Human Brain Mapping最新文献

{"title":"Relational Integration Demands Are Tracked by Temporally Delayed Neural Representations in Alpha and Beta Rhythms Within Higher-Order Cortical Networks","authors":"Conor Robinson,&nbsp;Luca Cocchi,&nbsp;Takuya Ito,&nbsp;Luke Hearne","doi":"10.1002/hbm.70272","DOIUrl":"https://doi.org/10.1002/hbm.70272","url":null,"abstract":"<p>Relational reasoning is the ability to infer and understand the relations between multiple elements. In humans, this ability supports higher cognitive functions and is linked to fluid intelligence. Relational complexity (RC) is a cognitive framework that offers a generalisable method for classifying the complexity of reasoning problems. To date, increased RC has been linked to static patterns of brain activity supported by the frontoparietal system, but limited work has assessed the multivariate spatiotemporal dynamics that code for RC. To address this, we conducted representational similarity analysis in two independent neuroimaging datasets (Dataset 1 fMRI, <i>n</i> = 40; Dataset 2 EEG, <i>n</i> = 45), where brain activity was recorded while participants completed a visuospatial reasoning task that included different levels of RC (Latin Square Task). Our findings revealed that spatially, RC representations were widespread, peaking in brain networks associated with higher-order cognition (frontoparietal, dorsal-attention, and cingulo-opercular). Temporally, RC was represented in the 2.5–4.1 s post-stimuli window and emerged in the alpha and beta frequency range. Finally, multimodal fusion analysis demonstrated that shared variability within EEG-fMRI signals within higher-order cortical networks were better explained by the theorized RC model, relative to a model of cognitive effort (CE). Altogether, the results further our understanding of the neural representations supporting relational processing, highlight the spatially distributed coding of RC and CE across cortical networks, and emphasize the importance of late-stage, frequency-specific neural dynamics in resolving RC.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70272","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144573171","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":"Sensory Entrained TMS (seTMS) Enhances Motor Cortex Excitability","authors":"Jessica M. Ross,&nbsp;Lily Forman,&nbsp;Juha Gogulski,&nbsp;Umair Hassan,&nbsp;Christopher C. Cline,&nbsp;Sara Parmigiani,&nbsp;Jade Truong,&nbsp;James W. Hartford,&nbsp;Nai-Feng Chen,&nbsp;Takako Fujioka,&nbsp;Scott Makeig,&nbsp;Alvaro Pascual-Leone,&nbsp;Corey J. Keller","doi":"10.1002/hbm.70267","DOIUrl":"https://doi.org/10.1002/hbm.70267","url":null,"abstract":"<p>Transcranial magnetic stimulation (TMS) applied to the motor cortex has revolutionized the study of motor physiology in humans. Despite this, TMS-evoked electrophysiological responses show significant fluctuation, due in part to inconsistencies between TMS pulse timing and ongoing brain oscillations. Small or inconsistent responses to TMS limit mechanistic insights and clinical efficacy, necessitating the development of methods to precisely coordinate the timing of TMS pulses to the phase of relevant oscillatory activity. We introduce Sensory Entrained TMS (seTMS), a novel approach that uses musical rhythms to synchronize brain oscillations and time TMS pulses to enhance cortical excitability. Focusing on the sensorimotor alpha rhythm, a neural oscillation associated with motor cortical inhibition, we examine whether rhythm-evoked sensorimotor alpha phase alignment affects primary motor cortical (M1) excitability in healthy young adults (<i>n</i> = 33). We first confirmed using electroencephalography (EEG) that passive listening to musical rhythms desynchronizes inhibitory sensorimotor brain rhythms (<i>mu oscillations</i>) around 200 ms before auditory rhythmic events (27 participants). We then targeted this optimal time window by delivering single TMS pulses over M1 200 ms before rhythmic auditory events while recording motor-evoked potentials (MEPs; 19 participants), which resulted in significantly larger MEPs compared to standard single pulse TMS and an auditory control condition. Neither EEG measures during passive listening nor seTMS-induced MEP enhancement showed dependence on musical experience or training. These findings demonstrate that seTMS effectively enhances corticomotor excitability and establishes a practical, cost-effective method for optimizing non-invasive brain stimulation outcomes.