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Andrikopoulos D, Vassiliou G, Fatouros P, Tsirmpas C, Pehlivanidis A, Papageorgiou C. Machine learning-enabled detection of attention-deficit/hyperactivity disorder with multimodal physiological data: a case-control study. BMC Psychiatry 2024; 24:547. [PMID: 39103819 DOI: 10.1186/s12888-024-05987-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 07/25/2024] [Indexed: 08/07/2024] Open
Abstract
BACKGROUND Attention-Deficit/Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental psychiatric condition that typically emerges during childhood but often persists into adulthood, significantly impacting individuals' functioning, relationships, productivity, and overall quality of life. However, the current diagnostic process exhibits limitations that can significantly affect its overall effectiveness. Notably, its face-to-face and time-consuming nature, coupled with the reliance on subjective recall of historical information and clinician subjectivity, stand out as key challenges. To address these limitations, objective measures such as neuropsychological evaluations, imaging techniques and physiological monitoring of the Autonomic Nervous System functioning, have been explored. METHODS The main aim of this study was to investigate whether physiological data (i.e., Electrodermal Activity, Heart Rate Variability, and Skin Temperature) can serve as meaningful indicators of ADHD, evaluating its utility in distinguishing adult ADHD patients. This observational, case-control study included a total of 76 adult participants (32 ADHD patients and 44 healthy controls) who underwent a series of Stroop tests, while their physiological data was passively collected using a multi-sensor wearable device. Univariate feature analysis was employed to identify the tests that triggered significant signal responses, while the Informative k-Nearest Neighbors (KNN) algorithm was used to filter out less informative data points. Finally, a machine-learning decision pipeline incorporating various classification algorithms, including Logistic Regression, KNN, Random Forests, and Support Vector Machines (SVM), was utilized for ADHD patient detection. RESULTS Results indicate that the SVM-based model yielded the optimal performance, achieving 81.6% accuracy, maintaining a balance between the experimental and control groups, with sensitivity and specificity of 81.4% and 81.9%, respectively. Additionally, integration of data from all physiological signals yielded the best results, suggesting that each modality captures unique aspects of ADHD. CONCLUSIONS This study underscores the potential of physiological signals as valuable diagnostic indicators of adult ADHD. For the first time, to the best of our knowledge, our findings demonstrate that multimodal physiological data collected via wearable devices can complement traditional diagnostic approaches. Further research is warranted to explore the clinical applications and long-term implications of utilizing physiological markers in ADHD diagnosis and management.
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Affiliation(s)
| | - Georgia Vassiliou
- First Department of Psychiatry, Eginition Hospital, Medical School National and Kapodistrian University of Athens, Athens, Greece
| | | | | | - Artemios Pehlivanidis
- First Department of Psychiatry, Eginition Hospital, Medical School National and Kapodistrian University of Athens, Athens, Greece
| | - Charalabos Papageorgiou
- First Department of Psychiatry, Eginition Hospital, Medical School National and Kapodistrian University of Athens, Athens, Greece
- Neurosciences and Precision Medicine Research Institute "Costas Stefanis", University Mental Health, Athens, Greece
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Kochhar P, Arora I, Bellato A, Ropar D, Hollis C, Groom M(MJ. A comparison of visual attention to pictures in the Autism Diagnostic Observation Schedule in children and adolescents with ADHD and/or autism. Front Psychiatry 2024; 15:1378593. [PMID: 38742132 PMCID: PMC11089217 DOI: 10.3389/fpsyt.2024.1378593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 04/08/2024] [Indexed: 05/16/2024] Open
Abstract
Background Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) are neurodevelopmental conditions which frequently co-occur. The Autism Diagnostic Observation Schedule (ADOS) is commonly used to aid with diagnostic assessment of ASD but was not originally designed for use in those with comorbid ADHD. Visual attention to social stimuli has been often studied in ASD using eye-tracking, to obtain quantitative indices of how attention is deployed to different parts of a social image/scene. As the ADOS includes tasks that rely on attending to and processing images of social scenes, these measures of visual attention could provide useful additional objective measurement alongside ADOS scores to enhance the characterisation of autistic symptoms in those with ADHD. Methods Children with ASD, comorbid ASD and ADHD, ADHD and Neurotypical (NT) controls were recruited (n=84). Visual