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Forbes EJ, Tiego J, Langmead J, Unruh KE, Mosconi MW, Finlay A, Kallady K, Maclachlan L, Moses M, Cappel K, Knott R, Chau T, Sindhu VPM, Bellato A, Groom MJ, Kerestes R, Bellgrove MA, Johnson BP. Oculomotor Function in Children and Adolescents with Autism, ADHD or Co-occurring Autism and ADHD. J Autism Dev Disord 2025:10.1007/s10803-024-06718-3. [PMID: 39856431 DOI: 10.1007/s10803-024-06718-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/29/2024] [Indexed: 01/27/2025]
Abstract
Oculomotor characteristics, including accuracy, timing, and sensorimotor processing, are considered sensitive intermediate phenotypes for understanding the etiology of neurodevelopmental conditions, such as autism and ADHD. Oculomotor characteristics have predominantly been studied separately in autism and ADHD. Despite the high rates of co-occurrence between these conditions, only one study has investigated oculomotor processes among those with co-occurring autism + ADHD. Four hundred and five (n = 405; 226 males) Australian children and adolescents aged 4 to 18 years (M = 9.64 years; SD = 3.20 years) with ADHD (n = 64), autism (n = 66), autism + ADHD (n = 146), or neurotypical individuals (n = 129) were compared across four different oculomotor tasks: visually guided saccade, anti-saccade, sinusoidal pursuit and step-ramp pursuit. Confirmatory analyses were conducted using separate datasets acquired from the University of Nottingham UK (n = 17 autism, n = 22 ADHD, n = 32 autism + ADHD, n = 30 neurotypical) and University of Kansas USA (n = 29 autism, n = 41 neurotypical). Linear mixed effect models controlling for sex, age and family revealed that children and adolescents with autism + ADHD exhibited increased variability in the accuracy of the final saccadic eye position compared to neurotypical children and adolescents. Autistic children and adolescents demonstrated a greater number of catch-up saccades during step-ramp pursuit compared to neurotypical children and adolescents. These findings suggest that select differences in saccadic precision are unique to autistic individuals with co-occurring ADHD, indicating that measuring basic sensorimotor processes may be useful for parsing neurodevelopment and clinical heterogeneity in autism.
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Affiliation(s)
- Elana J Forbes
- School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia.
| | - Jeggan Tiego
- School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia
| | - Joshua Langmead
- School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia
| | - Kathryn E Unruh
- Life Span Institute and Kansas Center for Autism Research and Training, The University of Kansas, 12610 Quivira Rd #270, Overland Park, KS, 66213, USA
| | - Matthew W Mosconi
- Life Span Institute and Kansas Center for Autism Research and Training, The University of Kansas, 12610 Quivira Rd #270, Overland Park, KS, 66213, USA
| | - Amy Finlay
- School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia
| | - Kathryn Kallady
- School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia
| | - Lydia Maclachlan
- School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia
| | - Mia Moses
- School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia
| | - Kai Cappel
- School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia
| | - Rachael Knott
- School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia
| | - Tracey Chau
- School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia
| | | | - Alessio Bellato
- School of Psychology, University of Southampton, Southampton, SO17 1PS, UK
- Centre for Innovation in Mental Health, University of Southampton, Southampton, UK
- Institute for Life Sciences, University of Southampton, Southampton, UK
- School of Psychology, University of Nottingham, Semenyih, Malaysia
- Mind and Neurodevelopment Research Group, University of Nottingham, Semenyih, Malaysia
| | - Madeleine J Groom
