Distinct Brain Regions Research Articles

Cobalt protoporphyrin modulates antioxidant enzyme activity in the hypothalamus and motor cortex of female rats.

Cobalt protoporphyrin (CoPP) is a synthetic heme analog that has been observed to reduce food intake and promote sustained weight loss. While the precise mechanisms responsible for these effects remain elusive, earlier research has hinted at the potential involvement of nitric oxide synthase in the hypothalamus. This study aimed to delve into CoPP's impact on the activities of crucial antioxidant enzymes: superoxide dismutase (SOD), catalase, glutathione peroxidase (GPx), glutathione reductase (GR), and glutathione-S-transferase (GST) across seven distinct brain regions (hippocampus, hypothalamus, prefrontal cortex, motor cortex, striatum, midbrain, and cerebellum), as well as in the liver and kidneys. Female Wistar rats weighing 180 to 200 grams received a single subcutaneous dose of 25 μmol/kg CoPP. After six days, brain tissue was extracted to assess the activities of antioxidant enzymes and quantify malondialdehyde levels. Our findings confirm that CoPP administration triggers the characteristic effects of decreased food intake and reduced body weight. Moreover, it led to an increase in SOD activity in the hypothalamus, a pivotal brain region associated with food intake regulation. Notably, CoPP-treated rats exhibited elevated enzymatic activity of catalase, GR, and GST in the motor cortex without concurrent signs of heightened oxidative stress. These results underscore a strong connection between the antioxidant system and food intake regulation. They also emphasize the need for further investigation into the roles of antioxidant enzymes in modulating food intake and the ensuing weight loss, using CoPP as a valuable research tool.

Comparing the Efficacy of Two Cognitive Screening Tools in Identifying Gray and White Matter Brain Damage among Older Adults.

Ageing is associated with structural changes in brain regions and functional decline in cognitive domains. Noninvasive tools for identifying structural damage in the brains of older adults are relevant for early treatment. This study aims to evaluate and compare the accuracy of the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA©) in identifying gray and white matter brain damage in older individuals with varying degrees of cognitive impairment. Ninety older adults (62 women) with an average age of 69 ± 7 years were enrolled and categorized as having no cognitive impairment (NCI), mild cognitive impairment (MCI), or moderate cognitive impairment (MoCI). Magnetic resonance imaging (MRI) was utilized to assess the number, volume, and distribution of brain damage. The Fazekas and Scheltens scales were applied to the brain MRIs, and inferential statistics were employed to compare variables among the groups. Cognitive impairment was observed in 56.7% of the participants (95% confidence interval (CI): 46.4-66.4%), with thirty-six older adults (40%) classified as MCI and 15 (17%) as MoCI. Cognitive impairment and medial temporal lobe (MTL) atrophy were found to be associated (p=0.001), exhibiting higher mean volume scales of the MTL atrophied area in the MoCI group (p < 0.001). The MMSE accurately revealed MTL atrophy based on the Scheltens (p < 0.05) and Fazekas (p < 0.05) scales. At the same time, the MoCA accurately identified periventricular white matter (PWM) abnormalities according to the Fazekas scale (p < 0.05). The MMSE and MoCA screening tools effectively identified gray and white matter brain damage in older adults with varying degrees of cognitive impairment. Lower MMSE scores are associated with MTL atrophy and lesions, and lower MoCA scores are related to PWM lesions. The concurrent use of MMSE and MoCA is recommended for assessing structural changes in distinct brain regions.

Distributed Sensitivity to Syntax and Semantics throughout the Language Network.

Human language is expressive because it is compositional: The meaning of a sentence (semantics) can be inferred from its structure (syntax). It is commonly believed that language syntax and semantics are processed by distinct brain regions. Here, we revisit this claim using precision fMRI methods to capture separation or overlap of function in the brains of individual participants. Contrary to prior claims, we find distributed sensitivity to both syntax and semantics throughout a broad frontotemporal brain network. Our results join a growing body of evidence for an integrated network for language in the human brain within which internal specialization is primarily a matter of degree rather than kind, in contrast with influential proposals that advocate distinct specialization of different brain areas for different types of linguistic functions.

