Increased Working Memory Load Research Articles

Investigating the effect of cognitive load on the intentionality bias

According to Rosset’s dual-process model of intention attribution, our judgements of intentionality can be guided either by an automatic process leading to intentional explanations of behaviour or by a higher-level and cognitively more demanding process enabling unintentional explanations of behaviour. Based on this model, under conditions of compromised cognitive capacity, individuals should judge more behaviour to be intentional rather than unintentional. This prediction was tested in one lab-based experiment and one online experiment. Specifically, we investigated whether increased working memory load would lead to higher intentionality endorsement of ambiguous action when controlling for individual differences in working memory. Results of both experiments indicated no effect of working memory load on intentionality endorsement. The implications of these results for the dual-process model of intention attribution are discussed.

Working memory load increases movement-related alpha and beta desynchronization

Working memory (WM) load has been well-documented to impair selective attention and inhibitory control. However, its effects on motor function remain insufficiently explored. To extend the existing literature, we investigated the impact of WM load on force control and movement-related brain activity. Sixteen healthy young participants performed a visual static force matching task using a pinch grip under varying WM loads. The task included low and high WM load conditions (memorizing one digit or six digits), and the precision level required to control force was adjusted by manipulating visual gain (low vs. high visual gains), with higher visual gain necessitating more precise force control. Peri-movement alpha and beta event-related desynchronization (ERD), along with force accuracy and steadiness, were measured using electroencephalography recorded over the central areas during the force control task. Results indicated that while force accuracy and steadiness significantly improved with higher visual gain, there was no significant effect of WM load on these measures. Alpha and beta ERD were greater under high than low visual gain, and also greater under high than low WM load. These findings suggest that in young adults, increased WM load leads to compensatory increases in sensorimotor cortical activity to mitigate potential declines in static force control performance that may result from the depletion of neural resources caused by WM load. Our findings extend current understanding of the interaction between WM and sensorimotor processes by offering new insights into how movement-related brain activity is influenced by heightened WM load.

Kinematic and neuromuscular characterization of cognitive involvement in gait control in healthy young adults.

The signature of cognitive involvement in gait control has rarely been studied using both kinematic and neuromuscular features. The present study aimed to address this gap. Twenty-four healthy young adults walked on an instrumented treadmill in a virtual environment under two optic flow conditions: normal (NOF) and perturbed (POF, continuous mediolateral pseudorandom oscillations). Each condition was performed under single-task and dual-task conditions of increasing difficulty (1-, 2-, 3-back). Subjective mental workload (raw NASA-TLX), cognitive performance (mean reaction time and d-prime), kinematic (steadiness, variability and complexity in the mediolateral and anteroposterior directions) and neuromuscular (duration and variability of motor primitives) control of gait were assessed. The cognitive performance and the number and composition of motor modules were unaffected by simultaneous walking, regardless of the optic flow condition. Kinematic and neuromuscular variability was greater under POF compared to NOF conditions. Young adults sought to counteract POF by rapidly correcting task-relevant gait fluctuations. The depletion of cognitive resources through dual-tasking led to reduced kinematic and neuromuscular variability and this occurred to the same extent regardless of simultaneous working memory (WM) load. Increasing WM load led to a prioritization of gait control in the mediolateral direction over the anteroposterior direction. The impact of POF on kinematic variability (step velocity) was reduced when a cognitive task was performed simultaneously, but this phenomenon was no modulated by WM load. Collectively, these results shed important light on how young adults adjust the processes involved in goal-directed locomotion when exposed to varying levels of task and environmental constraints.

To err is human- to understand error-processing is divine: Contributions of working memory and anxiety to error-related brain and pupil responses.

