Functional Brain Imaging of Mind-Body Interaction in Stroke Recovery

Research on hypnosis would be greatly enhanced by using physiological measures to quantify the depth of the hypnotic trance during experiments. This has not been done in previous research because no method for quantifying the hypnotic state is available. One possible measure of hypnotic depth is the control of the heart rate by the autonomic nervous system. Variations in the time between beats of the heart is termed heart rate variability (HRV). Entrainment of the heart rate at the respiratory rhythm via vagal innervation of the sino atrial node is a well-documented phenomenon called respiratory sinus arrhythmia (RSA). A study by Peng et al. (1999) found that RSA was significantly larger during meditation than during the control conditions of rhythmic breathing, sleeping, or spontaneous respiration by elite athletes. Another study found increased RSA in the HRV power spectrum during hypnosis (DeBenedittis, 1994). When viewed as a measure of cognitively mediated parasympathetic control over the heart, RSA changes during hypnosis are a good candidate for quantifying the depth of the hypnotic state. The use of HRV to quantify the hypnotic state will first be studied with normal subjects and later expanded to include elderly stroke patients.

Diffuse optical tomography (DOT) has tremendous potential as a functional brain imaging modality for the investigation of hypnosis and stroke recovery. The Photon Migration Laboratory headed by David Boas, Ph.D. is developing DOT for clinical use. I have become involved in the design of the cap that holds the optodes on the subject’s head. My current design holds 25 optical fibers in various patterns covering most of the scalp. Future DOT imaging systems will require a cap that supports as many as 64 optodes. The cap design for future DOT systems will integrate the optodes and optic fibers directly into the cap. An integrated cap requires that the pattern of source and detector fibers remains fixed. At the present time a fixed pattern has been avoided because it is not known what arrangement will provide for optimal image reconstruction of the functional brain activity in the underlying tissue. The logical progression is to first optimize the optode array geometry and image reconstruction algorithms through analytical analysis and computational modeling. The integrated DOT cap can then be designed to the resulting specifications. In addition to working on the cap design I am working to improve the homonymic signal to noise ratio by modeling physiological artifacts and I am experimenting with different methods of image reconstruction and visualization.

Researchers: S.G. Diamond