Avi Snyder

Intrinsic functional architecture in the anaesthetized monkey brain.

The traditional approach to studying brain function is to measure physiological responses to controlled sensory, motor and cognitive paradigms. However, most of the brain’s energy consumption is devoted to ongoing metabolic activity not clearly associated with any particular stimulus or behaviour. Functional magnetic resonance imaging studies in humans aimed at understanding this ongoing activity have shown that spontaneous fluctuations of the blood-oxygen-level-dependent signal occur continuously in the resting state. In humans, these fluctuations are temporally coherent within widely distributed cortical systems that recapitulate the functional architecture of responses evoked by experimentally administered tasks. Here, we show that the same phenomenon is present in anaesthetized monkeys even at anaesthetic levels known to induce profound loss of consciousness. We specifically demonstrate coherent spontaneous fluctuations within three well known systems (oculomotor, somatomotor and visual) and the ‘default’ system, a set of brain regions thought by some to support uniquely human capabilities. Our results indicate that coherent system fluctuations probably reflect an evolutionarily conserved aspect of brain functional organization that transcends levels of consciousness.

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.

Resting-state fMRI in the Human Connectome Project

Resting-state functional magnetic resonance imaging (rfMRI) allows one to study functional connectivity in the brain by acquiring fMRI data while subjects lie inactive in the MRI scanner, and taking advantage of the fact that functionally related brain regions spontaneously co-activate. rfMRI is one of the two primary data modalities being acquired for the Human Connectome Project (the other being diffusion MRI). A key objective is to generate a detailed in vivo mapping of functional connectivity in a large cohort of healthy adults (over 1000 subjects), and to make these datasets freely available for use by the neuroimaging community. In each subject we acquire a total of 1h of whole-brain rfMRI data at 3 T, with a spatial resolution of 2×2×2 mm and a temporal resolution of 0.7s, capitalizing on recent developments in slice-accelerated echo-planar imaging. We will also scan a subset of the cohort at higher field strength and resolution. In this paper we outline the work behind, and rationale for, decisions taken regarding the rfMRI data acquisition protocol and pre-processing pipelines, and present some initial results showing data quality and example functional connectivity analyses.

Function in the human connectome: task-fMRI and individual differences in behavior.

The primary goal of the Human Connectome Project (HCP) is to delineate the typical patterns of structural and functional connectivity in the healthy adult human brain. However, we know that there are important individual differences in such patterns of connectivity, with evidence that this variability is associated with alterations in important cognitive and behavioral variables that affect real world function. The HCP data will be a critical stepping-off point for future studies that will examine how variation in human structural and functional connectivity play a role in adult and pediatric neurological and psychiatric disorders that account for a huge amount of public health resources. Thus, the HCP is collecting behavioral measures of a range of motor, sensory, cognitive and emotional processes that will delineate a core set of functions relevant to understanding the relationship between brain connectivity and human behavior. In addition, the HCP is using task-fMRI (tfMRI) to help delineate the relationships between individual differences in the neurobiological substrates of mental processing and both functional and structural connectivity, as well as to help characterize and validate the connectivity analyses to be conducted on the structural and functional connectivity data. This paper describes the logic and rationale behind the development of the behavioral, individual difference, and tfMRI batteries and provides preliminary data on the patterns of activation associated with each of the fMRI tasks, at both group and individual levels.

Disability in optic neuritis correlates with diffusion tensor-derived directional diffusivities

Objective: To determine the potential of directional diffusivities from diffusion tensor imaging (DTI) to predict clinical outcome of optic neuritis (ON), and correlate with vision, optical coherence tomography (OCT), and visual evoked potentials (VEP). Methods: Twelve cases of acute and isolated ON were imaged within 30 days of onset and followed prospectively. Twenty-eight subjects with a remote clinical history of ON were studied cross-sectionally. Twelve healthy controls were imaged for comparison. DTI data were acquired at 3T with a surface coil and 1.3 × 1.3 × 1.3 mm3 isotropic voxels. Results: Normal DTI parameters (mean ± SD, μm2/ms) were axial diffusivity = 1.66 ± 0.18, radial diffusivity = 0.81 ± 0.26, apparent diffusion coefficient (ADC) = 1.09 ± 0.21, and fractional anisotropy (FA) = 0.43 ± 0.15. Axial diffusivity decreased up to 2.5 SD in acute ON. The decrease in axial diffusivity at onset correlated with visual contrast sensitivity 1 month (r = 0.59) and 3 months later (r = 0.65). In three subjects followed from the acute through the remote stage, radial diffusivity subsequently increased to >2.5 SD above normal, as did axial diffusivity and ADC. In remote ON, radial diffusivity correlated with OCT (r = 0.81), contrast sensitivity (r = 0.68), visual acuity (r = 0.56), and VEP (r = 0.54). Conclusion: In acute and isolated demyelination, axial diffusivity merits further investigation as a predictor of future clinical outcome. Diffusion parameters are dynamic in acute and isolated optic neuritis, with an initial acute decrease in axial diffusivity. In remote disease, radial diffusivity correlates with functional, structural, and physiologic tests of vision.

