Pub Date : 2025-12-17DOI: 10.1016/j.neuroimage.2025.121661
Péter Nagy , Luca Béres , Brigitta Tóth , István Winkler , Betty Barthel , Gábor P. Háden
Interpersonal synchrony—moving and thinking in time with someone else—may be a key engine of children’s learning. We studied 5–6-year-olds and their caregivers as they played an imitation-based “Mirror Game” and a goal-directed “Labyrinth Game,” recording full-body motion and dual-EEG. To ensure effects reflected real interaction, we compared each dyad to many randomly recombined “pseudo pairs.”
Dyads aligned both their movements and their brain activity, with the most consistent neural coupling in the gamma range—a rhythm linked to attention and real-time coordination. Alignment shifted with task demands and was associated with more efficient performance, yet it did not track children’s general motor ability (MABC-2), suggesting that synchrony is an emergent property of interaction rather than a simple proxy for motor maturity. By jointly measuring behavior and brain in naturalistic tasks, this work points to synchrony as a measurable mechanism—and potential target—for boosting engagement and motor learning in early childhood.
{"title":"Neural and motor coupling in interpersonal synchronization: mechanisms for motor learning and development in 5- to 6-year-old children","authors":"Péter Nagy , Luca Béres , Brigitta Tóth , István Winkler , Betty Barthel , Gábor P. Háden","doi":"10.1016/j.neuroimage.2025.121661","DOIUrl":"10.1016/j.neuroimage.2025.121661","url":null,"abstract":"<div><div>Interpersonal synchrony—moving and thinking in time with someone else—may be a key engine of children’s learning. We studied 5–6-year-olds and their caregivers as they played an imitation-based “Mirror Game” and a goal-directed “Labyrinth Game,” recording full-body motion and dual-EEG. To ensure effects reflected real interaction, we compared each dyad to many randomly recombined “pseudo pairs.”</div><div>Dyads aligned both their movements and their brain activity, with the most consistent neural coupling in the gamma range—a rhythm linked to attention and real-time coordination. Alignment shifted with task demands and was associated with more efficient performance, yet it did not track children’s general motor ability (MABC-2), suggesting that synchrony is an emergent property of interaction rather than a simple proxy for motor maturity. By jointly measuring behavior and brain in naturalistic tasks, this work points to synchrony as a measurable mechanism—and potential target—for boosting engagement and motor learning in early childhood.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"326 ","pages":"Article 121661"},"PeriodicalIF":4.5,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145794427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Humans comprehend speech in noisy environments more effectively when they can see the talker’s facial movements. While the benefits of audiovisual (AV) speech are well established, the specific visual features that support this enhancement and its underlying neural mechanisms remain unclear. Here, we examine how simplified facial signals that preserve structural and dynamic information affect AV speech-in-noise comprehension as well as neural speech tracking. In a behavioural experiment, participants viewed natural or progressively simplified facial videos while listening to short sentences in background noise. Visual stimuli included natural facial recordings, coarse facial outlines, and a simple geometric analogue of visual speech—a disk whose radius oscillated with the speech envelope. In an EEG experiment, we assessed how the progressively simplified visual signals influenced cortical tracking of the speech envelope during continuous AV speech. Behaviourally, we found that comprehension improved with increasing visual detail, while the disk provided no AV benefit, underscoring the importance of dynamic facial cues. For the EEG experiment, only the most natural visual signals enhanced delta-band (1–4 Hz) temporal response functions (TRFs) relative to audio-only stimulation, peaking around 180 ms. This neural enhancement correlated with behavioural benefit across participants. Theta-band effects were weaker and less consistent, suggesting a more limited role in AV integration. Together, these findings highlight the importance of facial detail in AV speech perception, with natural visual input driving stronger delta-band tracking and potentially reflecting alignment of auditory processing with word-level visual cues.
