Dedifferentiation Does Not Account for Hyperconnectivity after Traumatic Brain Injury

Graph Analysis of the Visual Cortical Network during Naturalistic Movie Viewing Reveals Increased Integration and Decreased Segregation Following Mild TBI

Traditional neuroimaging methods have identified alterations in brain activity patterns following mild traumatic brain injury (mTBI), particularly during rest, complex tasks, and normal vision. However, studies using graph theory to examine brain network changes in mTBI have produced varied results, influenced by the specific networks and task demands analyzed. In our study, we employed functional MRI to observe 17 mTBI patients and 54 healthy individuals as they viewed a simple, non-narrative underwater film, simulating everyday visual tasks. This approach revealed significant mTBI-related changes in network connectivity, efficiency, and organization. Specifically, the mTBI group exhibited higher overall connectivity and local network specialization, suggesting enhanced information integration without overwhelming the brain's processing capabilities. Conversely, these patients showed reduced network segregation, indicating a less compartmentalized brain function compared to healthy controls. These patterns were consistent across various visual cortex subnetworks, except in primary visual areas. Our findings highlight the potential of using naturalistic stimuli in graph-based neuroimaging to understand brain network alterations in mTBI and possibly other conditions affecting brain integration.

Aberrant dynamic properties of whole-brain functional connectivity in acute mild traumatic brain injury revealed by hidden Markov models

OBJECTIVES

This study aimed to investigate the temporal dynamics of brain activity and characterize the spatiotemporal specificity of transitions and large-scale networks on short timescales in acute mild traumatic brain injury (mTBI) patients and those with cognitive impairment in detail.

METHODS

Resting-state functional magnetic resonance imaging (rs-fMRI) was acquired for 71 acute mTBI patients and 57 age-, sex-, and education-matched healthy controls (HCs). A hidden Markov model (HMM) analysis of rs-fMRI data was conducted to identify brain states that recurred over time and to assess the dynamic patterns of activation states that characterized acute mTBI patients and those with cognitive impairment. The dynamic parameters (fractional occupancy, lifetime, interval time, switching rate, and probability) between groups and their correlation with cognitive performance were analyzed.

RESULTS

Twelve HMM states were identified in this study. Compared with HCs, acute mTBI patients and those with cognitive impairment exhibited distinct changes in dynamics, including fractional occupancy, lifetime, and interval time. Furthermore, the switching rate and probability across HMM states were significantly different between acute mTBI patients and patients with cognitive impairment (all p < 0.05). The temporal reconfiguration of states in acute mTBI patients and those with cognitive impairment was associated with several brain networks (including the high-order cognition network [DMN], subcortical network [SUB], and sensory and motor network [SMN]).

CONCLUSIONS

Hidden Markov models provide additional information on the dynamic activity of brain networks in patients with acute mTBI and those with cognitive impairment. Our results suggest that brain network dynamics determined by the HMM could reinforce the understanding of the neuropathological mechanisms of acute mTBI patients and those with cognitive impairment.

Concussion-Related Disruptions to Hub Connectivity in the Default Mode Network Are Related to Symptoms and Cognition

Concussions present with a myriad of symptomatic and cognitive concerns; however, the relationship between these functional disruptions and the underlying changes in the brain are not yet well understood. Hubs, or brain regions that are connected to many different functional networks, may be specifically disrupted after concussion. Given the implications in concussion research, we quantified hub disruption within the default mode network (DMN) and between the DMN and other brain networks. We collected resting-state functional magnetic resonance imaging data from collegiate student-athletes (n = 44) at three time points: baseline (before beginning their athletic season), acute post-injury (approximately 48h after a diagnosed concussion), and recovery (after starting return-to-play progression, but before returning to contact). We used self-reported symptoms and computerized cognitive assessments collected across similar time points to link these functional connectivity changes to clinical outcomes. Concussion resulted in increased connectivity between regions within the DMN compared with baseline and recovery, and this post-injury connectivity was more positively related to symptoms and more negatively related to visual memory performance compared with baseline and recovery. Further, concussion led to decreased connectivity between DMN hubs and visual network non-hubs relative to baseline and recovery, and this post-injury connectivity was more negatively related to somatic symptoms and more positively related to visual memory performance compared with baseline and recovery. Relationships between functional connectivity, symptoms, and cognition were not significantly different at baseline versus recovery. These results highlight a unique relationship between self-reported symptoms, visual memory performance, and acute functional connectivity changes involving DMN hubs after concussion in athletes. This may provide evidence for a disrupted balance of within- and between-network communication highlighting possible network inefficiencies after concussion. These results aid in our understanding of the pathophysiological disruptions after concussion and inform our understanding of the associations between disruptions in brain connectivity and specific clinical presentations acutely post-injury.

