Knowledge is growing on the essential role of neural circuits involved in aberrant cognitive control and reward sensitivity for the onset and maintenance of binge eating.

To investigate how the brain's reward (bottom-up) and inhibition control (top-down) systems potentially and dynamically interact to contribute to subclinical binge eating.

Functional magnetic resonance imaging data were acquired from 30 binge eaters and 29 controls while participants performed a food reward Go/NoGo task. Dynamic causal modelling with the parametric empirical Bayes framework, a novel brain connectivity technique, was used to examine between-group differences in the directional influence between reward and executive control regions. We explored the proximal risk factors for binge eating and its neural basis, and assessed the predictive ability of neural indices on future disordered eating and body weight.

The binge eating group relative to controls displayed fewer reward-inhibition undirectional and directional synchronisations (i.e. medial orbitofrontal cortex [mOFC]–superior parietal gyrus [SPG] connectivity, mOFC → SPG excitatory connectivity) during food reward_nogo condition. Trait impulsivity is a key proximal factor that could weaken the mOFC–SPG connectivity and exacerbate binge eating. Crucially, this core mOFC–SPG connectivity successfully predicted binge eating frequency 6 months later.

These findings point to a particularly important role of the bottom-up interactions between cortical reward and frontoparietal control circuits in subclinical binge eating, which offers novel insights into the neural hierarchical mechanisms underlying problematic eating, and may have implications for the early identification of individuals suffering from strong binge eating-associated symptomatology in the general population.

The present study explored how individual differences and development of gray matter architecture in inferior frontal gyri (IFG), anterior cingulate (ACC), and inferior parietal lobe (IPL) relate to development of response inhibition as measured by both the Stop Signal Task (SST) and the Go/No-Go (GNG) task in a longitudinal sample of healthy adolescents and young adults. Reliability of behavioral and neural measures was also explored.

A total of 145 individuals contributed data from the second through fifth timepoints of an accelerated longitudinal study focused on adolescent brain and behavioral development at the University of Minnesota. At baseline, participants were 9 to 23 years of age and were typically-developing. Assessment waves were spaced approximately 2 years apart. Behavioral measures of response inhibition collected at each assessment included GNG Commission Errors (CE) and the SST Stop Signal Reaction Time (SSRT). Structural T1 MRI scans were collected on a Siemens 3 T Tim Trio and processed with the longitudinal Freesurfer 6.0 pipeline to yield cortical thickness (CT) and surface area values. Regions of interest based on the Desikan-Killiany-Tourville atlas included IFG regions (pars opercularis (PO) and pars triangularis (PT)), ACC and IPL. The cuneus and global brain measures were evaluated as control regions. Retest stability of all measures was calculated using the psych package in R. Mixed linear effects modeling using the lme4 R package identified whether age-based trajectories for SSRTs and GNG CEs best fit linear, quadratic, or inverse curve. Then, disaggregated between- and within-subjects effects of regional cortical architecture measures were added to longitudinal behavioral models to identify individual differences and developmental effects, respectively.

Both response inhibition metrics demonstrated fair reliability and were best fit by an inverse age trajectory. Neural measures demonstrated excellent retest stability (all ICCs > 0.834). Age-based analyses of regional CT identified heterogeneous patterns of development, including linear trajectories for ACC and inverse age trajectories for bilateral PT. Individuals with thinner left PO showed worse performance on both response inhibition tasks. SSRTs were related to individual differences in right PO thickness and surface area. A developmental pattern was observed for right PT cortical thickness, where thinning over time was related to better GNG performance. Lower surface area of the right PT was related to worse GNG performance. No individual differences or developmental patterns were observed for the ACC, IPL, cuneus, or global metrics.

This study examined the adolescent development of response inhibition and its association with cortical architecture in the IFG, ACC and IPL. Separate response inhibition tasks demonstrated similar developmental patterns with steepest improvements in early adolescence and relationships with left PO thickness, but each measure had unique relationships with other IFG regions. This study indicates that a region of the IFG, the par opercularis, relates to both individual difference and developmental change in response inhibition. These patterns suggest brain-behavior association that could be further explored in functional imaging studies and that may index, in vulnerable individuals, risk for psychopathology.

