High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas

Persistent alterations in gray matter in COVID-19 patients experiencing sleep disturbances: a 3-month longitudinal study

JOURNAL/nrgr/04.03/01300535-202510000-00030/figure1/v/2024-11-26T163120Z/r/image-tiff Sleep disturbances are among the most prevalent neuropsychiatric symptoms in individuals who have recovered from severe acute respiratory syndrome coronavirus 2 infections. Previous studies have demonstrated abnormal brain structures in patients with sleep disturbances who have recovered from coronavirus disease 2019 (COVID-19). However, neuroimaging studies on sleep disturbances caused by COVID-19 are scarce, and existing studies have primarily focused on the long-term effects of the virus, with minimal acute phase data. As a result, little is known about the pathophysiology of sleep disturbances in the acute phase of COVID-19. To address this issue, we designed a longitudinal study to investigate whether alterations in brain structure occur during the acute phase of infection, and verified the results using 3-month follow-up data. A total of 26 COVID-19 patients with sleep disturbances (aged 51.5 ± 13.57 years, 8 women and 18 men), 27 COVID-19 patients without sleep disturbances (aged 47.33 ± 15.98 years, 9 women and 18 men), and 31 age- and gender-matched healthy controls (aged 49.19 ± 17.51 years, 9 women and 22 men) were included in this study. Eleven COVID-19 patients with sleep disturbances were included in a longitudinal analysis. We found that COVID-19 patients with sleep disturbances exhibited brain structural changes in almost all brain lobes. The cortical thicknesses of the left pars opercularis and left precuneus were significantly negatively correlated with Pittsburgh Sleep Quality Index scores. Additionally, we observed changes in the volume of the hippocampus and its subfield regions in COVID-19 patients compared with the healthy controls. The 3-month follow-up data revealed indices of altered cerebral structure (cortical thickness, cortical grey matter volume, and cortical surface area) in the frontal-parietal cortex compared with the baseline in COVID-19 patients with sleep disturbances. Our findings indicate that the sleep disturbances patients had altered morphology in the cortical and hippocampal structures during the acute phase of infection and persistent changes in cortical regions at 3 months post-infection. These data improve our understanding of the pathophysiology of sleep disturbances caused by COVID-19.

Electroconvulsive therapy-specific volume changes in nuclei of the amygdala and their relationship to long-term anxiety improvement in depression

Electroconvulsive therapy (ECT) is one of the most effective treatments for depression. ECT induces volume changes in the amygdala, a key center of anxiety. However, the clinical relevance of ECT-induced changes in amygdala volume remains uncertain. We hypothesized that nuclei-specific amygdala volumes and anxiety symptoms in depression could explain the clinical correlates of ECT-induced volume changes. To test this hypothesis, we enrolled patients with depression who underwent ECT (N = 20) in this multicenter observational study and collected MRI data at three time points: before and after treatment and a 6-month follow-up. Patients who received medication (N = 52), cognitive behavioral therapy (N = 63), or transcranial magnetic stimulation (N = 20), and healthy participants (N = 147) were included for comparison. Amygdala nuclei were identified using FreeSurfer and clustered into three subdivisions to enhance reliability and interpretability. Anxiety symptoms were quantified using the anxiety factor scores derived from the Hamilton Depression Rating Scale. Before treatment, basolateral and basomedial subdivisions of the right amygdala were smaller than those of healthy controls. The volumes of the amygdala subdivisions increased after ECT and decreased during the follow-up period, but the volumes at 6-month follow-up were larger than those observed before treatment. These volume changes were specific to ECT. Long-term volume changes in the right basomedial amygdala correlated with improvements in anxiety symptoms. Baseline volumes in the right basolateral amygdala correlated with long-term improvements in anxiety symptoms. These findings demonstrate that clinical correlates of ECT-induced amygdala volume changes are existent, but in a nucleus and symptom-specific manner.

Structural plasticity of the contralesional subfields of hippocampus and amygdala in patients with IDH-mutant astrocytoma and oligodendroglioma

PURPOSE

To detect the structural plasticity of the contralesional hippocampus and amygdala in patients with unilateral IDH-mutant astrocytoma and oligodendroglioma, and to compare the differences between these two types of tumors.

METHODS

3D T1-weighted MRI images were collected from 46 patients with left-hemispheric tumors (IDH-mutant astrocytoma, n = 22; oligodendroglioma, n = 24) and 23 healthy controls (HCs). Volumetric differences in the subregional volumes of the hippocampus and amygdala were assessed using FreeSurfer software. The differences were compared across groups.

RESULTS

In comparison to HCs, patients with unilateral IDH-mutant astrocytoma and oligodendroglioma exhibited a significantly larger volume of the hippocampal fissure in the contralesional hippocampus (p = 0.021, p = 0.041). In the astrocytoma group, volumetric increases were also observed in the contralesional amygdala subregions, including the medial-nucleus (p = 0.009), central-nucleus (p = 0.011), and cortical-nucleus (p = 0.039). Compared to the oligodendroglioma group, the astrocytoma group demonstrated significantly larger gray matter volume in the subiculum head (p = 0.008) of the contralesional hippocampus, as well as in the anterior amygdaloid area (AAA) (p = 0.044), central-nucleus (p = 0.025), and cortical-nucleus (p = 0.021) of the contralesional amygdala.

CONCLUSION

These findings provide robust evidence of macrostructural plasticity in the contralateral hippocampus and amygdala in patients with unilateral IDH-mutant astrocytomas and oligodendrogliomas. Furthermore, the structural differences between tumor types may reflect distinct effects on brain plasticity and variations in tumor invasiveness. These insights could contribute to optimization of clinical management strategies and personalized cognitive rehabilitation strategies for glioma patients.

Cross-ancestry and sex-stratified genome-wide association analyses of amygdala and subnucleus volumes

The amygdala is a small but critical multi-nucleus structure for emotion, cognition and neuropsychiatric disorders. Although genetic associations with amygdala volumetric traits have been investigated in sex-combined European populations, cross-ancestry and sex-stratified analyses are lacking. Here we conducted cross-ancestry and sex-stratified genome-wide association analyses for 21 amygdala volumetric traits in 6,923 Chinese and 48,634 European individuals. We identified 191 variant-trait associations (P < 2.38 × 10-9), including 47 new associations (12 new loci) in sex-combined univariate analyses and seven additional new loci in sex-combined and sex-stratified multivariate analyses. We identified 12 ancestry-specific and two sex-specific associations. The identified genetic variants include 16 fine-mapped causal variants and regulate amygdala and fetal brain gene expression. The variants were enriched for brain development and colocalized with mood, cognition and neuropsychiatric disorders. These results indicate that cross-ancestry and sex-stratified genetic association analyses may provide insight into the genetic architectures of amygdala and subnucleus volumes.

Multimodal magnetic resonance imaging analysis of early mild cognitive impairment

BackgroundEarly mild cognitive impairment (EMCI) represents a prodromal stage of dementia, and early detection is crucial for delaying dementia progression. However, accurately identifying its neuroimaging features remains challenging.ObjectiveTo comprehensively evaluate structural and functional neuroimaging changes in EMCI using multimodal magnetic resonance imaging (MRI) techniques.MethodsOne hundred and eleven participants were included from the Alzheimer's Disease Neuroimaging Initiative (ADNI): 36 with cognitively normal (CN), 30 with EMCI, 32 with late mild cognitive impairment (LMCI), and 13 with Alzheimer's disease (AD). FreeSurfer software was employed to segment hippocampal and amygdala subregions. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), and functional connectivity were processed using Data Processing & Analysis for Brain Imaging toolbox. Graph Theoretical Network Analysis toolbox was utilized to evaluate global functional network.ResultsThe volume of most hippocampal and amygdala subregions was decreased in AD group than those of EMCI group in structural MRI. Significant differences were found between EMCI and AD group in fALFF (right insula) and ReHo (bilateral caudate regions). EMCI group exhibited stronger functional connectivity between left hippocampus and right inferior temporal gyrus (compared to CN), left inferior temporal gyrus (compared to LMCI), and cerebellum crus 8 (compared to AD). EMCI group exhibited stronger connectivity between right hippocampus and left anterior cingulate gyrus compared to AD. Network metrics showed no significant differences among these groups, but all exhibited small-world properties.ConclusionsMultimodal MRI analysis revealed the neuroimaging characteristics of EMCI and promoted the understanding of the mechanisms underlying neuroimaging changes in EMCI.

Tau-PET pathology in the subregions of the amygdala and its associations with cognitive performance and neuropsychiatric symptoms in autosomal dominant Alzheimer's disease

BACKGROUND

The amygdala plays a role in behavior and emotional response and is vulnerable to Alzheimer's disease (AD) pathology, yet little is known about amygdala tau accumulation before clinical symptom onset. To investigate whether certain amygdala nuclei are particularly vulnerable to degeneration and might underlie early neuropsychiatric symptoms in AD, we aimed to characterize subregional amygdala tau pathology and its correlates associations with established biomarkers of early AD and cognitive-behavioral measures in Presenilin-1 E280A mutation carriers of autosomal dominant AD.

METHODS

Participants included 25 cognitively unimpaired mutation carriers and 37 non-carrier family members from the Colombia-Boston (COLBOS) Biomarker Study. Measures included 18F-flortaucipir, 11C-Pittsburgh compound B, Consortium to Establish a Registry for Alzheimer's Disease Word List Learning, Trail Making Test, Geriatric Depression Scale, and Geriatric Anxiety Inventory. We examined group differences in amygdala tau levels (whole amygdala, lateral nucleus and basal nucleus) and analyzed tau associations with disease markers and clinical measures.

RESULTS

Amygdala tau levels were higher in unimpaired carriers compared to non-carriers. Among carriers, the basal nucleus showed a greater tau burden than the lateral nucleus, and tau accumulation correlated with closer estimated age to clinical onset and increased cortical amyloid. Additionally, tau in both the basal and lateral amygdala was associated with poorer working memory, lower executive function and greater depressive symptoms. However, amygdala tau did not correlate with symptoms of anxiety. Notably, tau levels in the basal amygdala differentiated carriers from non-carriers, with higher predictive accuracy when neuropsychiatric measures were included.

