Most recent paper

Differences in resting-state brain networks and gray matter between APOE ε2 and APOE ε4 carriers in non-dementia elderly

Mon, 08/28/2023 - 18:00

Front Psychiatry. 2023 Aug 10;14:1197987. doi: 10.3389/fpsyt.2023.1197987. eCollection 2023.

ABSTRACT

BACKGROUND: Apolipoprotein E (APOE) ε2 and APOE ε4 are the most distinct alleles among the three APOE alleles, both structurally and functionally. However, differences in cognition, brain function, and brain structure between the two alleles have not been comprehensively reported in the literature, especially in non-demented elderly individuals.

METHODS: A neuropsychological test battery was used to evaluate the differences in cognitive performance in five cognitive domains. Independent component analysis (ICA) and voxel-based morphometry (VBM) were used separately to analyze resting-state functional magnetic resonance imaging (rs-fMRI) data and the structure MRI data between the two groups. Finally, correlations between differential brain regions and neuropsychological tests were calculated.

RESULTS: APOE ε2 carriers had better cognitive performance in general cognitive, memory, attention, and executive function than APOE ε4 carriers (all p < 0.05). In ICA analyses of rs-fMRI data, the difference in the resting-state functional connectivity (rsFC) between two groups is shown in 7 brain networks. In addition, VBM analyses of the T1-weighted image revealed that APOE ε2 carriers had a larger thalamus and right postcentral gyrus volume and a smaller bilateral putamen volume than APOE ε4 carriers. Finally, differences in brain function and structure may be might be the reason that APOE ε2 carriers are better than APOE ε4 carriers in cognitive performance.

CONCLUSION: These findings suggest that there are significant differences in brain function and structure between APOE ε2 carriers and APOE ε4 carriers, and these significant differences are closely related to their cognitive performance.

PMID:37636817 | PMC:PMC10449453 | DOI:10.3389/fpsyt.2023.1197987

Effects of the SNAP-25 Mnll variant on hippocampal functional connectivity in children with attention deficit/hyperactivity disorder

Mon, 08/28/2023 - 18:00

Front Hum Neurosci. 2023 Aug 10;17:1219189. doi: 10.3389/fnhum.2023.1219189. eCollection 2023.

ABSTRACT

OBJECTIVES: Attention-deficit/hyperactivity disorder (ADHD) is one of the most widespread and highly heritable neurodevelopmental disorders affecting children worldwide. Although synaptosomal-associated protein 25 (SNAP-25) is a possible gene hypothesized to be associated with working memory deficits in ADHD, little is known about its specific impact on the hippocampus. The goal of the current study was to determine how variations in ADHD's SNAP-25 Mnll polymorphism (rs3746544) affect hippocampal functional connectivity (FC).

METHODS: A total of 88 boys between the ages of 7 and 10 years were recruited for the study, including 60 patients with ADHD and 28 healthy controls (HCs). Data from resting-state functional magnetic resonance imaging (rs-fMRI) and clinical information were acquired and assessed. Two single nucleotide polymorphisms (SNP) in the SNAP-25 gene were genotyped, according to which the study's findings separated ADHD patients into two groups: TT homozygotes (TT = 35) and G-allele carriers (TG = 25).

RESULTS: Based on the rs-fMRI data, the FC of the right hippocampus and left frontal gyrus was evaluated using group-based comparisons. The corresponding sensitivities and specificities were assessed. Following comparisons between the patient groups, different hippocampal FCs were identified. When compared to TT patients, children with TG had a lower FC between the right precuneus and the right hippocampus, and a higher FC between the right hippocampus and the left middle frontal gyrus.

CONCLUSION: The fundamental neurological pathways connecting the SNAP-25 Mnll polymorphism with ADHD via the FC of the hippocampus were newly revealed in this study. As a result, the hippocampal FC may further serve as an imaging biomarker for ADHD.

PMID:37635807 | PMC:PMC10447972 | DOI:10.3389/fnhum.2023.1219189

Immediate Effects of Anti-Spastic Epidural Cervical Spinal Cord Stimulation on Functional Connectivity of the Central Motor System in Patients with Stroke- and Traumatic Brain Injury-Induced Spasticity: A Pilot Resting-State Functional Magnetic...

Sat, 08/26/2023 - 18:00

Biomedicines. 2023 Aug 14;11(8):2266. doi: 10.3390/biomedicines11082266.

ABSTRACT

OBJECTIVE: Spinal cord stimulation (SCS) is one approach to the potential improvement of patients with post-stroke or post-traumatic spasticity. However, little is known about whether and how such interventions alter supraspinal neural systems involved in the pathogenesis of spasticity. This pilot study investigated whether epidural spinal cord stimulation at the level of the C3-C5 cervical segments, aimed at reducing spasticity, alters the patterns of functional connectivity of the brain.

