Cerebral cortex最新文献

{"title":"Uncovering neural substrates across Alzheimer's disease stages using contrastive variational autoencoder.","authors":"Yan Tang, Chao Yang, Yuqi Wang, Yunhao Zhang, Jiang Xin, Hao Zhang, Hua Xie","doi":"10.1093/cercor/bhae393","DOIUrl":"https://doi.org/10.1093/cercor/bhae393","url":null,"abstract":"<p><p>Alzheimer's disease is the most common major neurocognitive disorder. Although currently, no cure exists, understanding the neurobiological substrate underlying Alzheimer's disease progression will facilitate early diagnosis and treatment, slow disease progression, and improve prognosis. In this study, we aimed to understand the morphological changes underlying Alzheimer's disease progression using structural magnetic resonance imaging data from cognitively normal individuals, individuals with mild cognitive impairment, and Alzheimer's disease via a contrastive variational autoencoder model. We used contrastive variational autoencoder to generate synthetic data to boost the downstream classification performance. Due to the ability to parse out the nonclinical factors such as age and gender, contrastive variational autoencoder facilitated a purer comparison between different Alzheimer's disease stages to identify the pathological changes specific to Alzheimer's disease progression. We showed that brain morphological changes across Alzheimer's disease stages were significantly associated with individuals' neurofilament light chain concentration, a potential biomarker for Alzheimer's disease, highlighting the biological plausibility of our results.</p>","PeriodicalId":9715,"journal":{"name":"Cerebral cortex","volume":"34 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142371066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multilayer network analysis reveals instability of brain dynamics in untreated first-episode schizophrenia.","authors":"Ziyang Gao, Yuan Xiao, Fei Zhu, Bo Tao, Qiannan Zhao, Wei Yu, John A Sweeney, Qiyong Gong, Su Lui","doi":"10.1093/cercor/bhae402","DOIUrl":"https://doi.org/10.1093/cercor/bhae402","url":null,"abstract":"<p><p>Although aberrant static functional brain network activity has been reported in schizophrenia, little is known about how the dynamics of neural function are altered in first-episode schizophrenia and are modulated by antipsychotic treatment. The baseline resting-state functional magnetic resonance imaging data were acquired from 122 first-episode drug-naïve schizophrenia patients and 128 healthy controls (HCs), and 44 patients were rescanned after 1-year of antipsychotic treatment. Multilayer network analysis was applied to calculate the network switching rates between brain states. Compared to HCs, schizophrenia patients at baseline showed significantly increased network switching rates. This effect was observed mainly in the sensorimotor (SMN) and dorsal attention networks (DAN), and in temporal and parietal regions at the nodal level. Switching rates were reduced after 1-year of antipsychotic treatment at the global level and in DAN. Switching rates at baseline at the global level and in the inferior parietal lobule were correlated with the treatment-related reduction of negative symptoms. These findings suggest that instability of functional network activity plays an important role in the pathophysiology of acute psychosis in early-stage schizophrenia. The normalization of network stability after antipsychotic medication suggests that this effect may represent a systems-level mechanism for their therapeutic efficacy.</p>","PeriodicalId":9715,"journal":{"name":"Cerebral cortex","volume":"34 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142388353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-intensity transcranial ultrasound stimulation modulates neurovascular coupling in mouse models of Alzheimer's disease.","authors":"Xin Li, Qiaoxuan Wang, Mengran Wang, Zhenfang Ma, Yi Yuan","doi":"10.1093/cercor/bhae413","DOIUrl":"https://doi.org/10.1093/cercor/bhae413","url":null,"abstract":"<p><p>Neurovascular coupling plays an important role in the progression of Alzheimer's disease. However, it is unclear how ultrasound stimulation modulates neurovascular coupling in Alzheimer's disease. Here, we found that (i) transcranial ultrasound stimulation modulates the time domain and frequency domain characteristics of cerebral blood oxygen metabolism in Alzheimer's disease mice; (ii) transcranial ultrasound stimulation can significantly modulate the relative power of theta and gamma frequency of local field potential in Alzheimer's disease mice; and (iii) transcranial ultrasound stimulation can significantly modulate the neurovascular coupling in time domain and frequency domain induced by forepaw electrical stimulation in Alzheimer's disease mice. It provides a research basis for the clinical application of transcranial ultrasound stimulation in Alzheimer's disease patients.