OBJECTIVE: To determine whether ascending arousal network (AAn) connectivity is reduced in patients presenting with traumatic coma. METHODS: We performed high-angular-resolution diffusion imaging in 16 patients with acute severe traumatic brain injury who were comatose on admission and in 16 matched controls. We used probabilistic tractography to measure the connectivity probability (CP) of AAn axonal pathways linking the brainstem tegmentum to the hypothalamus, thalamus, and basal forebrain. To assess the spatial specificity of CP differences between patients and controls, we also measured CP within 4 subcortical pathways outside the AAn. RESULTS: Compared to controls, patients showed a reduction in AAn pathways connecting the brainstem tegmentum to a region of interest encompassing the hypothalamus, thalamus, and basal forebrain. When each pathway was examined individually, brainstem-hypothalamus and brainstem-thalamus CPs, but not brainstem-forebrain CP, were significantly reduced in patients. Only 1 subcortical pathway outside the AAn showed reduced CP in patients. CONCLUSIONS: We provide initial evidence for the reduced integrity of axonal pathways linking the brainstem tegmentum to the hypothalamus and thalamus in patients presenting with traumatic coma. Our findings support current conceptual models of coma as being caused by subcortical AAn injury. AAn connectivity mapping provides an opportunity to advance the study of human coma and consciousness.

To determine whether the rich-club organization, essential for information transport in the human connectome, is an important biomarker of functional outcome after acute ischemic stroke (AIS). Consecutive AIS patients ( = 344) with acute brain magnetic resonance imaging (MRI) (<48 h) were eligible for this study. Each patient underwent a clinical MRI protocol, which included diffusion weighted imaging (DWI). All DWIs were registered to a template on which rich-club regions have been defined. Using manual outlines of stroke lesions, we automatically counted the number of affected rich-club regions and assessed its effect on the National Institute of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS; obtained at 90 days post-stroke) scores through ordinal regression. Of 344 patients (median age 65, inter-quartile range 54-76 years) with a median DWI lesion volume (DWIv) of 3cc, 64% were male. We established that an increase in number of rich-club regions affected by a stroke increases the odds of poor stroke outcome, measured by NIHSS (OR: 1.77, 95%CI 1.41-2.21) and mRS (OR: 1.38, 95%CI 1.11-1.73). Additionally, we demonstrated that the OR exceeds traditional markers, such as DWIv (OR 1.08, 95%CI 1.06-1.11; OR 1.05, 95%CI 1.03-1.07) and age (OR 1.03, 95%CI 1.01-1.05; OR 1.05, 95%CI 1.03-1.07). In this proof-of-concept study, the number of rich-club nodes affected by a stroke lesion presents a translational biomarker of stroke outcome, which can be readily assessed using standard clinical AIS imaging protocols and considered in functional outcome prediction models beyond traditional factors.

Background and Purpose- The ability to model long-term functional outcomes after acute ischemic stroke represents a major clinical challenge. One approach to potentially improve prediction modeling involves the analysis of connectomics. The field of connectomics represents the brain's connectivity as a graph, whose topological properties have helped uncover underlying mechanisms of brain function in health and disease. Specifically, we assessed the impact of stroke lesions on rich club organization, a high capacity backbone system of brain function. Methods- In a hospital-based cohort of 41 acute ischemic stroke patients, we investigated the effect of acute infarcts on the brain's prestroke rich club backbone and poststroke functional connectomes with respect to poststroke outcome. Functional connectomes were created using 3 anatomic atlases, and characteristic path-length () was calculated for each connectome. The number of rich club regions affected were manually determined using each patient's diffusion weighted image. We investigated differences in with respect to outcome (modified Rankin Scale score; 90 days) and the National Institutes of Health Stroke Scale (NIHSS; early: 2-5 days; late: 90-day follow-up). Furthermore, we assessed the effect of including number of rich club regions and in outcome models, using linear regression and assessing the explained variance (R). Results- Of 41 patients (mean age [range]: 70 [45-89] years), 61% were male. Lower was generally associated with better outcome. Including number of rich club regions in the backward selection models of outcome, R increased between 1.3- and 2.6-fold beyond that of traditional markers (age and acute lesion volume) for NIHSS and modified Rankin Scale score. Conclusions- In this proof-of-concept study, we showed that information on network topology can be leveraged to improve modeling of poststroke functional outcome. Future studies are warranted to validate this approach in larger prospective studies of outcome prediction in stroke.

