Most recent paper

J Prev Alzheimers Dis. 2025 Feb;12(2):100030. doi: 10.1016/j.tjpad.2024.100030. Epub 2025 Jan 1.

ABSTRACT

BACKGROUND: Imaging studies showed early atrophy of the cholinergic basal forebrain in prodromal sporadic Alzheimer's disease and reduced posterior basal forebrain functional connectivity in amyloid positive individuals with subjective cognitive decline. Similar investigations in familial cases of Alzheimer's disease are still lacking.

OBJECTIVES: To test whether presenilin-1 E280A mutation carriers have reduced basal forebrain functional connectivity and whether this is linked to amyloid pathology.

DESIGN: This is a cross-sectional study that analyzes baseline functional imaging data.

SETTING: We obtained data from the Colombia cohort Alzheimer's Prevention Initiative Autosomal-Dominant Alzheimer's Disease Trial.

PARTICIPANTS: We analyzed data from 215 asymptomatic subjects carrying the presenilin-1 E280A mutation [64% female; 147 carriers (M = 35 years), 68 noncarriers (M = 40 years)].

MEASUREMENTS: We extracted functional magnetic resonance imaging data using seed-based connectivity analysis to examine the anterior and posterior subdivisions of the basal forebrain. Subsequently, we performed a Bayesian Analysis of Covariance to assess the impact of carrier status on functional connectivity in relation to amyloid positivity. For comparison, we also investigated hippocampus connectivity.

RESULTS: We found no effect of carrier status on anterior (Bayesian Factor10 = 1.167) and posterior basal forebrain connectivity (Bayesian Factor10 = 0.033). In carriers, we found no association of amyloid positivity with basal forebrain connectivity.

CONCLUSIONS: We falsified the hypothesis of basal forebrain connectivity reduction in preclinical mutation carriers with amyloid pathology. If replicated, these findings may not only confirm a discrepancy between familial and sporadic Alzheimer's disease, but also suggest new potential targets for future treatments.

PMID:39863323 | DOI:10.1016/j.tjpad.2024.100030

J Affect Disord. 2025 Jan 23:S0165-0327(25)00136-3. doi: 10.1016/j.jad.2025.01.116. Online ahead of print.

ABSTRACT

BACKGROUND: The potential pairwise connections among high-sensitivity C-reactive protein (hs-CRP), striatum-based circuits, and anhedonia in adolescent depression are not clear. This study aimed to explore whether hs-CRP levels in adolescents with depression influence anhedonia via alterations of striatum-based functional connectivity (FC).

METHODS: A total of 201 adolescents (92 with depressive episodes with anhedonia (anDE), 58 with DE without anhedonia (non-anDE), and 51 healthy controls (HCs)) underwent resting-state functional magnetic resonance imaging (fMRI) and completed the anhedonia subscale of the Children's Depression Inventory (CDI). hs-CRP levels were measured from peripheral blood samples in all DE patients.

RESULTS: Compared with HCs, the anDE and non-anDE groups showed increased FC between the left dorsal caudate putamen (DCP_L) and bilateral Cerebellum Crus I, and decreased FC between the left ventral rostral putamen (VRP_L) and right parahippocampal cortex (PHC) (all p < 0.05). Only the non-anDE group exhibited increased FC between the right visual cortex (VC_R) and left cerebellum VI, VC_R, and right fusiform gyrus (FG), and the left visual cortex (VC_L) and right inferior temporal gyrus (ITG) compared to HCs (all p < 0.05). Compared to the non-anDE group, the anDE group showed reduced FC between the VC_R and left cerebellum VI and between the DCP_L and right superior frontal gyrus (SFG) (all p < 0.05). Multiple regression analysis revealed that DCP_L and right SFG FC negatively predicted anhedonia severity (β = -0.288, p = 0.007). Although hs-CRP levels had no direct effect, FC between the DCP_L and right SFG fully mediated the relationship between hs-CRP and anhedonia in the anDE group (effect = 0.184, Bootstrapping 95 % CI = 0.0156, 0.436).

CONCLUSION: The findings suggest that hs-CRP influences anhedonia through a fully mediated pathway involving alterations in the frontostriatal network, contributing to a greater understanding of the neurobiological mechanisms underlying anhedonia.

PMID:39862985 | DOI:10.1016/j.jad.2025.01.116

J Integr Neurosci. 2025 Jan 20;24(1):26280. doi: 10.31083/JIN26280.

ABSTRACT

BACKGROUND: The significance of tactile stimulation in human social development and personal interaction is well documented; however, the underlying cerebral processes remain under-researched. This study employed functional magnetic resonance imaging (fMRI) to investigate the neural correlates of social touch processing, with a particular focus on the functional connectivity associated with the aftereffects of touch.