</p>","PeriodicalId":9715,"journal":{"name":"Cerebral cortex","volume":"34 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142406166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Memory-related brain potentials for visual objects in early AD show impairment and compensatory mechanisms.","authors":"Jiangyi Xia, Marta Kutas, David P Salmon, Anna M Stoermann, Siena N Rigatuso, Sarah E Tomaszewski Farias, Steven D Edland, James B Brewer, John M Olichney","doi":"10.1093/cercor/bhae398","DOIUrl":"https://doi.org/10.1093/cercor/bhae398","url":null,"abstract":"<p><p>Impaired episodic memory is the primary feature of early Alzheimer's disease (AD), but not all memories are equally affected. Patients with AD and amnestic Mild Cognitive Impairment (aMCI) remember pictures better than words, to a greater extent than healthy elderly. We investigated neural mechanisms for visual object recognition in 30 patients (14 AD, 16 aMCI) and 36 cognitively unimpaired healthy (19 in the \"preclinical\" stage of AD). Event-related brain potentials (ERPs) were recorded while participants performed a visual object recognition task. Hippocampal occupancy (integrity), amyloid (florbetapir) PET, and neuropsychological measures of verbal & visual memory, executive function were also collected. A right-frontal ERP recognition effect (500-700 ms post-stimulus) was seen in cognitively unimpaired participants only, and significantly correlated with memory and executive function abilities. A later right-posterior negative ERP effect (700-900 ms) correlated with visual memory abilities across participants with low verbal memory ability, and may reflect a compensatory mechanism. A correlation of this retrieval-related negativity with right hippocampal occupancy (r = 0.55), implicates the hippocampus in the engagement of compensatory perceptual retrieval mechanisms. Our results suggest that early AD patients are impaired in goal-directed retrieval processing, but may engage compensatory perceptual mechanisms which rely on hippocampal function.</p>","PeriodicalId":9715,"journal":{"name":"Cerebral cortex","volume":"34 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142399509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neural representations of beat and rhythm in motor and association regions.","authors":"Joshua D Hoddinott, Jessica A Grahn","doi":"10.1093/cercor/bhae406","DOIUrl":"10.1093/cercor/bhae406","url":null,"abstract":"<p><p>Humans perceive a pulse, or beat, underlying musical rhythm. Beat strength correlates with activity in the basal ganglia and supplementary motor area, suggesting these regions support beat perception. However, the basal ganglia and supplementary motor area are part of a general rhythm and timing network (regardless of the beat) and may also represent basic rhythmic features (e.g. tempo, number of onsets). To characterize the encoding of beat-related and other basic rhythmic features, we used representational similarity analysis. During functional magnetic resonance imaging, participants heard 12 rhythms-4 strong-beat, 4 weak-beat, and 4 nonbeat. Multi-voxel activity patterns for each rhythm were tested to determine which brain areas were beat-sensitive: those in which activity patterns showed greater dissimilarities between rhythms of different beat strength than between rhythms of similar beat strength. Indeed, putamen and supplementary motor area activity patterns were significantly dissimilar for strong-beat and nonbeat conditions. Next, we tested whether basic rhythmic features or models of beat strength (counterevidence scores) predicted activity patterns. We found again that activity pattern dissimilarity in supplementary motor area and putamen correlated with beat strength models, not basic features. Beat strength models also correlated with activity pattern dissimilarities in the inferior frontal gyrus and inferior parietal lobe, though these regions encoded beat and rhythm simultaneously and were not driven by beat alone.</p>","PeriodicalId":9715,"journal":{"name":"Cerebral cortex","volume":"34 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11466846/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142399510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A network analysis of affective and motivational individual differences and error monitoring in a non-clinical sample.","authors":"Anna Grabowska, Filip Sondej, Magdalena Senderecka","doi":"10.1093/cercor/bhae397","DOIUrl":"10.1093/cercor/bhae397","url":null,"abstract":"<p><p>Error monitoring, which plays a crucial role in shaping adaptive behavior, is influenced by a complex interplay of affective and motivational factors. Understanding these associations often proves challenging due to the intricate nature of these variables. With the aim of addressing previous inconsistencies and methodological gaps, in this study, we utilized network analysis to investigate the relationship between affective and motivational individual differences and error monitoring. We employed six Gaussian Graphical Models on a non-clinical population ($N$ = 236) to examine the conditional dependence between the amplitude of response-related