Functional connectivity, tissue microstructure and T2 at 11.1 Tesla distinguishes neuroadaptive differences in two traumatic brain injury models in rats: A Translational Outcomes Project in NeuroTrauma (TOP-NT) UG3 phase study

The damage caused by contusive traumatic brain injuries (TBIs) is thought to involve breakdown in neuronal communication through focal and diffuse axonal injury along with alterations to the neuronal chemical environment, which adversely affects neuronal networks beyond the injury epicenter(s). In the present study, functional connectivity along with brain tissue microstructure coupled with T2 relaxometry were assessed in two experimental TBI models in rat, controlled cortical impact (CCI) and lateral fluid percussive injury (LFPI). Rats were scanned on an 11.1 Tesla scanner on days 2 and 30 following either CCI or LFPI. Naive controls were scanned once and used as a baseline comparison for both TBI groups. Scanning included functional magnetic resonance imaging (fMRI), diffusion weighted images (DWI), and multi-echo T2 images. fMRI scans were analyzed for functional connectivity across laterally and medially located region of interests (ROIs) across the cortical mantle, hippocampus, and dorsal striatum. DWI scans were processed to generate maps of fractional anisotropy, mean, axial, and radial diffusivities (FA, MD, AD, RD). The analyses focused on cortical and white matter (WM) regions at or near the TBI epicenter. Our results indicate that rats exposed to CCI and LFPI had significantly increased contralateral intra-cortical connectivity at 2 days post-injury. This was observed across similar areas of the cortex in both groups. The increased contralateral connectivity was still observed by day 30 in CCI, but not LFPI rats. Although both CCI and LFPI had changes in WM and cortical FA and diffusivities, WM changes were most predominant in CCI and cortical changes in LFPI. Our results provide support for the use of multimodal MR imaging for different types of contusive and skull-penetrating injury.

Functional hub disruption emphasizes consciousness recovery in severe traumatic brain injury

Severe traumatic brain injury can lead to transient or even chronic disorder of consciousness. To increase diagnosis and prognosis accuracy of disorder of consciousness, functional neuroimaging is recommended 1 month post-injury. Here, we investigated brain networks remodelling on longitudinal data between 1 and 3 months post severe traumatic brain injury related to change of consciousness. Thirty-four severe traumatic brain-injured patients were included in a cross-sectional and longitudinal clinical study, and their MRI data were compared to those of 20 healthy subjects. Long duration resting-state functional MRI were acquired in minimally conscious and conscious patients at two time points after their brain injury. The first time corresponds to the exit from intensive care unit and the second one to the discharge from post-intensive care rehabilitation ward. Brain networks data were extracted using graph analysis and metrics at each node quantifying local (clustering) and global (degree) connectivity characteristics. Comparison with brain networks of healthy subjects revealed patterns of hyper- and hypo-connectivity that characterize brain networks reorganization through the hub disruption index, a value quantifying the functional disruption in each individual severe traumatic brain injury graph. At discharge from intensive care unit, 24 patients' graphs (9 minimally conscious and 15 conscious) were fully analysed and demonstrated significant network disruption. Clustering and degree nodal metrics, respectively, related to segregation and integration properties of the network, were relevant to distinguish minimally conscious and conscious groups. At discharge from post-intensive care rehabilitation unit, 15 patients' graphs (2 minimally conscious, 13 conscious) were fully analysed. The conscious group still presented a significant difference with healthy subjects. Using mixed effects models, we showed that consciousness state, rather than time, explained the hub disruption index differences between minimally conscious and conscious groups. While severe traumatic brain-injured patients recovered full consciousness, regional functional connectivity evolved towards a healthy pattern. More specifically, the restoration of a healthy brain functional segregation could be necessary for consciousness recovery after severe traumatic brain injury. For the first time, extracting the hub disruption index directly from each patient's graph, we were able to track the clinical alteration and subsequent recovery of consciousness during the first 3 months following a severe traumatic brain injury.