CONCLUSIONS

These findings suggest that in autosomal dominant AD, tau accumulation in the amygdala begins early in the basal nucleus, while both the basal and the lateral nuclei are associated with early cognitive deficits and depressive symptoms. The nuclei's differential vulnerability to pathology underscores the importance of investigating tau spread within amygdala-associated networks, relative to the early clinical manifestations of AD. This study reinforces the potential of amygdala tau burden as a valuable biomarker for preclinical AD.

Linking birth experience and perinatal depression symptoms to neuroanatomical changes in hippocampus and amygdala

Childbirth is a life-changing event in a mother's life. While the transition to motherhood has recently been recognized as one of the most neuroplastic periods in adulthood, no study has yet explored whether the hippocampus and amygdala change during the peripartum in relation to childbirth experience and perinatal depression symptoms. In this longitudinal neuroimaging study, we assessed 88 first-time gestational mothers in late pregnancy and early postpartum and 30 nulliparous control women. We used optimized high-resolution MRI scans to quantify volumetric changes in the hippocampus and amygdala, along with their substructures. We found that increases in depression symptoms during the peripartum were positively correlated with changes in the right amygdala. A more challenging birth experience was associated with bilateral increases in hippocampal volume. These findings show that studying the neuroanatomical changes during the transition to motherhood can inform not only about adaptive processes but also about potential vulnerabilities, highlighting the importance of tracking perinatal experiences to enhance women's health.

Convolutional Neural Networks for the segmentation of hippocampal structures in postmortem MRI scans

BACKGROUND

The hippocampus plays a crucial role in memory and is one of the first structures affected by Alzheimer's disease. Postmortem MRI offers a way to quantify the alterations by measuring the atrophy of the inner structures of the hippocampus. Unfortunately, the manual segmentation of hippocampal subregions required to carry out these measures is very time-consuming.

NEW METHOD

In this study, we explore the use of fully automated methods relying on state-of-the-art Deep Learning approaches to produce these annotations. More specifically, we propose a new segmentation framework made of a set of encoder-decoder blocks embedding self-attention mechanisms and atrous spatial pyramidal pooling to produce better maps of the hippocampus and identify four hippocampal regions: the dentate gyrus, the hippocampal head, the hippocampal body, and the hippocampal tail.

RESULTS

Trained using slices extracted from 15 postmortem T1-weighted, T2-weighted, and susceptibility-weighted MRI scans, our new approach produces hippocampus parcellations that are better aligned with the manually delineated parcellations provided by neuroradiologists.

COMPARISON WITH EXISTING METHODS

Four standard deep learning segmentation architectures: UNet, Double UNet, Attention UNet, and Multi-resolution UNet have been utilized for the qualitative and quantitative comparison of the proposed hippocampal region segmentation model.

CONCLUSIONS

Postmortem MRI serves as a highly valuable neuroimaging technique for examining the effects of neurodegenerative diseases on the intricate structures within the hippocampus. This study opens the way to large sample-size postmortem studies of the hippocampal substructures.

Modulation mode of amygdala morphology and cognitive function under acute sleep deprivation in healthy male

The amygdala plays a crucial role in various behavioral functions and psychiatric conditions, with its morphology showing alterations in sleep disorders. While the impact of chronic sleep disorders on amygdala morphology has been studied, the effects of acute sleep deprivation (ASD) remain largely unexplored. The present study aimed to investigate the modulation between amygdala sub-region volumes and spatial working memory (SWM) performance under ASD conditions. Twenty-eight healthy male participants underwent MRI scanning and performed SWM tasks before and after 24 h of ASD. Amygdala sub-region volumes were segmented into nine sub-regions, and Granger causality analysis was employed to examine the relationship between amygdala morphology and SWM performance. Results revealed significant decreases in SWM accuracy and increases in reaction time following ASD. Localized changes in amygdala sub-regions were observed, with increased left cortico-amygdaloid transition area (CAT) volume and decreased right paralaminar nucleus (PL) volume. Granger causality analysis uncovered a bidirectional modulation between centromedial and cortical-like nuclei, and a progressive involvement of amygdala sub-regions in modulating SWM performance as task difficulty increased. These findings demonstrate a complex interplay between sleep, amygdala morphology, and cognitive function, suggesting that the amygdala plays a crucial role in modulating cognitive performance under ASD conditions. The differential involvement of amygdala sub-regions across varying cognitive loads indicates a flexible and adaptive system attempting to maintain performance in the face of sleep loss.

Multiple Neuropathologies Underly Hippocampal Subfield Atrophy in a Case With a Slowly Progressive Amnestic Syndrome: Challenging the Notion of Pure LATE-NC

Alzheimer's disease (AD) is the leading cause of dementia in the elderly, marked by abnormal protein buildup (beta-amyloid and tau) resulting in neuronal loss, especially in the medial temporal lobe and other limbic regions. The presence of transactive response DNA binding protein 43 (TDP-43) immunoreactive inclusions in medial temporal lobe regions has also been associated with neuroimaging changes in limbic regions. It has been proposed that hypometabolism in limbic regions on [18F] fluorodeoxyglucose positron emission tomography (FDG-PET) in a patient with a slowly evolving amnestic syndrome may be a signature of the presence of TDP-43. In this context, we observed an 86-year-old Caucasian female with dementia characterized by a slowly evolving amnestic syndrome, along with focal medial temporal atrophy evident on MRI and hypometabolism in limbic regions on FDG-PET. The patient subsequently died and underwent an autopsy. We performed detailed neuroimaging and digital neuropathological analyses of the hippocampal subfields to better understand the relationship between clinico-imaging findings and histopathology. In addition to TDP-43, we identified three other pathological processes in the medial temporal lobe: sequestosome-1/p62, argyrophilic grain disease (AGD), and primary age-related tauopathy (PART). Hippocampal subfield volumes and rates of atrophy were no different from those of matched healthy controls, except for the atrophy rate in cornu ammonis 1 (CA1). Digital histopathology revealed the relative highest burden of pathology for p62, followed by TDP-43, AGD, and PART in CA1. Multiple pathological processes appear to have contributed to the hippocampal atrophy and hypometabolism in our patient with a slowly progressive amnestic syndrome.

From histology to macroscale function in the human amygdala

The amygdala is a subcortical region in the mesiotemporal lobe that plays a key role in emotional and sensory functions. Conventional neuroimaging experiments treat this structure as a single, uniform entity, but there is ample histological evidence for subregional heterogeneity in microstructure and function. The current study characterized subregional structure-function coupling in the human amygdala, integrating post-mortem histology and in vivo MRI at ultra-high fields. Core to our work was a novel neuroinformatics approach that leveraged multiscale texture analysis as well as non-linear dimensionality reduction techniques to identify salient dimensions of microstructural variation in a 3D post-mortem histological reconstruction of the human amygdala. We observed two axes of subregional variation in this region, describing inferior-superior as well as mediolateral trends in microstructural differentiation that in part recapitulated established atlases of amygdala subnuclei. Translating our approach to in vivo MRI data acquired at 7 Tesla, we could demonstrate the generalizability of these spatial trends across 10 healthy adults. We then cross-referenced microstructural axes with functional blood-oxygen-level dependent (BOLD) signal analysis obtained during task-free conditions, and revealed a close association of structural axes with macroscale functional network embedding, notably the temporo-limbic, default mode, and sensory-motor networks. Our novel multiscale approach consolidates descriptions of amygdala anatomy and function obtained from histological and in vivo imaging techniques.

Longitudinal Magnetic Resonance Imaging in Asymptomatic C9orf72 Mutation Carriers Distinguishes Phenoconverters to Amyotrophic Lateral Sclerosis or Amyotrophic Lateral Sclerosis With Frontotemporal Dementia

OBJECTIVE

We prospectively studied asymptomatic C9orf72 mutation carriers, identifying those developing amyotrophic lateral sclerosis (ALS) or frontotemporal dementia (FTD).

METHODS

We enrolled 56 asymptomatic family members (AFM) with a C9orf72 mutation (AFM C9+), 132 non-carriers (AFM C9-), and 359 population-based controls. Using 3 T magnetic resonance imaging, we measured cortical thickness, gyrification, and subcortical volumes longitudinally. Linear mixed-effects models on non-converting AFM C9+ scans (n = 107) created a reference for these measurements, establishing individual atrophy patterns. Atrophy patterns from presymptomatic phenoconverters (n = 10 scans) served as a template for group comparisons and similarity assessments. Similarity with phenoconverters was quantified using Dice similarity coefficient (DSC) for cortical and Kullback-Leibler similarity (KLS) for subcortical measures. Using longitudinal similarity assessments, we predicted when participants would reach the average similarity level of phenoconverters at their first post-onset scan.

RESULTS

Five AFM C9+ converted to ALS or ALS-FTD. Up to 6 years before symptoms, these phenoconverters exhibited significant atrophy in frontal, temporal, parietal, and cingulate cortex, along with smaller thalamus, hippocampus, and amygdala compared to other AFM C9+. Some non-converted AFM C9+ had high DSC and KLS, approaching values of phenoconverters, whereas others, along with AFM C9- and controls, had lower values. At age 80, we predicted 27.9% (95% confidence interval, 13.2-40.1%) of AFM C9+ and no AFM C9- would reach the same DSC as phenoconverters.

INTERPRETATION

Distinctive atrophy patterns are visible years before symptom onset on presymptomatic scans of phenoconverters. Combining baseline and follow-up similarity measures may serve as a promising imaging biomarker for identifying those at risk of ALS or ALS-FTD. ANN NEUROL 2025;97:281-295.

Exploring individual differences in amygdala-mediated memory modulation

Amygdala activation by emotional arousal during memory formation can prioritize events for long-term memory. Building upon our prior demonstration that brief electrical stimulation to the human amygdala reliably improved long-term recognition memory for images of neutral objects without eliciting an emotional response, our study aims to explore and describe individual differences and stimulation-related factors in amygdala-mediated memory modulation. Thirty-one patients undergoing intracranial monitoring for intractable epilepsy were shown neutral object images paired with direct amygdala stimulation during encoding with recognition memory tested immediately and one day later. Adding to our prior sample, we found an overall memory enhancement effect without subjective emotional arousal at the one-day delay, but not at the immediate delay, for previously stimulated objects compared to not stimulated objects. Importantly, we observed a larger variation in performance across this larger sample than our initial sample, including some participants who showed a memory impairment for stimulated objects. Of the explored individual differences, the factor that most accounted for variability in memory modulation was each participant's pre-operative memory performance. Worse memory performance on standardized neuropsychological tests was associated with a stronger susceptibility to memory modulation in a positive or negative direction. Sex differences and the frequency of interictal epileptiform discharges (IEDs) during testing also accounted for some variance in amygdala-mediated memory modulation. Given the potential and challenges of this memory modulation approach, we discuss additional individual and stimulation factors that we hope will differentiate between memory enhancement and impairment to further optimize the potential of amygdala-mediated memory enhancement for therapeutic interventions.