attention was measured using eye-tracking during free viewing of social scenes selected from the ADOS. The full ADOS was then administered. Stimulant medication was temporarily withdrawn during this assessment. Research diagnoses were based on the Development and Wellbeing Assessment (DAWBA), ADOS, Social Communication Questionnaire (SCQ, a measure of ASD severity) and Conners' Rating Scales (CRS-3, a measure of ADHD severity) following clinical consensus. Results Using factorial ANOVAs to model ADHD, Autism and their interaction, we found that fixation duration to faces was reduced in those with ASD (ASD and ASD+ADHD) compared to those without ASD (ADHD and NT). Reduced visual attention to faces in the whole sample was associated with Autism symptom severity (SCQ subscale scores) but not ADHD symptom severity (CRS-3 scores). Discussion Our findings provide preliminary evidence in support of implementing visual attention measurement during assessment of ASD in the context of comorbidity with ADHD. For example, if a child with ADHD was found to reduce attention to faces in ADOS pictures this may suggest additive difficulties on the autism spectrum. Replication across a larger sample would be informative. This work has future potential in the clinic to help with complex cases, including those with co-occurring ADHD and ASD.
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Affiliation(s)
- Puja Kochhar
- Neurodevelopmental Specialist Service, Nottinghamshire Healthcare National Health Service (NHS) Foundation Trust, Nottingham, United Kingdom
- Institute of Mental Health, University of Nottingham, Nottingham, United Kingdom
| | - Iti Arora
- Institute of Mental Health, University of Nottingham, Nottingham, United Kingdom
- Division of Psychology and Language Sciences, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Alessio Bellato
- Institute of Mental Health, University of Nottingham, Nottingham, United Kingdom
- School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, United Kingdom
| | - Danielle Ropar
- School of Psychology, University of Nottingham, Nottingham, United Kingdom
| | - Chris Hollis
- Institute of Mental Health, University of Nottingham, Nottingham, United Kingdom
- National Institute for Health and Care Research (NIHR) MindTech Medtech Co-operative, Institute of Mental Health, UK NIHR, Nottingham, United Kingdom
- Nottingham Biomedical Research Centre, Institute of Mental Health, Nottingham, United Kingdom
| | - Madeleine (Maddie) J. Groom
- Institute of Mental Health, University of Nottingham, Nottingham, United Kingdom
- National Institute for Health and Care Research (NIHR) MindTech Medtech Co-operative, Institute of Mental Health, UK NIHR, Nottingham, United Kingdom
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Bellato A, Arora I, Kochhar P, Ropar D, Hollis C, Groom MJ. Relationship between autonomic arousal and attention orienting in children and adolescents with ADHD, autism and co-occurring ADHD and autism. Cortex 2023; 166:306-321. [PMID: 37459680 DOI: 10.1016/j.cortex.2023.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 05/22/2023] [Accepted: 06/08/2023] [Indexed: 08/29/2023]
Abstract
INTRODUCTION Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) may be characterized by different profiles of visual attention orienting. However, there are also many inconsistent findings emerging from the literature, probably due to the fact that the potential effect of autonomic arousal (which has been proposed to be dysregulated in these conditions) on oculomotor performance has not been investigated before. Moreover, it is not known how visual attention orienting is affected by the co-occurrence of ADHD and autism in people with a double diagnosis. METHODS 99 children/adolescents with or without ADHD and/or autism (age 10.79 ± 2.05 years, 65% boys) completed an adapted version of the gap-overlap task (with baseline and overlap trials only). The social salience and modality of stimuli were manipulated between trials. Eye movements and pupil size were recorded. We compared saccadic reaction times (SRTs) between diagnostic groups and investigated if a trial-by-trial association existed between pre-saccadic pupil size and SRTs. RESULTS Faster orienting (shorter SRT) was found for baseline compared to overlap trials, faces compared to non-face stimuli and-more evidently in children without ADHD and/or autism-for multi-modal compared to uni-modal stimuli. We also found a linear negative association between pre-saccadic pupil size and SRTs, in autistic participants (without ADHD), and a quadratic association in children with ADHD (without autism), for which SRTs were slower when intra-individual pre-saccadic pupil size was smallest or largest. CONCLUSION Our findings are in line with previous literature and indicate a possible effect of dysregulated autonomic arousal on oculomotor mechanisms in autism and ADHD, which should be further investigated in future research studies with larger samples, to reliably investigate possible differences between children with single and dual diagnoses.