{"title":"Delta-band cortical speech tracking predicts audiovisual speech-in-noise benefit from natural and simplified visual cues","authors":"Enrico Varano , Mike Thornton , Dorothea Kolossa , Steffen Zeiler , Tobias Reichenbach","doi":"10.1016/j.neuroimage.2025.121654","DOIUrl":"10.1016/j.neuroimage.2025.121654","url":null,"abstract":"<div><div>Humans comprehend speech in noisy environments more effectively when they can see the talker’s facial movements. While the benefits of audiovisual (AV) speech are well established, the specific visual features that support this enhancement and its underlying neural mechanisms remain unclear. Here, we examine how simplified facial signals that preserve structural and dynamic information affect AV speech-in-noise comprehension as well as neural speech tracking. In a behavioural experiment, participants viewed natural or progressively simplified facial videos while listening to short sentences in background noise. Visual stimuli included natural facial recordings, coarse facial outlines, and a simple geometric analogue of visual speech—a disk whose radius oscillated with the speech envelope. In an EEG experiment, we assessed how the progressively simplified visual signals influenced cortical tracking of the speech envelope during continuous AV speech. Behaviourally, we found that comprehension improved with increasing visual detail, while the disk provided no AV benefit, underscoring the importance of dynamic facial cues. For the EEG experiment, only the most natural visual signals enhanced delta-band (1–4 Hz) temporal response functions (TRFs) relative to audio-only stimulation, peaking around 180 ms. This neural enhancement correlated with behavioural benefit across participants. Theta-band effects were weaker and less consistent, suggesting a more limited role in AV integration. Together, these findings highlight the importance of facial detail in AV speech perception, with natural visual input driving stronger delta-band tracking and potentially reflecting alignment of auditory processing with word-level visual cues.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"325 ","pages":"Article 121654"},"PeriodicalIF":4.5,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145781295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-16DOI: 10.1016/j.neuroimage.2025.121656
Ekin Taskin , Gabriel Girard , Juan Luis Villarreal Haro , Jonathan Rafael-Patiño , Eleftherios Garyfallidis , Jean-Philippe Thiran , Erick Jorge Canales-Rodríguez
Constrained Spherical Deconvolution (CSD) is widely used to estimate the white matter fiber orientation distribution (FOD) from diffusion MRI data. Its angular resolution depends on the maximum spherical harmonic order (): low yields smooth but poorly resolved FODs, while high , as in Super-CSD, enables resolving fiber crossings with small inter-fiber angles but increases sensitivity to noise. In this proof-of-concept study, we introduce Spatially Regularized Super-Resolved CSD (SR-CSD), a novel method that regularizes Super-CSD using a spatial FOD prior estimated via a self-calibrated total variation denoiser. We evaluated SR-CSD against CSD and Super-CSD across four datasets: (i) the HARDI-2013 challenge numerical phantom, assessing angular and peak number errors across multiple signal-to-noise ratio (SNR) levels and CSD variants (single-/multi-shell, single-/multi-tissue); (ii) the Sherbrooke in vivo dataset, evaluating spatial coherence of FODs; (iii) a six-subject test–retest dataset acquired with both full (96 gradient directions) and subsampled (45 directions) protocols, assessing reproducibility; and (iv) the DiSCo phantom, evaluating tractography accuracy under varying SNR levels and multiple noise repetitions. Across all evaluations, SR-CSD consistently reduced angular and peak number errors, improved spatial coherence, enhanced test–retest reproducibility, and yielded connectivity matrices more strongly correlated with ground-truth. Most improvements were statistically significant under multiple-comparison correction. These results demonstrate that incorporating spatial priors into CSD is feasible, mitigates estimation instability, and improves FOD reconstruction accuracy.
