Simultaneous EEG-fMRI during a working memory task: modulations in low and high frequency bands

Cortical and white matter substrates supporting visuospatial working memory

OBJECTIVE

In tasks involving new visuospatial information, we rely on working memory, supported by a distributed brain network. We investigated the dynamic interplay between brain regions, including cortical and white matter structures, to understand how neural interactions change with different memory loads and trials, and their subsequent impact on working memory performance.

METHODS

Patients undertook a task of immediate spatial recall during intracranial EEG monitoring. We charted the dynamics of cortical high-gamma activity and associated functional connectivity modulations in white matter tracts.

RESULTS

Elevated memory loads were linked to enhanced functional connectivity via occipital longitudinal tracts, yet decreased through arcuate, uncinate, and superior-longitudinal fasciculi. As task familiarity grew, there was increased high-gamma activity in the posterior inferior-frontal gyrus (pIFG) and diminished functional connectivity across a network encompassing frontal, parietal, and temporal lobes. Early pIFG high-gamma activity was predictive of successful recall. Including this metric in a logistic regression model yielded an accuracy of 0.76.

CONCLUSIONS

Optimizing visuospatial working memory through practice is tied to early pIFG activation and decreased dependence on irrelevant neural pathways.

SIGNIFICANCE

This study expands our knowledge of human adaptation for visuospatial working memory, showing the spatiotemporal dynamics of cortical network modulations through white matter tracts.

Extended wakefulness alters the relationship between EEG oscillations and performance in a sustained attention task

During drowsiness, maintaining consistent attention becomes difficult, leading to behavioural lapses. Bursts of oscillations in the electroencephalogram (EEG) might predict such lapses, given that alpha bursts increase during inattention and theta bursts increase with time spent awake. Paradoxically, however, alpha bursts decrease with time awake and theta bursts increase during focussed attention and cognitive tasks. Therefore, we investigated to what extent theta and alpha bursts predicted performance in a sustained attention task, either when well rested (baseline, BL) or following 20 h of extended wakefulness (EW). High-density EEG was measured in 18 young adults, and the timing of bursts was related to trial outcomes (fast, slow, and lapse trials). To increase the likelihood of lapses, the task was performed under soporific conditions. Against expectations, alpha bursts were more likely before fast trials and less likely before lapses at baseline, although the effect was substantially reduced during extended wakefulness. Theta bursts showed no significant relationship to behavioural outcome either at baseline or extended wakefulness. However, following exploratory analyses, we found that large-amplitude theta and alpha bursts were more likely to be followed by lapse trials during extended wakefulness but not baseline. In summary, alpha bursts during baseline anticipated better trial outcomes, whereas large-amplitude theta and alpha bursts during extended wakefulness anticipated worse outcomes. Therefore, neither theta nor alpha bursts maintain a consistent relationship with behaviour under different levels of overall vigilance.

Neurovascular coupling in eye-open-eye-close task and resting state: Spectral correspondence between concurrent EEG and fMRI

Neurovascular coupling serves as an essential neurophysiological mechanism in functional neuroimaging, which is generally presumed to be robust and invariant across different physiological states, encompassing both task engagement and resting state. Nevertheless, emerging evidence suggests that neurovascular coupling may exhibit state dependency, even in normal human participants. To investigate this premise, we analyzed the cross-frequency spectral correspondence between concurrently recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, utilizing them as proxies for neurovascular coupling during the two conditions: an eye-open-eye-close (EOEC) task and a resting state. We hypothesized that given the state dependency of neurovascular coupling, EEG-fMRI spectral correspondences would change between the two conditions in the visual system. During the EOEC task, we observed a negative phase-amplitude-coupling (PAC) between EEG alpha-band and fMRI visual activity. Conversely, in the resting state, a pronounced amplitude-amplitude-coupling (AAC) emerged between EEG and fMRI signals, as evidenced by the spectral correspondence between the EEG gamma-band of the midline occipital channel (Oz) and the high-frequency fMRI signals (0.15-0.25 Hz) in the visual network. This study reveals distinct scenarios of EEG-fMRI spectral correspondence in healthy participants, corroborating the state-dependent nature of neurovascular coupling.

Open-Source Tools to Analyze Temporal and Spatial Properties of Local Field Potentials

Analysis of local field potentials (LFPs) is important for understanding how ensemble neurons function as a network in a specific region of the brain. Despite the availability of tools for analyzing LFP data, there are some missing features such as analysis of high frequency oscillations (HFOs) and spatial properties. In addition, accessibility of most tools is restricted due to closed source code and/or high costs. To overcome these issues, we have developed two freely available tools that make temporal and spatial analysis of LFP data easily accessible. The first tool, hfoGUI (High Frequency Oscillation Graphical User Interface), allows temporal analysis of LFP data and scoring of HFOs such as ripples and fast ripples which are important in understanding memory function and neurological disorders. To complement the temporal analysis tool, a second tool, SSM (Spatial Spectral Mapper), focuses on the spatial analysis of LFP data. The SSM tool maps the spectral power of LFPs as a function of subject's position in a given environment allowing investigation of spatial properties of LFP signal. Both hfoGUI and SSM are open-source tools that have unique features not offered by any currently available tools, and allow visualization and spatio-temporal analysis of LFP data.

Cross-frequency coupling in cortico-hippocampal networks supports the maintenance of sequential auditory information in short-term memory

It has been suggested that cross-frequency coupling in cortico-hippocampal networks enables the maintenance of multiple visuo-spatial items in working memory. However, whether this mechanism acts as a global neural code for memory retention across sensory modalities remains to be demonstrated. Intracranial EEG data were recorded while drug-resistant patients with epilepsy performed a delayed matched-to-sample task with tone sequences. We manipulated task difficulty by varying the memory load and the duration of the silent retention period between the to-be-compared sequences. We show that the strength of theta-gamma phase amplitude coupling in the superior temporal sulcus, the inferior frontal gyrus, the inferior temporal gyrus, and the hippocampus (i) supports the short-term retention of auditory sequences; (ii) decodes correct and incorrect memory trials as revealed by machine learning analysis; and (iii) is positively correlated with individual short-term memory performance. Specifically, we show that successful task performance is associated with consistent phase coupling in these regions across participants, with gamma bursts restricted to specific theta phase ranges corresponding to higher levels of neural excitability. These findings highlight the role of cortico-hippocampal activity in auditory short-term memory and expand our knowledge about the role of cross-frequency coupling as a global biological mechanism for information processing, integration, and memory in the human brain.

Fast & scrupulous: Gesture-based alarms improve accuracy and reaction times under various mental workload levels. An ERSP study

In high-risk environments, fast and accurate responses to warning systems are essential to efficiently handle emergency situations. The aim of the present study was twofold: 1) investigating whether hand action videos (i.e., gesture alarms) trigger faster and more accurate responses than text alarm messages (i.e., written alarms), especially when mental workload (MWL) is high; and 2) investigating the brain activity in response to both types of alarms as a function of MWL. Regardless of MWL, participants (N = 28) were found to be both faster and more accurate when responding to gesture alarms than to written alarms. Brain electrophysiological results suggest that this greater efficiency might be due to a facilitation of the action execution, reflected by the decrease in mu and beta power observed around the response time window observed at C3 and C4 electrodes. These results suggest that gesture alarms may improve operators' performances in emergency situations.

