Feed aggregator

bioRxiv [Preprint]. 2026 Jan 2:2026.01.02.697199. doi: 10.64898/2026.01.02.697199.

ABSTRACT

Intrinsic brain activity is characterized by large-scale spatiotemporal patterns that underpin functional connectivity and cognition. Quasi-periodic patterns (QPPs) and complex principal component analysis (cPCA) have emerged as reproducible methods for capturing spatiotemporal network interactions in resting-state functional magnetic resonance imaging (rs-fMRI). However, these methods remain sensitive to methodological factors such as scan duration, repetition time (TR), and frequency band selection. This study systematically evaluates how these parameters influence the stability and reliability of QPP- and cPCA-derived functional connectivity patterns across multiple datasets. Using five independent rs-fMRI datasets, we evaluate the impact of scan length on pattern reliability, explore the effects of TR on spatiotemporal patterns, and compare the sensitivity of different frequency bands (Slow-5, Slow-4, infraslow) in capturing network dynamics. Our findings reveal that while both QPPs and cPCA detect intrinsic network activity, their reliability varies with acquisition parameters. QPPs exhibit greater stability in shorter scans, making them suitable for individual-level analyses, whereas cPCA provides a broader representation of phase-coherent fluctuations but shows greater between-subject variability and benefits more from longer, group-level acquisitions. Additionally, frequency band selection significantly influences the temporal structure of extracted patterns: in our analyses, Slow-5 (0.01-0.027 Hz) tended to emphasize more recurrent, synchronized network configurations, whereas Slow-4 (0.027-0.073 Hz) more often revealed transitions between connectivity states. These results provide critical insights into optimizing methodological choices for dynamic functional connectivity analysis, enhancing the interpretability of spatiotemporal patterns in both basic and clinical neuroimaging research.

PMID:41509284 | PMC:PMC12776408 | DOI:10.64898/2026.01.02.697199

Alzheimers Res Ther. 2026 Jan 9. doi: 10.1186/s13195-026-01956-2. Online ahead of print.

NO ABSTRACT

PMID:41507977 | DOI:10.1186/s13195-026-01956-2

Alzheimers Dement. 2025 Dec;21 Suppl 2:e107126. doi: 10.1002/alz70856_107126.

ABSTRACT

BACKGROUND: Time-frequency analysis of resting-state fMRI (rs-fMRI) is essential for uncovering intrinsic frequency and amplitude characteristics. Mean energy and frequency profiles of different resting-state networks (RSNs) can provide fundamental information about brain activity and its impairment in aging, and characterize stage-specific alterations across the Alzheimer's disease (AD) continuum: cognitively normal (CN), mild cognitive impairment (MCI), and AD.

METHOD: Using the ADNI database (adni.loni.usc.edu), a total of 297 fMRI sessions from 150 participants (all positive for amyloid PET) were included in this study. We determined RSNs using standard group ICA software. Then, using Empirical Mode Decomposition (EMD), all RSN time series were decomposed into intrinsic mode functions (IMFs). Only the first 4 IMFs that spanned a frequency range above 0.01 Hz were used for the characterization of the RSNs. We estimated energy and frequency measures to characterize our 3 groups.

RESULT: With respect to the mean energy profiles, we found significantly reduced energy in the diseased groups (MCI and AD) in IMF2 and IMF3 of many RSNs with reference to the controls. For certain RSNs, specifically, frontoparietal; visual; temporal; the IMF4 showed the opposite trend (with large effect size, Cohen's d>0.8) with the AD group having increased mean energy compared to the other two groups. In terms of the frequency profiles a similar increase in the mean frequency was observed for IMF2, IMF3 and IMF4 in the AD and MCI patients with respect to the controls.

CONCLUSION: We found that MCI and AD participants showed reduced energy and increased frequency in many RSNs. In particular, the DMN network (DMN1) showed the largest group difference in energy and frequency for IMF2 and IMF3. This is consistent with the fact that low-frequency power (<0.1 Hz) is more related with cognitive function, while high-frequency power (>0.1 Hz) is more associated with physiological activity. From a clinical perspective the decreased energy shown by the AD patients for many RSNs highlights the potential of fMRI in capturing differences between diagnostic groups. Specifically, these variables could act as potential biomarkers that models the characteristic changes in different brain networks along the AD continuum.

PMID:41506779 | DOI:10.1002/alz70856_107126

Psychiatry Res Neuroimaging. 2025 Dec 31;357:112118. doi: 10.1016/j.pscychresns.2025.112118. Online ahead of print.

ABSTRACT

BACKGROUND: Postpartum depression (PPD) is a common women's psychological health issue. While studies have identified regional functional abnormalities, the global functional topological alterations associated with PPD remain to be fully characterized. This study aims to investigate the alteration of functional topological properties in PPD patients.