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Affiliation(s)
- Alessio Bellato
- School of Psychology, University of Nottingham, Malaysia; Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK.
| | - Iti Arora
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK
| | - Puja Kochhar
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK; Neurodevelopmental Specialist Service (NeSS), Nottinghamshire Healthcare NHS Foundation Trust, Highbury Hospital, Highbury Road, Nottingham, NG6 9DR, UK
| | - Danielle Ropar
- School of Psychology, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Chris Hollis
- Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK; NIHR MindTech Medtech Co-operative, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK NIHR; Nottingham Biomedical Research Centre, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK
| | - Madeleine J Groom
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK; Nottingham Biomedical Research Centre, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK
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van Ruitenbeek P, Franzen L, Mason NL, Stiers P, Ramaekers JG. Methylphenidate as a treatment option for substance use disorder: a transdiagnostic perspective. Front Psychiatry 2023; 14:1208120. [PMID: 37599874 PMCID: PMC10435872 DOI: 10.3389/fpsyt.2023.1208120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 07/14/2023] [Indexed: 08/22/2023] Open
Abstract
A transition in viewing mental disorders from conditions defined as a set of unique characteristics to one of the quantitative variations on a collection of dimensions allows overlap between disorders. The overlap can be utilized to extend to treatment approaches. Here, we consider the overlap between attention-deficit/hyperactivity disorder and substance use disorder to probe the suitability to use methylphenidate as a treatment for substance use disorder. Both disorders are characterized by maladaptive goal-directed behavior, impaired cognitive control, hyperactive phasic dopaminergic neurotransmission in the striatum, prefrontal hypoactivation, and reduced frontal cortex gray matter volume/density. In addition, methylphenidate has been shown to improve cognitive control and normalize associated brain activation in substance use disorder patients and clinical trials have found methylphenidate to improve clinical outcomes. Despite the theoretical basis and promising, but preliminary, outcomes, many questions remain unanswered. Most prominent is whether all patients who are addicted to different substances may equally profit from methylphenidate treatment.
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Affiliation(s)
- Peter van Ruitenbeek
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
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Abstract
Attention-Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental condition associated with impaired function and increased risk of poor outcomes in children, young people and adults with the condition. Currently approved pharmacological treatments for ADHD include a range of stimulant (methylphenidate, amphetamine) and nonstimulant (atomoxetine, guanfacine, clonidine) medications. All have been shown to be effective in treating the symptoms of ADHD and improving other functional outcomes including quality of life, academic performance, rates of accidents and injuries, and do not appear to be associated with significant adverse outcomes or side effects. In this chapter, we review medications for ADHD by summarising the mechanisms of action of each of the two main classes of compounds (stimulants and nonstimulants), the formulations of the most commonly prescribed medications within each class, their efficacy in treating ADHD symptoms and other outcomes, and other factors that influence treatment decisions including side effects and tolerability, comorbidities and medical history. We conclude with a summary of the treatment decisions made by clinicians and suggest some next steps for research. Further research is needed to understand the mechanisms of action of these medications and how exactly they improve symptoms, and to examine their effects on commonly occurring comorbidities.