Effect of homeostatic pressure and circadian arousal on the storage and executive components of working memory: Evidence from EEG power spectrum

Diurnal fluctuations in working memory (WM) performance, characterized by task-specific peaks and troughs, are likely attributed to the differential regulation of WM subcomponents by interactions between circadian and homeostatic processes. The current study aimed to investigate the independent effects of circadian and homeostatic processes on the storage and executive subcomponents of WM. We assessed the change in frontal-midline theta (FMT) power supporting WM executive component and posterior alpha/beta power supporting WM storage during N-back tasks in the morning, midafternoon with and without a nap from 31 healthy adults. The results suggested that when the accumulated sleep homeostasis was alleviated in the midafternoon by a daytime nap, higher ACC, less number of omissions, and a stronger increase in FMT power from the no nap to nap conditions. Compared to the morning, a stronger decrease in posterior alpha power, and posterior beta power (only in the 3-back task), was observed in the no-nap condition because of circadian arousal regulation. These findings suggest that the circadian process primarily influences the storage aspect of WM supported by posterior alpha and beta activity, while sleep homeostasis has a greater impact on the execution aspect supported by FMT activity.

Examination of distraction and discomfort caused by using glare monitors: a simultaneous electroencephalography and eye-tracking study

Background

Since the COVID-19 pandemic started, remote work and education and digital display use have become more prevalent. However, compared with printed material, digital displays cause more eye fatigue and may decrease task performance. For instance, the reflections on the monitor can cause discomfort or distraction, particularly when glare monitors are used with black backgrounds.

Methods

This study simultaneously uses electroencephalography (EEG) and an eye-tracker to measure the possible negative effects of using a glare monitor on the illegibility of sentences.

Results

The experiment results showed no difference in reading time and subjective illegibility rating between glare and non-glare monitors. However, with glare monitors, eye fixation when reading lasted longer. Further, EEG beta (15-20 Hz) power variations suggested that the participants were less engaged in the reading task when a glare monitor was used with a black background.

Conclusions

These results indicate that the negative effects of using a glare monitor are subtle but certainly present. They also show that physiological measures such as EEG and eye tracking can assess the subtle effects in an objective manner, even if behavioral measures such as subjective illegibility ratings or reading time may not show the differences.

Is Hypnotic Induction Necessary to Experience Hypnosis and Responsible for Changes in Brain Activity?

The relevance of formal hypnotic induction to the experience of trance and its neural correlates is not clear, in that hypnotizability, beliefs and expectation of hypnosis may play a major role. The aim of the study was assessing the EEG brain activity of participants with high (highs) or low hypnotizability scores (lows), aware of their hypnotizability level and informed that the session will include simple relaxation, formal hypnotic induction and neutral hypnosis. A total of 16 highs and 15 lows (according to the Stanford Hypnotic Susceptibility Scale, form A) were enrolled. Their EEGs were recorded during consecutive conditions of open/closed-eyes relaxation, hypnotic induction, neutral hypnosis and post hypnosis not interrupted by interviews. The studied variables were theta, alpha and gamma power spectral density (PSD), and the Determinism (DET) and Entropy (ENT) of the EEG signal Multidimensional Recurrence Plot (mRP). Highs reported significantly greater changes in their state of consciousness than lows across the session. The theta, alpha and gamma PSD did not exhibit condition-related changes in both groups. The Alpha PSD was larger in highs than in lows on midline sites, and the different sides/regions' theta and gamma PSD were observed in the two groups independently from conditions. ENT showed no correlation with hypnotizability, while DET positively correlated with hypnotizability during hypnosis. In conclusion, the relevance of formal hypnotic induction to the experience of trance may be scarce in highs, as they are aware of their hypnotizability scores and expecting hypnosis. Cognitive processing varies throughout the session depending on the hypnotizability level.

Electrophysiological and Clinical Predictors of Methylphenidate, Guanfacine, and Combined Treatment Outcomes in Children With Attention-Deficit/Hyperactivity Disorder

OBJECTIVE

The combination of d-methylphenidate and guanfacine (an α-2A agonist) has emerged as a potential alternative to either monotherapy in children with attention-deficit/hyperactivity disorder (ADHD), but it is unclear what predicts response to these treatments. This study is the first to investigate pretreatment clinical and electroencephalography (EEG) profiles as predictors of treatment outcome in children randomized to these different medications.

METHOD

A total of 181 children with ADHD (aged 7-14 years; 123 boys) completed an 8-week randomized, double-blind, comparative study with d-methylphenidate, guanfacine, or combined treatments. Pretreatment assessments included ratings on ADHD, anxiety, and oppositional behavior. EEG activity from cortical sources localized within midfrontal and midoccipital regions was measured during a spatial working memory task with encoding, maintenance, and retrieval phases. Analyses tested whether pretreatment clinical and EEG measures predicted treatment-related change in ADHD severity.

RESULTS

Higher pretreatment hyperactivity-impulsivity and oppositional symptoms and lower anxiety predicted greater ADHD improvements across all medication groups. Pretreatment event-related midfrontal beta power predicted treatment outcome with combined and monotherapy treatments, albeit in different directions. Weaker beta modulations predicted improvements with combined treatment, whereas stronger modulation during encoding and retrieval predicted improvements with d-methylphenidate and guanfacine, respectively. A multivariate model including EEG and clinical measures explained twice as much variance in ADHD improvement with guanfacine and combined treatment (R2= 0.34-0.41) as clinical measures alone (R2 = 0.14-.21).

CONCLUSION

We identified treatment-specific and shared predictors of response to different pharmacotherapies in children with ADHD. If replicated, these findings would suggest that aggregating information from clinical and brain measures may aid personalized treatment decisions in ADHD.

CLINICAL TRIAL REGISTRATION INFORMATION

Single Versus Combination Medication Treatment for Children With Attention Deficit Hyperactivity Disorder; https://clinicaltrials.gov; NCT00429273.

Online Left-Hemispheric In-Phase Frontoparietal Theta tACS Modulates Theta-Band EEG Source-Based Large-Scale Functional Network Connectivity in Patients with Schizophrenia: A Randomized, Double-Blind, Sham-Controlled Clinical Trial

EEG studies indicated that schizophrenia patients had increased resting-state theta-band functional connectivity, which was associated with negative symptoms. We recently published the first study showing that theta (6 Hz) transcranial alternating current stimulation (tACS) over left prefrontal and parietal cortices during a working memory task for accentuating frontoparietal theta-band synchronization (in-phase theta-tACS) reduced negative symptoms in schizophrenia patients. Here, we hypothesized that in-phase theta-tACS can modulate theta-band large-scale networks connectivity in schizophrenia patients. In this randomized, double-blind, sham-controlled trial, patients received twice-daily, 2 mA, 20-min sessions of in-phase theta-tACS for 5 consecutive weekdays (n = 18) or a sham stimulation (n = 18). Resting-state electroencephalography data were collected at baseline, end of stimulation, and at one-week follow-up. Exact low resolution electromagnetic tomography (eLORETA) was used to compute intra-cortical activity. Lagged phase synchronization (LPS) was used to measure whole-brain source-based functional connectivity across 84 cortical regions at theta frequency (5-7 Hz). EEG data from 35 patients were analyzed. We found that in-phase theta-tACS significantly reduced the LPS between the posterior cingulate (PC) and the parahippocampal gyrus (PHG) in the right hemisphere only at the end of stimulation relative to sham (p = 0.0009, corrected). The reduction in right hemispheric PC-PHG LPS was significantly correlated with negative symptom improvement at the end of the stimulation (r = 0.503, p = 0.039). Our findings suggest that in-phase theta-tACS can modulate theta-band large-scale functional connectivity pertaining to negative symptoms. Considering the failure of right hemispheric PC-PHG functional connectivity to predict improvement in negative symptoms at one-week follow-up, future studies should investigate whether it can serve as a surrogate of treatment response to theta-tACS.

