Bilateral Hippocampus Research Articles

Disrupted Structural Brain Networks and Structural-Functional Decoupling in First-Episode Drug-Naïve Adolescent Major Depressive Disorder

PurposeMajor depressive disorder (MDD) tends to emerge during adolescence, but the neurobiology of adolescent MDD is still poorly understood. This study aimed to explore the topological organization of white matter structural networks and the relationship between structural and functional connectivity in adolescent MDD. MethodsStructural and functional magnetic resonance imaging data were acquired from 94 first-episode drug-naïve adolescent MDD patients and 78 healthy adolescents. Whole brain structural and functional brain networks were constructed for each subject. Then, the topological organization of structural brain networks and the coupling strength between structural and functional connectivity were analyzed. ResultsCompared with controls, adolescent MDD patients showed disrupted small-world, rich-club, and modular organizations. Nodal centralities in the medial part of bilateral superior frontal gyrus, bilateral hippocampus, right superior occipital gyrus, right angular gyrus, bilateral precuneus, left caudate nucleus, bilateral putamen, right superior temporal gyrus, and right temporal pole part of superior temporal gyrus were significantly lower in adolescent MDD patients compared with controls. The coupling strength between structural and functional connectivity was significantly lower in adolescent MDD patients compared with controls. DiscussionOur findings suggest widespread disruption of structural brain networks and structural-functional decoupling in adolescent MDD, potentially leading to reduced network communication capacity.

Functional connectivity changes of the hippocampal subregions in anti-N-methyl-D-aspartate receptor encephalitis.

The hippocampus plays an important role in the pathophysiological mechanism of Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis. Nevertheless, the connection between the resting-state activity of the hippocampal subregions and neuropsychiatric disorders in patients remains unclear. This study aimed to explore the changes in functional connectivity (FC) in the hippocampal subregions of patients with anti-NMDAR encephalitis and its association with clinical symptoms and cognitive performance. Twenty-three patients with anti-NMDAR encephalitis and 23 healthy controls (HC) were recruited. All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans and completed clinical cognitive scales. Based on the Brainnetome Atlas, the rostral (anterior) and caudal (posterior) hippocampi of both the left and right hemispheres were selected as regions of interest (ROIs) for FC analysis. First, a one-sample t-test was used to observe the whole-brain connectivity distribution of hippocampal subregions within the patient and HC groups at a threshold of p < 0.05. The two-sample t-test was used to compare the differences in hippocampal ROIs connectivity between groups, followed by a partial correlation analysis between the FC values of brain regions with statistical differences and clinical variables. This study observed that the distribution of whole-brain functional connectivity in the rostral and caudal hippocampi aligned with the connectivity differences between the anterior and posterior hippocampi. Compared to the HC group, the patients showed significantly decreased FC between the bilateral rostral hippocampus and the left inferior orbitofrontal gyrus and between the right rostral hippocampus and the right cerebellum. However, a significant increase in FC was observed between the right rostral hippocampus and left superior temporal gyrus, the left caudal hippocampus and right superior frontal gyrus, and the right caudal hippocampus and left gyrus rectus. Partial correlation analysis showed that FC between the left inferior orbitofrontal gyrus and the right rostral hippocampus was significantly negatively correlated with the California Verbal Learning Test (CVLT) and Brief Visuospatial Memory Test (BVMT) scores. The FC between the right rostral hippocampus and the left superior temporal gyrus was negatively correlated with BVMT scores. FC abnormalities in the hippocampal subregions of patients with anti-NMDAR encephalitis were associated with cognitive impairment, emotional changes, and seizures. These results may help explain the pathophysiological mechanisms and clinical manifestations of anti-NMDAR encephalitis and NMDAR dysfunction-related diseases such as schizophrenia.

Preliminary study on early diagnosis of Alzheimer's disease in APP/PS1 transgenic mice using multimodal magnetic resonance imaging.

