Abstract:Alzheimer's disease (AD) is a kind of degenerative disease. In the early stage, AD is characterized by the aggregation of β amyloid (Aβ) and tau proteins in the brain and memory loss. This paper summarizes the relationship between Aβ and cognitive function of the brain, reviews current research on how Aβ affects cognitive function (memory, execution and language), and also provides an outlook on future research trends to provide new ideas for the identification of Aβ deposition.

Abstract:Objective: To detect the application of the Cambridge semantic memory test battery (CST) in patients with semantic dementia (SD). Methods: In the study, 26 SD patients and 25 normal control subjects were given language scales and other tests including mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA). Results: ①The overall evaluation results of the SD group were worse than those of the normal control group (P<0.001). ②The AUC values of the 4 subtests of CST in the detection of SD patients and the normal control group were 0.984 (95%CI=0.951-1.000), 0.915 (95%CI=0.826-1.000), 0.898 (95%CI=0.808-0.988), 0.857 (95%CI=0.733-0.980) (P<0.001). ③Bivariate analysis of CST results and MMSE, MoCA, comprehensive cognitive assessment, activity of daily living scale (ADL), clinical dementia rating scale (CDR) and other results had significant correlation at the 0.01 level (P<0.001). ④SD patients had significant atrophy of the anterior lower part of the temporal lobe, and focused on the left side, which was consistent with the evaluation results of the relevant neuropsychological scale. Conclusion: CST can be used to screen SD patients.

Abstract:The clinical manifestations of hypofunction of the brain are complex and diverse, while the assessment content of traditional cognitive scale is single, ignoring many behavioral details, which has limitations in the diagnosis of dementia. With the continuous increase of research on the intersection of artificial intelligence and medicine, new evaluation methods continue to emerge. The exploration of speech, writing process, gait, eye movements, virtual reality technology and wearable devices in cognitive evaluation have become hotspots. This article focuses on the exploration and application of the above new cognitive assessment techniques, and discusses the advantages and prospects of these new cognitive assessment techniques compared to traditional scale assessment, which would provid guidance for the future application of such evaluation methods in clinical practice.

Abstract:Objective: To study the neuropsychological performance of the elderly with reversible cognitive frailty (RCF), and to compare the differences among them and the normal, the single subjective cognitive decline (SCD) and the single frailty. Methods: The study selected 166 elderly people aged≥60 years old and without obvious cognitive impairments in the clinic of Fuxing Hospital Affiliated to Capital Medical University and its surrounding communities from January 2015 to June 2018.Demographic and general clinical data of the elderly were collected, and the frailty or cognitive function of them were assessed. They were divided into four groups: normal control, single SCD, single frailty and RCF. The neuropsychological performances between different groups were studied. Results: From normal to RCF, the scores of memory and language function-related tests of the four groups were reduced in turn. Between the RCF and the normal control group, the immediate recall (P=0.036) and short delay recall (P=0.020) of the auditory vocabulary learning test (P=0.032), and the animal-household products alternating fluency test (P=0.011) were statistically different. Conclusion: From normal to SCD and RCF, they appear a tendency to decline in memory and language functions, and there are significant differences between subjects with RCF and normal controls.

Abstract:Alzheimer's disease (AD) is an irreversible neurodegenerative disorder, which is mainly manifested as memory, execution, language and other impairments. Early detection and intervention can delay the progression of the disease. At present, traditional neuropsychological scales are commonly used clinically to assess patients'cognitive function, but it has certain subjectivity and limitations. Artificial intelligence natural language processing (NLP) is a cognitive assessment tool that integrates linguistics, computer science and machine learning, which can more objectively assess the degree of cognitive decline in patients by analyzing human language and help clinicians identify patients with mild cognitive impairment (MCI) and AD early and classify AD patients. This review will summarize the application of artificial intelligence NLP in AD.

