Functional Connectivity Mechanisms Underlying Symptom Reduction Following Lisdexamfetamine Treatment in Binge-Eating Disorder: A Clinical Trial.

Background: Speculation exists as to whether lisdexamfetamine dimesylate (LDX) acts on the functional connectivity (FC) of brain networks that modulate appetite, reward, or inhibitory control in binge-eating disorder (BED). Better insights into its action may help guide the development of more targeted therapeutics and identify who will benefit most from this medication. Here, we use a comprehensive data-driven approach to investigate the brain FC changes that underlie the therapeutic action of LDX in patients with BED. Methods: Forty-six participants with moderate to severe BED received LDX titrated to 50 or 70 mg for an 8-week period. Twenty age-matched healthy control participants were also recruited. Resting-state functional magnetic resonance imaging was used to probe changes in brain FC pre- and post treatment and correlated with change in clinical measures. Results: Ninety-seven percent of trial completers (n = 31) experienced remission or a reduction to mild BED during the 8-week LDX trial. Widespread neural FC changes occurred, with changes in default mode to limbic, executive control to subcortical, and default mode to executive control networks associated with improvements in clinical outcomes. These connections were not distinct from control participants at pretreatment but were different from control participants following LDX treatment. Pretreatment connectivity did not predict treatment response. Conclusions: FC between networks associated with self-referential processing, executive function, and reward seem to underlie the therapeutic effect of LDX in BED. This suggests that LDX activates change via multiple systems, with most changes in compensatory networks rather than in those characterizing the BED diagnosis.

My Diet Study: protocol for a two-part observational, longitudinal, psycho-biological study of dieting in Australian youth.

Introduction: Self-directed dieting (i.e., unsupervised) is very common among adolescents and young adults but has had almost no direct research. This paper describes the protocol for the My Diet Study, a two-arm observational investigation of the natural progression of dieting among young people over a period of 6-months. The study aims to examine the links between self-directed dieting, general physiological and psychological metrics of wellbeing (e.g., depressive symptoms) and biomarkers of gut-brain axis functions (e.g., microbiome and hormones) that are predicted to influence diet adherence through appetite, mood and metabolism regulation. Methods: Young people aged 16-25, intending to start a diet will be invited to participate in this observational study. For Part 1 (psychological arm), participants will be asked to complete a set of questionnaires and diaries at the beginning of every month for 6 months, to assess overall mental (e.g., psychological distress, disordered eating) and physical (e.g., weight) health, perceived diet success, food intake and gastrointestinal movements. For Part 2 (biological arm), a subsample of 50 participants will be asked to provide feces, blood and saliva for bio-sampling each month for the first 3-months of their participation in Part 1. Discussion: The My Diet Study will be the first longitudinal, observational study of dieting in young people combining in-depth psychological and biological data. It is anticipated that the findings will yield psychological & biological information about the impacts and effectiveness of self-directed dieting in young people, inform a framework for advice on safety in dieting among young people and help to establish the potential for biomarkers for risk management and improvement of diet-based lifestyle interventions.

The Motivational Determinants of Human Action, Their Neural Bases and Functional Impact in Adolescents With Obsessive-Compulsive Disorder.

