Pub Date : 2026-02-15Epub Date: 2026-01-25DOI: 10.1016/j.neuroimage.2026.121754
Yujing Huang (黄玉晶) , Hao Zhang (张灏) , Buqing Ma (马步青) , Zhe Yu (俞哲) , Shenyi Dai (戴珅懿) , Lu Cheng (程璐) , Li Su (苏里) , Alzheimer’s Disease Neuroimaging Initiative (ADNI), Gaoyi Yang (杨高怡) , Qingguo Ma (马庆国)
Introduction
Longitudinal trajectories from healthy aging to Mild Cognitive Impairment and Alzheimer’s Disease involve complex mechanisms.
Methods
We evaluated five machine learning approaches (Random Forest, Support Vector Machines, Radial Basis Function Networks, Backpropagation Networks, Convolutional Neural Network) to assess the importance of potential predictive markers across the health-to-dementia continuum. Using the ADNI cohort across four phases (ADNI1, ADNIGO, ADNI2, ADNI3), we analyzed participants with distinct trajectories: stable, convertible, and reverse progression.
Results
Random Forest outperformed other models across key effectiveness metrics and achieved a macro-averaged sensitivity of 70.8 % and specificity of 96.8 % across all participant groups. Random Forest identified visuospatial and memory-related cognitive dysfunction as key predictive clinical features and several amyloid-related neuroimaging biomarkers — including temporal variations of amyloid uptake within inferior lateral ventricles, para-hippocampus—for classifying participant groups. Additionally, plasma APOE4 and long neurofilament light chain levels emerged as promising predictors for tracking progression.
Conclusion
These findings highlight the potential of machine learning in classifying disease trajectories.
{"title":"Converse or reverse? Machine-learning modeling for disease progression: A study based on Alzheimer’s disease continuum cohort","authors":"Yujing Huang (黄玉晶) , Hao Zhang (张灏) , Buqing Ma (马步青) , Zhe Yu (俞哲) , Shenyi Dai (戴珅懿) , Lu Cheng (程璐) , Li Su (苏里) , Alzheimer’s Disease Neuroimaging Initiative (ADNI), Gaoyi Yang (杨高怡) , Qingguo Ma (马庆国)","doi":"10.1016/j.neuroimage.2026.121754","DOIUrl":"10.1016/j.neuroimage.2026.121754","url":null,"abstract":"<div><h3>Introduction</h3><div>Longitudinal trajectories from healthy aging to Mild Cognitive Impairment and Alzheimer’s Disease involve complex mechanisms.</div></div><div><h3>Methods</h3><div>We evaluated five machine learning approaches (Random Forest, Support Vector Machines, Radial Basis Function Networks, Backpropagation Networks, Convolutional Neural Network) to assess the importance of potential predictive markers across the health-to-dementia continuum. Using the ADNI cohort across four phases (ADNI1, ADNIGO, ADNI2, ADNI3), we analyzed participants with distinct trajectories: stable, convertible, and reverse progression.</div></div><div><h3>Results</h3><div>Random Forest outperformed other models across key effectiveness metrics and achieved a macro-averaged sensitivity of 70.8 % and specificity of 96.8 % across all participant groups. Random Forest identified visuospatial and memory-related cognitive dysfunction as key predictive clinical features and several amyloid-related neuroimaging biomarkers — including temporal variations of amyloid uptake within inferior lateral ventricles, para-hippocampus—for classifying participant groups. Additionally, plasma APOE4 and long neurofilament light chain levels emerged as promising predictors for tracking progression.</div></div><div><h3>Conclusion</h3><div>These findings highlight the potential of machine learning in classifying disease trajectories.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"327 ","pages":"Article 121754"},"PeriodicalIF":4.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146065352","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}
Diacylglycerol kinase (DGK) is an enzyme catalyzing ATP-dependent conversion of diacylglycerol to phosphatidic acid. Among DGK subtypes, DGKγ is localized in the brain and plays important roles in the central nervous system, although its detailed functions remain unknown. Recently, [11C]T-278 was developed as a selective positron emission tomography (PET) imaging agent for DGKγ. This study aimed to conduct the first quantitative analysis using PET with [11C]T-278 in nonhuman primate brains. In rhesus monkeys, compartmental analyses showed superior goodness-of-fit in two-tissue compartment model than one-tissue compartment model. Full kinetic analysis of [11C]T-278 yielded reliable estimates of the total distribution volume (VT) values across various brain regions, showing a strong correlation (slope = 1.07, r > 0.995) with VT value derived from Logan GA. Furthermore, time-stability analysis for VT estimations showed small variations (< 5 %) between 70 and 90 min of scan durations across most regions of interest. This study provides the first in vivo visualization of DGKγ in monkey brain using quantitative PET analysis with [11C]T-278.
