Longitudinal Changes in Hippocampal Network Connectivity in Alzheimer's Disease

Exploring morphological similarity and randomness in Alzheimer's disease using adjacent grey matter voxel-based structural analysis

BACKGROUND

Alzheimer's disease is characterized by large-scale structural changes in a specific pattern. Recent studies developed morphological similarity networks constructed by brain regions similar in structural features to represent brain structural organization. However, few studies have used local morphological properties to explore inter-regional structural similarity in Alzheimer's disease.

METHODS

Here, we sourced T1-weighted MRI images of 342 cognitively normal participants and 276 individuals with Alzheimer's disease from the Alzheimer's Disease Neuroimaging Initiative database. The relationships of grey matter intensity between adjacent voxels were defined and converted to the structural pattern indices. We conducted the information-based similarity method to evaluate the structural similarity of structural pattern organization between brain regions. Besides, we examined the structural randomness on brain regions. Finally, the relationship between the structural randomness and cognitive performance of individuals with Alzheimer's disease was assessed by stepwise regression.

RESULTS

Compared to cognitively normal participants, individuals with Alzheimer's disease showed significant structural pattern changes in the bilateral posterior cingulate gyrus, hippocampus, and olfactory cortex. Additionally, individuals with Alzheimer's disease showed that the bilateral insula had decreased inter-regional structural similarity with frontal regions, while the bilateral hippocampus had increased inter-regional structural similarity with temporal and subcortical regions. For the structural randomness, we found significant decreases in the temporal and subcortical areas and significant increases in the occipital and frontal regions. The regression analysis showed that the structural randomness of five brain regions was correlated with the Mini-Mental State Examination scores of individuals with Alzheimer's disease.

CONCLUSIONS

Our study suggested that individuals with Alzheimer's disease alter micro-structural patterns and morphological similarity with the insula and hippocampus. Structural randomness of individuals with Alzheimer's disease changed in temporal, frontal, and occipital brain regions. Morphological similarity and randomness provide valuable insight into brain structural organization in Alzheimer's disease.

Differential atrophy along the longitudinal hippocampal axis in Alzheimer's disease for the Alzheimer's Disease Neuroimaging Initiative

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that primarily affects the hippocampus. Since hippocampal studies have highlighted a differential subregional regulation along its longitudinal axis, a more detailed analysis addressing subregional changes along the longitudinal hippocampal axis has the potential to provide new relevant biomarkers. This study included structural brain MRI data of 583 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Cognitively normal (CN) subjects, mild cognitively impaired (MCI) subjects and AD patients were conveniently selected considering the age and sex match between clinical groups. Structural MRI acquisitions were pre-processed and analysed with a new longitudinal axis segmentation method, dividing the hippocampus in three subdivisions (anterior, intermediate, and posterior). When normalizing the volume of hippocampal sub-divisions to total hippocampus, the posterior hippocampus negatively correlates with age only in CN subjects (r = -.31). The longitudinal ratio of hippocampal atrophy (anterior sub-division divided by the posterior one) shows a significant increase with age only in CN (r = .25). Overall, in AD, the posterior hippocampus is predominantly atrophied early on. Consequently, the anterior/posterior hippocampal ratio is an AD differentiating metric at early disease stages with potential for diagnostic and prognostic applications.

Distinct functional subnetworks of cognitive domains in older adults with minor cognitive deficits

Although past research has established a relationship between functional connectivity and cognitive function, less is known about which cognitive domains are associated with which specific functional networks. This study investigated associations between functional connectivity and global cognitive function and performance in the domains of memory, executive function and psychomotor speed in 166 older adults aged 75-91 years (mean = 80.3 ± 3.8) with minor cognitive deficits (Mini-Mental State Examination scores between 21 and 27). Functional connectivity was assessed within 10 standard large-scale resting-state networks and on a finer spatial resolution between 300 nodes in a functional connectivity matrix. No domain-specific associations with mean functional connectivity within large-scale resting-state networks were found. Node-level analysis revealed that associations between functional connectivity and cognitive performance differed across cognitive functions in strength, location and direction. Specific subnetworks of functional connections were found for each cognitive domain in which higher connectivity between some nodes but lower connectivity between other nodes were related to better cognitive performance. Our findings add to a growing body of literature showing differential sensitivity of functional connections to specific cognitive functions and may be a valuable resource for hypothesis generation of future studies aiming to investigate specific cognitive dysfunction with resting-state functional connectivity in people with beginning cognitive deficits.

