Introduction to fMRI: experimental design and data analysis

This provides an introduction to functional MRI, experimental design and data analysis procedures using statistical parametric mapping approach

Spatio-temporal wavelet regularization for parallel MRI reconstruction: application to functional MRI

Parallel MRI is a fast imaging technique that enables the acquisition of highly resolved images in space or/and in time. The performance of parallel imaging strongly depends on the reconstruction algorithm, which can proceed either in the original k-space (GRAPPA, SMASH) or in the image domain (SENSE-like methods). To improve the performance of the widely used SENSE algorithm, 2D- or slice-specific regularization in the wavelet domain has been deeply investigated. In this paper, we extend this approach using 3D-wavelet representations in order to handle all slices together and address reconstruction artifacts which propagate across adjacent slices. The gain induced by such extension (3D-Unconstrained Wavelet Regularized -SENSE: 3D-UWR-SENSE) is validated on anatomical image reconstruction where no temporal acquisition is considered. Another important extension accounts for temporal correlations that exist between successive scans in functional MRI (fMRI). In addition to the case of 2D+t acquisition schemes addressed by some other methods like kt-FOCUSS, our approach allows us to deal with 3D+t acquisition schemes which are widely used in neuroimaging. The resulting 3D-UWR-SENSE and 4D-UWR-SENSE reconstruction schemes are fully unsupervised in the sense that all regularization parameters are estimated in the maximum likelihood sense on a reference scan. The gain induced by such extensions is illustrated on both anatomical and functional image reconstruction, and also measured in terms of statistical sensitivity for the 4D-UWR-SENSE approach during a fast event-related fMRI protocol. Our 4D-UWR-SENSE algorithm outperforms the SENSE reconstruction at the subject and group levels (15 subjects) for different contrasts of interest (eg, motor or computation tasks) and using different parallel acceleration factors (R=2 and R=4) on 2x2x3mm3 EPI images.Comment: arXiv admin note: substantial text overlap with arXiv:1103.353

Simultaneous intracranial EEG and fMRI of interictal epileptic discharges in humans

Simultaneous scalp EEG–fMRI measurements allow the study of epileptic networks and more generally, of the coupling between neuronal activity and haemodynamic changes in the brain. Intracranial EEG (icEEG) has greater sensitivity and spatial specificity than scalp EEG but limited spatial sampling. We performed simultaneous icEEG and functional MRI recordings in epileptic patients to study the haemodynamic correlates of intracranial interictal epileptic discharges (IED). Two patients undergoing icEEG with subdural and depth electrodes as part of the presurgical assessment of their pharmaco-resistant epilepsy participated in the study. They were scanned on a 1.5 T MR scanner following a strict safety protocol. Simultaneous recordings of fMRI and icEEG were obtained at rest. IED were subsequently visually identified on icEEG and their fMRI correlates were mapped using a general linear model (GLM). On scalp EEG–fMRI recordings performed prior to the implantation, no IED were detected. icEEG–fMRI was well tolerated and no adverse health effect was observed. intra-MR icEEG was comparable to that obtained outside the scanner. In both cases, significant haemodynamic changes were revealed in relation to IED, both close to the most active electrode contacts and at distant sites. In one case, results showed an epileptic network including regions that could not be sampled by icEEG, in agreement with findings from magneto-encephalography, offering some explanation for the persistence of seizures after surgery. Hence, icEEG–fMRI allows the study of whole-brain human epileptic networks with unprecedented sensitivity and specificity. This could help improve our understanding of epileptic networks with possible implications for epilepsy surgery

Does higher sampling rate (multiband + SENSE) improve group statistics - An example from social neuroscience block design at 3T

