Human Brain Mapping最新文献

{"title":"The Impact of Atlas Parcellation on Functional Connectivity Analysis Across Six Psychiatric Disorders","authors":"Xiaoya Wu,&nbsp;Chuang Liang,&nbsp;Juan Bustillo,&nbsp;Peter Kochunov,&nbsp;Xuyun Wen,&nbsp;Jing Sui,&nbsp;Rongtao Jiang,&nbsp;Xiao Yang,&nbsp;Zening Fu,&nbsp;Daoqiang Zhang,&nbsp;Vince D. Calhoun,&nbsp;Shile Qi","doi":"10.1002/hbm.70206","DOIUrl":"https://doi.org/10.1002/hbm.70206","url":null,"abstract":"<p>Neuropsychiatric disorders are associated with altered functional connectivity (FC); however, the reported regional patterns of functional alterations suffered from low replicability and high variability. This is partly because of differences in the atlas and delineation techniques used to measure FC-related deficits within/across disorders. We systematically investigated the impact of the brain parcellation approach on the FC-based brain network analysis. We focused on identifying the replicable FCs using three structural brain atlases, including Automated Anatomical Labeling (AAL), Brainnetome atlas (BNA) and HCP_MMP_1.0, and four functional brain parcellation approaches: Yeo-Networks (Yeo), Gordon parcel (Gordon) and two Schaefer parcelletions, among correlation, group difference, and classification tasks in six neuropsychiatric disorders: attention deficit and hyperactivity disorder (ADHD, <i>n</i> = 340), autism spectrum disorder (ASD, <i>n</i> = 513), schizophrenia (SZ, <i>n</i> = 200), schizoaffective disorder (SAD, <i>n</i> = 142), bipolar disorder (BP, <i>n</i> = 172), and major depression disorder (MDD, <i>n</i> = 282). Our cross-atlas/disorder analyses demonstrated that frontal-related FC deficits were reproducible in all disorders, independent of the atlasing approach; however, replicable FC extraction in other areas and the classification accuracy were affected by the parcellation schema. Overall, functional atlases with finer granularity performed better in classification tasks. Specifically, the Schaefer atlases generated the most repeatable FC deficit patterns across six illnesses. These results indicate that frontal-related FCs may serve as potential common and robust neuro-abnormalities across 6 psychiatric disorders. Furthermore, in order to improve the replicability of rsfMRI-based FC analyses, this study suggests the use of functional templates at larger granularity.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70206","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749644","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":"Phase Locking of 40 Hz Auditory Steady State Responses Is Modulated by Sensory Predictability and Linked to Cerebellar Myelination","authors":"Kit Melissa Larsen,&nbsp;Kiran Thapaliya,&nbsp;Markus Barth,&nbsp;Chin-Husan Sophie Lin,&nbsp;Hartwig R. Siebner,&nbsp;Marta I. Garrido","doi":"10.1002/hbm.70178","DOIUrl":"https://doi.org/10.1002/hbm.70178","url":null,"abstract":"<p>40 Hz auditory steady-state responses (ASSR) can be evoked by brief auditory clicks delivered at 40 Hz. While the neuropharmacology behind the generation of ASSR is well examined, the link between ASSR and microstructural properties of the brain is unclear. Further, whether the 40 Hz ASSR can be manipulated through processes involving top-down control, such as prediction, is currently unknown. We recorded EEG in 50 neurotypical participants while they engaged in a 40 Hz auditory steady-state paradigm. We manipulated the predictability of the stimuli to test the modulatory effect of prediction on 40 Hz steady-state responses. Further, we acquired T1w and T2w structural MRI on the same individuals and used the T1/T2 ratio as a proxy to determine myelination content in gray matter. The phase locking of the 40 Hz ASSR was indeed modulated by prediction, suggesting that prediction violation directly affects phase locking to the 40 Hz ASSR. We found that the prediction violation of the phase locking at 40 Hz (gamma) was associated with the degree of gray matter myelination in the right cerebellum, such that greater myelin led to less desynchronization induced by prediction violations. We demonstrate that prediction violations modulate steady-state activity at 40 Hz and suggest that the efficiency of this process is promoted by greater cerebellar myelin. Our findings provide a structural-functional relationship for myelin and phase locking of auditory oscillatory activity. These results introduce a framework for investigating the interaction of predictive processes and ASSR in disorders where these processes are impaired, such as in psychosis.