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Introduction: Speech-based testing shows promise for sensitive and scalable objective screening for Alzheimer's disease (AD), but research to date offers limited evidence of generalizability., Methods: Data were taken from the AMYPRED (Amyloid Prediction in Early Stage Alzheimer's Disease from Acoustic and Linguistic Patterns of Speech) studies (N = 101, N = 46 mild cognitive impairment [MCI]) and Alzheimer's Disease Neuroimaging Initiative 4 (ADNI4) remote digital (N = 426, N = 58 self-reported MCI, mild AD or dementia) and in-clinic (N = 57, N = 13 MCI) cohorts, in which participants provided audio-recorded responses to automated remote story recall tasks in the Storyteller test battery. Text similarity, lexical, temporal, and acoustic speech feature sets were extracted. Models predicting early AD were developed in AMYPRED and tested out of sample in the demographically more diverse cohorts in ADNI4 (> 33% from historically underrepresented populations)., Results: Speech models generalized well to unseen data in ADNI4 remote and in-clinic cohorts. The best-performing models evaluated text-based metrics (text similarity, lexical features: area under the curve 0.71-0.84 across cohorts)., Discussion: Speech-based predictions of early AD from Storyteller generalize across diverse samples., Highlights: The Storyteller speech-based test is an objective digital prescreener for Alzheimer's Disease Neuroimaging Initiative 4 (ADNI4). Speech-based models predictive of Alzheimer's disease (AD) were developed in the AMYPRED (Amyloid Prediction in Early Stage Alzheimer's Disease from Acoustic and Linguistic Patterns of Speech) sample (N = 101). Models were tested out of sample in ADNI4 in-clinic (N = 57) and remote (N = 426) cohorts. Models showed good generalization out of sample. Models evaluating text matching and lexical features were most predictive of early AD., (© 2024 Novoic Ltd. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: We evaluated preliminary feasibility of a digital, culturally-informed approach to recruit and screen participants for the Alzheimer's Disease Neuroimaging Initiative (ADNI4)., Methods: Participants were recruited using digital advertising and completed digital surveys (e.g., demographics, medical exclusion criteria, 12-item Everyday Cognition Scale [ECog-12]), Novoic Storyteller speech-based cognitive test). Completion rates and assessment performance were compared between underrepresented populations (URPs: individuals from ethnoculturally minoritized or low education backgrounds) and non-URPs., Results: Of 3099 participants who provided contact information, 654 enrolled in the cohort, and 595 completed at least one assessment. Two hundred forty-seven participants were from URPs. Of those enrolled, 465 met ADNI4 inclusion criteria and 237 evidenced possible cognitive impairment from ECog-12 or Storyteller performance. URPs had lower ECog and Storyteller completion rates. Scores varied by ethnocultural group and educational level., Discussion: Preliminary results demonstrate digital recruitment and screening assessment of an older diverse cohort, including those with possible cognitive impairment, are feasible. Improving engagement and achieving educational diversity are key challenges., Highlights: A total of 654 participants enrolled in a digital cohort to facilitate ADNI4 recruitment. Culturally-informed digital ads aided enrollment of underrepresented populations. From those enrolled, 42% were from underrepresented ethnocultural and educational groups. Digital screening tools indicate > 50% of participants likely cognitively impaired. Completion rates and assessment performance vary by ethnocultural group and education., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Normative cognitive data can distinguish impairment from healthy cognitive function and pathological decline from normal ageing. Traditional methods for deriving normative data typically require extremely large samples of healthy participants, stratifying test variation by pre-specified age groups and key demographic features (age, sex, education). Linear regression approaches can provide normative data from more sparsely sampled datasets, but non-normal distributions of many cognitive test results may lead to violation of model assumptions, limiting generalisability., Method: The current study proposes a novel Bayesian framework for normative data generation. Participants ( n  = 728; 368 male and 360 female, age 18-75 years), completed the Cambridge Neuropsychological Test Automated Battery via the research crowdsourcing website Prolific.ac. Participants completed tests of visuospatial recognition memory (Spatial Working Memory test), visual episodic memory (Paired Associate Learning test) and sustained attention (Rapid Visual Information Processing test). Test outcomes were modelled as a function of age using Bayesian Generalised Linear Models, which were able to derive posterior distributions of the authentic data, drawing from a wide family of distributions. Markov Chain Monte Carlo algorithms generated a large synthetic dataset from posterior distributions for each outcome measure, capturing normative distributions of cognition as a function of age, sex and education., Results: Comparison with stratified and linear regression methods showed converging results, with the Bayesian approach producing similar age, sex and education trends in the data, and similar categorisation of individual performance levels., Conclusion: This study documents a novel, reproducible and robust method for describing normative cognitive performance with ageing using a large dataset., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Wragg, Skirrow, Dente, Cotter, Annas, Lowther, Backx, Barnett, Cree, Kroll and Cormack.)

Background: Cognitive symptoms are an underrecognized aspect of depression that are often untreated. High-frequency cognitive assessment holds promise for improving disease and treatment monitoring. Although we have previously found it feasible to remotely assess cognition and mood in this capacity, further work is needed to ascertain the optimal methodology to implement and synthesize these techniques., Objective: The objective of this study was to examine (1) longitudinal changes in mood, cognition, activity levels, and heart rate over 6 weeks; (2) diurnal and weekday-related changes; and (3) co-occurrence of fluctuations between mood, cognitive function, and activity., Methods: A total of 30 adults with current mild-moderate depression stabilized on antidepressant monotherapy responded to testing delivered through an Apple Watch (Apple Inc) for 6 weeks. Outcome measures included cognitive function, assessed with 3 brief n-back tasks daily; self-reported depressed mood, assessed once daily; daily total step count; and average heart rate. Change over a 6-week duration, diurnal and day-of-week variations, and covariation between outcome measures were examined using nonlinear and multilevel models., Results: Participants showed initial improvement in the Cognition Kit N-Back performance, followed by a learning plateau. Performance reached 90% of individual learning levels on average 10 days after study onset. N-back performance was typically better earlier and later in the day, and step counts were lower at the beginning and end of each week. Higher step counts overall were associated with faster n-back learning, and an increased daily step count was associated with better mood on the same (P<.001) and following day (P=.02). Daily n-back performance covaried with self-reported mood after participants reached their learning plateau (P=.01)., Conclusions: The current results support the feasibility and sensitivity of high-frequency cognitive assessments for disease and treatment monitoring in patients with depression. Methods to model the individual plateau in task learning can be used as a sensitive approach to better characterize changes in behavior and improve the clinical relevance of cognitive data. Wearable technology allows assessment of activity levels, which may influence both cognition and mood., (©Francesca Cormack, Maggie McCue, Caroline Skirrow, Nathan Cashdollar, Nick Taptiklis, Tempest van Schaik, Ben Fehnert, James King, Lambros Chrones, Sara Sarkey, Jasmin Kroll, Jennifer H Barnett. Originally published in JMIR Mental Health (https://mental.jmir.org), 31.05.2024.)

