Direct magnetic resonance detection of neuronal electrical activity

Functional conductivity imaging: quantitative mapping of brain activity

Theory and modelling suggest that detection of neuronal activity may be feasible using phase sensitive MRI methods. Successful detection of neuronal activity both in vitro and in vivo has been described while others have reported negative results. Magnetic resonance electrical properties tomography may be a route by which signal changes can be identified. Here, we report successful and repeatable detection at 3 Tesla of human brain activation in response to visual and somatosensory stimuli using a functional version of tissue conductivity imaging (funCI). This detects activation in both white and grey matter with apparent tissue conductivity changes of 0.1 S/m (17-20%, depending on the tissue baseline conductivity measure) allowing visualization of complete system circuitry. The degree of activation scales with the degree of the stimulus (duration or contrast). The conductivity response functions show a distinct timecourse from that of traditional fMRI haemodynamic (BOLD or Blood Oxygenation Level Dependent) response functions, peaking within milliseconds of stimulus cessation and returning to baseline within 3-4 s. We demonstrate the utility of the funCI approach by showing robust activation of the lateral somatosensory circuitry on stimulation of an index finger, on stimulation of a big toe or of noxious (heat) stimulation of the face as well as activation of visual circuitry on visual stimulation in up to five different individuals. The sensitivity and repeatability of this approach provides further evidence that magnetic resonance imaging approaches can detect brain activation beyond changes in blood supply.

A fully Bayesian approach for comprehensive mapping of magnitude and phase brain activation in complex-valued fMRI data

Functional magnetic resonance imaging (fMRI) plays a crucial role in neuroimaging, enabling the exploration of brain activity through complex-valued signals. These signals, composed of magnitude and phase, offer a rich source of information for understanding brain functions. Traditional fMRI analyses have largely focused on magnitude information, often overlooking the potential insights offered by phase data. In this paper, we propose a novel fully Bayesian model designed for analyzing single-subject complex-valued fMRI (cv-fMRI) data. Our model, which we refer to as the CV-M&P model, is distinctive in its comprehensive utilization of both magnitude and phase information in fMRI signals, allowing for independent prediction of different types of activation maps. We incorporate Gaussian Markov random fields (GMRFs) to capture spatial correlations within the data, and employ image partitioning and parallel computation to enhance computational efficiency. Our model is rigorously tested through simulation studies, and then applied to a real dataset from a unilateral finger-tapping experiment. The results demonstrate the model's effectiveness in accurately identifying brain regions activated in response to specific tasks, distinguishing between magnitude and phase activation.

In vivo magnetic recording of single-neuron action potentials Abbreviated title: In vivo magnetic single-neuron action potentials

Measuring fast neuronal signals is the domain of electrophysiology and magnetophysiology. While electrophysiology is easier to perform, magnetophysiology avoids tissue-based distortions and measures a signal with directional information. At the macroscale, magnetoencephalography (MEG) is established, and at the mesoscale, visually evoked magnetic fields have been reported. At the microscale however, while benefits of recording magnetic counterparts of electric spikes would be numerous, they are also highly challenging in vivo. Here, we combine magnetic and electric recordings of neuronal action potentials in anesthetized rats using miniaturized giant magneto-resistance (GMR) sensors. We reveal the magnetic signature of action potentials of well-isolated single units. The recorded magnetic signals showed a distinct waveform and considerable signal strength. This demonstration of in vivo magnetic action potentials opens a wide field of possibilities to profit from the combined power of magnetic and electric recordings and thus to significantly advance the understanding of neuronal circuits.

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.

In vivo direct imaging of neuronal activity at high temporospatial resolution

There has been a long-standing demand for noninvasive neuroimaging methods that can detect neuronal activity at both high temporal and high spatial resolution. We present a two-dimensional fast line-scan approach that enables direct imaging of neuronal activity with millisecond precision while retaining the high spatial resolution of magnetic resonance imaging (MRI). This approach was demonstrated through in vivo mouse brain imaging at 9.4 tesla during electrical whisker-pad stimulation. In vivo spike recording and optogenetics confirmed the high correlation of the observed MRI signal with neural activity. It also captured the sequential and laminar-specific propagation of neuronal activity along the thalamocortical pathway. This high-resolution, direct imaging of neuronal activity will open up new avenues in brain science by providing a deeper understanding of the brain's functional organization, including the temporospatial dynamics of neural networks.