Transcranial magneto-acoustic stimulation improves spatial memory and modulates hippocampal neural oscillations in a mouse model of Alzheimer's disease

Introduction

In our study, we applied transcranial magneto-acoustic stimulation (TMAS), a technique based on focused ultrasound stimulation within a static magnetic field, in the APP/PS1 mouse model of Alzheimer's disease (AD) to explore the feasibility of TMAS on improving AD related spatial memory deficits and abnormal neural oscillations.

Methods

The mice treated with TMAS once daily for 21 days. We recorded local field potential signals in the hippocampal CA1 region of the mice after TMAS treatment with in-vivo electrophysiology and evaluated the neural rehabilitative effect of TMAS with sharp-wave ripple (SWR), gamma oscillations during SWRs, and phase-amplitude coupling (PAC). The spatial memory function of the mice was examined by the Morris water maze (MWM) task.

Results

We found that TMAS improved the performance of MWM related spatial cognitive functions compared with AD group. Furthermore, our results implied that TMAS alleviated abnormalities in hippocampal SWRs, increased slow gamma power during SWRs, and promoted theta-slow gamma phase-amplitude coupling. These findings suggest that TMAS could have a positive influence on spatial memory through the modulation of neural oscillations.

Discussion

This work emphasizes the potential of TMAS to serve as a non-invasive method for Alzheimer's disease rehabilitation and promote the application of TMAS for the treatment of more neurological and brain aging diseases in the future.

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.

[Alzheimer's disease classification based on nonlinear high-order features and hypergraph convolutional neural network]

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder that damages patients' memory and cognitive abilities. Therefore, the diagnosis of AD holds significant importance. The interactions between regions of interest (ROIs) in the brain often involve multiple areas collaborating in a nonlinear manner. Leveraging these nonlinear higher-order interaction features to their fullest potential contributes to enhancing the accuracy of AD diagnosis. To address this, a framework combining nonlinear higher-order feature extraction and three-dimensional (3D) hypergraph neural networks is proposed for computer-assisted diagnosis of AD. First, a support vector machine regression model based on the radial basis function kernel was trained on ROI data to obtain a base estimator. Then, a recursive feature elimination algorithm based on the base estimator was applied to extract nonlinear higher-order features from functional magnetic resonance imaging (fMRI) data. These features were subsequently constructed into a hypergraph, leveraging the complex interactions captured in the data. Finally, a four-dimensional (4D) spatiotemporal hypergraph convolutional neural network model was constructed based on the fMRI data for classification. Experimental results on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database demonstrated that the proposed framework outperformed the Hyper Graph Convolutional Network (HyperGCN) framework by 8% and traditional two-dimensional (2D) linear feature extraction methods by 12% in the AD/normal control (NC) classification task. In conclusion, this framework demonstrates an improvement in AD classification compared to mainstream deep learning methods, providing valuable evidence for computer-assisted diagnosis of AD.

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.

Statistical models of complex brain networks: a maximum entropy approach

The brain is a highly complex system. Most of such complexity stems from the intermingled connections between its parts, which give rise to rich dynamics and to the emergence of high-level cognitive functions. Disentangling the underlying network structure is crucial to understand the brain functioning under both healthy and pathological conditions. Yet, analyzing brain networks is challenging, in part because their structure represents only one possible realization of a generative stochastic process which is in general unknown. Having a formal way to cope with such intrinsic variability is therefore central for the characterization of brain network properties. Addressing this issue entails the development of appropriate tools mostly adapted from network science and statistics. Here, we focus on a particular class of maximum entropy models for networks, i.e. exponential random graph models, as a parsimonious approach to identify the local connection mechanisms behind observed global network structure. Efforts are reviewed on the quest for basic organizational properties of human brain networks, as well as on the identification of predictive biomarkers of neurological diseases such as stroke. We conclude with a discussion on how emerging results and tools from statistical graph modeling, associated with forthcoming improvements in experimental data acquisition, could lead to a finer probabilistic description of complex systems in network neuroscience.