Modulation of theta and gamma oscillations during familiarization with previously unknown music

Repeated listening to unknown music leads to gradual familiarization with musical sequences. Passively listening to musical sequences could involve an array of dynamic neural responses in reaching familiarization with the musical excerpts. This study elucidates the dynamic brain response and its variation over time by investigating the electrophysiological changes during the familiarization with initially unknown music. Twenty subjects were asked to familiarize themselves with previously unknown 10 s classical music excerpts over three repetitions while their electroencephalogram was recorded. Dynamic spectral changes in neural oscillations are monitored by time-frequency analyses for all frequency bands (theta: 5-9 Hz, alpha: 9-13 Hz, low-beta: 13-21 Hz, high beta: 21-32 Hz, and gamma: 32-50 Hz). Time-frequency analyses reveal sustained theta event-related desynchronization (ERD) in the frontal-midline and the left pre-frontal electrodes which decreased gradually from 1st to 3rd time repetition of the same excerpts (frontal-midline: 57.90 %, left-prefrontal: 75.93 %). Similarly, sustained gamma ERD decreased in the frontal-midline and bilaterally frontal/temporal areas (frontal-midline: 61.47 %, left-frontal: 90.88 %, right-frontal: 87.74 %). During familiarization, the decrease of theta ERD is superior in the first part (1-5 s) whereas the decrease of gamma ERD is superior in the second part (5-9 s) of music excerpts. The results suggest that decreased theta ERD is associated with successfully identifying familiar sequences, whereas decreased gamma ERD is related to forming unfamiliar sequences.

The Theta Paradox: 4-8 Hz EEG Oscillations Reflect Both Sleep Pressure and Cognitive Control

Human electroencephalographic (EEG) oscillations characterize specific behavioral and vigilance states. The frequency of these oscillations is typically sufficient to distinguish a given state; however, theta oscillations (4-8 Hz) have instead been found in near-opposite conditions of drowsiness during sleep deprivation and alert cognitive control. While the latter has been extensively studied and is often referred to as "frontal midline theta," (fmTheta) the former has been investigated far less but is considered a marker for sleep pressure during wake. In this study we investigated to what extent theta oscillations differed during cognitive tasks and sleep deprivation. We measured high-density EEG in 18 young healthy adults (nine female) performing six tasks under three levels of sleep deprivation. We found both cognitive load and sleep deprivation increased theta power in medial prefrontal cortical areas; however, sleep deprivation caused additional increases in theta in many other, predominantly frontal, areas. The sources of sleep deprivation theta (sdTheta) were task dependent, with a visual-spatial task and short-term memory (STM) task showing the most widespread effects. Notably, theta was highest in supplementary motor areas during passive music listening, and highest in the inferior temporal cortex (responsible for object recognition) during a spatial game. Furthermore, while changes in task performance were correlated with increases in theta during sleep deprivation, this relationship was not specific to the EEG of the same task and did not survive correction for multiple comparisons. Altogether, these results suggest that both during sleep deprivation and cognition theta oscillations may preferentially occur in cortical areas not involved in ongoing behavior.SIGNIFICANCE STATEMENT Electroencephalographic (EEG) research in sleep has often remained separate from research in cognition. This has led to two incompatible interpretations of the function of theta brain oscillations (4-8 Hz): that they reflect local sleep events during sleep deprivation, or that they reflect cognitive processing during tasks. With this study, we found no fundamental differences between theta oscillations during cognition and theta during sleep deprivation that would suggest different functions. Instead, our results indicate that in both cases, theta oscillations are generated by cortical areas not required for ongoing behavior. Therefore, at least in humans, theta may reflect either cortical disengagement or inhibition.

Decoding working memory-related information from repeated psychophysiological EEG experiments using convolutional and contrastive neural networks

OBJECTIVE

Extracting reliable information from EEG signals is difficult because the low signal-to-noise ratio and significant intersubject variability seriously hinder statistical analyses. However, recent advances in explainable machine learning open a new strategy to address this problem.

APPROACH

The current study evaluates this approach using results from the classification and decoding of electrical brain activity associated with information retention. We designed four neural network models differing in architecture, training strategies, and input representation to classify single experimental trials of a working memory task.

MAIN RESULTS

Our best models achieved an accuracy of 65.29$±0.76 and Matthews correlation coefficient of 0.288±0.018, outperforming the reference model trained on the same data. The highest correlation between classification score and behavioral performance was 0.36 (p=0.0007). Using analysis of input perturbation, we estimated the importance of EEG channels and frequency bands in the task at hand. The set of essential features identified for each network varies. We identified a subset of features common to all models that identified brain regions and frequency bands consistent with current neurophysiological knowledge of the processes critical to attention and working memory. Finally, we proposed sanity checks to examine further the robustness of each model's set of features.

SIGNIFICANCE

Our results indicate that explainable deep learning is a powerful tool for decoding information from EEG signals. It is crucial to train and analyze a range of models to identify stable and reliable features. Our results highlight the need for explainable modeling as the model with the highest accuracy appeared to use residual artifactual activity.

Magnetoencephalography Hyperscanning Evidence of Differing Cognitive Strategies Due to Social Role During Auditory Communication

Auditory communication is an essential form of human social interaction. However, the intra-brain cortical-oscillatory drivers of auditory communication exchange remain relatively unexplored. We used improvisational music performance to simulate and capture the creativity and turn-taking dynamics of natural auditory communication. Using magnetoencephalography (MEG) hyperscanning in musicians, we targeted brain activity during periods of music communication imagery, and separately analyzed theta (5–7 Hz), alpha (8–13 Hz), and beta (15–29 Hz) source-level activity using a within-subjects, two-factor approach which considered the assigned social role of the subject (leader or follower) and whether communication responses were improvisational (yes or no). Theta activity related to improvisational communication and social role significantly interacted in the left isthmus cingulate cortex. Social role was furthermore differentiated by pronounced occipital alpha and beta amplitude increases suggestive of working memory retention engagement in Followers but not Leaders. The results offer compelling evidence for both musical and social neuroscience that the cognitive strategies, and correspondingly the memory and attention-associated oscillatory brain activities of interlocutors during communication differs according to their social role/hierarchy, thereby indicating that social role/hierarchy needs to be controlled for in social neuroscience research.

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 (4–8 Hz) 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.

