Medial temporal lobe connectivity and its associations with cognition in early Alzheimer's disease

Evaluating frontoparietal network topography for diagnostic markers of Alzheimer's disease

Numerous prospective biomarkers are being studied for their ability to diagnose various stages of Alzheimer's disease (AD). High-density electroencephalogram (EEG) methods show promise as an accurate, economical, non-invasive approach to measuring the electrical potentials of brains associated with AD. Event-related potentials (ERPs) may serve as clinically useful biomarkers of AD. Through analysis of secondary data, the present study examined the performance and distribution of N4/P6 ERPs across the frontoparietal network (FPN) using EEG topographic mapping. ERP measures and memory as a function of reaction time (RT) were compared between a group of (n = 63) mild untreated AD patients and a control group of (n = 73) healthy age-matched adults. Based on the literature presented, it was expected that healthy controls would outperform patients in peak amplitude and mean component latency across three parameters of memory when measured at optimal N4 (frontal) and P6 (parietal) locations. It was also predicted that the control group would exhibit neural cohesion through FPN integration during cross-modal tasks, thus demonstrating healthy cognitive functioning consistent with older healthy adults. By targeting select frontal and parietal EEG reference channels based on N4/P6 component time windows and positivity, our findings demonstrated statistically significant group variations between controls and patients in N4/P6 peak amplitudes and latencies during cross-modal testing. Our results also support that the N4 ERP might be stronger than its P6 counterpart as a possible candidate biomarker. We conclude through topographic mapping that FPN integration occurs in healthy controls but is absent in AD patients during cross-modal memory tasks.

Divergent functional connectivity changes associated with white matter hyperintensities

Age-related white matter hyperintensities are a common feature and are known to be negatively associated with structural integrity, functional connectivity, and cognitive performance. However, this has yet to be fully understood mechanistically. We analyzed multiple MRI modalities acquired in 465 non-demented individuals from the Swedish BioFINDER study including 334 cognitively normal and 131 participants with mild cognitive impairment. White matter hyperintensities were automatically quantified using fluid-attenuated inversion recovery MRI and parameters from diffusion tensor imaging were estimated in major white matter fibre tracts. We calculated fMRI resting state-derived functional connectivity within and between predefined cortical regions structurally linked by the white matter tracts. How change in functional connectivity is affected by white matter lesions and related to cognition (in the form of executive function and processing speed) was explored. We examined the functional changes using a measure of sample entropy. As expected hyperintensities were associated with disrupted structural white matter integrity and were linked to reduced functional interregional lobar connectivity, which was related to decreased processing speed and executive function. Simultaneously, hyperintensities were also associated with increased intraregional functional connectivity, but only within the frontal lobe. This phenomenon was also associated with reduced cognitive performance. The increased connectivity was linked to increased entropy (reduced predictability and increased complexity) of the involved voxels' blood oxygenation level-dependent signal. Our findings expand our previous understanding of the impact of white matter hyperintensities on cognition by indicating novel mechanisms that may be important beyond this particular type of brain lesions.

Prior-Guided Adversarial Learning With Hypergraph for Predicting Abnormal Connections in Alzheimer's Disease

Alzheimer's disease (AD) is characterized by alterations of the brain's structural and functional connectivity during its progressive degenerative processes. Existing auxiliary diagnostic methods have accomplished the classification task, but few of them can accurately evaluate the changing characteristics of brain connectivity. In this work, a prior-guided adversarial learning with hypergraph (PALH) model is proposed to predict abnormal brain connections using triple-modality medical images. Concretely, a prior distribution from anatomical knowledge is estimated to guide multimodal representation learning using an adversarial strategy. Also, the pairwise collaborative discriminator structure is further utilized to narrow the difference in representation distribution. Moreover, the hypergraph perceptual network is developed to effectively fuse the learned representations while establishing high-order relations within and between multimodal images. Experimental results demonstrate that the proposed model outperforms other related methods in analyzing and predicting AD progression. More importantly, the identified abnormal connections are partly consistent with previous neuroscience discoveries. The proposed model can evaluate the characteristics of abnormal brain connections at different stages of AD, which is helpful for cognitive disease study and early treatment.

Exploring Brain Effective Connectivity Networks Through Spatiotemporal Graph Convolutional Models

Learning brain effective connectivity networks (ECN) from functional magnetic resonance imaging (fMRI) data has gained much attention in recent years. With the successful applications of deep learning in numerous fields, several brain ECN learning methods based on deep learning have been reported in the literature. However, current methods ignore the deep temporal features of fMRI data and fail to fully employ the spatial topological relationship between brain regions. In this article, we propose a novel method for learning brain ECN based on spatiotemporal graph convolutional models (STGCM), named STGCMEC, in which we first adopt the temporal convolutional network to extract the deep temporal features of fMRI data and utilize the graph convolutional network to update the spatial features of each brain region by aggregating information from neighborhoods, which makes the features of brain regions more discriminative. Then, based on such features of brain regions, we design a joint loss function to guide STGCMEC to learn the brain ECN, which includes a task prediction loss and a graph regularization loss. The experimental results on a simulated dataset and a real Alzheimer's disease neuroimaging initiative (ADNI) dataset show that the proposed STGCMEC is able to better learn brain ECN compared with some state-of-the-art methods.

Emergence of the brain-border immune niches and their contribution to the development of neurodegenerative diseases

Historically, the central nervous system (CNS) was regarded as 'immune-privileged', possessing its own distinct immune cell population. This immune privilege was thought to be established by a tight blood-brain barrier (BBB) and blood-cerebrospinal-fluid barrier (BCSFB), which prevented the crossing of peripheral immune cells and their secreted factors into the CNS parenchyma. However, recent studies have revealed the presence of peripheral immune cells in proximity to various brain-border niches such as the choroid plexus, cranial bone marrow (CBM), meninges, and perivascular spaces. Furthermore, emerging evidence suggests that peripheral immune cells may be able to infiltrate the brain through these sites and play significant roles in driving neuronal cell death and pathology progression in neurodegenerative disease. Thus, in this review, we explore how the brain-border immune niches may contribute to the pathogenesis of neurodegenerative disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and multiple sclerosis (MS). We then discuss several emerging options for harnessing the neuroimmune potential of these niches to improve the prognosis and treatment of these debilitative disorders using novel insights from recent studies.

Oxytocin attenuates hypothalamic injury-induced cognitive dysfunction by inhibiting hippocampal ERK signaling and Aβ deposition

In clinical settings, tumor compression, trauma, surgical injury, and other types of injury can cause hypothalamic damage, resulting in various types of hypothalamic dysfunction. Impaired release of oxytocin can lead to cognitive impairment and affect prognosis and long-term quality of life after hypothalamic injury. Hypothalamic injury-induced cognitive dysfunction was detected in male animals. Behavioral parameters were measured to assess the characteristics of cognitive dysfunction induced by hypothalamic-pituitary stalk lesions. Brains were collected for high-throughput RNA sequencing and immunostaining to identify pathophysiological changes in hippocampal regions highly associated with cognitive function after injury to corresponding hypothalamic areas. Through transcriptomic analysis, we confirmed the loss of oxytocin neurons after hypothalamic injury and the reversal of hypothalamic-induced cognitive dysfunction after oxytocin supplementation. Furthermore, overactivation of the ERK signaling pathway and β-amyloid deposition in the hippocampal region after hypothalamic injury were observed, and cognitive function was restored after inhibition of ERK signaling pathway overactivation. Our findings suggest that cognitive dysfunction after hypothalamic injury may be caused by ERK hyperphosphorylation in the hippocampal region resulting from a decrease in the number of oxytocin neurons, which in turn causes β-amyloid deposition.

Phosphodiesterase 8 (PDE8): Distribution and Cellular Expression and Association with Alzheimer's Disease

Phosphodiesterase 8 (PDE8), as a member of PDE superfamily, specifically promotes the hydrolysis and degradation of intracellular cyclic adenosine monophosphate (cAMP), which may be associated with pathogenesis of Alzheimer's disease (AD). However, little is currently known about potential role in the central nervous system (CNS). Here we investigated the distribution and expression of PDE8 in brain of mouse, which we believe can provide evidence for studying the role of PDE8 in CNS and the relationship between PDE8 and AD. Here, C57BL/6J mice were used to observe the distribution patterns of two subtypes of PDE8, PDE8A and PDE8B, in different sexes in vivo by western blot (WB). Meanwhile, C57BL/6J mice were also used to demonstrate the distribution pattern of PDE8 in selected brain regions and localization in neural cells by WB and multiplex immunofluorescence staining. Furthermore, the triple transgenic (3×Tg-AD) mice and wild type (WT) mice of different ages were used to investigate the changes of PDE8 expression in the hippocampus and cerebral cortex during the progression of AD. PDE8 was found to be widely expressed in multiple tissues and organs including heart, kidney, stomach, brain, and liver, spleen, intestines, and uterus, with differences in expression levels between the two subtypes of PDE8A and PDE8B, as well as two sexes. Meanwhile, PDE8 was widely distributed in the brain, especially in areas closely related to cognitive function such as cerebellum, striatum, amygdala, cerebral cortex, and hippocampus, without differences between sexes. Furthermore, PDE8A was found to be expressed in neuronal cells, microglia and astrocytes, while PDE8B is only expressed in neuronal cells and microglia. PDE8A expression in the hippocampus of both female and male 3×Tg-AD mice was gradually increased with ages and PDE8B expression was upregulated only in cerebral cortex of female 3×Tg-AD mice with ages. However, the expression of PDE8A and PDE8B was apparently increased in both cerebral cortex and hippocampus in both female and male 10-month-old 3×Tg-AD mice compared WT mice. These results suggest that PDE8 may be associated with the progression of AD and is a potential target for its prevention and treatment in the future.

