Fast fMRI Research Articles

Subject-level reliability analysis of fast fMRI with application to epilepsy.

Recent studies have applied the new magnetic resonance encephalography (MREG) sequence to the study of interictal epileptic discharges (IEDs) in the electroencephalogram (EEG) of epileptic patients. However, there are no criteria to quantitatively evaluate different processing methods, to properly use the new sequence. We evaluated different processing steps of this new sequence under the common generalized linear model (GLM) framework by assessing the reliability of results. A bootstrap sampling technique was first used to generate multiple replicated data sets; a GLM with different processing steps was then applied to obtain activation maps, and the reliability of these maps was assessed. We applied our analysis in an event-related GLM related to IEDs. A higher reliability was achieved by using a GLM with head motion confound regressor with 24 components rather than the usual 6, with an autoregressive model of order 5 and with a canonical hemodynamic response function (HRF) rather than variable latency or patient-specific HRFs. Comparison of activation with IED field also favored the canonical HRF, consistent with the reliability analysis. The reliability analysis helps to optimize the processing methods for this fast fMRI sequence, in a context in which we do not know the ground truth of activation areas. Magn Reson Med 78:370-382, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Concordance of Epileptic Networks Associated with Epileptic Spikes Measured by High-Density EEG and Fast fMRI.

ObjectiveThe present study aims to investigate whether a newly developed fast fMRI called MREG (magnetic resonance encephalography) measures metabolic changes related to interictal epileptic discharges (IED). For this purpose BOLD changes are correlated with the IED distribution and variability.MethodsPatients with focal epilepsy underwent EEG-MREG using a 64 channel cap. IED voltage maps were generated using 32 and 64 channels and compared regarding their correspondence to the BOLD response. The extents of IEDs (defined as number of channels with >50% of maximum IED negativity) were correlated with the extents of positive and negative BOLD responses. Differences in inter-spike variability were investigated between interictal epileptic discharges (IED) sets with and without concordant positive or negative BOLD responses.Results17 patients showed 32 separate IED types. In 50% of IED types the BOLD changes could be confirmed by another independent imaging method. The IED extent significantly correlated with the positive BOLD extent (p = 0.04). In 6 patients the 64-channel EEG voltage maps better reflected the positive or negative BOLD response than the 32-channel EEG; in all others no difference was seen. Inter-spike variability was significantly lower in IED sets with than without concordant positive or negative BOLD responses (with p = 0.04).SignificanceHigher density EEG and fast fMRI seem to improve the value of EEG-fMRI in epilepsy. The correlation of positive BOLD and IED extent could suggest that widespread BOLD responses reflect the IED network. Inter-spike variability influences the likelihood to find IED concordant positive or negative BOLD responses, which is why single IED analysis may be promising.

Significant feed-forward connectivity revealed by high frequency components of BOLD fMRI signals

Granger causality analysis has been suggested as a method of estimating causal modulation without specifying the direction of information flow a priori. Using BOLD-contrast functional MRI (fMRI) data, such analysis has been typically implemented in the time domain. In this study, we used magnetic resonance inverse imaging, a method of fast fMRI enabled by massively parallel detection allowing up to 10Hz sampling rate, to investigate the causal modulation at different frequencies up to 5Hz. Using a visuomotor two-choice reaction-time task, both the spectral decomposition of Granger causality and isolated effective coherence revealed that the BOLD signal at frequency up to 3Hz can still be used to estimate significant dominant directions of information flow consistent with results from the time-domain Granger causality analysis. We showed the specificity of estimated dominant directions of information flow at high frequencies by contrasting causality estimates using data collected during the visuomotor task and resting state. Our data suggest that hemodynamic responses carry physiological information related to inter-regional modulation at frequency higher than what has been commonly considered.

