Structural and Functional Hippocampal Changes in Subjective Cognitive Decline From the Community

Accurate identification of individuals with subjective cognitive decline using 3D regional fractal dimensions on structural magnetic resonance imaging

BACKGROUND AND OBJECTIVE

Accurate identification of individuals with subjective cognitive decline (SCD) is crucial for early intervention and prevention of neurodegenerative diseases. Fractal dimensionality (FD) has emerged as a robust and replicable measure, surpassing traditional geometric metrics, in characterizing the intricate fractal geometrical properties of brain structure. Nevertheless, the effectiveness of FD in identifying individuals with SCD remains largely unclear. A 3D regional FD method can be suggested to characterize and quantify the spatial complexity of the precise gray matter, providing insights into cognitive aging and aiding in the automated identification of individuals with SCD.

METHODS

This study introduces a novel integer ratio based 3D box-counting fractal analysis (IRBCFA) to quantify regional fractal dimensions (FDs) in structural magnetic resonance imaging (MRI) data. The innovative method overcomes limitations of conventional box-counting techniques by accommodating arbitrary box sizes, thereby enhancing the precision of FD estimation in small, yet neurologically significant, brain regions.

RESULTS

The application of IRBCFA to two publicly available datasets, OASIS-3 and ADNI, consisting of 520 and 180 subjects, respectively. The method identified discriminative regions of interest (ROIs) predominantly within the limbic system, fronto-parietal region, occipito-temporal region, and basal ganglia-thalamus region. These ROIs exhibited significant correlations with cognitive functions, including executive functioning, memory, social cognition, and sensory perception, suggesting their potential as neuroimaging markers for SCD. The identification model trained on these ROIs demonstrated exceptional performance achieving over 93 % accuracy on the discovery dataset and exceeding 87 % on the independent testing dataset. Furthermore, an exchange experiment between datasets revealed a substantial overlap in discriminative ROIs, highlighting the robustness of our method across diverse populations.

CONCLUSION

Our findings indicate that IRBCFA can serve as a valuable tool for quantifying the spatial complexity of gray matter, providing insights into cognitive aging and aiding in the automated identification of individuals with SCD. The demonstrated generalizability and robustness of this method position it as a promising tool for neurodegenerative disease research and offer potential for clinical applications.

Cognitive and Hippocampal Changes in Older Adults With Subjective Cognitive Decline After Acupuncture Intervention

OBJECTIVE

Converging evidence indicates that subjective cognitive decline (SCD) could be an early indicator of dementia. The hippocampus is the earliest affected region during the progression of cognitive impairment. However, little is known about whether and how acupuncture change the hippocampal structure and function of SCD individuals.

METHODS

Here, we used multi-modal MRI to reveal the mechanism of acupuncture in treating SCD. Seventy-two older participants were randomized into acupuncture or sham acupuncture group and treated for 12 weeks.

RESULTS

At the end of the intervention, compared to sham acupuncture, participants with acupuncture treatment showed improvement in composite Z score from multi-domain neuropsychological tests, as well as increased hippocampal volume and functional connectivity. Moreover, the greater white matter integrity of the fornix, which is the major output tract of the hippocampus, was shown in the acupuncture group.

CONCLUSION

These findings suggest that acupuncture may improve the cognitive function of SCD individuals, and increase hippocampal volume on the regional level and enhance the structural and functional connectivity of hippocampus on the connective level.

Correlations between plasma markers and brain Aβ deposition across the AD continuum: Evidence from SILCODE

BACKGROUND

Previous studies have found that Alzheimer's disease (AD)-related plasma markers are associated with amyloid beta (Aβ) deposition, but the change of this association in different Aβ pathological stages remains unclear.

METHODS

Data were obtained from the SILCODE. According to the standardized uptake value ratio (SUVR) and Aβ stage classification, correlation analysis was performed among plasma biomarkers, and voxel/SUVR values in the regions of interest (ROI) and clinical scale information, respectively. Mediation analysis was used to study the possible pathways.

RESULTS

The proportion of cognitively normal (CN) and subjective cognitive decline (SCD) was the highest in stages A0 to 1, while in stages A2 to 4, the proportion of mild cognitive impairment (MCI) and AD increased. Plasma phosphorylated tau (p-tau)181 and glial fibrillary acidic protein (GFAP) levels were significantly lower in stage A0 compared to the later phases. Two pathways demonstrated fully mediated effects: positron emission tomography (PET) SUVR-plasma p-tau181-Mini-Mental State Examination (MMSE) and PET SUVR-plasma GFAP-MMSE.

