A reliable protocol for the manual segmentation of the human amygdala and its subregions using ultra-high resolution MRI

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.

Neuromorphometric associations with mood, cognition, and self-reported exercise levels in epilepsy and healthy individuals

Regular physical activity may promote beneficial neuroplasticity, e.g., increased hippocampus volume. However, it is unclear whether self-reported physical exercise in leisure (PEL) levels are associated with the brain structure features demonstrated by exercise interventions. This pilot study investigated the relationship between PEL, mood, cognition, and neuromorphometry in patients with idiopathic generalized epilepsy (IGEs) compared to healthy controls (HCs). Seventeen IGEs and 19 age- and sex-matched HCs underwent magnetic resonance imaging (MRI) at 3T. The Baecke Questionnaire of Habitual Physical Activity, Profile of Mood States, and Montreal Cognitive Assessment (MoCA) assessed PEL, mood, and cognition, respectively. Structural MRI data were analyzed by voxel- and surface-based morphometry. IGEs had significantly lower PEL (p < 0.001), poorer mood (p = 0.029), and lower MoCA scores (p = 0.027) than HCs. These group differences were associated with reduced volume, decreased gyrification, and altered surface topology (IGEs < HCs) in frontal, temporal and cerebellar regions involved in executive function, memory retrieval, and emotional regulation, respectively. These preliminary results support the notion that increased PEL may promote neuroplasticity in IGEs, thus emphasizing the role of physical activity in promoting brain health in people with epilepsy.

Shrinkage of olfactory amygdala connotes cognitive impairment in patients with Parkinson's disease

During the caudo-rostral progression of Lewy pathology, the amygdala is involved relatively early in Parkinson's disease (PD). However, lesser is known about the volumetric differences at the amygdala subdivisions, although the evidence mainly implicates the olfactory amygdala. We aimed to investigate the volumetric differences between the amygdala's nuclear and sectoral subdivisions in the PD cognitive impairment continuum compared to healthy controls (HC). The volumes of nine nuclei of the amygdala were estimated with FreeSurfer (nuclear parcellation-NP) from T1-weighted images of PD patients with normal cognition (PD-CN), PD with mild cognitive impairment (PD-MCI), PD with dementia (PD-D), and HC. The appropriate nuclei were then merged to obtain three sectors of the amygdala (sectoral parcellation-SP). The nuclear and sectoral volumes were compared among the four groups and between the hyposmic and normosmic PD patients. There was a significant difference in the total amygdala volume among the four groups. In terms of nuclei, the bilateral cortico-amygdaloid transition area (CAT) and sectors superficial cortex-like region (sCLR) volumes of PD-MCI and PD-D were less than those of the PD-CN and HC. A linear discriminant analysis revealed that left CAT and left sCLR volumes classified the PD-CN and cognitively impaired PD (PD-CI: PD-MCI plus PD-D) with 90.7% accuracy according to NP and 85.2% accuracy to SP. Similarly, left CAT and sCLR volumes correctly identified the hyposmic and normosmic PD with 64.8% and 61.1% accuracies. Notably, the left olfactory amygdala volume successfully discriminated cognitive impairment in PD and could be used as neuroimaging-based support for PD-CI diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09887-y.

A comparison of the five-minute cognitive test with the mini-mental state examination in the elderly for cognitive impairment screening

The five-minute cognitive test (FCT) is a novel cognitive screening method with the quick and reliable merit for detecting cognitive impairment at an early stage. The diagnostic power of FCT in differentiating subjects with cognitive impairment from people with cognition in a normal range was demonstrated effective as that of the Mini-Mental Status Evaluation (MMSE) in a previous cohort study. Here, we analyzed the effect of sociodemographic and health-related factors on FCT performance and further investigated the consistency of FCT. Then, we compared the correlation of subitem scores of FCT or MMSE with a comprehensive battery of neuropsychological tests that focus on specific domains of cognition. Finally, the association of the total FCT scores with the volumes of brain subregions was investigated. There were 360 subjects aged 60 years or above enrolled in this study, including 226 adults with cognitive abilities in normal range, 107 subjects with mild cognitive impairment (MCI) and 27 mild Alzheimer's disease (AD). The results showed that the total FCT scores was negatively associated with increasing age (β = -0.146, p < 0.001), and positively associated with education attainment (β = 0.318, p < 0.001), dwelling condition with family (β = 0.153, p < 0.001) and the Body Mass Index (β = 1.519, p < 0.01). The internal consistency of the FCT (Cronbach's α) was 0.644. The sub-scores of FCT showed a significant correlation with other specific neuropsychological tests. Impressively, the total FCT scores showed a significantly positive association with the volumes of hippocampus related subregions (r = 0.523, p < 0.001) and amygdala (r = 0.479, p < 0.001), but not with cerebellum (r = 0.158, p > 0.05) or subcortical subregions (r = 0.070, p > 0.05). Combining with previous data, FCT is a reliable and valid cognitive screening test for detecting cognitive impairment in a community setting.

Quantifying numerical and spatial reliability of hippocampal and amygdala subdivisions in FreeSurfer

On-going, large-scale neuroimaging initiatives can aid in uncovering neurobiological causes and correlates of poor mental health, disease pathology, and many other important conditions. As projects grow in scale with hundreds, even thousands, of individual participants and scans collected, quantification of brain structures by automated algorithms is becoming the only truly tractable approach. Here, we assessed the spatial and numerical reliability for newly deployed automated segmentation of hippocampal subfields and amygdala nuclei in FreeSurfer 7. In a sample of participants with repeated structural imaging scans (N = 928), we found numerical reliability (as assessed by intraclass correlations, ICCs) was reasonable. Approximately 95% of hippocampal subfields had "excellent" numerical reliability (ICCs ≥ 0.90), while only 67% of amygdala subnuclei met this same threshold. In terms of spatial reliability, 58% of hippocampal subfields and 44% of amygdala subnuclei had Dice coefficients ≥ 0.70. Notably, multiple regions had poor numerical and/or spatial reliability. We also examined correlations between spatial reliability and person-level factors (e.g., participant age; T1 image quality). Both sex and image scan quality were related to variations in spatial reliability metrics. Examined collectively, our work suggests caution should be exercised for a few hippocampal subfields and amygdala nuclei with more variable reliability.

Reorganization in the macaque interoceptive-allostatic network following anterior cingulate cortex damage

Accumulating evidence indicates that the adult brain is capable of significant structural change following damage-a capacity once thought to be largely limited to developing brains. To date, most existing research on adult plasticity has focused on how exteroceptive sensorimotor networks compensate for damage to preserve function. Interoceptive networks-those that represent and process sensory information about the body's internal state-are now recognized to be critical for a wide range of physiological and psychological functions from basic energy regulation to maintaining a sense of self, but the extent to which these networks remain plastic in adulthood has not been established. In this report, we used detailed histological analyses to pinpoint precise changes to gray matter volume in the interoceptive-allostatic network in adult rhesus monkeys (Macaca mulatta) who received neurotoxic lesions of the anterior cingulate cortex (ACC) and neurologically intact control monkeys. Relative to controls, monkeys with ACC lesions had significant and selective unilateral expansion of the ventral anterior insula and significant relative bilateral expansion of the lateral nucleus of the amygdala. This work demonstrates the capacity for neuroplasticity in the interoceptive-allostatic network which, given that changes included expansion rather than atrophy, is likely to represent an adaptive response following damage.

