Human Brain Mapping最新文献

{"title":"Cross-Modality Comparison of Fetal Brain Phenotypes: Insights From Short-Interval Second-Trimester MRI and Ultrasound Imaging","authors":"Madeleine K. Wyburd,&nbsp;Nicola K. Dinsdale,&nbsp;Vanessa Kyriakopoulou,&nbsp;Lorenzo Venturini,&nbsp;Robert Wright,&nbsp;Alena Uus,&nbsp;Jacqueline Matthew,&nbsp;Emily Skelton,&nbsp;Lilla Zöllei,&nbsp;Joseph Hajnal,&nbsp;Ana I. L. Namburete","doi":"10.1002/hbm.70349","DOIUrl":"10.1002/hbm.70349","url":null,"abstract":"<p>Advances in fetal three-dimensional (3D) ultrasound (US) and magnetic resonance imaging (MRI) have revolutionized the study of fetal brain development, enabling detailed analysis of brain structures and growth. Despite their complementary capabilities, these modalities capture fundamentally different physical signals, potentially leading to systematic differences in image-derived phenotypes (IDPs). Here, we evaluate the agreement of IDPs between US and MRI by comparing the volumes of eight brain structures from 90 subjects derived using deep-learning algorithms from majority same-day imaging (days between scans: mean = 1.2, mode = 0 and max = 4). Excellent agreement (intra-class correlation coefficient, <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>ICC</mi>\u0000 <mo>&gt;</mo>\u0000 <mn>0.75</mn>\u0000 </mrow>\u0000 <annotation>$$ ICC&gt;0.75 $$</annotation>\u0000 </semantics></math>) was observed for the cerebellum, cavum septum pellucidum, thalamus, white matter and deep grey matter volumes, with significant correlations <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mfenced>\u0000 <mrow>\u0000 <mi>p</mi>\u0000 <mo>&lt;</mo>\u0000 <mn>0.001</mn>\u0000 </mrow>\u0000 </mfenced>\u0000 </mrow>\u0000 <annotation>$$ left(p&lt;0.001right) $$</annotation>\u0000 </semantics></math> for most structures, except the ventricular system. Bland–Altman analysis revealed some systematic biases: intracranial and cortical plate volumes were larger on US than MRI, by an average of <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>35</mn>\u0000 <mspace></mspace>\u0000 <msup>\u0000 <mi>cm</mi>\u0000 <mn>3</mn>\u0000 </msup>\u0000 </mrow>\u0000 <annotation>$$ 35 {mathrm{cm}}^3 $$</annotation>\u0000 </semantics></math> and <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>4.1</mn>\u0000 <mspace></mspace>\u0000 <msup>\u0000 <mi>cm</mi>\u0000 <mn>3</mn>\u0000 </msup>\u0000 </mrow>\u0000 <annotation>$$ 4.1 {mathrm{cm}}^3 $$</annotation>\u0000 </semantics></math>, respectively. Finally, we found the labels of the brainstem and ventricular system were not comparable between the modalities. These findings highlight the necessity of structure-specific adjustments when interpreting fetal brain IPDs across modalities and underscore the complementary roles of US and MRI in advancing fetal neuroimaging.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 14","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12485670/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145199190","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":"Relationships Between Intra-Spinal Resting-State Functional Connectivity and Electrophysiology Following Spinal Cord Injury","authors":"Pai-Feng Yang,&nbsp;Jamie L. Reed,&nbsp;Anirban Sengupta,&nbsp;Arabinda Mishra,&nbsp;Feng Wang,&nbsp;John C. Gore,&nbsp;Li Min Chen","doi":"10.1002/hbm.70370","DOIUrl":"10.1002/hbm.70370","url":null,"abstract":"<p>We previously reported that a unilateral dorsal column lesion (DCL) at the cervical C4 level primarily reduces inter-horn resting-state functional connectivity (rsFC) measured by functional Magnetic Resonance Imaging (fMRI) in segments below the lesion. This study compares changes in rsFC from fMRI with changes in local field potential (LFP) coherence over an extended post-injury period. High-resolution fMRI and LFP data were acquired bilaterally in healthy monkeys and at 3- and 6-months post-lesion. At 3 months post-injury, tactile-stimulus-evoked LFP power in the dorsal horn was significantly weaker than in the healthy cord and non-lesion side. LFP coherences increased on the lesion side for the dorsal-to-intermediate zone (D-IGM) and dorsal-to-ventral (D-V) pairs but decreased for the non-lesion side D-IGM. By 6 months, stimulus-evoked LFP power on the lesion side remained low. LFP coherences between dorsal-to-dorsal (D-D), ventral-to-ventral (V-V), and D-V pairs on both the lesion and non-lesion sides were significantly reduced relative to the healthy cord. Low-frequency (delta, theta, and alpha) D-IGM coherences on the lesion side, and high-frequency (beta and gamma) coherences on the non-lesion side, were also significantly weakened. Across specific inter-horn pairs and time points, changes in LFP coherences and rsFC measures were weakly correlated. Measurements of inter-horn correlations two segments caudal to the lesion level at C7 revealed distance-dependent intraspinal connectivity changes following DCL. Post-mortem histology confirmed a complete DCL in most animals (7/9). The extent of the disruption of ascending sensory afferents, as assessed histologically, did not appear to correlate with the degree of LFP power reduction or rsFC changes at post-injury time points. In summary, we observed temporally and spatially heterogeneous changes of fMRI correlations and LFP coherences within intraspinal circuits. fMRI rsFC and LFP coherences were not always concordant, with discrepancies depending on specific gray-matter horns and intermediate-zone pairs.