Most recent paper

Eur J Neurol. 2024 Jul 26:e16421. doi: 10.1111/ene.16421. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: Cognitive impairment (CI) in multiple sclerosis (MS) is associated with bidirectional changes in resting-state centrality measures. However, practicable functional magnetic resonance imaging (fMRI) biomarkers of CI are still lacking. The aim of this study was to assess the graph-theory-based degree rank order disruption index (kD) and its association with cognitive processing speed as a marker of CI in patients with MS (PwMS) in a secondary cross-sectional fMRI analysis.

METHODS: Differentiation between PwMS and healthy controls (HCs) using kD and its correlation with CI (Symbol Digit Modalities Test) was compared to established imaging biomarkers (regional degree, volumetry, diffusion-weighted imaging, lesion mapping). Additional associations were assessed for fatigue (Fatigue Scale for Motor and Cognitive Functions), gait and global disability.

RESULTS: Analysis in 56 PwMS and 58 HCs (35/27 women, median age 45.1/40.5 years) showed lower kD in PwMS than in HCs (median -0.30/-0.06, interquartile range 0.55/0.54; p = 0.009, Mann-Whitney U test), yielding acceptable yet non-superior differentiation (area under curve 0.64). kD and degree in medial prefrontal cortex (MPFC) correlated with CI (kD/MPFC Spearman's ρ = 0.32/-0.45, p = 0.019/0.001, n = 55). kD also explained fatigue (ρ = -0.34, p = 0.010, n = 56) but neither gait nor disability.

CONCLUSIONS: kD is a potential biomarker of CI and fatigue warranting further validation.

PMID:39058296 | DOI:10.1111/ene.16421

Front Hum Neurosci. 2024 Jun 26;18:1363125. doi: 10.3389/fnhum.2024.1363125. eCollection 2024.

ABSTRACT

INTRODUCTION: Numerous modes or patterns of neural activity can be seen in the brain of individuals during the resting state. However, those functions do not persist long, and they are continuously altering in the brain. We have hypothesized that the brain activations during the resting state should themselves be responsible for this alteration of the activities.

METHODS: Using the resting-state fMRI data of 63 healthy young individuals, we estimated the causality effects of each resting-state activation map on all other networks. The resting-state networks were identified, their causality effects on the other components were extracted, the networks with the top 20% of the causality were chosen, and the networks which were under the influence of those causal networks were also identified.

RESULTS: Our results showed that the influence of each activation component over other components is different. The brain areas which showed the highest causality coefficients were subcortical regions, such as the brain stem, thalamus, and amygdala. On the other hand, nearly all the areas which were mostly under the causal effects were cortical regions.

DISCUSSION: In summary, our results suggest that subcortical brain areas exert a higher influence on cortical regions during the resting state, which could help in a better understanding the dynamic nature of brain functions.

PMID:39055533 | PMC:PMC11271203 | DOI:10.3389/fnhum.2024.1363125

Heliyon. 2024 Jun 27;10(13):e33833. doi: 10.1016/j.heliyon.2024.e33833. eCollection 2024 Jul 15.

ABSTRACT

Major depressive disorder (MDD) is a debilitating mental health condition that poses significant risks and burdens. Resting-state functional magnetic resonance imaging (fMRI) has emerged as a promising tool in investigating the neural mechanisms underlying MDD. However, a comprehensive bibliometric analysis of resting-state fMRI in MDD is currently lacking. Here, we aimed to thoroughly explore the trends and frontiers of resting-state fMRI in MDD research. The relevant publications were retrieved from the Web of Science database for the period between 1998 and 2022, and the CiteSpace software was employed to identify the influence of authors, institutions, countries/regions, and the latest research trends. A total of 1501 publications met the search criteria, revealing a gradual increase in the number of annual publications over the years. China contributed the largest publication output, accounting for the highest percentage among all countries. Particularly, the University of Electronic Science and Technology of China, Capital Medical University, and Harvard Medical School were identified as key institutions that have made substantial contributions to this growth. Neuroimage, Biological Psychiatry, Journal of Affective Disorders, and Proceedings of the National Academy of Sciences of the United States of America are among the influential journals in the field of resting-state fMRI research in MDD. Burst keywords analysis suggest the emerging research frontiers in this field are characterized by prominent keywords such as dynamic functional connectivity, cognitive control network, transcranial brain stimulation, and childhood trauma. Overall, our study provides a systematic overview into the historical development, current status, and future trends of resting-state fMRI in MDD, thus offering a useful guide for researchers to plan their future research.