Cerebral blood flow changes in maintenance hemodialysis patients with restless legs syndrome and their clinical significance:a cross-sectional case-control study

ObjectiveRestless legs syndrome (RLS) stands as a prevalent neurological complication within maintenance hemodialysis (MHD) patients. However, the alterations in cerebral blood flow (CBF) among MHD-RLS patients remain uncharted. Through the utilization of the arterial spin labeling (ASL) technique, we evaluated the fluctuations in CBF within distinct brain regions and analyzed the risk factors for the development of RLS in MHD patients in the context of the clinic.MethodsThirty-one MHD patients with concomitant RLS (MHD-RLS group) and thirty-one non-RLS patients matched based on age, gender, as well as cognitive function (MHD-nRLS group) were included. Through image preprocessing and data analysis, the changes in CBF values in distinct brain regions were obtained, and the CBF values of brain regions with substantial differences between the two groups were correlated with the RLS scores. Furthermore, the differences in baseline data were compared, and through the utilization of multifactorial logistic regression, the independent risk factors for the development of RLS were examined.ResultsCompared with the MHD-nRLS group, the MHD-RLS group had increased CBF in the right superior temporal gyrus, reduced CBF in the right hippocampus, left middle frontal gyrus, inferior frontal gyrus of right triangle, middle frontal gyrus of left orbit, left precentral gyrus, and left precuneus. Only left precentral gyrus CBF were negatively correlated with RLS scores after correction for dialysis duration(r = -0.436, P = 0.016). Accordingly, multifactorial regression analysis by stepwise method yielded that the left precentral gyrus CBF values(OR: 0.968, 95%CI: 0.944–0.993, P = 0.012) remained an independent risk factor for RLS in MHD patients. In addition, the results showed that hemodialysis duration (OR: 1.055, 95%CI: 1.014–1.098, P = 0.008) and serum iron levels (OR: 0.685, 95%CI: 0.551–0.852, P = 0.001) were also risk factors for the development of RLS.ConclusionPatients afflicted with MHD-RLS exhibit alterations in CBF across several brain regions. Notably, the left precentral gyrus might serve as a pivotal region influencing the onset of RLS among MHD patients. Furthermore, extended hemodialysis duration and a relative insufficiency in serum iron levels independently contribute as risk factors for RLS development within the MHD patient population.

Remote Associations Between Tau and Cortical Amyloid-β Are Stage-Dependent.

Histopathologic studies of Alzheimer's disease (AD) suggest that extracellular amyloid-β (Aβ) plaques promote the spread of neurofibrillary tau tangles. However, these two proteinopathies initiate in spatially distinct brain regions, so how they interact during AD progression is unclear. In this study, we utilized Aβ and tau positron emission tomography (PET) scans from 572 older subjects (476 healthy controls (HC), 14 with mild cognitive impairment (MCI), 82 with mild AD), at varying stages of the disease, to investigate to what degree tau is associated with cortical Aβ deposition. Using multiple linear regression models and a pseudo-longitudinal ordering technique, we investigated remote tau-Aβ associations in four pathologic phases of AD progression based on tau spread: 1) no-tau, 2) pre-acceleration, 3) acceleration, and 4) post-acceleration. No significant tau-Aβ association was detected in the no-tau phase. In the pre-acceleration phase, the earliest stage of tau deposition, associations emerged between regional tau in medial temporal lobe (MTL) (i.e., entorhinal cortex, parahippocampal gyrus) and cortical Aβ in lateral temporal lobe regions. The strongest tau-Aβ associations were found in the acceleration phase, in which tau in MTL regions was strongly associated with cortical Aβ (i.e., temporal and frontal lobes regions). Strikingly, in the post-acceleration phase, including 96% of symptomatic subjects, tau-Aβ associations were no longer significant. The results indicate that associations between tau and Aβ are stage-dependent, which could have important implications for understanding the interplay between these two proteinopathies during the progressive stages of AD.

