Realistic simulations of neuronal activity: a contribution to the debate on direct detection of neuronal currents by MRI

Can MRI Be Used as a Sensor to Record Neural Activity?

Magnetic resonance provides exquisite anatomical images and functional MRI monitors physiological activity by recording blood oxygenation. This review attempts to answer the following question: Can MRI be used as a sensor to directly record neural behavior? It considers MRI sensing of electrical activity in the heart and in peripheral nerves before turning to the central topic: recording of brain activity. The primary hypothesis is that bioelectric current produced by a nerve or muscle creates a magnetic field that influences the magnetic resonance signal, although other mechanisms for detection are also considered. Recent studies have provided evidence that using MRI to sense neural activity is possible under ideal conditions. Whether it can be used routinely to provide functional information about brain processes in people remains an open question. The review concludes with a survey of artificial intelligence techniques that have been applied to functional MRI and may be appropriate for MRI sensing of neural activity.

Electric Current Detection Based on the MR Signal Magnitude Decay

Purpose

Conventional current density imaging method, which relies on the detection of the magnetic field induced by the current in an image phase, is demanding and difficult to perform. In this study, a much simpler signal‐magnitude‐decay (SMD)–based current detection method is proposed.

Methods

Conductive test and biological samples were imaged at various TE times using the gradient‐ or spin‐echo imaging sequences with superimposed constant or bipolar currents, respectively. The SMD curve was sampled for each image voxel, which enabled voxel‐vise current density calculation by fitting an appropriate SMD model curve to the measured SMD curve. Effect of the voxel size on the signal decay and precision of the current density calculation was studied as well.

Results

It was shown theoretically, as well as verified by experiments on test and biological samples, that the current flowing though the sample creates an inhomogeneous magnetic field, which, as a consequence has a faster signal decay. Estimated current density from the measured signal decay increase agreed reasonably well with the actual current density, especially with the larger voxel sizes and longer times to signal acquisition. The sensitivity of the SMD method is up to 1/6 the sensitivity of the current density imaging method.

Conclusion

SMD method of current detection is not limited to any particular sample orientation or geometry, and any pulse sequence capable of acquisition of the current‐induced signal evolution in a voxel can be used for it. This widens the scope of its application from tissues to in vivo studies on animals and humans.

Neural magnetic field dependent fMRI toward direct functional connectivity measurements: A phantom study

Recently, the main issue in neuroscience has been the imaging of the functional connectivity in the brain. No modality that can measure functional connectivity directly, however, has been developed yet. Here, we show the novel MRI sequence, called the partial spinlock sequence toward direct measurements of functional connectivity. This study investigates a probable measurement of phase differences directly associated with functional connectivity. By employing partial spinlock imaging, the neural magnetic field might influence the magnetic resonance signals. Using simulation and phantom studies to model the neural magnetic fields, we showed that magnetic resonance signals vary depending on the phase of an externally applied oscillating magnetic field with non-right flip angles. These results suggest that the partial spinlock sequence is a promising modality for functional connectivity measurements.

Feasibility of functional MRI at ultralow magnetic field via changes in cerebral blood volume

We investigate the feasibility of performing functional MRI (fMRI) at ultralow field (ULF) with a Superconducting QUantum Interference Device (SQUID), as used for detecting magnetoencephalography (MEG) signals from the human head. While there is negligible magnetic susceptibility variation to produce blood oxygenation level-dependent (BOLD) contrast at ULF, changes in cerebral blood volume (CBV) may be a sensitive mechanism for fMRI given the five-fold spread in spin-lattice relaxation time (T₁) values across the constituents of the human brain. We undertook simulations of functional signal strength for a simplified brain model involving activation of a primary cortical region in a manner consistent with a blocked task experiment. Our simulations involve measured values of T₁ at ULF and experimental parameters for the performance of an upgraded ULFMRI scanner. Under ideal experimental conditions we predict a functional signal-to-noise ratio of between 3.1 and 7.1 for an imaging time of 30 min, or between 1.5 and 3.5 for a blocked task experiment lasting 7.5 min. Our simulations suggest it may be feasible to perform fMRI using a ULFMRI system designed to perform MRI and MEG in situ.

Functional magnetic resonance electrical impedance tomography (fMREIT) sensitivity analysis using an active bidomain finite-element model of neural tissue

PURPOSE

A direct method of imaging neural activity was simulated to determine typical signal sizes.

METHODS

An active bidomain finite-element model was used to estimate approximate perturbations in MR phase data as a result of neural tissue activity, and when an external MR electrical impedance tomography imaging current was added to the region containing neural current sources.

RESULTS

Modeling-predicted, activity-related conductivity changes should produce measurable differential phase signals in practical MR electrical impedance tomography experiments conducted at moderate resolution at noise levels typical of high field systems. The primary dependence of MR electrical impedance tomography phase contrast on membrane conductivity changes, and not source strength, was demonstrated.

CONCLUSION

Because the injected imaging current may also affect the level of activity in the tissue of interest, this technique can be used synergistically with neuromodulation techniques such as deep brain stimulation, to examine mechanisms of action.

The effect of potassium chloride on Aplysia Californica abdominal ganglion activity

Objective

Spontaneous activity in the abdominal ganglion of Aplysia can be used as a convenient bioelectricity source in tests of novel MRI-based functional imaging methods, such as functional Magnetic Resonance Electrical Impedance Tomography (fMREIT). In these tests, it is necessary to find a consistent treatment that modulates neural activity, so that these results can be compared with control data. Effects of MREIT imaging currents combined with treatment were also of interest.

Approach

Potassium chloride (KCl) was employed as a rhythm modulator. In a series of experiments, effects of adding different volumes of KCl solution were tested and compared with experiments on control groups that had artificial sea water administered. In all cases, neuronal activity was measured with micro electrode arrays.

