Reliable Attention Network Scores and Mutually Inhibited Inter-network Relationships Revealed by Mixed Design and Non-orthogonal Method

Analysis of functional connectivity changes in attention networks and default mode networks in patients with depression and insomnia

PURPOSE

Major Depressive Disorder (MDD) and Insomnia Disorder (ID) are prevalent psychiatric conditions often occurring concurrently, leading to substantial impairment in daily functioning. Understanding the neurobiological underpinnings of these disorders and their comorbidity is crucial for developing effective interventions. This study aims to analyze changes in functional connectivity within attention networks and default mode networks in patients with depression and insomnia.

METHODS

The functional connectivity alterations in individuals with MDD, ID, comorbid MDD and insomnia (iMDD), and healthy controls (HC) were assessed from a cohort of 174 participants. They underwent rs-fMRI scans, demographic assessments, and scale evaluations for depression and sleep quality. Functional connectivity analysis was conducted using region-of-interest (ROI) and whole-brain methods.

RESULTS

The MDD and iMDD groups exhibited higher Hamilton Depression Scale (HAMD) scores compared to HC and ID groups (P < 0.001). Both ID and MDD groups displayed enhanced connectivity between the left and right orbital frontal cortex compared to HC (P < 0.05), while the iMDD group showed reduced connectivity compared to HC and ID groups (P < 0.05). In the left insula, reduced connectivity with the right medial superior frontal gyrus was observed across patient groups compared to HC (P < 0.05), with the iMDD group showing increased connectivity compared to MDD (P < 0.05). Moreover, alterations in functional connectivity between the left thalamus and left temporal pole were found in iMDD compared to HC and MDD (P < 0.05). Correlation analyses revealed associations between abnormal connectivity and symptom severity in MDD and ID groups.

CONCLUSIONS

Our findings demonstrate distinct patterns of altered functional connectivity in individuals with MDD, ID, and iMDD compared to healthy controls. These findings contribute to a better understanding of the pathophysiology of depression and insomnia, which could be used as a reference for the diagnosis and treatments of these patients.

Understanding mental fatigue and its detection: a comparative analysis of assessments and tools

Mental fatigue has shown to be one of the root causes of decreased productivity and overall cognitive performance, by decreasing an individual's ability to inhibit responses, process information and concentrate. The effects of mental fatigue have led to occupational errors and motorway accidents. Early detection of mental fatigue can prevent the escalation of symptoms that may lead to chronic fatigue syndrome and other disorders. To date, in clinical settings, the assessment of mental fatigue and stress is done through self-reported questionnaires. The validity of these questionnaires is questionable, as they are highly subjective measurement tools and are not immune to response biases. This review examines the wider presence of mental fatigue in the general population and critically compares its various detection techniques (i.e., self-reporting questionnaires, heart rate variability, salivary cortisol levels, electroencephalogram, and saccadic eye movements). The ability of these detection tools to assess inhibition responses (which are sensitive enough to be manifested in a fatigue state) is specifically evaluated for a reliable marker in identifying mentally fatigued individuals. In laboratory settings, antisaccade tasks have been long used to assess inhibitory control and this technique can potentially serve as the most promising assessment tool to objectively detect mental fatigue. However, more studies need to be conducted in the future to validate and correlate this assessment with other existing measures of mental fatigue detection. This review is intended for, but not limited to, mental health professionals, digital health scientists, vision researchers, and behavioral scientists.

Deep Learning in the Identification of Electroencephalogram Sources Associated with Sexual Orientation

INTRODUCTION

It is unclear if sexual orientation is a biological trait that has neurofunctional footprints. With deep learning, the power to classify biological datasets without an a priori selection of features has increased by magnitudes. The aim of this study was to correctly classify resting-state electroencephalogram (EEG) data from males with different sexual orientation using deep learning and to explore techniques to identify the learned distinguishing features.

METHODS

Three cohorts (homosexual men, heterosexual men, and a mixed sex cohort), one pretrained network on sex classification, and one newly trained network for sexual orientation classification were used to classify sex. Further, Grad-CAM methodology and source localization were used to identify the spatiotemporal patterns that were used for differentiation by the networks.