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70178","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749643","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 Shape of the Brain's Connections Is Predictive of Cognitive Performance: An Explainable Machine Learning Study","authors":"Yui Lo,&nbsp;Yuqian Chen,&nbsp;Dongnan Liu,&nbsp;Wan Liu,&nbsp;Leo Zekelman,&nbsp;Jarrett Rushmore,&nbsp;Fan Zhang,&nbsp;Yogesh Rathi,&nbsp;Nikos Makris,&nbsp;Alexandra J. Golby,&nbsp;Weidong Cai,&nbsp;Lauren J. O'Donnell","doi":"10.1002/hbm.70166","DOIUrl":"https://doi.org/10.1002/hbm.70166","url":null,"abstract":"<p>The shape of the brain's white matter connections is relatively unexplored in diffusion magnetic resonance imaging (dMRI) tractography analysis. While it is known that tract shape varies in populations and across the human lifespan, it is unknown if the variability in dMRI tractography-derived shape may relate to the brain's functional variability across individuals. This work explores the potential of leveraging tractography fiber cluster shape measures to predict subject-specific cognitive performance. We implement two machine learning models (1D-CNN and Least Absolute Shrinkage and Selection Operator [LASSO]) to predict individual cognitive performance scores. We study a large-scale database from the Human Connectome Project Young Adult study (<i>n</i> = 1065). We apply an atlas-based fiber cluster parcellation (953 fiber clusters) to the dMRI tractography of each individual. We compute 15 shape, microstructure, and connectivity features for each fiber cluster. Using these features as input, we train a total of 210 models (using fivefold cross-validation) to predict 7 different NIH Toolbox cognitive performance assessments. We apply an explainable AI technique, SHapley Additive exPlanations (SHAP), to assess the importance of each fiber cluster for prediction. Our results demonstrate that fiber cluster shape measures are predictive of individual cognitive performance. The studied shape measures, such as irregularity, diameter, total surface area, volume, and branch volume, are generally as effective for prediction as traditional microstructure and connectivity measures. The 1D-CNN model generally outperforms the LASSO method for prediction. Further interpretation and analysis using SHAP values from the 1D-CNN suggest that fiber clusters with features highly predictive of cognitive ability are widespread throughout the brain, including fiber clusters from the superficial association, deep association, cerebellar, striatal, and projection pathways. This study demonstrates the strong potential of shape descriptors to enhance the study of the brain's white matter and its relationship to cognitive function.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70166","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143707217","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":"Evaluating Traditional, Deep Learning and Subfield Methods for Automatically Segmenting the Hippocampus From MRI","authors":"Sabrina Sghirripa,&nbsp;Gaurav Bhalerao,&nbsp;Ludovica Griffanti,&nbsp;Grace Gillis,&nbsp;Clare Mackay,&nbsp;Natalie Voets,&nbsp;Stephanie Wong,&nbsp;Mark Jenkinson,&nbsp;For the Alzheimer's Disease Neuroimaging Initiative","doi":"10.1002/hbm.70200","DOIUrl":"https://doi.org/10.1002/hbm.70200","url":null,"abstract":"<p>Given the relationship between hippocampal atrophy and cognitive impairment in various pathological conditions, hippocampus segmentation from MRI is an important task in neuroimaging. Manual segmentation, though considered the gold standard, is time-consuming and error-prone, leading to the development of numerous automatic segmentation methods. However, no study has yet independently compared the performance of traditional, deep learning-based and hippocampal subfield segmentation methods within a single investigation. We evaluated 10 automatic hippocampal segmentation methods (FreeSurfer, SynthSeg, FastSurfer, FIRST, e2dhipseg, Hippmapper, Hippodeep, FreeSurfer-Subfields, HippUnfold and HSF) across 3 datasets with manually segmented hippocampus labels. Performance metrics included overlap with manual labels, correlations between manual and automatic volumes, volume similarity, diagnostic group differentiation and systematically located false positives and negatives. Most methods, especially deep learning-based ones that were trained on manual labels, performed well on public datasets but showed more error and variability on clinical data. Many methods tended to over-segment, particularly at the anterior hippocampus border, but were able to distinguish between healthy controls, MCI, and dementia patients based on hippocampal volume. Our findings highlight the challenges in hippocampal segmentation from MRI and the need for more publicly accessible datasets with manual labels across diverse ages and pathological conditions.