Sustaining visual attention in the face of distraction: a novel gradual-onset continuous performance task

Are Mindfulness and Mind-Wandering Opposite Constructs? It Depends on How Mindfulness is Conceptualised

This study investigated if trait mindfulness and its components, mindful attention, acceptance, and non-judging correlate negatively with self-reported and indirect markers of mind-wandering. The 552 participants of the study completed an anonymous online questionnaire consisting of trait mindfulness and mind-wandering scales. They also completed the computer-based Sustained Attention to Response Task (SART), an objective measure of mind-wandering. The total mindfulness score and acceptance and non-judging subscale scores were strongly negatively correlated with both self-reported trait mind-wandering (TMW) and SART indices of mind-wandering. In contrast, attention was significantly positively correlated with both. These findings suggest that trait mindfulness conceptualised as a multi-component construct, but not a uni-component one, is probably an opposing construct to trait mind-wandering. Furthermore, mindfulness and its components, acceptance and non-judging, are associated with a reduction in the more common form of SART errors. However, only the acceptance component made a unique contribution to the variance in TMW and SART performance. Therefore, it is advisable for researchers to specify whether they investigated mindfulness as a uni-component or multi-component construct. Furthermore, it would be beneficial if future research investigates the relationship of mindfulness and its components with mind-wandering further by also incorporating a measure of state mindfulness.

Slow and steady: Validating the rhythmic visual response task as a marker for attentional states

A principal goal of attention research is to develop tasks with clear behavioral signatures of attentional fluctuations. Measures that index attentional states often fall under two broad umbrellas: decision tasks, in which participants make responses based on the changing requirements of each trial, and rhythm tasks, in which participants respond rhythmically to a uniform stimulus (e.g., a metronome tone). In the former, response speeding typically precedes errors (indicative of attention failures). In the latter, increased response variability precedes subjective reports of off-task states. We developed and validated the rhythmic visual response task (RVRT); a rhythm task incorporating trial-unique scene stimuli. The RVRT incorporates two important advances from both task categories: (1) it is free from the influence that differential decision-making has on fluctuations in attentional states, and (2) trial-unique stimuli enable later cognitive judgments to be mapped to specific moments in the task. These features allow a relatively unobtrusive measure of mind wandering that facilitates the downstream assessment of its consequences. Participants completed 900 trials of the RVRT, interrupted periodically by thought probes that assessed their attentional state. We found that both response time variance and speed predicted depth of mind wandering. Encouraged by these findings, we used the same analysis approach on archival data to demonstrate that the combination of variance and speed best predicted attentional states in several rhythm and decision task datasets. We discuss the implications of these findings and suggest future research that uses the RVRT to investigate the impact of spontaneous mind wandering on memory, decision-making, and perception.

Integrating Chiropractic Care and Tai Chi Training for the Treatment of Chronic Nonspecific Neck Pain in Nurses: A Single-Arm Mixed-Methods Pilot Trial

Objectives: Chronic nonspecific neck pain (CNNP) is prevalent among health care workers, with particularly high rates among nurses. Nurses experiencing CNNP often report decreased job satisfaction, increased absenteeism, and reduced productivity. In recent years, nonpharmacologic approaches have gained attention as effective treatments for the management of CNNP, with exercise and manual therapies representing two of the most common. Early evidence shows that multimodal treatments may be more effective than unimodal strategies. The purpose of this current study was to assess the feasibility and observe the clinical outcomes of combined multimodal chiropractic care (MCC) and Tai Chi (TC) for CNNP in nurses. Methods: A single-arm mixed-methods pilot trial was conducted including 16 weeks of MCC and TC in nurses with self-reported CNNP. Feasibility outcomes were recruitment, retention, and adherence to the interventions. Clinical outcomes of interest included neck pain and related disabilities. Secondary outcomes of interest were functional, affective, and work-related performance. Qualitative interviews were also conducted. Results: Of the 59 screened, 36 met the eligibility criteria, and 21 were enrolled. The retention rate was 71.4%, and adherence rates were 85.3% for MCC and 62.5% for TC classes. Multiple pain and disability-related outcomes exhibited modest improvement from baseline to 16-week follow-up. Qualitative analysis identified six emergent themes: (1) neck pain being an inherent part of nursing, (2) nurses push through their pain, (3) MCC relieves pain and is instructive for preventing pain, (4) TC provides overall relaxation, (5) both interventions increased body awareness and improved posture, and (6) scheduling difficulties were a key obstacle for participating. Conclusions: Observed reductions in neck pain and disability suggest the potential utility of combined MCC and TC interventions for managing CNNP. Along with qualitative feedback regarding facilitators and barriers to participation, the findings support and inform a future randomized trial evaluating the combined benefits of MCC and TC for CNNP in nurses. Clinical Trial Registration #NCT06523036.

Going beyond video game consumption when considering Internet Gaming Disorder

BACKGROUND

Recognizing the crucial importance of understanding the impact of video games on health in today's gaming-dominated world, our study aimed to investigate the relationship between gaming time and Internet Gaming Disorder (IGD). Despite the widespread assumption that a connection exists between both, previous studies have revealed highly variable associations, highlighting significant weaknesses in establishing a robust link.

METHODS

To unravel this complex relationship, we recruited two independent samples of League of Legends players. We combined the collection of self-reported and actual gameplay data, together with assessments of mental health, personality traits, and cognitive abilities.

RESULTS

Surprisingly, none of the gaming variables demonstrated a robust and stable association with IGD, regardless of whether players spent less than or more than 30 hours per week gaming-a threshold suggested by the American Psychiatric Association as a potential indicator of disordered gaming. Notably, mental health factors, such as anxiety, depression and ADHD, emerged as the most influential predictors of IGD.

CONCLUSION

These findings, replicated across two independent samples, challenge the prevailing belief that limiting screen time alone effectively combats IGD. Instead, mental health factors play a crucial role in mitigating risks associated with gaming. Policies focusing solely on restricting screen time are insufficient in reducing the prevalence or symptoms of IGD. Rather, a comprehensive approach that considers mental health and key personality traits must be adopted to safeguard the well-being of individuals engaged in gaming.

Dispositional mindfulness: Dissociable affective and cognitive processes

Mindfulness has been linked to a range of positive social-emotional and cognitive outcomes, but the underlying mechanisms are unclear. As one of the few traits or dispositions that are associated with both affective and cognitive benefits, we asked whether mindfulness is associated with affective and cognitive outcomes through a shared, unitary process or through two dissociable processes. We examined this in adolescents using behavioral measures and also reanalyzed previously reported neuroimaging findings relating mindfulness training to either affect (negative emotion, stress) or cognition (sustained attention). Using multivariate regression analyses, our findings suggest that the relationships between dispositional mindfulness and affective and cognitive processes are behaviorally dissociable and converge with neuroimaging data indicating that mindfulness modulates affect and cognition through separate neural pathways. These findings support the benefits of trait mindfulness on both affective and cognitive processes, and reveal that those benefits are at least partly dissociable in the mind and brain.

Edge-Based General Linear Models Capture Moment-to-Moment Fluctuations in Attention

Although we must prioritize the processing of task-relevant information to navigate life, our ability to do so fluctuates across time. Previous work has identified fMRI functional connectivity (FC) networks that predict an individual's ability to sustain attention and vary with attentional state from 1 min to the next. However, traditional dynamic FC approaches typically lack the temporal precision to capture moment-to-moment network fluctuations. Recently, researchers have "unfurled" traditional FC matrices in "edge cofluctuation time series" which measure timepoint-by-timepoint cofluctuations between regions. Here we apply event-based and parametric fMRI analyses to edge time series to capture moment-to-moment fluctuations in networks related to attention. In two independent fMRI datasets examining young adults of both sexes in which participants performed a sustained attention task, we identified a reliable set of edges that rapidly deflects in response to rare task events. Another set of edges varies with continuous fluctuations in attention and overlaps with a previously defined set of edges associated with individual differences in sustained attention. Demonstrating that edge-based analyses are not simply redundant with traditional regions-of-interest-based approaches, up to one-third of reliably deflected edges were not predicted from univariate activity patterns alone. These results reveal the large potential in combining traditional fMRI analyses with edge time series to identify rapid reconfigurations in networks across the brain.

