Alzheimer's disease biomarker burden in primary motor cortices is associated with poorer dexterity performance.

INTRODUCTION: Motor function has correlated with longevity and functionality; however, there is limited research on those with Alzheimer's disease (AD). We studied the association between motor functionality and AD pathology in primary motor and medial temporal cortices. METHODS: A total of 206 participants with a clinical diagnosis of cognitively healthy, AD, or mild cognitive impairment (MCI) underwent imaging and motor assessment. Linear regressions and analyses of variance were applied to test the prediction from AD imaging biomarkers to motor performance and the diagnosis group differences in motor performance. RESULTS: Increased neurodegeneration was associated with worsening dexterity and lower walking speed, and increased amyloid and tau were associated with worsening dexterity. AD and MCI participants had lower motor performance than the cognitively healthy participants. DISCUSSION: Increased AD pathology is associated with worsening dexterity performance. The decline in dexterity in those with AD pathology may offer an opportunity for non-pharmacological therapy intervention. HIGHLIGHTS: Noted worsening dexterity performance was associated with greater Alzheimer's disease (AD) pathology (tau, amyloid beta, and neurodegeneration) in primary motor cortices. Similarly, increased neurodegeneration and tau pathology in parahippocampal, hippocampal, and entorhinal cortices is associated with worsening dexterity performance. Motor performance declined in those with clinical and preclinical AD among an array of motor assessments.

Neural control of cerebral blood flow: scientific basis of scalp acupuncture in treating brain diseases.

Scalp acupuncture (SA), as a modern acupuncture therapy in the treatment of brain diseases, especially for acute ischemic strokes, has accumulated a wealth of experience and tons of success cases, but the current hypothesized mechanisms of SA therapy still seem to lack significant scientific validity, which may not be conducive to its ultimate integration into mainstream medicine. This review explores a novel perspective about the mechanisms of SA in treating brain diseases based on its effects on cerebral blood flow (CBF). To date, abundant evidence has shown that CBF is significantly increased by stimulating specific SA points, areas or nerves innervating the scalp, which parallels the instant or long-term improvement of symptoms of brain diseases. Over time, the neural pathways that improve CBF by stimulating the trigeminal, the facial, and the cervical nerves have also been gradually revealed. In addition, the presence of the core SA points or areas frequently used for brain diseases can be rationally explained by the characteristics of nerve distribution, including nerve overlap or convergence in certain parts of the scalp. But such characteristics also suggest that the role of these SA points or areas is relatively specific and not due to a direct correspondence between the current hypothesized SA points, areas and the functional zones of the cerebral cortex. The above evidence chain indicates that the efficacy of SA in treating brain diseases, especially ischemic strokes, is mostly achieved by stimulating the scalp nerves, especially the trigeminal nerve to improve CBF. Of course, the mechanisms of SA in treating various brain diseases might be multifaceted. However, the authors believe that understanding the neural regulation of SA on CBF not only captures the main aspects of the mechanisms of SA therapy, but also facilitates the elucidation of other mechanisms, which may be of greater significance to further its clinical applications.

Imminent cognitive decline in normal elderly individuals is associated with hippocampal hyperconnectivity in the variant neural correlates of episodic memory.

The secondary prevention trials of Alzheimer's disease (AD) require an enrichment strategy to recruit individuals with imminent cognitive decline at the preclinical stage. Previously, we demonstrated a variant neural correlates of episodic memory (EM) function in apolipoprotein E (APOE) ε4 carriers. Herein, we investigated whether this variation was associated with longitudinal EM performance. This 3-year longitudinal study included 88 normal elderly subjects with EM assessment and resting-state functional MRI data at baseline; 48 subjects (27 ε3 homozygotes and 21 ε4 carriers) underwent follow-up EM assessment. In the identified EM neural correlates, multivariable regression models examined the association between hippocampal functional connectivity (HFC) and longitudinal EM change. Independent validation was performed using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. At baseline, the EM neural correlates were characterized in the Papez circuit regions in the ε3 homozygotes, but in the sensorimotor cortex and cuneus in the ε4 carriers. Longitudinally, the ε4 carriers exhibited a negative association of the baseline HFC strength in the EM neural correlates with annual rate of EM change (R2 = 0.25, p = 0.05). This association also showed a trend in the ADNI dataset (R2 = 0.42, p = 0.06). These results indicate that hippocampal hyperconnectivity in the variant EM neural correlates is associated with imminent EM decline in ε4 carriers, which may serve as a promising enrichment strategy for secondary prevention trials of AD.