- School of Medicine, Academic Unit of Mental Health & Clinical Neurosciences, Institute of Mental Health, University of Nottingham, Triumph Road, Nottingham, NG7 2TU, UK
| | - Rebecca Kerestes
- School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia
| | - Mark A Bellgrove
- School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia
| | - Beth P Johnson
- School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia
- Department of Pediatrics, Monash University, Monash Children's Hospital, Level 5, 246 Clayton Rd, Melbourne, VIC, 3168, Australia
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Constable PA, Pinzon-Arenas JO, Mercado Diaz LR, Lee IO, Marmolejo-Ramos F, Loh L, Zhdanov A, Kulyabin M, Brabec M, Skuse DH, Thompson DA, Posada-Quintero H. Spectral Analysis of Light-Adapted Electroretinograms in Neurodevelopmental Disorders: Classification with Machine Learning. Bioengineering (Basel) 2024; 12:15. [PMID: 39851292 PMCID: PMC11761560 DOI: 10.3390/bioengineering12010015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2024] [Revised: 12/26/2024] [Accepted: 12/27/2024] [Indexed: 01/26/2025] Open
Abstract
Electroretinograms (ERGs) show differences between typically developing populations and those with a diagnosis of autism spectrum disorder (ASD) or attention deficit/hyperactivity disorder (ADHD). In a series of ERGs collected in ASD (n = 77), ADHD (n = 43), ASD + ADHD (n = 21), and control (n = 137) groups, this analysis explores the use of machine learning and feature selection techniques to improve the classification between these clinically defined groups. Standard time domain and signal analysis features were evaluated in different machine learning models. For ASD classification, a balanced accuracy (BA) of 0.87 was achieved for male participants. For ADHD, a BA of 0.84 was achieved for female participants. When a three-group model (ASD, ADHD, and control) the BA was lower, at 0.70, and fell further to 0.53 when all groups were included (ASD, ADHD, ASD + ADHD, and control). The findings support a role for the ERG in establishing a broad two-group classification of ASD or ADHD, but the model's performance depends upon sex and is limited when multiple classes are included in machine learning modeling.
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Affiliation(s)
- Paul A. Constable
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide 5000, SA, Australia;
| | - Javier O. Pinzon-Arenas
- Biomedical Engineering Department, University of Connecticut, Storrs, CT 06269, USA; (J.O.P.-A.); (L.R.M.D.); (H.P.-Q.)
| | - Luis Roberto Mercado Diaz
- Biomedical Engineering Department, University of Connecticut, Storrs, CT 06269, USA; (J.O.P.-A.); (L.R.M.D.); (H.P.-Q.)
| | - Irene O. Lee
- Behavioural and Brain Sciences Unit, Population Policy and Practice Programme, UCL Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK; (I.O.L.); (D.H.S.)
| | | | - Lynne Loh
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide 5000, SA, Australia;
| | - Aleksei Zhdanov
- “VisioMed.AI”, Golovinskoe Highway, 8/2A, 125212 Moscow, Russia;
| | - Mikhail Kulyabin
- Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany;
| | - Marek Brabec
- Institute of Computer Science of the Czech Academy of Sciences, Pod Vodarenskou Vezi 2, 182 00 Prague, Czech Republic;
- National Institute of Public Health, Srobarova 48, 100 00 Prague, Czech Republic
| | - David H. Skuse
- Behavioural and Brain Sciences Unit, Population Policy and Practice Programme, UCL Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK; (I.O.L.); (D.H.S.)
| | - Dorothy A. Thompson
- The Tony Kriss Visual Electrophysiology Unit, Clinical and Academic Department of Ophthalmology, Great Ormond Street Hospital for Children NHS Trust, London WC1N 3BH, UK;
- UCL Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
| | - Hugo Posada-Quintero
- Biomedical Engineering Department, University of Connecticut, Storrs, CT 06269, USA; (J.O.P.-A.); (L.R.M.D.); (H.P.-Q.)