Enhanced magnetic transduction of neuronal activity by nanofabricated inductors quantified via finite element analysis

Objective.Methods for the detection of neural signals involve a compromise between invasiveness, spatiotemporal resolution, and the number of neurons or brain regions recorded. Electrode-based probes provide excellent response but usually require transcranial wiring and capture activity from limited neuronal populations. Noninvasive methods such as electroencephalography and magnetoencephalography offer fast readouts of field potentials or biomagnetic signals, respectively, but have spatial constraints that prohibit recording from single neurons. A cell-sized device that enhances neurogenic magnetic fields can be used as anin situsensor for magnetic-based modalities and increase the ability to detect diverse signals across multiple brain regions.Approach.We designed and modeled a device capable of forming a tight electromagnetic junction with single neurons, thereby transducing changes in cellular potential to magnetic field perturbations by driving current through a nanofabricated inductor element.Main results.We present detailed quantification of the device performance using realistic finite element simulations with signals and geometries acquired from patch-clamped neuronsin vitroand demonstrate the capability of the device to produce magnetic signals readable via existing modalities. We compare the magnetic output of the device to intrinsic neuronal magnetic fields (NMFs) and show that the transduced magnetic field intensity from a single neuron is more than three-fold higher at its peak (1.62 nT vs 0.51 nT). Importantly, we report on a large spatial enhancement of the transduced magnetic field output within a typical voxel (40 × 40 × 10µm) over 250 times higher than the intrinsic NMF strength (0.64 nT vs 2.5 pT). We use this framework to perform optimizations of device performance based on nanofabrication constraints and material choices.Significance.Our quantifications institute a foundation for synthesizing and applying electromagnetic sensors for detecting brain activity and can serve as a general method for quantifying recording devices at the single cell level.

A rapid-onset diffusion functional MRI signal reflects neuromorphological coupling dynamics

Functional Magnetic Resonance Imaging (fMRI) has transformed our understanding of brain function in-vivo. However, the neurovascular coupling mechanisms underlying fMRI are somewhat "distant" from neural activity. Interestingly, evidence from Intrinsic Optical Signals (IOSs) indicates that neural activity is also coupled to (sub)cellular morphological modulations. Diffusion-weighted functional MRI (dfMRI) experiments have been previously proposed to probe such neuromorphological couplings, but the underlying mechanisms have remained highly contested. Here, we provide the first direct link between in vivo ultrafast dfMRI signals upon rat forepaw stimulation and IOSs in acute slices stimulated optogenetically. We reveal a hitherto unreported rapid onset (<100 ms) dfMRI signal component which (i) agrees with fast-rising IOSs dynamics; (ii) evidences a punctate quantitative correspondence to the stimulation period; and (iii) is rather insensitive to a vascular challenge. Our findings suggest that neuromorphological coupling can be detected via dfMRI signals, auguring well for future mapping of neural activity more directly compared with blood-oxygenation-level-dependent mechanisms.

Magnetic resonance imaging with submillisecond temporal resolution

PURPOSE

To demonstrate an MRI technique-Submillisecond Periodic Event Encoded Dynamic Imaging (SPEEDI)-for capturing cyclic dynamic events with submillisecond temporal resolution.

METHODS

The SPEEDI technique is based on an FID or an echo signal in which each time point in the signal is used to sample a distinct k-space raster, followed by repeated FIDs or echoes to produce the remaining k-space data in each k-space raster. All acquisitions are synchronized with a cyclic event, resulting in a set of time-resolved images of the cyclic event with a temporal resolution determined by the dwell time. In SPEEDI, spatial encoding is accomplished by phase encoding. The SPEEDI technique was demonstrated in two experiments at 3 T to (1) visualize fast-changing electric currents that mimicked the waveform of an action potential, and (2) characterize rapidly decaying eddy currents in an MRI system, with a temporal resolution of 0.2 ms and 0.4 ms, respectively. In both experiments, compressed sensing was incorporated to reduce the scan times. Phase difference maps related to the dynamics of electric currents or eddy currents were then obtained.