Seeking the Amygdala: Novel Use of Diffusion Tensor Imaging to Delineate the Basolateral Amygdala

The amygdaloid complex, including the basolateral nucleus (BLA), contributes crucially to emotional and cognitive brain functions, and is a major target of research in both humans and rodents. However, delineating structural amygdala plasticity in both normal and disease-related contexts using neuroimaging has been hampered by the difficulty of unequivocally identifying the boundaries of the BLA. This challenge is a result of the poor contrast between BLA and the surrounding gray matter, including other amygdala nuclei. Here, we describe a novel diffusion tensor imaging (DTI) approach to enhance contrast, enabling the optimal identification of BLA in the rodent brain from magnetic resonance (MR) images. We employed this methodology together with a slice-shifting approach to accurately measure BLA volumes. We then validated the results by direct comparison to both histological and cellular-identity (parvalbumin)-based conventional techniques for defining BLA in the same brains used for MRI. We also confirmed BLA connectivity targets using DTI-based tractography. The novel approach enables the accurate and reliable delineation of BLA. Because this nucleus is involved in and changed by developmental, degenerative and adaptive processes, the instruments provided here should be highly useful to a broad range of neuroimaging studies. Finally, the principles used here are readily applicable to numerous brain regions and across species.

Human amygdala compared to orbitofrontal cortex connectivity, and emotion

The amygdala and orbitofrontal cortex have been implicated in emotion. To understand these regions better in humans, their effective connectivity with 360 cortical regions was measured in 171 humans from the Human Connectome Project, and complemented with functional connectivity and diffusion tractography. The human amygdala has effective connectivity from few cortical regions compared to the orbitofrontal cortex: primarily from auditory cortex A5 and the related superior temporal gyrus and temporal pole regions; the piriform (olfactory) cortex; the lateral orbitofrontal cortex 47m; somatosensory cortex; the hippocampus, entorhinal cortex, perirhinal cortex, and parahippocampal TF; and from the cholinergic nucleus basalis. The amygdala has effective connectivity to the hippocampus, entorhinal and perirhinal cortex; to the temporal pole; and to the lateral orbitofrontal cortex. The orbitofrontal cortex has effective connectivity from gustatory, olfactory, and temporal visual, auditory and pole cortex, and to the pregenual anterior and posterior cingulate cortex, hippocampal system, and prefrontal cortex, and provides for rewards and punishers to be used in reported emotions, and memory and navigation to goals. Given the paucity of amygdalo-neocortical connectivity in humans, it is proposed that the human amygdala is involved primarily in autonomic and conditioned responses via brainstem connectivity, rather than in reported (declarative) emotion.

High-resolution atlasing and segmentation of the subcortex: Review and perspective on challenges and opportunities created by machine learning

This paper reviews almost three decades of work on atlasing and segmentation methods for subcortical structures in human brain MRI. In writing this survey, we have three distinct aims. First, to document the evolution of digital subcortical atlases of the human brain, from the early MRI templates published in the nineties, to the complex multi-modal atlases at the subregion level that are available today. Second, to provide a detailed record of related efforts in the automated segmentation front, from earlier atlas-based methods to modern machine learning approaches. And third, to present a perspective on the future of high-resolution atlasing and segmentation of subcortical structures in in vivo human brain MRI, including open challenges and opportunities created by recent developments in machine learning.

Cortical and subcortical grey matter atrophy in Amyotrophic Lateral Sclerosis correlates with measures of disease accumulation independent of disease aggressiveness

There is a growing demand for reliable biomarkers to monitor disease progression in Amyotrophic Lateral Sclerosis (ALS) that also take the heterogeneity of ALS into account. In this study, we explored the association between Magnetic Resonance Imaging (MRI)-derived measures of cortical thickness (CT) and subcortical grey matter (GM) volume with D50 model parameters. T1-weighted MRI images of 72 Healthy Controls (HC) and 100 patients with ALS were analyzed using Surface-based Morphometry for cortical structures and Voxel-based Morphometry for subcortical Region-Of-Interest analyses using the Computational Anatomy Toolbox (CAT12). In Inter-group contrasts, these parameters were compared between patients and HC. Further, the D50 model was used to conduct subgroup-analyses, dividing patients by a) Phase of disease covered at the time of MRI-scan and b) individual overall disease aggressiveness. Finally, correlations between GM and D50 model-derived parameters were examined. Inter-group analyses revealed ALS-related cortical thinning compared to HC located mainly in frontotemporal regions and a decrease in GM volume in the left hippocampus and amygdala. A comparison of patients in different phases showed further cortical and subcortical GM atrophy along with disease progression. Correspondingly, regression analyses identified negative correlations between cortical thickness and individual disease covered. However, there were no differences in CT and subcortical GM between patients with low and high disease aggressiveness. By application of the D50 model, we identified correlations between cortical and subcortical GM atrophy and ALS-related functional disability, but not with disease aggressiveness. This qualifies CT and subcortical GM volume as biomarkers representing individual disease covered to monitor therapeutic interventions in ALS.

Convolutional Neural Networks Enable Robust Automatic Segmentation of the Rat Hippocampus in MRI After Traumatic Brain Injury

Registration-based methods are commonly used in the automatic segmentation of magnetic resonance (MR) brain images. However, these methods are not robust to the presence of gross pathologies that can alter the brain anatomy and affect the alignment of the atlas image with the target image. In this work, we develop a robust algorithm, MU-Net-R, for automatic segmentation of the normal and injured rat hippocampus based on an ensemble of U-net-like Convolutional Neural Networks (CNNs). MU-Net-R was trained on manually segmented MR images of sham-operated rats and rats with traumatic brain injury (TBI) by lateral fluid percussion. The performance of MU-Net-R was quantitatively compared with methods based on single and multi-atlas registration using MR images from two large preclinical cohorts. Automatic segmentations using MU-Net-R and multi-atlas registration were of excellent quality, achieving cross-validated Dice scores above 0.90 despite the presence of brain lesions, atrophy, and ventricular enlargement. In contrast, the performance of single-atlas segmentation was unsatisfactory (cross-validated Dice scores below 0.85). Interestingly, the registration-based methods were better at segmenting the contralateral than the ipsilateral hippocampus, whereas MU-Net-R segmented the contralateral and ipsilateral hippocampus equally well. We assessed the progression of hippocampal damage after TBI by using our automatic segmentation tool. Our data show that the presence of TBI, time after TBI, and whether the hippocampus was ipsilateral or contralateral to the injury were the parameters that explained hippocampal volume.