Alzheimer's disease (AD) has an insidious onset and lacks clear early diagnostic markers, and by the time overt dementia symptoms appear, the disease is already in the mid-to-late stages. The search for early diagnostic markers of AD may open a critical window for Alzheimer's treatment and facilitate early intervention to slow the progression of AD. In this study, we aimed to explore the imaging markers for early diagnosis of AD through the combined application of structural magnetic resonance imaging (sMRI), resting-state functional magnetic resonance imaging (rs-fMRI), and 1H-magnetic resonance spectroscopy (1H-MRS) multimodal magnetic resonance imaging (MRI) techniques at the animal experimental level, with the aim to provide a certain reference for early clinical diagnosis of AD. First, sMRI scans were performed on 4-month-old amyloid beta precursor protein/presenilin 1 (APP/PS1) transgenic AD model mice and wild type mice of the same litter using a 7.0 T animal MRI scanner to analyze the differential brain regions with structural changes in the gray matter of the brain by voxel-based morphometry (VBM). Next, rs-fMRI scans were performed to analyze the differential brain regions between groups for local spontaneous brain activity and functional connectivity (FC) between brain regions. Finally, 1H-MRS scans were performed to quantify and analyze intergroup differences in the relative concentrations of different metabolites within regions of interest (cortex and hippocampus). Compared with wild type mice, the volume of the left hippocampus, and right olfactory bulb of APP/PS1 transgenic AD model mice were reduced, the functional activity of the bilateral hippocampus, right piriform cortex and right caudate putamen was reduced, the functional network connectivity of the hippocampus was impaired, and the relative content of N-acetylaspartate (NAA)in the hippocampus was decreased. In addition, this study found that imaging changes in olfactory-related brain regions were closely associated with AD diagnosis, and these findings may provide some reference for the early diagnosis of AD.

Alterations in cortical volume and complexity in Parkinson's disease with depression.

The aim of this study is to investigate differences in gray matter volume and cortical complexity between Parkinson's disease with depression (PDD) patients and Parkinson's disease without depression (PDND) patients. A total of 41 PDND patients, 36 PDD patients, and 38 healthy controls (HC) were recruited and analyzed by Voxel-based morphometry (VBM) and surface-based morphometry (SBM). Differences in gray matter volume and cortical complexity were compared using the one-way analysis of variance (ANOVA) and correlated with the Hamilton Depression Scale-17 (HAMD-17) scores. PDD patients exhibited significant cortical atrophy in various regions, including bilateral medial parietal-occipital-temporal lobes, right dorsolateral temporal lobes, bilateral parahippocampal gyrus, and bilateral hippocampus, compared to HC and PDND groups. A negative correlation between the GMV of left precuneus and HAMD-17 scores in the PDD group tended to be significant (r = -0.318, p = 0.059). Decreased gyrification index was observed in the bilateral insular and dorsolateral temporal cortex. However, there were no significant differences found in fractal dimension and sulcal depth. Our research shows extensive cortical structural changes in the insular cortex, parietal-occipital-temporal lobes, and hippocampal regions in PDD. This provides a morphological perspective for understanding the pathophysiological mechanism underlying depression in Parkinson's disease.

A nonhuman primate model with Alzheimer’s disease-like pathology induced by hippocampal overexpression of human tau

BackgroundAlzheimer’s disease (AD) is one of the most burdening diseases of the century with no disease-modifying treatment at this time. Nonhuman primates (NHPs) share genetic, anatomical, and physiological similarities with humans, making them ideal model animals for investigating the pathogenesis of AD and potential therapies. However, the use of NHPs in AD research has been hindered by the paucity of AD monkey models due to their long generation time, ethical considerations, and technical challenges in genetically modifying monkeys.MethodsHere, we developed an AD-like NHP model by overexpressing human tau in the bilateral hippocampi of adult rhesus macaque monkeys. We evaluated the pathological features of these monkeys with immunostaining, Nissl staining, cerebrospinal fluid (CSF) analysis, magnetic resonance imaging (MRI), positron emission tomography (PET), and behavioural tests.ResultsWe demonstrated that after hippocampal overexpression of tau protein, these monkeys displayed multiple pathological features of AD, including 3-repeat (3R)/4-repeat (4R) tau accumulation, tau hyperphosphorylation, tau propagation, neuronal loss, hippocampal atrophy, neuroinflammation, Aβ clearance deficits, blood vessel damage, and cognitive decline. More interestingly, the accumulation of both 3R and 4R tau is specific to NHPs but not found in adult rodents.ConclusionsThis work establishes a tau-induced AD-like NHP model with many key pathological and behavioural features of AD. In addition, our model may potentially become one of the AD NHP models adopted by researchers worldwide since it can be generated within 2 ~ 3 months through a single injection of AAVs into the monkey brains. Hence, our model NHPs may facilitate mechanistic studies and therapeutic treatments for AD.