The relationship between sustained attention and parasympathetic functioning

Sustained attention (SA) is an important cognitive ability that plays a crucial role in successful cognitive control. Resting vagally-mediated heart rate variability (vmHRV) has emerged as an informative index of parasympathetic nervous system activity and a sensitive correlate of individual differences in cognitive control. However, it is unclear how resting vmHRV is associated with individual differences in sustained attention. The primary aim of the current study was to assess if resting vmHRV was associated with individual differences in performance on a neuropsychological assessment of sustained attention. We further aimed to characterize the relationship between resting vmHRV and dispositional factors related to sustained attention, specifically attentional errors in daily life, self-regulation, mindfulness and media-multitasking. Based on previous work, we hypothesized higher resting vmHRV would be associated with better sustained attention across task-based and self-report measures. We did not find resting vmHRV to be significantly associated with performance measures on a task-based assessment of sustained attention. Further, resting vmHRV was not significantly associated with attention errors, self-regulation, mindfulness, or media-multitasking. This work stands to expand the current understanding between parasympathetic functioning, cognition, and behavior, investigating the unexplored domain of sustained attention and related dispositional factors.

Time-varying functional connectivity predicts fluctuations in sustained attention in a serial tapping task

The mechanisms for how large-scale brain networks contribute to sustained attention are unknown. Attention fluctuates from moment to moment, and this continuous change is consistent with dynamic changes in functional connectivity between brain networks involved in the internal and external allocation of attention. In this study, we investigated how brain network activity varied across different levels of attentional focus (i.e., "zones"). Participants performed a finger-tapping task, and guided by previous research, in-the-zone performance or state was identified by low reaction time variability and out-of-the-zone as the inverse. In-the-zone sessions tended to occur earlier in the session than out-of-the-zone blocks. This is unsurprising given the way attention fluctuates over time. Employing a novel method of time-varying functional connectivity, called the quasi-periodic pattern analysis (i.e., reliable, network-level low-frequency fluctuations), we found that the activity between the default mode network (DMN) and task positive network (TPN) is significantly more anti-correlated during in-the-zone states versus out-of-the-zone states. Furthermore, it is the frontoparietal control network (FPCN) switch that differentiates the two zone states. Activity in the dorsal attention network (DAN) and DMN were desynchronized across both zone states. During out-of-the-zone periods, FPCN synchronized with DMN, while during in-the-zone periods, FPCN switched to synchronized with DAN. In contrast, the ventral attention network (VAN) synchronized more closely with DMN during in-the-zone periods compared with out-of-the-zone periods. These findings demonstrate that time-varying functional connectivity of low frequency fluctuations across different brain networks varies with fluctuations in sustained attention or other processes that change over time.

A Nomothetic Span Approach to the Construct Validation of Sustained Attention Consistency: Re-Analyzing Two Latent-Variable Studies of Performance Variability and Mind-Wandering Self-Reports

The ability to sustain attention consistency is frequently assessed using either objective behavioral measures, such as reaction time (RT) variability, or subjective self-report measures, such as rates of task-unrelated thought (TUT). The current studies examined whether the individual-difference covariation in these measures provides a more construct valid assessment of attention consistency than does either alone. We argue that performance and self-report measures mutually validate each other; each measurement approach has its own sources of error, so their shared variance should best reflect the attention consistency construct. We reanalyzed two latent-variable studies where RT variability and TUTs were measured in multiple tasks (Kane et al. in J Exp Psychol Gen 145:1017-1048, 2016; Unsworth et al. in J Exp Psychol Gen 150:1303-1331, 2021), along with several nomological network constructs to test the convergent and discriminant validity of a general attention consistency factor. Confirmatory factor analyses assessing bifactor (preregistered) and hierarchical (non-preregistered) models suggested that attention consistency can be modeled as the shared variance among objective and subjective measures. This attention consistency factor was related to working memory capacity, attention (interference) control, processing speed, state motivation and alertness, and self-reported cognitive failures and positive schizotypy. Although bifactor models of general attention consistency provide the most compelling construct validity evidence for a specific ability to sustain attention, multiverse analyses of outlier decisions suggested they are less robust than hierarchical models. The results provide evidence for the general ability to sustain attention consistency and suggestions for improving its measurement.

A combined experimental-correlational approach to the construct validity of performance-based and self-report-based measures of sustained attention

The ability to sustain attention is often measured with either objective performance indicators, like within-person RT variability, or subjective self-reports, like mind wandering propensity. A more construct valid approach, however, may be to assess the covariation in these performance and self-report measures, given that each of these is influenced by different sources of measurement error. If the correlation between performance-variability and self-report measures reflects the sustained attention construct, then task manipulations aimed at reducing the sustained attention demands of tasks should reduce the correlation between them (in addition to reducing mean levels of variability and mind wandering). The current study investigated this claim with a combined experimental-correlation approach. In two experiments (Ns ~ 1,500 each), participants completed tasks that either maximized or minimized the demand for sustained attention. Our demand manipulations successfully reduced the mean levels of sustained attention failures in both the objective and subjective measures, in both experiments. In neither experiment, however, did the covariation between these measures change as a function of the sustained attention demands of the tasks. We can therefore claim only minimal support for the construct validity of our measurement approach to sustained attention.

Mindfulness-based real-time fMRI neurofeedback: a randomized controlled trial to optimize dosing for depressed adolescents

BACKGROUND

Adolescence is characterized by a heightened vulnerability for Major Depressive Disorder (MDD) onset, and currently, treatments are only effective for roughly half of adolescents with MDD. Accordingly, novel interventions are urgently needed. This study aims to establish mindfulness-based real-time fMRI neurofeedback (mbNF) as a non-invasive approach to downregulate the default mode network (DMN) in order to decrease ruminatory processes and depressive symptoms.

METHODS

Adolescents (N = 90) with a current diagnosis of MDD ages 13-18-years-old will be randomized in a parallel group, two-arm, superiority trial to receive either 15 or 30 min of mbNF with a 1:1 allocation ratio. Real-time neurofeedback based on activation of the frontoparietal network (FPN) relative to the DMN will be displayed to participants via the movement of a ball on a computer screen while participants practice mindfulness in the scanner. We hypothesize that within-DMN (medial prefrontal cortex [mPFC] with posterior cingulate cortex [PCC]) functional connectivity will be reduced following mbNF (Aim 1: Target Engagement). Additionally, we hypothesize that participants in the 30-min mbNF condition will show greater reductions in within-DMN functional connectivity (Aim 2: Dosing Impact on Target Engagement). Aim 1 will analyze data from all participants as a single-group, and Aim 2 will leverage the randomized assignment to analyze data as a parallel-group trial. Secondary analyses will probe changes in depressive symptoms and rumination.

DISCUSSION

Results of this study will determine whether mbNF reduces functional connectivity within the DMN among adolescents with MDD, and critically, will identify the optimal dosing with respect to DMN modulation as well as reduction in depressive symptoms and rumination.

TRIAL REGISTRATION

This study has been registered with clinicaltrials.gov, most recently updated on July 6, 2023 (trial identifier: NCT05617495).

Impact of Overnight Glucose on Next-Day Functioning in Adults With Type 1 Diabetes: An Exploratory Intensive Longitudinal Study

OBJECTIVE

While there is evidence that functioning, or ability to perform daily life activities, can be adversely influenced by type 1 diabetes, the impact of acute fluctuations in glucose levels on functioning is poorly understood.