MRI factors associated with cognitive functioning after acute onset brain injury: Systematic review and meta-analysis

Impairments of memory, attention, and executive functioning are frequently reported after acute onset brain injury. MRI markers hold potential to contribute to identification of patients at risk for cognitive impairments and clarification of mechanisms. The aim of this systematic review was to summarize and value the evidence on MRI markers of memory, attention, and executive functioning after acute onset brain injury. We included ninety-eight studies, on six classes of MRI factors (location and severity of damage (n = 15), volume/atrophy (n = 36), signs of small vessel disease (n = 15), diffusion-weighted imaging measures (n = 36), resting-state functional MRI measures (n = 13), and arterial spin labeling measures (n = 1)). Three measures showed consistent results regarding their association with cognition. Smaller hippocampal volume was associated with worse memory in fourteen studies (pooled correlation 0.58 [95% CI: 0.46-0.68] for whole, 0.11 [95% CI: 0.04-0.19] for left, and 0.34 [95% CI: 0.17-0.49] for right hippocampus). Lower fractional anisotropy in cingulum and fornix was associated with worse memory in six and five studies (pooled correlation 0.20 [95% CI: 0.08-0.32] and 0.29 [95% CI: 0.20-0.37], respectively). Lower functional connectivity within the default-mode network was associated with worse cognition in four studies. In conclusion, hippocampal volume, fractional anisotropy in cingulum and fornix, and functional connectivity within the default-mode network showed consistent associations with cognitive performance in all types of acute onset brain injury. External validation and cut off values for predicting cognitive impairments are needed for clinical implementation.

Functional brain connectomes reflect acute and chronic cannabis use

Resting state fMRI has been employed to identify alterations in functional connectivity within or between brain regions following acute and chronic exposure to Δ9-tetrahydrocannabinol (THC), the psychoactive component in cannabis. Most studies focused a priori on a limited number of local brain areas or circuits, without considering the impact of cannabis on whole-brain network organization. The present study attempted to identify changes in the whole-brain human functional connectome as assessed with ultra-high field (7T) resting state scans of cannabis users (N = 26) during placebo and following vaporization of cannabis. Two distinct data-driven methodologies, i.e. network-based statistics (NBS) and connICA, were used to identify changes in functional connectomes associated with acute cannabis intoxication and history of cannabis use. Both methodologies revealed a broad state of hyperconnectivity within the entire range of major brain networks in chronic cannabis users compared to occasional cannabis users, which might be reflective of an adaptive network reorganization following prolonged cannabis exposure. The connICA methodology also extracted a distinct spatial connectivity pattern of hypoconnectivity involving the dorsal attention, limbic, subcortical and cerebellum networks and of hyperconnectivity between the default mode and ventral attention network, that was associated with the feeling of subjective high during THC intoxication. Whole-brain network approaches identified spatial patterns in functional brain connectomes that distinguished acute from chronic cannabis use, and offer an important utility for probing the interplay between short and long-term alterations in functional brain dynamics when progressing from occasional to chronic use of cannabis.

Resting-State Functional MRI Metrics in Patients With Chronic Mild Traumatic Brain Injury and Their Association With Clinical Cognitive Performance

Mild traumatic brain injury (mTBI) accounts for more than 80% of people experiencing brain injuries. Symptoms of mTBI include short-term and long-term adverse clinical outcomes. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) was conducted to measure voxel-based indices including fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and functional connectivity (FC) in patients suffering from chronic mTBI; 64 patients with chronic mTBI at least 3 months post injury and 40 healthy controls underwent rs-fMRI scanning. Partial correlation analysis controlling for age and gender was performed within mTBI cohort to explore the association between rs-fMRI metrics and neuropsychological scores. Compared with controls, chronic mTBI patients showed increased fALFF in the left middle occipital cortex (MOC), right middle temporal cortex (MTC), and right angular gyrus (AG), and increased ReHo in the left MOC and left posterior cingulate cortex (PCC). Enhanced FC was observed from left MOC to right precuneus; from right MTC to right superior temporal cortex (STC), right supramarginal, and left inferior parietal cortex (IPC); and from the seed located at right AG to left precuneus, left superior medial frontal cortex (SMFC), left MTC, left superior temporal cortex (STC), and left MOC. Furthermore, the correlation analysis revealed a significant correlation between neuropsychological scores and fALFF, ReHo, and seed-based FC measured from the regions with significant group differences. Our results demonstrated that alterations of low-frequency oscillations in chronic mTBI could be representative of disruption in emotional circuits, cognitive performance, and recovery in this cohort.