{"title":"In vivo quantitative assessments with [11C]T-278, a PET imaging agent for diacylglycerol kinase gamma, in nonhuman primate brain","authors":"Yasushi Hattori , Tomoteru Yamasaki , Yuji Nagai , Takashi Okauchi , Masayuki Fujinaga , Wakana Mori , Takafumi Minamimoto , Makoto Higuchi , Tatsuki Koike , Ming-Rong Zhang","doi":"10.1016/j.neuroimage.2026.121731","DOIUrl":"10.1016/j.neuroimage.2026.121731","url":null,"abstract":"<div><div>Diacylglycerol kinase (DGK) is an enzyme catalyzing ATP-dependent conversion of diacylglycerol to phosphatidic acid. Among DGK subtypes, DGKγ is localized in the brain and plays important roles in the central nervous system, although its detailed functions remain unknown. Recently, [<sup>11</sup>C]T-278 was developed as a selective positron emission tomography (PET) imaging agent for DGKγ. This study aimed to conduct the first quantitative analysis using PET with [<sup>11</sup>C]T-278 in nonhuman primate brains. In rhesus monkeys, compartmental analyses showed superior goodness-of-fit in two-tissue compartment model than one-tissue compartment model. Full kinetic analysis of [<sup>11</sup>C]T-278 yielded reliable estimates of the total distribution volume (<em>V</em><sub>T</sub>) values across various brain regions, showing a strong correlation (slope = 1.07, <em>r</em> > 0.995) with <em>V</em><sub>T</sub> value derived from Logan GA. Furthermore, time-stability analysis for <em>V</em><sub>T</sub> estimations showed small variations (< 5 %) between 70 and 90 min of scan duration<del>s</del> across most regions of interest. This study provides the first <em>in vivo</em> visualization of DGKγ in monkey brain using quantitative PET analysis with [<sup>11</sup>C]T-278.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"327 ","pages":"Article 121731"},"PeriodicalIF":4.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145994544","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 : 2026-02-15Epub Date: 2026-01-23DOI: 10.1016/j.neuroimage.2026.121751
Yihao Sheng , Woxin Pan , Haibing Huang , Shenghao Geng , Fangyan Jia , Liyv Lu , Ke Chen , Chunyan Zhu , Dandan Li
Background
Repetitive transcranial magnetic stimulation (rTMS) shows therapeutic potential for obsessive-compulsive disorder (OCD). Brain entropy has recently emerged as a candidate biomarker in neuropsychiatry, yet its modulation by rTMS in OCD remains unclear. Given EEG's superior temporal resolution for capturing rapid fluctuations in neural complexity, it was used to evaluate the effects of fMRI-neuronavigated rTMS on frontal entropy and its potential as an objective treatment marker.
Methods
Resting-state EEG was recorded from 44 OCD patients and 24 healthy controls (HCs) to compute frontal entropy- and complexity-based measures, including approximate entropy (ApEn), sample entropy (SampEn), and Lempel–Ziv complexity (LZC). Patients were randomized to an active (n = 22) or sham (n = 22) rTMS group, with the active group receiving individualized 1 Hz stimulation over the right pre-supplementary motor area for 14 consecutive days. EEG was repeated post-intervention.
Results
At baseline, OCD patients exhibited higher frontal complexity than healthy controls across all three measures. Linear mixed-effects models consistently revealed significant main effects of time and stimulation, as well as their interaction. Bayesian and FDR-corrected analyses confirmed significant reductions in all three measures following active stimulation. Post-treatment, frontal complexity remained elevated in the sham group relative to healthy controls, whereas no such difference was observed in the active stimulation group.
Conclusion
OCD is characterized by increased frontal neural complexity as indexed by multiple entropy- and complexity-based EEG measures. Individualized rTMS modulated these abnormalities, supporting frontal EEG complexity as a promising objective biomarker of neuromodulatory effects.