The left amygdala is genetically sexually-dimorphic: multi-omics analysis of structural MRI volumes

Brain anatomy plays a key role in complex behaviors and mental disorders that are sexually divergent. While our understanding of the sex differences in the brain anatomy remains relatively limited, particularly of the underlying genetic and molecular mechanisms that contribute to these differences. We performed the largest study of sex differences in brain volumes (N = 33,208) by examining sex differences both in the raw brain volumes and after controlling the whole brain volumes. Genetic correlation analysis revealed sex differences only in the left amygdala. We compared transcriptome differences between males and females using data from GTEx and characterized cell-type compositions using GTEx bulk amygdala RNA-seq data and LIBD amygdala single-cell reference profiles. We also constructed polygenic risk scores (PRS) to investigate sex-specific genetic correlations between left amygdala volume and mental disorders (N = 25,576~105,318) of Psychiatric Genomics Consortium and other traits of UKB (N = 347,996). Although there were pronounced sex differences in brain volumes, there was no difference in the heritability between sexes. There was a significant sex-specific genetic correlation between male and female left amygdala. We identified sex-differentiated genetic effects of PRSs for schizophrenia on left amygdala volume, as well as significant sex-differentiated genetic correlations between PRSs of left amygdala and six traits in UKB. We also found several sex-differentially expressed genes in the amygdala. These findings not only advanced the current knowledge of genetic basis of sex differences in brain anatomy, but also presented an important clue for future research on the mechanism of sex differences in mental disorders and targeted treatments.

Evaluating conversion from mild cognitive impairment to Alzheimer's disease with structural MRI: a machine learning study

Alzheimer's disease is a disabling neurodegenerative disorder for which no effective treatment currently exists. To predict the diagnosis of Alzheimer's disease could be crucial for patients' outcome, but current Alzheimer's disease biomarkers are invasive, time consuming or expensive. Thus, developing MRI-based computational methods for Alzheimer's disease early diagnosis would be essential to narrow down the phenotypic measures predictive of cognitive decline. Amnestic mild cognitive impairment (aMCI) is associated with higher risk for Alzheimer's disease, and here, we aimed to identify MRI-based quantitative rules to predict aMCI to possible Alzheimer's disease conversion, applying different machine learning algorithms sequentially. At baseline, T1-weighted brain images were collected for 104 aMCI patients and processed to obtain 146 volumetric measures of cerebral grey matter regions [regions of interest (ROIs)]. One year later, patients were classified as converters (aMCI-c = 32) or non-converters, i.e. clinically and neuropsychologically stable (aMCI-s = 72) based on cognitive performance. Feature selection was performed by random forest (RF), and the identified seven ROIs volumetric data were used to implement support vector machine (SVM) and decision tree (DT) classification algorithms. Both SVM and DT reached an average accuracy of 86% in identifying aMCI-c and aMCI-s. DT found a critical threshold volume of the right entorhinal cortex (EC-r) as the first feature for differentiating aMCI-c/aMCI-s. Almost all aMCI-c had an EC-r volume <1286 mm3, while more than half of the aMCI-s patients had a volume above the identified threshold for this structure. Other key regions for the classification between aMCI-c/aMCI-s were the left lateral occipital (LOC-l), the middle temporal gyrus and the temporal pole cortices. Our study reinforces previous evidence suggesting that the morphometry of the EC-r and LOC-l best predicts aMCI to Alzheimer's disease conversion. Further investigations are needed prior to deeming our findings as a broadly applicable predictive framework. However, here, a first indication was derived for volumetric thresholds that, being easy to obtain, may assist in early identification of Alzheimer's disease in clinical practice, thus contributing to establishing MRI as a useful non-invasive prognostic instrument for dementia onset.

Investigating amygdala nuclei volumes in military personnel with post-traumatic stress disorder, major depressive disorder, and adjustment disorder: A retrospective cross-sectional study using clinical routine data

BACKGROUND

Post-traumatic Stress Disorder (PTSD), Major Depressive Disorder (MDD), and Adjustment Disorder (AdjD) are highly prevalent among military personnel, often presenting diagnostic challenges due to overlapping symptoms and reliance on self-reporting. The amygdala, particularly the basolateral complex involved in fear-related memory formation and extinction recall, plays a crucial role in emotional processing. Abnormalities in these amygdala nuclei are implicated in PTSD and may distinguish it from other disorders like MDD and AdjD, where these mechanisms are less central. Investigating structural differences in specific amygdala nuclei could enhance diagnostic precision and inform targeted interventions.

GOAL

This study aimed to explore volumetric differences in amygdala nuclei among patients with PTSD, MDD, comorbid PTSD and MDD (PTSD+MDD), and AdjD using routine clinical MRI data. We hypothesized that patients with PTSD would exhibit distinct amygdala nuclei volumes compared to those with MDD or AdjD. Additionally, we examined the influence of symptom duration, prior medication, and psychotherapeutic experience on amygdala volumes.

METHODS

We conducted a retrospective cross-sectional study with 185 military personnel (162 men, 23 women) diagnosed with PTSD (n = 50), MDD (n = 70), PTSD+MDD (n = 38), and AdjD (n = 27). High-resolution T1-weighted MRI scans were obtained using a 3T Siemens Skyra scanner. Amygdala subfields were automatically segmented and volumetrized using FreeSurfer software. Analysis of covariance (ANCOVA) models compared amygdala nuclei volumes across diagnostic groups, controlling for estimated total intracranial volume (eTIV), age, and gender. Exploratory analyses included symptom duration, medication use, and prior psychotherapy as additional covariates. Sensitivity analyses further examined the impact of depressive episode type (first vs. recurrent), severity (mild, moderate, severe), and AdjD symptom duration.

RESULTS

The main analyses revealed no significant differences in the volumes of the basolateral and medial amygdala nuclei among the PTSD, MDD, PTSD+MDD, and AdjD groups. Exploratory analyses did not identify significant associations between amygdala volumes and symptom duration, medication use, or prior psychotherapy. Sensitivity analyses also showed no significant volumetric differences related to depressive episode type, severity, or AdjD symptom duration.

CONCLUSION

Our findings suggest that, within this military population, amygdala nuclei volumes measured using routine clinical MRI data do not significantly differ among patients with PTSD, MDD, PTSD+MDD, and AdjD. This indicates that structural amygdala volumetry alone may not suffice to distinguish between these stress-related disorders in clinical settings. The study highlights the complexity of diagnosing overlapping mental health conditions and underscores the need for comprehensive approaches that integrate neuroimaging with clinical assessments. Future research should include healthy control groups, consider additional brain regions and functional connectivity, and employ longitudinal designs to better understand the temporal dynamics of amygdala changes and their relation to symptomatology.

Amygdala Nuclei Atrophy in Cognitive Impairment and Dementia: Insights from High-Resolution Magnetic Resonance Imaging

Background and Objectives: Cognitive impairment affects memory, reasoning, and problem-solving, with early detection being critical for effective management. The amygdala, a key structure in emotional processing and memory, may play a pivotal role in detecting cognitive decline. This study examines differences in amygdala nuclei volumes in patients with varying levels of cognitive performance to evaluate its potential as a biomarker. Material and methods: This cross-sectional study of 35 participants was conducted and classified into three groups: the normal (≥26), moderate (15-25), and low (≤14) cognitive performance groups based on the Montreal Cognitive Assessment (MoCA) scores. High-resolution magnetic resonance imaging at 3.0 T scanner was used to assess amygdala nuclei volumes. Results: Significant amygdala atrophy was observed in multiple amygdala nuclei across cognitive performance groups, with more pronounced changes in the low-performance group. The right hemisphere nuclei, including the lateral and basal nuclei, showed more significant differences, indicating their sensitivity to cognitive decline. Conclusions: This study highlights the potential of amygdala nuclei atrophy as a biomarker for cognitive impairment. Additional research with larger sample sizes and longitudinal designs is needed to confirm these findings and determine their diagnostic value.

Abnormal developmental of hippocampal subfields and amygdalar subnuclei volumes in young adults with heavy cannabis use: A three-year longitudinal study

BACKGROUND

Differences in the volumes of the hippocampus and amygdala have consistently been observed between young adults with heavy cannabis use relative to their non-using counterparts. However, it remains unclear whether the subfields of these functionally and structurally heterogenous regions exhibit similar patterns of change in young adults with long-term heavy cannabis use disorder (CUD).

OBJECTIVES

This study aims to investigate the effects of long-term heavy cannabis use in young adults on the subregional structures of the hippocampus and amygdala, as well as their longitudinal alterations.

METHODS

The study sample comprised 20 young adults with heavy cannabis use and 22 matched non-cannabis using healthy volunteers. All participants completed the Cannabis Use Disorder Identification Test (CUDIT) and underwent two T1-structural magnetic resonance imaging (MRI) scans, one at baseline and another at follow-up 3 years later. The amygdala, hippocampus, and their subregions were segmented on T1-weighted anatomical MRI scans, using a previously validated procedure.

RESULTS

At baseline, young adults with heavy CUD exhibited significantly larger volumes in several hippocampal (bilateral presubiculum, subiculum, Cornu Ammonis (CA) regions CA1, CA2-CA3, and right CA4-Dentate Gyrus (DG)) and amygdala (bilateral paralaminar nuclei, right medial nucleus, and right lateral nucleus) subregions compared to healthy controls, but these differences were attenuated at follow-up. Longitudinal analysis revealed an accelerated volumetric decrease in these subregions in young adults with heavy CUD relative to controls. Particularly, compared to healthy controls, significant accelerated volume decreases were observed in the right hippocampal subfields of the parasubiculum, subiculum, and CA4-DG. In the amygdala, similar trends of accelerated volumetric decreases were observed in the left central nucleus, right paralaminar nucleus, right basal nucleus, and right accessory basal nucleus.

