Cécile Bordier

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The subjective experience of color by synesthetes when viewing achromatic letters and numbers supposedly relates to real color experience, as exemplified by the recruitment of the V4 color center observed in some brain imaging studies. Phenomenological reports and psychophysics tests indicate, however, that both experiences are different. Using functional(More)
The investigation of brain activity using naturalistic, ecologically-valid stimuli is becoming an important challenge for neuroscience research. Several approaches have been proposed, primarily relying on data-driven methods (e.g. independent component analysis, ICA). However, data-driven methods often require some post-hoc interpretation of the imaging(More)
For statistical analysis of functional magnetic resonance imaging (fMRI) data sets, we propose a data-driven approach based on independent component analysis (ICA) implemented in a new version of the AnalyzeFMRI R package. For fMRI data sets, spatial dimension being much greater than temporal dimension, spatial ICA is the computationally tractable approach(More)
We are usually unaware of the brief but large illumination changes caused by blinks, presumably because of blink suppression mechanisms. In fMRI however, increase of the BOLD signal was reported in the visual cortex, e.g. during blocks of voluntary blinks (Bristow, Frith and Rees, 2005) or after spontaneous blinks recorded during the prolonged fixation of a(More)
PURPOSE The influence of background attenuation on the spatial frequency bandwidth requirements for image recognition was assessed in normal young and older groups and in a group with age-related macular degeneration (AMD). Bandwidth requirements were also assessed in the visual periphery of young normal observers. METHODS In Experiment 1, each observer(More)
The use of naturalistic stimuli to probe sensory functions in the human brain is gaining increasing interest. Previous imaging studies examined brain activity associated with the processing of cinematographic material using both standard "condition-based" designs, as well as "computational" methods based on the extraction of time-varying features of the(More)
Graph theory provides a powerful framework to investigate brain functional connectivity networks and their modular organization. However, most graph-based methods suffer from a fundamental resolution limit that may have affected previous studies and prevented detection of modules, or "communities", that are smaller than a specific scale. Surprise, a(More)
fMRI retinotopic mapping usually relies upon Fourier analysis of functional responses to periodic visual stimuli that encode eccentricity or polar angle in the visual field. Generally, phase estimations are assigned to a surface model of the cerebral cortex and borders between retinotopic areas are eventually determined following ad hoc phase analysis on(More)
FMRI retinotopic mapping is a non-invasive technique for the delineation of low-level visual areas in individual subjects. It generally relies upon the analysis of functional responses to periodic visual stimuli that encode eccentricity or polar angle in the visual field. This technique is used in vision research when the precise assignation of brain(More)
For statistical analysis of functional Magnetic Resonance Imaging (fMRI) data sets, we propose a data-driven approach based on Independent Component Analysis (ICA) implemented in a new version of the AnalyzeFMRI R package. For fMRI data sets, spatial dimension being much greater than temporal dimension, spatial ICA is the tractable approach generally(More)