potentials (error-related negativity; correct-related negativity) and 29 self-report measures related to anxiety, depression, obsessive thoughts, compulsive behavior, and motivation while adjusting for covariates: age, handedness, and latency of error-related negativity and correct-related negativity. We then validated our results on an independent sample of 107 participants. Our findings revealed unique associations between error-related negativity amplitudes and specific traits. Notably, more pronounced error-related negativity amplitudes were associated with increased rumination and obsessing, and decreased reward sensitivity. Importantly, in our non-clinical sample, error-related negativity was not directly associated with trait anxiety. These results underscore the nuanced effects of affective and motivational traits on error processing in healthy population.</p>","PeriodicalId":9715,"journal":{"name":"Cerebral cortex","volume":"34 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11513196/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142495876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disentangling gray matter atrophy and its neurotransmitter architecture in drug-naïve Parkinson's disease: an atlas-based correlation analysis.","authors":"Huize Pang, Xiaolu Li, Ziyang Yu, Hongmei Yu, Shuting Bu, Juzhou Wang, Mengwan Zhao, Yu Liu, Yueluan Jiang, Guoguang Fan","doi":"10.1093/cercor/bhae420","DOIUrl":"https://doi.org/10.1093/cercor/bhae420","url":null,"abstract":"<p><p>Parkinson's disease is characterized by multiple neurotransmitter systems beyond the traditional dopaminergic pathway, yet their influence on volumetric alterations is not well comprehended. We included 72 de novo, drug-naïve Parkinson's disease patients and 61 healthy controls. Voxel-wise gray matter volume was evaluated between Parkinson's disease and healthy controls, as well as among Parkinson's disease subgroups categorized by clinical manifestations. The Juspace toolbox was utilized to explore the spatial relationship between gray matter atrophy and neurotransmitter distribution. Parkinson's disease patients exhibited widespread GM atrophy in the cerebral and cerebellar regions, with spatial correlations with various neurotransmitter receptors (FDR-P < 0.05). Cognitively impaired Parkinson's disease patients showed gray matter atrophy in the left middle temporal atrophy, which is associated with serotoninergic, dopaminergic, cholinergic, and glutamatergic receptors (FDR-P < 0.05). Postural and gait disorder patients showed atrophy in the right precuneus, which is correlated with serotoninergic, dopaminergic, gamma-aminobutyric acid, and opioid receptors (FDR-P < 0.05). Patients with anxiety showed atrophy in the right superior orbital frontal region; those with depression showed atrophy in the left lingual and right inferior occipital regions. Both conditions were linked to serotoninergic and dopaminergic receptors (FDR-P < 0.05). Parkinson's disease patients exhibited regional gray matter atrophy with a significant distribution of specific neurotransmitters, which might provide insights into the underlying pathophysiology of clinical manifestations and develop targeted intervention strategies.</p>","PeriodicalId":9715,"journal":{"name":"Cerebral cortex","volume":"34 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142458933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"REVEALS: an open-source multi-camera GUI for rodent behavior acquisition.","authors":"Rhushikesh A Phadke, Austin M Wetzel, Luke A Fournier, Alison Brack, Mingqi Sha, Nicole M Padró-Luna, Ryan Williamson, Jeff Demas, Alberto Cruz-Martín","doi":"10.1093/cercor/bhae421","DOIUrl":"10.1093/cercor/bhae421","url":null,"abstract":"<p><p>Deciphering the rich repertoire of mouse behavior is crucial for understanding the functions of both the healthy and diseased brain. However, the current landscape lacks effective, affordable, and accessible methods for acquiring such data, especially when employing multiple cameras simultaneously. We have developed REVEALS (Rodent Behavior Multi-Camera Laboratory Acquisition), a graphical user interface for acquiring rodent behavioral data via commonly used USB3 cameras. REVEALS allows for user-friendly control of recording from one or multiple cameras simultaneously while streamlining the data acquisition process, enabling researchers to collect and analyze large datasets efficiently. We release this software package as a stand-alone, open-source framework for researchers to use and modify according to their needs. We describe the details of the graphical user interface implementation, including the camera control software and the video recording functionality. We validate results demonstrating the graphical user interface's stability, reliability, and accuracy for capturing rodent behavior using DeepLabCut in various behavioral tasks. REVEALS can be incorporated into existing DeepLabCut, MoSeq, or other custom pipelines to analyze complex behavior. In summary, REVEALS offers an interface for collecting behavioral data from single or multiple perspectives, which, when combined with deep learning algorithms, enables the scientific community to identify and characterize complex behavioral phenotypes.