CONCLUSIONS

The current findings suggest that long-term heavy cannabis use impacts maturational process of the amygdala and hippocampus, especially in subregions with high concentrations of cannabinoid type 1 receptors (CB1Rs) and involvement in adult neurogenesis.

Multiscale Analysis Reveals Hippocampal Subfield Vulnerabilities to Chronic Cortisol Overexposure: Evidence From Cushing's Disease

BACKGROUND

Chronic cortisol overexposure plays a significant role in the development of neuropathological changes associated with neuropsychiatric and neurodegenerative disorders. The hippocampus, the primary target of cortisol, may exhibit characteristic regional responses due to its internal heterogeneity. In this study, we explored structural and functional alterations of hippocampal (HP) subfields in Cushing's disease (CD), an endogenous model of chronic cortisol overexposure.

METHODS

Utilizing structural and resting-state functional magnetic resonance imaging data from 169 participants (86 patients with CD and 83 healthy control participants [HCs]) recruited from a single center, we investigated specific structural changes in HP subfields and explored the functional connectivity alterations driven by these structural abnormalities. We also analyzed potential associative mechanisms between these changes and biological attributes, neuropsychiatric representations, cognitive function, and gene expression profiles.

RESULTS

Compared with HCs, patients with CD exhibited significant bilateral volume reductions in multiple HP subfields. Notably, volumetric decreases in the left HP body and tail subfields were significantly correlated with cortisol levels, Montreal Cognitive Assessment scores, and quality of life measures. Disrupted connectivity between the structurally abnormal HP subfields and the ventromedial prefrontal cortex may impair reward-based decision making and emotional regulation, with this dysconnectivity being linked to structural changes in right HP subfields. Another region that exhibited dysconnectivity was located in the left pallidum and putamen. Gene expression patterns associated with synaptic components may underlie these macrostructural alterations.

CONCLUSIONS

Our findings elucidate the subfield-specific effects of chronic cortisol overexposure on the hippocampus, enhancing understanding of shared neuropathological traits linked to cortisol dysregulation in neuropsychiatric and neurodegenerative disorders.

Late-onset temporal lobe epilepsy: insights from brain atrophy and Alzheimer's disease biomarkers

Considering the growing age of the world population, the incidence of epilepsy in older adults is expected to increase significantly. It has been suggested that late-onset temporal lobe epilepsy (LO-TLE) may be neurodegenerative in origin and overlap with Alzheimer's disease (AD). Herein, we aimed to characterize the pattern of cortical atrophy and CSF biomarkers of AD (total and phosphorylated tau and amyloid-β) in a selected population of LO-TLE of unknown origin. We prospectively enrolled individuals with temporal lobe epilepsy onset after the age of 50 and no cognitive impairment. They underwent a structural MRI scan and CSF biomarkers measurement. Imaging and biomarkers data were compared to three retrospectively collected groups: (i) age-sex-matched healthy controls; (ii) patients with mild cognitive impairment (MCI) and abnormal CSF AD biomarkers (MCI-AD); and (iii) patients with MCI and normal CSF AD biomarkers (MCI-noAD). From a pool of 52 patients, 20 consecutive eligible LO-TLE patients with a mean disease duration of 1.8 years were recruited. As control populations, 25 patients with MCI-AD, 25 patients with MCI-noAD and 25 healthy controls were enrolled. CSF biomarkers returned normal values in LO-TLE, significantly different from patients with MCI due to AD. There were no differences in cortico-subcortical atrophy between epilepsy patients and healthy controls, while patients with MCI demonstrated widespread injuries of cortico-subcortical structures. Individuals with LO-TLE, characterized by short disease duration and normal CSF amyloid-β and tau protein levels, showed patterns of cortical thickness and subcortical volumes not significantly different from healthy controls, but highly different from patients with MCI, either due to AD or not.

Basolateral amygdala volume in affective disorders using 7T MRI in vivo

Background

The basolateral complex of the amygdala is a crucial neurobiological site for Pavlovian conditioning. Investigations into volumetric alterations of the basolateral amygdala in individuals with major depressive disorder (MDD) have yielded conflicting results. These may be reconciled in an inverted U-shape allostatic growth trajectory. This hypothesized trajectory unfolds with an initial phase of volumetric expansion, driven by enhanced dendritic arborization and synaptic plasticity. The increase in volume is followed by a reduction phase, as glucocorticoid exposure cumulatively results in excitotoxic damage, reflecting allostatic load.

Methods

7T magnetic resonance brain imaging was conducted on a total of 84 participants (mean age 38 ± 12 years), comprising 20 unmedicated and 20 medicated individuals with MDD, 21 individuals suffering from bipolar disorder and 23 healthy controls. We employed FreeSurfer 7.3.2 for automatic high-resolution segmentation of nine amygdala subnuclei. We conducted analyses of covariance, with volumes of the basolateral complex, the lateral nucleus and, exploratively, the whole amygdala, as dependent variables, while controlling for the total intracranial volume and sex. Quadratic regressions were computed within the MDD group and in relevant subgroups to investigate the presence of a U-shaped relationship between the number of preceding major depressive episodes or the duration of the disease since the first episode and the dependent variables.

Results

Diagnostic groups did not exhibit statistically significant differences in the volumes of the basolateral amygdala (left F (3,75) = 0.66, p >.05; right F (3,76) = 1.80, p >.05), the lateral nucleus (left F (3,75) = 1.22, p >.05; right F (3,76) = 2.30, p >.05)), or the whole amygdala (left F (3,75) = 0.48, p >.05; right F (3,76) = 1.58, p >.05). No quadratic associations were observed between surrogate parameters of disease progression and any of the examined amygdala volumes. There were no significant correlations between subregion volumes and clinical characteristics.

Conclusion

We found no evidence for the hypothesis of an inverted U-shaped volumetric trajectory of the basolateral amygdala in MDD. Future research with larger sample sizes, including the measurement of genetic and epigenetic markers, will hopefully further elucidate this compelling paradigm.

Voxel-Based Morphometry and Subfield Volumetry Analysis Reveal Limbic System Involvement in Tinnitus

BACKGROUND AND PURPOSE

Tinnitus is a condition in which individuals perceive sounds, such as ringing or buzzing, without any external source. Although the exact cause is not fully understood, recent studies have indicated the involvement of nonauditory brain structures, including the limbic system. We aimed to compare the volumes of specific brain structures between patients with tinnitus and controls.

METHODS

Voxel-based morphometry and subfield volumetry were applied to analyze the brain structures of 53 patients with tinnitus and 52 age- and sex-matched controls. The volumes of the amygdala, hippocampus, and thalamus were measured and compared between the groups.

RESULTS

Patients with tinnitus had larger volumes in the whole amygdala, basal nucleus, right lateral nucleus, and left paralaminar nucleus compared with controls. In addition, the subiculum head, left fimbria, and left presubiculum head in the hippocampus were larger in patients with tinnitus. No differences were found in the total thalamic volume or thalamic subnuclei between groups. The gray matter volumes in the thalamus, amygdala, and hippocampus were significantly high in the tinnitus group. The cortical thicknesses of both of the marginal branches of the cingulate sulcus, the left superior parietal lobule, and the left subparietal sulcus were also high in the tinnitus group.

CONCLUSIONS

These findings indicate the involvement of the limbic system in tinnitus, and enhance our understanding of the condition. The subfield volumetry technique used in this study may aid in identifying the structural differences associated with specific neurological and psychiatric conditions.

Differing Effects of Alcohol Use on Epigenetic and Brain Age in Adult Children of Parents with Alcohol Use Disorder

BACKGROUND

It is known that being the adult child of a parent with an alcohol use disorder (ACoA) can confer a wide variety of increased health and psychological risks, including higher rates of anxiety, depression, and post-traumatic stress disorder symptoms. Additionally, ACoAs are at greater risk of developing alcohol/substance use disorders (AUDs/SUDs) than individuals from families without a history of AUDs.

METHODS

ACoA individuals with risky hazardous alcohol use (n = 14) and those not engaged in hazardous use (n = 14) were compared to a group of healthy controls. We examined structural brain differences and applied machine learning algorithms to predict biological brain and DNA methylation ages to investigate differences and determine any accelerated aging between these groups.

RESULTS

Hazardous and non-hazardous ACoA groups had lower predicted brain ages than the healthy control group (n = 100), which may result from neuro-developmental differences between ACoA groups and controls. Within specific brain regions, we observed decreased cortical volume within bilateral pars orbitalis and frontal poles, and the left middle temporal gyrus and entorhinal cortex within the hazardous alcohol ACoA group. When looking at the epigenetic aging data, the hazardous ACoA participants had increased predicted epigenetic age difference scores compared to the control group (n = 34) and the non-hazardous ACoA participant groups.

CONCLUSIONS

The results demonstrate a decreased brain age in the ACoAs compared to control, concurrent with increased epigenetic age specifically in the hazardous ACoA group, laying the foundation for future research to identify individuals with an increased susceptibility to developing hazardous alcohol use. Together, these results provide a better understanding of the associations between epigenetic factors, brain structure, and alcohol use disorders.

Changes in hippocampal volume and affective functioning after a moderate intensity running intervention

This study examined the effects of a moderately intense seven-week running intervention on the hippocampal volume and depressive symptoms of young men (20-31 years of age) from the general population (N = 21). A within-subjects-design involving a two-week baseline period before the running intervention, and two subsequent intervention cycles was applied. At four time points of assessment (t1: start of the study; t2: end of baseline period/start of the intervention; t3: end of the first intervention cycle; t4: end of the 2nd intervention cycle/study end) magnetic resonance imaging was performed and symptoms related to depression were assessed employing the Center for Epidemiological Studies Depression (CES-D) Scale. The intervention resulted in a significant increase in the estimated maximum oxygen uptake (VO2max), measured with a standardized walking test (average increase from 42.07 ml*kg- 1*min- 1 to 46.07 ml*kg- 1*min- 1). The CES-D scores decreased significantly over the course of the running intervention (average decrease from 12.76 to 10.48 on a 20-point scale). Significant volumetric increases in the hippocampus were found, most notably after the first intervention cycle in the left (average increase from 613.41 mm³ to 620.55 mm³) and right hippocampal tail (average increase from 629.77 mm³ to 638.17 mm³). These findings provide new evidence regarding the temporal dynamics of hippocampal changes following engagement in physical activity.

