Most recent paper

Brain Imaging Behav. 2025 Feb 22. doi: 10.1007/s11682-025-00986-y. Online ahead of print.

ABSTRACT

OBJECTIVES: Tinnitus affects millions worldwide. Its neural mechanisms remain unclear. This study aimed to explore the causal relationships between brain functional networks and tinnitus risk using Mendelian randomization (MR) analyses.

METHODS: We performed MR analyses using brain activity data from resting-state functional magnetic resonance imaging (rs-fMRI) and genetic data from genome-wide association studies (GWAS). A total of 191 brain features, including amplitude traits and functional connectivity measures, were selected based on their genetic associations.

RESULTS: Forward MR analyses showed that increased activity in the parietal and inferior frontal regions was associated with a 41% reduction in tinnitus risk (OR = 0.59, p = 1.8 × 10-4). In contrast, increased activity in the precuneus, angular gyrus, and frontal areas was linked to a 49% increase in tinnitus risk (OR = 1.49, p = 8.9 × 10-4). Activities in the parietal and inferior frontal regions were negatively correlated with tinnitus risk (OR = 0.72, p = 0.0037). Additionally, higher activity in the parietal, frontal, and temporal regions doubled the risk (OR = 2.02, p = 0.015). Reverse MR showed that stronger connectivity between frontal and temporal regions was inversely related to tinnitus risk (beta = - 0.056, p = 0.049).

CONCLUSIONS: Specific brain activity and connectivity patterns are causally linked to tinnitus.

PMID:39984808 | DOI:10.1007/s11682-025-00986-y

Mol Psychiatry. 2025 Feb 21. doi: 10.1038/s41380-025-02897-2. Online ahead of print.

ABSTRACT

Chronic stress is a causal antecedent condition for major depressive disorder and associates with altered patterns of neural connectivity. There are nevertheless important individual differences in susceptibility to chronic stress. How functional connectivity (FC) amongst interconnected, depression-related brain regions associates with resilience and susceptibility to chronic stress is largely unknown. We used resting-state functional magnetic resonance imaging (rs-fMRI) to examine FC between established depression-related regions in susceptible (SUS) and resilient (RES) adult mice following chronic social defeat stress (CSDS). Seed-seed FC analysis revealed that the ventral dentate gyrus (vDG) exhibited the greatest number of FC group differences with other stress-related limbic brain regions. SUS mice showed greater FC between the vDG and subcortical regions compared to both control (CON) or RES groups. Whole brain vDG seed-voxel analysis supported seed-seed findings in SUS mice but also indicated significantly decreased FC between the vDG and anterior cingulate area compared to CON mice. Interestingly, RES mice exhibited enhanced FC between the vDG and anterior cingulate area compared to SUS mice. Moreover, RES mice showed greater FC between the infralimbic prefrontal cortex and the nucleus accumbens shell compared to CON mice. These findings indicate unique differences in FC patterns in phenotypically distinct SUS and RES mice that could represent a neurobiological basis for depression, anxiety, and negative-coping behaviors that are associated with exposure to chronic stress.

PMID:39984680 | DOI:10.1038/s41380-025-02897-2

J Affect Disord. 2025 Feb 19:S0165-0327(25)00261-7. doi: 10.1016/j.jad.2025.02.054. Online ahead of print.

ABSTRACT

OBJECTIVE: The "ideation-to-action" framework for suicide posited that the occurrence of suicidal ideation (SI) and suicide attempts (SA) may involve distinct neural mechanisms. However, the disparities in neurocognitive impairment between SI and SA, along with the underlying neural mechanisms, remain further investigation.

METHODS: A total of 730 participants were recruited, including depressed patients with recent SA (RSA group, n = 69), patients with recent SI but no history of SA (SI group, n = 327), patients without SI or SA (NSI group, n = 87) and 247 healthy controls. All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans and completed cognitive function assessments. The dynamic regional homogeneity (dReHo) was measured using a sliding-window approach. Differences in dReHo and cognitive function between groups were analyzed.

RESULTS: The SI group demonstrated decreased verbal memory compared to the NSI group. Critically, the RSA group exhibited more pronounced verbal memory impairment than the SI group, accompanied by deficits in working memory and cognitive flexibility. Neuroimaging results revealed elevated dReHo values in the right precuneus (PCUN.R) in the RSA group, distinguishing them from the SI, NSI, and HC groups. Additionally, the increased dReHo of PCUN.R was correlated with diminished cognitive performance.

CONCLUSIONS: Depressed patients with SA showed elevated variability of functional activity in PCUN.R, which may be related to their more severe cognitive impairment. This may be a potential neural basis for the development of SA. Our findings offer new insights for advancing neuroscience research on the progression from SI to SA.