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Affiliation(s)
- Madeleine J Groom
- Academic Unit of Mental Health and Clinical Neurosciences, School of Medicine, Institute of Mental Health, University of Nottingham, Nottingham, UK.
| | - Samuele Cortese
- Faculty of Environmental and Life Sciences, Center for Innovation in Mental Health, School of Psychology, University of Southampton, Southampton, UK
- Clinical and Experimental Sciences (CNS and Psychiatry), Faculty of Medicine, University of Southampton, Southampton, UK
- Solent NHS Trust, Southampton, UK
- Hassenfeld Children's Hospital at NYU Langone, New York University Child Study Center, New York, NY, USA
- Centre for ADHD and Neurodevelopmental Disorders Across the Lifespan, Institute of Mental Health, University of Nottingham, Nottingham, UK
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Bellato A, Arora I, Kochhar P, Ropar D, Hollis C, Groom MJ. Heart Rate Variability in Children and Adolescents with Autism, ADHD and Co-occurring Autism and ADHD, During Passive and Active Experimental Conditions. J Autism Dev Disord 2021; 52:4679-4691. [PMID: 34716841 PMCID: PMC9556357 DOI: 10.1007/s10803-021-05244-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/13/2021] [Indexed: 12/22/2022]
Abstract
Despite overlaps in clinical symptomatology, autism and ADHD may be associated with opposite autonomic arousal profiles which might partly explain altered cognitive and global functioning. We investigated autonomic arousal in 106 children/adolescents with autism, ADHD, co-occurring autism/ADHD, and neurotypical controls. Heart rate variability was recorded during resting-state, a 'passive' auditory oddball task and an 'active' response conflict task. Autistic children showed hyper-arousal during the active task, while those with ADHD showed hypo-arousal during resting-state and the passive task. Irrespective of diagnosis, children characterised by hyper-arousal showed more severe autistic symptomatology, increased anxiety and reduced global functioning than those displaying hypo-arousal, suggesting the importance of considering individual autonomic arousal profiles for differential diagnosis of autism/ADHD and when developing personalised interventions.
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Affiliation(s)
- Alessio Bellato
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK
| | - Iti Arora
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK
| | - Puja Kochhar
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK.,Child and Adolescent Mental Health Services (CAMHS), Derbyshire Healthcare NHS Foundation Trust, Temple House, Mill Hill Lane, Derby, DE23 6SA, UK
| | - Danielle Ropar
- School of Psychology, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Chris Hollis
- Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK.,NIHR MindTech Medtech Co-operative, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK.,NIHR Nottingham Biomedical Research Centre, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK
| | - Madeleine J Groom
- Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK. .,NIHR Nottingham Biomedical Research Centre, Institute of Mental Health, Innovation Park, Triumph Road, Nottingham, NG7 2TU, UK.
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Bellato A, Norman L, Idrees I, Ogawa CY, Waitt A, Zuccolo PF, Tye C, Radua J, Groom MJ, Shephard E. A systematic review and meta-analysis of altered electrophysiological markers of performance monitoring in Obsessive-Compulsive Disorder (OCD), Gilles de la Tourette Syndrome (GTS), Attention-Deficit/Hyperactivity disorder (ADHD) and Autism. Neurosci Biobehav Rev 2021; 131:964-987. [PMID: 34687698 DOI: 10.1016/j.neubiorev.2021.10.018] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 10/14/2021] [Accepted: 10/15/2021] [Indexed: 12/15/2022]
Abstract
Altered performance monitoring is implicated in obsessive-compulsive disorder (OCD), Gilles de la Tourette syndrome (GTS), attention-deficit/hyperactivity disorder (ADHD) and autism. We conducted a systematic review and meta-analysis of electrophysiological correlates of performance monitoring (error-related negativity, ERN; error positivity, Pe; feedback-related negativity, FRN; feedback-P3) in individuals with OCD, GTS, ADHD or autism compared to control participants, or associations between correlates and symptoms/traits of these conditions. Meta-analyses on 97 studies (5890 participants) showed increased ERN in OCD (Hedge's g = 0.54[CIs:0.44,0.65]) and GTS (g = 0.99[CIs:0.05,1.93]). OCD also showed increased Pe (g = 0.51[CIs:0.21,0.81]) and FRN (g = 0.50[CIs:0.26,0.73]). ADHD and autism showed reduced ERN (ADHD: g=-0.47[CIs:-0.67,-0.26]; autism: g=-0.61[CIs:-1.10,-0.13]). ADHD also showed reduced Pe (g=-0.50[CIs:-0.69,-0.32]). These findings suggest overlap in electrophysiological markers of performance monitoring alterations in four common neurodevelopmental conditions, with increased amplitudes of the markers in OCD and GTS and decreased amplitudes in ADHD and autism. Implications of these findings in terms of shared and distinct performance monitoring alterations across these neurodevelopmental conditions are discussed. PROSPERO pre-registration code: CRD42019134612.
