Very high-resolution three-dimensional functional MRI of the human visual cortex with elimination of large venous vessels

A mechanistic computational framework to investigate the hemodynamic fingerprint of the blood oxygenation level-dependent signal

Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is one of the most used imaging techniques to map brain activity or to obtain clinical information about human cortical vasculature, in both healthy and disease conditions. Nevertheless, BOLD fMRI is an indirect measurement of brain functioning triggered by neurovascular coupling. The origin of the BOLD signal is quite complex, and the signal formation thus depends, among other factors, on the topology of the cortical vasculature and the associated hemodynamic changes. To understand the hemodynamic evolution of the BOLD signal response in humans, it is beneficial to have a computational framework available that virtually resembles the human cortical vasculature, and simulates hemodynamic changes and corresponding MRI signal changes via interactions of intrinsic biophysical and magnetic properties of the tissues. To this end, we have developed a mechanistic computational framework that simulates the hemodynamic fingerprint of the BOLD signal based on a statistically defined, three-dimensional, vascular model that approaches the human cortical vascular architecture. The microvasculature is approximated through a Voronoi tessellation method and the macrovasculature is adapted from two-photon microscopy mice data. Using this computational framework, we simulated hemodynamic changes-cerebral blood flow, cerebral blood volume, and blood oxygen saturation-induced by virtual arterial dilation. Then we computed local magnetic field disturbances generated by the vascular topology and the corresponding blood oxygen saturation changes. This mechanistic computational framework also considers the intrinsic biophysical and magnetic properties of nearby tissue, such as water diffusion and relaxation properties, resulting in a dynamic BOLD signal response. The proposed mechanistic computational framework provides an integrated biophysical model that can offer better insights regarding the spatial and temporal properties of the BOLD signal changes.

Modelling the depth-dependent VASO and BOLD responses in human primary visual cortex

Functional magnetic resonance imaging (fMRI) using a blood-oxygenation-level-dependent (BOLD) contrast is a common method for studying human brain function noninvasively. Gradient-echo (GRE) BOLD is highly sensitive to the blood oxygenation change in blood vessels; however, the spatial signal specificity can be degraded due to signal leakage from activated lower layers to superficial layers in depth-dependent (also called laminar or layer-specific) fMRI. Alternatively, physiological variables such as cerebral blood volume using the VAscular-Space-Occupancy (VASO) contrast have shown higher spatial specificity compared to BOLD. To better understand the physiological mechanisms such as blood volume and oxygenation changes and to interpret the measured depth-dependent responses, models are needed which reflect vascular properties at this scale. For this purpose, we extended and modified the "cortical vascular model" previously developed to predict layer-specific BOLD signal changes in human primary visual cortex to also predict a layer-specific VASO response. To evaluate the model, we compared the predictions with experimental results of simultaneous VASO and BOLD measurements in a group of healthy participants. Fitting the model to our experimental data provided an estimate of CBV change in different vascular compartments upon neural activity. We found that stimulus-evoked CBV change mainly occurs in small arterioles, capillaries, and intracortical arteries and that the contribution from venules and ICVs is smaller. Our results confirm that VASO is less susceptible to large vessel effects compared to BOLD, as blood volume changes in intracortical arteries did not substantially affect the resulting depth-dependent VASO profiles, whereas depth-dependent BOLD profiles showed a bias towards signal contributions from intracortical veins.

Pre-processing of Sub-millimeter GE-BOLD fMRI Data for Laminar Applications

Over the past 30 years, brain function has primarily been evaluated non-invasively using functional magnetic resonance imaging (fMRI) with gradient-echo (GE) sequences to measure blood-oxygen-level-dependent (BOLD) signals. Despite the multiple advantages of GE sequences, e.g., higher signal-to-noise ratio, faster acquisitions, etc., their relatively inferior spatial localization compromises the routine use of GE-BOLD in laminar applications. Here, in an attempt to rescue the benefits of GE sequences, we evaluated the effect of existing pre-processing methods on the spatial localization of signals obtained with EPIK, a GE sequence that affords voxel volumes of 0.25 mm3 with near whole-brain coverage. The methods assessed here apply to both task and resting-state fMRI data assuming the availability of reconstructed magnitude and phase images.