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.

Transcranial alternating current stimulation combined with sound stimulation improves cognitive function in patients with Alzheimer's disease: Study protocol for a randomized controlled trial

Background

The number of patients with Alzheimer's disease (AD) worldwide is increasing yearly, but the existing treatment methods have poor efficacy. Transcranial alternating current stimulation (tACS) is a new treatment for AD, but the offline effect of tACS is insufficient. To prolong the offline effect, we designed to combine tACS with sound stimulation to maintain the long-term post-effect.

Materials and methods

To explore the safety and effectiveness of tACS combined with sound stimulation and its impact on the cognition of AD patients. This trial will recruit 87 patients with mild to moderate AD. All patients were randomly divided into three groups. The change in Alzheimer's Disease Assessment Scale-Cognitive (ADAS-Cog) scores from the day before treatment to the end of treatment and 3 months after treatment was used as the main evaluation index. We will also explore the changes in the brain structural network, functional network, and metabolic network of AD patients in each group after treatment.

Discussion

We hope to conclude that tACS combined with sound stimulation is safe and tolerable in 87 patients with mild to moderate AD under three standardized treatment regimens. Compared with tACS alone or sound alone, the combination group had a significant long-term effect on cognitive improvement. To screen out a better treatment plan for AD patients. tACS combined with sound stimulation is a previously unexplored, non-invasive joint intervention to improve patients' cognitive status. This study may also identify the potential mechanism of tACS combined with sound stimulation in treating mild to moderate AD patients.

Clinical Trial Registration

Clinicaltrials.gov, NCT05251649. Registered on February 22, 2022.

Evaluating the treatment outcomes of repetitive transcranial magnetic stimulation in patients with moderate-to-severe Alzheimer's disease

The repetitive transcranial magnetic stimulation (rTMS) shows great potential in the treatment of Alzheimer's disease (AD). However, its treatment efficacy for AD patients in moderate to severe stage is relatively evaluated. Here, we proposed a randomized, sham-controlled, clinical trial of rTMS among 35 moderate-to-severe AD patients. A high frequency (10 Hz) stimulation of the left dorsal lateral prefrontal cortex (DLPFC), 60-session long treatment lasting for 3 months procedure was adopted in the trial. Each participant completed a battery of neuropsychological tests at baseline and post-treatment for evaluation of the rTMS therapeutic effect. Twelve of them completed baseline resting-state functional magnetic resonance imaging (fMRI) for exploration of the underlying neural contribution to individual difference in treatment outcomes. The result showed that the rTMS treatment significantly improved cognitive performance on the severe impairment battery (SIB), reduced psychiatric symptoms on the neuropsychiatric inventory (NPI), and improved the clinician's global impression of change (CIBIC-Plus). Furthermore, the result preliminarily proposed resting-state multivariate functional connectivity in the (para) hippocampal region as well as two clusters in the frontal and occipital cortices as a pre-treatment neuroimaging marker for predicting individual differences in treatment outcomes. The finding could brought some enlightenment and reference for the rTMS treatment of moderate and severe AD patients.

Magnetic Resonance Imaging Studies of Neurodegenerative Disease: From Methods to Translational Research

Neurodegenerative diseases (NDs) have become a significant threat to an aging human society. Numerous studies have been conducted in the past decades to clarify their pathologic mechanisms and search for reliable biomarkers. Magnetic resonance imaging (MRI) is a powerful tool for investigating structural and functional brain alterations in NDs. With the advantages of being non-invasive and non-radioactive, it has been frequently used in both animal research and large-scale clinical investigations. MRI may serve as a bridge connecting micro- and macro-level analysis and promoting bench-to-bed translational research. Nevertheless, due to the abundance and complexity of MRI techniques, exploiting their potential is not always straightforward. This review aims to briefly introduce research progress in clinical imaging studies and discuss possible strategies for applying MRI in translational ND research.