Development of Efficient Brain Age Estimation Method Based on Regional Brain Volume From Structural Magnetic Resonance Imaging.

We aimed to create an efficient and valid predicting model which can estimate individuals' brain age by quantifying their regional brain volumes. A total of 2,560 structural brain magnetic resonance imaging (MRI) scans, along with demographic and clinical data, were obtained. Pretrained deep-learning models were employed to automatically segment the MRI data, which enabled fast calculation of regional brain volumes. Brain age gaps for each subject were estimated using volumetric values from predefined 12 regions of interest (ROIs): bilateral frontal, parietal, occipital, and temporal lobes, as well as bilateral hippocampus and lateral ventricles. A larger weight was given to the ROIs having a larger mean volumetric difference between the cognitively unimpaired (CU) and cognitively impaired group including mild cognitive impairment (MCI), and dementia groups. The brain age was predicted by adding or subtracting the brain age gap to the chronological age according to the presence or absence of the atrophy region. The study showed significant differences in brain age gaps among CU, MCI, and dementia groups. Furthermore, the brain age gaps exhibited significant correlations with education level and measures of cognitive function, including the clinical dementia rating sum-of-boxes and the Korean version of the Mini-Mental State Examination. The brain age that we developed enabled fast and efficient brain age calculations, and it also reflected individual's cognitive function and cognitive reserve. Thus, our study suggested that the brain age might be an important marker of brain health that can be used effectively in real clinical settings.

Gray matter covariations in autism: out-of-sample replication using the ENIGMA autism cohort

BackgroundAutism spectrum disorder (henceforth autism) is a complex neurodevelopmental condition associated with differences in gray matter (GM) volume covariations, as reported in our previous study of the Longitudinal European Autism Project (LEAP) data. To make progress on the identification of potential neural markers and to validate the robustness of our previous findings, we aimed to replicate our results using data from the Enhancing Neuroimaging Genetics Through Meta-Analysis (ENIGMA) autism working group.MethodsWe studied 781 autistic and 927 non-autistic individuals (6–30 years, IQ ≥ 50), across 37 sites. Voxel-based morphometry was used to quantify GM volume as before. Subsequently, we used spatial maps of the two autism-related independent components (ICs) previously identified in the LEAP sample as templates for regression analyses to separately estimate the ENIGMA-participant loadings to each of these two ICs. Between-group differences in participants’ loadings on each component were examined, and we additionally investigated the relation between participant loadings and autistic behaviors within the autism group.ResultsThe two components of interest, previously identified in the LEAP dataset, showed significant between-group differences upon regressions into the ENIGMA cohort. The associated brain patterns were consistent with those found in the initial identification study. The first IC was primarily associated with increased volumes of bilateral insula, inferior frontal gyrus, orbitofrontal cortex, and caudate in the autism group relative to the control group (β = 0.129, p = 0.013). The second IC was related to increased volumes of the bilateral amygdala, hippocampus, and parahippocampal gyrus in the autism group relative to non-autistic individuals (β = 0.116, p = 0.024). However, when accounting for the site-by-group interaction effect, no significant main effect of the group can be identified (p > 0.590). We did not find significant univariate association between the brain measures and behavior in autism (p > 0.085).LimitationsThe distributions of age, IQ, and sex between LEAP and ENIGMA are statistically different from each other. Owing to limited access to the behavioral data of the autism group, we were unable to further our understanding of the neural basis of behavioral dimensions of the sample.ConclusionsThe current study is unable to fully replicate the autism-related brain patterns from LEAP in the ENIGMA cohort. The diverse group effects across ENIGMA sites demonstrate the challenges of generalizing the average findings of the GM covariation patterns to a large-scale cohort integrated retrospectively from multiple studies. Further analyses need to be conducted to gain additional insights into the generalizability of these two GM covariation patterns.

Automatic detection of mild cognitive impairment based on deep learning and radiomics of MR imaging.

