Brain Changes Research Articles

Influence of individual's age on the characteristics of brain effective connectivity.

Given the increasing number of older adults in society, there is a growing need for studies on changes in the aging brain. The aim of this research is to investigate the effective connectivity of different age groups using resting-state functional magnetic resonance imaging (fMRI) and graph theory. By examining connectivity in different age groups, a better understanding of age-related changes can be achieved. Lifespan pilot data from the Human Connectome Project (HCP) were used to examine dynamic effective connectivity (dEC) changes across different age groups. The Granger causality method with time windowing was employed to calculate dEC. After extracting graph measures, statistical analyses were performed to compare the age groups. Support vector machine and decision tree classifiers were used to classify the different age groups based on the extracted graph measures. Based on the obtained results, it can be concluded that there are significant differences in the effective connectivity among the three age groups. Statistical analyses revealed disassortativity. The global efficiency exhibited a decreasing trend, and the transitivity measure showed an increasing trend with the advancing age. The decision tree classifier showed an accuracy of with Kruskal-Wallis selected features. This study demonstrates that changes in effective connectivity across different age brackets can serve as a tool for better understanding brain function during the aging process.

The brain and hypertension: how the brain regulates and suffers from blood pressure.

The brain plays several roles in the relationship between blood pressure (BP) and the brain: it acts as the control center for BP regulation, a target organ in hypertension, and a crucial component for cognitive function. This mini-review introduces recent findings on "brain and hypertension" from Hypertension Research and other journals. Activation of the angiotensin II type 1 receptor (AT1R) signaling pathway in the brain causes sympathoexcitation and hypertension. AT1R-associated protein and β-arrestin promote AT1R internalization and suppress AT1R signaling, with brain-specific roles in BP regulation. The brain receives various inputs from the peripheral system, including the heart and kidneys, and controls central sympathetic outflow. The brain mechanism involved in the enhanced cardiac sympathetic afferent reflex and the beneficial effects of renal denervation have been demonstrated. The brain's vulnerability in hypertension includes stroke, with cerebral small vessel disease (SVD) contributing to stroke risk and brain changes. Sex differences and the age of hypertension onset influence these outcomes. High salt intake exacerbates hypertension and stroke risk, with central mechanisms like sympathoexcitation implicated. Hypertension significantly impacts cognitive function, linking to cerebral SVD and cognitive decline. Orthostatic BP regulation abnormalities also emerge as early risk markers for dementia. Improved BP control in hypertensive individuals can significantly reduce the risk of stroke and cognitive decline, as well as cardiovascular disease, enhancing overall brain health and quality of life. Further understanding the brain's role in BP regulation and the pathogenesis of hypertension will facilitate the development of novel hypertension treatments and prevention strategies.

How the Paternal Brain Is Wired by Pregnancy.

This Viewpoint describes morphologic and functional changes in the paternal brain after childbirth.

TMET-13. SPATIAL METABOLOMIC CHANGES OF NUCLEOTIDE IN THE BRAINS OF ORTHOTOPIC MOUSE GLIOMA MODEL AFTER BORON NEUTRON CAPTURE THERAPY (BNCT)

Abstract Glioblastoma is the most lethal primary brain tumor. Boron Neutron Capture Therapy (BNCT) is a tumor-selective particle radiation therapy, in which high-LET α-particles and recoil 7Li are produced by the capture reaction between 10B and thermal neutrons and it has extended the prognosis of glioblastomas [Kawabata S, et al., Neuro-Oncology Advances 3(1), 1–9, 2021]. Augmented synthesis and use of nucleotide triphosphates is critical and universal metabolic dependency of tumor cells [Mullen, N.J., Singh, P.K. Nat Rev Cancer 23, 275–294 (2023)]. However, the effects of BNCT on metabolism of purine and pyrimidine in brain tumors and the surrounding normal brain are unknown. We spatially investigated metabolomic change in brains of orthotopic mouse glioma model, before and 2, 7, and 14 days after BNCT using mass spectrometry imaging (MSI). By separating tumor and non-tumor areas and performing Partial Least Squares Regression calculations, we have successfully visualized tumor-specific metabolites including adenine (ATP, ADP) and uridine (UTP, UDP-glucose, UDP-GlcNAc) with MSI. Of note, the signal of top-scored tumor specific metabolite, UDP-GlcNAc dramatically decreased and disappeared as the tumor regressed. Furthermore, the signal of ADP which was supposed to be released from tumor, colocalized with invading tumors along with corpus callosum. The value of adenylate energy charge, ([ATP]+0.5[ADP]/[ATP]+[ADP]+[AMP]) in the surrounding normal brain of the untreated tumor-bearing mouse increased up to 0.37 and decreased gradually down to 0.32 with BNCT, approaching to the value of normal control mouse brain, 0.27. These metabolomic changes reflected the tumor-killing effect and restoration of energy charge of surrounding normal brain by BNCT and have potential significance for development of biomarker or diagnosis.