Integrity of the default mode network (DMN) is believed to be essential for human consciousness. However, the effects of acute severe traumatic brain injury (TBI) on DMN functional connectivity are poorly understood. Furthermore, the temporal dynamics of DMN reemergence during recovery of consciousness have not been studied longitudinally in patients with acute severe TBI. We performed resting-state functional magnetic resonance imaging (rs-fMRI) to measure DMN connectivity in 17 patients admitted to the intensive care unit (ICU) with acute severe TBI and in 16 healthy control subjects. Eight patients returned for follow-up rs-fMRI and behavioral assessment six months post-injury. At each time point, we analyzed DMN connectivity by measuring intra-network correlations (i.e. positive correlations between DMN nodes) and inter-network anticorrelations (i.e. negative correlations between the DMN and other resting-state networks). All patients were comatose upon arrival to the ICU and had a disorder of consciousness (DoC) at the time of acute rs-fMRI (9.2 ± 4.6 days post-injury): 2 coma, 4 unresponsive wakefulness syndrome, 7 minimally conscious state, and 4 post-traumatic confusional state. We found that, while DMN anticorrelations were absent in patients with acute DoC, patients who recovered from coma to a minimally conscious or confusional state while in the ICU showed partially preserved DMN correlations. Patients who remained in coma or unresponsive wakefulness syndrome in the ICU showed no DMN correlations. All eight patients assessed longitudinally recovered beyond the confusional state by 6 months post-injury and showed normal DMN correlations and anticorrelations, indistinguishable from those of healthy subjects. Collectively, these findings suggest that recovery of consciousness after acute severe TBI is associated with partial preservation of DMN correlations in the ICU, followed by long-term normalization of DMN correlations and anticorrelations. Both intra-network DMN correlations and inter-network DMN anticorrelations may be necessary for full recovery of consciousness after acute severe TBI.

BACKGROUND: The etiology of altered consciousness in patients with high-grade aneurysmal subarachnoid hemorrhage (SAH) is not thoroughly understood. We hypothesized that decreased cerebral blood flow (CBF) in brain regions critical to consciousness may contribute. METHODS: We retrospectively evaluated arterial-spin labeled (ASL) perfusion magnetic resonance imaging (MRI) measurements of CBF in 12 patients with aneurysmal SAH admitted to our neurocritical care unit. CBF values were analyzed within gray matter nodes of the default mode network (DMN), whose functional integrity has been shown to be necessary for consciousness. DMN nodes studied were the bilateral medial prefrontal cortices, thalami, and posterior cingulate cortices. Correlations between nodal CBF and admission Glasgow Coma Scale (GCS) score, admission Hunt and Hess (HH) class, and GCS score at the time of MRI (MRI GCS) were tested. RESULTS: Spearman's correlation coefficients were not significant when comparing admission GCS, admission HH, and MRI GCS versus nodal CBF (p > 0.05). However, inter-rater reliability for nodal CBF was high (r = 0.71, p = 0.01). CONCLUSIONS: In this retrospective pilot study, we did not identify significant correlations between CBF and admission GCS, admission HH class, or MRI GCS for any DMN node. Potential explanations for these findings include small sample size, ASL data acquisition at variable times after SAH onset, and CBF analysis in DMN nodes that may not reflect the functional integrity of the entire network. High inter-rater reliability suggests ASL measurements of CBF within DMN nodes are reproducible. Larger prospective studies are needed to elucidate whether decreased cerebral perfusion contributes to altered consciousness in SAH.