Background: Establishing the motivational influences on human action is essential for understanding choice and decision making in health and disease. Here we used tests of value-based decision making, manipulating both predicted and experienced reward values to assess the motivational control of goal-directed action in healthy adolescents and those with obsessive-compulsive disorder (OCD). Methods: After instrumental training on a two action-two outcome probabilistic task, adolescents (n = 21) underwent Pavlovian conditioning using distinct stimuli predicting either the instrumental outcomes, a third outcome, or nothing. We then assessed functional magnetic resonance imaging during choice tests in which we varied the predicted value, using specific and general Pavlovian-instrumental transfer, and the experienced value, using outcome devaluation. To establish functional significance, we tested a matched cohort of adolescents with OCD (n = 20). Results: In healthy adolescents, both predicted and experienced values influenced the performance of goal-directed actions, mediated by distinct orbitofrontal-striatal circuits involving the lateral orbitofrontal cortex (OFC) and medial OFC, respectively. However, in adolescents with OCD, choice was insensitive to changes in either predicted or experienced values. These impairments were related to hypoactivity in the lateral OFC and hyperactivity in the medial OFC during specific Pavlovian-instrumental transfer and hypoactivity in the anterior prefrontal cortex, caudate nucleus, and their connectivity in the devaluation test. Conclusions: We found that predicted and experienced values exerted a potent influence on the performance of goal-directed actions in adolescents via distinct orbitofrontal- and prefrontal-striatal circuits. Furthermore, the influence of these motivational processes was severely blunted in OCD, as was the functional segregation of circuits involving medial and lateral OFC, producing dysregulated action control.

Brainmarker-I Differentially Predicts Remission to Various Attention-Deficit/Hyperactivity Disorder Treatments: A Discovery, Transfer, and Blinded Validation Study.

BACKGROUND: Attention-deficit/hyperactivity disorder is characterized by neurobiological heterogeneity, possibly explaining why not all patients benefit from a given treatment. As a means to select the right treatment (stratification), biomarkers may aid in personalizing treatment prescription, thereby increasing remission rates. METHODS: The biomarker in this study was developed in a heterogeneous clinical sample (N = 4249) and first applied to two large transfer datasets, a priori stratifying young males (<18 years) with a higher individual alpha peak frequency (iAPF) to methylphenidate (N = 336) and those with a lower iAPF to multimodal neurofeedback complemented with sleep coaching (N = 136). Blinded, out-of-sample validations were conducted in two independent samples. In addition, the association between iAPF and response to guanfacine and atomoxetine was explored. RESULTS: Retrospective stratification in the transfer datasets resulted in a predicted gain in normalized remission of 17% to 30%. Blinded out-of-sample validations for methylphenidate (n = 41) and multimodal neurofeedback (n = 71) corroborated these findings, yielding a predicted gain in stratified normalized remission of 36% and 29%, respectively. CONCLUSIONS: This study introduces a clinically interpretable and actionable biomarker based on the iAPF assessed during resting-state electroencephalography. Our findings suggest that acknowledging neurobiological heterogeneity can inform stratification of patients to their individual best treatment and enhance remission rates.

Altered resting-state neural networks in children and adolescents with functional neurological disorder.

OBJECTIVES: Previous studies with adults suggest that aberrant communication between neural networks underpins functional neurological disorder (FND). The current study adopts a data-driven approach to investigate the extent that functional resting-state networks are disrupted in a pediatric mixed-FND cohort. METHODS: 31 children with mixed FND and 33 age- and sex-matched healthy controls completed resting-state fMRI scans. Whole-brain independent component analysis (pFWE < 0.05) was then used to identify group differences in resting-state connectivity. Self-report measures included the Depression, Anxiety and Stress Scale (DASS-21) and Early Life Stress Questionnaire (ELSQ). Resting-state heart rate (HR) and cortisol-awakening response (CAR) were available in a subset. RESULTS: Children with FND showed wide-ranging connectivity changes in eight independent components corresponding to eight resting-state neural networks: language networks (IC6 and IC1), visual network, frontoparietal network, salience network, dorsal attention network, cerebellar network, and sensorimotor network. Children whose clinical presentation included functional seizures (vs children with other FND symptoms) showed greater connectivity decreases in the frontoparietal and dorsal attentional networks. Subjective distress (total DASS score), autonomic arousal (indexed by HR), and HPA dysregulation (attenuated/reversed CAR) contributed to changes in neural network connectivity. Children with FND (vs controls) reported more subjective distress (total DASS score) and more adverse childhood experiences (ACEs) across their lifespan. CONCLUSIONS: Children with FND demonstrate changes in resting-state connectivity. Identified network alterations underpin a broad range of functions typically disrupted in children with FND. This study complements the adult literature by suggesting that FND in children and adolescents emerges in the context of their lived experience and that it reflects aberrant communication across neural networks.

