Human Brain Mapping最新文献

{"title":"Flexible Reconfigurations of Brain Networks During Decisions With Predefined Versus Self-Generated Options","authors":"Qianying Wu,&nbsp;Zhihao Zhang,&nbsp;Ming Hsu,&nbsp;Andrew S. Kayser","doi":"10.1002/hbm.70351","DOIUrl":"https://doi.org/10.1002/hbm.70351","url":null,"abstract":"<p>How do large-scale brain networks dynamically reorganize to support different types of decision-making with distinct yet overlapping cognitive demands? While we often make decisions by evaluating and choosing from a set of externally defined choice options, we can also generate options internally from our existing knowledge store. Such flexibility suggests the ability for decision-related brain networks to reconfigure in response to the need to recruit sensory processing and semantic retrieval modules to evaluate externally and internally generated options, respectively. Here we sought to test this hypothesis by applying graph-theoretic tools to functional neuroimaging data obtained for (i) decisions with externally provided options (external-menu choices/EMC); (ii) decisions with self-generated options (internal-menu choices/IMC); and (ii) a semantic fluency condition in which individuals generated but were not required to evaluate options (semantic fluency; SF). Using categorical multi-slice community detection, we found that variations in cognitive demands across the tasks were associated with distinct reconfigurations of hierarchically organized modular brain networks. Specifically, global network organization that differed primarily along the dimension of external visual/sensory input distinguished EMC from both of the internally oriented tasks (IMC and SF). At submodular levels, IMC was distinguished from SF by stronger interactions between presumptive semantic retrieval and valuation networks hypothesized to support the generation and evaluation of choice options. These findings are consistent with a hierarchical architecture in which modules at multiple levels interact to support adaptive decision-making.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 14","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70351","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038464","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":"Trauma Timing and Its Impact on Brain Activation During Flexible Emotion Regulation in PTSD: Insights From Functional MRI","authors":"Sijun Liu,&nbsp;Yunxiao Guo,&nbsp;Wei Liu,&nbsp;Yuyi Zhang,&nbsp;Junrong Zhao,&nbsp;Yinong Liu,&nbsp;Lianzhong Liu,&nbsp;Zhihong Ren","doi":"10.1002/hbm.70346","DOIUrl":"https://doi.org/10.1002/hbm.70346","url":null,"abstract":"<p>Patients with Post-Traumatic Stress Disorder (PTSD) exhibit deficits in flexible emotion regulation and display abnormal brain activation patterns. Previous research has not examined how the age at which trauma occurs influences associated behavioral and neural abnormalities. In this study, 76 adult participants (60.5% women) diagnosed with PTSD were categorized into three age-matched groups based on the age at trauma onset: childhood, adolescence, and adulthood. Forty-five healthy adults served as a control group. All participants engaged in the Shifted Attention Emotion Appraisal Task (SEAT) while undergoing functional magnetic resonance imaging (fMRI). Our findings reveal that both the childhood and adulthood trauma groups showed significantly greater activation in the left thalamus, left frontal gyrus, and Brodmann Area 48 compared to the adolescent trauma group. Additionally, the childhood trauma group exhibited higher activation in the left inferior frontal gyrus than the adolescent group and greater activation in the left pregenual anterior cingulate cortex compared to the adulthood trauma group. These results highlight the critical role of trauma timing in understanding the behavioral and neural dimensions of PTSD, offering new insights for clinical intervention and treatment strategies.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 14","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70346","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038465","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":"The Role of Deep Cerebral Tracts in Predicting Postoperative Aphasia: An nTMS-Based Investigation of the Corticothalamic Fibers","authors":"Zixu Bao,&nbsp;Haosu Zhang,&nbsp;Maximilian Schwendner,&nbsp;Axel Schröder,&nbsp;Bernhard Meyer,&nbsp;Sandro M. Krieg,&nbsp;Sebastian Ille","doi":"10.1002/hbm.70344","DOIUrl":"10.1002/hbm.70344","url":null,"abstract":"<p>Postoperative aphasia (POA) is a common complication in patients undergoing surgery for language-eloquent lesions. This study aimed to enhance the prediction of POA by leveraging preoperative navigated transcranial magnetic stimulation (nTMS) language mapping and diffusion tensor imaging (DTI)-based tractography, incorporating deep learning (DL) algorithms. One hundred patients with left-hemispheric lesions were retrospectively enrolled (43 developed postoperative aphasia, as the POA group; 57 did not, as the non-aphasia (NA) group). Fiber tracking was performed at fractional anisotropy threshold (FAthres) of 0.10 and 0.15, analyzing the total fiber volume (Vfiber_total), average fractional anisotropy (FA_whole), and number of visualized tracts. Additionally, the visualization ratio (VR) and FA-sensitive visualization were assessed for individual tractography. The NA group demonstrated significantly higher Vfiber_total (FAthres = 0.10: 61.1 vs. 51.7 cm³, <i>p</i> = 0.029; FAthres = 0.15: 36.9 vs. 29.6 cm³, <i>p</i> = 0.008), higher FA_whole (FAthres = 0.10: 0.38 vs. 0.35, <i>p</i> = 0.006; FAthres = 0.15: 