DISCUSSION

This study demonstrated the role of plasma biomarkers in the early stage of AD, especially in SCD, from both the clinical diagnosis and Aβ stage dimensions.

HIGHLIGHTS

Plasma ptau181 and GFAP level serve as indicators of early Alzheimer's disease and the pathologic Aβ staging classification. A possible ceiling effect of GFAP was observed in the mid-to-late stages of the AD course. This study confirms the role of AD plasma markers in promoting Aβ deposition at an early stage, particularly in females with subjective cognitive decline(SCD). The overlapping brain regions of plasma p-tau181, GFAP, and neurofilament light for Aβ deposition in the brain in early AD were distributed across various regions, including the posterior cingulate gyrus, rectus gyrus, and inferior temporal gyrus.

Disrupted morphological brain network organization in subjective cognitive decline and mild cognitive impairment

We aim to investigate the alterations in gray matter for subjective cognitive decline (SCD) and mild cognitive impairment (MCI) from the perspective of the human connectome. High-resolution T1-weighted images were acquired from 54 patients with SCD, 95 patients with MCI, and 65 healthy controls (HC). Morphological brain networks (MBN) were constructed using similarities in the distribution of gray matter volumes between regions. The strength of morphological connections and topographic metrics derived from the graph-theoretical analysis were compared. Furthermore, we assessed the relationship between the observed morphological abnormalities and disease severity. According to the results, we found a significantly decreased morphological connection between the somatomotor network and ventral attention network in SCD compared to HC and MCI compared to SCD. The graph-theoretic analysis illustrated disruptions in the whole network organization, where the normalized shortest path increased and the global efficiency (Eg) decreased in MCI compared to SCD. In addition, Montreal Cognitive Assessment scores of SCD patients had a significantly negative correlation with Eg. The primary limitations of the present study include the cross-sectional design, no enrolled AD patients, no assessment of amyloidosis, and the need for more comprehensive neuropsychological tests. Our findings indicate the abnormalities of morphological networks at early stages in the AD continuum, which could be interpreted as compensatory changes to retain a normal level of cognitive function. The present study could provide new insight into the mechanism of AD.

Dysfunctions of multiscale dynamic brain functional networks in subjective cognitive decline

Subjective cognitive decline is potentially the earliest symptom of Alzheimer's disease, whose objective neurological basis remains elusive. To explore the potential biomarkers for subjective cognitive decline, we developed a novel deep learning method based on multiscale dynamical brain functional networks to identify subjective cognitive declines. We retrospectively constructed an internal data set (with 112 subjective cognitive decline and 64 healthy control subjects) to develop and internally validate the deep learning model. Conventional deep learning methods based on static and dynamic brain functional networks are compared. After the model is established, we prospectively collect an external data set (26 subjective cognitive decline and 12 healthy control subjects) for testing. Meanwhile, our method provides monitoring of the transitions between normal and abnormal (subjective cognitive decline-related) dynamical functional network states. The features of abnormal dynamical functional network states are quantified by network and variability metrics and associated with individual cognitions. Our method achieves an area under the receiver operating characteristic curve of 0.807 ± 0.046 in the internal validation data set and of 0.707 (P = 0.007) in the external testing data set, which shows improvements compared to conventional methods. The method further suggests that, at the local level, the abnormal dynamical functional network states are characterized by decreased connectivity strength and increased connectivity variability at different spatial scales. At the network level, the abnormal states are featured by scale-specifically altered modularity and all-scale decreased efficiency. Low tendencies to stay in abnormal states and high state transition variabilities are significantly associated with high general, language and executive functions. Overall, our work supports the deficits in multiscale brain dynamical functional networks detected by the deep learning method as reliable and meaningful neural alternation underpinning subjective cognitive decline.

Machine learning classifiers and associations of cognitive performance with hippocampal subfields in amnestic mild cognitive impairment

Background

Neuroimaging studies have demonstrated alterations in hippocampal volume and hippocampal subfields among individuals with amnestic mild cognitive impairment (aMCI). However, research on using hippocampal subfield volume modeling to differentiate aMCI from normal controls (NCs) is limited, and the relationship between hippocampal volume and overall cognitive scores remains unclear.

Methods

We enrolled 50 subjects with aMCI and 44 NCs for this study. Initially, a univariate general linear model was employed to analyze differences in the volumes of hippocampal subfields. Subsequently, two sets of dimensionality reduction methods and four machine learning techniques were applied to distinguish aMCI from NCs based on hippocampal subfield volumes. Finally, we assessed the correlation between the relative volumes of hippocampal subfields and cognitive test variables (Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment Scale (MoCA)).