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70267","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144573170","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":"Analysis of Longitudinal Change Patterns in Developing Brain Using Functional and Structural Magnetic Resonance Imaging via Multimodal Fusion","authors":"Rekha Saha,&nbsp;Debbrata K. Saha,&nbsp;Zening Fu,&nbsp;Marlena Duda,&nbsp;Rogers F. Silva,&nbsp;Tony W. Wilson,&nbsp;Yu-Ping Wang,&nbsp;Julia M. Stephen,&nbsp;Vince D. Calhoun","doi":"10.1002/hbm.70241","DOIUrl":"https://doi.org/10.1002/hbm.70241","url":null,"abstract":"&lt;p&gt;Functional and structural magnetic resonance imaging (fMRI and sMRI) are complementary approaches that can be used to study longitudinal brain changes in adolescents. Each individual modality offers distinct insights into the brain. However each individual modality may overlook crucial aspects of brain analysis. By combining them, we can uncover hidden brain connections and gain a more comprehensive understanding. In previous work, we identified multivariate patterns of change in whole-brain function during adolescence. In this work, we focus on linking functional change patterns (FCPs) to brain structure. We introduced two approaches and applied them to data from the adolescent brain and cognitive development (ABCD) dataset. First, we evaluate voxel-wise sMRI-&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;FCP&lt;/mi&gt;\u0000 &lt;mtext&gt;asym&lt;/mtext&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {FCP}_{asym} $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; coupling to identify structural patterns linked to our previously identified FCPs. Our approach revealed multiple interesting patterns in functional network connectivity (FNC) and gray matter volume (GMV) data that were linked to subject-level variation. &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;FCP&lt;/mi&gt;\u0000 &lt;mtext&gt;asym&lt;/mtext&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {FCP}_{asym} $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; components 2 and 4 exhibit extensive associations between their loadings and voxel-wise GMV data. Secondly, we leveraged a symmetric multimodal fusion technique called multiset canonical correlation analysis (mCCA) + joint independent component analysis (jICA). Using this approach, we identified structured &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;FCPs&lt;/mtext&gt;\u0000 &lt;mi&gt;sym&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {FCPs}_{sym} $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; such as one showing increased connectivity between visual and sensorimotor domains and decreased connectivity between sensorimotor and cognitive control domains, linked to structural change patterns (&lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;SCPs&lt;/mtext&gt;\u0000 &lt;mi&gt;sym&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt;$$ {SCPs}_{sym} $$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;) including alterations in the bilateral sensorimotor cortex. Interestingly, females show stronger connection between brain function","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70241","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536899","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":"Coupling of Low Frequency Hemodynamic Oscillations Between the Brain and Spinal Cord","authors":"Andrew John Frels,&nbsp;Vidhya V. Nair,&nbsp;Brianna Kish,&nbsp;Kalen Riley,&nbsp;Gordon Mao,&nbsp;A. J. Schwichtenberg,&nbsp;Yunjie Tong","doi":"10.1002/hbm.70278","DOIUrl":"https://doi.org/10.1002/hbm.70278","url":null,"abstract":"<p>In Functional Magnetic Resonance Imaging (fMRI), the primary contrast is Blood Oxygen Level Dependent (BOLD) signal. Systemic Low Frequency Oscillations (sLFO) are BOLD signals between 0.01 and 0.1 Hz originating from systemic physiological processes. While sLFO signals in the brain have been shown to travel with blood in numerous studies, their behavior in the spinal cord (SC) remains unexplored. This study characterizes the coupling between brain-sLFO and SC-sLFO signals. Understanding brain-SC-coupling is pivotal for unraveling the vascular continuity of the central nervous system, which plays a crucial role in SC-injury pathophysiology. BOLD signal extraction involved registering structural masks to fMRI space to obtain average time series from the brain, SC, and superior sagittal sinus. The sLFOs of the time series were cross-correlated to determine vascular delays and analyzed for band power. It is found that the SC-sLFO signal comprises two components relative to the brain, showing opposite correlation polarity and varying delays. These findings suggest that highly oxygenated blood arrives at the spinal cord before arriving at the brain, and some component of the brain's venous output circulates to or near to the spinal cord later, likely due to unique arterial and venous pathways connecting the central nervous system. This insight offers a valuable imaging marker for future studies on the effects of SC injury on brain-SC interconnectivity.