Jeff H. Duyn

Dynamic functional connectivity: promise, issues, and interpretations.

The brain must dynamically integrate, coordinate, and respond to internal and external stimuli across multiple time scales. Non-invasive measurements of brain activity with fMRI have greatly advanced our understanding of the large-scale functional organization supporting these fundamental features of brain function. Conclusions from previous resting-state fMRI investigations were based upon static descriptions of functional connectivity (FC), and only recently studies have begun to capitalize on the wealth of information contained within the temporal features of spontaneous BOLD FC. Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain. Here, we review recent findings, methodological considerations, neural and behavioral correlates, and future directions in the emerging field of dynamic FC investigations.

High-field MRI of brain cortical substructure based on signal phase

The ability to detect brain anatomy and pathophysiology with MRI is limited by the contrast-to-noise ratio (CNR), which depends on the contrast mechanism used and the spatial resolution. In this work, we show that in MRI of the human brain, large improvements in contrast to noise in high-resolution images are possible by exploiting the MRI signal phase at high magnetic field strength. Using gradient-echo MRI at 7.0 tesla and a multichannel detector, a nominal voxel size of 0.24 × 0.24 × 1.0 mm3 (58 nl) was achieved. At this resolution, a strong phase contrast was observed both between as well as within gray matter (GM) and white matter (WM). In gradient-echo phase images obtained on normal volunteers at this high resolution, the CNR between GM and WM ranged from 3:1 to 20:1 over the cortex. This CNR is an almost 10-fold improvement over conventional MRI techniques that do not use image phase, and it is an ≈100-fold improvement when including the gains in resolution from high-field and multichannel detection. Within WM, phase contrast appeared to be associated with the major fiber bundles, whereas contrast within GM was suggestive of the underlying layer structure. The observed phase contrast is attributed to local variations in magnetic susceptibility, which, at least in part, appeared to originate from iron stores. The ability to detect cortical substructure from MRI phase contrast at high field is expected to greatly enhance the study of human brain anatomy in vivo.

Neural basis of global resting-state fMRI activity

Functional MRI (fMRI) has uncovered widespread hemodynamic fluctuations in the brain during rest. Recent electroencephalographic work in humans and microelectrode recordings in anesthetized monkeys have shown this activity to be correlated with slow changes in neural activity. Here we report that the spontaneous fluctuations in the local field potential (LFP) measured from a single cortical site in monkeys at rest exhibit widespread, positive correlations with fMRI signals over nearly the entire cerebral cortex. This correlation was especially consistent in a band of upper gamma-range frequencies (40–80 Hz), for which the hemodynamic signal lagged the neural signal by 6–8 s. A strong, positive correlation was also observed in a band of lower frequencies (2–15 Hz), albeit with a lag closer to zero. The global pattern of correlation with spontaneous fMRI fluctuations was similar whether the LFP signal was measured in occipital, parietal, or frontal electrodes. This coupling was, however, dependent on the monkeys behavioral state, being stronger and anticipatory when the animals’ eyes were closed. These results indicate that the often discarded global component of fMRI fluctuations measured during the resting state is tightly coupled with underlying neural activity.

Decoupling of the brain's default mode network during deep sleep

The recent discovery of a circuit of brain regions that is highly active in the absence of overt behavior has led to a quest for revealing the possible function of this so-called default-mode network (DMN). A very recent study, finding similarities in awake humans and anesthetized primates, has suggested that DMN activity might not simply reflect ongoing conscious mentation but rather a more general form of network dynamics typical of complex systems. Here, by performing functional MRI in humans, it is shown that a natural, sleep-induced reduction of consciousness is reflected in altered correlation between DMN network components, most notably a reduced involvement of frontal cortex. This suggests that DMN may play an important role in the sustenance of conscious awareness.

Unraveling multisensory integration: patchy organization within human STS multisensory cortex

Although early sensory cortex is organized along dimensions encoded by receptor organs, little is known about the organization of higher areas in which different modalities are integrated. We investigated multisensory integration in human superior temporal sulcus using recent advances in parallel imaging to perform functional magnetic resonance imaging (fMRI) at very high resolution. These studies suggest a functional architecture in which information from different modalities is brought into close proximity via a patchy distribution of inputs, followed by integration in the intervening cortex.

Low frequency BOLD fluctuations during resting wakefulness and light sleep: A simultaneous EEG-fMRI study †

Recent blood oxygenation level dependent functional MRI (BOLD fMRI) studies of the human brain have shown that in the absence of external stimuli, activity persists in the form of distinct patterns of temporally correlated signal fluctuations. In this work, we investigated the spontaneous BOLD signal fluctuations during states of reduced consciousness such as drowsiness and sleep. For this purpose, we performed BOLD fMRI on normal subjects during varying levels of consciousness, from resting wakefulness to light (non‐slow wave) sleep. Depth of sleep was determined based on concurrently acquired EEG data. During light sleep, significant increases in the fluctuation level of the BOLD signal were observed in several cortical areas, among which visual cortex was the most significant. Correlations among brain regions involved with the default‐mode network persisted during light sleep. These results suggest that activity in areas such as the default‐mode network and primary sensory cortex, as measured from BOLD fMRI fluctuations, does not require a level of consciousness typical of wakefulness. Hum Brain Mapp, 2008.