New acquisition techniques and their prospects for the achievable resolution of fMRI

This work reviews recent advances in technologies for functional magnetic resonance imaging (fMRI) of the human brain and highlights the push for higher functional specificity based on increased spatial resolution and specific MR contrasts to reveal previously undetectable functional properties of small-scale cortical structures. We discuss how the combination of MR hardware, advanced acquisition techniques and various MR contrast mechanisms have enabled recent progress in functional neuroimaging. However, these advanced fMRI practices have only been applied to a handful of neuroscience questions to date, with the majority of the neuroscience community still using conventional imaging techniques. We thus discuss upcoming challenges and possibilities for fMRI technology development in human neuroscience. We hope that readers interested in functional brain imaging acquire an understanding of current and novel developments and potential future applications, even if they don't have a background in MR physics or engineering. We summarize the capabilities of standard fMRI acquisition schemes with pointers to relevant literature and comprehensive reviews and introduce more recent developments.

Predicting the fMRI Signal Fluctuation with Recurrent Neural Networks Trained on Vascular Network Dynamics

Resting-state functional MRI (rs-fMRI) studies have revealed specific low-frequency hemodynamic signal fluctuations (<0.1 Hz) in the brain, which could be related to neuronal oscillations through the neurovascular coupling mechanism. Given the vascular origin of the fMRI signal, it remains challenging to separate the neural correlates of global rs-fMRI signal fluctuations from other confounding sources. However, the slow-oscillation detected from individual vessels by single-vessel fMRI presents strong correlation to neural oscillations. Here, we use recurrent neural networks (RNNs) to predict the future temporal evolution of the rs-fMRI slow oscillation from both rodent and human brains. The RNNs trained with vessel-specific rs-fMRI signals encode the unique brain oscillatory dynamic feature, presenting more effective prediction than the conventional autoregressive model. This RNN-based predictive modeling of rs-fMRI datasets from the Human Connectome Project (HCP) reveals brain state-specific characteristics, demonstrating an inverse relationship between the global rs-fMRI signal fluctuation with the internal default-mode network (DMN) correlation. The RNN prediction method presents a unique data-driven encoding scheme to specify potential brain state differences based on the global fMRI signal fluctuation, but not solely dependent on the global variance.

Interhemispheric functional connectivity in the zebra finch brain, absent the corpus callosum in normal ontogeny

Bilaterally symmetric intrinsic brain activity (homotopic functional connectivity; FC) is a fundamental feature of the mammalian brain's functional architecture. In mammals, homotopic FC is primarily mediated by the corpus callosum (CC), a large interhemispheric white matter tract thought to balance the bilateral coordination and hemispheric specialization critical for many complex brain functions, including human language. The CC first emerged with the Eutherian (placental) mammals ∼160 MYA and is not found among other vertebrates. Despite this, other vertebrates also exhibit complex brain functions requiring hemispheric specialization and coordination. For example, the zebra finch (Taeniopygia guttata) songbird learns to sing from tutors much as humans acquire speech and must balance hemispheric specialization and coordination to successfully learn and produce song. We therefore tested whether the zebra finch also exhibits homotopic FC, despite lacking the CC. Resting-state fMRI analyses demonstrated widespread homotopic FC throughout the zebra finch brain across development, including within a network required for learned song that lacks direct interhemispheric structural connectivity. The presence of homotopic FC in a non-Eutherian suggests that ancestral pathways, potentially including indirect connectivity via the anterior commissure, are sufficient for maintaining a homotopic functional architecture, an insight with broad implications for understanding interhemispheric coordination across phylogeny.