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FMT power supports WM functions

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During WM performance, posterior/parietal regions are coupled with FMT

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Multivariate decoding of WM content is mediated by these same posterior channels

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Frontal theta frequency slows with WM load supporting phase-coding models

Using a Novel Functional Brain Network Approach to Locate Important Nodes for Working Memory Tasks

Working Memory (WM) is a short-term memory for processing and storing information. When investigating WM mechanisms using Electroencephalogram (EEG), its rhythmic synchronization properties inevitably become one of the focal features. To further leverage these features for better improve WM task performance, this paper uses a novel algorithm: Weight K-order propagation number (WKPN) to locate important brain nodes and their coupling characteristic in different frequency bands while subjects are proceeding French word retaining tasks, which is an intriguing but original experiment paradigm. Based on this approach, we investigated the node importance of PLV brain networks under different memory loads and found that the connectivity between frontal and parieto-occipital lobes in theta and beta frequency bands enhanced with increasing memory load. We used the node importance of the brain network as a feature vector of the SVM to classify different memory load states, and the highest classification accuracy of 95% is obtained in the beta band. Compared to the Weight degree centrality (WDC) and Weight Page Rank (WPR) algorithm, the SVM with the node importance of the brain network as the feature vector calculated by the WKPN algorithm has higher classification accuracy and shorter running time. It is concluded that the algorithm can effectively spot active central hubs so that researchers can later put more energy to study these areas where active hubs lie in such as placing Transcranial alternating current stimulation (tACS).

Cognitive and emotional regulation processes of spontaneous facial self-touch are activated in the first milliseconds of touch: Replication of previous EEG findings and further insights

Spontaneously touching one’s own face (sFST) is an everyday behavior that occurs in people of all ages, worldwide. It is—as opposed to actively touching the own face—performed without directing one’s attention to the action, and it serves neither instrumental (scratching, nose picking) nor communicative purposes. These sFST have been discussed in the context of self-regulation, emotional homeostasis, working memory processes, and attention focus. Even though self-touch research dates back decades, neuroimaging studies of this spontaneous behavior are basically nonexistent. To date, there is only one electroencephalography study that analyzed spectral power changes before and after sFST in 14 participants. The present study replicates the previous study on a larger sample. Sixty participants completed a delayed memory task of complex haptic relief stimuli while distracting sounds were played. During the retention interval 44 of the participants exhibited spontaneous face touch. Spectral power analyses corroborated the results of the replicated study. Decreased power shortly before sFST and increased power right after sFST indicated an involvement of regulation of attentional, emotional, and working memory processes. Additional analyses of spectral power changes during the skin contact phase of sFST revealed that significant neurophysiological changes do not occur while skin contact is in progress but at the beginning of sFST (movement toward face and initial skin contact). The present findings clearly illustrate the complexity of sFST and that the specific trigger mechanisms and functions of this spontaneous behavior need to be further investigated in controlled, experimental studies.

High-definition transcranial direct current stimulation of the occipital cortices induces polarity dependent effects within the brain regions serving attentional reorientation

Numerous brain stimulation studies have targeted the posterior parietal cortex, a key hub of the attention network, to manipulate attentional reorientation. However, the impact of stimulating brain regions earlier in the pathway, including early visual regions, is poorly understood. In this study, 28 healthy adults underwent three high‐definition transcranial direct current stimulation (HD‐tDCS) visits (i.e., anodal, cathodal, and sham). During each visit, they completed 20 min of occipital HD‐tDCS and then a modified Posner task during magnetoencephalography (MEG). MEG data were transformed into the time‐frequency domain and significant oscillatory events were imaged using a beamformer. Oscillatory response amplitude values were extracted from peak voxels in the whole‐brain maps and were statistically compared. Behaviorally, we found that the participants responded slowly when attention reallocation was needed (i.e., the validity effect), irrespective of the stimulation condition. Our neural findings indicated that cathodal HD‐tDCS was associated with significantly reduced theta validity effects in the occipital cortices, as well as reduced alpha validity effects in the left occipital and parietal cortices relative to anodal HD‐tDCS. Additionally, anodal occipital stimulation significantly increased gamma amplitude in right occipital regions relative to cathodal and sham stimulation. Finally, we also found a negative correlation between the alpha validity effect and reaction time following anodal stimulation. Our findings suggest that HD‐tDCS of the occipital cortices has a polarity dependent impact on the multispectral neural oscillations serving attentional reorientation in healthy adults, and that such effects may reflect altered local GABA concentrations in the neural circuitry serving attentional reorientation.

A Routine Electroencephalography Monitoring System for Automated Sports-Related Concussion Detection

Cases of concussions in the United States keep increasing and are now up to 2 million to 3 million incidents per year. Although concussions are recoverable and usually not life-threatening, the degree and rate of recovery may vary depending on age, severity of the injury, and past concussion history. A subsequent concussion before full recovery may lead to more-severe brain damage and poorer outcomes. Electroencephalography (EEG) recordings can identify brain dysfunctionality and abnormalities, such as after a concussion. Routine EEG monitoring can be a convenient method for reducing unreported injuries and preventing long-term damage, especially among groups with a greater risk of experiencing a concussion, such as athletes participating in contact sports. Because of the relative availability of EEG compared to other brain-imaging techniques (e.g., functional magnetic resonance imaging), the use of EEG monitoring is growing for various neurological disorders. In this longitudinal study, EEG was analyzed from 4 football athletes before their athletic season and also within 7 days of concussion. Compared to a control group of 4 additional athletes, a concussion was detected with up to 99.5% accuracy using EEG recordings in the Theta-Alpha band. Classifiers that use data from only a subset of the EEG electrodes providing reliable detection are also proposed. The most effective classifiers used EEG recordings from the Central scalp region in the Beta band and over the Temporal scalp region using the Theta-Alpha band. This proof-of-concept study and preliminary findings suggest that EEG monitoring may be used to identify a sports-related concussion occurrence with a high level of accuracy and thus reduce the chance of unreported concussion.

Effects of Ketamine and Midazolam on Simultaneous EEG/fMRI Data During Working Memory Processes

Reliable measures of cognitive brain activity from functional neuroimaging techniques may provide early indications of efficacy in clinical trials. Functional magnetic resonance imaging and electroencephalography provide complementary spatiotemporal information and simultaneous recording of these two modalities can remove inter-session drug response and environment variability. We sought to assess the effects of ketamine and midazolam on simultaneous electrophysiological and hemodynamic recordings during working memory (WM) processes. Thirty participants were included in a placebo-controlled, three-way crossover design with ketamine and midazolam. Compared to placebo, ketamine administration attenuated theta power increases and alpha power decreases and midazolam attenuated low beta band decreases to increasing WM load. Additionally, ketamine caused larger blood-oxygen-dependent (BOLD) signal increases in the supplementary motor area and angular gyrus, and weaker deactivations of the default mode network (DMN), whereas no difference was found between midazolam and placebo. Ketamine administration caused positive temporal correlations between frontal-midline theta (fm-theta) power and the BOLD signal to disappear and attenuated negative correlations. However, the relationship between fm-theta and the BOLD signal from DMN areas was maintained in some participants during ketamine administration, as increasing theta strength was associated with stronger BOLD signal reductions in these areas. The presence of, and ability to manipulate, both positive and negative associations between the BOLD signal and fm-theta suggest the presence of multiple fm-theta components involved in WM processes, with ketamine administration disrupting one or more of these theta-linked WM strategies.