Both anxiety and working memory capacity appear to predict increased (more negative) error-related negativity (ERN) amplitudes, despite being inversely related to one another. Until the interactive effects of these variables on the ERN are clarified, there may be challenges posed to our ability to use the ERN as an endophenotype for anxiety, as some have suggested. The compensatory error monitoring hypothesis suggests that high trait-anxiety individuals have larger ERN amplitudes because they must employ extra, compensatory efforts to override the working memory demands of their anxiety. Yet, to our knowledge, no ERN study has employed direct manipulation of working memory demands in conjunction with direct manipulations of induced (state) anxiety. Furthermore, little is known about how these manipulations affect other measures of error processing, such as the error-related pupil dilation response and post-error behavioral adjustments. Therefore, we manipulate working memory load and anxiety in a 2 × 2 within-subjects design to examine the interactive effects of working memory load and anxiety on ERN amplitude, error-related pupil dilation response amplitude, and post-error behavior. There were no effects of our manipulations on ERN amplitude, suggesting a strong interpretation of compensatory error-processing theory. However, our worry manipulation affected post-error behavior, such that worry caused a reduction in post-error accuracy. Additionally, our working memory manipulation affected error-related PDR magnitude and the amplitude of the error-related positivity (Pe), such that increased working memory load decreased the amplitude of these responses. Implications of these results within the context of the compensatory error processing framework are discussed.

Temporal Error Monitoring Does Not Depend on Working Memory.

Working memory (WM) and metacognition has been documented to be in a reciprocal relationship. This study aims to address if temporal error monitoring performance can be diminished with increased working memory load. We hypothesized that if temporal error monitoring has commonalities with perceptual error monitoring, temporal error monitoring performance should be diminished by increased working memory load. Participants completed a temporal error monitoring task in a dual task design in which the secondary task was a letter alphabetization task. Results revealed no disrupting effect of WM load on either confidence or short-long judgments as being different metrics of temporal error monitoring ability. These results demonstrate that unlike perceptual error monitoring, WM and temporal error monitoring have distinct processing mechanisms. With this result, the current study suggests that temporal and perceptual error monitoring may partially rely on different mechanisms. Results are discussed within A Theory of Magnitude (ATOM), pacemaker-accumulator model and temporal error monitoring frameworks.

Exploring the Effects of EEG-Based Alpha Neurofeedback on Working Memory Capacity in Healthy Participants

Neurofeedback, an operant conditioning neuromodulation technique, uses information from brain activities in real-time via brain-computer interface (BCI) technology. This technique has been utilized to enhance the cognitive abilities, including working memory performance, of human beings. The aims of this study are to investigate how alpha neurofeedback can improve working memory performance in healthy participants and to explore the underlying neural mechanisms in a working memory task before and after neurofeedback. Thirty-six participants divided into the NFT group and the control group participated in this study. This study was not blinded, and both the participants and the researcher were aware of their group assignments. Increasing power in the alpha EEG band was used as a neurofeedback in the eyes-open condition only in the NFT group. The data were collected before and after neurofeedback while they were performing the N-back memory task (N = 1 and N = 2). Both groups showed improvement in their working memory performance. There was an enhancement in the power of their frontal alpha and beta activities with increased working memory load (i.e., 2-back). The experimental group showed improvements in their functional connections between different brain regions at the theta level. This effect was absent in the control group. Furthermore, brain hemispheric lateralization was found during the N-back task, and there were more intra-hemisphere connections than inter-hemisphere connections of the brain. These results suggest that healthy participants can benefit from neurofeedback and from having their brain networks changed after the training.

Neural signatures for the n-back task with different loads: An event-related potential study

The n-back task is widely used in working memory (WM) research. However, it remains unclear how the electrophysiological correlates of WM processes, the P2, N2, P300, and negative slow wave (NSW), are affected by differences in load. Specifically, while previous work has examined the P300, less attention has been paid to the other components assessing the load of the n-back paradigm. The present study aims to investigate whether other sub-processes in WM (such as inhibitory control) are as sensitive to n-back load changes as the update process by observing changes in the above event-related potential (ERP) components. The results showed poorer behavioral performance with increasing WM load. Greater NSW and smaller P300 amplitudes were elicited by n-back task with a higher load compared to that with lower load. In contrast, there was no significant effect of the n-back load on the amplitudes of P2 and N2. These findings suggest that the updating process and the maintenance process are sensitive to the n-back load change. Therefore, changes in the updating and maintenance processes should be considered when using the n-back task to manipulate the WM load in experiments. The present study may contribute to the understanding of the complexity of WM loads. Additionally, a theoretical basis for follow-up research to explore ways of improving WM performance with high load is provided.

