Elsevier

NeuroImage

Volume 37, Issue 1, 1 August 2007, Pages 137-148
NeuroImage

Modelling the magnetic signature of neuronal tissue

https://doi.org/10.1016/j.neuroimage.2007.04.033Get rights and content

Abstract

Neuronal communication in the brain involves electrochemical currents, which produce magnetic fields. Stimulus-evoked brain responses lead to changes in these fields and can be studied using magneto- and electro-encephalography (MEG/EEG). In this paper we model the spatiotemporal distribution of the magnetic field of a physiologically idealized but anatomically realistic neuron to assess the possibility of using magnetic resonance imaging (MRI) for directly mapping the neuronal currents in the human brain. Our results show that the magnetic field several centimeters from the centre of the neuron is well approximated by a dipole source, but the field close to the neuron is not, a finding particularly important for understanding the possible contrast mechanism underlying the use of MRI to detect and locate these currents. We discuss the importance of the spatiotemporal characteristics of the magnetic field in cortical tissue for evaluating and optimizing an experiment based on this mechanism and establish an upper bound for the expected MRI signal change due to stimulus-induced cortical response. Our simulations show that the expected change of the signal magnitude is 1.6% and its phase shift is 1°. An unexpected finding of this work is that the cortical orientation with respect to the external magnetic field has little effect on the predicted MRI contrast. This encouraging result shows that magnetic resonance contrast directly based on the neuronal currents present in the cortex is theoretically a feasible imaging technique. MRI contrast generation based on neuronal currents depends on the dendritic architecture and we obtained high-resolution optical images of cortical tissue to discuss the spatial structure of the magnetic field in grey matter.

Section snippets

Neuron simulations

Our simulations are based on compartmentalized models of neurons. Our computer code, BioSENSE (biologically-based sensory-enhanced neural simulation engine), solves the balance of currents in each compartment through successive time steps. It is one of the original neural simulators (Travis, 1986, Travis, 1988) and has undergone a number of revisions since its introduction. It can simulate the dynamics of individual neurons or collections of neurons, including structured systems such as sensory

Results and discussions

The modelled neuron and its electric current distribution and magnetic field produced at a fixed moment of time are shown in Fig. 1. The chosen reference frame is such that the z-axis is parallel to the magnetic field of the MR scanner, and the dendritic arbour of the neuron is predominantly in the xy plane. This frame of reference is chosen arbitrarily with respect to the apical dendrite since, in an MRI experiment, the neuronal orientation will vary throughout the cortex.

In Fig. 2A, the time

Conclusions

This study is a step in the chain of efforts to determine the detectability of neuronal activity via MRI (Bandettini et al., 2005). Details of the dynamics of the magnetic fields of individual neurons may be important for resolving this issue and should be examined before, or at least in conjunction with, studies of populations of realistic neurons. There are relatively few reported studies on neuronal magnetic fields in brain tissue. Xue et al. (2006) considered synchronized activity of

Acknowledgments

K.B. Blagoev would like to thank Vince Clark, Anders Dale, Anna Devor, Paul Mullins, Bruce Rosen, Kamil Ugurbil and Van J. Wedeen for valuable discussions.

Supported by LANL-LDRD and NS44623.

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