Early and rapid diagnosis of mild cognitive impairment (MCI) has important clinical value in improving the prognosis of Alzheimer's disease (AD). The hippocampus and parahippocampal gyrus play crucial roles in the occurrence of cognitive function decline. In this study, deep learning and radiomics techniques were used to automatically detect MCI from healthy controls (HCs). This study included 115 MCI patients and 133 normal individuals with 3D-T1 weighted MR structural images from the ADNI database. The identification and segmentation of the hippocampus and parahippocampal gyrus were automatically performed with a VB-net, and radiomics features were extracted. Relief, Minimum Redundancy Maximum Correlation, Recursive Feature Elimination and the minimum absolute shrinkage and selection operator (LASSO) were used to reduce the dimensionality and select the optimal features. Five independent machine learning classifiers including Support Vector Machine (SVM), Random forest (RF), Logistic Regression (LR), Bagging Decision Tree (BDT), and Gaussian Process (GP) were trained on the training set, and validated on the testing set to detect the MCI. The Delong test was used to assess the performance of different models. Our VB-net could automatically identify and segment the bilateral hippocampus and parahippocampal gyrus. After four steps of feature dimensionality reduction, the GP models based on combined features (11 features from the hippocampus, and 4 features from the parahippocampal gyrus) showed the best performance for the MCI and normal control subject discrimination. The AUC of the training set and test set were 0.954 (95% CI: 0.929-0.979) and 0.866 (95% CI: 0.757-0.976), respectively. Decision curve analysis showed that the clinical benefit of the line graph model was high. The GP classifier based on 15 radiomics features of bilateral hippocampal and parahippocampal gyrus could detect MCI from normal controls with high accuracy based on conventional MR images. Our fully automatic model could rapidly process the MRI data and give results in 1 minute, which provided important clinical value in assisted diagnosis.

Brain connectivity patterns associated with individual differences in the access to experience-near personal semantics: a resting-state fMRI study

It has been proposed that a continuum of specificity exists between episodic and semantic autobiographical memory. Personal semantics have been theorized to situate intermediately on this continuum, with more “experience-near” personal semantics (enPS) closer to the episodic end. We used individual differences in behavior as a model to investigate brain networks associated with the access to episodic autobiographical (EAM) and enPS information, assessing the relation between performance in the EAM and enPS conditions of the Autobiographical Fluency Task (AFT) and intrinsic brain connectivity. Results of an intrinsic connectivity contrast analysis showed that the global connectivity of two clusters in the left and right posterior cingulate cortex (PCC) was predicted by performance in the enPS conditions. Moreover, enPS scores predicted the connectivity strength of the right PCC with the bilateral anterior hippocampus (aHC), anterior middle temporal gyrus (aMTG) and medial orbitofrontal cortex, and the left aMTG and PCC. enPS scores also predicted the connectivity strength of the left PCC with the bilateral HC and MTG. The network highlighted involves parts of the core and of the dorsal medial subsystems of the Default Mode Network, in line with the proposal that enPS represents an intermediate entity between episodic and semantic memory.

Parallel cognitive maps for multiple knowledge structures in the hippocampal formation.

The hippocampal-entorhinal system uses cognitive maps to represent spatial knowledge and other types of relational information. However, objects can often be characterized by different types of relations simultaneously. How does the hippocampal formation handle the embedding of stimuli in multiple relational structures that differ vastly in their mode and timescale of acquisition? Does the hippocampal formation integrate different stimulus dimensions into one conjunctive map or is each dimension represented in a parallel map? Here, we reanalyzed human functional magnetic resonance imaging data from Garvert et al. (2017) that had previously revealed a map in the hippocampal formation coding for a newly learnt transition structure. Using functional magnetic resonance imaging adaptation analysis, we found that the degree of representational similarity in the bilateral hippocampus also decreased as a function of the semantic distance between presented objects. Importantly, while both map-like structures localized to the hippocampal formation, the semantic map was located in more posterior regions of the hippocampal formation than the transition structure and thus anatomically distinct. This finding supports the idea that the hippocampal-entorhinal system forms parallel cognitive maps that reflect the embedding of objects in diverse relational structures.