METHODS: A total of 27 experimental subjects were recruited for the study, all of whom underwent a 5-minute calf and foot massage prior to undergoing resting-state fMRI. Additionally, 11 healthy controls participated solely in the resting-state fMRI recording. A functional connectivity network analysis was conducted to examine the alterations in connections between different brain regions following massage.

RESULTS: The findings indicated the involvement of discrete neural networks in the processing of social touch, with notable discrepancies in functional connectivity observed between the experimental and control groups. The study revealed that the control group exhibited a higher degree of connectivity within a subnetwork comprising 25 connections and 23 nodes than the experimental group following the massage intervention. The experimental group showed hypoactivation in this subnetwork following the massage. The left anterior pulvinar thalamus and the right pregenual anterior cingulate cortex, which serve as the key hubs within this subnetwork, exhibited higher clustering and increased node strength in the control group. Relatively small and unequal sample sizes are the limitations of the study that may affect the generalizability of the results.

CONCLUSIONS: These findings elucidate the neural underpinnings of tactile experiences and their potential impact on behavior and emotional state. Gaining insight into these mechanisms could inform therapeutic approaches that utilize touch to mitigate stress and enhance mental health. From a practical standpoint, our results have significant implications for the development of sensory stimulation strategies for patients with prolonged disorders of consciousness, sensory loss, autism spectrum disorders, or limited access to tactile interaction in their upper extremities.

PMID:39862011 | DOI:10.31083/JIN26280

J Integr Neurosci. 2025 Jan 7;24(1):25041. doi: 10.31083/JIN25041.

ABSTRACT

Resting state networks (RSNs) of the brain are characterized as correlated spontaneous time-varying fluctuations in the absence of goal-directed tasks. These networks can be local or large-scale spanning the brain. The study of the spatiotemporal properties of such networks has helped understand the brain's fundamental functional organization under healthy and diseased states. As we age, these spatiotemporal properties change. Moreover, RSNs exhibit neural plasticity to compensate for the loss of cognitive functions. This narrative review aims to summarize current knowledge from functional magnetic resonance imaging (fMRI) studies on age-related alterations in RSNs. Underlying mechanisms influencing such changes are discussed. Methodological challenges and future directions are also addressed. By providing an overview of the current state of knowledge in this field, this review aims to guide future research endeavors aimed at promoting healthy brain aging and developing effective interventions for age-related cognitive impairment and neurodegenerative diseases.

PMID:39862002 | DOI:10.31083/JIN25041

Cortex. 2025 Jan 13;184:120-130. doi: 10.1016/j.cortex.2024.12.022. Online ahead of print.

ABSTRACT

The developing brain undergoes rapid changes throughout middle childhood and adolescence. The disambiguation of long-term changes in intrinsic activity following pediatric mild traumatic brain injury (pmTBI) from typical development can therefore only be ascertained in longitudinal studies with large sample size and at least three serial assessments. A comprehensive clinical battery and resting-state fMRI data were collected approximately 1-week (N = 263; 8-18 years old), 4-months (N = 192) and 1-year (N = 153) post-injury, with identical visits in a large cohort (N = 228) of age- and sex-matched healthy controls (HC). Results indicated persistent frontocerebellar and thalamic connectivity changes up to 1-year post-injury in pmTBI relative to controls (P's < .001), with similar longitudinal connectivity trajectories (i.e., typical neurodevelopment). Alterations in precuneal midline connectivity (p's < .05) and occupancy of a default mode/limbic dynamic brain state were present only up to 4-months (p's < .001) rather than 1-year (p's > .44) post-injury. However, absent group differences at 1-year post-injury may be explained as pseudo-normalization due to altered longitudinal connectivity trajectories in pmTBI associated with neurodevelopment. Persistent alterations of precuneal connectivity were also associated with lower executive function and long-term memory scores. In conclusion, pmTBI may result in chronic changes to both static and dynamic intrinsic connectivity which further interact with typical neurodevelopment. Longer follow-up studies may be needed to unravel this interaction.

PMID:39855053 | DOI:10.1016/j.cortex.2024.12.022

Brain Sci. 2024 Dec 25;15(1):7. doi: 10.3390/brainsci15010007.

ABSTRACT

BACKGROUND: Prolonged confinement in enclosed environments has raised concerns about its effects on both physical and mental health. Although increased rates of depression or anxiety during COVID-19 lockdowns have been reported, the effects of short-term restrictions on social activities and physical on brain function and structure remain poorly known.

METHODS: This study explored longitudinal changes in brain gray matter volume (GMV) and functional connectivity (FC) immediately after and four months following a short-term lockdown in comparison to pre-lockdown conditions. MRI data were collected from 20 participants before the lockdown, from 29 participants (14 original, 15 new) two months post-lockdown, and from 27 out of the 29 participants four months post-lifting of the lockdown.

RESULTS: Results showed significant GMV reductions in the right gyrus rectus and cuneus post-lockdown, with further reductions observed four months after lifting the restrictions, affecting additional brain regions. Longitudinal FC trajectories revealed decreased connectivity between the default mode network (DMN) and sensorimotor/attention networks post-lockdown, and recovery after four months post-lifting of the lockdown.

