Theta-gamma-coupling as predictor of working memory performance in young and elderly healthy people

The relationship between working memory (WM) and neuronal oscillations can be studied in detail using brain stimulation techniques, which provide a method for modulating these oscillations and thus influencing WM. The endogenous coupling between the amplitude of gamma oscillations and the phase of theta oscillations is crucial for cognitive control. Theta/gamma peak-coupled transcranial alternating current stimulation (TGCp-tACS) can modulate this coupling and thus influence WM performance. This study investigated the effects of TGCp-tACS on WM in older adults and compared their responses with those of younger participants from our previous work who underwent the same experimental design. Twenty-eight older subjects underwent both TGCp-tACS and sham stimulation sessions at least 72 h apart. Resting-state electroencephalography (EEG) was recorded before and after the interventions, and a WM task battery with five different WM tasks was performed during the interventions to assess various WM components. Outcomes measured included WM task performance (e.g., accuracy, reaction time (RT)) and changes in power spectral density (PSD) in different frequency bands. TGCp-tACS significantly decreased accuracy and RT on the 10- and 14-point Sternberg tasks and increased RT on the Digit Symbol Substitution Test in older adults. In contrast, younger participants showed a significant increase in accuracy only on the 14-item Sternberg task. Electrophysiological analysis revealed a decrease in delta and theta PSD and an increase in high gamma PSD in both younger and older participants after verum stimulation. In conclusion, theta-gamma coupling is essential for WM and modulation of this coupling affects WM performance. The effects of TGCp-tACS on WM vary with age due to natural brain changes. To better support older adults, the study suggests several strategies to improve cognitive function, including: Adjusting stimulation parameters, applying stimulation to two sites, conducting multiple sessions, and using brain imaging techniques for precise targeting.

Improving working memory by electrical stimulation and cross-frequency coupling

Working memory (WM) is essential for the temporary storage and processing of information required for complex cognitive tasks and relies on neuronal theta and gamma oscillations. Given the limited capacity of WM, researchers have investigated various methods to improve it, including transcranial alternating current stimulation (tACS), which modulates brain activity at specific frequencies. One particularly promising approach is theta-gamma peak-coupled-tACS (TGCp-tACS), which simulates the natural interaction between theta and gamma oscillations that occurs during cognitive control in the brain. The aim of this study was to improve WM in healthy young adults with TGCp-tACS, focusing on both behavioral and neurophysiological outcomes. Thirty-one participants completed five WM tasks under both sham and verum stimulation conditions. Electroencephalography (EEG) recordings before and after stimulation showed that TGCp-tACS increased power spectral density (PSD) in the high-gamma region at the stimulation site, while PSD decreased in the theta and delta regions throughout the cortex. From a behavioral perspective, although no significant changes were observed in most tasks, there was a significant improvement in accuracy in the 14-item Sternberg task, indicating an improvement in phonological WM. In conclusion, TGCp-tACS has the potential to promote and improve the phonological component of WM. To fully realize the cognitive benefits, further research is needed to refine the stimulation parameters and account for individual differences, such as baseline cognitive status and hormonal factors.

Cerebellar Transcranial Magnetic Stimulation (TMS) Impairs Visual Working Memory

An increasing body of evidence points to the involvement of the cerebellum in cognition. Specifically, previous studies have shown that the superior and inferior portions of the cerebellum are involved in different verbal working memory (WM) mechanisms as part of two separate cerebro-cerebellar loops for articulatory rehearsal and phonological storage mechanisms. In comparison, our understanding of the involvement of the cerebellum in visual WM remains limited. We have previously shown that performance in verbal WM is disrupted by single-pulse transcranial magnetic stimulation (TMS) of the right superior cerebellum. The present study aimed to expand on this notion by exploring whether the inferior cerebellum is similarly involved in visual WM. Here, we used fMRI-guided, double-pulse TMS to probe the necessity of left superior and left inferior cerebellum in visual WM. We first conducted an fMRI localizer using the Sternberg visual WM task, which yielded targets in left superior and inferior cerebellum. Subsequently, TMS stimulation of these regions at the end of the encoding phase resulted in decreased accuracy in the visual WM task. Differences in the visual WM deficits caused by stimulation of superior and inferior left cerebellum raise the possibility that these regions are involved in different stages of visual WM.