Neurite density imaging in amygdala nuclei reveals interindividual differences in neuroticism

Neuroticism is known to have significant health implications. While previous research revealed that interindividual differences in the amygdala function are associated with interindividual differences in neuroticism, the impact of the amygdala’s structure and especially microstructure on variations in neuroticism remains unclear. Here, we present the first study using NODDI to examine the association between the in vivo microstructural architecture of the amygdala and neuroticism at the level of neurites. We, therefore, acquired brain images from 221 healthy participants using advanced multi‐shell diffusion‐weighted imaging. Because the amygdala comprises several nuclei, we, moreover, used a high‐resolution T1 image to automatically segment the amygdala into eight different nuclei. Neuroticism and its facets have been assessed using the NEO‐PI‐R. Finally, we associated neuroticism and its facets with the volume and microstructure of the amygdala nuclei. Statistical analysis revealed that lower neurite density in the lateral amygdala nucleus (La) was significantly associated with higher scores in depression, one of the six neuroticism facets. The La is the sensory relay of the amygdala, filtering incoming information based on previous experiences. Reduced neurite density and related changes in the dendritic structure of the La could impair its filtering function. This again might cause harmless sensory information to be misevaluated as threatening and lead to the altered amygdala responsivity as reported in previous studies investigating the functional correlates of neuroticism and neuroticism‐related disorders like depression.

Nucleus accumbens projections: Validity and reliability of fiber reconstructions based on high-resolution diffusion-weighted MRI

Clinical effects of deep brain stimulation are largely mediated by the activation of myelinated axons. Hence, increasing attention has been paid in the past on targeting white matter tracts in addition to gray matter. Aims of the present study were: (i) visualization of discrete afferences and efferences of the nucleus accumbens (NAc), supposed to be a major hub of neural networks relating to mental disorders, using probabilistic fiber tractography and a data driven approach, and (ii) validation of the applied methodology for standardized routine clinical applications. MR‐data from 11 healthy subjects and 7 measurement sessions each were acquired on a 3T MRI‐scanner. For probabilistic fiber tracking the NAc as a seed region and the medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), amygdala (AMY), hippocampus (HPC), dorsomedial thalamus (dmT) and ventral tegmental area (VTA) as target regions were segmented for each subject and both hemispheres. To quantitatively assess the reliability and stability of the reconstructions, we filtered and clustered the individual fiber‐tracts (NAc to target) for each session and subject and performed a point‐by‐point calculation of the maximum cluster distances for intra‐subject comparison. The connectivity patterns formed by the obtained fibers were in good concordance with published data from tracer and/or fiber‐dissection studies. Furthermore, the reliability assessment of the (NAc to target)‐fiber‐tracts yielded to high correlations between the obtained clustered‐tracts. Using DBS with directional lead technology, the workflow elaborated in this study may guide selective electrical stimulation of NAc projections.

An extended Human Connectome Project multimodal parcellation atlas of the human cortex and subcortical areas

A modified and extended version, HCPex, is provided of the surface-based Human Connectome Project-MultiModal Parcellation atlas of human cortical areas (HCP-MMP v1.0, Glasser et al. 2016). The original atlas with 360 cortical areas has been modified in HCPex for ease of use with volumetric neuroimaging software, such as SPM, FSL, and MRIcroGL. HCPex is also an extended version of the original atlas in which 66 subcortical areas (33 in each hemisphere) have been added, including the amygdala, thalamus, putamen, caudate nucleus, nucleus accumbens, globus pallidus, mammillary bodies, septal nuclei and nucleus basalis. HCPex makes available the excellent parcellation of cortical areas in HCP-MMP v1.0 to users of volumetric software, such as SPM and FSL, as well as adding some subcortical regions, and providing labelled coronal views of the human brain.

Nonclinical psychotic-like experiences and schizotypy dimensions: Associations with hippocampal subfield and amygdala volumes

Schizotypy and psychotic-like experiences (PLE) form part of the wider psychosis continuum and may have brain structural correlates in nonclinical cohorts. This study aimed to compare the effects of differential schizotypy dimensions, PLE, and their interaction on hippocampal subfields and amygdala volumes in the absence of clinical psychopathology. In a cohort of 367 psychiatrically healthy individuals, we assessed schizotypal traits using the Oxford-Liverpool Inventory of Life Experiences (O-LIFE) and PLE using the short form of the Prodromal Questionnaire (PQ-16). Based on high-resolution structural MRI scans, we used automated segmentation to estimate volumes of limbic structures. Sex and total intracranial volume (Step 1), PLE and schizotypy dimensions (Step 2), and their interaction terms (Step 3) were entered as regressors for bilateral amygdala and hippocampal subfield volumes in hierarchical multiple linear regression models. Positive schizotypy, but not PLE, was negatively associated with left amygdala and subiculum volumes. O-LIFE Impulsive Nonconformity, as well as the two-way interaction between positive schizotypy and PLE, were associated with larger left subiculum volumes. None of the estimators for right hemispheric hippocampal subfield volumes survived correction for multiple comparisons. Our findings support differential associations of hippocampus subfield volumes with trait dimensions rather than PLE, and support overlap and interactions between psychometric positive schizotypy and PLE. In a healthy cohort without current psychosis risk syndromes, the positive association between PLE and hippocampal subfield volume occurred at a high expression of positive schizotypy. Further studies combining stable, transient, and genetic parameters are required.

A randomised, double-blind, sham-controlled trial of deep brain stimulation of the bed nucleus of the stria terminalis for treatment-resistant obsessive-compulsive disorder

Deep brain stimulation (DBS) is a promising treatment for severe, treatment-resistant obsessive-compulsive disorder (OCD). Here, nine participants (four females, mean age 47.9 ± 10.7 years) were implanted with DBS electrodes bilaterally in the bed nucleus of the stria terminalis (BNST). Following a one-month postoperative recovery phase, participants entered a three-month randomised, double-blind, sham-controlled phase before a twelve-month period of open-label stimulation incorporating a course of cognitive behavioural therapy (CBT). The primary outcome measure was OCD symptoms as rated with the Yale-Brown Obsessive-Compulsive Scale (YBOCS). In the blinded phase, there was a significant benefit of active stimulation over sham (p = 0.025, mean difference 4.9 points). After the open phase, the mean reduction in YBOCS was 16.6 ± 1.9 points (χ² (11) = 39.8, p = 3.8 × 10^-5), with seven participants classified as responders. CBT resulted in an additive YBOCS reduction of 4.8 ± 3.9 points (p = 0.011). There were two serious adverse events related to the DBS device, the most severe of which was an infection during the open phase necessitating device explantation. There were no serious psychiatric adverse events related to stimulation. An analysis of the structural connectivity of each participant's individualised stimulation field isolated right-hemispheric fibres associated with YBOCS reduction. These included subcortical tracts incorporating the amygdala, hippocampus and stria terminalis, in addition to cortical regions in the ventrolateral and ventromedial prefrontal cortex, parahippocampal, parietal and extrastriate visual cortex. In conclusion, this study provides further evidence supporting the efficacy and tolerability of DBS in the region of the BNST for individuals with otherwise treatment-refractory OCD and identifies a connectivity fingerprint associated with clinical benefit.