Dopamine D1–D5 Receptors in Brain Nuclei: Implications for Health and Disease

Understanding the intricate role of dopamine D1–D5 receptors is pivotal in addressing the challenges posed by the aging global population, as well as by social stress and advancing therapeutic interventions. Central to diverse brain functions such as movement, cognition, motivation, and reward, dopamine receptors are ubiquitously distributed across various brain nuclei. This comprehensive review explores the nuanced functions of each dopamine receptor, D1, D2, D3, D4, and D5, in distinct brain regions, elucidating the alterations witnessed in several neurological and psychiatric disorders. From the substantia nigra and ventral tegmental area, crucial for motor control and reward processing, to the limbic system influencing emotional responses, motivation, and cognitive functions, each brain nucleus reveals a specific involvement of dopamine receptors. In addition, genetic variations in dopamine receptors affect the risk of developing schizophrenia and parkinsonism. The review further investigates the physiological significance and pathogenic impacts of dopamine receptors in critical areas like the prefrontal cortex, hypothalamus, and striatum. By unraveling the complexities of dopamine receptor biology, especially those focused on different brain nuclei, this review provides a foundation for understanding their varied roles in health and disease, which is essential for the development of targeted therapeutic strategies aimed at mitigating the impact of aging and mental health on neurological well-being.

Recent advances in neural mechanism of general anesthesia induced unconsciousness: insights from optogenetics and chemogenetics.

For over 170years, general anesthesia has played a crucial role in clinical practice, yet a comprehensive understanding of the neural mechanisms underlying the induction of unconsciousness by general anesthetics remains elusive. Ongoing research into these mechanisms primarily centers around the brain nuclei and neural circuits associated with sleep-wake. In this context, two sophisticated methodologies, optogenetics and chemogenetics, have emerged as vital tools for recording and modulating the activity of specific neuronal populations or circuits within distinct brain regions. Recent advancements have successfully employed these techniques to investigate the impact of general anesthesia on various brain nuclei and neural pathways. This paper provides an in-depth examination of the use of optogenetic and chemogenetic methodologies in studying the effects of general anesthesia on specific brain nuclei and pathways. Additionally, it discusses in depth the advantages and limitations of these two methodologies, as well as the issues that must be considered for scientific research applications. By shedding light on these facets, this paper serves as a valuable reference for furthering the accurate exploration of the neural mechanisms underlying general anesthesia. It aids researchers and clinicians in effectively evaluating the applicability of these techniques in advancing scientific research and clinical practice.

Performance monitoring and error detection: The role of mid frontal theta and error-related negativity (ERN) among Indian adolescents from different socioeconomic background

The aim of the study was to investigate the relationship between socioeconomic status (SES) and executive functioning, focusing specifically on performance monitoring, error detection, and their association with mid-frontal theta and error-related negativity (ERN). Employing the widely used flanker task, the research involved two phases with participants aged 10-16 years (15 individuals in the pilot phase and 35 in the second phase). Electroencephalogram (EEG) recordings from distinct brain regions were analyzed during various conditions. The study revealed a notable increase in both absolute and relative theta power at Fcz during the flanker task, with a stronger effect observed during incorrect trials. Furthermore, it underscored the influence of socioeconomic status (SES) on mid-frontal theta, highlighting interactions between SES, gender, and experimental conditions impacting both absolute and relative theta. Intriguingly, the research disclosed a positive correlation between parental occupation and error-related negativity (ERN), as well as between age and ERN. These findings underscore the significance of SES, gender, and age in shaping the neural mechanisms associated with performance monitoring and executive functions. The study contributes valuable insights into the intricate interplay between socio-demographic factors and cognitive processes, shedding light on their impact on goal-directed behaviors and brain activity.

