Spatial smoothing hurts localization but not information: Pitfalls for brain mappers

• Published in: NeuroImage (Orlando, Fla.) Vol. 49; no. 3; pp. 1949 - 1952
• Main Authors: Kamitani, Yukiyasu, Sawahata, Yasuhito
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.02.2010; Elsevier Limited
• Subjects: Bias; Binomial distribution; Brain - physiology; Brain Mapping - methods; Classification; Humans; Image Processing, Computer-Assisted - methods; Magnetic Resonance Imaging; Mathematical models; Noise
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2009.06.040

Op de Beeck (Op de Beeck, H., 2009. Against hyperacuity in brain reading: Spatial smoothing does not hurt multivariate fMRI analyses? Neuroimage) challenges the possibility of extracting information from subvoxel representations via random biases associated with voxel sampling, the hypothesis proposed by Kamitani and Tong (Kamitani, Y., Tong, F., 2005. Decoding the visual and subjective contents of the human brain. Nat. Neurosci. 8, 679–685). Here, we show that his results provide no evidence against the possibility, being consistent with both of the subvoxel and supravoxel representation models. Classification of spatially smoothed fMRI data is not an effective means to probe into information sources for multivoxel decoding, since smoothing does not hurt the information contents of multivoxel patterns. We point out the danger of interpreting multivoxel decoding results based on intuitions guided by the conventional brain mapping paradigm.