{"title":"Spatially regularized super-resolved constrained spherical deconvolution (SR2-CSD) of diffusion MRI data","authors":"Ekin Taskin , Gabriel Girard , Juan Luis Villarreal Haro , Jonathan Rafael-Patiño , Eleftherios Garyfallidis , Jean-Philippe Thiran , Erick Jorge Canales-Rodríguez","doi":"10.1016/j.neuroimage.2025.121656","DOIUrl":"10.1016/j.neuroimage.2025.121656","url":null,"abstract":"<div><div>Constrained Spherical Deconvolution (CSD) is widely used to estimate the white matter fiber orientation distribution (FOD) from diffusion MRI data. Its angular resolution depends on the maximum spherical harmonic order (<span><math><msub><mrow><mi>l</mi></mrow><mrow><mi>m</mi><mi>a</mi><mi>x</mi></mrow></msub></math></span>): low <span><math><msub><mrow><mi>l</mi></mrow><mrow><mi>m</mi><mi>a</mi><mi>x</mi></mrow></msub></math></span> yields smooth but poorly resolved FODs, while high <span><math><msub><mrow><mi>l</mi></mrow><mrow><mi>m</mi><mi>a</mi><mi>x</mi></mrow></msub></math></span>, as in Super-CSD, enables resolving fiber crossings with small inter-fiber angles but increases sensitivity to noise. In this proof-of-concept study, we introduce Spatially Regularized Super-Resolved CSD (SR<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>-CSD), a novel method that regularizes Super-CSD using a spatial FOD prior estimated via a self-calibrated total variation denoiser. We evaluated SR<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>-CSD against CSD and Super-CSD across four datasets: (i) the HARDI-2013 challenge numerical phantom, assessing angular and peak number errors across multiple signal-to-noise ratio (SNR) levels and CSD variants (single-/multi-shell, single-/multi-tissue); (ii) the Sherbrooke in vivo dataset, evaluating spatial coherence of FODs; (iii) a six-subject test–retest dataset acquired with both full (96 gradient directions) and subsampled (45 directions) protocols, assessing reproducibility; and (iv) the DiSCo phantom, evaluating tractography accuracy under varying SNR levels and multiple noise repetitions. Across all evaluations, SR<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>-CSD consistently reduced angular and peak number errors, improved spatial coherence, enhanced test–retest reproducibility, and yielded connectivity matrices more strongly correlated with ground-truth. Most improvements were statistically significant under multiple-comparison correction. These results demonstrate that incorporating spatial priors into CSD is feasible, mitigates estimation instability, and improves FOD reconstruction accuracy.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"325 ","pages":"Article 121656"},"PeriodicalIF":4.5,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145781541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-15DOI: 10.1016/j.neuroimage.2025.121616
Axel Wismüller , Ali Vosoughi , Akhil Kasturi
Causal inference from high-dimensional and short time-series data is crucial to scientific discovery across diverse fields. Yet, standard approaches frequently fail under these constraints. We propose Large-scale Augmented Granger Causality (lsAGC), integrating dimension reduction, a Granger-based predictive framework, and data augmentation, to handle large-scale networks even when . Extensive simulations on synthetic and semi-realistic fMRI data (3–34 nodes, both linear and nonlinear) confirm lsAGC’s efficiency in tackling high-dimensional data. Validation on real clinical fMRI data from 40 subjects (118 brain regions) demonstrates superior performance, with lsAGC achieving AUC 0.83 versus 0.50–0.62 for modern baselines including PCMCI, sparse VAR, and deconvolution-based GC. Empirically, lsAGC outperforms baseline methods in multiple benchmarks. For instance, on a 34-node network with only 50 samples, lsAGC maintains an AUROC above 0.70, whereas others fall below 0.60. Moreover, lsAGC is computationally efficient (8.3s vs. hours for 118-region networks) and robust to noise, nonlinear effects, and short time spans. This combination of speed and accuracy renders lsAGC practical for real-world contexts in neuroscience, climate science, and economics, where short, large-scale time series predominate.
