title: Anatomically-adapted graph wavelets for improved group-level fMRI activation mapping.
abstract: A graph based framework for fMRI brain activation mapping is presented. The approach exploits the spectral graph wavelet transform (SGWT) for the purpose of defining an advanced multi-resolutional spatial transformation for fMRI data. The framework extends wavelet based SPM (WSPM), which is an alternative to the conventional approach of statistical parametric mapping (SPM), and is developed specifically for group-level analysis. We present a novel procedure for constructing brain graphs, with subgraphs that separately encode the structural connectivity of the cerebral and cerebellar gray matter (GM), and address the inter-subject GM variability by the use of template GM representations. Graph wavelets tailored to the convoluted boundaries of GM are then constructed as a means to implement a GM-based spatial transformation on fMRI data. The proposed approach is evaluated using real as well as semi-synthetic multi-subject data. Compared to SPM and WSPM using classical wavelets, the proposed approach shows superior type-I error control. The results on real data suggest a higher detection sensitivity as well as the capability to capture subtle, connected patterns of brain activity.
authors.affiliation: Biomedical Signal Processing Group, Department of Biomedical Engineering, Lund University, Lund, Sweden. Electronic address: hamid.behjat@bme.lth.se.
authors.forename: Hamid
authors.initials: H
authors.lastname: Behjat
authors.affiliation: Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
authors.forename: Nora
authors.initials: N
authors.lastname: Leonardi
authors.affiliation: Biomedical Signal Processing Group, Department of Biomedical Engineering, Lund University, Lund, Sweden.
authors.forename: Leif
authors.initials: L
authors.lastname: Sörnmo
authors.affiliation: Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
authors.forename: Dimitri
authors.initials: D
authors.lastname: Van De Ville
mesh_terms: D000465:Algorithms; D001931:Brain Mapping / Q000379:methods*; D002531:Cerebellum / Q000033:anatomy & histology* / Q000502:physiology*; D002540:Cerebral Cortex / Q000033:anatomy & histology* / Q000502:physiology*; D003198:Computer Simulation; D066128:Gray Matter / Q000033:anatomy & histology / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D058067:Wavelet Analysis
keywords: Functional MRI; Graph wavelets; Spectral graph theory; Statistical parametric mapping (SPM); Wavelet thresholding