Anxiety and depression are associated with a range of impairments in cognitive functioning. Understanding the nature of these deficits may identify targets for intervention and prevent functional decline. We used observational and genetic methods to investigate the relationship of anxiety and depression with three cognitive domains: emotion recognition, response inhibition, and working memory, in the Avon Longitudinal Study of Parents and Children (ALSPAC). We examined: (i) cross-sectional associations between anxiety, depression, and cognition at age 24 ( n = 2187), (ii) prospective associations between anxiety and depression at age 18 and cognition at age 24 ( n = 1855), and (iii) the casual effect of anxiety and depression on cognition using Mendelian randomization (MR). Both disorders were associated with altered emotion recognition; anxiety with decreased happiness recognition ( b = - 0.27 [-0.54,0.01], p = 0.045), and depression with increased sadness recognition ( b = 0.35 [0.07,0.64], p = 0.016). Anxiety was also associated with poorer working memory ( b = - 0.14 [-0.24,0.04], p = 0.005). There was no evidence for an association with response inhibition. MR provided no clear evidence of causal relationships between mental health and cognition, but these analyses were underpowered. Overall, there was little evidence for impairments in executive functioning, but moderate alterations in emotion recognition. This may inform the development of psychosocial interventions., Competing Interests: M.R.M. and I.S.P.V. are co-directors of Jericoe Ltd, which produces software for the assessment and modification of emotion recognition. C.S. was employed by Cambridge Cognition during the period that this research was conducted. L.M., R.E.W. and S.S. report no conflicts of interest., (© 2023 The Authors.)

Introduction: Biomarkers of mental effort may help to identify subtle cognitive impairments in the absence of task performance deficits. Here, we aim to detect mental effort on a verbal task, using automated voice analysis and machine learning., Methods: Audio data from the digit span backwards task were recorded and scored with automated speech recognition using the online platform NeuroVocalix TM , yielding usable data from 2,764 healthy adults (1,022 male, 1,742 female; mean age 31.4 years). Acoustic features were aggregated across each trial and normalized within each subject. Cognitive load was dichotomized for each trial by categorizing trials at >0.6 of each participants' maximum span as "high load." Data were divided into training (60%), test (20%), and validate (20%) datasets, each containing different participants. Training and test data were used in model building and hyper-parameter tuning. Five classification models (Logistic Regression, Naive Bayes, Support Vector Machine, Random Forest, and Gradient Boosting) were trained to predict cognitive load ("high" vs. "low") based on acoustic features. Analyses were limited to correct responses. The model was evaluated using the validation dataset, across all span lengths and within the subset of trials with a four-digit span. Classifier discriminant power was examined with Receiver Operating Curve (ROC) analysis., Results: Participants reached a mean span of 6.34 out of 8 items (SD = 1.38). The Gradient Boosting classifier provided the best performing model on test data (AUC = 0.98) and showed excellent discriminant power for cognitive load on the validation dataset, across all span lengths (AUC = 0.99), and for four-digit only utterances (AUC = 0.95)., Discussion: A sensitive biomarker of mental effort can be derived from vocal acoustic features in remotely administered verbal cognitive tests. The use-case of this biomarker for improving sensitivity of cognitive tests to subtle pathology now needs to be examined., Competing Interests: The authors are current or former employees of Cambridge Cognition, a neuroscience technology company that has developed the NeuroVocalixTM platform., (Copyright © 2023 Taptiklis, Su, Barnett, Skirrow, Kroll and Cormack.)

Introduction: Artificial intelligence (AI) systems leveraging speech and language changes could support timely detection of Alzheimer's disease (AD)., Methods: The AMYPRED study (NCT04828122) recruited 133 subjects with an established amyloid beta (Aβ) biomarker (66 Aβ+, 67 Aβ-) and clinical status (71 cognitively unimpaired [CU], 62 mild cognitive impairment [MCI] or mild AD). Daily story recall tasks were administered via smartphones and analyzed with an AI system to predict MCI/mild AD and Aβ positivity., Results: Eighty-six percent of participants (115/133) completed remote assessments. The AI system predicted MCI/mild AD (area under the curve [AUC] = 0.85, ±0.07) but not Aβ (AUC = 0.62 ±0.11) in the full sample, and predicted Aβ in clinical subsamples (MCI/mild AD: AUC = 0.78 ±0.14; CU: AUC = 0.74 ±0.13) on short story variants (immediate recall). Long stories and delayed retellings delivered broadly similar results., Discussion: Speech-based testing offers simple and accessible screening for early-stage AD., Competing Interests: Emil Fristed, Jack Weston, Marton Meszaros, Caroline Skirrow, Raphael Lenain, and Udeepa Meepegama are employees of Novoic Ltd. Emil Fristed, Jack Weston, Marton Meszaros, and Raphael Lenain are shareholders and Marton Meszaros, Udeepa Meepegama, and Caroline Skirrow are option holders in the company. Emil Fristed and Jack Weston are directors on the board of Novoic. Stefano Cappa has received speaker's fees from Roche and Biogen. Dag Aarsland has received research support and/or honoraria from Astra‐Zeneca, Lundbeck, Novartis Pharmaceuticals, Evonik, Roche Diagnostics, and GE Health, and served as paid consultant for H. Lundbeck, Eisai, Heptares, Mentis Cura, Eli Lilly, Cognetivity, Enterin, Acadia, and Biogen. Author disclosures are available in the supporting information., (© 2022 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)