Safety observation of COVID-19 inactivated vaccine in immature mice

Objective To investigate the safety of COVID-19 inactivated vaccine in immature mice. Methods We selected 3-week-old immature BALB/c mice, continuously observed until 7 weeks old after continuous immunization with fully inactivated vaccine (initial strengthening), and sacrificed BALB/c mice at 7 weeks old, and used H&E, Masson, mast cells and Ki-67 staining to analyze the changes of heart, liver, spleen, kidney, lung and brain. In addition, RNA was extracted from important organs such as the heart, liver, spleen, kidney, lung, and brain, and to evaluate whether there was any effect after vaccination through bulk-RNA sequencing. Results After H&E, Masson, mast cells and Ki-67 staining analyses, there are no significant differences between tissues and organs in the vaccine group and the PBS group, and RNA-Seq did not show that the vaccine had any effect on immature mice. Conclusion COVID-19 inactivated vaccine is safe in immature mice.

Prolonged exertion of self-control causes increased sleep-like frontal brain activity and changes in aggressivity and punishment

Impulsive reactions in social interactions may result in poor or even detrimental outcomes. Particular cognitive states, such as mental fatigue induced by extended practice with cognitively demanding activities, especially if combined with sleep restriction or deprivation, seem to impair the individuals' ability to exert self-control effectively and may result in impulsive behaviors, including aggressive acts. We demonstrate that exertion of self-control for as little as 45 min can lead to an increased propensity for engaging in aggressive acts in the context of socially relevant choices, as measured by a set of economic games. Also, we show that such behavioral changes are associated with increased sleep-like (delta) activity within frontal brain areas related to decision-making and impulse control. The local occurrence of sleep-like slow waves may lead to a disengagement of frontal areas and explain the reduced ability of individuals to exert self-control effectively. Our results suggest that sleep-like activity may emerge within the awake brain within a relatively short time scale, with detectable effects on socially relevant behavior.

Exploring the relationship among Alzheimer’s disease, aging and cognitive scores through neuroimaging-based approach

Alzheimer’s disease (AD) is a fatal neurodegenerative disorder, with the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating (CDR) serving significant roles in monitoring its progression. We hypothesize that while cognitive assessment scores can detect AD-related brain changes, the targeted brain regions may differ. Additionally, given AD’s strong association with aging, we propose that specific brain regions are influenced by both AD pathology and aging, exhibiting strong correlations with both. To test these hypotheses, we developed a 3D convolutional network with a mixed-attention mechanism to recognize AD subjects from structural magnetic resonance imaging (sMRI) data and utilize 3D convolutional methods to pinpoint brain regions significantly correlated with the AD, MMSE, CDR and age. All models were trained and internally validated on 417 samples from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), and the classification model was externally validated on 382 samples from the Australian Imaging and Lifestyle flagship (AIBL). This approach provided robust support for using MMSE and CDR in assessing AD progression and visually illustrated the relationship between aging and AD. The analysis revealed correlations among the four identification tasks (AD, MMSE, CDR and age) and highlighted asymmetric brain lesions in both AD and aging. Notably, we found that AD can accelerate aging to some extent, and a significant correlation exists between the rate of aging and cognitive assessment scores. This offers new insights into the relationship between AD and aging.

Connectome-based predictive modelling of ageing, overall cognitive functioning and memory performance.