Automated joint skull-stripping and segmentation with Multi-Task U-Net in large mouse brain MRI databases

Skull-stripping and region segmentation are fundamental steps in preclinical magnetic resonance imaging (MRI) studies, and these common procedures are usually performed manually. We present Multi-task U-Net (MU-Net), a convolutional neural network designed to accomplish both tasks simultaneously. MU-Net achieved higher segmentation accuracy than state-of-the-art multi-atlas segmentation methods with an inference time of 0.35 s and no pre-processing requirements. We trained and validated MU-Net on 128 T2-weighted mouse MRI volumes as well as on the publicly available MRM NeAT dataset of 10 MRI volumes. We tested MU-Net with an unusually large dataset combining several independent studies consisting of 1782 mouse brain MRI volumes of both healthy and Huntington animals, and measured average Dice scores of 0.906 (striati), 0.937 (cortex), and 0.978 (brain mask). Further, we explored the effectiveness of our network in the presence of different architectural features, including skip connections and recently proposed framing connections, and the effects of the age range of the training set animals. These high evaluation scores demonstrate that MU-Net is a powerful tool for segmentation and skull-stripping, decreasing inter and intra-rater variability of manual segmentation. The MU-Net code and the trained model are publicly available at https://github.com/Hierakonpolis/MU-Net.

A 7 Tesla Amygdalar-Hippocampal Shape Analysis of Lithium Response in Bipolar Disorder

Research to discover clinically useful predictors of lithium response in patients with bipolar disorder has largely found them to be elusive. We demonstrate here that detailed neuroimaging may have the potential to fill this important gap in mood disorder therapeutics. Lithium treatment and bipolar disorder have both been shown to affect anatomy of the hippocampi and amygdalae but there is no consensus on the nature of their effects. We aimed to investigate structural surface anatomy changes in amygdala and hippocampus correlated with treatment response in bipolar disorder. Patients with bipolar disorder (N = 14) underwent lithium treatment, were classified by response status at acute and long-term time points, and scanned with 7 Tesla structural MRI. Large Deformation Diffeomorphic Metric Mapping was applied to detect local differences in hippocampal and amygdalar anatomy between lithium responders and non-responders. Anatomy was also compared to 21 healthy comparison participants. A patch of the ventral surface of the left hippocampus was found to be significantly atrophied in non-responders as compared to responders at the acute time point and was associated at a trend-level with long-term response status. We did not detect an association between response status and surface anatomy of the right hippocampus or amygdala. To the best of our knowledge, this is the first shape analysis of hippocampus and amygdala in bipolar disorder using 7 Tesla MRI. These results can inform future work investigating possible neuroimaging predictors of lithium response in bipolar disorder.

Parcellation of the human amygdala using recurrence quantification analysis

Several previous attempts have been made to divide the human amygdala into smaller subregions based on the unique functional properties of the subregions. Although these attempts have provided valuable insight into the functional heterogeneity in this structure, the possibility that spatial patterns of functional characteristics can quickly change over time has rarely been considered in previous studies. In the present study, we explicitly account for the dynamic nature of amygdala activity. Our goal was not only to develop another parcellation method but also to augment existing methods with novel information about amygdala subdivisions. We performed state-specific amygdala parcellation using resting-state fMRI (rsfMRI) data and recurrence quantification analysis (RQA). RsfMRI data from 102 subjects were acquired with a 3T Trio Siemens scanner. We analyzed values of several RQA measures across all voxels in the amygdala and found two amygdala subdivisions, the ventrolateral (VL) and dorsomedial (DM) subdivisions, that differ with respect to one of the RQA measures, Shannon's entropy of diagonal lines. Compared to the DM subdivision, the VL subdivision can be characterized by a higher value of entropy. The results suggest that VL activity is determined and influenced by more brain structures than is DM activity. To assess the biological validity of the obtained subdivisions, we compared them with histological atlases and currently available parcellations based on structural connectivity patterns (Anatomy Probability Maps) and cytoarchitectonic features (SPM Anatomy toolbox). Moreover, we examined their cortical and subcortical functional connectivity. The obtained results are similar to those previously reported on parcellation performed on the basis of structural connectivity patterns. Functional connectivity analysis revealed that the VL subdivision has strong connections to several cortical areas, whereas the DM subdivision is mainly connected to subcortical regions. This finding suggests that the VL subdivision corresponds to the basolateral subdivision of the amygdala (BLA), while the DM subdivision has some characteristics typical of the centromedial amygdala (CMA). The similarity in functional connectivity patterns between the VL subdivision and BLA, as well as between the DM subdivision and CMA, confirm the utility of our parcellation method. Overall, the study shows that parcellation based on BOLD signal dynamics is a powerful tool for identifying distinct functional systems within the amygdala. This tool might be useful for future research on functional brain organization.

Quantitative MRI outcomes in child and adolescent leukemia survivors: Evidence for global alterations in gray and white matter

•

Studies of cognition in ALL survivors consistently show evidence of mild neurocognitive difficulties.

•

Structural MRI showed widespread differences between survivors and controls.

•

Gray and white matter volumes were respectively 5 and 6% smaller in survivors.

•

Survivors also exhibited altered white matter diffusion overall.

Introduction

Cure rates for pediatric acute lymphoblastic leukemia (ALL) have reached an all-time high (>90%); however, neurocognitive difficulties continue to affect quality of life in at least a subset of survivors. There are relatively few quantitative neuroimaging studies in child and adolescent ALL survivors treated with chemotherapy only. Use of different outcome measures or limited sample sizes restrict our ability to make inferences about patterns of brain development following chemotherapy treatment. In this study, we used magnetic resonance imaging (MRI) to evaluate brain outcomes in ALL survivors, comparing against a group of typically developing, cancer free peers.

Materials and methods

Participants included 71 ALL survivors, on average 8 years after diagnosis and 8–18 years of age, and 83 typically developing controls. Anatomical MRI was performed to evaluate brain structure; diffusion and magnetization transfer MRI were used to examine brain tissue microstructure.

Results

Successful MRI scans were acquired in 67 survivors (94%) and 82 controls (99%). Structurally, ALL survivors exhibited widespread reductions in brain volume, with 6% less white matter and 5% less gray matter than controls (p = 0.003 and 0.0006 respectively). Much of the brain appeared affected – 71 of 90 evaluated structures showed smaller volume – with the most notable exception being the occipital lobe, where no significant differences were observed. Average full-scale IQ in the survivor and control groups were 95 (CI 92–99) and 110 (CI 107–113), respectively. Using data from the NIH Pediatric MRI Data Repository, we evaluated the extent to which elevated IQ in the control group might affect the structural differences observed. We estimated that two thirds of the observed brain differences were attributable to ALL and its treatment. In addition to the structural changes, survivors showed, on average, globally lower white matter fractional anisotropy (-3%) and higher radial diffusivity (+5%) (p < 10⁻⁶), but no differences in magnetization transfer ratio.

Conclusions

Neuroanatomical alterations in late childhood and adolescent ALL survivors treated with chemotherapy-only protocols are widespread, with white matter being somewhat more affected than gray matter. These MRI results indicate brain development is altered in ALL survivors and highlight the need to examine how these alterations emerge.