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Xu G, Geng G, Wang A, Li Z, Liu Z, Liu Y, Hu J, Wang W, Li X. Three autism subtypes based on single-subject gray matter network revealed by semi-supervised machine learning. Autism Res 2024; 17:1962-1973. [PMID: 38925611 DOI: 10.1002/aur.3183] [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: 12/28/2023] [Accepted: 06/12/2024] [Indexed: 06/28/2024]
Abstract
Autism spectrum disorder (ASD) is a heterogeneous, early-onset neurodevelopmental condition characterized by persistent impairments in social interaction and communication. This study aims to delineate ASD subtypes based on individual gray matter brain networks and provide new insights from a graph theory perspective. In this study, we extracted and normalized single-subject gray matter networks and calculated each network's topological properties. The heterogeneity through discriminative analysis (HYDRA) method was utilized to subtype all patients based on network properties. Next, we explored the differences among ASD subtypes in terms of network properties and clinical measures. Our investigation identified three distinct ASD subtypes. In the case-control study, these subtypes exhibited significant differences, particularly in the precentral gyrus, lingual gyrus, and middle frontal gyrus. In the case analysis, significant differences in global and nodal properties were observed between any two subtypes. Clinically, subtype 1 showed lower VIQ and PIQ compared to subtype 3, but exhibited higher scores in ADOS-Communication and ADOS-Total compared to subtype 2. The results highlight the distinct brain network properties and behaviors among different subtypes of male patients with ASD, providing valuable insights into the neural mechanisms underlying ASD heterogeneity.
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Affiliation(s)
- Guomei Xu
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Guohong Geng
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Ankang Wang
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
- Department of Neurology, Southwest Hospital, Army Medical University, Chongqing, China
| | - Zhangyong Li
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Zhichao Liu
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Yanping Liu
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Jun Hu
- Department of Neurology, Southwest Hospital, Army Medical University, Chongqing, China
| | - Wei Wang
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
| | - Xinwei Li
- Chongqing Engineering Research Center of Medical Electronics and Information Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
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Michelini G, Carlisi CO, Eaton NR, Elison JT, Haltigan JD, Kotov R, Krueger RF, Latzman RD, Li JJ, Levin-Aspenson HF, Salum GA, South SC, Stanton K, Waldman ID, Wilson S. Where do neurodevelopmental conditions fit in transdiagnostic psychiatric frameworks? Incorporating a new neurodevelopmental spectrum. World Psychiatry 2024; 23:333-357. [PMID: 39279404 PMCID: PMC11403200 DOI: 10.1002/wps.21225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/18/2024] Open
Abstract
Features of autism spectrum disorder, attention-deficit/hyperactivity disorder, learning disorders, intellectual disabilities, and communication and motor disorders usually emerge early in life and are associated with atypical neurodevelopment. These "neurodevelopmental conditions" are grouped together in the DSM-5 and ICD-11 to reflect their shared characteristics. Yet, reliance on categorical diagnoses poses significant challenges in both research and clinical settings (e.g., high co-occurrence, arbitrary diagnostic boundaries, high within-disorder heterogeneity). Taking a transdiagnostic dimensional approach provides a useful alternative for addressing these limitations, accounting for shared underpinnings across neurodevelopmental conditions, and characterizing their common co-occurrence and developmental continuity with other psychiatric conditions. Neurodevelopmental features have not been adequately considered in transdiagnostic psychiatric frameworks, although this would have fundamental implications for research and clinical practices. Growing evidence from studies on the structure of neurodevelopmental and other psychiatric conditions indicates that features of neurodevelopmental conditions cluster together, delineating a "neurodevelopmental spectrum" ranging from normative to impairing profiles. Studies on shared genetic underpinnings, overlapping cognitive and neural profiles, and similar developmental course and efficacy of support/treatment strategies indicate the validity of this neurodevelopmental spectrum. Further, characterizing this spectrum alongside other psychiatric dimensions has clinical utility, as it provides a fuller view of an individual's needs and strengths, and greater prognostic utility than diagnostic categories. Based on this compelling body of evidence, we argue that incorporating a new neurodevelopmental spectrum into transdiagnostic frameworks has considerable potential for transforming our understanding, classification, assessment, and clinical practices around neurodevelopmental and other psychiatric conditions.