Many studies supported that children with autism spectrum disorder (ASD) have worse executive functions (EFs) when compared to typically developmental (TD) children in many domains, such as planning, flexibility, inhibition, and self-monitoring. The current study aims to use an adapted version of the computerized tower test to investigate the EFs of children with ASD. Furthermore, the researcher also assessed children's EFs-related behaviors in their schools using a teacher-filled behavior rating inventory of executive function, 2nd edition (BRIEF-2).

61 Children aged 7 to 12 years old (M = 9.23) were included in the current study. 29 of them were in the ASD group, and 31 of them were in the TD group. All participants conducted an adapted computerized tower test. All participants' teachers completed BRIEF-2 to investigate their EFs-related behaviors in their schools.

The results indicated that there were no significant differences in the tower test between the ASD group and TD group in all indexes. Therefore, it implied that the current indexes might not be sensitive enough to distinguish whether a child has ASD or not. In addition, we further investigate the correlations between the tower test and the teacher-filled BRIEF-2. We found the different patterns in the two groups. In the ASD group, we found that the task-monitor index was positively correlated with total-number-of-rule-violations, total-complete-time, and total-rule-violations-per-item-ratio. The task-monitor index was negatively correlated with total-achievement-score, implying that poorer ability to monitor tasks leads to a longer completion time, more rule violations, and a lower total achievement score. Moreover, we also found a high correlation between the organization-of-materials in BRIEF-2 and total-complete-time in the tower test, suggesting the long problem-solving time in ASD groups is highly related to the disability of keeping working space ordered. In addition, we found that the shift index is positively correlated with total-complete-time and total-rule-violations-per-item-ratio. Hence, it indicates that those with poor flexibility in solving problems tend to need more time to complete tasks and violate more rules in ASD groups. In the TD group, we only found the correlation effects were significant between inhibition and self-monitor in the BRIEF-2 and the total-rule-violations-per-item-ratio in the tower test. It suggested that individuals with behavioral regulation problems, such as impulse control and monitoring problems are more likely to make rule violations. The result indicated that behavioral regulations play a more significant role in the TD group. In contrast, cognitive and emotional regulations are more critical in ASD children.

Our findings found no significant difference in the computerized tower test between children with and without ASD, suggesting that the current indexed might not be sensitive enough to differentiate children with or without ASD. However, the results of the correlation between the tower test and teacher-filled BRIEF-2 showed that different patterns might be the cause of the EF performances between the two groups, indicating that there might be a different domain of EFs the children used in the tower test between two groups.

Therefore, further research could focus on developing new indexes in the Tower test and finding the EF mechanism of ASD children with different approaches.

Typical evaluations of adult ADHD consist of behavior self-report rating scales, cognitive or intellectual functioning measures, and specific measures designed to measure attention. Boone (2009) suggested monitoring continuous effort is essential throughout psychological assessments. However, very few research studies have contributed to malingering literature on the ADHD population. Many studies have reported the adequate use of symptom validity tests, which assess effortful performance in ADHD evaluations (Jasinski et al., 2011; Sollman et al., 2010; Schneider et al., 2014). Because of the length of ADHD assessments, individuals are likely to become weary and tired, thus impacting their performance. This study investigates the eye movement strategies used by a clinical ADHD population, non-ADHD subjects, and malingering simulators when playing a common simple visual search task.

A total of 153 college students participated in this study. To be placed in the ADHD group, a participant must endorse four or more symptoms on the ASRS (N = 37). To be placed in the non-ADHD, participants should have endorsed no ADHD symptoms (N = 43). Participants that did not meet the above criteria for ADHD and not-ADHD were placed in an Indeterminate group and were not included in the analysis. A total of 20 participants were instructed to fake symptoms related to ADHD during the session. A total of twelve Spot the Difference images were used as the visual picture stimuli. Sticky by Tobii Pro (2020) was used for the collection of eye-movement data was utilized. Sticky by Tobii Pro is an online self-service platform that combines online survey questions with an eye-tracking webcam, allowing participants to see images from their home computers.

Results indicated on the participants classified as Malingering had a significantly Visit Count (M = 17.16; SD= 4.99) compared to the ADHD(M = 12.53; SD= 43.92) and not-ADHD groups (M =11.51; SD=3.23). Results also indicated a statistically significant Area Under the Curve (AUC) = .784; SE = .067; p -.003; 95% CI = .652-.916. Optimal cutoffs suggest a Sensitivity of 50% with a False Positive Rate of 10%.

