2026-04-19T17:34:52Zhttps://recercat.cat/oai/request

oai:recercat.cat:11351/88342025-10-24T10:33:35Zcom_2072_378070com_2072_378040col_2072_378092

00925njm 22002777a 4500 dc Simeon, Guillem author Camara, Oscar author Pareto Onghena, Deborah author Piella, Gemma author 2023-01-13T08:22:56Z 2023-01-13T08:22:56Z 2022-05-23 Riemannian geometry; Attention-deficit/hyperactivity disorder; Functional connectivity Geometria riemanniana; Trastorn per dèficit d'atenció/hiperactivitat; Connectivitat funcional Geometría riemanniana; Trastorno por déficit de atención/hiperactividad; Conectividad funcional The use of multi-site datasets in neuroimaging provides neuroscientists with more statistical power to perform their analyses. However, it has been shown that the imaging-site introduces variability in the data that cannot be attributed to biological sources. In this work, we show that functional connectivity matrices derived from resting-state multi-site data contain a significant imaging-site bias. To this aim, we exploited the fact that functional connectivity matrices belong to the manifold of symmetric positive-definite (SPD) matrices, making it possible to operate on them with Riemannian geometry. We hereby propose a geometry-aware harmonization approach, Rigid Log-Euclidean Translation, that accounts for this site bias. Moreover, we adapted other Riemannian-geometric methods designed for other domain adaptation tasks and compared them to our proposal. Based on our results, Rigid Log-Euclidean Translation of multi-site functional connectivity matrices seems to be among the studied methods the most suitable in a clinical setting. This represents an advance with respect to previous functional connectivity data harmonization approaches, which do not respect the geometric constraints imposed by the underlying structure of the manifold. In particular, when applying our proposed method to data from the ADHD-200 dataset, a multi-site dataset built for the study of attention-deficit/hyperactivity disorder, we obtained results that display a remarkable correlation with established pathophysiological findings and, therefore, represent a substantial improvement when compared to the non-harmonization analysis. Thus, we present evidence supporting that harmonization should be extended to other functional neuroimaging datasets and provide a simple geometric method to address it. http://hdl.handle.net/11351/8834 Conjunts de dades Imatgeria per ressonància magnètica Trastorn per dèficit d'atenció amb hiperactivitat - Imatgeria ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Imaging::Tomography::Magnetic Resonance Imaging PSYCHIATRY AND PSYCHOLOGY::Mental Disorders::Neurodevelopmental Disorders::Attention Deficit and Disruptive Behavior Disorders::Attention Deficit Disorder with Hyperactivity ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES, AND EQUIPMENT::Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Imaging::Neuroimaging PUBLICATION CHARACTERISTICS::Publication Formats::Dataset TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::tomografía::imagen por resonancia magnética PSIQUIATRÍA Y PSICOLOGÍA::trastornos mentales::trastornos del desarrollo neurológico::trastornos conductuales disruptivos y déficit de atención::trastornos de déficit de atención con hiperactividad TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::neuroimágenes CARACTERÍSTICAS DE PUBLICACIONES::formatos de publicación::conjunto de datos Riemannian Geometry of Functional Connectivity Matrices for Multi-Site Attention-Deficit/Hyperactivity Disorder Data Harmonization