{"title":"Personalized repetitive transcranial magnetic stimulation reduces frontal eeg complexity in patients with obsessive–compulsive disorder","authors":"Yihao Sheng , Woxin Pan , Haibing Huang , Shenghao Geng , Fangyan Jia , Liyv Lu , Ke Chen , Chunyan Zhu , Dandan Li","doi":"10.1016/j.neuroimage.2026.121751","DOIUrl":"10.1016/j.neuroimage.2026.121751","url":null,"abstract":"<div><h3>Background</h3><div>Repetitive transcranial magnetic stimulation (rTMS) shows therapeutic potential for obsessive-compulsive disorder (OCD). Brain entropy has recently emerged as a candidate biomarker in neuropsychiatry, yet its modulation by rTMS in OCD remains unclear. Given EEG's superior temporal resolution for capturing rapid fluctuations in neural complexity, it was used to evaluate the effects of fMRI-neuronavigated rTMS on frontal entropy and its potential as an objective treatment marker.</div></div><div><h3>Methods</h3><div>Resting-state EEG was recorded from 44 OCD patients and 24 healthy controls (HCs) to compute frontal entropy- and complexity-based measures, including approximate entropy (ApEn), sample entropy (SampEn), and Lempel–Ziv complexity (LZC). Patients were randomized to an active (n = 22) or sham (n = 22) rTMS group, with the active group receiving individualized 1 Hz stimulation over the right pre-supplementary motor area for 14 consecutive days. EEG was repeated post-intervention.</div></div><div><h3>Results</h3><div>At baseline, OCD patients exhibited higher frontal complexity than healthy controls across all three measures. Linear mixed-effects models consistently revealed significant main effects of time and stimulation, as well as their interaction. Bayesian and FDR-corrected analyses confirmed significant reductions in all three measures following active stimulation. Post-treatment, frontal complexity remained elevated in the sham group relative to healthy controls, whereas no such difference was observed in the active stimulation group.</div></div><div><h3>Conclusion</h3><div>OCD is characterized by increased frontal neural complexity as indexed by multiple entropy- and complexity-based EEG measures. Individualized rTMS modulated these abnormalities, supporting frontal EEG complexity as a promising objective biomarker of neuromodulatory effects.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"327 ","pages":"Article 121751"},"PeriodicalIF":4.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146046675","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 : 2026-02-15Epub Date: 2026-01-13DOI: 10.1016/j.neuroimage.2026.121716
Jiaying Zhang , Junying Liang , Yiguang Liu , Cheng Luo
Speech comprehension is a multistage process involving both acoustic encoding and linguistic processing. Accumulating evidence has demonstrated that low-frequency cortical activity can track perceived linguistic units (e.g., words) on top of basic acoustic features (e.g., speech envelope). However, it remains unclear how the neural tracking of acoustic and linguistic information relates to second language (L2) speech comprehension in narrative contexts. Here, we investigate neural tracking of narrative speech for L2 listeners using electroencephalography (EEG). Notably, we introduce amplitude modulation (AM) cues aligned with word rhythm onto the basic envelope of speech and employ a frequency-tagging paradigm to measure neural responses to word and AM rhythm separately. When narrative speech was presented to L2 listeners during a speech comprehension task, reliable neural tracking of word and AM rhythm was observed in low-frequency cortical activity. While the introduction of AM cues enhances both comprehension performance and word-tracking responses, listeners with high versus low comprehension performance exhibit differences in their word-tracking responses rather than AM-tracking responses. Furthermore, the power and phase associated with word-tracking responses jointly reflect individual comprehension performance of L2 listeners. Our results indicate that bottom-up acoustic cues and top-down linguistic knowledge predominantly modulate the low-frequency neural tracking of linguistic units, which contributes to speech comprehension in a nonnative language.
{"title":"Cortical encoding of acoustic and linguistic rhythms reflects L2 narrative comprehension","authors":"Jiaying Zhang , Junying Liang , Yiguang Liu , Cheng Luo","doi":"10.1016/j.neuroimage.2026.121716","DOIUrl":"10.1016/j.neuroimage.2026.121716","url":null,"abstract":"<div><div>Speech comprehension is a multistage process involving both acoustic encoding and linguistic processing. Accumulating evidence has demonstrated that low-frequency cortical activity can track perceived linguistic units (e.g., words) on top of basic acoustic features (e.g., speech envelope). However, it remains unclear how the neural tracking of acoustic and linguistic information relates to second language (L2) speech comprehension in narrative contexts. Here, we investigate neural tracking of narrative speech for L2 listeners using electroencephalography (EEG). Notably, we introduce amplitude modulation (AM) cues aligned with word rhythm onto the basic envelope of speech and employ a frequency-tagging paradigm to measure neural responses to word and AM rhythm separately. When narrative speech was presented to L2 listeners during a speech comprehension task, reliable neural tracking of word and AM rhythm was observed in low-frequency cortical activity. While the introduction of AM cues enhances both comprehension performance and word-tracking responses, listeners with high versus low comprehension performance exhibit differences in their word-tracking responses rather than AM-tracking responses. Furthermore, the power and phase associated with word-tracking responses jointly reflect individual comprehension performance of L2 listeners. Our results indicate that bottom-up acoustic cues and top-down linguistic knowledge predominantly modulate the low-frequency neural tracking of linguistic units, which contributes to speech comprehension in a nonnative language.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"327 ","pages":"Article 121716"},"PeriodicalIF":4.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145990031","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 : 2026-02-15Epub Date: 2026-01-13DOI: 10.1016/j.neuroimage.2026.121719
Hui Li , John Chi-Kin Lee , Dandan Wu , Keya Ding
A foundational debate in education contrasts constructivist and instructivist pedagogies, yet their neurocognitive underpinnings remain largely unknown. This study provides a pioneering direct neural comparison of these pedagogical paradigms. Using functional near-infrared spectroscopy (fNIRS) hyperscanning, we simultaneously recorded prefrontal cortex activity from 54 teacher-child dyads (children aged 4–7 years) during a collaborative LEGO-building task in a Chinese context. Dyads were randomly assigned to either a constructivist (facilitator-led) or an instructivist (expert-led) approach. We analyzed intra-brain (within-person) and inter-brain (between-person) synchrony using wavelet transform coherence.
