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Proceedings Paper

A novel approach to image neural activity directly by MRI
Author(s): Manbir Singh; Witaya Sungkarat
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Paper Abstract

Though an approach to image the electrical activity of neurons directly by detecting phase shifts in MRI was first reported in 1991, results to-date remain equivocal due to the low signal-to-noise ratio. The objective of this work was to develop a stimulus-presentation and data acquisition strategy specially geared to detect phase-dispersion effects of neuronal currents within 10-100 ms following stimulation. The key feature is to set the repeated MR data acquisition time TR and the stimulus presentation interval (TI) slightly different from each other so that the time at which images are acquired shifts gradually from one acquisition to the next with respect to stimulus onset. For example, at TR=275ms and 4 Hz stimulus presentation (TI=250ms), initial synchronization of the stimulus onset and MR acquisition would result in the first image being acquired at a latency of 0± (temporal width of data acquisition window), second image at a latency of 25ms, third image at a latency of 50ms and so on up to a latency of 250ms, at which time the stimulus and data acquisition times would become re-synchronized to once again acquire an image at latency=0. Human data were acquired on a 1.5T GE EXCITE scanner from two 8mm thick contiguous slices bracketing the calcarine fissure during a checkerboard flashing at 4 Hz. Preliminary results show activity in the visual cortex at latencies consistent with EEG studies, suggesting the potential of this methodology to image neural activity directly.

Paper Details

Date Published: 14 April 2005
PDF: 10 pages
Proc. SPIE 5746, Medical Imaging 2005: Physiology, Function, and Structure from Medical Images, (14 April 2005); doi: 10.1117/12.595795
Show Author Affiliations
Manbir Singh, Univ. of Southern California (United States)
Witaya Sungkarat, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 5746:
Medical Imaging 2005: Physiology, Function, and Structure from Medical Images
Amir A. Amini; Armando Manduca, Editor(s)

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