RESULTS

Using a pretrained network for classification of males and females, no differences existed between classification of homosexual and heterosexual males. The newly trained network was able, however, to correctly classify the cohorts with a total accuracy of 83%. The retrograde activation using Grad-CAM technology yielded distinctive functional EEG patterns in the Brodmann area 40 and 1 when combined with Fourier analysis and a source localization.

DISCUSSION

This study shows that electrophysiological trait markers of male sexual orientation can be identified using deep learning. These patterns are different from the differentiating signatures of males and females in a resting-state EEG.

Exposure to conflicting COVID-19 information in undergraduates: Implications for pandemic-related information-seeking and concern, attention, and cognitive workload

Objectives: To examine college students' conflicting COVID-19 information exposure, information-seeking, concern, and cognitive functioning. Participants: 179 undergraduates were recruited in March-April 2020, and 220 in September 2020 (Samples 1 and 2, respectively). Methods: Students completed the Attention Network Test, NASA Task Load Index, and COVID-related questions. Results: In Sample 1, exposure to conflicting information predicted poorer attentional performance and greater COVID-related information-seeking and concern; concern was correlated with workload. In Sample 2, conflicting information was associated with information-seeking. In Sample 1, but not Sample 2, cognitive effects of conflicting information were mediated by information-seeking and virus-related concern. Conclusions: Conflicting COVID-19 information may undermine students' cognitive functions, bearing implications for health, academic performance, and stress. Strategies for countering these effects include enhancing the clarity of institutional messaging, and tailoring course curricula and offering workshops to students, faculty, administrators, and counseling staff to augment students' capacity to comprehend and utilize COVID-related communications.

Automaticity of Early Sexual Attention: An Event-Related Potential Study

A promising line of research on forensic assessment of paraphilic sexual interest focuses on behavioral measures of visual attention using sexual stimuli as distractors. The present study combined event-related potentials (ERPs) with behavioral measures to investigate whether detection of a hidden sexual preference can be improved with ERPs. Normal variants of sexual orientation were used for a proof-of-concept investigation. Accordingly, 40 heterosexual and 40 gay men participated in the study. Within each group, half of the participants were instructed to hide their sexual orientation. The results showed that a match between sexual orientation and stimulus delays responses and influences ERP before motor responses. Late ERP components showed higher potential in differentiating hidden sexual preferences than motor responses, thereby showing how ERPs can be used in combination with reaction time measures to potentially facilitate the detection of hidden sexual preferences.

Self-related objects increase alertness and orient attention through top-down saliency

Attention is influenced by information about relationships between ourselves and the objects around us. Self-related objects can either facilitate or disrupt task performance, creating a challenge for identifying the precise nature of the influence of self-relatedness on attention. To address this challenge, we measured different components of attention (alertness and orienting) in the presence of self-related objects using a revised attention network task (ANT). In a self-association task, participants first learned colour-person associations and then carried out a colour-person matching task. This was followed by the ANT, in which these coloured boxes associated with self or friend were displayed as peripheral cues; participants had to judge the direction of an arrow flanked by congruent (low-conflict) or incongruent (high-conflict) distractors presented within one coloured box. The results showed faster and more accurate responses to targets appearing within the self-colour than friend-colour cues in the association task. In the ANT, the analysis of alertness revealed that self-related cues facilitated task performance compared with friend-related cues. The analysis of orienting demonstrated that relative to friend cues, self-cues hampered task performance in invalid trials. Critically, the effects of self-cues on both orienting and alertness were observed only in high conflict situations. These results indicated that self-related objects are powerful cues that enhance attention intensity, which either facilitates task performance when the upcoming target falls within their location or disrupts performance when the target falls outside their location. The data suggest that attentional functions can be tuned by self-saliency in high-demand contexts.

