Spontaneous default network activity reflects behavioral variability independent of mind-wandering

Task-dependent functional connectivity changes in response to varying levels of social support

BACKGROUND

Having social support improves one's health outcomes and self-esteem, and buffers the negative impact of stressors. Previous studies have explored the association between social support and brain activity, but evidence from task-dependent functional connectivity is still limited.

AIMS

We aimed to explore how gradually decreasing levels of social support influence task-dependent functional connectivity across several major neural networks.

METHOD

We designed a social support task and recruited 72 young adults from real-life social groups. Of the four members in each group, one healthy participant (18 participants in total) completed the functional magnetic resonance imaging (fMRI) scan. The fMRI task included three phases with varying levels of social support: high-support phase, fair phase and low-support phase. Functional connectivity changes according to three phases were examined by generalised psychophysiological interaction analysis.

RESULTS

The results of the analysis demonstrated that participants losing expected support showed increased connectivity among salience network, default mood network and frontoparietal network nodes during the fair phase compared with the high-support phase. During the low-support phase, participants showed increased connectivity among only salience network nodes compared with the high-support phase.

CONCLUSIONS

The results indicate that the loss of support was perceived as a threat signal and induced widespread increased functional connectivity within brain networks. The observation of significant functional connectivity changes between fair and high-support phases suggests that even a small loss of social support from close ones leads to major changes in brain function.

Increasing mind wandering with accelerated intermittent theta burst stimulation over the left dorsolateral prefrontal cortex

Mind wandering (MW) is the intentional or unintentional experience of attending to internal task-unrelated thoughts while being occupied with an external task. Even though maintaining task focus is assumed to require executive functions (EF), it is not clear how and to what extent MW and EF interact. Research has found that activity in the dorsolateral prefrontal cortex (DLPFC) is associated with EF and MW. To understand the causal role of the DLPFC in relation to MW and EF, researchers have turned to non-invasive brain stimulation. Thus far, most studies have used transcranial direct current stimulation, but the results have been inconclusive. To further elucidate the relationship between the DLPFC, EF and MW, we conducted a pre-registered, sham-controlled, triple-blinded within-subject experiment by combining intermittent theta burst stimulation (iTBS) interleaved with a recently developed MW-EF task. In contrast to our expectations, participants reported significantly more MW following real iTBS as compared to sham stimulation. However, at the same time, psychomotor precision and EF improved, indicating that participants were able to engage in resource-intensive MW while simultaneously performing well on the task. We argue that iTBS enhanced the underlying executive resources that could be used to increase both MW and task performance in line with the resource-control view of MW. This finding opens exciting avenues for studying the complex interplay between MW and EF and provides empirical support for the utility of iTBS in improving executive performance during a demanding cognitive task.

Linking the neural signature of response time variability to Alzheimer's disease pathology and cognitive functioning

Promising evidence has suggested potential links between mind-wandering and Alzheimer's disease (AD). Yet, older adults with diagnosable neurocognitive disorders show reduced meta-awareness, thus questioning the validity of probe-assessed mind-wandering in older adults. In prior work, we employed response time variability as an objective, albeit indirect, marker of mind-wandering to identify patterns of functional connectivity that predicted mind-wandering. In the current study, we evaluated the association of this connectome-based, mind-wandering model with cerebral spinal fluid (CSF) p-tau/Aβ 42 ratio in 289 older adults from the Alzheimer's Disease NeuroImaging Initiative (ADNI). Moreover, we examined if this model was similarly associated with individual differences in composite measures of global cognition, episodic memory, and executive functioning. Edges from the high response time variability model were significantly associated with CSF p-tau/Aβ ratio. Furthermore, connectivity strength within edges associated with high response time variability was negatively associated with global cognition and episodic memory functioning. This study provides the first empirical support for a link between an objective neuromarker of mind-wandering and AD pathophysiology. Given the observed association between mind-wandering and cognitive functioning in older adults, interventions targeted at reducing mind-wandering, particularly before the onset of AD pathogenesis, may make a significant contribution to the prevention of AD-related cognitive decline.

Individual variability in neural representations of mind-wandering

Mind-wandering is a frequent, daily mental activity, experienced in unique ways in each person. Yet neuroimaging evidence relating mind-wandering to brain activity, for example in the default mode network (DMN), has relied on population- rather than individual-based inferences owing to limited within-person sampling. Here, three densely sampled individuals each reported hundreds of mind-wandering episodes while undergoing multi-session functional magnetic resonance imaging. We found reliable associations between mind-wandering and DMN activation when estimating brain networks within individuals using precision functional mapping. However, the timing of spontaneous DMN activity relative to subjective reports, and the networks beyond DMN that were activated and deactivated during mind-wandering, were distinct across individuals. Connectome-based predictive modeling further revealed idiosyncratic, whole-brain functional connectivity patterns that consistently predicted mind-wandering within individuals but did not fully generalize across individuals. Predictive models of mind-wandering and attention that were derived from larger-scale neuroimaging datasets largely failed when applied to densely sampled individuals, further highlighting the need for personalized models. Our work offers novel evidence for both conserved and variable neural representations of self-reported mind-wandering in different individuals. The previously unrecognized interindividual variations reported here underscore the broader scientific value and potential clinical utility of idiographic approaches to brain-experience associations.

From gut to brain: unveiling probiotic effects through a neuroimaging perspective-A systematic review of randomized controlled trials

The gut-brain axis, a bidirectional communication network between the gastrointestinal system and the brain, significantly influences mental health and behavior. Probiotics, live microorganisms conferring health benefits, have garnered attention for their potential to modulate this axis. However, their effects on brain function through gut microbiota modulation remain controversial. This systematic review examines the effects of probiotics on brain activity and functioning, focusing on randomized controlled trials using both resting-state and task-based functional magnetic resonance imaging (fMRI) methodologies. Studies investigating probiotic effects on brain activity in healthy individuals and clinical populations (i.e., major depressive disorder and irritable bowel syndrome) were identified. In healthy individuals, task-based fMRI studies indicated that probiotics modulate brain activity related to emotional regulation and cognitive processing, particularly in high-order areas such as the amygdala, precuneus, and orbitofrontal cortex. Resting-state fMRI studies revealed changes in connectivity patterns, such as increased activation in the Salience Network and reduced activity in the Default Mode Network. In clinical populations, task-based fMRI studies showed that probiotics could normalize brain function in patients with major depressive disorder and irritable bowel syndrome. Resting-state fMRI studies further suggested improved connectivity in mood-regulating networks, specifically in the subcallosal cortex, amygdala and hippocampus. Despite promising findings, methodological variability and limited sample sizes emphasize the need for rigorous, longitudinal research to clarify the beneficial effects of probiotics on the gut-brain axis and mental health.