Results

Significant volume differences were observed in several hippocampal subfields, notably in the left hippocampus. Specifically, the volumes of the hippocampal tail, subiculum, CA1, presubiculum, molecular layer, GC-ML-DG, CA3, CA4, and fimbria differed significantly between the two groups. The highest area under the curve (AUC) values for left and right hippocampal machine learning classifiers were 0.678 and 0.701, respectively. Moreover, the volumes of the left subiculum, left molecular layer, right subiculum, right CA1, right molecular layer, right GC-ML-DG, and right CA4 exhibited the strongest and most consistent correlations with MoCA scores.

Conclusion

Hippocampal subfield volume may serve as a predictive marker for aMCI. These findings underscore the sensitivity of hippocampal subfield volume to overall cognitive performance.

Subjective memory complaints are associated with decreased cortical thickness in Veterans with histories of mild traumatic brain injury

Objective: Memory problems are frequently endorsed in Veterans following mild traumatic brain injury (mTBI), but subjective complaints are poorly associated with objective memory performance. Few studies have examined associations between subjective memory complaints and brain morphometry. We investigated whether self-reported memory problems were associated with objective memory performance and cortical thickness in Veterans with a history of mTBI. Methods: 40 Veterans with a history of remote mTBI and 29 Veterans with no history of TBI completed the Prospective-Retrospective Memory Questionnaire (PRMQ), PTSD Checklist (PCL), California Verbal Learning Test-2nd edition (CVLT-II), and 3 T T1 structural magnetic resonance imaging. Cortical thickness was estimated in 14 a priori frontal and temporal regions. Multiple regressions adjusting for age and PCL scores examined associations between PRMQ, CVLT-II scores, and cortical thickness within each Veteran group. Results: Greater subjective memory complaints on the PRMQ were associated with lower cortical thickness in the right middle temporal gyrus (β = 0.64, q = .004), right inferior temporal gyrus (β = 0.56, q = .014), right rostral middle frontal gyrus (β = 0.45, q = .046), and right rostral anterior cingulate gyrus (β = 0.58, q = .014) in the mTBI group but not the control group (q's > .05). These associations remained significant after adjusting for CVLT-II learning. CVLT-II performance was not associated with PRMQ score or cortical thickness in either group. Conclusions: Subjective memory complaints were associated with lower cortical thickness in right frontal and temporal regions, but not with objective memory performance, in Veterans with histories of mTBI. Subjective complaints post-mTBI may indicate underlying brain morphometry independently of objective cognitive testing.

Low thalamic activity during a digit-symbol substitution task is associated with symptoms of subjective cognitive decline

Introduction

Subjective cognitive decline (SCD) may represent the earliest preclinical stage of Alzheimer's Disease (AD) for some older adults. However, the underlying neurobiology of SCD is not completely understood. Since executive function may be affected earlier than memory function in the progression of AD, we aimed to characterize SCD symptoms in terms of fMRI brain activity during the computerized digit-symbol substitution task (DSST), an executive function task. We also explored associations of DSST task performance with brain activation, SCD severity, and amyloid-ß (Aß) load.

Methods

We analyzed data from 63 cognitively normal older individuals (mean age 73.6 ± 7.2) with varying degree of SCD symptoms. Participants completed a computerized version of DSST in the MR scanner and a Pittsburgh Compound-B (PiB)-PET scan to measure global cerebral Aß load.

Results

A voxel-wise analysis revealed that greater SCD severity was associated with lower dorsomedial thalamus activation. While task performance was not associated with brain activation nor Aß load, slower reaction time was associated with greater SCD severity.

Discussion

The observed lower dorsomedial thalamus activation may reflect declining familiarity-based working memory and the trans-thalamic executive function pathway in SCD. SCD symptoms may reflect altered neural function and subtle decline of executive function, while Aß load may have an indirect impact on neural function and performance. Self-perceived cognitive decline may serve as a psychological/subjective marker reflecting subtle brain changes.

The relationship between learning slopes and Alzheimer's Disease biomarkers in cognitively unimpaired participants with and without subjective memory concerns

OBJECTIVE

Learning slopes represent serial acquisition of information during list-learning tasks. Although several calculations for learning slopes exist, the Learning Ratio (LR) has recently demonstrated the highest sensitivity toward changes in cognition and Alzheimer's disease (AD) biomarkers. However, investigation of learning slopes in cognitively unimpaired individuals with subjective memory concerns (SMC) has been limited. The current study examines the association of learning slopes to SMC, and the role of SMC in the relationship between learning slopes and AD biomarkers in cognitively unimpaired individuals.