Dysconnectivity of the amygdala and dorsal anterior cingulate cortex in drug-naive post-traumatic stress disorder.

Convergent studies have highlighted the amygdala-based and dorsal anterior cingulate cortex (dACC)-based circuit or network dysfunction in post-traumatic stress disorder (PTSD). However, previous studies are often complicated by various traumatic types, psychiatric comorbidities, chronic illness duration, and medication effect on brain function. Besides, little is known whether the functional integration with amygdala-dACC interaction disrupted or not in PTSD. Here, we investigated effective connectivity (EC) between the amygdala-dACC and rest of the cortex by applying psycho-physiological interaction (PPI) approach to resting-state functional magnetic resonance imaging data of 63 drug-naive PTSD patients and 74 matched trauma-exposed non-PTSD controls. Pearson correlation analysis was performed between EC values extracted from regions with between-group difference and clinical profiles in PTSD patients. We observed distinct amygdala-dACC interaction pattern between PTSD group and the control group, which is composed primarily by positive EC in the former and negative in the latter. In addition, compared with non-PTSD controls, PTSD patients showed increased EC between amygdala-dACC and the prefrontal cortex, left inferior parietal lobule, and bilateral ventral occipital cortex, and decreased EC between amygdala-dACC and the left fusiform gyrus. The EC increase between amygdala-dACC and the right middle frontal gyrus was negatively correlated with the clinician-administered PTSD scale scores in PTSD patients. Aberrent communication between amgydala-dACC and brain regions involved in central executive network and visual systems might be associated with the pathophysiology of PTSD. Further, these findings suggested that dysconnectivity of the amygdala and dACC could be adapted as a relatively early course diagnostic biomarker of PTSD.

Amygdala Functional Connectivity Features in Grief: A Pilot Longitudinal Study.

OBJECTIVE: Acute grief, in an important minority of older adults, can become protracted, intense, and debilitating, leading to the development of complicated grief (CG). However, the neurobiologic mechanisms underlying a maladaptive grief response after an attachment loss are unknown. The current study aimed to examine the amygdala brain network features that cross-sectionally explain the symptom variance and longitudinally relate to grief symptom trajectories after an attachment loss. METHODS: Baseline amygdala functional connectivity (Fc) was assessed using a seed-based resting-state functional magnetic resonance imaging method in 35 adults who were within 1-year after death of a loved one and 21 healthy comparison (HC) participants. Magnetic resonance imaging scans were obtained at baseline, and clinical assessments, including the inventory of complicated grief (ICG) were completed at weeks 0, 8, 16, and 26 (endpoint). RESULTS: Relative to HC participants, grief participants showed increased amygdala Fc in the posterior default mode (bilateral medial temporal lobes and left precuneus) and thalamus. Amygdala Fc in the default mode and ventral affective regions positively correlated with ICG scores at baseline. Furthermore, increased baseline amygdala functional connections with the dorsal frontal executive control and salience network regions correlated with worsening ICG scores over time. These longitudinal findings persisted after controlling for covariates, including baseline depressive and anxiety symptoms. CONCLUSION: These results provide novel preliminary evidence suggesting amygdala-based brain network measures to cross-sectionally explain symptom variance and longitudinally correlate with grief symptom trajectories in grievers. Amygdala brain network function measures may have the potential to serve as biomarkers of CG.

Functional connectivity and structural analysis of trial spinal cord stimulation responders in failed back surgery syndrome.

BACKGROUND: Chronic pain has been associated with alterations in brain structure and function that appear dependent on pain phenotype. Functional connectivity (FC) data on chronic back pain (CBP) is limited and based on heterogeneous pain populations. We hypothesize that failed back surgery syndrome (FBSS) patients being considered for spinal cord stimulation (SCS) therapy have altered resting state (RS) FC cross-network patterns that 1) specifically involve emotion and reward/aversion functions and 2) are related to pain scores. METHODS: RS functional MRI (fMRI) scans were obtained for 10 FBSS patients who are being considered for but who have not yet undergone implantation of a permanent SCS device and 12 healthy age-matched controls. Seven RS networks were analyzed including the striatum (STM). The Wilcoxon signed-rank test evaluated differences in cross-network FC strength (FCS). Differences in periaqueductal grey (PAG) FC were assessed with seed-based analysis. RESULTS: Cross-network FCS was decreased (p<0.05) between the STM and all other networks in these FBSS patients. There was a negative linear relationship (R2 = 0.76, p<0.0022) between STMFCS index and pain scores. The PAG showed decreased FC with network elements and amygdala but increased FC with the sensorimotor cortex and cingulate gyrus. CONCLUSIONS: Decreased FC between STM and other RS networks in FBSS has not been previously reported. This STMFCS index may represent a more objective measure of chronic pain specific to FBSS which may help guide patient selection for SCS and subsequent management.