Early detection of Alzheimer's disease is required to identify patients suitable for disease-modifying medications and to improve access to non-pharmacological preventative interventions. Prior research shows detectable changes in speech in Alzheimer's dementia and its clinical precursors. The current study assesses whether a fully automated speech-based artificial intelligence system can detect cognitive impairment and amyloid beta positivity, which characterize early stages of Alzheimer's disease. Two hundred participants (age 54-85, mean 70.6; 114 female, 86 male) from sister studies in the UK (NCT04828122) and the USA (NCT04928976), completed the same assessments and were combined in the current analyses. Participants were recruited from prior clinical trials where amyloid beta status (97 amyloid positive, 103 amyloid negative, as established via PET or CSF test) and clinical diagnostic status was known (94 cognitively unimpaired, 106 with mild cognitive impairment or mild Alzheimer's disease). The automatic story recall task was administered during supervised in-person or telemedicine assessments, where participants were asked to recall stories immediately and after a brief delay. An artificial intelligence text-pair evaluation model produced vector-based outputs from the original story text and recorded and transcribed participant recalls, quantifying differences between them. Vector-based representations were fed into logistic regression models, trained with tournament leave-pair-out cross-validation analysis to predict amyloid beta status (primary endpoint), mild cognitive impairment and amyloid beta status in diagnostic subgroups (secondary endpoints). Predictions were assessed by the area under the receiver operating characteristic curve for the test result in comparison with reference standards (diagnostic and amyloid status). Simulation analysis evaluated two potential benefits of speech-based screening: (i) mild cognitive impairment screening in primary care compared with the Mini-Mental State Exam, and (ii) pre-screening prior to PET scanning when identifying an amyloid positive sample. Speech-based screening predicted amyloid beta positivity (area under the curve = 0.77) and mild cognitive impairment or mild Alzheimer's disease (area under the curve = 0.83) in the full sample, and predicted amyloid beta in subsamples (mild cognitive impairment or mild Alzheimer's disease: area under the curve = 0.82; cognitively unimpaired: area under the curve = 0.71). Simulation analyses indicated that in primary care, speech-based screening could modestly improve detection of mild cognitive impairment (+8.5%), while reducing false positives (-59.1%). Furthermore, speech-based amyloid pre-screening was estimated to reduce the number of PET scans required by 35.3% and 35.5% in individuals with mild cognitive impairment and cognitively unimpaired individuals, respectively. Speech-based assessment offers accessible and scalable screening for mild cognitive impairment and amyloid beta positivity., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Background: ADHD in adults is a common and debilitating neurodevelopmental mental health condition. Yet, diagnosis, clinical management and monitoring are frequently constrained by scarce resources, low capacity in specialist services and limited awareness or training in both primary and secondary care. As a result, many people with ADHD experience serious barriers in accessing the care they need., Methods: Professionals across primary, secondary, and tertiary care met to discuss adult ADHD clinical care in the United Kingdom. Discussions identified constraints in service provision, and service delivery models with potential to improve healthcare access and delivery. The group aimed to provide a roadmap for improving access to ADHD treatment, identifying avenues for improving provision under current constraints, and innovating provision in the longer-term. National Institute for Health and Care Excellence (NICE) guidelines were used as a benchmark in discussions., Results: The group identified three interrelated constraints. First, inconsistent interpretation of what constitutes a 'specialist' in the context of delivering ADHD care. Second, restriction of service delivery to limited capacity secondary or tertiary care services. Third, financial limitations or conflicts which reduce capacity and render transfer of care between healthcare sectors difficult. The group recommended the development of ADHD specialism within primary care, along with the transfer of routine and straightforward treatment monitoring to primary care services. Longer term, ADHD care pathways should be brought into line with those for other common mental health disorders, including treatment initiation by appropriately qualified clinicians in primary care, and referral to secondary mental health or tertiary services for more complex cases. Long-term plans in the NHS for more joined up and flexible provision, using a primary care network approach, could invest in developing shared ADHD specialist resources., Conclusions: The relegation of adult ADHD diagnosis, treatment and monitoring to specialist tertiary and secondary services is at odds with its high prevalence and chronic course. To enable the cost-effective and at-scale access to ADHD treatment that is needed, general adult mental health and primary care must be empowered to play a key role in the delivery of quality services for adults with ADHD., (© 2022. The Author(s).)

Background: Story recall is a simple and sensitive cognitive test that is commonly used to measure changes in episodic memory function in early Alzheimer disease (AD). Recent advances in digital technology and natural language processing methods make this test a candidate for automated administration and scoring. Multiple parallel test stimuli are required for higher-frequency disease monitoring., Objective: This study aims to develop and validate a remote and fully automated story recall task, suitable for longitudinal assessment, in a population of older adults with and without mild cognitive impairment (MCI) or mild AD., Methods: The "Amyloid Prediction in Early Stage Alzheimer's disease" (AMYPRED) studies recruited participants in the United Kingdom (AMYPRED-UK: NCT04828122) and the United States (AMYPRED-US: NCT04928976). Participants were asked to complete optional daily self-administered assessments remotely on their smart devices over 7 to 8 days. Assessments included immediate and delayed recall of 3 stories from the Automatic Story Recall Task (ASRT), a test with multiple parallel stimuli (18 short stories and 18 long stories) balanced for key linguistic and discourse metrics. Verbal responses were recorded and securely transferred from participants' personal devices and automatically transcribed and scored using text similarity metrics between the source text and retelling to derive a generalized match score. Group differences in adherence and task performance were examined using logistic and linear mixed models, respectively. Correlational analysis examined parallel-forms reliability of ASRTs and convergent validity with cognitive tests (Logical Memory Test and Preclinical Alzheimer's Cognitive Composite with semantic processing). Acceptability and usability data were obtained using a remotely administered questionnaire., Results: Of the 200 participants recruited in the AMYPRED studies, 151 (75.5%)-78 cognitively unimpaired (CU) and 73 MCI or mild AD-engaged in optional remote assessments. Adherence to daily assessment was moderate and did not decline over time but was higher in CU participants (ASRTs were completed each day by 73/106, 68.9% participants with MCI or mild AD and 78/94, 83% CU participants). Participants reported favorable task usability: infrequent technical problems, easy use of the app, and a broad interest in the tasks. Task performance improved modestly across the week and was better for immediate recall. The generalized match scores were lower in participants with MCI or mild AD (Cohen d=1.54). Parallel-forms reliability of ASRT stories was moderate to strong for immediate recall (mean rho 0.73, range 0.56-0.88) and delayed recall (mean rho=0.73, range=0.54-0.86). The ASRTs showed moderate convergent validity with established cognitive tests., Conclusions: The unsupervised, self-administered ASRT task is sensitive to cognitive impairments in MCI and mild AD. The task showed good usability, high parallel-forms reliability, and high convergent validity with established cognitive tests. Remote, low-cost, low-burden, and automatically scored speech assessments could support diagnostic screening, health care, and treatment monitoring., (©Caroline Skirrow, Marton Meszaros, Udeepa Meepegama, Raphael Lenain, Kathryn V Papp, Jack Weston, Emil Fristed. Originally published in JMIR Aging (https://aging.jmir.org), 30.09.2022.)

Test-retest reliability is essential to the development and validation of psychometric tools. Here we respond to the article by Karlsen et al. (Applied Neuropsychology: Adult, 2020), reporting test-retest reliability on the Cambridge Neuropsychological Test Automated Battery (CANTAB), with results that are in keeping with prior research on CANTAB and the broader cognitive assessment literature. However, after adopting a high threshold for adequate test-retest reliability, the authors report inadequate reliability for many measures. In this commentary we provide examples of stable, trait-like constructs which we would expect to remain highly consistent across longer time periods, and contrast these with measures which show acute within-subject change in response to contextual or psychological factors. Measures characterized by greater true within-subject variability typically have lower test-retest reliability, requiring adequate powering in research examining group differences and longitudinal change. However, these measures remain sensitive to important clinical and functional outcomes. Setting arbitrarily elevated test-retest reliability thresholds for test adoption in cognitive research limits the pool of available tools and precludes the adoption of many well-established tests showing consistent contextual, diagnostic, and treatment sensitivity. Overall, test-retest reliability must be balanced with other theoretical and practical considerations in study design, including test relevance and sensitivity.

