Human Brain Mapping最新文献

{"title":"Distinct Physiological Mechanisms Drive Grey Matter Plasticity in Complex Versus Simple Sequence Learning","authors":"Jhelum Paul,&nbsp;A. T. P. Jäger,&nbsp;J. Huck,&nbsp;C. L. Tardif,&nbsp;A. Villringer,&nbsp;C. J. Gauthier,&nbsp;P. L. Bazin,&nbsp;Christopher J. Steele","doi":"10.1002/hbm.70562","DOIUrl":"10.1002/hbm.70562","url":null,"abstract":"<p>Ultra-high field magnetic resonance imaging at sub-millimeter resolution opens the possibility to assess subtle longitudinal changes in brain structure and function. Identifying the regions and putative mechanisms involved in learning specific motor sequences is a key step towards understanding neuroplasticity. To disambiguate sequence-specific learning from simple motor execution, the present study trained an experimental group over five consecutive days on a complex motor sequence and contrasted them with a control group who performed a simple sequence. Both groups were scanned at 4 time points with magnetic resonance imaging at 7 Tesla with MP2RAGE. Training-related grey matter (GM) structural plasticity was assessed with voxel-based morphometry (VBM: time by group interaction) on T1w uniform intensity images and followed up with a focused investigation of quantitative T1 values (qT1) to probe the physiological changes driving GM plasticity. Our interaction analyses identified significant differences in the precuneus, superior parietal cortex (SPC), and angular gyrus (AG) where GM increases were greater in the experimental group. Of these regions, only the left SPC (during slow learning) exhibited sequence-specific plasticity—where the magnitude of change was greater in the experimental vs. the control group. Interestingly, while the experimental group showed increased GM volume, the control group was characterized by decreases. Post hoc comparisons revealed that the control group exhibited increasing T1 across days 1, 2 and 5, while the experimental group initially increased (day 1 to 2) and then decreased (day 2 to 5), suggesting that the two groups underwent differential physiological change as a function of training. These findings align with invasive animal studies showing that learning simple tasks is characterized by angiogenesis while learning complex sequences initially leads to synaptogenesis and is then followed by intracortical myelination as the sequence is well learned. Our findings provide initial evidence in humans that learning a complex sequence induces GM increases that are likely driven by synaptogenesis for initial encoding and myelogenesis for later learning and consolidation, while habituating to a simple repeated task leads to GM decreases due to attenuated blood flow.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 8","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70562","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148156311","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":"Axon Diameter Mapping in the Living Human Brain with Ultra-High-Gradient Diffusion MRI at 500 mT/m Gradient Strength","authors":"Yixin Ma,&nbsp;Laleh Eskandarian,&nbsp;Kwok-Shing Chan,&nbsp;Hansol Lee,&nbsp;Gabriel Ramos-Llordén,&nbsp;Aneri Bhatt,&nbsp;Julianna Gerold,&nbsp;Mirsad Mahmutovic,&nbsp;Boris Keil,&nbsp;Hong-Hsi Lee,&nbsp;Susie Y. Huang","doi":"10.1002/hbm.70553","DOIUrl":"10.1002/hbm.70553","url":null,"abstract":"<p>Pushing the resolution limit of axon diameter mapping in the living human brain requires higher gradient strength than is currently available on most clinical MRI systems. The noninvasive quantification of axon diameter not only enables the exploration of axonal damage in a wide range of neurological disorders but also provides fundamental insights into axonal organization and conduction patterns of white matter tracts. The goal of this study was to evaluate the sensitivity of axon diameter mapping to small diameter axons using the next-generation Connectome MRI scanner (Connectome 2.0), which features a maximum gradient strength of 500 mT/m and slew rate of 600 T/m/s, compared to the original Connectome 1.0 scanner with 300 mT/m gradient strength. We applied the AxCaliber-SMT model to diffusion MRI data from 40 healthy adults, comprising 20 participants scanned on Connectome 1.0 before it was decommissioned and a separate cohort of 20 age- and sex-matched participants scanned on Connectome 2.0. Our findings are based on group-level comparisons between these two cohorts. The theoretical minimum detectable axon diameter was 2.5 μm on Connectome 2.0 and 3.6 μm on Connectome 1.0. The MR-estimated axon diameter in the corticospinal tract on the Connectome 2.0 scanner was 2.66 ± 0.54 μm, significantly