Tracy S. Nolan

Cortical network functional connectivity in the descent to sleep

Descent into sleep is accompanied by disengagement of the conscious brain from the external world. It follows that this process should be associated with reduced neural activity in regions of the brain known to mediate interaction with the environment. We examined blood oxygen dependent (BOLD) signal functional connectivity using conventional seed-based analyses in 3 primary sensory and 3 association networks as normal young adults transitioned from wakefulness to light sleep while lying immobile in the bore of a magnetic resonance imaging scanner. Functional connectivity was maintained in each network throughout all examined states of arousal. Indeed, correlations within the dorsal attention network modestly but significantly increased during light sleep compared to wakefulness. Moreover, our data suggest that neuronally mediated BOLD signal variance generally increases in light sleep. These results do not support the view that ongoing BOLD fluctuations primarily reflect unconstrained cognition. Rather, accumulating evidence supports the hypothesis that spontaneous BOLD fluctuations reflect processes that maintain the integrity of functional systems in the brain.

Atypical resting-state functional connectivity of affective pain regions in chronic migraine.

Chronic migraineurs (CM) have painful intolerances to somatosensory, visual, olfactory, and auditory stimuli during and between migraine attacks. These intolerances are suggestive of atypical affective responses to potentially noxious stimuli. We hypothesized that atypical resting‐state functional connectivity (rs‐fc) of affective pain‐processing brain regions may associate with these intolerances. This study compared rs‐fc of affective pain‐processing regions in CM with controls.

Resting states affect spontaneous BOLD oscillations in sensory and paralimbic cortex.

The brain exhibits spontaneous neural activity that depends on the behavioral state of the organism. We asked whether the blood oxygenation level-dependent (BOLD) signal reflects these modulations. BOLD was measured under three steady-state conditions: while subjects kept their eyes closed, kept their eyes open, or while fixating. The BOLD spectral density was calculated across brain voxels and subjects. Visual, sensory-motor, auditory, and retrosplenial cortex showed modulations of the BOLD spectral density by resting state type. All modulated regions showed greater spontaneous BOLD oscillations in the eyes closed than the eyes open or fixation conditions, suggesting that the differences were endogenously driven. Next, we examined the pattern of correlations between regions whose ongoing BOLD signal was modulated by resting state type. Regional neuronal correlations were estimated using an analytic procedure from the comparison of BOLD-BOLD covariances in the fixation and eyes closed conditions. Most regions were highly correlated with one another, with the exception of the primary visual cortices, which showed low correlations with the other regions. In conclusion, changes in resting state were associated with synchronous modulations of spontaneous BOLD oscillations in cortical sensory areas driven by two spatially overlapping, but temporally uncorrelated signals.

Modulation of the brain’s functional network architecture in the transition from wake to sleep

The transition from quiet wakeful rest to sleep represents a period over which attention to the external environment fades. Neuroimaging methodologies have provided much information on the shift in neural activity patterns in sleep, but the dynamic restructuring of human brain networks in the transitional period from wake to sleep remains poorly understood. Analysis of electrophysiological measures and functional network connectivity of these early transitional states shows subtle shifts in network architecture that are consistent with reduced external attentiveness and increased internal and self-referential processing. Further, descent to sleep is accompanied by the loss of connectivity in anterior and posterior portions of the default-mode network and more locally organized global network architecture. These data clarify the complex and dynamic nature of the transitional period between wake and sleep and suggest the need for more studies investigating the dynamics of these processes.

Allodynia and Descending Pain Modulation in Migraine: A Resting State Functional Connectivity Analysis

OBJECTIVE Most migraineurs develop cutaneous allodynia during migraines, and many have cutaneous sensitization between attacks. Atypical pain modulation via the descending pain system may contribute to this sensitization and allodynia. The objective of this study was to test the hypothesis that compared with non-allodynic migraineurs, allodynic migraineurs have atypical periaqueductal gray (PAG) and nucleus cuneiformis (NCF) resting-state functional connectivity (rs-fc) with other pain processing regions. DESIGN Ten minutes resting-state blood-oxygen-level-dependent data were collected from 38 adult migraineurs and 20 controls. Seed-based analyses compared whole-brain rs-fc with PAG and with NCF in migraineurs with severe ictal allodynia (N = 8) to migraineurs with no ictal allodynia (N = 8). Correlations between the strength of functional connections that differed between severely allodynic and non-allodynic migraineurs with allodynia severity were determined for all migraineurs (N = 38). PAG and NCF rs-fc in all migraineurs was compared with rs-fc in controls. RESULTS Migraineurs with severe allodynia had stronger PAG and NCF rs-fc to other brainstem, thalamic, insula and cerebellar regions that participate in discriminative pain processing, as well as to frontal and temporal regions implicated in higher order pain modulation. Evidence that these rs-fc differences were specific for allodynia included: 1) strong correlations between some rs-fc strengths and allodynia severity among all migraineurs; and 2) absence of overlap when comparing rs-fc differences in severely allodynic vs non-allodynic migraineurs with those in all migraineurs vs controls. CONCLUSION Atypical rs-fc of brainstem descending modulatory pain regions with other brainstem and higher order pain-modulating regions is associated with migraine-related allodynia.