Examination of Excessive Mind-Wandering Following Attention-Deficit and Hyperactivity Disorder Treatment in Adults

Although mind-wandering (MW) is a part of attention deficit and hyperactivity disorder (ADHD), the impact of psychostimulants on excessive MW remains unclear. We aimed to elucidate how psychostimulants impact the MW of adult ADHD patients post treatment. This cross-sectional cohort study consisted of 54 randomly selected ADHD patients who applied to our psychiatry outpatient clinic and 40 healthy controls. The ADHD patients were administered methylphenidate or atomoxetine. A Semi-Structured Sociodemographic and Clinical Data Form, the Adult ADHD Self-Report Scale (ASRS), and the Mind Excessively Wandering Scale (MEWS) were applied. Routine psychiatric assessments in the 1st, 2nd, and 3rd months of pharmacological treatment were carried out by a psychiatrist. The pre-treatment MEWS score of the ADHD patients was 26.09 ± 1.92, which significantly decreased to 12.78 ± 2.54 post-treatment (F = 715.250, p < .001). A statistically significant difference was identified between the mean pre-treatment ASRS total score (44.07 ± 10.09) and post-treatment score (27.34 ± 11.22; F = 50.364, p < .001). A lifetime history of alcohol/substance use was positively associated with the MEWS score. ADHD pharmacotherapy led to significant reductions in MW. Recognizing the interaction between MW and ADHD could help in the design of more specific and comprehensive interventions.

Effects of task type on spontaneous alternations of attentional states

Mind wandering is a common occurrence that can have serious consequences, but estimating when mind wandering occurs is a challenging research question. Previous research has shown that during meditation, people may spontaneously alternate between task-oriented and mind-wandering states without awareness (Zukosky & Wang, 2021, Cognition, 212, Article 104689). However, under what conditions such alternations occur is not clear. The present study examined the effects of task type on spontaneous alternations between task focus and mind wandering. In addition to a meditation task, participants performed either a scene-categorization-based CPT or a visual detection task while attentional orientation was assessed via self-monitoring and intermittent probes. The three tasks differ in the extent of their reliance on continuous monitoring (less required in the detection than meditation and CPT tasks) and attentional orientation (oriented internally in meditation task and externally in CPT and detection tasks). To overcome prior methodological challenges, we applied a technique designed to detect spontaneous alternations between focused and mind-wandering states without awareness, based on how the proportion of "focused" responses/ratings to intermittent probes changes during a focus-to-mind-wandering interval (i.e., the period from one self-report of mind wandering to the subsequent self-report). Our results showed that the proportion of "focused" responses to intermittent probes remained constant with increasing interprobe interval during meditation (consistent with previous work), but declined significantly in the CPT and detection tasks. These findings support the hypothesis that spontaneous alternations of attentional states without self-awareness occur during tasks emphasizing internally but not externally oriented attention.

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.

A three-dimensional model of neural activity and phenomenal-behavioral patterns

How phenomenal experience and behavior are related to neural activity in physiology and psychopathology represents a fundamental question in neuroscience and psychiatry. The phenomenal-behavior patterns may be deconstructed into basic dimensions, i.e., psychomotricity, affectivity, and thought, which might have distinct neural correlates. This work provides a data overview on the relationship of these phenomenal-behavioral dimensions with brain activity across physiological and pathological conditions (including major depressive disorder, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, anxiety disorders, addictive disorders, Parkinson's disease, Tourette syndrome, Alzheimer's disease, and frontotemporal dementia). Accordingly, we propose a three-dimensional model of neural activity and phenomenal-behavioral patterns. In this model, neural activity is organized into distinct units in accordance with connectivity patterns and related input/output processing, manifesting in the different phenomenal-behavioral dimensions. (1) An external neural unit, which involves the sensorimotor circuit/brain's sensorimotor network and is connected with the external environment, processes external inputs/outputs, manifesting in the psychomotor dimension (processing of exteroception/somatomotor activity). External unit hyperactivity manifests in psychomotor excitation (hyperactivity/hyperkinesia/catatonia), while external unit hypoactivity manifests in psychomotor inhibition (retardation/hypokinesia/catatonia). (2) An internal neural unit, which involves the interoceptive-autonomic circuit/brain's salience network and is connected with the internal/body environment, processes internal inputs/outputs, manifesting in the affective dimension (processing of interoception/autonomic activity). Internal unit hyperactivity manifests in affective excitation (anxiety/dysphoria-euphoria/panic), while internal unit hypoactivity manifests in affective inhibition (anhedonia/apathy/depersonalization). (3) An associative neural unit, which involves the brain's associative areas/default-mode network and is connected with the external/internal units (but not with the environment), processes associative inputs/outputs, manifesting in the thought dimension (processing of ideas). Associative unit hyperactivity manifests in thought excitation (mind-wandering/repetitive thinking/psychosis), while associative unit hypoactivity manifests in thought inhibition (inattention/cognitive deficit/consciousness loss). Finally, these neural units interplay and dynamically combine into various neural states, resulting in the complex phenomenal experience and behavior across physiology and neuropsychiatric disorders.

Low-frequency variability in theta activity modulates the attention-fluctuation across task and resting states

Sustained attention is not constant but fluctuates influencing our task performance. Albeit intensive investigations, it remains unclear whether the attention-fluctuation during tasks is derived from its spontaneous fluctuation in the resting state. Here, we addressed this issue by investigating the attention-fluctuation in both task and resting states, through the EEG measurement of theta-variability. We found significant rest-task modulation of theta-variability, i.e., reduced theta-variability in the task state compared to the resting state. This task and rest modulation was manifested in the low-frequency of theta-variability (<0.1 Hz). Furthermore, the low-frequency theta-variability exhibited a significant rest-task correlation, however, only the low-frequency theta-variability in the task state but not in the resting state was correlated with the behavioral performance. These findings shed light on the low-frequency feature of attention-fluctuation, and advanced our understanding of sustained attention by suggesting that the theta-variability in low-frequencies was relevant to attention level in task state.

Individual variability in neural representations of mind-wandering

Mind-wandering is a frequent, daily mental activity, experienced in unique ways in each person. Yet neuroimaging evidence relating mind-wandering to brain activity, for example in the default mode network (DMN), has relied on population-rather than individual-based inferences due to limited within-individual sampling. Here, three densely-sampled individuals each reported hundreds of mind-wandering episodes while undergoing multi-session functional magnetic resonance imaging. We found reliable associations between mind-wandering and DMN activation when estimating brain networks within individuals using precision functional mapping. However, the timing of spontaneous DMN activity relative to subjective reports, and the networks beyond DMN that were activated and deactivated during mind-wandering, were distinct across individuals. Connectome-based predictive modeling further revealed idiosyncratic, whole-brain functional connectivity patterns that consistently predicted mind-wandering within individuals but did not fully generalize across individuals. Predictive models of mind-wandering and attention that were derived from larger-scale neuroimaging datasets largely failed when applied to densely-sampled individuals, further highlighting the need for personalized models. Our work offers novel evidence for both conserved and variable neural representations of self-reported mind-wandering in different individuals. The previously-unrecognized inter-individual variations reported here underscore the broader scientific value and potential clinical utility of idiographic approaches to brain-experience associations.