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Affiliation(s)
- Giorgia Michelini
- Department of Biological and Experimental Psychology, School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, USA
| | - Christina O Carlisi
- Division of Psychology and Language Sciences, University College London, London, UK
| | - Nicholas R Eaton
- Department of Psychology, Stony Brook University, Stony Brook, NY, USA
| | - Jed T Elison
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | - John D Haltigan
- Department of Psychiatry, Division of Child and Youth Mental Health, University of Toronto, Toronto, ON, Canada
| | - Roman Kotov
- Department of Psychiatry, Stony Brook University, Stony Brook, NY, USA
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | | | - James J Li
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Giovanni A Salum
- Child Mind Institute, New York, NY, USA
- Universidade Federal do Rio Grande do Sul, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
- Instituto Nacional de Psiquiatria do Desenvolvimento para a Infância e Adolescência, São Paulo, Brazil
| | - Susan C South
- Department of Psychological Sciences, College of Health and Human Sciences, Purdue University, West Lafayette, IN, USA
| | - Kasey Stanton
- Department of Psychology, University of Wyoming, Laramie, WY, USA
| | - Irwin D Waldman
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Sylia Wilson
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
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Ciolino A, Ferreira ML, Loyacono N. Groups and Subgroups in Autism Spectrum Disorder (ASD) Considering an Advanced Integrative Model (AIM). J Pers Med 2024; 14:1031. [PMID: 39452538 PMCID: PMC11508306 DOI: 10.3390/jpm14101031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Revised: 09/09/2024] [Accepted: 09/23/2024] [Indexed: 10/26/2024] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD) is related to social communication difficulties, repetitive behaviors, and highly restricted interests beginning early in life. Currently, ASD is more diagnosed than in the past, and new models are needed. The Advanced Integrative Model (AIM) is a new model in which genes and concomitant medical problems to diagnosis (CMPD) and the impact of their rigorous and adequate treatment are considered. METHODS The role of a dynamic encephalopathy from which the individual response, susceptibilities in the brain and outside the brain, gut barrier and brain-blood-barrier permeabilities, and the plastic nature of the brain is proposed as a tool for diagnosis. The concomitant medical problems (CMP) are those at and outside the brain. The individual response to treatments of CMP is analyzed. RESULTS The AIM allows for classification into 3 main groups and 24 subgroups. CONCLUSIONS The groups and subgroups in ASD are obtained taking into account CMPD treatments and individual response.
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Affiliation(s)
- Andrés Ciolino
- Planta Piloto de Ingeniería Química–PLAPIQUI (UNS–CONICET), Camino La Carrindanga Km 7, CC 717, Bahía Blanca 8000, Argentina;
- Departamento de Ingeniería Química, Universidad Nacional del Sur (UNS), Avda. Alem 1253, Cuerpo C’-Primer Piso, Bahía Blanca 8000, Argentina
| | - María Luján Ferreira
- Planta Piloto de Ingeniería Química–PLAPIQUI (UNS–CONICET), Camino La Carrindanga Km 7, CC 717, Bahía Blanca 8000, Argentina;
- Departamento de Química, Universidad Nacional del Sur (UNS), Avda. Alem 1253, Bahía Blanca 8000, Argentina
| | - Nicolás Loyacono
- Sociedad Argentina de Neurodesarrollo y Trastornos Asociados (SANyTA), Migueletes 681, Piso 2, Departamento 2, Ciudad Autónoma de Buenos Aires C1426BUE, Argentina;
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Beaurenaut M, Kovarski K, Destais C, Mennella R, Grèzes J. Spontaneous instrumental approach-avoidance learning in social contexts in autism. Mol Autism 2024; 15:33. [PMID: 39085896 PMCID: PMC11293119 DOI: 10.1186/s13229-024-00610-8] [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: 12/21/2023] [Accepted: 07/17/2024] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND Individuals with Autism Spectrum Condition (ASC) are characterized by atypicalities in social interactions, compared to Typically Developing individuals (TD). The social motivation theory posits that these difficulties stem from diminished anticipation, reception, and/or learning from social rewards. Although learning from socioemotional outcomes is core to the theory, studies to date have been sparse and inconsistent. This possibly arises from a combination of theoretical, methodological and sample-related issues. Here, we assessed participants' ability to develop a spontaneous preference for actions that lead to desirable socioemotional outcomes (approaching/avoiding of happy/angry individuals, respectively), in an ecologically valid social scenario. We expected that learning abilities would be impaired in ASC individuals, particularly in response to affiliative social feedback. METHOD We ran an online social reinforcement learning task, on two large online cohorts with (n = 274) and without (n = 290) ASC, matched for