PMID:39050435 | PMC:PMC11266997 | DOI:10.1016/j.heliyon.2024.e33833

Curr Neurol Neurosci Rep. 2024 Jul 24. doi: 10.1007/s11910-024-01365-8. Online ahead of print.

ABSTRACT

PURPOSE OF THE REVIEW: In this review, we attempt to summarize the most updated studies that applied resting-state functional magnetic resonance imaging (rs-fMRI) in the field of Parkinsonisms and related dementia.

RECENT FINDINGS: Over the past decades, increasing interest has emerged on investigating the presence and pathophysiology of cognitive symptoms in Parkinsonisms and their possible role as predictive biomarkers of neurodegenerative brain processes. In recent years, evidence has been provided, applying mainly three methodological approaches (i.e. seed-based, network-based and graph-analysis) on rs-fMRI data, with promising results. Neural correlates of cognitive impairment and dementia have been detected in patients with Parkinsonisms along the diseases course. Interestingly, early functional connectivity signatures were proposed to track and predict future progression of neurodegenerative processes. However, longitudinal studies are still sparce and further investigations are needed to overcome this knowledge gap.

PMID:39046642 | DOI:10.1007/s11910-024-01365-8

Neuroradiology. 2024 Jul 24. doi: 10.1007/s00234-024-03436-6. Online ahead of print.

ABSTRACT

INTRODUCTION: Patients with Parkinson's Disease (PD) commonly experience Olfactory Dysfunction (OD). Our exploratory study examined hippocampal volumetric and resting-state functional magnetic resonance imaging (rs-fMRI) variations in a Healthy Control (HC) group versus a cognitively normal PD group, further categorized into PD with No/Mild Hyposmia (PD-N/MH) and PD with Severe Hyposmia (PD-SH).

METHODS: We calculated participants' relative Total Hippocampal Volume (rTHV) and performed Spearman's partial correlations, controlled for age and gender, to examine the correlation between rTHV and olfactory performance assessed by the Odor Stick Identification Test for the Japanese (OSIT-J) score. Mann-Whitney U tests assessed rTHV differences across groups and subgroups, rejecting the null hypothesis for p < 0.05. Furthermore, a seed-based rs-fMRI analysis compared hippocampal connectivity differences using a one-way ANCOVA covariate model with controls for age and gender.

RESULTS: Spearman's partial correlations indicated a moderate positive correlation between rTHV and OSIT-J in the whole study population (ρ = 0.406; p = 0.007), PD group (ρ = 0.493; p = 0.008), and PD-N/MH subgroup (ρ = 0.617; p = 0.025). Mann-Whitney U tests demonstrated lower rTHV in PD-SH subgroup compared to both HC group (p = 0.013) and PD-N/MH subgroup (p = 0.029). Seed-to-voxel rsfMRI analysis revealed reduced hippocampal connectivity in PD-SH subjects compared to HC subjects with a single cluster of voxels.

CONCLUSIONS: Although the design of the study do not allow to make firm conclusions, it is reasonable to speculate that the progressive involvement of the hippocampus in PD patients is associated with the progression of OD.

PMID:39046517 | DOI:10.1007/s00234-024-03436-6

Hum Brain Mapp. 2024 Aug 1;45(11):e26766. doi: 10.1002/hbm.26766.