Introduction: Neurodegenerative and psychiatric disorders (NPDs) confer a huge health burden, which is set to increase as populations age. New, remotely delivered diagnostic assessments that can detect early stage NPDs by profiling speech could enable earlier intervention and fewer missed diagnoses. The feasibility of collecting speech data remotely in those with NPDs should be established., Methods and Analysis: The present study will assess the feasibility of obtaining speech data, collected remotely using a smartphone app, from individuals across three NPD cohorts: neurodegenerative cognitive diseases (n=50), other neurodegenerative diseases (n=50) and affective disorders (n=50), in addition to matched controls (n=75). Participants will complete audio-recorded speech tasks and both general and cohort-specific symptom scales. The battery of speech tasks will serve several purposes, such as measuring various elements of executive control (eg, attention and short-term memory), as well as measures of voice quality. Participants will then remotely self-administer speech tasks and follow-up symptom scales over a 4-week period. The primary objective is to assess the feasibility of remote collection of continuous narrative speech across a wide range of NPDs using self-administered speech tasks. Additionally, the study evaluates if acoustic and linguistic patterns can predict diagnostic group, as measured by the sensitivity, specificity, Cohen's kappa and area under the receiver operating characteristic curve of the binary classifiers distinguishing each diagnostic group from each other. Acoustic features analysed include mel-frequency cepstrum coefficients, formant frequencies, intensity and loudness, whereas text-based features such as number of words, noun and pronoun rate and idea density will also be used., Ethics and Dissemination: The study received ethical approval from the Health Research Authority and Health and Care Research Wales (REC reference: 21/PR/0070). Results will be disseminated through open access publication in academic journals, relevant conferences and other publicly accessible channels. Results will be made available to participants on request., Trial Registration Number: NCT04939818., Competing Interests: Competing interests: RS has received an honorarium for speaking from Lundbeck. In the past 3 years, AY has received honoraria for speaking from AstraZeneca, Lundbeck, Eli Lilly and Sunovion; honoraria for consulting from Allergan, Livanova and Lundbeck, Sunovion and Janssen and research grant support from Janssen. ERH declares no conflicts of interest. EF is CEO of Novoic. MM, JW and CS are employees of Novoic, and EF, MM and JW are shareholders in the company., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ.)

Attention-deficit/hyperactive disorder (ADHD) is characterized by symptoms which are dynamic in nature: states of hyperactivity, inattention and impulsivity as core symptoms, and emotion dysregulation as associated feature. Although tremendous work has been done to investigate between-subject differences (how patients with ADHD differ from healthy controls or patients with other disorders), little is known about the relationship between symptoms with triggers and contexts, that may allow us to better understand their causes and consequences. Understanding the temporal associations between symptoms and environmental triggers in an ecologically valid manner may be the basis to developing just-in-time adaptive interventions. Fortunately, recent years have seen advances in methodology, hardware and innovative statistical approaches to study dynamic processes in daily life. In this narrative review, we provide a description of the methodology (ambulatory assessment), summarize the existing literature in ADHD, and discuss future prospects for these methods, namely mobile sensing to assess contextual information, real-time analyses and just-in-time adaptive interventions., (Copyright © 2021. Published by Elsevier Ltd.)

The ability of remote research tools to collect granular, high-frequency data on symptoms and digital biomarkers is an important strength because it circumvents many limitations of traditional clinical trials and improves the ability to capture clinically relevant data. This approach allows researchers to capture more robust baselines and derive novel phenotypes for improved precision in diagnosis and accuracy in outcomes. The process for developing these tools however is complex because data need to be collected at a frequency that is meaningful but not burdensome for the participant or patient. Furthermore, traditional techniques, which rely on fixed conditions to validate assessments, may be inappropriate for validating tools that are designed to capture data under flexible conditions. This paper discusses the process for determining whether a digital assessment is suitable for remote research and offers suggestions on how to validate these novel tools., (©Jennifer Ferrar, Gareth J Griffith, Caroline Skirrow, Nathan Cashdollar, Nick Taptiklis, James Dobson, Fiona Cree, Francesca K Cormack, Jennifer H Barnett, Marcus R Munafò. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 18.06.2021.)