Advantages and disadvantages of a fast fMRI sequence in the context of EEG–fMRI investigation of epilepsy patients: A realistic simulation study

EEG–fMRI is an established technique to allow mapping BOLD changes in response to interictal discharges recorded in the EEG of epilepsy patients. Traditional fMRI experiments rely on an echo planar imaging (EPI) sequence with a time resolution given by its time-to-repetition (TR) of ~2s. Recently, multiple fast fMRI sequences have been developed to get around the limited temporal resolution of the EPI sequence, and achieved a TR in the 100ms range or lower. One such sequence is called Magnetic Resonance EncephaloGraphy (MREG). Its high temporal resolution should offer increased detection sensitivity and statistical power in the context of epilepsy studies and in fMRI experiments in general. The aim of this work was to investigate the advantages and disadvantages offered by MREG. This was done by superimposing artificial event-related BOLD responses on EPI and MREG background signals, from 5 epileptic patients, that were free of epileptic discharges (spikes) on simultaneously recorded EEG. These functional datasets simulated different spiking rates and hemodynamic response amplitudes, and were analyzed with the commonly used General Linear Model (GLM) with the canonical hemodynamic response function (HRF) as a fixed model of the response. Robustness to violation of the assumptions of the GLM was additionally assessed with similar simulations using variable spike-to-spike response amplitudes and 8 non-canonical HRFs. Consistent with previous work, MREG yields higher maximum statistical t-values than EPI, but our simulations showed these statistics to be inflated, as the false positive rate at a standard threshold was high. At thresholds set to appropriately control specificity, EPI showed better true positive rate and larger cluster size than MREG. However, the lack of an appropriate calibration of the amplitude of the responses across the sequences precludes definitive judgment on their relative sensitivity. In addition, we show that a mismatch between the assumed and actual HRF impairs more MREG detection performance, but that EPI is more affected by non-modeled spike-to-spike variations of response amplitude. Filtering-out physiological noise, which is not aliased at the fast sampling rate of MREG, and the modeling of temporal autocorrelation are advantageous in increasing the detection power of MREG. This simulation study 1) warrants care when interpreting statistical t-values from fast fMRI sequences, 2) proposes thresholds for valid inferences and processing methods for maximal sensitivities, and 3) demonstrates the relative robustness/susceptibility of MREG and EPI to violation of the GLM's assumptions.

Fast fMRI Sequence Allows for Analysis of BOLD Responses to Single Interictal Epileptic Spikes

Fast fMRI Sequence Allows for Analysis of BOLD Responses to Single Interictal Epileptic Spikes

Negative BOLD in default-mode structures measured with EEG-MREG is larger in temporal than extra-temporal epileptic spikes.

Introduction: EEG-fMRI detects BOLD changes associated with epileptic interictal discharges (IED) and can identify epileptogenic networks in epilepsy patients. Besides positive BOLD changes, negative BOLD changes have sometimes been observed in the default-mode network, particularly using group analysis. A new fast fMRI sequence called MREG (Magnetic Resonance Encephalography) shows increased sensitivity to detect IED-related BOLD changes compared to the conventional EPI sequence, including frequent occurrence of negative BOLD responses in the DMN. The present study quantifies the concordance between the DMN and negative BOLD related to IEDs of temporal and extra-temporal origin.Methods: Focal epilepsy patients underwent simultaneous EEG-MREG. Areas of overlap were calculated between DMN regions, defined as precuneus, posterior cingulate, bilateral inferior parietal and mesial prefrontal cortices according to a standardized atlas, and significant negative BOLD changes revealed by an event-related analysis based on the timings of IED seen on EEG. Correlation between IED number/lobe of origin and the overlap were calculated.Results: 15 patients were analyzed, some showing IED over more than one location resulting in 30 different IED types. The average overlap between negative BOLD and DMN was significantly larger in temporal (23.7 ± 19.6 cm3) than extra-temporal IEDs (7.4 ± 5.1 cm3, p = 0.008). There was no significant correlation between the number of IEDs and the overlap between DMN structures and negative BOLD areas.Discussion: MREG results in an increased sensitivity to detect negative BOLD responses related to focal IED in single patients, with responses often occurring in DMN regions. In patients with high overlap with the DMN, this suggests that epileptic IEDs may be associated with a brief decrease in attention and cognitive ability. Interestingly this observation was not dependent on the frequency of IED but more common in IED of temporal origin.