Structural and covariance network alterations of the hippocampus and amygdala in congenital hearing loss children

OBJECTIVE

The hippocampus and amygdala, as important components of the limbic system, play crucial roles in central remodeling in congenital hearing loss. This study aimed to investigate the morphological integrity and network properties of the subfields of hippocampus and amygdala in children with congenital hearing loss.

METHODS

A total of 24 children with congenital hearing loss and 17 age- and sex- matched healthy controls (HC) are included in the study. T1-weighted images are analyzed by segmenting the brain into cortical and subcortical regions. Intergroup difference of volumes were explored. Structural covariance networks for the whole brain and hippocampus-amygdala subregions were constructed. Between-group differences of network property are investigated by comparing area under a range of network sparsity.

RESULTS

Patients with congenital hearing loss exhibited significantly larger volumes in the right dentate gyrus and CA3 of the hippocampus. However, there were no significant differences in total hippocampal or showed decreased global efficiency and increased characteristic path length, indicating reduced network integration. Lower betweenness centrality was observed in the left hippocampal fissure in the hearing loss group. The changes in volume and network topological properties are not affected by age and sex.

CONCLUSION

Children with congenital hearing loss display specific volumetric increases in hippocampal subregions, suggesting compensatory adaptations to auditory deprivation. The hippocampus-amygdala network shows significant reorganization, potentially underpinning cognitive and behavioral development issues associated with congenital hearing loss. These findings highlight the importance of targeted neural substrates in understanding and addressing the developmental challenges faced by children with congenital hearing loss.

Cannabis Dependence is Associated with Reduced Hippocampal Subregion Volumes Independently of Sex: Findings from an ENIGMA Addiction Working Group Multi-Country Study

Background: Males and females who consume cannabis can experience different mental health and cognitive problems. Neuroscientific theories of addiction postulate that dependence is underscored by neuroadaptations, but do not account for the contribution of distinct sexes. Further, there is little evidence for sex differences in the neurobiology of cannabis dependence as most neuroimaging studies have been conducted in largely male samples in which cannabis dependence, as opposed to use, is often not ascertained. Methods: We examined subregional hippocampus and amygdala volumetry in a sample of 206 people recruited from the ENIGMA Addiction Working Group. They included 59 people with cannabis dependence (17 females), 49 cannabis users without cannabis dependence (20 females), and 98 controls (33 females). Results: We found no group-by-sex effect on subregional volumetry. The left hippocampal cornu ammonis subfield 1 (CA1) volumes were lower in dependent cannabis users compared with non-dependent cannabis users (p<0.001, d=0.32) and with controls (p=0.022, d=0.18). Further, the left cornu ammonis subfield 3 (CA3) and left dentate gyrus volumes were lower in dependent versus non-dependent cannabis users but not versus controls (p=0.002, d=0.37, and p=0.002, d=0.31, respectively). All models controlled for age, intelligence quotient (IQ), alcohol and tobacco use, and intracranial volume. Amygdala volumetry was not affected by group or group-by-sex, but was smaller in females than males. Conclusions: Our findings suggest that the relationship between cannabis dependence and subregional volumetry was not moderated by sex. Specifically, dependent (rather than non-dependent) cannabis use may be associated with alterations in selected hippocampus subfields high in cannabinoid type 1 (CB1) receptors and implicated in addictive behavior. As these data are cross-sectional, it is plausible that differences predate cannabis dependence onset and contribute to the initiation of cannabis dependence. Longitudinal neuroimaging work is required to examine the time-course of the onset of subregional hippocampal alterations in cannabis dependence, and their progression as cannabis dependence exacerbates or recovers over time.

Medial Amygdalar Tau Is Associated With Mood Symptoms in Preclinical Alzheimer's Disease

BACKGROUND

While the amygdala receives early tau deposition in Alzheimer's disease (AD) and is involved in social and emotional processing, the relationship between amygdalar tau and early neuropsychiatric symptoms in AD is unknown. We sought to determine whether focal tau binding in the amygdala and abnormal amygdalar connectivity were detectable in a preclinical AD cohort and identify relationships between these and self-reported mood symptoms.

METHODS

We examined 598 individuals (347 amyloid positive [58% female], 251 amyloid negative [62% female] subset in tau positron emission tomography and functional magnetic resonance imaging cohorts) from the A4 (Anti-Amyloid Treatment in Asymptomatic AD) Study. In the tau positron emission tomography cohort, we used amygdalar segmentations to examine representative nuclei from 3 functional divisions of the amygdala. We analyzed between-group differences in division-specific tau binding in the amygdala in preclinical AD. We conducted seed-based functional connectivity analyses from each division in the functional magnetic resonance imaging cohort. Finally, we conducted exploratory post hoc correlation analyses between neuroimaging biomarkers of interest and anxiety and depression scores.

RESULTS

Amyloid-positive individuals demonstrated increased tau binding in the medial and lateral amygdala, and tau binding in these regions was associated with mood symptoms. Across amygdalar divisions, amyloid-positive individuals had relatively higher regional connectivity from the amygdala to other temporal regions, the insula, and the orbitofrontal cortex, but medial amygdala to retrosplenial cortex connectivity was lower. Medial amygdala to retrosplenial connectivity was negatively associated with anxiety symptoms, as was retrosplenial tau.

CONCLUSIONS

Our findings suggest that preclinical tau deposition in the amygdala and associated changes in functional connectivity may be related to early mood symptoms in AD.

Amygdala volumes and associations with socio-emotional competencies in preterm youth: cross-sectional and longitudinal data

BACKGROUND

Socio-emotional difficulties often result from very preterm (VPT) birth. The amygdala's developmental trajectory, including its nuclei, has been recognized as a significant factor in observed difficulties. This study aims to assess the relationship between amygdala volume and socio-emotional competencies in VPT children and adolescents.

METHODS

Socio-emotional competencies were assessed, and amygdala volumes, including subnuclei, were extracted automatically from structural scans in a cross-sectional cohort of VPT (n = 75) and full-term (FT, n = 41) aged 6-14 years. Group differences in amygdala volumes were assessed using ANCOVA, and associations with socio-emotional competencies were studied using partial least squares correlation (PLSC). In a VPT subgroup, additional longitudinal data with amygdala volumes at term-equivalent age (TEA) were manually extracted, growth rates calculated, and associations with school-age socio-emotional competencies investigated using PLSC.

RESULTS

Using cross-sectional data at school-age, amygdala volumes displayed comparable developmental patterns between the VPT and the FT groups. Greater volumes were associated with more emotional regulation difficulties in VPT and lower affect recognition competencies in FT. In the longitudinal VPT subgroup, no significant associations were found between amygdala volume trajectory and socio-emotional competencies.

CONCLUSION

Although our findings suggest typical amygdala development after VPT birth, further research is necessary to elucidate the developmental trajectory of amygdala and the role of resilience factors.

IMPACT

In our cohort, amygdala volumes, including subnuclei, displayed comparable developmental trajectories between the very preterm and the full-term groups. Higher amygdala volumes at school-age were associated with higher emotional regulation difficulties in the very-preterm born group, and with lower affect recognition abilities in full-term born children and adolescents. In a subgroup of very-preterm children and adolescents followed from birth to school-age, no significant associations were found between amygdala volumes at term-equivalent age and socio-emotional competencies at school-age.

Resting-State Functional Connectivity of the Amygdala in Autism: A Preregistered Large-Scale Study

OBJECTIVE

Three leading neurobiological hypotheses about autism spectrum disorder (ASD) propose underconnectivity between brain regions, atypical function of the amygdala, and generally higher variability between individuals with ASD than between neurotypical individuals. Past work has often failed to generalize, because of small sample sizes, unquantified data quality, and analytic flexibility. This study addressed these limitations while testing the above three hypotheses, applied to amygdala functional connectivity.

METHODS

In a comprehensive preregistered study, the three hypotheses were tested in a subset (N=488 after exclusions; N=212 with ASD) of the Autism Brain Imaging Data Exchange data sets. The authors analyzed resting-state functional connectivity (FC) from functional MRI data from two anatomically defined amygdala subdivisions, in three hypotheses with respect to magnitude, pattern similarity, and variability, across different anatomical scales ranging from whole brain to specific regions and networks.

RESULTS

A Bayesian approach to hypothesis evaluation produced inconsistent evidence in ASD for atypical amygdala FC magnitude, strong evidence that the multivariate pattern of FC was typical, and no consistent evidence of increased interindividual variability in FC. The results strongly depended on analytic choices, including preprocessing pipeline for the neuroimaging data, anatomical specificity, and subject exclusions.

CONCLUSIONS

A preregistered set of analyses found no reliable evidence for atypical functional connectivity of the amygdala in autism, contrary to leading hypotheses. Future studies should test an expanded set of hypotheses across multiple processing pipelines, collect deeper data per individual, and include a greater diversity of participants to ensure robust generalizability of findings on amygdala FC in ASD.

The human social cognitive network contains multiple regions within the amygdala

Reasoning about someone's thoughts and intentions-i.e., forming a "theory of mind"-is a core aspect of social cognition and relies on association areas of the brain that have expanded disproportionately in the human lineage. We recently showed that these association zones comprise parallel distributed networks that, despite occupying adjacent and interdigitated regions, serve dissociable functions. One network is selectively recruited by social cognitive processes. What circuit properties differentiate these parallel networks? Here, we show that social cognitive association areas are intrinsically and selectively connected to anterior regions of the medial temporal lobe that are implicated in emotional learning and social behaviors, including the amygdala at or near the basolateral complex and medial nucleus. The results suggest that social cognitive functions emerge through coordinated activity between internal circuits of the amygdala and a broader distributed association network, and indicate the medial nucleus may play an important role in social cognition in humans.

Exploring the association between childhood trauma and limbic system subregion volumes in healthy individuals: a neuroimaging study

BACKGROUND

Childhood trauma (CT) is a major risk factor for psychiatric disorders. Emotional and cognitive functions are often affected in many psychiatric conditions, and these functions are mediated by the limbic system. However, previous research has primarily focused on patient populations. Therefore, we aim to examine the impact of CT on the limbic brain structure in healthy individuals.