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70200","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143707628","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":"Prediction of Verbal Abilities From Brain Connectivity Data Across the Lifespan Using a Machine Learning Approach","authors":"Deborah Früh,&nbsp;Camilla Mendl-Heinisch,&nbsp;Nora Bittner,&nbsp;Susanne Weis,&nbsp;Svenja Caspers","doi":"10.1002/hbm.70191","DOIUrl":"https://doi.org/10.1002/hbm.70191","url":null,"abstract":"<p>Compared to nonverbal cognition such as executive or memory functions, language-related cognition generally appears to remain more stable until later in life. Nevertheless, different language-related processes, for example, verbal fluency versus vocabulary knowledge, appear to show different trajectories across the life span. One potential explanation for differences in verbal functions may be alterations in the functional and structural network architecture of different large-scale brain networks. For example, differences in verbal abilities have been linked to the communication within and between the frontoparietal (FPN) and default mode network (DMN). It, however, remains open whether brain connectivity within these networks may be informative for language performance at the individual level across the life span. Further information in this regard may be highly desirable as verbal abilities allow us to participate in daily activities, are associated with quality of life, and may be considered in preventive and interventional setups to foster cognitive health across the life span. So far, mixed prediction results based on resting-state functional connectivity (FC) and structural connectivity (SC) data have been reported for language abilities across different samples, age groups, and machine-learning (ML) approaches. Therefore, the current study set out to investigate the predictability of verbal fluency and vocabulary knowledge based on brain connectivity data in the DMN, FPN, and the whole brain using an ML approach in a lifespan sample (<i>N</i> = 717; age range: 18–85) from the 1000BRAINS study. Prediction performance was, thereby, systematically compared across (i) verbal [verbal fluency and vocabulary knowledge] and nonverbal abilities [processing speed and visual working memory], (ii) modalities [FC and SC data], (iii) feature sets [DMN, FPN, DMN-FPN, and whole brain], and (iv) samples [total, younger, and older aged group]. Results from the current study showed that verbal abilities could not be reliably predicted from FC and SC data across feature sets and samples. Thereby, no predictability differences emerged between verbal fluency and vocabulary knowledge across input modalities, feature sets, and samples. In contrast to verbal functions, nonverbal abilities could be moderately predicted from connectivity data, particularly SC, in the total and younger age group. Satisfactory prediction performance for nonverbal cognitive functions based on currently chosen connectivity data was, however, not encountered in the older age group. Current results, hence, emphasized that verbal functions may be more difficult to predict from brain connectivity data in domain-general cognitive networks and the whole brain compared to nonverbal abilities, particularly executive functions, across the life span. Thus, it appears warranted to more closely investigate differences in predictability between different cognitive functions and age groups.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70191","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143689753","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":"Temporal Structure of Music Improves the Cortical Encoding of Speech","authors":"Laura Fernández-Merino,&nbsp;Mikel Lizarazu,&nbsp;Nicola Molinaro,&nbsp;Marina Kalashnikova","doi":"10.1002/hbm.70199","DOIUrl":"https://doi.org/10.1002/hbm.70199","url":null,"abstract":"<p>Long- and short-term musical training has been proposed to improve the efficiency of cortical tracking of speech, which refers to the synchronization of brain oscillations and the acoustic temporal structure of external stimuli. Here, we study how musical sequences with different rhythm structures can guide the temporal dynamics of auditory oscillations synchronized with the speech envelope. For this purpose, we investigated the effects of prior exposure to rhythmically structured musical sequences on cortical tracking of speech in Basque–Spanish bilingual adults (Experiment 1; <i>N</i> = 33, 22 female, Mean age = 25 years). We presented participants with sentences in Basque and Spanish preceded by musical sequences that differed in their rhythmical structure. The rhythmical structure of the musical sequences was created to (1) reflect and match the syllabic structure of the sentences, (2) reflect a regular rhythm but not match the syllabic structure of the sentences, and (3) follow an irregular