Common and differential neural mechanisms underlying mood disorders.

BACKGROUND: Despite homogenous clinical presentations between bipolar and unipolar disorders, there are distinct neurobiological differences. Chronicity of illness may be a factor impacting and sustaining certain neural features. The goal of this study was to investigate common and shared neural mechanisms underlying mood disorders, and possible sustained neural changes relating to illness chronicity by investigating a cohort of euthymic patients with bipolar disorder (BD), unipolar depression who had responded to treatment (treatment-sensitive depression, TSD), and a chronically treatment-resistant depressed (TRD) group. METHODS: One hundred and seventy-two participants (40 BD, 39 TSD, 40 TRD, and 53 age-gender-matched healthy controls) underwent resting-state fMRI scans. Seed-based and independent component analyses were performed to investigate group differences in resting-state connectivity between the four groups. RESULTS: All three clinical groups had significantly lower connectivity within the frontoparietal network (FPN) relative to controls. TRD and BD were significantly different from TSD (TRD, BD > TSD) but were not significantly different from each other. TRDs were also significantly different from both BD and TSD for salience network connectivity with the posterior cingulate (DMN) and the FPN with frontal pole (DMN). Additionally, the BD group exhibited greater DMN-FPN (sgACC-RDLPFC) connectivity relative to TRD, TSD, and controls, which was correlated with a previous number of depressive episodes, in the BD group only. CONCLUSIONS: BD demonstrated shared and differential connectivity features relative to symptomatic TRD and euthymic TSD groups. The increased sgACC-RDLPFC connectivity in BD and its correlation with a number of depressive episodes could be a neural feature associated with illness chronicity.

Intrinsic Functional Connectivity in the Default Mode Network Differentiates the Combined and Inattentive Attention Deficit Hyperactivity Disorder Types.

Neuroimaging studies have revealed neurobiological differences in ADHD, particularly studies examining connectivity disruption and anatomical network organization. However, the underlying pathophysiology of ADHD types remains elusive as it is unclear whether dysfunctional network connections characterize the underlying clinical symptoms distinguishing ADHD types. Here, we investigated intrinsic functional network connectivity to identify neural signatures that differentiate the combined (ADHD-C) and inattentive (ADHD-I) presentation types. Applying network-based statistical (NBS) and graph theoretical analysis to task-derived intrinsic connectivity data from completed fMRI scans, we evaluated default mode network (DMN) and whole-brain functional network topology in a cohort of 34 ADHD participants (aged 8-17 years) defined using DSM-IV criteria as predominantly inattentive (ADHD-I) type (n = 15) or combined (ADHD-C) type (n = 19), and 39 age and gender-matched typically developing controls. ADHD-C were characterized from ADHD-I by reduced network connectivity differences within the DMN. Additionally, reduced connectivity within the DMN was negatively associated with ADHD-RS hyperactivity-impulsivity subscale score. Compared with controls, ADHD-C but not ADHD-I differed by reduced connectivity within the DMN; inter-network connectivity between the DMN and somatomotor networks; the DMN and limbic networks; and between the somatomotor and cingulo-frontoparietal, with ventral attention and dorsal attention networks. However, graph-theoretical measures did not significantly differ between groups. These findings provide insight into the intrinsic networks underlying phenotypic differences between ADHD types. Furthermore, these intrinsic functional connectomic signatures support neurobiological differences underlying clinical variations in ADHD presentations, specifically reduced within and between functional connectivity of the DMN in the ADHD-C type.

The Neural Bases of Action-Outcome Learning in Humans.