Resting-state functional magnetic resonance imaging (rs-fMRI) and brain functional connectome (we use 'brain connectome' hereafter for simplicity) have advanced our understanding of the ageing brain and age-related changes in cognitive function. Previous studies have investigated the association among brain connectome and age, global cognition, and memory function separately. However, very few have predicted age, overall cognitive functioning and memory performance in a single study to better understand their complex relationship. In this cross-sectional study, we applied an exploratory, data-driven method to investigate the brain connectome markers that could predict ageing, overall cognitive functioning assessed as intelligence quotient (IQ, measured by Wechsler Memory Scale) and memory performance assessed as memory quotient (MQ, measured by Wechsler Memory Scale) in a carefully designed, multicentre, normal ageing cohort (n = 313). Our results showed that brain connectome could predict ageing and IQ, but the association with MQ was weak. We found that the connectivity with orbital frontal cortex was associated with both ageing and IQ. Mediation analysis further showed that the brain connectome mediated the relationship between age and overall cognitive functioning, suggesting a protective brain connectomic mechanism for maintaining normal cognitive functions during healthy ageing. This work may shed light on the potential neural correlates of healthy ageing, overall cognitive functioning and memory performance.

Changes in the functional connections of the brain in patients with hypersomnia in acute ischemic stroke

BACKGROUND: The Disorders of cerebral circulation and sleep are inextricably related, since sleep disorders, including hypersomnia, are closely intertwined with cardiovascular diseases and increase the risk of stroke. Research works on visualization of functional brain changes in patients with sleep disorders and acute ischemic stroke are very few and need more study. AIM: to determine the functional connections of the brain in hypersomnia in patients with acute ischemic stroke by performing functional magnetic resonance imaging at rest. A study of 40 patients with acute ischemic stroke and sleep disorders was performed on the basis of the Federal State Budgetary Institution Almazov Research Center of the Ministry of Health of the Russian Federation. All patients underwent neurological examination, assessment of sleepiness, worry and depression, magnetic resonance imaging was performed on tomographs with a magnetic field induction force of 1.5T, using a standard protocol and special pulse sequences of T-gradient echo 3D MPRAGE and BOLD. Functional magnetic resonance imaging of the brain at rest was used to assess functional connections. Postprocessing was performed using specialized CONN-TOOLBOX software with an appropriate graphical representation of quantitative results based on the selection of areas of interest. RESULTS: Among the examined patients, 23 had hypersomnolence; of these, 8 patients were diagnosed with secondary hypersomnia associated with sleep apnea syndrome. Thus, in the examined sample, post-stroke hypersomnolence was detected in 15 patients (34%). Patients with an unspecified subtype of stroke and right-sided lesions showed a high degree of drowsiness (p 0.05). With the help of functional magnetic resonance imaging of the brain at rest, changes in functional connections between the main nodes of the default mode network with the left temporal pole, cerebellum, central cerebral cortex on the left, angular gyrus on the left, with the dorsal attention network on the right are determined (p 0.05). CONCLUSION: The use of complex magnetic resonance imaging, which includes structural and functional magnetic resonance imaging in patients with acute ischemic stroke and sleep disorders, allows us to identify structural changes and changes in functional connectivity and identify neuroimaging markers of this pathology. Hypersomnolence is typical for patients with an unspecified subtype of ischemic stroke and damage to the right hemisphere of the brain.

Functional connectivity and cognitive decline: a review of rs-fMRI, EEG, MEG, and graph theory approaches in aging and dementia

Age-related changes in the brain cause cognitive decline and dementia. In recent year’s researchers’ extensively studied the relationship between age related changes in functional connectivity (FC) in dementia. Those studies explore the alterations in FC patterns observed in aging and neurodegenerative disorders using techniques such as resting-state functional magnetic resonance imaging (rs-fMRI), electroencephalography (EEG) coherence analysis, and graph theory approaches. The current review summarizes the findings, which highlight the impact of FC changes on cognitive decline and neurodegenerative disease progression using these techniques and emphasize the importance of understanding neural alterations for early detection and intervention. The findings underscore the complexity of cognitive aging and the need for further research to differentiate normal aging from pathological conditions. rs-fMRI is essential for studying brain changes associated with aging and pathology by capturing coherent fluctuations in brain activity during rest, providing insights into FC without task-related confounds. Key networks such as the default mode network and front parietal control network are crucial in revealing age-related connectivity changes. Despite challenges like neurovascular uncoupling and data complexity, ongoing advancements promise improved clinical applications of rs-fMRI in understanding cognitive decline across the lifespan. EEG and magnetoencephalography (MEG) are cost-effective techniques with high temporal resolution, allowing detailed study of brain rhythms and FC. Recent studies highlight EEG/MEG’s potential in early Alzheimer’s disease detection by identifying changes in brain connectivity patterns. Integration of machine learning techniques enhances diagnostic accuracy, although further validation and research are necessary. Graph theory offers a quantitative framework to analyze cognitive networks, identifying distinct topological differences between healthy aging and pathological conditions. Future research should expand exploration into diverse neurodegenerative disorders beyond mild cognitive impairment, integrating neuroimaging techniques to refine diagnostic precision and deepen insights into brain function and connectivity.