Age-Related Brain Atrophy and the Positive Effects of Behavioral Enrichment in Middle-Aged Beagles

Aging dogs serve as a valuable preclinical model for Alzheimer's disease (AD) due to their natural age-related development of β-amyloid (Aβ) plaques, human-like metabolism, and large brains that are ideal for studying structural brain aging trajectories from serial neuroimaging. Here we examined the effects of chronic treatment with the calcineurin inhibitor (CNI) tacrolimus or the nuclear factor of activated T cells (NFAT)-inhibiting compound Q134R on age-related canine brain atrophy from a longitudinal study in middle-aged beagles (36 females, 7 males) undergoing behavioral enrichment. Annual MRI was analyzed using modern, automated techniques for region-of-interest-based and voxel-based volumetric assessments. We found that the frontal lobe showed accelerated atrophy with age, while the caudate nucleus remained relatively stable. Remarkably, the hippocampus increased in volume in all dogs. None of these changes were influenced by tacrolimus or Q134R treatment. Our results suggest that behavioral enrichment can prevent atrophy and increase the volume of the hippocampus but does not prevent aging-associated prefrontal cortex atrophy.

The Neuropsychological Assessment Battery Driving Scenes Test in a Dementia Clinic

OBJECTIVE

In dementia research, the Driving Scenes test from the Neuropsychological Assessment Battery has been shown to relate to memory, dementia diagnosis, and functional impairment. The aim of the current study was to examine Driving Scenes and its component scores, and their relationships with cognition and daily functioning, in a mixed dementia clinic sample.

METHOD

One hundred U.S. military veterans between the ages of 55 and 88 were administered a full neuropsychological protocol that included Driving Scenes.

RESULTS

The Driving Scenes score and its subscores were strongly related to memory skills, and there were additional subscore associations with language and visuospatial functions. Driving Scenes uniquely predicted reported bill payment difficulties and tendency to get lost while driving, which were not predicted by other performances across cognitive domains.

CONCLUSION

Driving Scenes is a clinically and functionally relevant measure of memory. Although the Driving Scenes total score remains useful in dementia evaluations, component scores and error scores contribute additional practical information.

Explainable AI-based Deep-SHAP for mapping the multivariate relationships between regional neuroimaging biomarkers and cognition

BACKGROUND

Mild cognitive impairment (MCI)/Alzheimer's disease (AD) is associated with cognitive decline beyond normal aging and linked to the alterations of brain volume quantified by magnetic resonance imaging (MRI) and amyloid-beta (Aβ) quantified by positron emission tomography (PET). Yet, the complex relationships between these regional imaging measures and cognition in MCI/AD remain unclear. Explainable artificial intelligence (AI) may uncover such relationships.

METHOD

We integrate the AI-based deep learning neural network and Shapley additive explanations (SHAP) approaches and introduce the Deep-SHAP method to investigate the multivariate relationships between regional imaging measures and cognition. After validating this approach on simulated data, we apply it to real experimental data from MCI/AD patients.

RESULTS

Deep-SHAP significantly predicted cognition using simulated regional features and identified the ground-truth simulated regions as the most significant multivariate predictors. When applied to experimental MRI data, Deep-SHAP revealed that the insula, lateral occipital, medial frontal, temporal pole, and occipital fusiform gyrus are the primary contributors to global cognitive decline in MCI/AD. Furthermore, when applied to experimental amyloid Pittsburgh compound B (PiB)-PET data, Deep-SHAP identified the key brain regions for global cognitive decline in MCI/AD as the inferior temporal, parahippocampal, inferior frontal, supratemporal, and lateral frontal gray matter.

CONCLUSION

Deep-SHAP method uncovered the multivariate relationships between regional brain features and cognition, offering insights into the most critical modality-specific brain regions involved in MCI/AD mechanisms.

Brain functional connectivity in hyperthyroid patients: systematic review

Introduction

Functional connectivity (FC) is the correlation between brain regions' activities, studied through neuroimaging techniques like fMRI. It helps researchers understand brain function, organization, and dysfunction. Hyperthyroidism, characterized by high serum levels of free thyroxin and suppressed thyroid stimulating hormone, can lead to mood disturbance, cognitive impairment, and psychiatric symptoms. Excessive thyroid hormone exposure can enhance neuronal death and decrease brain volume, affecting memory, attention, emotion, vision, and motor planning.

Methods

We conducted thorough searches across Google Scholar, PubMed, Hinari, and Science Direct to locate pertinent articles containing original data investigating FC measures in individuals diagnosed with hyperthyroidism.

Results

The systematic review identified 762 articles, excluding duplicates and non-matching titles and abstracts. Four full-text articles were included in this review. In conclusion, a strong bilateral hippocampal connection in hyperthyroid individuals suggests a possible neurobiological influence on brain networks that may affect cognitive and emotional processing.

Systematic Review Registration

PROSPERO, CRD42024516216.

Multi-modal Neuroimaging Phenotyping of Mnemonic Anosognosia in the Aging Brain

BACKGROUND

Unawareness is a behavioral condition characterized by a lack of self-awareness of objective memory decline. In the context of Alzheimer's Disease (AD), unawareness may develop in predementia stages and contributes to disease severity and progression. Here, we use in-vivo multi-modal neuroimaging to profile the brain phenotype of individuals presenting altered self-awareness of memory during aging.

METHODS

Amyloid- and tau-PET (N = 335) and resting-state functional MRI (N = 713) imaging data of individuals from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4)/Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) Study were used in this research. We applied whole-brain voxel-wise and region-of-interest analyses to characterize the cortical intersections of tau, amyloid, and functional connectivity networks underlying unawareness in the aging brain compared to aware, complainer and control groups.

RESULTS

Individuals with unawareness present elevated amyloid and tau burden in midline core regions of the default mode network compared to aware, complainer or control individuals. Unawareness is characterized by an altered network connectivity pattern featuring hyperconnectivity in the medial anterior prefrontal cortex and posterior occipito-parietal regions co-locating with amyloid and tau deposition.

CONCLUSIONS

Unawareness is an early behavioral biomarker of AD pathology. Failure of the self-referential system in unawareness of memory decline can be linked to amyloid and tau burden, along with functional network connectivity disruptions, in several medial frontal and parieto-occipital areas of the human brain.

Brain-based sex differences in schizophrenia: A systematic review of fMRI studies

Schizophrenia is a chronic psychiatric disorder with characteristic symptoms of delusions, hallucinations, lack of motivation, and paucity of thought. Recent evidence suggests that the symptoms of schizophrenia, negative symptoms in particular, vary widely between the sexes and that symptom onset is earlier in males. A better understanding of sex-based differences in functional magnetic resonance imaging (fMRI) studies of schizophrenia may provide a key to understanding sex-based symptom differences. This study aimed to summarize sex-based functional magnetic resonance imaging (fMRI) differences in brain activity of patients with schizophrenia. We searched PubMed and Scopus to find fMRI studies that assessed sex-based differences in the brain activity of patients with schizophrenia. We excluded studies that did not evaluate brain activity using fMRI, did not evaluate sex differences, and were nonhuman or in vitro studies. We found 12 studies that met the inclusion criteria for the current systematic review. Compared to females with schizophrenia, males with schizophrenia showed more blood oxygen level-dependent (BOLD) activation in the cerebellum, the temporal gyrus, and the right precuneus cortex. Male patients also had greater occurrence of low-frequency fluctuations in cerebral blood flow in frontal and parietal lobes and the insular cortex, while female patients had greater occurrence of low-frequency fluctuations in the hippocampus, parahippocampus, and lentiform nucleus. The current study summarizes fMRI studies that evaluated sex-based fMRI brain differences in schizophrenia that may help to shed light on the underlying pathophysiology and further understanding of sex-based differences in the clinical presentation and course of the disorder.

Efficacy and safety of repetitive Transcranial Magnetic Stimulation and transcranial Direct Current Stimulation in memory deficits in patients with Alzheimer's disease: Meta-analysis and systematic review

Repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) are two of the most used non-pharmacological interventions for Alzheimer's Disease (AD). However, most of the clinical trials have focused on evaluating the effects on global cognition and not on specific cognitive functions. Therefore, considering that memory loss is one of the hallmark symptoms of AD, we aim to assess the efficacy and safety of tDCS and rTMS in memory deficits. For that, multilevel random effect models were performed considering the standardized mean difference (SMD) between active and sham stimulation. A total of 19 studies with 411 participants demonstrated positive effects in memory after tDCS (SMD=0.20, p = 0.04) and rTMS (SMD=0.44, p = 0.001). Subgroup analysis revealed that tDCS had greater efficacy when administered in temporal regions (SMD=0.32, p = 0.04), whereas rTMS was superior when applied in frontal regions (SMD=0.61, p < 0.001). Therefore, depending on the brain region of stimulation, both interventions produced a positive effect on memory symptoms in AD patients. Finally, the safety of both techniques was observed in the AD population after the reporting of almost no serious events.

Effects of childhood maltreatment and major depressive disorder on functional connectivity in hippocampal subregions

Major Depressive Disorder (MDD) with childhood maltreatment is a prevalent clinical phenotype. Prior studies have observed abnormal hippocampal activity in MDD patients, considering the hippocampus as a single nucleus. However, there is limited research investigating the static and dynamic changes in hippocampal subregion functional connectivity (FC) in MDD patients with childhood maltreatment. Therefore, we employed static and dynamic FC analyses using hippocampal subregions, including the anterior hippocampus and posterior hippocampus, as seed regions to investigate the neurobiological alterations associated with MDD resulting from childhood maltreatment. This study involved four groups: MDD with (n = 48) and without childhood maltreatment (n = 30), as well as healthy controls with (n = 57) and without (n = 46) childhood maltreatment. Compared to MDD patients without childhood maltreatment, those with childhood maltreatment exhibit altered FC between the hippocampal subregion and multiple brain regions, including the anterior cingulate gyrus, superior frontal gyrus, putamen, calcarine gyrus, superior temporal gyrus, angular gyrus, and supplementary motor area. Additionally, dynamic FC between the right medial-2 hippocampal head and the right calcarine gyrus shows a positive correlation with childhood maltreatment across all its subtypes. Moreover, dFC between the right hippocampal tail and the left angular gyrus moderates the relationship between childhood maltreatment and the depression severity. Our findings of distinct FC patterns within hippocampal subregions provide new clues for understanding the neurobiological basis of MDD with childhood maltreatment.