METHODS: Eight patients with spasticity in the right limbs as a result of left cerebral hemisphere damage (due to hemorrhagic and ischemic stroke or traumatic and anoxic brain injury) were assessed with fMRI immediately before and immediately after short-term (1 to 6 days) test cervical epidural SCS therapy. Eight demographically and clinically comparable patients with spasticity in the right extremities due to a left hemisphere ischemic stroke and brain injury who received conventional therapy were examined as a control group. All patients also had paresis of one or two limbs and hyperreflexia.

RESULTS: After the SCS therapy, there were three main findings: (1) higher functional connectivity of the brainstem to the right premotor cortex and changes in functional connectivity between cortical motor areas, (2) increased functional connectivity between the right and left lateral nodes of the sensorimotor network, and (3) a positive correlation between decreased spasticity in the right leg and increased functional connectivity within the right hemisphere sensorimotor cortex. All these changes in functional connectivity occurred with a statistically significant decrease in spasticity, as assessed using the modified Ashworth scale. The control group showed no decrease in spasticity or increase in functional connectivity in any of the seeds of interest. On the contrary, a decrease in functional connectivity of the brainstem and right postcentral gyrus was observed in this group during the observation period.

CONCLUSIONS: We were thus able to detect intrinsic brain connectivity rearrangements that occurred during spasticity mitigation following short epidural SCS therapy.

SIGNIFICANCE: The clinical results obtained confirmed the efficacy of short-term anti-spastic SCS therapy. The obtained data on functional rearrangements of the central motor system may shed light on the mechanism of antispastic action of this procedure.

PMID:37626762 | DOI:10.3390/biomedicines11082266

Functional network structure supports resilience to memory deficits in cognitively normal older adults with amyloid-β pathology

Fri, 08/25/2023 - 18:00

Sci Rep. 2023 Aug 25;13(1):13953. doi: 10.1038/s41598-023-40092-x.

ABSTRACT

Older adults may harbor large amounts of amyloid-β (Aβ) pathology, yet still perform at age-normal levels on memory assessments. We tested whether functional brain networks confer resilience or compensatory mechanisms to support memory in the face of Aβ pathology. Sixty-five cognitively normal older adults received high-resolution resting state fMRI to assess functional networks, 18F-florbetapir-PET to measure Aβ, and a memory assessment. We characterized functional networks with graph metrics of local efficiency (information transfer), modularity (specialization of functional modules), and small worldness (balance of integration and segregation). There was no difference in functional network measures between older adults with high Aβ (Aβ+) compared to those with no/low Aβ (Aβ-). However, in Aβ+ older adults, increased local efficiency, modularity, and small worldness were associated with better memory performance, while this relationship did not occur Aβ- older adults. Further, the association between increased local efficiency and better memory performance in Aβ+ older adults was localized to local efficiency of the default mode network and hippocampus, regions vulnerable to Aβ and involved in memory processing. Our results suggest functional networks with modular and efficient structures are associated with resilience to Aβ pathology, providing a functional target for intervention.

PMID:37626094 | DOI:10.1038/s41598-023-40092-x

Ketamine-induced 1-Hz oscillation of spontaneous neural activity is not directly visible in the hemodynamics

Fri, 08/25/2023 - 18:00

Biochem Biophys Res Commun. 2023 Aug 18;678:102-108. doi: 10.1016/j.bbrc.2023.08.034. Online ahead of print.

ABSTRACT

The extent to which resting-state hemodynamics reflects the underlying neural activity is still under debate. Especially in the delta frequency band (0.5-4 Hz), it is unclear whether the hemodynamics can directly track the dynamics of underlying neural activity. Based on a recent report showing that ketamine administration induced a 1-Hz neural activity oscillation in the retrosplenial cortex, we conducted simultaneous recordings of the calcium signal and hemodynamics in mice and examined whether the hemodynamics tracked the oscillatory neural activity. Although we observed that the oscillation induced by ketamine appeared in the calcium signal, no sign of oscillation was detected in the simultaneously recorded hemodynamics. Consistently, there was a notable decrease in the correlation between simultaneously recorded calcium signal and hemodynamics. However, on a much longer time scale (10-60 min), we unexpectedly observed an ultraslow increase of hemodynamic signals specifically in the same cortical region exhibiting the neural activity oscillation. These results indicated that hemodynamics cannot track the 1-Hz oscillation in neural activity, although the presence of neural activity oscillation was detectable on a longer timescale. Such ultraslow hemodynamics may be useful for detecting abnormal neural activity induced by psychotic drugs or mental disorders.