Background: Although studies have examined the association between tobacco and cannabis use in adolescence with subsequent cognitive functioning, study designs are usually not able to distinguish correlation from causation., Methods: Separate patterns of tobacco and cannabis use were derived using longitudinal latent class analysis based on measures assessed on five occasions from age 13-18 in a large UK population cohort (Avon Longitudinal Study of Parents and Children). Cognitive functioning measures comprised of working memory, response inhibition, and emotion recognition assessed at 24 years of age. Mendelian randomization was used to examine the possible causal relationship between smoking initiation, lifetime cannabis use and cognitive functioning., Results: We found evidence of a relationship between tobacco and cannabis use and diminished cognitive functioning for each of the outcomes in the observational analyses. There was evidence to suggest that late-onset regular tobacco smokers (b=-0.29, 95 %CI=-0.45 to -0.13), early-onset regular tobacco smokers (b=-0.45, 95 %CI=-0.84 to -0.05), and early-onset regular cannabis users (b=-0.62, 95 %CI=-0.93 to -0.31) showed poorer working memory. Early-onset regular tobacco smokers (b = 0.18, 95 %CI = 0.07 to 0.28), and early-onset regular cannabis users (b = 0.30, 95 %CI = 0.08 to 0.52) displayed poorer ability to inhibit responses. Late-onset regular (b=-0.02, 95 %CI=-0.03 to - 0.00), and early-onset regular tobacco smokers (b=-0.04, 95 %CI=-0.08 to -0.01) showed poorer ability to recognise emotions. Mendelian randomization analyses were imprecise and did not provide additional support for the observational results., Conclusion: There was some evidence to suggest that adolescent tobacco and cannabis use were associated with deficits in working memory, response inhibition and emotion recognition. Better powered genetic studies are required to determine whether these associations are causal., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Despite evidence-based national guidelines for ADHD in the United Kingdom (UK), ADHD is under-identified, under-diagnosed, and under-treated. Many seeking help for ADHD face prejudice, long waiting lists, and patchy or unavailable services, and are turning to service-user support groups and/or private healthcare for help. Methods: A group of UK experts representing clinical and healthcare providers from public and private healthcare, academia, ADHD patient groups, educational, and occupational specialists, met to discuss shortfalls in ADHD service provision in the UK. Discussions explored causes of under-diagnosis, examined biases operating across referral, diagnosis and treatment, together with recommendations for resolving these matters. Results: Cultural and structural barriers operate at all levels of the healthcare system, resulting in a de-prioritization of ADHD. Services for ADHD are insufficient in many regions, and problems with service provision have intensified as a result of the response to the COVID-19 pandemic. Research has established a range of adverse outcomes of untreated ADHD, and associated long-term personal, social, health and economic costs are high. The consensus group called for training of professionals who come into contact with people with ADHD, increased funding, commissioning and monitoring to improve service provision, and streamlined communication between health services to support better outcomes for people with ADHD. Conclusions: Evidence-based national clinical guidelines for ADHD are not being met. People with ADHD should have access to healthcare free from discrimination, and in line with their legal rights. UK Governments and clinical and regulatory bodies must act urgently on this important public health issue., Competing Interests: SY, SCu, BZ, CJ, HR, ND, AL, WC, and PM have pecuniary affiliations with consultancy organizations and/or private practices. CS was employed by the company Cambridge Cognition. SY received honoraria for consultancy and educational talks years from Janssen, HB Pharma and/or Shire. She is author of the ADHD Child Evaluation (ACE) and ACE+ for adults. She is a consultant at the Cognitive Center of Canada, who publish R&R2 for ADHD Youths and Adults. PM received honoraria for consultancy and educational talks from Shire, Takeda, and Flynn Pharma. KvR received honoraria for educational talks from Shire/Takeda, Lilly, Janssen, Medice, and Flynn. CJ provided educational talks for Lilly and Janssen. MP received honoraria for talks and advisory board participation, and travel support for conference attendance, from Shire/Takeda & Flynn Pharma. TN-D reported travel and consultation fees paid for attendance at Transition into Adulthood ADHD (TiAA) Advisory Board Meeting hosted by Shire, October 2018. BZ reported paid lectures for Flynn Pharma. MAr received sponsorships to educational/scientific meetings and honoraria for consultancy and educational talks from Janssen, Lily, Takeda (Shire), and Flynn-pharma. SCo declares reimbursement for travel/accommodation expenses and honoraria in relation to lectures/courses delivered for the Association for Child and Adolescent Health (ACAMH), Canadian ADHD Alliance Resource (CADDRA), British Association of Psychopharmacology (BAP), and Healthcare Convention. PA/King's College London (KCL) received honoraria for consultancy to Takeda/Shire, Eli-Lilly, Medice, Novartis and Janssen, and for speaking at sponsored events for Shire, Lilly, Flynn Pharma, Medice, Novartis and Janssen. KCL was supported by funds for education and research from Shire, Medice, Flynn, Janssen, Vifor Pharma, GW Pharma, and QbTech. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Young, Asherson, Lloyd, Absoud, Arif, Colley, Cortese, Cubbin, Doyle, Morua, Ferreira-Lay, Gudjonsson, Ivens, Jarvis, Lewis, Mason, Newlove-Delgado, Pitts, Read, van Rensburg, Zoritch and Skirrow.)

Background: Emotional dysregulation (ED) is a core diagnostic symptom in borderline personality disorder (BPD) and an associated feature of attention-deficit/hyperactivity disorder (ADHD). We aimed to investigate differences in dynamical indices of ED in daily life in ADHD and BPD., Methods: We used experience sampling method (ESM) and multilevel modelling to assess momentary changes in reports of affective symptoms, and retrospective questionnaire measures of ED in a sample of 98 adult females with ADHD, BPD, comorbid ADHD+BPD and healthy controls., Results: We found marked differences between the clinical groups and healthy controls. However, the ESM assessments did not show differences in the intensity of feeling angry and irritable, and the instability of feeling sad, irritable and angry, findings paralleled by data from retrospective questionnaires. The heightened intensity in negative emotions in the clinical groups compared to controls was only partially explained by bad events at the time of reporting negative emotions, suggesting both reactive and endogenous influences on ED in both ADHD and BPD., Conclusions: This study supports the view that ED is a valuable trans-diagnostic aspect of psychopathology in both ADHD and BPD, with similar levels of intensity and instability. These findings suggest that the presence or severity of ED should not be used in clinical practice to distinguish between the two disorders.

Background and Aims: There have been few longitudinal studies of association between alcohol use and cognitive functioning in young people. We aimed to examine whether alcohol use is a causal risk factor for deficient cognitive functioning in young adults., Design: Linear regression was used to examine the relationship between longitudinal latent class patterns of binge drinking and subsequent cognitive functioning. Two-sample Mendelian randomization (MR) tested evidence for the causal relationship between alcohol use and cognitive functioning., Setting: South West England., Participants: The observational study included 3155 adolescents and their parents (fully adjusted models) from the Avon Longitudinal Study of Parents and Children (ALSPAC). Genetic instruments for alcohol use were based on almost 1 000 000 individuals from the genome-wide association studies (GWAS) and Sequencing Consortium of Alcohol and Nicotine use (GSCAN). Genome-wide association studies for cognitive outcomes were based on 2500 individuals from ALSPAC., Measurements: Binge drinking was assessed at approximately 16, 17, 18, 21 and 23 years. Cognitive functioning comprised working memory, response inhibition and emotion recognition assessed at 24 years of age. Ninety-nine independent genome-wide significant single nucleotide polymorphisms (SNPs) associated with 'number of drinks per week' were used as the genetic instrument for alcohol consumption. Potential confounders were included in the observational analyses., Findings: Four binge drinking classes were identified: 'low-risk' (41.3%), 'early-onset monthly' (19.1%), 'adult frequent' (22.5%) and 'early-onset frequent' (17.0%). The association between early-onset frequent binge drinking and cognitive functioning: working memory (b = -0.42, 95% confidence interval (CI) = -1.24 to 0.41), response inhibition (b = 31.9, 95% CI = -25.3 to 89.2), and emotion recognition (b = 0.02, 95% CI = -0.07 to 0.10) in comparison to low-risk drinkers were inconclusive as to whether a difference was present. Two-sample MR analyses similarly provided little evidence that alcohol use is associated with deficits in working memory using the inverse variance weight (b = 0.29, 95% CI = -0.42 to 0.99), response inhibition (b = -0.32, 95% CI = -1.04 to 0.39) and emotion recognition (b = 0.03, 95% CI = -0.55 to 0.61)., Conclusions: Binge drinking in adolescence and early adulthood may not be causally related to deficiencies in working memory, response inhibition or emotion recognition in youths., (© 2020 Society for the Study of Addiction.)