Precision of phonological errors in aphasia supports resource models of phonological working memory in language production

ABSTRACT Working memory (WM) is critical for many cognitive functions including language production. A key feature of WM is its capacity limitation. Two models have been proposed to account for such capacity limitation: slot models and resource models. In recent years, resource models have found support in both visual and auditory perception, but do they also extend to production? We investigate this by analyzing sublexical errors from four individuals with aphasia. Using tools from computational linguistics, we first define the concept of “precision” of sublexical errors. We then demonstrate that such precision decreases with increased working memory load, i.e., word length, as predicted by resource models. Finally, we rule out alternative accounts of this effect, such as articulatory simplification. These data provide the first evidence for the applicability of the resource model to production and further point to the generalizability of this account as a model of resource division in WM.

K-means Clustering Machine Learning Approach Reveals Groups of Homogeneous Individuals with Unique Brain Activation, Task, and Performance Dynamics using fNIRS.

Wearable functional near-infrared spectroscopy (fNIRS) for measuring brain function, in terms of hemodynamic responses, is pervading our everyday life and holds the potential to reliably classify cognitive load in a naturalistic environment. However, human's brain hemodynamic response, behavior, and cognitive and task performance vary, even within and across homogeneous individuals (with same training and skill sets), which limits the reliability of any predictive model for human. In the context of high-stakes tasks, such as in military and first-responder operations, the real-time monitoring of cognitive functions and relating it to the ongoing task, performance outcomes, and behavioral dynamics of the personnel and teams is invaluable. In this work, a portable wearable fNIRS system (WearLight) developed by the author was upgraded, and an experimental protocol was designed to image the prefrontal cortex (PFC) area of the brain of 25 healthy homogeneous participants in a naturalistic environment while participants performed n-back working memory (WM) tasks with four difficulty levels. The raw fNIRS signals were processed using a signal processing pipeline to derive the brain's hemodynamic responses. An unsupervised k-means machine learning (ML) clustering approach, utilizing the task-induced hemodynamic responses as input variables, suggested three unique participant groups. Task performance in terms of % correct, % missing, reaction time, inverse efficiency score (IES), and a proposed IES was extensively evaluated for each participant and the three groups. Results showed that, on average, brain hemodynamic response increased, whereas task performance degraded, with increasing WM load. However, the regression and correlation analysis of WM task, performance, and the brain's hemodynamic responses (TPH) revealedinteresting hidden characteristics and the variation in the TPH relationship between groups. The proposed IES also served as a better scoring method that had distinct score ranges for different load levels as opposed to the overlapping scores of the traditional IES method. Results showed that the k-means clustering has the potential to find groups of individuals in an unsupervised manner using the brain's hemodynamic responses and to study the underlying relationship between the TPH in groups. Using the method presented in this paper,real-time monitoring of cognitive and task performance of soldiers, and preferentially forming small units to accomplish tasks based on the insights and goals may be helpful. The results showed that WearLight can image PFC, and this study also suggests future directions for the multi-modal body sensor network (BSN) combining advanced ML algorithms for real-time state classification, cognitive and physical performance prediction, and the mitigation of performance degradation in the high-stakes environment.

Dynamic hippocampal functional connectivity responses to varying working memory loads following total sleep deprivation.

Sleep loss with work overload can impact human cognitive performance. However, the brain's response to an increased working memory load following total sleep deprivation (TSD) remains unclear. In the present study, we focussed on the dynamic response of the hippocampus to increased working memory load before and after total sleep deprivation of 36 h. A total of 16 male participants completed a verbal working memory task under functional magnetic resonance imaging. After whole-brain activation analysis and region of interest analysis of the hippocampus, the generalised form of context-dependent psychophysiological interactions (gPPI) was used to analyse the hippocampal functional connectivity with the whole brain. The results revealed that as the working memory load increased within a small range, from 0-back to 1-back task, the left hippocampal functional connectivity decreased with the left supplementary motor area, left pars opercularis, left rolandic operculum, right superior frontal gyrus, bilateral precentral gyrus, and left middle cingulate cortex following total sleep deprivation compared with that observed in resting wakefulness. When the working memory load further increased from 1-back to 2-back task, the connectivity increased between the left hippocampus and the left superior parietal lobule as well as between the left hippocampus and right lingual gyrus after total sleep deprivation compared with that observed in resting wakefulness. Moreover, the left hippocampus gPPI effect on the left middle cingulate cortex and left superior parietal lobule could predict the behavioural test accuracy in 1-back and 2-back task, respectively, following total sleep deprivation. These findings indicated that increased working memory load after total sleep deprivation disrupts working memory processes. The brain reacts to these disruptions in a dynamic and flexible manner, involving not only brain activation but also hippocampus-related functional network connections.