Altered functional connectivity between the default mode network in primary angle-closure glaucoma patients

Previous studies have recognized glaucoma as a neurodegenerative disease that causes extensive brain damage and is closely associated with cognitive function. In this study, we employed functional MRI to examine the intrinsic functional connectivity patterns of the default mode network (DMN) in patients diagnosed with primary angle-closure glaucoma (PACG), exploring its association with cognitive dysfunction. A total of 34 patients diagnosed with PACG and 34 healthy controls (HC), who were matched in terms of sex, age, and education, were included in the control group. The posterior cingulate cortex (PCC) was selected as the region of interest to examine functional connectivity alterations. Compared with the HC group, functional connectivity was attenuated in left anterior cingulum cortex and left paracentral lobule between with PCC in the PACG group, the results are statistically significant. Our study revealed that patients with PACG exhibit weakened functional connectivity within the DMN. This finding suggests the presence of a neurological mechanism that is associated with both visual dysfunction and cognitive impairments in PACG patients. Furthermore, our study provides neuroimaging evidence that can aid in the exploration of spontaneous neurological alterations and facilitate a deeper investigation of alterations in the visual conduction pathways of PACG patients.

Effects of mixed metal exposures on MRI diffusion features in the medial temporal lobe

Background

Environmental exposure to metal mixtures is common and may be associated with increased risk for neurodegenerative disorders including Alzheimer's disease.

Objective

This study examined associations of mixed metal exposures with medial temporal lobe (MTL) MRI structural metrics and neuropsychological performance.

Methods

Metal exposure history, whole blood metal, and neuropsychological tests were obtained from subjects with/without a history of mixed metal exposure from welding fumes (42 exposed subjects; 31 controls). MTL structures (hippocampus, entorhinal and parahippocampal cortices) were assessed by morphologic (volume, cortical thickness) and diffusion tensor imaging [mean (MD), axial (AD), radial diffusivity (RD), and fractional anisotropy (FA)] metrics. In exposed subjects, correlation, multiple linear, Bayesian kernel machine regression, and mediation analyses were employed to examine effects of single- or mixed-metal predictor(s) and their interactions on MTL structural and neuropsychological metrics; and on the path from metal exposure to neuropsychological consequences.

Results

Compared to controls, exposed subjects had higher blood Cu, Fe, K, Mn, Pb, Se, and Zn levels (p's<0.026) and poorer performance in processing/psychomotor speed, executive, and visuospatial domains (p's<0.046). Exposed subjects displayed higher MD, AD, and RD in all MTL ROIs (p's<0.040) and lower FA in entorhinal and parahippocampal cortices (p's<0.033), but not morphological differences. Long-term mixed-metal exposure history indirectly predicted lower processing speed performance via lower parahippocampal FA (p=0.023). Higher whole blood Mn and Cu predicted higher entorhinal diffusivity (p's<0.043) and lower Delayed Story Recall performance (p=0.007) without overall metal mixture or interaction effects.

Discussion

Mixed metal exposure predicted MTL structural and neuropsychological features that are similar to Alzheimer's disease at-risk populations. These data warrant follow-up as they may illuminate the path for environmental exposure to Alzheimer's disease-related health outcomes.

White Matter Microstructure Analysis in Subjective Memory Complaints and Cognitive Impairment: Insights from Diffusion Kurtosis Imaging and Free-Water DTI

Background

Dementia is characterized by a cognitive decline in memory and other domains that lead to functional impairments. As people age, subjective memory complaints (SMC) become common, where individuals perceive cognitive decline without objective deficits on assessments. SMC can be an early sign and may precede amnestic mild cognitive impairment (MCI), which frequently advances to Alzheimer's disease (AD).

Objective

This study aims to investigate white matter microstructure in individuals with SMC, in cognitively impaired (CI) cohorts, and in cognitively normal individuals using diffusion kurtosis imaging (DKI) and free water imaging (FWI). The study also explores voxel-based correlations between DKI/FWI metrics and cognitive scores to understand the relationship between brain microstructure and cognitive function.

Methods

Twelve healthy controls (HCs), ten individuals with SMC, and eleven CI individuals (MCI or AD) were enrolled in this study. All participants underwent MRI 3T scan and the BNI Screen (BNIS) for Higher Cerebral Functions.

Results

The mean kurtosis tensor and anisotropy of the kurtosis tensor showed significant differences across the three groups, indicating altered white matter microstructure in CI and SMC individuals. The free water volume fraction (f) also revealed group differences, suggesting changes in extracellular water content. Notably, these metrics effectively discriminated between the CI and HC/SMC groups. Additionally, correlations between imaging metrics and BNIS scores were found for CI and SMC groups.

Conclusions

These imaging metrics hold promise in discriminating between individuals with CI and SMC. The observed differences indicate their potential as sensitive and specific biomarkers for early detection and differentiation of cognitive decline.

The functional role of the pulvinar in discriminating between objective and subjective cognitive impairment in major depressive disorder

INTRODUCTION

Emotionally driven cognitive complaints represent a major diagnostic challenge for clinicians and indicate the importance of objective confirmation of the accuracy of depressive patients' descriptions of their cognitive symptoms.

METHODS

We compared cognitive status and structural and functional brain connectivity changes in the pulvinar and hippocampus between patients with total depression and healthy controls. The depressive group was also classified as "amnestic" or "nonamnestic," based on the members' subjective reports concerning their forgetfulness. We then sought to determine whether these patients would differ in terms of objective neuroimaging and cognitive findings.

RESULTS

The right pulvinar exhibited altered connectivity in individuals with depression with objective cognitive impairment, a finding which was not apparent in depressive patients with subjective cognitive impairment.

DISCUSSION

The pulvinar may play a role in depression-related cognitive impairments. Connectivity network changes may differ between objective and subjective cognitive impairment in depression and may play a role in the increased risk of dementia in patients with depression.

Macroscale neurovascular coupling and functional integration in end-stage renal disease patients with cognitive impairment: A multimodal MRI study

End-stage renal disease (ESRD) is associated with vascular and neuronal dysfunction, causing neurovascular coupling (NVC) dysfunction, but how NVC dysfunction acts on the mechanism of cognitive impairment in ESRD patients from local to remote is still poorly understood. We recruited 48 ESRD patients and 35 demographically matched healthy controls to scan resting-state functional MRI and arterial spin labeling, then investigated the four types of NVC between amplitude of low-frequency fluctuation (ALFF), fractional ALFF, regional homogeneity, degree centrality, and cerebral blood perfusion (CBF), and associated functional networks. Our results indicated that ESRD patients showed NVC dysfunction in global gray matter and multiple brain regions due to the mismatch between CBF and neural activity, and associated disrupted functional connectivity (FC) within sensorimotor network (SMN), visual network (VN), default mode network (DMN), salience network (SN), and disrupted FC between them with limbic network (LN), while increased FC between SMN and DMN. Anemia may affect the NVC of middle occipital gyrus and precuneus, and increased pulse pressure may result in disrupted FC with SMN. The NVC dysfunction of the right precuneus, middle frontal gyrus, and parahippocampal gyrus and the FC between the right angular gyrus and the right anterior cingulate gyrus may reflect cognitive impairment in ESRD patients. Our study confirmed that ESRD patients may exist NVC dysfunction and disrupted functional integration in SMN, VN, DMN, SN and LN, serving as one of the mechanisms of cognitive impairment. Anemia and increased pulse pressure may be related risk factors.

Analysis of Resting-State Functional Magnetic Resonance Imaging in Alzheimer's Disease

Alzheimer's disease (AD) has been characterized by widespread network disconnection among brain regions, widely overlapping with the hallmarks of the disease. Functional connectivity has been studied with an upward trend in the last two decades, predominantly in AD among other neuropsychiatric disorders, and presents a potential biomarker with various features that might provide unique contributions to foster our understanding of neural mechanisms of AD. The resting-state functional MRI (rs-fMRI) is usually used to measure the blood-oxygen-level-dependent signals that reflect the brain's functional connectivity. Nevertheless, the rs-fMRI is still underutilized, which might be due to the fairly complex acquisition and analytic methodology. In this chapter, we presented the common methods that have been applied in rs-fMRI literature, focusing on the studies on individuals in the continuum of AD. The key methodological aspects will be addressed that comprise acquiring, processing, and interpreting rs-fMRI data. More, we discussed the current and potential implications of rs-fMRI in AD.

Communication Regarding the Myocardial Ischemia/Reperfusion and Cognitive Impairment: A Narrative Literature Review

Coronary artery disease is a prevalent ischemic disease that results in insufficient blood supply to the heart muscle due to narrowing or occlusion of the coronary arteries. Various reperfusion strategies, including pharmacological thrombolysis and percutaneous coronary intervention, have been developed to enhance blood flow restoration. However, these interventions can lead to myocardial ischemia/reperfusion injury (MI/RI), which can cause unpredictable complications. Recent research has highlighted a compelling association between MI/RI and cognitive function, revealing pathophysiological mechanisms that may explain altered brain cognition. Manifestations in the brain following MI/RI exhibit pathological features resembling those observed in Alzheimer's disease (AD), implying a potential link between MI/RI and the development of AD. The pro-inflammatory state following MI/RI may induce neuroinflammation via systemic inflammation, while impaired cardiac function can result in cerebral under-perfusion. This review delves into the role of extracellular vesicles in transporting deleterious substances from the heart to the brain during conditions of MI/RI, potentially contributing to impaired cognition. Addressing the cognitive consequence of MI/RI, the review also emphasizes potential neuroprotective interventions and pharmacological treatments within the MI/RI model. In conclusion, the review underscores the significant impact of MI/RI on cognitive function, summarizes potential mechanisms of cardio-cerebral communication in the context of MI/RI, and offers ideas and insights for the prevention and treatment of cognitive dysfunction following MI/RI.

