Noam Harel

The Human Connectome Project: A data acquisition perspective

The Human Connectome Project (HCP) is an ambitious 5-year effort to characterize brain connectivity and function and their variability in healthy adults. This review summarizes the data acquisition plans being implemented by a consortium of HCP investigators who will study a population of 1200 subjects (twins and their non-twin siblings) using multiple imaging modalities along with extensive behavioral and genetic data. The imaging modalities will include diffusion imaging (dMRI), resting-state fMRI (R-fMRI), task-evoked fMRI (T-fMRI), T1- and T2-weighted MRI for structural and myelin mapping, plus combined magnetoencephalography and electroencephalography (MEG/EEG). Given the importance of obtaining the best possible data quality, we discuss the efforts underway during the first two years of the grant (Phase I) to refine and optimize many aspects of HCP data acquisition, including a new 7T scanner, a customized 3T scanner, and improved MR pulse sequences.

Multiband multislice GE-EPI at 7 tesla, with 16-fold acceleration using partial parallel imaging with application to high spatial and temporal whole-brain fMRI†

Parallel imaging in the form of multiband radiofrequency excitation, together with reduced k‐space coverage in the phase‐encode direction, was applied to human gradient echo functional MRI at 7 T for increased volumetric coverage and concurrent high spatial and temporal resolution. Echo planar imaging with simultaneous acquisition of four coronal slices separated by 44mm and simultaneous 4‐fold phase‐encoding undersampling, resulting in 16‐fold acceleration and up to 16‐fold maximal aliasing, was investigated. Task/stimulus‐induced signal changes and temporal signal behavior under basal conditions were comparable for multiband and standard single‐band excitation and longer pulse repetition times. Robust, whole‐brain functional mapping at 7 T, with 2 × 2 × 2mm3 (pulse repetition time 1.25 sec) and 1 × 1 × 2mm3 (pulse repetition time 1.5 sec) resolutions, covering fields of view of 256 × 256 × 176mm3 and 192 × 172 × 176mm3, respectively, was demonstrated with current gradient performance. Magn Reson Med 63:1144–1153, 2010.

High-field fMRI unveils orientation columns in humans

Functional (f)MRI has revolutionized the field of human brain research. fMRI can noninvasively map the spatial architecture of brain function via localized increases in blood flow after sensory or cognitive stimulation. Recent advances in fMRI have led to enhanced sensitivity and spatial accuracy of the measured signals, indicating the possibility of detecting small neuronal ensembles that constitute fundamental computational units in the brain, such as cortical columns. Orientation columns in visual cortex are perhaps the best known example of such a functional organization in the brain. They cannot be discerned via anatomical characteristics, as with ocular dominance columns. Instead, the elucidation of their organization requires functional imaging methods. However, because of insufficient sensitivity, spatial accuracy, and image resolution of the available mapping techniques, thus far, they have not been detected in humans. Here, we demonstrate, by using high-field (7-T) fMRI, the existence and spatial features of orientation- selective columns in humans. Striking similarities were found with the known spatial features of these columns in monkeys. In addition, we found that a larger number of orientation columns are devoted to processing orientations around 90° (vertical stimuli with horizontal motion), whereas relatively similar fMRI signal changes were observed across any given active column. With the current proliferation of high-field MRI systems and constant evolution of fMRI techniques, this study heralds the exciting prospect of exploring unmapped and/or unknown columnar level functional organizations in the human brain.

Origin of negative blood oxygenation level-dependent fMRI signals

Functional magnetic resonance imaging (fMRI) techniques are based on the assumption that changes in spike activity are accompanied by modulation in the blood oxygenation level—dependent (BOLD) signal. In addition to conventional increases in BOLD signals, sustained negative BOLD signal changes are occasionally observed and are thought to reflect a decrease in neural activity. In this study, the source of the negative BOLD signal was investigated using T2*-weighted BOLD and cerebral blood volume (CBV) techniques in isoflurane-anesthetized cats. A positive BOLD signal change was observed in the primary visual cortex (area 18) during visual stimulation, while a prolonged negative BOLD change was detected in the adjacent suprasylvian gyrus containing higher-order visual areas. However, in both regions neurons are known to increase spike activity during visual stimulation. The positive and negative BOLD amplitudes obtained at six spatial-frequency stimuli were highly correlated, and negative BOLD percent changes were approximately one third of the postitive changes. Area 18 with positive BOLD signals experienced an increase in CBV, while regions exhibiting the prolonged negative BOLD signal underwent a decrease in CBV. The CBV changes in area 18 were faster than the BOLD signals from the same corresponding region and the CBV changes in the suprasylvian gyrus. The results support the notion that reallocation of cortical blood resources could overcome a local demand for increased cerebral blood flow induced by increased neural activity. The findings of this study imply that caution should be taken when interpreting the negative BOLD signals as a decrease in neuronal activity.