Propofol Sedation Alters Perceptual and Cognitive Functions in Healthy Volunteers as Revealed by Functional Magnetic Resonance Imaging.

BACKGROUND: Elucidating networks underlying conscious perception is important to understanding the mechanisms of anesthesia and consciousness. Previous studies have observed changes associated with loss of consciousness primarily using resting paradigms. The authors focused on the effects of sedation on specific cognitive systems using task-based functional magnetic resonance imaging. The authors hypothesized deepening sedation would degrade semantic more than perceptual discrimination. METHODS: Discrimination of pure tones and familiar names were studied in 13 volunteers during wakefulness and propofol sedation targeted to light and deep sedation. Contrasts highlighted specific cognitive systems: auditory/motor (tones vs. fixation), phonology (unfamiliar names vs. tones), and semantics (familiar vs. unfamiliar names), and were performed across sedation conditions, followed by region of interest analysis on representative regions. RESULTS: During light sedation, the spatial extent of auditory/motor activation was similar, becoming restricted to the superior temporal gyrus during deep sedation. Region of interest analysis revealed significant activation in the superior temporal gyrus during light (t [17] = 9.71, P < 0.001) and deep sedation (t [19] = 3.73, P = 0.001). Spatial extent of the phonologic contrast decreased progressively with sedation, with significant activation in the inferior frontal gyrus maintained during light sedation (t [35] = 5.17, P < 0.001), which didn't meet criteria for significance in deep sedation (t [38] = 2.57, P = 0.014). The semantic contrast showed a similar pattern, with activation in the angular gyrus during light sedation (t [16] = 4.76, P = 0.002), which disappeared in deep sedation (t [18] = 0.35, P = 0.731). CONCLUSIONS: Results illustrate broad impairment in cognitive cortex during sedation, with activation in primary sensory cortex beyond loss of consciousness. These results agree with clinical experience: a dose-dependent reduction of higher cognitive functions during light sedation, despite partial preservation of sensory processes through deep sedation.

Chronic pain in adults with sickle cell disease is associated with alterations in functional connectivity of the brain.

Chronic pain affects 50% of adults with sickle cell disease (SCD). Although central sensitization is thought to contribute to the pathogenesis of this chronic pain, no studies have examined differences in functional connectivity of the brain between patients with SCD with and without chronic pain. We performed an observational cohort study using resting-state functional MRI (rsfMRI) of the brain on adults with SCD with and without chronic pain. We tested the hypothesis that, compared to those without chronic pain, those with chronic pain would have differences in functional connectivity between the periaqueductal grey (PAG) and other regions of the brain. Twenty-two adults with SCD, 15 with chronic pain and 7 without chronic pain, as well as 10 African-American controls, underwent rsfMRI of the brain. When SCD patients with chronic pain were compared to those without chronic pain, significant differences in connectivity were noted between the PAG and 9 regions of the brain, including several in the default mode network, a network involved in introspection that has been implicated in other chronic pain syndromes. Changes in functional connectivity between patients with SCD with and without chronic pain suggest a mechanism for chronic pain that involves neuro-plastic changes to the brain.

Predicting progression from mild cognitive impairment to Alzheimer's disease on an individual subject basis by applying the CARE index across different independent cohorts.