Frequency specific interactions of MEG resting state activity within and across brain networks as revealed by the multivariate interaction measure.

Resting state networks (RSNs) are sets of brain regions exhibiting temporally coherent activity fluctuations in the absence of imposed task structure. RSNs have been extensively studied with fMRI in the infra-slow frequency range (nominally <10(-1)Hz). The topography of fMRI RSNs reflects stationary temporal correlation over minutes. However, neuronal communication occurs on a much faster time scale, at frequencies nominally in the range of 10(0)-10(2)Hz. We examined phase-shifted interactions in the delta (2-3.5 Hz), theta (4-7 Hz), alpha (8-12 Hz) and beta (13-30 Hz) frequency bands of resting-state source space MEG signals. These analyses were conducted between nodes of the dorsal attention network (DAN), one of the most robust RSNs, and between the DAN and other networks. Phase shifted interactions were mapped by the multivariate interaction measure (MIM), a measure of true interaction constructed from the maximization of imaginary coherency in the virtual channels comprised of voxel signals in source space. Non-zero-phase interactions occurred between homologous left and right hemisphere regions of the DAN in the delta and alpha frequency bands. Even stronger non-zero-phase interactions were detected between networks. Visual regions bilaterally showed phase-shifted interactions in the alpha band with regions of the DAN. Bilateral somatomotor regions interacted with DAN nodes in the beta band. These results demonstrate the existence of consistent, frequency specific phase-shifted interactions on a millisecond time scale between cortical regions within RSN as well as across RSNs.

Adding dynamics to the Human Connectome Project with MEG

The Human Connectome Project (HCP) seeks to map the structural and functional connections between network elements in the human brain. Magnetoencephalography (MEG) provides a temporally rich source of information on brain network dynamics and represents one source of functional connectivity data to be provided by the HCP. High quality MEG data will be collected from 50 twin pairs both in the resting state and during performance of motor, working memory and language tasks. These data will be available to the general community. Additionally, using the cortical parcellation scheme common to all imaging modalities, the HCP will provide processing pipelines for calculating connection matrices as a function of time and frequency. Together with structural and functional data generated using magnetic resonance imaging methods, these data represent a unique opportunity to investigate brain network connectivity in a large cohort of normal adult human subjects. The analysis pipeline software and the dynamic connectivity matrices that it generates will all be made freely available to the research community.

Increased diffusivity in acute multiple sclerosis lesions predicts risk of black hole

Objective: Diffusion tensor imaging (DTI) quantifies Brownian motion of water within tissue. Inflammation leads to tissue injury, resulting in increased diffusivity and decreased directionality. We hypothesize that DTI can quantify the damage within acute multiple sclerosis (MS) white matter lesions to predict gadolinium (Gd)-enhancing lesions that will persist 12 months later as T1 hypointensities. Methods: A cohort of 22 individuals underwent 7 brain MRI scans over 15 months. DTI parameters were temporally quantified within regions of Gd enhancement. Comparison to the homologous region in the hemisphere contralateral to the Gd-enhancing lesion was also performed to standardize individual lesion DTI parameters. Results: After classifying each Gd-enhancing region as to black hole outcome, radial diffusivity, mean diffusivity, and fractional anisotropy, along with their standardized values, were significantly altered for persistent black holes (PBHs), and remained elevated throughout the study. A Gd-enhancing region with a 40% elevation in radial diffusivity had a 5.4-fold (95% confidence interval [CI]: 2.1, 13.8) increased risk of becoming a PBH, with 70% (95% CI: 51%, 85%) sensitivity and 69% (95% CI: 57%, 80%) specificity. A model of radial diffusivity, with volume and length of Gd enhancement, was associated with a risk of becoming a PBH of 5.0 (95% CI: 2.6, 9.9). Altered DTI parameters displayed a dose relationship to duration of black hole persistence. Conclusions: Elevated radial diffusivity during gadolinium enhancement was associated with increased risk for development of a persistent black hole, a surrogate of severe demyelination and axonal injury. An elevated radial diffusivity within active multiple sclerosis lesions may be indicative of more severe tissue injury.