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Open Access Highly Accessed Research article

The relationship between magnetic and electrophysiological responses to complex tactile stimuli

Zhao Zhu12, Johanna M Zumer1, Marianne E Lowenthal2, Jeff Padberg2, Gregg H Recanzone23, Leah A Krubitzer24, Srikantan S Nagarajan1 and Elizabeth A Disbrow125*

Author Affiliations

1 Biomagnetic Imaging Laboratory, Department of Radiology, University of California, San Francisco, San Francisco, CA 94143-0628, USA

2 Center for Neuroscience, University of California, Davis, Davis, CA 95616, USA

3 Section of Neurobiology, Physiology & Behavior, University of California, Davis, Davis, CA 95616, USA

4 Department of Psychology, University of California, Davis, Davis, CA 95616, USA

5 Department of Neurology, University of California, Davis, Davis, CA 95616, USA

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BMC Neuroscience 2009, 10:4  doi:10.1186/1471-2202-10-4

Published: 15 January 2009

Abstract

Background

Magnetoencephalography (MEG) has become an increasingly popular technique for non-invasively characterizing neuromagnetic field changes in the brain at a high temporal resolution. To examine the reliability of the MEG signal, we compared magnetic and electrophysiological responses to complex natural stimuli from the same animals. We examined changes in neuromagnetic fields, local field potentials (LFP) and multi-unit activity (MUA) in macaque monkey primary somatosensory cortex that were induced by varying the rate of mechanical stimulation. Stimuli were applied to the fingertips with three inter-stimulus intervals (ISIs): 0.33s, 1s and 2s.

Results

Signal intensity was inversely related to the rate of stimulation, but to different degrees for each measurement method. The decrease in response at higher stimulation rates was significantly greater for MUA than LFP and MEG data, while no significant difference was observed between LFP and MEG recordings. Furthermore, response latency was the shortest for MUA and the longest for MEG data.

Conclusion

The MEG signal is an accurate representation of electrophysiological responses to complex natural stimuli. Further, the intensity and latency of the MEG signal were better correlated with the LFP than MUA data suggesting that the MEG signal reflects primarily synaptic currents rather than spiking activity. These differences in latency could be attributed to differences in the extent of spatial summation and/or differential laminar sensitivity.