Degenerate mapping of environmental location presages deficits in object-location encoding and memory in the 5xFAD mouse model for Alzheimer's disease

A key challenge in developing diagnosis and treatments for Alzheimer's disease (AD) is to detect abnormal network activity at as early a stage as possible. To date, behavioral and neurophysiological investigations in AD model mice have yet to conduct a longitudinal assessment of cellular pathology, memory deficits, and neurophysiological correlates of neuronal activity. We therefore examined the temporal relationships between pathology, neuronal activities and spatial representation of environments, as well as object location memory deficits across multiple stages of development in the 5xFAD mice model and compared these results to those observed in wild-type mice. We performed longitudinal in vivo calcium imaging with miniscope on hippocampal CA1 neurons in behaving mice. We find that 5xFAD mice show amyloid plaque accumulation, depressed neuronal calcium activity during immobile states, and degenerate and unreliable hippocampal neuron spatial tuning to environmental location at early stages by 4 months of age while their object location memory (OLM) is comparable to WT mice. By 8 months of age, 5xFAD mice show deficits of OLM, which are accompanied by progressive degradation of spatial encoding and, eventually, impaired CA1 neural tuning to object-location pairings. Furthermore, depressed neuronal activity and unreliable spatial encoding at early stage are correlated with impaired performance in OLM at 8-month-old. Our results indicate the close connection between impaired hippocampal tuning to object-location and the presence of OLM deficits. The results also highlight that depressed baseline firing rates in hippocampal neurons during immobile states and unreliable spatial representation precede object memory deficits and predict memory deficits at older age, suggesting potential early opportunities for AD detecting.

Deep brain stimulation of the nucleus basalis of Meynert modulates hippocampal-frontoparietal networks in patients with advanced Alzheimer's disease

BACKGROUND

Deep brain stimulation (DBS) of the nucleus basalis of Meynert (NBM) has shown potential for the treatment of mild-to-moderate Alzheimer's disease (AD). However, there is little evidence of whether NBM-DBS can improve cognitive functioning in patients with advanced AD. In addition, the mechanisms underlying the modulation of brain networks remain unclear. This study was aimed to assess the cognitive function and the resting-state connectivity following NBM-DBS in patients with advanced AD.

METHODS

Eight patients with advanced AD underwent bilateral NBM-DBS and were followed up for 12 months. Clinical outcomes were assessed by neuropsychological examinations using the Mini-Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale. Resting-state functional magnetic resonance imaging and positron emission tomography data were also collected.

RESULTS

The cognitive functioning of AD patients did not change from baseline to the 12-month follow-up. Interestingly, the MMSE score indicated clinical efficacy at 1 month of follow-up. At this time point, the connectivity between the hippocampal network and frontoparietal network tended to increase in the DBS-on state compared to the DBS-off state. Additionally, the increased functional connectivity between the parahippocampal gyrus (PHG) and the parietal cortex was associated with cognitive improvement. Further dynamic functional network analysis showed that NBM-DBS increased the proportion of the PHG-related connections, which was related to improved cognitive performance.

CONCLUSION

The results indicated that NBM-DBS improves short-term cognitive performance in patients with advanced AD, which may be related to the modulation of multi-network connectivity patterns, and the hippocampus plays an important role within these networks.

TRIAL REGISTRATION

ChiCTR, ChiCTR1900022324. Registered 5 April 2019-Prospective registration. https://www.chictr.org.cn/showproj.aspx?proj=37712.

A diagnostic index based on pseudo-continuous arterial spin labeling and T1-mapping improves efficacy in discriminating Alzheimer’s disease from normal cognition

Background

Pseudo-continuous arterial spin labeling (pCASL) is widely used to quantify cerebral blood flow (CBF) abnormalities in patients with Alzheimer’s disease (AD). T1-mapping techniques assess microstructural characteristics in various pathologic changes, but their application in AD remains in the exploratory stage. We hypothesized that combining quantitative CBF and T1 values would generate diagnostic results with higher accuracy than using either method alone in discriminating AD patients from cognitively normal control (NC) subjects.

