Auxiliary Diagnosis of Children With Attention-Deficit/Hyperactivity Disorder Using Eye-Tracking and Digital Biomarkers: Case-Control Study (Preprint) DOI
Z. Liu, Jinkai Li, Yuanyuan Zhang

et al.

Published: March 29, 2024

BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental in school-aged children. The lack of objective biomarkers for ADHD often results missed diagnoses or misdiagnoses, which lead to inappropriate delayed interventions. Eye-tracking technology provides an method assess children’s neuropsychological behavior. OBJECTIVE aim this study was develop and reliable auxiliary diagnostic system using eye-tracking technology. This would be valuable screening schools communities may help identify the clinical diagnosis ADHD. METHODS We conducted case-control children with typically developing (TD) designed assessment paradigm based on core cognitive deficits extracted various digital that represented participant behaviors. These developmental patterns were compared between TD groups. Machine learning (ML) implemented validate ability predict performance ML models evaluated 5-fold cross-validation. RESULTS recruited 216 participants, whom 94 (43.5%) 122 (56.5%) group showed significantly poorer (for accuracy completion time) than prosaccade, antisaccade, saccade tasks. In addition, there substantial differences biomarkers, such as pupil diameter fluctuation, regularity gaze trajectory, fixations unrelated areas. Although task speed increased over time, their eye-movement remained irregular. aged 5 6 years outperformed 9 10 years, difference relatively stable indicated followed unique pattern. model effective discriminating groups, achieving area under curve 0.965 0.908. CONCLUSIONS proposed effectively identified aspects constructed these achieved high reliability identifying Our can facilitate early provide clinicians reference.

Language: Английский

Editorial: Exploring goal-directed behavior through creativity: perspectives from psychology, neuroscience, and psychiatry DOI Creative Commons
Chong Chen, Hadi Moradi, Leila Kashani Vahid

et al.

Frontiers in Psychology, Journal Year: 2024, Volume and Issue: 15

Published: April 19, 2024

Editorial: Exploring goal-directed behavior through creativity: perspectives from psychology, neuroscience, and psychiatry

Language: Английский

Citations

0
Alignment of Consumers’ Expected Brain Benefits from Food and Supplements with Measurable Cognitive Performance Tests DOI Open Access
Hayley Young, Alecia L. Cousins, Carol Byrd‐Bredbenner

et al.

Nutrients, Journal Year: 2024, Volume and Issue: 16(12), P. 1950 - 1950

Published: June 19, 2024

Consumers often cite cognitive improvements as reasons for making dietary changes or using supplements, a motivation that if leveraged could greatly enhance public health. However, rarely is it considered whether standardized tests are used in nutrition research aligned to outcomes of interest the consumer. This knowledge gap presents challenge scientific substantiation nutrition-based health benefits. Here we combined focus group transcript review reflexive thematic analysis and multidisciplinary expert panel exercise evaluate applicability performance tools/tasks substantiating specific benefits articulated by consumers with objectives (1) understand how comprehend potential brain health, (2) determine alignment between desired validated tools. We derived ‘Consumer Taxonomy Cognitive Affective Health Nutrition Research’ which describes affective structure from perspective. Experts agreed exist some consumer including focused attention, sustained episodic memory, energy levels, anxiety. Prospective flow, presence represented novel require development validation new Closing science fostering co-creative approaches critical products recommendations support realizable benefit

Language: Английский

Citations

0
Auxiliary Diagnosis of Children With Attention-Deficit/Hyperactivity Disorder Using Eye-Tracking and Digital Biomarkers: Case-Control Study (Preprint) DOI
Z. Liu, Jinkai Li, Yuanyuan Zhang

et al.

Published: March 29, 2024

BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental in school-aged children. The lack of objective biomarkers for ADHD often results missed diagnoses or misdiagnoses, which lead to inappropriate delayed interventions. Eye-tracking technology provides an method assess children’s neuropsychological behavior. OBJECTIVE aim this study was develop and reliable auxiliary diagnostic system using eye-tracking technology. This would be valuable screening schools communities may help identify the clinical diagnosis ADHD. METHODS We conducted case-control children with typically developing (TD) designed assessment paradigm based on core cognitive deficits extracted various digital that represented participant behaviors. These developmental patterns were compared between TD groups. Machine learning (ML) implemented validate ability predict performance ML models evaluated 5-fold cross-validation. RESULTS recruited 216 participants, whom 94 (43.5%) 122 (56.5%) group showed significantly poorer (for accuracy completion time) than prosaccade, antisaccade, saccade tasks. In addition, there substantial differences biomarkers, such as pupil diameter fluctuation, regularity gaze trajectory, fixations unrelated areas. Although task speed increased over time, their eye-movement remained irregular. aged 5 6 years outperformed 9 10 years, difference relatively stable indicated followed unique pattern. model effective discriminating groups, achieving area under curve 0.965 0.908. CONCLUSIONS proposed effectively identified aspects constructed these achieved high reliability identifying Our can facilitate early provide clinicians reference.

Language: Английский

Citations

0