BROCCOLI: Software for fast fMRI analysis on many-core CPUs and GPUs

Analysis of functional magnetic resonance imaging (fMRI) data is becoming ever more computationally demanding as temporal and spatial resolutions improve, and large, publicly available data sets proliferate. Moreover, methodological improvements in the neuroimaging pipeline, such as non-linear spatial normalization, non-parametric permutation tests and Bayesian Markov Chain Monte Carlo approaches, can dramatically increase the computational burden. Despite these challenges, there do not yet exist any fMRI software packages which leverage inexpensive and powerful graphics processing units (GPUs) to perform these analyses. Here, we therefore present BROCCOLI, a free software package written in OpenCL (Open Computing Language) that can be used for parallel analysis of fMRI data on a large variety of hardware configurations. BROCCOLI has, for example, been tested with an Intel CPU, an Nvidia GPU, and an AMD GPU. These tests show that parallel processing of fMRI data can lead to significantly faster analysis pipelines. This speedup can be achieved on relatively standard hardware, but further, dramatic speed improvements require only a modest investment in GPU hardware. BROCCOLI (running on a GPU) can perform non-linear spatial normalization to a 1 mm3 brain template in 4–6 s, and run a second level permutation test with 10,000 permutations in about a minute. These non-parametric tests are generally more robust than their parametric counterparts, and can also enable more sophisticated analyses by estimating complicated null distributions. Additionally, BROCCOLI includes support for Bayesian first-level fMRI analysis using a Gibbs sampler. The new software is freely available under GNU GPL3 and can be downloaded from github (https://github.com/wanderine/BROCCOLI/).

Short repetition time multiband echo‐planar imaging with simultaneous pulse recording allows dynamic imaging of the cardiac pulsation signal

Recently developed simultaneous multislice echo-planar imaging (EPI) sequences permit imaging of the whole brain at short repetition time (TR), allowing the cardiac fluctuations to be fully sampled in blood-oxygen-level dependent functional MRI (BOLD fMRI). A novel low computational analytical method was developed to dynamically map the passage of the pulsation signal through the brain and visualize the whole cerebral vasculature affected by the pulse signal. This algorithm is based on a simple combination of fast BOLD fMRI and the scanner's own built-in pulse oximeter. Multiple, temporally shifted copies of the pulse oximeter data (with 0.08 s shifting step and coverage of a 1-s span) were downsampled and used as cardiac pulsation regressors in a general linear model based analyses (FSL) of the fMRI data. The resulting concatenated z-statistics maps show the voxels that are affected as the cardiac signal travels through the brain. Many voxels were highly correlated with the pulsation regressor or its temporally shifted version. The dynamic and static cardiac pulsation maps obtained from both the task and resting state scans, resembled cerebral vasculature. The results demonstrated: (i) cardiac pulsation significantly affects most voxels in the brain; (ii) combining fast fMRI and this analytical method can reveal additional clinical information to functional studies.