PMID:37625269 | DOI:10.1016/j.bbrc.2023.08.034

Resting-state fMRI reveals changes within the anxiety and social avoidance circuitry of the brain in mice with psoriasis-like skin lesions

Fri, 08/25/2023 - 18:00

Exp Dermatol. 2023 Aug 25. doi: 10.1111/exd.14914. Online ahead of print.

ABSTRACT

Psoriasis is an autoimmune skin disease that often co-occurs with psychological morbidities such as anxiety and depression, and psychosocial issues also lead psoriasis patients to avoid other people. However, the precise mechanism underlying the comorbidity of psoriasis and anxiety is unknown. Also, whether the social avoidance phenomenon seen in human patients also exists in psoriasis-like animal models remains unknown. In the present study, anxiety-like behaviours and social avoidance-like behaviours were observed in an imiquimod-induced psoriasis-like C57-BL6 mouse model along with typical psoriasis-like dermatitis and itch-like behaviours. The 11.7T resting-state functional magnetic resonance imaging showed differences in brain regions between the model and control group, and voxel-based morphometry showed that the grey matter volume changed in the basal forebrain region, anterior commissure intrabulbar and striatum in the psoriasis-like mice. Seed-based resting state functional connectivity analysis revealed connectivity changes in the amygdala, periaqueductal gray, raphe nuclei and lateral septum. We conclude that the imiquimod-induced psoriasis-like C57-BL6 mouse model is well suited for mechanistic studies and for performing preclinical therapeutic trials for treating anxiety and pathological social avoidance in psoriasis patients.

PMID:37622736 | DOI:10.1111/exd.14914

Neural representation of collective self-esteem in resting-state functional connectivity and its validation in task-dependent modality

Thu, 08/24/2023 - 18:00

Neuroscience. 2023 Aug 22:S0306-4522(23)00367-6. doi: 10.1016/j.neuroscience.2023.08.017. Online ahead of print.

ABSTRACT

INTRODUCTION: Collective self-esteem (CSE) is an important personality variable, defined as self-worth derived from membership in social groups. A study explored the neural basis of CSE using a task-based functional magnetic resonance imaging (fMRI) paradigm; however, task-independent neural basis of CSE remains to be explored, and whether the CSE neural basis of resting-state fMRI is consistent with that of task-based fMRI is unclear.

METHODS: We built support vector regression (SVR) models to predict CSE scores using topological metrics measured in the resting-state functional connectivity network (RSFC) as features. Then, to test the reliability of the SVR analysis, the activation pattern of the identified brain regions from SVR analysis was used as features to distinguish collective self-worth from other conditions by multivariate pattern classification in task-based fMRI dataset.

RESULTS: SVR analysis results showed that leverage centrality successfully decoded the individual differences in CSE. The ventromedial prefrontal cortex, anterior cingulate cortex, posterior cingulate gyrus, precuneus, orbitofrontal cortex, posterior insula, postcentral gyrus, inferior parietal lobule, temporoparietal junction, and inferior frontal gyrus, which are involved in self-referential processing, affective processing, and social cognition networks, participated in this prediction. Multivariate pattern classification analysis found that the activation pattern of the identified regions from the SVR analysis successfully distinguished collective self-worth from relational self-worth, personal self-worth and semantic control.

CONCLUSION: Our findings revealed CSE neural basis in the whole-brain RSFC network, and established the concordance between leverage centrality and the activation pattern (evoked during collective self-worth task) of the identified regions in terms of representing CSE.

PMID:37619767 | DOI:10.1016/j.neuroscience.2023.08.017

Study protocol: effects of treatment expectation toward repetitive transcranial magnetic stimulation (rTMS) in major depressive disorder-a randomized controlled clinical trial

Thu, 08/24/2023 - 18:00

Trials. 2023 Aug 24;24(1):553. doi: 10.1186/s13063-023-07579-4.

ABSTRACT

BACKGROUND: Patients' expectations toward any given treatment are highly important for the effectiveness of such treatment, as has been demonstrated for several disorders. In particular, in major depressive disorder (MDD), one of the most frequent and most serious mental disorders with severe consequences for the affected, the augmentation of available treatment options could mean a ground-breaking success. Repetitive transcranial magnetic stimulation (rTMS), a new, non-invasive, and well-tolerated intervention with proven effects in the treatment of MDD, appears particularly suitable in this context as it is assumed to exert its effect via structures implicated in networks relevant for both expectation and depression.