Multiband (MB) or Simultaneous multi-slice (SMS) acquisition schemes allow the acquisition of MRI signals from more than one spatial coordinate at a time. Commercial availability has brought this technique within the reach of many neuroscientists and psychologists. Most early evaluation of the performance of MB acquisition employed resting state fMRI or the most basic tasks. In this study, we tested whether the advantages of using MB acquisition schemes generalize to group analyses using a cognitive task more representative of typical cognitive neuroscience applications. Twenty-three subjects were scanned on a Philips 3 ​T scanner using five sequences, up to eight-fold acceleration with MB-factors 1 to 4, SENSE factors up to 2 and corresponding TRs of 2.45s down to 0.63s, while they viewed (i) movie blocks showing complex actions with hand object interactions and (ii) control movie blocks without hand object interaction. Data were processed using a widely used analysis pipeline implemented in SPM12 including the unified segmentation and canonical HRF modelling. Using random effects group-level, voxel-wise analysis we found that all sequences were able to detect the basic action observation network known to be recruited by our task. The highest t-values were found for sequences with MB4 acceleration. For the MB1 sequence, a 50% bigger voxel volume was needed to reach comparable t-statistics. The group-level t-values for resting state networks (RSNs) were also highest for MB4 sequences. Here the MB1 sequence with larger voxel size did not perform comparable to the MB4 sequence. Altogether, we can thus recommend the use of MB4 (and SENSE 1.5 or 2) on a Philips scanner when aiming to perform group-level analyses using cognitive block design fMRI tasks and voxel sizes in the range of cortical thickness (e.g. 2.7 ​mm isotropic). While results will not be dramatically changed by the use of multiband, our results suggest that MB will bring a moderate but significant benefit

Following one's heart: cardiac rhythms gate central initiation of sympathetic reflexes

Central nervous processing of environmental stimuli requires integration of sensory information with ongoing autonomic control of cardiovascular function. Rhythmic feedback of cardiac and baroreceptor activity contributes dynamically to homeostatic autonomic control. We examined how the processing of brief somatosensory stimuli is altered across the cardiac cycle to evoke differential changes in bodily state. Using functional magnetic resonance imaging of brain and noninvasive beat-to-beat cardiovascular monitoring, we show that stimuli presented before and during early cardiac systole elicited differential changes in neural activity within amygdala, anterior insula and pons, and engendered different effects on blood pressure. Stimulation delivered during early systole inhibited blood pressure increases. Individual differences in heart rate variability predicted magnitude of differential cardiac timing responses within periaqueductal gray, amygdala and insula. Our findings highlight integration of somatosensory and phasic baroreceptor information at cortical, limbic and brainstem levels, with relevance to mechanisms underlying pain control, hypertension and anxiety

Optimal Correction of The Slice Timing Problem and Subject Motion Artifacts in fMRI