Main results

It was possible to reversibly stop spontaneous activity in ganglia by increasing the extracellular potassium chloride concentration to 89 mM. There was no effect on experimental outcomes when current was administered to the sample chamber between recordings.

Significance

KCl can be used as a reversible neural modulator for testing neural detection methods.

Direct detection of neural activity in vitro using magnetic resonance electrical impedance tomography (MREIT)

We describe a sequence of experiments performed in vitro to verify the existence of a new magnetic resonance imaging contrast - Magnetic Resonance Electrical Impedance Tomography (MREIT) -sensitive to changes in active membrane conductivity. We compared standard deviations in MREIT phase data from spontaneously active Aplysia abdominal ganglia in an artificial seawater background solution (ASW) with those found after treatment with an excitotoxic solution (KCl). We found significant increases in MREIT treatment cases, compared to control ganglia subject to extra ASW. This distinction was not found in phase images from the same ganglia using no imaging current. Further, significance and effect size depended on the amplitude of MREIT imaging current used. We conclude that our observations were linked to changes in cell conductivity caused by activity. Functional MREIT may have promise as a more direct method of functional neuroimaging than existing methods that image correlates of blood flow such as BOLD fMRI.

Estimation of phase signal change in neuronal current MRI for evoke response of tactile detection with realistic somatosensory laminar network model

Magnetic field generated by neuronal activity could alter magnetic resonance imaging (MRI) signals but detection of such signal is under debate. Previous researches proposed that magnitude signal change is below current detectable level, but phase signal change (PSC) may be measurable with current MRI systems. Optimal imaging parameters like echo time, voxel size and external field direction, could increase the probability of detection of this small signal change. We simulate a voxel of cortical column to determine effect of such parameters on PSC signal. We extended a laminar network model for somatosensory cortex to find neuronal current in each segment of pyramidal neurons (PN). 60,000 PNs of simulated network were positioned randomly in a voxel. Biot-savart law applied to calculate neuronal magnetic field and additional phase. The procedure repeated for eleven neuronal arrangements in the voxel. PSC signal variation with the echo time and voxel size was assessed. The simulated results show that PSC signal increases with echo time, especially 100/80 ms after stimulus for gradient echo/spin echo sequence. It can be up to 0.1 mrad for echo time = 175 ms and voxel size = 1.48 × 1.48 × 2.18 mm(3). With echo time less than 25 ms after stimulus, it was just acquired effects of physiological noise on PSC signal. The absolute value of the signal increased with decrease of voxel size, but its components had complex variation. External field orthogonal to local surface of cortex maximizes the signal. Expected PSC signal for tactile detection in the somatosensory cortex increase with echo time and have no oscillation.

Functionalized anatomical models for EM-neuron Interaction modeling

The understanding of interactions between electromagnetic (EM) fields and nerves are crucial in contexts ranging from therapeutic neurostimulation to low frequency EM exposure safety. To properly consider the impact of in vivo induced field inhomogeneity on non-linear neuronal dynamics, coupled EM-neuronal dynamics modeling is required. For that purpose, novel functionalized computable human phantoms have been developed. Their implementation and the systematic verification of the integrated anisotropic quasi-static EM solver and neuronal dynamics modeling functionality, based on the method of manufactured solutions and numerical reference data, is described. Electric and magnetic stimulation of the ulnar and sciatic nerve were modeled to help understanding a range of controversial issues related to the magnitude and optimal determination of strength-duration (SD) time constants. The results indicate the importance of considering the stimulation-specific inhomogeneous field distributions (especially at tissue interfaces), realistic models of non-linear neuronal dynamics, very short pulses, and suitable SD extrapolation models. These results and the functionalized computable phantom will influence and support the development of safe and effective neuroprosthetic devices and novel electroceuticals. Furthermore they will assist the evaluation of existing low frequency exposure standards for the entire population under all exposure conditions.

Direct neural current imaging in an intact cerebellum with magnetic resonance imaging

The ability to detect neuronal currents with high spatiotemporal resolution using magnetic resonance imaging (MRI) is important for studying human brain function in both health and disease. While significant progress has been made, we still lack evidence showing that it is possible to measure an MR signal time-locked to neuronal currents with a temporal waveform matching concurrently recorded local field potentials (LFPs). Also lacking is evidence that such MR data can be used to image current distribution in active tissue. Since these two results are lacking even in vitro, we obtained these data in an intact isolated whole cerebellum of turtle during slow neuronal activity mediated by metabotropic glutamate receptors using a gradient-echo EPI sequence (TR=100ms) at 4.7T. Our results show that it is possible (1) to reliably detect an MR phase shift time course matching that of the concurrently measured LFP evoked by stimulation of a cerebellar peduncle, (2) to detect the signal in single voxels of 0.1mm(3), (3) to determine the spatial phase map matching the magnetic field distribution predicted by the LFP map, (4) to estimate the distribution of neuronal current in the active tissue from a group-average phase map, and (5) to provide a quantitatively accurate theoretical account of the measured phase shifts. The peak values of the detected MR phase shifts were 0.27-0.37°, corresponding to local magnetic field changes of 0.67-0.93nT (for TE=26ms). Our work provides an empirical basis for future extensions to in vivo imaging of neuronal currents.

Detecting neuronal currents with MRI: a human study

PURPOSE

Recently developed neuronal current magnetic resonance imaging aims to directly detect neuronal currents associated with brain activity, but controversial results have been reported in different studies on human subjects. Although there is no dispute that local neuronal currents produce weak transient magnetic fields that would attenuate local MR signal intensity, there is not yet consensus as to whether this attenuation is detectable with present magnetic resonance imaging techniques. This study investigates the magnitude of neuronal current-induced signal attenuation in human visual cortex.

