Detection of fast oscillating magnetic fields using dynamic multiple TR imaging and Fourier analysis
January
Detection of fast oscillating magnetic fields using dynamic multiple TR imaging and Fourier analysis
Ki Hwan Kim 0 1
Hyo-Im Heo 0 1
Sung-Hong Park 0 1
0 Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology , Daejeon , South Korea , 2 Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology , Daejeon , South Korea
1 Editor: Viktor Vegh, University of Queensland , AUSTRALIA
Neuronal oscillations produce oscillating magnetic fields. There have been trials to detect neuronal oscillations using MRI, but the detectability in in vivo is still in debate. Major obstacles to detecting neuronal oscillations are (i) weak amplitudes, (ii) fast oscillations, which are faster than MRI temporal resolution, and (iii) random frequencies and on/off intervals. In this study, we proposed a new approach for direct detection of weak and fast oscillating magnetic fields. The approach consists of (i) dynamic acquisitions using multiple times to repeats (TRs) and (ii) an expanded frequency spectral analysis. Gradient echo echo-planar imaging was used to test the feasibility of the proposed approach with a phantom generating oscillating magnetic fields with various frequencies and amplitudes and random on/off intervals. The results showed that the proposed approach could precisely detect the weak and fast oscillating magnetic fields with random frequencies and on/off intervals. Complex and phase spectra showed reliable signals, while no meaningful signals were observed in magnitude spectra. A two-TR approach provided an absolute frequency spectrum above Nyquist sampling frequency pixel by pixel with no a priori target frequency information. The proposed dynamic multiple-TR imaging and Fourier analysis are promising for direct detection of neuronal oscillations and potentially applicable to any pulse sequences.
Data Availability Statement; All relevant data are within the paper
-
Funding: This work was supported by Samsung
Research Funding Center of Samsung Electronics
(https://www.samsungftf.com) under Project
Number SRFC-IT1401-05. The funder had no role
in study design, data collection and analysis,
decision to publish, or preparation of the
manuscript.
Competing interests: The authors have declared
that no competing interests exist.
Introduction
Functional MRI (fMRI) based on blood-oxygenation-level-dependent (BOLD) contrast was
introduced more than 20 years ago, and now has become a dominant tool for mapping brain
function noninvasively [1±3]. Further, resting-state fMRI has been widely used to uncover the
ªfunctional connectivityº of the resting-state brain [
4, 5
]. However, BOLD signals originate
from veins, which are affected by secondary hemodynamic responses associated with local
neuronal activity [6±9]. To overcome the limitation of BOLD fMRI, many researchers have
tried to use MRI for more than 15 years to directly detect magnitude or phase signals produced
by transient magnetic fields. Phantom experiments demonstrated that MRI can detect weak
magnetic fields in the order of 0.1−1 nT [10±13]. However, many research groups have
reported both positive [12±16] and negative results [17±22] in in vivo studies, and a consensus
has not been reached on the detectability of the neuronal currents in vivo.
Recently, a method based on the spin-locking mechanism, named stimulus-induced rotary
saturation (SIRS), was introduced to resonate the B1±induced rotation with neuronal
oscillations [23]. The sensitivity has been improved with a modified SIRS technique, which detected
oscillating magnetic fields with < 1 nT in a phantom study [
24
]. The same research group
tried in vivo studies using the modified SIRS technique, but failed to detect the neuronal
currents in vivo [
24
]. Such failures of in vivo imaging suggest that there are problems other than
the sensitivity of the MR methods.
Understanding the characteristics of neuronal oscillations is crucial for imaging neuronal
activity. Based on this, several factors should be considered for in vivo experiments. First,
neuronal oscillations are faster than the temporal resolution of MRI. Since high frequency
oscillations such as gamma oscillation cannot be sufficiently captured even by a fast technique (e.g.
EPI), previous experiments using EPI mostly focused on slow alpha waves [
19, 25
]. Recently,
signals from non-BOLD sources with frequencies above 0.5 Hz have been investigated with
resting-state fMRI, however, the frequency of interest is still limited [26±32]. When neuronal
oscillations are sampled at a rate insufficient to capture the up/down of the oscillations,
aliasing occurs according to the Nyquist theorem [33]. Therefore, a new analytical strategy is
necessary for evaluating insufficiently sampled data to detect fast neuronal oscillations. Second, a
previous study based on magnetoencephalography (MEG) experiments indicated that the
magnetic fields generated by spon (...truncated)