METHODS

We enrolled 48 individuals in health, evenly split into two groups: 24 healthy participants with CT (HP-CT) and 24 healthy participants without CT (HP-nCT). They underwent scale assessments and MRI data acquisition. Comparisons between the two groups were performed after subcortical subregion volume segmentation using FreeSufer. Lastly, we examined correlations between volume changes and scale scores.

RESULTS

We found that HP-CT group had smaller volumes in several subregions of the hippocampus, amygdala, and cortical limbic structures, including the subiculum (Sub) head and body, cornu ammonis (CA)1 head, molecular layer (ML) head, granule cell layer of the dentate gyrus (GC-ML-DG) body, CA4 body, fimbria, hippocampus-amygdala transition area (HATA), whole hippocampus head and body, whole hippocampus, basal nucleus (Ba), accessory basal nucleus (AB), cortico-amygdaloid transition area (CAT), paralaminar nucleus (PL) of the left hemisphere; and hippocampal tail, presubiculum (PreSub) body, and basal forebrain of the right hemisphere. Volume changes in the CA4 body and GC-ML-DG body were correlated with sexual abuse. Changes in the volume of the right basal forebrain were linked to emotional neglect. However, these findings were not significant after correction for multiple comparisons.

CONCLUSION

CT impacts multiple structures of the limbic system, including the hippocampus, and amygdala. This also suggests that region-specific changes within the limbic system can serve as clinical biomarkers supporting cross-diagnostic psychiatric illnesses.

Widespread asymmetries of amygdala nuclei predict auditory verbal hallucinations in schizophrenia

BACKGROUND

Auditory verbal hallucinations, which frequently involve negative emotions, are reliable symptoms of schizophrenia. Brain asymmetries have also been linked to the condition, but the relevance of asymmetries within the amygdala, which coordinates all emotional signals, to the content of and response to auditory verbal hallucinations has not been explored.

METHODS

We evaluated the performance of two asymmetry biomarkers that were recently introduced in literature: the distance index, which captures global asymmetries, and a revised version of the laterality index, which captures left-right local asymmetries. We deployed random forest regression models over values computed with the distance index and with the laterality index over amygdala nuclei volumes (lateral, basal, accessory-basal, anterior amygdaloid area, central, medial, cortical, cortico-amygdaloid area, and paralaminar) for 71 patients and 71 age-matched controls.

RESULTS

Both biomarkers made successful predictions for the 35 items of the revised version of the Belief About Voices Questionnaire, such that hallucination severity increased with increasing local asymmetries and with decreasing global asymmetries of the amygdala.

CONCLUSIONS

Our findings highlight a global reorganization of the amygdala, where left and right nuclei volumes differ pairwise but become proportionally more similar as hallucinations increase in severity. Identifying asymmetries in particular brain structures relevant to specific symptoms could help monitor the evolution and outcome of psychopathological conditions.

A cross-species analysis of neuroanatomical covariance sex difference in humans and mice

Structural covariance in brain anatomy is thought to reflect inter-regional sharing of developmental influences - although this hypothesis has proved hard to causally test. Here, we use neuroimaging in humans and mice to study sex-differences in anatomical covariance - asking if regions that have developed shared sex differences in volume across species also show shared sex difference in volume covariance. This study design illuminates both the biology of sex-differences and theoretical models for anatomical covariance - benefitting from tests of inter-species convergence. We find that volumetric structural covariance is stronger in adult females compared to adult males for both wild-type mice and healthy human subjects: 98% of all comparisons with statistically significant covariance sex differences in mice are female-biased, while 76% of all such comparisons are female-biased in humans (q < 0.05). In both species, a region's covariance and volumetric sex-biases have weak inverse relationships to each other: volumetrically male-biased regions contain more female-biased covariations, while volumetrically female-biased regions have more male-biased covariations (mice: r = -0.185, p = 0.002; humans: r = -0.189, p = 0.001). Our results identify a conserved tendency for females to show stronger neuroanatomical covariance than males, evident across species, which suggests that stronger structural covariance in females could be an evolutionarily conserved feature that is partially related to volumetric alterations through sex.

Leveraging ultra-high field (7T) MRI in psychiatric research

Non-invasive brain imaging has played a critical role in establishing our understanding of the neural properties that contribute to the emergence of psychiatric disorders. However, characterizing core neurobiological mechanisms of psychiatric symptomatology requires greater structural, functional, and neurochemical specificity than is typically obtainable with standard field strength MRI acquisitions (e.g., 3T). Ultra-high field (UHF) imaging at 7 Tesla (7T) provides the opportunity to identify neurobiological systems that confer risk, determine etiology, and characterize disease progression and treatment outcomes of major mental illnesses. Increases in scanner availability, regulatory approval, and sequence availability have made the application of UHF to clinical cohorts more feasible than ever before, yet the application of UHF approaches to the study of mental health remains nascent. In this technical review, we describe core neuroimaging methodologies which benefit from UHF acquisition, including high resolution structural and functional imaging, single (1H) and multi-nuclear (e.g., 31P) MR spectroscopy, and quantitative MR techniques for assessing brain tissue iron and myelin. We discuss advantages provided by 7T MRI, including higher signal- and contrast-to-noise ratio, enhanced spatial resolution, increased test-retest reliability, and molecular and neurochemical specificity, and how these have begun to uncover mechanisms of psychiatric disorders. Finally, we consider current limitations of UHF in its application to clinical cohorts, and point to ongoing work that aims to overcome technical hurdles through the continued development of UHF hardware, software, and protocols.

Cognitive impairment and amygdala subregion volumes in elderly with cerebral small vessel disease: A large prospective cohort study

Although the amygdala is associated with cognitive impairment resulting from cerebral small vessel disease, the relationship between alterations in amygdala structure and cerebral small vessel disease (CSVD) remains controversial. Given that the amygdala comprises several subregions, detecting subtle regional changes through total amygdala volume measurement is challenging. This study aimed to identify the patterns of amygdala subregion atrophy in cerebral small vessel disease patients and their relationship with cognitive impairment. A total of 114 participants diagnosed with cerebral small vessel disease and 129 healthy participants, aged 40 to 70, underwent 3 T magnetic resonance imaging scans. The amygdala subregions were automatically segmented using FreeSurfer. In the Propensity Score Matching (PSM)-matched cohort, Lasso regression was employed to identify subregions associated with cerebral small vessel disease, and restricted cubic splines (RCS) were used to explore their nonlinear relationship with cognitive abilities. Subsequently, multivariate linear regression models were used to investigate the impact of amygdala subregion volumes on various cognitive abilities. Compared to healthy controls (HC), the volume of the left cortical nucleus was significantly reduced in cerebral small vessel disease patients. The volume of the left cortical nucleus was significantly negatively correlated with cerebral small vessel disease progression, and atrophy in this region was also identified as an independent risk factor for decreased cognitive control and processing ability. Our findings suggest that patients with cerebral small vessel disease exhibit atrophy in specific amygdala subregions compared to healthy controls, which correlates with poorer cognitive control and processing abilities. These insights may advance our understanding of the pathogenesis of cerebral small vessel disease.

Functional connectivity of the amygdala subnuclei in various mood states of bipolar disorder

Amygdala functional dysconnectivity lies at the heart of the pathophysiology of bipolar disorder (BD). Recent preclinical studies suggest that the amygdala is a heterogeneous group of nuclei, whose specific connectivity could drive positive or negative emotional valence. We investigated functional connectivity (FC) changes within these circuits emerging from each amygdala's subdivision in 127 patients with BD in different mood states and 131 healthy controls (HC), who underwent resting-state functional MRI. FC was evaluated between lateral and medial nuclei of amygdalae, and key subcortical regions of the emotion processing network: anterior and posterior parts of the hippocampus, and core and shell parts of the nucleus accumbens. FC was compared across groups, and subgroups of patients depending on their mood states, using linear mixed models. We also tested correlations between FC and depression (MADRS) and mania (YMRS) scores. We found no difference between the whole sample of BD patients vs. HC but a significant correlation between MADRS and right lateral amygdala /right anterior hippocampus, right lateral amygdala/right posterior hippocampus and right lateral amygdala/left anterior hippocampus FC (r = -0.44, r = -0.32, r = -0.27, respectively, all pFDR<0.05). Subgroup analysis revealed decreased right lateral amygdala/right anterior hippocampus and right lateral amygdala/right posterior hippocampus FC in depressed vs. non-depressed patients and increased left medial amygdala/shell part of the left nucleus accumbens FC in manic vs non-manic patients. These results demonstrate that acute mood states in BD concur with FC changes in individual nuclei of the amygdala implicated in distinct emotional valence processing. Overall, our data highlight the importance to consider the amygdala subnuclei separately when studying its FC patterns including patients in distinct homogeneous mood states.

Alterations of subcortical structure volume in pediatric bipolar disorder patients with manic or depressive first-episode

BACKGROUND

Bipolar disorder may begin as depression or mania, which can affect the treatment and prognosis. The physiological and pathological differences among pediatric bipolar disorder (PBD) patients with different onset symptoms are not clear. The aims of the present study were to investigate subcortical structural alterations in PBD patients with first-episode depressive (PBD-FED) and first-episode manic (PBD-FEM).

METHODS

A total of 59 individuals including 28 PBD-FED, 13 PBD-FEM, and 18 healthy controls (HCs) underwent high-resolution structural magnetic resonance scans. FreeSurfer 7.2 was used to detect changes in subcortical volumes. Simultaneously, thalamic, hippocampal, and amygdala subregion volumes were compared between the three groups.

RESULTS

Analysis of covariance controlling for age, sex, education, and estimated intracranial volume shows third and fourth ventricle enlargement in patients with PBD. Compared with the PBD-FED and HCs, the PBD-FEM group had reduced gray matter volume in the left thalamus, bilateral hippocampus, and right amygdala. Subsequent subregion analyses showed right cortico-amygdaloid transient, bilateral accessory-basal nucleus, left hippocampal tail, right hippocampal head, and body volume reduction in the PBD-FEM group.

CONCLUSIONS

The present findings provided evidence of decreased subcortical structure in PBD-FEM patients, which might present its trait feature.

Morphological correlates of anxiety-related experiences during a ketamine infusion

OBJECTIVES

Ketamine exerts rapid antidepressant effects by enhancing neuroplasticity, particularly in the amygdala and hippocampus-regions involved in fear processing and learning. While the role of ketamine's dissociative effects in its antidepressant response is debated, anxiety experienced during infusion has been negatively correlated with treatment outcomes.