Shared and Specific Changes of Cortico-Striatal Functional Connectivity in Stable Mild Cognitive Impairment and Progressive Mild Cognitive Impairment

Background

Mild cognitive impairment (MCI), the prodromal stage of Alzheimer's disease, has two distinct subtypes: stable MCI (sMCI) and progressive MCI (pMCI). Early identification of the two subtypes has important clinical significance.

Objective

We aimed to compare the cortico-striatal functional connectivity (FC) differences between the two subtypes of MCI and enhance the accuracy of differential diagnosis between sMCI and pMCI.

Methods

We collected resting-state fMRI data from 31 pMCI patients, 41 sMCI patients, and 81 healthy controls. We chose six pairs of seed regions, including the ventral striatum inferior, ventral striatum superior, dorsal-caudal putamen, dorsal-rostral putamen, dorsal caudate, and ventral-rostral putamen and analyzed the differences in cortico-striatal FC among the three groups, additionally, the relationship between the altered FC within the MCI subtypes and cognitive function was examined.

Results

Compared to sMCI, the pMCI patients exhibited decreased FC between the left dorsal-rostral putamen and right middle temporal gyrus, the right dorsal caudate and right inferior temporal gyrus, and the left dorsal-rostral putamen and left superior frontal gyrus. Additionally, the altered FC between the right inferior temporal gyrus and right putamen was significantly associated with episodic memory and executive function.

Conclusions

Our study revealed common and distinct cortico-striatal FC changes in sMCIs and pMCI across different seeds; these changes were associated with cognitive function. These findings can help us understand the underlying pathophysiological mechanisms of MCI and distinguish pMCI and sMCI in the early stage potentially.

FDG-PET markers of heterogeneity and different risk of progression in amnestic MCI

INTRODUCTION

Amnestic mild cognitive impairment (aMCI) is emerging as a heterogeneous condition.

METHODS

We looked at a cohort of N = 207 aMCI subjects, with baseline fluorodeoxyglucose positron emission tomography (FDG-PET), T1 magnetic resonance imaging, cerebrospinal fluid (CSF), apolipoprotein E (APOE), and neuropsychological assessment. An algorithm based on FDG-PET hypometabolism classified each subject into subtypes, then compared biomarker measures and clinical progression.

RESULTS

Three subtypes emerged: hippocampal sparing-cortical hypometabolism, associated with younger age and the highest level of Alzheimer's disease (AD)-CSF pathology; hippocampal/cortical hypometabolism, associated with a high percentage of APOE ε3/ε4 or ε4/ε4 carriers; medial-temporal hypometabolism, characterized by older age, the lowest AD-CSF pathology, the most severe hippocampal atrophy, and a benign course. Within the whole cohort, the severity of temporo-parietal hypometabolism, correlated with AD-CSF pathology and marked the rate of progression of cognitive decline.

DISCUSSION

FDG-PET can distinguish clinically comparable aMCI at single-subject level with different risk of progression to AD dementia or stability. The obtained results can be useful for the optimization of pharmacological trials and automated-classification models.

HIGHLIGHTS

Algorithm based on FDG-PET hypometabolism demonstrates distinct subtypes across aMCI; Three different subtypes show heterogeneous biological profiles and risk of progression; The cortical hypometabolism is associated with AD pathology and cognitive decline; MTL hypometabolism is associated with the lowest conversion rate and CSF-AD pathology.

Progression of cognitive dysfunction in NPC survivors with radiation-induced brain necrosis: A prospective cohort

BACKGROUND AND PURPOSE

The evidence of longitudinal changes in cognition in nasopharyngeal carcinoma (NPC) survivors with radiation-induced brain necrosis (RIBN) after radiotherapy (RT) remained insufficient. We aimed to estimate the clinical progression rate of cognitive decline and identify patients with differential decline rates.

MATERIALS AND METHODS

Based on an ongoing prospective cohort study, NPC patients aged ≥18 years old and diagnosed with RIBN were included in this current analysis if they finished the time frame of 3-year follow-up and had at least twice cognition assessments. The Chinese version of the Montreal Cognitive Assessment (MoCA) was used to assess the cognitive state. Linear mixed-effect models were used to analyze the annual progression rates of MoCA total and seven sub-items scores.

RESULTS

Among 134 patients in this study, the transition probability from normal to mild/moderate cognitive dysfunction were 14.2 % (19/134) and 1.49 % (2/134) respectively during the median follow-up time of 2.35 years. The total MoCA score declined by -0.569 (SE 0.208) points annually (p = 0.008). Patients with ≤6 years of duration from RT to RIBN have higher annual progression rate of total scores [-0.851 (SE 0.321), p = 0.013; p for interaction = 0.041].

CONCLUSION

Our findings of the annual decline rate of cognition in NPC patients with RIBN from a 3-year longitudinal data, particularly for those who developed RIBN rapidly after RT, have important implications for the upcoming clinical trials designed to prevent or decrease cognitive decline in NPC patients with RIBN, regarding the selection of study patients and the calculation of sample size.

ApoER2-Dab1 disruption as the origin of pTau-associated neurodegeneration in sporadic Alzheimer's disease

In sporadic Alzheimer's disease (sAD) specific regions, layers and neurons accumulate hyperphosphorylated Tau (pTau) and degenerate early while others remain unaffected even in advanced disease. ApoER2-Dab1 signaling suppresses Tau phosphorylation as part of a four-arm pathway that regulates lipoprotein internalization and the integrity of actin, microtubules, and synapses; however, the role of this pathway in sAD pathogenesis is not fully understood. We previously showed that multiple ApoER2-Dab1 pathway components including ApoE, Reelin, ApoER2, Dab1, pP85αTyr607, pLIMK1Thr508, pTauSer202/Thr205 and pPSD95Thr19 accumulate together within entorhinal-hippocampal terminal zones in sAD, and proposed a unifying hypothesis wherein disruption of this pathway underlies multiple aspects of sAD pathogenesis. However, it is not yet known whether ApoER2-Dab1 disruption can help explain the origin(s) and early progression of pTau pathology in sAD. In the present study, we applied in situ hybridization and immunohistochemistry (IHC) to characterize ApoER2 expression and accumulation of ApoER2-Dab1 pathway components in five regions known to develop early pTau pathology in 64 rapidly autopsied cases spanning the clinicopathological spectrum of sAD. We found that (1) these selectively vulnerable neuron populations strongly express ApoER2; and (2) multiple ApoER2-Dab1 components representing all four arms of this pathway accumulate in abnormal neurons and neuritic plaques in mild cognitive impairment (MCI) and sAD cases and correlate with histological progression and cognitive deficits. Multiplex-IHC revealed that Dab1, pP85αTyr607, pLIMK1Thr508, pTauSer202/Thr205 and pPSD95Thr19 accumulate together within many of the same ApoER2-expressing neurons and in the immediate vicinity of ApoE/ApoJ-enriched extracellular plaques. Collective findings reveal that pTau is only one of many ApoER2-Dab1 pathway components that accumulate in multiple neuroanatomical sites in the earliest stages of sAD and provide support for the concept that ApoER2-Dab1 disruption drives pTau-associated neurodegeneration in human sAD.

Disentangling in-vivo microstructural changes of white and gray matter in mild cognitive impairment and Alzheimer's disease: a systematic review and meta-analysis

The microstructural characteristics of white and gray matter in mild cognitive impairment (MCI) and the early-stage of Alzheimer's disease (AD) remain unclear. This study aimed to systematically identify the microstructural damages of MCI/AD in studies using neurite orientation dispersion and density imaging (NODDI), and explore their correlations with cognitive performance. Multiple databases were searched for eligible studies. The 10 eligible NODDI studies were finally included. Patients with MCI/AD showed overall significant reductions in neurite density index (NDI) of specific white matter structures in bilateral hemispheres (left hemisphere: -0.40 [-0.53, -0.27], P < 0.001; right: -0.33 [-0.47, -0.19], P < 0.001), involving the bilateral superior longitudinal fasciculus (SLF), uncinate fasciculus (UF), the left posterior thalamic radiation (PTR), and the left cingulum. White matter regions exhibited significant increased orientation dispersion index (ODI) (left: 0.25 [0.02, 0.48], P < 0.05; right: 0.27 [0.07, 0.46], P < 0.05), including the left cingulum, the right UF, and the bilateral parahippocampal cingulum (PHC), and PTR. Additionally, the ODI of gray matter showed significant reduction in bilateral hippocampi (left: -0.97 [-1.42, -0.51], P < 0.001; right: -0.90 [-1.35, -0.45], P < 0.001). The cognitive performance in MCI/AD was significantly associated with NDI (r = 0.50, P < 0.001). Our findings highlight the microstructural changes in MCI/AD were characterized by decreased fiber orientation dispersion in the hippocampus, and decreased neurite density and increased fiber orientation dispersion in specific white matter tracts, including the cingulum, UF, and PTR. Moreover, the decreased NDI may indicate the declined cognitive level of MCI/AD patients.