Multitasking While Driving: Central Bottleneck or Problem State Interference?

The objective of this work was to investigate if visuospatial attention and working memory load interact at a central control resource or at a task-specific, information processing resource during driving. In previous multitasking driving experiments, interactions between different cognitive concepts (e.g., attention and working memory) have been found. These interactions have been attributed to a central bottleneck or to the so-called problem-state bottleneck, related to working memory usage. We developed two different cognitive models in the cognitive architecture ACT-R, which implement the central vs. problem-state bottleneck. The models performed a driving task, during which we varied visuospatial attention and working memory load. We evaluated the model by conducting an experiment with human participants and compared the behavioral data to the model's behavior. The problem-state-bottleneck model could account for decreased driving performance due to working memory load as well as increased visuospatial attentional demands as compared to the central-bottleneck model, which could not account for effects of increased working memory load. The interaction between working memory and visuospatial attention in our dual tasking experiment can be best characterized by a bottleneck in the working memory. The model results suggest that as working memory load becomes higher, drivers manage to perform fewer control actions, which leads to decreasing driving performance. Predictions about the effect of different mental loads can be used to quantify the contribution of each subtask allowing for precise assessments of the current overall mental load, which automated driving systems may adapt to.

Effects of decorative pictures on mental processing demands and learning: An EEG and eye-tracking study

Across two experiments, the effects of presenting decorative pictures (DP) alongside texts were assessed with respect to the mental processing demands during reading, learning outcomes, and subjective task experience. DP were thought to function as so-called seductive details. Eye-tracking and the electroencephalogram (EEG) were recorded during reading. Pupil dilation and the EEG theta (4–8 Hz) and alpha (8–13 Hz) frequency band power served as measures of the mental processing demands. Texts on features and habitats of animals served as learning materials. Working memory (WM) load was manipulated as an additional factor during reading. Neither the additional WM load nor DP had significant effects on learning outcomes, albeit in both experiments the increased WM load affected the physiological measures as expected. DP with a few different motifs generally were not very seductive (Experiment 1). DP with more diverse motifs resulted in increased mental processing demands as indicated by the EEG alpha frequency band power (Experiment 2). Subjective task experience was positively affected by the DP present in Experiment 2 as indicated by higher subjective ratings of interestingness, comprehensibility, emotionality, and aesthetical pleasantness when DP were present. In sum, the study indicates that DP with diverse motifs may function as seductive details, increasing mental processing demands without detrimental effects on learning outcomes.

Evaluating the Effect of Increasing Working Memory Load on EEG-Based Functional Brain Networks

Purpose: Working Memory (WM) plays a crucial role in many cognitive functions of the human brain. Examining how the inter-regional connectivity and characteristics of functional brain networks modulate with increasing WM load could lead to a more in-depth understanding of the WM system. Materials and Methods: To investigate the effect of WM load alterations on the inter-regional synchronization and functional network characteristics, we used Electroencephalogram (EEG) data recorded from 21 healthy participants during an n-back task with three load levels (0-back, 2-back, and 3-back). The networks were constructed based on the weighted Phase Lag Index (wPLI) in the theta, alpha, beta, low-gamma, and high-gamma frequency bands. After constructing the fully connected, weighted, and undirected networks, the node-to-node connections, graph-theory metrics consisting of mean Clustering coefficient (C), characteristic path Length (L), and node strength were analyzed by statistical tests. Results: It was revealed that in the presence of WM load (2- and 3-back tasks) compared with the WM-free condition (0-back task) within the alpha range, the Inter-Regional Functional Connectivity (IRFC), functional integration, functional segregation, and node strength in channels located at the frontal, parietal and occipital regions were significantly reduced. In the high-gamma band, IRFC was significantly higher in the difficult task (3-back) compared to the easy and moderate tasks (0- and 2-back). Besides, locally clustered connections were significantly increased in 3-back relative to the 2-back task. Conclusion: Inter-regional alpha synchronization and alpha-band network metrics can distinguish between the WM and WM-free tasks. In contrast, phase synchronization of high-gamma oscillations can differentiate between the levels of WM load, which demonstrates the potential of the phase-based functional connectivity and brain network metrics for predicting the WM load level.