lower than 3.35 ± 1.00 μm on Connectome 1.0 (Welch's t-test: <i>p</i> = 0.0110). Comparison was performed across independently acquired datasets from age- and sex-matched individuals on different scanners; therefore, the observed group differences should be interpreted as strong and supportive, though not strictly causal, evidence of the proposed scanner capability. Furthermore, we examined 7 healthy adults for scan-rescan repeatability and demonstrated that the voxel-wise mean absolute difference in axon diameter estimates between scan and rescan decreased to 0.29 μm on the Connectome 2.0 (vs. 0.65 μm on the Connectome 1.0), indicating improved repeatability of the axon diameter estimates. These improvements are enabled not only by the higher gradient strength of Connectome 2.0, but also by the associated reduction in echo time and increase in SNR, which together enhance sensitivity to restricted diffusion and improve parameter reliability. Our findings highlight the importance of stronger and faster gradients for accurate and robust mapping of the axonal microstructure in the human brain.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 8","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70553","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148156361","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":"Primary Somatosensory to Motor Cortex Microstructural Connectivity Predicts the Mu-Rhythm Phase Effect on Corticospinal Excitability: An EEG-TMS Study","authors":"Juliana R. Hougland,&nbsp;Timo Roine,&nbsp;Andreas Jooß,&nbsp;Dania Humaidan,&nbsp;Ulf Ziemann","doi":"10.1002/hbm.70576","DOIUrl":"10.1002/hbm.70576","url":null,"abstract":"&lt;p&gt;The employment of brain-state dependent stimulation has been favored in recent years to reduce the variability in effects and increase the benefits of non-invasive brain stimulation methods, such as transcranial magnetic stimulation (TMS) (Baur et al. &lt;span&gt;2020&lt;/span&gt;; Bergmann &lt;span&gt;2018&lt;/span&gt;; Wischnewski et al. &lt;span&gt;2022&lt;/span&gt;; Zrenner et al. &lt;span&gt;2018&lt;/span&gt;, &lt;span&gt;2023&lt;/span&gt;). Brain state is generally determined through electroencephalography (EEG) oscillations (Wischnewski et al. &lt;span&gt;2022&lt;/span&gt;; Zrenner et al. &lt;span&gt;2018&lt;/span&gt;, &lt;span&gt;2023&lt;/span&gt;). In particular, the sensorimotor mu-rhythm phase reflects fluctuating corticospinal excitability states. When TMS is delivered to the primary motor cortex (M1) at the trough or early rising phase of the mu-rhythm, larger motor-evoked potentials (MEP) are elicited, representing a high corticospinal excitability state (Suresh and Hussain &lt;span&gt;2023&lt;/span&gt;; Wischnewski et al. &lt;span&gt;2022&lt;/span&gt;; Zrenner et al. &lt;span&gt;2018&lt;/span&gt;, &lt;span&gt;2023&lt;/span&gt;). The opposite (i.e., smaller MEPs) is found when delivering TMS at the mu-phase peak, thus indicating low excitability (Suresh and Hussain &lt;span&gt;2023&lt;/span&gt;; Wischnewski et al. &lt;span&gt;2022&lt;/span&gt;; Zrenner et al. &lt;span&gt;2018&lt;/span&gt;, &lt;span&gt;2023&lt;/span&gt;). Although multiple studies have shown an effect of mu-phase on MEP amplitude, this mu-phase effect is variable at the single-subject level (Hougland et al. &lt;span&gt;2025&lt;/span&gt;; Kirchhoff et al. &lt;span&gt;2024&lt;/span&gt;; Zrenner et al. &lt;span&gt;2023&lt;/span&gt;). In fact, only approximately half of subjects demonstrate a significant mu-phase effect (Hougland et al. &lt;span&gt;2025&lt;/span&gt;; Zrenner et al. &lt;span&gt;2023&lt;/span&gt;), and some studies found no effect of mu-phase on corticospinal excitability (Madsen et al. &lt;span&gt;2019&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;The variability in the strength of the mu-phase effect could be, in part, due to structural differences in the brain. The effects and propagation of TMS are influenced by white matter architecture and microstructure (Martin-Signes et al. &lt;span&gt;2024&lt;/span&gt;; Ning et al. &lt;span&gt;2022&lt;/span&gt;; Rodriguez-Herreros et al. &lt;span&gt;2015&lt;/span&gt;), which can be assessed with diffusion magnetic resonance imaging (dMRI). For example, fractional anisotropy (FA) is a dMRI measure of the microstructural integrity of white matter tissue. Lower FA in cerebral white matter, pyramidal tract, and corpus callosum has been associated with higher resting motor thresholds (RMT) (Kloppel et al. &lt;span&gt;2008&lt;/span&gt;). Additionally, FA of corpus callosum fibers was positively correlated with the level of M1 interhemispheric inhibition measured with TMS (Koerte et al. &lt;span&gt;2009&lt;/span&gt;; Wahl