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 14","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12477704/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145185761","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":"Applying Bayesian Multilevel Modeling to Single Trial Dynamics: A Demonstration in Aversive Conditioning","authors":"Andrew H. Farkas,&nbsp;Judith Cediel Escobar,&nbsp;Faith E. Gilbert,&nbsp;Christian Panitz,&nbsp;Mingzhou Ding,&nbsp;Andreas Keil","doi":"10.1002/hbm.70360","DOIUrl":"https://doi.org/10.1002/hbm.70360","url":null,"abstract":"<p>Aversive conditioning changes visuocortical responses to conditioned cues, and the generalization of these changes to perceptually similar cues may provide mechanistic insights into anxiety and fear disorders. Yet, as in many areas of cognitive neuroscience, testing hypotheses about trial-by-trial dynamics in conditioning paradigms is challenged by poor single-trial signal-to-noise ratios (SNR), missing trials, and inter-individual differences. The present technical report demonstrates how a state-of-the-art Bayesian workflow can overcome these issues, using a preliminary sample of simultaneously recorded EEG-fMRI data. A preliminary group of observers (<i>N</i> = 24) viewed circular gratings varying in orientation, with only one orientation paired with an aversive outcome (noxious electric pulse). Gratings were flickered at 15 Hz to evoke steady-state visual evoked potentials (ssVEPs), recorded with 31 channels of EEG in an MRI scanner. First, the benefits of a Bayesian multilevel structure are demonstrated on the fMRI data by improving a standard fMRI first-level multiple regression. Next, the Bayesian modeling approach is demonstrated by applying a theory-driven learning model to the EEG data. The multilevel structure of the Bayesian learning model informs and constrains estimates per participant, providing an interpretable generative model. In the example analysis provided in this report, it showed superior cross-validation accuracy and provided insights into participant-level learning dynamics. It also isolated the generalization effects of conditioning, providing improved statistical certainty. Lastly, missing trials were interpolated and weighted appropriately using the full model's structure. This is a critical aspect for single-trial analyses of simultaneously recorded physiological measures because each added measure will typically increase the number of trials missing a complete set of observations. The present report aims to illustrate the utility of this analytical framework. It shows how models may be iteratively built and compared in a modern Bayesian workflow. Future models may use different conceptualizations of learning, allow integration of clinically relevant factors, and enable the fusion of different simultaneous recordings such as EEG, autonomic, behavioral, and hemodynamic data.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 14","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70360","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145146953","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":"st-DenseViT: A Weakly Supervised Spatiotemporal Vision Transformer for Dense Prediction of Dynamic Brain Networks","authors":"Behnam Kazemivash,&nbsp;Pranav Suresh,&nbsp;Dong Hye Ye,&nbsp;Armin Iraji,&nbsp;Jingyu Liu,&nbsp;Sergey Plis,&nbsp;Peter Kochunov,&nbsp;David C. Zhu,&nbsp;Vince D. Calhoun","doi":"10.1002/hbm.70364","DOIUrl":"https://doi.org/10.1002/hbm.70364","url":null,"abstract":"<p>Modeling dynamic neuronal activity within brain networks enables the precise tracking of rapid temporal fluctuations across different brain regions. However, current approaches in computational neuroscience fall short of capturing and representing the spatiotemporal dynamics within each brain network. We developed a novel weakly supervised spatiotemporal dense prediction model capable of generating personalized 4D dynamic brain networks from fMRI data, providing a more granular representation of brain activity over time. We developed a model that leverages the vision transformer (ViT) as its backbone, jointly encoding spatial and temporal information from fMRI inputs using two different configurations: space–time and sequential encoders. The model generates 4D brain network maps that evolve over time, capturing dynamic changes in both spatial and temporal dimensions. In the absence of ground-truth data, we used spatially constrained windowed independent component analysis (ICA) components derived from fMRI data as weak supervision to guide the training process. The model was evaluated using large-scale resting-state fMRI datasets, and statistical analyses were conducted to assess the effectiveness of the generated dynamic maps using various metrics. Our model effectively produced 4D brain maps that captured both inter-subject and