Ultra-Slow Single-Vessel BOLD and CBV-Based fMRI Spatiotemporal Dynamics and Their Correlation with Neuronal Intracellular Calcium Signals

Functional MRI has been used to map brain activity and functional connectivity based on the strength and temporal coherence of neurovascular-coupled hemodynamic signals. Here, single-vessel fMRI reveals vessel-specific correlation patterns in both rodents and humans. In anesthetized rats, fluctuations in the vessel-specific fMRI signal are correlated with the intracellular calcium signal measured in neighboring neurons. Further, the blood-oxygen-level-dependent (BOLD) signal from individual venules and the cerebral-blood-volume signal from individual arterioles show correlations at ultra-slow (<0.1 Hz), anesthetic-modulated rhythms. These data support a model that links neuronal activity to intrinsic oscillations in the cerebral vasculature, with a spatial correlation length of ∼2 mm for arterioles. In complementary data from awake human subjects, the BOLD signal is spatially correlated among sulcus veins and specified intracortical veins of the visual cortex at similar ultra-slow rhythms. These data support the use of fMRI to resolve functional connectivity at the level of single vessels.

Mapping and characterization of positive and negative BOLD responses to visual stimulation in multiple brain regions at 7T

External stimuli and tasks often elicit negative BOLD responses in various brain regions, and growing experimental evidence supports that these phenomena are functionally meaningful. In this work, the high sensitivity available at 7T was explored to map and characterize both positive (PBRs) and negative BOLD responses (NBRs) to visual checkerboard stimulation, occurring in various brain regions within and beyond the visual cortex. Recently-proposed accelerated fMRI techniques were employed for data acquisition, and procedures for exclusion of large draining vein contributions, together with ICA-assisted denoising, were included in the analysis to improve response estimation. Besides the visual cortex, significant PBRs were found in the lateral geniculate nucleus and superior colliculus, as well as the pre-central sulcus; in these regions, response durations increased monotonically with stimulus duration, in tight covariation with the visual PBR duration. Significant NBRs were found in the visual cortex, auditory cortex, default-mode network (DMN) and superior parietal lobule; NBR durations also tended to increase with stimulus duration, but were significantly less sustained than the visual PBR, especially for the DMN and superior parietal lobule. Responses in visual and auditory cortex were further studied for checkerboard contrast dependence, and their amplitudes were found to increase monotonically with contrast, linearly correlated with the visual PBR amplitude. Overall, these findings suggest the presence of dynamic neuronal interactions across multiple brain regions, sensitive to stimulus intensity and duration, and demonstrate the richness of information obtainable when jointly mapping positive and negative BOLD responses at a whole-brain scale, with ultra-high field fMRI.

The impact of ultra-high field MRI on cognitive and computational neuroimaging

The ability to measure functional brain responses non-invasively with ultra high field MRI (7 T and above) represents a unique opportunity in advancing our understanding of the human brain. Compared to lower fields (3 T and below), ultra high field MRI has an increased sensitivity, which can be used to acquire functional images with greater spatial resolution, and greater specificity of the blood oxygen level dependent (BOLD) signal to the underlying neuronal responses. Together, increased resolution and specificity enable investigating brain functions at a submillimeter scale, which so far could only be done with invasive techniques. At this mesoscopic spatial scale, perception, cognition and behavior can be probed at the level of fundamental units of neural computations, such as cortical columns, cortical layers, and subcortical nuclei. This represents a unique and distinctive advantage that differentiates ultra high from lower field imaging and that can foster a tighter link between fMRI and computational modeling of neural networks. So far, functional brain mapping at submillimeter scale has focused on the processing of sensory information and on well-known systems for which extensive information is available from invasive recordings in animals. It remains an open challenge to extend this methodology to uniquely human functions and, more generally, to systems for which animal models may be problematic. To succeed, the possibility to acquire high-resolution functional data with large spatial coverage, the availability of computational models of neural processing as well as accurate biophysical modeling of neurovascular coupling at mesoscopic scale all appear necessary.

