The Impact of Atlas Parcellation on Functional Connectivity Analysis Across Six Psychiatric Disorders

Human Brain Mapping, Journal Year: 2025, Volume and Issue: 46(5)

Published: April 1, 2025

Neuropsychiatric disorders are associated with altered functional connectivity (FC); however, the reported regional patterns of alterations suffered from low replicability and high variability. This is partly because differences in atlas delineation techniques used to measure FC-related deficits within/across disorders. We systematically investigated impact brain parcellation approach on FC-based network analysis. focused identifying replicable FCs using three structural atlases, including Automated Anatomical Labeling (AAL), Brainnetome (BNA) HCP_MMP_1.0, four approaches: Yeo-Networks (Yeo), Gordon parcel (Gordon) two Schaefer parcelletions, among correlation, group difference, classification tasks six neuropsychiatric disorders: attention deficit hyperactivity disorder (ADHD, n = 340), autism spectrum (ASD, 513), schizophrenia (SZ, 200), schizoaffective (SAD, 142), bipolar (BP, 172), major depression (MDD, 282). Our cross-atlas/disorder analyses demonstrated that frontal-related FC were reproducible all disorders, independent atlasing approach; extraction other areas accuracy affected by schema. Overall, atlases finer granularity performed better tasks. Specifically, generated most repeatable across illnesses. These results indicate may serve as potential common robust neuro-abnormalities 6 psychiatric Furthermore, order improve rsfMRI-based analyses, this study suggests use templates at larger granularity.

Language: Английский

Testing the sensitivity of diagnosis‐derived patterns in functional brain networks to symptom burden in a Norwegian youth sample

Human Brain Mapping, Journal Year: 2024, Volume and Issue: 45(3)

Published: Feb. 15, 2024

Abstract Aberrant brain network development represents a putative aetiological component in mental disorders, which typically emerge during childhood and adolescence. Previous studies have identified resting‐state functional connectivity (RSFC) patterns reflecting psychopathology, but the generalisability to other samples politico‐cultural contexts has not been established. We investigated whether previously cross‐diagnostic case–control autism spectrum disorder (ASD)‐specific pattern of RSFC (discovery sample; aged 5–21 from New York City, USA; n = 1666) could be validated Norwegian convenience‐based youth sample (validation 9–25 Oslo, Norway; 531). As test generalisability, we if these diagnosis‐derived were sensitive levels symptom burden both samples, based on an independent measure burden. Both ASD‐specific across samples. Connectivity significantly associated with thematically appropriate dimensions discovery sample. In validation sample, showed weak, inverse relationship symptoms conduct problems, hyperactivity prosociality, while was linked symptoms. Diagnosis‐derived developmental clinical US convenience youth, however, they health

Language: Английский

Cognitive age prediction and psychological distress in adolescence

Published: May 21, 2024

Background: Adolescence is characterized by fine tuning of cognitive functions. Reduced functioning associated with increased psychological distress. Deviation from typical maturation may represent a marker later difficulty. Objectives: We examined the cross-sectional relationship between an estimate and symptoms distress in convenience sample youth (n=566, age 9-25 years, 73% females). Methods: Extending conceptual approach used for brain prediction, we machine learning out-of-sample validation to each participant, based on performance computerized test battery. For chronological was subtracted predicted procure gap (CAG) as measure deviant maturation. As measures distress, emotional symptoms, conduct problems, hyperactivity, peer depression generalized anxiety were assessed using sum scores Strength Difficulties Questionnaire (SDQ; Goodman, 1997), Short Mood Feelings (SMFQ; Angold et al., 1995) Generalized Anxiety Disorder-7 (GAD-7; Spitzer 2006). tested association age-corrected CAG (cCAG)and domains linear models accounting relevant confounders corrected multiple comparisons. Results: The prediction accuracy cognition model acceptable (r=.57, R2=0.33, RMSE=2.34, MAE=1.84). Lower cCAG higher (ß=-.08, SE=0.029, p=.005, pcorr=.032) (ß=-.07, SE=0.030 p=.014, pcorr=.044). No significant associations found remaining distress.Conclusion: Deviating negatively expected this population-based youth. This supports that development represents factor wellbeing.

Language: Английский