RESEARCH DESIGN AND METHODS

Using dynamic structural equation modeling, we examined whether overnight glucose (coefficient of variation[CV], percent time <70 mg/dL, percent time >250 mg/dL) predicted seven next-day functioning outcomes (mobile cognitive tasks, accelerometry-derived physical activity, self-reported activity participation) in adults with type 1 diabetes. We examined mediation, moderation, and whether short-term relationships were predictive of global patient-reported outcomes.

RESULTS

Overall next-day functioning was significantly predicted from overnight CV (P = 0.017) and percent time >250 mg/dL (P = 0.037). Pairwise tests indicate that higher CV is associated with poorer sustained attention (P = 0.028) and lower engagement in demanding activities (P = 0.028), time <70 mg/dL is associated with poorer sustained attention (P = 0.007), and time >250 mg/dL is associated with more sedentary time (P = 0.024). The impact of CV on sustained attention is partially mediated by sleep fragmentation. Individual differences in the effect of overnight time <70 mg/dL on sustained attention predict global illness intrusiveness (P = 0.016) and diabetes-related quality of life (P = 0.036).

CONCLUSIONS

Overnight glucose predicts problems with objective and self-reported next-day functioning and can adversely impact global patient-reported outcomes. These findings across diverse outcomes highlight the wide-ranging effects of glucose fluctuations on functioning in adults with type 1 diabetes.

Quantifying attention span across the lifespan

Introduction

Studies examining sustained attention abilities typically utilize metrics that quantify performance on vigilance tasks, such as response time and response time variability. However, approaches that assess the duration that an individual can maintain their attention over time are lacking.

Methods

Here we developed an objective attention span metric that quantified the maximum amount of time that a participant continuously maintained an optimal "in the zone" sustained attention state while performing a continuous performance task.

Results

In a population of 262 individuals aged 7-85, we showed that attention span was longer in young adults than in children and older adults. Furthermore, declines in attention span over time during task engagement were related to clinical symptoms of inattention in children.

Discussion

These results suggest that quantifying attention span is a unique and meaningful method of assessing sustained attention across the lifespan and in populations with inattention symptoms.

Examining reaction time variability on the stop-signal task in the ABCD study

OBJECTIVE

Reaction time variability (RTV) has been estimated using Gaussian, ex-Gaussian, and diffusion model (DM) indices. Rarely have studies examined interrelationships among these performance indices in childhood, and the use of reaction time (RT) computational models has been slow to take hold in the developmental psychopathology literature. Here, we extend prior work in adults by examining the interrelationships among different model parameters in the ABCD sample and demonstrate how computational models of RT can clarify mechanisms of time-on-task effects and sex differences in RTs.

METHOD

This study utilized trial-level data from the stop signal task from 8916 children (9-10 years old) to examine Gaussian, ex-Gaussian, and DM indicators of RTV. In addition to describing RTV patterns, we examined interrelations among these indicators, temporal patterns, and sex differences.

RESULTS

There was no one-to-one correspondence between DM and ex-Gaussian parameters. Nonetheless, drift rate was most strongly associated with standard deviation of RT and tau, while nondecisional processes were most strongly associated with RT, mu, and sigma. Performance worsened across time with changes driven primarily by decreasing drift rate. Boys were faster and less variable than girls, likely attributable to girls' wide boundary separation.

CONCLUSIONS

Intercorrelations among model parameters are similar in children as has been observed in adults. Computational approaches play a crucial role in understanding performance changes over time and can also clarify mechanisms of group differences. For example, standard RT models may incorrectly suggest slowed processing speed in girls that is actually attributable to other factors.

Performance-linked visual feedback slows response times during a sustained attention task

In the present study, we tested a visual feedback triggering system based on real-time tracking of response time (RT) in a sustained attention task. In our task, at certain points, brief visual feedback epochs were presented without interrupting the task itself. When these feedback epochs were performance-linked-meaning that they were triggered because participants were responding more quickly than usual-RTs were slowed after the presentation of feedback. However, visual feedback epochs displayed at predetermined times that were independent of participants' performance did not slow RTs. Results from a second experiment support the idea that this is not simply a return to baseline that would have occurred had the feedback not been presented, but instead suggest that the feedback itself was effective in altering participants' responses. In a third experiment, we replicated this result across with both written word feedback and visual symbolic feedback, as well as in cases where the participant was explicitly told that the feedback was linked to their performance. All together, these data provide insight into potential mechanisms for detecting and disrupting lapses in sustained attention without interrupting a continuous task.

A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth

Difficulty with attention is an important symptom in many conditions in psychiatry, including neurodiverse conditions such as autism. There is a need to better understand the neurobiological correlates of attention and leverage these findings in healthcare settings. Nevertheless, it remains unclear if it is possible to build dimensional predictive models of attentional state in a sample that includes participants with neurodiverse conditions. Here, we use 5 datasets to identify and validate functional connectome-based markers of attention. In dataset 1, we use connectome-based predictive modeling and observe successful prediction of performance on an in-scan sustained attention task in a sample of youth, including participants with a neurodiverse condition. The predictions are not driven by confounds, such as head motion. In dataset 2, we find that the attention network model defined in dataset 1 generalizes to predict in-scan attention in a separate sample of neurotypical participants performing the same attention task. In datasets 3-5, we use connectome-based identification and longitudinal scans to probe the stability of the attention network across months to years in individual participants. Our results help elucidate the brain correlates of attentional state in youth and support the further development of predictive dimensional models of other clinically relevant phenotypes.

Attentional fluctuations and the temporal organization of memory

Event boundaries and temporal context shape the organization of episodic memories. We hypothesized that attentional fluctuations during encoding serve as "events" that affect temporal context representations and recall organization. Individuals encoded trial-unique objects during a modified sustained attention task. Memory was tested with free recall. Response time variability during the encoding tasks was used to characterize "in the zone" and "out of the zone" attentional states. We predicted that: 1) "in the zone", vs. "out of the zone", attentional states should be more conducive to maintaining temporal context representations that can cue temporally organized recall; and 2) temporally distant "in the zone" states may enable more recall "leaps" across intervening items. We replicated several important findings in the sustained attention and memory fields, including more online errors during "out of the zone" vs. "in the zone" attentional states and recall that was temporally structured. Yet, across four studies, we found no evidence for either of our main hypotheses. Recall was robustly temporally organized, and there was no difference in recall organization for items encoded "in the zone" vs. "out of the zone". We conclude that temporal context serves as a strong scaffold for episodic memory, one that can support organized recall even for items encoded during relatively poor attentional states. We also highlight the numerous challenges in striking a balance between sustained attention tasks (long blocks of a repetitive task) and memory recall tasks (short lists of unique items) and describe strategies for researchers interested in uniting these two fields.

Predictors of quality of life among adults with self-reported cancer related cognitive impairment

OBJECTIVE

The purpose of the current study was to examine the unique contribution of personal and medical factors, objective and subjective cognition, and self-efficacy to the explained variance of quality of life (QoL) among survivors with self-reported cancer related cognitive impairment (CRCI).

METHOD

Seventy-three cancer survivors (non-central nervous system) with CRCI (mean age: 50.85 ± 10.82 years old, mean years post-treatment: 3 ± 2.7) participated in this cross-sectional study. QoL was assessed using the Functional Assessment of Cancer Therapy (FACT)-GP, while the cognitive function was assessed both objectively using tests of attentional control, speed of processing and sustained attention, and subjectively using the FACT-Cognition perceived cognitive impairments (FACTcog-PCI) subscale. Self-efficacy was assessed using the New General Self-Efficacy Scale (NGSE).