rhythm. Participants' brain responses were recorded using electroencephalography, and speech-brain coherence in the delta and theta bands was calculated. Results showed stronger speech-brain coherence in the delta band in the first condition, but only for Spanish stimuli. A follow-up experiment including a subset of the initial sample (Experiment 2; <i>N</i> = 20) was conducted to investigate whether language-specific stimuli properties influenced the Basque results. Similar to Experiment 1, we found stronger speech-brain coherence in the delta and theta bands when the sentences were preceded by musical sequences that matched their syllabic structure. These results suggest that not only the regularity in music is crucial for influencing cortical tracking of speech, but so is adjusting this regularity to optimally reflect the rhythmic characteristics of listeners' native language(s). Despite finding some language-specific differences across frequencies, we showed that rhythm, inherent in musical signals, guides the adaptation of brain oscillations, by adapting the temporal dynamics of the oscillatory activity to the rhythmic scaffolding of the musical signal.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70199","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143689752","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 New Multiple Imputation Method for High-Dimensional Neuroimaging Data","authors":"Tong Lu,&nbsp;Peter Kochunov,&nbsp;Chixiang Chen,&nbsp;Hsin-Hsiung Huang,&nbsp;L. Elliot Hong,&nbsp;Shuo Chen","doi":"10.1002/hbm.70161","DOIUrl":"10.1002/hbm.70161","url":null,"abstract":"<p>Missing data are a prevalent challenge in neuroimaging, with significant implications for downstream statistical analysis. Neglecting this issue can introduce bias and lead to erroneous inferential conclusions, making it crucial to employ appropriate statistical methods for handling missing data. Although the multiple imputation is a widely used technique, its application in neuroimaging is severely hindered by the high dimensionality of neuroimaging data, and the substantial computational demands. To tackle the critical computational challenges, we propose a novel approach, <b>H</b>igh d<b>i</b>mensional <b>M</b>ultiple Imput<b>a</b>tion (HIMA), based on Bayesian models specifically designed for large-scale neuroimaging datasets. HIMA introduces a new computational strategy to sample large covariance matrices based on a robustly estimated posterior mode, significantly improving both computational efficiency and numerical stability. To assess the effectiveness of HIMA, we conducted extensive simulation studies and real-data analysis from a Schizophrenia brain imaging dataset with around 1000 voxels. HIMA showcases a remarkable reduction of computational burden, for example, 1 hour by HIMA versus 800 hours by classic multiple imputation packages. HIMA also demonstrates improved precision and stability of imputed data.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926575/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143669498","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":"Effects of Aging, Estimated Fitness, and Cerebrovascular Status on White Matter Microstructural Health","authors":"Grace M. Clements,&nbsp;Paul Camacho,&nbsp;Daniel C. Bowie,&nbsp;Kathy A. Low,&nbsp;Bradley P. Sutton,&nbsp;Gabriele Gratton,&nbsp;Monica Fabiani","doi":"10.1002/hbm.70168","DOIUrl":"10.1002/hbm.70168","url":null,"abstract":"<p>White matter (WM) microstructural health declines with increasing age, with evidence suggesting that improved cardiorespiratory fitness (CRF) may mitigate this decline. Specifically, higher fit older adults tend to show preserved WM microstructural integrity compared to their lower fit counterparts. However, the extent to which fitness and aging <i>independently</i> impact WM integrity across the adult lifespan is still an open question, as is the extent to which cerebrovascular health mediates these relationships. In a large sample (<i>N</i> = 125, aged 25–72), we assessed the impact of age and estimated cardiorespiratory fitness on fractional anisotropy (FA, derived using diffusion weighted imaging, dwMRI) and probed the mediating role of cerebrovascular health (derived using diffuse optical tomography of the cerebral arterial pulse, pulse-DOT) in these relationships. After orthogonalizing age and estimated fitness and computing a PCA on whole brain WM regions, we found several WM regions impacted by age that were independent from the regions impacted by estimated fitness (hindbrain areas, including brainstem and cerebellar tracts), whereas other areas showed interactive effects of age and estimated fitness (midline areas, including fornix and corpus callosum). Critically, cerebrovascular health mediated <i>both</i> relationships suggesting that vascular health plays a linking role between age, fitness, and brain health. Secondarily, we assessed potential sex differences in these relationships and found that, although females and males generally showed the same age-related FA declines, males exhibited somewhat steeper declines than females. Together, these results suggest that age and fitness impact specific WM regions and highlight the mediating role of cerebrovascular health in maintaining WM health across adulthood.