PMID:39983773 | DOI:10.1016/j.jad.2025.02.054

Neuroimage Clin. 2025 Feb 11;45:103753. doi: 10.1016/j.nicl.2025.103753. Online ahead of print.

ABSTRACT

Resting state functional MRI (rsfMRI) exploits variations in blood-oxygenation-level-dependent (BOLD) signals to infer resting state functional connectivity (FC) within and between brain networks. However, there have been few reports quantifying and validating the results of rsfMRI analyses with other metrics of brain circuits. We measured longitudinal changes in FC both within and between brain networks in three squirrel monkeys after focal lesions of the thalamic ventroposterior lateral nucleus (VPL) that were intended to disrupt the input to somatosensory cortex and impair manual dexterity. Local field potential signals were recorded to assess electrophysiological changes during each animal's recovery, and behavioral performances were measured longitudinally using a sugar-pellet grasping task. Finally, end-point histological evaluations were performed on brain tissue slices to quantify the VPL damage. The rsfMRI data analysis showed significant decrease in FC measures both within and between networks immediately post-injury, which started to recover at different time-points for each animal. The trajectories of FC recovery for each animal mirrored their individual behavioral recovery time-courses. Electrophysiological measurements of inter-electrode coherences and end-point histological measures also aligned well with the graded injury effects measured using rsfMRI-based FC. A simple algorithm employing FC measures from the somatosensory network could accurately predict each monkeys' behavioral recovery timeframe after four weeks post-injury. Whole brain between-network FC measures further revealed that the injury effects were not limited to thalamocortical connections but were rather more widespread. Overall, this study provides evidence of the validity of rsfMRI based FC measures as indicators of the functional integrity and behavioral relevance following an injury to a specific brain circuit.

PMID:39983550 | DOI:10.1016/j.nicl.2025.103753

Psychiatry Res Neuroimaging. 2025 Feb 11;348:111961. doi: 10.1016/j.pscychresns.2025.111961. Online ahead of print.

ABSTRACT

BACKGROUND: Depression is linked to abnormalities in brain networks. Resting-state functional connectivity (FC), as measured using resting-state fMRI (rs-fMRI), is a crucial tool for exploring the brain network abnormalities associated with depressive symptoms, as it reveals how disruptions in brain region interactions occur. However, research focusing on adolescents with depression is limited and inconsistent, highlighting the need for further studies in this area.

METHODS: Fifty-five adolescents with Depressive episodes (DE) and 26 healthy controls (HCs) underwent resting-state fMRI. Depressive symptoms were assessed using the 17-item Hamilton Rating Scale for Depression (HAMD-17). Seed regions were defined based on Yeo's seven-network scheme, including the sensorimotor network (SMN), ventral attention network (VAN), dorsal attention network (DAN), visual network (VN), frontoparietal network (FPN), default mode network (DMN), and limbic network (LN). These seed regions were derived from analysis of large-scale FC in healthy individuals, and were selected for their relevance to cognition, emotion, and depression research. Network-based statistical analyses were used to compare the adolescents with DE to the HCs, and correlation analyses were employed to examine the relationships between FC changes and cognitive performance.

RESULTS: The results showed significant differences in FC between the DE and HCs groups, involving 17 nodes and 17 edges across seven networks. Decreased FC was observed within the FPN, as well as between the FPN and VAN, the FPN and DMN, and the SMN and both the DAN and VN. Increased FC was observed between the FPN and VN, between the DAN and other networks (i.e., the DMN and FPN), and between the SMN and multiple networks. Notably, FC between the right superior parietal (SMN) and right precuneus (DMN) showed a negative correlation with HAMD-17 scores.

CONCLUSION: These results suggest that adolescents with DE experience widespread brain network abnormalities characterized by hypoactivity in external networks such as the SMN and VN, as well as hyperactivity in associative regions, including the DMN, FPN, SMN, and LN. Although these changes in FC are evident, the specific mechanisms linking them to clinical symptoms remain unclear and warrant further investigation.

PMID:39983531 | DOI:10.1016/j.pscychresns.2025.111961

PLoS One. 2025 Feb 21;20(2):e0317566. doi: 10.1371/journal.pone.0317566. eCollection 2025.