Materials and methods

A total of 45 patients diagnosed with AD and 33 NC subjects were enrolled, and cognitive assessment was performed for each participant according to the Chinese version of the Mini-Mental State Examination (MMSE). T1-weighted magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) and pCASL sequence were scanned on a 3T MR scanner. A brain morphometric analysis was integrated into prototype sequence, providing tissue classification and morphometric segmentation results. Quantitative CBF and T1 values of each brain region were automatically generated inline after data acquisition. Independent samples t-test was used to compare regional CBF and T1 values controlled by false discovery rate correction (corrected p < 0.01). The model with combined CBF and T1 values was compared with the individual index by performing receiver operating characteristic curves analysis. The associations between the MMSE score and CBF and T1 values of the brain were investigated using partial correlations.

Results

Cerebral blood flow of the right caudate nucleus (RCc) and left hippocampus (LHc) was significantly lower in the AD group compared with the NC group, while the T1 values of the right caudate nucleus (RCt) and left hippocampus (LHt) increased in the AD group. Prediction accuracies of 73.1, 77.2, 75.9, and 81.3% were achieved for each of the above parameters, respectively. In distinguishing patients from controls using the corresponding optimized cut-off values, most combinations of parameters were elevated (area under curve = 0.775–0.894). The highest area under curve value was 0.944, by combining RCc, LHc, RCt, and LHt.

Conclusion

In this preliminary study, the combined model based on pCASL and T1-mapping improved the diagnostic performance of discriminating AD and NC groups. T1-mapping may become a competitive technique for quantitatively measuring pathologic changes in the brain.

Modulation of entorhinal cortex–hippocampus connectivity and recognition memory following electroacupuncture on 3×Tg-AD model: Evidence from multimodal MRI and electrophysiological recordings

Memory loss and aberrant neuronal network activity are part of the earliest hallmarks of Alzheimer’s disease (AD). Electroacupuncture (EA) has been recognized as a cognitive stimulation for its effects on memory disorder, but whether different brain regions or neural circuits contribute to memory recovery in AD remains unknown. Here, we found that memory deficit was ameliorated in 3×Tg-AD mice with EA-treatment, as shown by the increased number of exploring and time spent in the novel object. In addition, reduced locomotor activity was observed in 3×Tg-AD mice, but no significant alteration was seen in the EA-treated mice. Based on the functional magnetic resonance imaging, the regional spontaneous activity alterations of 3×Tg-AD were mainly concentrated in the accumbens nucleus, auditory cortex, caudate putamen, entorhinal cortex (EC), hippocampus, insular cortex, subiculum, temporal cortex, visual cortex, and so on. While EA-treatment prevented the chaos of brain activity in parts of the above regions, such as the auditory cortex, EC, hippocampus, subiculum, and temporal cortex. And then we used the whole-cell voltage-clamp recording to reveal the neurotransmission in the hippocampus, and found that EA-treatment reversed the synaptic spontaneous release. Since the hippocampus receives most of the projections of the EC, the hippocampus-EC circuit is one of the neural circuits related to memory impairment. We further applied diffusion tensor imaging (DTI) tracking and functional connectivity, and found that hypo-connected between the hippocampus and EC with EA-treatment. These data indicate that the hippocampus–EC connectivity is responsible for the recognition memory deficit in the AD mice with EA-treatment, and provide novel insight into potential therapies for memory loss in AD.

Modulation of Brain Activity and Functional Connectivity by Acupuncture Combined With Donepezil on Mild-to-Moderate Alzheimer's Disease: A Neuroimaging Pilot Study

Background

Functional brain imaging changes have been proven as potential pathophysiological targets in early-stage AD. Current longitudinal neuroimaging studies of AD treated by acupuncture, which is one of the growingly acknowledged non-pharmacological interventions, have neither adopted comprehensive acupuncture protocols, nor explored the changes after a complete treatment duration. Thus, the mechanisms of acupuncture effects remain not fully investigated.