ABSTRACT

Mood variability, the day-to-day fluctuation in mood, differs between individuals and develops during adolescence. Because adolescents show higher mood variability and average mood than children and adults, puberty might be a potential biological mechanism underlying this increase. The goal of this preregistered developmental study was to examine the neural and hormonal underpinnings of adolescent-specific within-person changes in mood variability, with a specific focus on testosterone, cortisol, pubertal status, and resting-state functional brain connectivity. Data from two longitudinal cohorts were used: the L-CID twin study (aged 7-13, N at the first timepoint = 258) and the accelerated Leiden Self-Concept study (SC; aged 11-21, N at the first timepoint = 138). In both studies resting-state functional magnetic resonance imaging (rs-fMRI) data was collected, as well as daily mood. Additionally, in the SC study self-reported puberty testosterone and cortisol were collected. Random intercept cross-lagged panel models (RI-CLPM) were used to study the within-person relations between these biological measures and mood variability and average mood. Mood variability and average mood peaked in adolescence and testosterone levels and self-reported puberty also showed an increase. Connectivity between prefrontal cortex (dlPFC and vmPFC) and subcortical regions (caudate, amygdala) decreased across development. Moreover, higher testosterone predicted average negative mood at the next time point, but not vice versa. Further, stronger vmPFC-amygdala functional connectivity predicted decreases in mood variability. Here, we show that brain connectivity during development is an important within-person biological mechanism of the development of mood in adolescents. PRACTITIONER POINTS: Mood variability peaks in adolescence. Within-person changes in testosterone predict within-person changes in mood. Within-person changes in vmPFC-amygdala connectivity predict within-person changes in mood variability.

PMID:39046072 | DOI:10.1002/hbm.26766

Hum Brain Mapp. 2024 Aug 1;45(11):e26773. doi: 10.1002/hbm.26773.

ABSTRACT

Despite increasing interest in the dynamics of functional brain networks, most studies focus on the changing relationships over time between spatially static networks or regions. Here we propose an approach to study dynamic spatial brain networks in human resting state functional magnetic resonance imaging (rsfMRI) data and evaluate the temporal changes in the volumes of these 4D networks. Our results show significant volumetric coupling (i.e., synchronized shrinkage and growth) between networks during the scan, that we refer to as dynamic spatial network connectivity (dSNC). We find that several features of such dynamic spatial brain networks are associated with cognition, with higher dynamic variability in these networks and higher volumetric coupling between network pairs positively associated with cognitive performance. We show that these networks are modulated differently in individuals with schizophrenia versus typical controls, resulting in network growth or shrinkage, as well as altered focus of activity within a network. Schizophrenia also shows lower spatial dynamical variability in several networks, and lower volumetric coupling between pairs of networks, thus upholding the role of dynamic spatial brain networks in cognitive impairment seen in schizophrenia. Our data show evidence for the importance of studying the typically overlooked voxel-wise changes within and between brain networks.

PMID:39045900 | DOI:10.1002/hbm.26773

Data Brief. 2024 Jun 24;55:110668. doi: 10.1016/j.dib.2024.110668. eCollection 2024 Aug.

ABSTRACT

To achieve a comprehensive understanding of spontaneous brain dynamics in humans, in vivo acquisition of intrinsic activity across both cortical and subcortical regions is necessary. Here we present advanced whole-brain, resting-state functional magnetic resonance imaging (rs-fMRI) data acquired at 7 Tesla with 1.5 mm isotropic voxel resolution. Functional images were obtained from 56 healthy adults (33 females, ages 19-39 years) in two runs of 15 min eyes-open wakeful rest. The high spatial resolution and short echo times of the multiband echo-planar imaging (EPI) protocol optimizes blood oxygen level-dependent (BOLD)-sensitivity for the subcortex while concurrent respiratory and cardiac measures enable retrospective correction of physiological noise, resulting in data that is highly suitable for researchers interested in subcortical BOLD signal. Functional timeseries were coregistered to high-resolution T1-weighted structural data (0.75 mm isotropic voxels) acquired during the same scanning session. To accommodate data reutilization, functional and structural images were formatted to the Brain Imaging Data Structure (BIDS) and preprocessed with fMRIPrep.

PMID:39044905 | PMC:PMC11263741 | DOI:10.1016/j.dib.2024.110668

J Prev Alzheimers Dis. 2024;11(4):1140-1147. doi: 10.14283/jpad.2024.76.

ABSTRACT

BACKGROUND: Resting heart rate (RHR), has been related to increased risk of dementia, but the relationship between RHR and brain age is unclear.