Design and Implementation of a Brief Digital Mindfulness and Compassion Training App for Health Care Professionals: Cluster Randomized Controlled Trial

BACKGROUND

Several studies show that intense work schedules make health care professionals particularly vulnerable to emotional exhaustion and burnout.

OBJECTIVE

In this scenario, promoting self-compassion and mindfulness may be beneficial for well-being. Notably, scalable, digital app-based methods may have the potential to enhance self-compassion and mindfulness in health care professionals.

METHODS

In this study, we designed and implemented a scalable, digital app-based, brief mindfulness and compassion training program called "WellMind" for health care professionals. A total of 22 adult participants completed up to 60 sessions of WellMind training, 5-10 minutes in duration each, over 3 months. Participants completed behavioral assessments measuring self-compassion and mindfulness at baseline (preintervention), 3 months (postintervention), and 6 months (follow-up). In order to control for practice effects on the repeat assessments and calculate effect sizes, we also studied a no-contact control group of 21 health care professionals who only completed the repeated assessments but were not provided any training. Additionally, we evaluated pre- and postintervention neural activity in core brain networks using electroencephalography source imaging as an objective neurophysiological training outcome.

RESULTS

Findings showed a post- versus preintervention increase in self-compassion (Cohen d=0.57; P=.007) and state-mindfulness (d=0.52; P=.02) only in the WellMind training group, with improvements in self-compassion sustained at follow-up (d=0.8; P=.01). Additionally, WellMind training durations correlated with the magnitude of improvement in self-compassion across human participants (ρ=0.52; P=.01). Training-related neurophysiological results revealed plasticity specific to the default mode network (DMN) that is implicated in mind-wandering and rumination, with DMN network suppression selectively observed at the postintervention time point in the WellMind group (d=-0.87; P=.03). We also found that improvement in self-compassion was directly related to the extent of DMN suppression (ρ=-0.368; P=.04).

CONCLUSIONS

Overall, promising behavioral and neurophysiological findings from this first study demonstrate the benefits of brief digital mindfulness and compassion training for health care professionals and compel the scale-up of the digital intervention.

TRIAL REGISTRATION

Trial Registration: International Standard Randomized Controlled Trial Number Registry ISRCTN94766568, https://www.isrctn.com/ISRCTN94766568.

Neural Systems Underlying the Implementation of Working Memory Removal Operations

Recently, multi-voxel pattern analysis has verified that information can be removed from working memory (WM) via three distinct operations replacement, suppression, or clearing compared to information being maintained ( Kim et al., 2020). While univariate analyses and classifier importance maps in Kim et al. (2020) identified brain regions that contribute to these operations, they did not elucidate whether these regions represent the operations similarly or uniquely. Using Leiden-community-detection on a sample of 55 humans (17 male), we identified four brain networks, each of which has a unique configuration of multi-voxel activity patterns by which it represents these WM operations. The visual network (VN) shows similar multi-voxel patterns for maintain and replace, which are highly dissimilar from suppress and clear, suggesting this network differentiates whether an item is held in WM or not. The somatomotor network (SMN) shows a distinct multi-voxel pattern for clear relative to the other operations, indicating the uniqueness of this operation. The default mode network (DMN) has distinct patterns for suppress and clear, but these two operations are more similar to each other than to maintain and replace, a pattern intermediate to that of the VN and SMN. The frontoparietal control network (FPCN) displays distinct multi-voxel patterns for each of the four operations, suggesting that this network likely plays an important role in implementing these WM operations. These results indicate that the operations involved in removing information from WM can be performed in parallel by distinct brain networks, each of which has a particular configuration by which they represent these operations.

Resting state network connectivity is associated with cognitive flexibility performance in youth in the Adolescent Brain Cognitive Development Study

Cognitive flexibility is an executive functioning skill that develops in childhood, and when impaired, has transdiagnostic implications for psychiatric disorders. To identify how intrinsic neural architecture at rest is linked to cognitive flexibility performance, we used the data-driven method of independent component analysis (ICA) to investigate resting state networks (RSNs) and their whole-brain connectivity associated with levels of cognitive flexibility performance in children. We hypothesized differences by cognitive flexibility performance in RSN connectivity strength in cortico-striatal circuitry, which would manifest via the executive control network, right and left frontoparietal networks (FPN), salience network, default mode network (DMN), and basal ganglia network. We selected participants from the Adolescent Brain Cognitive Development (ABCD) Study who scored at the 25th, ("CF-Low"), 50th ("CF-Average"), or 75th percentiles ("CF-High") on a cognitive flexibility task, were early to middle puberty, and did not exhibit significant psychopathology (n = 967, 47.9% female; ages 9-10). We conducted whole-brain ICA, identifying 14 well-characterized RSNs. Groups differed in connectivity strength in the right FPN, anterior DMN, and posterior DMN. Planned comparisons indicated CF-High had stronger connectivity between right FPN and supplementary motor/anterior cingulate than CF-Low. CF-High had more anti-correlated connectivity between anterior DMN and precuneus than CF-Average. CF-Low had stronger connectivity between posterior DMN and supplementary motor/anterior cingulate than CF-Average. Post-hoc correlations with reaction time by trial type demonstrated significant associations with connectivity. In sum, our results suggest childhood cognitive flexibility performance is associated with DMN and FPN connectivity strength at rest, and that there may be optimal levels of connectivity associated with task performance that vary by network.

The Influence of Probe Frequency on Self-Reported Mind Wandering During Tasks With Different Cognitive Loads

The use of thought-probe methodologies during tasks with varying loads has become commonplace. The current study aimed to investigate whether there exists an interaction between probe frequency and task load on responses of mind wandering episodes, using within-subject designs. In Experiment 1, We performed 0-back, 1-back, and 3-back tasks, in which low-frequency and high-frequency thought probes were presented to the participants. The results indicated that fewer probes led to more reported mind wandering episodes during 0-back and 1-back tasks. Conversely, a significant increase in mind wandering was observed in the 3-back task when higher-frequency probes were used. Experiment 2 introduced the probe relatedness dimension to the medium- and high-load tasks. Both experiments demonstrated that increasing probe frequency reduced mind wandering during the low- and medium-load tasks, but increased it during the high-load task. Additionally, Experiment 2 revealed that higher probe frequency resulted in more probe-related mind wandering during the high-load task, but not during the medium-load task. The current findings reveal the interaction effect of probe frequency and task load on mind wandering and offer possible explanations.