Low-frequency fluctuations in the cardiac rate as a source of variance in the resting-state fMRI BOLD signal

Heart rate fluctuations occur in the low-frequency range (<0.1 Hz) probed in functional magnetic resonance imaging (fMRI) studies of resting-state functional connectivity and most fMRI block paradigms and may be related to low-frequency blood-oxygenation-level-dependent (BOLD) signal fluctuations. To investigate this hypothesis, temporal correlations between cardiac rate and resting-state fMRI signal timecourses were assessed at 3 T. Resting-state BOLD fMRI and accompanying physiological data were acquired and analyzed using cross-correlation and regression. Time-shifted cardiac rate timecourses were included as regressors in addition to established physiological regressors (RETROICOR (Glover, G.H., Li, T.Q., Ress, D., 2000. Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magn Reson Med 44, 162-167) and respiration volume per unit time (Birn, R.M., Diamond, J.B., Smith, M.A., Bandettini, P.A., 2006b. Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI. NeuroImage 31, 1536-1548). Significant correlations between the cardiac rate and BOLD signal timecourses were revealed, particularly negative correlations in gray matter at time shifts of 6-12 s and positive correlations at time shifts of 30-42 s (TR=6 s). Regressors consisting of cardiac rate timecourses shifted by delays of between 0 and 24 s explained an additional 1% of the BOLD signal variance on average over the whole brain across 9 subjects, a similar additional variance to that explained by respiration volume per unit time and RETROICOR regressors, even when used in combination with these other physiological regressors. This suggests that including such time-shifted cardiac rate regressors will be beneficial for explaining physiological noise variance and will thereby improve the statistical power in future task-based and resting-state fMRI studies.

Investigation of low frequency drift in fMRI signal

Low frequency drift (0.0-0.015 Hz) has often been reported in time series fMRI data. This drift has often been attributed to physiological noise or subject motion, but no studies have been done to test this assumption. Time series T*2-weighted volumes were acquired on two clinical 1.5 T MRI systems using spiral and EPI readout gradients from cadavers, a normal volunteer, and nonhomogeneous and homogeneous phantoms. The data were tested for significant differences (P = 0.001) from Gaussian noise in the frequency range 0.0-0.015 Hz. The percentage of voxels that were significant in data from the cadaver, normal volunteer, nonhomogeneous and homogeneous phantoms were 13.7-49.0%, 22.1-61.9%, 46.4-68.0%, and 1.10%, respectively. Low frequency drift was more pronounced in regions with high spatial intensity gradients. Significant drifting was present in data acquired from cadavers and nonhomogeneous phantoms and all pulse sequences tested, implying that scanner instabilities and not motion or physiological noise may be the major cause of the drift.

H215O PET validation of steady-state arterial spin tagging cerebral blood flow measurements in humans

Steady‐state arterial spin tagging approaches can provide quantitative images of CBF, but have not been validated in humans. The work presented here compared CBF values measured using steady‐state arterial spin tagging with CBF values measured in the same group of human subjects using the H215O IV bolus PET method. Blood flow values determined by H215O PET were corrected for the known effects of incomplete extraction of water across the blood brain barrier. For a cortical strip ROI, blood flow values determined using arterial spin tagging (64 ± 12 cc/100g/min) were not statistically different from corrected blood flow values determined using H215O PET (67 ± 13 cc/100g/min). However, for a central white matter ROI, blood flow values determined using arterial spin tagging were significantly underestimated compared to corrected blood flow values determined using H215O PET. This underestimation could be caused by an underestimation of the arterial transit time for white matter regions. Magn Reson Med 44:450–456, 2000. Published 2000 Wiley‐Liss, Inc.

Layer-specific variation of iron content in cerebral cortex as a source of MRI contrast

Recent advances in high-field MRI have dramatically improved the visualization of human brain anatomy in vivo. Most notably, in cortical gray matter, strong contrast variations have been observed that appear to reflect the local laminar architecture. This contrast has been attributed to subtle variations in the magnetic properties of brain tissue, possibly reflecting varying iron and myelin content. To establish the origin of this contrast, MRI data from postmortem brain samples were compared with electron microscopy and histological staining for iron and myelin. The results show that iron is distributed over laminae in a pattern that is suggestive of each region’s myeloarchitecture and forms the dominant source of the observed MRI contrast.