RESULTS

In the first experiment, time-resolved phase maps resulting from the action potential-mimicking current waveform were successfully obtained and agreed well with theoretical calculations (normalized RMS error = 0.07). In the second experiment, spatially resolved eddy current phase maps revealed time constants (27.1 ± 0.2 ms, 41.1 ± 3.5 ms, and 34.8 ± 0.7 ms) that matched well with those obtained from an established method using point sources (26.4 ms, 41.2 ms and 34.8 ms). For both experiments, phase maps from fully sampled and compressed-sensing-accelerated k-space data exhibited a high structural similarity (> 0.8) despite a two-fold to three-fold acceleration.

CONCLUSIONS

We have illustrated that SPEEDI can provide submillisecond temporal resolution. This capability will likely lead to future exploration of ultrafast, cyclic biomedical processes using MRI.

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.

Selected Topics Relating to Functional MRI Study of the Brain

The authors selected some interesting current topics among many in the field of functional MRI (fMRI) of the brain. The selection was based on authours' immediate interests in exploring these aspects further; the topics are presented and discussed along with their perspectives. If progress can be made in these areas, it would be very advantageous to the field of brain research. The topics are (I) Detectable MRI signals in response to functional activity of the brain, including the current status of neurocurrent MRI; (II) Vascular-dependent and vascular-independent MRI signals, leading to the distinction of functional and structural MRI; (III) Functional specificity and functional connectivity of local sites, including differences between task-fMRI and resting state fMRI; (IV) Functional networks: an example of application to assessing the vocational aptitude test by fMRI; (V) Neural oscillation relevant to the formation of fMRI signals and of networks; (VI) Upgrading fMRI to "information-content-reflecting" fMRI, discussed as one of the prospects of near-future fMRI.

Toward direct MRI of neuro-electro-magnetic oscillations in the human brain

PURPOSE

Neuroimaging techniques are widely used to investigate the function of the human brain, but none are currently able to accurately localize neuronal activity with both high spatial and temporal specificity. Here, a new in vivo MRI acquisition and analysis technique based on the spin-lock mechanism is developed to noninvasively image local magnetic field oscillations resulting from neuroelectric activity in specifiable frequency bands.

METHODS

Simulations, phantom experiments, and in vivo experiments using an eyes-open/eyes-closed task in 8 healthy volunteers were performed to demonstrate its sensitivity and specificity for detecting oscillatory neuroelectric activity in the alpha-band (8-12 Hz). A comprehensive postprocessing procedure was designed to enhance the neuroelectric signal, while minimizing any residual hemodynamic and physiological confounds.

RESULTS

The phantom results show that this technique can detect 0.06-nT magnetic field oscillations, while the in vivo results demonstrate that it can image task-based modulations of neuroelectric oscillatory activity in the alpha-band. Multiple control experiments and a comparison with conventional BOLD functional MRI suggest that the activation was likely not due to any residual hemodynamic or physiological confounds.

CONCLUSION

These initial results provide evidence suggesting that this new technique has the potential to noninvasively and directly image neuroelectric activity in the human brain in vivo. With further development, this approach offers the promise of being able to do so with a combination of spatial and temporal specificity that is beyond what can be achieved with existing neuroimaging methods, which can advance our ability to study the functions and dysfunctions of the human brain.

Brain active transmembrane water cycling measured by MR is associated with neuronal activity

PURPOSE

fMRI is widely used to study brain activity. Unfortunately, conventional fMRI methods assess neuronal activity only indirectly, through hemodynamic coupling. Here, we show that active, steady-state transmembrane water cycling (AWC) could serve as a basis for a potential fMRI mechanism for direct neuronal activity detection.

METHODS

AWC and neuronal actitivity in rat organotypic cortical cultures were simultaneously measured with a hybrid MR-fluorescence system. Perfusion with a paramagnetic MRI contrast agent, Gadoteridol, allows NMR determination of the kinetics of transcytolemmal water exchange. Changes in intracellular calcium concentration, [Ca_i ²⁺ ] were used as a proxy of neuronal activity and were monitored by fluorescence imaging.

RESULTS

When we alter neuronal activity by titrating with extracellular [K⁺ ] near the normal value, we see an AWC response resembling Na⁺ -K⁺ -ATPase (NKA) Michaelis-Menten behavior. When we treat with the voltage-gated sodium channel inhibitor, or with an excitatory postsynaptic inhibitor cocktail, we see AWC decrease by up to 71%. AWC was found also to be positively correlated with the basal level of spontaneous activity, which varies in different cultures.