From an associative perspective the acquisition of new goal-directed actions requires the encoding of specific action-outcome (AO) associations and, therefore, sensitivity to the validity of an action as a predictor of a specific outcome relative to other events. Although competitive architectures have been proposed within associative learning theory to achieve this kind of identity-based selection, whether and how these architectures are implemented by the brain is still a matter of conjecture. To investigate this issue, we trained human participants to encode various AO associations while undergoing functional neuroimaging (fMRI). We then degraded one AO contingency by increasing the probability of the outcome in the absence of its associated action while keeping other AO contingencies intact. We found that this treatment selectively reduced performance of the degraded action. Furthermore, when a signal predicted the unpaired outcome, performance of the action was restored, suggesting that the degradation effect reflects competition between the action and the context for prediction of the specific outcome. We used a Kalman filter to model the contribution of different causal variables to AO learning and found that activity in the medial prefrontal cortex (mPFC) and the dorsal anterior cingulate cortex (dACC) tracked changes in the association of the action and context, respectively, with regard to the specific outcome. Furthermore, we found the mPFC participated in a network with the striatum and posterior parietal cortex to segregate the influence of the various competing predictors to establish specific AO associations.SIGNIFICANCE STATEMENT Humans and other animals learn the consequences of their actions, allowing them to control their environment in a goal-directed manner. Nevertheless, it is unknown how we parse environmental causes from the effects of our own actions to establish these specific action-outcome (AO) relationships. Here, we show that the brain learns the causal structure of the environment by segregating the unique influence of actions from other causes in the medial prefrontal and anterior cingulate cortices and, through a network of structures, including the caudate nucleus and posterior parietal cortex, establishes the distinct causal relationships from which specific AO associations are formed.

Cognitive and Executive Contributions to Trail-Making Task Performance on Adolescents With and Without Attention Deficit Hyperactivity Disorder.

OBJECTIVE: The trail making task is used to assess executive functioning in ADHD youth, yet has only been validated in adult populations. We compare the relative contributions of various cognitive measures to performance on a trail making task analog, the Switching of Attention (SoA) task, in typically-developing and ADHD adolescents. METHOD: Participants were 160 adolescents with ADHD from the International Study to Predict Optimized Treatment-in ADHD, assessed at pretreatment baseline and 6-week medicated follow-up, and 160 matched typically-developing peers. Attention, processing speed, working memory, impulsivity, and motor speed were assessed using a cognitive battery. RESULTS: Processing speed and working memory significantly contributed to SoA performance in ADHD, regardless of medication status. While medicated, motor speed also underpinned the prediction of most task measures. For typically-developing adolescents, sustained attention and working memory contributed to SoA performance. CONCLUSION: Typically-developing, unmedicated and treated ADHD adolescents recruit different aspects of cognition during SoA completion.

Default-mode and fronto-parietal network connectivity during rest distinguishes asymptomatic patients with bipolar disorder and major depressive disorder.

Bipolar disorder (BD) is commonly misdiagnosed as major depressive disorder (MDD). This is understandable, as depression often precedes mania and is otherwise indistinguishable in both. It is therefore imperative to identify neural mechanisms that can differentiate the two disorders. Interrogating resting brain neural activity may reveal core distinguishing abnormalities. We adopted an a priori approach, examining three key networks documented in previous mood disorder literature subserving executive function, salience and rumination that may differentiate euthymic BD and MDD patients. Thirty-eight patients with BD, 39 patients with MDD matched for depression severity, and 39 age-gender matched healthy controls, completed resting-state fMRI scans. Seed-based and data-driven Independent Component analyses (ICA) were implemented to examine group differences in resting-state connectivity (pFDR < 0.05). Seed analysis masks were target regions identified from the fronto-parietal (FPN), salience (SN) and default-mode (DMN) networks. Seed-based analyses identified significantly greater connectivity between the subgenual cingulate cortex (DMN) and right dorsolateral prefrontal cortex (FPN) in BD relative to MDD and controls. The ICA analyses also found greater connectivity between the DMN and inferior frontal gyrus, an FPN region in BD relative to MDD. There were also significant group differences across the three networks in both clinical groups relative to controls. Altered DMN-FPN functional connectivity is thought to underlie deficits in the processing, management and regulation of affective stimuli. Our results suggest that connectivity between these networks could potentially distinguish the two disorders and could be a possible trait mechanism in BD persisting even in the absence of symptoms.