Cognitive decline in Cushing's syndrome: A systematic review.

The neurocognitive and psychiatric effects of Cushing's syndrome (CS) are well recognized and negatively impact quality of life. The aim of this systematic review is to compare neurocognitive disease, psychiatric symptoms, and structural brain changes in patients with Cushing's disease (CD)/CS and those with non-functioning pituitary adenoma (NFPA), both before and after surgical treatment, and in comparison to healthy controls. Possible predictors of persistent neurocognitive symptoms and reduced quality of life in patients with CS are highlighted. We reviewed the English literature published in Medline/Pubmed until 2021 to identify eligible studies. This systematic review was registered on Prospero and reported following the PRISMA statement guidelines. The initial literature search yielded 1772 articles, of which 1096 articles remained after removing duplicates. After excluding case reports, animal studies, narrative reviews, comparative reviews, and articles not in English, 86 papers underwent full-text review. Studies eligible for inclusion met the following criteria: (1) described patients with CD/CS, (2) reports of psychiatric symptoms, (3) written in English or with available English translation, and (4) published in a peer-reviewed journal. The full-text review process identified 40 eligible studies. The 40 studies included a total of 2603 participants with CD or CS, with 45.2% of the total participants having CD. The majority of studies were case-control studies and used validated questionnaires such as the Beck's Depression Index, Trail Making Test, Hospital Anxiety and Depression Scale, and Cushing Quality of Life for screening. Compared to NFPA controls, patients with CD who had greater baseline serum cortisol levels had worse cognitive function, even after surgical remission. This suggests a possible association between greater baseline cortisol levels in patients with CS and persistent cognitive impairment. A longer duration of uncontrolled CS was associated with worse cognitive function; however, there was no association found between the length of remission and memory. Overall brain volume was increased in patients in remission from CD compared to active disease. However, temporal and frontal lobe volumes did not recover to normal volumes. Patients with CS experience neurocognitive dysfunction, psychiatric disorders, and diminished quality of life, and symptoms may persist after curative surgery. We found several factors consistently associated with persistent cognitive and neuropsychiatric symptoms in patients with CS including higher pre-operatively baseline cortisol production, longer duration of disease, frontal and temporal lobe atrophy, and the presence of cognitive and neuropsychiatric symptoms at baseline. Larger prospective studies are required to validate these findings.

Magnetic resonance diffusion tensor imaging for detecting the cerebral microstructure changes in patients with CSVD -induced mild cognitive impairment.

Cerebral small vessel disease (CSVD)-induced mild cognitive impairment (MCI) has been linked to cognitive decline. Brain atrophy is considered the most common change in MCI patients, which can be measured by diffusion tensor imaging (DTI). The study aimed to explore the relationship between DTI parameters and cognitive function in CSVD patients with MCI. This retrospective analysis involved 185 patients with CSVD, comprising 87 cases with MCI and 98 cases without MCI (NMCI). Analyses of demographic and clinical characteristics were conducted. DTI-measured fractional anisotropy (FA) and mean diffusivity (MD) in the hippocampus and entorhinal cortex regions were examined. The diagnostic values were determined using receiver-operative-curve (ROC) analysis, with the Youden Index identifying optimum sensitivity and specificity. Correlations between Montreal cognitive assessment (MoCA) scores and FA or MD in MCI patients were further assessed. No significant differences were observed in demographic and clinical characteristics between MCI and NMCI groups (all p>0.05), except for diabetes prevalence (p=0.011). Notably, the ROC analysis highlighted the diagnostic potential of FA, showing the maximum area under the curve values (Hippocampus-Left: 0.76; Hippocampus-Right: 0.66; Entorhinal cortex-Left: 0.62; Entorhinal cortex-Right: 0.64). MD exhibited a significant negative correlation with MoCA scores (Hippocampus-Left: r=-0.58, p<0.001; Hippocampus-Right: r=-0.41, p<0.001; Entorhinal cortex-Left: r=-0.49, p<0.001; Entorhinal cortex-Right: r=-0.27, p<0.001), while FA showed a significant positive correlation (Hippocampus-Left: r=0.51, p<0.001; Hippocampus-Right: r=0.31, p=0.004; Entorhinal cortex-Left: r=0.35, p<0.001; Entorhinal cortex-Right: r=0.38, p<0.001). The study demonstrates the diagnostic value of DTI parameters in CSVD patients with MCI, emphasizing the associations between microstructural brain changes and cognitive function.