Alterations in GABAA Receptor Subunit Expression in the Amygdala and Entorhinal Cortex in Human Temporal Lobe Epilepsy

The amygdala has long been implicated in the pathophysiology of human temporal lobe epilepsy (TLE). The different nuclei of this complex structure are interconnected and share reciprocal connections with the hippocampus and other brain structures, partly via the entorhinal cortex. Expression of GABAA receptor subunits α1, α2, α3, α5, β2, β2/3, and γ2 was evaluated by immunohistochemistry in amygdala specimens and the entorhinal cortex of 12 TLE patients and 12 autopsy controls. A substantial decrease in the expression of α1, α2, α3, and β2/3 subunits was found in TLE cases, accompanied by an increase of γ2 subunit expression in many nuclei. In the entorhinal cortex, the expression of all GABAA receptor subunits was decreased except for the α1 subunit, which was increased on cellular somata. The overall reduction in α subunit expression may lead to decreased sensitivity to GABA and its ligands and compromise phasic inhibition, whereas upregulation of the γ2 subunit might influence clustering and kinetics of receptors and impair tonic inhibition. The description of these alterations in the human amygdala is important for the understanding of network changes in TLE as well as the development of subunit-specific therapeutic agents for the treatment of this disease.

Multi-Label Active Learning Algorithms for Image Classification: Overview and Future Promise

Image classification is a key task in image understanding, and multi-label image classification has become a popular topic in recent years. However, the success of multi-label image classification is closely related to the way of constructing a training set. As active learning aims to construct an effective training set through iteratively selecting the most informative examples to query labels from annotators, it was introduced into multi-label image classification. Accordingly, multi-label active learning is becoming an important research direction. In this work, we first review existing multi-label active learning algorithms for image classification. These algorithms can be categorized into two top groups from two aspects respectively: sampling and annotation. The most important component of multi-label active learning is to design an effective sampling strategy that actively selects the examples with the highest informativeness from an unlabeled data pool, according to various information measures. Thus, different informativeness measures are emphasized in this survey. Furthermore, this work also makes a deep investigation on existing challenging issues and future promises in multi-label active learning with a focus on four core aspects: example dimension, label dimension, annotation, and application extension.

The Amygdala in Schizophrenia and Bipolar Disorder: A Synthesis of Structural MRI, Diffusion Tensor Imaging, and Resting-State Functional Connectivity Findings

Frequently implicated in psychotic spectrum disorders, the amygdala serves as an important hub for elucidating the convergent and divergent neural substrates in schizophrenia and bipolar disorder, the two most studied groups of psychotic spectrum conditions. A systematic search of electronic databases through December 2017 was conducted to identify neuroimaging studies of the amygdala in schizophrenia and bipolar disorder, focusing on structural MRI, diffusion tensor imaging (DTI), and resting-state functional connectivity studies, with an emphasis on cross-diagnostic studies. Ninety-four independent studies were selected for the present review (49 structural MRI, 27 DTI, and 18 resting-state functional MRI studies). Also selected, and analyzed in a separate meta-analysis, were 33 volumetric studies with the amygdala as the region-of-interest. Reduced left, right, and total amygdala volumes were found in schizophrenia, relative to both healthy controls and bipolar subjects, even when restricted to cohorts in the early stages of illness. No volume abnormalities were observed in bipolar subjects relative to healthy controls. Shape morphometry studies showed either amygdala deformity or no differences in schizophrenia, and no abnormalities in bipolar disorder. In contrast to the volumetric findings, DTI studies of the uncinate fasciculus tract (connecting the amygdala with the medial- and orbitofrontal cortices) largely showed reduced fractional anisotropy (a marker of white matter microstructure abnormality) in both schizophrenia and bipolar patients, with no cross-diagnostic differences. While decreased amygdalar-orbitofrontal functional connectivity was generally observed in schizophrenia, varying patterns of amygdalar-orbitofrontal connectivity in bipolar disorder were found. Future studies can consider adopting longitudinal approaches with multimodal imaging and more extensive clinical subtyping to probe amygdalar subregional changes and their relationship to the sequelae of psychotic disorders.

Accuracy of automated amygdala MRI segmentation approaches in Huntington's disease in the IMAGE-HD cohort

Smaller manually-segmented amygdala volumes have been associated with poorer motor and cognitive function in Huntington's disease (HD). Manual segmentation is the gold standard in terms of accuracy; however, automated methods may be necessary in large samples. Automated segmentation accuracy has not been determined for the amygdala in HD. We aimed to determine which of three automated approaches would most accurately segment amygdalae in HD: FreeSurfer, FIRST, and ANTS nonlinear registration followed by FIRST segmentation. T1-weighted images for the IMAGE-HD cohort including 35 presymptomatic HD (pre-HD), 36 symptomatic HD (symp-HD), and 34 healthy controls were segmented using FreeSurfer and FIRST. For the third approach, images were nonlinearly registered to an MNI template using ANTS, then segmented using FIRST. All automated methods overestimated amygdala volumes compared with manual segmentation. Dice overlap scores, indicating segmentation accuracy, were not significantly different between automated approaches. Manually segmented volumes were most statistically differentiable between groups, followed by those segmented by FreeSurfer, then ANTS/FIRST. FIRST-segmented volumes did not differ between groups. All automated methods produced a bias where volume overestimation was more severe for smaller amygdalae. This bias was subtle for FreeSurfer, but marked for FIRST, and moderate for ANTS/FIRST. Further, FreeSurfer introduced a hemispheric bias not evident with manual segmentation, producing larger right amygdalae by 8%. To assist choice of segmentation approach, we provide sample size estimation graphs based on sample size and other factors. If automated segmentation is employed in samples of the current size, FreeSurfer may effectively distinguish amygdala volume between controls and HD.

Tractostorm: The what, why, and how of tractography dissection reproducibility

Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called "virtual dissection." Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. It is our opinion that if the field of dMRI tractography wants to be taken seriously as a widespread clinical tool, it is imperative to harmonize WM bundle segmentations and develop protocols aimed to be used in clinical settings. The EADC-ADNI Harmonized Hippocampal Protocol achieved such standardization through a series of steps that must be reproduced for every WM bundle. This article is an observation of the problematic. A specific bundle segmentation protocol was used in order to provide a real-life example, but the contribution of this article is to discuss the need for reproducibility and standardized protocol, as for any measurement tool. This study required the participation of 11 experts and 13 nonexperts in neuroanatomy and "virtual dissection" across various laboratories and hospitals. Intra-rater agreement (Dice score) was approximately 0.77, while inter-rater was approximately 0.65. The protocol provided to participants was not necessarily optimal, but its design mimics, in essence, what will be required in future protocols. Reporting tractometry results such as average fractional anisotropy, volume or streamline count of a particular bundle without a sufficient reproducibility score could make the analysis and interpretations more difficult. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction protocols in this era of open and collaborative science.