0.42 vs. 0.39, <i>p</i> = 0.006), and greater tract numbers (FAthres = 0.10: 6.1 vs. 5.7, <i>p</i> = 0.111; FAthres = 0.15: 5.6 vs. 4.8, <i>p</i> = 0.004). Among individual fiber tracts, the corticothalamic fibers (CtF) showed significantly higher VR in the NA group (86.0% vs. 58.1%, <i>p</i> = 0.003), whereas FA-sensitive visualization of CtF was higher in the POA group (11.6% vs. 0.0%, <i>p</i> = 0.013). A binary DL model developed to predict POA achieved a sensitivity of 72.3% and specificity of 85.3%, with an area underthecurve (AUC) of 0.82. Our findings demonstrate the potential of nTMS-based tractography to predict POA by integrating DL. The CtF showed the most significant potential in predicting aphasia risk and understanding the complexity of the language network, whereas their individual predictive contribution within the model remained limited.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 13","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70344","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145033223","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":"Neuroimaging Data Informed Mood and Psychosis Diagnosis Using an Ensemble Deep Multimodal Framework","authors":"Hooman Rokham,&nbsp;Haleh Falakshahi,&nbsp;Godfrey D. Pearlson,&nbsp;Vince D. Calhoun","doi":"10.1002/hbm.70347","DOIUrl":"https://doi.org/10.1002/hbm.70347","url":null,"abstract":"<p>Investigating neuroimaging data to identify brain-based markers of mental illnesses has gained significant attention. Nevertheless, these endeavors encounter challenges arising from a reliance on symptoms and self-report assessments in making an initial diagnosis. The absence of biological data to delineate nosological categories hinders the provision of additional neurobiological insights into these disorders. This study explores the use of neuroimaging to identify brain-based markers for mental illnesses, addressing the limitations of existing diagnoses. Previous research showed the potential of integrating structural neuroimaging data by treating diagnostic categories as uncertain and adjusting them to align better with biological data. Building on this, our current research incorporates multimodal neuroimaging data, combining fMRI with structural MRI, and introduces methodological advances to enhance diagnosis by creating more homogeneous categories based on MRI-derived neurobiological information. Unlike other studies that reclassify psychiatric groups purely based on biological data, our approach integrates neuroimaging and symptom-based categories using ensemble methods, deep learning, and data fusion. This strategy aims to improve symptom-based categorization by identifying biologically-based categories that help distinguish between correctly classified, challenging, and noisy samples. Our goals include identifying potential biomarkers for existing symptom-based categories, determining biologically homogeneous groups, and mitigating label noise across mood and psychosis categories. We analyzed the relationship between biological findings and existing categories, highlighting discrepancies between brain imaging features and symptom-based categories, and assessing the potential of augmenting label categories for sample heterogeneity. Notably, visualization techniques provided insights into distinct brain patterns in well-classified versus challenging samples. We used a deep convolutional framework and bagging approaches for diagnostic classification, finding that ensemble deep models outperformed individual models, and multimodal frameworks consistently surpassed unimodal approaches. In sum, this work highlights the potential of combining existing symptom-based categorization with multimodal data and advanced data-driven approaches to improve the categorization of mental illness.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 13","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70347","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145022125","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":"Voxel Volume Overlap: Voxel-Size Sensitive Indicators of Subject Motion in Functional MRI","authors":"Marko Wilke","doi":"10.1002/hbm.70337","DOIUrl":"https://doi.org/10.1002/hbm.70337","url":null,"abstract":"<p>Subject motion is a significant problem for the analysis of functional MRI data and is usually described by “total displacement” or “scan-to-scan displacement”. Neither parameter, however, takes into account voxel size, which clearly is relevant for the actual effects of motion on the data. Consequently, it is hitherto impossible to compare motion between subjects/studies acquired using different voxel dimensions, precluding the development of generally applicable recommendations for fMRI quality control procedures. Here, a new set of “voxel volume overlap” (VVO) parameters is developed and explored, assessing the actual volumetric effects of subject motion on the voxel-level. Further, the extent of out-of-plane movement (particularly detrimental to image quality) can be quantified. Analyses show the new parameters to be valid and sensitive to voxel sizes. Their relation to existing parameters is explored, and defaults are suggested. The algorithm is freely available as a toolbox for a common image processing software solution (SPM).