THEORY

A temporally well-controlled visual stimulation paradigm with a known neuronal firing pattern in monkey visual cortex provides a means of detecting and testing the magnitude of the neuronal current-induced attenuation in neuronal current magnetic resonance imaging.

METHODS

Placing a series of acquisition windows to fully cover the entire response duration enables a thorough detection of any detectable MR signal attenuation induced by the stimulus-evoked neuronal currents.

RESULTS

No significant neuronal current-induced MR signal attenuation was observed in the putative V1 in any participated subjects.

CONCLUSION

The present magnetic resonance imaging technique is not sensitive enough to detect neuronal current-induced MR signal attenuation, and the upper limit of this attenuation was found to be less than 0.07% under the study condition.

Modeling the effect of dendritic input location on MEG and EEG source dipoles

The cerebral sources of magneto- and electroencephalography (MEG, EEG) signals can be represented by current dipoles. We used computational modeling of realistically shaped passive-membrane dendritic trees of pyramidal cells from the human cerebral cortex to examine how the spatial distribution of the synaptic inputs affects the current dipole. The magnitude of the total dipole moment vector was found to be proportional to the vertical location of the synaptic input. The dipole moment had opposite directions for inputs above and below a reversal point located near the soma. Inclusion of shunting-type inhibition either suppressed or enhanced the current dipole, depending on whether the excitatory and inhibitory synapses were on the same or opposite side of the reversal point. Relating the properties of the macroscopic current dipoles to dendritic current distributions can help to provide means for interpreting MEG and EEG data in terms of synaptic connection patterns within cortical areas.

Computational Modeling of Neuronal Current MRI Signals with Rat Somatosensory Cortical Neurons

Magnetic field generated by active neurons has recently been considered to determine location of neuronal activity directly with magnetic resonance imaging (MRI), but controversial results have been reported about detection of such small magnetic fields. In this study, multiple neuronal morphologies of rat tissue were modeled to investigate better estimation of MRI signal change produced by neuronal magnetic field (NMF). Ten pyramidal neurons from layer II to VI of rat somatosensory area with realistic morphology, biophysics, and neuronal density were modeled to simulate NMF of neuronal tissue, from which effects of NMF on MRI signals were obtained. Neuronal current MRI signals, which consist of relative magnitude signal change (RMSC) and phase signal change (PSC), were at least three and one orders of magnitude less than a tissue with single neuron type, respectively. Also, a reduction in voxel size could increase signal alterations. Furthermore, with selection of zenith angle of external main magnetic field related to tissue surface near to 90°, RMSC could be maximized. This value for PSC would be 90° for small voxel size and zero degree for large ones.

Magnetic resonance imaging of ionic currents in solution: the effect of magnetohydrodynamic flow

PURPOSE

Reliably detecting MRI signals in the brain that are more tightly coupled to neural activity than blood-oxygen-level-dependent fMRI signals could not only prove valuable for basic scientific research but could also enhance clinical applications such as epilepsy presurgical mapping. This endeavor will likely benefit from an improved understanding of the behavior of ionic currents, the mediators of neural activity, in the presence of the strong magnetic fields that are typical of modern-day MRI scanners.

THEORY

Of the various mechanisms that have been proposed to explain the behavior of ionic volume currents in a magnetic field, only one-magnetohydrodynamic flow-predicts a slow evolution of signals, on the order of a minute for normal saline in a typical MRI scanner.

METHODS

This prediction was tested by scanning a volume-current phantom containing normal saline with gradient-echo-planar imaging at 3 T.

RESULTS

Greater signal changes were observed in the phase of the images than in the magnitude, with the changes evolving on the order of a minute.

CONCLUSION

These results provide experimental support for the MHD flow hypothesis. Furthermore, MHD-driven cerebrospinal fluid flow could provide a novel fMRI contrast mechanism.

Generalized cable formalism to calculate the magnetic field of single neurons and neuronal populations

Neurons generate magnetic fields which can be recorded with macroscopic techniques such as magnetoencephalography. The theory that accounts for the genesis of neuronal magnetic fields involves dendritic cable structures in homogeneous resistive extracellular media. Here we generalize this model by considering dendritic cables in extracellular media with arbitrarily complex electric properties. This method is based on a multiscale mean-field theory where the neuron is considered in interaction with a "mean" extracellular medium (characterized by a specific impedance). We first show that, as expected, the generalized cable equation and the standard cable generate magnetic fields that mostly depend on the axial current in the cable, with a moderate contribution of extracellular currents. Less expected, we also show that the nature of the extracellular and intracellular media influence the axial current, and thus also influence neuronal magnetic fields. We illustrate these properties by numerical simulations and suggest experiments to test these findings.

MRI signal phase oscillates with neuronal activity in cerebral cortex: implications for neuronal current imaging

Neuronal activity produces transient ionic currents that may be detectable using magnetic resonance imaging (MRI). We examined the feasibility of MRI-based detection of neuronal currents using computer simulations based on the laminar cortex model (LCM). Instead of simulating the activity of single neurons, we decomposed neuronal activity to action potentials (AP) and postsynaptic potentials (PSP). The geometries of dendrites and axons were generated dynamically to account for diverse neuronal morphologies. Magnetic fields associated with APs and PSPs were calculated during spontaneous and stimulated cortical activity, from which the neuronal current induced MRI signal was determined. We found that the MRI signal magnitude change (<0.1 ppm) is below currently detectable levels but that the signal phase change is likely to be detectable. Furthermore, neuronal MRI signals are sensitive to temporal and spatial variations in neuronal activity but independent of the intensity of neuronal activation. Synchronised neuronal activity produces large phase changes (in the order of 0.1 mrad). However, signal phase oscillates with neuronal activity. Consequently, MRI scans need to be synchronised with neuronal oscillations to maximise the likelihood of detecting signal phase changes due to neuronal currents. These findings inform the design of MRI experiments to detect neuronal currents.