Hippocampal region metabolites and cognitive impairment in patients with general paresis: based on 1H-proton magnetic resonance spectroscopy.

This study utilizes Hydrogen proton magnetic resonance spectroscopy (1H-MRS) to investigate metabolite concentrations in the bilateral hippocampus of general paresis (GP) patients. A total of 80GP patients and 57 normal controls (NCs) were enrolled. Metabolite ratios in the bilateral hippocampus were measured using 1H-MRS. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Based on MMSE scores, participants were categorized into normal control, mild cognitive impairment, and moderate-severe dementia groups. Metabolite ratios (N-acetylaspartate (NAA)/creatine (Cr), choline (Cho)/creatine (Cr), N-acetylaspartate (NAA)/choline (Cho), myoinositol (MI)/creatine (Cr), choline (Cho)/N-acetylaspartate (NAA)) were compared between groups, and correlations between metabolite ratios and cognitive performance were examined. MMSE scores progressively decreased in the normal, mild cognitive impairment, and moderate-severe dementia groups (p < 0.001). The moderate-severe dementia group showed significantly lower NAA/Cr ratios in the left hippocampus region (L-NAA/Cr ratios) (p < 0.001) and higher Cho/NAA ratios in the left hippocampus region (L-Cho/NAA ratios) (p < 0.05) compared to the other groups. However, differences in L-NAA/Cr and L-Cho/NAA ratios between the mild cognitive impairment group and the NC group were not significant in the hippocampus region (p > 0.05). NAA/Cho and NAA/Cr ratios in the right hippocampus region (R-NAA/Cho and R-NAA/Cr ratios) in the moderate-severe dementia group were lower than those in the control group (p < 0.05). No correlation was found between metabolite ratios and MMSE scores in bilateral hippocampus regions. There are distinctive metabolic characteristics in the hippocampus of GP patients. GP patients exhibited lower NAA/Cr and NAA/Cho ratios in the bilateral hippocampus, indicating neuron loss in these areas, which may become more pronounced as the disease progresses.

Dosimetric comparison of hippocampal-sparing technologies in patients with low-grade glioma.

Radiotherapy (RT) plays an integral role in the management of low-grade gliomas (LGG). Late toxicity from RT can cause progressive neurocognitive dysfunction. Radiation-induced damage to the hippocampus (HCP) plays a considerable role in memory decline. Advancements in photon planning software have resulted in the development of multi-criteria optimization (MCO) and HyperArc technologies which may improve HCP sparing while maintaining planning target volume (PTV) target coverage. Three planning methods for hippocampal sparing (HS) were compared, volumetric modulated arc therapy (VMAT) without HS (VMAT_noHS), VMAT with HS (VMAT_HS), MCO with HS (MCO_HS), and HyperArc with HS (HyperArc_HS). Twenty-five patients were identified. The contralateral HCP was spared in 16 patients and bilateral HCP in 9 patients with superiorly located tumors. All 3 HS planning techniques showed significant reductions in dose to the spared HCP in contralateral cases but only VMAT_HS and MCO_HS achieved this in bilateral cases (P < .008). Only MCO_HS was superior to VMAT_HS in lowering the dose to both contralateral HCP and bilateral HCP in all measured metrics (P < .008). PTV and OAR (organ at risk) dose constraints were achieved for all plans. This retrospective dosimetric study demonstrated the feasibility of HS for low-grade glioma. All 3 HS planning techniques achieved significant dose reductions to the spared contralateral hippocampus, but only MCO_HS and VMAT_HS achieved this in bilateral cases. MCO was superior to other planning techniques for sparing both bilateral and contralateral hippocampi.

A systematic review of clinical efficacy and safety of cell-based therapies in Alzheimer's disease.

