challenges in cognitive electrophysiology

Here we discuss five methodological challenges facing the current cognitive electrophysiology literature that address the roles of brain oscillations in cognition. The challenges focus on (1) unambiguous and consistent terminology, (2) neurophysiologically meaningful interpretations of results, (3) evaluation and comparison of different spatial filters often used in M/EEG research, (4) the role of multiscale interactions in brain and cognitive function, and (5) development of biophysically plausible cognitive models. We also suggest research directions that will help address these challenges. We hope that this paper will help foster discussions and debates about important themes in the study of how the brain's rhythmic patterns of spatiotemporal electrophysiological activity support cognition

Protecting visual short-term memory during maintenance:Attentional modulation of target and distractor representations

In the presence of distraction, attentional filtering is a key predictor of efficient information storage in visual short-term memory (VSTM). Yet, the role of attention in distractor filtering, and the extent to which attentional filtering continues to protect information during post-perceptual stages of VSTM, remains largely unknown. In the current study, we investigated the role of spatial attention in distractor filtering during VSTM encoding and maintenance. Participants performed a change detection task with varying distractor load. Attentional deployment to target and distractor locations was tracked continuously by means of Steady-State Visual Evoked Potentials (SSVEPs). Analyses revealed that attention strongly modulated the amplitude of the second harmonic SSVEP response, with larger amplitudes at target compared to distractor locations. These attentional modulations commenced during encoding, and remained present during maintenance. Furthermore, the amount of attention paid to distractor locations was directly related to behavioral distractor costs: Individuals who paid more attention to target compared to distractor locations during VSTM maintenance generally suffered less from the presence of distractors. Together, these findings support an important role of spatial attention in distractor filtering at multiple stages of VSTM, and highlight the usefulness of SSVEPs in continuously tracking attention to multiple locations during VSTM

The role of midfrontal theta oscillations across the development of cognitive control in preschoolers and school‐age children

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Cognitive Load Theory and Time Considerations: Using the Time-Based Resource Sharing Model

International audienceFor a long time, Cognitive Load Theory has considered working memory models as tools to advance research on learning. It has used working memory capacity models, where working memory is viewed as being composed of a discrete number of slots (i.e., chunks) that can be kept active. However, recent results have shown that for a fixed quantity of information, the mere pace of information presentation can affect learning performance. Commonly used working memory models cannot explain such results. Here, we propose to use a new model in the field of Cognitive Load Theory, the Time-Based Resource Sharing model, which enables time to be taken into account when describing working memory solicitation. In two experiments, we tested hypotheses allowed by the model. Results showed that the Time-Based Resource Sharing model can assist the investigation of information presentation pace effects during learning, as long as prior knowledge is taken into account. Particularly, the results suggest a new interpretation of intrinsic and extrinsic load that could relate them to the time needed to process information