Octopus visual system: a functional MRI model for detecting neuronal electric currents without a blood-oxygen-level-dependent confound

PURPOSE

Despite the efforts that have been devoted to detecting the transient magnetic fields generated by neuronal firing, the conclusion that a functionally relevant signal can be measured with MRI is still controversial. For human studies of neuronal current MRI (nc-MRI), the blood-oxygen-level-dependent (BOLD) effect remains an irresolvable confound. For tissue studies where hemoglobin is removed, natural sensory stimulation is not possible. This study investigates the feasibility of detecting a physiologically induced nc-MRI signal in vivo in a BOLD-free environment.

METHODS

The cephalopod mollusc Octopus bimaculoides has vertebrate-like eyes, large optic lobes (OLs), and blood that does not contain hemoglobin. Visually evoked potentials were measured in the octopus retina and OL by electroretinogram and local field potential. nc-MRI scans were conducted at 9.4 Tesla to capture these activities.

RESULTS

Electrophysiological recording detected strong responses in the retina and OL in vivo; however, nc-MRI failed to demonstrate any statistically significant signal change with a detection threshold of 0.2° for phase and 0.2% for magnitude. Experiments in a dissected eye-OL preparation yielded similar results.

CONCLUSION

These findings in a large hemoglobin-free nervous system suggest that sensory evoked neuronal magnetic fields are too weak for direct detection with current MRI technology.

Bloch simulations towards direct detection of oscillating magnetic fields using MRI with spin-lock sequence

A new MRI method using the spin-lock sequence has attracted wide attention because of its potential for detecting small oscillating magnetic fields. However, as the mechanism involved is complicated, we visualized the magnetization performance during the spin-lock sequence in order to better understand interaction of the spin-lock pulse and the externally applied oscillating magnetic fields by means of a fast-and-simple method using matrix operations to solve a time-dependent Bloch equation. To improve spin-lock imaging in the detection of small magnetic fields (in an fMRI experiment that modeled neural magnetic fields), we observed that the phenomenon decreases MR signals, which led us to investigate how spin-lock parameters cause the MR signal to decrease; based on this, we determined that MR signals decrease in oscillating magnetic fields that are resonant with the spin-lock pulse. We also determined that MR signals decrease is directly proportional to spin-lock duration. Our results suggest that MRI can feasibly detect oscillating magnetic fields directly by using of the spin-lock sequence.

Is it possible to detect dendrite currents using presently available magnetic resonance imaging techniques?

The action currents of a dendrite, peripheral nerve or skeletal muscle create their own magnetic field. Many investigators have attempted to detect neural and dendritic currents directly using magnetic resonance imaging that can cause the phase of the spins to change. Our goal in this paper is to use the calculated magnetic field of a dendrite to estimate the resulting phase shift in the magnetic resonance signal. The field produced by a dense collection of simultaneously active dendrites may be just detectable under the most ideal circumstances, but in almost every realistic case the field cannot be detected using current MRI technology.

Direct detection of a single evoked action potential with MRS in Lumbricus terrestris

Functional MRI (fMRI) measures neural activity indirectly by detecting the signal change associated with the hemodynamic response following brain activation. In order to alleviate the temporal and spatial specificity problems associated with fMRI, a number of attempts have been made to detect neural magnetic fields (NMFs) with MRI directly, but have thus far provided conflicting results. In this study, we used MR to detect axonal NMFs in the median giant fiber of the earthworm, Lumbricus terrestris, by examining the free induction decay (FID) with a sampling interval of 0.32 ms. The earthworm nerve cords were isolated from the vasculature and stimulated at the threshold of action potential generation. FIDs were acquired shortly after the stimulation, and simultaneous field potential recordings identified the presence or absence of single evoked action potentials. FIDs acquired when the stimulus did not evoke an action potential were summed as background. The phase of the background-subtracted FID exhibited a systematic change, with a peak phase difference of (-1.2 ± 0.3) × 10(-5) radians occurring at a time corresponding to the timing of the action potential. In addition, we calculated the possible changes in the FID magnitude and phase caused by a simulated action potential using a volume conductor model. The measured phase difference matched the theoretical prediction well in both amplitude and temporal characteristics. This study provides the first evidence for the direct detection of a magnetic field from an evoked action potential using MR.

Phase stability in fMRI time series: effect of noise regression, off-resonance correction and spatial filtering techniques

Although the majority of fMRI studies exploit magnitude changes only, there is an increasing interest regarding the potential additive information conveyed by the phase signal. This integrated part of the complex number furnished by the MR scanners can also be used for exploring direct detection of neuronal activity and for thermography. Few studies have explicitly addressed the issue of the available signal stability in the context of phase time-series, and therefore we explored the spatial pattern of frequency specific phase fluctuations, and evaluated the effect of physiological noise components (heart beat and respiration) on the phase signal. Three categories of retrospective noise reduction techniques were explored and the temporal signal stability was evaluated in terms of a physiologic noise model, for seven fMRI measurement protocols in eight healthy subjects at 3T, for segmented CSF, gray and white matter voxels. We confirmed that for most processing methods, an efficient use of the phase information is hampered by the fact that noise from physiological and instrumental sources contributes significantly more to the phase than to the magnitude instability. Noise regression based on the phase evolution of the central k-space point, RETROICOR, or an orthonormalized combination of these were able to reduce their impact, but without bringing phase stability down to levels expected from the magnitude signal. Similar results were obtained after targeted removal of scan-to-scan variations in the bulk magnetic field by the dynamic off-resonance in k-space (DORK) method and by the temporal off-resonance alignment of single-echo time series technique (TOAST). We found that spatial high-pass filtering was necessary, and in vivo a Gaussian filter width of 20mm was sufficient to suppress physiological noise and bring the phase fluctuations to magnitude levels. Stronger filters brought the fluctuations down to levels dictated by thermal noise contributions, and for 62.5mm(3) voxels the phase stability was as low as 5 mrad (0.27°). In conditions of low SNR(o) and high temporal sampling rate (short TR); we achieved an upper bound for the phase instabilities at 0.0017 ppm, which is close to the dHb contribution to the GM/WM phase contrast.

