A critique of Tensor Probabilistic Independent Component Analysis: Implications and recommendations for multi-subject fMRI data analysis

• Published in: Journal of neuroscience methods Vol. 213; no. 2; pp. 263 - 273
• Main Authors: Helwig, Nathaniel E., Hong, Sungjin
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 15.03.2013
• Subjects: Humans; Image Interpretation, Computer-Assisted - methods; Magnetic Resonance Imaging; Neuroimage data analysis; Parafac; Parallel Factor Analysis; PICA; Tensor PICA; Tensor Probabilistic Independent Component Analysis; Neuroimage data analysis; Tensor PICA; Tensor Probabilistic Independent Component Analysis; PICA; Parallel Factor Analysis; Parafac

Tensor Probabilistic Independent Component Analysis (TPICA) is a popular tool for analyzing multi-subject fMRI data (voxels×time×subjects) because of TPICA's supposed robustness. In this paper, we show that TPICA is not as robust as its authors claim. Specifically, we discuss why TPICA's o...