METHODS: Resting-state functional MRI (rs-fMRI) was acquired from 30 PPD patients, 23 healthy pregnant women (HPW), and 26 healthy non-pregnant women (HC). Functional brain networks were constructed using inter-regional Pearson's correlation coefficient and analyzed via graph theory. Machine learning was applied to the functional connectome to distinguish PPD from HPW.

RESULTS: Compared to HC and HPW, the PPD group showed a shift toward a more regularized network topology in functional brain network. In comparison with HC, PPD had altered topological properties mainly in the salience network (SN, e.g., left insula) and associated subcortical regions (e.g., amygdala), while HPW exhibited functional differences mainly within the default mode network (DMN). Abnormal regions (e.g., pallidum, precuneus) between PPD and HPW correlated with depression severity. Combining machine learning with functional connectivity metrics predicted PPD with 88 % accuracy.

CONCLUSION: Pregnancy may alter the functional connectome in DMN, and postpartum depression may disrupt the connectivity in SN. The insula and precuneus are critical for identifying PPD and HPW. These findings suggest that functional connectome alterations are clinical significant and may facilitate the timely clinical detection of PPD.

PMID:41506130 | DOI:10.1016/j.pscychresns.2025.112118

Neuroimage Clin. 2026 Jan 4;49:103942. doi: 10.1016/j.nicl.2026.103942. Online ahead of print.

ABSTRACT

OBJECTIVES: Understanding the progression mechanisms of glioma holds significant implications for improving clinical management. However, the natural progression patterns of glioma remain poorly understood due to the lack of longitudinal clinical samples from untreated patients.

MATERIALS AND METHODS: In this study, we systematically explored the natural progression trajectory of glioma by combining functional magnetic resonance imaging (fMRI) analysis of 24 rare multifocal glioma patients with bioinformatic analysis of single-cell RNA sequencing (scRNA-seq) data obtained from tumor samples of glioma mouse with early, mid, and endpoint lesions.

RESULTS: We discovered that larger tumors in multifocal gliomas exhibit stronger functional connectivity with the cerebral cortex and higher degree centrality within brain networks. ScRNA-seq of longitudinal mouse glioma samples revealed progressive activation of synaptic organization and associated regulatory pathways during the natural progression of glioma.

CONCLUSION: Our multimodal, cross-scale study demonstrates that the natural progression pattern of glioma macroscopically manifests as functional hyperconnectivity with the cerebral cortex, which is supported by microscale molecular programs driving synaptogenesis. These findings elucidate the characteristics and mechanisms underlying glioma natural progression.

PMID:41506055 | DOI:10.1016/j.nicl.2026.103942

Magn Reson Med. 2026 Jan 8. doi: 10.1002/mrm.70248. Online ahead of print.

ABSTRACT

PURPOSE: Functional MRI (fMRI) in awake rodents presents countless valuable opportunities for researchers to probe questions that may not be accessible through anesthetized models, such as voluntary locomotion. The commonly used echo planar imaging (EPI) sequence is highly sensitive to motion that occurs even outside of the imaging plane. Recently, zero echo time sequences have been adopted for fMRI to address this challenge.

METHODS: This study proposes a robust and reproducible protocol for longitudinal imaging of awake mice during spontaneous locomotion, using an implanted headpiece, incremental training, zero TE fMRI, reinforcement learning, and a custom treadmill module. Locomotion is known to have wide-ranging effects on brain activity and can alter neurovascular coupling, making it critical to understand this aspect of natural behavior.

RESULTS: We present results from 10 trained mice across three different fMRI scanning sessions, finding minimal head motion across scans (average framewise displacement matched anesthetized EPI (p > 0.05)), consistent resting-state functional connectivity across subjects and scans, and evidence of a minimal stress response at the group and individual level. We also demonstrate little difference on signal quality during locomotion and altered functional connectivity and spatiotemporal dynamics during locomotion compared to rest.

CONCLUSIONS: This work establishes a new benchmark for awake rodent fMRI, enabling the direct investigation of naturalistic behaviors like locomotion and their whole-brain correlates without the confounding effects of anesthesia or excessive restraint.

PMID:41505251 | DOI:10.1002/mrm.70248

J Integr Neurosci. 2025 Dec 25;24(12):43660. doi: 10.31083/JIN43660.

ABSTRACT

BACKGROUND: Disorders of consciousness (DoCs) following traumatic brain injury (TBI), or cerebrovascular disease (CVD) are difficult to prognose, as reliable biomarkers are lacking. Resting-state functional magnetic resonance imaging (fMRI) amplitude of low-frequency amplitude (ALFF) may capture etiology-specific neural activity, but its prognostic value for spinal cord stimulation (SCS) outcomes remains unknown. In this study we therefore investigated etiology-specific ALFF patterns in TBI- and CVD-induced DoCs and evaluated their prognostic value for recovery after SCS.

METHODS: Resting-state fMRI data from patients with TBI (n = 16) and CVD (n = 15), and healthy controls (n = 12), were analyzed. Whole-brain ALFF differences were also compared between the groups. Correlations between ALFF and 6-month post-SCS Coma Recovery Scale-Revised (CRS-R) score improvements were assessed. Logistic regression was used to identify consciousness recovery markers.