Results indicated that eye-tracking technology could help differentiate simulator malingerers from non-malingerers with ADHD. Eye-tracking research’ relates to a patchwork of fields more diverse than the study of perceptual systems. Due to their close relation to attentional mechanisms, the study’s results can provide an insight into cognitive processes related to malingering performance.

Individuals with attention-deficit/hyperactivity disorder (ADHD) exhibit deficits in reward-based learning, which have important implications for behavioral regulation. Prior research has shown that these individuals show altered patterns of risky decision-making, which may be partially explained as a function of dysfunctional reactivity to rewards and punishments. However, research findings on the relationships between ADHD and punishment sensitivity have been mixed. The current study used the Balloon Analog Risk Task (BART) to examine risky decision-making in adults with and without ADHD, with a particular interest in characterizing the manner in which participants react to loss.

612 individuals (Mage = 31.04, SDage = 78.77; 329 females, 283 males) were recruited through the UCLA Consortium for Neuropsychiatric Phenomics (CNP). All participants were administered the Structured Clinical Interview for DSM-IV-TR (SCID-IV), which provided diagnoses used for group comparisons between adults with ADHD (n = 35) and healthy controls (n = 577). A computerized BART paradigm was used to examine impulsivity and risky decision-making, while participants also completed the Barratt Impulsiveness Scale (BIS-11), and ADHD participants completed the Adult Self-Report Scale-V1.1 (ASRS-V1.1). The BART presented two colors of balloons with differing probabilities of exploding, and participants were incentivized to pump the balloons as many times as possible without causing them to explode. The primary endpoint was "mean adjusted pumps", determined as mean across trials of the number of pumps on trials that did not end in explosion. An index of reactivity to loss was calculated as the difference between the mean adjusted pumps following an explosion and the mean adjusted pumps following trials in which the balloon did not explode.

The ADHD and control groups did not differ on mean adjusted pumps across trials, but they did differ in their reactivity to explosion of balloons that followed the most pumps, incurring the greatest level of loss (F(1, 551) = 7.1, p < 0.01). Interestingly, ADHD participants showed a greater reactivity to loss on these balloons than controls (p < 0.05), indicating that they reduced their number of pumps following balloon explosions more than controls. For participants as a whole, there were small correlations between loss reactivity and scales of everyday impulsivity on the BIS-II (ps < 0.05). For ADHD participants, loss reactivity was unrelated to symptoms of inattention but was significantly correlated with symptoms of hyperactivity/impulsivity (p = 0.01) and total ADHD symptoms (p < 0.05) on the ASRS-V1.1.

In the context of a risky decision-making task, adults with ADHD showed greater reactivity to loss than controls, despite showing comparable patterns of overall performance during the BART. The magnitude of behavioral adjustment following loss was correlated with symptoms of hyperactivity/impulsivity in adults with ADHD, suggesting that loss sensitivity is clinically related to impulsive behavior in everyday life. These findings help to expand our understanding of motivational processing in ADHD and suggest new insight into the ways in which everyday symptoms of ADHD are related to sensitivity to losses and punishments.

Sleep is a restorative function that supports various aspects of well-being, including cognitive function. College students, especially females, report getting less sleep than recommended and report more irregular sleep patterns than their male counterparts. Inadequate and irregular sleep are associated with neuropsychological deficits including more impulsive responding in lab-based tasks. Although many lab-based experiments ask participants to report their sleep patterns, few studies have analyzed how potential changes in sleep affect their findings. Utilizing data from a previously collected study, this study aims to investigate relations between sleep (i.e., sleep duration and changes in sleep duration) and performance-based measures of inhibition among female college students.

