Hum Brain Mapp [JOURNAL]
Sun
200 papers
Lifespan Trajectories of Asymmetry in White Matter Tracts.
Bogdanov S, Kanakaraj P, Kim ME … +31 more , Samir J, Gao C, Ramadass K, Rudravaram G, Newlin NR, Archer D, Hohman TJ, Jefferson AL, Morgan VL, Roche A, Englot DJ, Resnick SM, Beason Held LL, Cutting LE, Barquero LA, D'Archangel MA, Nguyen TQ, Humphreys KL, Niu Y, Vinci-Booher S, Cascio CJ, HABS‐HD Study Team, Alzheimer's Disease Neuroimaging Initiative, BIOCARD Study Team, Li Z, Vandekar SN, Zhang P, Gore JC, Forkel SJ, Landman BA, Schilling KG
Hum Brain Mapp · 2026 Jun · PMID 42249731 · Full text
Asymmetry in white matter is believed to give rise to the brain's capacity for specialized processing and is involved in the lateralization of various cognitive processes, such as language and visuo-spatial reasoning. Al...
Asymmetry in white matter is believed to give rise to the brain's capacity for specialized processing and is involved in the lateralization of various cognitive processes, such as language and visuo-spatial reasoning. Although studies of white matter asymmetry have been previously documented, they have often been constrained by limited age ranges, sample sizes, or the scope of the tracts and structural features examined. While normative lifespan charts for brain structures are emerging, comprehensive charts detailing white matter asymmetries across numerous pathways and diverse structural measures have been notably absent. This study addresses this gap by leveraging a large-scale dataset of 35,120 typically developing and aging individuals, ranging from 0 to 100 years of age, from 50 primary neuroimaging studies. We generated comprehensive lifespan trajectories for 30 lateralized association and projection white matter tracts, examining six distinct microstructural and macrostructural features of these pathways. Our findings reveal that: (1) asymmetries are widespread across the brain's white matter and are present in all 30 pathways; (2) for a given pathway, the degree and direction of asymmetry differ between features of tissue microstructure and pathway macrostructure; (3) asymmetries vary across and within pathway types (association and projection tracts); and (4) these asymmetries are not static, following unique trajectories across the lifespan, with distinct changes during development, and a general trend of becoming more asymmetric with increasing age (particularly in later adulthood) across pathways. This study represents the most extensive characterization of white matter asymmetry across the lifespan to date, charting how lateralization patterns emerge, mature, and change throughout life. It provides a foundational resource for understanding the principles of white matter organization from early to late life, its relation to functional specialization and inter-individual variability, and offers a key reference for interpreting deviations during healthy development and aging as well as those associated with clinical populations.
Energy-Based Phase-Locking State Analysis in Brain State Identification.
Ye C, Deng Z, Cong S … +4 more , Ran C, Gong T, Huang S, Ma T
Hum Brain Mapp · 2026 Jun · PMID 42246108 · Full text
The human brain exhibits inherent multistability, with Energy Landscape Analysis (ELA) providing effective frameworks for investigating this property through BOLD signals. However, traditional amplitude-based approaches...
The human brain exhibits inherent multistability, with Energy Landscape Analysis (ELA) providing effective frameworks for investigating this property through BOLD signals. However, traditional amplitude-based approaches fundamentally neglect critical phase synchronization dynamics that mediate large-scale neural coordination, while existing phase-based methods like Leading Eigenvector Dynamic Analysis (LEiDA) lack thermodynamic formalism for state stability quantification. Here, we introduce Energy-based Phase-Locking State Analysis (EPLSA), a transformative computational framework that synergistically integrates instantaneous phase-coupling dynamics with rigorous energy landscape principles, addressing fundamental limitations of conventional methodologies. Comprehensive validation across two independent neuroimaging datasets (HCP and Natural Sleep) demonstrated EPLSA's marked superiority over LEiDA and conventional ELA in terms of test-retest reliability, task-specific brain state differentiation, and individual-level classification performance. To demonstrate the physiological and clinical utility of the proposed method, sleep-wake analysis was performed to reveal EPLSA's enhanced sensitivity to consciousness state transitions, identifying decreased primary state occupancy and increased minor state prevalence during sleep, with significantly reduced direct transition probabilities. Furthermore, application to patients with Alzheimer's disease using the OASIS-3 dataset identified shortened dwell time and occurrence frequency for the frontoparietal control network-default mode network (FPCN-DMN) co-activation state, and prolonged dwell time and occurrence frequency for the visual network-limbic network (VIS-LMN) co-activation state, with these metrics significantly correlating with cognitive impairment. By unifying phase-coupling and thermodynamic principles, EPLSA provides novel insights into neurodynamic mechanisms across cognitive tasks, consciousness states, and neurodegenerative conditions, offering a transformative analytical tool for investigating brain function in health and disease with particular promise for early detection and monitoring of neurological disorders.