gender, age and education. Participants had to indicate where they would sit in a waiting room. Each seat was associated with different probabilities of approaching/avoiding emotional individuals. Importantly, the task was implicit, as participants were not instructed to learn, and emotional expressions were never mentioned. We applied both categorical analyses contrasting the ASC and TD groups and dimensional factor analysis on affective questionnaires. RESULTS Contrary to our hypothesis, participants showed spontaneous learning from socioemotional outcomes, regardless of their diagnostic group. Yet, when accounting for dimensional variations in autistic traits, as well as depression and anxiety, two main findings emerged among females who failed to develop explicit learning strategies: (1) autism severity in ASC correlated with reduced learning to approach happy individuals; (2) anxiety-depression severity across both ASC and TD participants correlated with reduced learning to approach/avoid happy/angry individuals, respectively. CONCLUSIONS Implicit spontaneous learning from socioemotional outcomes is not generally impaired in autism but may be specifically associated with autism severity in females with ASC, when they do not have an explicit strategy for adapting to their social environment. Clinical diagnosis and intervention ought to take into account individual differences in their full complexity, including the presence of co-morbid anxiety and depression, when dealing with social atypicalities in autism.
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Affiliation(s)
- Morgan Beaurenaut
- Laboratoire sur les Interactions Cognition, Action, Émotion (LICAÉ), Université Paris Nanterre, 200 avenue de La République, Nanterre Cedex, 92001, France.
| | - Klara Kovarski
- Sorbonne Université, INSPE, Paris, France
- Laboratoire de Psychologie du Développement et de l'Éducation de l'enfant (LaPsyDÉ), Université Paris Cité, CNRS, 46 rue Saint-Jacques, Paris, 75005, France
| | - Constance Destais
- Cognitive and Computational Neuroscience Laboratory (LNC2), Inserm U960, Department of Cognitive Studies, École Normale Supérieure, PSL University, 29 rue d'Ulm, Paris, 75005, France
| | - Rocco Mennella
- Laboratoire sur les Interactions Cognition, Action, Émotion (LICAÉ), Université Paris Nanterre, 200 avenue de La République, Nanterre Cedex, 92001, France
- Cognitive and Computational Neuroscience Laboratory (LNC2), Inserm U960, Department of Cognitive Studies, École Normale Supérieure, PSL University, 29 rue d'Ulm, Paris, 75005, France
| | - Julie Grèzes
- Cognitive and Computational Neuroscience Laboratory (LNC2), Inserm U960, Department of Cognitive Studies, École Normale Supérieure, PSL University, 29 rue d'Ulm, Paris, 75005, France.
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Kamp-Becker I. Autism spectrum disorder in ICD-11-a critical reflection of its possible impact on clinical practice and research. Mol Psychiatry 2024; 29:633-638. [PMID: 38273107 PMCID: PMC11153155 DOI: 10.1038/s41380-023-02354-y] [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: 07/04/2023] [Revised: 11/23/2023] [Accepted: 11/27/2023] [Indexed: 01/27/2024]
Abstract
This perspective article compares and contrasts the conceptualization of Autism Spectrum Disorder (ASD) in ICD-11 and DSM-5. By guiding the user through the ICD-11 text, it is argued that, in contrast to DSM-5, ICD-11 allows a high variety in symptom combinations, which results in an operationalization of ASD that is in favor of an extreme diverse picture, yet possibly at the expense of precision, including unforeseeable effects on clinical practice, care, and research. The clinical utility is questionable as this conceptualization can hardly be differentiated from other mental disorders and autism-like traits. It moves away from an observable, behavioral, and neurodevelopmental disorder to a disorder of inner experience that can hardly be measured objectively. It contains many vague and subjective concepts that lead to non-falsifiable diagnoses. This bears a large danger of false positive diagnoses, of further increased prevalence rates, limitations of access to ASD-specific services and of increasing the non-specificity of treatments. For research, the hypothesis is that the specificity of ASD will be reduced and this will additional increase the already high heterogeneity with the effect that replication of studies will be hampered. This could limit our understanding of etiology and biological pathways of ASD and bears the risk that precision medicine, i.e., a targeted approach for individual treatment strategies based on precise diagnostic markers, is more far from becoming reality. Thus, a more precise, quantitative description and more objective measurement of symptoms are suggested that define the clinical ASD phenotype. Identification of core ASD subtypes/endophenotypes and a precise description of symptoms is the necessary next step to advance diagnostic classification systems. Therefore, employing a more finely grained, objective, clinical symptom characterization which is more relatable to neurobehavioral concepts is of central significance.