RESULTS: Compared with healthy controls, patients with TBI demonstrated a significant increase in ALFF within the bilateral insula, thalamus, and brainstem (p < 0.05), suggesting compensatory neural hyperactivity potentially involving glutamatergic pathways. Patients with CVD exhibited elevated ALFF in the contralateral sensorimotor cortex (p < 0.05), indicating ipsilateral neural reorganization. Notably, the thalamic ALFF were strongly correlated with consciousness recovery, as measured by improvements in CRS-R score at 6 months in both the TBI (r= 0.64, p = 0.0071) and CVD (r = 0.59, p = 0.02) groups. Furthermore, logistic regression analysis identified increased ALFF in the anterior cingulate cortex-thalamic loop (odds ratio [OR] = 3.21, p < 0.05) as a potential cross-etiology biomarker for recovery following SCS.

CONCLUSIONS: ALFF reveal distinct neuroplasticity mechanisms, including compensatory activation in TBI and ipsilateral reorganization in CVD. Elevated anterior cingulate cortex (ACC)-thalamic ALFF are a key cross-etiology biomarker for consciousness recovery to guide SCS target selection.

PMID:41503991 | DOI:10.31083/JIN43660

medRxiv [Preprint]. 2026 Jan 2:2025.12.31.25343265. doi: 10.64898/2025.12.31.25343265.

ABSTRACT

BACKGROUND: Adolescence is a period of rapid neurobiological and behavioural change, yet it remains unclear how deviations from normative brain maturation relate to the development of internalising and externalising symptoms.

METHODS: Using data from the Adolescent Brain Cognitive Development (ABCD) Study, we combined multimodal brain age prediction with bivariate latent growth curve (BLGC) models to test whether deviations in brain maturation - indexed by the brain age gap (BAG) - relate to mental health development across late childhood and adolescence. Brain age was estimated from T1-weighted, diffusion MRI (dMRI), and resting-state fMRI (rs-fMRI) data across four MRI waves (ages ~8.3-17.5). Internalising and externalising symptoms were assessed across ten waves with the self-report Brief Problem Monitor (BPM).

RESULTS: Across T1, dMRI, and multimodal models, deviations from age-expected brain maturation and internalising and externalising symptoms showed coordinated nonlinear development across adolescence. Adolescents whose brains increasingly diverged from age-expected maturation over time also showed accelerating symptom trajectories. These associations were small to moderate in magnitude and were most consistent for internalising symptoms in females (r = .15-.23), whereas externalising symptoms showed broader but less selective nonlinear associations across modalities (r = .15-.32). Linear and intercept-level associations were weaker (r = .06-.11) and modality-specific. Formal tests provided no evidence for robust sex differences in these associations after correction for multiple comparisons.

CONCLUSION: These results indicate that adolescent mental health problems are most strongly linked to nonlinear changes in how individuals diverge from age-expected brain trajectories, rather than to fixed differences in brain age. Nonlinear shifts in maturational tempo may therefore be a key developmental feature underlying vulnerability to psychopathology in youth.

PMID:41503487 | PMC:PMC12772674 | DOI:10.64898/2025.12.31.25343265

Neuroimage Rep. 2025 Dec 17;6(1):100304. doi: 10.1016/j.ynirp.2025.100304. eCollection 2026 Mar.

ABSTRACT

Understanding alterations in functional connectivity among individuals with substance use disorder (SUD) is critical for elucidating the neural mechanisms underlying addiction. In this study, we applied Energy Landscape Analysis (ELA), an energy-based machine learning method, to examine whole-brain functional connectivity differences between SUD patients and healthy controls (HCs). A key methodological challenge in ELA lies in the selection of appropriate Regions of Interest (ROIs) from comprehensive brain atlases. To address this, we employed seed-based connectivity analysis to identify task-relevant ROIs, thereby overcoming the limitation of focusing on a restricted subset of regions. The dataset comprised 53 cocaine users (CUs) and 52 age- and sex-matched HCs, with functional MRI data preprocessed using the CONN toolbox. ROI-to-ROI seed-based connectivity was computed through first- and second-level analyses. ELA revealed that HCs exhibited stronger positive connectivity between cerebellar and visual regions, whereas CUs showed stronger positive connectivity between the cerebellum and the inferior temporal gyrus (temporooccipital part; toITG). Seven low-energy connectivity states were identified that differentiated the two groups. In these states, the cerebellum and toITG demonstrated antagonistic activation patterns, while the cerebellum and visual cortex co-activated in HCs. Temporal dynamics analyses further indicated that HCs visited these low-energy states more frequently, driven by shorter dwell times but higher transition rates. These findings suggest that cocaine addiction may reflect a weakening of adaptive, protective ("guardian") connectivity patterns, rather than an increased propensity to remain in maladaptive connectivity states. Collectively, these results highlight key network-level distinctions between HCs and CUs and offer new insights into the neurobiological mechanisms of cocaine addiction.