</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 13","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70337","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145011961","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":"Functional Connectivity of Hippocampal Circuits and Visual Memory Function in Children and Adolescents With Perinatal Stroke","authors":"Armaan Dhanoa,&nbsp;Nomazulu Dlamini,&nbsp;John Andersen,&nbsp;Darcy Fehlings,&nbsp;Adam Kirton,&nbsp;Helen L. Carlson","doi":"10.1002/hbm.70342","DOIUrl":"https://doi.org/10.1002/hbm.70342","url":null,"abstract":"<p>Perinatal stroke is a vascular injury occurring early in life, often resulting in motor deficits (hemiplegic cerebral palsy/HCP). Comorbidities may also include poor neuropsychological outcomes, such as deficits in memory. Previous studies have used resting state functional MRI (fMRI) to demonstrate that functional connectivity (FC) within hippocampal circuits is associated with memory function in typically developing controls (TDC) and in adults after stroke, but this is unexplored in perinatal stroke. Investigating links with visual memory function has the potential to inform prognosis and personalized cognitive rehabilitation strategies. This study aimed to quantify FC within hippocampal circuits of children and adolescents with perinatal stroke and associations with visual memory. We hypothesized that FC would differ between participant groups (AIS, PVI, TDC) and hemispheres (left vs. right stroke), and would correlate with visual memory function. Participants aged 6–19 years with HCP and MRI-confirmed unilateral perinatal stroke (<i>n</i> = 30) arterial ischemic stroke (AIS), <i>n</i> = 38 periventricular venous infarction (PVI) were recruited through the Alberta Perinatal Stroke Project and compared to <i>n</i> = 43 TDC. Resting fMRI volumes (150 volumes, TR/TE = 2000/30 ms, voxels 3.6 mm isotropic, 36 axial slices) were processed to compute FC values between memory-related seeds (including bilateral hippocampi) using a standard pipeline in the CONN toolbox. Seed-to-voxel and seed-to-seed analyses computed FC with each hippocampus. Hemispheric and group differences in FC were examined. A subset of stroke participants (<i>n</i> = 46) completed visual memory testing via CNS Vital Signs (CNSVS), a computerized neurocognitive test battery. Partial correlations assessed associations between FC and visual memory function, factoring out age. We found hemispheric differences in FC within each group. Participants with left perinatal stroke showed greater FC between the hippocampus and lateral prefrontal cortex in the lesioned compared to non-lesioned hemisphere. TDCs had higher hippocampal FC when compared to the lesioned hemisphere of stroke groups. For participants with right hemisphere stroke, associations were observed between hippocampal FC and visual memory function. We describe differences in bilateral hippocampal functional connectivity in children and adolescents with perinatal stroke that are associated with visual memory function. Our findings suggest that developmental plasticity may occur in the non-lesioned hippocampus after perinatal stroke. These findings may inform our understanding of how visual memory function is affected after early unilateral brain injury and facilitate the development of novel therapies for individuals affected by perinatal stroke.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 13","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70342","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145007948","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":"Maturational Changes in Action-Effect Integration Processes Are Reflected by Changes in the Directed Cortical Network Communication","authors":"Jasmin Mayer,&nbsp;Moritz Mückschel,&nbsp;Bernhard Hommel,&nbsp;Christian Beste","doi":"10.1002/hbm.70339","DOIUrl":"https://doi.org/10.1002/hbm.70339","url":null,"abstract":"<p>Acting intentionally is a major aspect of human cognitive development and depends on the ability to link actions with their consequences. Action-effect binding (AEB) is a fundamental mechanism enabling this. While AEB has been well-characterized in adults, its neurophysiological underpinnings during adolescence remain unclear. This study investigates differences between adolescence and adulthood in the directed cortical network communication underlying AEB. Using an EEG frequency tagging approach, we examined differences in theta-driven directed connectivity between adolescents and adults. Our findings reveal that both groups engage a core network comprising the insular cortex, anterior temporal lobe, and inferior frontal cortex. However, adolescents exhibit stronger directed connectivity within this network, particularly in anterior temporal lobe-mediated interactions, suggesting a greater reliance on representational processing for action-effect integration. Furthermore, adolescents uniquely recruit posterior ventral stream regions, including the lingual gyrus. This additional involvement suggests an increased demand for sensory integration in adolescents, potentially compensating for immaturities in action-effect representation. These results indicate that while the essential neural architecture for AEB is established in adolescence, its functional organization differs from that of adults. This study provides novel insights into developmental changes in cortical network communication underlying intentional action control.