OBJECTIVE: We aimed to investigate the association of RHR with brain age and brain age gap (BAG, the difference between predicted brain age and chronological age) assessed by multimodal Magnetic Resonance Imaging (MRI) in mid- and old-aged adults.

DESIGN: A longitudinal study from the UK Biobank neuroimaging project where participants underwent brain MRI scans 9+ years after baseline.

SETTING: A population-based study.

PARTICIPANTS: A total of 33,381 individuals (mean age 54.74 ± 7.49 years; 53.44% female).

MEASUREMENTS: Baseline RHR was assessed by blood pressure monitor and categorized as <60, 60-69 (reference), 70-79, or ≥80 beats per minute (bpm). Brain age was predicted using LASSO through 1,079 phenotypes in six MRI modalities (including T1-weighted MRI, T2-FLAIR, T2*, diffusion-MRI, task fMRI, and resting-state fMRI). Data were analyzed using linear regression models.

RESULTS: As a continuous variable, higher RHR was associated with older brain age (β for per 1-SD increase: 0.331, 95% [95% confidence interval, CI]: 0.265, 0.398) and larger BAG (β: 0.263, 95% CI: 0.202, 0.324). As a categorical variable, RHR 70-79 bpm and RHR ≥80 bpm were associated with older brain age (β [95% CI]: 0.361 [0.196, 0.526] / 0.737 [0.517, 0.957]) and larger BAG (0.256 [0.105, 0.407] / 0.638 [0.436, 0.839]), but RHR< 60 bpm with younger brain age (-0.324 [-0.500, -0.147]) and smaller BAG (-0.230 [-0.392, -0.067]), compared to the reference group. These associations between elevated RHR and brain age were similar in both middle-aged (<60) and older (≥60) adults, whereas the association of RHR< 60 bpm with younger brain age and larger BAG was only significant among middle-aged adults. In stratification analysis, the association between RHR ≥80 bpm and older brain age was present in people with and without CVDs, while the relation of RHR 70-79 bpm to brain age present only in people with CVD.

CONCLUSION: Higher RHR (>80 bpm) is associated with older brain age, even among middle-aged adults, but RHR< 60 bpm is associated with younger brain age. Greater RHR could be an indicator for accelerated brain aging.

PMID:39044526 | DOI:10.14283/jpad.2024.76

J Prev Alzheimers Dis. 2024;11(4):881-888. doi: 10.14283/jpad.2024.140.

ABSTRACT

BACKGROUND: Stronger resting-state functional connectivity of the default mode and frontoparietal control networks has been associated with cognitive resilience to Alzheimer's disease related pathology and neurodegeneration in smaller cohort studies.

OBJECTIVES: We investigated whether these networks are associated with longitudinal CR to AD biomarkers of beta-amyloid (Aβ).

DESIGN: Longitudinal mixed.

SETTING: The Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) study and its natural history observation arm, the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) study.

PARTICIPANTS: A sample of 1,021 cognitively unimpaired older adults (mean age = 71.2 years [SD = 4.7 years], 61% women, 42% APOEε4 carriers, 52% Aβ positive).

MEASUREMENTS: Global cognitive performance (Preclinical Alzheimer's Cognitive Composite) was assessed over an average 5.4 year follow-up period (SD = 2 years). Cortical Aβ and functional connectivity (left and right frontoparietal control and default mode networks) were estimated from fMRI and PET, respectively, at baseline. Covariates included baseline age, APOEε4 carrier status, years of education, adjusted gray matter volume, head motion, study group, cumulative treatment exposure, and cognitive test version.

RESULTS: Mixed effects models revealed that functional connectivity of the left frontoparietal control network moderated the negative effect of Aβ on cognitive change (p = .025) such that stronger connectivity was associated with reduced Aβ-related cognitive decline.

CONCLUSIONS: Our results demonstrate a potential protective effect of functional connectivity in preclinical AD, such that stronger connectivity in this network is associated with slower Aβ-related cognitive decline.

PMID:39044497 | DOI:10.14283/jpad.2024.140

Eur Arch Psychiatry Clin Neurosci. 2024 Jul 24. doi: 10.1007/s00406-024-01871-3. Online ahead of print.