PMID:41503436 | PMC:PMC12771301 | DOI:10.1016/j.ynirp.2025.100304

Alzheimers Dement (N Y). 2026 Jan 5;12(1):e70198. doi: 10.1002/trc2.70198. eCollection 2026 Jan-Mar.

ABSTRACT

INTRODUCTION: Ultrasound neuromodulation has emerged as a promising adjunctive therapy in Alzheimer's disease (AD), yet a controversial issue remains: whether its reported long-term therapeutic effects could be attributed to potential confounds rather than genuine neuromodulatory mechanisms. Although auditory confounds via air- or bone-conducted sound have been discussed for immediate effects, their relevance for enduring therapeutic outcomes-essential for clinical application-remains unknown. This exploratory study is the first to examine whether long-term cognitive and neural effects of transcranial pulse stimulation (TPS) in AD are linked to persistent auditory network activation.

METHODS: A comprehensive re-analysis of task-based and resting-state functional magnetic resonance imaging (fMRI) data was conducted using data from the currently largest sham-controlled clinical ultrasound neuromodulation study (Matt et al., 2025). To isolate possible auditory contributions, we applied a contrast-based framework targeting (1) air-conducted sound, (2) combined air- and possibly bone-conducted sound, and (3) bone-conduction-specific effects. Analyses included: (a) task-based auditory cortex co-activation, (b) functional connectivity between auditory and dorsal attention networks (the latter was modulated in the original study), (c) global efficiency within the auditory network, and (d) correlations with neuropsychological test battery scores.

RESULTS: No significant long-term activation of auditory cortices was observed in task-based fMRI. Resting-state analyses showed no altered connectivity between auditory and attention networks, no changes in auditory network global efficiency, and no associations between auditory metrics and cognitive performance. Effect-size estimates were small, and 95% confidence intervals placed conservative upper bounds that argue against sizeable, sustained auditory confounds. These findings were consistent across all contrast conditions.

CONCLUSION: Using data from a rigorously controlled cognitive trial, we found no evidence of long-term auditory network effects following TPS. This makes it unlikely that auditory confounds are a key factor underlying the cognitive network effects observed with long-term ultrasound neuromodulation in typical verum-sham settings as investigated here.

HIGHLIGHTS: Long-term transcranial pulse stimulation effects were evaluated for potential auditory confounds using functional magnetic resonance imaging (fMRI).Analyses included task-fMRI, resting-state functional connectivity, and auditory network efficiency.No auditory long-term effects were detected.Auditory confounds are unlikely to be the key factor for cognitive network effects.

PMID:41503119 | PMC:PMC12771597 | DOI:10.1002/trc2.70198

ArXiv [Preprint]. 2025 Dec 29:arXiv:2512.23137v1.

ABSTRACT

Integrating non-Euclidean brain imaging data with Euclidean tabular data, such as clinical and demographic information, poses a substantial challenge for medical imaging analysis, particularly in forecasting future outcomes. While machine learning and deep learning techniques have been applied successfully to cross-sectional classification and prediction tasks, effectively forecasting outcomes in longitudinal imaging studies remains challenging. To address this challenge, we introduce a time-aware graph neural network model with transformer fusion (GNN-TF). This model flexibly integrates both tabular data and dynamic brain connectivity data, leveraging the temporal order of these variables within a coherent framework. By incorporating non-Euclidean and Euclidean sources of information from a longitudinal resting-state fMRI dataset from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA), the GNN-TF enables a comprehensive analysis that captures critical aspects of longitudinal imaging data. Comparative analyses against a variety of established machine learning and deep learning models demonstrate that GNN-TF outperforms these state-of-the-art methods, delivering superior predictive accuracy for predicting future tobacco usage. The end-to-end, time-aware transformer fusion structure of the proposed GNN-TF model successfully integrates multiple data modalities and leverages temporal dynamics, making it a valuable analytic tool for functional brain imaging studies focused on clinical outcome prediction.

PMID:41503105 | PMC:PMC12772699

Alzheimers Dement. 2025 Dec;21 Suppl 2:e104872. doi: 10.1002/alz70856_104872.

ABSTRACT

BACKGROUND: Tau PET patterns show notable spatial heterogeneity across subjects in Alzheimer's disease (AD). In vitro findings suggest that tau may spread 'prion-like' across neuronal connections in an activity-dependent manner, a hypothesis strengthened by group-level studies showing association between resting-state functional connectivity (FC) networks and tau deposition patterns. This hypothesis would be better supported by evidence at the individual level, an investigation that is the focus of this study.