Change in striatal functional connectivity networks across 2 years due to stimulant exposure in childhood ADHD: results from the ABCD sample.

Widely prescribed for Attention-Deficit/Hyperactivity Disorder (ADHD), stimulants (e.g., methylphenidate) have been studied for their chronic effects on the brain in prospective designs controlling dosage and adherence. While controlled approaches are essential, they do not approximate real-world stimulant exposure contexts where medication interruptions, dosage non-compliance, and polypharmacy are common. Brain changes in real-world conditions are largely unexplored. To fill this gap, we capitalized on the observational design of the Adolescent Brain Cognitive Development (ABCD) study to examine effects of stimulants on large-scale bilateral cortical networks' resting-state functional connectivity (rs-FC) with 6 striatal regions (left and right caudate, putamen, and nucleus accumbens) across two years in children with ADHD. Bayesian hierarchical regressions revealed associations between stimulant exposure and change in rs-FC of multiple striatal-cortical networks, affiliated with executive and visuo-motor control, which were not driven by general psychotropic medication. Of these connections, three were selective to stimulants versus stimulant naive: reduced rs-FC between caudate and frontoparietal network, and between putamen and frontoparietal and visual networks. Comparison with typically developing children in the ABCD sample revealed stronger rs-FC reduction in stimulant-exposed children for putamen and frontoparietal and visual networks, suggesting a normalizing effect of stimulants. 14% of stimulant-exposed children demonstrated reliable reduction in ADHD symptoms, and were distinguished by stronger rs-FC reduction between right putamen and visual network. Thus, stimulant exposure for a two-year period under real-world conditions modulated striatal-cortical functional networks broadly, had a normalizing effect on a subset of networks, and was associated with potential therapeutic effects involving visual attentional control.

Distinct brain and neurocognitive transformations after bariatric surgery: a pilot study

BackgroundObese patients have worse outcomes after surgery and are at increased risk for perioperative neurocognitive disorders (PND). Our aim was to detail the cognitive trajectories of patients undergoing bariatric surgery (BS) and map distinct structural brain changes using magnetic resonance imaging (MRI) to better understand the association between the vulnerable brain, surgery, and the arc of PND.MethodsProspective pilot study with longitudinal comprehensive cognitive assessments and MRI were performed on obese patients scheduled for BS. We analyzed baseline cognitive function and high-resolution T1-/T2-weighted brain images on 19 obese patients [age, 54 (9) years, BMI, 40 (36, 42) kg m−2] and compared with 50 healthy control subjects [age, 52 (6) years; BMI, 25 (24, 27) kg m−2]. Patients were evaluated within five days of BS (baseline), immediately after (within 48h), and follow up at six months.ResultsAt baseline, obese patients had significant brain tissue changes seen in MRI and decreased cognitive scores compared to controls (MoCA 26 vs 28, P = 0.017). Surgery induced further gray matter volume and brain tissue changes along with reduced cognitive scores within the immediate postoperative period (MoCA 26 vs 24, P &amp;lt; 0.001). At six months, we observed reversal of brain alterations for most patients and a concomitant rebound of cognitive scores to patient’s baseline status.ConclusionsBariatric surgery resulted in worsening of preexisting brain structural integrity and lower cognitive function for obese patients compared to baseline. These distinct brain lesions are consistent with specific domains of cognition. Most of these changes reverted to patient’s baseline condition within six months after surgery.

Volumetric Integrated Classification Index: An Integrated Voxel-Based Morphometry and Machine Learning Interpretable Biomarker for Post-Traumatic Stress Disorder.