METHODS: All patients will receive rTMS according to its approval. Half of the patients will be randomized to a psychological intervention, which is a comprehensive medical consultation aiming to improve positive treatment expectations; the control group will receive a conventional informed consent discussion (in the sense of a treatment-as-usual condition). As outcome parameters, instruments for both self-assessment and external assessment of depression symptoms will be applied. Furthermore, psycho-immunological parameters such as inflammation markers and the cortisol awakening response in saliva will be investigated. Resting-state functional magnetic resonance imaging (rs fMRI) will be performed to analyze functional connectivity, including the cerebellum, and to identify neuronal predictors of expectation effects. In addition, possible cerebellar involvement will be assessed based on a cerebellar-dependent motor learning paradigm (i.e., eyeblink conditioning).

DISCUSSION: In this study, the effects of treatment expectations towards rTMS are investigated in patients with MDD. The aim of this study is to identify the mechanisms underlying the expectation effects and, beyond that, to expand the potential of non-invasive and well-tolerated treatments of MDD.

TRIAL REGISTRATION: German Registry of Clinical Studies (DRKS DRKS00028017. Registered on 2022/03/07. URL: https://www.drks.de/drks_web/ .

PMID:37620946 | DOI:10.1186/s13063-023-07579-4

Individualized assessment of brain Aβ deposition with fMRI using deep learning

Thu, 08/24/2023 - 18:00

IEEE J Biomed Health Inform. 2023 Aug 24;PP. doi: 10.1109/JBHI.2023.3306460. Online ahead of print.

ABSTRACT

PET-based Alzheimer's disease (AD) assessment has many limitations in large-scale screening. Non-invasive techniques such as resting-state functional magnetic resonance imaging (rs-fMRI) have been proven valuable in early AD diagnosis. This study investigated feasibility of using rs-fMRI, especially functional connectivity (FC), for individualized assessment of brain amyloid-β deposition derived from PET. We designed a Graph Convolutional Networks (GCNs) and random forest (RF) based integrated framework for using rs-fMRI-derived multi-level FC networks to predict amyloid-β PET patterns with the OASIS-3 (N = 258) and ADNI-2 (N = 291) datasets. Our method achieved satisfactory accuracy not only in Aβ-PET grade classification (for negative, intermediate, and positive grades, with accuracy in the three-class classification as 62.8% and 64.3% on two datasets, respectively), but also in prediction of whole-brain region-level Aβ-PET standard uptake value ratios (SUVRs) (with the mean square errors as 0.039 and 0.074 for two datasets, respectively). Model interpretability examination also revealed the contributive role of the limbic network. This study demonstrated high feasibility and reproducibility of using low-cost, more accessible magnetic resonance imaging (MRI) to approximate PET-based diagnosis.

PMID:37616143 | DOI:10.1109/JBHI.2023.3306460

Transdiagnostic indicators predict developmental changes in cognitive control resting-state networks

Thu, 08/24/2023 - 18:00

Dev Psychopathol. 2023 Aug 24:1-11. doi: 10.1017/S0954579423001013. Online ahead of print.

ABSTRACT

Over the past decade, transdiagnostic indicators in relation to neurobiological processes have provided extensive insight into youth's risk for psychopathology. During development, exposure to childhood trauma and dysregulation (i.e., so-called AAA symptomology: anxiety, aggression, and attention problems) puts individuals at a disproportionate risk for developing psychopathology and altered network-level neural functioning. Evidence for the latter has emerged from resting-state fMRI studies linking mental health symptoms and aberrations in functional networks (e.g., cognitive control (CCN), default mode networks (DMN)) in youth, although few of these investigations have used longitudinal designs. Herein, we leveraged a three-year longitudinal study to identify whether traumatic exposures and concomitant dysregulation trigger changes in the developmental trajectories of resting-state functional networks involved in cognitive control (N = 190; 91 females; time 1 Mage = 11.81). Findings from latent growth curve analyses revealed that greater trauma exposure predicted increasing connectivity between the CCN and DMN across time. Greater levels of dysregulation predicted reductions in within-network connectivity in the CCN. These findings presented in typically developing youth corroborate connectivity patterns reported in clinical populations, suggesting there is predictive utility in using transdiagnostic indicators to forecast alterations in resting-state networks implicated in psychopathology.

PMID:37615120 | DOI:10.1017/S0954579423001013

Altered Spontaneous Brain Activity and Its Predictive Role in Patients with Central Retinal Artery Occlusion Using fMRI and Machine Learning

Thu, 08/24/2023 - 18:00

Int J Gen Med. 2023 Aug 18;16:3593-3601. doi: 10.2147/IJGM.S421215. eCollection 2023.

ABSTRACT

OBJECTIVE: To investigate spontaneous neuronal activity changes in patients with central retinal artery occlusion (CRAO) using the resting-state functional magnetic resonance imaging (fMRI) and detect whether these brain functional alterations can represent an objective biomarker of clinical response using a machine learning algorithm.