Participants (n = 39) were majority first-year students (Mage =19.27) and Caucasian (51%). Participants were recruited to participate in a larger study exploring how food commercials affect inhibitory control. Participants were randomized to each study condition (watching a food or non-food commercial) over two visits to the lab (T1 and T2). During both visits, they completed questionnaires asking about their 1) sleep duration the night before and 2) their “typical” sleep duration to capture changes in sleep duration. They also completed a computer-based stop signal task (SST) which required them to correctly identify healthy food images (stop signal accuracy [SSA] healthy) and unhealthy food images (SSA unhealthy) while inhibiting their response during a stop signal delay (SSD) which became increasingly more difficult (or delayed) as they successfully progressed. Since the main aim of the study was to explore the impact of sleep, analyses controlled for study condition. Analyses involving changes in sleep also accounted for sleep duration the night before the study visit.

On average, students reported being under slept the night before the lab visit, reporting that they got 38 minutes less sleep than their “typical” sleep (7 hrs 3 min). Hierarchical regression analyses demonstrated that sleep duration the night before the lab visit was not associated with inhibition (i.e., SSA unhealthy, SSA healthy, SSD). In contrast, a greater change in sleep, or getting less sleep than “typical,” was associated with worsened inhibition across inhibition variables (SSA healthy, SSA unhealthy, SSD) above and beyond sleep duration at T1. At T2, only one analysis remained significant, such that getting less sleep than “typical” was associated with lower accuracy of appropriately identifying unhealthy images (SSA unhealthy) whereas other analyses only approached statistical significance.

These findings suggest that changes in sleep, or getting less sleep than typical, may impact inhibition performance measured in a lab, even when accounting for how much sleep they got the night before. Specifically, getting less sleep than typical was associated with reduced accuracy in selecting unhealthy images, a finding that was consistent across two visits to the lab. These preliminary findings offer opportunities for lab-based experiments to investigate the role of sleep when measuring inhibition performance. Further, clinicians conducting neuropsychological assessments in clinical settings may benefit from assessing sleep the night before the appointment and determine if this represents a change from their typical sleep pattern.

Rapid neurodevelopment occurs during adolescence, which may increase the developing brain’s susceptibility to environmental risk and resilience factors. Adverse childhood experiences (ACEs) may confer additional risk to the developing brain, where ACEs have been linked with alterations in BOLD signaling in brain regions underlying inhibitory control. Potential resiliency factors, like a positive family environment, may attenuate the risk associated with ACEs, but limited research has examined potential buffers to adversity’s impact on the developing brain. The current study aimed to examine how ACEs relate to BOLD response during successful inhibition on the Stop Signal Task (SST) in regions underlying inhibitory control from late childhood to early adolescence and will assess whether aspects of the family environment moderate this relationship.

Participants (N= 9,080; Mage= 10.7, range= 9-13.8 years old; 48.5% female, 70.1% non-Hispanic White) were drawn from the larger Adolescent Brain Cognitive Development (ABCD) Study cohort. ACE risk scores were created (by EAS) using parent and child reports of youth’s exposure to adverse experiences collected at baseline to 2-year follow-up. For family environment, levels of family conflict were assessed based on youth reports on the Family Environment Scale at baseline and 2-year follow-up. The SST, a task-based fMRI paradigm, was used to measure inhibitory control (contrast: correct stop > correct go); the task was administered at baseline and 2-year follow-up. Participants were excluded if flagged for poor task performance. ROIs included left and right dorsolateral prefrontal cortex, anterior cingulate cortex, anterior insula, inferior frontal gyrus (IFG), and pre-supplementary motor area (pre-SMA). Separate linear mixed-effects models were conducted to assess the relationship between ACEs and BOLD signaling in ROIs while controlling for demographics (age, sex assigned at birth, race, ethnicity, household income, parental education), internalizing scores, and random effects of subject and MRI model.

Greater ACEs was associated with reduced BOLD response in the opercular region of the right IFG (b= -0.002, p= .02) and left (b= -0.002, p= .01) and right pre-SMA (b= -0.002, p= .01). Family conflict was related to altered activation patterns in the left pre-SMA, where youth with lower family conflict demonstrated a more robust negative relationship (b=.001, p= .04). ACEs were not a significant predictor in other ROIs, and the relationship between ACEs and BOLD response did not significantly differ across time. Follow-up brain-behavior correlations showed that in youth with lower ACEs, there was a negative correlation between increased activation in the pre-SMA and less impulsive behaviors.