temporal variations, offering a dynamic representation of evolving brain networks. Notably, the model demonstrated the ability to produce smooth maps from noisy priors, effectively denoising the resulting brain dynamics. Additionally, statistically significant differences were observed in the temporally averaged brain maps, as well as in the summation of absolute temporal gradient maps, between patients with schizophrenia and healthy controls. For example, within the Default Mode Network (DMN), significant differences emerged in the temporally averaged space–time configurations, particularly in the thalamus, where healthy controls exhibited higher activity levels compared to subjects with schizophrenia. These findings highlight the model's potential for differentiating between clinical populations. The proposed spatiotemporal dense prediction model offers an effective approach for generating dynamic brain maps by capturing significant spatiotemporal variations in brain activity. Leveraging weak supervision through ICA components enables the model to learn dynamic patterns without direct ground-truth data, making it a robust and efficient tool for brain mapping. Significance: This work presents an important new approach for dynamic brain mapping, potentially opening up new opportunities for studying brain dynamics within specific networks. By framing the problem as a spatiotemporal dense prediction task in computer vision, we leverage the spatiotemporal ViT architecture combined with weakly supervised learning techniques to efficiently and effectively estimate these maps.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 14","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70364","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145146950","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":"Neural Correlates of Peripheral Inflammation in Major Depressive Disorder and Their Transcriptomic Architecture, Neurochemical Basis, and Behavioral Relevance","authors":"Wenming Zhao,&nbsp;Dao-min Zhu,&nbsp;Yongqi Zhang,&nbsp;Yu Zhang,&nbsp;Yuxian Shen,&nbsp;Yongqiang Yu,&nbsp;Jiajia Zhu","doi":"10.1002/hbm.70371","DOIUrl":"https://doi.org/10.1002/hbm.70371","url":null,"abstract":"<p>The role of inflammation in the neuropathology of major depressive disorder (MDD) is evident. However, the neural correlates of peripheral inflammation in MDD and their transcriptomic architecture, neurochemical basis, and behavioral relevance have not been systematically investigated. We adopted functional and diffusion magnetic resonance imaging to assess gray matter function and white matter integrity, whose associations with serum C-reactive protein (CRP) levels were explored in a large sample of MDD patients. Further, we examined the spatial relationships of the identified neural correlates of CRP with transcriptome, neurotransmitter, and behavioral domain atlases. Higher serum CRP levels were associated with local gray matter function alterations and widespread white matter integrity changes in MDD patients, but not HC. Moreover, the gray matter functional correlates of CRP in MDD were spatially correlated with functional gene categories involving inflammatory signaling pathways (macrophage activation, NF-κB signaling, and JUN kinase activity), specific neurotransmitters (serotonin, GABA, and glutamate), and diverse behavioral domains (sensorimotor, cognition, emotion, and sleep). In addition, some neural correlates of CRP (anterior cingulate cortex function and superior corona radiata integrity) mediated the relationships of serum CRP with sustained attention and sleep structure in MDD patients. Our findings may not only confirm the role of inflammation in the neuropathology of MDD, but also inform a novel conceptualization of targeting inflammatory processes to treat this disorder.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 14","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70371","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145146955","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 Mismatch Negativity Compared: EEG, SQUID-MEG, and Novel 4Helium-OPMs","authors":"Tjerk P. Gutteling,&nbsp;Jérémie Mattout,&nbsp;Sébastien Daligault,&nbsp;Julien Jung,&nbsp;Etienne Labyt,&nbsp;Denis Schwartz,&nbsp;Françoise Lecaignard","doi":"10.1002/hbm.70368","DOIUrl":"https://doi.org/10.1002/hbm.70368","url":null,"abstract":"<p>Magneto-encephalography (MEG) provides a higher spatial resolution than electro-encephalography (EEG) to measure human auditory responses. However, conventional cryogenic MEG systems (SQUID-MEG) suffer from severe technological restrictions limiting, for instance, routine clinical use. Fortunately, a new generation of MEG sensors, optically pumped magnetometers (OPMs), has been developed to bridge the gap, combining the wearability of EEG with the benefits of MEG signal acquisition. We aim to assess their potential for studying auditory mismatch processing. The auditory mismatch negativity (MMN) is a well-characterized evoked component observable using a passive oddball paradigm with two-tone sound sequences. It has been extensively described using both EEG and MEG and is part of many EEG-based