CONCLUSIONS

These results suggest that AWC is associated with neuronal activity and NKA activity is a major contributor in coupling AWC to neuronal activity. Although AWC comprises steady-state, homeostatic transmembrane water exchange, our analysis also yields a simultaneous measure of the average cell volume, which reports any slower net transmembrane water transport.

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.

Detection of fast oscillating magnetic fields using dynamic multiple TR imaging and Fourier analysis

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.

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.

Local recording of biological magnetic fields using Giant Magneto Resistance-based micro-probes

The electrical activity of brain, heart and skeletal muscles generates magnetic fields but these are recordable only macroscopically, such as in magnetoencephalography, which is used to map neuronal activity at the brain scale. At the local scale, magnetic fields recordings are still pending because of the lack of tools that can come in contact with living tissues. Here we present bio-compatible sensors based on Giant Magneto-Resistance (GMR) spin electronics. We show on a mouse muscle in vitro, using electrophysiology and computational modeling, that this technology permits simultaneous local recordings of the magnetic fields from action potentials. The sensitivity of this type of sensor is almost size independent, allowing the miniaturization and shaping required for in vivo/vitro magnetophysiology. GMR-based technology can constitute the magnetic counterpart of microelectrodes in electrophysiology, and might represent a new fundamental tool to investigate the local sources of neuronal magnetic activity.

MR imaging of oscillatory magnetic field changes: Progressing from phantom to human

Detection of ultra-weak oscillatory magnetic field changes using MRI is of great research interest not only for neuronal current MRI of endogenous neuronal oscillations but also for direct visualization of exogenous transcranial currents or iron oxide contrast agent distribution. In this work, we present a novel oscillatory-selective detection (OSD) method that is magnitude-sensitive to the oscillatory magnetic field changes and immune to the main field inhomogeneity. In OSD, a train of 180° pulses with alternating polarity and mirror symmetry are used to refocus and accumulate magnetization changes induced by external oscillatory fields. After taking both the signal change and image signal-to-noise ratio (SNR) into account, a final 90° pulse with a phase offset of 45° is applied to store a combination of the current-induced signal change and background magnetization for the subsequent EPI acquisition. Its performance was demonstrated in phantom and human studies, both of which showed much better detection in the comparison with the recently proposed spin-lock oscillatory excitation (SLOE) method. OSD was further successfully applied in imaging transcranial alternating current stimulation (tACS) induced field changes in the human brain. These promising results suggest that OSD can overcome the limitation of field inhomogeneity impeding previous oscillatory current MRI sensitivity and be a viable tool in future tACS study.

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.

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.

Focal Epilepsy: MR Imaging of Nonhemodynamic Field Effects by Using a Phase-cycled Stimulus-induced Rotary Saturation Approach with Spin-Lock Preparation

Purpose To investigate whether nonhemodynamic resonant saturation effects can be detected in patients with focal epilepsy by using a phase-cycled stimulus-induced rotary saturation (PC-SIRS) approach with spin-lock (SL) preparation and whether they colocalize with the seizure onset zone and surface interictal epileptiform discharges (IED). Materials and Methods The study was approved by the local ethics committee, and all subjects gave written informed consent. Eight patients with focal epilepsy undergoing presurgical surface and intracranial electroencephalography (EEG) underwent magnetic resonance (MR) imaging at 3 T with a whole-brain PC-SIRS imaging sequence with alternating SL-on and SL-off and two-dimensional echo-planar readout. The power of the SL radiofrequency pulse was set to 120 Hz to sensitize the sequence to high gamma oscillations present in epileptogenic tissue. Phase cycling was applied to capture distributed current orientations. Voxel-wise subtraction of SL-off from SL-on images enabled the separation of T2* effects from rotary saturation effects. The topography of PC-SIRS effects was compared with the seizure onset zone at intracranial EEG and with surface IED-related potentials. Bayesian statistics were used to test whether prior PC-SIRS information could improve IED source reconstruction. Results Nonhemodynamic resonant saturation effects ipsilateral to the seizure onset zone were detected in six of eight patients (concordance rate, 0.75; 95% confidence interval: 0.40, 0.94) by means of the PC-SIRS technique. They were concordant with IED surface negativity in seven of eight patients (0.88; 95% confidence interval: 0.51, 1.00). Including PC-SIRS as prior information improved the evidence of the standard EEG source models compared with the use of uninformed reconstructions (exceedance probability, 0.77 vs 0.12; Wilcoxon test of model evidence, P < .05). Nonhemodynamic resonant saturation effects resolved in patients with favorable postsurgical outcomes, but persisted in patients with postsurgical seizure recurrence. Conclusion Nonhemodynamic resonant saturation effects are detectable during interictal periods with the PC-SIRS approach in patients with epilepsy. The method may be useful for MR imaging-based detection of neuronal currents in a clinical environment. (©) RSNA, 2016 Online supplemental material is available for this article.