Objective

This study aimed to investigate the changes in spontaneous brain activity and functional connectivity and provide evidence for central mechanism of a 12-week acupuncture program on mild-to-moderate AD.

Methods

A total of forty-four patients with mild-to-moderate AD and twenty-two age- and education-level-matched healthy subjects were enrolled in this study. The forty-four patients with AD received a 12-week intervention of either acupuncture combined with Donepezil (the treatment group) or Donepezil alone (the control group). The two groups received two functional magnetic resonance imaging (fMRI) scans before and after treatment. The healthy subject group underwent no intervention, and only one fMRI scan was performed after enrollment. The fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity (FC) were applied to analyze the imaging data. The correlations between the imaging indicators and the changed score of Alzheimer's Disease Assessment Scale-Cognitive Section (ADAS-cog) were also explored.

Results

After the 12-week intervention, compared to those in the control group, patients with AD in the treatment group scored significantly lower on ADAS-cog value. Moreover, compared to healthy subjects, the areas where the fALFF value decreased in patients with AD were mainly located in the right inferior temporal gyrus, middle/inferior frontal gyrus, middle occipital gyrus, left precuneus, and bilateral superior temporal gyrus. Compared with the control group, the right precuneus demonstrated the greatest changed value of fALFF after the intervention in the treatment group. The difference in ADAS-cog after interventions was positively correlated with the difference in fALFF value in the left temporal lobe. Right precuneus-based FC analysis showed that the altered FC by the treatment group compared to the control group was mainly located in the bilateral middle temporal gyrus.

Conclusion

The study revealed the key role of precuneus in the effect of the combination of acupuncture and Donepezil on mild-to-moderate AD for cognitive function, as well as its connection with middle temporal gyrus, which provided a potential treating target for AD.

Trial Registration Number:

NCT03810794 (http://www.clinicaltrials.gov).

A Spatiotemporal Brain Network Analysis of Alzheimer's Disease Based on Persistent Homology

Current brain network studies based on persistent homology mainly focus on the spatial evolution over multiple spatial scales, and there is little research on the evolution of a spatiotemporal brain network of Alzheimer's disease (AD). This paper proposed a persistent homology-based method by combining multiple temporal windows and spatial scales to study the spatiotemporal evolution of brain functional networks. Specifically, a time-sliding window method was performed to establish a spatiotemporal network, and the persistent homology-based features of such a network were obtained. We evaluated our proposed method using the resting-state functional MRI (rs-fMRI) data set from Alzheimer's Disease Neuroimaging Initiative (ADNI) with 31 patients with AD and 37 normal controls (NCs). In the statistical analysis experiment, most network properties showed a better statistical power in spatiotemporal networks than in spatial networks. Moreover, compared to the standard graph theory properties in spatiotemporal networks, the persistent homology-based features detected more significant differences between the groups. In the clustering experiment, the brain networks on the sliding windows of all subjects were clustered into two highly structured connection states. Compared to the NC group, the AD group showed a longer residence time and a higher window ratio in a weak connection state, which may be because patients with AD have not established a firm connection. In summary, we constructed a spatiotemporal brain network containing more detailed information, and the dynamic spatiotemporal brain network analysis method based on persistent homology provides stronger adaptability and robustness in revealing the abnormalities of the functional organization of patients with AD.

The many dimensions of human hippocampal organization and (dys)function

The internal organization of hippocampal formation has been studied for more than a century. Although early accounts emphasized its subfields along the medial-lateral axis, findings in recent decades have highlighted also the anterior-to-posterior (i.e., longitudinal) axis as a key contributor to this brain region's functional organization. Hence, understanding of hippocampal function likely demands characterizing both medial-to-lateral and anterior-to-posterior axes, an approach that has been concretized by recent advances in in vivo parcellation and gradient mapping techniques. Following a short historical overview, we review the evidence provided by these approaches in brain-mapping studies, as well as the perspectives they open for addressing the behavioral relevance of the interacting organizational axes in healthy and clinical populations.