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 13","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70339","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145007949","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":"Reciprocal Predictions Between Reading Achievement and Cognitive Flexibility Development in Children and the Mediating Roles of the Left Middle Frontal Gyrus","authors":"Leilei Ma,&nbsp;Yanpei Wang,&nbsp;Jiali Wang,&nbsp;Rui Chen,&nbsp;Gai Zhao,&nbsp;Zhiying Pan,&nbsp;Ningyu Liu,&nbsp;Haibo Zhang,&nbsp;Weiwei Men,&nbsp;Shuping Tan,&nbsp;Jia-Hong Gao,&nbsp;Shaozheng Qin,&nbsp;Yong He,&nbsp;Qi Dong,&nbsp;Sha Tao","doi":"10.1002/hbm.70309","DOIUrl":"https://doi.org/10.1002/hbm.70309","url":null,"abstract":"<p>The development of reading skills and cognitive flexibility is crucial for success in childhood and adulthood. Although previous studies demonstrate the existing links between the development of cognitive flexibility and the reading acquisition in children, it remains unclear how baseline reading achievement influences later cognitive flexibility, or vice versa, particularly in relation to the underlying brain development. Therefore, in this prospective longitudinal study, we investigated the reciprocal prediction between reading achievement and cognitive flexibility, along with the underlying brain development that potentially mediated this relationship in school-aged children. By employing a self-recruited longitudinal dataset with two time points spaced 12 months apart, we found a significant association between baseline reading achievement and later cognitive flexibility, as well as between baseline cognitive flexibility and later reading achievement. Moreover, the left middle frontal gyrus emerged as a central neural hub supporting the development of both abilities. Increases in its gray matter volume and enhanced its functional connectivity to the salience network significantly mediated the longitudinal associations between reading achievement and cognitive flexibility. Taken together, our findings demonstrate the vital role of the left middle frontal gyrus in integrating language information processing and higher-order cognitive control. This provides evidence for future reading or cognitive interventions.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 13","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70309","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998701","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 Practical Guide to Identifying Robust Clusters in Neuroimaging Data","authors":"Johan Nakuci,&nbsp;Dobromir Rahnev","doi":"10.1002/hbm.70330","DOIUrl":"https://doi.org/10.1002/hbm.70330","url":null,"abstract":"<p>Clustering algorithms are essential tools in data-driven research, enabling the discovery of hidden structures in complex datasets. In neuroimaging, data-driven research and clustering have been instrumental in identifying and unraveling hidden relationships. However, there are concerns associated with exploratory techniques in that they can provide erroneous results unless properly verified. Here we address this issue by examining three widely used approaches: K-means, community detection via modularity maximization, and hierarchical clustering. We first highlight their methodologies, applications, and limitations. We then discuss the critical steps for rigorous validation strategies. We further show how to apply these steps using both synthetic and real data, and provide code to facilitate their application. By contextualizing clustering within robust methodological frameworks, we demonstrate the potential of clustering-based analyses to reveal meaningful patterns and provide practical guidelines for their application in neuroscience and related fields. Clustering, when appropriately applied, is a powerful and indispensable computational method.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 13","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70330","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144929889","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":"Lifespan Tree of Brain Anatomy: Diagnostic Values for Motor and Cognitive Neurodegenerative Diseases","authors":"Pierrick Coupé,&nbsp;Boris Mansencal,&nbsp;José V. Manjón,&nbsp;Patrice Péran,&nbsp;Wassilios G. Meissner,&nbsp;Thomas Tourdias,&nbsp;Vincent Planche","doi":"10.1002/hbm.70336","DOIUrl":"https://doi.org/10.1002/hbm.70336","url":null,"abstract":"<p>The differential diagnosis of neurodegenerative diseases, characterized by overlapping symptoms, may be challenging. Brain imaging coupled with artificial intelligence has been previously proposed for diagnostic support, but most of these methods have been trained to discriminate only isolated diseases from controls. Here, we develop a novel machine learning framework, named <i>lifespan tree</i> of brain anatomy, dedicated to the differential diagnosis between multiple diseases simultaneously. It integrates the modeling of volume changes for 124 brain structures during the lifespan with nonlinear dimensionality reduction and synthetic sampling techniques to create easily interpretable representations of brain anatomy over the course of disease progression. As clinically relevant proof-of-concept applications, we constructed a <i>cognitive lifespan tree</i> of brain anatomy for the differential diagnosis of six causes of neurodegenerative dementia and a <i>motor lifespan tree</i> of brain anatomy for the differential diagnosis of four causes of parkinsonism using 37,594 MRIs as a training dataset. This original approach significantly enhanced the efficiency of differential diagnosis in the external validation cohort of 1754 cases, outperforming existing state-of-the-art machine learning techniques. <i>Lifespan tree</i> holds promise as a valuable tool for differential diagnosis in relevant clinical conditions, especially for diseases still lacking effective biological markers.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 13","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70336","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923485","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}