Compensatory functional connectome changes in a rat model of traumatic brain injury

Penetrating cortical impact injuries alter neuronal communication beyond the injury epicentre, across regions involved in affective, sensorimotor and cognitive processing. Understanding how traumatic brain injury reorganizes local and brain wide nodal interactions may provide valuable quantitative parameters for monitoring pathological progression and recovery. To this end, we investigated spontaneous fluctuations in the functional MRI signal obtained at 11.1 T in rats sustaining controlled cortical impact and imaged at 2- and 30-days post-injury. Graph theory-based calculations were applied to weighted undirected matrices constructed from 12 879 pairwise correlations between functional MRI signals from 162 regions. Our data indicate that on Days 2 and 30 post-controlled cortical impact there is a significant increase in connectivity strength in nodes located in contralesional cortical, thalamic and basal forebrain areas. Rats imaged on Day 2 post-injury had significantly greater network modularity than controls, with influential nodes (with high eigenvector centrality) contained within the contralesional module and participating less in cross-modular interactions. By Day 30, modularity and cross-modular interactions recover, although a cluster of nodes with low strength and low eigenvector centrality remain in the ipsilateral cortex. Our results suggest that changes in node strength, modularity, eigenvector centrality and participation coefficient track early and late traumatic brain injury effects on brain functional connectivity. We propose that the observed compensatory functional connectivity reorganization in response to controlled cortical impact may be unfavourable to brain wide communication in the early post-injury period.

Altered gray matter structural covariance networks at both acute and chronic stages of mild traumatic brain injury

Cognitive and emotional impairments observed in mild traumatic brain injury (mTBI) patients may reflect variances of brain connectivity within specific networks. Although previous studies found altered functional connectivity (FC) in mTBI patients, the alterations of brain structural properties remain unclear. In the present study, we analyzed structural covariance (SC) for the acute stages of mTBI (amTBI) patients, the chronic stages of mTBI (cmTBI) patients, and healthy controls. We first extracted the mean gray matter volume (GMV) of seed regions that are located in the default-mode network (DMN), executive control network (ECN), salience network (SN), sensorimotor network (SMN), and the visual network (VN). Then we determined and compared the SC for each seed region among the amTBI, the cmTBI and the healthy controls. Compared with healthy controls, the amTBI patients showed lower SC for the ECN, and the cmTBI patients showed higher SC for the both DMN and SN but lower SC for the SMN. The results revealed disrupted ECN in the amTBI patients and disrupted DMN, SN and SMN in the cmTBI patients. These alterations suggest that early disruptions in SC between bilateral insula and the bilateral prefrontal cortices may appear in amTBI and persist into cmTBI, which might be potentially related to the cognitive and emotional impairments.

Duration of post-traumatic amnesia is uniquely associated with memory functioning in chronic moderate-to-severe traumatic brain injury

BACKGROUND

Disrupted memory circuitry may contribute to post-traumatic amnesia (PTA) after traumatic brain injury (TBI). It is unclear whether duration of PTA (doPTA) uniquely impacts memory functioning in the chronic post-injury stage.

OBJECTIVE

To examine the relationship between doPTA and memory functioning, independent of other cognitive abilities, in chronic moderate-to-severe TBI.

METHODS

Participants were 82 individuals (median chronicity = 10.5 years) with available doPTA estimates and neuropsychological data. Composite memory, processing speed (PS), and executive functioning (EF) performance scores, as well as data on subjective memory (SM) beliefs, were extracted. DoPTA-memory associations were evaluated via linear modeling of doPTA with memory performance and clinical memory status (impaired/unimpaired), controlling for PS, EF and demographic covariates. Interrelationships between doPTA, objective memory functioning, and SM were assessed.

RESULTS

DoPTA was significantly related to memory performance, even after covariate adjustment. Impairment in memory, but not PS or EF, was associated with a history of longer doPTA. SM was associated with memory performance, but unrelated to doPTA.

CONCLUSIONS

Findings suggest a specific association between doPTA-an acute injury phenomenon-and chronic memory deficits after TBI. Prospective studies are needed to understand how underlying mechanisms of PTA shape distinct outcome trajectories, particularly functional abilities related to memory processing.