Preadolescents with ACE history show blunted activation in regions underlying inhibitory control, which may increase the risk for future poorer inhibitory control with downstream implications for behavioral/health outcomes. Further, results demonstrate preliminary evidence for the family environment’s contributions to brain health. Future work is needed to examine other resiliency factors that may modulate the impact of ACE exposure during childhood and adolescence. Further, clinical scientists should continue to examine the relationship between ACEs and neural and behavioral correlates of inhibitory control across adolescent development, as risk-taking behaviors progress.

Inhibitory control impairment is highly prevalent following traumatic brain injury (TBI). There have not been any empirical investigations into whether this could explain social disinhibition following severe TBI, i.e. socially inappropriate behaviour of verbal, physical or sexual nature. Further, social context has proven to be important in studying social disinhibition and using a social version of an established task for the assessment of inhibitory control may provide a new perspective. Therefore, the objectives of this research study were to investigate the role of inhibitory control impairment in social disinhibition following severe TBI, using a social and a non-social task. We hypothesized that people with TBI and clinical levels of social disinhibition would perform worse on both task versions, when compared to those with low disinhibition levels. Further, we hypothesized that participants high on social disinhibition would perform worse on the social, when compared to the non-social version.

We conducted a between-group comparative study. Twenty-six adult participants with severe TBI were matched with 27 adult, healthy controls based on gender, age and education. Frontal Systems Behavior Scale and Social Disinhibition Interview were used to assess social disinhibition. A computerized task based on the cued go/no-go paradigm was used to assess inhibitory control. We included two versions of this task – a coloured (non-social) Go/No-Go with different colored rectangles, and an emotional (social) Go/No-Go with emotional faces serving as ‘go‘ and ‘no-go‘ cues. Two-way mixed ANCOVAs were used to test between-group differences in errors of commission and response speed.

Unexpectedly, the TBI and the control group did not significantly differ on their levels of depression, anxiety, stress, or their level of social disinhibition. Overall, participants were slower (F(1,47) = 15.212, p<.001, ηp2 = .245) and made more errors of commission on no-go trials (F(1,44) = 11.560, p = .001, ηp2 = .208) on the social Go/No-Go task. There was no main effect of participants‘ brain injury status on errors of commission on no-go trials or mean reaction times. When categorized based on disinhibition level (high vs low), participants in the highdisinhibition group made more errors on the social task (F(1,41) = 4.095, p = .050, ηp2 = .091) than those in the low-disinhibition group, and more errors on the social, compared to the non-social task (task-group interaction (F(1,41) = 7.233, p = .010, ηp2 = .150)).

Based on these initial results, social disinhibition is associated with inhibitory control impairment, although this is only evident when a social inhibitory control task is used for assessment. We did not find any relationship between social disinhibition and the speed with which people react to stimuli. The results of this study add to the conceptualization of social disinhibition that is commonly present after severe TBI.

The current study had two primary objectives: 1) To assess the dose-response relationship between acute bouts of aerobic exercise intensity and performance in multiple cognitive domains (episodic memory, attention, and executive function) and 2) To replicate and extend the literature by examining the dose-response relationship between aerobic exercise intensity and pattern separation.

18 young adults (mean age = 21.6, sd = 2.6; mean education = 13.9, sd = 3.4; 50% female) were recruited from The Ohio State University and surrounding area (Columbus, OH). Participants completed control (no exercise), light intensity, and vigorous intensity exercise conditions across three counterbalanced appointments. For each participant, all three appointments occurred at approximately the same time of day with at least 2 days between appointments. Following the rest or exercise conditions and after an approximately 7 minute delay, participants completed a Mnemonic Similarity Task (MST; Stark et al., 2019) to assess pattern separation. This task was always administered first as we attempted to replicate previous studies and further clarify the relationship between acute bouts of aerobic exercise and pattern separation by implementing an exercise stimulus that varied in intensity. After the MST, three brief cognitive tasks (roughly 5 min each) were administered in a counterbalanced order: a gradual-onset continuous performance task (gradCPT; Esterman et al., 2013), the flanker task from the NIH toolbox, and a face-name episodic memory task. Here we report results from the gradCPT, which assesses sustained attention and inhibitory control. Heart rate and ratings of perceived exertion were collected to validate the rest and exercise conditions. Repeated-measures ANOVAs were used to assess the relationship between exercise condition and dependent measures of sustained attention and inhibitory control and pattern separation.