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926577/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143673526","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":"Investigating the Human Brain's Integration of Internal and External Reference Frames: The Role of the Alpha and Beta Bands in a Modified Temporal Order Judgment Task","authors":"Xianhao Wei,&nbsp;Jian Zhang,&nbsp;Jinyan Zhang,&nbsp;Zimo Li,&nbsp;Qi Li,&nbsp;Jinglong Wu,&nbsp;Jingjing Yang,&nbsp;Zhilin Zhang","doi":"10.1002/hbm.70196","DOIUrl":"10.1002/hbm.70196","url":null,"abstract":"<p>The integration of the internal and external reference frames of the human brain is crucial for achieving accurate tactile spatial localization. However, the mechanisms underlying this integration have yet to be fully elucidated. This study adopted a modified temporal order judgment paradigm with an advanced weighted phase lag index method to investigate brain network interactions when the internal and external reference frames were integrated. We found that when the brain integrated internal and external reference frames, alpha oscillations decreased, beta oscillations increased, and inter-hemispheric connectivity increased. Specifically, compared with the match condition: first, the alpha band oscillation predominantly contributed to processing the internal reference frame mismatch; second, the alpha and late beta band oscillation predominantly contributed to processing the external reference frame mismatch; third, the early alpha and late beta band oscillation predominantly contributed to processing the internal and external reference frame mismatch. These findings suggest that the neural oscillation of the alpha and beta bands plays an essential role in tactile spatial localization.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926452/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143669518","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 Neural Association Between Symptom and Cognition in Major Depressive Disorder: A Network Control Theory Study","authors":"Aoxiang Zhang,&nbsp;Qian Zhang,&nbsp;Ziyuan Zhao,&nbsp;Qian Li,&nbsp;Fei Li,&nbsp;Yongbo Hu,&nbsp;Xiaoqi Huang,&nbsp;Weihong Kuang,&nbsp;Graham J. Kemp,&nbsp;Youjin Zhao,&nbsp;Qiyong Gong","doi":"10.1002/hbm.70198","DOIUrl":"10.1002/hbm.70198","url":null,"abstract":"<p>Major depressive disorder (MDD) is characterized by intercorrelated clinical symptoms and cognitive deficits, whose neural mechanisms in relation to these disturbances remain unclear. To elucidate this, we applied the relatively new approach of Network Control Theory (NCT), which considers how network topology informs brain dynamics based on white matter connectivity data. We used the NCT parameter of average controllability (AC) to assess the potential control that brain network nodes have on brain-state transitions associated with clinical and cognitive symptoms in MDD. DTI and high-resolution T1-weighted anatomical imaging were performed on 170 MDD patients (mean age 31.6 years; 72 males, 98 females) and 137 healthy controls (HC; mean age 33.4 years; 64 males, 73 females). We used an NCT approach to compare AC between the groups. We then performed partial Spearman's rank correlation and moderation/mediation analyses for AC and cognition and clinical symptom scores. Compared with HC, MDD patients had lower AC in the left precuneus and superior parietal lobule and higher AC in the right precentral gyrus (preCG) and superior frontal gyrus (SFG), predominantly in the default-mode, somatomotor, and attention networks. In the HC group, AC of right preCG was positively associated with processing speed. While in the MDD group, AC of right SFG was negatively associated with memory function and also negatively moderated the association between memory and anxiety symptoms. The current study highlighted that the altered brain controllability may provide a novel understanding of the neural substrate underlying cognitive control in MDD. Disrupted control of right SFG during state transitions may partially explain the variable relationship between memory and anxiety symptoms in MDD.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11923719/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143663543","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}