title: Which fMRI clustering gives good brain parcellations?
abstract: Analysis and interpretation of neuroimaging data often require one to divide the brain into a number of regions, or parcels, with homogeneous characteristics, be these regions defined in the brain volume or on the cortical surface. While predefined brain atlases do not adapt to the signal in the individual subject images, parcellation approaches use brain activity (e.g., found in some functional contrasts of interest) and clustering techniques to define regions with some degree of signal homogeneity. In this work, we address the question of which clustering technique is appropriate and how to optimize the corresponding model. We use two principled criteria: goodness of fit (accuracy), and reproducibility of the parcellation across bootstrap samples. We study these criteria on both simulated and two task-based functional Magnetic Resonance Imaging datasets for the Ward, spectral and k-means clustering algorithms. We show that in general Ward's clustering performs better than alternative methods with regard to reproducibility and accuracy and that the two criteria diverge regarding the preferred models (reproducibility leading to more conservative solutions), thus deferring the practical decision to a higher level alternative, namely the choice of a trade-off between accuracy and stability.
authors: Parietal Project-Team, Institut National de Recherche en Informatique et Automatique Palaiseau, France ; Commissariat à l'énergie Atomique et Aux Énergies Alternatives, DSV, Neurospin, I2 BM Gif-sur-Yvette, France.
authors: Bertrand
authors: B
authors: Thirion
authors: Parietal Project-Team, Institut National de Recherche en Informatique et Automatique Palaiseau, France ; Commissariat à l'énergie Atomique et Aux Énergies Alternatives, DSV, Neurospin, I2 BM Gif-sur-Yvette, France.
authors: Gaël
authors: G
authors: Varoquaux
authors: Parietal Project-Team, Institut National de Recherche en Informatique et Automatique Palaiseau, France ; Commissariat à l'énergie Atomique et Aux Énergies Alternatives, DSV, Neurospin, I2 BM Gif-sur-Yvette, France.
authors: Elvis
authors: E
authors: Dohmatob
authors: Commissariat à l'énergie Atomique et Aux Énergies Alternatives, DSV, Neurospin, I2 BM Gif-sur-Yvette, France ; Henry H. Wheeler Jr. Brain Imaging Center, University of California at Berkeley Berkeley, CA, USA.
authors: Jean-Baptiste
authors: JB
authors: Poline
keywords: brain atlas; clustering; cross-validation; functional neuroimaging; group studies; model selection