Oligomeric, phosphorylated, and truncated tau and spliceosome pathology within the entorhinal-hippocampal connectome across stages of Alzheimer's disease

Neurofibrillary tangles (NFTs) contain abnormally phosphorylated tau proteins, which spread within components of the medial temporal lobe (MTL) memory circuit in Alzheimer's disease (AD). Here, we used quantitative immunohistochemistry to determine the density of posttranslational oligomeric (TOC1 and TNT1), phosphorylated (AT8), and late truncated (TauC3) tau epitopes within the MTL subfields including entorhinal cortex (EC) layer II, subiculum, Cornu Ammonis (CA) subfields, and dentate gyrus (DG) in subjects who died with a clinical diagnosis of no cognitive impairment (NCI), mild cognitive impairment (MCI), and AD. We also examined whether alterations of the nuclear alternative splicing protein, SRSF2, are associated with tau pathology. Although a significant increase in TOC1, TNT1, and AT8 neuron density occurred in the EC in MCI and AD, subicular, DG granule cell, and CA1 and CA3 densities were only significantly higher in AD. TauC3 counts were not different between connectome regions and clinical groups. SRSF2 intensity in AT8-positive cells decreased significantly in all regions independent of the clinical groups examined. CA1 and subicular AT8, TauC3, and oligomeric densities correlated across clinical groups. EC AT8 counts correlated with CA subfields and subicular and DG values across clinical groups. Oligomeric and AT8 CA1, EC, and subicular density correlated with Braak stage. Decreased nuclear SRSF2 in the presence of cytoplasmic phosphorylated tau suggests a dual-hit process in NFT formation within the entorhinal hippocampal connectome during the onset of AD. Although oligomeric and phosphorylated tau follow a stereotypical pattern, clinical disease stage determined density of tau deposition and not anatomic location within the entorhinal-hippocampal connectome.

Exploring Successful Cognitive Aging: Insights Regarding Brain Structure, Function, and Demographics

In the realm of cognitive science, the phenomenon of "successful cognitive aging" stands as a hallmark of individuals who exhibit cognitive abilities surpassing those of their age-matched counterparts. However, it is paramount to underscore a significant gap in the current research, which is marked by a paucity of comprehensive inquiries that deploy substantial sample sizes to methodically investigate the cerebral biomarkers and contributory elements underpinning this cognitive success. It is within this context that our present study emerges, harnessing data derived from the UK Biobank. In this study, a highly selective cohort of 1060 individuals aged 65 and above was meticulously curated from a larger pool of 17,072 subjects. The selection process was guided by their striking cognitive resilience, ascertained via rigorous evaluation encompassing both generic and specific cognitive assessments, compared to their peers within the same age stratum. Notably, the cognitive abilities of the chosen participants closely aligned with the cognitive acumen commonly observed in middle-aged individuals. Our study leveraged a comprehensive array of neuroimaging-derived metrics, obtained from three Tesla MRI scans (T1-weighted images, dMRI, and resting-state fMRI). The metrics included image-derived phenotypes (IDPs) that addressed grey matter morphology, the strength of brain network connectivity, and the microstructural attributes of white matter. Statistical analyses were performed employing ANOVA, Mann-Whitney U tests, and chi-square tests to evaluate the distinctive aspects of IDPs pertinent to the domain of successful cognitive aging. Furthermore, these analyses aimed to elucidate lifestyle practices that potentially underpin the maintenance of cognitive acumen throughout the aging process. Our findings unveiled a robust and compelling association between heightened cognitive aptitude and the integrity of white matter structures within the brain. Furthermore, individuals who exhibited successful cognitive aging demonstrated markedly enhanced activity in the cerebral regions responsible for auditory perception, voluntary motor control, memory retention, and emotional regulation. These advantageous cognitive attributes were mirrored in the health-related lifestyle choices of the surveyed cohort, characterized by elevated educational attainment, a lower incidence of smoking, and a penchant for moderate alcohol consumption. Moreover, they displayed superior grip strength and enhanced walking speeds. Collectively, these findings furnish valuable insights into the multifaceted determinants of successful cognitive aging, encompassing both neurobiological constituents and lifestyle practices. Such comprehensive comprehension significantly contributes to the broader discourse on aging, thereby establishing a solid foundation for the formulation of targeted interventions aimed at fostering cognitive well-being among aging populations.

Alterations via inter-regional connective relationships in Alzheimer's disease

Disruptions in the inter-regional connective correlation within the brain are believed to contribute to memory impairment. To detect these corresponding correlation networks in Alzheimer's disease (AD), we conducted three types of inter-regional correlation analysis, including structural covariance, functional connectivity and group-level independent component analysis (group-ICA). The analyzed data were obtained from the Alzheimer's Disease Neuroimaging Initiative, comprising 52 cognitively normal (CN) participants without subjective memory concerns, 52 individuals with late mild cognitive impairment (LMCI) and 52 patients with AD. We firstly performed vertex-wise cortical thickness analysis to identify brain regions with cortical thinning in AD and LMCI patients using structural MRI data. These regions served as seeds to construct both structural covariance networks and functional connectivity networks for each subject. Additionally, group-ICA was performed on the functional data to identify intrinsic brain networks at the cohort level. Through a comparison of the structural covariance and functional connectivity networks with ICA networks, we identified several inter-regional correlation networks that consistently exhibited abnormal connectivity patterns among AD and LMCI patients. Our findings suggest that reduced inter-regional connectivity is predominantly observed within a subnetwork of the default mode network, which includes the posterior cingulate and precuneus regions, in both AD and LMCI patients. This disruption of connectivity between key nodes within the default mode network provides evidence supporting the hypothesis that impairments in brain networks may contribute to memory deficits in AD and LMCI.

Brain Structure-Function Fusing Representation Learning Using Adversarial Decomposed-VAE for Analyzing MCI

Integrating the brain structural and functional connectivity features is of great significance in both exploring brain science and analyzing cognitive impairment clinically. However, it remains a challenge to effectively fuse structural and functional features in exploring the complex brain network. In this paper, a novel brain structure-function fusing-representation learning (BSFL) model is proposed to effectively learn fused representation from diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (fMRI) for mild cognitive impairment (MCI) analysis. Specifically, the decomposition-fusion framework is developed to first decompose the feature space into the union of the uniform and unique spaces for each modality, and then adaptively fuse the decomposed features to learn MCI-related representation. Moreover, a knowledge-aware transformer module is designed to automatically capture local and global connectivity features throughout the brain. Also, a uniform-unique contrastive loss is further devised to make the decomposition more effective and enhance the complementarity of structural and functional features. The extensive experiments demonstrate that the proposed model achieves better performance than other competitive methods in predicting and analyzing MCI. More importantly, the proposed model could be a potential tool for reconstructing unified brain networks and predicting abnormal connections during the degenerative processes in MCI.

Functional gradients reveal altered functional segregation in patients with amnestic mild cognitive impairment and Alzheimer's disease

Alzheimer's disease and amnestic mild cognitive impairment are associated with disrupted functional organization in brain networks, involved with alteration of functional segregation. Connectome gradients are a new tool representing brain functional topological organization to smoothly capture the human macroscale hierarchy. Here, we examined altered topological organization in amnestic mild cognitive impairment and Alzheimer's disease by connectome gradient mapping. We further quantified functional segregation by gradient dispersion. Then, we systematically compared the alterations observed in amnestic mild cognitive impairment and Alzheimer's disease patients with those in normal controls in a two-dimensional functional gradient space from both the whole-brain level and module level. Compared with normal controls, the first gradient, which described the neocortical hierarchy from unimodal to transmodal regions, showed a more distributed and significant suppression in Alzheimer's disease than amnestic mild cognitive impairment patients. Furthermore, gradient dispersion showed significant decreases in Alzheimer's disease at both the global level and module level, whereas this alteration was limited only to limbic areas in amnestic mild cognitive impairment. Notably, we demonstrated that suppressed gradient dispersion in amnestic mild cognitive impairment and Alzheimer's disease was associated with cognitive scores. These findings provide new evidence for altered brain hierarchy in amnestic mild cognitive impairment and Alzheimer's disease, which strengthens our understanding of the progressive mechanism of cognitive decline.

Brain amyloid-β deposition associated functional connectivity changes of ultra-large structural scale in mild cognitive impairment

In preclinical Alzheimer's disease, neuro-functional changes due to amyloid-β (Aβ) deposition are not synchronized in different brain lobes and subcortical nuclei. This study aimed to explore the correlation between brain Aβ burden, connectivity changes in an ultra-large structural scale, and cognitive function in mild cognitive impairment. Participants with mild cognitive impairment were recruited and underwent florbetapir (F18-AV45) PET, resting-state functional MRI, and multidomain neuropsychological tests. AV-45 standardized uptake value ratio (SUVR) and functional connectivity of all participants were calculated. Of the total 144 participants, 72 were put in the low Aβ burden group and 72 in the high Aβ burden group. In the low Aβ burden group, all connectivities between lobes and nuclei had no correlation with SUVR. In the high Aβ burden group, SUVR showed negative correlations with the Subcortical-Occipital connectivity (r=-0.36, P = 0.02) and Subcortical-Parietal connectivity (r=-0.26, P = 0.026). Meanwhile, in the high Aβ burden group, SUVR showed positive correlations with the Temporal-Prefrontal connectivity (r = 0.27, P = 0.023), Temporal-Occipital connectivity (r = 0.24, P = 0.038), and Temporal-Parietal connectivity (r = 0.32, P = 0.006). Subcortical to Occipital and Parietal connectivities had positive correlations with general cognition, language, memory, and executive function. Temporal to Prefrontal, Occipital, and Parietal connectivities had negative correlations with memory function, executive function, and visuospatial function, and a positive correlation with language function. In conclusion, Individuals with mild cognitive impairment with high Aβ burden have Aβ-related bidirectional functional connectivity changes between lobes and subcortical nuclei that are associated with cognitive decline in multiple domains. These connectivity changes reflect neurological impairment and failed compensation.

