Human Brain Mapping最新文献

{"title":"Morphometric Evidence of a U-Shaped Relationship Between Loss Aversion and Posterior Insular/Somatosensory Cortical Features","authors":"Maria Arioli,&nbsp;Letizia Richelli,&nbsp;Giulia Mattavelli,&nbsp;Zaira Cattaneo,&nbsp;Paolo Poggi,&nbsp;Nicola Canessa","doi":"10.1002/hbm.70274","DOIUrl":"https://doi.org/10.1002/hbm.70274","url":null,"abstract":"<p>Neuroeconomic findings show that interoceptive sensitivity contributes to the typical overweighting of prospective losses over gains known as “loss aversion.” Whether the latter is related to the morphometric properties of the insula—a key node for interoception—remains, however, debated, due to previous conflicting evidence of both positive and negative correlations between their respective metrics. We combined a well-established behavioral modeling approach with a comprehensive morphometric protocol to explore both a linear and quadratic relationship between loss aversion and distinct voxel-based and surface-based cortical features in a sample of 208 healthy young individuals. Both univariate and multivariate analyses highlighted a positive quadratic (i.e., U-shaped) relationship between loss aversion and distinct morphometric features of the posterior insula and somatosensory-parietal cortex. These results first suggest that previous inconsistent findings might reflect methodological differences across studies, facilitating the detection of either the descending or ascending sectors of a U-shaped relationship between loss aversion and structural features. Moreover, they provide novel insights into the interoceptive modulation of choice-related evaluations guiding decision-making towards or away from loss avoidance, thus paving the way to studies investigating alterations of this mechanism in neuro-psychiatric conditions and its susceptibility to different types of intervention including neuromodulation.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70274","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144503072","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":"Accelerated Epigenetic Aging and Its Role in Brain Dynamics and Cognition in Young Adulthood","authors":"Tomáš Jordánek,&nbsp;Radek Mareček,&nbsp;Anna Pačínková,&nbsp;Lenka Andrýsková,&nbsp;Milan Brázdil,&nbsp;Klára Marečková","doi":"10.1002/hbm.70261","DOIUrl":"https://doi.org/10.1002/hbm.70261","url":null,"abstract":"<p>Accelerated epigenetic aging has been associated with changes in cognition. However, due to the lack of neuroimaging epigenetics studies, it is still unclear whether accelerated epigenetic. Aging in young adulthood might underlie the relationship between altered brain dynamics and cognitive functioning. We conducted neuroimaging epigenetics follow-up of the European Longitudinal Study of Pregnancy and Childhood (ELSPAC) prenatal birth cohort in young adulthood and tested the possible mediatory role of accelerated epigenetic aging in the relationship between dynamic functional connectivity (DFC) and worse cognition. A total of 240 young adults (51% men; 28–30 years, all of European ancestry) participated in the neuroimaging epigenetics follow-up. Buccal swabs were collected to assess DNA methylation and calculate epigenetic aging using Horvath's epigenetic clock. Full-scale IQ was assessed using the Wechsler adult intelligence scale (WAIS). Resting-state functional magnetic resonance imaging (rs-fMRI) was acquired using a 3T Siemens Prisma MRI scanner, and DFC was assessed using mixture factor analysis, revealing information about the coverage of different DFC states. In women (but not men), lower coverage of DFC state 4 and thus lower frequency of epochs with high connectivity within the default mode network and between default mode, fronto-parietal, and visual networks was associated with lower full-scale IQ (Adj<i>R</i>² = 0.05, std. beta = 0.245, <i>p</i> = 0.008). This relationship was mediated by accelerated epigenetic aging (ab = 7.660, SE = 4.829, 95% CI [0.473, 19.264]). In women, accelerated epigenetic aging in young adulthood mediates the relationship between altered brain dynamics and cognitive functioning. Prevention of cognitive decline should target women already in young adulthood.