Healthy or not? The impact of conflicting health-related information on attentional resources

Despite its ubiquity, little is known about the impact of exposure to conflicting health information on cognitive efficiency. We hypothesized that it would reduce attentional capacity, as evidenced by (1) increased response errors during the Attention Network Test (ANT), (2) decreased efficiency of each ANT system (alerting, orienting, execute control), and (3) increased self-reported workload, (4) nutritional confusion and (5) nutritional backlash. A sample of 184 online participants were assigned randomly to read an article containing either congruent or conflicting health information. Subsequently, they completed the ANT and self-report measures of workload, nutritional confusion, and backlash at nutritional recommendations and research. Participants in the conflicting health information condition made more errors, had overall slower reaction times, and reported greater workload, nutritional confusion, and backlash. No differences were found for individual ANT systems. These findings suggest that exposure to conflicting health information can degrade attentional mechanisms responsible for accurate and prompt responding to incoming information.

Alerting, Orienting, and Executive Control: The Effect of Bilingualism and Age on the Subcomponents of Attention

Life-long experience of using two or more languages has been shown to enhance cognitive control abilities in young and elderly bilinguals in comparison to their monolingual peers. This advantage has been found to be larger in older adults in comparison to younger adults, suggesting that bilingualism provides advantages in cognitive control abilities. However, studies showing this effect have used a variety of tasks (Simon Task, Stroop task, Flanker Task), each measuring different subcomponents of attention and raising mixed results. At the same time, attention is not a unitary function but comprises of subcomponents which can be distinctively addressed within the Attention Network Test (ANT) (1, 2). The purpose of this work was to examine the neurofunctional correlates of the subcomponents of attention in healthy young and elderly bilinguals taking into account the L2 age of acquisition, language usage, and proficiency. Participants performed an fMRI version of the ANT task, and speed, accuracy, and BOLD data were collected. As expected, results show slower overall response times with increasing age. The ability to take advantage of the warning cues also decreased with age, resulting in reduced alerting and orienting abilities in older adults. fMRI results showed an increase in neurofunctional activity in the frontal and parietal areas in elderly bilinguals when compared to young bilinguals. Furthermore, higher L2 proficiency correlated negatively with activation in frontal area, and that faster RTs correlated negatively with activation in frontal and parietal areas. Such a correlation, especially with L2 proficiency was not present in young bilinguals and provides evidence for a bilingual advantage in the alerting subcomponent of attention that characterizes elderly bilinguals' performance. This study thus provides extra details about the bilingual advantage in the subcomponent of attention, in older bilinguals. Consequently, speaking more than one language impacts cognition and the brain later in life.

Neuromodulating Attention and Mind-Wandering Processes with a Single Session Real Time EEG

Our minds are continuously alternating between external attention (EA) and mind wandering (MW). An appropriate balance between EA and MW is important for promoting efficient perceptual processing, executive functioning, decision-making, auto-biographical memory, and creativity. There is evidence that EA processes are associated with increased activity in high-frequency EEG bands (e.g., SMR), contrasting with the dominance of low-frequency bands during MW (e.g., Theta). The aim of the present study was to test the effects of two distinct single session real-time EEG (rtEEG) protocols (SMR up-training/Theta down-training-SMR⇑Theta⇓; Theta up-training/SMR down-training-Theta⇑SMR⇓) on EA and MW processes. Thirty healthy volunteers were randomly assigned to one of two rtEEG training protocols (SMR⇑Theta⇓; Theta⇑SMR⇓). Before and after the rtEEG training, participants completed the attention network task (ANT) along with several MW measures. Both training protocols were effective in increasing SMR (SMR⇑Theta⇓) and theta (Theta⇑SMR⇓) amplitudes but not in decreasing the amplitude of down-trained bands. There were no significant effects of the rtEEG training in either EA or MW measures. However, there was a significant positive correlation between post-training SMR increases and the use of deliberate MW (rather than spontaneous) strategies. Additionally, for the Theta⇑SMR⇓ protocol, increase in post-training Theta amplitude was significantly associated with a decreased efficiency in the orientation network.