Recent advances in the neuroscience of spontaneous and off-task thought: implications for mental health

People spend a remarkable 30-50% of awake life thinking about something other than what they are currently doing. These experiences of being "off-task" can be described as spontaneous thought when mental dynamics are relatively flexible. Here we review recent neuroscience developments in this area and consider implications for mental wellbeing and illness. We provide updated overviews of the roles of the default mode network and large-scale network dynamics, and we discuss emerging candidate mechanisms involving hippocampal memory (sharp-wave ripples, replay) and neuromodulatory (noradrenergic and serotonergic) systems. We explore how distinct brain states can be associated with or give rise to adaptive and maladaptive forms of thought linked to distinguishable mental health outcomes. We conclude by outlining new directions in the neuroscience of spontaneous and off-task thought that may clarify mechanisms, lead to personalized biomarkers, and facilitate therapy developments toward the goals of better understanding and improving mental health.

Gradual Loss of Social Group Support during Competition Activates Anterior TPJ and Insula but Deactivates Default Mode Network

Group forming behaviors are common in many species to overcome environmental challenges. In humans, bonding, trust, group norms, and a shared past increase consolidation of social groups. Being a part of a social group increases resilience to mental stress; conversely, its loss increases vulnerability to depression. However, our knowledge on how social group support affects brain functions is limited. This study observed that default mode network (DMN) activity reduced with the loss of social group support from real-life friends in a challenging social competition. The loss of support induced anterior temporoparietal activity followed by anterior insula and the dorsal attentional network activity. Being a part of a social group and having support provides an environment for high cognitive functioning of the DMN, while the loss of group support acts as a threat signal and activates the anterior temporoparietal junction (TPJ) and insula regions of salience and attentional networks for individual survival.

Effects of goal-setting on sustained attention and attention lapses

In three experiments, we examined the effects of goal-setting on sustained attention and attention lapses. We measured both behavioral task performance and subjective attentional states during a four -choice reaction time task (Experiments 1 and 2 administered online; Experiment 3 conducted in-person). Experiment 1 compared a vague goal versus a specific goal. The specific goal reduced lapses in the form of long response times (RTs) but did not impact task-unrelated thoughts. Experiment 2 expanded on E1 by making the specific goal progressively harder. Behavioral lapses (i.e., long RTs) were reduced in the harder-over-time goal condition compared to the control condition. Additionally, while RTs increased with time-on-task in the control condition, RTs in the harder-over-time goal condition remained stable with time-on-task. Experiment 3 aimed to replicate the results of E2 in-person and adjusted the difficulty of the harder-over-time goals to be slightly harder. The results largely replicated E2. Overall, setting specific and difficult task goals led to a reduction in lapses of attention and increased sustained attention performance.

Personalized repetitive transcranial magnetic stimulation (prtms®) for post-traumatic stress disorder (ptsd) in military combat veterans

Emerging data suggest that post-traumatic stress disorder (PTSD) arises from disrupted brain default mode network (DMN) activity manifested by dysregulated encephalogram (EEG) alpha oscillations. Hence, we pursued the treatment of combat veterans with PTSD (n = 185) using an expanded form of repetitive transcranial magnetic stimulation (rTMS) termed personalized-rTMS (PrTMS). In this treatment methodology spectral EEG based guidance is used to iteratively optimize symptom resolution via (1) stimulation of multiple motor sensory and frontal cortical sites at reduced power, and (2) adjustments of cortical treatment loci and stimulus frequency during treatment progression based on a proprietary frequency algorithm (PeakLogic, Inc. San Diego) identifying stimulation frequency in the DMN elements of the alpha oscillatory band. Following 4 - 6 weeks of PrTMS® therapy in addition to routine PTSD therapy, veterans exhibited significant clinical improvement accompanied by increased cortical alpha center frequency and alpha oscillatory synchronization. Full resolution of PTSD symptoms was attained in over 50% of patients. These data support DMN involvement in PTSD pathophysiology and suggest a role in therapeutic outcomes. Prospective, sham controlled PrTMS® trials may be warranted to validate our clinical findings and to examine the contribution of DMN targeting for novel preventive, diagnostic, and therapeutic strategies tailored to the unique needs of individual patients with both combat and non-combat PTSD.

Edge-based general linear models capture high-frequency 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 one minute to the next. However, traditional dynamic FC approaches typically lack the temporal precision to capture moment-by-moment network fluctuations. Recently, researchers have 'unfurled' traditional FC matrices in 'edge cofluctuation time series' which measure time point-by-time point cofluctuations between regions. Here we apply event-based and parametric fMRI analyses to edge time series to capture high-frequency fluctuations in networks related to attention. In two independent fMRI datasets 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.

Cardiorespiratory fitness modulates prestimulus EEG microstates during a sustained attention task

Higher cardiorespiratory fitness is associated with an increased ability to perform sustained attention tasks and detect rare and unpredictable signals over prolonged periods. The electrocortical dynamics underlying this relationship were mainly investigated after visual stimulus onset in sustained attention tasks. Prestimulus electrocortical activity supporting differences in sustained attention performance according to the level of cardiorespiratory fitness have yet to be examined. Consequently, this study aimed to investigate EEG microstates 2 seconds before the stimulus onset in 65 healthy individuals aged 18-37, differing in cardiorespiratory fitness, while performing a psychomotor vigilance task. The analyses showed that a lower duration of the microstate A and a higher occurrence of the microstate D correlated with higher cardiorespiratory fitness in the prestimulus periods. In addition, increased global field power and occurrence of microstate A were associated with slower response times in the psychomotor vigilance task, while greater global explained variance, coverage, and occurrence of microstate D were linked to faster response times. Our collective findings showed that individuals with higher cardiorespiratory fitness exhibit typical electrocortical dynamics that allow them to allocate their attentional resources more efficiently when engaged in sustained attention tasks.

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.

Beyond mind wandering: Performance variability and neural activity during off-task thought and other attention lapses

To study the characteristics of attention lapses, a metronome response task and experience sampling were employed while recording fMRI data. Thought prompts queried several attention states (on-task, task-related interference, off-task, inattention). Off-task thoughts were probed on whether they arose in a spontaneous or constrained (i.e., directed) manner. Increased fMRI activation was observed in the default mode network during off-task thought and in subregions of the anterior cingulate cortex and inferior frontal gyrus during inattention. Activation also increased in the left hippocampus during constrained thoughts. Functional connectivity increased between the left superior temporal sulcus and right temporoparietal junction for constrained compared to spontaneous thoughts. Overall, behavioral results indicated a monotonic increase in performance variability from on-task to inattention. However, subtle but consistent differences were observed between self-reported attention state and performance. Results are discussed from perspectives of mind wandering frameworks, the function of brain networks, and the role of engagement in off-task thought.