Fast fMRI provides high statistical power in the analysis of epileptic networks

EEG-fMRI is a unique method to combine the high temporal resolution of EEG with the high spatial resolution of MRI to study generators of intrinsic brain signals such as sleep grapho-elements or epileptic spikes. While the standard EPI sequence in fMRI experiments has a temporal resolution of around 2.5–3s a newly established fast fMRI sequence called MREG (Magnetic-Resonance-Encephalography) provides a temporal resolution of around 100ms. This technical novelty promises to improve statistics, facilitate correction of physiological artifacts and improve the understanding of epileptic networks in fMRI. The present study compares simultaneous EEG-EPI and EEG-MREG analyzing epileptic spikes to determine the yield of fast MRI in the analysis of intrinsic brain signals.Patients with frequent interictal spikes (>3/20min) underwent EEG-MREG and EEG-EPI (3T, 20min each, voxel size 3×3×3mm, EPI TR=2.61s, MREG TR=0.1s). Timings of the spikes were used in an event-related analysis to generate activation maps of t-statistics. (FMRISTAT, |t|>3.5, cluster size: 7 voxels, p<0.05 corrected). For both sequences, the amplitude and location of significant BOLD activations were compared with the spike topography.13 patients were recorded and 33 different spike types could be analyzed. Peak T-values were significantly higher in MREG than in EPI (p<0.0001). Positive BOLD effects correlating with the spike topography were found in 8/29 spike types using the EPI and in 22/33 spikes types using the MREG sequence. Negative BOLD responses in the default mode network could be observed in 3/29 spike types with the EPI and in 19/33 with the MREG sequence. With the latter method, BOLD changes were observed even when few spikes occurred during the investigation.Simultaneous EEG-MREG thus is possible with good EEG quality and shows higher sensitivity in regard to the localization of spike-related BOLD responses than EEG-EPI. The development of new methods of analysis for this sequence such as modeling of physiological noise, temporal analysis of the BOLD signal and defining appropriate thresholds is required to fully profit from its high temporal resolution.

P 212. A novel high sensitivity MR-device for combined TMS/fMRI experiments

Introduction Studies with simultaneous functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) have become increasingly popular as the combination of these techniques allows investigation of TMS effects on the brain and could help answer unresolved questions concerning causality in fMRI ( Kobayashi, 2003 ). So far, experiments are being performed using rather large, standard MRI head coils, with the TMS positioned between head and MR coil, resulting in poor sensitivity for the MRI experiment, while also preventing visualization of activation spots directly below the TMS focus. Objective To gain sensitivity for combined TMS and fMRI experiments, we developed a dedicated, slim MR coil on a curved, form-fitted surface that can be placed between TMS and the head. This way, the TMS is close enough to the brain to achieve efficient stimulation, and the MR coil can provide far higher sensitivity than in the conventional arrangement due to its proximity to the head. This way, the TMS coil itself does not cause artifacts in the fMRI maps. Materials and methods This dedicated receive coil is designed for 3T MR systems, with a field of view of 15 cm and a target depth of 5.0–7.5 cm. It consists of seven hexagonally arranged loop elements of 6 cm diameter each. To decouple adjacent elements, loops were overlapped. The array is placed on a spherical support with a curvature to fit the average human head. An illustration of the device positioned for investigations in the dorsolateral prefrontal cortex is shown in ( Fig. 1 ). All elements of the MR coil are passively and actively detunable for decoupling from the MR system’s body coil during signal transmission. A second stage matching network ( Reykowski, 1995 ) connects the coil elements to low noise preamplifiers, additionally improving mutual decoupling between array elements. Preamplifiers are not placed directly on the coil, minimizing coil thickness to assure efficient TMS stimulation, and avoiding damage to the preamplifiers by TMS pulses. Results Mutual coupling between elements of the MR coil is below-9 dB for all channels. Additional-20 dB decoupling was achieved by preamplifier decoupling, minimizing noise correlation between elements, and thus, enabling parallel imaging with low g-factors. The dedicated MR coil is well isolated from the transmitting MR body coil, proven by field distortions well below 5%. This avoids image artifacts and ensures patient safety. A gradient echo image of a phantom acquired with one of the seven elements is shown in ( Fig. 2 ), demonstrating the high sensitivity of the basic elements in cortical areas. Conclusion A dedicated 7-channel MR coil array for simultaneous fMRI/TMS measurements is presented. Individual coil elements were efficiently decoupled from each other and from the transmit body coil. Due to the substantial gain in SNR and good isolation between channels, parallel imaging can also be implemented to speed up TMS-fMRI measurements. This novel hardware development will boost sensitivity of fMRI in combined fMRI/TMS experiments, enabling fast and high-resolution fMRI while efficiently and safety stimulating the brain with TMS.