A comprehensive study of sensitivity in measuring oscillatory magnetic fields using rotary saturation pulse sequences

Detecting the oscillatory currents with a specific frequency distribution may have the potential to make neuronal current MRI (ncMRI) come true. The phase shift or dephasing induced by both positive and negative episodes of oscillatory neuronal currents is likely to be canceled out over the echo time in typical BOLD-contrast fMRI experiments. Based on the contrast of rotary saturation, both of the recently developed spin-locked oscillatory excitation (SLOE) and stimulus-induced rotary saturation (SIRS) pulse sequences have been demonstrated to be able to detect weak oscillatory magnetic fields in phantoms with 3T MR scanners. In this report, through Bloch equation simulation as well as water phantom and anesthetic rats experiments, we comprehensively evaluate and compare the sensitivities of these two methods (SLOE and SIRS) in detecting the oscillatory magnetic fields for both high (100 Hz) and low (10 Hz) oscillation frequencies, while using their respective optimal imaging parameters. In agreement with the theoretical predications, both the simulated and experimental results showed that the SLOE method features a much higher detection sensitivity of weak magnetic fields than that of the SIRS method. SLOE was able to detect applied oscillatory magnetic fields as low as 0.1 nT in a water phantom and 0.5 nT in rat brains and the deteriorated noise levels in rat data may account for the reduced sensitivity in vivo. These promising results form the foundation for direct detection of in vivo neuronal currents using MRI.

Simultaneous calcium fluorescence imaging and MR of ex vivo organotypic cortical cultures: a new test bed for functional MRI

Recently, several new functional (f)MRI contrast mechanisms including diffusion, phase imaging, proton density, etc. have been proposed to measure neuronal activity more directly and accurately than blood-oxygen-level dependent (BOLD) fMRI. However, these approaches have proved difficult to reproduce, mainly because of the dearth of reliable and robust test systems to vet and validate them. Here we describe the development and testing of such a test bed for non-BOLD fMRI. Organotypic cortical cultures were used as a stable and reproducible biological model of neuronal activity that shows spontaneous activity similar to that of in vivo brain cortex without any hemodynamic confounds. An open-access, single-sided magnetic resonance (MR) "profiler" consisting of four permanent magnets with magnetic field of 0.32 T was used in this study to perform MR acquisition. A fluorescence microscope with long working distance objective was mounted on the top of a custom-designed chamber that keeps the organotypic culture vital, and the MR system was mounted on the bottom of the chamber to achieve real-time simultaneous calcium fluorescence optical imaging and MR acquisition on the same specimen. In this study, the reliability and performance of the proposed test bed were demonstrated by a conventional CPMG MR sequence acquired simultaneously with calcium imaging, which is a well-characterized measurement of neuronal activity. This experimental design will make it possible to correlate directly the other candidate functional MR signals to the optical indicia of neuronal activity in the future.

Direct detection of optogenetically evoked oscillatory neuronal electrical activity in rats using SLOE sequence

The direct detection of neuronal electrical activity is one of the most challenging goals in non-BOLD fMRI research. Previous work has demonstrated its feasibility in phantom and cell culture studies, but attempts in in vivo studies remain few and far between. Most recent in vivo studies used T2*-weighted sequences to directly detect neuronal electrical activity evoked by sensory stimulus. As neuronal electrical signal is usually comprised of a series of spectrally distributed oscillatory waveforms rather than being a direct current, it is most likely to be detected using oscillatory current sensitive sequences. In this study, we explored the potential of using the spin-lock oscillatory excitation (SLOE) sequence with spiral readout to directly detect optogenetically evoked oscillatory neuronal electrical activity, whose main spectral component can be manipulated artificially to match the resonance frequency of spin-lock RF field. In addition, experiments using the stimulus-induced rotary saturation (SIRS) sequence with spiral readout were also performed. Electrophysiological recording and MRI data acquisition were conducted on separate animals. Robust optogenetically evoked oscillatory LFP signals were observed and significant BOLD signals were acquired with the GE-EPI sequence before and after the whole SLOE and SIRS acquisitions, but no significant neuronal current MRI (ncMRI) signal changes were detected. These results indicate that the sensitivity of oscillatory current sensitive sequences needs to be further improved for direct detection of neuronal electrical activity.