METHOD

Data from 950 cognitively unimpaired participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 89) were used to calculate learning slope metrics. Learning slopes among those with and without SMC were compared with demographic correction, and the relationships of learning slopes with AD biomarkers of bilateral hippocampal volume and β-amyloid pathology were determined.

RESULTS

Learning slopes were consistently predictive of hippocampal atrophy and β-amyloid deposition. Results were heightened for LR relative to the other learning slopes. Additionally, interaction analyses revealed different associations between learning slopes and hippocampal volume as a function of SMC status.

CONCLUSIONS

Learning slopes appear to be sensitive to SMC and AD biomarkers, with SMC status influencing the relationship in cognitively unimpaired participants. These findings advance our knowledge of SMC, and suggest that LR - in particular - can be an important tool for the detection of AD pathology in both SMC and in AD clinical trials.

Machine learning analysis reveals aberrant dynamic changes in amplitude of low-frequency fluctuations among patients with retinal detachment

Background

There is increasing evidence that patients with retinal detachment (RD) have aberrant brain activity. However, neuroimaging investigations remain focused on static changes in brain activity among RD patients. There is limited knowledge regarding the characteristics of dynamic brain activity in RD patients.

Aim

This study evaluated changes in dynamic brain activity among RD patients, using a dynamic amplitude of low-frequency fluctuation (dALFF), k-means clustering method and support vector machine (SVM) classification approach.

Methods

We investigated inter-group disparities of dALFF indices under three different time window sizes using resting-state functional magnetic resonance imaging (rs-fMRI) data from 23 RD patients and 24 demographically matched healthy controls (HCs). The k-means clustering method was performed to analyze specific dALFF states and related temporal properties. Additionally, we selected altered dALFF values under three distinct conditions as classification features for distinguishing RD patients from HCs using an SVM classifier.

Results

RD patients exhibited dynamic changes in local intrinsic indicators of brain activity. Compared with HCs, RD patients displayed increased dALFF in the bilateral middle frontal gyrus, left putamen (Putamen_L), left superior occipital gyrus (Occipital_Sup_L), left middle occipital gyrus (Occipital_Mid_L), right calcarine (Calcarine_R), right middle temporal gyrus (Temporal_Mid_R), and right inferior frontal gyrus (Frontal_Inf_Tri_R). Additionally, RD patients showed significantly decreased dALFF values in the right superior parietal gyrus (Parietal_Sup_R) and right paracentral lobule (Paracentral_Lobule_R) [two-tailed, voxel-level p < 0.05, Gaussian random field (GRF) correction, cluster-level p < 0.05]. For dALFF, we derived 3 or 4 states of ALFF that occurred repeatedly. There were differences in state distribution and state properties between RD and HC groups. The number of transitions between the dALFF states was higher in the RD group than in the HC group. Based on dALFF values in various brain regions, the overall accuracies of SVM classification were 97.87, 100, and 93.62% under three different time windows; area under the curve values were 0.99, 1.00, and 0.95, respectively. No correlation was found between hamilton anxiety (HAMA) scores and regional dALFF.

Conclusion

Our findings offer important insights concerning the neuropathology that underlies RD and provide robust evidence that dALFF, a local indicator of brain activity, may be useful for clinical diagnosis.

Shared alterations in hippocampal structural covariance in subjective cognitive decline and migraine

Introduction

Subjective cognitive decline (SCD) and migraine are often comorbid. Hippocampal structural abnormalities have been observed in individuals with both SCD and migraine. Given the known structural and functional heterogeneity along the long axis (anterior to posterior) of the hippocampus, we aimed to identify altered patterns of structural covariance within hippocampal subdivisions associated with SCD and migraine comorbidities.

Methods

A seed-based structural covariance network analysis was applied to examine large-scale anatomical network changes of the anterior and posterior hippocampus in individuals with SCD, migraine and healthy controls. Conjunction analyses were used to identify shared network-level alterations in the hippocampal subdivisions in individuals with both SCD and migraine.