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Affiliation(s)
- Inge Kamp-Becker
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Philipps University Marburg, Hans-Sachs Str. 6, 36037, Marburg, Germany.
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Loffi RG, Cruz TKF, Paiva GM, Souto DO, Barreto SR, Santana PAN, Nascimento AAAC, Costa FRM, Cota EB, Haase VG. Theoretical-Methodological Foundations for the Global Integration Method (Método de Integração Global-MIG) in the Treatment of Autism Spectrum Disorder. CHILDREN (BASEL, SWITZERLAND) 2024; 11:191. [PMID: 38397303 PMCID: PMC10887636 DOI: 10.3390/children11020191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/30/2024] [Accepted: 01/31/2024] [Indexed: 02/25/2024]
Abstract
Currently, there is no intervention model for autism spectrum disorder (ASD) that addresses all levels and factors of the International Classification of Functioning, Disability and Health (ICF, WHO). The most researched programs focus on naturalistic, developmental and behavioral approaches to socio-communication. Less attention has been paid to motor and environmental reactivity aspects (behavior/interest restriction and sensory reactivity). The evidence rationale for the Global Integration Method (MIG, "Método de Integração Global"), a model addressing sensorimotor reactivity in addition to socio-communication, is presented. MIG is an integrative, interdisciplinary, family-oriented intervention and naturalistic program that addresses all levels and moderating factors of ASD's impact. MIG's theoretical rationale is based on the predictive coding impairment and embodied cognition hypotheses. MIG incorporates both bottom-up (flexible therapeutic suit, social-motor synchronization) and top-down (schematic social information processing, narratives, imagery) strategies to promote the building and use of accurate, flexible and context-sensitive internal predictive models. MIG is based on the premises that predictive coding improves both socio-communication and environmental reactivity, and that the postural stabilization provided by the flexible therapeutic suit frees information processing resources for socio-cognitive learning. MIG builds on interdisciplinary, professionally and parentally mediated work based on behavioral principles of intensive training in a situated environment.
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Affiliation(s)
- Renato Guimarães Loffi
- Instituto de Neurodesenvolvimento, Cognição e Educação Inclusiva (INCEI), TREINITEC Ltda., Rua Carmélia Loffi 17, Justinópolis, Ribeirão das Neves 33900-730, MG, Brazil; (R.G.L.); (G.M.P.); (D.O.S.); (S.R.B.); (P.A.N.S.); (A.A.A.C.N.); (F.R.M.C.); (E.B.C.); (V.G.H.)
| | - Thalita Karla Flores Cruz
- Instituto de Neurodesenvolvimento, Cognição e Educação Inclusiva (INCEI), TREINITEC Ltda., Rua Carmélia Loffi 17, Justinópolis, Ribeirão das Neves 33900-730, MG, Brazil; (R.G.L.); (G.M.P.); (D.O.S.); (S.R.B.); (P.A.N.S.); (A.A.A.C.N.); (F.R.M.C.); (E.B.C.); (V.G.H.)
- Programa de Pós-Graduação em Neurociências, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
| | - Giulia Moreira Paiva
- Instituto de Neurodesenvolvimento, Cognição e Educação Inclusiva (INCEI), TREINITEC Ltda., Rua Carmélia Loffi 17, Justinópolis, Ribeirão das Neves 33900-730, MG, Brazil; (R.G.L.); (G.M.P.); (D.O.S.); (S.R.B.); (P.A.N.S.); (A.A.A.C.N.); (F.R.M.C.); (E.B.C.); (V.G.H.)