Noninvasive Language Mapping in Patients With Epilepsy or Brain Tumors

Functional magnetic resonance imaging (fMRI) has become part of routine brain mapping in patients with epilepsy or tumor undergoing resective surgery. However, robust localization of crucial functional areas is required. To establish a simple, short fMRI task that reliably localizes crucial language areas in individual patients who undergo respective surgery. fMRI was measured during an 8-minute auditory semantic decision task in 28 healthy controls and 35 consecutive patients who had focal epilepsy or a brain tumor. Nineteen underwent resective surgery. Group and individual analyses were performed. Results in patients were compared with postsurgical language outcome and electrocortical stimulation when available. fMRI activations concordant with the anterior and posterior language areas were found in 96% and 89% of the controls, respectively. The anterior and posterior language areas were both activated in 93% of the patients. These results were concordant with electrocortical stimulation results in 5 patients. Transient postsurgical language deficits were found in 2 patients in whom surgery was performed in the vicinity of the fMRI activations or who had postsurgical complications implicating areas of fMRI activations. The proposed fast fMRI language protocol reliably localized the most relevant language areas in individual subjects. It appears to be a valuable complementary tool for surgical planning of epileptogenic foci and of brain tumors.

A 3D GRASE ASL technique for fast whole-brain perfusion fMRI: Perfomance investigation and comparison with standard BOLD fMRI in motor-task and reward-learning experiments

A 3D GRASE ASL technique for fast whole-brain perfusion fMRI: Perfomance investigation and comparison with standard BOLD fMRI in motor-task and reward-learning experiments

Fast spin echo sequences for BOLD functional MRI

At higher field strengths, spin echo (SE) functional MRI (fMRI) is an attractive alternative to gradient echo (GE) as the increased weighting towards the microvasculature results in intrinsically better localization of the BOLD signal. Images are free of signal voids but the commonly used echo planar imaging (EPI) sampling scheme causes geometric distortions, and T2* effects often contribute considerably to the signal changes measured upon brain activation. Multiply refocused SE sequences such as fast spin echo (FSE) are essentially artifact free but their application to fast fMRI is usually hindered due to high energy deposition, and long sampling times. In the work presented here, a combination of parallel imaging and partial Fourier acquisition is used to shorten FSE acquisition times to near those of conventional SE-EPI, permitting sampling of eight slices (matrix 64 × 64) per second. Signal acquisition is preceded by a preparation experiment that aims at increasing the relative contribution of extravascular dynamic averaging to the BOLD signal. Comparisons are made with conventional SE-EPI using a visual stimulation paradigm. While the observed signal changes are approximately 30% lower, most likely due to the absence of T2* contamination, activation size and t-scores are comparable for both methods, suggesting that HASTE fMRI is a viable alternative, particularly if distortion free images are required. Our data also indicate that the BOLD post-stimulus undershoot is most probably attributable to persistent elevated oxygen metabolism rather than to delayed vascular compliance.

FMRI Adaptation Reveals Separate Mechanisms for First-Order and Second-Order Motion

A key unresolved debate in human vision concerns whether we have two different low-level mechanisms for encoding image motion. Separate neural mechanisms have been suggested for first-order (luminance modulation) and second-order (e.g., contrast modulation) motion in the retinal image but a single mechanism could handle both. Human functional magnetic resonance imaging (fMRI) has not so far convincingly revealed separate anatomical substrates. To examine whether two separate but co-localized mechanisms might exist, we used the technique of fast fMRI adaptation. We found direction-selective adaptation independently for each type of motion in the motion area V5/MT+ of the human brain. However, there was a total absence of cross-adaptation between first-order and second-order motion stimuli. This was true in both of the two subcomponents of MT+ (MT and MST) and similar results were found in V3A. This pattern of adaptation was consistent with psychophysical measurements of detection thresholds in similar stimulus sequences. The results provide strong evidence for separate neural populations that are responsible for detecting first- and second-order motion.

