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Decreased coherence in electroencephalogram (EEG) has been reported in Alzheimer's disease (AD) experimentally, which could be considered as a typical electrophysiological characteristic in AD. This work aimed to investigate the effect of AD on coherence in the dorsal visual pathway by the technique of neurocomputation. Firstly, according to the hierarchical organization of the cerebral cortex and the information flows of the dorsal visual pathway, a more physiologically plausible neural mass model including cortical areas v1, v2, and v5 was established in the dorsal visual pathway. The three interconnected cortical areas were connected by ascending and descending projections. Next, the pathological condition of loss of long synaptic projections in AD was simulated by reducing the parameters of long synaptic projections in the model. Then, the loss of long synaptic projections on coherence among different visual cortex areas was explored by means of power spectral analysis and coherence function. The results demonstrate that the coherence between these interconnected cortical areas showed an obvious decline with the gradual decrease of long synaptic projections, i.e. decrease in descending projections from area v2 to v1 and v5 to v2 and ascending projection from area v2 to v5. Hopefully, the results of this study could provide theoretical guidance for understanding the dynamical mechanism of AD. [ABSTRACT FROM AUTHOR]

Previous works imply that involving brainstem in neuropathological studies of Alzheimer's disease (AD) is of clinically significant. This work constructs a comprehensive neural mass model for cholinergic neuropathogenesis that involves brainstem, thalamus and cortex, wherein how acetylcholine deficiency in AD affects neural oscillation of the model output is systematically explored from the perspective of neurocomputation. By decreasing synapse connectivity parameters in direct cholinergic pathway from brainstem to thalamus or in indirect glutamatergic synapse pathway from cortex to brainstem to mimic the pathological condition of reduced acetylcholine release in patients with AD, the property of neural oscillation in this model is numerically investigated by means of power spectrum in frequency domain and amplitude distribution in time domain. Simulated results demonstrate that decreasing synapse connectivity whether in the direct cholinergic pathway or in the indirect glutamatergic synapse pathway can alter the neural oscillation significantly in three aspects: it induces an obvious decrease of dominant frequency; it leads to a degraded rhythmic activity in the alpha frequency band as well as an enhanced rhythmic activity in the theta frequency band; it results in reduced oscillation amplitude of the model output. These results are agreement with the characteristic of electrophysiological EEG measurement recorded in AD, especially support the hypothesis that cholinergic deficiency is a promising pathophysiological origin of EEG slowing in AD. Our analysis indicates that targeting the cholinergic system may have potential prospects in early diagnosis and treatment of AD. [ABSTRACT FROM AUTHOR]

Note that identifying Mild Cognitive Impairment (MCI) is crucial to early detection and diagnosis of Alzheimer's disease (AD). This work explores how classification features and experimental algorithms influence classification performances on the ADNI database. Based on structural Magnetic Resonance Images (sMRI), two features including gray matter (GM) volume and lateralization index (LI) are firstly extracted through hypothesis testing. Afterward, several classifier algorithms including Random Forest (RF), Decision Tree (DT), K-Nearest Neighbor(KNN) and Support Vector Machine (SVM) with RBF kernel, Linear kernel or Polynomial kernel are established to realize binary classification among Normal Control (NC), Early Mild Cognitive Impairment (EMCI), Late Mild Cognitive Impairment (LMCI) and AD groups. The main experimental results are as follows. (1) The classification performance in the feature of LI is poor compared with those in the feature of GM volume or the combined feature of LI and GM volume, i.e., the classification accuracies in the feature of LI are relatively low and unstable for most classifier models and subject groups. (2) Comparing with the classification performances in the feature of GM volume and the combined feature of LI and GM volume, the classification accuracy of NC group versus AD group is relatively stable for different classifier models, moreover, the accuracy of AD group versus NC group is almost the highest, with the most classification accuracy of 98.0909%. (3) For different subject groups, the SVM classifier algorithm with Polynomial kernel and the KNN classifier algorithm show relatively stable and high classification accuracy, while DT classifier algorithm shows relatively unstable and lower classification accuracy. (4) Except the groups of EMCI versus LMCI and NC versus EMCI, the classification accuracies are significantly enhanced by emerging the LI into the original feature of GM volume, with the maximum accuracy increase of 5.6364%. These results indicate that various factors of subject data, feature types and experimental algorithms influence classification performances remarkably, especially the newly introduced feature of LI into the feature of GM volume is helpful to improve classification results in some certain extent. [ABSTRACT FROM AUTHOR]

