Left Amygdala Research Articles

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

BackgroundBipolar 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).MethodsA 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.ResultsAnalysis 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.ConclusionsThe present findings provided evidence of decreased subcortical structure in PBD-FEM patients, which might present its trait feature.

Augmenting mindfulness training through neurofeedback: a pilot study of the pre-post changes on resting-state functional connectivity in typically developing adolescents

BackgroundMindfulness training has been shown to promote positive mental health outcomes and related changes in neural networks such as the default mode network, which has a central node in the posterior cingulate cortex (PCC). Previous work from our group reported on the impact of a novel, neurofeedback augmented mindfulness training (NAMT) task on regulation of PCC hemodynamic activity in typically developing adolescents. The present pilot study aimed to expand on this finding by examining the pre-post changes of the NAMT task on resting-state functional connectivity of the PCC.MethodsThirty-one typically developing adolescents (14.77 ± 1.23 years; 45% female) underwent a resting-state functional magnetic resonance imaging scan both before and after completing the NAMT task. A linear mixed effects model was used to assess for changes in functional connectivity of the PCC across the two resting-state runs.ResultsData did not support the hypothesized decrease in connectivity between the PCC seed and other DMN regions from pre- to post-NAMT task. However, we observed a significant increase in functional connectivity between the PCC and a cluster encompassing the left hippocampus and amygdala following completion of the NAMT task (run 1 Fisher’s Z = 0.16; run 2 Fisher’s Z = 0.26).ConclusionAlthough preliminary, this finding suggests NAMT has the potential to strengthen connectivity between default mode and salience regions. We speculate that such changed connectivity may facilitate enhanced self-referential and emotional processing in adolescents.Clinical trial registrationhttps://clinicaltrials.gov/, identifier NCT04053582.

Predictive and Explainable Artificial Intelligence for Neuroimaging Applications

Background: The aim of this review is to highlight the new advance of predictive and explainable artificial intelligence for neuroimaging applications. Methods: Data came from 30 original studies in PubMed with the following search terms: “neuroimaging” (title) together with “machine learning” (title) or ”deep learning” (title). The 30 original studies were eligible according to the following criteria: the participants with the dependent variable of brain image or associated disease; the interventions/comparisons of artificial intelligence; the outcomes of accuracy, the area under the curve (AUC), and/or variable importance; the publication year of 2019 or later; and the publication language of English. Results: The performance outcomes reported were within 58–96 for accuracy (%), 66–97 for sensitivity (%), 76–98 for specificity (%), and 70–98 for the AUC (%). The support vector machine and the convolutional neural network registered the best performance (AUC 98%) for the classifications of low- vs. high-grade glioma and brain conditions, respectively. Likewise, the random forest delivered the best performance (root mean square error 1) for the regression of brain conditions. The following factors were discovered to be major predictors of brain image or associated disease: (demographic) age, education, sex; (health-related) alpha desynchronization, Alzheimer’s disease stage, CD4, depression, distress, mild behavioral impairment, RNA sequencing; (neuroimaging) abnormal amyloid-β, amplitude of low-frequency fluctuation, cortical thickness, functional connectivity, fractal dimension measure, gray matter volume, left amygdala activity, left hippocampal volume, plasma neurofilament light, right cerebellum, regional homogeneity, right middle occipital gyrus, surface area, sub-cortical volume. Conclusion: Predictive and explainable artificial intelligence provide an effective, non-invasive decision support system for neuroimaging applications.

The impact of cannabidiol placebo on amygdala-based neural responses to an acute stressor.

Cannabidiol (CBD) impacts brain regions implicated in anxiety reactivity and stress reactivity (e.g., amygdala, anterior cingulate cortex (ACC), anterior insula (AI)); however, placebo-controlled studies are mixed regarding CBD's anxiolytic effects. We previously reported that CBD expectancy alone can alter subjective, physiological, and endocrine markers of stress/anxiety; however, it is unclear whether these findings reflect altered brain reactivity. This study evaluated whether CBD expectancy independently alters amygdala resting-state functional connectivity (rsFC) with the ACC and AI following acute stress. Thirty-eight (20 females) healthy adults were randomly assigned to receive accurate or inaccurate information regarding the CBD content of a CBD-free oil administered during a single experimental session. Following a baseline resting state MRI scan, participants administered their assigned oil sublingually, engaged in a stress task (serial subtraction with negative feedback) inside the scanner, and underwent another resting state MRI scan. Amygdala rsFC with the ACC and AI was measured during each scan, and the subjective state was assessed at six time points. Outcomes were analyzed using ANCOVA. CBD expectancy (vs CBD-free expectancy) was associated with significantly weaker rsFC between the left amygdala and right ACC (p = 0.042), but did not systematically alter amygdala-AI rsFC (p-values > 0.05). We also replicated our previously reported CBD expectancy effects on subjective stress/anxiety in the scanner context. CBD placebo effects may be sufficient to alter neural responses relevant to its purported anxiolytic and stress-relieving properties. Future work is needed to replicate these results and determine whether CBD expectancy and pharmacology interact to alter neural anxiety reactivity and stress reactivity.