Impulsivity and Its Relationship With Lisdexamfetamine Dimesylate Treatment in Binge Eating Disorder.

High trait impulsivity is thought to contribute to the sense of loss of control over eating and impulses to binge eat experienced by those with binge eating disorder (BED). Lisdexamfetamine dimesylate (LDX), a drug approved for treatment of moderate to severe BED, has been shown to decrease impulsive features of BED. However, the relationship between LDX-related reductions of binge eating (BE) episodes and impulsivity has not yet been explored. Forty-one adults aged 18-40years with moderate to severe BED completed questionnaires and tasks assessing impulsivity at baseline and after 8weeks of 50-70mg of LDX. Twenty age-matched healthy controls were also assessed at two timepoints for normative comparison. Data were analysed using linear mixed models. BED participants exhibited increased self-reported motor, non-planning, cognitive and food-related impulsivity relative to controls but no differences in objective task-based measures of impulsivity. Food-related and non-planning impulsivity was significantly reduced by LDX, but not to normative levels. Individuals with higher baseline levels of motor and non-planning impulsivity, and loss of control over eating scores experienced the greatest reduction in BE frequency after 8weeks of LDX. Further, there were significant associations between the degree to which subjective loss of control over eating, non-planning impulsivity and BE frequency reduced after 8weeks of LDX. These data suggest that specific subjective measures of impulsivity may be able to predict who will have the greatest benefit from LDX treatment and that reductions in BE frequency may be moderated by concurrent reductions in non-planning impulsivity.

Age-related resting-state functional connectivity of the Vigilant Attention network in children and adolescents.

The development of Vigilant Attention (VA), the ability to focus and maintain our attention to repetitive and cognitively unchallenging tasks over time, has been investigated for more than a decade. The development of this critical executive function across the lifespan has been characterised by a rapid improvement in VA performance throughout childhood and adolescence, a steady improvement in adulthood and a slow decline in older adulthood. However, the development of the neural correlates of VA in children and adolescents remains poorly understood. Using a cross-sectional design, the present study used a meta-analytically defined VA network in children and adolescents to explore the developmental trend of the resting-state functional connectivity (rsFC) within the VA network across two independent cohorts. The results showed a linear and non-linear decrease of rsFC between the left and right VA brain regions across age. However, the results could not be reproduced in the replication cohort, potentially due to a smaller sample size. Based on previous findings from behavioural studies, the present findings suggest that changes in rsFC may underlie a developmental shift in cognitive strategies in neurotypical children and adolescents.

No support for white matter connectivity differences in the combined and inattentive ADHD presentations.

Evidence from functional neuroimaging studies support neural differences between the Attention Deficit Hyperactivity Disorder (ADHD) presentation types. It remains unclear if these neural deficits also manifest at the structural level. We have previously shown that the ADHD combined, and ADHD inattentive types demonstrate differences in graph properties of structural covariance suggesting an underlying difference in neuroanatomical organization. The goal of this study was to examine and validate white matter brain organization between the two subtypes using both scalar and connectivity measures of brain white matter. We used both tract-based spatial statistical (TBSS) and tractography analyses with network-based Statistics (NBS) and graph-theoretical analyses in a cohort of 35 ADHD participants (aged 8-17 years) defined using DSM-IV criteria as combined (ADHD-C) type (n = 19) or as predominantly inattentive (ADHD-I) type (n = 16), and 28 matched neurotypical controls. We performed TBSS analyses on scalar measures of fractional anisotropy (FA), mean (MD), radial (RD), and axial (AD) diffusivity to assess differences in WM between ADHD types and controls. NBS and graph theoretical analysis of whole brain inter-regional tractography examined connectomic differences and brain network organization, respectively. None of the scalar measures significantly differed between ADHD types or relative to controls. Similarly, there were no tractography connectivity differences between the two subtypes and relative to controls using NBS. Global and regional graph measures were also similar between the groups. A single significant finding was observed for nodal degree between the ADHD-C and controls, in the right insula (corrected p = .029). Our result of no white matter differences between the subtypes is consistent with most previous findings. These findings together might suggest that the white matter structural architecture is largely similar between the DSM-based ADHD presentations is similar to the extent of being undetectable with the current cohort size.