Are brain currents detectable by means of low-field NMR? A phantom study

A number of different methods have been developed in order to detect the spreading of neuronal currents by means of noninvasive imaging techniques. However, all of these are subjected to limitations in the temporal or spatial resolution. A new approach of neuronal current detection is based on the use of low-field nuclear magnetic resonance (LF-NMR) that records brain activity directly. In the following, we describe a phantom study in order to assess the feasibility of neuronal current detection using LF-NMR. In addition to that, necessary preliminary subject studies examining somatosensory evoked neuronal currents are presented. During the phantom study, the influences of two different neuronal time signals on (1)H-NMR signals were observed. The measurements were carried out by using a head phantom with an integrated current dipole to simulate neuronal activity. Two LF-NMR methods based on a DC and an AC (resonant) mechanism were utilized to study the feasibility of detecting both types of magnetic brain signals. Measurements were made inside an extremely magnetically shielded room by using a superconducting quantum interference device magnetometer system. The measurement principles were validated applying currents of higher intensity than those typical of the neuronal currents. Through stepwise reduction of the amplitude of the current dipole strength, the resolution limits of the two measuring procedures were found. The results indicate that it is necessary to improve the signal-to-noise ratio of the measurement system by at least a factor of 38 in order to detect typical human neuronal activity directly by means of LF-NMR. In addition to that, ways of achieving this factor are discussed.

On multiple alternating steady states induced by periodic spin phase perturbation waveforms

Direct measurement of neural currents by means of MRI can potentially open a high temporal resolution (10-100 ms) window applicable for monitoring dynamics of neuronal activity without loss of the high spatial resolution afforded by MRI. Previously, we have shown that the alternating balanced steady state imaging affords high sensitivity to weak periodic currents owing to its amplification of periodic spin phase perturbations. This technique, however, requires precise synchronization of such perturbations to the radiofrequency pulses. Herein, we extend alternating balanced steady state imaging to multiple balanced alternating steady states for estimation of neural current waveforms. Simulations and phantom experiments show that the off-resonance profile of the multiple alternating steady state signal carries information about the frequency content of driving waveforms. In addition, the method is less sensitive than alternating balanced steady state to precise waveform timing relative to radiofrequency pulses. Thus, multiple alternating steady state technique is potentially applicable to MR imaging of the waveforms of periodic neuronal activity.

Modeling magnitude and phase neuronal current MRI signal dependence on echo time

To enhance sensitivity in measuring neuronal current MRI (ncMRI) signal using T(2)*-weighted sequences, appropriate selection of echo time (TE) is vital for optimizing data acquisition strategy. The purpose of this study is to establish the contrast-to-noise ratio of neuronal current MRI signal dependence on TE and determine the optimum TE (TE(opt)) in achieving its highest detection power. The TE(opt) in human brain and tissue preparation at 1.5, 3, and 7 T are estimated with different voxel sizes. Our results show that TE(opt) values are different between magnitude and phase images, and TE(opt) is larger in magnitude than phase imaging. This suggests that a dual-echo data acquisition strategy would provide the best efficiency in detecting magnitude and phase neuronal current MRI signals simultaneously. Our results also indicated that the detection sensitivity will be stronger at lower magnetic fields for human brain, whereas the sensitivity will be enhanced/reduced as field strength increases for phase/magnitude imaging on tissue preparation.

Detection of neuronal current MRI in human without BOLD contamination

Controversial results regarding the detectability of neuronal current magnetic resonance imaging (ncMRI) have been reported in different studies on human subjects. In all the previous studies, the ncMRI signal was detected under a continuous and paradigm task-induced blood oxygen level dependent (BOLD) signal background. The aim of this study is to investigate the possibility of detecting ncMRI signal in human brain in the situation that task-induced BOLD background is absent or minimum. In this study, by adopting an event-related visuomotor paradigm with long interstimulus interval (=20 s), the ncMRI signal was detected when the BOLD signal fully returned to its baseline, and the potential BOLD background contamination was avoided effectively. The results showed that the visuomotor stimulation elicited BOLD activation in visual and motor cortices, but no significant ncMRI signal change (in magnitude) was detected in human brain. These experimental findings are consistent with theoretical predications.

Modeling neuronal current MRI signal with human neuron

Up to date, no consensus has been achieved regarding the possibility of detecting neuronal currents by MRI (ncMRI) in human brain. To evaluate the detectability of ncMRI, an effective way is to simulate ncMRI signal with the realistic neuronal geometry and electrophysiological processes. Unfortunately, previous realistic ncMRI models are based on rat and monkey neurons. The species difference in neuronal morphology and physiology would prevent these models from simulating the ncMRI signal accurately in human subjects. The aim of this study is to bridge this gap by establishing a realistic ncMRI model specifically for human cerebral cortex. In this model, the ncMRI signal was simulated using anatomically reconstructed human pyramidal neurons and their biophysical properties. The modeling results showed that the amplitude of ncMRI signal significantly depends on the density of synchronously firing neurons and imaging conditions such as position of imaging voxel, direction of main magnetic field (B(0) ) relative to the cortical surface and echo time. The results indicated that physiologically-evoked ncMRI signal is too weak to be detected (magnitude/phase change ≤ -1.4 × 10(-6) /0.02°), but the phase signal induced by spontaneous activity may reach a detectable level (up to 0.2°) in favorable conditions.