Abstract:Objective: To compare the performance of mini mental state examination (MMSE) and Chinese version of brief assessment of impaired cognition (BASIC) in the cognitive assessment of patients with stroke, so as to provide theoretical reference for clinical use. Methods: A total of 97 patients with stroke hospitalized in The First People's Hospital of Changzhou from May 2020 to January 2021 were selected as the stroke group, and another 40 healthy individuals matched with age, sex and education level were selected as the control group. All subjects were assessed by trained rehabilitation physicians for MMSE and BASIC, and the results were compared and analyzed. Results: ①Compared with the control group, the scores of MMSE and BASIC in the stroke group decreased significantly, indicating that the cognitive function of patients with stroke was significantly impaired. ②The results of MMSE and BASIC in the stroke group were positively correlated (r=0.662, P=0.000). ③Linear correlation suggested that age was negatively correlated with MMSE (r=-0.324, P=0.001) and BASIC (r=-0.401, P=0.000), while education years were positively correlated with MMSE (r=0.349, P=0.000) and BASIC (r=0.378, P=0.000). However, multiple linear regression showed that the results of MMSE were not affected by age.④MMSE and BASIC had no significant ceiling and floor effects.⑤Kappa analysis showed that the consistency of the two scales in screening for cognitive dysfunction in stroke patients was fair (Kappa=0.286, P=0.005). ⑥The receiver operating characteristic curve showed that there was no significant difference in the areas under the curve between MMSE and BASIC. The best cut-off values of MMSE and BASIC were 27.5 and 20.5, respectively. Conclusion: BASIC scale has low attenuation effect and short operation time, which can be used as an early rapid screening tool for cognitive dysfunction after stroke. However, it is necessary to further improve its assessment accuracy and pay attention to the selection of the assessment population.

Abstract:Objective: To study and analyze the predictive effect of cognitive screening scale on behavioral memory impairments in patients with brain injury. Methods: A total of 58 brain injury patients were included in the study. Each patient completed the minimental state examination (MMSE), Montreal cognitive assessment scale (MoCA), and Rivermead behavioural memory test-third edition (RBMT-3), and the results were analyzed and compared. Results: Behavioral memory (RBMT-3 score) was significantly related to attention and calculation (MMSE-AC: P=0.007, β=0.371) and recall (MMSE-Re: P=0.016, β=0.352) in the MMSE sub-items. The sum of the scores of each sub-item and the total score of the MMSE scale had intermediate predictive value for behavioral memory impairments (AUC=0.845, 0.793). Behavioral memory and visual space/execution (MoCA-VE: P=0.004, β=0.278), language (MoCA-L: P=0.003, β=0.250), delayed recall (MoCA-DR: P<0.001, β=0.479) and orientation (MoCA-O: P=0.002, β=0.240) were significantly correlated. The sum of the scores of the four sub-items of MoCA and the total score of the MoCA scale had high levels of behavioral memory impairments (AUC=0.953, 0.938). When the score of the four sub-items of MoCA was lower than 13.5, or the total score was lower than 24.5, it indi cated that the patient could have behavioral memory impairments. Conclusion: The behavioral memory impairments can be predicted based on the scores of MMSE or MoCA scale in patients with brain injury, and the diagnostic value of MoCA scale is higher.

Abstract:Objective: To test the reliability and validity of the self-designed simple clinical aphasia scale. Methods: A total of 45 normal subjects and 46 patients with aphasia after stroke were assessed twice with the self-designed clinical aphasia scale among different raters, and Aphasia Battery of Chinese (ABCJ) scale evaluation was conducted. The retest reliability, internal consistency, inter rater reliability, calibration validity, construction validity and discriminant validity were calculated. Results: The retest reliability of the simple clinical aphasia scale was 0.867-0.990.The Cronbach's α coefficient of the scale was 0.873.The reliability inter the raters was 0.862-0.992.Factor analysis KMO was 0.825, discriminant validity was P<0.001, and calibration validity was 0.805-0.953. Conclusion: The simple clinical aphasia scale has good reliability and validity in the diagnosis of Chinese aphasia after stroke, and can be used as a tool to evaluate the language impairment of patients with aphasia after stroke.

Abstract:With the aging of the population, the incidence of neurodegenerative diseases such as Alzheimer's disease (AD) is rising year by year. Cognitive impairment and neuropsychiatric symptoms are typical manifestations of AD. Cognitive impairment is mainly manifested in the decline of memory, logical ability, language ability, executive ability and attention. Neuropsychiatric symptoms mainly include depression, euphoria, apathy and so on. The above symptoms can affect the patient's daily living ability and quality of life. At present, there is no cure for AD, so early detection, diagnosis and treatment are of great significance for delaying the progression of the disease, improving the quality of life of patients, and reducing the burden on caregivers and society. At present, the cognitive assessment of AD is mainly based on neuropsychological scale test, but this method still has many disadvantages. This review focuses on the latest advances in cognitive assessment based on virtual reality (VR), which aims to provide more reliable diagnosis for home or clinical settings.