METHODS

In this single-blind, placebo-controlled study, a subset of 17 healthy volunteers (6 males, 23.12 ± 1.9 years) received intravenously a placebo in the first and 0.5 mg/kg racemic ketamine in the second session. Anxiety-related experiences were assessed by the 5D-ASC score obtained post-infusion, structural magnetic resonance imaging scans were acquired 4 h post-infusion. An anxiety-score was obtained from the 5D-ASC. Relation between post-placebo amygdala volume, hippocampal volume, and its subfields with the anxiety-score were assessed using linear regression models.

RESULTS

Results showed a statistically significant negative relation between hippocampal head volume and the anxiety score (β = -0.733, p = 0.006), with trending negative association for each subfield's head and the score.

CONCLUSION

These findings suggest that anxiety-related experiences during ketamine infusion may be mediated by the hippocampus, with smaller hippocampal volumes leading to more anxiety-related experiences. Thus, hippocampal subfield volumes may be used as a predictor for anxiety-related events during ketamine use and might predict treatment outcome in future approaches.

Histology-guided MRI segmentation of brainstem nuclei critical to consciousness

While substantial progress has been made in mapping the connectivity of cortical networks responsible for conscious awareness, neuroimaging analysis of subcortical arousal networks that modulate arousal (i.e., wakefulness) has been limited by a lack of a robust segmentation procedures for brainstem arousal nuclei. Automated segmentation of brainstem arousal nuclei is an essential step toward elucidating the physiology of arousal in human consciousness and the pathophysiology of disorders of consciousness. We created a probabilistic atlas of brainstem arousal nuclei built on diffusion MRI scans of five ex vivo human brain specimens scanned at 750 μm isotropic resolution. Labels of arousal nuclei used to generate the probabilistic atlas were manually annotated with reference to nucleus-specific immunostaining in two of the five brain specimens. We then developed a Bayesian segmentation algorithm that utilizes the probabilistic atlas as a generative model and automatically identifies brainstem arousal nuclei in a resolution- and contrast-agnostic manner. The segmentation method displayed high accuracy in both healthy and lesioned in vivo T1 MRI scans and high test-retest reliability across both T1 and T2 MRI contrasts. Finally, we show that the segmentation algorithm can detect volumetric changes and differences in magnetic susceptibility within brainstem arousal nuclei in Alzheimer's disease and traumatic coma, respectively. We release the probabilistic atlas and Bayesian segmentation tool in FreeSurfer to advance the study of human consciousness and its disorders.

Outdoor Air Pollution Relates to Amygdala Subregion Volume and Apportionment in Early Adolescents

Background

Outdoor air pollution is associated with an increased risk for psychopathology. Although the neural mechanisms remain unclear, air pollutants may impact mental health by altering limbic brain regions, such as the amygdala. Here, we examine the association between ambient air pollution exposure and amygdala subregion volumes in 9-10-year-olds.

Methods

Cross-sectional Adolescent Brain Cognitive DevelopmentSM (ABCD) Study® data from 4,473 participants (55.4% male) were leveraged. Air pollution was estimated for each participant's primary residential address. Using the probabilistic CIT168 atlas, we quantified total amygdala and 9 distinct subregion volumes from T1- and T2-weighted images. First, we examined how criteria pollutants (i.e., fine particulate matter [PM2.5], nitrogen dioxide, ground-level ozone) and 15 PM2.5 components related with total amygdala volumes using linear mixed-effect (LME) regression. Next, partial least squares correlation (PLSC) analyses were implemented to identify relationships between co-exposure to criteria pollutants as well as PM2.5 components and amygdala subregion volumes. We also conducted complementary analyses to assess subregion apportionment using amygdala relative volume fractions (RVFs).

Results

No significant associations were detected between pollutants and total amygdala volumes. Using PLSC, one latent dimension (LD) (52% variance explained) captured a positive association between calcium and several basolateral subregions. LDs were also identified for amygdala RVFs (ranging from 30% to 82% variance explained), with PM2.5 and component co-exposure associated with increases in lateral, but decreases in medial and central, RVFs.

Conclusions

Fine particulate and its components are linked with distinct amygdala differences, potentially playing a role in risk for adolescent mental health problems.

Different structural connectivity patterns in the subregions of the thalamus, hippocampus, and cingulate cortex between schizophrenia and psychotic bipolar disorder

OBJECTIVE

Schizophrenia (SCZ) and psychotic bipolar disorder (PBD) are two major psychotic disorders with similar symptoms and tight associations on the psychopathological level, posing a clinical challenge for their differentiation. This study aimed to investigate and compare the structural connectivity patterns of the limbic system between SCZ and PBD, and to identify specific regional disruptions associated with psychiatric symptoms.

METHODS

Using sMRI data from 146 SCZ, 160 PBD, and 145 healthy control (HC) participants, we employed a data-driven approach to segment the hippocampus, thalamus, hypothalamus, amygdala, and cingulate cortex into subregions. We then investigated the structural connectivity patterns between these subregions at the global and nodal levels. Additionally, we assessed psychotic symptoms by utilizing the subscales of the Brief Psychiatric Rating Scale (BPRS) to examine correlations between symptom severity and network metrics between groups.

RESULTS

Patients with SCZ and PBD had decreased global efficiency (Eglob) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.003), local efficiency (Eloc) (SCZ and PBD: adjusted P<0.001), and clustering coefficient (Cp) (SCZ and PBD: adjusted P<0.001), and increased path length (Lp) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.004) compared to HC. Patients with SCZ showed more pronounced decreases in Eglob (adjusted P<0.001), Eloc (adjusted P<0.001), and Cp (adjusted P = 0.029), and increased Lp (adjusted P = 0.024) compared to patients with PBD. The most notable structural disruptions were observed in the hippocampus and thalamus, which correlated with different psychotic symptoms, respectively.

CONCLUSION

This study provides evidence of distinct structural connectivity disruptions in the limbic system of patients with SCZ and PBD. These findings might contribute to our understanding of the neuropathological basis for distinguishing SCZ and PBD.

Multi-modal MRI for objective diagnosis and outcome prediction in depression

RESEARCH PURPOSE

The low treatment effectiveness in major depressive disorder (MDD) may be caused by the subjectiveness in clinical examination and the lack of quantitative tests. Objective biomarkers derived from magnetic resonance imaging (MRI) may support clinical experts during decision-making. Numerous studies have attempted to identify such MRI-based biomarkers. However, the majority is uni-modal (based on a single MRI modality) and focus on either MDD diagnosis or outcome. Uncertainty remains regarding whether key features or classification models for diagnosis may also be used for outcome prediction. Therefore, we aim to find multi-modal predictors of both, MDD diagnosis and outcome. By addressing these research questions using the same dataset, we eliminate between-study confounding factors. Various structural (T1-weighted, T2-weighted, diffusion tensor imaging (DTI)) and functional (resting-state and task-based functional MRI) scans were acquired from 32 MDD and 31 healthy control (HC) subjects during the first visit at the investigational site (baseline). Depression severity was assessed at baseline and 6 months later. Features were extracted from the baseline MRI images with different modalities. Binary 6-months negative and positive outcome (NO; PO) classes were defined based on relative (to baseline) change in depression severity. Support vector machine models were employed to separate MDD from HC (diagnosis) and NO from PO subjects (outcome). Classification was performed through a uni-modal (features from a single MRI modality) and multi-modal (combination of features from different modalities) approach.

PRINCIPAL RESULTS

Our results show that DTI features yielded the highest uni-modal performance for diagnosis and outcome prediction: mean diffusivity (AUC (area under the curve) = 0.701) and the sum of streamline weights (AUC = 0.860), respectively. Multi-modal ensemble classifiers with T1-weighted, resting-state functional MRI and DTI features improved classification performance for both diagnosis and outcome (AUC = 0.746 and 0.932, respectively). Feature analyses revealed that the most important features were located in frontal, limbic and parietal areas. However, the modality or location of these features was different between diagnostic and prognostic models.

MAJOR CONCLUSIONS

Our findings suggest that combining features from different MRI modalities predict MDD diagnosis and outcome with higher performance. Furthermore, we demonstrated that the most important features for MDD diagnosis were different and located in other brain regions than those for outcome. This longitudinal study contributes to the identification of objective biomarkers of MDD and its outcome. Follow-up studies may further evaluate the generalizability of our models in larger or multi-center cohorts.

Associations between parental rearing style and amygdala and hippocampal subfield abnormalities in drug-naive females with anorexia nervosa

BACKGROUND

Altered volumes in the hippocampus and amygdala have been linked to anorexia nervosa (AN). This study aimed to investigate amygdala and hippocampal subfields volume abnormalities in AN patients, and their associations with parental rearing practices and clinical psychological characteristics.

METHODS

This study included twenty-nine drug-naive females with AN from West China Hospital of Sichuan University, China, and fifty-nine age- and gender-matched healthy controls (HCs) recruited through advertisement. All participants underwent T1-weighted imaging. Amygdala and hippocampal subfields volume was calculated using FreeSurfer 7.0. The Core Self-Evaluation Scale (CSES) and Rosenberg Self-Esteem Scale (RSES) were used to assess the psychological characteristics of AN patients. The Egna Minnen av Barndoms Uppfostran (EMBU) was employed to evaluate parental rearing practices. Group differences in brain volumes were analyzed with covariates like age and total intracranial volume (TIV). Partial correlation analysis explored the correlations between brain region volumes and clinical psychological characteristics.

RESULTS

AN patients exhibited lower RSES and CSES scores, and more adverse parental rearing style than healthy norms. After adjusting for covariates, AN patients showed decreased gray matter volume (GMV) in the left medial (Me) and cortical (Co) nucleus, as well as in the right hippocampal-amygdala transition area (HATA). GMV in the left Me was correlated with years of education among HCs but not among AN patients. GMV in the right HATA was positively correlated with paternal penalty and severity, as well as maternal overinterference.

CONCLUSION

This study supports structure abnormalities in amygdala and hippocampus in AN patients and suggests that parental rearing practices may be associated with hippocampal abnormalities, potentially contributing to the pathophysiology of AN. Addressing appropriate parental rearing styles may offer a positive impact on AN.