This study aspires to estimate the efficacy and safety of cell-based treatments in AD. Observing the Joanna Briggs Institute (JBI) methods and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, a systematic search was accomplished in PubMed, Medical Literature Analysis and Retrieval System Online (Medline, via Ovid), Embase; Cochrane, and Cumulative Index of Nursing and Allied Health Literature - CINAHL (via EBSCO) databases up to June 2023. The relevant clinical studies in which cell-based therapies were utilized to manage AD were included. The risk of bias was evaluated using the JBI checklists, based on the study designs. Out of 1,014 screened records, a total of five studies with 70 individuals (including 59 patients receiving stem cells and 11 placebo controls) were included. In all these studies, despite the discrepancy in the origin of stem cells, cell density, and transplant site, safety goals were obtained. The intracerebroventricular injection of adipose-derived stromal vascular fraction (ADSVF) and umbilical cord-derived mesenchymal stem cells (UC-MSCs), the intravenous injection of Lomecel-B, and the bilateral hippocampi and right precuneus injection of UC-MSCs are not linked to any significant safety concerns, according to the five included studies. Studies also revealed improvements in biomarkers and clinical outcomes as a secondary outcome. Three studies had no control groups and there are concerns regarding the similarity of the groups in others. Also, there is considerable risk of bias regarding the outcome assessment scales. Cell-based therapies are well tolerated by AD patients, which emphasizes the need for further, carefully planned randomized studies to reach evidence-based clinical recommendations in this respect.

Hippocampal volume and resting-state functional connectivity on magnetic resonance imaging in patients with Parkinson and depression.

Recent structural and functional imaging studies of depression in Parkinson disease (DPD) have failed to reveal the relevant mechanism, and relatively few studies have been conducted on limbic systems such as the hippocampus. This study thus aimed to gain new insights into the pathogenesis of DPD by detecting the changes in the hippocampal structure and the resting-state functional connectivity (FC) of patients with DPD. This study included 30 patients with DPD (DPD group), 30 patients with nondepressed Parkinson disease (NDPD; NDPD group), and 30 normal controls (NCs; NC group) with no significant age or gender differences with the DPD group. The Hamilton Depression Rating Scale (HAMD) and three-dimensional T1-weighted imaging and blood oxygen level-dependent imaging data of all patients were collected. The hippocampal volumes were measured using MATLAB software (MathWorks). The correlation between hippocampal volume and the HAMD score in the DPD group was analyzed with Pearson correlation coefficient. The bilateral hippocampi were used as the regions of interest and as the seed points for FC. FC analysis was performed between the preprocessed functional data of the whole brain and the two seed points with Data Processing Assistant for Resting-State and Statistical Parametric Mapping 8 software, respectively. The correlation between FC and HAMD scores in the patients with DPD was determined using partial correlation analysis. Compared with those in the NC group and the NDPD group, the bilateral hippocampal volumes in the DPD group were significantly decreased (P<0.05). There was a negative correlation between the bilateral hippocampal volume and the HAMD score in the DPD group (P<0.05). Compared with that of the NDPD group, the FC of the right hippocampus with the right occipital lobe and left precuneus was reduced in the DPD group. In the DPD group, the FC values of the right hippocampus, right occipital lobe, and left anterior cuneiform lobe were negatively correlated with HAMD scores. The volume of bilateral hippocampi in patients with DPD is significantly decreased and negatively correlated with the severity of depressive disorder. The weakened FC of the right hippocampus to the right occipital lobe and the left precuneus may play an important role in the neurological basis of DPD.

Patient with Foreign Accent Syndrome in Post Infarct Thrombotic Stroke: A Case Report

Background: Stroke is the second leading cause of death in the world and the leading cause of disability worldwide. One of the disabilities is language disorder. Foreign Accent Syndrome (FAS) is a clinical condition associated with a noticeable change of accent, affecting verbal communication and social interaction skills. By identifying this case earlier, we hope the patient’s daily living is less disrupted. Case: A 54-year-old woman came with complaints of weakness and tingling in the right limbs accompanied by a change in language accent. Weakness in the right limbs was felt since 4 years ago, then 1 year later the patient began to experience a change in the speech accent, from a Javanese accent to a Madurese accent, where previously the patient had never lived or studied Madurese. The results of the neurobehavior examination showed the patient had disturbances in the language and memory domain. MRI revealed cerebral infarction in the bilateral hippocampi, small vessel ischemic in the bilateral frontal lobes, and corona radiata. Discussion: The accent change, known as FAS experienced by the patients, is thought to be due to neurological causes, which was stroke. In a study using a lesion network mapping approach, it was concluded that the lesion causing accent disorder was located within a single network in the bilateral frontal lobe. In line with the existing theory, the MRI results in this patient showed ischemia in the blood vessels of the bilateral frontal lobes.