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.

Neuronal or hemodynamic? Grappling with the functional MRI signal

Magnetic resonance imaging (MRI) and functional MRI (fMRI) continue to advance because creative physicists, engineers, neuroscientists, clinicians, and physiologists find new ways for extracting more information from the signal. Innovations in pulse sequence design, paradigm design, and processing methods have advanced the field and firmly established fMRI as a cornerstone for understanding the human brain. In this article, the field of fMRI is described through consideration of the central problem of separating hemodynamic from neuronal information. Discussed here are examples of how pulse sequences, activation paradigms, and processing methods are integrated such that novel, high-quality information can be obtained. Examples include the extraction of information such as activation onset latency, metabolic rate, neuronal adaptation, vascular patency, vessel diameter, vigilance, and subvoxel activation. Experimental measures include time series latency, hemodynamic shape, MR phase, multivoxel patterns, ratios of activation-related R2* to R2, metabolic rate changes, fluctuation correlations and frequencies, changes in fluctuation correlations and frequencies over time, resting correlation states, echo time dependence, and more.

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.

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.

An advanced phantom study assessing the feasibility of neuronal current imaging by ultra-low-field NMR

In ultra-low-field (ULF) NMR/MRI, a common scheme is to magnetize the sample by a polarizing field of up to hundreds of mT, after which the NMR signal, precessing in a field on the order of several μT, is detected with superconducting quantum interference devices (SQUIDs). In our ULF-NMR system, we polarize with up to 50mT and deploy a single-stage DC-SQUID current sensor with an integrated input coil which is connected to a wire-wound Nb gradiometer. We developed this system (white noise 0.50fT/√Hz) for assessing the feasibility of imaging neuronal currents by detecting their effect on the ULF-NMR signal. Magnetoencephalography investigations of evoked brain activity showed neuronal dipole moments below 50nAm. With our instrumentation, we have studied two different approaches for neuronal current imaging. In the so-called DC effect, long-lived neuronal activity shifts the Larmor frequency of the surrounding protons. An alternative strategy is to exploit fast neuronal activity as a tipping pulse. This so-called AC effect requires the proton Larmor frequency to match the frequency of the neuronal activity, which ranges from near-DC to ∼kHz. We emulated neuronal activity by means of a single dipolar source in a physical phantom, consisting of a hollow sphere filled with an aqueous solution of CuSO4 and NaCl. In these phantom studies, with physiologically relevant dipole depths, we determined resolution limits for our set-up for the AC and the DC effect of ∼10μAm and ∼50nAm, respectively. Hence, the DC effect appears to be detectable in vivo by current ULF-NMR technology.

Modeling nigrostriatal degeneration in organotypic cultures, a new ex vivo model of Parkinson's disease

Parkinson's disease (PD) is the second most frequent neurodegenerative disorder afflicting 2% of the population older than 65 years worldwide. Recently, brain organotypic slices have been used to model neurodegenerative disorders, including PD. They conserve brain three-dimensional architecture, synaptic connectivity and its microenvironment. This model has allowed researchers a simple and rapid method to observe cellular interactions and mechanisms. In the present study, we developed an organotypic PD model from rat brains that includes all the areas involved in the nigrostriatal pathway in a single slice preparation, without using neurotoxins to induce the dopaminergic lesion. The mechanical transection of the nigrostriatal pathway obtained during slice preparation induced PD-like histopathology. Progressive nigrostriatal degeneration was monitored combining innovative approaches, such as diffusion tensor magnetic resonance imaging (DT-RMI) to follow fiber degeneration and mass spectrometry to quantify striatal dopamine content, together with bright-field and fluorescence microscopy imaging. A substantia nigra dopaminergic cell number decrease was observed by immunohistochemistry against rat tyrosine hydroxylase (TH) reaching 80% after 2 days in culture associated with a 30% decrease of striatal TH-positive fiber density, a 15% loss of striatal dopamine content quantified by mass spectrometry and a 70% reduction of nigrostriatal fiber fractional anisotropy quantified by DT-RMI. In addition, a significant decline of medium spiny neuron density was observed from days 7 to 16. These sagittal organotypic slices could be used to study the early stage of PD, namely dopaminergic degeneration, and the late stage of the pathology with dopaminergic and GABAergic neuron loss. This novel model might improve the understanding of PD and may represent a promising tool to refine the evaluation of new therapeutic approaches.