Individual-specific functional connectivity of the amygdala: A substrate for precision psychiatry

The amygdala is central to the pathophysiology of many psychiatric illnesses. An imprecise understanding of how the amygdala fits into the larger network organization of the human brain, however, limits our ability to create models of dysfunction in individual patients to guide personalized treatment. Therefore, we investigated the position of the amygdala and its functional subdivisions within the network organization of the brain in 10 highly sampled individuals (5 h of fMRI data per person). We characterized three functional subdivisions within the amygdala of each individual. We discovered that one subdivision is preferentially correlated with the default mode network; a second is preferentially correlated with the dorsal attention and fronto-parietal networks; and third subdivision does not have any networks to which it is preferentially correlated relative to the other two subdivisions. All three subdivisions are positively correlated with ventral attention and somatomotor networks and negatively correlated with salience and cingulo-opercular networks. These observations were replicated in an independent group dataset of 120 individuals. We also found substantial across-subject variation in the distribution and magnitude of amygdala functional connectivity with the cerebral cortex that related to individual differences in the stereotactic locations both of amygdala subdivisions and of cortical functional brain networks. Finally, using lag analyses, we found consistent temporal ordering of fMRI signals in the cortex relative to amygdala subdivisions. Altogether, this work provides a detailed framework of amygdala-cortical interactions that can be used as a foundation for models relating aberrations in amygdala connectivity to psychiatric symptoms in individual patients.

Amygdala volume and social anxiety symptom severity: Does segmentation technique matter?

The amygdala factors prominently in neurobiological models of social anxiety (SA), yet amygdala volume findings regarding SA have been inconsistent and largely focused on case-control characterization. One source of discrepant findings could be variability in volumetric techniques. Therefore, we compared amygdala volumes derived via an automated technique (Freesurfer) against a manually corrected approach, also involving Freesurfer. Additionally, we tested whether the relationship between volume and SA symptom severity would differ across volumetric techniques. We pooled participants (n = 76) from archival studies. SA severity was assessed with the Liebowitz Social Anxiety Scale; scores ranged from non-clinical to clinical levels. Freesurfer produced significantly larger amygdalar volumes for participants with poor image quality. Even after excluding such participants, paired sample t-tests showed Freesurfer's boundaries produced significantly larger amygdalar volumes than manually corrected ones, bilaterally. Yet, intra-class correlation coefficients between the two methods were high, which suggests that Freesurfer's over-estimation of amygdala volume was systemic. Regardless of segmentation technique, volumes were not associated with SA symptom severity. Potentially, amygdala sub-regions may yield clearer patterns regarding SA symptoms. Further, our study underscores the importance of image quality for segmentation of the amygdala, and image quality may be particularly valuable when examining anatomical data for subtle inter-individual differences.

Study on the sub-regions volume of hippocampus and amygdala in schizophrenia

Background

Many studies have found volume changes in the hippocampus and amygdala in patients with schizophrenia, but these findings have not reached an agreement. Particularly, few results showed the volumes of the sub-regions of the amygdala. In this research, we aim to clarify volume changes of hippocampus and amygdala sub-regions in patients with schizophrenia.

Methods

The sample consisted of 69 patients with schizophrenia and 72 control subjects aged from 18 to 65 years. FreeSurfer 6.0 software was used on T1-weighted images to assess the volumes of hippocampus and amygdala and their sub-regions. The general linear model (GLM) was used to analyze the volume changes between the two groups. False discovery rate (FDR) correction was performed, and the significance level was set at 0.05.

Results

The hippocampus volume in schizophrenia showed reduction compared to healthy control (P<0.05). Several hippocampal subfields showed smaller volume in schizophrenia patients, including bilateral presubiculum and molecular layer, left hippocampal tail, subiculum and cornus ammonis (CA)1, and right parasubiculum (P<0.05). Left amygdala volume showed a decrease as well, sub-regions including the bilateral basal nucleus, anterior-amygdaloid-area (AAA), paralaminar nucleus and left lateral nucleus (P<0.05).

Conclusions

Several sub-regions of hippocampus and amygdala showed a volumetric decline in patients group, which suggest the key roles of these regions in the pathophysiology of schizophrenia. Based on these results, we speculate that these regions could be used to assess the early finding of schizophrenia.

Cytoarchitectonically-driven MRI atlas of nonhuman primate hippocampus: Preservation of subfield volumes in aging

Identification of primate hippocampal subfields in vivo using structural MRI imaging relies on variable anatomical guidelines, signal intensity differences, and heuristics to differentiate between regions (Yushkevich et al., 2015a). Thus, a clear anatomically-driven basis for subfield demarcation is lacking. Recent work, however, has begun to develop methods to use ex vivo histology or ex vivo MRI (Adler et al., 2014; Iglesias et al., 2015) that have the potential to inform subfield demarcations of in vivo images. For optimal results, however, ex vivo and in vivo images should ideally be matched within the same healthy brains, with the goal to develop a neuroanatomically-driven basis for in vivo structural MRI images. Here, we address this issue in young and aging rhesus macaques (young n = 5 and old n = 5) using ex vivo Nissl-stained sections in which we identified the dentate gyrus, CA3, CA2, CA1, subiculum, presubiculum, and parasubiculum guided by morphological cell properties (30 μm thick sections spaced at 240 μm intervals and imaged at 161 nm/pixel). The histologically identified boundaries were merged with in vivo structural MRIs (0.625 × 0.625 × 1 mm) from the same subjects via iterative rigid and diffeomorphic registration resulting in probabilistic atlases of young and old rhesus macaques. Our results indicate stability in hippocampal subfield volumes over an age range of 13 to 32 years, consistent with previous results showing preserved whole hippocampal volume in aged macaques (Shamy et al., 2006). Together, our methods provide a novel approach for identifying hippocampal subfields in non-human primates and a potential 'ground truth' for more accurate identification of hippocampal subfield boundaries on in vivo MRIs. This could, in turn, have applications in humans where accurately identifying hippocampal subfields in vivo is a critical research goal.

Previous glucocorticoid treatment in childhood and adolescence is associated with long-term differences in subcortical grey matter volume and microstructure

BACKGROUND

Glucocorticoids are widely used in the treatment of several pediatric diseases with undisputed disease-related benefits. Perinatal exposure to high levels of glucocorticoids can have long-term adverse cerebral effects. In adults, glucocorticoid treatment has been associated with smaller volumes of subcortical grey matter structures. Recently, we observed smaller total brain volumes in children and adolescents treated with glucocorticoid during childhood compared to healthy controls. The possible long-term effects of glucocorticoid treatment during childhood on subcortical brain volume and microstructure remain unknown.

METHOD

We examined 30 children and adolescents, who had previously been treated with glucocorticoids for nephrotic syndrome or rheumatic disease, and 30 healthy volunteers. Patients and healthy control groups were matched by age, gender, and level of parent education. Participants underwent 3 T magnetic resonance (MR) brain imaging. T1-weighted and diffusion-weighted images were acquired. Volume and mean diffusivity (MD) measures were extracted for hippocampus, amygdala, nucleus accumbens, caudate nucleus and putamen. Multiple linear regression analyses were used to assess differences between patients and controls, and to evaluate possible dose-response relationships. A priori, we expected patients to display lower hippocampal and amygdala volumes.