Time-variant Analysis of Fast-fMRI and Dynamic Contrast Agent MRI Sequences as Examples of 4-dimensional Image Analysis

Image sequences with time-varying information content need appropriate analysis strategies. The exploration of directed information transfer (interactions) between neuronal assemblies is one of the most important aims of current functional MRI (fMRI) analysis. Additionally, we examined perfusion maps in dynamic contrast agent MRI sequences of stroke patients. In this investigation, the focus centers on distinguishing between brain areas with normal and reduced perfusion on the basis of the dynamics of contrast agent inflow and washout. Fast fMRI sequences were analyzed with time-variant Granger causality (tvGC). The tvGC is based on a time-variant autoregressive model and is used for the quantification of the directed information transfer between activated brain areas. Generalized Dynamic Neural Networks (GDNN) with time-variant weights were applied on dynamic contrast agent MRI sequences as a nonlinear operator in order to enhance differences in the signal courses of pixels of normal and injured tissues. A simple motor task (self-paced finger tapping) is used in an fMRI design to investigate directed interactions between defined brain areas. A significant information transfer can be determined for the direction primary motor cortex to supplementary motor area during a short time period of about five seconds after stimulus. The analysis of dynamic contrast agent MRI sequences demonstrates that the trained GDNN enables a reliable tissue classification. Three classes are of interest: normal tissue, tissue at risk for death, and dead tissue. The time-variant multivariate analysis of directed information transfer derived from fMRI sequences and the computation of perfusion maps by GDNN demonstrate that dynamic analysis methods are essential tools for 4D image analysis.

Fast Spiral fMRI During a Periodic Working Memory Task

Fast Spiral fMRI During a Periodic Working Memory Task

Characterizing Dynamic Brain Responses with fMRI: A Multivariate Approach

In this paper we present a multivariate analysis of evoked hemodynamic responses and their spatiotemporal dynamics as measured with fast fMRI. This analysis uses standard multivariate statistics (MANCOVA) and the general linear model to make inferences about effects of interest and canonical variates analysis (CVA) to describe the important features of these effects. We have used these techniques to characterize the form of hemodynamic transients that are evoked during a cognitive or sensorimotor task. In particular we do not assume that the neural or hemodynamic response reaches some "steady state" but acknowledge that these physiological changes could show profound task-dependent adaptation and time-dependent changes during the task. To address this issue we have modeled hemodynamic responses using appropriate temporal basis functions and estimated their exact form within the general linear model using MANCOVA. We do not propose that this analysis is a particularly powerful way to make inferences about functional specialization (or more generally functional anatomy) because it only provides statistical inferences about the distributed (whole brain) responses evoked by different conditions. However, its application to characterizing the temporal aspects of evoked hemodynamic responses reveals some compelling and somewhat unexpected perspectives on transient but stereotyped responses to changes in cognitive or sensorimotor processing. The most remarkable observation is that these responses can be biphasic and show profound differences in their form depending on the extant task or condition. Furthermore these differences can be seen in the absence of changes in mean signal.

GPO moving forward in the electronic age: A strategic outlook

The spontaneous dynamics of the brain modulate its function from moment to moment, shaping neural computation and cognition. Functional MRI (fMRI), while classically used as a tool for spatial localization, is increasingly being used to identify the temporal dynamics of brain activity. fMRI analyses focused on the temporal domain have revealed important new information about the dynamics underlying states such as arousal, attention, and sleep. Dense temporal sampling – either by using fast fMRI acquisition, or multiple repeated scan sessions within individuals – can further enrich the information present in these studies. This review focuses on recent developments in using fMRI to identify dynamics across brain states, particularly vigilance and sleep states, and the potential for highly temporally sampled fMRI to answer these questions.