Results revealed distinct neural signatures for each approach. Both teachers and children exhibited unique patterns of intra-brain connectivity reflecting the different cognitive demands of each role. Critically, dyads in the constructivist approach displayed significantly higher inter-brain synchrony in right prefrontal regions (implicated in social cognition and mentalizing) compared to dyads in the instructivist condition. These findings suggest that constructivism fosters a neurally coupled, collaborative state between teacher and child, potentially reflecting a shared cognitive space. In contrast, instructivist teaching appears to impose a higher, more independent cognitive load on the teacher with less dyadic neural alignment. This work provides the first neurobiological evidence differentiating these cornerstone teaching frameworks and offers a new avenue for a neurally-informed science of learning.
{"title":"The neural correlates of pedagogy: An fNIRS hyperscanning study of constructivist and instructivist approaches in teacher-child dyads","authors":"Hui Li , John Chi-Kin Lee , Dandan Wu , Keya Ding","doi":"10.1016/j.neuroimage.2026.121719","DOIUrl":"10.1016/j.neuroimage.2026.121719","url":null,"abstract":"<div><div>A foundational debate in education contrasts constructivist and instructivist pedagogies, yet their neurocognitive underpinnings remain largely unknown. This study provides a pioneering direct neural comparison of these pedagogical paradigms. Using functional near-infrared spectroscopy (fNIRS) hyperscanning, we simultaneously recorded prefrontal cortex activity from 54 teacher-child dyads (children aged 4–7 years) during a collaborative LEGO-building task in a Chinese context. Dyads were randomly assigned to either a constructivist (facilitator-led) or an instructivist (expert-led) approach. We analyzed intra-brain (within-person) and inter-brain (between-person) synchrony using wavelet transform coherence.</div><div>Results revealed distinct neural signatures for each approach. Both teachers and children exhibited unique patterns of intra-brain connectivity reflecting the different cognitive demands of each role. Critically, dyads in the constructivist approach displayed significantly higher inter-brain synchrony in right prefrontal regions (implicated in social cognition and mentalizing) compared to dyads in the instructivist condition. These findings suggest that constructivism fosters a neurally coupled, collaborative state between teacher and child, potentially reflecting a shared cognitive space. In contrast, instructivist teaching appears to impose a higher, more independent cognitive load on the teacher with less dyadic neural alignment. This work provides the first neurobiological evidence differentiating these cornerstone teaching frameworks and offers a new avenue for a neurally-informed science of learning.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"327 ","pages":"Article 121719"},"PeriodicalIF":4.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145990085","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 : 2026-02-15Epub Date: 2026-01-20DOI: 10.1016/j.neuroimage.2026.121743
Zi-Jian Feng , Ziyu Wei , Liquan Hong , Hongli Fang , Yu Han , Peifeng Yang , Dongsheng Lv , Yu-Feng Zang
Personalized repetitive transcranial magnetic stimulation (rTMS) increasingly relies on resting-state functional magnetic resonance imaging (fMRI) to select stimulation sites, yet most pipelines depend on user-defined thresholds and atlas masks, which can shift individualized targets. We propose a watershed-based approach, implemented in a graphical user interface, that performs threshold-independent segmentation of functional images to support rTMS target localization. As a proof-of-concept, we focused on Alzheimer’s disease–related circuits within the default mode network, designating the posterior cingulate cortex (PCC) as the deep effective region and the inferior parietal lobule (IPL) as the superficial stimulation target. In a cohort of 21 healthy participants, quantitative comparison with a conventional threshold-based, mask-constrained peak strategy revealed high concordance for PCC peaks but a median spatial displacement of 6.0 mm (95 % CI: 0.0–12.7 mm) for IPL targets. Qualitative examples further illustrate that watershed segmentation reduces bias from neighboring functional clusters, truncation by atlas boundaries, and ambiguity among multiple local peaks. By decoupling target definition from user-chosen thresholds and packaging the method in an accessible toolbox, this framework offers a generalizable tool for individualized fMRI-guided rTMS.