Direct MRI detection of the neuronal magnetic field: the effect of the dendrite branch

In recent years, neuronal current MRI (nc-MRI) was proposed as a new imaging method to directly map the magnetic field change caused by neuronal activity. Nc-MRI could offer improved spatial and temporal resolution compared to blood hemodynamics-based functional magnetic resonance imaging (fMRI). In this paper, with a finite current dipole as the model of dendrite or dendrite branch, we investigated the spatial distribution of the magnetic field generated by synchronously activated neurons to evaluate the possibility of nc-MRI. Our simulations imply that the existence of a dendrite branch may not only increase the strength of the neuronal magnetic field (NMF), but also raise the non-uniform and unsymmetry of the NMF; therefore, it can enhance the detectability of the neuronal current magnetic field by MRI directly. The results show that the signal phase shift is enlarged, but it is unstable and is still very small, <<1 radian, while the magnitude signal may be strong enough for a typical MRI voxel to be detected. We suggest making further efforts to measure the magnitude signal which may induce a large effect in an nc-MRI experiment.

Magnetic resonance imaging of oscillating electrical currents

Functional MRI has become an important tool of researchers and clinicians who seek to understand patterns of neuronal activation that accompany sensory and cognitive processes. However, the interpretation of fMRI images rests on assumptions about the relationship between neuronal firing and hemodynamic response that are not firmly grounded in rigorous theory or experimental evidence. Further, the blood-oxygen-level-dependent effect, which correlates an MRI observable to neuronal firing, evolves over a period that is 2 orders of magnitude longer than the underlying processes that are thought to cause it. Here, we instead demonstrate experiments to directly image oscillating currents by MRI. The approach rests on a resonant interaction between an applied rf field and an oscillating magnetic field in the sample and, as such, permits quantitative, frequency-selective measurements of current density without spatial or temporal cancellation. We apply this method in a current loop phantom, mapping its magnetic field and achieving a detection sensitivity near the threshold required for the detection of neuronal currents. Because the contrast mechanism is under spectroscopic control, we are able to demonstrate how ramped and phase-modulated spin-lock radiation can enhance the sensitivity and robustness of the experiment. We further demonstrate the combination of these methods with remote detection, a technique in which the encoding and detection of an MRI experiment are separated by sample flow or translation. We illustrate that remotely detected MRI permits the measurement of currents in small volumes of flowing water with high sensitivity and spatial resolution.

Simulating the effects of time-varying magnetic fields with a realistic simulated scanner

Transient magnetic fields induce changes in magnetic resonance (MR) images ranging from small, visually undetectable effects (caused, for instance, by neuronal currents) to more significant ones, such as those created by the gradient fields and eddy currents. Accurately simulating these effects may assist in correcting or optimising MR imaging for many applications (e.g., diffusion imaging, current density imaging, use of magnetic contrast agents, neuronal current imaging, etc.). Here we have extended an existing MR simulator (POSSUM) with a model for changing magnetic fields at a very high-resolution time-scale. This simulator captures a realistic range of scanner and physiological artifacts by modeling the scanner environment, pulse sequence details and subject properties (e.g., brain geometry and air-tissue boundaries). The simulations were validated by using previously published experimental data sets. In the first dataset a transient magnetic field was produced by a single conducting wire with varying current amplitude (between 17 muA and 765 muA). The second was identical except that current amplitude was fixed (at 7.8 mA) and current timing varied. A very close match between simulated images and experimental data was observed. In addition, these validation results led to the observation that the current-induced effects included ringing in the image, which extended away from the conductor, primarily in the phase-encode direction. This effect had previously not been noticed in the noisy, experimentally-acquired images, demonstrating one way in which simulated images can provide potential insight into imaging experiments.

Can high-field MREIT be used to directly detect neural activity? Theoretical considerations

We sought to determine the feasibility of directly studying neural tissue activity by analysis of differential phase shifts in MRI signals that occurred when trickle currents were applied to a bath containing active or resting neural tissue. We developed a finite element bidomain model of an aplysia abdominal ganglion in order to estimate the sensitivity of this contrast mechanism to changes in cell membrane conductance occurring during a gill-withdrawal reflex. We used our model to determine both current density and magnetic potential distributions within a sample chamber containing an isolated ganglion when it was illuminated with current injected synchronously with the MR imaging sequence and predicted the resulting changes in MRI phase images. This study provides the groundwork for attempts to image neural function using Magnetic Resonance Electrical Impedance Tomography (MREIT). We found that phase noise in a candidate 17.6 T MRI system should be sufficiently low to detect phase signal differences between active and resting membrane states at resolutions around 1 mm(3). We further delineate the broad dependencies of signal-to-noise ratio on activity frequency, current application time and active tissue fractions and outline strategies that can be used to lower phase noise below that presently observed in conventional MREIT techniques. We also propose the idea of using MREIT as an alternative means of studying neuromodulation.

