Prioritizing flexible working memory representations through retrospective attentional strengthening

The neural dynamics of integrating prior and kinematic information during action anticipation in sport

Effective action anticipation in sports hinges on the integration of prior knowledge and kinematic cues, enabling athletes to respond swiftly and accurately in real-time scenarios. However, the neural mechanisms supporting this integrative process remain insufficiently understood. This study addressed this gap by using electroencephalography (EEG), combined with both multivariate and univariate analyses, to investigate how expert basketball players and non-athlete controls process prior and kinematic information during a sport-specific action anticipation task. Eighty-five participants (44 experts and 41 controls) were asked to predict the outcomes of basketball free throws presented via video clips, either with or without outcome-based prior information cues. Multivariate pattern classification and contingent negative variation (CNV) analyses revealed distinct anticipatory strategies between groups, with experts predominantly relying on kinematic information, whereas controls showed greater sensitivity to prior information. Additionally, time-frequency analysis of alpha-band activity indicated stronger desynchronization in experts, reflecting enhanced cortical engagement during kinematic processing. Notably, alpha ERD was significantly stronger for incongruent trials in the later phase of the task, suggesting increased cortical engagement when resolving conflicts between prior expectations and observed actions. These findings advance our understanding of the temporal dynamics and neural mechanisms underlying action anticipation, and highlight the value of combining EEG with multivariate decoding approaches to characterize individual differences in predictive processing.

Re-focusing visual working memory during expected and unexpected memory tests

A classic distinction from the domain of external attention is that between anticipatory orienting and subsequent re-orienting of attention to unexpected events. Whether and how humans also re-orient attention 'in mind' following expected and unexpected working-memory tests remains elusive. We leveraged spatial modulations in neural activity and gaze to isolate re-orienting within the spatial layout of visual working memory following central memory tests of certain, expected, or unexpected mnemonic content. Besides internal orienting after predictive cues, we unveil a second stage of internal attentional deployment following both expected and unexpected memory tests. Following expected tests, internal attentional deployment was not contingent on prior orienting, suggesting an additional verification - 'double checking' - in memory. Following unexpected tests, re-focusing of alternative memory content was prolonged. This brings attentional re-orienting to the domain of working memory and underscores how memory tests can invoke either a verification or a revision of our internal focus.

Using multivariate pattern analysis to increase effect sizes for event-related potential analyses

Multivariate pattern analysis (MVPA) approaches can be applied to the topographic distribution of event-related potential (ERP) signals to "decode" subtly different stimulus classes, such as different faces or different orientations. These approaches are extremely sensitive, and it seems possible that they could also be used to increase effect sizes and statistical power in traditional paradigms that ask whether an ERP component differs in amplitude across conditions. To assess this possibility, we leveraged the open-source ERP CORE data set and compared the effect sizes resulting from conventional univariate analyses of mean amplitude with two MVPA approaches (support vector machine decoding and the cross-validated Mahalanobis distance, both of which are easy to compute using open-source software). We assessed these approaches across seven widely studied ERP components (N170, N400, N2pc, P3b, lateral readiness potential, error related negativity, and mismatch negativity). Across all components, we found that multivariate approaches yielded effect sizes that were as large or larger than the effect sizes produced by univariate approaches. These results indicate that researchers could obtain larger effect sizes, and therefore greater statistical power, by using multivariate analysis of topographic voltage patterns instead of traditional univariate analyses in many ERP studies.

Using Multivariate Pattern Analysis to Increase Effect Sizes for Event-Related Potential Analyses

Multivariate pattern analysis approaches can be applied to the topographic distribution of event-related potential (ERP) signals to 'decode' subtly different stimulus classes, such as different faces or different orientations. These approaches are extremely sensitive, and it seems possible that they could also be used to increase effect sizes and statistical power in traditional paradigms that ask whether an ERP component differs in amplitude across conditions. To assess this possibility, we leveraged the open-source ERP CORE dataset and compared the effect sizes resulting from conventional univariate analyses of mean amplitude with two multivariate pattern analysis approaches (support vector machine decoding and the cross-validated Mahalanobis distance, both of which are easy to compute using open-source software). We assessed these approaches across seven widely studied ERP components (N170, N400, N2pc, P3b, lateral readiness potential, error related negativity, and mismatch negativity). Across all components, we found that multivariate approaches yielded effect sizes that were as large or larger than the effect sizes produced by univariate approaches. These results indicate that researchers could obtain larger effect sizes, and therefore greater statistical power, by using multivariate analysis of topographic voltage patterns instead of traditional univariate analyses in many ERP studies.

Neural and behavioral evidence supporting the relationship between habitual exercise and working memory precision in healthy young adults

Introduction

Working memory (WM) is a well-known fundamental ability related to various high-level cognitive functions, such as executive functioning, decision-making, and problem-solving. Although previous studies have posited that chronic exercise may improve cognitive functions, its underlying neural mechanisms and whether habitual exercise is associated with individual WM ability remain unclear.

Methods

In the current study, 36 participants reported their habitual physical activity through the International Physical Activity Questionnaire (IPAQ). In addition to assessments of intelligence quotient (IQ), WM storage capacity (K score), and visuomotor coordination capacity, electroencephalogram (EEG) signals were recorded while the participants performed a WM precision task fusing conventional visual and motor retrospective cue (retro-cue) WM tasks.

Results

We found that greater amounts of and higher frequencies of vigorous-intensity exercise were highly correlated with smaller recall errors in the WM precision task. Contralateral delay activity (CDA), a well-known WM-related event-related potential (ERP) component evoked by the valid retro-cue, predicted individual behavioral recall error. Participants who met the medium or high level of IPAQ criteria (the regular exercise group) showed smaller behavioral recall error and larger CDA than participants who did not meet the criteria (the irregular exercise group). The two groups did not differ in other assessments, such as IQ, WM storage capacity, and visuomotor coordination ability.

Discussion

Habitual exercise was specifically correlated with individual differences in WM precision, rather than IQ, WM storage capacity, and visuomotor coordination ability, suggesting potential mechanisms of how modulations of chronic exercise improve cognition through visual and/or motor WM precision.