Projective light-sheet microscopy with flexible parameter selection

Projection imaging accelerates volumetric interrogation in fluorescence microscopy, but for multi-cellular samples, the resulting images may lack contrast, as many structures and haze are summed up. Here, we demonstrate rapid projective light-sheet imaging with parameter selection (props) of imaging depth, position and viewing angle. This allows us to selectively image different sub-volumes of a sample, rapidly switch between them and exclude background fluorescence. Here we demonstrate the power of props by functional imaging within distinct regions of the zebrafish brain, monitoring calcium firing inside muscle cells of moving Drosophila larvae, super-resolution imaging of selected cell layers, and by optically unwrapping the curved surface of a Drosophila embryo. We anticipate that props will accelerate volumetric interrogation, ranging from subcellular to mesoscopic scales.

Mapping the Neural Substrates of Cocaine Craving: A Systematic Review.

Craving is one of the most important symptoms of cocaine use disorder (CUD) since it contributes to the relapse and persistence of such disorder. This systematic review aimed to investigate which brain regions are modulated during cocaine craving. The articles were obtained through searches in the Google Scholar, Regional BVS Portal, PubMed, and Scielo databases. Overall, there was a selection of 36 studies with 1574 individuals, the majority being participants with CUD, whereby about 61.56% were individuals with CUD and 38.44% were controls (mean age = 40.4 years). Besides the methodological points, the neurobiological investigations comprised fMRI (58.34%) and PET (38.89%). The induction of cocaine craving was studied using different methods: exposure to cocaine cues (69.45%), stressful stimuli, food cues, and methylphenidate. Brain activations demonstrated widespread activity across the frontal, parietal, temporal, and occipital lobes, basal ganglia, diencephalon, brainstem, and the limbic system. In addition to abnormalities in prefrontal cortex activity, abnormalities in various other brain regions' activity contribute to the elucidation of the neurobiology of cocaine craving. Abnormalities in brain activity are justified not only by the dysfunction of dopaminergic pathways but also of the glutamatergic and noradrenergic pathways, and distinct ways of inducing craving demonstrated the involvement of distinct brain circuits and regions.

Exploring non-Euclidean relationships in EEG emotion recognition: A dynamic graph attention network

Deep learning classification models based on electroencephalogram (EEG) emotion recognition have demonstrated considerable proficiency in the categorization of emotional states. However, these models have limitations in their capability to analyze the active states and cooperative relationships among distinct brain regions. This study proposes a dynamic graph attention network (DGAT) for EEG emotion recognition, which learns the features of each channel and leverages multiple-head self-attention mechanisms to capture non-Euclidean relationships between channels. Then, we use differential entropy features of emotions signals on the SJTU emotion EEG dataset (SEED). The DGAT model achieved improved subject-dependent and cross-subject classification accuracy compared to previous models. Moreover, ablation studies show that the channel weight matrix(CWM) and appropriate hyper-parameters can improve the performance of the DGAT model significantly. Furthermore, by conducting interpretable analysis of the new connections and electrode weights learned by the model, we find that these connection weight relationships reflect a certain degree of coordination within the brain for EEG-based emotion recognition. These findings provide a new method for EEG emotion recognition and highlights the potential for using deep learning models to analyze the active state and synergistic relationships among brain regions.

Differential depletion of GluN2A induces heterogeneous schizophrenia-related phenotypes in mice