ABSTRACT

Dynamic functional network connectivity (dFNC) is an expansion of static FNC (sFNC) that reflects connectivity variations among brain networks. This study aimed to investigate changes in sFNC and dFNC strength and temporal properties in individuals with subthreshold depression (StD). Forty-two individuals with subthreshold depression and 38 healthy controls (HCs) were included in this study. Group independent component analysis (GICA) was used to determine target resting-state networks, namely, executive control network (ECN), default mode network (DMN), sensorimotor network (SMN) and dorsal attentional network (DAN). Sliding window and k-means clustering analyses were used to identify dFNC patterns and temporal properties in each subject. We compared sFNC and dFNC differences between the StD and HCs groups. Relationships between changes in FNC strength, temporal properties, and neurophysiological score were evaluated by Spearman's correlation analysis. The sFNC analysis revealed decreased FNC strength in StD individuals, including the DMN-CEN, DMN-SMN, SMN-CEN, and SMN-DAN. In the dFNC analysis, 4 reoccurring FNC patterns were identified. Compared to HCs, individuals with StD had increased mean dwell time and fraction time in a weakly connected state (state 4), which is associated with self-focused thinking status. In addition, the StD group demonstrated decreased dFNC strength between the DMN-DAN in state 2. sFNC strength (DMN-ECN) and temporal properties were correlated with HAMD-17 score in StD individuals (all p < 0.01). Our study provides new evidence on aberrant time-varying brain activity and large-scale network interaction disruptions in StD individuals, which may provide novel insight to better understand the underlying neuropathological mechanisms.

PMID:39044022 | DOI:10.1007/s00406-024-01871-3

IEEE Trans Biomed Eng. 2024 Jul 23;PP. doi: 10.1109/TBME.2024.3432273. Online ahead of print.

ABSTRACT

Independent component analysis (ICA) is now a widely used solution for the analysis of multi-subject functional magnetic resonance imaging (fMRI) data. Independent vector analysis (IVA) generalizes ICA to multiple datasets (multi-subject data). Along with higher-order statistical information in ICA, it leverages the statistical dependence across the datasets as an additional type of statistical diversity. As such, IVA preserves variability in the estimation of single-subject maps but its performance might suffer when the number of datasets increases. Constrained IVA is an effective way to bypass computational issues and improve the quality of separation by incorporating available prior information. Existing constrained IVA approaches often rely on user-defined threshold values to define the constraints. However, an improperly selected threshold can have a negative impact on the final results. This paper proposes two novel methods for constrained IVA: one using an adaptive-reverse scheme to select variable thresholds for the constraints and a second one based on a threshold-free formulation by leveraging the unique structure of IVA. Notably, the proposed algorithms do not require all components to be constrained, utilizing free components to model interferences and components that might not be in the reference set. We demonstrate that our solutions provide an attractive solution to multi-subject fMRI analysis both by simulations and through analysis of resting state fMRI data collected from 98 subjects - the highest number of subjects ever used by IVA algorithms. Our results show that both proposed approaches obtain significantly better separation quality and model match while providing computationally efficient and highly reproducible solutions.

PMID:39042541 | DOI:10.1109/TBME.2024.3432273

Front Psychiatry. 2024 Jul 8;15:1401623. doi: 10.3389/fpsyt.2024.1401623. eCollection 2024.

ABSTRACT

BACKGROUND: Obsessive-compulsive disorder (OCD) is a chronic psychiatric illness with complex clinical manifestations. Cognitive dysfunction may underlie OC symptoms. The frontoparietal network (FPN) is a key region involved in cognitive control. However, the findings of impaired FPN regions have been inconsistent. We employed meta-analysis to identify the fMRI-specific abnormalities of the FPN in OCD.

METHODS: PubMed, Web of Science, Scopus, and EBSCOhost were searched to screen resting-state functional magnetic resonance imaging (rs-fMRI) studies exploring dysfunction in the FPN of OCD patients using three indicators: the amplitude of low-frequency fluctuation/fractional amplitude of low-frequency fluctuation (ALFF/fALFF), regional homogeneity (ReHo) and functional connectivity (FC). We compared all patients with OCD and control group in a primary analysis, and divided the studies by medication in secondary meta-analyses with the activation likelihood estimation (ALE) algorithm.