RESULTS

A hierarchical multiple linear regression analysis revealed that sustained attention, perceived cognitive impairment and self-efficacy, accounted for 54% of the variance of QoL (R² = 0.543, p < 0.000), each providing a unique contribution to the explained variance (15-20% each) after controlling for age and gender.

CONCLUSIONS

Considering that these variables may be amenable to change, this model can serve as a conceptual framework for designing effective cognitive treatment options for CRCI. Clinical Trial Registration: ClinicalTrials.gov NCTImplication for rehabilitationCancer related cognitive impairment is characterized by difficulties in the speed of processing performance, severe perceived cognitive impairments, and relatively low general self-efficacy.Multi-dimensional assessments including subjective and objective cognition as well as self-efficacy should be administered to cancer survivors with cognitive complaints to understand the underlying mechanisms of their QoL.Integrative cognitive rehabilitation interventions that aim to improve QoL among people with cancer-related cognitive impairment should target sustained attention, perceived cognitive impairment, and self-efficacy.

TTLL11 gene is associated with sustained attention performance and brain networks: A genome-wide association study of a healthy Chinese sample

Genetic studies on attention have mainly focused on children with attention-deficit/hyperactivity disorder (ADHD), so little systematic research has been conducted on genetic correlates of attention performance and their potential brain mechanisms among healthy individuals. The current study included a genome-wide association study (GWAS, N = 1145 healthy young adults) aimed to identify genes associated with sustained attention and an imaging genetics study (an independent sample of 483 healthy young adults) to examine any identified genes' influences on brain function. The GWAS found that TTLL11 showed genome-wide significant associations with sustained attention, with rs13298112 as the most significant SNP and the GG homozygotes showing more impulsive but also more focused responses than the A allele carriers. A retrospective examination of previously published ADHD GWAS results confirmed an un-reported, small but statistically significant effect of TTLL11 on ADHD. The imaging genetics study replicated this association and showed that the TTLL11 gene was associated with resting state activity and connectivity of the somatomoter network, and can be predicted by dorsal attention network connectivity. Specifically, the GG homozygotes showed lower brain activity, weaker brain network connectivity, and non-significant brain-attention association compared to the A allele carriers. Expression database showed that expression of this gene is enriched in the brain and that the G allele is associated with lower expression level than the A allele. These results suggest that TTLL11 may play a major role in healthy individuals' attention performance and may also contribute to the etiology of ADHD.

Abrupt vs. gradual visual onsets in go/no-go sustained attention tasks

Two experiments compared both average performance and changes in performance across time in abrupt- and gradual-onset sustained attention tasks. Experiment 1 compared abrupt- and gradual-onset digits. In conditions where the digits onset and offset abruptly and appeared only briefly, similar to typical conditions in the Sustained Attention to Response Task (SART), participants committed more errors on no-go trials and responded faster overall, indicative of a shift in the speed/accuracy tradeoff toward speed. When the digits abruptly onset but remained on-screen for a longer period of time, there were no differences in no-go error rates, hit rates, or reaction time (RT) variability, but participants still emitted faster RTs overall. Experiment 2 compared abrupt- and gradual-onset images. Similar to Experiment 1, abrupt-onset, short-duration images induced more no-go errors and faster RTs, but also more RT variability and reduced hit rates. In the abrupt-onset, long-duration condition, again the only performance difference was a decrease in average RTs. We discuss implications for using these two types of tasks in sustained attention research.

Default mode network mediates low-frequency fluctuations in brain activity and behavior during sustained attention

The low-frequency (<0.1 Hz) fluctuation in sustained attention attracts enormous interest in cognitive neuroscience and clinical research since it always leads to cognitive and behavioral lapses. What is the source of the spontaneous fluctuation in sustained attention in neural activity, and how does the neural fluctuation relate to behavioral fluctuation? Here, we address these questions by collecting and analyzing two independent fMRI and behavior datasets. We show that the neural (fMRI) fluctuation in a key brain network, the default-mode network (DMN), mediate behavioral (reaction time) fluctuation during sustained attention. DMN shows the increased amplitude of fluctuation, which correlates with the behavioral fluctuation in a similar frequency range (0.01-0.1 Hz) but not in the lower (<0.01 Hz) or higher (>0.1 Hz) frequency range. This was observed during both auditory and visual sustained attention and was replicable across independent datasets. These results provide a novel insight into the neural source of attention-fluctuation and extend the former concept that DMN was deactivated in cognitive tasks. More generally, our findings highlight the temporal dynamic of the brain-behavior relationship.

Pay attention and you might miss it: Greater learning during attentional lapses

Attentional lapses have been found to impair everything from basic perception to learning and memory. Yet, despite the well-documented costs of lapses on cognition, recent work suggests that lapses might unexpectedly confer some benefits. One potential benefit is that lapses broaden our learning to integrate seemingly irrelevant content that could later prove useful-a benefit that prior research focusing only on goal-relevant memory would miss. Here, we measure how fluctuations in sustained attention influence the learning of seemingly goal-irrelevant content that competes for attention with target content. Participants completed a correlated flanker task in which they categorized central targets (letters or numbers) while ignoring peripheral flanking symbols that shared hidden probabilistic relationships with the targets. We found that across participants, higher rates of attentional lapses correlated with greater learning of the target-flanker relationships. Moreover, within participants, learning was more evident during attentional lapses. These findings address long-standing theoretical debates and reveal a benefit of attentional lapses: they expand the scope of learning and decisions beyond the strictly relevant.

Predicting visual memory across images and within individuals

We only remember a fraction of what we see-including images that are highly memorable and those that we encounter during highly attentive states. However, most models of human memory disregard both an image's memorability and an individual's fluctuating attentional states. Here, we build the first model of memory synthesizing these two disparate factors to predict subsequent image recognition. We combine memorability scores of 1100 images (Experiment 1, n = 706) and attentional state indexed by response time on a continuous performance task (Experiments 2 and 3, n = 57 total). Image memorability and sustained attentional state explained significant variance in image memory, and a joint model of memory including both factors outperformed models including either factor alone. Furthermore, models including both factors successfully predicted memory in an out-of-sample group. Thus, building models based on individual- and image-specific factors allows for directed forecasting of our memories. SIGNIFICANCE STATEMENT: Although memory is a fundamental cognitive process, much of the time memory failures cannot be predicted until it is too late. However, in this study, we show that much of memory is surprisingly pre-determined ahead of time, by factors shared across the population and highly specific to each individual. Specifically, we build a new multidimensional model that predicts memory based just on the images a person sees and when they see them. This research synthesizes findings from disparate domains ranging from computer vision, attention, and memory into a predictive model. These findings have resounding implications for domains such as education, business, and marketing, where it is a top priority to predict (and even manipulate) what information people will remember.

Brain-phenotype models fail for individuals who defy sample stereotypes

Individual differences in brain functional organization track a range of traits, symptoms and behaviours1-12. So far, work modelling linear brain-phenotype relationships has assumed that a single such relationship generalizes across all individuals, but models do not work equally well in all participants13,14. A better understanding of in whom models fail and why is crucial to revealing robust, useful and unbiased brain-phenotype relationships. To this end, here we related brain activity to phenotype using predictive models-trained and tested on independent data to ensure generalizability15-and examined model failure. We applied this data-driven approach to a range of neurocognitive measures in a new, clinically and demographically heterogeneous dataset, with the results replicated in two independent, publicly available datasets16,17. Across all three datasets, we find that models reflect not unitary cognitive constructs, but rather neurocognitive scores intertwined with sociodemographic and clinical covariates; that is, models reflect stereotypical profiles, and fail when applied to individuals who defy them. Model failure is reliable, phenotype specific and generalizable across datasets. Together, these results highlight the pitfalls of a one-size-fits-all modelling approach and the effect of biased phenotypic measures18-20 on the interpretation and utility of resulting brain-phenotype models. We present a framework to address these issues so that such models may reveal the neural circuits that underlie specific phenotypes and ultimately identify individualized neural targets for clinical intervention.