CONCLUSIONS: The observed plasticity in brain FC indicates substantial recovery potential with the potential long-term effect of structural changes. Our findings offer insights into the effects of isolation on the human brain, potentially informing rehabilitation mechanisms and interventions for individuals in similar conditions.

PMID:39851375 | DOI:10.3390/brainsci15010007

J Psychiatry Neurosci. 2025 Jan 23;50(1):E57-E66. doi: 10.1503/jpn.240093. Print 2025 Jan-Feb.

ABSTRACT

BACKGROUND: Schizophrenia is hypothesized to involve a disturbance in the temporal dynamics of self-processing, specifically within the interoceptive, exteroceptive, and cognitive layers of the self. This study aimed to investigate the intrinsic neural timescales (INTs) within these self-processing layers among people with schizophrenia.

METHODS: We conducted a functional magnetic resonance imaging (fMRI) study to investigate INTs, as measured by the autocorrelation window, among people with schizophrenia and healthy controls during both resting-state and task (memory encoding and retrieval) conditions. We obtained data from the UCLA Consortium for Neuropsychiatric Phenomics data set and preprocessed using fMRIPrep.

RESULTS: We included 45 people with schizophrenia and 65 healthy controls. Compared with controls, participants with schizophrenia exhibited significantly shorter INTs across all 3 self-processing layers during rest (p < 0.05). In addition, those with schizophrenia showed less INT shortening during task states, leading to reduced rest-task differences in INT across all self-processing layers (p < 0.05). We observed similar patterns of shortened INTs in primary sensory and motor regions.

LIMITATIONS: We included people with schizophrenia taking medication, which may influence INTs; our study was also limited by the relatively slow temporal resolution of the fMRI data and the higher variability of the autocorrelation function in the schizophrenia group, compared with the control group.

CONCLUSION: Our findings suggest that schizophrenia is characterized by a global temporal disturbance of the self, manifesting as shorter and inflexible INTs across self-processing and sensorimotor regions. These results support the hypothesis that schizophrenia involves a fundamental disruption in the temporal integration of neural signals, contributing to the core self-disturbance observed in the disorder.

PMID:39848684 | DOI:10.1503/jpn.240093

Hum Brain Mapp. 2025 Feb 1;46(2):e26806. doi: 10.1002/hbm.26806.

ABSTRACT

Irregular and unpredictable fetal movement is the most common cause of artifacts in in utero functional magnetic resonance imaging (fMRI), affecting analysis and limiting our understanding of early functional brain development. The accurate detection of corrupted functional connectivity (FC) resulting from motion artifacts or preprocessing, instead of neural activity, is a prerequisite for reliable and valid analysis of FC and early brain development. Approaches to address this problem in adult data are of limited utility in fetal fMRI. In this study, we evaluate a novel technique for robust computational assessment of motion artifacts, and the quantitative comparison of regression models for artifact removal in fetal FC analysis. It exploits the association between dynamic FC and non-stationarity of fetal movement, to detect residual noise. To validate our motion artifact detection technique in detail, we used a parametric generative model for neural events and fMRI blood oxygenation level-dependent (BOLD) signal. We conducted a systematic evaluation of 11 commonly used regression models in a sample of 70 fetuses with gestational age of 19-39 weeks. Results demonstrate that the proposed method has better accuracy in identifying corrupted FC compared to methods designed for adults. The technique, suggests that censoring, global signal regression and anatomical component-based regression models are the most effective models for compensating motion. The benchmarking technique, and the generative model for realistic fetal fMRI BOLD enables investigators conducting in utero fMRI analysis to effectively quantify the impact of fetal motion and evaluate alternative regression strategies for mitigating this impact. The code is publicly available at: https://github.com/cirmuw/fetalfMRIproc.

PMID:39846325 | DOI:10.1002/hbm.26806

Front Neurol. 2025 Jan 7;15:1503737. doi: 10.3389/fneur.2024.1503737. eCollection 2024.

ABSTRACT

OBJECTIVE: This study aims to observe the effect of enrichment rehabilitation (ER) on cognitive function in post-stroke patients and to clarify its underlying mechanism.

METHODS: Forty patients with post-stroke cognitive impairment (PSCI) meeting the inclusion criteria were randomly assigned to two groups: conventional medical rehabilitation (CM group) and ER intervention (ER group). All patients underwent assessments of overall cognitive function, attention function, and executive function within 24 h before the start of training and within 24 h after the 8 weeks of training. We investigated the altered resting-state functional connectivity (RSFC) with the right dorsolateral prefrontal cortex (DLPFC) in patients with PSCI following ER training through functional magnetic resonance imaging (fMRI). Additionally, twenty people undergoing routine physical examinations in the outpatient department of our hospital were selected as the healthy control (HC) group.