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70278","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536900","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 Cerebellar Partitioning Method Using Spectral Clustering With Optimized Nonlinear Functional Connectivity","authors":"Tengyue Wang,&nbsp;Kai Zhou,&nbsp;Xiaoyan Zhou,&nbsp;Xiaoming Wang,&nbsp;Haoyang Xing,&nbsp;Rong Li,&nbsp;Wei Liao,&nbsp;Jiali Yu,&nbsp;Fengmei Lu,&nbsp;Xiaofei Hu,&nbsp;Huafu Chen,&nbsp;Qing Gao","doi":"10.1002/hbm.70268","DOIUrl":"https://doi.org/10.1002/hbm.70268","url":null,"abstract":"<p>Cerebellum has a stronger individual specificity of functional signals than the brain and is associated with a variety of neuropsychiatric disorders, and increasing attention is being paid to neuropsychiatric symptoms caused by cerebellar dysfunction. However, there is a lack of a suitable cerebellar partition utilizing researchers to fully understand the functional and structural organization of the cerebellum, reduce data dimensionality, and improve the applicability of various types of models to cerebellar functional imaging data, impeding progress in cerebellum-related research. In this study, we use order-preserving variations with spatial constraints to optimize functional connectivity matrices and employ a spectral clustering algorithm combined with a clustering ensemble technique to construct a cerebellar partitioning algorithm with a variable number of partitions. Our method was initially validated by using two separate sets of functional magnetic resonance data (fMRI), demonstrating high reproducibility across individuals. Comparative analysis revealed that our partitions exhibited enhanced signal coherence and greater spatial congruence with established cerebellar structural templates compared to four publicly available cerebellar atlases. Furthermore, preliminarily applying these partitions to Parkinson's disease (PD) data, we extracted cerebellar connectivity network features and constructed a classification model using a logistic regression model with L2 regularization. The connectivity features derived from our newly constructed cerebellar partitions substantially improved the usability of the Parkinson's classification model, with the classification of PD optimized at a number of partitions equal to 185, suggesting that the optimal number of cerebellar partitions may also vary based on the problem under study. Notably, cerebellar regions implicated in motor execution were identified to exhibit higher feature importance in the Parkinson's classification model, offering an important direction for feature selection in the multimodal classification models of PD.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70268","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524871","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":"Unraveling Hierarchical Brain Dysfunction in Major Depressive Disorder: A Multimodal Imaging and Transcriptomic Approach","authors":"Chen Xiayan,&nbsp;Dai Haowei,&nbsp;Niu Lijing,&nbsp;Chen Zini,&nbsp;Xiaoyue Li,&nbsp;Zeng Yuanyuan,&nbsp;Zhu Qingzi,&nbsp;Lin Kangguang,&nbsp;Zhang Ruibin","doi":"10.1002/hbm.70277","DOIUrl":"https://doi.org/10.1002/hbm.70277","url":null,"abstract":"<p>Major depressive disorder (MDD) is characterized by deficits in sensory processing and higher-order executive functions, reflecting dysfunction in the hierarchical organization of the brain. However, current methods for investigating brain hierarchy in MDD have not fully integrated multimodal data, and the underlying biological mechanisms remain poorly understood. We acquired diffusion tensor imaging and functional magnetic resonance imaging (fMRI) data from 100 participants with MDD and 77 healthy controls (HCs). The structural-decoupling index (SDI) was employed to quantify the hierarchical organization in MDD and HC. We identified intergroup differences in the hierarchical brain organization and explored the molecular mechanism related to significantly different brain regions by investigating genetic factors and their relationship with neurotransmitter receptors/transporters. Finally, 10-fold cross-validation was used to develop a support vector machine (SVM) classification model. Dysfunctional hierarchical organization in MDD was characterized by increased SDI in the bilateral somatosensory cortex, while decreased SDI was observed in the bilateral visual, prefrontal, and parietal cortices, as well as the left orbitofrontal cortex and temporal pole. Moreover, SDI alterations showed negative correlations with neurotransmitters, including 5-HT1a, 5-HT2a, D1, GABAa, SERT, and mGluR5. The SDI alteration-related genes were enriched in kinase binding. After 10-fold cross-validation, the SVM exhibited a mean accuracy of 0.767 (area under the curve = 0.972). Our research employed multimodal data to investigate hierarchical brain dysfunction in MDD and established its associations with neurotransmitters and transcriptome profiles. This approach may improve the understanding of the neural, biological, and molecular genetic underpinning of SDI in MDD.