Results

Altered structural covariance integrity of the anterior and posterior hippocampus was observed in the temporal, frontal, occipital, cingulate, precentral, and postcentral areas in individuals with SCD and migraine compared with healthy controls. Conjunction analysis revealed that, in both SCD and migraine, altered structural covariance integrity was shared between the anterior hippocampus and inferior temporal gyri and between the posterior hippocampus and precentral gyrus. Additionally, the structural covariance integrity of the posterior hippocampus-cerebellum axis was associated with the duration of SCD.

Conclusion

This study highlighted the specific role of hippocampal subdivisions and specific structural covariance alterations within these subdivisions in the pathophysiology of SCD and migraine. These network-level changes in structural covariance may serve as potential imaging signatures for individuals who have both SCD and migraine.

Brain structure-function coupling associated with cognitive impairment in cerebral small vessel disease

Cerebral small vessel disease (CSVD) is a common chronic and progressive disease that can lead to mental and cognitive impairment. Damage to brain structure and function may play an important role in the neuropsychiatric disorders of patients with CSVD. Increasing evidence suggests that functional changes are accompanied by structural changes in corresponding brain regions. Thus, normal structure-function coupling is essential for optimal brain performance, and disrupted structure-function coupling can be found in many neurological and psychiatric disorders. To date, most studies on patients with CSVD have focused on separate structures or functions, including reductions in white matter volume and blood flow, which lead to cognitive dysfunction. However, there are few studies on brain structure-function coupling in patients with CSVD. In recent years, with the rapid development of multilevel (voxel-wise, neurovascular, regional level, and network level) brain structure-functional coupling analysis methods based on multimodal magnetic resonance imaging (MRI), new evidence has been provided to reveal the correlation between brain function and structural abnormalities and cognitive impairment. Therefore, studying brain structure-function coupling has a potential significance in the exploration and elucidation of the neurobiological mechanism of cognitive impairment in patients with CSVD. This article mainly describes the currently popular brain structure-function coupling analysis technology based on multimodal MRI and the important research progress of these coupling technologies on CSVD and cognitive impairment to provide a perspective for the study of the pathogenesis and early diagnosis of CSVD.

The Role of Aberrant Neural Oscillations in the Hippocampal-Medial Prefrontal Cortex Circuit in Neurodevelopmental and Neurological Disorders

The hippocampus (HPC) and medial prefrontal cortex (mPFC) have well-established roles in cognition, emotion, and sensory processing. In recent years, interests have shifted towards developing a deeper understanding of the mechanisms underlying interactions between the HPC and mPFC in achieving these functions. Considerable research supports the idea that synchronized activity between the HPC and the mPFC is a general mechanism by which brain functions are regulated. In this review, we summarize current knowledge on the hippocampal-medial prefrontal cortex (HPC-mPFC) circuit in normal brain function with a focus on oscillations and highlight several neurodevelopmental and neurological disorders associated with aberrant HPC-mPFC circuitry. We further discuss oscillatory dynamics across the HPC-mPFC circuit as potentially useful biomarkers to assess interventions for neurodevelopmental and neurological disorders. Finally, advancements in brain stimulation, gene therapy and pharmacotherapy are explored as promising therapies for disorders with aberrant HPC-mPFC circuit dynamics.

Polyrhachis vicina Roger Alleviates Memory Impairment in a Rat Model of Alzheimer's Disease Through the EGR1/BACE1/APP Axis

Memory deficits and loss are the earliest and most prominent features of Alzheimer's disease (AD). This study was aimed to clarify the mechanistic basis of an active fraction of Polyrhachis vicina Roger (AFPR) on the memory abilities of AD rat models, which involves early growth response 1 (EGR1) expression and β-secretase 1 (BACE1)-mediated deposition of amyloid β peptide (Aβ). An AD rat model was developed by Aβ25-35, which was further treated with AFPR alone or in combination with lentiviral EGR1. The Morris water maze test and HE and Fluoro-Jade C staining were adopted to observe the memory behaviors, hippocampus neuron morphology, and Aβ deposition. Aβ25-35-induced SK-N-SH and HT22 neurons were subjected to AFPR for in vitro experiments on neuronal viability and apoptosis. AFPR improved the impaired memory function, preserved the neuron structure, and suppressed Aβ deposition in AD rat models. Further, the expression of APP pathway-related proteins was downregulated by AFPR in both rat and cellular models. Moreover, AFPR inhibited the Aβ25-35-induced neuronal apoptosis. AFPR suppressed the expression of EGR1, downregulated the BACE1 expression via impeding the binding of EGR1 to the BACE1 promoter, and thus blocked the activation of the APP signaling, ultimately protecting neurons. Notably, the aforementioned effects of AFPR were in a concentration-dependent manner; among three doses, 3.65, 15.6, and 30 mg/(kg·d), high-dose AFPR exhibited the most appreciable effects. In conclusion, AFPR inhibited the BACE1 expression by repressing the binding of EGR1 to the promoter of BACE1, thereby suppressing the Aβ deposition and improving the memory function of AD rats.