RESULTS: Before training, both groups of PSCI patients exhibited significant impairment in overall cognitive function, attention function, and executive function compared to the HC group. However, there was no significant difference between the two PSCI patient groups. Following 8 weeks of treatment, both PSCI patient groups demonstrated substantial improvement in overall cognitive function, attention function, and executive function. Moreover, the ER group exhibited greater improvement after training compared to the CM group. Despite the improvements, the cognitive behavioral performance assessment scores of both PSCI patient groups remained lower than those of the HC group. RSFC analysis in the ER group revealed strengthened positive functional connectivity between the right DLPFC and the left superior frontal gyrus (SFG) and left anterior cingulate gyrus (ACG), along with decreased functional connectivity between the right DLPFC and the right superior temporal gyrus (STG) and right precentral gyrus post-ER intervention.

CONCLUSION: ER intervention is more effective than conventional medical rehabilitation in improving the cognitive function of PSCI patients, potentially by augmenting the FC between the right DLPFC and dominant cognitive brain regions, such as the left SFG and left ACG while attenuating the FC between the right DLPFC and non-dominant hemisphere areas including the STG and precentral gyrus within the right hemisphere.

PMID:39845930 | PMC:PMC11752906 | DOI:10.3389/fneur.2024.1503737

Front Hum Neurosci. 2025 Jan 8;18:1427532. doi: 10.3389/fnhum.2024.1427532. eCollection 2024.

ABSTRACT

Spontaneous blood oxygen level-dependent signals can be indirectly recorded in different brain regions with functional magnetic resonance imaging. In this study resting-state functional magnetic resonance imaging was used to measure the differences in connectivity and activation seen in major depressive disorder (MDD) patients with and without suicidal ideation and the control group. For our investigation, a brain atlas containing 116 regions of interest was used. We also used four voxel-based connectivity models, including degree centrality, the fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity, and voxel-mirrored Homotopic Connectivity. Feature selection was conducted using a sequential backward floating selection approach along with a Random Forest Classifier and Elastic Net. While all four models yield significant results, fALFF demonstrated higher accuracy rates in classifying the three groups. Further analysis revealed three features that demonstrated statistically significant differences between these three, resulting in a 90.00% accuracy rate. Prominent features identified from our analysis, with suicide ideation as the key variable, included the Superior frontal gyrus (dorsolateral and orbital parts), the median cingulate, and the paracingulate gyri. These areas are associated with the Central Executive Control Network (ECN), the Default Mode Network, and the ECN, respectively. Comparing the results of MDD patients with suicidal ideation to those without suicidal ideations suggests dysfunctions in decision-making ability, in MDD females suffering from suicidal tendencies. This may be related to a lack of inhibition or emotion regulation capability, which contributes to suicidal ideations.

PMID:39845411 | PMC:PMC11751011 | DOI:10.3389/fnhum.2024.1427532

J Neurosci. 2025 Jan 22:e1699242024. doi: 10.1523/JNEUROSCI.1699-24.2024. Online ahead of print.

ABSTRACT

The brain's activity fluctuations have different temporal scales across the brain regions, with associative regions displaying slower timescales than sensory areas. This so-called hierarchy of timescales has been shown to correlate with both structural brain connectivity and intrinsic regional properties. Here, using publicly available human resting-state fMRI and dMRI data it was found that, while more structurally connected brain regions presented activity fluctuations with longer timescales, their activity fluctuations presented lower variance. The opposite relationships between the structural connectivity and the variance and temporal scales of resting-state fluctuations, respectively, were not trivially explained by simple network propagation principles. To understand these structure-function relationships, two commonly used whole-brain models were studied, namely the Hopf and Wilson-Cowan models. These models use the brain's connectome to coupled local nodes (representing brain regions) displaying noise-driven oscillations. The models show that the variance and temporal scales of activity fluctuations can oppositely relate to connectivity within specific model's parameter regions, even when all nodes have the same intrinsic dynamics -but also when intrinsic dynamics are constrained by the myelinization-related macroscopic gradient. These results show that, setting aside intrinsic regional differences, connectivity and network state are sufficient to explain the regional differences in fluctuations' scales. State-dependence supports the vision that structure-function relationships can serve as biomarkers of altered brain states. Finally, the results indicate that the hierarchies of timescales and variances reflect a balance between stability and responsivity, with greater and faster responsiveness at the network periphery, while the network core ensures overall system robustness.Significance Statement Brain regions exhibit activity fluctuations at different temporal scales, with associative areas displaying slower timescales than sensory areas. This hierarchical organization is shaped by both large-scale connectivity and local properties. The present study demonstrates that the variance of fluctuations is also hierarchically organized but, in contrast to timescales, it decreases as a function of structural connectivity. Whole-brain models show that the hierarchies of timescales and variances jointly emerge within specific parameter regions, indicating a state-dependence that could serve as a biomarker for brain states and disorders. Furthermore, these hierarchies link to the responsivity of different network parts, with greater and faster responsiveness at the network periphery and more stable dynamics at the core, achieving a balance between stability and responsiveness.