Altered Functional Coupling of the Bed Nucleus of the Stria Terminalis and Amygdala in Spider Phobic Fear.

Background: Individuals with spider phobic (SP) fear show hypervigilance and amygdala hyperactivity toward fear-associated stimuli, which may promote the development of other anxiety disorders. The amygdala is a key region within the fear network, which is connected to the anxiety system, where the bed nucleus of the stria terminalis (BNST) plays a crucial role. However, the BNST's involvement in phobic fear is unknown. Therefore, this study investigated the association of phobic fear and anxiety on these regions' functional connectivity (FC) in SP compared to healthy controls (HC). Methods: 7T-functional MRI resting-state FC of 30 individuals with SP and 45 HC was assessed to detect network differences between these groups. The association of phobic fear severity, trait anxiety, and social anxiety on FC was explored using linear regressions combined with seed-to-voxel analyses with amygdala and BNST as primary seeds, corrected for age and sex. Results: In SP, phobic fear was associated with reduced FC between the left amygdala and the right supramarginal gyrus. In contrast, anxiety severity was related to increased FC between the right BNST and the left inferior frontal gyrus. Moreover, social anxiety was related to decreased FC between bilateral BNST and left precuneus. Conclusions: These findings show changes in FC in SP, connecting fear with altered activity in the BNST and amygdala. The results suggest that persistent anxiety in phobic fear is associated with abnormal brain function in these regions, potentially explaining susceptibility to anxiety disorders and processes involved in phobic fear, such as threat perception, avoidance, and salience. Impact statement This is the first study to report altered FC mechanisms of BNST and amygdala in individuals with SP using 7T ultra-high field resting-state data. So far, only distinct characterization of brain regions, especially of BNST and amygdala, involved in those disorders exists. Our results contribute to closing this knowledge gap by providing the first evidence that deviant BNST and amygdala function in SP might elucidate the susceptibility to other anxiety disorders.

Structural disruption in subjective cognitive decline and mild cognitive impairment.

Subjective cognitive decline (SCD) marks the initial stage in Alzheimer's disease continuum. Nonetheless, current research findings regarding brain structural changes in the SCD are inconsistent. In this study, 37 SCD patients, 28 mild cognitive impairment (MCI) patients, and 42 healthy controls (HC) were recruited to investigate structural alterations. Morphological and microstructural differences among the three groups were analyzed based on T1- and diffusion-weighted images, correlating them with neuropsychological assessments. Additionally, classification analysis was performed by using support vector machines (SVM) categorize participants into three groups based on MRI features. Both SCD and MCI showed decreased volume in left inferior parietal lobe (IPL) compared to HC, while SCD showed altered morphologies in the right inferior temporal gyrus (ITG), right insula and right amygdala, and microstructures in fiber tracts of the right ITG, lateral occipital cortex (LOC) and insula relative to MCI. Moreover, the volume in the left IPL, right LOC, right amygdala and diffusivity value in fiber tracts of right LOC were significantly correlated with cognitive functions across all subjects. The classification models achieved an accuracy of > 0.7 (AUC = 0.8) in distinguishing the three groups. Our findings suggest that SCD and MCI share similar atrophy in the IPL but show more differences in morphological and microstructural features of cortical-subcortical areas.

Amygdala activity after subchronic escitalopram administration in healthy volunteers: A pharmaco-functional magnetic resonance imaging study.