The purposes of this study are to investigate whether the Characterizing Alzheimer's disease Risk Events (CARE) index can accurately predict progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) on an individual subject basis, and to investigate whether this model can be generalized to an independent cohort. Using an event-based probabilistic model approach to integrate widely available biomarkers from behavioral data and brain structural and functional imaging, we calculated the CARE index. We then applied the CARE index to identify which MCI individuals from the ADNI dataset progressed to AD during a three-year follow-up period. Subsequently, the CARE index was generalized to the prediction of MCI individuals from an independent Nanjing Aging and Dementia Study (NADS) dataset during the same time period. The CARE index achieved high prediction performance with 80.4% accuracy, 75% sensitivity, 82% specificity, and 0.809 area under the receiver operating characteristic (ROC) curve (AUC) on MCI subjects from the ADNI dataset over three years, and a highly validated prediction performance with 87.5% accuracy, 81% sensitivity, 90% specificity, and 0.861 AUC on MCI subjects from the NADS dataset. In conclusion, the CARE index is highly accurate, sufficiently robust, and generalized for predicting which MCI individuals will develop AD over a three-year period. This suggests that the CARE index can be usefully applied to select individuals with MCI for clinical trials and to identify which individuals will convert from MCI to AD for administration of early disease-modifying treatment.

Distinct neural correlates of episodic memory among apolipoprotein E alleles in cognitively normal elderly.

The apolipoprotein E (APOE) ε4 and ε2 alleles are acknowledged genetic factors modulating Alzheimer's disease (AD) risk and episodic memory (EM) deterioration in an opposite manner. Mounting neuroimaging studies describe EM-related brain activity differences among APOE alleles but remain limited in elucidating the underlying mechanism. Here, we hypothesized that the APOE ε2, ε3, and ε4 alleles have distinct EM neural substrates, as a manifestation of degeneracy, underlying their modulations on EM-related brain activity and AD susceptibility. To test the hypothesis, we identified neural correlates of EM function by correlating intrinsic hippocampal functional connectivity networks with neuropsychological EM performances in a voxelwise manner, with 129 cognitively normal elderly subjects (36 ε2 carriers, 44 ε3 homozygotes, and 49 ε4 carriers). We demonstrated significantly different EM neural correlates among the three APOE allele groups. Specifically, in the ε3 homozygotes, positive EM neural correlates were characterized in the Papez circuit regions; in the ε4 carriers, positive EM neural correlates involved the lateral temporal cortex, premotor cortex/sensorimotor cortex/superior parietal lobule, and cuneus; and in the ε2 carriers, negative EM neural correlates appeared in the bilateral frontopolar, posteromedial, and sensorimotor cortex. Further, in the ε4 carriers, the interaction between age and EM function occurred in the temporoparietal junction and prefrontal cortex. Our findings suggest that the underlying mechanism of APOE polymorphism modulations on EM function and AD susceptibility is genetically related to the neural degeneracy of EM function across APOE alleles.

Regional entropy of functional imaging signals varies differently in sensory and cognitive systems during propofol-modulated loss and return of behavioral responsiveness.

The level and richness of consciousness depend on information integration in the brain. Altered interregional functional interactions may indicate disrupted information integration during anesthetic-induced unconsciousness. How anesthetics modulate the amount of information in various brain regions has received less attention. Here, we propose a novel approach to quantify regional information content in the brain by the entropy of the principal components of regional blood oxygen-dependent imaging signals during graded propofol sedation. Fifteen healthy individuals underwent resting-state scans in wakeful baseline, light sedation (conscious), deep sedation (unconscious), and recovery (conscious). Light sedation characterized by lethargic behavioral responses was associated with global reduction of entropy in the brain. Deep sedation with completely suppressed overt responsiveness was associated with further reductions of entropy in sensory (primary and higher sensory plus orbital prefrontal cortices) but not high-order cognitive (dorsal and medial prefrontal, cingulate, parietotemporal cortices and hippocampal areas) systems. Upon recovery of responsiveness, entropy was restored in the sensory but not in high-order cognitive systems. These findings provide novel evidence for a reduction of information content of the brain as a potential systems-level mechanism of reduced consciousness during propofol anesthesia. The differential changes of entropy in the sensory and high-order cognitive systems associated with losing and regaining overt responsiveness are consistent with the notion of "disconnected consciousness", in which a complete sensory-motor disconnection from the environment occurs with preserved internal mentation.

Disrupted Interactions Between Arousal and Cortical Awareness Networks in MCS and VS/UWS Patients: Evidence from Resting-state Functional Imaging Connectivity.