Magnetic measurements of peripheral nerve function using a neuromagnetic current probe

The progress made during the last three decades in mathematical modeling and technology development for the recording of magnetic fields associated with cellular current flow in biological tissues has provided a means of examining action currents more accurately than that of using traditional electrical recordings. It is well known to the biomedical research community that the room-temperature miniature toroidal pickup coil called the neuromagnetic current probe can be employed to measure biologically generated magnetic fields in nerve and muscle fibers. In contrast to the magnetic resonance imaging technique, which relies on the interaction between an externally applied magnetic field and the magnetic properties of individual atomic nuclei, this device, along with its room-temperature, low-noise amplifier, can detect currents in the nano-Ampere range. The recorded magnetic signals using neuromagnetic current probes are relatively insensitive to muscle movement since these probes are not directly connected to the tissue, and distortions of the recorded data due to changes in the electrochemical interface between the probes and the tissue are minimal. Contrary to the methods used in electric recordings, these probes can be employed to measure action currents of tissues while they are lying in their own natural settings or in saline baths, thereby reducing the risk associated with elevating and drying the tissue in the air during experiments. This review primarily describes the investigations performed on peripheral nerves using the neuromagnetic current probe. Since there are relatively few publications on these topics, a comprehensive review of the field is given. First, magnetic field measurements of isolated nerve axons and muscle fibers are described. One of the important applications of the neuromagnetic current probe to the intraoperative assessment of damaged and reconstructed nerve bundles is summarized. The magnetic signals of crushed nerve axons and the determination of the conduction velocity distribution of nerve bundles are also reviewed. Finally, the capabilities and limitations of the probe and the magnetic recordings are discussed.

Looking for neuronal currents using MRI: an EEG-fMRI investigation of fast MR signal changes time-locked to frequent focal epileptic discharges

RATIONALE

Reproducible direct measurement of neuronal electrical activity using MRI signal changes due to local magnetic field perturbations would represent a step change in neuroimaging methods. While some previous studies using experiments based on evoked and spontaneous activity provided encouraging results no clear demonstration of neuronal current-related MR changes in the human brain has emerged to date. The availability of simultaneously acquired EEG-fMRI in patients with frequent interictal epileptic discharges (IED), which have significantly greater amplitude than evoked potentials, offers the opportunity to further investigate the phenomenon.

METHODS

We re-analysed simultaneously acquired EEG-fMRI data in 6 epilepsy patients with very frequent focal IED and a well-localised generator. A model of MRI signal changes due to fast activity and BOLD signal changes was used to identify fast MR signal changes, potentially directly reflecting neuronal activity. Simultaneously-acquired EEG allowed the comparison of electrical source localisation (ESI), clinical epilepsy localisation and BOLD signal changes with the fast MR signal changes.

RESULTS

Clusters of IED-related fast MR signal change were observed in all cases. Spatial correspondence between the IED-related fast MR, BOLD, ESI clusters and irritative zone (IZ) was observed in one slice of a single dataset. The other IED-related fast MR clusters were remote from electro-clinically determined generators of interictal activity. The sign and magnitude of the fast MR signal changes varied across regions and subjects.

CONCLUSION

The observed fast MR changes cannot be confidently attributed to the direct effect of neuronal currents due to lack of spatial concordance with generators of interictal activity, IED-related BOLD clusters and ESI estimates.

Effect of peripheral nerve action currents on magnetic resonance imaging

Many researchers have attempted to detect neural currents directly using magnetic resonance imaging (MRI). The action currents of a peripheral nerve create their own magnetic field that can cause the phase of the spins to change. Our goal in this paper is to use the measured magnetic field of a nerve to estimate the resulting phase shift in the magnetic resonance signal. We examine three cases: the squid giant axon, the frog sciatic nerve, and the human median nerve. In each case, the phase shift is much less than one degree, and will be very difficult to measure with current technology.

Direct MRI mapping of neuronal activity evoked by electrical stimulation of the median nerve at the right wrist

Magnetic source MRI (msMRI) has being developed recently for direct detections of neuronal magnetic fields to map brain activity. However, controversial results have been reported by different research groups. In this study, more evidence was provided to demonstrate that the neuronal current signal could be detected by MRI using a rapid median nerve stimulation paradigm. The experiments were performed on six normal human participants to investigate the temporal specificity of the effect, as well as inter- and intrasubject reproducibility. Significant activation of contralateral primary sensory cortex (S1) was detected 80 ms after stimulation onset (corresponding to the P80 evoked potential peak). The 80-ms latency S1 activation was observed over three independent sessions for one subject and for all six participants. The magnitude of the signal change was 0.2-0.3%. Coinciding with our expectations, no S1 activation was found when MRI data acquisitions were targeted at the N20 and P30 peaks because of mutual cancellation of magnetic fields generated by those peaks. The results demonstrated good reproducibility of S1 activations and indicated that the S1 activations most likely originated from neuronal magnetic field rather than hemodynamic response.

Detection of peripheral nerve and skeletal muscle action currents using magnetic resonance imaging

Many researchers have attempted to detect neural currents directly using magnetic resonance imaging (MRI). The action currents of a peripheral nerve or skeletal muscle create their own magnetic field that can cause the phase of the spins to change. Our goal in this paper is to use the measured magnetic field of a nerve or muscle to estimate the resulting phase shift in the magnetic resonance signal. We examine four cases: the squid giant axon, the frog sciatic nerve, the human median nerve, and the rat EDL muscle. In each case, the phase shift is much less than one tenth of one degree, and will be very difficult to measure with current technology.

Physiologically evoked neuronal current MRI in a bloodless turtle brain: detectable or not?

Contradictory reports regarding the detection of neuronal currents have left the feasibility of neuronal current MRI (ncMRI) an open question. Most previous ncMRI studies in human subjects are suspect due to their inability to separate or eliminate hemodynamic effects. In this study, we used a bloodless turtle brain preparation that eliminates hemodynamic effects, to explore the feasibility of detecting visually-evoked ncMRI signals at 9.4 T. Intact turtle brains, with eyes attached, were dissected from the cranium and placed in artificial cerebral spinal fluid. Light flashes were delivered to the eyes to evoke neuronal activity. Local field potential (LFP) and MRI signals were measured in an interleaved fashion. Robust visually-evoked LFP signals were observed in turtle brains, but no significant signal changes synchronized with neuronal currents were found in the ncMRI images. In this study, detection thresholds of 0.1% and 0.1 degrees were set for MRI magnitude and phase signal changes, respectively. The absence of significant signal changes in the MRI images suggests that visually-evoked ncMRI signals in the turtle brain are below these detectable levels.