Amygdala atrophies in specific subnuclei in preclinical Alzheimer's disease

INTRODUCTION

Magnetic resonance imaging (MRI) segmentation algorithms make it possible to study detailed medial temporal lobe (MTL) substructures as hippocampal subfields and amygdala subnuclei, offering opportunities to develop biomarkers for preclinical Alzheimer's disease (AD).

METHODS

We identified the MTL substructures significantly associated with tau-positron emission tomography (PET) signal in 581 non-demented individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI-3). We confirmed our results in our UCLouvain cohort including 110 non-demented individuals by comparing volumes between individuals with different visual Braak's stages and clinical diagnosis.

RESULTS

Four amygdala subnuclei (cortical, central, medial, and accessory basal) were associated with tau in amyloid beta-positive (Aβ+) clinically normal (CN) individuals, while the global amygdala and hippocampal volumes were not. Using UCLouvain data, we observed that both Braak I-II and Aβ+ CN individuals had smaller volumes in these subnuclei, while no significant difference was observed in the global structure volumes or other subfields.

CONCLUSION

Measuring specific amygdala subnuclei, early atrophy may serve as a marker of temporal tauopathy in preclinical AD, identifying individuals at risk of progression.

HIGHLIGHTS

Amygdala atrophy is not homogeneous in preclinical Alzheimer's disease (AD). Tau pathology is associated with atrophy of specific amygdala subnuclei, specifically, the central, medial, cortical, and accessory basal subnuclei. Hippocampal and amygdala volume is not associated with tau in preclinical AD. Hippocampus and CA1-3 volume is reduced in preclinical AD, regardless of tau.

Elevated tau in the piriform cortex in Alzheimer's but not Parkinson's disease using PET-MR

INTRODUCTION

Olfactory dysfunction can be an early sign of Alzheimer's disease (AD). We used tau positron emission tomography-magnetic resonance (PET-MR) to analyze a key region of the olfactory circuit, the piriform cortex, in comparison to the adjacent medial temporal lobe.

METHODS

Using co-registered magnetic resonance imaging (MRI) and 18F-PI-2620 tau PET-MR scans in 94 older adults, we computed tau uptake in the piriform-periamygdaloid cortex, amygdala, entorhinal-perirhinal cortices, and hippocampus.

RESULTS

We found an ordinal cross-sectional increase in piriform cortex tau uptake with increasing disease severity (amyloid-negative controls, amyloid-positive controls, mild cognitive impairment [MCI] and AD), comparable to entorhinal-perirhinal cortex. Amyloid-positive controls showed significantly greater tau uptake than amyloid-negative controls. Negative correlations were present between memory performance and piriform uptake. Piriform uptake was not elevated in cognitively unimpaired Parkinson's disease.

DISCUSSION

Cross-sectionally, there is an early increase in tau uptake in the piriform cortex in AD but not in Parkinson's disease.

Highlights

Positron emission tomography-magnetic resonance (PET-MR) analysis of the piriform cortex sheds light on its role as a potential early region affected by neurodegenerative disorders underlying olfactory dysfunction.Uptake of tau tracer was elevated in the piriform cortex in Alzheimer's disease (AD) and mild cognitive impairment (MCI) but not in Parkinson's disease (PD).Memory performance was worse with greater piriform uptake.

The volumes of amygdala subregions and peripheral programmed cell death protein-1 levels are associated with cognitive decline in individuals with knee osteoarthritis

BACKGROUND

Persistent pain is a prominent symptom of knee osteoarthritis (KOA) and has been associated with cognitive decline in individuals with KOA. The amygdala, a complex structure consisting of nine subnuclei, and programmed cell death protein-1 (PD-1) levels play crucial roles in pain regulation and cognitive processing. This study aims to investigate the relationships among amygdala subregion volumes, cognitive function, and PD-1 levels to elucidate the underlying mechanism of cognitive decline in KOA.

METHODS

In this cross-sectional study, we recruited 36 patients with KOA and 25 age/gender-matched healthy controls for neuropsychological tests, structural magnetic resonance imaging scanning, and measurement of serum PD-1 levels. We used the atlas provided by FreeSurfer software to automatically segment the amygdala subnuclei. Subsequently, we compared the volumes of amygdala subregions between groups and explored their correlation with clinical scores and PD-1 levels.

RESULTS

Compared to healthy controls, individuals with KOA exhibited significantly lower scores on global cognition tasks, such as long-delay free recall, short-delay free recall, and immediate recall tasks. Moreover, they displayed decreased volumes in lateral nucleus basal nucleus paralaminar nucleus while showing increased volumes in accessory basal nucleus, central nucleus, medial nucleus, and cortical nucleus. Within the KOA group specifically, paralaminar volume was negatively correlated with immediate recall scores; pain scores were negatively correlated with global cognition; basal volume was negatively correlated with PD-1 levels.

CONCLUSION

Our findings highlight those alterations in amygdala subregion volumes along with changes in serum PD-1 levels may contribute to observe cognitive decline among individuals suffering from KOA.

Coordinated NREM sleep oscillations among hippocampal subfields modulate synaptic plasticity in humans

The integration of hippocampal oscillations during non-rapid eye movement (NREM) sleep is crucial for memory consolidation. However, how cardinal sleep oscillations bind across various subfields of the human hippocampus to promote information transfer and synaptic plasticity remains unclear. Using human intracranial recordings from 25 epilepsy patients, we find that hippocampal subfields, including DG/CA3, CA1, and SUB, all exhibit significant delta and spindle power during NREM sleep. The DG/CA3 displays strong coupling between delta and ripple oscillations with all the other hippocampal subfields. In contrast, the regions of CA1 and SUB exhibit more precise coordination, characterized by event-level triple coupling between delta, spindle, and ripple oscillations. Furthermore, we demonstrate that the synaptic plasticity within the hippocampal circuit, as indexed by delta-wave slope, is linearly modulated by spindle power. In contrast, ripples act as a binary switch that triggers a sudden increase in delta-wave slope. Overall, these results suggest that different subfields of the hippocampus regulate one another through diverse layers of sleep oscillation synchronization, collectively facilitating information processing and synaptic plasticity during NREM sleep.

A next-generation, histological atlas of the human brain and its application to automated brain MRI segmentation

Magnetic resonance imaging (MRI) is the standard tool to image the human brain in vivo. In this domain, digital brain atlases are essential for subject-specific segmentation of anatomical regions of interest (ROIs) and spatial comparison of neuroanatomy from different subjects in a common coordinate frame. High-resolution, digital atlases derived from histology (e.g., Allen atlas [7], BigBrain [13], Julich [15]), are currently the state of the art and provide exquisite 3D cytoarchitectural maps, but lack probabilistic labels throughout the whole brain. Here we present NextBrain, a next-generation probabilistic atlas of human brain anatomy built from serial 3D histology and corresponding highly granular delineations of five whole brain hemispheres. We developed AI techniques to align and reconstruct ~10,000 histological sections into coherent 3D volumes with joint geometric constraints (no overlap or gaps between sections), as well as to semi-automatically trace the boundaries of 333 distinct anatomical ROIs on all these sections. Comprehensive delineation on multiple cases enabled us to build the first probabilistic histological atlas of the whole human brain. Further, we created a companion Bayesian tool for automated segmentation of the 333 ROIs in any in vivo or ex vivo brain MRI scan using the NextBrain atlas. We showcase two applications of the atlas: automated segmentation of ultra-high-resolution ex vivo MRI and volumetric analysis of Alzheimer's disease and healthy brain ageing based on ~4,000 publicly available in vivo MRI scans. We publicly release: the raw and aligned data (including an online visualisation tool); the probabilistic atlas; the segmentation tool; and ground truth delineations for a 100 μm isotropic ex vivo hemisphere (that we use for quantitative evaluation of our segmentation method in this paper). By enabling researchers worldwide to analyse brain MRI scans at a superior level of granularity without manual effort or highly specific neuroanatomical knowledge, NextBrain holds promise to increase the specificity of MRI findings and ultimately accelerate our quest to understand the human brain in health and disease.

Segmentation of supragranular and infragranular layers in ultra-high-resolution 7T ex vivo MRI of the human cerebral cortex

Accurate labeling of specific layers in the human cerebral cortex is crucial for advancing our understanding of neurodevelopmental and neurodegenerative disorders. Building on recent advancements in ultra-high-resolution ex vivo MRI, we present a novel semi-supervised segmentation model capable of identifying supragranular and infragranular layers in ex vivo MRI with unprecedented precision. On a dataset consisting of 17 whole-hemisphere ex vivo scans at 120 $\mu $m, we propose a Multi-resolution U-Nets framework that integrates global and local structural information, achieving reliable segmentation maps of the entire hemisphere, with Dice scores over 0.8 for supra- and infragranular layers. This enables surface modeling, atlas construction, anomaly detection in disease states, and cross-modality validation while also paving the way for finer layer segmentation. Our approach offers a powerful tool for comprehensive neuroanatomical investigations and holds promise for advancing our mechanistic understanding of progression of neurodegenerative diseases.

Advancing cerebral small vessel disease diagnosis: Integrating quantitative susceptibility mapping with MRI-based radiomics

Cerebral small vessel disease (CSVD) is a neurodegenerative disease with hidden symptoms and difficult to diagnose. The diagnosis mainly depends on clinical symptoms and neuroimaging. Therefore, we explored the potential of combining clinical detection with MRI-based radiomics features for the diagnosis of CSVD in a large cohort. A total of 118 CSVD patients and 127 healthy controls underwent quantitative susceptibility mapping and 3D-T1 scans, and all completed multiple cognitive tests. Lasso regression was used to select features, and the radiomics model was constructed based on the regression coefficients of these features. Clinical cognitive and motor tests were added to the model to construct a hybrid model. All models were cross-validated to analyze the generalization ability of the models. The AUCs of the radiomics and hybrid models in the internal test set were 0.80 and 0.87, respectively. In the validation set, the AUCs were 0.77 and 0.79, respectively. The hybrid model demonstrated higher decision efficiency. The Trail Making Test, which enhances the diagnostic performance of the model, is associated with multiple brain regions, particularly the right cortical nuclei and the right fimbria. The hybrid model based on radiomics features and cognitive tests can achieve quantitative diagnosis of CSVD and improve the diagnostic efficiency. Furthermore, the reduced processing capacity due to atrophy of the right cortical nucleus and right fimbria suggests the importance of these regions in improving the diagnostic accuracy of the model.