METHODS: Eighteen patients with CRAO and eighteen healthy controls (HCs) were recruited. The regional homogeneity (ReHo) method of resting-state fMRI was conducted to evaluate the synchronous brain activity alterations between two groups. Differences of ReHo values between two groups were compared using the independent two-sample t-test. The support vector machine algorithm was to distinguish patients of CRAO from HCs based on the two groups' whole-brain ReHo patterns. The accuracy, sensitivity, and specificity for the classification were calculated. The classification performance was evaluated using the non-parametric permutation test.

RESULTS: Compared to HCs, individuals with CRAO showed significantly lower ReHo in the right cerebellum and precuneus. Meanwhile, significant higher ReHo values were observed in the left superior temporal gyrus, postcentral gyrus, and precentral gyrus in the CRAO group compared to HCs. Furthermore, our results suggested that 77.78% individuals with CRAO could be successfully distinguished from HCs by the machine learning, with a sensitivity of 72.22% and a specificity of 83.33%, respectively. The area of receiver operating characteristic curve was calculated to be 0.85.

CONCLUSION: This study uncovered individuals with CRAO exhibited disturbed synchronous neuronal activities in multiple brain areas using neuroimaging techniques. The ReHo variability could distinguish individuals with CRAO from HCs with high accuracy.

PMID:37614555 | PMC:PMC10443681 | DOI:10.2147/IJGM.S421215

A deep learning framework for identifying Alzheimer's disease using fMRI-based brain network

Thu, 08/24/2023 - 18:00

Front Neurosci. 2023 Aug 8;17:1177424. doi: 10.3389/fnins.2023.1177424. eCollection 2023.

ABSTRACT

BACKGROUND: The convolutional neural network (CNN) is a mainstream deep learning (DL) algorithm, and it has gained great fame in solving problems from clinical examination and diagnosis, such as Alzheimer's disease (AD). AD is a degenerative disease difficult to clinical diagnosis due to its unclear underlying pathological mechanism. Previous studies have primarily focused on investigating structural abnormalities in the brain's functional networks related to the AD or proposing different deep learning approaches for AD classification.

OBJECTIVE: The aim of this study is to leverage the advantages of combining brain topological features extracted from functional network exploration and deep features extracted by the CNN. We establish a novel fMRI-based classification framework that utilizes Resting-state functional magnetic resonance imaging (rs-fMRI) with the phase synchronization index (PSI) and 2D-CNN to detect abnormal brain functional connectivity in AD.

METHODS: First, PSI was applied to construct the brain network by region of interest (ROI) signals obtained from data preprocessing stage, and eight topological features were extracted. Subsequently, the 2D-CNN was applied to the PSI matrix to explore the local and global patterns of the network connectivity by extracting eight deep features from the 2D-CNN convolutional layer.

RESULTS: Finally, classification analysis was carried out on the combined PSI and 2D-CNN methods to recognize AD by using support vector machine (SVM) with 5-fold cross-validation strategy. It was found that the classification accuracy of combined method achieved 98.869%.

CONCLUSION: These findings show that our framework can adaptively combine the best brain network features to explore network synchronization, functional connections, and characterize brain functional abnormalities, which could effectively detect AD anomalies by the extracted features that may provide new insights into exploring the underlying pathogenesis of AD.

PMID:37614342 | PMC:PMC10442560 | DOI:10.3389/fnins.2023.1177424

Sleep dysfunction mediates the relationship between hypothalamic-insula connectivity and anxiety-depression symptom severity bidirectionally in young adults

Wed, 08/23/2023 - 18:00

Neuroimage. 2023 Aug 21:120340. doi: 10.1016/j.neuroimage.2023.120340. Online ahead of print.

ABSTRACT

BACKGROUND: The hypothalamus plays a crucial role in regulating sleep-wake cycle and motivated behavior. Sleep disturbance is associated with impairment in cognitive and affective functions. However, how hypothalamic dysfunction may contribute to inter-related sleep, cognitive, and emotional deficits remain unclear.

METHODS: We curated the Human Connectome Project dataset and investigated how hypothalamic resting state functional connectivities (rsFC) were associated with sleep dysfunction, as evaluated by the Pittsburgh Sleep Quality Index (PSQI), cognitive performance, and subjective mood states in 687 young adults (342 women). Imaging data were processed with published routines and evaluated with a corrected threshold. We examined the inter-relationship amongst hypothalamic rsFC, PSQI score, and clinical measures with mediation analyses.