METHOD: Structural MRI, resting-state fMRI, tau-PET, and amyloid-β (Aβ)-PET data from 733 participants aged 50+ from the BioFINDER-2 study were used: 402 cognitively unimpaired (CU, CSF Aβ+=89), 157 with mild cognitive impairment (MCI), and 174 with AD dementia, with 523 follow-up tau-PET scans (323 CU, 109 MCI, 91 AD); individuals with MCI or AD dementia were all CSF Aβ+. fMRI data were pre-processed, and surface parcellated in subject-space. To reduce instability in subject-level estimations while retaining individual information, template FC (CU Aβ- group-average) and each participant's individual FC were used to build an individualised 'hybrid' FC; template and subject-specific regional FC profiles were integrated by statistically estimating the contribution of each in explaining the participant's tau-PET. FC-based results were compared against using canonical PET patterns estimated from the distribution of regional PET values across the cohort.

RESULT: Hybrid (i.e. individualized) FC explained tau-PET patterns better than template FC across the continuum (Fig-1A), which exceeded chance based on null modeling (Fig-1B). Baseline hybrid FC also explained follow-up tau-PET patterns better than template FC (Fig-1C). For individuals with MCI or AD dementia, hybrid FC alone explained tau better than enforcing canonical tau patterns on everyone (Fig-2), whereas canonical patterns better explained the data of individuals at early stages of the disease. However, in contrast to tau-PET patterns, individual Aβ-PET patterns-for which prion-like spread hypothesis was not assumed-were not better explained by hybrid FC than by Aβ-PET canonical patterns (Fig-3).

CONCLUSION: Our results provide compelling implicit evidence in support for the hypothesis of tau spread via communicating neurons at the individual-level. These findings strengthen the potential of using brain network-based models for sample stratification in AD clinical trials and prognosis in clinical practice.

PMID:41502344 | DOI:10.1002/alz70856_104872

BMC Med Imaging. 2026 Jan 7. doi: 10.1186/s12880-025-02145-7. Online ahead of print.

ABSTRACT

BACKGROUND: The loss of an only child represents a profound psychological trauma that is a significant risk factor for adverse mental health outcomes, including post-traumatic stress disorder (PTSD) and executive dysfunction. Research indicates that cerebral small vessel disease (CSVD) shares partial pathophysiological mechanisms with PTSD and may directly contribute to cognitive impairment through multiple pathways. Therefore, CSVD could serve as a pivotal entry point for understanding the neural mechanisms underlying executive dysfunction in parents who have lost their only child.

METHODS: We utilized resting-state fMRI in a cross-sectional design, comparing 39 individuals with executive dysfunction with 115 matched trauma-exposed controls without executive dysfunction. We quantified spontaneous neural activity via fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and ALFF, while CSVD burden was assessed. Moderation analysis was used to identify the moderating role of CSVD on executive dysfunction-related neural alterations in adults who lost their only child.

RESULTS: Individuals with executive dysfunction exhibited decreased fALFF in the left superior frontal gyrus (SFG) and reduced ReHo in the right medial SFG, alongside elevated ALFF and fALFF in the superior temporal gyrus (STG). fALFF in the left SFG demonstrated higher diagnostic accuracy for detecting executive dysfunction. Crucially, moderation analysis revealed that higher CSVD burden was associated with a greater reduction in fALFF in the left SFG, among individuals in the executive dysfunction group.

CONCLUSION: Executive dysfunction subjects demonstrated abnormal spontaneous activity in SFG and STG. The moderation analysis suggested that CSVD burden may be associated with a greater reduction in executive dysfunction-related frontal hypoactivity, supporting the construction of a "vascular-neuro-cognitive" triad model.

PMID:41501666 | DOI:10.1186/s12880-025-02145-7

Alzheimers Dement. 2025 Dec;21 Suppl 2:e105308. doi: 10.1002/alz70856_105308.

ABSTRACT

BACKGROUND: Hippocampal hyperexcitability is an early feature of Alzheimer's disease (AD) that may drive pathology. However, current models of AD risk focusing on the A/T/N framework (Aβ /Tau/Neurodegeneration) do not include hyperexcitability as a key disease biomarker. Here, we investigated a candidate hyperexcitability ("H") biomarker from resting-state fMRI (rsfMRI) - the amplitude of low-frequency fluctuations (ALFF), which reflects the intensity of spontaneous brain activity - to determine if it provides sensitive information about AD progression.

METHOD: We analyzed 386 older adults spanning the AD spectrum (277 cognitively normal, CN; 84 Aβ+ mild cognitive impairment, MCI; 25 Aβ+ AD dementia) from ADNI who underwent rsfMRI, Aβ-PET (18F-FBP/18F-FBB), and tau-PET (18F-FTP) within a year. ALFF was quantified from rsfMRI in the hippocampus as the primary "H" candidate, as well as the retrosplenial cortex, which served as a control region. Aβ-PET (18F-florbetapir or 18F-Florbetaben) global Centiloids (CL) and Aβ+ status (>20 CL), tau-PET (18F-Flortaucipr) in the medial temporal lobe (MTL) composite (entorhinal and amygdala mean SUVR), and hippocampal volume were used as A/T/N biomarkers, respectively. Relationships between ALFF, A/T/N biomarkers, and diagnosis were examined, controlling for age, sex, and education.