</p>","PeriodicalId":9715,"journal":{"name":"Cerebral cortex","volume":"34 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11486610/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142458936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intrinsic functional networks for distinct sources of error in visual working memory.","authors":"Xuqian Li, Lena K L Oestreich, Dragan Rangelov, Delphine Lévy-Bencheton, Michael J O'Sullivan","doi":"10.1093/cercor/bhae401","DOIUrl":"10.1093/cercor/bhae401","url":null,"abstract":"<p><p>Visual working memory (VWM) is a core cognitive function wherein visual information is stored and manipulated over short periods. Response errors in VWM tasks arise from the imprecise memory of target items, swaps between targets and nontargets, and random guesses. However, it remains unclear whether these types of errors are underpinned by distinct neural networks. To answer this question, we recruited 80 healthy adults to perform delayed estimation tasks and acquired their resting-state functional magnetic resonance imaging scans. The tasks required participants to reproduce the memorized visual feature along continuous scales, which, combined with mixture distribution modeling, allowed us to estimate the measures of memory precision, swap errors, and random guesses. Intrinsic functional connectivity within and between different networks, identified using a hierarchical clustering approach, was estimated for each participant. Our analyses revealed that higher memory precision was associated with increased connectivity within a frontal-opercular network, as well as between the dorsal attention network and an angular-gyrus-cerebellar network. We also found that coupling between the frontoparietal control network and the cingulo-opercular network contributes to both memory precision and random guesses. Our findings demonstrate that distinct sources of variability in VWM performance are underpinned by different yet partially overlapping intrinsic functional networks.</p>","PeriodicalId":9715,"journal":{"name":"Cerebral cortex","volume":"34 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11464681/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142388352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal association of depressive symptoms with cognition and neuroimaging biomarkers in cognitively unimpaired older adults, mild cognitive impairment, and Alzheimer's disease.","authors":"Ying Hu, Ting Zhu, Minlan Yuan, Hongru Zhu, Wei Zhang","doi":"10.1093/cercor/bhae423","DOIUrl":"https://doi.org/10.1093/cercor/bhae423","url":null,"abstract":"<p><p>We aimed to longitudinally examine the relationship between depression and cognitive function and investigate the mediating effects of imaging indicators in this relationship. 2,251 subjects with longitudinal assessment of geriatric depression scale, Mini-Mental State Examination, Montreal Cognitive Assessment, Clinical Dementia Rating-Sum of Boxes (CDRSB), Alzheimer's Disease Assessment Scale11, Alzheimer's Disease Assessment Scale13 and imaging of 3DT1, diffusion tensor imaging, fluid-attenuated inversion recovery, arterial spin labeling, fluorodeoxyglucose positron emission tomography, 18F-AV45-PET, and 18F-AV1451-PET were included from the Alzheimer's Disease Neuroimaging Initiative database. The multivariate mixed-effects models were employed to analyze the correlation between geriatric depression scale scores, cognitive function, and imaging indicators. The sgmediation software package was utilized to analyze the mediating effects of imaging indicators. The geriatric depression scale was negatively correlated with Mini-Mental State Examination and Montreal Cognitive Assessment, and positively correlated with CDRSB, Alzheimer's Disease Assessment Scale11, and Alzheimer's Disease Assessment Scale13 when the subjects were not grouped. The geriatric depression scale was negatively correlated with Montreal Cognitive Assessment and positively correlated with Alzheimer's Disease Assessment Scal13 in groups with baseline diagnosis of early mild cognitive impairment and late mild cognitive impairment. Furthermore, depression was associated with regional imaging indicators, while cognitive function was linked to broad imaging indicators. Some of these indicators were related to both depression and cognitive function, playing a mediating role in their relationship. Depression was related to cognitive function, especially in subjects with mild cognitive impairment. Some imaging indicators may represent the underlying basis for the association between depression and cognitive function.</p>","PeriodicalId":9715,"journal":{"name":"Cerebral cortex","volume":"34 10","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142495878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}