Disrupted Functional Rich-Club Organization of the Brain Networks in Children with Attention-Deficit/Hyperactivity Disorder, a Resting-State EEG Study

Growing evidence indicates that disruptions in the brain's functional connectivity play an important role in the pathophysiology of ADHD. The present study investigates alterations in resting-state EEG source connectivity and rich-club organization in children with inattentive (ADHDI) and combined (ADHDC) ADHD compared with typically developing children (TD) under the eyes-closed condition. EEG source analysis was performed by eLORETA in different frequency bands. The lagged phase synchronization (LPS) and graph theoretical metrics were then used to examine group differences in the topological properties and rich-club organization of functional networks. Compared with the TD children, the ADHDI children were characterized by a widespread significant decrease in delta and beta LPS, as well as increased theta and alpha LPS in the left frontal and right occipital regions. The ADHDC children displayed significant increases in LPS in the central, temporal and posterior areas. Both ADHD groups showed small-worldness properties with significant increases and decreases in the network degree in the θ and β bands, respectively. Both subtypes also displayed reduced levels of network segregation. Group differences in rich-club distribution were found in the central and posterior areas. Our findings suggest that resting-state EEG source connectivity analysis can better characterize alterations in the rich-club organization of functional brain networks in ADHD patients.

Proof-of-concept evidence for trimodal simultaneous investigation of human brain function

The link between spatial (where) and temporal (when) aspects of the neural correlates of most psychological phenomena is not clear. Elucidation of this relation, which is crucial to fully understand human brain function, requires integration across multiple brain imaging modalities and cognitive tasks that reliably modulate the engagement of the brain systems of interest. By overcoming the methodological challenges posed by simultaneous recordings, the present report provides proof‐of‐concept evidence for a novel approach using three complementary imaging modalities: functional magnetic resonance imaging (fMRI), event‐related potentials (ERPs), and event‐related optical signals (EROS). Using the emotional oddball task, a paradigm that taps into both cognitive and affective aspects of processing, we show the feasibility of capturing converging and complementary measures of brain function that are not currently attainable using traditional unimodal or other multimodal approaches. This opens up unprecedented possibilities to clarify spatiotemporal integration of brain function.

What's in Your Gamma? Activation of the Ventral Fronto-Parietal Attentional Network in Response to Distracting Sounds

Auditory attention operates through top-down (TD) and bottom-up (BU) mechanisms that are supported by dorsal and ventral brain networks, respectively, with the main overlap in the lateral prefrontal cortex (lPFC). A good TD/BU balance is essential to be both task-efficient and aware of our environment, yet it is rarely investigated. Oscillatory activity is a novel method to probe the attentional dynamics with evidence that gamma activity (>30 Hz) could signal BU processing and thus would be a good candidate to support the activation of the ventral BU attention network. Magnetoencephalography data were collected from 21 young adults performing the competitive attention task, which enables simultaneous investigation of BU and TD attentional mechanisms. Distracting sounds elicited an increase in gamma activity in regions of the BU ventral network. TD attention modulated these gamma responses in regions of the inhibitory cognitive control system: the medial prefrontal and anterior cingulate cortices. Finally, distracting-sound-induced gamma activity was synchronous between the auditory cortices and several distant brain regions, notably the lPFC. We provide novel insight into the role of gamma activity 1) in supporting the activation of the ventral BU attention network and 2) in subtending the TD/BU attention balance in the PFC.

Working memory load modulates oscillatory activity and the distribution of fast frequencies across frontal theta phase during working memory maintenance

Working memory (WM) is a keystone of our cognitive abilities. Increasing load has been shown to dampen its performance and affect oscillatory neural activity in different frequency bands. Nevertheless, mixed results regarding fast frequencies activity and a lack of research on WM load modulations of cross-frequency phase-amplitude coupling mechanisms preclude a better understanding of the impact of increased WM load levels on brain activity as well as inter-regional communication and coordination supporting WM processes. Hence, we analyzed the EEG activity of 25 participants while performing a delayed-matching-to-sample (DMS) WM task with three WM load levels. Current density power and distribution at the source level for theta, beta, and gamma frequencies during the task's delay period were compared for each pair of WM load conditions. Results showed maximal increases of theta activity in frontal areas and of fast frequencies' activity in posterior regions with WM load, showing the involvement of frontal theta activity in WM maintenance and the control of attentional resources and visual processing by beta and gamma activity. To study whether WM load modulates communication between cortical areas, posterior beta and gamma amplitudes distribution across frontal theta phase was also analysed for those areas showing the largest significant WM load modulations. Higher beta activity amplitude at bilateral cuneus and right middle occipital gyrus, and higher gamma activity amplitude at bilateral posterior cingulate were observed during frontal theta phase peak in low than high memory load conditions. Moreover, greater fast beta amplitude at the right postcentral gyrus was observed during theta phase trough at right middle frontal gyrus in high than low memory load conditions. These results show that WM load modulates whether interregional communication occurs during theoretically optimal or non-optimal time windows, depending on the demands of frontal control of posterior areas required to perform the task successfully.

EEG-fMRI Signal Coupling Is Modulated in Subjects With Mild Cognitive Impairment and Amyloid Deposition

Cognitive impairment indicates disturbed brain physiology which can be due to various mechanisms including Alzheimer's pathology. Combined functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) recordings (EEG-fMRI) can assess the interplay between complementary measures of brain activity and EEG changes to be localized to specific brain regions. We used a two-step approach, where we first examined changes related to a syndrome of mild cognitive impairment irrespective of pathology and then studied the specific impact of amyloid pathology. After detailed clinical and neuropsychological characterization as well as a positron emission tomography (PET) scans with the tracer 11-[C]-Pittsburgh Compound B to estimate cerebral amyloid deposition, 14 subjects with mild cognitive impairment (MCI) (mean age 75.6 SD: 8.9) according to standard criteria and 21 cognitively healthy controls (HCS) (mean age 71.8 SD: 4.2) were assessed with EEG-fMRI. Thalamo-cortical alpha-fMRI signal coupling was only observed in HCS. Additional EEG-fMRI signal coupling differences between HCS and MCI were observed in parts of the default mode network, salience network, fronto-parietal network, and thalamus. Individuals with significant cerebral amyloid deposition (amyloid-positive MCI and HCS combined compared to amyloid-negative HCS) displayed abnormal EEG-fMRI signal coupling in visual, fronto-parietal regions but also in the parahippocampus, brain stem, and cerebellum. This finding was paralleled by stronger absolute fMRI signal in the parahippocampus and weaker absolute fMRI signal in the inferior frontal gyrus in amyloid-positive subjects. We conclude that the thalamocortical coupling in the alpha band in HCS more closely reflects previous findings observed in younger adults, while in MCI there is a clearly aberrant coupling in several networks dominated by an anticorrelation in the posterior cingulate cortex. While these findings may broadly indicate physiological changes in MCI, amyloid pathology was specifically associated with abnormal fMRI signal responses and disrupted coupling between brain oscillations and fMRI signal responses, which especially involve core regions of memory: the hippocampus, para-hippocampus, and lateral prefrontal cortex.