Axon Diameter Mapping in the Living Human Brain with Ultra-High-Gradient Diffusion MRI at 500 mT/m Gradient Strength.
Ma Y, Eskandarian L, Chan KS … +8 more , Lee H, Ramos-Llordén G, Bhatt A, Gerold J, Mahmutovic M, Keil B, Lee HH, Huang SY
Hum Brain Mapp · 2026 Jun · PMID 42240067 · Full text
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...
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: p = 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.
Distinct Physiological Mechanisms Drive Grey Matter Plasticity in Complex Versus Simple Sequence Learning.
Paul J, Jäger ATP, Huck J … +5 more , Tardif CL, Villringer A, Gauthier CJ, Bazin PL, Steele CJ
Hum Brain Mapp · 2026 Jun · PMID 42237744 · Full text
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 involv...
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.
Disgust Propensity, Not Disgust Sensitivity, Shapes the Reactivity of a Subjective Disgust Circuit in Humans.
Gan X, Zheng Z, Zhang R … +10 more , Zhou F, Xu T, Qiu N, Wang J, Jiang H, Gao S, Wu Y, Klugah-Brown B, Yao D, Becker B
Hum Brain Mapp · 2026 Jun · PMID 42237663 · Publisher ↗
Disgust constitutes an evolutionary adaptive defensive-avoidance response, yet humans vary markedly in their dispositional tendency to experience disgust (disgust propensity) and in their negative appraisal of such exper...
Disgust constitutes an evolutionary adaptive defensive-avoidance response, yet humans vary markedly in their dispositional tendency to experience disgust (disgust propensity) and in their negative appraisal of such experience (disgust sensitivity). Conceptual frameworks and neuroimaging studies suggest that these traits may differentially modulate neural responses to disgust-eliciting stimuli; however, methodological constraints have left their precise roles unresolved. Our comparably large fMRI study (n = 142) therefore aimed to systematically determine how trait disgust modulates neural responses to carefully selected and validated disgust-specific visual stimuli across varying levels of subjective disgust experience. The whole-brain voxel-wise regression analyses revealed a differential pattern of neural associations between the two disgust traits, with disgust propensity, but not disgust sensitivity, modulating disgust-related neural activity in the anterior, middle, and posterior insula, as well as the caudate, putamen, thalamus, hippocampus, and parahippocampal gyrus. Mediation and network-level analyses further supported this partly dissociable pattern by showing that disgust propensity shapes disgust experience via insula-striatal-hippocampal pathways. Together, these findings provide evidence for a differential association between disgust propensity and disgust sensitivity with disgust-related neural responses and elucidate how trait disgust shapes subjective experiences. They further suggest that disgust propensity and the identified systems may represent promising targets for the regulation of disgust-related pathology.
Primary Somatosensory to Motor Cortex Microstructural Connectivity Predicts the Mu-Rhythm Phase Effect on Corticospinal Excitability: An EEG-TMS Study.
Hougland JR, Roine T, Jooß A … +2 more , Humaidan D, Ziemann U
Hum Brain Mapp · 2026 Jun · PMID 42237633 · Publisher ↗
Sensorimotor mu-rhythm phase modulates corticospinal excitability; however, the influence of mu-phase varies across individuals and could be related to microstructural connectivity between primary somatosensory (S1) and...