Brain Status Transferring Generative Adversarial Network for Decoding Individualized Atrophy in Alzheimer's Disease

Deep learning has been widely investigated in brain image computational analysis for diagnosing brain diseases such as Alzheimer's disease (AD). Most of the existing methods built end-to-end models to learn discriminative features by group-wise analysis. However, these methods cannot detect pathological changes in each subject, which is essential for the individualized interpretation of disease variances and precision medicine. In this article, we propose a brain status transferring generative adversarial network (BrainStatTrans-GAN) to generate corresponding healthy images of patients, which are further used to decode individualized brain atrophy. The BrainStatTrans-GAN consists of generator, discriminator, and status discriminator. First, a normative GAN is built to generate healthy brain images from normal controls. However, it cannot generate healthy images from diseased ones due to the lack of paired healthy and diseased images. To address this problem, a status discriminator with adversarial learning is designed in the training process to produce healthy brain images for patients. Then, the residual between the generated and input images can be computed to quantify pathological brain changes. Finally, a residual-based multi-level fusion network (RMFN) is built for more accurate disease diagnosis. Compared to the existing methods, our method can model individualized brain atrophy for facilitating disease diagnosis and interpretation. Experimental results on T1-weighted magnetic resonance imaging (MRI) data of 1,739 subjects from three datasets demonstrate the effectiveness of our method.

Spatial cognition is associated with levels of phosphorylated-tau and β-amyloid in clinically normal older adults

Spatial cognition is associated with Alzheimer's disease (AD) biomarkers in the symptomatic stages of the disease. We investigated whether cerebrospinal fluid (CSF) biomarkers (phosphorylated-tau [p-tau] and β-amyloid) are associated with poorer spatial cognition in clinically normal older adults. Participants were 1875 clinically normal adults (age 67.8 [8.5] years) from the European Prevention of Alzheimer's Dementia Consortium. Mixed effect models assessed the cross-sectional association between p-tau181, β-amyloid1-42 (Aβ1-42) and p-tau181/Aβ1-42 ratio and spatial cognition measured using semi-automated Supermarket Task and the 4 Mountains Task. Levels of p-tau181, Aβ1-42, and p-tau181/Aβ1-42 ratio were significantly associated with spatial cognition scores on both tasks. The p-tau181/Aβ1-42 ratio showed the largest effect sizes (β = -0.04/0.05, p < 0.001). Lower entorhinal cortical volume was associated with poorer outcomes on both tasks (β = 0.06, p < 0.002) and accounted for 18%-22% of the direct association between p-tau181 and spatial cognition scores. In conclusion, degeneration of the entorhinal cortex mediates a significant proportion of the association between p-tau181 and spatial assessments in cognitively normal adults. Future studies should focus on increasing the sensitivity of digital spatial assessments.

Deciphering the Mysterious Relationship between the Cross-Pathogenetic Mechanisms of Neurodegenerative and Oncological Diseases

The relationship between oncological pathologies and neurodegenerative disorders is extremely complex and is a topic of concern among a growing number of researchers around the world. In recent years, convincing scientific evidence has accumulated that indicates the contribution of a number of etiological factors and pathophysiological processes to the pathogenesis of these two fundamentally different diseases, thus demonstrating an intriguing relationship between oncology and neurodegeneration. In this review, we establish the general links between three intersecting aspects of oncological pathologies and neurodegenerative disorders, i.e., oxidative stress, epigenetic dysregulation, and metabolic dysfunction, examining each process in detail to establish an unusual epidemiological relationship. We also focus on reviewing the current trends in the research and the clinical application of the most promising chemical structures and therapeutic platforms that have a modulating effect on the above processes. Thus, our comprehensive analysis of the set of molecular determinants that have obvious cross-functional pathways in the pathogenesis of oncological and neurodegenerative diseases can help in the creation of advanced diagnostic tools and in the development of innovative pharmacological strategies.

Effect of Alzheimer's Pathology on Task-Related Brain Network Reconfiguration in Aging

Large-scale brain networks undergo widespread changes with older age and in neurodegenerative diseases such as Alzheimer's disease (AD). Research in young adults (YA) suggest that the underlying functional architecture of brain networks remains relatively consistent between rest and task states. However, it remains unclear whether the same is true in aging and to what extent any changes may be related to accumulation of AD pathology such as β-amyloid (Aβ) and tau. Here, we examined age-related differences in functional connectivity (FC) between rest and an object-scene mnemonic discrimination task using fMRI in young and older adults (OA; both females and males). We used an a priori episodic memory network (EMN) parcellation scheme associated with object and scene processing, that included anterior-temporal regions and posterior-medial regions. We also used positron emission topography to measure Aβ and tau in older adults. The correlation between rest and task FC (i.e., FC similarity) was reduced in older compared with younger adults. Older adults with lower FC similarity in EMN had higher levels of tau in the same EMN regions and performed worse during object, but not scene, trials during the fMRI task. These findings link AD pathology, particularly tau, to a less stable functional architecture in memory networks. They also suggest that smaller changes in FC organization between rest and task states may facilitate better performance in older age. Interpretations are limited by methodological factors related to different acquisition directions and durations between rest and task scans.SIGNIFICANCE STATEMENT The brain's large-scale network organization is relatively consistent between rest and task states in young adults (YA). We found that memory networks in older adults (OA) were less correlated between rest and (memory) task states compared with young adults. Older adults with less correlated brain networks also had higher levels of Alzheimer's disease (AD) pathology in the same regions, suggesting that a less stable network architecture may reflect the early evolution of AD. Older adults with less correlated brain networks also performed worse during the memory task suggesting that more similar network organization between rest and task states may facilitate better performance in older age.

Aging and Alzheimer's disease have dissociable effects on local and regional medial temporal lobe connectivity

Functional disruption of the medial temporal lobe-dependent networks is thought to underlie episodic memory deficits in aging and Alzheimer's disease. Previous studies revealed that the anterior medial temporal lobe is more vulnerable to pathological and neurodegenerative processes in Alzheimer's disease. In contrast, cognitive and structural imaging literature indicates posterior, as opposed to anterior, medial temporal lobe vulnerability in normal aging. However, the extent to which Alzheimer's and aging-related pathological processes relate to functional disruption of the medial temporal lobe-dependent brain networks is poorly understood. To address this knowledge gap, we examined functional connectivity alterations in the medial temporal lobe and its immediate functional neighbourhood-the Anterior-Temporal and Posterior-Medial brain networks-in normal agers, individuals with preclinical Alzheimer's disease and patients with Mild Cognitive Impairment or mild dementia due to Alzheimer's disease. In the Anterior-Temporal network and in the perirhinal cortex, in particular, we observed an inverted 'U-shaped' relationship between functional connectivity and Alzheimer's stage. According to our results, the preclinical phase of Alzheimer's disease is characterized by increased functional connectivity between the perirhinal cortex and other regions of the medial temporal lobe, as well as between the anterior medial temporal lobe and its one-hop neighbours in the Anterior-Temporal system. This effect is no longer present in symptomatic Alzheimer's disease. Instead, patients with symptomatic Alzheimer's disease displayed reduced hippocampal connectivity within the medial temporal lobe as well as hypoconnectivity within the Posterior-Medial system. For normal aging, our results led to three main conclusions: (i) intra-network connectivity of both the Anterior-Temporal and Posterior-Medial networks declines with age; (ii) the anterior and posterior segments of the medial temporal lobe become increasingly decoupled from each other with advancing age; and (iii) the posterior subregions of the medial temporal lobe, especially the parahippocampal cortex, are more vulnerable to age-associated loss of function than their anterior counterparts. Together, the current results highlight evolving medial temporal lobe dysfunction in Alzheimer's disease and indicate different neurobiological mechanisms of the medial temporal lobe network disruption in aging versus Alzheimer's disease.

Disease progression model anchored around clinical diagnosis in longitudinal cohorts: example of Alzheimer's disease and related dementia

BACKGROUND

Alzheimer's disease and related dementia (ADRD) are characterized by multiple and progressive anatomo-clinical changes including accumulation of abnormal proteins in the brain, brain atrophy and severe cognitive impairment. Understanding the sequence and timing of these changes is of primary importance to gain insight into the disease natural history and ultimately allow earlier diagnosis. Yet, modeling changes over disease course from cohort data is challenging as the usual timescales (time since inclusion, chronological age) are inappropriate and time-to-clinical diagnosis is available on small subsamples of participants with short follow-up durations prior to diagnosis. One solution to circumvent this challenge is to define the disease time as a latent variable.

METHODS

We developed a multivariate mixed model approach that realigns individual trajectories into the latent disease time to describe disease progression. In contrast with the existing literature, our methodology exploits the clinical diagnosis information as a partially observed and approximate reference to guide the estimation of the latent disease time. The model estimation was carried out in the Bayesian Framework using Stan. We applied the methodology to the MEMENTO study, a French multicentric clinic-based cohort of 2186 participants with 5-year intensive follow-up. Repeated measures of 12 ADRD markers stemmed from cerebrospinal fluid (CSF), brain imaging and cognitive tests were analyzed.

RESULTS

The estimated latent disease time spanned over twenty years before the clinical diagnosis. Considering the profile of a woman aged 70 with a high level of education and APOE4 carrier (the main genetic risk factor for ADRD), CSF markers of tau proteins accumulation preceded markers of brain atrophy by 5 years and cognitive decline by 10 years. However we observed that individual characteristics could substantially modify the sequence and timing of these changes, in particular for CSF level of A[Formula: see text].

