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

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.

Detection of tiny oscillatory magnetic fields using low-field MRI: A combined phantom and simulation study

We demonstrated the feasibility of the spin-lock preparation sequence using low-field magnetic resonance (MR) imaging that prevents interference from blood-oxygenation-level-dependent effects. We focused on two spin-lock preparations: spin-lock Mz (SL-Mz) and stimulus-induced rotary saturation (SIRS) and analyzed the magnetization dynamics during the sequences using the Bloch equation. Next, we performed phantom experiments using a loop coil to investigate the MR signal change as a function of the target signal strength and phase. Furthermore, we performed curve fittings to consider the radio frequency, which agreed with the experimental results. Then, we investigated the detectable strength of the magnetic field, and the SL-Mz detected a signal strength of 2.34 nT. In conclusion, our experimental results showed good agreement with the results obtained using the Bloch equation.

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.

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.

The movement of a nerve in a magnetic field: application to MRI Lorentz effect imaging

Direct detection of neural activity with MRI would be a breakthrough innovation in brain imaging. A Lorentz force method has been proposed to image nerve activity using MRI; a force between the action currents and the static MRI magnetic field causes the nerve to move. In the presence of a magnetic field gradient, this will cause the spins to precess at a different frequency, affecting the MRI signal. Previous mathematical modeling suggests that this effect is too small to explain the experimental data, but that model was limited because the action currents were assumed to be independent of position along the nerve and because the magnetic field was assumed to be perpendicular to the nerve. In this paper, we calculate the nerve displacement analytically without these two assumptions. Using realistic parameter values, the nerve motion is <5 nm, which induced a phase shift in the MRI signal of <0.02°. Therefore, our results suggest that Lorentz force imaging is beyond the capabilities of current technology.

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.

On consciousness, resting state fMRI, and neurodynamics

BACKGROUND

During the last years, functional magnetic resonance imaging (fMRI) of the brain has been introduced as a new tool to measure consciousness, both in a clinical setting and in a basic neurocognitive research. Moreover, advanced mathematical methods and theories have arrived the field of fMRI (e.g. computational neuroimaging), and functional and structural brain connectivity can now be assessed non-invasively.

RESULTS

The present work deals with a pluralistic approach to "consciousness'', where we connect theory and tools from three quite different disciplines: (1) philosophy of mind (emergentism and global workspace theory), (2) functional neuroimaging acquisitions, and (3) theory of deterministic and statistical neurodynamics - in particular the Wilson-Cowan model and stochastic resonance.

CONCLUSIONS

Based on recent experimental and theoretical work, we believe that the study of large-scale neuronal processes (activity fluctuations, state transitions) that goes on in the living human brain while examined with functional MRI during "resting state", can deepen our understanding of graded consciousness in a clinical setting, and clarify the concept of "consiousness" in neurocognitive and neurophilosophy research.