Physical principles for scalable neural recording

Simultaneously measuring the activities of all neurons in a mammalian brain at millisecond resolution is a challenge beyond the limits of existing techniques in neuroscience. Entirely new approaches may be required, motivating an analysis of the fundamental physical constraints on the problem. We outline the physical principles governing brain activity mapping using optical, electrical, magnetic resonance, and molecular modalities of neural recording. Focusing on the mouse brain, we analyze the scalability of each method, concentrating on the limitations imposed by spatiotemporal resolution, energy dissipation, and volume displacement. Based on this analysis, all existing approaches require orders of magnitude improvement in key parameters. Electrical recording is limited by the low multiplexing capacity of electrodes and their lack of intrinsic spatial resolution, optical methods are constrained by the scattering of visible light in brain tissue, magnetic resonance is hindered by the diffusion and relaxation timescales of water protons, and the implementation of molecular recording is complicated by the stochastic kinetics of enzymes. Understanding the physical limits of brain activity mapping may provide insight into opportunities for novel solutions. For example, unconventional methods for delivering electrodes may enable unprecedented numbers of recording sites, embedded optical devices could allow optical detectors to be placed within a few scattering lengths of the measured neurons, and new classes of molecularly engineered sensors might obviate cumbersome hardware architectures. We also study the physics of powering and communicating with microscale devices embedded in brain tissue and find that, while radio-frequency electromagnetic data transmission suffers from a severe power-bandwidth tradeoff, communication via infrared light or ultrasound may allow high data rates due to the possibility of spatial multiplexing. The use of embedded local recording and wireless data transmission would only be viable, however, given major improvements to the power efficiency of microelectronic devices.

Sensitivity of MRI for directly detecting neuronal electrical activities in rat brain slices

We developed an experimental setup for magnetic resonance imaging (MRI) of rat brain slices maintained in a hemoglobin-free medium and showed that the MRI system has a sensitivity to magnetic fields of 10(-11) T. The originally developed non-magnetic sample holder consisted of a microelectrode array for recording neuronal potentials and perfusing channels for the medium. Because of the hemoglobin-free condition, the magnetic fields could be distinguished from the baseline signal fluctuations due to hemoglobin. A theoretical estimation of the signal-to-noise ratio showed a sensitivity of 3.3 × 10(-10) T. Parameter optimization using a 7-T MRI system with the developed sample holder resulted in an experimental sensitivity of 4.0 × 10(-10) T. These MRI sensitivities potentially enable us to detect weak magnetic fields arising from neuronal activities, and are sufficiently high for detecting neuronal magnetic fields of 1.4 × 10(-11) T generated in rat brain slices by averaging signals 810 times.

Water diffusion in brain cortex closely tracks underlying neuronal activity

Neuronal activity results in a local increase in blood flow. This concept serves as the basis for functional MRI. Still, this approach remains indirect and may fail in situations interfering with the neurovascular coupling mechanisms (drugs, anesthesia). Here we establish that water molecular diffusion is directly modulated by underlying neuronal activity using a rat forepaw stimulation model under different conditions of neuronal stimulation and neurovascular coupling. Under nitroprusside infusion, a neurovascular-coupling inhibitor, the diffusion response and local field potentials were maintained, whereas the hemodynamic response was abolished. As diffusion MRI reflects interactions of water molecules with obstacles (e.g., cell membranes), the observed changes point to a dynamic modulation of the neural tissue structure upon activation, which remains to be investigated. These findings represent a significant shift in concept from the current electrochemical and neurovascular coupling principles used for brain imaging, and open unique avenues to investigate mechanisms underlying brain function.