Background: There is evidence to suggest that the broad discrepancy in the ratio of males to females with diagnosed ADHD is due, at least in part, to lack of recognition and/or referral bias in females. Studies suggest that females with ADHD present with differences in their profile of symptoms, comorbidity and associated functioning compared with males. This consensus aims to provide a better understanding of females with ADHD in order to improve recognition and referral. Comprehensive assessment and appropriate treatment is hoped to enhance longer-term clinical outcomes and patient wellbeing for females with ADHD., Methods: The United Kingdom ADHD Partnership hosted a meeting of experts to discuss symptom presentation, triggers for referral, assessment, treatment and multi-agency liaison for females with ADHD across the lifespan., Results: A consensus was reached offering practical guidance to support medical and mental health practitioners working with females with ADHD. The potential challenges of working with this patient group were identified, as well as specific barriers that may hinder recognition. These included symptomatic differences, gender biases, comorbidities and the compensatory strategies that may mask or overshadow underlying symptoms of ADHD. Furthermore, we determined the broader needs of these patients and considered how multi-agency liaison may provide the support to meet them., Conclusions: This practical approach based upon expert consensus will inform effective identification, treatment and support of girls and women with ADHD. It is important to move away from the prevalent perspective that ADHD is a behavioural disorder and attend to the more subtle and/or internalised presentation that is common in females. It is essential to adopt a lifespan model of care to support the complex transitions experienced by females that occur in parallel to change in clinical presentation and social circumstances. Treatment with pharmacological and psychological interventions is expected to have a positive impact leading to increased productivity, decreased resource utilization and most importantly, improved long-term outcomes for girls and women.

Background: Computerized assessments are already used to derive accurate and reliable measures of cognitive function. Web-based cognitive assessment could improve the accessibility and flexibility of research and clinical assessment, widen participation, and promote research recruitment while simultaneously reducing costs. However, differences in context may influence task performance., Objective: This study aims to determine the comparability of an unsupervised, web-based administration of the Cambridge Neuropsychological Test Automated Battery (CANTAB) against a typical in-person lab-based assessment, using a within-subjects counterbalanced design. The study aims to test (1) reliability, quantifying the relationship between measurements across settings using correlational approaches; (2) equivalence, the extent to which test results in different settings produce similar overall results; and (3) agreement, by quantifying acceptable limits to bias and differences between measurement environments., Methods: A total of 51 healthy adults (32 women and 19 men; mean age 36.8, SD 15.6 years) completed 2 testing sessions, which were completed on average 1 week apart (SD 4.5 days). Assessments included equivalent tests of emotion recognition (emotion recognition task [ERT]), visual recognition (pattern recognition memory [PRM]), episodic memory (paired associate learning [PAL]), working memory and spatial planning (spatial working memory [SWM] and one touch stockings of Cambridge), and sustained attention (rapid visual information processing [RVP]). Participants were randomly allocated to one of the two groups, either assessed in-person in the laboratory first (n=33) or with unsupervised web-based assessments on their personal computing systems first (n=18). Performance indices (errors, correct trials, and response sensitivity) and median reaction times were extracted. Intraclass and bivariate correlations examined intersetting reliability, linear mixed models and Bayesian paired sample t tests tested for equivalence, and Bland-Altman plots examined agreement., Results: Intraclass correlation (ICC) coefficients ranged from ρ=0.23-0.67, with high correlations in 3 performance indices (from PAL, SWM, and RVP tasks; ρ≥0.60). High ICC values were also seen for reaction time measures from 2 tasks (PRM and ERT tasks; ρ≥0.60). However, reaction times were slower during web-based assessments, which undermined both equivalence and agreement for reaction time measures. Performance indices did not differ between assessment settings and generally showed satisfactory agreement., Conclusions: Our findings support the comparability of CANTAB performance indices (errors, correct trials, and response sensitivity) in unsupervised, web-based assessments with in-person and laboratory tests. Reaction times are not as easily translatable from in-person to web-based testing, likely due to variations in computer hardware. The results underline the importance of examining more than one index to ascertain comparability, as high correlations can present in the context of systematic differences, which are a product of differences between measurement environments. Further work is now needed to examine web-based assessments in clinical populations and in larger samples to improve sensitivity for detecting subtler differences between test settings., (©Rosa Backx, Caroline Skirrow, Pasquale Dente, Jennifer H Barnett, Francesca K Cormack. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 04.08.2020.)

Background: Cognitive symptoms are common in major depressive disorder and may help to identify patients who need treatment or who are not experiencing adequate treatment response. Digital tools providing real-time data assessing cognitive function could help support patient treatment and remediation of cognitive and mood symptoms., Objective: The aim of this study was to examine feasibility and validity of a wearable high-frequency cognitive and mood assessment app over 6 weeks, corresponding to when antidepressant pharmacotherapy begins to show efficacy., Methods: A total of 30 patients (aged 19-63 years; 19 women) with mild-to-moderate depression participated in the study. The new Cognition Kit app was delivered via the Apple Watch, providing a high-resolution touch screen display for task presentation and logging responses. Cognition was assessed by the n-back task up to 3 times daily and depressed mood by 3 short questions once daily. Adherence was defined as participants completing at least 1 assessment daily. Selected tests sensitive to depression from the Cambridge Neuropsychological Test Automated Battery and validated questionnaires of depression symptom severity were administered on 3 occasions (weeks 1, 3, and 6). Exploratory analyses examined the relationship between mood and cognitive measures acquired in low- and high-frequency assessment., Results: Adherence was excellent for mood and cognitive assessments (95% and 96%, respectively), did not deteriorate over time, and was not influenced by depression symptom severity or cognitive function at study onset. Analyses examining the relationship between high-frequency cognitive and mood assessment and validated measures showed good correspondence. Daily mood assessments correlated moderately with validated depression questionnaires (r=0.45-0.69 for total daily mood score), and daily cognitive assessments correlated moderately with validated cognitive tests sensitive to depression (r=0.37-0.50 for mean n-back)., Conclusions: This study supports the feasibility and validity of high-frequency assessment of cognition and mood using wearable devices over an extended period in patients with major depressive disorder., (©Francesca Cormack, Maggie McCue, Nick Taptiklis, Caroline Skirrow, Emilie Glazer, Elli Panagopoulos, Tempest A van Schaik, Ben Fehnert, James King, Jennifer H Barnett. Originally published in JMIR Mental Health (http://mental.jmir.org), 18.11.2019.)

Objective: Intelligence quotient (IQ) outcomes after pediatric epilepsy surgery show significant individual variation. Clinical factors such as seizure cessation or antiepileptic medication discontinuation have been implicated, but do not fully account for the heterogeneity seen. Less is known about the impact of neurobiological factors, such as brain development and resection location. This study examines clinical and neuroimaging factors associated with cognitive outcome after epilepsy surgery in childhood., Methods: Fifty-two children (28 boys, 24 girls) were evaluated for epilepsy surgery and reassessed on average 7.7 years later. In the intervening time, 13 were treated pharmacologically and 39 underwent focal surgery (17 temporal, 16 extratemporal, six multilobar; mean age at surgery = 14.0 years). Pre- and postsurgical assessments included IQ tests and T1-weighted brain images. Predictors of IQ change were investigated, including voxel-based analyses of resection location, and gray and white matter volume change., Results: Overall modest IQ improvement was seen in children treated surgically, but not in those treated pharmacologically only. Applying a ≥10-point change threshold, 39% of the surgically treated children improved, whereas 10% declined. Clinical factors associated with IQ increases were lower preoperative IQ and longer follow-up duration, whereas seizure and antiepileptic medication cessation were not predictive. Among neuroimaging factors, we observed that left anterior temporal resections impacted negatively on verbal reasoning, linked to full-scale IQ decline. In contrast, gray matter volume change in ipsi- and contralesional hemispheres was positively correlated with IQ change. Voxel-based morphometry identified the gray matter volume change in the contralesional dorsolateral frontal cortex as most strongly associated with IQ improvement., Significance: We show that a variety of factors are likely to contribute to patterns of postsurgical change in IQ. Neuroimaging results indicate that left anterior temporal resections constrain development of verbal cognition, whereas simultaneously cortical growth after surgical treatment can support improvements in IQ., (Wiley Periodicals, Inc. © 2019 International League Against Epilepsy.)