{"title":"Inferring causal relations from multivariate data using Large-Scale Augmented Granger Causality (lsAGC)","authors":"Axel Wismüller , Ali Vosoughi , Akhil Kasturi","doi":"10.1016/j.neuroimage.2025.121616","DOIUrl":"10.1016/j.neuroimage.2025.121616","url":null,"abstract":"<div><div>Causal inference from high-dimensional and short time-series data is crucial to scientific discovery across diverse fields. Yet, standard approaches frequently fail under these constraints. We propose Large-scale Augmented Granger Causality (lsAGC), integrating dimension reduction, a Granger-based predictive framework, and data augmentation, to handle large-scale networks even when <span><math><mrow><mi>T</mi><mo><</mo><mi>N</mi></mrow></math></span>. Extensive simulations on synthetic and semi-realistic fMRI data (3–34 nodes, both linear and nonlinear) confirm lsAGC’s efficiency in tackling high-dimensional data. Validation on real clinical fMRI data from 40 subjects (118 brain regions) demonstrates superior performance, with lsAGC achieving AUC 0.83 versus 0.50–0.62 for modern baselines including PCMCI, sparse VAR, and deconvolution-based GC. Empirically, lsAGC outperforms baseline methods in multiple benchmarks. For instance, on a 34-node network with only 50 samples, lsAGC maintains an AUROC above 0.70, whereas others fall below 0.60. Moreover, lsAGC is computationally efficient (8.3s vs. hours for 118-region networks) and robust to noise, nonlinear effects, and short time spans. This combination of speed and accuracy renders lsAGC practical for real-world contexts in neuroscience, climate science, and economics, where short, large-scale time series predominate.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"324 ","pages":"Article 121616"},"PeriodicalIF":4.5,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145649097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-15DOI: 10.1016/j.neuroimage.2025.121633
Inge M. van Ooijen , Gaby van Iersel , Lotte Meijerink , Jalmar Teeuw , Elise Turk , Maaike Nijman , Daniel Cromb , Alena Uus , Serena Counsell , Mireille N. Bekker , Maria Luisa Tataranno , Hilleke E. Hulshoff Pol , Sonja M.C. de Zwarte , Manon J.N.L. Benders
Objective(s)
Recent advances in fetal three-dimensional (3D) ultrasound (US) enable automated intracranial volume (ICV) measurements. If US yields results comparable to magnetic resonance imaging (MRI), it could serve as a fast, cost-effective, and scalable alternative. This study directly compares and visualizes ICV measurements from fetal 3D US and 3D MRI.
Study Design
We applied automated ICV segmentation to US and MRI data from healthy participants. In a subset of fetuses who underwent both US and MRI within 24 h, we evaluated ICV agreement using the intraclass correlation coefficient (ICC) and the Dice similarity coefficient (DSC). As a proof of principle, we also generated a multimodal ICV trajectory incorporating fetal US, fetal MRI, and neonatal MRI.
Results
Among the 71 participants, 47 had high-quality US scans at 20 and 30 weeks of gestation, 61 had high-quality fetal MRI, and 47 had high-quality neonatal MRI. Thirteen fetuses around 30 weeks had US and MRI scans acquired within 24 h, showing good agreement with an ICC of 0.797 and DSCUS−MRI scores of 0.900–0.925. Mean ICV values were 80 ± 12 ml around 22 weeks (US), 248 ± 28 ml around 30 weeks (US), 294 ± 36 ml around 32 weeks (fetal MRI) and 508 ± 51 ml around 43 weeks (neonatal MRI).
Conclusion(s)
Fetal US and MRI yield comparable ICV measurements around 30 weeks of gestation, validating automatic 3D US volumetric methods. The use of 3D US may support development of normative curves and improve comparisons with at-risk fetuses, including in regions where fetal MRI is less accessible.
{"title":"Head to head: Comparing intracranial volumes using 3D ultrasound and fetal MRI","authors":"Inge M. van Ooijen , Gaby van Iersel , Lotte Meijerink , Jalmar Teeuw , Elise Turk , Maaike Nijman , Daniel Cromb , Alena Uus , Serena Counsell , Mireille N. Bekker , Maria Luisa Tataranno , Hilleke E. Hulshoff Pol , Sonja M.C. de Zwarte , Manon J.N.L. Benders","doi":"10.1016/j.neuroimage.2025.121633","DOIUrl":"10.1016/j.neuroimage.2025.121633","url":null,"abstract":"<div><h3>Objective(s)</h3><div>Recent advances in fetal three-dimensional (3D) ultrasound (US) enable automated intracranial volume (ICV) measurements. If US yields results comparable to magnetic resonance imaging (MRI), it could serve as a fast, cost-effective, and scalable alternative. This study directly compares and visualizes ICV measurements from fetal 3D US and 3D MRI.</div></div><div><h3>Study Design</h3><div>We applied automated ICV segmentation to US and MRI data from healthy participants. In a subset of fetuses who underwent both US and MRI within 24 h, we evaluated ICV agreement using the intraclass correlation coefficient (ICC) and the Dice similarity coefficient (DSC). As a proof of principle, we also generated a multimodal ICV trajectory incorporating fetal US, fetal MRI, and neonatal MRI.