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70277","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519586","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":"Morphological Brain Analysis Using Ultra Low-Field MRI","authors":"Peter Hsu,&nbsp;Elisa Marchetto,&nbsp;Daniel K. Sodickson,&nbsp;Patricia M. Johnson,&nbsp;Jelle Veraart","doi":"10.1002/hbm.70232","DOIUrl":"https://doi.org/10.1002/hbm.70232","url":null,"abstract":"<p>Ultra low-field (ULF) MRI is an accessible neuroimaging modality that can bridge healthcare disparities and advance population-level brain health research. However, the inherently low signal-to-noise ratio of ULF-MRI often necessitates reductions in spatial resolution and, combined with the field-dependency of MRI contrast, challenges the accurate extraction of clinically relevant brain morphology. We evaluate the current state of ULF-MRI brain volumetry utilizing techniques for enhancing spatial resolution and leveraging recent advancements in brain segmentation. This is based on the agreement between ULF and corresponding high-field (HF) MRI brain volumes, and test–retest repeatability for multiple ULF scans. In this study, we find that accurate brain volumes can be measured from ULF-MRIs when combining orthogonal imaging directions for T₂-weighted images to form a higher resolution image volume. We also demonstrate that not all orthogonal imaging directions contribute equally to volumetric accuracy and provide a recommended scan protocol given the constraints of the current technology.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70232","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515131","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":"Individualized Functional and Structural Language Lateralities in Temporal Lobe Epilepsy and Their Impact on Memory","authors":"Ankeeta Ankeeta,&nbsp;Qirui Zhang,&nbsp;Sam Sharifzadeh Javidi,&nbsp;Shilpi Modi,&nbsp;Michael R. Sperling,&nbsp;Joseph I. Tracy","doi":"10.1002/hbm.70250","DOIUrl":"https://doi.org/10.1002/hbm.70250","url":null,"abstract":"<p>The basis and impact of functional asymmetries in the brain, particularly language lateralization, are not fully understood, and the relationship between functional and structural asymmetries remains largely untested. This study investigated the degree to which asymmetries in hemispheric language laterality are concordant with asymmetries in gray matter (GM) structure and whether the hemispheric organization of memory is influenced by functional language asymmetries. Structural and functional MR data was acquired from 261 individuals, including those with unilateral temporal lobe epilepsy (LTLE = 96, RTLE = 69) and matched with healthy participants (HPs = 96). Functional language laterality indices (LIs) were calculated using two methods: (1) standard LIs from the frontal, temporal, and parietal lobes and (2) targeted LIs (T-LIs) from individually defined activation peaks. Structural LIs (ST-LIs) were derived from the GM volumes underlying these functional LIs. We observed significant shifts in language laterality in LTLE compared to HPs in 8 out of 12 brain regions. Strong correlations were observed between functional LIs and their structural counterparts. Discriminant analyses demonstrated that targeted LIs and ST-LIs more effectively distinguished TLE patients from HPs, with ST-LIs being the most powerful discriminator. Partial least squares analyses showed verbal and visual memory have a direct dependence on targeted LIs in HPs and LTLE, with this effect more pronounced in HPs. In RTLE, verbal memory showed a similar dependency. These findings underscored the importance of individualized, region-specific measures for understanding language laterality, its relation to structural underpinnings, and its impact on the organization of other cognitive functions such as memory.