CONCLUSION

By leveraging the available clinical diagnosis timing information, our disease progression model does not only realign trajectories into the most homogeneous way. It accounts for the inherent residual inter-individual variability in dementia progression to describe the long-term anatomo-clinical degradations according to the years preceding clinical diagnosis, and to provide clinically meaningful information on the sequence of events.

TRIAL REGISTRATION

clinicaltrials.gov, NCT01926249. Registered on 16 August 2013.

Neural network process simulations support a distributed memory system and aid design of a novel computer adaptive digital memory test for preclinical and prodromal Alzheimer's disease

OBJECTIVE

Growing evidence supports the importance of learning as a central deficit in preclinical/prodromal Alzheimer's disease. The aims of this study were to conduct a series of neural network simulations to develop a functional understanding of a distributed, nonmodular memory system that can learn efficiently without interference. This understanding is applied to the development of a novel digital memory test.

METHOD

Simulations using traditional feed forward neural network architectures to learn simple logic problems are presented. The simulations demonstrate three limitations: (a) inefficiency, (b) an inability to learn problems consistently, and (c) catastrophic interference when given multiple problems. A new mirrored cascaded architecture is introduced to address these limitations, with support provided by a series of simulations.

RESULTS

The mirrored cascaded architecture demonstrates efficient and consistent learning relative to feed forward networks but also suffers from catastrophic interference. Addition of context values to add the capability of distinguishing features as part of learning eliminates the problem of interference in the mirrored cascaded, but not the feed forward, architectures.

CONCLUSIONS

A mirrored cascaded architecture addresses the limitations of traditional feed forward neural networks, provides support for a distributed memory system, and emphasizes the importance of context to avoid interference. These process models contributed to the design of a digital computer-adaptive word list learning test that places maximum stress on the capability to distinguish specific episodes of learning. Process simulations provide a useful method of testing models of brain function and contribute to new approaches to neuropsychological assessment. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Infection with COVID-19 is no longer a public emergency: But what about degenerative dementia?

Although no longer considered a public health threat, post-COVID cognitive syndrome continues to impact on a considerable proportion of individuals who were infected with COVID-19. Recent studies have also suggested that COVID may be represent a critical risk factor for the development of Alzheimer's disease (AD). We compared 17 COVID patients with 20 controls and evaluated the effects of COVID-19 on general cognitive performance, hippocampal volume, and connections using structural and seed-based connectivity analysis. We showed that COVID patients exhibited considerably worse cognitive functioning and increased hippocampal connectivity supported by the strong correlation between hippocampal connectivity and cognitive scores. Our findings of higher hippocampal connectivity with no observable hippocampal morphological changes even in mild COVID cases may be represent evidence of a prestructural compensatory mechanism for stimulating additional neuronal resources to combat cognitive dysfunction as recently shown for the prodromal stages of degenerative cognitive disorders. Our findings may be also important in light of recent data showing that other viral infections as well as COVID may constitute a critical risk factor for the development of AD. To our knowledge, this is the first study that investigated network differences in COVID patients, with a particular focus on compensatory hippocampal connectivity.

Functional and structural connectivity in the Papez circuit in different stages of Alzheimer's disease

OBJECTIVE

Alzheimer's disease (AD) is a progressive neurodegenerative continuum with memory impairment. We aimed to examine the detailed functional (FC) and structural connectivity (SC) pattern of the Papez circuit, known as the memory circuit, along the AD.

METHODS

MRI data of 15 patients diagnosed with AD dementia (ADD), 15 patients with the amnestic mild cognitive impairment (MCI), and 15 patients with subjective cognitive impairment were analyzed. The FC analyses were performed between main nodes of the Papez circuit, and the SC was quantified as fractional anisotropy (FA) of the main white matter pathways of the Papez circuit.

RESULTS

The FC between the retrosplenial (RSC) and parahippocampal cortices (PHC) was the earliest affected FC, while a manifest SC change in the ventral cingulum and fornix was observed in the later ADD stage. The RSC-PHC FC and the ventral cingulum FA efficiently predicted the memory performance of the non-demented participants.

CONCLUSIONS

Our findings revealed the importance of the Papez circuit as target regions along the AD.

SIGNIFICANCE

The ventral cingulum connecting the RSC and PHC, a critical overlap area between the Papez circuit and the default mode network, seems to be a target region associated with the earliest objective memory findings in AD.

Evaluation of volumetric asymmetry of the dorsolateral prefrontal cortex and medial temporal lobe in Alzheimer's disease using the atlas-based method

Brain areas affected during neurodegenerative disease progression are considered anatomically connected to the first affected areas. The dorsolateral prefrontal cortex (DLPFC) has connections with the medial temporal lobe (MTL), which includes regions that become atrophic in Alzheimer's disease. In this study, we aimed to investigate the degree of volumetric asymmetry of DLPFC and MTL structures. This is a cross-sectional volumetric study involving 25 Alzheimer's disease patients and 25 healthy adults who underwent MRI with a 3D turbo spin echo sequence at 1.5 Tesla. The atlas-based method incorporated MRIStudio software to automatically measure the volume of brain structures. We compared the asymmetry index and volumetric changes across study groups and correlated them with Mini-Mental State Examination scores. We observed significant volumetric rightward lateralization in the DLPFC and superior frontal gyrus in Alzheimer's disease patients compared to the healthy controls. There was a significant volume loss in the MTL structures of Alzheimer's disease patients. Atrophy of MTL structures was positively correlated with right DLPFC volume changes in Alzheimer's disease patients. Volumetric asymmetry of the DLPFC may be a characteristic for determining disease progression in Alzheimer's disease patients. Future studies are recommended to evaluate whether these volumetric asymmetrical changes are specific to Alzheimer's disease and whether asymmetry measurements can serve as diagnostic markers.

Xenon inhalation attenuates neuronal injury and prevents epilepsy in febrile seizure Sprague-Dawley pups

Background

Febrile seizures (FS) usually occur in childhood and may cause irreversible neuronal damage, cognitive functional defects, and an increase in the risk of epilepsy later in life. Anti-epileptic drugs (AEDs), currently used to treat FS in children, can relieve seizures. However, their effects in preventing the risk of developing epilepsy in later life are unsatisfactory. Moreover, AEDs may damage child brain development. Here, we evaluated the efficiency of xenon in treating prolonged FS (PFS) and preventing epilepsy in Sprague-Dawley pups.

Methods

Prolonged FS was induced by hyperthermic treatment. After 90 min of PFS, the pups in the xenon treatment group were immediately treated with 70% xenon/21% oxygen/9% nitrogen for 60 min. The levels of glutamate, mitochondrial oxidative stress, mitophagy, and neuronal injury, seizures, learning, and memory functions were measured at specific time points.

Results

Neonatal period PFS led to spontaneous seizure, learning and memory dysfunction, accompanied by increased levels of glutamate, mitochondrial oxidative stress, mitophagy, and neuronal injury. Xenon treatment alleviated the changes caused by PFS and reduced the risk of PFS developing into epilepsy later.

Conclusion

Our results suggest that xenon inhalation could be a potential therapeutic strategy to attenuate neuronal injury and prevent epilepsy in patients with FS.

Managing Cancer and Living Meaningfully (CALM) alleviates chemotherapy related cognitive impairment (CRCI) in breast cancer survivors: A pilot study based on resting-state fMRI

BACKGROUND

Chemotherapy related cognitive impairment (CRCI) is a type of memory and cognitive impairment induced by chemotherapy and has become a growing clinical problem. Breast cancer survivors (BCs) refer to patients from the moment of breast cancer diagnosis to the end of their lives. Managing Cancer and Living Meaningfully (CALM) is a convenient and easy-to-apply psychological intervention that has been proven to improve quality of life and alleviate CRCI in BCs. However, the underlying neurobiological mechanisms remain unclear. Resting-state functional magnetic resonance imaging (rs-fMRI) has become an effective method for understanding the neurobiological mechanisms of brain networks in CRCI. The fractional amplitude of low-frequency fluctuations (fALFF) and ALFF have often been used in analyzing the power and intensity of spontaneous regional resting state neural activity.

METHODS

The recruited BCs were randomly divided into the CALM group and the care as usual (CAU) group. All BCs were evaluated by the Functional Assessment of Cancer Therapy Cognitive Function (FACT-Cog) before and after CALM or CAU. The rs-fMRI imaging was acquired before and after CALM intervention in CALM group BCs. The BCs were defined as before CALM intervention (BCI) group and after CALM intervention (ACI) group.

RESULTS

There were 32 BCs in CALM group and 35 BCs in CAU group completed the overall study. There were significant differences between the BCI group and the ACI group in the FACT-Cog-PCI scores. Compared with the BCI group, the ACI group showed lower fALFF signal in the left medial frontal gyrus and right sub-gyral and higher fALFF in the left occipital_sup and middle occipital gyrus. There was a significant positive correlation between hippocampal ALFF value and FACT-Cog-PCI scores.

CONCLUSIONS

CALM intervention may have an effective function in alleviating CRCI of BCs. The altered local synchronization and regional brain activity may be correlated with the improved cognitive function of BCs who received the CALM intervention. The ALFF value of hippocampus seems to be an important factor in reflect cognitive function in BCs with CRCI and the neural network mechanism of CALM intervention deserves further exploration to promote its application.