Clinical patients in a vegetative state or unresponsive wakefulness syndrome (VS/UWS) demonstrate distinct arousal-awareness dissociation; the neuropathological mechanisms underlying such dissociation remain poorly understood. Here, we systematically examined how functional connectivity from the brainstem areas regulating arousal to the cortical networks supporting internal and external awareness is disrupted in minimally conscious state (MCS) and VS/UWS patients. Resting-state functional imaging was conducted in 23 MCS patients, 31 VS/UWS patients, and 20 age-matched healthy individuals. A hierarchical cluster analysis was conducted using all voxel-based signals in the brainstem to identify the specific areas for arousal. We found that the pontine tegmentum area (PTA) and caudal midbrain area persistently formed a distinct cluster that exclusively showed extensive connections with the cortical networks supporting internal and external awareness in healthy individuals, confirming their role in arousal. We show that functional connectivity from the PTA and caudal midbrain area to the cortical-awareness-supporting networks were significantly reduced in MCS and VS/UWS patients; importantly, as the clinical symptoms of consciousness disorders deepen from MCS to VS/UWS, functional connectivity strength became significantly reduced, changing from presenting no significant connections in MCS to widespread negative connections in VS/UWS. Additionally, we observed increased connectivity from the PTA and caudal midbrain area to limbic structures, the brainstem areas, and the cerebellum in MCS and VS/UWS patients, consistent with prior studies. These findings offer important insights into the neural network mechanisms underlying the long-observed arousal-awareness dissociation in VS/UWS patients and provide additional neuroimaging-based biomarkers for the clinical diagnosis of MCS and VS/UWS patients.

Reduced Functional Connectivity Between the Hypothalamus and High-order Cortical Regions in Adolescent Patients With Irritable Bowel Syndrome.

The hypothalamus plays a critical role in maintaining visceral homeostasis. Altered hypothalamus activation has been implicated in functional gastrointestinal disorders, including irritable bowel syndrome (IBS). One important aspect of homeostatic regulation is the cortical modulation of limbic and paralimbic subsystems, including the hypothalamus, which in turn affects the descending regulatory processes mediating visceral homeostasis. Using neuroimaging, we evaluated hypothalamus functional connectivity in adolescent patients with IBS and age-matched healthy controls who received rectal distension stimulations. More extensive hypothalamus connectivity was observed in liminal than subliminal condition in controls, but not in patients with IBS. Compared with controls, patients with IBS showed significantly reduced hypothalamus connectivity in the bilateral prefrontal cortices, supplementary motor and premotor areas, bilateral sensorimotor cortex, and limbic subareas, which are specifically involved in homeostatic regulation. The findings support the generalized homeostatic regulation model that reduced cortical and limbic modulations of hypothalamus functioning underlies disrupted visceral homeostasis in patients with IBS.

The Effect of Apolipoprotein E ε4 (APOE ε4) on Visuospatial Working Memory in Healthy Elderly and Amnestic Mild Cognitive Impairment Patients: An Event-Related Potentials Study.

Background: Apolipoprotein E (APOE) ε4 is the only established risk gene for late-onset, sporadic Alzheimer's disease (AD). Previous studies have provided inconsistent evidence for the effect of APOE ε4 status on the visuospatial working memory (VSWM). Objective: The aim was to investigate the effect of APOE ε4 on VSWM with an event-related potential (ERP) study in healthy controls (HC) and amnestic mild cognitive impairment (aMCI) patients. Methods: The study recorded 39 aMCI patients (27 APOE ε4 non-carriers and 12 APOE ε4 carriers) and their 43 matched controls (25 APOE ε4 non-carriers and 18 APOE ε4 carriers) with an 64-channel electroencephalogram. Participants performed an N-back task, a VSWM paradigm that manipulated the number of items to be stored in memory. Results: The present study detected reduced accuracy and delayed mean correct response time (RT) in aMCI patients compared to HC. P300, a positive component that peaks between 300 and 500 ms, was elicited by the VSWM task. In addition, aMCI patients showed decreased P300 amplitude at the central-parietal (CP1, CPz, and CP2) and parietal (P1, Pz, and P2) electrodes in 0- and 1-back task compared to HC. In both HC and aMCI patients, APOE ε4 carriers showed reduced P300 amplitude with respect to non-carriers, whereas no significant differences in accuracy or RT were detected between APOE ε4 carriers and non-carriers. Additionally, standardized low-resolution brain electromagnetic tomography analysis (s-LORETA) showed enhanced brain activation in the right parahippocampal gyrus (PHG) during P300 time range in APOE ε4 carriers with respect to non-carriers in aMCI patients. Conclusion: It demonstrated that P300 amplitude could predict VSWM deficits in aMCI patients and contribute to early detection of VSWM deficits in APOE ε4 carriers.