个性化重复经颅磁刺激（rTMS）越来越依赖于静息状态功能磁共振成像（fMRI）来选择刺激位点，然而大多数管道依赖于用户定义的阈值和图谱掩模，这可以改变个性化的目标。我们提出了一种基于分水岭的方法，在图形用户界面中实现，该方法对功能图像进行阈值无关的分割，以支持rTMS目标定位。作为概念验证，我们重点研究了默认模式网络中与阿尔茨海默病相关的回路，将后扣带皮层（PCC）指定为深部有效区，将下顶叶（IPL）指定为浅表刺激目标。在21名健康参与者的队列中，与传统的基于阈值的面罩约束峰策略进行定量比较，发现PCC峰的一致性很高，但IPL目标的中位空间位移为6.0 mm （95% CI: 0.0-12.7 mm）。定性的例子进一步说明分水岭分割减少了邻近功能簇的偏差、图谱边界的截断以及多个局部峰之间的模糊性。通过将目标定义与用户选择的阈值解耦，并将方法打包到一个可访问的工具箱中，该框架为个性化fmri引导的rTMS提供了一个通用的工具。
{"title":"A watershed algorithm GUI for personalized fMRI-guided rTMS target","authors":"Zi-Jian Feng , Ziyu Wei , Liquan Hong , Hongli Fang , Yu Han , Peifeng Yang , Dongsheng Lv , Yu-Feng Zang","doi":"10.1016/j.neuroimage.2026.121743","DOIUrl":"10.1016/j.neuroimage.2026.121743","url":null,"abstract":"<div><div>Personalized repetitive transcranial magnetic stimulation (rTMS) increasingly relies on resting-state functional magnetic resonance imaging (fMRI) to select stimulation sites, yet most pipelines depend on user-defined thresholds and atlas masks, which can shift individualized targets. We propose a watershed-based approach, implemented in a graphical user interface, that performs threshold-independent segmentation of functional images to support rTMS target localization. As a proof-of-concept, we focused on Alzheimer’s disease–related circuits within the default mode network, designating the posterior cingulate cortex (PCC) as the deep effective region and the inferior parietal lobule (IPL) as the superficial stimulation target. In a cohort of 21 healthy participants, quantitative comparison with a conventional threshold-based, mask-constrained peak strategy revealed high concordance for PCC peaks but a median spatial displacement of 6.0 mm (95 % CI: 0.0–12.7 mm) for IPL targets. Qualitative examples further illustrate that watershed segmentation reduces bias from neighboring functional clusters, truncation by atlas boundaries, and ambiguity among multiple local peaks. By decoupling target definition from user-chosen thresholds and packaging the method in an accessible toolbox, this framework offers a generalizable tool for individualized fMRI-guided rTMS.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"327 ","pages":"Article 121743"},"PeriodicalIF":4.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025231","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 : 2026-02-15Epub Date: 2026-01-20DOI: 10.1016/j.neuroimage.2026.121738
Jia Li , Rong Wang , Jianze Wu , Qian Xiao , Yuan Zhong
Pediatric bipolar disorder (PBD) is characterized by disrupted cognitive control, particularly in response inhibition under emotional interference. However, the neural underpinnings of these deficits, particularly how these impairments vary across emotional valence and whether they reflect trait markers or state alterations, remain unclear. While traditional univariate fMRI analyses reveal broad activation differences, they lack sensitivity to fine-grained neural patterns. This study aims to examine the neural representations of emotional response inhibition in PBD under valence-dependent interference using representational similarity analysis(RSA). We included manic (n = 15) and euthymic (n = 18) PBD patients, along with matched healthy controls (n = 17). Participants completed an emotional Go/NoGo task with happy, sad, and neutral faces during fMRI. Six contrast conditions were modeled to assess trait- and state-related effects. Whole-brain searchlight RSA (8 mm radius) was used to identify regions showing group differences in neural representational patterns. Results showed that emotional response inhibition engaged distributed neural systems, with distinct patterns across valence conditions. Compared to controls, PBD patients exhibited trait-related representational differences during happy inhibition, sad inhibition, and sad-specific inhibition, involving regions such as the precentral gyrus, middle frontal gyrus, and inferior parietal lobule. Manic patients showed state-related reductions in neural representations during sad-specific inhibition within frontal areas compared to euthymic patients. These findings indicate that emotional response inhibition deficits in PBD arise from both trait- and state-dependent abnormalities in neural representations. The study highlights the value of multivariate fMRI in uncovering clinically relevant biomarkers and provides a novel framework for developing phase-specific interventions.
