Classifying social anxiety disorder using multivoxel pattern analyses of brain function and structure.
Functional neuroimaging of social anxiety disorder (SAD) support altered neural activation to threat-provoking stimuli focally in the fear network, while structural differences are distributed over the temporal and frontal cortices as well as limbic structures. Previous neuroimaging studies have investigated the brain at the voxel level using mass-univariate methods which do not enable detection of more complex patterns of activity and structural alterations that may separate SAD from healthy individuals. Support vector machine (SVM) is a supervised machine learning method that capitalizes on brain activation and structural patterns to classify individuals. The aim of this study was to investigate if it is possible to discriminate SAD patients (n=14) from healthy controls (n=12) using SVM based on (1) functional magnetic resonance imaging during fearful face processing and (2) regional gray matter volume. Whole brain and region of interest (fear network) SVM analyses were performed for both modalities. For functional scans, significant classifications were obtained both at whole brain level and when restricting the analysis to the fear network while gray matter SVM analyses correctly classified participants only when using the whole brain search volume. These results support that SAD is characterized by aberrant neural activation to affective stimuli in the fear network, while disorder-related alterations in regional gray matter volume are more diffusely distributed over the whole brain. SVM may thus be useful for identifying imaging biomarkers of SAD.
Department of Psychology, Uppsala University, Uppsala, Sweden. Electronic address: andreas.frick@psyk.uu.se.
Andreas
A
Frick
Department of Psychology, Uppsala University, Uppsala, Sweden; Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden.
Malin
M
Gingnell
Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, King's College London, London, UK.
Andre F
AF
Marquand
Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Katarina
K
Howner
Department of Psychology, Stockholm University, Stockholm, Sweden.
Håkan
H
Fischer
Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Marianne
M
Kristiansson
Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, King's College London, London, UK.
Steven C R
SC
Williams
Department of Psychology, Uppsala University, Uppsala, Sweden.
Mats
M
Fredrikson
Department of Psychology, Uppsala University, Uppsala, Sweden.
Tomas
T
Furmark
D000328:Adult; D001921:Brain / Q000098:blood supply* / Q000503:physiopathology*; D001931:Brain Mapping; D004644:Emotions; D006801:Humans; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging; D008297:Male; D010364:Pattern Recognition, Visual; D010698:Phobic Disorders / Q000145:classification* / Q000473:pathology*; D010775:Photic Stimulation; D060388:Support Vector Machine; D055815:Young Adult
Biomarker; Classification; Multivoxel pattern analysis; Social anxiety disorder; Support vector machine