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70250","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515132","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":"Dynamic Functional Connectivity Between Amygdala and Cognitive Control Network Predicts Delay Discounting in Older Adolescents","authors":"Attakias T. Mertens,&nbsp;Callum Goldsmith,&nbsp;Derek J. Pavelka,&nbsp;Jacob J. Oleson,&nbsp;Gaelle E. Doucet","doi":"10.1002/hbm.70270","DOIUrl":"https://doi.org/10.1002/hbm.70270","url":null,"abstract":"<p>There is a spike in reward sensitivity during adolescence. Delay discounting involves subjective valuation of a reward in context of when it is gained. This study sought to assess if dynamic functional connectivity between the cognitive control network and the amygdala could predict delay discounting in adolescents and young adults. 448 participants were separated into three age groups, including younger and older adolescents and young adults. A sliding-window approach was used to calculate dynamic functional connectivity between the left/right amygdala and the cognitive control network. Hierarchical models were run for each age group to determine if dynamic functional connectivity could predict delay discounting behavior in two delayed amount conditions above and beyond age and sex. Results showed that dynamic functional connectivity between the left, but not the right, amygdala and cognitive control network significantly predicted delay discounting in the larger amount condition for older adolescents. No significant results were found for the smaller amount condition in older adolescents or either condition in younger adolescents or adults. Stronger dynamic functional connectivity indicated a preference for immediate rewards during a larger amount condition in older adolescents only.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70270","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144515128","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":"Neuropathological Correlates of Volume and Shape of Deep Gray Matter Structures in Community-Based Older Adults","authors":"Khalid Saifullah,&nbsp;Nazanin Makkinejad,&nbsp;Md Tahmid Yasar,&nbsp;Arnold M. Evia,&nbsp;Sue E. Leurgans,&nbsp;David A. Bennett,&nbsp;Julie A. Schneider,&nbsp;Konstantinos Arfanakis","doi":"10.1002/hbm.70273","DOIUrl":"https://doi.org/10.1002/hbm.70273","url":null,"abstract":"<p>Age-related neurodegenerative and cerebrovascular neuropathologies often coexist in the brain of older adults and contribute to brain abnormalities, cognitive decline and dementia. While deep gray matter structures are implicated early and/or strongly in these processes, the independent effects of various age-related neuropathologies on these structures remain poorly understood. The goal of this study was to investigate the independent association of various age-related neuropathologies with the volume and shape of deep gray matter structures in a large number of community-based older adults that came to autopsy. Cerebral hemispheres from 842 participants of four community studies at the Rush Alzheimer's Disease Center were imaged with MRI ex vivo and underwent detailed neuropathologic examination. Linear regression was used to study the association of various neuropathologies with the volume and shape of six deep gray matter structures (hippocampus, amygdala, caudate, thalamus, nucleus accumbens, putamen) controlling for age at death, sex, years of education, scanner, and postmortem intervals. Both the volumetric and shape analyses showed independent associations of tangles with structural abnormalities in all deep brain structures, of limbic-predominant age-related TDP-43 encephalopathy neuropathological change (LATE-NC) with hippocampus and amygdala, of atherosclerosis with hippocampus, and of gross infarcts with caudate (all <i>p</i> &lt; 0.05 corrected for multiple comparisons). Shape analysis revealed the corresponding independent spatial patterns of inward deformation and also showed additional associations of neuropathologies with deep brain structures (<i>p</i> &lt; 0.05 corrected for multiple comparisons). When analyses were repeated in left and right hemispheres separately, the results were mostly similar in both hemispheres. Mixed pathologies are very common in the older adult brain and the present comprehensive study disentangles their independent effects on multiple deep gray matter structures. These neuropathologic signatures may potentially be used in combination with other features toward in vivo prediction of neuropathologies which could have important implications in future clinical trials and the development of prevention and treatment strategies.</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.70273","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144503250","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}