Abstract:Objective: To explore the relationship between cognitive impairment, negative symptoms and stigma in patients with deficit schizophrenia. Methods: There were 72 patients with stable schizophrenia who were collected in the study. Their cognitive function and stigma were measured with RBANS scale, Stroop test and Link series of stigma scales. Then they were divided into deficit group (29 cases) and non-deficit group (43 cases) according to the schedule for the deficit syndrome (SDS). Besides, 40 normal controls were recruited in the surrounding community, and their cognitive function was measured by RBANS scale and Stroop test. Results: The scores of all dimensions except education (P>0.05) in RBANS scale (P<0.05) and stigma scales (P<0.05) of patients with deficit schizophrenia were significantly higher than those of non-deficit schizophrenia patients. In Stroop test, the test time of deficit patients was significantly longer than that of non-deficit patients (P<0.05). Spearman correlation analysis of 72 schizophrenic patients showed that the absolute value of Spearman correlation coefficient between each dimension of RBANS and devaluation discrimination, withdrawal, coping, misunderstanding, difference/shame, emotional experience and total score of stigma was greater than 0.3, showing a negative correlation. The absolute value of Spearman correlation coefficient between color time and derogation discrimination/shame, emotional experience and total score of stigma in each dimension of Stroop test was greater than 0.3.That between word time and all dimensions except confidentiality, education, challenge, separation and response was greater than 0.3; that between color word time and all dimensions except confidentiality, education, challenge and separation was greater than 0.3, and between color word time word time and stigma was greater than 0.3 except for education and separation. These absolute values greater than 0.3 showed a positive correlation. The correlation analysis between SDS score and stigma showed that the Spearman correlation coefficients of all dimensions except education were greater than 0.3, showing a positive correlation. Conclusion: The cognitive impairment and stigma are more serious in the patients with deficit schizophrenia than in those with non-deficit schizophrenia. The results of correlation analysis suggest that there is a negative correlation between stigma and non-social cognitive impairment, and a moderate positive correlation with negative symptoms.

Abstract:Objective: To analyze the expression profile of peripheral blood of patients with mild cognitive impairment (MCI) and search for genetic biomarkers of MCI. Methods: The expression profile data of GSE63063 was downloaded from GEO database. Weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression modules related to MCI. Functional enrichment analysis was performed on the most significant module. Then, the protein-protein interaction (PPI) network of the module was constructed by STRING database, and the Hub genes in the network were identified to establish the diagnosis model of MCI which was established based on the support vector machine (SVM). Finally, the receiver operating characteristic (ROC) analysis was carried out to detect its diagnostic ability. Results: Through WGCNA analysis, 9 co-expression modules related to MCI were found and brown module had the strongest correlation with MCI. The top 15 Hub genes of each module were screened out by MCC algorithm, among which Hub gene of brown module had the highest diagnosis ability, and the area under the ROC curve in the training set and the verification set was 0.864 and 0.789 respectively. Conclusion: Hub gene of brown module can be potential biomarkers for diagnosis of MCI.

Abstract:In recent years, with the improvement and popularization of neuroimaging technology, more and more cases of cerebral small vessel disease (CSVD) have been correctly identified, and it has become a common disease among the elderly. CSVD can cause a series of problems threatening patients'health, especially cognitive impairment. However, due to the lack of prominent early symptoms and lagging imaging examination, there is still a lack of effective means to identify such diseases as soon as possible. This paper expounds the imaging classification of CSVD and its characteristic cognitive function changes, and discusses its relationship between sleep and plasma biomarkers, so as to provide a strong basis for early clinical differential diagnosis and individualized treatment.

Abstract:Alzheimer's disease (AD) is one of the main causes of dementia, and subjective cognitive decline (SCD) is considered as the pre-clinical stage of AD. Early diagnosis of SCD is of great significance to the prevention and treatment of AD. Among various diagnostic methods of SCD, biochemical diagnosis is one relatively simple, low cost and less invasive. The combination of biochemical diagnosis and neuropsychological assessment has a good prospect in the diagnosis of SCD. Therefore, this paper has reviewed the research on cerebrospinal fluid, plasma, urine and other biochemical detection methods of SCD.

Abstract:Alzheimer's disease (AD) is the main cause of senile dementia. With the proposal of the "brain-gut axis" theory, more and more studies have confirmed the occurrence and development of AD are closely related to the change of gut microbiota and its metabolites. This article reviews and discusses the changes of fecal gut microbiota and its metabolites occurred in AD. Besides, the application prospects of fecal gut microbiota and its metabolites as AD diagnostic biomarkers are described.