A brain-based general measure of attention

Attention is central to many aspects of cognition, but there is no singular neural measure of a person's overall attentional functioning across tasks. Here, using original data from 92 participants performing three different attention-demanding tasks during functional magnetic resonance imaging, we constructed a suite of whole-brain models that can predict a profile of multiple attentional components (sustained attention, divided attention and tracking, and working memory capacity) for novel individuals. Multiple brain regions across the salience, subcortical and frontoparietal networks drove accurate predictions, supporting a common (general) attention factor across tasks, distinguished from task-specific ones. Furthermore, connectome-to-connectome transformation modelling generated an individual's task-related connectomes from rest functional magnetic resonance imaging, substantially improving predictive power. Finally, combining the connectome transformation and general attention factor, we built a standardized measure that shows superior generalization across four independent datasets (total N = 495) of various attentional measures, suggesting broad utility for research and clinical applications.

Generalizable predictive modeling of semantic processing ability from functional brain connectivity

Semantic processing (SP) is one of the critical abilities of humans for representing and manipulating conceptual and meaningful information. Neuroimaging studies of SP typically collapse data from many subjects, but its neural organization and behavioral performance vary between individuals. It is not yet understood whether and how the individual variabilities in neural network organizations contribute to the individual differences in SP behaviors. We aim to identify the neural signatures underlying SP variabilities by analyzing functional connectivity (FC) patterns based on a large‐sample Human Connectome Project (HCP) dataset and rigorous predictive modeling. We used a two‐stage predictive modeling approach to build an internally cross‐validated model and to test the model's generalizability with unseen data from different HCP samples and other out‐of‐sample datasets. FC patterns within a putative semantic brain network were significantly predictive of individual SP scores summarized from five SP‐related behavioral tests. This cross‐validated model can be used to predict unseen HCP data. The model generalizability was enhanced in the language task compared with other tasks used during scanning and was better for females than males. The model constructed from the HCP dataset can be partially generalized to two independent cohorts that participated in different semantic tasks. FCs connecting to the Perisylvian language network show the most reliable contributions to predictive modeling and the out‐of‐sample generalization. These findings contribute to our understanding of the neural sources of individual differences in SP, which potentially lay the foundation for personalized education for healthy individuals and intervention for SP and language deficits patients.

Hallucinating visual structure: Individual differences in 'scaffolded attention'

Our percepts usually derive their structure from particular cues in the incoming sensory information, but this is not so in the phenomenon of scaffolded attention - where shifting patterns of attention give rise to 'everyday hallucinations' of visual structure even in the absence of sensory cues. When looking at a piece of graph paper, for example, the squares are all identical - yet many people see a shifting array of structured patterns such as lines, crosses, or even block-letters - something that doesn't occur when staring at a blank page. We have informally noted that scaffolded attention is a widely but not universally shared phenomenon - with some people spontaneously experiencing such percepts (even without instruction), others seeing such 'phantom' structures only when actively trying to so, and still others never having such experiences at all. Accordingly, the present study assessed the prevalence of scaffolded attention - both as an ability, and a spontaneous phenomenon. These results were then correlated with several measures of imagery and attention, in an attempt to explain the nature and origin of such individual differences. 40% of observers experienced scaffolded attention spontaneously, and 78% did so when trying - and these differences were uniquely modulated by certain measures of attention (such as attentional breadth, as measured by the 'functional field of view'), but not by measures of the vividness or spontaneity of mental imagery. These results inspire an explanation for scaffolded attention based on spontaneous perceptual grouping.

The Infraslow Frequency Oscillatory Transcranial Direct Current Stimulation Over the Left Dorsolateral Prefrontal Cortex Enhances Sustained Attention

Background

The vigilance fluctuation and decrement of sustained attention have large detrimental consequences to most tasks in daily life, especially among the elderly. Non-invasive brain stimulations (e.g., transcranial direct current stimulation, tDCS) have been widely applied to improve sustained attention, however, with mixed results.

Objective

An infraslow frequency oscillatory tDCS approach was designed to improve sustained attention.

Methods

The infraslow frequency oscillatory tDCS (O-tDCS) over the left dorsolateral prefrontal cortex at 0.05 Hz was designed and compared with conventional tDCS (C-tDCS) to test whether this new protocol improves sustained attention more effectively. The sustained attention was evaluated by reaction time and accuracy.

Results

Compared with the C-tDCS and sham, the O-tDCS significantly enhanced sustained attention by increasing response accuracy, reducing response time, and its variability. These effects were predicted by the evoked oscillation of response time at the stimulation frequency.

Conclusion

Similar to previous studies, the modulation effect of C-tDCS on sustained attention is weak and unstable. In contrast, the O-tDCS effectively and systematically enhances sustained attention by optimizing vigilance fluctuation. The modulation effect of O-tDCS is probably driven by neural oscillations at the infraslow frequency range.

Characterizing mood disorders in the AFFECT study: a large, longitudinal, and phenotypically rich genetic cohort in the US

There has recently been marked progress in identifying genetic risk factors for major depression (MD) and bipolar disorder (BD); however, few systematic efforts have been made to elucidate heterogeneity that exists within and across these diagnostic taxa. The Affective disorders, Environment, and Cognitive Trait (AFFECT) study presents an opportunity to identify and associate the structure of cognition and symptom-level domains across the mood disorder spectrum in a prospective study from a diverse US population.Participants were recruited from the 23andMe, Inc research participant database and through social media; self-reported diagnosis of MD or BD by a medical professional and medication status data were used to enrich for mood-disorder cases. Remote assessments were used to acquire an extensive range of phenotypes, including mood state, transdiagnostic symptom severity, task-based measures of cognition, environmental exposures, personality traits. In this paper we describe the study design, and the demographic and clinical characteristics of the cohort. In addition we report genetic ancestry, SNP heritability, and genetic correlations with other large cohorts of mood disorders.A total of 48,467 participants were enrolled: 14,768 with MD, 9864 with BD, and 23,835 controls. Upon enrollment, 47% of participants with MD and 27% with BD indicated being in an active mood episode. Cases reported early ages of onset (mean = 13.2 and 14.3 years for MD and BD, respectively), and high levels of recurrence (78.6% and 84.9% with >5 episodes), psychotherapy, and psychotropic medication use. SNP heritability on the liability scale for the ascertained MD participants (0.19-0.21) was consistent with the high level of disease severity in this cohort, while BD heritability estimates (0.16-0.22) were comparable to reports in other large scale genomic studies of mood disorders. Genetic correlations between the AFFECT cohort and other large-scale cohorts were high for MD but not for BD. By incorporating transdiagnostic symptom assessments, repeated measures, and genomic data, the AFFECT study represents a unique resource for dissecting the structure of mood disorders across multiple levels of analysis. In addition, the fully remote nature of the study provides valuable insights for future virtual and decentralized clinical trials within mood disorders.

Neurocognition after motor vehicle collision and adverse post-traumatic neuropsychiatric sequelae within 8 weeks: Initial findings from the AURORA study

BACKGROUND

Previous work has indicated that differences in neurocognitive functioning may predict the development of adverse post-traumatic neuropsychiatric sequelae (APNS). Such differences may be vulnerability factors or simply correlates of APNS-related symptoms. Longitudinal studies that measure neurocognitive functioning at the time of trauma are needed to determine whether such differences precede the development of APNS.