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70261","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144482063","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":"Big Data, Small Bias: Harmonizing Diffusion MRI-Based Structural Connectomes to Mitigate Site-Related Bias in Data Integration","authors":"Rui Sherry Shen,&nbsp;Drew Parker,&nbsp;Andrew An Chen,&nbsp;Benjamin E. Yerys,&nbsp;Birkan Tunç,&nbsp;Timothy P. L. Roberts,&nbsp;Russell T. Shinohara,&nbsp;Ragini Verma","doi":"10.1002/hbm.70256","DOIUrl":"https://doi.org/10.1002/hbm.70256","url":null,"abstract":"<p>Diffusion MRI-based structural connectomes are increasingly used to investigate brain connectivity changes associated with various disorders. However, small sample sizes in individual studies, along with highly heterogeneous disorder-related manifestations, underscore the need to pool datasets across multiple studies to be able to identify coherent and generalizable connectivity patterns linked to these disorders. Yet, combining datasets introduces site-related differences due to variations in scanner hardware or acquisition protocols. These differences highlight the necessity for statistical data harmonization to mitigate site-related effects on structural connectomes while preserving the biological information associated with participant demographics and the disorders. While several paradigms exist for harmonizing normally distributed neuroimaging measures, this paper represents the first effort to establish a harmonization framework specifically tailored for the structural connectome. We conduct a thorough investigation of various statistical harmonization methods, adapting them to accommodate the unique distributional characteristics and graph-based properties of structural connectomes. Through rigorous evaluation, we show that our MATCH algorithm, based on the gamma-distributed model, consistently outperforms existing approaches in modeling structural connectomes, enabling the effective removal of site-related biases in both edge-based and downstream graph analyses while preserving biological variability. Two real-world applications further highlight the utility of our harmonization framework in addressing challenges in multi-site structural connectome analysis. Specifically, harmonization with MATCH enhances the generalizability of connectome-based machine learning predictors to new datasets and increases statistical power for detecting group-level differences. Our work provides essential guidelines for harmonizing multi-site structural connectomes, paving the way for more robust discoveries through collaborative research in the era of team science and big data.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 9","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70256","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144482141","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":"Correction of Physiological Artifacts in Multi-Echo fMRI Data—Evaluation of Possible RETROICOR Implementations","authors":"Anežka Kovářová,&nbsp;Michal Mikl","doi":"10.1002/hbm.70264","DOIUrl":"https://doi.org/10.1002/hbm.70264","url":null,"abstract":"<p>The study evaluates the efficacy of RETROICOR (Retrospective Image Correction) in mitigating physiological artifacts within multi-echo (ME) fMRI data. Two RETROICOR implementations were compared: applying corrections to individual echoes (RTC_ind) versus composite multi-echo data (RTC_comp). Data from 50 healthy participants were collected using diverse acquisition parameters, including multiband acceleration factors and varying flip angles, on a Siemens Prisma 3T scanner. Key metrics such as temporal signal-to-noise ratio (tSNR), signal fluctuation sensitivity (SFS), and variance of residuals demonstrated improved data quality in both RETROICOR models, particularly in moderately accelerated runs (multiband factors 4 and 6) with lower flip angles (45°). Differences between RTC_ind and RTC_comp were minimal, suggesting both methods are viable for practical applications. While the highest acceleration (multiband factor 8) degraded data quality, RETROICOR's compatibility with faster acquisition sequences was confirmed. These findings underscore the importance of optimizing acquisition parameters and noise correction techniques for reliable fMRI investigations.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 9","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70264","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144339319","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":"Cross-Modality Image Translation of 3 Tesla Magnetic Resonance Imaging to 7 Tesla Using Generative Adversarial Networks","authors":"Eduardo Diniz,&nbsp;Tales Santini,&nbsp;Helmet Karim,&nbsp;Howard J. Aizenstein,&nbsp;Tamer S. Ibrahim","doi":"10.1002/hbm.70246","DOIUrl":"https://doi.org/10.1002/hbm.70246","url":null,"abstract":"<p>The rapid advancements in magnetic resonance imaging (MRI) technology have precipitated a new paradigm wherein cross-modality data translation across diverse imaging platforms, field strengths, and different sites is increasingly challenging. This issue is particularly accentuated when transitioning from 3 Tesla (3T) to 7 Tesla (7T) MRI systems. This study proposes a novel solution to these challenges using generative adversarial networks (GANs)—specifically, the