et al. &lt;span&gt;2007&lt;/span&gt;). In regard to mu-rhythm phase, higher fiber density and cross-section of callosal motor fibers were positively related to the synchronization of mu-rhythm peak and trough phases between the left and right M1 (Momi et al. &lt;span&gt;2022&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;Previous research has shown that the phase of the mu-rhythm signal extr","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 8","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70576","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148156304","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":"Cardiometabolic Risk and Structural Brain Development in a Large Community-Based US Cohort","authors":"Dani Beck,&nbsp;Lars T. Westlye,&nbsp;Christian K. Tamnes","doi":"10.1002/hbm.70575","DOIUrl":"10.1002/hbm.70575","url":null,"abstract":"<p>Cardiometabolic risk factors are already detectable in childhood and adolescence, but their relation to the developing brain remains unclear. The current study tested whether poorer cardiometabolic health is associated with brain structure and microstructure development in 10–17-year-old youth. Using the Adolescent Brain Cognitive Development Study, we analysed data from 3527 participants with 4433 observations across three waves (single wave: <i>n</i> = 2745; two waves: <i>n</i> = 658 participants; three waves: <i>n</i> = 124 participants). We related anthropometric (body-mass index, waist circumference), cardiovascular (systolic and diastolic blood pressure, resting heart rate) and metabolic (haemoglobin A1c, high-density lipoprotein cholesterol) indices to global cortical thickness and surface area, and to white matter fractional anisotropy and mean diffusivity. Bayesian multilevel models were fitted to estimate main and time-interaction effects, and sensitivity analyses tested within-person change, prospective prediction to the next wave, and replaced chronological age with puberty status. Higher resting heart rate was associated with higher mean diffusivity, an association that strengthened over time. Higher waist circumference was associated with larger surface area. Other cardiometabolic measures favoured the null, and sensitivity analyses provided little evidence that wave-to-wave changes in cardiometabolic health tracked contemporaneous brain change or predicted subsequent brain structure. Across late childhood and adolescence, brain architecture appears largely insensitive to short-term variation in cardiometabolic risk indices.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 8","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70575","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148149642","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":"Cerebellar Transcranial Alternating Current Stimulation in the Theta Band Prevents Recall of the Initial Fear Association After Extinction Training","authors":"Giorgi Batsikadze,&nbsp;Zsofia Spisak,&nbsp;Philippe Zeidan,&nbsp;Michael Klein,&nbsp;Enzo Nio,&nbsp;Thomas M. Ernst,&nbsp;Nicolas Diekmann,&nbsp;Sophia Göricke,&nbsp;Sen Cheng,&nbsp;Christian J. Merz,&nbsp;Fatemeh Yavari,&nbsp;Michael A. Nitsche,&nbsp;Andreas Thieme,&nbsp;Dagmar Timmann","doi":"10.1002/hbm.70556","DOIUrl":"10.1002/hbm.70556","url":null,"abstract":"<p>Although the neural network underlying fear extinction has been extensively studied, the cerebellum's role has received little attention – despite its well-established involvement in associative learning. Our study therefore aimed to provide additional evidence that the cerebellum is part of the circuitry supporting fear-extinction processes, and to get a better understanding of how the cerebellum may contribute to fear extinction learning. In this study, 6 Hz cerebellar transcranial alternating current stimulation (ctACS) or sham stimulation was applied during extinction training in a two-day differential fear conditioning paradigm in young, healthy participants undergoing 3T fMRI, using a double-blind randomized design. Acquisition and extinction training occurred on day 1, followed by extinction recall on day 2. Skin conductance responses showed that 6 Hz ctACS applied during extinction training reduced spontaneous fear recovery during recall. During extinction training, differential fMRI activation (CS+ &gt; CS-) was significantly higher in the occipital cortex in the verum compared to the sham group. During recall, differential fMRI activation was significantly higher in the precentral gyrus in the sham compared to the verum group at the time the aversive unconditioned response (US) was expected but did not occur. Furthermore, in recall, parametric modulation