Sensorimotor mu-rhythm phase modulates corticospinal excitability; however, the influence of mu-phase varies across individuals and could be related to microstructural connectivity between primary somatosensory (S1) and motor (M1) cortices. Our findings suggest that higher S1-M1 microstructural connectivity is associated with a stronger mu-phase effect on corticospinal excitability.
Cerebellar Transcranial Alternating Current Stimulation in the Theta Band Prevents Recall of the Initial Fear Association After Extinction Training.
Batsikadze G, Spisak Z, Zeidan P … +11 more , Klein M, Nio E, Ernst TM, Diekmann N, Göricke S, Cheng S, Merz CJ, Yavari F, Nitsche MA, Thieme A, Timmann D
Hum Brain Mapp · 2026 Jun · PMID 42233442 · Full text
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 there...
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+ > 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.
Cardiometabolic Risk and Structural Brain Development in a Large Community-Based US Cohort.
Beck D, Westlye LT, Tamnes CK
Hum Brain Mapp · 2026 Jun · PMID 42233371 · Full text
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 w...
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: n = 2745; two waves: n = 658 participants; three waves: n = 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.
Improved Multiscale Structural Mapping with Supervertex Vision Transformer for the Detection of Alzheimer's Disease Neurodegeneration.
Baek G, Salat DH, Jang I … +1 more , Alzheimer's Disease Neuroimaging Initiative
Hum Brain Mapp · 2026 Jun · PMID 42227644 · Full text
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 thic...
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.
Correction to "Evidence of White Matter Neuroinflammation in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Diffusion-Based Neuroinflammation Imaging Study".
Hum Brain Mapp · 2026 Jun · PMID 42227214 · Full text
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Standardizing TMS Intensity Across Different Coils Using Individualized Electric Field Modeling.
Kim E, Daneshzand M, Zhu K … +8 more , Bhutto DF, Kimberley TJ, Edwards D, Pajankar N, Kotlarz P, Raij T, Makaroff SN, Nummenmaa A
Hum Brain Mapp · 2026 Jun · PMID 42216705 · Full text
Quantitative measures for Transcranial Magnetic Stimulation (TMS) intensity are needed to ensure safe and consistent application in therapeutic and research settings. However, resting motor thresholds (rMTs), commonly us...
Quantitative measures for Transcranial Magnetic Stimulation (TMS) intensity are needed to ensure safe and consistent application in therapeutic and research settings. However, resting motor thresholds (rMTs), commonly used to determine stimulation intensity, depend on the coil used. Unless motor mapping and treatment coils are identical, re-thresholding is necessary, increasing patient discomfort and potentially introducing variability across studies. These considerations raise an unresolved fundamental question: does individual rMT reflect a consistent cortical electric field (E-field) magnitude independent of coil geometry? We tested the hypothesis that rMT corresponds to a coil-invariant cortical E-field magnitude and evaluated a computational method for predicting stimulator output across different coils using a reference rMT. Thirteen healthy, right-handed participants were recruited; ten were included in the primary analysis. Participants underwent TMS with two figure-of-eight coils of different sizes. E-field distributions were simulated using a fast multipole boundary element method, in free space and within personalized MRI-based head models. rMT prediction accuracy was compared between a detailed five-layer and a simplified three-layer head model, and both were evaluated against direct rMT scaling using the reference coil. The personalized E-field-based approach significantly improved rMT prediction accuracy over direct scaling (p < 0.001). The root-mean-square error (RMSE) was 1.26% and 1.32% of maximum stimulator output (MSO) for detailed and simplified models, versus 6.1% MSO for direct scaling. Individual rMT corresponds to a constant cortical E-field magnitude ratio across coil types. E-field-based prediction offers a more accurate, coil-independent method for standardizing TMS intensity, reducing the need for repeated thresholding.
Normative T and T Brain Atlases Across the Adult Lifespan in a Chinese Cohort: Multicenter Quantitative MRI Benchmarks for Ageing and Neurodegenerative Research.