RESULT: Hippocampal and retrosplenial ALFF were elevated in individuals with MCI compared to CN individuals (Figure 1). Higher hippocampal ALFF significantly correlated with increased MTL tau in Aβ+ individuals, whereas there was no relationship with retrosplenial ALFF (Figure 2A-B). Further, among Aβ+ individuals, those with high hippocampal ALFF (A+H+) had greater MTL tau than those with high Aβ alone (A+H-), demonstrating hippocampal hyperexcitability in the context of Aβ is related to elevated tau pathology (Figure 2C). Finally, ROC analyses revealed that adding hippocampal ALFF to a basic A/T/N biomarker model improved diagnostic discrimination (Figure 3), suggesting hippocampal ALFF captures cognitive impairment beyond the A/T/N framework.

CONCLUSION: These findings indicate that hippocampal ALFF, a proxy of hippocampal hyperexcitability, serves as a valuable biomarker of AD. Planned analyses include assessing the sensitivity of hippocampal ALFF for longitudinal prediction of AD pathology and phenoconversion from CN to MCI or dementia. Future frameworks of AD should incorporate "H" biomarkers of hyperexcitability to further understand disease progression and risk.

PMID:41501404 | DOI:10.1002/alz70856_105308

Alzheimers Dement. 2025 Dec;21 Suppl 2:e105620. doi: 10.1002/alz70856_105620.

ABSTRACT

BACKGROUND: The nucleus basalis of Meynert (NBM) is crucial for learning, attention, and memory. While its involvement in Alzheimer's disease (AD) has been widely reported, the role in frontotemporal dementia (FTD) remains unclear. Here we examined NBM functional connectivity (FC) as well as NBM and cortical volume changes in AD, healthy controls (HC), and FTD subtypes: behavioral variant FTD (bvFTD), unclassified primary progressive aphasia (PPA), progressive nonfluent aphasia (PNFA), semantic dementia (SemD), and progressive logopenic aphasia (PLA).

METHOD: Resting-state fMRI and T1-weighted scans were collected from HC (n = 66), individuals with AD (n = 50), bvFTD (n = 63), PLA (n = 18), PPA (n = 20), PNFA (n = 32), and SemD (n = 15). We performed seed-based FC analyses in FSL with left and right NBM as seeds. We compared HC with AD (cluster-based threshold z > 2.3, p < 0.05). Significant clusters were used to extract mean FC for the other groups. We then compared FC values and normalized NBM volumes across HC and FTD subtypes using the Kruskal-Wallis test, followed by Bonferroni-corrected pairwise comparisons where applicable. Voxel-based morphometry (VBM) was conducted to explore cortical atrophy patterns.

RESULT: HC showed stronger NBM connectivity than AD in the hippocampus/parahippocampal gyrus, frontal pole, paracingulate cortex, precuneus, and lateral occipital cortex (Figure 1, left NBM results). Across HC and FTD subtypes, we found significant group differences for the paracingulate (H = 36.15, p < 0.001) and lateral occipital cortex (H = 18.25, p = 0.003). Connectivity was higher in bvFTD, PPA, and LPA than in HC, with the strongest effect for bvFTD in the paracingulate cortex (r = 0.48) and moderate effects across other contrasts (r = 0.28-0.42, all p < 0.020). Volumetric analyses indicated no significant group differences in NBM volumes but distinct cortical atrophy patterns: PNFA, PLA, and PPA exhibited temporal- frontal atrophy similar to AD, while bvFTD showed predominantly frontal and SemD primarily temporal atrophy.

CONCLUSION: Differential functional connectivity of the NBM and distinct cortical atrophy patterns were observed between HC and AD and between HC and FTD subtypes. Ongoing analyses on subgroup comparisons and integration of cognitive assessments aim to elucidate these relationships and their clinical implications.

PMID:41500961 | DOI:10.1002/alz70856_105620

Biol Psychiatry Cogn Neurosci Neuroimaging. 2026 Jan 5:S2451-9022(26)00001-7. doi: 10.1016/j.bpsc.2025.12.012. Online ahead of print.

ABSTRACT

BACKGROUND: Major depressive disorder (MDD) is a highly prevalent psychiatric disorder marked by disrupted brain dynamics. However, the neural mechanisms underlying remission remain poorly understood, particularly regarding common neural markers across diverse therapeutic interventions. Emerging evidence suggests that temporal brain dynamics and their hierarchical organization, referred to as Metastates, serve as sensitive markers of individual variability across cognitive functions. This study evaluated whether Metastate dynamics derived from resting-state functional magnetic resonance imaging (fMRI) differ according to remission status across pharmacotherapy, psychotherapy, and neuromodulation.

METHODS: This multicenter observational study included 370 participants: 229 individuals with depression and 141 healthy controls. The depression cohort comprised individuals undergoing cognitive behavioral therapy (n=92), pharmacotherapy (n=59), electroconvulsive therapy (n=50), and repetitive transcranial magnetic stimulation (n=28). Resting-state functional MRI data were analyzed to derive Metastate dynamics, and comparisons were made according to remission status across treatment modalities.