Differential Abnormality in Functional Connectivity Density in Preclinical and Early-Stage Alzheimer's Disease

Background

Both subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI) have a high risk of progression to Alzheimer's disease (AD). While most of the available evidence described changes in functional connectivity (FC) in SCD and aMCI, there was no confirmation of changes in functional connectivity density (FCD) that have not been confirmed. Therefore, the purpose of this study was to investigate the specific alterations in resting-state FCD in SCD and aMCI and further assess the extent to which these changes can distinguish the preclinical and early-stage AD.

Methods

A total of 57 patients with SCD, 59 patients with aMCI, and 78 healthy controls (HC) were included. The global FCD, local FCD, and long-range FCD were calculated for each voxel to identify brain regions with significant FCD alterations. The brain regions with abnormal FCD were then used as regions of interest for FC analysis. In addition, we calculated correlations between neuroimaging alterations and cognitive function and performed receiver-operating characteristic analyses to assess the diagnostic effect of the FCD and FC alterations on SCD and aMCI.

Results

FCD mapping revealed significantly increased global FCD in the left parahippocampal gyrus (PHG.L) and increased long-range FCD in the left hippocampus for patients with SCD when compared to HCs. However, when compared to SCD, patients with aMCI showed significantly decreased global FCD and long-range FCD in the PHG.L. The follow-up FC analysis further revealed significant variations between the PHG.L and the occipital lobe in patients with SCD and aMCI. In addition, patients with SCD also presented significant changes in FC between the left hippocampus, the left cerebellum anterior lobe, and the inferior temporal gyrus. Moreover, changes in abnormal indicators in the SCD and aMCI groups were significantly associated with cognitive function. Finally, combining FCD and FC abnormalities allowed for a more precise differentiation of the clinical stages.

Conclusion

To our knowledge, this study is the first to investigate specific alterations in FCD and FC for both patients with SCD and aMCI and confirms differential abnormalities that can serve as potential imaging markers for preclinical and early-stage Alzheimer's disease (AD). Also, it adds a new dimension of understanding to the diagnosis of SCD and aMCI as well as the evaluation of disease progression.

Altered Default Mode Network Is Associated With Cognitive Impairment in CADASIL as Revealed by Multimodal Neuoimaging

Background and Purpose: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy caused by mutations in the NOTCH3 gene is a hereditary cerebral small vessel disease, manifesting with stroke, cognitive impairment, and mood disturbances. Functional or structural changes in the default mode network (DMN), which plays important role in cognitive and mental maintenance, have been found in several neurological and mental diseases. However, it remains unclear whether DMN is altered in patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). Methods: Multimodal imaging methods, including MRI and positron emission tomography (PET), were applied to evaluate the functional, structural, and metabolic characteristics of DMN in 25 patients with CADASIL and 42 healthy controls. Results: Compared with controls, patients with CADASIL had decreased nodal efficiency and degree centrality of the dorsal medial pre-frontal cortex and hippocampal formation within DMN. Structural MRI and diffusion tensor imaging (DTI) showed decreased gray matter volume and fiber tracks presented in the bilateral hippocampal formation. Meanwhile, PET imaging showed decreased metabolism within the whole DMN in CADASIL. Furthermore, correlation analyses showed that these nodal characteristics, gray matter volume, and metabolic signals of DMN were related to cognitive scores in CADASIL. Conclusions: Our results suggested that altered network characteristics of DMN might play important roles in cognitive deficits of CADASIL.

A potential biomarker of preclinical Alzheimer's disease: The olfactory dysfunction and its pathogenesis-based neural circuitry impairments

The olfactory dysfunction can signal and act as a potential biomarker of preclinical AD. However, the precise regulatory mechanism of olfactory function on the neural pathogenesis of AD is still unclear. The impairment of neural networks in olfaction system has been shown to be tightly associated with AD. As key brain regions of the olfactory system, the olfactory bulb (OB) and the piriform cortex (PCx) have a profound influence on the olfactory function. Therefore, this review will explore the mechanism of olfactory dysfunction in preclinical AD in the perspective of abnormal neural networks in the OB and PCx and their associated brain regions, especially from two aspects of aberrant oscillations and synaptic plasticity damages, which help better understand the underlying mechanism of olfactory neural network damages related to AD.