Managing Increased Cognitive Load in a Guided Search

In the Sternberg item recognition task and its variants, an individual's mean reaction time increases with the number of items to be retained in the memory set. An increase in reaction time has also been seen when a secondary task was added. The usual interpretation for this increased reaction time is that adding cognitive load makes tasks more difficult. In a series of three experiments, we manipulated cognitive load through increases in the memory set or through a second task. In each experiment, high cognitive load was associated with higher mean response times but a reduced slope, based on the target position in a series of probes. Thus, in a Sternberg task with multiple word targets and multiple word probes, participants searched more efficiently per probe under high load than under low load. This pattern was replicated with the addition of a working memory task requiring participants to calculate a cumulative price based on the price per target word item. By considering both initial response times and reaction time slopes in large memory sets, this study provides a challenge to the traditional interpretation of cognitive load effects on search performance.

Network-Targeted, Multi-site Direct Cortical Stimulation Enhances Working Memory by Modulating Phase Lag of Low-Frequency Oscillations

Working memory is mediated by the coordinated activation of frontal and parietal cortices occurring in the theta and alpha frequency ranges. Here, we test whether electrically stimulating frontal and parietal regions at the frequency of interaction is effective in modulating working memory. We identify working memory nodes that are functionally connected in theta and alpha frequency bands and intracranially stimulate both nodes simultaneously in participants performing working memory tasks. We find that in-phase stimulation results in improvements in performance compared to sham stimulation. In addition, in-phase stimulation results in decreased phase lag between regions within working memory network, while anti-phase stimulation results in increased phase lag, suggesting that shorter phase lag in oscillatory connectivity may lead to better performance. The results support the idea that phase lag may play a key role in information transmission across brain regions. Thus, brain stimulation strategies to improve cognition may require targeting multiple nodes of brain networks.

An Integrative Clustering Approach to tDCS Individual Response Variability in Cognitive Performance: Beyond a Null Effect on Working Memory

Despite the growing interest in the use of transcranial direct current stimulation (tDCS) for the modulation of human cognitive function, there are contradictory findings regarding the cognitive benefits of this technique. Inter-individual response variability to tDCS may play a significant role. We explored the effects of anodal versus sham tDCS over the left prefrontal cortex (LPFC) on working memory performance, taking into account the inter-individual variability. Twenty-nine healthy volunteers received an 'offline' anodal tDCS (1.5 mA, 15 min) to the left prefrontal cortex (F3 electrode site) in an intra-individual, cross-over, sham-controlled experimental design. n-back and Sternberg task performance was assessed before (baseline), immediately after tDCS administration (T1) and 5 min post-T1 (T2). We applied an integrative clustering approach to characterize both the group and individual responses to tDCS, as well as identifying naturally occurring subgroups that may be present within the total sample. Anodal tDCS failed to improve working memory performance in the total sample. Cluster analysis identified a subgroup of 'responders' who significantly improved their performance after anodal (vs. sham) stimulation, although not to a greater extent than the best baseline or sham condition. The proportion of 'responders' ranged from 15% to 59% across task conditions and behavioral outputs. Our findings show a high inter-individual variability of the tDCS response, suggesting that the use of tCDS may not be an effective tool to improve working memory performance in healthy subjects. We propose that the use of clustering methods is more suitable in identifying 'responders' and for evaluating the efficacy of this technique.

Different Topological Properties of EEG-Derived Networks Describe Working Memory Phases as Revealed by Graph Theoretical Analysis