Abstract:Objective: To explore whether serum neurofilament light chain protein (NFL) can be used as a peripheral blood biomarker to predict the early stage of Alzheimer's disease (AD). Methods: The study included 50 AD patients (AD group) from the Alzheimer's disease clinical database of the Affiliated Hospital of Traditional Chinese Medicine of Xinjiang Medical University, 50 patients with amnestic mild cognitive impairment (aMCI group) and the same time period 50 cognitively normal controls (CN group) matched by age and educational level. The subjects were all collected serum and detected the serum NFL protein level by enzyme linked immunosorbent assay (ELISA). Results: ①The AD group, aMCI group and CN group had no statistical difference in age, education years and BMI (P>0.05), and the data were comparable. ②AD patients MMSE score was significantly lower than that of aMCI group and CN group [AD group (17.48±7.50), aMCI group (25.56±1.63), CN group (28.60±1.09); F=81.830, P=0.000]. The MoCA score had the most significant difference [AD group (12.04±6.31), aMCI group (19.92±3.17), CN group (27.62±1.16); F=177.187, P=0.000]. ③The NFL protein level of AD group and aMCI group were significantly higher than that of CN group, among which aMCI group was the highest [AD group (4.486±2.463) ng/mL, aMCI group (5.101±2.172) ng/mL and CN group (2.885±1.469) ng/mL, F=15.167, P=0.000]. Spearman correlation analysis found that age, MMSE score, MoCA score, ADL score and CDR score were not correlated with NFL protein levels among the three groups (P>0.05). Conclusion: Serum NFL levels in patients with MCI is the highest, suggesting that serum NFL level may be a peripheral blood biomarker for predicting the early stage of AD.

Abstract:Objective: To investigate the relationship between vascular endothelial growth factor (VEGF) and pigment epithelial derived factors (PEDF) and cognitive disorder caused by cerebral small-vascular disease (CSVD), so as to provide valuable biomarkers for the early warning screening of vascular cognitive impairment (VCI) caused by CVSD. Methods: Patients with CVSD hospitalized in the Neurology Department of The First Affiliated Hospital of Baotou Medical College from June 2019 to June 2020 were continuously enrolled in the study. The relevant clinical data of the patients were collected and 3.0 T cranial MRI examinations were performed on them, including T1-weighted imaging, T2-weighted imaging, fluid attenuated inversion recovery (FLAIR) sequence, diffusion-weighted imaging and susceptibility weighted imaging. Serum VEGF and PEDF level were detected by VEGF and PEDF Elisa Kit. Multivariate logistic regression analysis was used to determine the independent influencing factors of CVSD-caused VCI. SPSS 26.0 was used to describe the receiver operating characteristic (ROC) curve, and the predictive serum VEGF and VEGF level for CVSD-caused VCI was evaluated. Results: A total of 193 patients were enrolled, including 90 patients in VCI group (46.6%) and 103 ones in non-VCI group (53.4%). Compared with non-VCI group, there were significant differences in educational years, past history of hypertension, lacunar infarction or transient ischemic attack (TIA), systolic and diastolic blood pressure, fasting blood glucose, serum creatinine, cystatin-C, serum VEGF and serum PEDF concentrations (P<0.05). Multivariate logistic regression analysis showed that the higher level of serum VEGF (odds ratio: 1.393; 95%CI=1.011-1.920, P=0.042) was the independent risk factor for VCI in CSVD; and relative lower expression of serum PEDF (odds ratio: 0.521, 95%CI=0.384-0.707, P=0.000) was the independent protective factor for VCI in CSVD patients. ROC curve analysis showed that the area under the curve of serum VEGF concentration combined with PEDF concentration to predict VCI in CSVD was 0.769 (95%CI=0.705-0.832, P<0.001), the sensitivity was 0.911, and the specificity was 0.612.The best cutoff values were 128.61 pg/mL and 100.95 ng/mL, which were of good predictive value. Conclusion: The concentrations of serum VEGF and PEDF are significantly correlated with VCI in CSVD patients, and the levels of serum VEGF and PEDF are expected to serve as the alternative indicators for the assessment of VCI in CSVD.