Selective serotonin reuptake inhibitors (SSRIs) are used for the treatment of several conditions including anxiety disorders, but the basic neurobiology of serotonin function remains unclear. The amygdala and prefrontal cortex are strongly innervated by serotonergic projections and have been suggested to play an important role in anxiety expression. However, serotonergic function in behaviour and SSRI-mediated neurobiological changes remain incompletely understood. To investigate the neural correlates of subchronic antidepressant administration. We investigated whether the 2- to 3-week administration of a highly selective SSRI (escitalopram) would alter brain activation on a task robustly shown to recruit the bilateral amygdala and frontal cortices in a large healthy volunteer sample. Participants performed the task during a functional magnetic resonance imaging acquisition before (n = 96) and after subchronic escitalopram (n = 46, days of administration mean (SD) = 15.7 (2.70)) or placebo (n = 40 days of administration mean (SD) = 16.2 (2.90)) self-administration. Compared to placebo, we found an elevation in right amygdala activation to the task after escitalopram administration without significant changes in mood. This effect was not seen in the left amygdala, the dorsomedial region of interest, the subgenual anterior cingulate cortex or the right fusiform area. There were no significant changes in connectivity between the dorsomedial cortex and amygdala or the subgenual anterior cingulate cortex after escitalopram administration. To date, this most highly powered study of subchronic SSRI administration indicates that, contrary to effects often seen in patients with anxiety disorders, subchronic SSRI treatment may increase amygdala activation in healthy controls. This finding highlights important gaps in our understanding of the functional role of serotonin.

COVID-19 related cognitive, structural and functional brain changes among Italian adolescents and young adults: a multimodal longitudinal case-control study

Coronavirus disease 2019 (COVID-19) has been associated with brain functional, structural, and cognitive changes that persist months after infection. Most studies of the neurologic outcomes related to COVID-19 focus on severe infection and aging populations. Here, we investigated the neural activities underlying COVID-19 related outcomes in a case-control study of mildly infected youth enrolled in a longitudinal study in Lombardy, Italy, a global hotspot of COVID-19. All participants (13 cases, 27 controls, mean age 24 years) completed resting-state functional (fMRI), structural MRI, cognitive assessments (CANTAB spatial working memory) at baseline (pre-COVID) and follow-up (post-COVID). Using graph theory eigenvector centrality (EC) and data-driven statistical methods, we examined differences in ECdelta (i.e., the difference in EC values pre- and post-COVID-19) and Volumetricdelta (i.e., the difference in cortical volume of cortical and subcortical areas pre- and post-COVID) between COVID-19 cases and controls. We found that ECdelta significantly between COVID-19 and healthy participants in five brain regions; right intracalcarine cortex, right lingual gyrus, left hippocampus, left amygdala, left frontal orbital cortex. The left hippocampus showed a significant decrease in Volumetricdelta between groups (p = 0.041). The reduced ECdelta in the left amygdala associated with COVID-19 status mediated the association between COVID-19 and disrupted spatial working memory. Our results show persistent structural, functional and cognitive brain changes in key brain areas associated with olfaction and cognition. These results may guide treatment efforts to assess the longevity, reversibility and impact of the observed brain and cognitive changes following COVID-19.

Standardized weighted low-resolution electromagnetic tomography study of the amygdala activity in patients with comorbid major depressive disorder and anxiety symptoms

Major depressive disorder (MDD) often coexists with anxiety disorders or symptoms, as identified by previous functional magnetic resonance imaging (fMRI) studies. These studies have found abnormal amplitudes of low-frequency fluctuations (ALFF) in the amygdala, which serve as traits and state markers of MDD. This study used standardized weighted low-resolution electromagnetic tomography (swLORETA) technology to explore amygdala markers in patients with comorbid MDD and anxiety. Participants included patients with MDD comorbid with anxiety symptoms (MDD group) and healthy controls (HC group) who completed the Beck Depression Inventory-II (BDI-II) and the Beck Anxiety Inventory (BAI). EEG data collected under resting state, happiness recall, and depressive recall tasks were converted into current-source density (CSD) values using swLORETA to assess amygdala activation. The results indicated higher beta2, beta3, and high beta levels in both the left and right amygdalae during the resting state in the MDD group than in the HC group. Similarly, elevated levels of beta2, beta3, and high beta were observed in the left and right amygdalae of the MDD group during happiness and depressive recall tasks. These findings support the presence of hyperactivity in the amygdala under resting state and emotional tasks in patients with comorbid MDD and anxiety symptoms.