What's new in neuroimaging methods?

The rapid advancement of neuroimaging methodology and its growing availability has transformed neuroscience research. The answers to many questions that we ask about how the brain is organized depend on the quality of data that we are able to obtain about the locations, dynamics, fluctuations, magnitudes, and types of brain activity and structural changes. In this review an attempt is made to take a snapshot of the cutting edge of a small component of the very rapidly evolving field of neuroimaging. For each area covered, a brief context is provided along with a summary of a few of the current developments and issues. Then, several outstanding papers, published in the past year or so, are described, providing an example of the directions in which each area is progressing. The areas covered include functional magnetic resonance imaging (fMRI), voxel-based morphometry (VBM), diffusion tensor imaging (DTI), electroencephalography (EEG), magnetoencephalography (MEG), optical imaging, and positron emission tomography (PET). More detail is included on fMRI; its subsections include fMRI interpretation, new fMRI contrasts, MRI technology, MRI paradigms and processing, and endogenous oscillations in fMRI.

Neuronal current detection with low-field magnetic resonance: simulations and methods

The noninvasive detection of neuronal currents in active brain networks [or direct neuronal imaging (DNI)] by means of nuclear magnetic resonance (NMR) remains a scientific challenge. Many different attempts using NMR scanners with magnetic fields >1 T (high-field NMR) have been made in the past years to detect phase shifts or magnitude changes in the NMR signals. However, the many physiological (i.e., the contemporarily BOLD effect, the weakness of the neuronal-induced magnetic field, etc.) and technical limitations (e.g., the spatial resolution) in observing the weak signals have led to some contradicting results. In contrast, only a few attempts have been made using low-field NMR techniques. As such, this paper was aimed at reviewing two recent developments in this front. The detection schemes discussed in this manuscript, the resonant mechanism (RM) and the DC method, are specific to NMR instrumentations with main fields below the earth magnetic field (50 microT), while some even below a few microteslas (ULF-NMR). However, the experimental validation for both techniques, with differentiating sensitivity to the various neuronal activities at specific temporal and spatial resolutions, is still in progress and requires carefully designed magnetic field sensor technology. Additional care should be taken to ensure a stringent magnetic shield from the ambient magnetic field fluctuations. In this review, we discuss the characteristics and prospect of these two methods in detecting neuronal currents, along with the technical requirements on the instrumentation.

The effect of physiological noise in phase functional magnetic resonance imaging: from blood oxygen level-dependent effects to direct detection of neuronal currents

Recently, the possibility to use both magnitude and phase image sets for the statistical evaluation of fMRI has been proposed, with the prospective of increasing both statistical power and the spatial specificity. In the present work, several issues that affect the spatial and temporal stability in fMRI phase time series in the presence of physiologic noise processes are reviewed, discussed and illustrated by experiments performed at 3 T. The observed phase value is a fingerprint of the underlying voxel averaged magnetic field variations. Those related to physiological processes can be considered static or dynamic in relation to the temporal scale of a 2D acquisition and will play out on different spatial scales as well: globally across the entire images slice, and locally depending on the constituents and their relative fractions inside the MRI voxel. The 'static' respiration-induced effects lead to magneto-mechanic scan-to-scan variations in the global magnetic field but may also contribute to local BOLD fluctuations due to respiration-related variations in arterial carbon dioxide. Likewise, the 'dynamic' cardiac-related effects will lead to global susceptibility effects caused by pulsatile motion of the brain as well as local blood pressure-related changes in BOLD and changes in blood flow velocity. Finally, subject motion may lead to variations in both local and global tissue susceptibility that will be especially pronounced close to air cavities. Since dissimilar manifestations of physiological processes can be expected in phase and in magnitude images, a direct relationship between phase and magnitude scan-to-scan fluctuations cannot be assumed a priori. Therefore three different models were defined for the phase stability, each dependent on the relation between phase and magnitude variations and the best will depend on the underlying noise processes. By experiments on healthy volunteers at rest, we showed that phase stability depends on the type of post-processing and can be improved by reducing the low-frequency respiration-induced mechano-magnetic effects. Although the manifestations of physiological noise were in general more pronounced in phase than in magnitude images, due to phase wraps and global Bo effects, we suggest that a phase stability similar to that found in magnitude could theoretically be achieved by adequate correction methods. Moreover, as suggested by our experimental data regarding BOLD-related phase effects, phase stability could even supersede magnitude stability in voxels covering dense microvascular networks with BOLD-related fluctuations as the dominant noise contributor. In the interest of the quality of both BOLD-based and nc-MRI methods, future studies are required to find alternative methods that can improve phase stability, designed to match the temporal and spatial scale of the underlying neuronal activity.

Microscopic investigation of the resonant mechanism for the implementation of nc-MRI at ultra-low field MRI

In this paper the possible use of the resonant mechanism between some spectral components of the neuronal activity and the spin dynamics in ultra-low field MRI experiments--for the implementation of the nc-MRI techniques and proposed by Kraus et al., 2008--is investigated by means of "realistic" simulations of the neuronal activity of a modelled neuronal network. Previously characterized digital neurons are used to reproduce neuronal currents based on biophysical details and the distribution of the local magnetic field inside a MRI cubic voxel (having a dimension of 1.2 mm) is evaluated. The properties of the water proton spin dynamics as a consequence of the neuronal field and of external applied fields are extrapolated integrating the Bloch equations. The characteristics of the expected MR signals are discussed in relation to the specifics of the NMR sequence used and to the properties of the neuronal activity. The great potentialities of the technique are provided by: a) the possible easy implementation of the technique, b) the possible cheap instrumentation required; c) the flexibility of the ultra-low field systems.