Schizophrenia, a debilitating psychiatric disorder, displays considerable interindividual variation in clinical presentations. The ongoing debate revolves around whether this heterogeneity signifies a continuum of severity linked to a singular causative factor or a collection of distinct subtypes with unique origins. Within the realm of schizophrenia, the functional impairment of GluN2A, a subtype of the NMDA receptor, has been associated with an elevated risk. Despite GluN2A's expression across various neuronal types throughout the brain, its specific contributions to schizophrenia and its involvement in particular cell types or brain regions remain unexplored. We generated age-specific, cell type-specific or brain region-specific conditional knockout mice targeting GluN2A and conducted a comprehensive analysis using tests measuring phenotypes relevant to schizophrenia. Through the induction of germline ablation of GluN2A, we observed the emergence of numerous schizophrenia-associated abnormalities in adult mice. Intriguingly, GluN2A knockout performed at different ages, in specific cell types and within distinct brain regions, we observed overlapping yet distinct schizophrenia-related phenotypes in mice. Our interpretation suggests that the dysfunction of GluN2A is sufficient to evoke heterogeneous manifestations associated with schizophrenia, indicating that GluN2A stands as a prominent risk factor and a potential therapeutic target for schizophrenia. This project received support from the Shanghai Municipal Science and Technology Major Project (Grant No. 2019SHZDZX02) awarded to Y.C. and the Natural Science Foundation of Shanghai (Grant No. 19ZR1468600 and 201409003800) awarded to G.Y.

Electrophysiological correlates of temporal numerosity adaptation.

Much research has revealed the human visual system is capable to estimate numerical quantities, rapidly and reliably, in both the spatial and the temporal domain. This ability is highly susceptible to short-term plastic phenomena related to previous exposure to visual numerical information (i.e., adaptation). However, while determinants of spatial numerosity adaptation have been widely investigated, little is known about the neural underpinnings of short-term plastic phenomena related to the encoding of temporal numerical information. In the present study we investigated the electrophysiological correlates of temporal numerosity adaptation. Participants were asked to estimate the numerosity of a test sequence of flashes after being exposed to either a high or low numerous adapting sequence. Behavioral results confirmed the expected underestimation of test stimulus when this was preceded by a high numerous sequence as compared to when preceded by a low numerous sequence. Electrophysiological data revealed that this behavior was tightly linked to the amplitude of the steady-state visual evoked (ssVEP) response elicited by the test stimulus. When preceded by a high numerous sequence, the test stimulus elicited larger ssVEP responses as compared to when preceded by a low numerous sequence with this pattern being robustly correlated with behavior. Finally, topographical maps showed that this difference was mostly evident across two antero-posterior distributed clusters of electrodes and correlated with changes in functional connectivity. Taken together, our results suggest that visual plastic phenomena related to the encoding of temporal numerosity information reflect changes in rhythmic evoked activity that are likely related to long range communications between distinct brain regions.

Effector-independent Representations Guide Sequential Target Selection Biases in Action.

Previous work shows that automatic attention biases toward recently selected target features transfer across action and perception and even across different effectors such as the eyes and hands on a trial-by-trial basis. Although these findings suggest a common neural representation of selection history across effectors, the extent to which information about recently selected target features is encoded in overlapping versus distinct brain regions is unknown. Using fMRI and a priming of pop-out task where participants selected unpredictable, uniquely colored targets among homogeneous distractors via reach or saccade, we show that color priming is driven by shared, effector-independent underlying representations of recent selection history. Consistent with previous work, we found that the intraparietal sulcus (IPS) was commonly activated on trials where target colors were switched relative to those where the colors were repeated; however, the dorsal anterior insula exhibited effector-specific activation related to color priming. Via multivoxel cross-classification analyses, we further demonstrate that fine-grained patterns of activity in both IPS and the medial temporal lobe encode information about selection history in an effector-independent manner, such that ROI-specific models trained on activity patterns during reach selection could predict whether a color was repeated or switched on the current trial during saccade selection and vice versa. Remarkably, model generalization performance in IPS and medial temporal lobe also tracked individual differences in behavioral priming sensitivity across both types of action. These results represent a first step to clarify the neural substrates of experience-driven selection biases in contexts that require the coordination of multiple actions.

Understanding functional brain reorganization for naturalistic piano playing in novice pianists.