The Spatiotemporal Neural Dynamics of Intersensory Attention Capture of Salient Stimuli: A Large-Scale Auditory-Visual Modeling Study.

The spatiotemporal dynamics of the neural mechanisms underlying endogenous (top-down) and exogenous (bottom-up) attention, and how attention is controlled or allocated in intersensory perception are not fully understood. We investigated these issues using a biologically realistic large-scale neural network model of visual-auditory object processing of short-term memory. We modeled and incorporated into our visual-auditory object-processing model the temporally changing neuronal mechanisms for the control of endogenous and exogenous attention. The model successfully performed various bimodal working memory tasks, and produced simulated behavioral and neural results that are consistent with experimental findings. Simulated fMRI data were generated that constitute predictions that human experiments could test. Furthermore, in our visual-auditory bimodality simulations, we found that increased working memory load in one modality would reduce the distraction from the other modality, and a possible network mediating this effect is proposed based on our model.

Chunking by social relationship in working memory

ABSTRACT Working memory (WM) uses knowledge and relations to organize and store multiple items in fewer structured units, or chunks. We investigated: (a) whether a crowd that exceeds the WM capacity is retained better if individuals can be grouped in social chunks; and (b) what counts as a social chunk: two individuals involved in a meaningful interaction or just spatially close and face-to-face. In a delayed change-detection task, participants were more accurate in reporting changes in arrays involving facing (vs. non-facing) dyads whether they depicted meaningful interactions or not (Experiments 1, 2 and 4). This advantage survived a secondary task that increased WM load, only when facing dyads formed meaningful interactions (Experiment 3). Thus, WM uses representation of interaction to chunk crowds in social groups. The mere face-to-face positioning is sufficient to trigger social chunking, although without a semantic anchor this process is fainter and more susceptible to interference.

P203. Emotional Working Memory in Individuals With Borderline Personality Disorder

Borderline Personality Disorder (BPD) is a serious mental illness characterized by executive functioning deficits, specifically in working memory (WM). It remains unclear if these deficits scale with increasing WM load and how emotional arousal impacts this relationship.

Fronto-medial theta coordinates posterior maintenance of working memory content

How does the human brain manage multiple bits of information to guide goal-directed behavior? Successful working memory (WM) functioning has consistently been linked to oscillatory power in the theta frequency band (4-8Hz) over fronto-medial cortex (fronto-medial theta [FMT]). Specifically, FMT is thought to reflect the mechanism of an executive sub-system that coordinates maintenance of memory contents in posterior regions. However, direct evidence for the role of FMT in controlling specific WM content is lacking. Here, we collected high-density electroencephalography (EEG) data while participants engaged in WM-dependent tasks and then used multivariate decoding methods to examine WM content during the maintenance period. Engagement of WM was accompanied by a focal increase in FMT. Importantly, decoding of WM content was driven by posterior sites, which, in turn, showed increased functional theta coupling with fronto-medial channels. Finally, we observed a significant slowing of FMT frequency with increasing WM load, consistent with the hypothesized broadening of a theta "duty cycle" to accommodate additional WM items. Together, these findings demonstrate that frontal theta orchestrates posterior maintenance of WM content. Moreover, the observed frequency slowing elucidates the function of FMT oscillations by specifically supporting phase-coding accounts of WM.

The role of sex in the association between cannabis use and working memory-related brain activity.