RESULTS

While children previously treated with glucocorticoids displayed smaller right hippocampal volumes than controls, this difference did not survive correction for multiple comparisons. Furthermore, patients as compared to controls showed lower right hippocampal MD, which remained when correcting for global changes in MD. The longer the time between the glucocorticoid treatment termination and MR-scan, the more right hippocampal MD values resembled that of healthy controls. Patient and controls did not differ in amygdala volume or MD. Analyses of the nucleus accumbens, caudate nucleus and putamen only revealed smaller putamen volumes in patients compared to controls, which remained significant when controlling for total brain volume.

CONCLUSION

The results suggest that extra-cerebral diseases during childhood treated with glucocorticoids may be associated with reduced subcortical grey matter volumes and lower right hippocampal mean diffusivity later in life. Our findings warrant replication and elaboration in larger, preferably prospective and longitudinal studies. Such studies may also allow disentangling disease-specific effects from possible glucocorticoid treatment effects.

Dissociable medial temporal pathways for encoding emotional item and context information

Emotional experiences are typically remembered with a greater sense of recollection than neutral experiences, but memory benefits for emotional items do not typically extend to their source contexts. Item and source memory have been attributed to different subregions of the medial temporal lobes (MTL), but it is unclear how emotional item recollection fits into existing models of MTL function and, in particular, what is the role of the hippocampus. To address these issues, we used high-resolution functional magnetic resonance imaging (fMRI) to examine MTL contributions to successful emotional item and context encoding. The results showed that emotional items were recollected more often than neutral items. Whereas amygdala and perirhinal cortex (PRC) activity supported the recollection advantage for emotional items, hippocampal and parahippocampal cortex activity predicted subsequent source memory for both types of items, reflecting a double dissociation between anterior and posterior MTL regions. In addition, amygdala activity during encoding modulated the relationships of PRC activity and hippocampal activity to subsequent item recollection and source memory, respectively. Specifically, whereas PRC activity best predicted subsequent item recollection when amygdala activity was relatively low, hippocampal activity best predicted source memory when amygdala activity was relatively high. We interpret these findings in terms of complementary compared to synergistic amygdala-MTL interactions. The results suggest that emotion-related enhancements in item recollection are supported by an amygdala-PRC pathway, which is separable from the hippocampal pathway that binds items to their source context.

Amygdala subnuclei and healthy cognitive aging

Amygdala is a group of nuclei involved in the neural circuits of fear, reward learning, and stress. The main goal of this magnetic resonance imaging (MRI) study was to investigate the relationship between age and the amygdala subnuclei volumes in a large cohort of healthy individuals. Our second goal was to determine effects of the apolipoprotein E (APOE) and brain-derived neurotrophic factor (BDNF) polymorphisms on the amygdala structure. One hundred and twenty-six healthy participants (18-85 years old) were recruited for this study. MRI datasets were acquired on a 4.7 T system. Amygdala was manually segmented into five major subdivisions (lateral, basal, accessory basal nuclei, and cortical, and centromedial groups). The BDNF (methionine and homozygous valine) and APOE genotypes (ε2, homozygous ε3, and ε4) were obtained using single nucleotide polymorphisms. We found significant nonlinear negative associations between age and the total amygdala and its lateral, basal, and accessory basal nuclei volumes, while the cortical amygdala showed a trend. These age-related associations were found only in males but not in females. Centromedial amygdala did not show any relationship with age. We did not observe any statistically significant effects of APOE and BDNF polymorphisms on the amygdala subnuclei volumes. In contrast to APOE ε2 allele carriers, both older APOE ε4 and ε3 allele carriers had smaller lateral, basal, accessory basal nuclei volumes compared to their younger counterparts. This study indicates that amygdala subnuclei might be nonuniformly affected by aging and that age-related association might be gender specific.

Evaluation of methods for volumetric analysis of pediatric brain data: The child pipeline versus adult-based approaches

Pediatric brain volumetric analysis based on Magnetic Resonance Imaging (MRI) is of particular interest in order to understand the typical brain development and to characterize neurodevelopmental disorders at an early age. However, it has been shown that the results can be biased due to head motion, inherent to pediatric data, and due to the use of methods based on adult brain data that are not able to accurately model the anatomical disparity of pediatric brains. To overcome these issues, we proposed childmetrix, a tool developed for the analysis of pediatric neuroimaging data that uses an age-specific atlas and a probabilistic model-based approach in order to segment the gray matter (GM) and white matter (WM). The tool was extensively validated on 55 scans of children between 5 and 6 years old (including 13 children with developmental dyslexia) and 10 pairs of test-retest scans of children between 6 and 8 years old and compared with two state-of-the-art methods using an adult atlas, namely icobrain (applying a probabilistic model-based segmentation) and Freesurfer (applying a surface model-based segmentation). The results obtained with childmetrix showed a better reproducibility of GM and WM segmentations and a better robustness to head motion in the estimation of GM volume compared to Freesurfer. Evaluated on two subjects, childmetrix showed good accuracy with 82-84% overlap with manual segmentation for both GM and WM, thereby outperforming the adult-based methods (icobrain and Freesurfer), especially for the subject with poor quality data. We also demonstrated that the adult-based methods needed double the number of subjects to detect significant morphological differences between dyslexics and typical readers. Once further developed and validated, we believe that childmetrix would provide appropriate and reliable measures for the examination of children's brain.

Amygdala-stimulation-induced apnea is attention and nasal-breathing dependent

OBJECTIVE

Evidence suggests that disordered breathing is critically involved in Sudden Unexpected Death in Epilepsy (SUDEP). To that end, evaluating structures that are activated by seizures and can activate brain regions that produce cardiorespiratory changes can further our understanding of the pathophysiology of SUDEP. Past preclinical studies have shown that electrical stimulation of the human amygdala induces apnea, suggesting a role for the amygdala in controlling respiration. In this study, we aimed to both confirm these findings in a larger group of patients with intractable temporal lobe epilepsy (TLE) and also further explore the anatomical and cognitive properties of this effect.

METHODS

Seven surgical TLE patients had depth electrodes implanted in the amygdala that were used to deliver electrical stimulation during functional mapping preceding resection. Real-time respiratory monitoring was performed in each patient to confirm apnea.

RESULTS

Our data confirm that amygdala stimulation reliably induces apnea (occurring in all 7 patients) and further suggest that apnea can be overcome by instructing the patient to inhale, and can be prevented entirely by breathing through the mouth before electrical stimulation. Finally, stimulation-induced apnea occurred only when stimulating the medial-most amygdalar contacts located in the central nucleus.

INTERPRETATION

These findings confirm a functional connection between the amygdala and respiratory control in humans. Moreover, they suggest specific amygdalar nuclei may be critical in mediating this effect and that attentional state is critical to apnea mediated by amygdala activation-perhaps alluding to future development of strategies for the prevention of SUDEP. Ann Neurol 2018;83:460-471.