Coexistence of thought types as an attentional state during a sustained attention task

Some studies have asked participants about attentional state on a scale from on-task to off-task, which set the middle option as attention focused on both, including the possibility of the coexistence of thoughts. In addition, studies using multidimensional probes explicitly assumed coexistence within spontaneous thoughts and task-focus dimensions. Although several studies have assumed the coexistence of some thought dimensions, none has explored whether these are different types of thoughts (task-focus, mind-wandering, task-related, external stimuli-related). To examine whether this coexistence of thought types occurred, we used thought probes to determine the degree of immersion in each. The participants responded to probes presented at random during a sustained attention task. The results revealed a mixture of thought types in many self-reports. In addition, the state of attentional allocation behind self-reports was estimated using the hidden Markov model. We observed the following attentional states: task-focused, task-unrelated, task-related, external stimuli-focused, and task-focused-but also focused on other thoughts. These results suggest that individuals can simultaneously allocate attention to thought types and discriminate between reporting. In some cases, probe options should also be considered for this coexistence. We also examined the relationship between self-reports and behavioral indexes, and discussed the necessity of separately measuring the degree of immersion for each thought type.

EEG source derived salience network coupling supports real-world attention switching

While the brain mechanisms underlying selective attention have been studied in great detail in controlled laboratory settings, it is less clear how these processes function in the context of a real-world self-paced task. Here, we investigated engagement on a real-world computerized task equivalent to a standard academic test that consisted of solving high-school level problems in a self-paced manner. In this task, we used EEG-source derived estimates of effective coupling between brain sources to characterize the neural mechanisms underlying switches of sustained attention from the attentive on-task state to the distracted off-task state. Specifically, since the salience network has been implicated in sustained attention and attention switching, we conducted a hypothesis-driven analysis of effective coupling between the core nodes of the salience network, the anterior insula (AI) and the anterior cingulate cortex (ACC). As per our hypothesis, we found an increase in AI - > ACC effective coupling that occurs during the transitions of attention from on-task focused to off-task distracted state. This research may inform the development of future neural function-targeted brain-computer interfaces to enhance sustained attention.

Detecting inattentiveness caused by mind-wandering during a driving task: A behavioral study

This study aims to investigate whether behavioral variability and participants' self-ratings can be used to detect mind-wandering while driving and to examine their effects on braking performance during a driving task. We created a novel driving task and added a sustained attention response task (SART). We examined the effects of mind-wandering on braking performance and whether mind-wandering could be detected from SART response variability. The within-subjects results showed that self-reports of inattentiveness during driving correlated significantly with SART response variability. Multiple regression analysis with brake reaction time as the dependent variable revealed a significant relationship between self-reports of inattentiveness and mind-wandering. However, there were no other consistent linear associations between mind-wandering and SART response variability. Our results not only suggest that inattentiveness to driving caused by mind-wandering impairs braking performance but also emphasize the importance and difficulty of detecting this state from behavioral data alone.

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.

Neural mechanisms of brand love relationship dynamics: Is the development of brand love relationships the same as that of interpersonal romantic love relationships?

Brand love is a relationship between brands and consumers. Managing the relationship is an important issue for marketing strategy since it changes according to temporal flow. Brand love theories, including their dynamics, have been developed based on interpersonal romantic love theories. Although many brand love studies have provided useful findings, the neural mechanism of brand love remains unclear. Especially, its dynamics have not been considered from a neuroscience perspective. The present study addressed the commonalities and differentiations of activated brain regions between brand love and interpersonal romantic love relationships using a quantitative neuroimaging meta-analytic approach, from the view of brain connectivity. Regarding the mental processes of each love relationship related to these activated brain regions, decoding analysis was conducted using the NeuroQuery platform to prevent reverse inference. The results revealed that different neural mechanisms and mental processes were distinctively involved in the dynamics of each love relationship, although the anterior insula overlapped across all stages and the reinforcement learning system was driven between both love relationships in the early stage. Remarkably, regarding the distinctive mental processes, although prosocial aspects were involved in the mental processes of interpersonal romantic love relationships across all stages, they were not involved in the mental processes of brand love relationships. Conclusively, although common brain regions and mental processes between both love relationships were observed, neural mechanisms and mental processes in brand love relationship dynamics might be innately different from those in the interpersonal romantic love relationship dynamics. As this finding indicates essential distinctiveness between both these relationships, theories concerning interpersonal romantic love should be applied cautiously when investigating brand love relationship dynamics.

Linguistic Equivalence, Validity and Reliability Study of the Mind Excessively Wandering Scale

INTRODUCTION

The main objective was to study the linguistic equivalence, validity and reliability of the transliterated Turkish version of Mind Excessively Wandering Scale (MEWS) developed by Prof. Philip Asherson in England (2016). Mind excessively wandering defines uncontrolled mental phenomena, which is proposed as the psychological counterpart of Default Mode Network in literature.

METHOD

Mind Excessively Wandering Scale, Adult Attention Deficit Hyperactivity Disorder Self-Report Scale, Barratt Impulsiveness Scale, Difficulties in Emotion Regulation Scale have been used. The sample group consists of 64 patients previously diagnosed as adult Attention Deficit Hyperactivity Disorder for validity, 60 students for transliteral equivalence, and 80 healthy controls for test re-test reliability.

RESULTS

Transliteral equivalence study demonstrates that Turkish version of MEWS is highly correlated with the English version and is statistically significant. The sixth item in the scale was removed in order to ensure the consistency model established by LISREL in the validity study according to the confirmatory factor analysis. When the sixth item was excluded, it was concluded that the structure of the scale was compatible. In the reliability study of the MEWS, the Cronbach's alpha value (α) of the scale was found to be 0.826. It is seen that the item with the highest distinctiveness feature is Item-10 (0.618) and the item with the lowest distinctiveness feature is Item-5 (0.318). In the linguistic equivalence study, no statistical difference was found between the English form and the Turkish versions of the scale.

CONCLUSION

As a result of the practical and statistical evaluations, our study demonstrated that the Turkish version of the MEWS is a valid and reliable measurement tool.

Brain networks are decoupled from external stimuli during internal cognition

Our cognition can be directed to external stimuli or to internal information. While there are many different forms of internal cognition (mind-wandering, recall, imagery etc.), their essential feature is independence from the immediate sensory input, conceptually referred to as perceptual decoupling. Perceptual decoupling is thought to be reflected in brain activity transitioning from a stimulus-processing to internally-processing mode, but a direct investigation of this remains outstanding. Here we present a conceptual and analysis framework that quantifies the extent to which brain networks reflect stimulus processing. We tested this framework by presenting subjects with an audiovisual stimulus and instructing them to either attend to the stimulus (external task) or engage in mental imagery, recall or arithmetic (internal tasks) while measuring the evoked brain activity using functional MRI. We found that stimulus responses were generally attenuated for the internal tasks, though they increased in a subset of tasks and brain networks. However, using our new framework, we showed that brain networks became less reflective of stimulus processing, even in the subset of tasks and brain networks in which stimulus responses increased. These results quantitatively demonstrate that during internal cognition brain networks become decoupled from the external stimuli, opening the door for a fundamental and quantitative understanding of internal cognition.