Quantitative multimodal imaging in traumatic brain injuries producing impaired cognition

PURPOSE OF REVIEW

Cognitive impairments are a devastating long-term consequence following traumatic brain injury (TBI). This review provides an update on the quantitative mutimodal neuroimaging studies that attempt to elucidate the mechanism(s) underlying cognitive impairments and their recovery following TBI.

RECENT FINDINGS

Recent studies have linked individual specific behavioural impairments and their changes over time to physiological activity and structural changes using EEG, PET and MRI. Multimodal studies that combine measures of physiological activity with knowledge of neuroanatomical and connectivity damage have also illuminated the multifactorial function-structure relationships that underlie impairment and recovery following TBI.

SUMMARY

The combined use of multiple neuroimaging modalities, with focus on individual longitudinal studies, has the potential to accurately classify impairments, enhance sensitivity of prognoses, inform targets for interventions and precisely track spontaneous and intervention-driven recovery.

Toward a global and reproducible science for brain imaging in neurotrauma: the ENIGMA adult moderate/severe traumatic brain injury working group

The global burden of mortality and morbidity caused by traumatic brain injury (TBI) is significant, and the heterogeneity of TBI patients and the relatively small sample sizes of most current neuroimaging studies is a major challenge for scientific advances and clinical translation. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Adult moderate/severe TBI (AMS-TBI) working group aims to be a driving force for new discoveries in AMS-TBI by providing researchers world-wide with an effective framework and platform for large-scale cross-border collaboration and data sharing. Based on the principles of transparency, rigor, reproducibility and collaboration, we will facilitate the development and dissemination of multiscale and big data analysis pipelines for harmonized analyses in AMS-TBI using structural and functional neuroimaging in combination with non-imaging biomarkers, genetics, as well as clinical and behavioral measures. Ultimately, we will offer investigators an unprecedented opportunity to test important hypotheses about recovery and morbidity in AMS-TBI by taking advantage of our robust methods for large-scale neuroimaging data analysis. In this consensus statement we outline the working group's short-term, intermediate, and long-term goals.

Disrupted functional network connectivity predicts cognitive impairment after acute mild traumatic brain injury

Aims

This study aimed to detect alterations of brain functional connectivity (FC) in acute mild traumatic brain injury (mTBI) and to estimate the extent to which these FC differences predicted the characteristics of posttraumatic cognitive impairment.

Methods

Resting‐state fMRI data were acquired from acute mTBI patients (n = 50) and healthy controls (HCs) (n = 43). Resting‐state networks (RSNs) were established based on independent component analysis (ICA), and functional network connectivity (FNC) analysis was performed. Subsequently, we analyzed the correlations between FNC abnormalities and cognitive impairment outcomes.

Results

Altered FC within the salience network (SN), sensorimotor network (SMN), default mode network (DMN), executive control network (ECN), visual network (VN), and cerebellum network (CN) was found in the mTBI group relative to the HC group. Moreover, different patterns of altered network interactions were found between the mTBI patients and HCs, including the SN‐CN, VN‐SMN, and ECN‐DMN connections. Correlations between functional disconnection and cognitive impairment measurements in acute mTBI patients were also found.

Conclusion

This study indicated that widespread FNC impairment and altered integration existed in mTBI patients at acute stage, suggesting that FNC disruption as a biomarker may be applied for the early diagnosis and prediction of cognitive impairment in mTBI.

On the time-course of functional connectivity: theory of a dynamic progression of concussion effects

The current literature presents a discordant view of mild traumatic brain injury and its effects on the human brain. This dissonance has often been attributed to heterogeneities in study populations, aetiology, acuteness, experimental paradigms and/or testing modalities. To investigate the progression of mild traumatic brain injury in the human brain, the present study employed data from 93 subjects (48 healthy controls) representing both acute and chronic stages of mild traumatic brain injury. The effects of concussion across different stages of injury were measured using two metrics of functional connectivity in segments of electroencephalography time-locked to an active oddball task. Coherence and weighted phase-lag index were calculated separately for individual frequency bands (delta, theta, alpha and beta) to measure the functional connectivity between six electrode clusters distributed from frontal to parietal regions across both hemispheres. Results show an increase in functional connectivity in the acute stage after mild traumatic brain injury, contrasted with significantly reduced functional connectivity in chronic stages of injury. This finding indicates a non-linear time-dependent effect of injury. To understand this pattern of changing functional connectivity in relation to prior evidence, we propose a new model of the time-course of the effects of mild traumatic brain injury on the brain that brings together research from multiple neuroimaging modalities and unifies the various lines of evidence that at first appear to be in conflict.