RESULTS: In whole-brain regressions with age and drinking severity as covariates, men showed higher hypothalamic rsFC with the right insula in correlation with PSQI score. No clusters were identified in women at the same threshold. Both hypothalamic-insula rsFC and PSQI score were significantly correlated with anxiety and depression scores in men. Further, mediation analyses showed that PSQI score mediated the relationship between hypothalamic-insula rsFC and anxiety/depression symptom severity bidirectionally in men.

CONCLUSIONS: Sleep dysfunction is associated with negative emotions and hypothalamic rsFC with the right insula, a core structure of the interoceptive circuits. Notably, anxiety-depression symptom severity and altered hypothalamic-insula rsFC are related bidirectionally by poor sleep quality. These findings are specific to men, suggesting potential sex differences in the neural circuits regulating sleep and emotional states that need to be further investigated.

PMID:37611815 | DOI:10.1016/j.neuroimage.2023.120340

Prenatal Exposure to Maternal Mood Entropy is Associated with a Weakened and Inflexible Salience Network in Adolescence

Wed, 08/23/2023 - 18:00

Biol Psychiatry Cogn Neurosci Neuroimaging. 2023 Aug 21:S2451-9022(23)00215-X. doi: 10.1016/j.bpsc.2023.08.002. Online ahead of print.

ABSTRACT

BACKGROUND: Fetal exposure to maternal mood dysregulation influences child cognitive and emotional development with long-lasting implications for mental illness. Yet, the neurobiological alterations associated with this dimension of adversity have yet to be explored. Here, we tested the hypothesis that fetal exposure to entropy, a novel index of dysregulated maternal mood, predicts the integrity of the salience network, which is involved in emotional processing.

METHODS: A sample of 138 child-mother pairs (70 females) participated in this prospective longitudinal study. Maternal negative mood level and entropy (an index of variable and unpredictable mood) were assessed five times during pregnancy. Adolescents engaged in a fMRI task acquired between two resting-state scans. Changes in network integrity were analyzed using mixed effect and latent growth curve models. The amplitude of low frequency fluctuations (ALFF) was analyzed to corroborate findings.

RESULTS: Prenatal maternal mood entropy, but not mood level, was associated with salience network integrity. Both prenatal negative mood level and entropy were associated with ALFF of the salience network. Latent class analysis yielded two profiles based on changes in network integrity across all fMRI sequences. The profile that exhibited little variation in network connectivity (i.e., inflexibility) consisted of adolescents who were exposed to higher negative maternal mood levels and more entropy.

CONCLUSIONS: These findings suggest that fetal exposure to maternal mood dysregulation is associated with a weakened and inflexible salience network. More broadly, they identify maternal mood entropy as a novel marker of early adversity exhibiting long-lasting associations with offspring brain development.

PMID:37611745 | DOI:10.1016/j.bpsc.2023.08.002

Estimation of the density of veins from susceptibility-weighted imaging by using Mamdani fuzzy-type rule-based system. Investigating the neurovascular coupling in migraine

Wed, 08/23/2023 - 18:00

Neuroimage Clin. 2023 Aug 7;39:103489. doi: 10.1016/j.nicl.2023.103489. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: An impaired neurovascular coupling has been described as a possible player in neurodegeneration and cognitive decline. Migraine is a recurrent and incapacitating disorder that starts early in life and has shown neurovascular coupling abnormalities. Despite its high prevalence, the physiology and underlying mechanisms are poorly understood. In this context, new biomarkers from magnetic resonance imaging (MRI) are needed to bring new knowledge into the field. The aim of this study was to determine the vein density from Susceptibility-Weighted Imaging (SWI) MRI, in subjects with migraine and healthy controls; and to assess whether it relates to Resting-State functional MRI (RS-fMRI).

MATERIALS AND METHODS: The cohort included 30 healthy controls and 70 subjects with migraine (26 episodic, 44 chronic) who underwent a brain 3.0 T MRI. Clinical characteristics were also collected. Maps of density of veins were generated based on a Mamdani Fuzzy-Type Rule-Based System from the SWI MRI. Mean values of vein density were obtained in grey (GM) and white matter (WM) Freesurfer lobar parcellations. The Amplitude of Low-Frequency Fluctuations (ALFF) image was calculated for the RS-fMRI, and the mean values over the parcellated GM lobes were estimated. Differences between groups were assessed through and analysis of variance (age, sex, education and anxiety as covariates; p < 0.05), followed by post-hoc comparisons. Associations were run between clinical and MRI-derived variables.