Structural brain network topology underpinning ADHD and response to methylphenidate treatment.

Behavioural disturbances in attention deficit hyperactivity disorder (ADHD) are thought to be due to dysfunction of spatially distributed, interconnected neural systems. While there is a fast-growing literature on functional dysconnectivity in ADHD, far less is known about the structural architecture underpinning these disturbances and how it may contribute to ADHD symptomology and treatment prognosis. We applied graph theoretical analyses on diffusion MRI tractography data to produce quantitative measures of global network organisation and local efficiency of network nodes. Support vector machines (SVMs) were used for comparison of multivariate graph measures of 37 children and adolescents with ADHD relative to 26 age and gender matched typically developing children (TDC). We also explored associations between graph measures and functionally-relevant outcomes such as symptom severity and prediction of methylphenidate (MPH) treatment response. We found that multivariate patterns of reduced local efficiency, predominantly in subcortical regions (SC), were able to distinguish between ADHD and TDC groups with 76% accuracy. For treatment prognosis, higher global efficiency, higher local efficiency of the right supramarginal gyrus and multivariate patterns of increased local efficiency across multiple networks at baseline also predicted greater symptom reduction after 6 weeks of MPH treatment. Our findings demonstrate that graph measures of structural topology provide valuable diagnostic and prognostic markers of ADHD, which may aid in mechanistic understanding of this complex disorder.

White matter microstructural differences in underweight adolescents with anorexia nervosa and a preliminary longitudinal investigation of change following short-term weight restoration.

PURPOSE: Anorexia nervosa (AN) affects approximately 2.9% of females and has the highest mortality rate among all psychiatric disorders. Despite several advances, the neurobiology of this disorder is still not well understood. Several studies have reported abnormalities in the white matter, but it is not know if these are disease-related or secondary to undernutrition. This study aimed to further our understanding of white matter pathology using diffusion-weighted imaging in underweight adolescents with AN, and to examine changes occurring after short-term weight restoration. METHODS: Analyses were conducted on diffusion-weighted imaging from 24 female adolescents with AN and 17 age- and gender-matched healthy controls (HC), aged 14-19 years. Groups were compared on fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) using tract-based spatial statistics analysis and DTI measures were correlated with eating disorder examination questionnaire (EDE-Q) subscales and body mass index (BMI). Preliminary repeated-measure analyses were also conducted on eight participants after short-term weight restoration (median 41 days). RESULTS: Widespread increases in MD of up to 9% were found in underweight AN relative to HC, particularly in the corpus callosum. This was associated with both increased AD and RD, suggestive of dys- or de-myelination. There were no significant group differences in FA, and no significant correlations between DTI measures, BMI or EDE-Q subscale score. Weight restoration therapy significantly reduced MD, to levels significantly lower than HC, but did not consistently alter FA across individuals. CONCLUSIONS: White matter microstructure is significantly altered in female adolescents with AN, with preliminary longitudinal data suggesting that it may be reversible with short-term weight restoration. LEVEL OF EVIDENCE: Level III: evidence obtained from well-designed cohort or case-control analytic studies.