PMID:39843234 | DOI:10.1523/JNEUROSCI.1699-24.2024

J Affect Disord. 2025 Jan 20:S0165-0327(25)00111-9. doi: 10.1016/j.jad.2025.01.094. Online ahead of print.

ABSTRACT

Childhood maltreatment represents a strong psychological stressor that may lead to the development of later psychopathology as well as a heightened risk of health and social problems. Despite a surge of interest in examining behavioral, neurocognitive, and brain connectivity profiles sculpted by such early adversity over the past decades, little is known about the neurobiological substrates underpinning childhood maltreatment. Here, we aim to detect the effects of childhood maltreatment on whole-brain resting-state functional connectivity (RSFC) in a cohort of healthy adults and to explore whether such RSFC profiles can be used to predict the severity of childhood trauma in subjects based on a data-driven connectome-based predictive modeling (CPM). Resting-state functional MRI (rs-fMRI) data were acquired from 97 healthy adults, each of whom was assessed for childhood maltreatment levels using the Childhood Trauma Questionnaire-Short Form (CTQ-SF). CPM was used to examine the association between whole-brain RSFC and childhood maltreatment levels. The results showed that CPM was able to decode individual childhood maltreatment levels from RSFC across multiple neural systems including RSFC between and within limbic and prefrontal systems as well as their connectivity with other networks. Key nodes contributing to the prediction model included the amygdala, prefrontal, and anterior cingulate regions that have been linked to childhood maltreatment. These results remained robust using different validation procedures. Our findings revealed that RSFC among multiple neural systems can be used to predict childhood maltreatment levels in individuals.

PMID:39842674 | DOI:10.1016/j.jad.2025.01.094

Nat Sci Sleep. 2025 Jan 15;17:97-113. doi: 10.2147/NSS.S488911. eCollection 2025.

ABSTRACT

BACKGROUND: COVID-19 has led to reports of fatigue and sleep problems. Brain function changes underlying sleep problems (SP) post-COVID-19 are unclear.

PURPOSE: This study investigated SP-related brain functional connectivity (FC) alterations.

PATIENTS AND METHODS: Fifty-five COVID-19 survivors with SP (COVID_SP) and 33 without SP (COVID_NSP), matched for demographics, completed PSQI and underwent rs-fMRI at baseline and 2-month follow-up. Correlations between FC and clinical data were analyzed by Pearson correlation analysis with Gaussian random field (GRF) correction. The repeated-measures analysis of variance (R-M ANOVA) was completed to explore the interaction with time.

RESULTS: At baseline, COVID_SP exhibited elevated FC: right precentral gyrus (PrG) with left lateral occipital cortex (LOcC)/right PrG, left inferior parietal lobule (IPL) with right superior frontal gyrus (SFG), left hippocampus with right inferior frontal gyrus (IFG). Higher FC between left hippocampus and right SFG correlated with PSQI scores. At 2-month follow-up, decreased FC implicated in emotion regulation, executive function, and memory; increased FC in semantics, attention, and auditory-visual processing. The changes in these regions are correlated with the scores of PSQI, GAD, and PHQ. The Repeated-Measures Analysis of Variance (R-M ANOVA) revealed a significant time interaction effect between sleep and various emotion scales. Moreover, the analysis of the functional connectivity between the right PrG and the right PrG as well as that between the left IPL and the right SFG also discovered a significant time interaction effect.

CONCLUSION: This study provides insight into the changes in brain function associated with SP after COVID-19. These changes may partially explain the development of SP, and they also changed over time.

PMID:39839964 | PMC:PMC11748004 | DOI:10.2147/NSS.S488911

Quant Imaging Med Surg. 2025 Jan 2;15(1):608-622. doi: 10.21037/qims-24-1227. Epub 2024 Dec 19.

ABSTRACT

BACKGROUND: There are currently no deep learning models applying resting-state functional magnetic resonance imaging (rs-fMRI) data to distinguish patients with Parkinson's disease (PD) and healthy controls (HCs). Moreover, no study has correlated objective gait parameters with brain network alterations in patients with PD. We propose BrainNetCNN + CL, applying a convolutional neural network (CNN) and joint contrastive learning (CL) method to brain network analysis to classify patients with PD and HCs, and compare their performance with classical classification methods. This study aimed to explore more accurate abnormal connecting regions that may serve as potential therapeutic targets, and to explore the correlation between abnormal connecting regions and gait parameters.

METHODS: We enrolled 29 patients with PD and 38 HCs. Rs-fMRI data and high-resolution three-dimensional structural T1-weighted images were acquired for each participant. BrainNetCNN + CL were utilized to classify the PD and HC groups.