Functional magnetic resonance imaging (fMRI) is an extremely popular investigative and clinical imaging tool that allows safe and noninvasive study of the functional living brain. Fundamentally, fMRI measures a physiological signal as it changes over time. The manner in which this spatio-temporal signal is acquired can create technical challenges during image reconstruction that must be corrected for if any meaningful information is to be extracted from the data. Two particular challenges that are fundamentally intertwined with each other are temporal misalignment and spatial misalignment. Temporal misalignment is due to the nature of fMRI acquisition protocols themselves: a 3D volume is created by sampling and stacking multiple 2D slices. However, these slices are not acquired simultaneously or sequentially, and therefore will always be temporally misaligned with each other. Spatial misalignment arises when subject motion is present during the scan, resulting in individual volumes being spatially misaligned with each other. Spatial and temporal misalignment are not independent from each other, and their interaction can cause additional artifacts and reconstruction challenges if not addressed properly. The purpose of this thesis is to critically examine the problem of both spatial and temporal misalignment from a signal processing perspective, while considering the physical nature and origin of the signal itself, and develop optimal correction routines for spatial and temporal misalignment and their associated artifacts. One of the most immediate problems associated with temporal misalignment is that the order in which the slices are acquired must be known in order for correction to be possible. Surprisingly, this information is rarely provided with old or shared data, meaning that this critical preprocessing step must be skipped, significantly lowering the value of the data. We use the spatio-temporal properties of the fMRI signal to develop a robust and accurate algorithm to infer the slice acquisition order retrospectively from any fMRI scan. The ability to extract the interleave parameter from any data set allows us to perform slice timing correction even if this information had been lost, or was not provided with the scan. In the next section of this work, we develop a new optimal method of slice timing correction (Filter-Shift) based on the fundamental properties of sampling theory in digital signal processing. By examining the properties of the signal of interest (The blood oxygen level depended signal: BOLD signal), we are able to design and implement an effective FIR filter to simultaneously remove noise and reconstruct the signal of interest at any shifted offset, without the need for sub-optimal interpolation. In the final section, we investigate the effects of different motion types on the MR signal based on the Bloch equation, in order to develop a theoretical foundation from which we can create an optimal correction method. We devise a novel method to remove these artifacts: Discrete reconstruction of irregular fMRI trajectory (DRIFT). Our method calculates the exact displacement of the k-space samples due to motion at each dwell time and retrospectively corrects each slice of the fMRI volume using an inverse nonuniform Fourier transform. We conclude that a hybrid approach with both prospective and retrospective components are essentially required for optimal removal of motion artifacts from the fMRI data. The combined work of this thesis provides two theoretically sound and extremely effective correction routines, that both remove artifacts and restore the underlying sampled signal. Motion correction and slice timing correction are typically the first two preprocessing steps to be applied to any fMRI data, and thus provide the foundation for any further analysis. While many other preprocessing steps can be omitted or included depending on the analysis, motion correction and slice timing correction are unequivocally beneficial and necessary for accurate and reliable results. This work provides a theoretical and quantitative framework that describes the optimal removal of artifacts associated with motion and slice timing

Diffusion Imaging in the Rat Cervical Spinal Cord

Magnetic resonance imaging (MRI) is the state of the art approach for assessing the status of the spinal cord noninvasively, and can be used as a diagnostic and prognostic tool in cases of disease or injury. Diffusion weighted imaging (DWI), is sensitive to the thermal motion of water molecules and allows for inferences of tissue microstructure. This report describes a protocol to acquire and analyze DWI of the rat cervical spinal cord on a small-bore animal system. It demonstrates an imaging setup for the live anesthetized animal and recommends a DWI acquisition protocol for high-quality imaging, which includes stabilization of the cord and control of respiratory motion. Measurements with diffusion weighting along different directions and magnitudes (b-values) are used. Finally, several mathematical models of the resulting signal are used to derive maps of the diffusion processes within the spinal cord tissue that provide insight into the normal cord and can be used to monitor injury or disease processes noninvasively. The video component of this article can be found at http://www.jove.com/video/52390/ Introduction Magneti

Third-person self-talk facilitates emotion regulation without engaging cognitive control: Converging evidence from ERP and fMRI.

Does silently talking to yourself in the third-person constitute a relatively effortless form of self control? We hypothesized that it does under the premise that third-person self-talk leads people to think about the self similar to how they think about others, which provides them with the psychological distance needed to facilitate self control. We tested this prediction by asking participants to reflect on feelings elicited by viewing aversive images (Study 1) and recalling negative autobiographical memories (Study 2) using either I or their name while measuring neural activity via ERPs (Study 1) and fMRI (Study 2). Study 1 demonstrated that third-person self-talk reduced an ERP marker of self-referential emotional reactivity (i.e., late positive potential) within the first second of viewing aversive images without enhancing an ERP marker of cognitive control (i.e., stimulus preceding negativity). Conceptually replicating these results, Study 2 demonstrated that third-person self-talk was linked with reduced levels of activation in an a priori defined fMRI marker of self-referential processing (i.e., medial prefrontal cortex) when participants reflected on negative memories without eliciting increased levels of activity in a priori defined fMRI markers of cognitive control. Together, these results suggest that third-person self-talk may constitute a relatively effortless form of self-control