Working Memory Decline in Alzheimer's Disease Is Detected by Complexity Analysis of Multimodal EEG-fNIRS

Alzheimer's disease (AD) is characterized by working memory (WM) failures that can be assessed at early stages through administering clinical tests. Ecological neuroimaging, such as Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests to support AD early diagnosis within clinical settings. Multimodal EEG-fNIRS could measure brain activity along with neurovascular coupling (NC) and detect their modifications associated with AD. Data analysis procedures based on signal complexity are suitable to estimate electrical and hemodynamic brain activity or their mutual information (NC) during non-structured experimental paradigms. In this study, sample entropy of whole-head EEG and frontal/prefrontal cortex fNIRS was evaluated to assess brain activity in early AD and healthy controls (HC) during WM tasks (i.e., Rey-Osterrieth complex figure and Raven's progressive matrices). Moreover, conditional entropy between EEG and fNIRS was evaluated as indicative of NC. The findings demonstrated the capability of complexity analysis of multimodal EEG-fNIRS to detect WM decline in AD. Furthermore, a multivariate data-driven analysis, performed on these entropy metrics and based on the General Linear Model, allowed classifying AD and HC with an AUC up to 0.88. EEG-fNIRS may represent a powerful tool for the clinical evaluation of WM decline in early AD.

Oscillatory brain activity and maintenance of verbal and visual working memory: A systematic review

Brain oscillations likely play a significant role in the storage of information in working memory (WM). Despite the wide popularity of the topic, current attempts to summarize the research in the field are narrative reviews. We address this gap by providing a descriptive systematic review, in which we investigated oscillatory correlates of maintenance of verbal and visual information in WM. The systematic approach enabled us to challenge some common views popularized by previous research. The identified literature (100 EEG/MEG studies) highlighted the importance of theta oscillations in verbal WM: frontal midline theta enhanced with load in most verbal studies, while more equivocal results have been obtained in visual studies. Increasing WM load affected alpha activity in most studies, but the direction of the effect was inconsistent: the ratio of studies that found alpha increase versus decrease with increasing load was 80/20% in the verbal WM domain and close to 60/40% in the visual domain. Alpha asymmetry (left < right) was a common finding in both verbal and visual WM studies. Beta and gamma activity studies yielded the least convincing data: a diversity in the spatial and frequency distribution of beta activity prevented us from making a coherent conclusion; gamma rhythm was virtually neglected in verbal WM studies with no systematic support for sustained gamma changes during the delay in EEG studies in general.

Electroencephalography source localization analysis in epileptic children during a visual working-memory task

We localize the sources of brain activity of children with epilepsy based on electroencephalograph (EEG) recordings acquired during a visual discrimination working memory task. For the numerical solution of the inverse problem, with the aid of age-specific MRI scans processed from a publicly available database, we use and compare three regularization numerical methods, namely the standardized low resolution brain electromagnetic tomography (sLORETA), the weighted minimum norm estimation (wMNE) and the dynamic statistical parametric mapping (dSPM). We show that all three methods provide the same spatio-temporal patterns of differences between the groups of epileptic and control children. In particular, our analysis reveals statistically significant differences between the two groups in regions of the parietal cortex indicating that these may serve as "biomarkers" for diagnostic purposes and ultimately localized treatment.

Electrophysiology of the Human Superior Temporal Sulcus during Speech Processing

The superior temporal sulcus (STS) is a crucial hub for speech perception and can be studied with high spatiotemporal resolution using electrodes targeting mesial temporal structures in epilepsy patients. Goals of the current study were to clarify functional distinctions between the upper (STSU) and the lower (STSL) bank, hemispheric asymmetries, and activity during self-initiated speech. Electrophysiologic properties were characterized using semantic categorization and dialog-based tasks. Gamma-band activity and alpha-band suppression were used as complementary measures of STS activation. Gamma responses to auditory stimuli were weaker in STSL compared with STSU and had longer onset latencies. Activity in anterior STS was larger during speaking than listening; the opposite pattern was observed more posteriorly. Opposite hemispheric asymmetries were found for alpha suppression in STSU and STSL. Alpha suppression in the STS emerged earlier than in core auditory cortex, suggesting feedback signaling within the auditory cortical hierarchy. STSL was the only region where gamma responses to words presented in the semantic categorization tasks were larger in subjects with superior task performance. More pronounced alpha suppression was associated with better task performance in Heschl's gyrus, superior temporal gyrus, and STS. Functional differences between STSU and STSL warrant their separate assessment in future studies.

Extraction of Common Task Features in EEG-fMRI Data Using Coupled Tensor-Tensor Decomposition

The fusion of simultaneously recorded EEG and fMRI data is of great value to neuroscience research due to the complementary properties of the individual modalities. Traditionally, techniques such as PCA and ICA, which rely on strong non-physiological assumptions such as orthogonality and statistical independence, have been used for this purpose. Recently, tensor decomposition techniques such as parallel factor analysis have gained more popularity in neuroimaging applications as they are able to inherently contain the multidimensionality of neuroimaging data and achieve uniqueness in decomposition without making strong assumptions. Previously, the coupled matrix-tensor decomposition (CMTD) has been applied for the fusion of the EEG and fMRI. Only recently the coupled tensor-tensor decomposition (CTTD) has been proposed. Here for the first time, we propose the use of CTTD of a 4th order EEG tensor (space, time, frequency, and participant) and 3rd order fMRI tensor (space, time, participant), coupled partially in time and participant domains, for the extraction of the task related features in both modalities. We used both the sensor-level and source-level EEG for the coupling. The phase shifted paradigm signals were incorporated as the temporal initializers of the CTTD to extract the task related features. The validation of the approach is demonstrated on simultaneous EEG-fMRI recordings from six participants performing an N-Back memory task. The EEG and fMRI tensors were coupled in 9 components out of which seven components had a high correlation (more than 0.85) with the task. The result of the fusion recapitulates the well-known attention network as being positively, and the default mode network working negatively time-locked to the memory task.

Frequency-specific neural synchrony in autism during memory encoding, maintenance and recognition

Working memory impairment is associated with symptom severity and poor functional outcome in autistic individuals, and yet the neurobiology underlying such deficits is poorly understood. Neural oscillations are an area of investigation that can shed light on this issue. Theta and alpha oscillations have been found consistently to support working memory in typically developing individuals and have also been shown to be functionally altered in people with autism. While there is evidence, largely from functional magnetic resonance imaging studies, that neural processing underlying working memory is altered in autism, there remains a dearth of information concerning how sub-processes supporting working memory (namely encoding, maintenance and recognition) are impacted. In this study, we used magnetoencephalography to investigate inter-regional theta and alpha brain synchronization elicited during the widely used one-back task across encoding, maintenance and recognition in 24 adults with autism and 30 controls. While both groups performed comparably on the working-memory task, we found process- and frequency-specific differences in networks recruited between groups. In the theta frequency band, both groups used similar networks during encoding and recognition, but different networks specifically during maintenance. In comparison, the two groups recruited distinct networks across encoding, maintenance and recognition in alpha that showed little overlap. These differences may reflect a breakdown of coherent theta and alpha synchronization that supports mnemonic functioning, or in the case of alpha, impaired inhibition of task-irrelevant neural processing. Thus, these data provide evidence for specific theta and widespread alpha synchrony alterations in autism, and underscore that a detailed examination of the sub-processes that comprise working memory is warranted for a complete understanding of cognitive impairment in this population.

