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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) e4 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 e3 homozygotes and 21 e4 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 e3 homozygotes, but in the sensorimotor cortex and cuneus in the e4 carriers. Longitudinally, the e4 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 e4 carriers, which may serve as a promising enrichment strategy for secondary prevention trials of AD.

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.

Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New 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.

According to recent criteria of classification, amnestic mild cognitive impairment (aMCI) could be divided into two categories: single-domain aMCI (sd-aMCI) and multiple-domain aMCI (md-aMCI). The difference between sd-aMCI and md-aMCI needs further exploration. The present study aimed to compare deficits in visuospatial working memory (VSWM) and executive function between sd-aMCI versus md-aMCI patients by use of event-related potentials (ERP) and standardized low-resolution brain electromagnetic tomography analysis (sLORETA).The ERP data were measured and analyzed in 26 sd-aMCI, 13 md-aMCI patients and 46 healthy elderly controls (HEC) during VSWM and Go/Nogo processes.During VSWM task, md-aMCI patients showed decreased P300 amplitude compared to HEC and sd-aMCI patients (All p 0.05). As compared to sd-aMCI, md-aMCI showed a hypoactivation in the right middle frontal gyrus in 1-back task during the P300 time range. During the Go/Nogo task, sd-aMCI and md-aMCI patients showed reduced N200 amplitude, compared to HEC (All p 0.05). However, md-aMCI patients had decreased N200 amplitude, with respect to sd-aMCI patients. Further, as compared to sd-aMCI patients, md-aMCI patients showed a hypoactivation in the right superior frontal gyrus during the N200 time range.These findings with a combined ERP and sLORETA study showed more severe deficits in updating operations of WM, detections of the target stimulus and conflict processes in md-aMCI, compared to sd-aMCI patients.The present study showed that a combined ERP and sLORETA study during the VSWM and Go/Nogo tasks could distinguish md-aMCI from sd-aMCI.

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.

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.

Functional connectivity magnetic resonance imaging (fcMRI), a specific form of MRI imaging, quantitatively assesses connectivity between brain regions that share functional properties. Functional connectivity magnetic resonance imaging has already provided unique insights into changes in the brain in patients with conditions such as depression and pain and symptoms that have been reported by patients with psoriasis and are known to impact quality of life. To identify the central neurological impact of psoriasiform inflammation of the skin, we applied fcMRI analysis to mice that had been topically treated with the Toll-like receptor agonist, imiquimod (IMQ) to induce psoriasiform dermatitis. Brain insula regions, due to their suggested role in stress, were chosen as seed regions for fcMRI analysis. Mouse ear and head skin developed psoriasiform epidermal thickening (up to 4-fold, P < .05) and dermal inflammation after 4 days of topical treatment with IMQ. After fcMRI analysis, IMQ-treated mice showed significantly increased insula fc with wide areas throughout the brain, including, but not limited to, the somatosensory cortex, anterior cingulate cortex, and caudate putamen ( P < .005). This reflects a potential central neurological impact of IMQ-induced psoriasis-like skin inflammation. These data indicate that fcMRI may be valuable tool to quantitatively assess the neurological impact of skin inflammation in patients with psoriasis.

Objectives The study aimed to investigate and compare the effect of cognitive reserve (CR) on brain activation in healthy controls (HC) and amnestic mild cognitive impairment (aMCI) patients during 0-back and 1-back tasks measured by event-related potential (ERP). Methods The study recorded 85 subjects (39 aMCI patients and 46 their matched controls) with a 64-channel electroencephalogram (EEG). Subjects performed 0- and 1-back tasks. Results Compared to HC, aMCI patients showed reduced accuracy, delayed mean correct response time (RT) and decreased P300 amplitude at central-parietal and parietal electrodes. A mediation analysis indicated that higher CR reduced neural inefficiency, which might be associated with better task performance in HC. However, no correlation was detected between CR and neural inefficiency in aMCI patients, whereas higher CR was still related to enhanced accuracy and prolonged RT in aMCI patients. Conclusions The present study reported that higher CR could contribute to better task performance via down-regulating neural inefficiency in HC. In addition, higher CR might modulate attention processes in aMCI via a way distinct from that in HC, and eventually result in better task performance. Significance The study provided evidence for that improving CR might lower cognitive impairment of healthy elderly and aMCI patients.

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.

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.

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 (

The parahippocampal gyrus-orbitofrontal cortex (PHG-OFC) circuit in humans is homologous to the postrhinal cortex (POR)-ventral lateral orbitofrontal cortex (vlOFC) circuit in rodents. Both are associated with visuospatial malfunctions in Alzheimer's disease (AD). However, the underlying mechanisms remain to be elucidated. In this study, we explored the relationship between an impaired POR-vlOFC circuit and visuospatial memory deficits through retrograde tracing and in vivo local field potential recordings in 5XFAD mice, and investigated alterations of the PHG-OFC circuit by multi-domain magnetic resonance imaging (MRI) in patients on the AD spectrum. We demonstrated that an impaired glutamatergic POR-vlOFC circuit resulted in deficient visuospatial memory in 5XFAD mice. Moreover, MRI measurements of the PHG-OFC circuit had an accuracy of 77.33% for the classification of amnestic mild cognitive impairment converters versus non-converters. Thus, the PHG-OFC circuit explains the neuroanatomical basis of visuospatial memory deficits in AD, thereby providing a potential predictor for AD progression and a promising interventional approach for AD.

The apolipoprotein E (APOE) e4 and e2 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 e2, e3, and e4 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 e2 carriers, 44 e3 homozygotes, and 49 e4 carriers). We demonstrated significantly different EM neural correlates among the three APOE allele groups. Specifically, in the e3 homozygotes, positive EM neural correlates were characterized in the Papez circuit regions; in the e4 carriers, positive EM neural correlates involved the lateral temporal cortex, premotor cortex/sensorimotor cortex/superior parietal lobule, and cuneus; and in the e2 carriers, negative EM neural correlates appeared in the bilateral frontopolar, posteromedial, and sensorimotor cortex. Further, in the e4 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.

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-β 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.

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.