RESULTS: The top 20 connections with the highest contribution to the classification results obtained using BrainNetCNN + CL included the default mode network (DMN), ventral attention network (VAN), and limbic network (LN). The strength of the functional connectivity (FC) between the right inferior occipital gyrus and left postcentral gyrus in the PD group was negatively correlated with the step length at the self-selected pace (SSP) speed in the "ON" state (P=0.001, r=-0.589). The strength of the FC between the right fusiform gyrus and the right calcarine fissure and surrounding cortex was negatively correlated with the Beck Anxiety Inventory (BAI) score (P=0.032, r=-0.406) and positively correlated with the Berg Balance Scale (BBS) score measured in the "ON" state (P=0.037, r=0.395).

CONCLUSIONS: BrainNetCNN + CL accurately identified abnormally connected regions associated with gait impairments, which may serve as potential therapeutic targets for PD.

PMID:39839056 | PMC:PMC11744164 | DOI:10.21037/qims-24-1227

Quant Imaging Med Surg. 2025 Jan 2;15(1):217-229. doi: 10.21037/qims-24-1265. Epub 2024 Dec 9.

ABSTRACT

BACKGROUND: Cognitive decline may occur in patients with end-stage renal disease (ESRD), and is particularly severe in patients with ESRD undergoing hemodialysis; however, the mechanism of this relationship between cognitive decline and ESRD is unclear. Cortical-based structural and functional analysis can be used to understand these cortical changes and their relationship with cognitive decline in non-dialysis and maintenance dialysis ESRD patients. This study aimed to examine whether there was any correlation between alterations in cortical and resting-state function changes and cognitive decline in patients diagnosed with ESRD.

METHODS: The study included a total of 126 participants who underwent laboratory assessments, neuropsychological tests, and brain magnetic resonance imaging (MRI). Of the 126 patients, 40 were ESRD without hemodialysis (ESRD-ND) patients, 40 were ESRD with hemodialysis (ESRD-HD) patients, and 46 were healthy controls (HCs).

RESULTS: In terms of the cortical changes, the thickness and volume of the left medial temporal cortex were smaller in the ESRD-ND group than in the HC group. The thickness and volume of the double medial temporal cortex were reduced in the ESRD-HD group compared to the ESRD-ND group. The cortical volume in the anterior cingulate and medial prefrontal cortex (AntCing_MedPFC) was reduced in ESRD-HD group compared to both the ESRD-ND and HC groups. In terms of the functional changes, the regional homogeneity (ReHo) of the double medial temporal cortex was higher in the ESRD-HD group than in the ESRD-ND group, and higher in the ESRD-ND group than in the HC group. The ReHo of the AntCing_MedPFC was higher in both the ESRD-HD and ESRD-ND groups than in the HC group. The correlation analysis after covariation-correction showed that the cortical thickness (r=0.360, P=0.026) and cortical volume (r=0.440, P=0.006) of the medial temporal lobe in the ESRD-HD group were positively correlated with the Montreal Cognitive Assessment (MoCA) score. The cortical thickness (r=0.571, P<0.001) and cortical volume (r=0.529, P=0.001) of the posterior cingulated gyrus were positively correlated with the MoCA score in the ESRD-ND group.

CONCLUSIONS: Our findings suggest that ESRD patients undergo more cognitively related cortical structural and functional changes than HCs. Dialysis can aggravate or cause changes in new brain regions. Changes in the cortex and volume of the posterior cingulate gyrus in ESRD patients is an important cause of cognitive decline. Damage to the medial temporal lobe by dialysis exacerbates this trend.

PMID:39839046 | PMC:PMC11744114 | DOI:10.21037/qims-24-1265

Quant Imaging Med Surg. 2025 Jan 2;15(1):352-369. doi: 10.21037/qims-24-1196. Epub 2024 Dec 27.

ABSTRACT

BACKGROUND: Rapid eye movement sleep behavior disorder (RBD) is associated with pathological α-synuclein deposition and may have different damage directions due to α-synuclein spreading orientations. Recent functional imaging studies of Parkinson's disease (PD) with RBD have identified abnormalities in connectivity, but effective connectivity (EC) for this altered orientation is understudied. Here, we aimed to explore altered intrinsic functional connectivity (FC) and EC in PD patients with probable RBD (pRBD).

METHODS: This was a cross-sectional study. A total of 31 PD patients with pRBD (PD-pRBD), 35 PD without pRBD (PD-npRBD), and 32 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (RS-fMRI) scans. The voxel-wise degree centrality (DC) calculation was first performed to investigate the inherent connectivity of the PD-pRBD patients. Subsequently, we applied Granger causality analysis (GCA) to probe the causal effects of anomalous brain regions. Finally, the support vector machine (SVM) method was executed to evaluate the DC values in identifying PD-pRBD.