Effects of mild traumatic brain injury and post-traumatic stress disorder on resting-state default mode network connectivity

Mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD) are common outcomes for service members. Abnormal connectivity within neural networks has been reported in the resting brain of mTBI and PTSD patients, respectively; however, the potential role of PTSD in changes to neural networks following injury has not been studied in detail. Using a data-driven approach, the present analysis aimed to elucidate resting state functional connectivity in the default mode network (DMN) in those with mTBI only and those with comorbid mTBI and PTSD. A secondary analysis focused on distinct contributions by the anterior and posterior DMN components. Group-level independent component analysis was used to identify the DMN, and a dual-regression method was utilized to measure connectivity within the overall network and its anterior (medial prefrontal cortex) and posterior (posterior cingulate cortex) nodes. Connectivity within the overall DMN was significantly higher for the mTBI only group (p = 0.001), as compared to controls and mTBI + PTSD. For all subjects with mTBI, network connectivity correlated inversely with PTSD checklist score (p < 0.05). Additionally, distinct associations (p < 0.05) between medial prefrontal cortex connectivity and PTSD symptoms and, separately, posterior cingulate cortex connectivity and mTBI-related cognitive deficits were found. To our knowledge, this is the first study to report a differential relationship between DMN components and both post-traumatic symptoms and cognitive outcomes.

Traumatic brain injury and frontal lobe plasticity

Over 1.4 million people in the United States experience traumatic brain injury (TBI) each year and approximately 52,000 people die annually due to complications related to TBI. Traditionally, TBI has been viewed as a static injury with significant consequences for frontal lobe functioning that plateaus after some window of recovery, remaining relatively stable thereafter. However, over the past decade there has been growing consensus that the consequences of TBI are dynamic, with unique characteristics expressed at the individual level and over the life span. This chapter first discusses the pathophysiology of TBI in order to understand its dynamic process and then describes the behavioral changes that are the result of injury with focus on frontal lobe functions. It integrates a historical perspective on structural and functional brain-imaging approaches used to understand how TBI impacts the frontal lobes, as well as more recent approaches to examine large-scale network changes after TBI. The factors most useful for outcome prediction are surveyed, along with how the theoretical frameworks used to predict recovery have developed over time. In this chapter, the authors argue for the need to understand outcome after TBI as a dynamic process with individual trajectories, taking a network theory perspective to understand the consequences of disrupting frontal systems in TBI. Within this framework, understanding frontal lobe dysfunction within a larger coordinated neural network to study TBI may provide a novel perspective in outcome prediction and in developing individualized treatments.

Stage-dependent remodeling of projections to motor cortex in ALS mouse model revealed by a new variant retrograde-AAV9

Amyotrophic lateral sclerosis (ALS) is characterized by the progressive degeneration of motoneurons in the primary motor cortex (pMO) and in spinal cord. However, the pathogenic process involves multiple subnetworks in the brain and functional MRI studies demonstrate an increase in functional connectivity in areas connected to pMO despite the ongoing neurodegeneration. The extent and the structural basis of the motor subnetwork remodeling in experimentally tractable models remain unclear. We have developed a new retrograde AAV9 to quantitatively map the projections to pMO in the SOD1(G93A) ALS mouse model. We show an increase in the number of neurons projecting from somatosensory cortex to pMO at presymptomatic stages, followed by an increase in projections from thalamus, auditory cortex and contralateral MO (inputs from 20 other structures remains unchanged) as disease advances. The stage- and structure-dependent remodeling of projection to pMO in ALS may provide insights into the hyperconnectivity observed in ALS patients.

The correlation of asymmetrical functional connectivity with cognition and reperfusion in carotid stenosis patients

Objective

Neural disruption and cognitive impairment have been reported in patients with carotid stenosis (CS), but carotid artery stenting (CAS) may not contribute to the cognitive recovery. Although functional hyper-connectivity is one of the physiological over-compensation phenomena in neurological diseases, the literature on the cognitive influence of functional hyper-connectivity in CS patients is limited. We aimed to investigate the longitudinal changes of hyper-connectivity after CAS and its association with cognition in CS patients.