METHODS

Here, we present findings from a subsample of 666 ambulatory patients from the AURORA (Advancing Understanding of RecOvery afteR trumA) study. All patients presented to EDs after a motor vehicle collision (MVC). We examined associations of neurocognitive test performance shortly after MVC with peritraumatic symptoms in the ED and APNS (depression, post-traumatic stress, post-concussive symptoms, and pain) 2 weeks and 8 weeks later. Neurocognitive tests assessed processing speed, attention, verbal reasoning, memory, and social perception.

RESULTS

Distress in the ED was associated with poorer processing speed and short-term memory. Poorer short-term memory was also associated with depression at 2 weeks post-MVC, even after controlling for peritraumatic distress. Finally, higher vocabulary scores were associated with pain 2 weeks post-MVC.

LIMITATIONS

Self-selection biases among those who present to the ED and enroll in the study limit generalizability. Also, it is not clear whether observed neurocognitive differences predate MVC exposure or arise in the immediate aftermath of MVC exposure.

CONCLUSIONS

Our results suggest that processing speed and short-term memory may be useful predictors of trauma-related characteristics and the development of some APNS, making such measures clinically-relevant for identifying at-risk individuals.

The Roles of Salience and Value in Inattention Among Children With Attention-Deficit/Hyperactivity Disorder: A Pilot Investigation

Although inattention is a key symptom subdomain of attention-deficit/hyperactivity disorder (ADHD), the mechanisms underlying this subdomain and related symptoms remain unclear. There is a need for more granular approaches that allow for greater specificity in linking disruptions in specific domains of cognitive performance (e.g., executive function and reward processing) with behavioral manifestations of ADHD. Such approaches may inform the development of more targeted therapeutic interventions. Here, we describe the results of a pilot study of elementary-aged children (ages 6–12years) with ADHD (n=50) and typically developing children (n=48) utilizing a cognitive science task designed to target two dissociable mechanisms of attentional selection: a goal-driven mechanism (i.e., reward/value-driven) and a salience-driven mechanism. Participants were asked to optimally extract and combine information about stimulus salience and value to maximize rewards. While results of this pilot study are ambiguous due to the small sample size and limited number of task trials, data suggest that neither participants with ADHD nor typically developing participants performed optimally to maximize rewards, though typically developing participants were somewhat more successful at the task (i.e., more likely to report high-value targets) regardless of task condition. Further, the manuscript examines several follow-up questions regarding group differences in task response times and group differences in task performance as related to sustained attention across the duration of the task. Finally, the manuscript examines follow-up questions related to heterogeneity in the ADHD group (i.e., age, DSM 5 presentation, and comorbid diagnosis) in predicting task performance.

Sustained Attention and Spatial Attention Distinctly Influence Long-term Memory Encoding

Our attention is critically important for what we remember. Prior measures of the relationship between attention and memory, however, have largely treated "attention" as a monolith. Here, across three experiments, we provide evidence for two dissociable aspects of attention that influence encoding into long-term memory. Using spatial cues together with a sensitive continuous report procedure, we find that long-term memory response error is affected by both trial-by-trial fluctuations of sustained attention and prioritization via covert spatial attention. Furthermore, using multivariate analyses of EEG, we track both sustained attention and spatial attention before stimulus onset. Intriguingly, even during moments of low sustained attention, there is no decline in the representation of the spatially attended location, showing that these two aspects of attention have robust but independent effects on long-term memory encoding. Finally, sustained and spatial attention predicted distinct variance in long-term memory performance across individuals. That is, the relationship between attention and long-term memory suggests a composite model, wherein distinct attentional subcomponents influence encoding into long-term memory. These results point toward a taxonomy of the distinct attentional processes that constrain our memories.

Neural signatures of attentional engagement during narratives and its consequences for event memory

As we comprehend narratives, our attentional engagement fluctuates over time. Despite theoretical conceptions of narrative engagement as emotion-laden attention, little empirical work has characterized the cognitive and neural processes that comprise subjective engagement in naturalistic contexts or its consequences for memory. Here, we relate fluctuations in narrative engagement to patterns of brain coactivation and test whether neural signatures of engagement predict subsequent memory. In behavioral studies, participants continuously rated how engaged they were as they watched a television episode or listened to a story. Self-reported engagement was synchronized across individuals and driven by the emotional content of the narratives. In functional MRI datasets collected as different individuals watched the same show or listened to the same story, engagement drove neural synchrony, such that default mode network activity was more synchronized across individuals during more engaging moments of the narratives. Furthermore, models based on time-varying functional brain connectivity predicted evolving states of engagement across participants and independent datasets. The functional connections that predicted engagement overlapped with a validated neuromarker of sustained attention and predicted recall of narrative events. Together, our findings characterize the neural signatures of attentional engagement in naturalistic contexts and elucidate relationships among narrative engagement, sustained attention, and event memory.

How do we measure attention? Using factor analysis to establish construct validity of neuropsychological tests

We investigated whether standardized neuropsychological tests and experimental cognitive paradigms measure the same cognitive faculties. Specifically, do neuropsychological tests commonly used to assess attention measure the same construct as attention paradigms used in cognitive psychology and neuroscience? We built on the “general attention factor”, comprising several widely used experimental paradigms (Huang et al., 2012). Participants (n = 636) completed an on-line battery (TestMyBrain.org) of six experimental tests [Multiple Object Tracking, Flanker Interference, Visual Working Memory, Approximate Number Sense, Spatial Configuration Visual Search, and Gradual Onset Continuous Performance Task (Grad CPT)] and eight neuropsychological tests [Trail Making Test versions A & B (TMT-A, TMT-B), Digit Symbol Coding, Forward and Backward Digit Span, Letter Cancellation, Spatial Span, and Arithmetic]. Exploratory factor analysis in a subset of 357 participants identified a five-factor structure: (1) attentional capacity (Multiple Object Tracking, Visual Working Memory, Digit Symbol Coding, Spatial Span), (2) search (Visual Search, TMT-A, TMT-B, Letter Cancellation); (3) Digit Span; (4) Arithmetic; and (5) Sustained Attention (GradCPT). Confirmatory analysis in 279 held-out participants showed that this model fit better than competing models. A hierarchical model where a general cognitive factor was imposed above the five specific factors fit as well as the model without the general factor. We conclude that Digit Span and Arithmetic tests should not be classified as attention tests. Digit Symbol Coding and Spatial Span tap attentional capacity, while TMT-A, TMT-B, and Letter Cancellation tap search (or attention-shifting) ability. These five tests can be classified as attention tests.

EEG Correlates of Sustained Attention Variability during Discrete Multi-finger Force Control Tasks

The neurophysiological characteristics of sustained attention states are unclear in discrete multi-finger force control tasks. In this article, we developed an immersive visuo-haptic task for conducting stimulus-response measurements. Visual cues were randomly provided to signify the required amplitude and tolerance of fingertip force. Participants were required to respond to the visual cues by pressing force transducers using their fingertips. Response time variation was taken as a behavioral measure of sustained attention states during the task. 50% low-variability trials were classified as the optimal state and the other high-variability trials were classified as the suboptimal state using z-scoring over time. A 64-channel electroencephalogram (EEG) acquisition system was used to collect brain activities during the tasks. The haptics-elicited potential amplitude at 20 ∼ 40 ms in latency and over the frontal-central region significantly decreased in the optimal state. Furthermore, the alpha-band power in the spectra of 8 ∼ 13 Hz was significantly suppressed in the frontal-central, right temporal, and parietal regions in the optimal state. Taken together, we have identified neuroelectrophysiological features that were associated with sustained attention during multi-finger force control tasks, which would be potentially used in the development of closed-loop attention detection and training systems exploiting haptic interaction.

Do concerns about COVID-19 impair sustained attention?

