A neural network approach to detect functional MRI signal

In fMRI the key problem of data analysis is to detect the weak BOLD signal component (about 2-5%) in the MR signal. Standard approaches, that typically use cross-correlation analysis or statistical parametric mapping, imply a presumptive knowledge of the expected stimulus-response pattern, which is not available in spontaneous events like hallucinations, sleep, or epileptic seizures. To evidence the possibility of analyzing these events by means of fMRI, we investigated a computational approach based on a self-organizing neural network (Neural Gas) that detects time-dependent alterations in the regional intensity of the functional signal.