Multimodal neuroimaging in Long-COVID and its correlates with cognition 1.8 years after SARS-CoV-2 infection: a cross-sectional study of the Aliança ProHEpiC-19 Cognitiu.

There is a growing interest in the effect of Long-COVID (LC) on cognition, and neuroimaging allows us to gain insight into the structural and functional changes underlying cognitive impairment in LC. We used multimodal neuroimaging data in combination with neuropsychological evaluations to study cognitive complaints in a cohort of LC patients with mild to moderate severity symptoms. We conducted a 3T brain magnetic resonance imaging (MRI) study with diffusion tensor imaging (DTI) and functional MRI (fMRI) sequences on 53 LC patients 1.8 years after acute COVID-19 onset. We administered neuropsychological tests to evaluate cognitive domains and examined correlations with Tract-Based Spatial Statistics (TBSS) and resting state. We included 53 participants with LC (mean age, 48.23 years; 88.7% females). According to the Frascati criteria, more than half of the participants had deficits in the executive (59%) and attentional (55%) domains, while 40% had impairments in the memory domain. Only one participant (1.89%) showed problems in the visuospatial and visuoconstructive domain. We observed that increased radial diffusivity in different white matter tracts was negatively correlated with the memory domain. Our results showed that higher resting state activity in the fronto-parietal network was associated with lower memory performance. Moreover, we detected increased functional connectivity among the bilateral hippocampus, the right hippocampus and the left amygdala, and the right hippocampus and the left middle temporal gyrus. These connectivity patterns were inversely related to memory and did not survive false discovery rate (FDR) correction. People with LC exhibit cognitive impairments linked to long-lasting changes in brain structure and function, which justify the cognitive alterations detected.

Structural Neuroimaging and Molecular Signatures of Drug‐Naive Depression With Melancholic Features

Objectives: Melancholic depression (MD) is a common subtype of major depressive disorder (MDD). It is difficult to treat because its neurobiological basis is poorly understood. Therefore, to investigate whether MD patients have any structural changes in gray matter (GM) and the molecular foundation of these changes, we combined voxel‐based morphometry (VBM) analysis with neurotransmitter system‐derived mapping from public data.Methods: 137 drug‐naive MDD patients and 75 healthy controls (HCs) were recruited for structural magnetic resonance imaging. The imaging results were analyzed using VBM analysis. MDD patients were then divided into MD and nonmelancholic depression (NMD) subgroups according to their scores on the Montgomery–Asberg Depression Rating Scale (MADRS) and the Hamilton Depression Rating Scale. Next, we analyzed the spatial correlation between the changes in the gray matter volume (GMV) maps and the neurotransmitter receptor/transporter protein density maps provided by the JuSpace toolbox.Results: Compared to HCs, patients with MD had significant GMV reduction in the bilateral hippocampus, bilateral thalamus, right amygdala, and right posterior cingulate cortex (PCC)/precuneus. Compared to patients with NMD, MD patients had significant GMV reduction in the bilateral PCC/precuneus and lateral occipital cortex. Moreover, compared to HCs, changes in GMV introduced by MD were spatially associated with the serotonin transporter, cannabinoid receptor, and μ‐opioid receptor. Compared to NMD patients, changes in GMV introduced by MD were spatially associated with the vesicular acetylcholine transporter.Conclusion: The present study discovered abnormal GMV alterations in patients with subtypes of depression. We also found a series of neurotransmitter receptors that may be associated with the alterations. The findings of the current study may provide a more comprehensive understanding of the molecular mechanisms underlying the structural abnormalities in subtypes of depression and potentially offer new insights into developing new therapeutic strategies.