CycleGAN architecture—to create synthetic 7T images from 3T data. Employing a dataset of 1112 and 490 unpaired 3T and 7T MR images, respectively, we trained a 2-dimensional (2D) CycleGAN model, evaluating its performance on a paired dataset of 22 participants scanned at 3T and 7T. Independent testing on 22 distinct participants affirmed the model's proficiency in accurately predicting various tissue types, encompassing cerebral spinal fluid, gray matter, and white matter. Our approach provides a reliable and efficient methodology for synthesizing 7T images, achieving a median Dice coefficient of 83.62% for cerebral spinal fluid (CSF), 81.42% for gray matter (GM), and 89.75% for White Matter (WM), while the corresponding median Percentual Area Differences (PAD) were 6.82%, 7.63%, and 4.85% for CSF, GM, and WM, respectively, in the testing dataset, thereby aiding in harmonizing heterogeneous datasets. Furthermore, it delineates the potential of GANs in amplifying the contrast-to-noise ratio (CNR) from 3T, potentially enhancing the diagnostic capability of the images. While acknowledging the risk of model overfitting, our research underscores a promising progression toward harnessing the benefits of 7T MR systems in research investigations while preserving compatibility with existing 3T MR data. This work was previously presented at the ISMRM 2021 conference.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 9","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70246","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144339111","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":"Harmonization of Structural Brain Connectivity Through Distribution Matching","authors":"Zhen Zhou,&nbsp;Bruce Fischl,&nbsp;Iman Aganj,&nbsp;for the Alzheimer's Disease Neuroimaging Initiative","doi":"10.1002/hbm.70257","DOIUrl":"https://doi.org/10.1002/hbm.70257","url":null,"abstract":"<p>The increasing prevalence of multi-site diffusion-weighted magnetic resonance imaging (dMRI) studies potentially offers enhanced statistical power to investigate brain structure. However, these studies face challenges due to variations in scanner hardware and acquisition protocols. While several methods for dMRI data harmonization exist, few specifically address structural brain connectivity. We introduce a new distribution-matching approach to harmonizing structural brain connectivity across different sites and scanners. We evaluate our method using structural brain connectivity data from three distinct datasets (OASIS-3, ADNI-2, and PREVENT-AD), comparing its performance to the widely used ComBat method and the more recent CovBat approach. We examine the impact of harmonization on the correlation of brain connectivity with the Mini-Mental State Examination score and age. Our results demonstrate that our distribution-matching technique effectively harmonizes structural brain connectivity while maintaining non-negativity of the connectivity values and produces correlation strengths and significance levels competitive with alternative approaches. Qualitative assessments illustrate the desired distributional alignment across datasets, while quantitative evaluations confirm competitive performance. This work contributes to the growing field of dMRI harmonization, potentially improving the reliability and comparability of structural connectivity studies that combine data from different sources in neuroscientific and clinical research.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 9","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70257","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144339110","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":"Cost Efficiency of fMRI Studies Using Resting-State Vs. Task-Based Functional Connectivity","authors":"Xinzhi Zhang,&nbsp;Leslie A. Hulvershorn,&nbsp;Todd Constable,&nbsp;Yize Zhao,&nbsp;Selena Wang","doi":"10.1002/hbm.70260","DOIUrl":"https://doi.org/10.1002/hbm.70260","url":null,"abstract":"<p>We investigate whether and how we can improve the cost efficiency of neuroimaging studies with well-tailored fMRI tasks. The comparative study is conducted using a novel network science-driven Bayesian connectome-based predictive method, which incorporates network theories in model building and substantially improves precision and robustness in imaging biomarker detection. The robustness of the method lays the foundation for identifying predictive power differentials across fMRI task conditions if such differences exist. When applied to a clinically heterogeneous transdiagnostic cohort, we find shared and distinct functional fingerprints of neuropsychological outcomes across seven fMRI conditions. For example, the emotional N-back memory task is found to be less optimal for negative emotion outcomes, and the gradual-onset continuous performance task is found to have stronger links with sensitivity and sociability outcomes than with cognitive control outcomes. Together, our results show that there are unique optimal pairings of task-based fMRI conditions and neuropsychological outcomes that should not be ignored when designing well-powered neuroimaging studies.