</div></div><div><h3>Results</h3><div>Among the 71 participants, 47 had high-quality US scans at 20 and 30 weeks of gestation, 61 had high-quality fetal MRI, and 47 had high-quality neonatal MRI. Thirteen fetuses around 30 weeks had US and MRI scans acquired within 24 h, showing good agreement with an ICC of 0.797 and DSC<sub>US−MRI</sub> scores of 0.900–0.925. Mean ICV values were 80 ± 12 ml around 22 weeks (US), 248 ± 28 ml around 30 weeks (US), 294 ± 36 ml around 32 weeks (fetal MRI) and 508 ± 51 ml around 43 weeks (neonatal MRI).</div></div><div><h3>Conclusion(s)</h3><div>Fetal US and MRI yield comparable ICV measurements around 30 weeks of gestation, validating automatic 3D US volumetric methods. The use of 3D US may support development of normative curves and improve comparisons with at-risk fetuses, including in regions where fetal MRI is less accessible.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"324 ","pages":"Article 121633"},"PeriodicalIF":4.5,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145687802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-15DOI: 10.1016/j.neuroimage.2025.121635
Ilenia Salsano , Ryan J. Glesinger , Jason A. John , Grant M. Garrison , Lucy K. Horne , Grace C. Ende , Danielle L. Rice , Anna T. Coutant , Kennedy A. Kress , Aubrie J. Petts , Georg Oeltzschner , Tony W. Wilson
Aging has been associated with widespread alterations in neural structure and function, but the underlying biochemical changes remain less understood despite recent neurophysiological work suggesting age-related alterations in the excitatory/inhibitory (E/I) balance. In the current study, we used ¹H-MRS to quantify levels of excitatory (Glx: glutamate + glutamine) and inhibitory (GABA+: GABA + macromolecules) neurotransmitters in the calcarine cortex in 187 healthy adults (19–79 years-old). These neurotransmitter estimates were used to compute the E/I ratio, and all three parameters were examined for aging effects. Given our large sample, we also conducted supplementary analyses to estimate the concentration of secondary metabolites commonly implicated in aging, including total creatine (tCr), total N-acetyl aspartate (tNAA), total choline (tCho), and myo-inositol (mI). Following best practices, metabolite concentrations were estimated relative to the unsuppressed water signal and corrected for voxel tissue composition (i.e., gray matter, white matter, CSF). Our results indicated significant age-related declines in both GABA+ and Glx, along with a reduction in the E/I ratio, suggesting diminished inhibitory and excitatory tone with advancing age. We also found a decline in tNAA and an increase in tCr with increasing age. In summary, we provide compelling evidence through one of the largest studies of its kind for age-related shifts in excitatory and inhibitory neurotransmitter levels in the visual cortex. These changes may be critical to well-known, age-related physiological changes, including reduced neural selectivity and processing efficiency. These findings provide novel evidence that neurochemical alterations may contribute to the functional declines in cortical processing seen in healthy aging.
{"title":"Neurochemical changes in GABA+, Glx, and the excitatory/inhibitory ratio in the calcarine cortex with healthy aging","authors":"Ilenia Salsano , Ryan J. Glesinger , Jason A. John , Grant M. Garrison , Lucy K. Horne , Grace C. Ende , Danielle L. Rice , Anna T. Coutant , Kennedy A. Kress , Aubrie J. Petts , Georg Oeltzschner , Tony W. Wilson","doi":"10.1016/j.neuroimage.2025.121635","DOIUrl":"10.1016/j.neuroimage.2025.121635","url":null,"abstract":"<div><div>Aging has been associated with widespread alterations in neural structure and function, but the underlying biochemical changes remain less understood despite recent neurophysiological work suggesting age-related alterations in the excitatory/inhibitory (E/I) balance. In the current study, we used ¹H-MRS to quantify levels of excitatory (Glx: glutamate + glutamine) and inhibitory (GABA+: GABA + macromolecules) neurotransmitters in the calcarine cortex in 187 healthy adults (19–79 years-old). These neurotransmitter estimates were used to compute the E/I ratio, and all three parameters were examined for aging effects. Given our large sample, we also conducted supplementary analyses to estimate the concentration of secondary metabolites commonly implicated in aging, including total creatine (tCr), total N-acetyl aspartate (tNAA), total choline (tCho), and myo-inositol (mI). Following best practices, metabolite concentrations were estimated relative to the