Wang J, Piredda GF, Hilbert T … +7 more , He H, Thiran JP, Qian T, Sun Y, Liang P, Kober T, Li K
Hum Brain Mapp · 2026 Jun · PMID 42212671 · Full text
Quantitative MR relaxometry provides sensitive and reproducible measures of brain microstructure and is increasingly used in studies of ageing and neurodegenerative disease. However, normative brain atlases covering the...
Quantitative MR relaxometry provides sensitive and reproducible measures of brain microstructure and is increasingly used in studies of ageing and neurodegenerative disease. However, normative brain atlases covering the adult lifespan remain scarce, especially from large, harmonized, multicenter datasets. This study aimed to establish lifespan-based normative T and T atlases to support individualized assessment and group-level comparisons. We retrospectively analyzed 947 healthy Han Chinese adults (421 males; median age 39 years; range 19-72) from 11 imaging centers in China. T and T maps were acquired with harmonized MP2RAGE and GRAPPATINI protocols, processed using a unified pipeline, and modeled with voxelwise mixed-effects regression including linear and quadratic age terms, sex, and random intercepts for site. Intersite reproducibility was further evaluated in three traveling subjects scanned at all centers. The atlases demonstrated region-specific age and sex effects in both white and gray matter. Intersite variability was minimal (intraclass correlation coefficients > 0.99 for T and > 0.90 for T). Both T and T followed quadratic trajectories, decreasing in early adulthood, reaching minima in midlife, and increasing in later decades, with the strongest effects in cortical gray matter. Sex differences were most pronounced in parietal and callosal regions. These lifespan-based normative relaxometry atlases provide high-fidelity references for age- and sex-related microstructural changes in the healthy brain. They provide quantitative benchmarks for individualized profiling and group comparisons in Chinese adult populations, while validation in other ethnic populations remains necessary before broader application.
Modulation of Visual Contrast Perception Associated With Dorsal Attention Network Connectivity Assessed by Magnetoencephalography.
Sklar AL, Coffman BA, López-Caballero F … +6 more , Seebold D, Kocsis J, Fowler L, Rhorer H, Kavanagh J, Salisbury DF
Hum Brain Mapp · 2026 Jun · PMID 42178769 · Full text
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 (C...
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.
ComBat-Predict Enhances Generalizability of Neuroimaging Models to New Sites.
Xin Y, Gardner M, Tustison NJ … +10 more , Cook P, Gee J, Benitez A, Jensen JH, Alzheimer's Disease Neuroimaging Initiative, Lifespan Brain Chart Consortium, Bethlehem R, Seidlitz J, Alexander-Bloch AF, Chen AA
Hum Brain Mapp · 2026 Jun · PMID 42157534 · Publisher ↗
Neuroimaging is vital in quantifying brain atrophy due to typical aging and due to neurodegenerative diseases. To collect large samples necessary to model lifespan brain development, research consortiums aggregate images...
Neuroimaging is vital in quantifying brain atrophy due to typical aging and due to neurodegenerative diseases. To collect large samples necessary to model lifespan brain development, research consortiums aggregate images acquired across multiple study sites. Previous studies have demonstrated that this multi-site study design can lead to site-related bias, necessitating harmonization of these "site effects." However, current methodologies are unable to generalize to new sites outside the original harmonized sample, limiting translation to new sites or clinical practice. Here, we propose a method called ComBat-Predict (CB-Predict) building upon the ComBat method for site effect adjustment, which extends to data from a new site with smaller sample sizes and unknown site effects. In data from the Alzheimer's Disease Neuroimaging Initiative, our proposed method mitigates bias and yields high accuracy in predicting cortical thickness measures when generalizing the model to new data. Furthermore, we demonstrate that our proposed harmonization method can reduce site-related variance in centile scores estimated using data from the Lifespan Brain Chart Consortium. Altogether, our results demonstrate that CB-Predict effectively harmonizes new sites and thereby enables effective translation of neuroimaging models to additional samples.
Striatal Prediction Error Tracking Moderates the Influence of Social Exposure on Adolescent Substance Use Curiosity.