Systemic Low-Frequency Oscillations in BOLD Signal Vary with Tissue Type

Blood-oxygen-level dependent (BOLD) signals are widely used in functional magnetic resonance imaging (fMRI) as a proxy measure of brain activation. However, because these signals are blood-related, they are also influenced by other physiological processes. This is especially true in resting state fMRI, during which no experimental stimulation occurs. Previous studies have found that the amplitude of resting state BOLD is closely related to regional vascular density. In this study, we investigated how some of the temporal fluctuations of the BOLD signal also possibly relate to regional vascular density. We began by identifying the blood-bound systemic low-frequency oscillation (sLFO). We then assessed the distribution of all voxels based on their correlations with this sLFO. We found that sLFO signals are widely present in resting state BOLD signals and that the proportion of these sLFOs in each voxel correlates with different tissue types, which vary significantly in underlying vascular density. These results deepen our understanding of the BOLD signal and suggest new imaging biomarkers based on fMRI data, such as amplitude of low-frequency fluctuation (ALFF) and sLFO, a combination of both, for assessing vascular density.

Dense, shape-optimized posterior 32-channel coil for submillimeter functional imaging of visual cortex at 3T

Purpose

Functional neuroimaging of small cortical patches such as columns is essential for testing computational models of vision, but imaging from cortical columns at conventional 3T fields is exceedingly difficult. By targeting the visual cortex exclusively, we tested whether combined optimization of shape, coil placement, and electronics would yield the necessary gains in signal‐to‐noise ratio (SNR) for submillimeter visual cortex functional MRI (fMRI).

Method

We optimized the shape of the housing to a population‐averaged atlas. The shape was comfortable without cushions and resulted in the maximally proximal placement of the coil elements. By using small wire loops with the least number of solder joints, we were able to maximize the Q factor of the individual elements. Finally, by planning the placement of the coils using the brain atlas, we were able to target the arrangement of the coil elements to the extent of the visual cortex.

Results

The combined optimizations led to as much as two‐fold SNR gain compared with a whole‐head 32‐channel coil. This gain was reflected in temporal SNR as well and enabled fMRI mapping at 0.75 mm resolutions using a conventional GRAPPA‐accelerated gradient echo echo planar imaging.

Conclusion

Integrated optimization of shape, electronics, and element placement can lead to large gains in SNR and empower submillimeter fMRI at 3T. Magn Reson Med 76:321–328, 2016. © 2015 Wiley Periodicals, Inc.

Regional variations in vascular density correlate with resting-state and task-evoked blood oxygen level-dependent signal amplitude

Functional magnetic resonance imaging (fMRI) has become one of the primary tools used for noninvasively measuring brain activity in humans. For the most part, the blood oxygen level-dependent (BOLD) contrast is used, which reflects the changes in hemodynamics associated with active brain tissue. The main advantage of the BOLD signal is that it is relatively easy to measure and thus is often used as a proxy for comparing brain function across population groups (i.e., control vs. patient). However, it is particularly weighted toward veins whose structural architecture is known to vary considerably across the brain. This makes it difficult to interpret whether differences in BOLD between cortical areas reflect true differences in neural activity or vascular structure. We therefore investigated how regional variations of vascular density (VAD) relate to the amplitude of resting-state and task-evoked BOLD signals. To address this issue, we first developed an automated method for segmenting veins in images acquired with susceptibility-weighted imaging, allowing us to visualize the venous vascular tree across the brain. In 19 healthy subjects, we then applied voxel-based morphometry (VBM) to T1-weighted images and computed regional measures of gray matter density (GMD). We found that, independent of spatial scale, regional variations in resting-state and task-evoked fMRI amplitudes were better correlated to VAD compared to GMD. Using a general linear model (GLM), it was observed that the bulk of regional variance in resting-state activity could be modeled by VAD. Cortical areas whose resting-state activity was most suppressed by VAD correction included Cuneus, Precuneus, Culmen, and BA 9, 10, and 47. Taken together, our results suggest that resting-state BOLD signals are significantly related to the underlying structure of the brain vascular system. Calibrating resting BOLD activity by venous structure may result in a more accurate interpretation of differences observed between cortical areas and/or individuals.