{"title":"Neural representations of emotional response inhibition reveal trait and state biomarkers in pediatric bipolar disorder","authors":"Jia Li , Rong Wang , Jianze Wu , Qian Xiao , Yuan Zhong","doi":"10.1016/j.neuroimage.2026.121738","DOIUrl":"10.1016/j.neuroimage.2026.121738","url":null,"abstract":"<div><div>Pediatric bipolar disorder (PBD) is characterized by disrupted cognitive control, particularly in response inhibition under emotional interference. However, the neural underpinnings of these deficits, particularly how these impairments vary across emotional valence and whether they reflect trait markers or state alterations, remain unclear. While traditional univariate fMRI analyses reveal broad activation differences, they lack sensitivity to fine-grained neural patterns. This study aims to examine the neural representations of emotional response inhibition in PBD under valence-dependent interference using representational similarity analysis(RSA). We included manic (<em>n</em> = 15) and euthymic (<em>n</em> = 18) PBD patients, along with matched healthy controls (<em>n</em> = 17). Participants completed an emotional Go/NoGo task with happy, sad, and neutral faces during fMRI. Six contrast conditions were modeled to assess trait- and state-related effects. Whole-brain searchlight RSA (8 mm radius) was used to identify regions showing group differences in neural representational patterns. Results showed that emotional response inhibition engaged distributed neural systems, with distinct patterns across valence conditions. Compared to controls, PBD patients exhibited trait-related representational differences during happy inhibition, sad inhibition, and sad-specific inhibition, involving regions such as the precentral gyrus, middle frontal gyrus, and inferior parietal lobule. Manic patients showed state-related reductions in neural representations during sad-specific inhibition within frontal areas compared to euthymic patients. These findings indicate that emotional response inhibition deficits in PBD arise from both trait- and state-dependent abnormalities in neural representations. The study highlights the value of multivariate fMRI in uncovering clinically relevant biomarkers and provides a novel framework for developing phase-specific interventions.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"327 ","pages":"Article 121738"},"PeriodicalIF":4.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146030258","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 : 2026-02-15Epub Date: 2026-01-15DOI: 10.1016/j.neuroimage.2026.121730
Jonghyun Bae , Angelique De Rouen , Zhaoyuan Gong , Nathan Zhang , Noam Y. Fox , Murat Bilgel , Christopher M. Bergeron , Luigi Ferrucci , Mustapha Bouhrara
BACKGROUND
Cerebral iron accumulation is a hallmark of aging and age-related neurodegenerative conditions. This study explored whether higher iron levels in deep gray matter (DGM) structures contribute to motor and cognitive decline and whether this association is mediated by demyelination in white matter (WM) tracts connecting the DGM to the cortex.
METHOD
We used quantitative susceptibility mapping (QSM) to quantify brain iron and multi-component relaxometry to estimate myelin content in 86 cognitively unimpaired adults (ages 22–94) who underwent longitudinal assessments of cognitive and motor function. We analyzed age-related differences in DGM iron levels, examined their association with cognitive and functional decline, and conducted mediation analyses to evaluate the role of WM myelination.
RESULTS
Higher iron levels in the putamen and caudate nucleus were significantly correlated with older age. Higher putamen iron level was negatively associated with usual and rapid gait speed. In longitudinal analyses, higher iron levels in DGM were associated with a steeper decline in verbal fluency, processing speed, and motor function. Myelin content revealed a significant indirect mediated effect on the relationship between high iron content and motor function in the superior corona radiata, a WM tract connecting the putamen to the cortex.
CONCLUSION
These findings suggest that excessive iron is linked to cognitive and functional decline in aging, with motor deterioration specifically mediated by demyelination of white matter pathways connecting the deep gray matter to the cortex. Together, iron and myelin metrics may serve as early biomarkers of age-related clinical decline and represent promising therapeutic targets for preserving motor function in older adults.
{"title":"Excess iron in deep gray matter is associated with cognitive and functional decline: The mediating role of white matter myelin","authors":"Jonghyun Bae , Angelique De Rouen , Zhaoyuan Gong , Nathan Zhang , Noam Y. Fox , Murat Bilgel , Christopher M. Bergeron , Luigi Ferrucci , Mustapha Bouhrara","doi":"10.1016/j.neuroimage.2026.121730","DOIUrl":"10.1016/j.neuroimage.2026.121730","url":null,"abstract":"<div><h3>BACKGROUND</h3><div>Cerebral iron accumulation is a hallmark of aging and age-related neurodegenerative conditions. This study explored whether higher iron levels in deep gray matter (DGM) structures contribute to motor and cognitive decline and whether this association is mediated by demyelination in white matter (WM) tracts connecting the DGM to the cortex.