Methods

Thirteen patients with unilateral CS and 17 controls without CS were included. Cognitive function was evaluated at baseline, and resting-state functional MRI was performed 1 week before and 1 month and 1 year after CAS. Comparisons of functional connectivity (FC) between CS patients and controls in multiple brain networks were performed.

Results

In patients before CAS, FC in the cerebral hemispheres ipsilateral and contralateral to CS was mainly decreased and increased, respectively, compared with normal controls. Part of the FC alterations gradually recovered to the normal condition after CAS. The stronger FC abnormality (both hypo- and hyper-connectivity compared with normal controls) was associated with poorer cognitive performances, especially in memory and executive functions.

Conclusion

The study demonstrated the lateralization of hyper-connectivity and hypo-connectivity in patients with unilateral CS in contrast to the FC in normal controls. These FC alterations were associated with poor cognitive performances and tended to recover after CAS, implying that hyper-connectivity is served as a compensation for neural challenge.

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Cerebral hypoconnectivity on functional MRI is lateralized to carotid stenosis side.

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Cerebral hyperconnectivity is in regions contralateral to carotid stenosis side.

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Abnormal connectivity gradually returns back to normal after carotid stenting.

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Hypo- and hyper-connectivity associate with poor cognitive performances.

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Hyperconnectivity could be served as a compensation for neural challenge.

Diminished neural network dynamics after moderate and severe traumatic brain injury

Over the past decade there has been increasing enthusiasm in the cognitive neurosciences around using network science to understand the system-level changes associated with brain disorders. A growing literature has used whole-brain fMRI analysis to examine changes in the brain's subnetworks following traumatic brain injury (TBI). Much of network modeling in this literature has focused on static network mapping, which provides a window into gross inter-nodal relationships, but is insensitive to more subtle fluctuations in network dynamics, which may be an important predictor of neural network plasticity. In this study, we examine the dynamic connectivity with focus on state-level connectivity (state) and evaluate the reliability of dynamic network states over the course of two runs of intermittent task and resting data. The goal was to examine the dynamic properties of neural networks engaged periodically with task stimulation in order to determine: 1) the reliability of inter-nodal and network-level characteristics over time and 2) the transitions between distinct network states after traumatic brain injury. To do so, we enrolled 23 individuals with moderate and severe TBI at least 1-year post injury and 19 age- and education-matched healthy adults using functional MRI methods, dynamic connectivity modeling, and graph theory. The results reveal several distinct network "states" that were reliably evident when comparing runs; the overall frequency of dynamic network states are highly reproducible (r-values>0.8) for both samples. Analysis of movement between states resulted in fewer state transitions in the TBI sample and, in a few cases, brain injury resulted in the appearance of states not exhibited by the healthy control (HC) sample. Overall, the findings presented here demonstrate the reliability of observable dynamic mental states during periods of on-task performance and support emerging evidence that brain injury may result in diminished network dynamics.

Diminished neural network dynamics in amnestic mild cognitive impairment

Mild cognitive impairment (MCI) is widely regarded as an intermediate stage between typical aging and dementia, with nearly 50% of patients with amnestic MCI (aMCI) converting to Alzheimer's dementia (AD) within 30 months of follow-up (Fischer et al., 2007). The growing literature using resting-state functional magnetic resonance imaging reveals both increased and decreased connectivity in individuals with MCI and connectivity loss between the anterior and posterior components of the default mode network (DMN) throughout the course of the disease progression (Hillary et al., 2015; Sheline & Raichle, 2013; Tijms et al., 2013). In this paper, we use dynamic connectivity modeling and graph theory to identify unique brain "states," or temporal patterns of connectivity across distributed networks, to distinguish individuals with aMCI from healthy older adults (HOAs). We enrolled 44 individuals diagnosed with aMCI and 33 HOAs of comparable age and education. Our results indicated that individuals with aMCI spent significantly more time in one state in particular, whereas neural network analysis in the HOA sample revealed approximately equivalent representation across four distinct states. Among individuals with aMCI, spending a higher proportion of time in the dominant state relative to a state where participants exhibited high cost (a measure combining connectivity and distance), predicted better language performance and less perseveration. This is the first report to examine neural network dynamics in individuals with aMCI.