RESULTS: PD-pRBD patients exhibited reduced z-DC values in the right precentral gyrus relative to PD-npRBD (voxel-level P<0.001, cluster-level P<0.05), as well as decreased z-DC values in the right postcentral gyrus and the superior parietal lobule compared to HCs. Then, our GCA revealed that decreased EC was located predominantly from the right precentral gyrus to the right caudate nucleus in the PD-pRBD group. Additionally, the SVM results revealed that the z-DC values of the right precentral gyrus could discriminate PD-pRBD from the PD-npRBD group [area under the curve (AUC) =0.905].

CONCLUSIONS: The altered z-DC in the right precentral gyrus and the anomaly causal effects from the precentral motor cortex to the ipsilateral striatum represented by the caudate nucleus might play vital roles in the pathogenesis of PD-pRBD. It was speculated that the attenuation of FC from the precentral motor cortex to the subcortical striatum might be associated with nocturnal muscle dyskinesia and behavioral abnormalities in PD-pRBD patients. This disruption pattern may be a prospective imaging marker in the characterization of PD with pRBD.

PMID:39839023 | PMC:PMC11744126 | DOI:10.21037/qims-24-1196

Quant Imaging Med Surg. 2025 Jan 2;15(1):563-580. doi: 10.21037/qims-24-1342. Epub 2024 Dec 11.

ABSTRACT

BACKGROUND: Approximately half of human immunodeficiency virus (HIV) patients experience HIV-associated neurocognitive disorders (HAND); however, the neurophysiological mechanisms underlying HAND remain unclear. This study aimed to evaluate changes in functional brain activity patterns during the early stages of HIV infection by comparing local and global indicators using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS: A total of 165 people living with HIV (PLWH) but without neurocognitive disorders (PWND), 173 patients with asymptomatic neurocognitive impairment (ANI), and 100 matched healthy controls (HCs) were included in the study. A cross-sectional study of the participants was conducted. The metrics of functional segregation and integration were computed, using graph theory to explore differences across methodologies. Brain functional changes in the PWND and ANI groups were assessed, and correlations between the rs-fMRI metrics, clinical data, and cognitive function were examined.

RESULTS: As cognitive function declined, changes reflected by regional homogeneity (ReHo) were primarily observed in the default mode network (DMN). In the DMN and visual network (VIS), amplitude of low-frequency fluctuation (ALFF) decreases were mainly observed in the parieto-occipital lobes, while increases were mainly observed in the limbic network (LIM). Reductions in fractional ALFF (fALFF) were mainly observed in the somatomotor network (SMN) and LIM, while increases were observed in the DMN and LIM. Unlike local indicators, global functional connectivity (FC) significantly decreased in both the PWND and ANI groups compared to the HC group. The ANI group showed partial increases in FC compared to the PWND group, with major changes observed in the DMN, VIS, and LIM. Notably, FC between the right insula and right supramarginal gyrus decreased significantly following HIV infection, while FC between the right caudate nucleus and the left middle frontal gyrus declined further in the ANI group. Graph theory further confirmed the significance of the DMN, and revealed changes in the eigenvector centrality mapping (ECM) values of the frontoparietal network (FPN) and dorsal attention network (DAN).

CONCLUSIONS: HIV patients exhibit complex changes in both local and global brain activity, regardless of cognitive impairment. Widespread abnormalities primarily involve the DMN, VIS, and LIM. Changes in FC along the fronto-striatal pathway may play a crucial role in the decline of cognitive function in individuals with HAND. Our findings provide new insights that may assist in the early detection of brain damage in the early stages of HIV infection. The use of multiple methodologies may offer a more comprehensive and effective approach, enabling the early detection of brain damage in HIV patients.

PMID:39838977 | PMC:PMC11744116 | DOI:10.21037/qims-24-1342

Hum Brain Mapp. 2025 Feb 1;46(2):e70131. doi: 10.1002/hbm.70131.

ABSTRACT

Spontaneous neural activity coherently relays information across the brain. Several efforts have been made to understand how spontaneous neural activity evolves at the macro-scale level as measured by resting-state functional magnetic resonance imaging (rsfMRI). Previous studies observe the global patterns and flow of information in rsfMRI using methods such as sliding window or temporal lags. However, to our knowledge, no studies have examined spatial propagation patterns evolving with time across multiple overlapping 4D networks. Here, we propose a novel approach to study how dynamic states of the brain networks spatially propagate and evaluate whether these propagating states contain information relevant to mental illness. We implement a lagged windowed correlation approach to capture voxel-wise network-specific spatial propagation patterns in dynamic states. Results show systematic spatial state changes over time, which we confirmed are replicable across multiple scan sessions using human connectome project data. We observe networks varying in propagation speed; for example, the default mode network (DMN) propagates slowly and remains positively correlated with blood oxygenation level-dependent (BOLD) signal for 6-8 s, whereas the visual network propagates much quicker. We also show that summaries of network-specific propagative patterns are linked to schizophrenia. More specifically, we find significant group differences in multiple dynamic parameters between patients with schizophrenia and controls within four large-scale networks: default mode, temporal lobe, subcortical, and visual network. Individuals with schizophrenia spend more time in certain propagating states. In summary, this study introduces a promising general approach to exploring the spatial propagation in dynamic states of brain networks and their associated complexity and reveals novel insights into the neurobiology of schizophrenia.