Although cannabis use patterns differ between men and women, studies on sex differences on the effects of cannabis on the brain and cognitive control are largely lacking. Working memory (WM) is a component of cognitive control believed to be involved in the development and maintenance of addiction. In this study, we evaluated the association between cannabis use and WM (load) related brain activity in a large sample, enabling us to assess sex effects in this association. The brain activity of 104 frequent cannabis users (63% men) and 85 controls (53% men) was recorded during an N‐back WM task. Behavioral results showed a significant interaction between WM load and group for both accuracy and reaction time, with cannabis users showing a relatively larger decrease in performance with increasing WM load. Cannabis users compared to controls showed a relatively smaller reduction in WM (load) related activity in the precuneus and posterior cingulate cortex at higher WM load. This WM (load) related activity was not associated with performance nor cannabis use and related problems. An exploratory analysis showed higher WM‐related activity in the superior frontal gyrus in men compared to women. While cannabis users showed higher WM (load) related activity in central nodes of the default mode network, this was not directly attributable to group specific worsening of performance under higher cognitive load. Further research is necessary to assess whether observed group differences increase with higher cognitive load, how group differences relate to measures of cannabis use, and how sex affects these group differences.

Sex-Based Differences in Functional Brain Activity During Working Memory in Survivors of Pediatric Acute Lymphoblastic Leukemia.

BackgroundLong-term survivors of pediatric acute lymphoblastic leukemia are at elevated risk for neurocognitive deficits and corresponding brain dysfunction. This study examined sex-based differences in functional neuroimaging outcomes in acute lymphoblastic leukemia survivors treated with chemotherapy alone.MethodsFunctional magnetic resonance imaging (fMRI) and neurocognitive testing were obtained in 123 survivors (46% male; median [min-max] age = 14.2 years [8.3-26.5 years]; time since diagnosis = 7.7 years [5.1-12.5 years]) treated on the St. Jude Total XV treatment protocol. Participants performed the n-back working memory task in a 3 T scanner. Functional neuroimaging data were processed (realigned, slice time corrected, normalized, smoothed) and analyzed using statistical parametric mapping with contrasts for 1-back and 2-back conditions, which reflect varying degrees of working memory and task load. Group-level fMRI contrasts were stratified by sex and adjusted for age and methotrexate exposure. Statistical tests were 2-sided (P < .05 statistical significance threshold).ResultsRelative to males, female survivors exhibited less activation (ie, reduced blood oxygen dependent–level signals) in the right parietal operculum, supramarginal gyrus and inferior occipital gyrus, and bilateral superior frontal medial gyrus during increased working memory load (family-wise error–corrected P = .004 to .008, adjusting for age and methotrexate dose). Female survivors were slower to correctly respond to the 2-back condition than males (P < .05), though there were no differences in overall accuracy. Performance accuracy was negatively correlated with fMRI activity in female survivors (Pearson’s r = −0.39 to −0.29, P = .001 to .02), but not in males.ConclusionsThese results suggest the working memory network is more impaired in female survivors than male survivors, which may contribute to ongoing functional deficits.

Do cognitive load and ADHD traits affect the tendency to prioritise social information in scenes?

We report two experiments investigating the effect of working memory (WM) load on selective attention. Experiment 1 was a modified version of Lavie et al. and confirmed that increasing memory load disrupted performance in the classic flanker task. Experiment 2 used the same manipulation of WM load to probe attention during the viewing of complex scenes while also investigating individual differences in attention deficit hyperactivity disorder (ADHD) traits. In the image-viewing task, we measured the degree to which fixations targeted each of two crucial objects: (1) a social object (a person in the scene) and (2) a non-social object of higher or lower physical salience. We compared the extent to which increasing WM load would change the pattern of viewing of the physically salient and socially salient objects. If attending to the social item requires greater default voluntary top-down resources, then the viewing of social objects should show stronger modulation by WM load compared with viewing of physically salient objects. The results showed that the social object was fixated to a greater degree than the other object (regardless of physical salience). Increased salience drew fixations away from the background leading to slightly increased fixations on the non-social object, without changing fixations on the social object. Increased levels of ADHD-like traits were associated with fewer fixations on the social object, but only in the high-salient, low-load condition. Importantly, WM load did not affect the number of fixations on the social object. Such findings suggest rather surprisingly that attending to a social area in complex stimuli is not dependent on the availability of voluntary top-down resources.