RESULTS: A total of 31 eligible studies with 1359 OCD patients (756 men) and 1360 healthy controls (733 men) were included in the primary meta-analysis. We concluded specific changes in brain regions of FPN, mainly in the left dorsolateral prefrontal cortex (DLPFC, BA9), left inferior frontal gyrus (IFG, BA47), left superior temporal gyrus (STG, BA38), right posterior cingulate cortex (PCC, BA29), right inferior parietal lobule (IPL, BA40) and bilateral caudate. Additionally, altered connectivity within- and between-FPN were observed in the bilateral DLPFC, right cingulate gyrus and right thalamus. The secondary analyses showed improved convergence relative to the primary analysis.

CONCLUSION: OCD patients showed dysfunction FPN, including impaired local important nodal brain regions and hypoconnectivity within the FPN (mainly in the bilateral DLPFC), during the resting state. Moreover, FPN appears to interact with the salience network (SN) and default mode network (DMN) through pivotal brain regions. Consistent with the hypothesis of fronto-striatal circuit dysfunction, especially in the dorsal cognitive circuit, these findings provide strong evidence for integrating two pathophysiological models of OCD.

PMID:39041046 | PMC:PMC11260709 | DOI:10.3389/fpsyt.2024.1401623

Pol J Radiol. 2024 Jun 21;89:e308-e315. doi: 10.5114/pjr/188633. eCollection 2024.

ABSTRACT

PURPOSE: The aim of this study was to assess the activity of motor cortical areas and the resting brain activity in a group of multiple sclerosis (MS) patients compared to a group of healthy individuals according to task-based functional magnetic resonance imaging (t-fMRI), resting state functional MRI (rs-fMRI), and volumetric MRI studies.

MATERIAL AND METHODS: The study enrolled 28 MS patients and 20 healthy volunteers who underwent MRI examinations. Primary motor cortex (M1), premotor area (PMA), supplementary motor area, as well as resting state networks (RSN's) and volumes of selected brain structures were subjected to a detailed analysis.

RESULTS: In MS patients, a motor task more often resulted in the activation of ipsilateral M1 cortex (observed in 39% of the studied group) as well as the PMA cortex (observed in 32% of MS patients). No differences in resting brain activity were found between the studied groups. Significant differences were observed in volumetric parameters of the total brain volume (healthy volunteers vs. MS patients, respectively): (1197 cm³ vs. 1150 cm³) and volumes of the grey matter (517 cm³ vs. 481 cm³), cerebellum (150 cm³ vs. 136 cm³), thalamus (16.3 cm³ vs. 12.6 cm³), putamen (8.9 cm³ vs. 7.7 cm³), and globus pallidus (4.57 cm³ vs. 3.57 cm³).

CONCLUSIONS: In the MS patients, the motor task required significantly more frequent activation of the primary and secondary ipsilateral motor cortex compared to the group of healthy volunteers. The rs-fMRI study showed no differences in activity patterns within the RSN's. Differences in the total cerebral volume and the volume of the grey matter, cerebellum, thalamus, putamen, and globus pallidus were observed.

PMID:39040563 | PMC:PMC11262016 | DOI:10.5114/pjr/188633

Soc Neurosci. 2024 Jul 22:1-13. doi: 10.1080/17470919.2024.2382768. Online ahead of print.

ABSTRACT

Aggression can be categorized into reactive aggression (RA) and proactive aggression (PA) based on their underlying motivations. However, previous research has rarely identified the relationship between femininity and RA/PA, and there is a lack of understanding regarding the femininity-related neurofunctional basis of these aggressive behaviors. Thus, this study first examined the relationships between femininity and aggression, then explored the aggression-by-femininity interactions on the fractional amplitude of low-frequency fluctuations using resting-state fMRI among 705 university participants (mean age = 19.14 ± 0.99). The behavioral data indicated that femininity was more negatively associated with RA and PA when masculinity was controlled for. Additionally, the neural data revealed that femininity-specific relationships of RA in the left middle occipital gyrus (i.e. individuals with low femininity had positive relationships between RA and the left middle occipital gyrus, whereas those with high femininity had negative relationships) as well as of PA in the left middle frontal gyrus (i.e. individuals with high femininity showed significant negative relationships, whereas those with low femininity did not exhibit significant relationships). These findings reflect that individuals with varying levels of femininity exhibit distinct neural bases when expressing different subtypes of aggression, which are associated with societal expectations of gender.