A decrease in alpha band power is defined as a hallmark of electroencephalogram (EEG) in Alzheimer's disease (AD). This study devotes to understanding the neuronal correlates of alpha rhythm slowing associated with AD from the view of neurocomputation. Firstly, a modified computational model of thalamo-cortico-thalamic (TCT) circuitry is constructed by incorporating two important biologically plausible ingredients. One is the disinhibition property between different inhibitory interneurons in the cortical module. The other is the full relay function of thalamic relay nucleus (TCR) to the cortical module. Then, by decreasing synaptic connectivity parameters to mimic the neuropathological condition of synapse loss in AD, the correlation between neuronal synaptic behavior and abnormal alpha rhythm is simulated by means of power spectral analysis. The results indicate that these decreases of synaptic activity, i.e., not only the excitatory synaptic connections from TCR to fast inhibitory interneurons Cfte and from excitatory interneurons to pyramidal neurons Cpxe but also the inhibitory synaptic connections from fast inhibitory interneurons to slow inhibitory interneurons Clfi and from inhibitory interneurons to TCR Ctii, can significantly diminish the peak power density over the alpha band of the thalamic output, which implies that there is a slowing of alpha band. Furthermore, the underlying mechanism behind the alpha rhythmic changes is analyzed using nonlinear dynamical technique. The results reveal that decreases of Cfte, Cpxe, Clfi and Ctii can make the thalamic module transfer from a limit cycle mode to a point attractor mode, which may lead to the alpha rhythm slowing in the modified TCT model. We expect this work can be helpful in identifying early biomarkers of AD's EEG and understanding potential pathogenesis of AD. [ABSTRACT FROM AUTHOR]

There is growing evidence that metabolic dysregulation contributes to the pathogenesis of Alzheimer's disease (AD). It is however difficult to detect multiple metabolites simultaneously in the different areas of the entire AD brain. Our research used a modified mass spectrometry imaging technique based on desorption electrospray ionization to visualize the spatial distributions of more than 300 compounds, including 119 putative metabolite candidates, in the whole brain slices from AD mice. Through such imaging measurements, we had quantified the level changes of more than 70 metabolites in 12 brain regions of AD mice. We had also evaluated metabolic pathway alterations in AD mice of various ages. In AD mice, we found a dysfunctional glutamine-glutamate/GABA cycle with deficient production and release of glutamate in glutamatergic neurons and aberrant increase of GABA. Disordered metabolism of excitatory glutamate and inhibitory GABA might contribute to the abnormal neural activity. The untargeted mapping of metabolic dysregulations during pathological progression in the AD model might provide implications for the pathogenesis and treatment of AD. [Display omitted] • Mass spectrometry imaging allowed simultaneous mapping of over 300 compounds. • The level changes of 71 metabolites were investigated in 12 brain regions in a mouse model of Alzheimer's disease. • About 20 metabolic pathways were examined in the mouse brains of Alzheimer's disease at different ages. • Dysregulated metabolism of neurotransmitters led to impaired neuronal firing in Alzheimer's disease mice. [ABSTRACT FROM AUTHOR]

Background: It is believed that there is a certain correlation between the brain and kidneys, but it is poorly understood. Many findings suggested that there were previously unknown signaling pathways involving AβPP and BACE1 in the kidney.Objective: Exploring the changes of BACE1 activity in APP23 mouse kidneys, providing evidence for the function of AβPP and BACE1 activity in the kidney.Methods: The activity and expression of BACE1 were detected in the kidney of APP23 mice by enzymatic assay and western blotting. The protein expression levels of AβPP, claudin1, occludin, VE-cadherin, and Klotho (membrane-form klotho) were examined by using western blotting. The renal pathological changes of APP23 mice were examined by the routine renal pathological procedures.Results: In this study, we found that the AβPP protein level was increased in kidneys of APP23 mice compared with wild-type (WT) mice. Additionally, the activity and expression of BACE1 were increased in kidneys of APP23 mice compared to that of WT. BACE1 was predominantly distributed on the lumen side of renal tubular epithelial cells. The protein levels of Klotho and VE-cadherin were decreased, occludin expression was also decreased, and claudin-1 expression was increased. Renal pathological damage which observed in kidneys of APP23 mice was more serious than that in kidneys of WT mice.Conclusion: Our findings suggest that the increase of AβPP protein levels under Thy-1 neuron promoter in the APP23 mice promoted the increase of renal BACE1 expression and enzymatic activity in the kidneys. Moreover, certain pathological damage in the kidneys of APP23 mice were observed. APP23 mice are easily affected by external risk factors compared with WT mice. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that mostly strikes the elderly. However, the exact molecular and cellular pathogenesis of AD, especially the dynamic changes of neurons during disease progression, remains poorly understood. Here we used single-nucleus RNA sequencing (snRNA-seq) to access the transcriptional changes of hippocampal neurons in APP23 mouse model of AD. We performed snRNA-seq using a modified Smart-seq2 technique on 3,280 neuronal nuclei from the hippocampus of young and aged APP23 and control mice and identified four distinct subpopulations. Comparative transcriptional analysis showed multiple changes in different subtypes of hippocampal neurons of APP23 mice in comparison to control mice, as well as the transcriptional changes in these neurons during disease progression. Our findings revealed multiple neuronal subtype-specific transcriptional changes that may lead to targets for future studies of AD. Single-nucleus RNA-seq for identifying the transcriptional changes in hippocampal neurons of an Alzheimer's disease mouse model. [ABSTRACT FROM AUTHOR]