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.

Enhancing the utility of complex-valued functional magnetic resonance imaging detection of neurobiological processes through postacquisition estimation and correction of dynamic B(0) errors and motion

Functional magnetic resonance imaging (fMRI) time series analysis is typically performed using only the magnitude portion of the data. The phase information remains unused largely due to its sensitivity to temporal variations in the magnetic field unrelated to the functional response of interest. These phase changes are commonly the result of physiologic processes such as breathing or motion either inside or outside the imaging field of view. As a result, although the functional phase response carries pertinent physiological information concerning the vasculature, one aspect of which is the location of large draining veins, the full hemodynamic phase response is understudied and is poorly understood, especially in comparison with the magnitude response. It is likely that the magnitude and phase contain disjoint information, which could be used in tandem to better characterize functional hemodynamics. In this work, simulated and human fMRI experimental data are used to demonstrate how statistical analysis of complex-valued fMRI time series can be problematic, and how robust analysis using these powerful and flexible complex-valued statistics is possible through postprocessing with correction for dynamic magnetic field fluctuations in conjunction with estimated motion parameters. These techniques require no special pulse sequence modifications and can be applied to any complex-valued echo planar imaging data set. This analysis shows that the phase component appears to contain information complementary to that in the magnitude and that processing and analysis techniques are available to investigate it in a robust and flexible manner.

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.

Physiologic noise regression, motion regression, and TOAST dynamic field correction in complex-valued fMRI time series

As more evidence is presented suggesting that the phase, as well as the magnitude, of functional MRI (fMRI) time series may contain important information and that there are theoretical drawbacks to modeling functional response in the magnitude alone, removing noise in the phase is becoming more important. Previous studies have shown that retrospective correction of noise from physiologic sources can remove significant phase variance and that dynamic main magnetic field correction and regression of estimated motion parameters also remove significant phase fluctuations. In this work, we investigate the performance of physiologic noise regression in a framework along with correction for dynamic main field fluctuations and motion regression. Our findings suggest that including physiologic regressors provides some benefit in terms of reduction in phase noise power, but it is small compared to the benefit of dynamic field corrections and use of estimated motion parameters as nuisance regressors. Additionally, we show that the use of all three techniques reduces phase variance substantially, removes undesirable spatial phase correlations and improves detection of the functional response in magnitude and phase.

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 MR signal change induced by oxygen effect in neural tissue preparations of various geometries

Tissue preparation has recently been utilized for detection of neuronal activation in multiple non-BOLD based functional MRI studies to eliminate vascular contamination. However, undesired signal change could still occur in such systems due to the concentration change of dissolved O(2) upon tissue activation. To estimate the impact of such effects, the O(2) concentration distribution and the consequent susceptibility field in tissue-solution systems were simulated with various tissue geometries and experimental parameters. Our results indicate that substantial signal change between the resting and activated states could potentially be induced by the O(2) effect in highly oxygenated solutions, and thus caution should be taken in interpreting any signal change observed in such experiments.

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.

Fast human brain magnetic resonance responses associated with epileptiform spikes

Neuronal currents produce local electromagnetic fields that can potentially modulate the phase of the magnetic resonance signal and thus provide a contrast mechanism tightly linked to neuronal activity. Previous work has demonstrated the feasibility of direct MRI of neuronal activity in phantoms and cell culture, but in vivo efforts have yielded inconclusive, conflicting results. The likelihood of detecting and validating such signals can be increased with (i) fast gradient-echo echo-planar imaging, with acquisition rates sufficient to resolve neuronal activity, (ii) subjects with epilepsy, who frequently experience stereotypical electromagnetic discharges between seizures, expressed as brief, localized, high-amplitude spikes (interictal discharges), and (iii) concurrent electroencephalography. This work demonstrates that both MR magnitude and phase show large-amplitude changes concurrent with electroencephalography spikes. We found a temporal derivative relationship between MR phase and scalp electroencephalography, suggesting that the MR phase changes may be tightly linked to local cerebral activity. We refer to this manner of MR acquisition, designed explicitly to track the electroencephalography, as encephalographic MRI (eMRI). Potential extension of this technique into a general purpose functional neuroimaging tool requires further study of the MR signal changes accompanying lower amplitude neuronal activity than those discussed here.

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.