Advances in High-Field BOLD fMRI

This review article examines the current state of BOLD fMRI at a high magnetic field strength of 7 Tesla. The following aspects are covered: a short description of the BOLD contrast, spatial and temporal resolution, BOLD sensitivity, localization and spatial specificity, technical challenges as well as an outlook on future developments are given. It is shown that the main technical challenges of performing BOLD fMRI at high magnetic field strengths-namely development of array coils, imaging sequences and parallel imaging reconstruction-have been solved successfully. The combination of these developments has lead to the availability of high-resolution BOLD fMRI protocols that are able to cover the whole brain with a repetition time (TR) shorter than 3 s. The structural information available from these high-resolution fMRI images itself is already very detailed, which helps to co-localize structure and function. Potential future applications include whole-brain connectivity analysis on a laminar resolution and single subject examinations.

Adjacent visual representations of self-motion in different reference frames

Recent investigations indicate that retinal motion is not directly available for perception when moving around [Souman JL, et al. (2010) J Vis 10:14], possibly pointing to suppression of retinal speed sensitivity in motion areas. Here, we investigated the distribution of retinocentric and head-centric representations of self-rotation in human lower-tier visual motion areas. Functional MRI responses were measured to a set of visual self-motion stimuli with different levels of simulated gaze and simulated head rotation. A parametric generalized linear model analysis of the blood oxygen level-dependent responses revealed subregions of accessory V3 area, V6(+) area, middle temporal area, and medial superior temporal area that were specifically modulated by the speed of the rotational flow relative to the eye and head. Pursuit signals, which link the two reference frames, were also identified in these areas. To our knowledge, these results are the first demonstration of multiple visual representations of self-motion in these areas. The existence of such adjacent representations points to early transformations of the reference frame for visual self-motion signals and a topography by visual reference frame in lower-order motion-sensitive areas. This suggests that visual decisions for action and perception may take into account retinal and head-centric motion signals according to task requirements.

Estimating neural signal dynamics in the human brain

Although brain imaging methods are highly effective for localizing the effects of neural activation throughout the human brain in terms of the blood oxygenation level dependent (BOLD) response, there is currently no way to estimate the underlying neural signal dynamics in generating the BOLD response in each local activation region (except for processes slower than the BOLD time course). Knowledge of the neural signal is critical if spatial mapping is to progress to the analysis of dynamic information flow through the cortical networks as the brain performs its tasks. We introduce an analytic approach that provides a new level of conceptualization and specificity in the study of brain processing by non-invasive methods. This technique allows us to use brain imaging methods to determine the dynamics of local neural population responses to their native temporal resolution throughout the human brain, with relatively narrow confidence intervals on many response properties. The ability to characterize local neural dynamics in the human brain represents a significant enhancement of brain imaging capabilities, with potential applications ranging from general cognitive studies to assessment of neuropathologies.

Real-time cardiac synchronization with fixed volume frame rate for reducing physiological instabilities in 3D FMRI

Although 2D echo-planar imaging (EPI) remains the dominant method for functional MRI (FMRI), 3D readouts are receiving more interest as these sequences have favorable signal-to-noise ratio (SNR) and enable imaging at a high isotropic resolution. Spoiled gradient-echo (SPGR) and balanced steady-state free-precession (bSSFP) are rapid sequences that are typically acquired with highly segmented 3D readouts, and thus less sensitive to image distortion and signal dropout. They therefore provide a powerful alternative for FMRI in areas with strong susceptibility offsets, such as deep gray matter structures and the brainstem. Unfortunately, the multi-shot nature of the readout makes these sequences highly sensitive to physiological fluctuations, and large signal instabilities are observed in the inferior regions of the brain. In this work a characterization of the source of these instabilities is given and a new method is presented to reduce the instabilities observed in 3D SPGR and bSSFP. Rapidly acquired single-slice data, which critically sampled the respiratory and cardiac waveforms, showed that cardiac pulsation is the dominant source of the instabilities. Simulations further showed that synchronizing the readout to the cardiac cycle minimizes the instabilities considerably. A real-time synchronization method was therefore developed, which utilizes parallel-imaging techniques to allow cardiac synchronization without alteration of the volume acquisition rate. The implemented method significantly improves the temporal stability in areas that are affected by cardiac-related signal fluctuations. In bSSFP data the tSNR in the brainstem increased by 45%, at the cost of a small reduction in tSNR in the cortical areas. In SPGR the temporal stability is improved by approximately 20% in the subcortical structures and as well as cortical gray matter when synchronization was performed.