PMID:39039838 | DOI:10.1080/17470919.2024.2382768

Pain. 2024 Jul 18. doi: 10.1097/j.pain.0000000000003334. Online ahead of print.

ABSTRACT

Menstrual pain is associated with deficits in central pain processing, yet neuroimaging studies to date have all been limited by focusing on group comparisons of adult women with vs without menstrual pain. This study aimed to investigate the role of the triple network model (TNM) of brain networks in adolescent girls with varied menstrual pain severity ratings. One hundred participants (ages 13-19 years) completed a 6-min resting state functional magnetic resonance imaging (fMRI) scan and rated menstrual pain severity, menstrual pain interference, and cumulative menstrual pain exposure. Imaging analyses included age and gynecological age (years since menarche) as covariates. Menstrual pain severity was positively associated with functional connectivity between the cingulo-opercular salience network (cSN) and the sensory processing regions, limbic regions, and insula, and was also positively associated with connectivity between the left central executive network (CEN) and posterior regions. Menstrual pain interference was positively associated with connectivity between the cSN and widespread brain areas. In addition, menstrual pain interference was positively associated with connectivity within the left CEN, whereas connectivity both within the right CEN and between the right CEN and cortical areas outside the network (including the insula) were negatively associated with menstrual pain interference. Cumulative menstrual pain exposure shared a strong negative association with connectivity between the default mode network and other widespread regions associated with large-scale brain networks. These findings support a key role for the involvement of TNM brain networks in menstrual pain characteristics and suggest that alterations in pain processing exist in adolescents with varying levels of menstrual pain.

PMID:39037861 | DOI:10.1097/j.pain.0000000000003334

Schizophr Bull. 2024 Jul 20:sbae123. doi: 10.1093/schbul/sbae123. Online ahead of print.

ABSTRACT

BACKGROUND: The time following a recent onset of psychosis is a critical period during which intervention may be maximally effective. Studying individuals in this period also offers an opportunity to investigate putative brain biomarkers of illness prior to the long-term effects of chronicity and medication. The Human Connectome Project for Early Psychosis (HCP-EP) was funded by the National Institutes of Mental Health (NIMH) as an extension of the original Human Connectome Project's approach to understanding the human brain and its structural and functional connections.

DESIGN: The HCP-EP data were collected at 3 sites in Massachusetts (Beth Israel Deaconess Medical Center, McLean Hospital, and Massachusetts General Hospital), and one site in Indiana (Indiana University). Brigham and Women's Hospital served as the data coordination center and as an imaging site.

RESULTS: The HCP-EP dataset includes high-quality clinical, cognitive, functional, neuroimaging, and blood specimen data acquired from 303 individuals between the ages of 16-35 years old with affective psychosis (n = 75), non-affective psychosis (n = 148), and healthy controls (n = 80). Participants with early psychosis were within 5 years of illness onset (mean duration = 1.9 years, standard deviation = 1.4 years). All data and novel or modified analytic tools developed as part of the study are publicly available to the research community through the NIMH Data Archive (NDA) or GitHub (https://github.com/pnlbwh).

CONCLUSIONS: This paper provides an overview of the specific HCP-EP procedures, assessments, and protocols, as well as a brief characterization of the study participants to make it easier for researchers to use this rich dataset. Although we focus here on discussing and comparing affective and non-affective psychosis groups, the HCP-EP dataset also provides sufficient information for investigators to group participants differently.

PMID:39036958 | DOI:10.1093/schbul/sbae123

Neurotrauma Rep. 2024 Jul 1;5(1):617-627. doi: 10.1089/neur.2023.0059. eCollection 2024.