Reconstruction of the orientation distribution function in single- and multiple-shell q-ball imaging within constant solid angle.

q‐Ball imaging is a high‐angular‐resolution diffusion imaging technique that has been proven very successful in resolving multiple intravoxel fiber orientations in MR images. The standard computation of the orientation distribution function (the probability of diffusion in a given direction) from q‐ball data uses linear radial projection, neglecting the change in the volume element along each direction. This results in spherical distributions that are different from the true orientation distribution functions. For instance, they are neither normalized nor as sharp as expected and generally require postprocessing, such as artificial sharpening. In this paper, a new technique is proposed that, by considering the solid angle factor, uses the mathematically correct definition of the orientation distribution function and results in a dimensionless and normalized orientation distribution function expression. Our model is flexible enough so that orientation distribution functions can be estimated either from single q‐shell datasets or by exploiting the greater information available from multiple q‐shell acquisitions. We show that the latter can be achieved by using a more accurate multiexponential model for the diffusion signal. The improved performance of the proposed method is demonstrated on artificial examples and high‐angular‐resolution diffusion imaging data acquired on a 7‐T magnet. Magn Reson Med, 2010.

An Assessment of Current Brain Targets for Deep Brain Stimulation Surgery With Susceptibility-Weighted Imaging at 7 Tesla

BACKGROUND: Deep brain stimulation (DBS) surgery is used for treating movement disorders, including Parkinson disease, essential tremor, and dystonia. Successful DBS surgery is critically dependent on precise placement of DBS electrodes into target structures. Frequently, DBS surgery relies on normalized atlas-derived diagrams that are superimposed on patient brain magnetic resonance imaging (MRI) scans, followed by microelectrode recording and macrostimulation to refine the ultimate electrode position. Microelectrode recording carries a risk of hemorrhage and requires active patient participation during surgery. OBJECTIVE: To enhance anatomic imaging for DBS surgery using high-field MRI with the ultimate goal of improving the accuracy of anatomic target selection. METHODS: Using a 7-T MRI scanner combined with an array of acquisition schemes using multiple image contrasts, we obtained high-resolution images of human deep nuclei in healthy subjects. RESULTS: Superior image resolution and contrast obtained at 7 T in vivo using susceptibility-weighted imaging dramatically improved anatomic delineation of DBS targets and allowed the identification of internal architecture within these targets. A patient-specific, 3-dimensional model of each target area was generated on the basis of the acquired images. CONCLUSION: Technical developments in MRI at 7 T have yielded improved anatomic resolution of deep brain structures, thereby holding the promise of improving anatomic-based targeting for DBS surgery. Future study is needed to validate this technique in improving the accuracy of targeting in DBS surgery.

A Hough transform global probabilistic approach to multiple-subject diffusion MRI tractography

A global probabilistic fiber tracking approach based on the voting process provided by the Hough transform is introduced in this work. The proposed framework tests candidate 3D curves in the volume, assigning to each one a score computed from the diffusion images, and then selects the curves with the highest scores as the potential anatomical connections. The algorithm avoids local minima by performing an exhaustive search at the desired resolution. The technique is easily extended to multiple subjects, considering a single representative volume where the registered high-angular resolution diffusion images (HARDI) from all the subjects are non-linearly combined, thereby obtaining population-representative tracts. The tractography algorithm is run only once for the multiple subjects, and no tract alignment is necessary. We present experimental results on HARDI volumes, ranging from simulated and 1.5T physical phantoms to 7T and 4T human brain and 7T monkey brain datasets.