Objective: This study investigates excessive mind wandering (MW) in adult ADHD using a new scale: the Mind Excessively Wandering Scale (MEWS)., Method: Data from two studies of adult ADHD was used in assessing the psychometric properties of the MEWS. Case-control differences in MW, the association with ADHD symptoms, and the contribution to functional impairment were investigated., Results: The MEWS functioned well as a brief measure of excessive MW in adult ADHD, showing good internal consistency (α > .9), and high sensitivity (.9) and specificity (.9) for the ADHD diagnosis, comparable with that of existing ADHD symptom rating scales. Elevated levels of MW were found in adults with ADHD, which contributed to impairment independently of core ADHD symptom dimensions., Conclusion: Findings suggest excessive MW is a common co-occurring feature of adult ADHD that has specific implications for the functional impairments experienced. The MEWS has potential utility as a screening tool in clinical practice to assist diagnostic assessment.

Introduction: Normative cognitive data can help to distinguish pathological decline from normal aging. This study presents normative data from the Cambridge Neuropsychological Test Automated Battery, using linear regression and nonlinear quantile regression approaches., Methods: Heinz Nixdorf Recall study participants completed Cambridge Neuropsychological Test Automated Battery tests: paired-associate learning, spatial working memory, and reaction time. Data were available for 1349-1529 healthy adults aged 57-84 years. Linear and nonlinear quantile regression analyses examined age-related changes, adjusting for sex and education. Quantile regression differentiated seven performance bands (percentiles: 97.7, 93.3, 84.1, 50, 15.9, 6.7, and 2.3)., Results: Normative data show age-related cognitive decline across all tests, but with quantile regression revealing heterogeneous trajectories of cognitive aging, particularly for the test of episodic memory function (paired-associate learning)., Discussion: This study presents normative data from Cambridge Neuropsychological Test Automated Battery in mid-to-late life. Quantile regression can model heterogeneity in age-related cognitive trajectories as seen in the paired-associate learning episodic memory measure.

Background: Recent literature on the comparison of machine learning methods has raised questions about the neutrality, unbiasedness and utility of many comparative studies. Reporting of results on favourable datasets and sampling error in the estimated performance measures based on single samples are thought to be the major sources of bias in such comparisons. Better performance in one or a few instances does not necessarily imply so on an average or on a population level and simulation studies may be a better alternative for objectively comparing the performances of machine learning algorithms., Methods: We compare the classification performance of a number of important and widely used machine learning algorithms, namely the Random Forests (RF), Support Vector Machines (SVM), Linear Discriminant Analysis (LDA) and k-Nearest Neighbour (kNN). Using massively parallel processing on high-performance supercomputers, we compare the generalisation errors at various combinations of levels of several factors: number of features, training sample size, biological variation, experimental variation, effect size, replication and correlation between features., Results: For smaller number of correlated features, number of features not exceeding approximately half the sample size, LDA was found to be the method of choice in terms of average generalisation errors as well as stability (precision) of error estimates. SVM (with RBF kernel) outperforms LDA as well as RF and kNN by a clear margin as the feature set gets larger provided the sample size is not too small (at least 20). The performance of kNN also improves as the number of features grows and outplays that of LDA and RF unless the data variability is too high and/or effect sizes are too small. RF was found to outperform only kNN in some instances where the data are more variable and have smaller effect sizes, in which cases it also provide more stable error estimates than kNN and LDA. Applications to a number of real datasets supported the findings from the simulation study., (© The Author(s) 2013.)

The temporal lobes play a prominent role in declarative memory function, including episodic memory (memory for events) and semantic memory (memory for facts and concepts). Surgical resection for medication-resistant and well-localized temporal lobe epilepsy has good prognosis for seizure freedom, but is linked to memory difficulties in adults, especially when the removal is on the left side. Children may benefit most from surgery, because brain plasticity may facilitate post-surgical reorganization, and seizure cessation may promote cognitive development. However, the long-term impact of this intervention in children is not known. We examined memory function in 53 children (25 males, 28 females) who were evaluated for epilepsy surgery: 42 underwent unilateral temporal lobe resections (25 left, 17 right, mean age at surgery 13.8 years), 11 were treated only pharmacologically. Average follow-up was 9 years (range 5-15). Post-surgical change in visual and verbal episodic memory, and semantic memory at follow-up were examined. Pre- and post-surgical T1-weighted MRI brain scans were analysed to extract hippocampal and resection volumes, and evaluate post-surgical temporal lobe integrity. Language lateralization indices were derived from functional magnetic resonance imaging. There were no significant pre- to postoperative decrements in memory associated with surgery. In contrast, gains in verbal episodic memory were seen after right temporal lobe surgery, and visual episodic memory improved after left temporal lobe surgery, indicating a functional release in the unoperated temporal lobe after seizure reduction or cessation. Pre- to post-surgical change in memory function was not associated with any indices of brain structure derived from MRI. However, better verbal memory at follow-up was linked to greater post-surgical residual hippocampal volumes, most robustly in left surgical participants. Better semantic memory at follow-up was associated with smaller resection volumes and greater temporal pole integrity after left temporal surgery. Results were independent of post-surgical intellectual function and language lateralization. Our findings indicate post-surgical, hemisphere-dependent material-specific improvement in memory functions in the intact temporal lobe. However, outcome was linked to the anatomical integrity of the temporal lobe memory system, indicating that compensatory mechanisms are constrained by the amount of tissue which remains in the operated temporal lobe. Careful tailoring of resections for children undergoing epilepsy surgery may enhance long-term memory outcome., (© The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Attention-deficit/hyperactivity disorder (ADHD) is associated with cognitive performance and functional brain changes that are sensitive to task conditions, indicating a role for dynamic impairments rather than stable cognitive deficits. Prominent hypotheses consistent with this observation are a failure to optimise brain arousal or activation states. Here we investigate cortical activation during different conditions. Using a sample of 41 non-comorbid adults with ADHD and 48 controls, we examine quantitative EEG activity during a resting state, a cued continuous performance test with flankers (CPT-OX) and the sustained attention to response task (SART). We further investigate the effects of methylphenidate in a subsample of 21 ADHD cases. Control participants showed a task-related increase in theta activity when engaged in cognitive tasks, primarily in frontal and parietal regions, which was absent in participants with ADHD. Treatment with methylphenidate resulted in normalisation of the resting state to task activation pattern. These findings suggest that ADHD in adults is associated with insufficient allocation of neuronal resources required for normal cortical activation commensurate with task demands. Further work is required to clarify the causal role of the deficit in cortical activation and provide a clearer understanding of the mechanisms involved., (Copyright © 2014 Elsevier B.V. and ECNP. All rights reserved.)