Rosmarinic acid attenuates lipopolysaccharide-induced neuroinflammation and cognitive impairment in rats

It has been recently demonstrated that rosmarinic acid (RA) through modulation in the amyloidogenic pathway exhibit neuroprotective potential in Alzheimer's disease. However, its effects on non-amyloidogenic pathways such as neuroinflammation (NI) and oxidative stress have not been elucidated carefully. Hence, this study aimed to investigate the effect of RA on cognitive function, cortical and hippocampal oxidant-antioxidant balance, and proinflammatory cytokines production in lipopolysaccharide (LPS)-induced NI in rats. NI was induced by intracerebroventricular injection of LPS (50 μg/20 μL; 10 μL into each ventricle) in Wistar rats. RA (25 and 50 mg/kg.) was intraperitoneally administrated to the experimental groups 30 min before the LPS injection and continued once per day for seven days. Cognitive function was investigated by the Y-maze test, and the production of proinflammatory cytokines and oxidative stress markers were evaluated in their hippocampi (HIP) and prefrontal cortex (PFC). In addition, neuronal damage was evaluated in the HIP subfields histologically. The RA administration could alleviate cognitive impairments caused by NI in LPS-treated rats as evidenced by improved working memory and attenuated neuronal injury in the HIP subfields. RA treatment in a dose-dependent manner prevented the overproduction of tumor necrosis factor-alpha (TNF-α), interleukin 1 beta (IL-1β), and IL-6 in both the HIP and PFC. RA significantly alleviated the HIP and PFC levels of malondialdehyde (MDA) and nitric oxide (NOx) and enhanced the superoxide dismutase (SOD) activity. These findings demonstrated that RA could also exert its neuroprotective effects by modulating non-amyloidogenic pathways such as inflammation and oxidative stress.

Hippocampal resting-state functional connectivity with the mPFC and DLPFC moderates and mediates the association between education level and memory function in subjective cognitive decline

Objective:

This study aims to determine the relationship between education level, memory function, and hippocampus functional and structural alterations in subjective cognitive decline (SCD).

Methods:

Seventy-five participants with SCD were divided into high education (HE) and low education (LE) level groups. A Wechsler Memory Scale–Chinese Revision test and functional and structural MRI were performed within 1 week after participant recruitment. The bilateral hippocampus resting-state functional connectivity (rsFC), gray matter volume (GMV) of brain regions identified by rsFC analysis, and moderating and mediating effects were assessed.

Results:

Compared with the LE group, HE individuals showed 1) higher memory quotient (MQ) and Digit Span subscore, 2) decreased hippocampal rsFC with the right medial prefrontal cortex (mPFC) and dorsolateral prefrontal cortex (DLPFC), and 3) increased GMV in the right mPFC and DLPFC. The bilateral hippocampus–right DLPFC rsFC significantly associated with the MQ and the bilateral hippocampus–right mPFCrsFC with the Digit Span subscore in each group. The bilateral hippocampus–right DLPFC rsFC moderated the relationship between the education level and MQ. The bilateral hippocampus–right mPFC rsFC mediated the relationship between the education level and Digit Span subscore in all subjects.

Conclusion:

The hippocampal rsFC with the right mPFC and DLPFC contributes to the education level effect on memory function in SCD.

COVID-19: Impact of diagnosis threat and suggestibility on subjective cognitive complaints

A subset of recovered COVID-19 patients report persistent neurological symptoms. These include non-specific symptoms (e.g., headaches and fatigue) which were found to be affected by psychological processes in other disorders (e.g., post-concussion syndrome, PCS, after mild traumatic brain injury). The current study assessed the impact of diagnosis threat (i.e., information regarding the long-term neurological impact of COVID-19) and suggestibility on endorsed symptoms of both recovered patients and healthy controls. Method: Recovered patients (n = 90) and healthy controls (n = 210) described their cognitive functioning after being randomly assigned to: (a) Experimental group: These participants read an article that explored long-term neurological symptoms among COVID-19 survivors. (b) Control group: These participants read an article providing general information regarding the disease. Results: Recovered patients, but not healthy controls, endorsed more symptoms in the experimental condition compared to the control condition. Moreover, suggestibility was correlated with endorsement of symptoms. Conclusions: Post COVID-19 neurological symptoms may, at least partially, be affected by non-neurological factors such as diagnosis threat. Information regarding long-term effects of COVID-19 may skew reported symptoms with highly suggestible individuals particularly susceptible to these effects. Further research, however, is needed to validate and elaborate upon these initial findings.