clinical applications, such as the assessment of patients with disorders of consciousness. MMN is therefore a relevant candidate to evaluate OPM performance. We use recently developed Helium-OPMs, which are high dynamic range MEG sensors that operate at room temperature. We compare their performance with cryogenic SQUID-MEG and EEG in a passive frequency oddball paradigm. Results show a significant MMN across subjects in all modalities as well as a high temporal similarity between modalities. Signal-to-noise ratios were also similar, and detection of significant individual MMN (within-subjects) using the OPM system was equal to or better than EEG. Given that the OPM system tested here is a prototype comprised of only five sensors, these results are a promising step towards wearable MEG that combines the advantages of MEG and EEG.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 14","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70368","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145146829","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":"Improvement on Attention Networks Among Military Personnel: The Right IFG and tDCS Matter","authors":"Hongliang Lu,&nbsp;Ye Miao,&nbsp;Yajuan Zhang,&nbsp;Zhihua Guo,&nbsp;Xianyang Wang,&nbsp;Qianbo Na,&nbsp;Xuanyi Tan,&nbsp;Yan Zhang,&nbsp;Xiaofei Yan,&nbsp;Yang Cao,&nbsp;Wendong Hu,&nbsp;Peng Huang,&nbsp;Jin Ma","doi":"10.1002/hbm.70365","DOIUrl":"https://doi.org/10.1002/hbm.70365","url":null,"abstract":"<p>Attention is crucial for military personnel to recover from mental dysfunction and maintain superior cognitive abilities. Transcranial electrical stimulation (tES) is a promising training method for enhancing attention; however, the optimal parameters for tES interventions remain unclear. This study aims to identify the most responsive cortical area and the most effective tES type for attention enhancement. In Experiment 1, 62 healthy male soldiers were examined to determine the most effective stimulation target for attention improvement after 4 (cathodal electrodes) × 1 (anodal electrodes) high-definition transcranial direct current stimulation (tDCS) on the right inferior frontal gyrus (IFG) or the left dorsolateral prefrontal cortex (DLPFC). Experiment 2, involving 75 participants, focused on modulating the previously identified appropriate cortex using both high-definition transcranial alternating current stimulation (tACS) and tDCS to ascertain the most effective tES method based on behavioral and neural activity changes. Both experiments were double-blind and sham-controlled. Executive control of attention networks was significantly improved after tDCS modulation of both the right IFG and the left DLPFC. Notably, only the modulation of the right IFG effectively decreased the Stroop effect. While both tACS and tDCS on the right IFG induced lower neural activity related to the Stroop effect, only tDCS significantly reduced the behavioral performance of the Stroop effect. Consequently, the right IFG emerges as a key targeted cortex for tES modulation in enhancing attention, with tDCS proving more effective than tACS in regulating the right IFG to improve executive control. These findings lay the groundwork for applying tES interventions in the training of attention abilities among military personnel.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 14","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70365","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145146954","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":"Exploring Deep Magnetoencephalography via Thalamo-Cortical Sleep Spindles","authors":"Gregory F. Rattray,&nbsp;Hugo R. Jourde,&nbsp;Sylvain Baillet,&nbsp;Emily B. J. Coffey","doi":"10.1002/hbm.70354","DOIUrl":"https://doi.org/10.1002/hbm.70354","url":null,"abstract":"<p>Subcortical brain regions like the thalamus are integral to numerous sensory and cognitive functions. Magnetoencephalography (MEG) enables the study of widespread brain networks with high temporal resolution, but the degree to which deep sources like the thalamus can be resolved remains unclear. Functional connectivity methods may enhance differentiation, yet few studies have extended them beyond the cortex. We investigated the possibility of resolving deep sources via connectivity patterns during thalamo-cortical sleep spindles to leverage their well-characterized circuitry, and during spindle-free periods of non-rapid eye movement sleep to explore neural recordings that lack such high-amplitude bursts of activity. MEG and electroencephalography (EEG) were recorded in 19 participants during a 2-h nap. Spindle and non-spindle periods were identified, and connectivity was assessed using coherence and imaginary coherence within a spindle-related network. Graph theory was also applied to identify network hubs. As expected, functional connectivity increased during spindles within a distributed thalamo-cortical-hippocampal network. Cortical connectivity patterns allowed differentiation among small thalamic nuclei, but metric choice and contrast use influenced topography and distance effects. Graph theory revealed distinct cortical, thalamic, and hippocampal contributions to fast (13–16 Hz) and slow (10–13 Hz) sigma-band connectivity. These findings demonstrate that MEG functional connectivity can resolve deep brain networks during NREM sleep and during spindles, and demonstrate how it can be used to study the functional roles of subcortical regions non-invasively in healthy humans. By clarifying methodological influences, we aim to guide future research design and interpretation.