Predicting response time variability from task and resting-state functional connectivity in the aging brain

Aging is associated with declines in a host of cognitive functions, including attentional control, inhibitory control, episodic memory, processing speed, and executive functioning. Theoretical models attribute the age-related decline in cognitive functioning to deficits in goal maintenance and attentional inhibition. Despite these well-documented declines in executive control resources, older adults endorse fewer episodes of mind-wandering when assessed using task-embedded thought probes. Furthermore, previous work on the neural basis of mind-wandering has mostly focused on young adults with studies predominantly focusing on the activity and connectivity of a select few canonical networks. However, whole-brain functional networks associated with mind-wandering in aging have not yet been characterized. In this study, using response time variability-the trial-to-trial fluctuations in behavioral responses-as an indirect marker of mind-wandering or an "out-of-the-zone" attentional state representing suboptimal behavioral performance, we show that brain-based predictive models of response time variability can be derived from whole-brain task functional connectivity. In contrast, models derived from resting-state functional connectivity alone did not predict individual response time variability. Finally, we show that despite successful within-sample prediction of response time variability, our models did not generalize to predict response time variability in independent cohorts of older adults with resting-state connectivity. Overall, our findings provide evidence for the utility of task-based functional connectivity in predicting individual response time variability in aging. Future research is needed to derive more robust and generalizable models.

Local-to-Remote Brain Functional Connectivity in Patients with Thyroid-Associated Ophthalmopathy and Assessment of Its Predictive Value Using Machine Learning

Purpose

To explore the alterations in both local and remote brain connectivity in patients with thyroid-associated ophthalmopathy (TAO) and to investigate whether the alterations of local neural function could be used to distinguish patients with TAO from healthy controls (HCs) using support vector machine (SVM) classifier.

Materials and Methods

In total, 21 patients with TAO and 21 well-matched HCs were enrolled in our study and underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning. We employed regional homogeneity (ReHo) algorithm to evaluate local neural function and selected significantly altered brain regions as seed areas for subsequent study of the remote functional connectivity (FC). Moreover, we chose the observed alterations in the ReHo analysis as classification features to differentiate patients with TAO from HCs through SVM classification method.

Results

Compared with the HCs, TAO patients showed significantly lower ReHo values in the right middle occipital gyrus (MOG) and right angular (ANG). In contrast, TAO patients displayed higher ReHo values in the left hippocampus (Hipp). We further found TAO patients exhibited decreased FC between the left and right Hipp, right MOG and left cerebellum (CER), right ANG and left rectus, right superior temporal pole gyrus (PSTG) (voxel-level p < 0.01, Gaussian random field correction, cluster-level p < 0.05). The alterations in local neural function exhibited an accuracy of 78.57% and area under curve of 0.81 for distinguishing the patients from HCs.

Conclusion

We mainly found the results that patients with TAO showed significantly dysfunctional local and remote brain functional connectivity in several brain regions associated with visual and cognitive functions. The ReHo variability has potential value in differentiating patients with TAO from HCs. These findings may provide novel insights into the neurological mechanisms underlying visual and cognitive disorders in patients with TAO.

The trait and state negative affect can be separately predicted by stable and variable resting-state functional connectivity

BACKGROUND

Many emotional experiences such as anxiety and depression are influenced by negative affect (NA). NA has both trait and state features, which play different roles in physiological and mental health. Attending to NA common to various emotional experiences and their trait-state features might help deepen the understanding of the shared foundation of related emotional disorders.

METHODS

The principal component of five measures was calculated to indicate individuals' NA level. Applying the connectivity-based correlation analysis, we first identified resting-state functional connectives (FCs) relating to NA in sample 1 (n = 367), which were validated through an independent sample (n = 232; sample 2). Next, based on the variability of FCs across large timescale, we further divided the NA-related FCs into high- and low-variability groups. Finally, FCs in different variability groups were separately applied to predict individuals' neuroticism level (which is assumed to be the core trait-related factor underlying NA), and the change of NA level (which represents the state-related fluctuation of NA).

RESULTS

The low-variability FCs were primarily within the default mode network (DMN) and between the DMN and dorsal attention network/sensory system and significantly predicted trait rather than state NA. The high-variability FCs were primarily between the DMN and ventral attention network, the fronto-parietal network and DMN/sensory system, and significantly predicted the change of NA level.

CONCLUSIONS

The trait and state NA can be separately predicted by stable and variable spontaneous FCs with different attentional processes and emotion regulatory mechanisms, which could deepen our understanding of NA.

Molecular basis of cycloheximide resistance in the Ophiostomatales revealed

Resistance to the antibiotic Cycloheximide has been reported for a number of fungal taxa. In particular, some yeasts are known to be highly resistant to this antibiotic. Early research showed that this resulted from a transition mutation in one of the 60S ribosomal protein genes. In addition to the yeasts, most genera and species in the Ophiostomatales are highly resistant to this antibiotic, which is widely used to selectively isolate these fungi. Whole-genome sequences are now available for numerous members of the Ophiostomatales providing an opportunity to determine whether the mechanism of resistance in these fungi is the same as that reported for yeast genera such as Kluyveromyces. We examined all the available genomes for the Ophiostomatales and discovered that a transition mutation in the gene coding for ribosomal protein eL42, which results in the substitution of the amino acid Proline to Glutamine, likely confers resistance to this antibiotic. This change across all genera in the Ophiostomatales suggests that the mutation arose early in the evolution of these fungi.

The impact of image degradation and temporal dynamics on sustained attention

Many clinical populations that have sustained attention deficits also have visual deficits. Therefore, it is necessary to understand how the quality of visual input and different forms of image degradation can contribute to worse performance on sustained attention tasks, particularly those with dynamic and complex visual stimuli. This study investigated the impact of image degradation on an adapted version of the gradual-onset continuous performance task (gradCPT), where participants must discriminate between gradually fading city and mountain scenes. Thirty-six normal-vision participants completed the task, which featured two blocks of six resolution and contrast levels. Subjects either completed a version with gradually fading or static image presentations. The results show decreases in image resolution impair performance under both types of temporal dynamics, whereas performance is only impaired under gradual temporal dynamics for decreases in image contrast. Image similarity analyses showed that performance has a higher association with an observer's ability to gather an image's global spatial layout (i.e. gist) than local variations in pixel luminance, particularly under gradual image presentation. This work suggests that gradually fading attention paradigms are sensitive to deficits in primary visual function, potentially leading to these issues being misinterpreted as attentional failures.

