A baseline or control state is fundamental to the understanding of most complex systems. Defining a baseline state in the human brain, arguably our most complex system, poses a particular challenge. Many suspect that left unconstrained, its activity will vary unpredictably. Despite this prediction we identify a baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF. The OEF is defined as the ratio of oxygen used by the brain to oxygen delivered by flowing blood and is remarkably uniform in the awake but resting state (e.g., lying quietly with eyes closed). Local deviations in the OEF represent the physiological basis of signals of changes in neuronal activity obtained with functional MRI during a wide variety of human behaviors. We used quantitative metabolic and circulatory measurements from positron-emission tomography to obtain the OEF regionally throughout the brain. Areas of activation were conspicuous by their absence. All significant deviations from the mean hemisphere OEF were increases, signifying deactivations, and resided almost exclusively in the visual system. Defining the baseline state of an area in this manner attaches meaning to a group of areas that consistently exhibit decreases from this baseline, during a wide variety of goal-directed behaviors monitored with positron-emission tomography and functional MRI. These decreases suggest the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.

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A default mode of brain function.

AFNI: software for analysis and visualization of functional magnetic resonance neuroimages

Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.

The organization of the human cerebral cortex estimated by intrinsic functional connectivity

Magnetoencephalography (MEG) is a noninvasive technique for investigating neuronal activity in the living human brain. The time resolution of the method is better than 1 ms and the spatial discrimination is, under favorable circumstances, 2-3 mm for sources in the cerebral cortex. In MEG studies, the weak 10 fT-1 pT magnetic fields produced by electric currents flowing in neurons are measured with multichannel SQUID (superconducting quantum interference device) gradiometers. The sites in the cerebral cortex that are activated by a stimulus can be found from the detected magnetic-field distribution, provided that appropriate assumptions about the source render the solution of the inverse problem unique. Many interesting properties of the working human brain can be studied, including spontaneous activity and signal processing following external stimuli. For clinical purposes, determination of the locations of epileptic foci is of interest. The authors begin with a general introduction and a short discussion of the neural basis of MEG. The mathematical theory of the method is then explained in detail, followed by a thorough description of MEG instrumentation, data analysis, and practical construction of multi-SQUID devices. Finally, several MEG experiments performed in the authors' laboratory are described, covering studies of evoked responses and of spontaneous activity in both healthy and diseased brains. Many MEG studies by other groups are discussed briefly as well.

/pdf/magnetoencephalography-theory-instrumentation-and-1oezfk882m.pdf

Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain

The WU-Minn Human Connectome Project: An Overview

We report that visual stimulation produces an easily detectable (5-20%) transient increase in the intensity of water proton magnetic resonance signals in human primary visual cortex in gradient echo images at 4-T magnetic-field strength. The observed changes predominantly occur in areas containing gray matter and can be used to produce high-spatial-resolution functional brain maps in humans. Reducing the image-acquisition echo time from 40 msec to 8 msec reduces the amplitude of the fractional signal change, suggesting that it is produced by a change in apparent transverse relaxation time T*2. The amplitude, sign, and echo-time dependence of these intrinsic signal changes are consistent with the idea that neural activation increases regional cerebral blood flow and concomitantly increases venous-blood oxygenation.

https://www.pnas.org/content/pnas/89/13/5951.full.pdf

Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging

Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model.

For the first time, we demonstrate here functional magnetic resonance imaging (fMRI) using intermolecular multiple-quantum coherences (iMQCs). iMQCs are normally not observed in liquid-state NMR because dipolar interactions between spins average to zero. If the magnetic isotropy of the sample is broken through the use of magnetic field gradients, dipolar couplings can reappear, and hence iMQCs can be observed. Conventional (BOLD) fMRI measures susceptibility variations averaged over each voxel. In the experiment performed here, the sensitivity of iMQCs to frequency variations over mesoscopic and well-defined distances is exploited. We show that iMQC contrast is qualitatively and quantitatively different from BOLD contrast in a visual stimulation task. While the number of activated pixels is smaller in iMQC contrast, the intensity change in some pixels exceeds that of BOLD contrast severalfold. © 2000 Elsevier Science Inc. All rights reserved.

Rapid communication Functional magnetic resonance imaging with intermolecular multiple-quantum coherences

ofmetabolites. Precise adjustment of higher-order shims, whichwas achieved with FASTMAP, was crucial to beneﬁt from thishigh magnetic ﬁeld. Sensitivity improvements were evidentfrom single-shot spectra and from the direct detection of glu-cose at 5.23 ppm in 8-ml volumes. The linewidth of the creatinemethyl resonance was at best 9 Hz. In spite of the increasedlinewidth of singlet resonances at 7 T, the ability to resolveoverlapping multiplets of J-coupled spin systems, such as glu-tamine and glutamate, was substantially increased. Character-istic spectral patterns of metabolites, e.g.,

http://core.ac.uk/download/pdf/12652299.pdf

In Vivo 1 H NMR Spectroscopy of the Human Brain at 7 T

Experiments were conducted on a 90-cm bore whole body 7 Tesla magnet interfaced with a Varian (Freemont, CA) console. Using a quadrature surface coil sensitive to the occipital cortex, a sagittal slice, 6 mm away from the midline, is selected. An IR prepared Turbo-FLASH sequence (matrix: 256x256, TI: 1.4 s, FOV: 20x20 cm’, slice thickness: 5 mm) was used to obtain an anatomic image of the slice. For fMRI studies, a T2*-weighted EPI sequence (matrix: 64x64 matrix, FOV: 2Ox2Ocm*, TR: 0.4 s, TE: 15 msec, slice thickness: 5mm, and an average flip angle of 30’) with half-Fourier acquisition was used. During the fMlU data acquisition, the subject’s respiration and heartbeat were monitored for subsequent removal of physiological noise. Four subjects participated in this study, with proper written consent and institutional approval. Two to 4 runs were performed in each subject and each run consisted of an initial baseline of 100 images and 4 epochs, each lasting 50 s. In each epoch, the visual stimulus (red LED goggles flashing at 8 Hz), synchronized with the scanner, was turned on for 4 s and off in the rest of the epoch. The acquired fMlU data were preprocessed for

/pdf/observation-of-the-initial-dip-in-fmr1-signal-in-human-4ag5x0w71g.pdf

Hellmut Merkle

Papers

Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging

Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model.

Rapid communication Functional magnetic resonance imaging with intermolecular multiple-quantum coherences

In Vivo 1 H NMR Spectroscopy of the Human Brain at 7 T

Observation of the Initial "Dip" in fMR1 Signal in Human Visual Cortex at 7 Tesla