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 14","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70354","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145146897","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 Combined Neuroanatomy, Ex Vivo Imaging, and Immunohistochemistry Defined MRI Mask for the Human Paraventricular Nucleus of the Thalamus","authors":"Madison R. Tetzlaff,&nbsp;Bianca T. Leonard,&nbsp;Michael A. Yassa,&nbsp;Tallie Z. Baram,&nbsp;Jerod M. Rasmussen","doi":"10.1002/hbm.70366","DOIUrl":"10.1002/hbm.70366","url":null,"abstract":"<p>The paraventricular nucleus of the thalamus (PVT) is an evolutionarily conserved midline thalamic structure known to contribute to arousal, interoceptive states, and motivated behaviors. Yet, a consensus anatomical definition of the human PVT across tissue-based and MRI-based approaches remains elusive, thereby limiting reliable translation between its cellular characteristics and in vivo functional connectivity. To address this challenge, we describe a histologically informed PVT segmentation compatible with standard 3 T MR imaging pipelines. We performed postmortem anatomical MRI scans on an intact whole brain and an excised thalamic block, manually segmented the PVT at high resolution using ex vivo calretinin staining and neuroanatomical landmarks, registered the resulting image-label pair to a commonly used MRI template space (Montreal Neurological Institute's MNI152), and performed a comparative reanalysis using this newly defined mask. This tissue-grounded PVT mask largely overlaps spatially with existing MRI-based PVT masks, with the exception of additional voxels posteriorly. Importantly, the functional connectivity patterns of this tissue-grounded mask are highly consistent with those previously reported. Collectively, this multimodal definition of the human PVT balances tissue-based ground truth with in vivo MRI features, providing a valuable resource for advancing translation between cellular level features identified by histology and in vivo functional connectivity at the meso/macro scale in the understudied human PVT.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 14","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70366","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145137360","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":"Multimodal Neuroimaging-Guided Stratification in Amyotrophic Lateral Sclerosis Reveals Three Disease Subtypes: A Multi-Cohort Analysis","authors":"Tobias R. Baumeister,&nbsp;Henk-Jan Westeneng,&nbsp;Leonard van den Berg,&nbsp;Canadian ALS Neuroimaging Consortium (CALSNIC),&nbsp;Sanjay Kalra,&nbsp;Yasser Iturria-Medina","doi":"10.1002/hbm.70341","DOIUrl":"10.1002/hbm.70341","url":null,"abstract":"<p>Amyotrophic lateral sclerosis (ALS) is a multisystem disease with marked pathophysiological and clinical heterogeneity, making individual and objective characterization of the degree of disease progression and disease-related subtrajectories challenging. Here, we use in vivo multimodal neuroimaging data and computational models to generate personalized indices of ALS progression and subtrajectory. We used structural and diffusion weighted imaging of 691 participants (58% ALS) from two independent ALS data sets (North American and Utrecht cohorts) to extract regional values of grey matter (DM) density and white matter (WM) microstructural integrity. Contrastive trajectory inference (cTI) allowed us to identify and separate latent, multivariate patterns in neuroimaging features highlighting ALS-associated pathological processes, which were used to generate subject-specific indices of disease progression and subtrajectory. Disease subtrajectories were based on distinct patterns of alterations in neuroimaging data considering subjects at different disease progression levels. The neuroimaging-based, personalized index of disease progression is indicative of clinical symptom severity (North American: <i>p</i> &lt; 0.01 and Utrecht: <i>p</i> &lt; 0.01) and displays alignment with the King's College staging system (<i>p</i> = 0.001 and <i>p</i> = 0.002). Three ALS subtrajectories were identified that displayed distinct alterations in the motor, limbic system, and widespread cortical and subcortical changes that also differed in clinical symptom manifestation. Our analysis has shown that neuroimaging data encodes subject-specific, disease-related patterns that can be leveraged to obtain an in vivo proxy of disease progression and putative disease subtype.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"46 14","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70341","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145130513","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}