The novel coronavirus disease 2019 (COVID-19) has considerably heightened health and financial concerns for many individuals. Similar concerns, such as those associated with poverty, impair performance on cognitive control tasks. If ongoing concerns about COVID-19 substantially increase the tendency to mind wander in tasks requiring sustained attention, these worries could degrade performance on a wide range of tasks, leading, for example, to increased traffic accidents, diminished educational achievement, and lower workplace productivity. In two pre-registered experiments, we investigated the degree to which young adults' concerns about COVID-19 correlated with their ability to sustain attention. Experiment 1 tested mainly European participants during an early phase of the pandemic. After completing a survey probing COVID-related concerns, participants engaged in a continuous performance task (CPT) over two, 4-min blocks, during which they responded to city scenes that occurred 90% of the time and withheld responses to mountain scenes that occurred 10% of the time. Despite large and stable individual differences, performance on the scene CPT did not significantly correlate with the severity of COVID-related concerns obtained from the survey. Experiment 2 tested US participants during a later phase of the pandemic. Once again, CPT performance did not significantly correlate with COVID concerns expressed in a pre-task survey. However, participants who had more task-unrelated thoughts performed more poorly on the CPT. These findings suggest that although COVID-19 increased anxiety in a broad swath of society, young adults are able to hold these concerns in a latent format, minimizing their impact on performance in a demanding sustained attention task.

Moment-to-Moment Continuous Attention Fluctuation Monitoring through Consumer-Grade EEG Device

While numerous studies have explored using various sensing techniques to measure attention states, moment-to-moment attention fluctuation measurement is unavailable. To bridge this gap, we applied a novel paradigm in psychology, the gradual-onset continuous performance task (gradCPT), to collect the ground truth of attention states. GradCPT allows for the precise labeling of attention fluctuation on an 800 ms time scale. We then developed a new technique for measuring continuous attention fluctuation, based on a machine learning approach that uses the spectral properties of EEG signals as the main features. We demonstrated that, even using a consumer grade EEG device, the detection accuracy of moment-to-moment attention fluctuations was 73.49%. Next, we empirically validated our technique in a video learning scenario and found that our technique match with the classification obtained through thought probes, with an average F1 score of 0.77. Our results suggest the effectiveness of using gradCPT as a ground truth labeling method and the feasibility of using consumer-grade EEG devices for continuous attention fluctuation detection.

Intracranial Electroencephalography Reveals Selective Responses to Cognitive Stimuli in the Periventricular Heterotopias

Our recent work suggests that non-lesional epileptic brain tissue is capable of generating normal neurophysiological responses during cognitive tasks, which are then seized by ongoing pathologic epileptic activity. Here, we aim to extend the scope of our work to epileptic periventricular heterotopias (PVH) and examine whether the PVH tissue also exhibits normal neurophysiological responses and network-level integration with other non-lesional cortical regions. As part of routine clinical assessment, three adult patients with PVH underwent implantation of intracranial electrodes and participated in experimental cognitive tasks. We obtained simultaneous recordings from PVH and remote cortical sites during rest as well as controlled experimental conditions. In all three subjects (two females), cognitive experimental conditions evoked significant electrophysiological responses in discrete locations within the PVH tissue that were correlated with responses seen in non-epileptic cortical sites. Moreover, the responsive PVH sites exhibited correlated electrophysiological activity with responsive, non-lesional cortical sites during rest conditions. Taken together, our work clearly demonstrates that the PVH tissue may be functionally organized and it may be functionally integrated within cognitively engaged cortical networks despite its anatomic displacement during neurodevelopment.SIGNIFICANCE STATEMENT Periventricular heterotopias (PVH) are developmentally abnormal brain tissues that frequently cause epileptic seizures. In a rare opportunity to obtain direct electrophysiological recordings from PVH, we were able to show that, contrary to common assumptions, PVH functional activity is similar to healthy cortical sites during a well-established cognitive task and exhibits clear resting state connectivity with the responsive cortical regions.

Brain state-based detection of attentional fluctuations and their modulation

In the search for brain markers of optimal attentional focus, the mainstream approach has been to first define attentional states based on behavioral performance, and to subsequently investigate "neural correlates" associated with these performance variations. However, this approach constrains the range of contexts in which attentional states can be operationalized by relying on overt behavior, and assumes a one-to-one correspondence between behavior and brain state. Here, we reversed the logic of these previous studies and sought to identify behaviorally-relevant brain states based solely on brain activity, agnostic to behavioral performance. In four independent datasets, we found that the same two brain states were dominant during a sustained attention task. One state was behaviorally optimal, with higher accuracy and stability, but a greater tendency to mind wander (State1). The second state was behaviorally suboptimal, with lower accuracy and instability (State2). We further demonstrate how these brain states were impacted by motivation and attention-deficit/hyperactivity disorder (ADHD). Individuals with ADHD spent more time in suboptimal State2 and less time in optimal State1 than healthy controls. Motivation overcame the suboptimal behavior associated with State2. Our study provides compelling evidence for the existence of two attentional states from the sole viewpoint of brain activity.

Neural signatures of vigilance decrements predict behavioural errors before they occur

There are many monitoring environments, such as railway control, in which lapses of attention can have tragic consequences. Problematically, sustained monitoring for rare targets is difficult, with more misses and longer reaction times over time. What changes in the brain underpin these 'vigilance decrements'? We designed a multiple-object monitoring (MOM) paradigm to examine how the neural representation of information varied with target frequency and time performing the task. Behavioural performance decreased over time for the rare target (monitoring) condition, but not for a frequent target (active) condition. This was mirrored in neural decoding using magnetoencephalography: coding of critical information declined more during monitoring versus active conditions along the experiment. We developed new analyses that can predict behavioural errors from the neural data more than a second before they occurred. This facilitates pre-empting behavioural errors due to lapses in attention and provides new insight into the neural correlates of vigilance decrements.

Real-Time Decoding of Attentional States Using Closed-Loop EEG Neurofeedback

Sustained attention is a cognitive ability to maintain task focus over extended periods of time (Mackworth, 1948; Chun, Golomb, & Turk-Browne, 2011). In this study, scalp electroencephalography (EEG) signals were processed in real time using a 32 dry-electrode system during a sustained visual attention task. An attention training paradigm was implemented, as designed in DeBettencourt, Cohen, Lee, Norman, and Turk-Browne (2015) in which the composition of a sequence of blended images is updated based on the participant's decoded attentional level to a primed image category. It was hypothesized that a single neurofeedback training session would improve sustained attention abilities. Twenty-two participants were trained on a single neurofeedback session with behavioral pretraining and posttraining sessions within three consecutive days. Half of the participants functioned as controls in a double-blinded design and received sham neurofeedback. During the neurofeedback session, attentional states to primed categories were decoded in real time and used to provide a continuous feedback signal customized to each participant in a closed-loop approach. We report a mean classifier decoding error rate of 34.3% (chance = 50%). Within the neurofeedback group, there was a greater level of task-relevant attentional information decoded in the participant's brain before making a correct behavioral response than before an incorrect response. This effect was not visible in the control group (interaction p=7.23e-4), which strongly indicates that we were able to achieve a meaningful measure of subjective attentional state in real time and control participants' behavior during the neurofeedback session. We do not provide conclusive evidence whether the single neurofeedback session per se provided lasting effects in sustained attention abilities. We developed a portable EEG neurofeedback system capable of decoding attentional states and predicting behavioral choices in the attention task at hand. The neurofeedback code framework is Python based and open source, and it allows users to actively engage in the development of neurofeedback tools for scientific and translational use.

Bistable perception alternates between internal and external modes of sensory processing

Perceptual history can exert pronounced effects on the contents of conscious experience: when confronted with completely ambiguous stimuli, perception does not waver at random between diverging stimulus interpretations but sticks with recent percepts for prolonged intervals. Here, we investigated the relevance of perceptual history in situations more similar to everyday experience, where sensory stimuli are usually not completely ambiguous. Using partially ambiguous visual stimuli, we found that the balance between past and present is not stable over time but slowly fluctuates between two opposing modes. For time periods of up to several minutes, perception was either largely determined by perceptual history or driven predominantly by disambiguating sensory evidence. Computational modeling suggested that the construction of unambiguous conscious experiences is modulated by slow fluctuations between internally and externally oriented modes of sensory processing.