Learning to play the piano is a unique complex task, integrating multiple sensory modalities and higher order cognitive functions. Longitudinal neuroimaging studies on adult novice musicians show training-related functional changes in music perception tasks. The reorganization of brain activity while actually playing an instrument was studied only on a very short time frame of a single fMRI session, and longer interventions have not yet been performed. Thus, our aim was to investigate the dynamic complexity of functional brain reorganization while playing the piano within the first half year of musical training. We scanned 24 novice keyboard learners (female, 18-23 years old) using fMRI while they played increasingly complex musical pieces after 1, 6, 13, and 26 weeks of training. Playing music evoked responses bilaterally in the auditory, inferior frontal, and supplementary motor areas, and the left sensorimotor cortex. The effect of training over time, however, invoked widespread changes encompassing the right sensorimotor cortex, cerebellum, superior parietal cortex, anterior insula and hippocampus, among others. As the training progressed, the activation of these regions decreased while playing music. Post hoc analysis revealed region-specific time-courses for independent auditory and motor regions of interest. These results suggest that while the primary sensory, motor, and frontal regions are associated with playing music, the training decreases the involvement of higher order cognitive control and integrative regions, and basal ganglia. Moreover, training might affect distinct brain regions in different ways, providing evidence in favor of the dynamic nature of brain plasticity.

Early language dissociation in bilingual minds: magnetoencephalography evidence through a machine learning approach.

Does neural activity reveal how balanced bilinguals choose languages? Despite using diverse neuroimaging techniques, prior studies haven't provided a definitive solution to this problem. Nonetheless, studies involving direct brain stimulation in bilinguals have identified distinct brain regions associated with language production in different languages. In this magnetoencephalography study with 45 proficient Spanish-Basque bilinguals, we investigated language selection during covert picture naming and word reading tasks. Participants were prompted to name line drawings or read words if the color of the stimulus changed to green, in 10% of trials. The task was performed either in Spanish or Basque. Despite similar sensor-level evoked activity for both languages in both tasks, decoding analyses revealed language-specific classification ~100ms post-stimulus onset. During picture naming, right occipital-temporal sensors predominantly contributed to language decoding, while left occipital-temporal sensors were crucial for decoding during word reading. Cross-task decoding analysis unveiled robust generalization effects from picture naming to word reading. Our methodology involved a fine-grained examination of neural responses using magnetoencephalography, offering insights into the dynamics of language processing in bilinguals. This study refines our understanding of the neural underpinnings of language selection and bridges the gap between non-invasive and invasive experimental evidence in bilingual language production.

Examination of reward processing dysfunctions in the left dorsal striatum and other brain regions among psychiatric inpatients with substance use

BackgroundSubstance misuse is a major public health issue and research has established attenuated reward responses to drug cues in those who misuse substances. Yet, little is known about whether the expectation of natural reinforcers engages distinct brain regions in substance misuse. MethodsUsing functional magnetic resonance imaging (fMRI), we delivered juice at expected and unexpected times to examine reward processing dysfunctions. We focused on the responses within the left dorsal striatum (DS) in individuals with high-risk substance use (HRU, n = 65), low-risk substance use (psychiatric controls, PC, n = 65), and healthy controls (HC, n = 65). Additionally, we investigated whether the dysfunction in reward processing within the left DS is correlated with other common psychiatric symptoms. Finally, we conducted a comprehensive analysis of the whole brain to investigate other non-hypothesized brain regions. ResultsCompared to HC, HRU displayed lower responses to juice delivery (i.e., reward) in the left DS (p <.05). The whole-brain analysis demonstrated that compared to HC, HRU displayed significantly lower responses to reward stimuli in various brain regions, including the bilateral caudate, temporal gyrus, left frontal gyrus, middle frontal gyrus, and right thalamus. LimitationsParticipants were individuals with polysubstance use; therefore, we were not able to examine the effects of individual substances. ConclusionsOur findings suggest that HRU displays lower responses to reward stimuli within the left DS and other non-hypothesized brain regions. Our findings may help further elucidate reward processing dysfunctions related to substance misuse.