unsuppressed water signal and corrected for voxel tissue composition (i.e., gray matter, white matter, CSF). Our results indicated significant age-related declines in both GABA+ and Glx, along with a reduction in the E/I ratio, suggesting diminished inhibitory and excitatory tone with advancing age. We also found a decline in tNAA and an increase in tCr with increasing age. In summary, we provide compelling evidence through one of the largest studies of its kind for age-related shifts in excitatory and inhibitory neurotransmitter levels in the visual cortex. These changes may be critical to well-known, age-related physiological changes, including reduced neural selectivity and processing efficiency. These findings provide novel evidence that neurochemical alterations may contribute to the functional declines in cortical processing seen in healthy aging.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"324 ","pages":"Article 121635"},"PeriodicalIF":4.5,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145701323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-15DOI: 10.1016/j.neuroimage.2025.121636
Jie Song , Qian Lu , Shuai Zhang , Chuan He , Tianjiao Zhang , Hailang Yan , Han Yang , Huanping Wang , Hanjun Liu , Zhiyong Zhao , Ying Shen
Background
Disruptions in synaptic plasticity and alterations in effective connectivity (EC) involving the hippocampus and amygdala are hallmarks of early Alzheimer’s disease (AD). However, the interplay between these neurophysiological changes and their relationships with cognitive functions in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remains poorly understood.
Methods
Transcranial magnetic stimulation (TMS) and resting-state functional magnetic resonance imaging (rs-fMRI) were used to assess long-term potentiation (LTP)-like plasticity and EC involving the amygdala and hippocampus in 34 individuals with SCD, 27 with MCI, and 35 healthy controls (HC). Between-group differences in cognitive performance, EC alterations, and LTP-like plasticity were examined and their relationships were assessed via correlation and mediation analyses.
Results
Both SCD and MCI groups exhibited disrupted EC between the amygdala/hippocampus and the inferior occipital gyrus (IOG), inferior parietal lobule (IPL), medial frontal lobe (MFL), and precuneus. Also, both LTP-5min and LTP-10min were significantly reduced in MCI group compared to SCD and HC groups. Importantly, EC from the left hippocampus to the IPL and from the IPL, MFL, and precuneus to the hippocampus was correlated with memory and executive functions. Moreover, precuneus-to-hippocampus EC was positively correlated with LTP-10min and mediated the relationship between LTP-like plasticity and cognitive performance.
Conclusions
This study provides novel evidence that precuneus-to-hippocampus EC mediates the link between synaptic plasticity and cognitive function in SCD and MCI, suggesting the precuneus–hippocampus pathway as a promising target for early diagnosis and intervention.
{"title":"Precuneus-to-hippocampus connectivity links LTP-like plasticity to cognitive function in subjective cognitive decline and mild cognitive impairment","authors":"Jie Song , Qian Lu , Shuai Zhang , Chuan He , Tianjiao Zhang , Hailang Yan , Han Yang , Huanping Wang , Hanjun Liu , Zhiyong Zhao , Ying Shen","doi":"10.1016/j.neuroimage.2025.121636","DOIUrl":"10.1016/j.neuroimage.2025.121636","url":null,"abstract":"<div><h3>Background</h3><div>Disruptions in synaptic plasticity and alterations in effective connectivity (EC) involving the hippocampus and amygdala are hallmarks of early Alzheimer’s disease (AD). However, the interplay between these neurophysiological changes and their relationships with cognitive functions in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remains poorly understood.</div></div><div><h3>Methods</h3><div>Transcranial magnetic stimulation (TMS) and resting-state functional magnetic resonance imaging (rs-fMRI) were used to assess long-term potentiation (LTP)-like plasticity and EC involving the amygdala and hippocampus in 34 individuals with SCD, 27 with MCI, and 35 healthy controls (HC). Between-group differences in cognitive performance, EC alterations, and LTP-like plasticity were examined and their relationships were assessed via correlation and mediation analyses.</div></div><div><h3>Results</h3><div>Both SCD and MCI groups exhibited disrupted EC between the amygdala/hippocampus and the inferior occipital gyrus (IOG), inferior parietal lobule (IPL), medial frontal lobe (MFL), and precuneus. Also, both LTP-5min and LTP-10min were significantly reduced in MCI group compared to SCD and HC groups. Importantly, EC from the left hippocampus to the IPL and from the IPL, MFL, and precuneus to the hippocampus was correlated with memory and executive functions. Moreover, precuneus-to-hippocampus EC was positively correlated with LTP-10min and mediated the relationship between LTP-like plasticity and cognitive performance.</div></div><div><h3>Conclusions</h3><div>This study provides novel evidence that precuneus-to-hippocampus EC mediates the link between synaptic plasticity and cognitive function in SCD and MCI, suggesting the precuneus–hippocampus pathway as a promising target for early diagnosis and intervention.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"324 ","pages":"Article 121636"},"PeriodicalIF":4.5,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145715239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-15DOI: 10.1016/j.neuroimage.2025.121653