Layer-Specific fMRI Reflects Different Neuronal Computations at Different Depths in Human V1

Recent work has established that cerebral blood flow is regulated at a spatial scale that can be resolved by high field fMRI to show cortical columns in humans. While cortical columns represent a cluster of neurons with similar response properties (spanning from the pial surface to the white matter), important information regarding neuronal interactions and computational processes is also contained within a single column, distributed across the six cortical lamina. A basic understanding of underlying neuronal circuitry or computations may be revealed through investigations of the distribution of neural responses at different cortical depths. In this study, we used T2-weighted imaging with 0.7 mm (isotropic) resolution to measure fMRI responses at different depths in the gray matter while human subjects observed images with either recognizable or scrambled (physically impossible) objects. Intact and scrambled images were partially occluded, resulting in clusters of activity distributed across primary visual cortex. A subset of the identified clusters of voxels showed a preference for scrambled objects over intact; in these clusters, the fMRI response in middle layers was stronger during the presentation of scrambled objects than during the presentation of intact objects. A second experiment, using stimuli targeted at either the magnocellular or the parvocellular visual pathway, shows that laminar profiles in response to parvocellular-targeted stimuli peak in more superficial layers. These findings provide new evidence for the differential sensitivity of high-field fMRI to modulations of the neural responses at different cortical depths.

Comprehensive in vivo mapping of the human basal ganglia and thalamic connectome in individuals using 7T MRI.

Basal ganglia circuits are affected in neurological disorders such as Parkinsons disease (PD), essential tremor, dystonia and Tourette syndrome. Understanding the structural and functional connectivity of these circuits is critical for elucidating the mechanisms of the movement and neuropsychiatric disorders, and is vital for developing new therapeutic strategies such as deep brain stimulation (DBS). Knowledge about the connectivity of the human basal ganglia and thalamus has rapidly evolved over recent years through non-invasive imaging techniques, but has remained incomplete because of insufficient resolution and sensitivity of these techniques. Here, we present an imaging and computational protocol designed to generate a comprehensive in vivo and subject-specific, three-dimensional model of the structure and connections of the human basal ganglia. High-resolution structural and functional magnetic resonance images were acquired with a 7-Tesla magnet. Capitalizing on the enhanced signal-to-noise ratio (SNR) and enriched contrast obtained at high-field MRI, detailed structural and connectivity representations of the human basal ganglia and thalamus were achieved. This unique combination of multiple imaging modalities enabled the in-vivo visualization of the individual human basal ganglia and thalamic nuclei, the reconstruction of seven white-matter pathways and their connectivity probability that, to date, have only been reported in animal studies, histologically, or group-averaged MRI population studies. Also described are subject-specific parcellations of the basal ganglia and thalamus into sub-territories based on their distinct connectivity patterns. These anatomical connectivity findings are supported by functional connectivity data derived from resting-state functional MRI (R-fMRI). This work demonstrates new capabilities for studying basal ganglia circuitry, and opens new avenues of investigation into the movement and neuropsychiatric disorders, in individual human subjects.

The spatial dependence of the poststimulus undershoot as revealed by high-resolution BOLD- and CBV-weighted fMRI.

The hemodynamic response to neural activity consists of changes in blood flow, blood volume and oxygen metabolism. Changes in the vascular state after sensory stimulation have different spatial and temporal characteristics in the brain. This has been shown using imaging techniques, such as BOLD functional magnetic resonance imaging (fMRI), which monitor vascular changes once the stimulus is turned on, and the eventual return to baseline levels, once the stimulus is turned off. The BOLD fMRI signal during sensory stimulation has been well characterized and modeled in terms of the spatial and temporal characteristics of the vascular response. However, the return of the signals to baseline levels after sensory stimulation is not as well characterized. During this period, a poststimulus undershoot in the BOLD signal is observed. This poststimulus undershoot has been modeled and investigated to characterize the physiological mechanisms (cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral oxygen consumption) associated with the response. However, the data in the literature, which lack any spatially dependent information, appear to be contradictory in terms of the mechanisms associated with this poststimulus response. With a high spatial resolution cat model at 9.4 T, we show that CBV changes in the tissue persist once the stimulus is turned off, while CBV changes in the surface vessels quickly return to baseline levels, despite a concurrent undershoot in the BOLD signal in both the tissue and surface vessel areas. In addition, the BOLD data alone indicate that different physiological mechanisms regulate the poststimulus response in the tissue versus the surface vessel regions.