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 9","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70260","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144336057","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":"Structural White Matter Correlates of the Crowding Effect: Insights From a Tractography Study of the Arcuate Fasciculus Post-Hemispherotomy","authors":"Justus Bisten,&nbsp;Johannes Grün,&nbsp;Christian Hoppe,&nbsp;Tobias Bauer,&nbsp;Nina R. Held,&nbsp;Renata Rose,&nbsp;Anita Althausen,&nbsp;Juri-Alexander Witt,&nbsp;Valeri Borger,&nbsp;Matthias Schneider,&nbsp;Hartmut Vatter,&nbsp;Christoph Helmstaedter,&nbsp;Alexander Radbruch,&nbsp;Rainer Surges,&nbsp;Thomas Schultz,&nbsp;Theodor Rüber","doi":"10.1002/hbm.70258","DOIUrl":"https://doi.org/10.1002/hbm.70258","url":null,"abstract":"&lt;p&gt;The neuropsychological crowding effect denotes the reallocation of cognitive functions within the contralesional hemisphere following unilateral brain damage, prioritizing language at the expense of nonverbal abilities. This study investigates structural white matter correlates of crowding in the arcuate fasciculus (AF), a key language tract, using hemispherotomy as a unique setting to explore structural reorganization supporting language preservation. We explore two main hypotheses. First, the contralesional right AF undergoes white matter reorganization correlated with preserved language function at the expense of nonverbal abilities following left-hemispheric damage. Second, this reorganization varies with epilepsy etiology, influencing different stages of developmental language lateralization. This retrospective study included individuals post-hemispherotomy and healthy controls. Inclusion criteria were; (1) being a native German speaker, (2) having no MRI contraindication, (3) the ability to undergo approximately 2 h of MRI scans, and (4) the ability to participate in neuropsychological assessments over two consecutive days. Neuroimaging included T1-, T2-, and diffusion-weighted imaging, alongside postoperative neuropsychological assessments, where it was taken as evidence for crowding if verbal IQ exceeded performance IQ by at least 10 points. The AF was reconstructed using advanced tractography, and CoBundleMAP was used to compare morphologically corresponding AF subsections. Statistical significance was set at &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mi&gt;p&lt;/mi&gt;\u0000 &lt;mo&gt;&lt;&lt;/mo&gt;\u0000 &lt;mn&gt;0.05&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ p&lt;0.05 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;, with correction for multiple comparisons applied across contiguous tract sections using Threshold-Free Cluster Enhancement. The final cohort comprised 22 individuals post-hemispherotomy (median age: &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;20.4&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ 20.4 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; years, range: &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;12.3&lt;/mn&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;mn&gt;43.9&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ 12.3-43.9 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;; 55% female; 55% with left-sided surgeries) and 20 healthy controls (median age: &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;23.8&lt;/mn&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ 23.8 $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; years, range: &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mn&gt;15.5&lt;/mn&gt;\u0000 ","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 9","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70258","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144315144","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 Iron Homeostasis Imbalance in T2DM-Associated Cognitive Dysfunction: A Prospective Cohort Study Utilizing Quantitative Susceptibility Mapping","authors":"Zhenyu Cheng,&nbsp;Linfeng Yang,&nbsp;Meng Li,&nbsp;Qihao Zhang,&nbsp;Jing Li,&nbsp;Nan Zhang,&nbsp;Yena Che,&nbsp;Yiwen Chen,&nbsp;Pengcheng Liang,&nbsp;Yuanyuan Wang,&nbsp;Na Wang,&nbsp;Xinyue Zhang,&nbsp;Changhu Liang,&nbsp;Lingfei Guo","doi":"10.1002/hbm.70263","DOIUrl":"https://doi.org/10.1002/hbm.70263","url":null,"abstract":"<p>Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder that significantly impacts cognitive