Multimodal imaging of the amygdala in non-clinical subjects with high vs. low autistic-like social skills traits

Recent clinical and theoretical frameworks suggest that social skills and theory of mind impairments characteristic of autism spectrum disorder (ASD) are distributed in the general population on a continuum between healthy individuals and patients. The present multimodal study aimed at investigating the amygdala's function, perfusion, and volume in 56 non-clinical subjects from the general population with high (n=28 High-SOC) or low (n=28 Low-SOC) autistic-like social skills traits. Participants underwent magnetic resonance imaging to evaluate the amygdala's functional connectivity at rest, blood perfusion by means of arterial spin labelling, its activation during a face evaluation task and lastly grey matter volumes. The High-SOC group was characterised by higher blood perfusion in both amygdalae, lower volume of the left amygdala and higher activations of the right amygdala during processing of human faces with fearful value. Resting state analyses did not reveal any significant difference between the two groups. Overall, our results highlight the presence of overlapping morpho-functional alterations of the amygdala between healthy individuals and ASD patients confirming the importance of the amygdala in this disorder and in social and emotional processing. Our findings may help disentangle the neurobiological facets of ASD elucidating aetiology and the relationship between clinical symptomatology and neurobiology.

Sex-Specific Effects of Early Life Unpredictability on Hippocampal and Amygdala Responses to Novelty in Adolescents.

Unpredictable childhood experiences are an understudied form of early life adversity that impacts neurodevelopment in a sex-specific manner. The neurobiological processes by which exposure to early-life unpredictability impacts development and vulnerability to psychopathology remain poorly understood. The present study investigates the sex-specific consequences of early-life unpredictability on the limbic network, focusing on the hippocampus and the amygdala. Participants included 150 youth (54% female). Early life unpredictability was assessed using the Questionnaire of Unpredictability in Childhood (QUIC). Participants engaged in a task-fMRI scan between the ages of 8 and 17 (223 total observations) measuring BOLD responses to novel and familiar scenes. Exposure to early-life unpredictability associated with BOLD contrast (novel vs. familiar) in a sex-specific manner. For males, but not females, higher QUIC scores were associated with lower BOLD activation in response to novel vs. familiar stimuli in the hippocampal head and amygdala. Secondary psychophysiological interaction (PPI) analyses revealed complementary sex-specific associations between QUIC and condition-specific functional connectivity between the right and left amygdala, as well as between the right amygdala and hippocampus bilaterally. Exposure to unpredictability in early life has persistent implications for the functional operations of limbic circuits. Importantly, consistent with emerging experimental animal and human studies, the consequences of early life unpredictability differ for males and females. Further, impacts of early-life unpredictability were independent of other risk factors including lower household income and negative life events, indicating distinct consequences of early-life unpredictability over and above more commonly studied types of early life adversity.

Investigating Functional Connectivity in Adolescent Depression and Suicide Attempt during Neurofeedback Sessions: A Multivariate Random Covariance Model Approach

Background A recent neurofeedback functional magnetic resonance imaging (NF, fMRI) study on depressed vs. healthy adolescents elicited differential functional connectivity (FC) amongst brain regions of interest (ROIs). Previous results employed univariate methods and included only two seed areas of FC (amygdala and hippocampus). In this study, we propose a new multivariate analysis for whole-network FC estimation. Methods Primary analyses concerned a pre-identified network of 17 salient ROIs reflecting key regions in self-processing and emotion regulation. A random covariance model (RCM) was applied to jointly estimate participant- and group-specific connectivity, where FC was measured by partial correlation conditioned on or adjusted for rest-of-network connectivity patterns. Secondary analyses concerned participant-specific network association with mental functioning changes and the AAL3 whole-brain atlas. Results New findings suggested that depressed adolescents with a suicide attempt expressed significantly higher positive FC between the left temporal gyrus and the left amygdala during NF, compared to negative FC in non-attempting depressed youth, while healthy controls displayed negative FC between the insula, inferior frontal gyrus to inferior parietal lobe connection, compared to mild negative connectivity in depressed adolescents. Previous cross-hemispheric findings in depressed vs. healthy adolescents were corroborated. Conclusion A multivariate RCM uncovered key ROI-pairwise connections differentiating FC patterns between depressed youth vs. healthy controls and among depressed youth, with and without a suicide attempt. Findings were strengthened by enhanced inference vs. univariate methods, and corroboration of previous NF secondary analyses demonstrated future utility for participant-specific study in association with clinical outcomes and/or whole-brain analyses with larger sample sizes.