PMID:39835629 | DOI:10.1002/hbm.70131

Neurogastroenterol Motil. 2025 Jan 21:e15005. doi: 10.1111/nmo.15005. Online ahead of print.

ABSTRACT

BACKGROUND: Constipation is one of the most common non-motor symptoms in patients with Parkinson's disease (PD), which could manifest during the early stage of the disease. However, the etiology of constipation in PD remains largely unknown. Previous studies supported that gastrointestinal dysfunction may be associated with functional connectivity alterations in paraventricular hypothalamic nucleus (PVN). Therefore, this study aimed to investigate the potential contribution of the PVN to the pathogenesis of constipation in a cohort of early-stage patients with PD and to compare brain network organization between PD patients with and without constipation.

METHODS: A total of 66 PD patients (PD with constipation and without constipation) and 30 healthy controls were prospectively enrolled. All participants acquired T1-weighted and resting-state fMRI scans. Then we employed voxel-based morphometry analysis and functional connectivity analysis.

RESULTS: We observed a decreased functional connectivity in the PVN-pontine tegmentum pathway in PD patients with constipation compared to the patients without constipation (p = 0.006, t = 5.37), while we did not find any changes in basal ganglia circuitry between these two groups. In addition, we found that the functional connectivity between PVN and pontine tegmentum was negatively associated with the UPDRS I, II, III and NMSS scores (p < 0.05). Meanwhile, these two types of patients also showed substantial differences in functional connections linking the inferior frontal gyrus and cerebellum with multiple brain regions. We discovered no statistical difference in gray matter volume among these two groups.

CONCLUSIONS: Our study provides further insights into the dysfunctional mechanisms of constipation, suggesting that abnormal PVN functional connectivity may be related to the mechanism of constipation in PD. Meanwhile, the inferior frontal gyrus and cerebellum may be involved in the occurrence of constipation in PD patients.

PMID:39835618 | DOI:10.1111/nmo.15005

Hum Brain Mapp. 2025 Feb 1;46(2):e70139. doi: 10.1002/hbm.70139.

ABSTRACT

Apathy is a common neuropsychiatric symptom following stroke, characterized by reduced goal-directed behavior. The reward decision network (RDN), which plays a crucial role in regulating goal-directed behaviors, is closely associated with apathy. However, the relationship between poststroke apathy (PSA) and RDN dysfunction remains unclear due to apathy heterogeneity, the confounding effect of depression and individual variability in lesion impacts. This study aims to dissect the heterogeneity of PSA and explore the link between lesion-induced RDN damage and PSA. We prospectively recruited 207 patients with acute ischemic infarction and 60 demographically matched healthy controls. Participants underwent neuroimaging and longitudinal neuropsychiatric assessments. To characterize PSA heterogeneity, we employed multivariate analysis and clustering algorithms based on whole-brain functional connectivity and clinical assessments to classify patients into different PSA biotypes. We embedded each patient's lesion into a structural connectome atlas to obtain white matter (WM) disconnection maps. On this basis, WM disconnection scores were calculated for each brain region to quantify lesion-induced WM damage. We employed the XGBoost model to predict PSA biotypes based on WM disconnection scores, comparing the performance of models focusing on RDN-specific versus whole-brain WM disconnection. Additionally, we explored WM damage patterns across different biotypes by comparing disconnection scores in critical brain regions. We identified four PSA biotypes with unique clinical trajectories and neurobiological underpinnings. Biotype 4 was characterized by persistent apathy with depressive symptoms. Biotype 2 showed persistent apathy. Biotype 3 was non-apathetic. Biotype 1 exhibited delayed-onset apathy. The XGBoost models, when focused on the RDN-specific WM disconnection, performed significantly better in predicting PSA biotypes compared to the whole-brain WM disconnection model (t(164.66) = 8.871, p < 0.001). Analysis of WM disconnection patterns revealed that Biotype 4 exhibited more extensive RDN damage in crucial regions, Biotype 1 had a unique pattern of damage in the anterior cingulate cortex (t(61) = 1.874, p = 0.032), and Biotype 2 had a unique pattern of damage in the orbitofrontal cortex (t(53)= 1.827, p = 0.036). This study dissected PSA heterogeneity and demonstrated that RDN damage is a critical factor in PSA variability. We found that lesion-induced WM disconnections in anterior cingulate cortex and orbitofrontal cortex can lead to delayed-onset and persistent apathy, respectively. Furthermore, our findings revealed that apathy not only has distinct pathogenic mechanisms, but also shares neurobiological substrates with depression.

PMID:39835577 | DOI:10.1002/hbm.70139