Morning-evening variation in human brain metabolism and memory circuits

It has been posited that a critical function of sleep is synaptic renormalization following a net increase in synaptic strength during wake. We hypothesized that wake would alter the resting-state functional organization of the brain and increase its metabolic cost. To test these hypotheses, two experiments were performed. In one, we obtained morning and evening resting-state functional MRI scans to assess changes in functional brain organization. In the second experiment, we obtained quantitative positron emission tomography measures of glucose and oxygen consumption to assess the cost of wake. We found selective changes in brain organization. Most prominently, bilateral medial temporal regions were locally connected in the morning but in the evening exhibited strong correlations with frontal and parietal brain regions involved in memory retrieval. We speculate that these changes may reflect aspects of memory consolidation recurring on a daily basis. Surprisingly, these changes in brain organization occurred without increases in brain metabolism.

Characterization of Scale-Free Properties of Human Electrocorticography in Awake and Slow Wave Sleep States

Like many complex dynamic systems, the brain exhibits scale-free dynamics that follow power-law scaling. Broadband power spectral density (PSD) of brain electrical activity exhibits state-dependent power-law scaling with a log frequency exponent that varies across frequency ranges. Widely divergent naturally occurring neural states, awake and slow wave sleep (SWS), were used to evaluate the nature of changes in scale-free indices of brain electrical activity. We demonstrate two analytic approaches to characterizing electrocorticographic (ECoG) data obtained during awake and SWS states. A data-driven approach was used, characterizing all available frequency ranges. Using an equal error state discriminator (EESD), a single frequency range did not best characterize state across data from all six subjects, though the ability to distinguish awake and SWS ECoG data in individual subjects was excellent. Multi-segment piecewise linear fits were used to characterize scale-free slopes across the entire frequency range (0.2–200 Hz). These scale-free slopes differed between awake and SWS states across subjects, particularly at frequencies below 10 Hz and showed little difference at frequencies above 70 Hz. A multivariate maximum likelihood analysis (MMLA) method using the multi-segment slope indices successfully categorized ECoG data in most subjects, though individual variation was seen. In exploring the differences between awake and SWS ECoG data, these analytic techniques show that no change in a single frequency range best characterizes differences between these two divergent biological states. With increasing computational tractability, the use of scale-free slope values to characterize ECoG and EEG data will have practical value in clinical and research studies.

Automated measurement of pediatric cranial bone thickness and density from clinical computed tomography

Skull thickness and density measures of normal pediatric crania would inform multiple disciplines including neurosurgery, optical and magnetoelectrophysiological imaging, and biomechanical modeling of head trauma. We report on a new method for automated extraction of in vivo skull thickness and density measures of pediatric crania based on x-ray computed tomography scans (CT). Data were obtained from a clinical image repository for pediatric populations in whom no pathology was noted. Skull thickness and density measures were systematically obtained across the calvarium. We find a set of measures that correlated with physiological age that are likely to prove useful in multiple disciplines.

Sources of non-physiologic noise in simultaneous EEG-fMRI data: A phantom study

Simultaneous EEG-fMRI studies require an understanding of the noise characteristics of the acquisition environment so that appropriate pre-processing steps may be taken to remove known artifacts from the data stream. Using a phantom approach, we have developed a general methodology for characterizing non-physiologic noise in EEG signal and demonstrate the use of this methodology for a specific MR scanner and EEG data acquisition system configuration. Our results show the δ frequency band is significantly impacted by baseline drift or baseline correction algorithms while the β and γ bands are impacted by residual gradient artifact and gradient corrections.

The public cancer radiology imaging collections of The Cancer Imaging Archive

The Cancer Imaging Archive (TCIA) is the U.S. National Cancer Institute’s repository for cancer imaging and related information. TCIA contains 30.9 million radiology images representing data collected from approximately 37,568 subjects. This data is organized into collections by tumor-type with many collections also including analytic results or clinical data. TCIA staff carefully de-identify and curate all incoming collections prior to making the information available via web browser or programmatic interfaces. Each published collection within TCIA is assigned a Digital Object Identifier that references the collection. Additionally, researchers who use TCIA data may publish the subset of information used in their analysis by requesting a TCIA generated Digital Object Identifier. This data descriptor is a review of a selected subset of existing publicly available TCIA collections. It outlines the curation and publication methods employed by TCIA and makes available 15 collections of cancer imaging data.