Intrinsic functional connectivity of the default mode and cognitive control networks relate to change in behavioral performance over two years.

Understanding how brain circuitry mediates cognitive control of behavior is crucial for understanding both mental health and disease. Cognitive control describes the group of behaviors that guide goal-directed action such as sustaining attention, processing information and inhibiting impulsive responses. We rely on these behaviors for daily social, occupational and emotional functioning. Two brain networks, the cognitive control network (CCN) and default mode network (DMN), are thought to cooperate in an inverse relationship to support these functions. However, we do not yet know how connectivity within and between these networks directly relates to healthy cognitive control behaviors, and whether these interactions change over time. Here, we employed a longitudinal design to investigate if change in intrinsic connectivity in these networks will correlate with change in a range of cognitive control functions. Over two years, 109 healthy individuals, aged eight to thirty-eight, were tested twice using fMRI to assess intrinsic functional connectivity of the CCN and DMN and a validated cognitive battery. We found that increased within-network connectivity through central and left DMN was associated with increased memory performance. Additionally, decreased connectivity between posterior parietal CCN and DMN nodes and decreased connectivity between left and right dorsolateral prefrontal nodes was associated with increased cognitive performance. These findings were age and gender controlled, suggesting that age-independent plastic change in intrinsic connectivity through these networks directly relate to changing behavior. This has implications for targeting intrinsic connectivity as a possible mechanism to improve cognitive function.

A Systematic Review of Imaging Studies in the Combined and Inattentive Subtypes of Attention Deficit Hyperactivity Disorder.

Objective: Insights to underlying neural mechanisms in attention deficit hyperactivity disorder (ADHD) have emerged from neuroimaging research; however, the neural mechanisms that distinguish ADHD subtypes remain inconclusive. Method: We reviewed 19 studies integrating magnetic resonance imaging [MRI; structural (sMRI), diffusion, functional MRI (fMRI)] findings into a framework exploring pathophysiological mechanisms underlying the combined (ADHD-C) and predominantly inattentive (ADHD-I) ADHD subtypes. Results: Despite equivocal structural MRI results, findings from fMRI and DTI imaging modalities consistently implicate disrupted connectivity in regions and tracts involving frontal striatal thalamic in ADHD-C and frontoparietal neural networks in ADHD-I. Alterations of the default mode, cerebellum, and motor networks in ADHD-C and cingulo-frontoparietal attention and visual networks in ADHD-I highlight network organization differences between subtypes. Conclusion: Growing evidence from neuroimaging studies highlight neurobiological differences between ADHD clinical subtypes, particularly from a network perspective. Understanding brain network organization and connectivity may help us to better conceptualize the ADHD types and their symptom variability.

Understanding the neural mechanisms of lisdexamfetamine dimesylate (LDX) pharmacotherapy in Binge Eating Disorder (BED): a study protocol.

BACKGROUND: The efficacy and safety of Lisdexamfetamine dimesylate (LDX) in the treatment of moderate to severe binge eating disorder (BED) has been demonstrated in multiple randomised clinical trials. Despite this, little is known about how LDX acts to improve binge eating symptoms. This study aims to provide a comprehensive understanding of the neural mechanisms by which LDX improves symptoms of BED. We hypothesise that LDX will act by normalising connectivity within neural circuits responsible for reward and impulse control, and that this normalisation will correlate with reduced binge eating episodes. METHODS: This is an open-label Phase 4 clinical trial of LDX in adults with moderate to severe BED. Enrolment will include 40 adults with moderate to severe BED aged 18-40 years and Body Mass Index (BMI) of 20-45 kg/m2, and 22 healthy controls matched for age, gender and BMI. Clinical interview and validated scales are used to confirm diagnosis and screen for exclusion criteria, which include comorbid anorexia nervosa or bulimia nervosa, use of psychostimulants within the past 6 months, and current use of antipsychotics or noradrenaline reuptake inhibitors. Baseline assessments include clinical symptoms, multimodal neuroimaging, cognitive assessment of reward sensitivity and behavioural inhibition, and an (optional) genetic sample. A subset of these assessments are repeated after eight weeks of treatment with LDX titrated to either 50 or 70 mg. The primary outcome measures are resting-state intrinsic connectivity and the number of binge eating episodes. Analyses will be applied to resting-state fMRI data to characterise pharmacological effects across the functional connectome, and assess correlations with symptom measure changes. Comparison of neural measures between controls and those with BED post-treatment will also be performed to determine whether LDX normalises brain function. DISCUSSION: First enrolment was in May 2018, and is ongoing. This study is the first comprehensive investigation of the neurobiological changes that occur with LDX treatment in adults with moderate to severe BED. TRIAL REGISTRATION: ACTRN12618000623291, Australian and New Zealand Clinical Trials Registry URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374913&isReview=true. Date of Registration: 20 April 2018.