based on trial-by-trial model-derived prediction errors for no-US events revealed significantly higher activation in frontal cortical areas, including the anterior cingulate cortex, and parietal cortical areas in the sham compared to the verum group. Volume of interest analyses showed significantly higher beta values towards the CS+ compared to the CS- in the sham group, but not in the verum group in the right insula related to the prediction of the US and its unexpected omission in early recall. Although direct stimulation effects cannot be ruled out, 6 Hz ctACS-related increases in activation in visual regions during extinction training may indicate enhanced attention to CS-related visual and/or contextual cues. Furthermore, 6 Hz ctACS facilitated the downregulation of brain regions involved in fear conditioning during recall, potentially reducing spontaneous recovery. Future studies are warranted to further evaluate whether enhancement of cerebellar theta oscillations can help to stabilize extinction effects and therefore support exposure therapy.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 8","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70556","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148149613","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":"Improved Multiscale Structural Mapping with Supervertex Vision Transformer for the Detection of Alzheimer's Disease Neurodegeneration","authors":"Geonwoo Baek,&nbsp;David H. Salat,&nbsp;Ikbeom Jang,&nbsp;for the Alzheimer's Disease Neuroimaging Initiative","doi":"10.1002/hbm.70548","DOIUrl":"10.1002/hbm.70548","url":null,"abstract":"<p>Alzheimer's disease (AD) confirmation often relies on positron emission tomography (PET) or cerebrospinal fluid (CSF) analysis, which are costly and invasive. Consequently, structural MRI biomarkers such as cortical thickness (CT) are widely used for noninvasive AD screening. Multiscale structural mapping (MSSM) was recently proposed to integrate gray–white matter contrasts (GWCs) with CT from a single T1-weighted MRI (T1w) scan. Building on this framework, we propose MSSM+, together with surface supervertex mapping (SSVM) and a Supervertex Vision Transformer (SV-ViT). 3D T1w images from individuals with AD and cognitively normal (CN) controls were analyzed. MSSM+ extends MSSM by incorporating sulcal depth and cortical curvature at the vertex level. SSVM partitions the cortical surface into supervertices (surface patches) that effectively represent inter- and intra-regional spatial relationships. SV-ViT is a Vision Transformer architecture operating on these supervertices, enabling anatomically informed learning from surface mesh representations. Compared with MSSM, MSSM+ identified more spatially extensive and statistically significant group differences between AD and CN. In AD versus CN classification, MSSM+ achieved a 3%p higher area under the precision–recall curve than MSSM. Vendor-specific analyses further demonstrated reduced signal variability and consistently improved classification performance across MR manufacturers relative to CT, GWCs, and MSSM. These findings suggest that MSSM+ combined with SV-ViT is a promising MRI-based imaging marker for AD detection prior to CSF/PET confirmation.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 8","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70548","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148143417","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 to “Evidence of White Matter Neuroinflammation in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Diffusion-Based Neuroinflammation Imaging Study”","authors":"","doi":"10.1002/hbm.70544","DOIUrl":"10.1002/hbm.70544","url":null,"abstract":"&lt;p&gt;Yu, Q., K. Kothe, R. A. Kwiatek, et al. 2026. “Evidence of White Matter Neuroinflammation in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Diffusion-Based Neuroinflammation Imaging Study.” &lt;i&gt;Human Brain Mapping&lt;/i&gt; 47, no. 4: e70505. https://doi.org/10.1002/hbm.70505.&lt;/p&gt;&lt;p&gt;In the Abstract section, the text “This study provides in vivo evidence of white matter neuroinflammation in ME/CFS, characterised by cerebral edema (reduced NII-HR), cellular infiltration (reduced NII-RF), and axonal reorganisation (increased NII-FF).” was incorrect and should have read: “This study provides in vivo evidence of white matter neuroinflammation in ME/CFS, characterised by cerebral edema (reduced NII-HR), cell shape change or a chronic depletion of microglia (reduced NII-RF), and axonal reorganisation (increased NII-FF).”