ABSTRACT

Traumatic brain injury (TBI), a significant global health issue, is affecting ∼69 million annually. To better understand TBI's impact on brain function and assess the efficacy of treatments, this study uses a novel temporal-spatial cross-group approach with a porcine model, integrating resting-state functional magnetic resonance imaging (rs-fMRI) for temporal and arterial spin labeling for spatial information. Our research used 18 four-week-old pigs divided into three groups: TBI treated with saline (SLN, n = 6), TBI treated with fecal microbial transplant (FMT, n = 6), and a sham group (sham, n = 6) with only craniectomy surgery as the baseline. By applying machine learning techniques-specifically, independent component analysis and sparse dictionary learning-across seven identified resting-state networks, we assessed the temporal and spatial correlations indicative of treatment efficacy. Both temporal and spatial analyses revealed a consistent increase of correlation between the FMT and sham groups in the executive control and salience networks. Our results are further evidenced by a simulation study designed to mimic the progression of TBI severity through the introduction of variable Gaussian noise to an independent rs-fMRI dataset. The results demonstrate a decreasing temporal correlation between the sham and TBI groups with increasing injury severity, consistent with the experimental results. This study underscores the effectiveness of the methodology in evaluating post-TBI treatments such as the FMT. By presenting comprehensive experimental and simulated data, our research contributes significantly to the field and opens new paths for future investigations into TBI treatment evaluations.

PMID:39036426 | PMC:PMC11257111 | DOI:10.1089/neur.2023.0059

Eur J Neurosci. 2024 Jul 21. doi: 10.1111/ejn.16459. Online ahead of print.

ABSTRACT

Recent studies have shown that during the typical resting-state, echo planar imaging (EPI) time series obtained from the eye orbit area correlate with brain regions associated with oculomotor control and lower-level visual cortex. Here, we asked whether congenitally blind (CB) shows similar patterns, suggesting a hard-wired constraint on connectivity. We find that orbital EPI signals in CB do correlate with activity in the motor cortex, but less so with activity in the visual cortex. However, the temporal patterns of this eye movement-related signal differed strongly between CB and sighted controls. Furthermore, in CB, a few participants showed uncoordinated orbital EPI signals between the two eyes, each correlated with activity in different brain networks. Our findings suggest a retained circuitry between motor cortex and eye movements in blind, but also a moderate reorganization due to the absence of visual input, and the inability of CB to control their eye movements or sense their positions.

PMID:39034499 | DOI:10.1111/ejn.16459

Prog Neuropsychopharmacol Biol Psychiatry. 2024 Jul 19:111088. doi: 10.1016/j.pnpbp.2024.111088. Online ahead of print.

ABSTRACT

BACKGROUND: Brain aging is a complex process that involves functional alterations in multiple subnetworks and brain regions. However, most previous studies investigating aging-related functional connectivity (FC) changes using resting-state functional magnetic resonance images (rs-fMRIs) have primarily focused on the linear correlation between brain subnetworks, ignoring the nonlinear casual properties of fMRI signals.

METHODS: We introduced the neural Granger causality technique to investigate the sex-dependent nonlinear Granger connectivity (NGC) during aging on a publicly available dataset of 227 healthy participants acquired cross-sectionally in Leipzig, Germany.

RESULTS: Our findings indicate that brain aging may cause widespread declines in NGC at both regional and subnetwork scales. These findings exhibit high reproducibility across different network sparsities, demonstrating the efficacy of static and dynamic analysis strategies. Females exhibit greater heterogeneity and reduced stability in NGC compared to males during aging, especially the NGC between the visual network and other subnetworks. Besides, NGC strengths can well reflect the individual cognitive function, which may therefore work as a sensitive metric in cognition-related experiments for individual-scale or group-scale mechanism understanding.

CONCLUSION: These findings indicate that NGC analysis is a potent tool for identifying sex-dependent brain aging patterns. Our results offer valuable perspectives that could substantially enhance the understanding of sex differences in neurological diseases in the future, especially in degenerative disorders.

PMID:39033955 | DOI:10.1016/j.pnpbp.2024.111088