Neuronal dynamics underlying high- and low-frequency EEG oscillations contribute independently to the human BOLD signal

Work on animals indicates that BOLD is preferentially sensitive to local field potentials, and that it correlates most strongly with gamma band neuronal synchronization. Here we investigate how the BOLD signal in humans performing a cognitive task is related to neuronal synchronization across different frequency bands. We simultaneously recorded EEG and BOLD while subjects engaged in a visual attention task known to induce sustained changes in neuronal synchronization across a wide range of frequencies. Trial-by-trial BOLD fluctuations correlated positively with trial-by-trial fluctuations in high-EEG gamma power (60-80 Hz) and negatively with alpha and beta power. Gamma power on the one hand, and alpha and beta power on the other hand, independently contributed to explaining BOLD variance. These results indicate that the BOLD-gamma coupling observed in animals can be extrapolated to humans performing a task and that neuronal dynamics underlying high- and low-frequency synchronization contribute independently to the BOLD signal.

Layer-specific BOLD activation in human V1

The neocortex is known to have a distinct laminar structure which has previously been probed in animals using high-resolution fMRI. Detection of layer-specific activation in humans has however to date proven elusive. In this study we demonstrate for the first time such layer-specific activation, specifically at a depth corresponding to layer IV of human primary visual cortex (V1). We used a gradient-echo (GE) sequence at 3T with an isotropic resolution of 0.75 mm, in which a stria at the depth of layer IV was visible in the averaged time series, and could be used as an anatomical landmark. Upon visual stimulation (7.5 Hz flickering checkerboard) the signal increase of 3% in layer IV was significantly higher than in the neighboring laminae. The width of this activation peak was 0.8-1 mm. Based on this result and known laminar organization of the intracortical vasculature we conclude that in the direction perpendicular to the cortical surface the intrinsic spatial resolution of the GE-BOLD fMRI signal is in the submillimetre range. Human laminar fMRI is a significant development which may improve our understanding of intracortical activation patterns and of the way in which different cortical regions interact.

T2-weighted 3D fMRI using S2-SSFP at 7 tesla

In this study, the sensitivity of the S(2)-steady-state free precession (SSFP) signal for functional MRI at 7 T was investigated. In order to achieve the necessary temporal resolution, a three-dimensional acquisition scheme with acceleration along two spatial axes was employed. Activation maps based on S(2)-steady-state free precession data showed similar spatial localization of activation and sensitivity as spin-echo echo-planar imaging (SE-EPI), but data can be acquired with substantially lower power deposition. The functional sensitivity estimated by the average z-values was not significantly different for SE-EPI compared to the S(2)-signal but was slightly lower for the S(2)-signal (6.74 +/- 0.32 for the TR = 15 ms protocol and 7.51 +/- 0.78 for the TR = 27 ms protocol) compared to SE-EPI (7.49 +/- 1.44 and 8.05 +/- 1.67) using the same activated voxels, respectively. The relative signal changes in these voxels upon activation were slightly lower for SE-EPI (2.37% +/- 0.18%) compared to the TR = 15 ms S(2)-SSFP protocol (2.75% +/- 0.53%) and significantly lower than the TR = 27 ms protocol (5.38% +/- 1.28%), in line with simulations results. The large relative signal change for the long TR SSFP protocol can be explained by contributions from multiple coherence pathways and the low intrinsic intensity of the S(2) signal. In conclusion, whole-brain T(2)-weighted functional MRI with negligible image distortion at 7 T is feasible using the S(2)-SSFP sequence and partially parallel imaging.