Flannery JS, Escalante ES, Ma R … +2 more , Lindquist KA, Telzer EH
Hum Brain Mapp · 2026 Jun · PMID 42153343 · Full text
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 h...
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.
Trial-By-Trial Changes in Neural Indices of Performance Monitoring Uniquely Correspond to Behavioral Adjustments During a Flanker Task.
Lutz MC, Park B, Rast P … +3 more , Baldwin SA, Larson MJ, Clayson PE
Hum Brain Mapp · 2026 May · PMID 42132191 · Full text
Behavioral and neural indices of performance monitoring are key to understanding behavioral adaptation during task performance. However, associations between performance monitoring event-related potentials (ERPs) and tas...
Behavioral and neural indices of performance monitoring are key to understanding behavioral adaptation during task performance. However, associations between performance monitoring event-related potentials (ERPs) and task behavior have been inconsistent. This inconsistency may partly reflect reliance on single-subject averages that obscure trial-by-trial changes in ERPs and behavior, and a tendency to examine only one or two ERP indices at a time. Our objective was to uncover how neural variability during performance monitoring contributes to behavioral adaptation, revealing variability as a functional signature of cognitive control. We investigated whether current-trial response times (RTs) and accuracy can be predicted from previous- and current-trial congruency and accuracy and ERP indices of performance monitoring (N2, P3, error-related negativity [ERN], error positivity, [Pe]). Flanker data from 291 healthy participants (54% female) were analyzed using multilevel location-scale modeling. This modeling framework facilitates simultaneous examination of mean and variance relationships of single-trial data. Previous- and current-trial ERP amplitudes uniquely predict current-trial RTs and accuracy, beyond previous- and current-trial congruency and accuracy effects. Previous- and current-trial N2, P3, ERN, and Pe were concurrently related to the mean and variance of RTs and to accuracy. The observed within-person changes in the relationship between performance-monitoring ERPs and task behavior indicate that trial-by-trial neural fluctuations reflect dynamic adjustments in cognitive control across successive actions. These findings demonstrate the value of modeling intraindividual variability in neurophysiological measures to understand adaptive behavior.
The In Vivo Microstructural Profile of Human Hippocampal Subfield CA1 and Its Relation to Memory Performance.
Hayek D, Fernandes JH, Vockert N … +11 more , Garcia-Garcia B, Mattern H, Behrenbruch N, Fischer L, Kalyani A, Doehler J, Hämmerer D, Yi YJ, Schreiber S, Maass A, Kuehn E
Hum Brain Mapp · 2026 May · PMID 42125937 · Full text
The hippocampal CA1 subregion supports learning, memory formation, and spatial navigation. Although its three-layered architecture has been described in ex vivo investigations, the in vivo microstructural profile of CA1...
The hippocampal CA1 subregion supports learning, memory formation, and spatial navigation. Although its three-layered architecture has been described in ex vivo investigations, the in vivo microstructural profile of CA1 and its relation to individual variations in memory performance remain poorly characterized. In this study, we used ultra-high field structural MRI at 7 Tesla to investigate the depth-dependent myelination patterns (measured by quantitative T1) of CA1 in younger adults, their relation to the local arterial architecture, and their association with individual differences in cognitive functions, specifically memory performance. Results show that left and right CA1 present depth-dependent patterns of myelination, with the outer and inner compartments showing higher myelination than the middle compartment. No significant relationship between layer-specific myelination of CA1 and distance to the nearest artery was observed. Right CA1 was found to be more myelinated than left CA1. Pairwise correlations and regression models showed that higher left CA1 myelination is linked to higher accuracy in object localization. Together, our data demonstrate the feasibility of describing the three-layered myelin architecture of CA1 in vivo, and provide information on how alterations in the architecture of CA1 may relate to alterations in cognitive performance in younger adults.
Neural Mechanisms of Bidirectional Visuo-Linguistic Transformation in Interactive Communication.