Modulation of attention networks serving reorientation in healthy aging

Orienting attention to behaviorally relevant stimuli is essential for everyday functioning and mainly involves activity in the dorsal and ventral frontoparietal networks. Many studies have shown declines in the speed and accuracy of attentional reallocation with advancing age, but the underlying neural dynamics remain less understood. We investigated this age-related decline using magnetoencephalography (MEG) and a Posner task in 94 healthy adults (22-72 years old). MEG data were examined in the time-frequency domain, and significant oscillatory responses were imaged using a beamformer. We found that participants responded slower when attention reallocation was needed (i.e., the validity effect) and that this effect was positively correlated with age. We also found age-related validity effects on alpha activity in the left parietal and beta in the left frontal-eye fields from 350-950 ms. Overall, stronger alpha and beta responses were observed in younger participants during attention reallocation trials, but this pattern was reversed in the older participants. Interestingly, this alpha validity effect fully mediated the relationship between age and behavioral performance. In conclusion, older adults were slower in reorienting attention and exhibited age-related alterations in alpha and beta responses within parietal and frontal regions, which may reflect increased task demands depleting their compensatory resources.

Assessment of mental workload based on multi-physiological signals

BACKGROUND:

Mental workload is one of the contributing factors to human errors in road accidents or other potentially adverse incidents.

OBJECTIVE:

This research probes the effects of mental workload on the electroencephalographic (EEG) and electrocardiogram (ECG) of subjects in visual monitoring tasks, based on which a comprehensive evaluation model for mental workload is established effectively.

METHODS:

Three degrees of mental workload were obtained by monitoring tasks with different levels of difficulty. 20 healthy subjects were selected to take part in the research.

RESULTS:

The subjective scores showed a significant increase with the increase of task difficulty, meanwhile the reaction time (RT) increased and the accuracy decreased significantly, which proved the validity of three degrees of mental workload induced. For the EEG parameters, a significant decrease of θ energy was found in Frontal, Parietal and Occipital with the increase of level of mental workload, as well as a significant decrease of α energy in Frontal, Central and Occipital, meanwhile a significant increase of β energy occurred in Frontal and Occipital. There was a significant decrease of α/θ in Occipital, and significant increases of θ/β and (α+β)/θ in Frontal, Central and Occipital, meanwhile (α+θ)/β and WPE decreased significantly in Frontal and Occipital. Among the ECG parameters, it was shown that Mean RR, RMSSD, HF_norm and SampEn decreased significantly with the increase of task difficulty, while LF_norm and LF/HF showed significant increases. These EEG indictors in Occipital and ECG indictors were chosen and constituted a multidimensional original sample. Principal Component Analysis (PCA) was used to extract the principal elements and decreased the dimension of sample space in order to simplify the calculation, based on which an effective classification model with accuracy of 80% was achieved by support vector machine (SVM).

CONCLUSION:

This study demonstrates that the proposed algorithm can be applied to mental workload monitoring.

Is learning scale-free? Chemistry learning increases EEG fractal power and changes the power law exponent

Learning in chemistry and other areas of science involves developing one's mental models of invisible processes and manipulating temporal and spatial domains during visual information processing. While some aspects learning have been well studied by EEG (e.g., theta and gamma oscillations), the role of spontaneous and scale-free brain activity remains unclear. We used a continuous chemistry learning EEG paradigm to explore how scale-free brain activity is related learning. We found a learning effect in participants (N = 22) with an increase in test accuracy (learning gain) and decrease in test question response times in a counterbalanced pre/post-test experiment. In the brain we found increased overall (mixed) broadband power (1-50 Hz) during learning compared to rest. We then used the IRASA method to separate oscillatory and fractal (i.e. scale-free) spectral components and observed an increase in low-frequency oscillatory band powers during learning. More importantly, we found that fractal power increased during the learning sessions relative to oscillatory power. Finally, the structure of the fractal power spectra (PLE) correlated to the individual participants' learning gains. These findings support the importance of scale-free activity for learning from a complex visual paradigm. We tentatively hypothesize that this fractal component is involved in integrating the different time scales of the learning material with those of the spontaneous activity during learning and mental model shaping.

Analgesic Effects of Compression at Trigger Points Are Associated With Reduction of Frontal Polar Cortical Activity as Well as Functional Connectivity Between the Frontal Polar Area and Insula in Patients With Chronic Low Back Pain: A Randomized Trial

Background

Compression of myofascial trigger points (MTrPs) in muscles is reported to reduce chronic musculoskeletal pain. Although the prefrontal cortex (PFC) is implicated in development of chronic pain, the mechanisms of how MTrP compression at low back regions affects PFC activity remain under debate. In this study, we investigated effects of MTrP compression on brain hemodynamics and EEG oscillation in subjects with chronic low back pain.

Methods

The study was a prospective, randomized, parallel-group trial and an observer and subject-blinded clinical trial. Thirty-two subjects with chronic low back pain were divided into two groups: subjects with compression at MTrPs (n = 16) or those with non-MTrPs (n = 16). Compression at MTrP or non-MTrP for 30 s was applied five times, and hemodynamic activity (near-infrared spectroscopy; NIRS) and EEGs were simultaneously recorded during the experiment.

Results

The results indicated that compression at MTrPs significantly (1) reduced subjective pain (P < 0.05) and increased the pressure pain threshold (P < 0.05), (2) decreased the NIRS hemodynamic activity in the frontal polar area (pPFC) (P < 0.05), and (3) increased the current source density (CSD) of EEG theta oscillation in the anterior part of the PFC (P < 0.05). CSD of EEG theta oscillation was negatively correlated with NIRS hemodynamic activity in the pPFC (P < 0.05). Furthermore, functional connectivity in theta bands between the medial pPFC and insula cortex was significantly decreased in the MTrP group (P < 0.05). The functional connectivity between those regions was positively correlated with subjective low back pain (P < 0.05).

Discussion

The results suggest that MTrP compression at the lumbar muscle modulates pPFC activity and functional connectivity between the pPFC and insula, which may relieve chronic musculoskeletal pain.

Trial registration

This trial was registered at University Hospital Medical Information Network Clinical Trials Registry (UMIN000033913) on 27 August 2018, at https://upload.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000038660.

A Comparison of Mental Workload in Individuals with Transtibial and Transfemoral Lower Limb Loss during Dual-Task Walking under Varying Demand

OBJECTIVES

This study aimed to evaluate the influence of lower limb loss (LL) on mental workload by assessing neurocognitive measures in individuals with unilateral transtibial (TT) versus those with transfemoral (TF) LL while dual-task walking under varying cognitive demand.

METHODS

Electroencephalography (EEG) was recorded as participants performed a task of varying cognitive demand while being seated or walking (i.e., varying physical demand).

RESULTS

The findings revealed both groups of participants (TT LL vs. TF LL) exhibited a similar EEG theta synchrony response as either the cognitive or the physical demand increased. Also, while individuals with TT LL maintained similar performance on the cognitive task during seated and walking conditions, those with TF LL exhibited performance decrements (slower response times) on the cognitive task during the walking in comparison to the seated conditions. Furthermore, those with TF LL neither exhibited regional differences in EEG low-alpha power while walking, nor EEG high-alpha desynchrony as a function of cognitive task difficulty while walking. This lack of alpha modulation coincided with no elevation of theta/alpha ratio power as a function of cognitive task difficulty in the TF LL group.

CONCLUSIONS

This work suggests that both groups share some common but also different neurocognitive features during dual-task walking. Although all participants were able to recruit neural mechanisms critical for the maintenance of cognitive-motor performance under elevated cognitive or physical demands, the observed differences indicate that walking with a prosthesis, while concurrently performing a cognitive task, imposes additional cognitive demand in individuals with more proximal levels of amputation.