Large-Scale Network Analysis of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Comparative Study.

Network analysis based on graph theory depicts the brain as a complex network that allows inspection of overall brain connectivity pattern and calculation of quantifiable network metrics. To date, large-scale network analysis has not been applied to resting-state functional networks in complete spinal cord injury (SCI) patients. To characterize modular reorganization of whole brain into constituent nodes and compare network metrics between SCI and control subjects, fifteen subjects with chronic complete cervical SCI and 15 neurologically intact controls were scanned. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI). Correlation analysis was performed between every ROI pair to construct connectivity matrices and ROIs were categorized into distinct modules. Subsequently, local efficiency (LE) and global efficiency (GE) network metrics were calculated at incremental cost thresholds. The application of a modularity algorithm organized the whole-brain resting-state functional network of the SCI and the control subjects into nine and seven modules, respectively. The individual modules differed across groups in terms of the number and the composition of constituent nodes. LE demonstrated statistically significant decrease at multiple cost levels in SCI subjects. GE did not differ significantly between the two groups. The demonstration of modular architecture in both groups highlights the applicability of large-scale network analysis in studying complex brain networks. Comparing modules across groups revealed differences in number and membership of constituent nodes, indicating modular reorganization due to neural plasticity.

Fine-Grained Parcellation of Brain Connectivity Improves Differentiation of States of Consciousness During Graded Propofol Sedation.

Conscious perception relies on interactions between spatially and functionally distinct modules of the brain at various spatiotemporal scales. These interactions are altered by anesthesia, an intervention that leads to fading consciousness. Relatively little is known about brain functional connectivity and its anesthetic modulation at a fine spatial scale. Here, we used functional imaging to examine propofol-induced changes in functional connectivity in brain networks defined at a fine-grained parcellation based on a combination of anatomical and functional features. Fifteen healthy volunteers underwent resting-state functional imaging in wakeful baseline, mild sedation, deep sedation, and recovery of consciousness. Compared with wakeful baseline, propofol produced widespread, dose-dependent functional connectivity changes that scaled with the extent to which consciousness was altered. The dominant changes in connectivity were associated with the frontal lobes. By examining node pairs that demonstrated a trend of functional connectivity change between wakefulness and deep sedation, quadratic discriminant analysis differentiated the states of consciousness in individual participants more accurately at a fine-grained parcellation (e.g., 2000 nodes) than at a coarse-grained parcellation (e.g., 116 anatomical nodes). Our study suggests that defining brain networks at a high granularity may provide a superior imaging-based distinction of the graded effect of anesthesia on consciousness.

Evaluation of Whole-Brain Resting-State Functional Connectivity in Spinal Cord Injury: A Large-Scale Network Analysis Using Network-Based Statistic.

Large-scale network analysis characterizes the brain as a complex network of nodes and edges to evaluate functional connectivity patterns. The utility of graph-based techniques has been demonstrated in an increasing number of resting-state functional MRI (rs-fMRI) studies in the normal and diseased brain. However, to our knowledge, graph theory has not been used to study the reorganization pattern of resting-state brain networks in patients with traumatic complete spinal cord injury (SCI). In the present analysis, we applied a graph-theoretical approach to explore changes to global brain network architecture as a result of SCI. Fifteen subjects with chronic (> 2 years) complete (American Spinal Injury Association [ASIA] A) cervical SCI and 15 neurologically intact controls were scanned using rs-fMRI. The data were preprocessed followed by parcellation of the brain into 116 regions of interest (ROI) or nodes. The average time series was extracted at each node, and correlation analysis was performed between every pair of nodes. A functional connectivity matrix for each subject was then generated. Subsequently, the matrices were averaged across groups, and network changes were evaluated between groups using the network-based statistic (NBS) method. Our results showed decreased connectivity in a subnetwork of the whole brain in SCI compared with control subjects. Upon further examination, increased connectivity was observed in a subnetwork of the sensorimotor cortex and cerebellum network in SCI. In conclusion, our findings emphasize the applicability of NBS to study functional connectivity architecture in diseased brain states. Further, we show reorganization of large-scale resting-state brain networks in traumatic SCI, with potential prognostic and therapeutic implications.