Shen Y, Koike T, Tsuchimoto S … +4 more , Yoshioka A, Ogasawara K, Sadato N, Tanabe HC
Hum Brain Mapp · 2026 May · PMID 42117286 · Full text
Human communication requires the flexible transformation of visual input into verbal descriptions and the reconstruction of mental imagery from language. However, the neural mechanisms underlying these bidirectional tran...
Human communication requires the flexible transformation of visual input into verbal descriptions and the reconstruction of mental imagery from language. However, the neural mechanisms underlying these bidirectional transformations during social interaction remain poorly understood. Using hyperscanning fMRI and a role-switching communicative task, we investigated how individuals alternately encode visual stimuli into language and decode language into mental imagery within an interactive context. Whole-brain analyses identified brain regions implicated in these processes. Based on these findings, we selected three key regions-the inferior frontal gyrus (IFG), fusiform face area (FFA), and intraparietal sulcus (IPS)-and applied dynamic causal modeling (DCM) to examine their effective connectivity. The DCM results revealed that connectivity among IFG, FFA, and IPS dynamically reconfigures to support role-dependent shifts between top-down and bottom-up information flow. These findings highlight a flexible, coordinated neural architecture that integrates visual and linguistic information, offering new insights into how communication arises from the interplay between perceptual and language systems.
Age-Related Low Frequency Amplitude Differences in Resting-State Blood Oxygenation Level-Dependent Signal in the Cerebellum.
Korte JA, Steele CJ, Joiner WM … +1 more , Fan AP
Hum Brain Mapp · 2026 May · PMID 42108695 · Full text
There is a growing interest to study cerebellar contributions to aging outside of traditional sensory processing and motor tasks. While cerebellar aging analyses typically utilize functional connectivity (FC) to study fu...
There is a growing interest to study cerebellar contributions to aging outside of traditional sensory processing and motor tasks. While cerebellar aging analyses typically utilize functional connectivity (FC) to study functional differences with age, this study aimed to identify a marker of healthy aging based on resting state blood oxygenation level dependent (BOLD) signal dynamics in the cerebellum. To do this, we investigated both Amplitude of Low Frequency Fluctuations (ALFF) and fractional ALFF (fALFF), semi-quantitative metrics of the strength of the BOLD signal. We found that fALFF is a highly repeatable metric of cerebellar function that demonstrates a significant increase in BOLD signal fluctuations at 0.008-0.1 Hz in cerebellar regions Crus I and II with aging. Furthermore, cerebellar fALFF of these regions was associated with FC to cortical regions across separate scanning sessions. These results highlight age-related differences in spontaneous cerebellar dynamics, particularly in regions tied to the frontal cortex, motivating the use of fALFF as a potential biomarker of healthy aging and motivate the need to incorporate the cerebellum in existing models of brain network changes with age.
Directed Communication in Theta and Alpha Networks Supports Content Handling in Working Memory.
Elmers J, Mückschel M, Beste C
Hum Brain Mapp · 2026 May · PMID 42057539 · Full text
Executive functions enable flexible control of behavior by dynamically coordinating perception, memory, and action. Among them, working memory plays a central role by maintaining and transforming information to meet curr...
Executive functions enable flexible control of behavior by dynamically coordinating perception, memory, and action. Among them, working memory plays a central role by maintaining and transforming information to meet current goals. Here, we examined mental rotation-a core operation that exemplifies these control dynamics-and delineated the role of directed communication in theta and alpha band activity in cortical networks. Replicating the typical behavioral pattern in mental rotation, we showed that high-demand rotations were characterized by decreased theta and increased alpha power, reflecting a functional reallocation from control-intensive monitoring to stabilized maintenance of visual representations. EEG-beamforming localization identified anterior temporal, inferior frontal, and insular regions showing stronger directed information transfer to temporo-parietal and occipito-temporal regions. These findings suggest that mental rotation is associated with frequency-specific, hierarchically organized, directed communication between anterior control-related and posterior representational systems. In this directed communication, theta band dynamics likely coordinate working memory updating and response selection, whereas alpha-band coupling stabilizes mnemonic representations through inhibitory gating. The study suggests that directed theta and alpha dynamics may support the flexible transformation of internal representations in working memory.
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