Association between subcortical nuclei volume changes and cognition in preschool-aged children with tetralogy of Fallot after corrective surgery: a cross-sectional study

BackgroundNeurocognitive disorders frequently occur in patients with cyanotic congenital heart disease (CCHD) because of the hemodynamic abnormalities induced by preoperative cardiac structural changes. We aimed to evaluate subcortical nuclei volume changes and cognition in postoperative tetralogy of Fallot (TOF) children, and analyze their relationship with preoperative cardiac structural changes.MethodsThis case-control study involved thirty-six children with repaired TOF and twenty-nine healthy controls (HCs). We utilized three-dimensional (3D) T1-weighted high-resolution structural images alongside the Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition (WPPSI-IV) to evaluate the cognitive differences between the TOF and HC group.ResultsWe observed notable differences in subcortical nuclei volume between the TOF and HC group, specifically in the left amygdala nucleus (LAM, TOF: 1292.60 ± 155.57; HC: 1436.27 ± 140.62, p < 0.001), left thalamus proper nucleus (LTHA, TOF: 6771.54 ± 666.03; HC: 7435.36 ± 532.84, p < 0.001), and right thalamus proper nucleus (RTHA, TOF: 6514.61 ± 715.23; HC: 7162.94 ± 554.60, p < 0.001). Furthermore, a diminished integrity of LAM ( β:-19.828, 95% CI: -36.462, -3.193), which showed an inverse relationship with the size of the preoperative ventricular septal defect (VSD), correlated with lower working memory indices in children with TOF.ConclusionsOur findings indicate that subcortical nuclei structural injuries possibly potentially stemming from cardiac anatomical abnormalities, are associated with impaired working memory in preschool-aged children with TOF. The LAM in particular may serve as a potential biomarker for neurocognitive deficits in TOF, offering predictive value for future neurodevelopmental outcomes, and shedding light on the neurophysiological mechanisms of these cognitive impairments.

Neural adaptation of the reward system in primary dysmenorrhea.

Introduction: The brain's reward system (RS) reacts differently to pain and its alleviation. This study examined the correlation between RS activity and behavior during both painful and pain-free periods in individuals with primary dysmenorrhea (PDM) to elucidate their varying responses throughout the menstrual cycle. Methods: Ninety-two individuals with PDM and 90 control participants underwent resting-state functional magnetic resonance imaging (rsfMRI) scans during their menstrual and peri-ovulatory phases. Regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) analyses were used to evaluate RS responses. Psychological evaluations were conducted using the McGill Pain Questionnaire and the Pain Catastrophizing Scale. Results: ReHo analysis showed higher values in the left putamen and right amygdala of the PDM group during the peri-ovulatory phase compared to the menstrual phase. ALFF analysis revealed lower values in the putamen of the PDM group compared to controls, regardless of phase. ReHo and ALFF values in the putamen, amygdala, and nucleus accumbens were positively correlated with pain scales during menstruation, while ALFF values in the ventral tegmental area inversely correlated with pain intensity. Those with severe PDM (pain intensity ≥7) displayed distinct amygdala ALFF patterns between pain and pain-free phases. PDM participants also had lower ReHo values in the left insula during menstruation, with no direct correlation to pain compared to controls. Discussion: Our study highlights the pivotal role of the RS in dysmenorrhea management, exhibiting varied responses between menstrual discomfort and non-painful periods among individuals with PDM. During menstruation, the RS triggers mechanisms for pain avoidance and cognitive coping strategies, while it transitions to processing rewards during the peri-ovulatory phase. This demonstrates the flexibility of the RS in adapting to the recurring pain experienced by those with PDM.

Decision-Making with Predictions of Others' Likely and Unlikely Choices in the Human Brain.