One-way repeated-measures ANOVAs revealed a main effect of exercise condition on gradCPT task performance for task discrimination ability (d') and commission error rate (p’s < .05). Pairwise comparisons revealed task discrimination ability was significantly higher following the light intensity exercise condition versus the control condition. Commission error rate was significantly lower for both the light and vigorous exercise conditions compared to the control condition. For the MST, two-way repeated-measures ANOVAs revealed an expected significant main effect of lure similarity on task performance; however, there was not a significant main effect of exercise intensity on task performance (or a significant interaction).

The current study indicated that acute bouts of exercise improve both sustained attention and inhibitory control as measured with the gradCPT. We did not replicate previous work reporting that acute bouts of exercise improve pattern separation in young adults. Our results further indicate that vigorous exercise did not detrimentally impact or improve pattern separation performance. Our results indicate that light intensity exercise is sufficient to enhance sustained attention and inhibitory control, as there were no significant differences in performance following light versus vigorous exercise.

Recent findings suggest that brief dialectical behavior therapy (DBT) for borderline personality disorder is effective for reducing self-harm, but it remains unknown which patients are likely to improve in brief v. 12 months of DBT. Research is needed to identify patient characteristics that moderate outcomes. Here, we characterized changes in cognition across brief DBT (DBT-6) v. a standard 12-month course (DBT-12) and examined whether cognition predicted self-harm outcomes in each arm.

In this secondary analysis of 240 participants in the FASTER study (NCT02387736), cognitive measures were administered at pre-treatment, after 6 months, and at 12 months. Self-harm was assessed from pre-treatment to 2-year follow-up. Multilevel models characterized changes in cognition across treatment. Generalized estimating equations examined whether pre-treatment cognitive performance predicted self-harm outcomes in each arm.

Cognitive performance improved in both arms after 6 months of treatment, with no between-arm differences at 12-months. Pre-treatment inhibitory control was associated with different self-harm outcomes in DBT-6 v. DBT-12. For participants with average inhibitory control, self-harm outcomes were significantly better when assigned to DBT-12, relative to DBT-6, at 9–18 months after initiating treatment. In contrast, participants with poor inhibitory control showed better self-harm outcomes when assigned to brief DBT-6 v. DBT-12, at 12–24 months after initiating treatment.

This work represents an initial step toward an improved understanding of patient profiles that are best suited to briefer v. standard 12 months of DBT, but observed effects should be replicated in a waitlist-controlled study to confirm that they were treatment-specific.

Inhibitory control develops in early childhood, and atypical development may be a measurable marker of risk for the later development of psychosis. Additionally, inhibitory control may be a target for intervention.

Behavioral performance on a developmentally appropriate Go/No-Go task including a frustration manipulation completed by children ages 3–5 years (early childhood; n = 107) was examined in relation to psychotic-like experiences (PLEs; ‘tween’; ages 9–12), internalizing symptoms, and externalizing symptoms self-reported at long-term follow-up (pre-adolescence; ages 8–11). ERP N200 amplitude for a subset of these children (n = 34) with electrophysiological data during the task was examined as an index of inhibitory control.

Children with lower accuracy on No-Go trials compared to Go trials in early childhood (F(1,101) = 3.976, p = 0.049), evidenced higher PLEs at the transition to adolescence 4–9 years later, reflecting a specific deficit in inhibitory control. No association was observed with internalizing or externalizing symptoms. Decreased accuracy during the frustration manipulation predicted higher internalizing, F(2,202) = 5.618, p = 0.004, and externalizing symptoms, F(2,202) = 4.663, p = 0.010. Smaller N200 amplitudes were observed on No-Go trials for those with higher PLEs, F(1,101) = 6.075, p = 0.020; no relationship was observed for internalizing or externalizing symptoms.

Long-term follow-up demonstrates for the first time a specific deficit in inhibitory control behaviorally and electrophysiology, for individuals who later report more PLEs. Decreases in task performance under frustration induction indicated risk for internalizing and externalizing symptoms. These findings suggest that pathophysiological mechanisms for psychosis are relevant and discriminable in early childhood, and further, suggest an identifiable and potentially modifiable target for early intervention.