Propofol attenuates low-frequency fluctuations of resting-state fMRI BOLD signal in the anterior frontal cortex upon loss of consciousness.

Recent studies indicate that spontaneous low-frequency fluctuations (LFFs) of resting-state functional magnetic resonance imaging (rs-fMRI) blood oxygen level-dependent (BOLD) signals are driven by the slow (<0.1Hz) modulation of ongoing neuronal activity synchronized locally and across remote brain regions. How regional LFFs of the BOLD fMRI signal are altered during anesthetic-induced alteration of consciousness is not well understood. Using rs-fMRI in 15 healthy participants, we show that during administration of propofol to achieve loss of behavioral responsiveness indexing unconsciousness, the fractional amplitude of LFF (fALFF index) was reduced in comparison to wakeful baseline in the anterior frontal regions, temporal pole, hippocampus, parahippocampal gyrus, and amygdala. Such changes were absent in large areas of the motor, parietal, and sensory cortices. During light sedation characterized by the preservation of overt responsiveness and therefore consciousness, fALFF was reduced in the subcortical areas, temporal pole, medial orbital frontal cortex, cingulate cortex, and cerebellum. Between light sedation and deep sedation, fALFF was reduced primarily in the medial and dorsolateral frontal areas. The preferential reduction of LFFs in the anterior frontal regions is consistent with frontal to sensory-motor cortical disconnection and may contribute to the suppression of consciousness during general anesthesia.

Intrinsic inter-network brain dysfunction correlates with symptom dimensions in late-life depression.

Prior studies have demonstrated dysfunctions within the core neurocognitive networks (the executive control [ECN], default mode [DMN] and salience [SN] networks) in late-life depression (LLD). Whether inter-network dysfunctional connectivity is present in LLD, and if such disruptions are associated with core symptom dimensions is unknown. A cross-sectional resting-state functional connectivity magnetic resonance imaging investigation was conducted of LLD (n = 39) and age- and gender-equated healthy comparison (HC) (n = 29) participants. Dual regression independent component analysis approach was used to identify components that represented the ECN, DMN and SN. The intrinsic inter-network connectivity was compared between LLD and HC participants and the relationship of inter-network connectivity abnormalities with dimensional measures was examined. Relative to HC participants, LLD subjects showed decreased inter-network connectivity between the bilateral ECN and default mode subcortical (thalamus, basal ganglia and ventral striatum) networks, and the left ECN and SN insula component; and increased inter-network connections between the left ECN and posterior DMN and salience (dorsal anterior cingulate) network components. Distinct inter-network connectivity abnormalities correlated with depression and anxiety severity, and executive dysfunction in LLD participants. LLD subjects also showed pronounced intra-network connectivity differences within the ECN, whereas fewer but significant DMN and SN disruptions were also detected. Investigating the intrinsic inter-network functional connectivity could provide a mechanistic framework to better understand the neural basis that underlies core symptom dimensions in LLD. Inter-network connectivity measures have the potential to be neuroimaging biomarkers of symptom dimensions comprising LLD, and may assist in developing symptom-specific treatment algorithms.

Staging Alzheimer's Disease Risk by Sequencing Brain Function and Structure, Cerebrospinal Fluid, and Cognition Biomarkers.

This study aims to develop a composite biomarker that can accurately measure the sequential biological stages of Alzheimer's disease (AD) on an individual level. We selected 144 subjects from the Alzheimer's Disease Neuroimaging Initiative 2 datasets. Ten biomarkers, from brain function and structure, cerebrospinal fluid, and cognitive performance, were integrated using the event-based probabilistic model to estimate their optimal temporal sequence (Soptimal). We identified the numerical order of the Soptimal as the characterizing Alzheimer's disease risk events (CARE) index to measure disease stage. The results show that, in the Soptimal, hippocampal and posterior cingulate cortex network biomarkers occur first, followed by aberrant cerebrospinal fluid amyloid-ß and p-tau levels, then cognitive deficit, and finally regional gray matter loss and fusiform network abnormality. The CARE index significantly correlates with disease severity and exhibits high reliability. Our findings demonstrate that use of the CARE index would advance AD stage measurement across the whole AD continuum and facilitate personalized treatment of AD.