Abstract

Most brain imaging studies of pain are done using a two-state subtraction design (state-related design). More recently event-related functional magnetic reasonance imaging (fMRI) has also been used for studying pain. Both designs severely limit the application of the technology to clinical pain states. Recently we demonstrated that monitoring time fluctuations of perceived pain could be used with fMRI to identify brain regions involved in conscious, subjective perception of pain. Here we extend the methodology to demonstrate that the same approach can be used to study clinical pain states. Subjects are equipped with a finger-spanning device to continuously rate and log their perceived pain during fMRI data collection. These ratings are convolved with a canonical hemodynamic response function to generate predictor waveforms with which related brain activity can be identified. Chronic low back pain patients and a normal volunteer were used. In one series of fMRI scans the patient simply lies in the scanner and indicates spontaneous fluctuations of the subjective pain. In other fMRI scans, a straight-leg raising procedure is performed to exacerbate the back pain. In the normal volunteer, fMRI scans were done during painful and non-painful straight-leg raisings. The results indicate the feasibility of differentiating between different pain states. We argue that the approach can be generalized to identify brain circuitry underlying diverse clinical pain conditions.

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