PTSD is a complex mental health condition triggered by individuals' traumatic experiences, with long-term and broad impacts on sufferers' psychological health and quality of life. Despite decades of research providing partial understanding of the pathobiological aspects of PTSD, precise neurobiological markers and imaging indicators remain challenging to pinpoint. This study employed VBM analysis and machine learning algorithms to investigate structural brain changes in PTSD patients. Data were sourced ADNI-DoD database for PTSD cases and from the ADNI database for healthy controls. Various machine learning models, including SVM, RF, and LR, were utilized for classification. Additionally, the VICI was proposed to enhance model interpretability, incorporating SHAP analysis. The association between PTSD risk genes and VICI values was also explored through gene expression data analysis. Among the tested machine learning algorithms, RF emerged as the top performer, achieving high accuracy in classifying PTSD patients. Structural brain abnormalities in PTSD patients were predominantly observed in prefrontal areas compared to healthy controls. The proposed VICI demonstrated classification efficacy comparable to the optimized RF model, indicating its potential as a simplified diagnostic tool. Analysis of gene expression data revealed significant associations between PTSD risk genes and VICI values, implicating synaptic integrity and neural development regulation. This study reveals neuroimaging and genetic characteristics of PTSD, highlighting the potential of VBM analysis and machine learning models in diagnosis and prognosis. The VICI offers a promising approach to enhance model interpretability and guide clinical decision-making. These findings contribute to a better understanding of the pathophysiological mechanisms of PTSD and provide new avenues for future diagnosis and treatment.

Biomarkers for cognitive impairment in alpha-synucleinopathies: an overview of systematic reviews and meta-analyses

Cognitive impairment (CI) is common in α-synucleinopathies, i.e., Parkinson’s disease, Lewy bodies dementia, and multiple system atrophy. We summarize data from systematic reviews/meta-analyses on neuroimaging, neurophysiology, biofluid and genetic diagnostic/prognostic biomarkers of CI in α-synucleinopathies. Diagnostic biomarkers include atrophy/functional neuroimaging brain changes, abnormal cortical amyloid and tau deposition, and cerebrospinal fluid (CSF) Alzheimer’s disease (AD) biomarkers, cortical rhythm slowing, reduced cortical cholinergic and glutamatergic and increased cortical GABAergic activity, delayed P300 latency, increased plasma homocysteine and cystatin C and decreased vitamin B12 and folate, increased CSF/serum albumin quotient, and serum neurofilament light chain. Prognostic biomarkers include brain regional atrophy, cortical rhythm slowing, CSF amyloid biomarkers, Val66Met polymorphism, and apolipoprotein-E ε2 and ε4 alleles. Some AD/amyloid/tau biomarkers may diagnose/predict CI in α-synucleinopathies, but single, validated diagnostic/prognostic biomarkers lack. Future studies should include large consortia, biobanks, multi-omics approach, artificial intelligence, and machine learning to better reflect the complexity of CI in α-synucleinopathies.

Transcutaneous Auricular Vagus Nerve Stimulation for Visually Induced Motion Sickness: An eLORETA Study

Transcutaneous auricular vagus nerve stimulation (taVNS), a non-invasive form of electrical brain stimulation, has shown potent therapeutic potential for a wide spectrum of conditions. How taVNS influences the characterization of motion sickness – a long mysterious syndrome with a polysymptomatic onset – remains unclear. Here, to examine taVNS-induced effects on brain function in response to motion-induced nausea, 64-channel electroencephalography (EEG) recordings from 42 healthy participants were analyzed; collected during nauseogenic visual stimulation concurrent with taVNS administration, in a crossover randomized sham-controlled study. Cortical neuronal generators were estimated from the obtained EEG using exact low-resolution brain electromagnetic tomography (eLORETA). While both sham and taVNS increased insula activation during electrical stimulation, compared to baseline, taVNS additionally augmented middle frontal gyrus neuronal activity. Following taVNS, brain regions including the supramarginal, parahippocampal, and precentral gyri were activated. Contrasting sham, taVNS markedly increased activity in the middle occipital gyrus during stimulation. A repeated-measures ANOVA showed that taVNS reduced motion sickness symptoms. This reduction in symptoms correlated with taVNS-induced neural activation. Our findings provide new insights into taVNS-induced brain changes, during and after nauseogenic stimuli exposure, including accompanying behavioral response. Together, these findings suggest that taVNS has promise as an effective neurostimulation tool for motion sickness management.