Investigating the Impact of Local Manipulations on Spontaneous and Evoked Brain Complexity Indices: A Large-Scale Computational Model

Brain complexity relies on the integrity of structural and functional brain networks, where specialized areas synergistically cooperate on a large scale. Local alterations within these areas can lead to widespread consequences, leading to a reduction in overall network complexity. Investigating the mechanisms governing this occurrence and exploring potential compensatory interventions is a pressing research focus. In this study, we employed a whole-brain in silico model to simulate the large-scale impact of local node alterations. These were assessed by network complexity metrics derived from both the model’s spontaneous activity (i.e., Lempel–Ziv complexity (LZc)) and its responses to simulated local perturbations (i.e., the Perturbational Complexity Index (PCI)). Compared to LZc, local node silencing of distinct brain regions induced large-scale alterations that were paralleled by a systematic drop of PCI. Specifically, while the intact model engaged in complex interactions closely resembling those obtained in empirical studies, it displayed reduced PCI values across all local manipulations. This approach also revealed the heterogeneous impact of different local manipulations on network alterations, emphasizing the importance of posterior hubs in sustaining brain complexity. This work marks an initial stride toward a comprehensive exploration of the mechanisms underlying the loss and recovery of brain complexity across different conditions.

Multimodal diagnosis model of Alzheimer’s disease based on improved Transformer

PurposeRecent technological advancements in data acquisition tools allowed neuroscientists to acquire different modality data to diagnosis Alzheimer’s disease (AD). However, how to fuse these enormous amount different modality data to improve recognizing rate and find significance brain regions is still challenging.MethodsThe algorithm used multimodal medical images [structural magnetic resonance imaging (sMRI) and positron emission tomography (PET)] as experimental data. Deep feature representations of sMRI and PET images are extracted by 3D convolution neural network (3DCNN). An improved Transformer is then used to progressively learn global correlation information among features. Finally, the information from different modalities is fused for identification. A model-based visualization method is used to explain the decisions of the model and identify brain regions related to AD.ResultsThe model attained a noteworthy classification accuracy of 98.1% for Alzheimer’s disease (AD) using the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. Upon examining the visualization results, distinct brain regions associated with AD diagnosis were observed across different image modalities. Notably, the left parahippocampal region emerged consistently as a prominent and significant brain area.ConclusionsA large number of comparative experiments have been carried out for the model, and the experimental results verify the reliability of the model. In addition, the model adopts a visualization analysis method based on the characteristics of the model, which improves the interpretability of the model. Some disease-related brain regions were found in the visualization results, which provides reliable information for AD clinical research.

Deciphering ApoE Genotype-Driven Proteomic and Lipidomic Alterations in Alzheimer's Disease Across Distinct Brain Regions.

Alzheimer's disease (AD) is a neurodegenerative disease with a complex etiology influenced by confounding factors such as genetic polymorphisms, age, sex, and race. Traditionally, AD research has not prioritized these influences, resulting in dramatically skewed cohorts such as three times the number of Apolipoprotein E (APOE) ε4-allele carriers in AD relative to healthy cohorts. Thus, the resulting molecular changes in AD have previously been complicated by the influence of apolipoprotein E disparities. To explore how apolipoprotein E polymorphism influences AD progression, 62 post-mortem patients consisting of 33 AD and 29 controls (Ctrl) were studied to balance the number of ε4-allele carriers and facilitate a molecular comparison of the apolipoprotein E genotype. Lipid and protein perturbations were assessed across AD diagnosed brains compared to Ctrl brains, ε4 allele carriers (APOE4+ for those carrying 1 or 2 ε4s and APOE4- for non-ε4 carriers), and differences in ε3ε3 and ε3ε4 Ctrl brains across two brain regions (frontal cortex (FCX) and cerebellum (CBM)). The region-specific influences of apolipoprotein E on AD mechanisms showcased mitochondrial dysfunction and cell proteostasis at the core of AD pathophysiology in the post-mortem brains, indicating these two processes may be influenced by genotypic differences and brain morphology.