RESULTS: When comparing the density of veins in GM, no differences between groups were found, neither associations with clinical variables. The density of veins was significantly higher in the WM of the occipital lobe for subjects with chronic migraine compared to controls (30%, p < 0.05). WM vein density in either frontal, temporal or cingulate regions was associated with clinical variables such as headache days, disability scores, and cognitive impairment (r between 0.25 and 0.41; p < 0.05). Mean values of ALFF did not differ significantly between controls and subjects with migraine. Strong significant associations between vein density and ALFF measures were obtained in most GM lobes for healthy subjects (r between 0.50 and 0.67; p < 0.05), instead, vein density in WM was significantly associated with ALFF for subjects with migraine (r between 0.32 and 0.58; p < 0.05).

CONCLUSIONS: Results point towards an increase in vein density in subjects with migraine, when compared to healthy controls. In addition, the association between GM vein density and ALFF found in healthy subjects was lost in migraine. Taken together, these results support the idea of abnormalities in the neurovascular coupling in migraine. Quantitative SWI MRI indicators in migraine might be an interesting target that may contribute to its comprehension.

PMID:37611372 | DOI:10.1016/j.nicl.2023.103489

Predicting phenotypes of elderly from resting state fMRI

Wed, 08/23/2023 - 18:00

Res Sq. 2023 Aug 7:rs.3.rs-3201603. doi: 10.21203/rs.3.rs-3201603/v1. Preprint.

ABSTRACT

Machine learning techniques are increasingly embraced in neuroimaging studies of healthy and diseased human brains. They have been used successfully in predicting phenotypes, or even clinical outcomes, and in turning functional connectome metrics into phenotype biomarkers of both healthy individuals and patients. In this study, we used functional connectivity characteristics based on resting state functional magnetic resonance imaging data to accurately classify healthy elderly in terms of their phenotype status. Additionally, as the functional connections that contribute to the classification can be identified, we can draw inferences about the network that is predictive of the investigated phenotypes. Our proposed pipeline for phenotype classification can be expanded to other phenotypes (cognitive, psychological, clinical) and possibly be used to shed light on the modifiable risk and protective factors in normative and pathological brain aging.

PMID:37609310 | PMC:PMC10441519 | DOI:10.21203/rs.3.rs-3201603/v1

Indirect evidence for altered dopaminergic neurotransmission in very premature-born adults

Wed, 08/23/2023 - 18:00

Hum Brain Mapp. 2023 Aug 22. doi: 10.1002/hbm.26451. Online ahead of print.

ABSTRACT

While animal models indicate altered brain dopaminergic neurotransmission after premature birth, corresponding evidence in humans is scarce due to missing molecular imaging studies. To overcome this limitation, we studied dopaminergic neurotransmission changes in human prematurity indirectly by evaluating the spatial co-localization of regional alterations in blood oxygenation fluctuations with the distribution of adult dopaminergic neurotransmission. The study cohort comprised 99 very premature-born (<32 weeks of gestation and/or birth weight below 1500 g) and 107 full-term born young adults, being assessed by resting-state functional MRI (rs-fMRI) and IQ testing. Normative molecular imaging dopamine neurotransmission maps were derived from independent healthy control groups. We computed the co-localization of local (rs-fMRI) activity alterations in premature-born adults with respect to term-born individuals to different measures of dopaminergic neurotransmission. We performed selectivity analyses regarding other neuromodulatory systems and MRI measures. In addition, we tested if the strength of the co-localization is related to perinatal measures and IQ. We found selectively altered co-localization of rs-fMRI activity in the premature-born cohort with dopamine-2/3-receptor availability in premature-born adults. Alterations were specific for the dopaminergic system but not for the used MRI measure. The strength of the co-localization was negatively correlated with IQ. In line with animal studies, our findings support the notion of altered dopaminergic neurotransmission in prematurity which is associated with cognitive performance.

PMID:37608591 | DOI:10.1002/hbm.26451

Improved processing speed and decreased functional connectivity in individuals with chronic stroke after paired exercise and motor training

Tue, 08/22/2023 - 18:00

Sci Rep. 2023 Aug 22;13(1):13652. doi: 10.1038/s41598-023-40605-8.

ABSTRACT

After stroke, impaired motor performance is linked to an increased demand for cognitive resources. Aerobic exercise improves cognitive function in neurologically intact populations and may be effective in altering cognitive function post-stroke. We sought to determine if high-intensity aerobic exercise paired with motor training in individuals with chronic stroke alters cognitive-motor function and functional connectivity between the dorsolateral prefrontal cortex (DLPFC), a key region for cognitive-motor processes, and the sensorimotor network. Twenty-five participants with chronic stroke were randomly assigned to exercise (n = 14; 66 ± 11 years; 4 females), or control (n = 11; 68 ± 8 years; 2 females) groups. Both groups performed 5-days of paretic upper limb motor training after either high-intensity aerobic exercise (3 intervals of 3 min each, total exercise duration of 23-min) or watching a documentary (control). Resting-state fMRI, and trail making test part A (TMT-A) and B were recorded pre- and post-intervention. Both groups showed implicit motor sequence learning (p < 0.001); there was no added benefit of exercise for implicit motor sequence learning (p = 0.738). The exercise group experienced greater overall cognitive-motor improvements measured with the TMT-A. Regardless of group, the changes in task score, and dwell time during TMT-A were correlated with a decrease in DLPFC-sensorimotor network functional connectivity (task score: p = 0.025; dwell time: p = 0.043), which is thought to reflect a reduction in the cognitive demand and increased automaticity. Aerobic exercise may improve cognitive-motor processing speed post-stroke.

