@article {Gao135087, author = {Xiaoqing Gao and Francesco Gentile and Bruno Rossion}, title = {Fast Periodic Stimulation (FPS): A highly effective approach in fMRI brain mapping}, elocation-id = {135087}, year = {2017}, doi = {10.1101/135087}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Functional magnetic resonance imaging (fMRI) is a major technique for human brain mapping. We present a Fast Periodic Stimulation (FPS) fMRI approach, demonstrating its high effectiveness in defining category-selective brain regions. Observers see a dynamic stream of widely variable natural object images alternating at a fast rate (6 images/sec). Every 9 seconds, a short burst of variable face images contrasting with objects in pairs induces an objective 0.111 Hz face-selective neural response in the ventral occipito-temporal cortex and beyond. A model-free Fourier analysis achieves a two-fold increase in signal-to-noise ratio compared to a conventional block-design approach with identical stimuli. Periodicity of category contrast and random variability among images minimize low-level visual confounds while preserving naturalness of the stimuli, leading to the highest values (80-90\%) of test-retest reliability yet reported in this area of research. FPS-fMRI opens a new avenue for understanding brain function with low temporal resolution methods.Highlights FPS-fMRI achieves a two-fold increase in peak SNR over conventional approachFPS-fMRI reveals comprehensive extended face-selective areas including ATLFPS-fMRI achieves high specificity by minimizing influence of low-level visual cuesFPS-fMRI achieves very high test-retest reliability (80\%-90\%) in spatial activation mapeTOC Blurb In BriefGao et al. present a novel FPS-fMRI approach, which achieves a two-fold increase in peak signal-to-noise ratio in defining the neural basis of visual categorization while preserving ecological validity, minimizing low-level visual confounds and reaching very high (80\%-90\%) test-retest reliability.}, URL = {https://www.biorxiv.org/content/early/2017/05/08/135087}, eprint = {https://www.biorxiv.org/content/early/2017/05/08/135087.full.pdf}, journal = {bioRxiv} }