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

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.

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.

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.

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.

Temporal-spatial mean-shift clustering analysis to improve functional MRI activation detection

Cluster analysis (CA) is often used in functional magnetic resonance imaging (fMRI) analysis to improve detection of functional activations. Commonly used clustering techniques typically only consider spatial information of a statistical parametric image (SPI) in their calculations. This study examines incorporating the temporal characteristics of acquired fMRI data with mean-shift clustering (MSC) for fMRI analysis to enhance activation detections. Simulated data and real fMRI data was used to compare the commonly used cluster analysis with MSC using a feature space containing temporal characteristics. Receiver Operating Characteristic curves show that improvements in low contrast to noise scenarios using MSC over CA and our previous MSC technique at all tested simulated activation sizes. The proposed MSC technique with a feature space using both temporal and spatial data characteristics shows improved activation detection for both simulated and real Blood oxygen level dependent (BOLD) fMRI data (approximately 60% increase). The proposed techniques are useful in techniques that inherently have low contrast to noise ratios, such as non-proton imaging or high resolution BOLD fMRI.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.