Laminar analysis of 7T BOLD using an imposed spatial activation pattern in human V1

With sufficient image encoding, high-resolution fMRI studies are limited by the biological point-spread of the hemodynamic signal. The extent of this spread is determined by the local vascular distribution and by the spatial specificity of blood flow regulation, as well as by measurement parameters that (i) alter the relative sensitivity of the acquisition to activation-induced hemodynamic changes and (ii) determine the image contrast as a function of vessel size. In particular, large draining vessels on the cortical surface are a major contributor to both the BOLD signal change and to the spatial bias of the BOLD activation away from the site of neuronal activity. In this work, we introduce a laminar surface-based analysis method and study the relationship between spatial localization and activation strength as a function of laminar depth by acquiring 1mm isotropic, single-shot EPI at 7 T and sampling the BOLD signal exclusively from the superficial, middle, or deep cortical laminae. We show that highly-accelerated EPI can limit image distortions to the point where a boundary-based registration algorithm accurately aligns the EPI data to the surface reconstruction. The spatial spread of the BOLD response tangential to the cortical surface was analyzed as a function of cortical depth using our surface-based analysis. Although sampling near the pial surface provided the highest signal strength, it also introduced the most spatial error. Thus, avoiding surface laminae improved spatial localization by about 40% at a cost of 36% in z-statistic, implying that optimal spatial resolution in functional imaging of the cortex can be achieved using anatomically-informed spatial sampling to avoid large pial vessels.

A dual echo approach to removing motion artefacts in fMRI time series

In fMRI, subject motion can severely affect data quality. This is a particular problem when movement is correlated with the experimental paradigm as this potentially causes artefactual activation. A method is presented that uses linear regression, to utilise the time course of an image acquired at very short echo time (TE) as a voxel-wise regressor for a second image in the same echo train, that is acquired with high BOLD sensitivity. The value of this approach is demonstrated using task-locked motion combined with visual stimulation. Results obtained at both 1.5 and 3 T show improvements in functional activation maps for individual subjects. The method is straightforward to implement, does not require extra scan time and can easily be embedded in a multi-echo acquisition framework.

MR relaxation in multiple sclerosis

This article provides an overview of relaxation times and their application to normal brain and brain and cord affected by multiple sclerosis. The goal is to provide readers with an intuitive understanding of what influences relaxation times, how relaxation times can be accurately measured, and how they provide specific information about the pathology of MS. The article summarizes significant results from relaxation time studies in the normal human brain and cord and from people who have multiple sclerosis. It also reports on studies that have compared relaxation time results with results from other MR techniques.

Does clinical memory fMRI provide a comprehensive map of medial temporal lobe structures?

Successful clinical application of fMRI tasks requires reliable knowledge about the brain structures mapped by the task. With memory fMRI, diverging evidence exists concerning the location of major signal sources as well as hippocampal contributions. To clarify these issues, we investigated a frequently applied memory test (home town walking) in 33 patients with unilateral medial temporal lobe pathology, comparing healthy and diseased hemispheres. We focused on a detailed investigation of individual fMRI maps on non-transformed high-resolution functional images. Results show a clear dominance of activations around the collateral sulcus, corresponding to parahippocampal and entorhinal cortex activities. Hippocampus activity was absent in the vast majority of patients. The diseased hemispheres showed lower activation than the healthy hemispheres. We conclude that (1) the investigated memory test may be successfully applied for evaluation of the parahippocampal cortex, (2) the hippocampus is not reliably mapped by the task, and (3) the methods described for investigation of individual high-resolution functional images allow generation of application profiles for clinical fMRI tasks.