Deep brain stimulation of fornix in Alzheimer's disease: From basic research to clinical practice

Alzheimer's disease (AD) is one of the most common progressive neurodegenerative diseases associated with the degradation of memory and cognitive ability. Current pharmacotherapies show little therapeutic effect in AD treatment and still cannot prevent the pathological progression of AD. Deep brain stimulation (DBS) has shown to enhance memory in morbid obese, epilepsy and traumatic brain injury patients, and cognition in Parkinson's disease (PD) patients deteriorates during DBS off. Some relevant animal studies and clinical trials have been carried out to discuss the DBS treatment for AD. Reviewing the fornix trials, no unified conclusion has been reached about the clinical benefits of DBS in AD, and the dementia ratings scale has not been effectively improved in the long term. However, some patients have presented promising results, such as improved glucose metabolism, increased connectivity in cognition-related brain regions and even elevated cognitive function rating scale scores. The fornix plays an important regulatory role in memory, attention, and emotion through its complex fibre projection to cognition-related structures, making it a promising target for DBS for AD treatment. Moreover, the current stereotaxic technique and various evaluation methods have provided references for the operator to select accurate stimulation points. Related adverse events and relatively higher costs in DBS have been emphasized. In this article, we summarize and update the research progression on fornix DBS in AD and seek to provide a reliable reference for subsequent experimental studies on DBS treatment of AD.

ApoER2-Dab1 disruption as the origin of pTau-related neurodegeneration in sporadic Alzheimer's disease

BACKGROUND

Sporadic Alzheimer's disease (sAD) is not a global brain disease. Specific regions, layers and neurons degenerate early while others remain untouched even in advanced disease. The prevailing model used to explain this selective neurodegeneration-prion-like Tau spread-has key limitations and is not easily integrated with other defining sAD features. Instead, we propose that in humans Tau hyperphosphorylation occurs locally via disruption in ApoER2-Dab1 signaling and thus the presence of ApoER2 in neuronal membranes confers vulnerability to degeneration. Further, we propose that disruption of the Reelin/ApoE/ApoJ-ApoER2-Dab1-P85α-LIMK1-Tau-PSD95 (RAAAD-P-LTP) pathway induces deficits in memory and cognition by impeding neuronal lipoprotein internalization and destabilizing actin, microtubules, and synapses. This new model is based in part on our recent finding that ApoER2-Dab1 disruption is evident in entorhinal-hippocampal terminal zones in sAD. Here, we hypothesized that neurons that degenerate in the earliest stages of sAD (1) strongly express ApoER2 and (2) show evidence of ApoER2-Dab1 disruption through co-accumulation of multiple RAAAD-P-LTP components.

METHODS

We applied in situ hybridization and immunohistochemistry to characterize ApoER2 expression and accumulation of RAAAD-P-LTP components in five regions that are prone to early pTau pathology in 64 rapidly autopsied cases spanning the clinicopathological spectrum of sAD.

RESULTS

We found that: (1) selectively vulnerable neuron populations strongly express ApoER2; (2) numerous RAAAD-P-LTP pathway components accumulate in neuritic plaques and abnormal neurons; and (3) RAAAD-P-LTP components were higher in MCI and sAD cases and correlated with histological progression and cognitive deficits. Multiplex-IHC revealed that Dab1, pP85αTyr607, pLIMK1Thr508, pTau and pPSD95Thr19 accumulated together within dystrophic dendrites and soma of ApoER2-expressing neurons in the vicinity of ApoE/ApoJ-enriched extracellular plaques. These observations provide evidence for molecular derangements that can be traced back to ApoER2-Dab1 disruption, in each of the sampled regions, layers, and neuron populations that are prone to early pTau pathology.

CONCLUSION

Findings support the RAAAD-P-LTP hypothesis, a unifying model that implicates dendritic ApoER2-Dab1 disruption as the major driver of both pTau accumulation and neurodegeneration in sAD. This model provides a new conceptual framework to explain why specific neurons degenerate and identifies RAAAD-P-LTP pathway components as potential mechanism-based biomarkers and therapeutic targets for sAD.

A PAM of the α1A-Adrenergic receptor rescues biomarker, long-term potentiation, and cognitive deficits in Alzheimer's disease mouse models without effects on blood pressure

α1-Adrenergic Receptors (ARs) regulate the sympathetic nervous system by the binding of norepinephrine (NE) and epinephrine (Epi) through different subtypes (α1A, α1B, α1D). α1A-AR activation is hypothesized to be memory forming and cognitive enhancing but drug development has been stagnant due to unwanted side effects on blood pressure. We recently reported the pharmacological characterization of the first positive allosteric modulator (PAM) for the α1A-AR with predictive pro-cognitive and memory properties. In this report, we now demonstrate the in vivo characteristics of Compound 3 (Cmpd-3) in two genetically-different Alzheimer's Disease (AD) mouse models. Drug metabolism and pharmacokinetic studies indicate sufficient brain penetrance and rapid uptake into the brain with low to moderate clearance, and a favorable inhibition profile against the major cytochrome p450 enzymes. Oral administration of Cmpd-3 (3-9 mg/kg QD) can fully rescue long-term potentiation defects and AD biomarker profile (amyloid β-40, 42) within 3 months of dosing to levels that were non-significant from WT controls and which outperformed donepezil (1 mg/kg QD). There were also significant effects on paired pulse facilitation and cognitive behavior. Long-term and high-dose in vivo studies with Cmpd-3 revealed no effects on blood pressure. Our results suggest that Cmpd-3 can maintain lasting therapeutic levels and efficacy with disease modifying effects with a once per day dosing regimen in AD mouse models with no observed side effects.

Altered resting-state functional connectivity patterns in late middle-aged and older adults with obstructive sleep apnea

Introduction

Obstructive sleep apnea (OSA) is increasingly recognized as a risk factor for cognitive decline, and has been associated with structural brain alterations in regions relevant to memory processes and Alzheimer's disease. However, it is unclear whether OSA is associated with disrupted functional connectivity (FC) patterns between these regions in late middle-aged and older populations. Thus, we characterized the associations between OSA severity and resting-state FC between the default mode network (DMN) and medial temporal lobe (MTL) regions. Second, we explored whether significant FC changes differed depending on cognitive status and were associated with cognitive performance.

Methods

Ninety-four participants [24 women, 65.7 ± 6.9 years old, 41% with Mild Cognitive Impairment (MCI)] underwent a polysomnography, a comprehensive neuropsychological assessment and a resting-state functional magnetic resonance imaging (MRI). General linear models were conducted between OSA severity markers (i.e., the apnea-hypopnea, oxygen desaturation and microarousal indices) and FC values between DMN and MTL regions using CONN toolbox. Partial correlations were then performed between OSA-related FC patterns and (i) OSA severity markers in subgroups stratified by cognitive status (i.e., cognitively unimpaired versus MCI) and (ii) cognitive scores in the whole sample. All analyzes were controlled for age, sex and education, and considered significant at a p < 0.05 threshold corrected for false discovery rate.

Results

In the whole sample, a higher apnea-hypopnea index was significantly associated with lower FC between (i) the medial prefrontal cortex and bilateral hippocampi, and (ii) the left hippocampus and both the posterior cingulate cortex and precuneus. FC patterns were not associated with the oxygen desaturation index, or micro-arousal index. When stratifying the sample according to cognitive status, all associations remained significant in cognitively unimpaired individuals but not in the MCI group. No significant associations were observed between cognition and OSA severity or OSA-related FC patterns.

Discussion

OSA severity was associated with patterns of lower FC in regions relevant to memory processes and Alzheimer's disease. Since no associations were found with cognitive performance, these FC changes could precede detectable cognitive deficits. Whether these FC patterns predict future cognitive decline over the long-term needs to be investigated.

Impaired large-scale cortico-hippocampal network connectivity, including the anterior temporal and posterior medial systems, and its associations with cognition in patients with first-episode schizophrenia

Background and objective

The cortico-hippocampal network is an emerging neural framework with striking evidence that it supports cognition in humans, especially memory; this network includes the anterior temporal (AT) system, the posterior medial (PM) system, the anterior hippocampus (aHIPPO), and the posterior hippocampus (pHIPPO). This study aimed to detect aberrant patterns of functional connectivity within and between large-scale cortico-hippocampal networks in first-episode schizophrenia patients compared with a healthy control group via resting-state functional magnetic resonance imaging (rs-fMRI) and to explore the correlations of these aberrant patterns with cognition.

Methods

A total of 86 first-episode, drug-naïve schizophrenia patients and 102 healthy controls (HC) were recruited to undergo rs-fMRI examinations and clinical evaluations. We conducted large-scale edge-based network analysis to characterize the functional architecture of the cortico-hippocampus network and investigate between-group differences in within/between-network functional connectivity. Additionally, we explored the associations of functional connectivity (FC) abnormalities with clinical characteristics, including scores on the Positive and Negative Syndrome Scale (PANSS) and cognitive scores.

Results

Compared with the HC group, schizophrenia patients exhibited widespread alterations to within-network FC of the cortico-hippocampal network, with decreases in FC involving the precuneus (PREC), amygdala (AMYG), parahippocampal cortex (PHC), orbitofrontal cortex (OFC), perirhinal cortex (PRC), retrosplenial cortex (RSC), posterior cingulate cortex (PCC), angular gyrus (ANG), aHIPPO, and pHIPPO. Schizophrenia patients also showed abnormalities in large-scale between-network FC of the cortico-hippocampal network, in the form of significantly decreased FC between the AT and the PM, the AT and the aHIPPO, the PM and the aHIPPO, and the aHIPPO and the pHIPPO. A number of these signatures of aberrant FC were correlated with PANSS score (positive, negative, and total score) and with scores on cognitive test battery items, including attention/vigilance (AV), working memory (WM), verbal learning and memory (Verb_Lrng), visual learning and memory (Vis_Lrng), reasoning and problem-solving (RPS), and social cognition (SC).

Conclusion

Schizophrenia patients show distinct patterns of functional integration and separation both within and between large-scale cortico-hippocampal networks, reflecting a network imbalance of the hippocampal long axis with the AT and PM systems, which regulate cognitive domains (mainly Vis_Lrng, Verb_Lrng, WM, and RPS), and particularly involving alterations to FC of the AT system and the aHIPPO. These findings provide new insights into the neurofunctional markers of schizophrenia.