- Programa de Pós-Graduação em Neurociências, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
| | - Deisiane Oliveira Souto
- Instituto de Neurodesenvolvimento, Cognição e Educação Inclusiva (INCEI), TREINITEC Ltda., Rua Carmélia Loffi 17, Justinópolis, Ribeirão das Neves 33900-730, MG, Brazil; (R.G.L.); (G.M.P.); (D.O.S.); (S.R.B.); (P.A.N.S.); (A.A.A.C.N.); (F.R.M.C.); (E.B.C.); (V.G.H.)
| | - Simone Rosa Barreto
- Instituto de Neurodesenvolvimento, Cognição e Educação Inclusiva (INCEI), TREINITEC Ltda., Rua Carmélia Loffi 17, Justinópolis, Ribeirão das Neves 33900-730, MG, Brazil; (R.G.L.); (G.M.P.); (D.O.S.); (S.R.B.); (P.A.N.S.); (A.A.A.C.N.); (F.R.M.C.); (E.B.C.); (V.G.H.)
- Programa de Pós-Graduação em Ciências Fonoaudiológicas, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
| | - Patrícia Aparecida Neves Santana
- Instituto de Neurodesenvolvimento, Cognição e Educação Inclusiva (INCEI), TREINITEC Ltda., Rua Carmélia Loffi 17, Justinópolis, Ribeirão das Neves 33900-730, MG, Brazil; (R.G.L.); (G.M.P.); (D.O.S.); (S.R.B.); (P.A.N.S.); (A.A.A.C.N.); (F.R.M.C.); (E.B.C.); (V.G.H.)
- Programa de Pós-Graduação em Neurociências, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
| | - Amanda Aparecida Alves Cunha Nascimento
- Instituto de Neurodesenvolvimento, Cognição e Educação Inclusiva (INCEI), TREINITEC Ltda., Rua Carmélia Loffi 17, Justinópolis, Ribeirão das Neves 33900-730, MG, Brazil; (R.G.L.); (G.M.P.); (D.O.S.); (S.R.B.); (P.A.N.S.); (A.A.A.C.N.); (F.R.M.C.); (E.B.C.); (V.G.H.)
- Programa de Pós-Graduação em Neurociências, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
| | - Fabiana Rachel Martins Costa
- Instituto de Neurodesenvolvimento, Cognição e Educação Inclusiva (INCEI), TREINITEC Ltda., Rua Carmélia Loffi 17, Justinópolis, Ribeirão das Neves 33900-730, MG, Brazil; (R.G.L.); (G.M.P.); (D.O.S.); (S.R.B.); (P.A.N.S.); (A.A.A.C.N.); (F.R.M.C.); (E.B.C.); (V.G.H.)
- Programa de Pós-Graduação em Psicologia: Cognição e Comportamento, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
| | - Elisa Braz Cota
- Instituto de Neurodesenvolvimento, Cognição e Educação Inclusiva (INCEI), TREINITEC Ltda., Rua Carmélia Loffi 17, Justinópolis, Ribeirão das Neves 33900-730, MG, Brazil; (R.G.L.); (G.M.P.); (D.O.S.); (S.R.B.); (P.A.N.S.); (A.A.A.C.N.); (F.R.M.C.); (E.B.C.); (V.G.H.)
| | - Vitor Geraldi Haase
- Instituto de Neurodesenvolvimento, Cognição e Educação Inclusiva (INCEI), TREINITEC Ltda., Rua Carmélia Loffi 17, Justinópolis, Ribeirão das Neves 33900-730, MG, Brazil; (R.G.L.); (G.M.P.); (D.O.S.); (S.R.B.); (P.A.N.S.); (A.A.A.C.N.); (F.R.M.C.); (E.B.C.); (V.G.H.)
- Programa de Pós-Graduação em Neurociências, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
- Programa de Pós-Graduação em Psicologia: Cognição e Comportamento, Universidade Federal de Minas Gerais, Belo Horizonte 31270-901, MG, Brazil
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