Alzheimer's Disease and Empathic Abilities: The Proposed Role of the Cingulate Cortex

In recent years there has been increasing interest in examining the role of empathic abilities in Alzheimer’s disease (AD). Empathy, the ability to understand and share another person’s feelings, implies the existence of emotional and cognitive processes and is a pivotal aspect for success in social interactions. In turn, self-empathy is oriented to one’s thoughts and feelings. Decline of empathy and self-empathy can occur during the AD continuum and can be linked to different neuroanatomical pathways in which the cingulate cortex may play a crucial role. Here, we will summarize the involvement of empathic abilities through the AD continuum and further discuss the potential neurocognitive mechanisms that contribute to decline of empathy and self-empathy in AD.

rTMS modulates precuneus-hippocampal subregion circuit in patients with subjective cognitive decline

Hippocampal subregions (HIPsub) and their network connectivities are generally aberrant in patients with subjective cognitive decline (SCD). This study aimed to investigate whether repetitive transcranial magnetic stimulation (rTMS) could ameliorate HIPsub network connectivity by modulating one node of HIPsub network in SCD. In the first cohort, the functional connectivity (FC) of three HIPsub (i.e., hippocampal emotional, cognitive, and perceptual regions: HIPe, HIPc, and HIPp) were analyzed so as to identify alterations in HIPsub connectivity associated with SCD. Afterwards, a support vector machine (SVM) approach was applied using the alterations in order to evaluate to what extent we could distinguish SCD from healthy controls (CN). In the second cohort, a 2-week rTMS course of 5-day, once-daily, was used to activate the altered HIPsub network connectivity in a sham-controlled design. SCD subjects exhibited distinct patterns alterations of HIPsub network connectivity compared to CN in the first cohort. SVM classifier indicated that the abnormalities had a high power to discriminate SCD from CN, with 92.9% area under the receiver operating characteristic curve (AUC), 86.0% accuracy, 83.8% sensitivity and 89.1% specificity. In the second cohort, changes of HIPc connectivity with the left parahippocampal gyrus and HIPp connectivity with the left middle temporal gyrus demonstrated an amelioration of episodic memory in SCD after rTMS. In addition, SCD exhibited improved episodic memory after the rTMS course. rTMS therapy could improve the posterior hippocampus connectivity by modulating the precuneus in SCD. Simultaneous correction of the breakdown in HIPc and HIPp could ameliorate episodic memory in SCD. Thus, these findings suggested that rTMS manipulation of precuneus-hippocampal circuit might prevent disease progression by improving memory as the earliest at-risk state of Alzheimer’s disease in clinical trials and in practice.

Voxelwise Meta-Analysis of Gray Matter Abnormalities in Mild Cognitive Impairment and Subjective Cognitive Decline Using Activation Likelihood Estimation

Background: Voxel-based morphometry studies have not yielded consistent results among patients with mild cognitive impairment (MCI) and subjective cognitive decline (SCD). Objective: Therefore, we aimed to conduct a meta-analysis of gray matter (GM) abnormalities acquired from these studies to determine their respective neuroanatomical changes. Methods: We systematically searched for voxel-based whole-brain morphometry studies that compared MCI or SCD subjects with healthy controls in PubMed, Web of Science, and EMBASE databases. We used the coordinate-based method of activation likelihood estimation to determine GM changes in SCD, MCI, and MCI sub-groups (amnestic MCI and non-amnestic MCI). Results: A total of 45 studies were included in our meta-analysis. In the MCI group, we found structural atrophy of the bilateral hippocampus, parahippocampal gyrus (PHG), amygdala, right lateral globus pallidus, right insula, and left middle temporal gyrus. The aMCI group exhibited GM atrophy in the bilateral hippocampus, PHG, and amygdala. The naMCI group presented with structural atrophy in the right putamen, right insula, right precentral gyrus, left medial/superior frontal gyrus, and left anterior cingulate. The right lingual gyrus, right cuneus, and left medial frontal gyrus were atrophic GM regions in the SCD group. Conclusion: Our meta-analysis identified unique patterns of neuroanatomical alternations in both the MCI and SCD group. Structural changes in SCD patients provide new evidence for the notion that subtle impairment of visual function, perception, and cognition may be related to early signs of cognitive impairment. In addition, our findings provide a foundation for future targeted interventions at different stages of preclinical Alzheimer’s disease.