</div></div><div><h3>METHOD</h3><div>We used quantitative susceptibility mapping (QSM) to quantify brain iron and multi-component relaxometry to estimate myelin content in 86 cognitively unimpaired adults (ages 22–94) who underwent longitudinal assessments of cognitive and motor function. We analyzed age-related differences in DGM iron levels, examined their association with cognitive and functional decline, and conducted mediation analyses to evaluate the role of WM myelination.</div></div><div><h3>RESULTS</h3><div>Higher iron levels in the putamen and caudate nucleus were significantly correlated with older age. Higher putamen iron level was negatively associated with usual and rapid gait speed. In longitudinal analyses, higher iron levels in DGM were associated with a steeper decline in verbal fluency, processing speed, and motor function. Myelin content revealed a significant indirect mediated effect on the relationship between high iron content and motor function in the superior corona radiata, a WM tract connecting the putamen to the cortex.</div></div><div><h3>CONCLUSION</h3><div>These findings suggest that excessive iron is linked to cognitive and functional decline in aging, with motor deterioration specifically mediated by demyelination of white matter pathways connecting the deep gray matter to the cortex. Together, iron and myelin metrics may serve as early biomarkers of age-related clinical decline and represent promising therapeutic targets for preserving motor function in older adults.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"327 ","pages":"Article 121730"},"PeriodicalIF":4.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145994498","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 : 2026-02-15Epub Date: 2026-01-27DOI: 10.1016/j.neuroimage.2026.121759
Gabriele Pirazzini , Antonio Cataneo , Silvana Pelle , Alice Marra , Giorgio Arcara , Simone Battaglia , Mauro Ursino , Alessio Avenanti
The posterior superior temporal sulcus (pSTS) and early visual cortex (V1/V2) form part of a lateral occipito-temporal network - proposed as a “third” visual pathway - supporting the processing of socially and emotionally relevant information. Prior studies using cortico-cortical paired associative stimulation (ccPAS) applied from pSTS to V1/V2 have shown enhanced recognition of facial emotional expressions, interpreted as reflecting strengthened temporo-occipital backward connectivity. However, direct evidence that ccPAS can modulate pSTS-to-V1/V2 connectivity has been lacking. Here, we applied ccPAS consisting of repeated paired TMS pulses, with the first pulse delivered over pSTS and the second pulse over V1/V2 (ccPASSTS-V1). A reverse-order protocol (ccPASV1-STS) served as a control. Resting-state EEG was recorded before, immediately after, and 30 min post-stimulation to assess functional connectivity. Multivariate spectral Granger Causality analysis characterized the directionality and frequency-dependent dynamics of connectivity. Outdegree metrics revealed that ccPASSTS-V1 enhanced backward functional connectivity immediately after stimulation, with effects persisting after 30 min, possibly consistent with Hebbian-like associative plasticity in top-down pathways. In addition, an increase in forward connectivity was observed 30 min after ccPASV1-STS, and more weakly after ccPASSTS-V1, possibly reflecting broader compensatory mechanisms. These findings demonstrate that ccPAS can transiently and selectively modulate directional connectivity within the “third” visual pathway, providing insights into the physiological basis of ccPAS and suggesting that previously observed improvements in emotion recognition following ccPASSTS-V1 may arise from plastic changes in backward pSTS-to-V1/V2 connectivity. More broadly, they underscore the potential of ccPAS to probe and modulate the dynamics of higher-order visual circuits.
{"title":"Evidence for enhanced backward connectivity in the third visual pathway following cortico-cortical paired associative stimulation","authors":"Gabriele Pirazzini , Antonio Cataneo , Silvana Pelle , Alice Marra , Giorgio Arcara , Simone Battaglia , Mauro Ursino , Alessio Avenanti","doi":"10.1016/j.neuroimage.2026.121759","DOIUrl":"10.1016/j.neuroimage.2026.121759","url":null,"abstract":"<div><div>The posterior superior temporal sulcus (pSTS) and early visual cortex (V1/V2) form part of a lateral occipito-temporal network - proposed as a “third” visual pathway - supporting the processing of socially and emotionally relevant information. Prior studies using cortico-cortical paired associative stimulation (ccPAS) applied from pSTS to V1/V2 have shown enhanced recognition of facial emotional expressions, interpreted as reflecting strengthened temporo-occipital backward connectivity. However, direct evidence that ccPAS can modulate pSTS-to-V1/V2 connectivity has been lacking. Here, we applied ccPAS consisting of repeated paired TMS pulses, with the first pulse delivered over pSTS and the second pulse over V1/V2 (ccPAS<em><sub>STS-V1</sub></em>). A reverse-order protocol (ccPAS<em><sub>V1-STS</sub></em>) served as a control. Resting-state EEG was recorded before, immediately after, and 30 min post-stimulation to assess functional connectivity. Multivariate spectral Granger Causality analysis characterized the directionality and frequency-dependent dynamics of connectivity. Outdegree metrics revealed that ccPAS<em><sub>STS-V1</sub></em> enhanced backward functional connectivity immediately after stimulation, with effects persisting after 30 min, possibly consistent with Hebbian-like associative plasticity in top-down pathways. In addition, an increase in forward connectivity was observed 30 min after ccPAS<em><sub>V1-STS</sub></em>, and more weakly after ccPAS<em><sub>STS-V1</sub></em>, possibly reflecting broader compensatory mechanisms. These findings demonstrate that ccPAS can transiently and selectively modulate directional connectivity within the “third” visual pathway, providing insights into the physiological basis of ccPAS and suggesting that previously observed improvements in emotion recognition following ccPAS<em><sub>STS-V1</sub></em> may arise from plastic changes in backward pSTS-to-V1/V2 connectivity. More broadly, they underscore the potential of ccPAS to probe and modulate the dynamics of higher-order visual circuits.