RESULTS: Two distinct Metastates were identified: one associated with higher-order cognitive brain regions, and another linked to sensory and motor systems. Participants who achieved remission exhibited greater predictability in transitions between brain states within Metastates, supporting higher-order cognitive functions. This altered transition pattern was accompanied by alterations in the anti-correlation between the default mode and executive function networks, which may underlie the increased predictability.

CONCLUSIONS: Remission from MDD may involve a reorganization of hierarchical brain dynamics-particularly in systems supporting cognitive control-and offer a potential treatment-modality-independent biomarker of remission.

PMID:41500385 | DOI:10.1016/j.bpsc.2025.12.012

Neurobiol Dis. 2026 Jan 5:107264. doi: 10.1016/j.nbd.2026.107264. Online ahead of print.

ABSTRACT

Left-sided temporal lobe epilepsy (LTLE) causes bihemispheric dysfunctions in large networks and poor cognitive performance. To address possible compensatory mechanism in the resting-state we investigated the functional alteration in LTLE patients with histologically proven sclerosis in the left hippocampal CA1-field compared to healthy controls. Eight drug resistant LTLE-patients and eight sex and age matched healthy controls were included in the study. The patients' hemispherical language and verbal memory function was determined by intracarotid amytal testing. Additional cognitive abilities and depression-like symptoms were collected using standard questionnaires. 7 T-fMRI of the resting-state and graph-theoretical whole-brain analysis including hippocampal subfields enabled sensitive detection of highly specific resting-state modulations without predefinition of regions of interest. Graph-theoretical network parameter were correlated with patients' cognitive performance and depression-like symptoms. Functional connectivity of the hippocampus of LTLE patients was reduced interhemispheric and to the cortex. However, the whole-brain functional connectivity was strengthened, indicating a compensating mechanism for the above mentioned reduced hippocampus connectivity. The network's small-world index did not differ between groups. Graph-theoretical node-parameter were lateralized to the left hemisphere, reflecting interhemispheric neuroplasticity. A network component mediated by the left globus pallidus, the right inferior temporal gyrus and the left anterior corona radiata reinforced the functional connectivity between the impaired hippocampus and the bilateral cortex. The graph-theoretical resilience of the globus pallidus was correlated with improved depression-like symptoms. Therefore, we hypothesize, that the observed compensatory circuit reflects an allostatic adaptation of the brain to balance energy and disease-induced environmental stress rather than to improve cognitive impairments.

PMID:41500267 | DOI:10.1016/j.nbd.2026.107264

Alzheimers Dement. 2025 Dec;21 Suppl 2:e104870. doi: 10.1002/alz70856_104870.

ABSTRACT

BACKGROUND: White matter hyperintensities (WMH) often co-exist with β-amyloid (Aβ) and tau tangles in Alzheimer's disease (AD). However, the association of WMH, Aβ plaques, and tau tangles in AD remains elusive. Using two large datasets, this study comprehensively examined the relationship between regional WMH and longitudinal tau accumulation in AD.

METHOD: A total of 951 participants from the ADNI and A4 cohorts with Aβ-PET, fluid-attenuated inversion recovery images (FLAIR), and tau-PET data were included, with Resting-state functional MRI (RS-fMRI) available for a subset of participants. FLAIR images were segmented using a U-Net deep learning model to obtain regional WMH volumes. Tau propagation along connectivity patterns was assessed using connectivity-associated tau spread metrics derived for the whole cortex and specific cortical regions (βGlobal, βFrontal, βParietal, βTemporal, and βOccipital). We examined the associations between regional WMH, tau accumulation, and connectivity-associated tau spread. Additionally, two cortical tau subtypes were identified: "Occipital > Parietal" and "Parietal > Occipital", characterized by higher or lower occipital tau relative to parietal tau, and the impact of regional WMH on tau accumulation was assessed within these subtypes.

RESULT: Aβ+ individuals showed higher baseline levels and faster increases in total WMH compared to Aβ- individuals, but no differences were observed between T+ and T- individuals. Among Aβ+ individuals, temporal meta-ROI tau was not associated with faster WMH increases. However, greater total WMH was linked to accelerated temporal meta-ROI tau accumulation (Figure 1), although this relationship did not persist after controlling for Aβ. Greater occipital WMH was associated with faster tau accumulation in occipital regions, particularly the cuneus, and with increasing βOccipital, independent of Aβ (Figure 2). The "Parietal > Occipital" subtype exhibited more rapid tau progression than the "Occipital > Parietal" subtype. In contrast, higher WMH was linked to faster tau increases in the cuneus exclusively within the latter subtype (Figure 3).