Mind Wandering and Task-Focused Attention: ERP Correlates

Previous studies looking at how Mind Wandering (MW) impacts performance in distinct Focused Attention (FA) systems, using the Attention Network Task (ANT), showed that the presence of pure MW thoughts did not impact the overall performance of ANT (alert, orienting and conflict) performance. However, it still remains unclear if the lack of interference of MW in the ANT, reported at the behavioral level, has a neurophysiological correspondence. We hypothesize that a distinct cortical processing may be required to meet attentional demands during MW. The objective of the present study was to test if, given similar levels of ANT performance, individuals predominantly focusing on MW or FA show distinct cortical processing. Thirty-three healthy participants underwent an EEG high-density acquisition while they were performing the ANT. MW was assessed following the ANT using an adapted version of the Resting State Questionnaire (ReSQ). The following ERP’s were analyzed: pN1, pP1, P1, N1, pN, and P3. At the behavioral level, participants were slower and less accurate when responding to incongruent than to congruent targets (conflict effect), benefiting from the presentation of the double (alerting effect) and spatial (orienting effect) cues. Consistent with the behavioral data, ERP’s waves were discriminative of distinct attentional effects. However, these results remained true irrespective of the MW condition, suggesting that MW imposed no additional cortical demand in alert, orienting, and conflict attention tasks.

Connection Disruption Underlying Attention Deficit in Subcortical Stroke

Purpose To investigate neural substrates underlying attention deficit in patients with chronic subcortical stroke by combining voxel-based lesion-symptom mapping (VLSM) and diffusion-tensor (DT) tractography. Materials and Methods Institutional review board approval and written informed consent were obtained. Diffusion magnetic resonance imaging data were prospectively acquired from August 1, 2014, to March 30, 2015, in 49 patients (32 men, 17 women; mean age, 55.7 years ± 8.0; age range, 40-71 years) with subcortical infarctions in the basal ganglia and neighboring regions and 52 control subjects (30 men, 22 women; mean age, 54.4 years ± 7.5; age range, 40-68 years). A modified version of the attention network test was used to assess visual attention function. On the basis of the lesion map at the acute stage, VLSM was used to identify lesion locations related to attention deficit in patients with stroke. DT tractography then was used to determine the responsible impaired connections by using diffusion data at the chronic stage (>6 months after stroke). Results When compared with control subjects, patients with chronic stroke exhibited prolonged reaction time (RT) of correct responses (P = .009). VLSM revealed that acute stroke lesion in the right caudate nucleus and nearby white matter (found in seven patients) was correlated with the prolonged RT (P < .05). DTT showed that the responsible lesion was located in the right thalamic- and caudate-prefrontal pathways in control subjects. The subgroup with right-sided brain damage had significantly decreased fractional anisotropy in these pathways (P < .001), which were correlated with the prolonged RT (P = .009 for the thalamic-prefrontal pathway, P < .001 for the caudate-prefrontal pathway). Conclusion Thalamic-prefrontal and caudate-prefrontal pathways impaired by stroke lesions appear to underlie attention deficit in patients with subcortical stroke in the right hemisphere.

Developmental implications of children's brain networks and learning

The human brain works as a synergistic system where information exchanges between functional neuronal networks. Rudimentary networks are observed in the brain during infancy. In recent years, the question of how functional networks develop and mature in children has been a hotly discussed topic. In this review, we examined the developmental characteristics of functional networks and the impacts of skill training on children's brains. We first focused on the general rules of brain network development and on the typical and atypical development of children's brain networks. After that, we highlighted the essentials of neural plasticity and the effects of learning on brain network development. We also discussed two important theoretical and practical concerns in brain network training. Finally, we concluded by presenting the significance of network training in typically and atypically developed brains.

Connectome-based Models Predict Separable Components of Attention in Novel Individuals

Although we typically talk about attention as a single process, it comprises multiple independent components. But what are these components, and how are they represented in the functional organization of the brain? To investigate whether long-studied components of attention are reflected in the brain's intrinsic functional organization, here we apply connectome-based predictive modeling (CPM) to predict the components of Posner and Petersen's influential model of attention: alerting (preparing and maintaining alertness and vigilance), orienting (directing attention to a stimulus), and executive control (detecting and resolving cognitive conflict) [Posner, M. I., & Petersen, S. E. The attention system of the human brain. Annual Review of Neuroscience, 13, 25-42, 1990]. Participants performed the Attention Network Task (ANT), which measures these three factors, and rested during fMRI scanning. CPMs tested with leave-one-subject-out cross-validation successfully predicted novel individual's overall ANT accuracy, RT variability, and executive control scores from functional connectivity observed during ANT performance. CPMs also generalized to predict participants' alerting scores from their resting-state functional connectivity alone, demonstrating that connectivity patterns observed in the absence of an explicit task contain a signature of the ability to prepare for an upcoming stimulus. Suggesting that significant variance in ANT performance is also explained by an overall sustained attention factor, the sustained attention CPM, a model defined in prior work to predict sustained attentional abilities, predicted accuracy, RT variability, and executive control from task-based data and predicted RT variability from resting-state data. Our results suggest that, whereas executive control may be closely related to sustained attention, the infrastructure that supports alerting is distinct and can be measured at rest. In the future, CPM may be applied to elucidate additional independent components of attention and relationships between the functional brain networks that predict them.