Altered very low-frequency electroencephalographic (VLF-EEG) activity is an endophenotype of ADHD in children and adolescents. We investigated VLF-EEG case-control differences in adult samples and the effects of methylphenidate (MPH). A longitudinal case-control study was conducted examining the effects of MPH on VLF-EEG (.02-0.2Hz) during a cued continuous performance task. 41 untreated adults with ADHD and 47 controls were assessed, and 21 cases followed up after MPH treatment, with a similar follow-up for 38 controls (mean follow-up=9.4months). Cases had enhanced frontal and parietal VLF-EEG and increased omission errors. In the whole sample, increased parietal VLF-EEG correlated with increased omission errors. After controlling for subthreshold comorbid symptoms, VLF-EEG case-control differences and treatment effects remained. Post-treatment, a time by group interaction emerged; VLF-EEG and omission errors reduced to the same level as controls, with decreased inattentive symptoms in cases. Reduced VLF-EEG following MPH treatment provides preliminary evidence that changes in VLF-EEG may relate to MPH treatment effects on ADHD symptoms; and that VLF-EEG may be an intermediate phenotype of ADHD. Further studies of the treatment effect of MPH in larger controlled studies are required to formally evaluate any causal link between MPH, VLF-EEG and ADHD symptoms., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Objective: Emotional lability is recognized as an associated feature of attention-deficit/hyperactivity disorder (ADHD). However, the degree of phenotypic and etiologic overlap between emotional lability and the ADHD dimensions of hyperactivity-impulsivity and inattention remains unclear. The present study examines these associations in a large, community twin sample., Method: Structural equation models were fit to data from 1,920 child and adolescent twin pairs (age range, 5-18 years). Symptoms of hyperactivity-impulsivity (HI) and inattention (IA) were assessed using a modified version of the DuPaul rating scale, completed by parents. Symptoms of emotional lability (EL) were assessed using the parent-rated Conners 10-item scale., Results: There were moderate to strong phenotypic correlations between HI, IA, and EL. Multivariate twin modeling revealed that a common pathway model best accounted for the covariance among these dimensions, represented by a highly heritable latent factor. Ad hoc analyses confirmed that all additive genetic influences on HI, IA, and EL were shared, and identified a significantly stronger association of EL with the latent ADHD factor in older than in younger individuals., Conclusions: Emotional lability was phenotypically and genetically associated with hyperactivity-impulsivity and inattention in children and adolescents. The finding that a single, heritable, latent factor accounted for covariation among these phenotypes indicates that their co-occurrence is primarily the result of overlapping genetic effects. These data support the hypothesis that emotional lability is etiologically relevant to the core ADHD phenotype, and that it should be targeted in assessment and treatment in clinical practice., (Copyright © 2014 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Adults with attention-deficit hyperactivity disorder (ADHD) frequently report emotional lability (EL). However, it is not known whether EL may be accounted for by comorbid psychiatric conditions or symptoms. This study evaluates the influence of comorbid clinical symptoms on EL, and investigates the relationship between EL and impairment., Methods: Over 500 consecutive male adult referrals at the ADHD Clinic for adults at the South London and Maudsley Hospital (U.K) were screened. 41 individuals with ADHD without comorbidity, current medication or frequent substance were identified, and compared with 47 matched healthy male control participants. Measures included IQ, clinical interview and self-reported ADHD symptoms, EL, impairment and antisocial behaviour., Results: ADHD participants reported elevated EL, showing good case-control differentiation in receiver operating curve analysis. EL was most strongly predicted by hyperactivity-impulsivity rather than subsyndromal comorbid symptoms, and contributed independently to impairment in daily life., Limitations: Results may not generalise to children with ADHD, or many adults with ADHD, who are frequently affected by comorbid psychiatric conditions and substance use disorders., Conclusions: EL in adults with ADHD appears to be primarily associated with ADHD itself rather than comorbid conditions, and helps to explain some of the impairments not accounted for by classical features of the disorder. Results indicate that adults presenting with long-term problems with EL should routinely be screened for the presence of ADHD., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Diagnostic formulations for attention deficit hyperactivity disorder (ADHD) and bipolar disorder (BD) both include symptoms of distractibility, psychomotor agitation and talkativeness, alongside associated emotional features (irritability and emotional lability). Treatment studies suggest the importance of accurate delineation of ADHD and BD. However, boundaries between the two disorders are blurred by the introduction of broader conceptualisations of BD. This review attempts to elucidate whether associations between ADHD and BD are likely to be driven by superficial symptomatological similarities or by a more meaningful etiological relationship between the disorders. This is achieved by outlining findings on comorbidity, temporal progression of the disorders, familial co-variation, and neurobiology in ADHD and BD across the lifespan. Longitudinal studies fail to consistently show developmental trajectories between ADHD and BD. Comparative research investigating neurobiology is in its infancy, and although some similarities are seen between ADHD and BD, studies also emphasise differences between the two disorders. However, comorbidity and family studies appear to show that the two disorders occur together and aggregate in families at higher than expected rates. Furthermore close inspection of results from population studies reveals heightened co-occurrence of ADHD and BD even in the context of high comorbidity commonly noted in psychopathology. These results point towards a meaningful association between ADHD and BD, going beyond symptomatic similarities. However, future research needs to account for heterogeneity of BD, making clear distinctions between classical episodic forms of BD, and broader conceptualisations of the disorder characterised by irritability and emotional lability, when evaluating the relationship with ADHD., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Attention-deficit/hyperactivity disorder (ADHD) is a common and debilitating psychiatric disorder characterized by symptoms of inattention, impulsivity and motor restlessness. Consistently noted alongside these symptoms is mood instability in the form of irritability, volatility, swift changes in mood, hot temper and low frustration tolerance. The current diagnostic classification systems do not include mood instability as a core aspect of ADHD, but rather as an associated feature of the disorder. However, the literature suggests that overlapping cognitive deficits and neuroanatomical substrates may underlie both the classical ADHD symptoms and mood instability. Furthermore, common neurotherapeutic interventions in the form of stimulant medications or atomoxetine may help to alleviate both types of symptoms when they co-occur. This research suggests that mood instability and symptoms of ADHD may be interlinked and that mood instability may be better understood as a core feature of the ADHD syndrome.