&lt;/p&gt;&lt;p&gt;In Table 2, the text “Suggests increased inflammatory cell infiltration” was incorrect and should have read: “Suggests cell shape change or a chronic depletion of microglia.” The correct table and its caption are provided below.&lt;/p&gt;&lt;p&gt;In the second paragraph of the Discussion section, the text “NII-RF reflects cellularity related to restricted isotropic diffusion, which may correspond to increased inflammatory cell infiltration.” was incorrect and should have read: “NII-RF reflects cellularity related to restricted isotropic diffusion. Rather than large, focal inflammatory lesions, ME/CFS may involve a subtle and chronic activation of microglia that causes the cells to change shape (e.g., from ramified to amoeboid) without necessarily increasing their number. The decreased NII-RF may reflect the shape changes of activated microglia or a chronic depletion of microglia. The reduction in NII-HR (extracellular water) suggests that the brain is not experiencing vasogenic edema (which would increase extracellular water) but rather a form of cellular swelling or” cytotoxic-like “edema where the water moves from the extracellular space into the cells or axonal fibres. This matches the observation of higher NII-AD and NII-FF, which would occur as the fibres swell and displace the extracellular fluid.”&lt;/p&gt;&lt;p&gt;In the third paragraph of the Discussion section, the text “The regions showing increased NII-AD and NII-MD largely overlapped with areas of reduced NII-HR and NII-RF, suggesting that inflammation-related edema and cellular infiltration may increase overall diffusivity in these regions.” was incorrect and should have read: “The regions showing increased NII-AD and NII-MD largely overlapped with areas of reduced NII-HR and NII-RF, suggesting that inflammation-related edema and cell shape change or a chronic depletion of microglia may increase overall diffusivity in these regions.”&lt;/p&gt;&lt;p&gt;In the fourth paragraph of the Discussion section, the text “Lower RF reflects more inflammatory cellularity, these positive associations imply that less cellular infiltration is associated with better mental health and better function.” was incorrect ","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 8","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.70544","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148143390","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":"Evaluation of a New Paracingulate Sulcus Identification and Measurement Protocol.","authors":"Héloïse de Vareilles, Samantha C Mitchell, Jane R Garrison, Shun-Chin Jim Wu, Laura Alvarez-Sanchez, Reuben Thomas, Suveththa Kugan, Atheer Al-Manea, Michail Mamalakis, Lynn Egeland Mørch-Johnsen, Ingrid Agartz, John Suckling, Jon S Simons, Graham K Murray","doi":"10.1002/hbm.70574","DOIUrl":"10.1002/hbm.70574","url":null,"abstract":"<p><p>The folding pattern of the anterior cingulate cortex is variable among individuals. The paracingulate sulcus (PCS), in particular, can be difficult to identify because of this variability. In this paper, we assessed the benefits of a new protocol to identify the PCS and measure its length using 3D reconstructions of the brain obtained through the BrainVISA software. Both the previous state-of-the-art protocol and the new protocol were applied to identify the PCS in subjects from a UK cohort (n = 50), with the length of the PCS computed automatically by BrainVISA after PCS identification. We assessed inter-rater reliability for PCS length under both protocols and the correlation of PCS length values output by the two protocols. Inspection of the results indicated an advantage of the new protocol as there are 8 out of 100 hemispheres in which the old protocol detects a PCS due to the mislabelling of the intra-limbic sulcus as the cingulate sulcus and the new protocol does not. This advantage is conferred by the incorporation of identification of the intra-limbic sulcus (when present) in the new protocol. For instances where the protocols agreed on the presence of a PCS, the new protocol for PCS length obtained intra-class correlations of 0.85 and 0.86 on respectively untrained and trained experimenters, compared to 0.81 when trained experimenters used the previous protocol. The PCS length correlation between both protocols was 0.73 for the entire sample and 0.85 after excluding instances where the protocols disagreed on the presence of a PCS. These findings suggest that taking into account the intra-limbic sulcus and taking advantage of 3D sulcal visualisation may help improve reliable PCS identification, and that the new protocol is a reliable tool that is likely to prove useful in research into cingulate and paracingulate cortical folding.