For better decisions in social interactions, humans often must understand the thinking of others and predict their actions. Since such predictions are uncertain, multiple predictions may be necessary for better decision-making. However, the neural processes and computations underlying such social decision-making remain unclear. We investigated this issue by developing a behavioral paradigm and performing functional magnetic resonance imaging and computational modeling. In our task, female and male participants were required to predict others' choices in order to make their own value-based decisions, as the outcome depended on others' choices. Results showed, to make choices, the participants mostly relied on a value difference (primary) generated from the case where others would make a likely choice, but sometimes they additionally used another value difference (secondary) from the opposite case where others make an unlikely choice. We found that the activations in the posterior cingulate cortex (PCC) correlated with the primary difference while the activations in the right dorsolateral prefrontal cortex (rdlPFC) correlated with the secondary difference. Analysis of neural coupling and temporal dynamics suggested a three-step processing network, beginning with the left amygdala signals for predictions of others' choices. Modulated by these signals, the PCC and rdlPFC reflect the respective value differences for self-decisions. Finally, the medial prefrontal cortex integrated these decision signals for a final decision. Our findings elucidate the neural process of constructing value-based decisions by predicting others and illuminate their key variables with social modulations, providing insight into the differential functional roles of these brain regions in this process.

A prediction model of dementia conversion for mild cognitive impairment by combining plasma pTau181 and structural imaging features.

The early stages of Alzheimer's disease (AD) are no longer insurmountable. Therefore, identifying at-risk individuals is of great importance for precise treatment. We developed a model to predict cognitive deterioration in patients with mild cognitive impairment (MCI). Based on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, we constructed models in a derivation cohort of 761 participants with MCI (138 of whom developed dementia at the 36th month) and verified them in a validation cohort of 353 cognitively normal controls (54 developed MCI and 19 developed dementia at the 36th month). In addition, 1303 participants with available AD cerebrospinal fluid core biomarkers were selected to clarify the ability of the model to predict AD core features. We assessed 32 parameters as candidate predictors, including clinical information, blood biomarkers, and structural imaging features, and used multivariable logistic regression analysis to develop our prediction model. Six independent variables of MCI deterioration were identified: apolipoprotein E ε4 allele status, lower Mini-Mental State Examination scores, higher levels of plasma pTau181, smaller volumes of the left hippocampus and right amygdala, and a thinner right inferior temporal cortex. We established an easy-to-use risk heat map and risk score based on these risk factors. The area under the curve (AUC) for both internal and external validations was close to 0.850. Furthermore, the AUC was above 0.800 in identifying participants with high brain amyloid-β loads. Calibration plots demonstrated good agreement between the predicted probability and actual observations in the internal and external validations. We developed and validated an accurate prediction model for dementia conversion in patients with MCI. Simultaneously, the model predicts AD-specific pathological changes. We hope that this model will contribute to more precise clinical treatment and better healthcare resource allocation.

Brain network analysis in Parkinson's disease patients based on graph theory

Development of Parkinson's disease causes functional impairment in the brain network of Parkinson's patients. The aim of this study is to analyze brain networks of people with Parkinson's disease based on higher resolution parcellations and newer graphical features. The topological features of brain networks were investigated in Parkinson's patients (19 individuals) compared to healthy individuals (17 individuals) using graph theory. In addition, four different methods were used in graph formation to detect linear and nonlinear relationships between functional magnetic resonance imaging (fMRI) signals. The functional connectivity between the left precuneus and the left amygdala, as well as between the vermis 1-2 and the left temporal lobe was evaluated for the healthy and the patient groups. The difference between the healthy and patient groups was evaluated by parametric t-test and nonparametric U-test. Based on the results, Parkinson's patients exhibited a noteworthy reduction in centrality criterion compared to healthy subjects. Moreover, alterations in the regional features of the brain network were evident. Applying centrality criteria and correlation coefficients revealed significant distinctions between healthy subjects and Parkinson's patients across various brain areas. The results obtained for topological features indicate changes in the functional brain network of Parkinson's patients. Finally, similar areas obtained by all three methods of graph formation in the evaluation of connectivity between paired regions in the brain network of Parkinson's patients increased the reliability of the results.

Acupuncture modulates emotional network resting-state functional connectivity in patients with insomnia disorder: a randomized controlled trial and fMRI study