Abstract:Objective: To explore the characteristics of quantitative analysis of EEG in patients with semantic dementia (SD). Methods: Nine SD patients and 30 normal controls sex and age matched were selected for electroencephalogram (EEG) examination. The results of the EEG data were visually scored and quantitatively analyzed. The relative power ratio of (δ+θ) / (α+β) (DTABR) at the whole brain, left and right frontal, anterior-temporal, middle-posterior temporal, center, parietal and occipital area was measured respectively. The value of DTABR and the result of visual analysis were compared between the two groups, and the symmetry of EEG activity of bilateral brain in SD patients was observed simultaneously. Results: Compared with the normal control group, the slowwave activity and the DTABR of SD patients were significantly increased (P<0.01). The DTABR on the left brain side was significantly higher than that on the right side in SD patients, especially on the anterior-temporal area (P<0.05). Conclusion: Quantitative EEG can reflect the changes in brain function of SD patients and provide objective quantitative indicators for exploring the electrophysiological mechanism of SD.

Abstract:Objective: To explore the relationship between [N-methyl-¹¹C] -2- (4-methylaminophenyl) -6-hydroxybenzothiazole, positron emission tomography (¹¹C-PIB-PET/CT) and neuropsychological scales in mild cognitive impairment (MCI) and Alzheimer's disease (AD). Methods: Twenty-seven outpatients and inpatients with AD and MCI who met the inclusion criteria were selected from the Department of Neurology, China-Japan Union Hospital of Jilin University from January 2018 to December 2020, and general information, neuropsychological test scale scale scores and ¹¹C-PIB-PET/CT imaging of them were collected. The standardized uptake value ratio (SUVR) of ¹¹C-PIB in each brain region of the patients was obtained by processing the patient's ¹¹C-PIB-PET/CT imaging using pMOD software. The brain areas with significant differences were compared between the two groups, and the SUVR and neuropsychological test scale of all patients with statistical differences were statistically analyzed. Results: ①The mean value of SUVR in the AD group was higher than the mean value of SUVR in the MCI group, and the differences between groups were statistically significant (P<0.01). ②There were significant differences in the SUVR values of the brain regions of the two groups of paatients (P<0.01): the left inferior frontal gyrus (P=0.009), left superior frontal gyrus (P=0.008), left parahippocampal gyrus and perirhinal gyrus (P=0.005), right parahippocampal gyrus and perirhinal gyrus (P=0.002), left syrinx (P=0.002), right syrinx (P=0.003), left postcentral gyrus (P=0.003), right cuneus (P=0.008), left cisternal nucleus (P=0.007), right cisternal nucleus (P=0.003), right pallidum (P=0.006) and right anterior cingulate gyrus (P=0.004). ③Further Pearson correlation analysis was performed between the significantly different SUVR values of brain regions and the scores of MMSE (Mini-Mental State Examination) and MoCA (Montreal Cognitive Assessment) scales in all patients. Among them, the SUVR values of the left superior frontal gyrus (r=-0.454, P=0.029), left parahippocampal gyrus and peripheral gyrus (r=-0.439, P=0.036), left syrinx (r=-0.421, P=0.045), and left postcentral gyrus (r=-0.482, P=0.020) were negatively correlated with MMSE scores (P<0.05). The left superior frontal gyrus (r=-0.430, P=0.040), left parahippocampal gyrus and peripheral gyrus (r=-0.418, P=0.047), left cingulate gyrus (r=-0.454, P=0.030), left postcentral gyrus (r=-0.477, P=0.021), left cisternal nucleus (r=-0.422, P=0.045) and right cisternal nucleus (r=-0.419, P=0.047) SUVR values were negatively correlated with MoCA scores (P<0.05). Conclusion: ①SUVR values of ¹¹CPIB in the brain of patients in the AD group were significantly higher than those of patients in the MCI group. ②SUVR values in several brain regions were significantly different between patients in the AD and MCI groups. ③The levels of Aβ protein deposition in the superior frontal gyrus (left), parahippocampal gyrus and perirhinal gyrus (left), sphenoid gyrus (left), postcentral gyrus (left), and nucleus accumbens (left and right) are associated with MCI. These results can provide some imaging evidence for the early identification and diagnosis of AD.