Several non-invasive imaging methods have contributed to shed light on the brain mechanisms underlying working memory (WM). The aim of the present study was to depict the topology of the relevant EEG-derived brain networks associated to distinct operations of WM function elicited by the Sternberg Item Recognition Task (SIRT) such as encoding, storage, and retrieval in healthy, middle age (46 ± 5 years) adults. High density EEG recordings were performed in 17 participants whilst attending a visual SIRT. Neural correlates of WM were assessed by means of a combination of EEG signal processing methods (i.e., time-varying connectivity estimation and graph theory), in order to extract synthetic descriptors of the complex networks underlying the encoding, storage, and retrieval phases of WM construct. The group analysis revealed that the encoding phase exhibited a significantly higher small-world topology of EEG networks with respect to storage and retrieval in all EEG frequency oscillations, thus indicating that during the encoding of items the global network organization could “optimally” promote the information flow between WM sub-networks. We also found that the magnitude of such configuration could predict subject behavioral performance when memory load increases as indicated by the negative correlation between Reaction Time and the local efficiency values estimated during the encoding in the alpha band in both 4 and 6 digits conditions. At the local scale, the values of the degree index which measures the degree of in- and out- information flow between scalp areas were found to specifically distinguish the hubs within the relevant sub-networks associated to each of the three different WM phases, according to the different role of the sub-network of regions in the different WM phases. Our findings indicate that the use of EEG-derived connectivity measures and their related topological indices might offer a reliable and yet affordable approach to monitor WM components and thus theoretically support the clinical assessment of cognitive functions in presence of WM decline/impairment, as it occurs after stroke.

Grounding Verbal Working Memory: The Case of Serial Order

The maintenance of serial order in verbal working memory (WM) is a major unsolved puzzle in cognitive science. Here we review a series of studies showing that serial order in verbal WM closely interacts with spatial processing. Accordingly, we outline the “mental whiteboard hypothesis,” which postulates that serial order in verbal WM is grounded in the spatial attention system. Specifically, serial context in verbal WM is provided by binding the memoranda to coordinates within an internal, spatially defined system within which (internal) spatial attention is at play to the purpose of searching for and retrieving information. Challenges and opportunities to be considered in future studies are discussed.

In defence of high-speed memory scanning

This paper reviews some of the evidence that bears on the existence of a mental high-speed serial exhaustive scanning process (SES) used by humans to interrogate the active memory of a set of items to determine whether it contains a test item. First proposed in the 1960s, based on patterns of reaction times (RTs), numerous later studies supported, elaborated, extended, and limited the generality of SES, while critics claimed that SES never occurred, that predictions from SES were violated, and that other mechanisms produced the RT patterns that led to the idea. I show that some of these claims result from ignoring variations in experimental procedure that produce superficially similar but quantitatively different RT patterns and that, for the original procedures, the most frequently repeated claims that predictions are violated are false. I also discuss evidence against the generality of competing theories of active-memory interrogation, especially those that depend on discrimination of directly accessible "memory-strength". Some of this evidence has been available since the 1960s but has been ignored by some proponents of alternative theories. Other evidence presented herein is derived from results of one relevant experiment described for the first time, results of another described in more detail than heretofore, and new analyses of old data. Knowledge of brain function acquired during the past half century has increased the plausibility of SES.

THE CONCLUSION

SES is alive and well, but many associated puzzles merit further investigation, suggestions for which are offered.

Cognitive state monitoring and the design of adaptive instruction in digital environments: lessons learned from cognitive workload assessment using a passive brain-computer interface approach

According to Cognitive Load Theory (CLT), one of the crucial factors for successful learning is the type and amount of working-memory load (WML) learners experience while studying instructional materials. Optimal learning conditions are characterized by providing challenges for learners without inducing cognitive over- or underload. Thus, presenting instruction in a way that WML is constantly held within an optimal range with regard to learners' working-memory capacity might be a good method to provide these optimal conditions. The current paper elaborates how digital learning environments, which achieve this goal can be developed by combining approaches from Cognitive Psychology, Neuroscience, and Computer Science. One of the biggest obstacles that needs to be overcome is the lack of an unobtrusive method of continuously assessing learners' WML in real-time. We propose to solve this problem by applying passive Brain-Computer Interface (BCI) approaches to realistic learning scenarios in digital environments. In this paper we discuss the methodological and theoretical prospects and pitfalls of this approach based on results from the literature and from our own research. We present a strategy on how several inherent challenges of applying BCIs to WML and learning can be met by refining the psychological constructs behind WML, by exploring their neural signatures, by using these insights for sophisticated task designs, and by optimizing algorithms for analyzing electroencephalography (EEG) data. Based on this strategy we applied machine-learning algorithms for cross-task classifications of different levels of WML to tasks that involve studying realistic instructional materials. We obtained very promising results that yield several recommendations for future work.