Functional brain changes in Mexican women with fibromyalgia

Fibromyalgia (FM) is a chronic condition marked by widespread pain, fatigue, sleep problems, cognitive decline, and other symptoms. Despite extensive research, the pathophysiology of FM remains poorly understood, complicating diagnosis and treatment, which often relies on self-report questionnaires. This study explored structural and functional brain changes in women with FM, identified potential biomarkers, and examined their relationship with FM severity. MRI data from 33 female FM patients and 33 matched healthy controls were utilized, focusing on T1-weighted MRI and resting-state fMRI scans. Functional connectivity (FC) analysis was performed using a machine learning framework to differentiate FM patients from healthy controls and predict FM symptom severity. No significant differences were found in brain structural features, such as gray matter volume, white matter volume, deformation-based morphometry, and cortical thickness. However, significant differences in FC were observed between FM patients and healthy controls, particularly in the default mode network (DMN), somatomotor network (SMN), visual network (VIS), and dorsal attention network (DAN). The FC metrics were significantly associated with FM severity. Our prediction model differentiated FM patients from healthy controls with an area under the curve of 0.65. FC measures accurately estimated FM symptom severities with a significant correlation (r = 0.45, p = 0.007). Functional connections in the DMN, VIS, and DAN were crucial in determining FM severity. These findings suggest that integrating brain FC measurements could serve as valuable biomarkers for identifying FM patients from healthy individuals and predicting FM symptom severity, improving diagnostic accuracy and facilitating the development of targeted therapeutic strategies.

Changes in thalamic functional connectivity in post-Covid patients with and without fatigue

BackgroundFunctional brain alterations in post-Covid-19 condition have been minimally explored to date. Here, we investigate differences in resting-state thalamic functional connectivity among post-Covid patients with and without fatigue, alongside structural brain changes and cognition. MethodsThirty-nine post-Covid patients (n=15 fatigued, n=24 non-fatigued) participated in our study, undergoing comprehensive cognitive assessments, as well as functional and structural neuroimaging. We conducted a seed-based functional connectivity analysis using the thalamus as a seed region, exploring its connectivity with the entire brain. To further elucidate our findings, correlation analyses were performed using the functional coupling between the thalamus and regions showing different connectivity between the two patient groups. ResultsOur results reveal that patients experiencing fatigue exhibit anti-correlated functional coupling between the thalamus and motor-associated regions, including the motor cortex (M1), supplementary motor area (SMA), and anterior cingulate cortex (ACC), compared to non-fatigued patients, who are showing positive functional coupling. Furthermore, this observed coupling was found to correlate with both the fatigue scores obtained from a fatigue questionnaire and performance on the Trail Making Test, Part A, which represents a measure of processing speed. ConclusionsOur study highlights significant differences in resting-state functional connectivity between post-Covid patients with and without fatigue, particularly within motor-associated brain regions. These findings suggest a potential neural mechanism underlying post-Covid fatigue and underscore the importance of considering both functional and structural brain changes in understanding the symptomatic sequelae of post-Covid-19 condition. Further research is warranted to provide insight into the longitudinal trajectories of these neural alterations.

Sleep quality and the integrity of ascending reticular activating system – A multimodal MRI study

Sleep is crucial for maintaining brain homeostasis and individuals with insufficient sleep are prone to more pronounced brain atrophy as compared to sufficiently sleeping peers. Moreover, sleep quality deteriorates with ageing and ageing is also associated with cerebral structural and functional changes, pointing to their mutual bidirectional interrelationship. This study aimed at determining whether sleep quality and age, separately, affect brain integrity and subsequently, whether sleep significantly modulates the effect of age on brain structural and functional integrity. 113 healthy volunteers underwent a multi-modal MRI imaging to extract information about the microstructure and function of major nodes of the ascending reticular activating system. Sleep quality was assessed by self-administered Pittsburgh's sleep quality index (PSQI) questionnaire. Subject were divided into good (global PSQI score <5) and poor (global PSQI score ≥5) sleep quality group. Whereas only borderline correlations were found between sleep quality and MRI metrics, age exhibited widespread correlations with both functional and microstructural MRI metrics. The latter effect was significantly modulated by sleep quality in ascending reticular activating system, hypothalamus, thalamus and also hippocampus in MRI metrics associated with iron load, cellularity and connectivity, mainly in the subgroup with poor sleep quality. Ergo, our results indicate sleep quality as a substantial contributor to both microstructural and functional brain changes in ageing and call for further research in this emerging topic.