BackgroundInsomnia disorder (ID) is one of the most common sleep problems, usually accompanied by anxiety and depression symptoms. Functional magnetic resonance imaging (fMRI) study suggests that both poor sleep quality and negative emotion are linked to the dysregulation of brain network related to emotion processing in ID patients. Acupuncture therapy has been proven effective in improving sleep quality and mood of ID patients, but the involved neurobiological mechanism remains unclear. We aimed to investigate the modulation effect of acupuncture on resting-state functional connectivity (rsFC) of the emotional network (EN) in patients experiencing insomnia.MethodsA total of 30 healthy controls (HCs) and 60 ID patients were enrolled in this study. Sixty ID patients were randomly assigned to real and sham acupuncture groups and attended resting-state fMRI scans before and after 4 weeks of acupuncture treatment. HCs completed an MRI/fMRI scan at baseline. The rsFC values within EN were calculated, and Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD), Pittsburgh Sleep Quality Index (PSQI), Hyperarousal Scale (HAS), and actigraphy data were collected for clinical efficacy evaluation.ResultsResting-state FC analysis showed abnormalities in rsFC centered on the thalamus and dorsolateral prefrontal cortex within EN of ID patients compared to HCs. After real acupuncture treatment, rsFC of the anterior cingulate cortex, hippocampus, and amygdala were increased compared with the sham acupuncture group (p < 0.05, FDR corrected). In real acupuncture group, the rsFC value was decreased between left amygdala and left thalamus after 4 weeks of treatment compared with baseline. A trend of correlation was found that the increased rsFC value between the right amygdala and left hippocampus was positively correlated with the decreased HAMA scores across all ID patients, and the decreased left amygdala rsFC value with the left thalamus was negatively correlated with the increased sleep efficiency in the real acupuncture group.ConclusionOur findings showed that real acupuncture could produce a positive effect on modulating rsFC within network related to emotion processing in ID patients, which may illustrate the central mechanism underlying acupuncture for insomnia in improving sleep quality and emotion regulation.Trial registrationhttp://www.chictr.org.cn., ChiCTR1800015282, 20/03/2018.

Amygdala connectivity is associated with withdrawn/depressed behavior in a large sample of children from the Adolescent Brain Cognitive Development (ABCD) Study®

Many psychopathologies tied to internalizing symptomatology emerge during adolescence, therefore identifying neural markers of internalizing behavior in childhood may allow for early intervention. We utilized data from the Adolescent Brain and Cognitive Development (ABCD) Study® to evaluate associations between cortico-amygdalar functional connectivity, polygenic risk for depression (PRSD), traumatic events experienced, internalizing behavior, and internalizing subscales: withdrawn/depressed behavior, somatic complaints, and anxious/depressed behaviors. Data from 6371 children (ages 9–11) were used to analyze amygdala resting-state fMRI connectivity to Gordon parcellation based whole-brain regions of interest (ROIs). Internalizing behaviors were measured using the parent-reported Child Behavior Checklist. Linear mixed-effects models were used to identify patterns of cortico-amygdalar connectivity associated with internalizing behaviors. Results indicated left amygdala connections to auditory, frontoparietal network (FPN), and dorsal attention network (DAN) ROIs were significantly associated with withdrawn/depressed symptomatology. Connections relevant for withdrawn/depressed behavior were linked to social behaviors. Specifically, amygdala connections to DAN were associated with social anxiety, social impairment, and social problems. Additionally, an amygdala connection to the FPN ROI and the auditory network ROI was associated with social anxiety and social problems, respectively. Therefore, it may be important to account for social behaviors when looking for brain correlates of depression.

Association of olfactory and cognitive function test scores with hippocampal and amygdalar grey matter volume: a cross-sectional study

Few population-based studies including younger adults have examined the potential of olfactory function tests to capture the degree of atrophy in memory-associated brain regions, which cannot be adequately explained by cognitive function tests screening for cognitive impairment. This population-based study investigated associations between high-resolution olfactory test data with few odours and grey matter volumes (GMVs) of the left and right hippocampi, amygdala, parahippocampi, and olfactory cortex, while accounting for differences in cognitive decline, in 1444 participants (aged 31–91 years). Regression analyses included intracranial volume (ICV)-normalised GMVs of eight memory-related regions as objective variables and age, sex, education duration, smoking history, olfaction test score, and the Montreal Cognitive Assessment-Japanese version (MoCA-J) score as explanatory variables. Significant relationships were found between olfactory test scores and ICV-normalised GMVs of the left and right hippocampi and left amygdala (p = 0.020, 0.024, and 0.028, respectively), adjusting for the MoCA-J score. The olfactory test score was significantly related to the right amygdalar GMV (p = 0.020) in older adults (age ≥ 65 years). These associations remained significant after applying Benjamini–Hochberg multiple testing correction (false discovery rate < 0.1). Therefore, olfactory and cognitive function tests may efficiently capture the degree of atrophy in the hippocampi and amygdala, especially in older adults.