Functional magnetic resonance imaging alternations in suicide attempts individuals and their association with gene expression

BackgroundFunctional Magnetic Resonance Imaging (fMRI) has shown brain activity alterations in individuals with a history of attempted suicide (SA) who are diagnosed with depression disorder (DD) or bipolar disorder (BD). However, patterns of spontaneous brain activity and their genetic correlations need further investigation. MethodsA voxel-based meta-analysis of 19 studies including 26 datasets, involving 742 patients with a history of SA and 978 controls (both nonsuicidal patients and healthy controls) was conducted. We examined fMRI changes in SA patients and analyzed the association between these changes and gene expression profiles using data from the Allen Human Brain Atlas by partial least squares regression analysis. ResultsSA patients demonstrated increased spontaneous brain activity in several brain regions including the bilateral inferior temporal gyrus, hippocampus, fusiform gyrus, and right insula, and decreased activity in areas like the bilateral paracentral lobule and inferior frontal gyrus. Additionally, 5,077 genes were identified, exhibiting expression patterns associated with SA-related fMRI alterations. Functional enrichment analyses demonstrated that these SA-related genes were enriched for biological functions including glutamatergic synapse and mitochondrial structure. Concurrently, specific expression analyses showed that these genes were specifically expressed in the brain tissue, in neurons cells, and during early developmental periods. ConclusionOur findings suggest a neurobiological basis for fMRI abnormalities in SA patients with DD or BD, potentially guiding future genetic and therapeutic research.

Neurostructural Consequences of Obstetric Brachial Plexus Palsy in Childhood.

Obstetric brachial plexus palsy (OBPP) is a condition impairing limb function caused by birth injury. In 20 to 30% of cases, severe OBPP can cause life constraints in feeding, grooming, and clothing tasks. The present study, using voxel- and surface-based morphometry (VBM and SBM), examined the brain structure of pediatric OBPP patients to better understand the effects of this peripheral motor deficit on early brain development. Thirty-six T1-weighted images of 18 patients (2-17 years old, mean age = 11.3, 8 females) and 18 healthy controls (2-17 years old, mean age = 10.1, 8 females) were collected for this study. MRI data were processed and analyzed using the Statistical Parametric Mapping 12 (SPM12) toolbox. The custom pediatric tissue probability map was created with the CerebroMatic (COM) toolbox. The results were considered significant if they survived whole-brain family-wise error correction (P < .05). We have found differences in grey matter volumes in the bilateral anterior hippocampus (left P < .001 and right P = .01) and left cerebellum exterior (Crus I) (P < .001). We have also found differences in cortical thickness in the bilateral parahippocampal gyri (left P = .001 and right P = .005) and right orbitofrontal cortex (OFC) (P < .001). These structural differences might be linked to the altered environmental adaptation that children with OBPP face due to their primary motor deficit. Our findings hint at a complex interplay between motor capabilities, brain structure development, and cognitive functions. However, more research combining neuroimaging, behavioral, cognitive, and clinical data is needed to support stronger conclusions on this subject.

Geodesic shape regression based deep learning segmentation for assessing longitudinal hippocampal atrophy in dementia progression

Longitudinal hippocampal atrophy is commonly used as progressive marker assisting clinical diagnose of dementia. However, precise quantification of the atrophy is limited by longitudinal segmentation errors resulting from MRI artifacts across multiple independent scans. To accurately segment the hippocampal morphology from longitudinal 3T T1-weighted MR images, we propose a diffeomorphic geodesic guided deep learning method called the GeoLongSeg to mitigate the longitudinal variabilities that unrelated to diseases by enhancing intra-individual morphological consistency. Specifically, we integrate geodesic shape regression, an evolutional model that estimates smooth deformation process of anatomical shapes, into a two-stage segmentation network. We adopt a 3D U-Net in the first-stage network with an enhanced attention mechanism for independent segmentation. Then, a hippocampal shape evolutional trajectory is estimated by geodesic shape regression and fed into the second network to refine the independent segmentation. We verify that GeoLongSeg outperforms other four state-of-the-art segmentation pipelines in longitudinal morphological consistency evaluated by test–retest reliability, variance ratio and atrophy trajectories. When assessing hippocampal atrophy in longitudinal data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), results based on GeoLongSeg exhibit spatial and temporal local atrophy in bilateral hippocampi of dementia patients. These features derived from GeoLongSeg segmentation exhibit the greatest discriminatory capability compared to the outcomes of other methods in distinguishing between patients and normal controls. Overall, GeoLongSeg provides an accurate and efficient segmentation network for extracting hippocampal morphology from longitudinal MR images, which assist precise atrophy measurement of the hippocampus in early stage of dementia.