health. Although the vascular complications of T2DM have been extensively studied, research on brain iron deposition in T2DM remains scarce, and few studies have directly linked iron accumulation in cognition-related subcortical nuclei to cognitive dysfunction. This study aims to evaluate brain iron deposition using quantitative susceptibility mapping (QSM) and identify key subcortical nuclei associated with T2DM-related cognitive decline. A total of 224 participants were recruited, including 112 T2DM patients and 112 healthy controls. QSM was used to assess iron deposition in subcortical nuclei. Structural equation modeling was employed to construct interaction models between metabolic changes, susceptibility values, and cognitive function. Additionally, polynomial regression analysis was performed to evaluate the association between glycemic variability and the QSM values of subcortical nuclei. Our findings confirmed that T2DM patients exhibited pronounced iron deposition in the caudate and putamen compared to healthy controls. Correlation analyses showed that higher QSM values in the anterior putamen, posterior putamen, and posterior caudate were associated with slower processing speed (SDMT), reduced memory performance (AVLT) and poorer executive function (TMT, SCWT), indicating that greater iron accumulation in these nuclei is associated with poorer cognitive performance. In our SEM, metabolic dysregulation was significantly associated with higher subcortical susceptibility (β = 0.224, <i>p</i> = 0.010). The model further demonstrated that susceptibility values partially mediated the effect of metabolic factors on cognition (indirect effect <i>β</i> = −0.056, <i>p</i> = 0.018) and that the overall impact of metabolic dysregulation on cognition remained significant (<i>β</i> = −0.142, <i>p</i> = 0.037). Polynomial regression found that HbA1c was the strongest predictor of anterior putamen susceptibility, and a similar pattern was observed in the posterior caudate. The study demonstrates that the role of brain iron deposition in T2DM-related cognitive dysfunction. These findings reveal an important underlying mechanism of T2DM-induced cognitive impairment and provide evidence for early intervention strategies to mitigate cognitive decline in T2DM patients.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 9","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70263","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144309057","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":"Asymmetric Cingulum Bundle Connectivity Is Modulated by Paracingulate Sulcus Morphology","authors":"Isabel A. Danstrom,&nbsp;Joshua A. Adkinson,&nbsp;Meghan E. Robinson,&nbsp;Lu Lin,&nbsp;Atul Maheshwari,&nbsp;Ben Shofty,&nbsp;Garrett Banks,&nbsp;Mohammed Hasen,&nbsp;Sameer A. Sheth,&nbsp;Alica M. Goldman,&nbsp;Eleonora Bartoli,&nbsp;Sarah R. Heilbronner,&nbsp;Kelly R. Bijanki","doi":"10.1002/hbm.70230","DOIUrl":"https://doi.org/10.1002/hbm.70230","url":null,"abstract":"<p>The cingulum bundle (CB) is a group of axons supporting connectivity among several functional brain networks relevant in healthy and diseased states. The paracingulate sulcus (PCS) is present in at least one cerebral hemisphere across 70% of the population. PCS presence versus absence is linked to differences in structure and function of the anterior cingulate cortex, though the influence of PCS on the white matter of the CB remains unknown. The objective of this work was to define the CB electrographic connectivity profile and determine the impact of PCS morphology on CB engagement. Single-pulse electrical stimulation in combination with stereo-electroencephalography recordings was used to measure neural responses to left and right CB stimulation in 19 patients undergoing intracranial monitoring for treatment of refractory epilepsy. Evoked potential responses were extracted from brain areas, and a connectivity robustness ratio was computed. Network-level responses were compared across left and right CB, and with consideration of PCS morphology. CB electrographic connectivity demonstrated leftward dominance, but this was strongly impacted by PCS morphology in both cerebral hemispheres. Maximal left CB connectivity was observed in the presence of left PCS morphology, while right CB connectivity was strongest in its absence. These data strongly suggest that bilateral CB engagement is modulated by PCS morphology in the left hemisphere. These findings are particularly relevant when considering the CB as a target for treating neuropsychiatric disorders.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 9","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70230","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144300399","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}