Catching Wandering Minds with Tapping Fingers: Neural and Behavioral Insights into Task-unrelated Cognition

When the human mind wanders, it engages in episodes during which attention is focused on self-generated thoughts rather than on external task demands. Although the sustained attention to response task is commonly used to examine relationships between mind wandering and executive functions, limited executive resources are required for optimal task performance. In the current study, we aimed to investigate the relationship between mind wandering and executive functions more closely by employing a recently developed finger-tapping task to monitor fluctuations in attention and executive control through task performance and periodical experience sampling during concurrent functional magnetic resonance imaging (fMRI) and pupillometry. Our results show that mind wandering was preceded by increases in finger-tapping variability, which was correlated with activity in dorsal and ventral attention networks. The entropy of random finger-tapping sequences was related to activity in frontoparietal regions associated with executive control, demonstrating the suitability of this paradigm for studying executive functioning. The neural correlates of behavioral performance, pupillary dynamics, and self-reported attentional state diverged, thus indicating a dissociation between direct and indirect markers of mind wandering. Together, the investigation of these relationships at both the behavioral and neural level provided novel insights into the identification of underlying mechanisms of mind wandering.

Spontaneous brain activity alterations in thyroid-associated ophthalmopathy patients using amplitude of low-frequency fluctuation: A resting-state fMRI study

OBJECTIVES

Previous studies demonstrated that thyroid-associated ophthalmopathy (TAO) patients were accompanied by cognitive decline. However, The exact neural mechanisms of cognitive decline in TAO patients remain unclear. Our study aimed to investigate the spontaneous brain activity alterations using amplitude of low-frequency fluctuation (ALFF) method and their relationships with clinical features in TAO patients.

MATERIALS AND METHODS

In total, twenty-one patients with TAO (14 men and 7 women) and 21 healthy control (HC) subjects (14 men and 7 women) were enrolled in this study. The ALFF method was used to assess the spontaneous brain activity changes. Meanwhile, receiver operating characteristic (ROC) curve was used to distinguish TAO group and HCs group. And Pearson correlation was performed to calculate the relationship between the observed mean ALFF values of the altered regions in patients with TAO and their clinical features.

RESULTS

Compared with the HCs, TAO patients had significantly lower ALFF values in the right superior occipital gyrus (SOG) and bilateral precuneus (preCUN). In contrast, TAO patients showed higher ALFF values in the left cerebellum (CER) and left insula (INS).

CONCLUSION

our result highlighted that TAO patients showed altered intrinsic brain activities in the preCUN, left CER, left INS and right SOG, which might provide useful information for explaining neural mechanisms in patients with TAO.

Temporal order of signal propagation within and across intrinsic brain networks

We studied the temporal dynamics of activity within and across functional MRI (fMRI)-derived nodes of intrinsic resting-state networks of the human brain using intracranial electroencephalography (iEEG) and repeated single-pulse electrical stimulation (SPES) in neurosurgical subjects implanted with intracranial electrodes. We stimulated and recorded from 2,133 and 2,372 sites, respectively, in 29 subjects. We found that N1 and N2 segments of the evoked responses are associated with intra- and internetwork communications, respectively. In a separate cognitive experiment, evoked electrophysiological responses to visual target stimuli occurred with less temporal separation across pairs of electrodes that were located within the same fMRI-defined resting-state networks compared with those located across different resting-state networks. Our results suggest intranetwork prior to internetwork information processing at the subsecond timescale.

Cognitive and Neural State Dynamics of Narrative Comprehension

Narrative comprehension involves a constant interplay of the accumulation of incoming events and their integration into a coherent structure. This study characterizes cognitive states during narrative comprehension and the network-level reconfiguration occurring dynamically in the functional brain. We presented movie clips of temporally scrambled sequences to human participants (male and female), eliciting fluctuations in the subjective feeling of comprehension. Comprehension occurred when processing events that were highly causally related to the previous events, suggesting that comprehension entails the integration of narratives into a causally coherent structure. The functional neuroimaging results demonstrated that the integrated and efficient brain state emerged during the moments of narrative integration with the increased level of activation and across-modular connections in the default mode network. Underlying brain states were synchronized across individuals when comprehending novel narratives, with increased occurrences of the default mode network state, integrated with sensory processing network, during narrative integration. A model based on time-resolved functional brain connectivity predicted changing cognitive states related to comprehension that are general across narratives. Together, these results support adaptive reconfiguration and interaction of the functional brain networks on causal integration of the narratives.SIGNIFICANCE STATEMENT The human brain can integrate temporally disconnected pieces of information into coherent narratives. However, the underlying cognitive and neural mechanisms of how the brain builds a narrative representation remain largely unknown. We showed that comprehension occurs as the causally related events are integrated to form a coherent situational model. Using fMRI, we revealed that the large-scale brain states and interaction between brain regions dynamically reconfigure as comprehension evolves, with the default mode network playing a central role during moments of narrative integration. Overall, the study demonstrates that narrative comprehension occurs through a dynamic process of information accumulation and causal integration, supported by the time-varying reconfiguration and brain network interaction.

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.

Contributions of Brain Function and Structure to Three Different Domains of Cognitive Control in Normal Aging

Cognitive control involves the flexible allocation of mental resources during goal-directed behavior and comprises three correlated but distinct domains-inhibition, shifting, and working memory. The work of Don Stuss and others has demonstrated that frontal and parietal cortices are crucial to cognitive control, particularly in normal aging, which is characterized by reduced control mechanisms. However, the structure-function relationships specific to each domain and subsequent impact on performance are not well understood. In the current study, we examined both age and individual differences in functional activity associated with core domains of cognitive control in relation to fronto-parietal structure and task performance. Participants (n = 140, aged 20-86 years) completed three fMRI tasks: go/no-go (inhibition), task switching (shifting), and n-back (working memory), in addition to structural and diffusion imaging. All three tasks engaged a common set of fronto-parietal regions; however, the contributions of age, brain structure, and task performance to functional activity were unique to each domain. Aging was associated with differences in functional activity for all tasks, largely in regions outside common fronto-parietal control regions. Shifting and inhibition showed greater contributions of structure to overall decreases in brain activity, suggesting that more intact fronto-parietal structure may serve as a scaffold for efficient functional response. Working memory showed no contribution of structure to functional activity but had strong effects of age and task performance. Together, these results provide a comprehensive and novel examination of the joint contributions of aging, performance, and brain structure to functional activity across multiple domains of cognitive control.