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Affiliation(s)
- Alessio Bellato
- Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK; Academic Unit of Mental Health & Clinical Neurosciences, School of Medicine, Institute of Mental Health, University of Nottingham, Nottingham, UK
| | - Luke Norman
- Section on Neurobehavioral and Clinical Research, Social and Behavioral Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Iman Idrees
- Academic Unit of Mental Health & Clinical Neurosciences, School of Medicine, Institute of Mental Health, University of Nottingham, Nottingham, UK
| | - Carolina Y Ogawa
- Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil
| | - Alice Waitt
- Academic Unit of Mental Health & Clinical Neurosciences, School of Medicine, Institute of Mental Health, University of Nottingham, Nottingham, UK
| | - Pedro F Zuccolo
- Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil
| | - Charlotte Tye
- Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK
| | - Joaquim Radua
- Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK; Imaging of Mood- and Anxiety-Related Disorders (IMARD) Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERSAM, Barcelona, Spain; Department of Clinical Neuroscience, Centre for Psychiatric Research and Education, Karolinska Institutet, Stockholm, Sweden
| | - Madeleine J Groom
- Academic Unit of Mental Health & Clinical Neurosciences, School of Medicine, Institute of Mental Health, University of Nottingham, Nottingham, UK
| | - Elizabeth Shephard
- Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK; Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, Brazil.
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Haigh SM, Walford TP, Brosseau P. Heart Rate Variability in Schizophrenia and Autism. Front Psychiatry 2021; 12:760396. [PMID: 34899423 PMCID: PMC8656307 DOI: 10.3389/fpsyt.2021.760396] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 11/01/2021] [Indexed: 11/23/2022] Open
Abstract
Suppressed heart rate variability (HRV) has been found in a number of psychiatric conditions, including schizophrenia and autism. HRV is a potential biomarker of altered autonomic functioning that can predict future physiological and cognitive health. Understanding the HRV profiles that are unique to each condition will assist in generating predictive models of health. In the current study, we directly compared 12 adults with schizophrenia, 25 adults with autism, and 27 neurotypical controls on their HRV profiles. HRV was measured using an electrocardiogram (ECG) channel as part of a larger electroencephalography (EEG) study. All participants also completed the UCLA Loneliness Questionnaire as a measure of social stress. We found that the adults with schizophrenia exhibited reduced variability in R-R peaks and lower low frequency power in the ECG trace compared to controls. The HRV in adults with autism was slightly suppressed compared to controls but not significantly so. Interestingly, the autism group reported feeling lonelier than the schizophrenia group, and HRV did not correlate with feelings of loneliness for any of the three groups. However, suppressed HRV was related to worse performance on neuropsychological tests of cognition in the schizophrenia group. Together, this suggests that autonomic functioning is more abnormal in schizophrenia than in autism and could be reflecting health factors that are unique to schizophrenia.
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Affiliation(s)
- Sarah M Haigh
- Department of Psychology and Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA, United States.,Department of Psychology and Center for Integrative Neuroscience, University of Nevada, Reno, Reno, NV, United States
| | - Tabatha P Walford
- Department of Psychology and Center for Integrative Neuroscience, University of Nevada, Reno, Reno, NV, United States
| | - Pat Brosseau
- Department of Psychology and Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA, United States
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