Loss of function and subsequent spontaneous recovery after stroke have been associated with physiological and anatomical alterations in neuronal networks in the brain. However, the spatiotemporal pattern of such changes has been incompletely characterized. Manganese-enhanced MRI (MEMRI) provides a unique tool for in vivo investigation of neuronal connectivity. In this study, we measured manganese-induced changes in longitudinal relaxation rate, R(1), to assess the spatiotemporal pattern of manganese distribution after focal injection into the intact sensorimotor cortex in control rats (n=10), and in rats at 2 weeks after 90-min unilateral occlusion of the middle cerebral artery (n=10). MEMRI data were compared with results from conventional tract tracing with wheat-germ agglutinin horseradish peroxidase (WGA-HRP). Distinct areas of the sensorimotor pathway were clearly visualized with MEMRI. At 2 weeks after stroke, manganese-induced changes in R(1) were significantly delayed and diminished in the ipsilateral caudate putamen, thalamus and substantia nigra. Loss of connectivity between areas of the sensorimotor network was also identified from reduced WGA-HRP staining in these areas on post-mortem brain sections. This study demonstrates that MEMRI enables in vivo assessment of spatiotemporal alterations in neuronal connectivity after stroke, which may lead to improved insights in mechanisms underlying functional loss and recovery after stroke.

Over the past decade, networks have become a leading model to illustrate both the anatomical relationships (structural networks) and the coupling of dynamic physiology (functional networks) linking separate brain regions. The relationship between these two levels of description remains incompletely understood and an area of intense research interest. In particular, it is unclear how cortical currents relate to underlying brain structural architecture. In addition, although theory suggests that brain communication is highly frequency dependent, how structural connections influence overlying functional connectivity in different frequency bands has not been previously explored. Here we relate functional networks inferred from statistical associations between source imaging of EEG activity and underlying cortico-cortical structural brain connectivity determined by probabilistic white matter tractography. We evaluate spontaneous fluctuating cortical brain activity over a long time scale (minutes) and relate inferred functional networks to underlying structural connectivity for broadband signals, as well as in seven distinct frequency bands. We find that cortical networks derived from source EEG estimates partially reflect both direct and indirect underlying white matter connectivity in all frequency bands evaluated. In addition, we find that when structural support is absent, functional connectivity is significantly reduced for high frequency bands compared to low frequency bands. The association between cortical currents and underlying white matter connectivity highlights the obligatory interdependence of functional and structural networks in the human brain. The increased dependence on structural support for the coupling of higher frequency brain rhythms provides new evidence for how underlying anatomy directly shapes emergent brain dynamics at fast time scales.

Recent anatomical studies have found that cortical neurons are mainly preserved during the aging process while myelin damage and even axonal loss is prominent throughout the forebrain. We used diffusion tensor imaging (DT-MRI) to evaluate the hypothesis that during the process of normal aging, white matter changes preferentially affect the integrity of long corticocortical association fiber tracts, specifically the superior longitudinal fasciculus II and the cingulum bundle. This would disrupt communication between the frontal lobes and other forebrain regions leading to cognitive impairments. We analyzed DT-MRI datasets from seven young and seven elderly behaviorally characterized rhesus monkeys, creating fractional anisotropy (FA) maps of the brain. Significant age-related reductions in mean FA values were found for the superior longitudinal fasciculus II and the cingulum bundle, as well as the anterior corpus callosum. Comparison of these FA reductions with behavioral measures demonstrated a statistically significant linear relationship between regional FA and performance on a test of executive function. These findings support the hypothesis that alterations to the integrity of these long association pathways connecting the frontal lobe with other forebrain regions contribute to cognitive impairments in normal aging. To our knowledge this is the first investigation reporting such alterations in the aging monkey.