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 8","pages":"e70574"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13266417/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148251293","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":"Modulation of Visual Contrast Perception Associated With Dorsal Attention Network Connectivity Assessed by Magnetoencephalography.","authors":"Alfredo L Sklar, Brian A Coffman, Fran López-Caballero, Dylan Seebold, Jenay Kocsis, Lauren Fowler, Hayley Rhorer, Jack Kavanagh, Dean F Salisbury","doi":"10.1002/hbm.70554","DOIUrl":"10.1002/hbm.70554","url":null,"abstract":"<p><p>The impact of executive attention on visual cortical responses depends upon the contrast of input stimuli. Functional neuroimaging has difficulty capturing non-linear gain modulations of the contrast response function (CRF) and dynamic communication within visual attention networks subserving it. The current study utilized magnetoencephalography (MEG) to examine gain modulation within primary visual cortex (V1) and its connectivity with regions of the dorsal attention network (DAN) during covert attention. Twenty-five participants completed a spatial covert attention task including neutral and valid cues. MEG was recorded and eye position monitored throughout the task. The CRF and its relevant parameters were modeled using peak V1 evoked responses. Cue-related alpha-band desynchronization within contralateral V1 and event-related spectral perturbations across DAN regions were assessed by wavelet analysis. Weighted phase-lag index was used to examine DAN-V1 functional connectivity. Valid cue trials produced increased CRF maxima without a significant impact on mid-saturation or baseline levels. Alpha desynchronization was observed between 10 and 12 Hz during cue presentation in V1. DAN-V1 functional connectivity, most robust within 10-12 Hz, was uniquely associated with larger asymptotic V1 response levels within this range. MEG recordings revealed a pattern of V1 response gain during covert attention associated with DAN-V1 connectivity, advancing our knowledge of this network's frequency-specific influence over gain modulation within basic visual processing centers. These findings highlight the advantages of MEG for examining interactions between sensory and attentional gain properties of the human visual system, providing a comprehensive understanding of their underlying local and distributed network dynamics.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 8","pages":"e70554"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13238592/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148015076","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":"Striatal Prediction Error Tracking Moderates the Influence of Social Exposure on Adolescent Substance Use Curiosity.","authors":"Jessica S Flannery, Elizabeth S Escalante, Ruofan Ma, Kristen A Lindquist, Eva H Telzer","doi":"10.1002/hbm.70545","DOIUrl":"10.1002/hbm.70545","url":null,"abstract":"<p><p>Adolescence is a period of social development marked by increased sensitivity to social feedback and substance use experimentation. Although reinforcement learning (RL) models provide a powerful framework for examining how individuals learn from experience, they have rarely been applied to understand how adolescents learn from social experiences or how these processes relate to real-world behavioral outcomes. In a sample of 261 youth (11.0 ± 1.6 years old), we applied computational modeling to a novel social RL fMRI paradigm. Q-learning models estimated individual differences in learning and trial-by-trial prediction errors, which were used as a parametric modulator to assess brain activity that tracked the degree to which social feedback was better or worse than expected. Among older participants (n = 73; 12.9 ± 0.9 years old), we assessed associations between RL metrics and measures of substance use propensity. Greater substance use curiosity and household exposure to substance use were both linked to weaker striatal prediction error tracking of better-than-expected outcomes. However, among youth with substance-using peers, curiosity was associated with elevated striatal prediction error signals and better positive RL performance. Findings suggest that both hypo- and hyper-sensitivity to positive reinforcement learning signals may confer an increased propensity for substance use, possibly through distinct pathways.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":"47 8","pages":"e70545"},"PeriodicalIF":4.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13184721/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147972053","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}