CONCLUSION: Greater WMH burden, particularly in the occipital lobe, is associated with faster tau accumulation and spread in posterior cortical regions, independent of Aβ. These findings provide novel insights into understanding how vascular damages reflected by WMH contribute to cortical tau aggregation in the posterior cortical region of AD.

PMID:41499810 | DOI:10.1002/alz70856_104870

Alzheimers Dement. 2025 Dec;21 Suppl 2:e105952. doi: 10.1002/alz70856_105952.

ABSTRACT

BACKGROUND: Pathological tau spreads trans-synaptically in an activity-dependent manner. Previous findings support that tau spread can be measured in vivo in regions functionally connected to the entorhinal cortex (ERC). We hypothesized that the functional connectivity (FC) strength of the basal forebrain (BF), another site of early tau deposition, would also predict patterns of tau spread.

METHOD: We quantified flortaucipir tau-PET scans from unimpaired older adults in ADNI (n = 351) and the Berkeley Aging Cohort Study (BACS; n = 99). For ERC and BF regions of interest, seed-to-voxel functional connectivity (FC) networks were generated using resting-state fMRI in a partially overlapping BACS sample (n = 120) (Table 1). Outside-network ROIs were created by subtracting the target FC network from a gray-matter mask. Tau-PET SUVR and the proportion of suprathreshold voxels (>1.4 SUVR) in FC network and outside-network ROIs were compared with paired t-tests. Voxel-wise multiple regression analyses were used to measure the correlation between tau-PET in the ERC or BF and the cortex. We used these maps to explore their relationship with seed-to-voxel FC strength.

RESULT: FC of the ERC included the medial temporal, lateral temporal, and limbic regions, while FC of the BF included the insula, dorsal anterior cingulate, and limbic regions (Figure 1). Tau-PET uptake was significantly greater in both the ERC and BF FC network compared to outside the network, using both SUVRs and proportion of suprathreshold voxels as tau measures. When comparing FC networks to the outside-network ROIs, effects were greater for the ERC seed compared to BF (proportion of suprathreshold voxels: ERC d=0.85; BF d=0.49). In voxels across the cortex, the strength of FC to the ERC or BF was significantly correlated with the strength of cortical tau association to the ERC or BF (Figure 2).

CONCLUSION: Significantly greater tau-PET signal in the ERC and BF FC networks suggests that FC patterns of early tau accumulating regions predict pathological tau deposition across the cortex. The ERC seed provided stronger evidence for FC-mediated tau spread compared to BF. Future research will investigate whether amyloid and APOE4 carrier status moderate the relationship between FC and tau spread from these early tau regions.

PMID:41499672 | DOI:10.1002/alz70856_105952

Alzheimers Dement. 2025 Dec;21 Suppl 2:e104805. doi: 10.1002/alz70856_104805.

ABSTRACT

BACKGROUND: Amyloid-β (Aβ) and neurofibrillary tau deposition are two hallmark pathological proteins of Alzheimer's disease (AD) that accumulate through brain networks and drive cognitive decline. This study investigates whether the functional network abnormalities influence the Aβ-tau interactions and cognitive impairment in AD, which may provide more insightful perspectives in understanding the neural mechanisms and pathogenesis of AD.

METHOD: We divided the 190 participants from Shanghai Renji Hospital (68.6 ± 8.4 years, 62% female) into three groups, A-/T- (control group, N = 48), A+/T- (N = 121), and A+/T+ (N = 21), based on established global 18F-AV-45 amyloid PET thresholds and 18F-PI-2620 PET (tau PET) thresholds. All subjects underwent 18F-AV-45 PET, 18F-PI-2620 PET, resting state functional magnetic resonance imaging (fMRI) and T1-weighted MRI scans. Functional activity and functional network connectivity were determined using regional homogeneity (ReHo) and functional connectivity (FC) respectively.

RESULT: Participant demographics and summary descriptive statistics of the cognitive assessments and the PET data analyses are provide Table 1. The health control group (A-/T-, n = 48): The average age is 69.9 ± 8.3 years, with 62.5% being female. The mean education level is 10.1 ± 4.0 years. A+/T- Group (n = 121): The average age is 68.2 ± 8.9 years, with 60.0% being female. The mean education level is 10.4 ± 3.9 years. A+/T+ group(n = 21): The average age is 68.3 ± 5.0 years, with 71.4% being female. No significant difference was found for age and years of education across health control group and AD groups. We compared the brain's functional activity among A-/T- group, A+/T- group, and A+/T+ group, and we found that functional activity in some brain regions, such as bilateral cerebellum, right insula cortex, right precentral gyrus, right middle frontal gyrus, differed significantly among these forementioned three groups CONCLUSION: This study found significant differences in functional activity in brain regions such as the cerebellum, insula cortex, precentral gyrus, and middle frontal gyrus among control, A+/T-, and A+/T+ AD groups. These results suggest functional network abnormalities may influence Aβ-tau interactions and contribute to cognitive impairment in AD, shedding light on the neural mechanisms of the disease.

PMID:41499380 | DOI:10.1002/alz70856_104805