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"327 ","pages":"Article 121759"},"PeriodicalIF":4.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146086294","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 : 2026-02-15Epub Date: 2026-01-07DOI: 10.1016/j.neuroimage.2026.121706
Xiaorong Hou , Jiajian Zhang , Junhong Duan , Yafei Song , Xuxiong Tang , Ziwei Gong , Ziwen Li , Zhineng Kang , Yunchen Huang , Jingqi He , Xiaoxia Zhou , Beisha Tang , Yin Liu , Lifang Lei
Depression in Parkinson's disease (PD) involves complex structural, functional and multiple neurotransmitter systems alterations. So far, the precise interplay between structural and functional brain alterations and their underlying neurotransmitter processes remains largely unexplored. The advent of parallel independent component analysis (pICA) and the JuSpace toolbox provide a possible clue to elucidate their interrelationships and underlying mechanisms. In this study, we employed pICA to examine co-varying components interaction between gray matter volume (GMV) and fractional amplitude of low-frequency fluctuations (fALFF) in a cohort of 142 PD patients, comprising 53 PD patients with depression (PDD) and 89 PD patients without depression (PDND). Furthermore, we examined the spatial correlations between the GMV/fALFF components identified by pICA and neurotransmitter system maps using the JuSpace toolbox. Our analysis revealed significant negative correlations between one fMRI component (fALFF_IC6, frontoparietal, temporal and cerebellar regions) and two sMRI components (GMV_IC1 and GMV_IC4, basal ganglia, thalamocortical circuits, cerebellum and sensorimotor networks), which was significantly different between PDD and PDND group. Meanwhile, we found that alterations in both fALFF and GMV were widely associated with multiple neurotransmitter systems, primarily the dopaminergic and serotonergic systems. Notably, the severity of depression in PD was significantly correlated with these two distinct structural networks, independent of disease duration, motor symptoms and cognitive performance. These findings suggest the PD related depression-specific interrelationships between intrinsic network activity and GMV, potentially elucidating the multimodal neural circuitry and potential neurotransmitter patterns underlying depression in PD.
{"title":"Multimodal MRI data fusion reveals distinct structural, functional and neurochemical correlates of depression in patients with Parkinson's disease","authors":"Xiaorong Hou , Jiajian Zhang , Junhong Duan , Yafei Song , Xuxiong Tang , Ziwei Gong , Ziwen Li , Zhineng Kang , Yunchen Huang , Jingqi He , Xiaoxia Zhou , Beisha Tang , Yin Liu , Lifang Lei","doi":"10.1016/j.neuroimage.2026.121706","DOIUrl":"10.1016/j.neuroimage.2026.121706","url":null,"abstract":"<div><div>Depression in Parkinson's disease (PD) involves complex structural, functional and multiple neurotransmitter systems alterations. So far, the precise interplay between structural and functional brain alterations and their underlying neurotransmitter processes remains largely unexplored. The advent of parallel independent component analysis (pICA) and the JuSpace toolbox provide a possible clue to elucidate their interrelationships and underlying mechanisms. In this study, we employed pICA to examine co-varying components interaction between gray matter volume (GMV) and fractional amplitude of low-frequency fluctuations (fALFF) in a cohort of 142 PD patients, comprising 53 PD patients with depression (PDD) and 89 PD patients without depression (PDND). Furthermore, we examined the spatial correlations between the GMV/fALFF components identified by pICA and neurotransmitter system maps using the JuSpace toolbox. Our analysis revealed significant negative correlations between one fMRI component (fALFF_IC6, frontoparietal, temporal and cerebellar regions) and two sMRI components (GMV_IC1 and GMV_IC4, basal ganglia, thalamocortical circuits, cerebellum and sensorimotor networks), which was significantly different between PDD and PDND group. Meanwhile, we found that alterations in both fALFF and GMV were widely associated with multiple neurotransmitter systems, primarily the dopaminergic and serotonergic systems. Notably, the severity of depression in PD was significantly correlated with these two distinct structural networks, independent of disease duration, motor symptoms and cognitive performance. These findings suggest the PD related depression-specific interrelationships between intrinsic network activity and GMV, potentially elucidating the multimodal neural circuitry and potential neurotransmitter patterns underlying depression in PD.</div></div>","PeriodicalId":19299,"journal":{"name":"NeuroImage","volume":"327 ","pages":"Article 121706"},"PeriodicalIF":4.5,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145945269","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}
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