PMID:37608062 | DOI:10.1038/s41598-023-40605-8

Altered Temporal Dynamics of Resting-State Functional Magnetic Resonance Imaging in Adolescent-Onset First-Episode Psychosis

Tue, 08/22/2023 - 18:00

Schizophr Bull. 2023 Aug 22:sbad107. doi: 10.1093/schbul/sbad107. Online ahead of print.

ABSTRACT

BACKGROUND: Dynamic functional connectivity (dFC) alterations have been reported in patients with adult-onset and chronic psychosis. We sought to examine whether such abnormalities were also observed in patients with first episode, adolescent-onset psychosis (AOP), in order to rule out potential effects of chronicity and protracted antipsychotic treatment exposure. AOP has been suggested to have less diagnostic specificity compared to psychosis with onset in adulthood and occurs during a period of neurodevelopmental changes in brain functional connections.

STUDY DESIGN: Seventy-nine patients with first episode, AOP (36 patients with schizophrenia-spectrum disorder, SSD; and 43 with affective psychotic disorder, AF) and 54 healthy controls (HC), aged 10 to 17 years were included. Participants underwent clinical and cognitive assessments and resting-state functional magnetic resonance imaging. Graph-based measures were used to analyze temporal trajectories of dFC, which were compared between patients with SSD, AF, and HC. Within patients, we also tested associations between dFC parameters and clinical variables.

STUDY RESULTS: Patients with SSD temporally visited the different connectivity states in a less efficient way (reduced global efficiency), visiting fewer nodes (larger temporal modularity, and increased immobility), with a reduction in the metabolic expenditure (cost and leap size), relative to AF and HC (effect sizes: Cohen's D, ranging 0.54 to.91). In youth with AF, these parameters did not differ compared to HC. Connectivity measures were not associated with clinical severity, intelligence, cannabis use, or dose of antipsychotic medication.

CONCLUSIONS: dFC measures hold potential towards the development of brain-based biomarkers characterizing adolescent-onset SSD.

PMID:37607335 | DOI:10.1093/schbul/sbad107

Robust hierarchically organized whole-brain patterns of dysconnectivity in schizophrenia spectrum disorders observed after personalized intrinsic network topography

Tue, 08/22/2023 - 18:00

Hum Brain Mapp. 2023 Aug 22. doi: 10.1002/hbm.26453. Online ahead of print.

ABSTRACT

BACKGROUND: Spatial patterns of brain functional connectivity can vary substantially at the individual level. Applying cortical surface-based approaches with individualized rather than group templates may accelerate the discovery of biological markers related to psychiatric disorders. We investigated cortico-subcortical networks from multi-cohort data in people with schizophrenia spectrum disorders (SSDs) and healthy controls (HC) using individualized connectivity profiles.

METHODS: We utilized resting-state and anatomical MRI data from n = 406 participants (n = 203 SSD, n = 203 HC) from four cohorts. Functional timeseries were extracted from previously defined intrinsic network subregions of the striatum, thalamus, and cerebellum as well as 80 cortical regions of interest, representing six intrinsic networks using (1) volume-based approaches, (2) a surface-based group atlas approaches, and (3) Personalized Intrinsic Network Topography (PINT).

RESULTS: The correlations between all cortical networks and the expected subregions of the striatum, cerebellum, and thalamus were increased using a surface-based approach (Cohen's D volume vs. surface 0.27-1.00, all p < 10-6 ) and further increased after PINT (Cohen's D surface vs. PINT 0.18-0.96, all p < 10-4 ). In SSD versus HC comparisons, we observed robust patterns of dysconnectivity that were strengthened using a surface-based approach and PINT (Number of differing pairwise-correlations: volume: 404, surface: 570, PINT: 628, FDR corrected).

CONCLUSION: Surface-based and individualized approaches can more sensitively delineate cortical network dysconnectivity differences in people with SSDs. These robust patterns of dysconnectivity were visibly organized in accordance with the cortical hierarchy, as predicted by computational models.

PMID:37605827 | DOI:10.1002/hbm.26453

Error | Forum of resting-state fMRI

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