Working Memory Capacity Is Negatively Associated with Memory Load Modulation of Alpha Oscillations in Retention of Verbal Working Memory

Working memory capacity (WMC) measures the amount of information that can be maintained online in the face of distraction. Past work has shown that the efficiency with which the frontostriatal circuit filters out task-irrelevant distracting information is positively correlated with WMC. Recent work has demonstrated a role of posterior alpha oscillations (8-13 Hz) in providing a sensory gating mechanism. We investigated the relationship between memory load modulation of alpha power and WMC in two verbal working memory experiments. In both experiments, we found that posterior alpha power increased with memory load during memory, in agreement with previous reports. Across individuals, the degree of alpha power modulation by memory load was negatively associated with WMC, namely, the higher the WMC, the less alpha power was modulated by memory load. After the administration of topiramate, a drug known to affect alpha oscillations and have a negative impact on working memory function, the negative correlation between memory load modulation of alpha power and WMC was no longer statistically significant but still somewhat detectable. These results suggest that (1) individuals with low WMC demonstrate stronger alpha power modulation by memory load, reflecting possibly an increased reliance on sensory gating to suppress task-irrelevant information in these individuals, in contrast to their high WMC counterparts who rely more on frontal areas to perform this function and (2) this negative association between memory load modulation of alpha oscillations and WMC is vulnerable to drug-related cognitive disruption.

Detecting Mental Workload in Surgical Teams Using a Wearable Single-Channel Electroencephalographic Device

OBJECTIVE

To assess the sensitivity of an electroencephalographic (EEG)-based index, the prefrontal beta power, to quantify the mental workload in surgeons in real scenarios. Such EEG-based index might offer unique and unbiased measures of overload, a crucial factor when designing learning and training surgical programs.

DESIGN

The experiment followed a 2 × 2 × 2 within subjects design with 3 factors: (1) Surgical Role during the surgery (primary surgeon vs. assistant surgeon), (2) the Surgical Procedure (laparo-endoscopic single-site [LESS] surgery vs. multiport laparoscopic surgery [MPS]), and (3) the Suturing Techniques (interrupted vs. continuous suture).

SETTING

The study was carried out at the Advanced Multi-Purpose Simulation and Technological Innovation Complex situated at IAVANTE (Granada, Spain).

METHODS

Four surgical teams (primary surgeon and assistant surgeon, experts in MPS) performed 8 surgical exercises on porcine models, under different task complexities. They performed 2 suturing techniques (continuous and interrupted), employing a low complex procedure (MPS) and a high complex procedure (LESS). Surgeons acted as the primary surgeon during half of the exercises, and, as the assistant surgeon, during the rest of them. Simultaneously, we monitored EEG prefrontal EEG beta power spectra of both surgeons, using 2 synchronized wearable EEG devices. We also collected performance and subjective data.

RESULTS

Surgical complexity modulated prefrontal beta power. LESS surgery caused significant higher prefrontal beta power for both suturing techniques for both surgical roles which indicates higher demands than MPS. Perceived task complexity, overall surgical evaluation, and laparoscopic execution time confirmed EEG-based results. Finally, subjective ratings of surgical complexity differentiated between surgical roles within the same exercise, even when prefrontal beta power did not.

CONCLUSIONS

To detect mental overload when surgeons are engaged with complex surgeries, real or simulated, is still guesswork. EEG-based indices have great potential as objective and nonintrusive measures to assess mental overload in surgeons. Furthermore, EEG-based indices might play a relevant role in monitoring surgeons and residents' cognitive state during their training.

Cognitive reappraisal capacity mediates the relationship between prefrontal recruitment during reappraisal of anger-eliciting events and paranoia-proneness

Difficulties in emotion regulation, particularly in using adaptive regulation strategies such as cognitive reappraisal, are a commonly observed correlate of paranoia. While it has been suggested that poor implementation of cognitive reappraisal in dealing with aversive events precedes the onset of subclinical paranoid thinking, there is little empirical research on neural activation patterns during cognitive reappraisal efforts that might indicate vulnerability towards paranoid thinking. Prefrontal EEG alpha asymmetry changes were recorded while n = 57 participants were generating alternative appraisals of anger-eliciting events, and were linked to a behavioral measure of basic cognitive reappraisal capacity and self-reported paranoia proneness (assessed by personality facets of hostility and suspiciousness; Personality Inventory for DSM-5). Mediation analysis revealed that less left-lateralized activation at ventrolateral prefrontal sites during reappraisal efforts predicted a higher degree of paranoia proneness. This relationship was mediated through poorer cognitive reappraisal capacity. Matching previous evidence, findings suggest that inappropriate brain activation during reappraisal efforts impairs individuals' capacity to come up with effective alternative interpretations for anger-evoking situations, which may accentuate personality features related to increased paranoid thinking. The findings add to our understanding of neurally underpinned impairments in the capacity to generate cognitive reappraisals and their link to maladaptive personality and behavior.

Working Memory Load-related Theta Power Decreases in Dorsolateral Prefrontal Cortex Predict Individual Differences in Performance

Holding information in working memory (WM) is an active and effortful process that is accompanied by sustained load-dependent changes in oscillatory brain activity. These proportional power increases are often reported in EEG studies recording theta over frontal midline sites. Intracranial recordings, however, yield mixed results, depending on the brain area being recorded from. We recorded intracranial EEG with depth electrodes in 13 patients with epilepsy who were performing a Sternberg WM task. Here, we investigated patterns of theta power changes as a function of memory load during maintenance in three areas critical for WM: dorsolateral prefrontal cortex (DLPFC), dorsal ACC (dACC), and hippocampus. Theta frequency power in both hippocampus and dACC increased during maintenance. In contrast, theta frequency power in the DLPFC decreased during maintenance, and this decrease was proportional to memory load. Only the power decreases in DLPFC, but not the power increases in hippocampus and dACC, were predictive of behavior in a given trial. The extent of the load-related theta power decreases in the DLPFC in a given participant predicted a participant's RTs, revealing that DLPFC theta explains individual differences in WM ability between participants. Together, these data reveal a pattern of theta power decreases in the DLPFC that is predictive of behavior and that is opposite of that in other brain areas. This result suggests that theta band power changes serve different cognitive functions in different brain areas and specifically that theta power decreases in DLPFC have an important role in maintenance of information.

Incremental benefits of EEG informed fMRI in the study of disorders related to meso-corticolimbic dopamine pathway dysfunction: A systematic review of recent literature

Functional magnetic resonance imaging (fMRI) is a non-invasive imaging modality that enables the assessment of neural connectivity and oxygen utility of the brain using blood oxygen level dependent (BOLD) imaging sequence. Electroencephalography (EEG), on the other hands, looks at cortical electrical impulses of the brain thus detecting brainwave patterns during rest and thought processing. The combination of these two modalities is called fMRI with simultaneous EEG (fMRI-EEG), which has emerged as a new tool for experimental neuroscience assessments and has been applied clinically in many settings, most commonly in epilepsy cases. Recent advances in imaging has led to fMRI-EEG being utilized in behavioural studies which can help in giving an objective assessment of ambiguous cases and help in the assessment of response to treatment by providing a non-invasive biomarker of the disease processes. We aim to review the role and interpretation of fMRI-EEG in studies pertaining to psychiatric disorders and behavioral abnormalities.