ABSTRACT

Parkinson's disease (PD) is a common neurodegenerative disorder with a poorly understood physiopathology and no established biomarkers for the diagnosis of early stages and for prediction of disease progression. Several neuroimaging biomarkers have been studied recently, but these are susceptible to several sources of variability related for instance to cohort selection or image analysis. In this context, an evaluation of the robustness of such biomarkers to variations in the data processing workflow is essential. This study is part of a larger project investigating the replicability of potential neuroimaging biomarkers of PD. Here, we attempt to fully reproduce (reimplementing the experiments with the same methods, including data collection from the same database) and replicate (different data and/or method) the models described in (Nguyen et al., 2021) to predict individual's PD current state and progression using demographic, clinical and neuroimaging features (fALFF and ReHo extracted from resting-state fMRI). We use the Parkinson's Progression Markers Initiative dataset (PPMI, ppmi-info.org), as in (Nguyen et al., 2021) and aim to reproduce the original cohort, imaging features and machine learning models as closely as possible using the information available in the paper and the code. We also investigated methodological variations in cohort selection, feature extraction pipelines and sets of input features. Different criteria were used to evaluate the reproduction attempt and compare the results with the original ones. Notably, we obtained significantly better than chance performance using the analysis pipeline closest to that in the original study (R2 > 0), which is consistent with its findings. In addition, we performed a partial reproduction using derived data provided by the authors of the original study, and we obtained results that were close to the original ones. The challenges encountered while attempting to reproduce (fully and partially) and replicating the original work are likely explained by the complexity of neuroimaging studies, in particular in clinical settings. We provide recommendations to further facilitate the reproducibility of such studies in the future.

PMID:39982930 | DOI:10.1371/journal.pone.0317566

Bipolar Disord. 2025 Feb 21. doi: 10.1111/bdi.70013. Online ahead of print.

ABSTRACT

INTRODUCTION: Exposure to childhood maltreatment can contribute to multiple behavioral and clinical manifestations, including the development of psychotic illnesses and pain-related abnormalities. Aberrant pain perception in individuals with psychosis may be associated with the worsening psychiatric symptoms, including an increase in mood episodes and a higher risk for suicidality. Despite the multiple connections between psychosis, pain, and childhood maltreatment, the combined investigation of these three domains remains limited.

METHODS: In this study, patients with schizophrenia (SZ, n = 20) or bipolar I disorder (BD, n = 24) and healthy controls (HC, n = 24) underwent a comprehensive clinical evaluation followed by quantitative sensory testing (QST), where behavioral sensitivity to thermal stimuli was quantified. Central pain circuitry was probed using a combination of functional and structural magnetic resonance imaging. Neuroimaging analyses focused on thermal stimulation fMRI responses, resting-state connectivity, and gray matter morphological properties.

RESULTS: fMRI demonstrated diminished sensorimotor activation during an evoked pain state for both SZ and BD patients, where reduced activity in thalamic subdivisions (i.e., pulvinar nucleus) in BD patients negatively correlates with the severity of childhood maltreatment. Resting-state connectivity analyses revealed altered connectivity of various cortical regions with the postcentral gyri and thalamic nuclei, suggesting potential altered neural mechanisms underlying pain perception in patients with SZ and BD. Morphological analysis identified reduced gray matter thickness in the postcentral sulcus of BD patients, which correlated with the severity of childhood maltreatment.

CONCLUSION: These findings provide insight into the multidimensional nature of clinical presentations in SZ and BD and contribute to our understanding of the complex relationship between childhood maltreatment and central pain processing in patients with psychotic illnesses.

PMID:39981600 | DOI:10.1111/bdi.70013

Hum Brain Mapp. 2025 Feb 15;46(3):e70049. doi: 10.1002/hbm.70049.

ABSTRACT

Early efforts to understand the human cerebral cortex focused on localization of function, assigning functional roles to specific brain regions. More recent evidence depicts the cortex as a dynamic system, organized into flexible networks with patterns of spatiotemporal activity corresponding to attentional demands. In functional MRI (fMRI), dynamic analysis of such spatiotemporal patterns is highly promising for providing non-invasive biomarkers of neurodegenerative diseases and neural disorders. However, there is no established neurotypical spectrum to interpret the burgeoning literature of dynamic functional connectivity from fMRI across attentional states. In the present study, we apply dynamic analysis of network-scale spatiotemporal patterns in a range of fMRI datasets across numerous tasks including a left-right moving dot task, visual working memory tasks, congruence tasks, multiple resting state datasets, mindfulness meditators, and subjects watching TV. We find that cortical networks show shifts in dynamic functional connectivity across a spectrum that tracks the level of external to internal attention demanded by these tasks. Dynamics of networks often grouped into a single task positive network show divergent responses along this axis of attention, consistent with evidence that definitions of a single task positive network are misleading. Additionally, somatosensory and visual networks exhibit strong phase shifting along this spectrum of attention. Results were robust on a group and individual level, further establishing network dynamics as a potential individual biomarker. To our knowledge, this represents the first study of its kind to generate a spectrum of dynamic network relationships across such an axis of attention.

PMID:39980439 | DOI:10.1002/hbm.70049