Mind wandering and the attention network system

Attention and mind wandering are often seen as anticorrelated. However, both attention and mind wandering are multi-component processes, and their relationship may be more complex than previously thought. In this study, we tested the interference of different types of thoughts as measured by a Thought Identification Task - TIT (on task thoughts, task related interference thoughts, external distractions, stimulus independent and task unrelated thoughts) on different components of the attention network system - ANT (alerting, orienting, executive). Results show that, during the ANT, individuals were predominantly involved in task related interference thoughts which, along with external distractors, significantly impaired their performance accuracy. However, mind wandering (i.e., stimulus independent and task unrelated thoughts) did not significantly interfere with accuracy in the ANT. No significant relationship was found between type of thoughts and alerting, orienting, or executive effects in the ANT. While task related interference thoughts and external distractions seemed to impair performance on the attention task, mind wandering was still compatible with satisfactory performance in the ANT. The present results confirmed the importance of differentiating type of "out of task" thoughts in studying the relationship between though distractors and attention.

Automaticity of phasic alertness: Evidence for a three-component model of visual cueing

The automaticity of phasic alertness is investigated using the attention network test. Results show that the cueing effect from the alerting cue-double cue-is strongly enhanced by the task relevance of visual cues, as determined by the informativeness of the orienting cue-single cue-that is being mixed (80 % vs. 50 % valid in predicting where the target will appear). Counterintuitively, the cueing effect from the alerting cue can be negatively affected by its visibility, such that masking the cue from awareness can reveal a cueing effect that is otherwise absent when the cue is visible. Evidently, then, top-down influences-in the form of contextual relevance and cue awareness-can have opposite influences on the cueing effect from the alerting cue. These findings lead us to the view that a visual cue can engage three components of attention-orienting, alerting, and inhibition-to determine the behavioral cueing effect. We propose that phasic alertness, particularly in the form of specific response readiness, is regulated by both internal, top-down expectation and external, bottom-up stimulus properties. In contrast to some existing views, we advance the perspective that phasic alertness is strongly tied to temporal orienting, attentional capture, and spatial orienting. Finally, we discuss how translating attention research to clinical applications would benefit from an improved ability to measure attention. To this end, controlling the degree of intraindividual variability in the attentional components and improving the precision of the measurement tools may prove vital.

Low frequency steady-state brain responses modulate large scale functional networks in a frequency-specific means

Neural oscillations are essential for brain functions. Research has suggested that the frequency of neural oscillations is lower for more integrative and remote communications. In this vein, some resting-state studies have suggested that large scale networks function in the very low frequency range (<1 Hz). However, it is difficult to determine the frequency characteristics of brain networks because both resting-state studies and conventional frequency tagging approaches cannot simultaneously capture multiple large scale networks in controllable cognitive activities. In this preliminary study, we aimed to examine whether large scale networks can be modulated by task-induced low frequency steady-state brain responses (lfSSBRs) in a frequency-specific pattern. In a revised attention network test, the lfSSBRs were evoked in the triple network system and sensory-motor system, indicating that large scale networks can be modulated in a frequency tagging way. Furthermore, the inter- and intranetwork synchronizations as well as coherence were increased at the fundamental frequency and the first harmonic rather than at other frequency bands, indicating a frequency-specific modulation of information communication. However, there was no difference among attention conditions, indicating that lfSSBRs modulate the general attention state much stronger than distinguishing attention conditions. This study provides insights into the advantage and mechanism of lfSSBRs. More importantly, it paves a new way to investigate frequency-specific large scale brain activities.