A Multi-Method Approach to a Comprehensive Examination of the Psychiatric and Neurological Consequences of Intimate Partner Violence in Women: A Methodology Protocol

The number of women in the United States that experience blows to the head during assaults by intimate partners is substantial. The number of head blows that result in a traumatic brain injury (TBI) is virtually unknown, but estimates far exceed numbers of TBI in parallel populations (e.g., blast exposure, accidents, sports) combined. Research on the impact of TBI on post-traumatic stress disorder (PTSD) in survivors of intimate partner violence (IPV) is sparse. This methodology paper describes the comprehensive, multi-method approach used by a multi-disciplinary team of investigators from several different fields of expertise to assess the interaction of psychiatric, cognitive, psychological, and physical conditions that result from IPV. Using state-of-the-art instruments, a comprehensive assessment of lifetime trauma exposure, lifetime history of TBI, psychiatric history, and a full assessment of current cognitive, neuropsychological and biomedical function was conducted with 51 female survivors of IPV who screened positive for PTSD. This multi-method assessment included clinician-administered diagnostic interviews modified to specifically assess the sequelae of IPV, standardized self-report surveys, neuropsychological tests, structural, diffusion, and functional neuroimaging and blood-based biomarkers. The specific details and full report of the results of the full study are beyond the scope of this methodology paper. Descriptive characteristics of the complex clinical presentation observed in this unique sample are described. The sample reported high rates of trauma exposure across the lifespan and 80% met full criteria for current PTSD. Women also reported high rates of lifetime subconcussive head injury (88.2%) and TBI (52.9%) from various etiologies (35.3% secondary to IPV). Descriptive findings from the methodological protocol described here have begun to reveal information that will advance our understanding of the impact of subconcussive head injury and TBI on recovery from mental injury among IPV survivors.

How to Interpret Resting-State fMRI: Ask Your Participants

Resting-state fMRI (rsfMRI) reveals brain dynamics in a task-unconstrained environment as subjects let their minds wander freely. Consequently, resting subjects navigate a rich space of cognitive and perceptual states (i.e., ongoing experience). How this ongoing experience shapes rsfMRI summary metrics (e.g., functional connectivity) is unknown, yet likely to contribute uniquely to within- and between-subject differences. Here we argue that understanding the role of ongoing experience in rsfMRI requires access to standardized, temporally resolved, scientifically validated first-person descriptions of those experiences. We suggest best practices for obtaining those descriptions via introspective methods appropriately adapted for use in fMRI research. We conclude with a set of guidelines for fusing these two data types to answer pressing questions about the etiology of rsfMRI.

Low-motion fMRI data can be obtained in pediatric participants undergoing a 60-minute scan protocol

Performing functional magnetic resonance imaging (fMRI) scans of children can be a difficult task, as participants tend to move while being scanned. Head motion represents a significant confound in fMRI connectivity analyses. One approach to limit motion has been to use shorter MRI protocols, though this reduces the reliability of results. Hence, there is a need to implement methods to achieve high-quality, low-motion data while not sacrificing data quantity. Here we show that by using a mock scan protocol prior to a scan, in conjunction with other in-scan steps (weighted blanket and incentive system), it is possible to achieve low-motion fMRI data in pediatric participants (age range: 7-17 years old) undergoing a 60 min MRI session. We also observe that motion is low during the MRI protocol in a separate replication group of participants, including some with autism spectrum disorder. Collectively, the results indicate it is possible to conduct long scan protocols in difficult-to-scan populations and still achieve high-quality data, thus potentially allowing more reliable fMRI findings.

Physiological Synchrony in EEG, Electrodermal Activity and Heart Rate Detects Attentionally Relevant Events in Time

Interpersonal physiological synchrony (PS), or the similarity of physiological signals between individuals over time, may be used to detect attentionally engaging moments in time. We here investigated whether PS in the electroencephalogram (EEG), electrodermal activity (EDA), heart rate and a multimodal metric signals the occurrence of attentionally relevant events in time in two groups of participants. Both groups were presented with the same auditory stimulus, but were instructed to attend either to the narrative of an audiobook (audiobook-attending: AA group) or to interspersed emotional sounds and beeps (stimulus-attending: SA group). We hypothesized that emotional sounds could be detected in both groups as they are expected to draw attention involuntarily, in a bottom-up fashion. Indeed, we found this to be the case for PS in EDA or the multimodal metric. Beeps, that are expected to be only relevant due to specific "top-down" attentional instructions, could indeed only be detected using PS among SA participants, for EDA, EEG and the multimodal metric. We further hypothesized that moments in the audiobook accompanied by high PS in either EEG, EDA, heart rate or the multimodal metric for AA participants would be rated as more engaging by an independent group of participants compared to moments corresponding to low PS. This hypothesis was not supported. Our results show that PS can support the detection of attentionally engaging events over time. Currently, the relation between PS and engagement is only established for well-defined, interspersed stimuli, whereas the relation between PS and a more abstract self-reported metric of engagement over time has not been established. As the relation between PS and engagement is dependent on event type and physiological measure, we suggest to choose a measure matching with the stimulus of interest. When the stimulus type is unknown, a multimodal metric is most robust.

Memory failure predicted by attention lapsing and media multitasking

With the explosion of digital media and technologies, scholars, educators and the public have become increasingly vocal about the role that an 'attention economy' has in our lives1. The rise of the current digital culture coincides with longstanding scientific questions about why humans sometimes remember and sometimes forget, and why some individuals remember better than others2-6. Here we examine whether spontaneous attention lapses-in the moment7-12, across individuals13-15 and as a function of everyday media multitasking16-19-negatively correlate with remembering. Electroencephalography and pupillometry measures of attention20,21 were recorded as eighty young adults (mean age, 21.7 years) performed a goal-directed episodic encoding and retrieval task22. Trait-level sustained attention was further quantified using task-based23 and questionnaire measures24,25. Using trial-to-trial retrieval data, we show that tonic lapses in attention in the moment before remembering, assayed by posterior alpha power and pupil diameter, were correlated with reductions in neural signals of goal coding and memory, along with behavioural forgetting. Independent measures of trait-level attention lapsing mediated the relationship between neural assays of lapsing and memory performance, and between media multitasking and memory. Attention lapses partially account for why we remember or forget in the moment, and why some individuals remember better than others. Heavier media multitasking is associated with a propensity to have attention lapses and forget.

Childhood Adversity and Dimensional Variations in Adult Sustained Attention

Background and Objective

Sustained attention is a transdiagnostic phenotype linked with most forms of psychopathology. We sought to understand factors that influence the development of sustained attention, by looking at the relationship between childhood adversity and adult sustained attention.

Participants, Setting, and Methods

Participants were 5,973 TestMyBrain.org visitors from English-speaking countries who completed a continuous performance task (gradCPT) of sustained attention and a childhood adversity questionnaire. We analyzed gradCPT performance using a signal detection approach.

Results

Discrimination ability (the main metric of performance on the gradCPT) was associated with total childhood adversity load, even when controlling for covariates related to age, gender, parental education, race, country of origin, and relative socioeconomic status (β = −0.079, b = −0.032).

Conclusion

Our results demonstrate that attention differences related to childhood adversity exposure can (1) be measured using brief, performance-based measures of sustained attention, (2) persist into adulthood, and (3) be detected at the population level. These results, paired with the well-documented associations between sustained attention and psychopathology, indicate that sustained attention may be an important mechanism for understanding early influences on mental health.