Qingwen Chen , Tao Zhong , Jian Liu , Dajun Yan , Han Gao
Stroke, a leading cause of death and disability worldwide, severely disrupts brain functional organization and cognitive abilities. Previous research has mainly focused on discrete functional network changes post-stroke, but how stroke affects whole-brain functional hierarchy and its relationship to cognitive recovery remains poorly understood. In this exploratory longitudinal study, we used connectome gradient mapping in 33 patients with first-ever stroke and 21 healthy controls to examine how stroke affects large-scale functional network organization across an early post-stroke(∼2 weeks), a subacute stage (3 months), and a chronic stage (1 year). By projecting functional connectivity patterns onto a low-dimensional gradient space, we found that although overall gradient structure remained relatively stable at the group level, individual patients exhibited significant deviations (EDfunc) from the healthy topology, most prominently at the early post-stroke across visual, somatomotor, ventral attention, and control networks. Furthermore, EDfunc showed time-specific associations with cognitive functions: broad negative correlations with visuospatial attention in the early post-stroke, transitioning to more selective associations with motor and attention measures in the chronic stage. In addition, dynamic interhemispheric functional imbalances emerged in the subacute and chronic stages. Taken together, these findings provide preliminary, hypothesis-generating evidence for dynamic reorganization of whole-brain functional hierarchy following stroke, and suggest that connectome gradient analysis and EDfunc may offer a sensitive framework for monitoring recovery and informing individualized rehabilitation strategies, pending confirmation in larger multi-center cohorts.
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Pub Date : 2025-12-15DOI: 10.1016/j.neuroimage.2025.121620
Yunzhou Liu , Rong Zhang , Qiao He , Xiaoyan Dong
Purpose
Investigate the effects of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on school-aged children's executive function and reveal how they affect executive function focusing on underlying neural substrates.
Methods
Sixty students (aged 9 to 10) from two fourth-grade classes in a primary school were selected as the research participants and randomly divided into the HIIT group, MICT group, and control group by using a random number table after gender matching. The control group was asked to continue their regular activities such as school physical education, recess activities and so on, while the HIIT group and MICT group were required to conduct jump rope exercises continuously for 8 weeks (5 times per week) according to the requirements, in addition to their regular activities. The HIIT group was required to jump fast with feet together for 1 min followed by 1 min of rest, repeated for 5 sets, with exercise intensity ≥85 % of maximum heart rate; the MICT group was required to jump at a moderate speed with feet together continuously for 5 min, with exercise intensity of 60–80 % of maximum heart rate. Stroop color-word test (SCWT) was performed on the day before and the day after the intervention, during both of which cortical hemodynamic changes in the prefrontal cortex were monitored using functional near infrared spectroscopy (fNIRS).
Results
In the SCWT after the intervention, both the HIIT and MICT groups showed reduced reaction time under incongruent conditions, but the accuracy remained unchanged, and oxy-Hb concentrations in the left dorsolateral prefrontal cortex (l-DLPFC) were reduced under incongruent conditions. McNemar test showed that HIIT and MICT-elicited improvement of inhibitory control and left-DLPFC activations were significantly coincided.
Conclusions
Using HIIT and MICT methods for rope skipping exercises can improve inhibitory function of children aged 9 to10, with reduced left 1-DLPFC activation potentially reflecting improved neural efficiency during task maintenance and performance.
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