A Signature of Attention-Elicited Electrocortical Activity Distinguishes Response From Non-Response to the Non-Stimulant Atomoxetine in Children and Adolescents With ADHD.

OBJECTIVE: Atomoxetine has several characteristics that make it an attractive alternative to stimulants for treating ADHD, but there are currently no tests identifying individuals for whom the medication should be a first-line option. METHOD: Within the ADHD Controlled Trial Investigation Of a Non-stimulant (ACTION) study, we examined neuro-cortical activity in 52 youth with ADHD. Baseline event-related potentials (ERP) were compared between those who subsequently responded to 6 weeks of atomoxetine versus those who did not. RESULTS: Responders were distinguished by significantly lower auditory oddball N2 amplitudes than both non-responders and typically developing controls, particularly in the right frontocentral region ( p = .002, Cohen's d = 1.1). Leave-one-out cross validation determined that N2 amplitude in this region was able to accurately predict non-responders with a specificity of 80.8%. There were no P3 differences between responders and non-responders. CONCLUSION: The N2 amplitude is a biomarker that may have utility in predicting response to atomoxetine for youth with ADHD.

Response inhibition and emotional cognition improved by atomoxetine in children and adolescents with ADHD: The ACTION randomized controlled trial.

Although the non-stimulant medication atomoxetine is effective for attention-deficit hyperactivity disorder (ADHD) in children and adolescents, there are still significant gaps in our knowledge about whether atomoxetine improves anxiety symptoms or cognition in children. Furthermore, while cognition has been proposed as an intermediate phenotype for ADHD dysfunction, the relationships between clinical and cognitive outcomes are not yet understood. We addressed these knowledge gaps in a controlled trial using objective assessments of both general and emotional cognitive functions implicated in ADHD and in anxiety, which commonly co-occurs with ADHD. A total of 136 children and adolescents with ADHD (ages 6-17years; 80% male; 31.6% with a comorbid anxiety disorder) were enrolled in a randomized double-blind, placebo-controlled, cross-over trial of 6-weeks treatment with atomoxetine. Of these, 109 completed the second cross-over phase. Selected cognitive domains associated with ADHD and anxiety disorders (Sustained attention, response inhibition and fearful face identification) were assessed using a normed, computerized test battery. Symptom outcomes were assessed by parent reports on the ADHD Rating Scale-IV and Conners' Anxious-Shy subscale. For completers, atomoxetine caused a greater improvement in the primary cognitive outcomes of response inhibition and fear identification compared to placebo, but not in sustained attention. Atomoxetine also improved ADHD and anxiety symptoms. Anxiety symptoms improved most for ADHD and anxiety disorder combined, but presence of an anxiety disorder did not moderate any other outcomes. Changes in cognitive and clinical outcomes were not correlated. These findings contribute to the foundations of measurement-based treatment planning and offer targets for probing the mechanisms of atomoxetine action.