Abstract:Objective: To explore the correlation between the hippocampal subfields and serial position effect in the elderly with normal cognition and mild cognitive impairment. Methods: A total of 21 subjects with mild cognitive impairment (MCI) treated in Fu Xing Hospital, Capital Medical University from January 2016 to January 2019 were selected as the MCI group, and 39 healthy controls (HC) with normal cognition (NC) from physical examination center and outpatient department were simultaneously selected as control group. All participants completed a set of neuropsychological assessment and were all examined by head MRI. The score of serial position effect was obtained using the auditory verbal learning test (AVLT). T1-weighted structural MRI data were collected after cognitive testing, and the subfields of the hippocampal formation were segmented automatically using the FreeSurfer 6.0 software, then volumetric estimates and estimated total intracranial volume were also calculated. Finally, the relationship between hippocampal subfields and serial position effect were analyzed. Results: The volume of each hippocampal subfield of MCI was smaller than that of the healthy control, but after Bonferroni correction of multiple comparison, only the difference in the presubiculum was statistically significant (P<0.05). The presubiculum was positively correlated with the total score of AVLT delayed recall and the score of primacy effect. Conclusion: Compared with the healthy control, the MCI patients show atrophy in all subfields. The volume of the presubiculum presents the most prominent reduction, which is correlated with the impairment of long-term memory.

Abstract:Objective: To study the correlation between subtypes of cerebral small vessel disease (CSVD) and extracranial carotid atherosclerosis and vascular cognitive impairment (VCI). Methods: The demographic and medication history data of 200 stroke-free CSVD patients were collected in the study. Carotid ultrasound was performed and carotid atherosclerosis was assessed using extracranial carotid atherosclerosis score. Brain magnetic resonance imaging (MRI) was performed and the lesions of various subtypes of CSVD were assessed. Montreal cognitive assessment (MoCA) score was used to screen patients with cognitive dysfunction. According to the total score of MoCA<23, the patients were divided into VCI group and non-VCI group. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for VCI in strokefree patients. We also established a model and used the receiver operating characteristic (ROC) curve to assess independent risk factors and calculated the cut-off value, etc. The best cut-off value of the CSVD score among the independent risk factors was used as a baseline to assess the cognitive impairment of the cerebral small vessels, cerebral small vascular cognitive burden score was calculated and was evaluated by the ROC curve. Results: Logistic regression analysis showed that the sum of lacunar infarction (LI) +lacune, Fazekas score and global cortical atrophy (GCA) score were positively correlated with VCI (P<0.05), while there was no significant correlation between extracranial carotid arteriosclerosis score and VCI (P>0.05). The area under the curve (AUC) of the established prediction model and the AUC of the cerebral small vascular cognitive burden score were>0.7, respectively. Conclusion: Some subtypes of CSVD are significantly correlated with VCI, while extracranial mild carotid atherosclerosis has no obvious correlation with VCI. The model can be established by CSVD or the cerebral small vascular cognitive burden score which is more convenient in clinic can be used to screen the small vascular cognitive impairment in strokefree patients.

Abstract:Alzheimer's disease (AD) is the most common form of dementia in the elderly who is characterized by progressive and irreversible loss of multidimensional cognitive function. Visual impairment is one of the features in AD and its high-risk population mild cognitive impairment (MCI) patients, and visual pathway dysfunction is associated with the underlying mechanism. Neuroimaging can reveal subtle changes in visual pathway in AD spectrum patients, which could help to early recognize and intervene in the progress of AD. In this article, we will review the progress of characteristics of abnormal visual pathway and its clinical application in AD spectrum patients.

Abstract:Alzheimer's disease (AD) is a progressive neurodegenerative disease. The hippocampus is the earliest and highly specific marker in the pathogenesis of AD, which can be divided into CA1-4 subregions. The hippocampal subregion is involved in the processing of episodic memory, social memory and associative memory, and is associated with aging, Aβ deposition, hyperphosphorylation of tau protein, ischemia and other influencing factors. The study of the changes in the hippocampal subregion in AD is of great clinical significance for the early identification and diagnosis of AD, and may provide new ideas for the treatment of AD.

Abstract:Alzheimer's disease (AD) and its risk population of mild cognitive impairment (MCI) are the most common cognitive impairments, whose core impairment is episodic memory dysfunction. The default network (DMN) is composed of the core subsystem (Core), the dorsal medial prefrontal cortex (DMPFC) subsystem and the medial temporal lobe (MTL) subsystem. The three subsystems cooperate with each other to maintain the steady state of episodic memory function. However, the patterns of interaction of these subsystems in AD spectrum patients are not clear yet. In this study, we will systematically review the advances of neuroimaging studies in this field, and the specific impairment characteristics of AD spectrum patients, which will provide important ideas for early screening, progression monitoring, efficacy evaluation and differential diagnosis of AD spectrum diseases.

Abstract:The cognitive decline caused by aging can cause a heavy social burden, and its pathogenesis has been studied widely in recent years. In this paper, we review the metabolism of the nervous system, aging of neurons, glial cells, neural stem cells, changes of components related to the blood-brain barrier, and their effects on cognitive function during aging.