A method to analyze low signal-to-noise ratio functional magnetic resonance imaging data

The current practice of using a single, representative hemodynamic response function (canonical HRF) to model functional magnetic resonance imaging (fMRI) data is questionable given the trial-to-trial variability of the brain's responses. In addition, the changes in blood-oxygenation level due to sensory stimulation may be small, especially when auditory stimuli are used. Here we introduce a correlation-based single trial analysis method for fMRI data analysis to deal with the low signal-to-noise (SNR) ratio and variability of the HRF in response to repeated, identical auditory stimuli. The correlation technique identifies the "active" trials, i.e., those showing a robust hemodynamic response among all single trials. Using data collected from 14 healthy subjects, it was found that the correlation method can find significant differences between brain areas and brain states in actual fMRI data. Also, the correlation-based method confirmed that the superior temporal gyrus (STG), inferior frontal gyrus (IFG), dorsolateral prefrontal cortex (DLPFC) and thalamus (THA) are involved in auditory information processing in general, and the involvement of the bilateral STG, right THA and left DLPFC in sensory gating. In contrast, conventional analysis failed to find any regions involved in sensory gating. The findings suggest that our single trial analysis method can increase the sensitivity of fMRI data analysis.