Variable rather than extreme slow reaction times distinguish brain states during sustained attention

A common behavioral marker of optimal attention focus is faster responses or reduced response variability. Our previous study found two dominant brain states during sustained attention, and these states differed in their behavioral accuracy and reaction time (RT) variability. However, RT distributions are often positively skewed with a long tail (i.e., reflecting occasional slow responses). Therefore, a larger RT variance could also be explained by this long tail rather than the variance around an assumed normal distribution (i.e., reflecting pervasive response instability based on both faster and slower responses). Resolving this ambiguity is important for better understanding mechanisms of sustained attention. Here, using a large dataset of over 20,000 participants who performed a sustained attention task, we first demonstrated the utility of the exGuassian distribution that can decompose RTs into a strategy factor, a variance factor, and a long tail factor. We then investigated which factor(s) differed between the two brain states using fMRI. Across two independent datasets, results indicate unambiguously that the variance factor differs between the two dominant brain states. These findings indicate that ‘suboptimal’ is different from ‘slow’ at the behavior and neural level, and have implications for theoretically and methodologically guiding future sustained attention research.

Effect of DRD4 Receptor -616 C/G Polymorphism on Thalamic GABA Levels in Pediatric Patients With Primary Nocturnal Enuresis

BACKGROUND

The single nucleotide polymorphism (SNP) of dopamine D4 receptor (DRD4) promoter (-616; rs747302) is associated with abnormalities of the thalamus in children suffering from primary nocturnal enuresis (PNE).

PURPOSE

To investigate the effect of DRD4 -616 C/G SNP on thalamic gamma-aminobutyric acid (GABA) levels in PNE children.

STUDY TYPE

Prospective, observational.

SUBJECTS

One hundred and seventy-six children with PNE and 161 healthy control children.

FIELD STRENGTH/SEQUENCE

3 T, three-dimensional T1-weighted turbo field echo sequence and MEscher-Garwood Point RESolved Spectroscopy (MEGA-PRESS) MRS sequence.

ASSESSMENT

The MEGA-PRESS MRS sequence was used to measure thalamic GABA spectra. The thalamic GABA+ level was calculated using the Gannet 3.0 software package for each participant. A questionnaire was used to determine arousal from sleep (AS) scores.

STATISTICAL TESTS

Comparisons of the AS scores and thalamic GABA+ levels were performed using the Mann-Whitney U test between C-allele carriers and GG homozygotes in the PNE and control groups. Spearman correlation analysis was performed to determine the association between AS scores and thalamic GABA levels in PNE children.

RESULTS

Thalamic GABA levels in the PNE group were significantly higher than those in the healthy control group (0.178 (0.169-0.186) vs. 0.154 (0.146-0.164), Z = 8.526, P_corrected  < 0.001). The GABA levels in C-allele carriers were significantly higher than those in GG homozygotes in both the PNE and control groups (0.184 (0.181-0.193) vs. 0.170 (0.165-0.177), Z = 8.683, P_corrected  < 0.001; 0.166 (0.156-0.170) vs. 0.147 (0.141-0.152), Z = 9.445, P_corrected  < 0.001). GABA levels in the thalamus were also significantly and positively correlated with AS scores in C-allele carriers in the PNE group (r = 0.747, P < 0.05).

DATA CONCLUSION

DRD4 -616 C allele may be associated with increased thalamic GABA+ levels, especially in C-allele carrying PNE children.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 3.

The squirrel monkey model in clinical neuroscience

Clinical neuroscience research relying on animal models brought valuable translational insights into the function and pathologies of the human brain. The anatomical, physiological, and behavioural similarities between humans and mammals have prompted researchers to study cerebral mechanisms at different levels to develop and test new treatments. The vast majority of biomedical research uses rodent models, which are easily manipulable and have a broadly resembling organisation to the human nervous system but cannot satisfactorily mimic some disorders. For these disorders, macaque monkeys have been used as they have a more comparable central nervous system. Still, this research has been hampered by limitations, including high costs and reduced samples. This review argues that a squirrel monkey model might bridge the gap by complementing translational research from rodents, macaque, and humans. With the advent of promising new methods such as ultrasound imaging, tool miniaturisation, and a shift towards open science, the squirrel monkey model represents a window of opportunity that will potentially fuel new translational discoveries in the diagnosis and treatment of brain pathologies.

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.

fMRI-based detection of alertness predicts behavioral response variability

Levels of alertness are closely linked with human behavior and cognition. However, while functional magnetic resonance imaging (fMRI) allows for investigating whole-brain dynamics during behavior and task engagement, concurrent measures of alertness (such as EEG or pupillometry) are often unavailable. Here, we extract a continuous, time-resolved marker of alertness from fMRI data alone. We demonstrate that this fMRI alertness marker, calculated in a short pre-stimulus interval, captures trial-to-trial behavioral responses to incoming sensory stimuli. In addition, we find that the prediction of both EEG and behavioral responses during the task may be accomplished using only a small fraction of fMRI voxels. Furthermore, we observe that accounting for alertness appears to increase the statistical detection of task-activated brain areas. These findings have broad implications for augmenting a large body of existing datasets with information about ongoing arousal states, enriching fMRI studies of neural variability in health and disease.

Mapping the "Funny Bone": Neuroanatomical Correlates of Humor Creativity in Professional Comedians

What are the neuroanatomical correlates of expertise in a specific creative domain? Professional comedians, amateurs and controls underwent a T1 MRI anatomical scan. Measures of cortical surface area (gyrification and sulcal depth) and thickness were extracted for each participant. Compared to controls, professional comedians had a greater cortical surface area in the left inferior temporal gyrus, angular gyrus, precuneus and right medial prefrontal cortex. These regions have been previously implicated in abstract, divergent thinking and the default-mode network. The high degree of overlap between the regions of greater surface area in professional comedians with the regions showing greater activation in the same group during comedy improvisation in our previous work (particularly the temporal regions and angular gyrus) suggests that these regions may be specifically involved in humor creativity.

Impaired executive function exacerbates neural markers of posttraumatic stress disorder

BACKGROUND

A major obstacle in understanding and treating posttraumatic stress disorder (PTSD) is its clinical and neurobiological heterogeneity. To address this barrier, the field has become increasingly interested in identifying subtypes of PTSD based on dysfunction in neural networks alongside cognitive impairments that may underlie the development and maintenance of symptoms. The current study aimed to determine if subtypes of PTSD, based on normative-based cognitive dysfunction across multiple domains, have unique neural network signatures.

METHODS

In a sample of 271 veterans (90% male) that completed both neuropsychological testing and resting-state fMRI, two complementary, whole-brain functional connectivity analyses explored the link between brain functioning, PTSD symptoms, and cognition.

RESULTS

At the network level, PTSD symptom severity was associated with reduced negative coupling between the limbic network (LN) and frontal-parietal control network (FPCN), driven specifically by the dorsolateral prefrontal cortex and amygdala Hubs of Dysfunction. Further, this relationship was uniquely moderated by executive function (EF). Specifically, those with PTSD and impaired EF had the strongest marker of LN-FPCN dysregulation, while those with above-average EF did not exhibit PTSD-related dysregulation of these networks.

CONCLUSION

These results suggest that poor executive functioning, alongside LN-FPCN dysregulation, may represent a neurocognitive subtype of PTSD.

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.