Intrinsic functional connectivity of the central extended amygdala

The central extended amygdala (EAc)-including the bed nucleus of the stria terminalis (BST) and central nucleus of the amygdala (Ce)-plays a critical role in triggering fear and anxiety and is implicated in the development of a range of debilitating neuropsychiatric disorders. Although it is widely believed that these disorders reflect the coordinated activity of distributed neural circuits, the functional architecture of the EAc network and the degree to which the BST and the Ce show distinct patterns of functional connectivity is unclear. Here, we used a novel combination of imaging approaches to trace the connectivity of the BST and the Ce in 130 healthy, racially diverse, community-dwelling adults. Multiband imaging, high-precision registration techniques, and spatially unsmoothed data maximized anatomical specificity. Using newly developed seed regions, whole-brain regression analyses revealed robust functional connectivity between the BST and Ce via the sublenticular extended amygdala, the ribbon of subcortical gray matter encompassing the ventral amygdalofugal pathway. Both regions displayed coupling with the ventromedial prefrontal cortex (vmPFC), midcingulate cortex (MCC), insula, and anterior hippocampus. The BST showed stronger connectivity with the thalamus, striatum, periaqueductal gray, and several prefrontal territories. The only regions showing stronger functional connectivity with the Ce were neighboring regions of the dorsal amygdala, amygdalohippocampal area, and anterior hippocampus. These observations provide a baseline against which to compare a range of special populations, inform our understanding of the role of the EAc in normal and pathological fear and anxiety, and showcase image registration techniques that are likely to be useful for researchers working with "deidentified" neuroimaging data.

Smaller amygdala volume and increased neuroticism predict anxiety symptoms in healthy subjects: A volumetric approach using manual tracing

Volume reductions in the amygdala (AMY) have been found in patients with anxiety disorders, but findings are mixed in subclinical participants with high trait anxiety scores, in whom both reductions and increases in AMY volume have been identified. One potential reason for such discrepancies could be the employment of different methods to determine the AMY volume (i.e., manual tracing in psychiatric research vs. automated methods), in non-patient research. In addition to trait anxiety, smaller AMY volume has also been linked to neuroticism, a personality trait consistently linked to increased vulnerability to anxiety. However, it is not clear how AMY volume and neuroticism together may contribute to anxiety symptoms in healthy functioning. These issues were investigated in a sample of 46 healthy participants who underwent anatomical MRI scanning and completed questionnaires measuring trait anxiety and neuroticism. AMY volume was assessed using manual tracing, based on anatomical landmarks identified in each participant's anatomical image. First, smaller left AMY volume was linked to higher levels of neuroticism (p = .013) and trait anxiety (p = .024), which in turn were positively correlated with each other. Moreover, AMY volume had a significant indirect effect on trait anxiety through neuroticism (ab = - .009, 95% CI [- .019, - .002]). This effect was not bidirectional, as trait anxiety did not predict AMY volume through neuroticism. Collectively, these findings provide support for a brain-personality-symptom framework of understanding affective dysregulation, which may help inform the development of prevention and intervention paradigms targeting preservation of AMY volume and reduction of neuroticism, to protect against anxiety symptoms.

Parcellation of Human Amygdala Subfields Using Orientation Distribution Function and Spectral K-means Clustering

Amygdala plays an important role in fear and emotional learning, which are critical for human survival. Despite the functional relevance and unique circuitry of each human amygdaloid subnuclei, there has yet to be an efficient imaging method for identifying these regions in vivo. A data-driven approach without prior knowledge provides advantages of efficient and objective assessments. The present study uses high angular and high spatial resolution diffusion magnetic resonance imaging to generate orientation distribution function, which bears distinctive microstructural features. The features were extracted using spherical harmonic decomposition to assess microstructural similarity within amygdala subfields are identified via similarity matrices using spectral k-mean clustering. The approach was tested on 32 healthy volunteers and three distinct amygdala subfields were identified including medial, posterior-superior lateral, and anterior-inferior lateral.

Hippocampal Damage Increases Deontological Responses during Moral Decision Making

Complex moral decision making is associated with the ventromedial prefrontal cortex (vmPFC) in humans, and damage to this region significantly increases the frequency of utilitarian judgments. Since the vmPFC has strong anatomical and functional links with the hippocampus, here we asked how patients with selective bilateral hippocampal damage would derive moral decisions on a classic moral dilemmas paradigm. We found that the patients approved of the utilitarian options significantly less often than control participants, favoring instead deontological responses—rejecting actions that harm even one person. Thus, patients with hippocampal damage have a strikingly opposite approach to moral decision making than vmPFC-lesioned patients. Skin-conductance data collected during the task showed increased emotional arousal in the hippocampal-damaged patients and they stated that their moral decisions were based on emotional instinct. By contrast, control participants made moral decisions based on the integration of an adverse emotional response to harming others, visualization of the consequences of one's action, and the rational re-evaluation of future benefits. This integration may be disturbed in patients with either hippocampal or vmPFC damage. Hippocampal lesions decreased the ability to visualize a scenario and its future consequences, which seemed to render the adverse emotional response overwhelmingly dominant. In patients with vmPFC damage, visualization might also be reduced alongside an inability to detect the adverse emotional response, leaving only the utilitarian option open. Overall, these results provide insights into the processes involved in moral decision making and highlight the complementary roles played by two closely connected brain regions.

SIGNIFICANCE STATEMENT The ventromedial prefrontal cortex (vmPFC) is closely associated with the ability to make complex moral judgements. When this area is damaged, patients become more utilitarian (the ends justify the means) and have decreased emotional arousal during moral decision making. The vmPFC is closely connected with another brain region—the hippocampus. In this study we found that patients with selective bilateral hippocampal damage show a strikingly opposite response pattern to those with vmPFC damage when making moral judgements. They rejected harmful actions of any kind (thus their responses were deontological) and showed increased emotional arousal. These results provide new insights into the processes involved in moral decision making and highlight the complementary roles played by two closely connected brain regions.

Regional gray matter correlates of memory for emotion-laden words in middle-aged and older adults: A voxel-based morphometry study

Emotional content is known to enhance memory in a content-dependent manner in healthy populations. In middle-aged and older adults, a reduced preference for negative material, or even an enhanced preference for positive material has been observed. This preference seems to be modulated by the emotional arousal that the material evokes. The neuroanatomical basis for emotional memory processes is, however, not well understood in middle-aged and older healthy people. Previous research on local gray matter correlates of emotional memory in older populations has mainly been conducted with patients suffering from various neurodegenerative diseases. To our knowledge, this is the first study to examine regional gray matter correlates of immediate free recall and recognition memory of intentionally encoded positive, negative, and emotionally neutral words using voxel-based morphometry (VBM) in a sample of 50-to-79-year-old cognitively intact normal adults. The behavioral analyses yielded a positivity bias in recognition memory, but not in immediate free recall. No associations with memory performance emerged from the region-of-interest (ROI) analyses using amygdalar and hippocampal volumes. Controlling for total intracranial volume, age, and gender, the whole-brain VBM analyses showed statistically significant associations between immediate free recall of negative words and volumes in various frontal regions, between immediate free recall of positive words and cerebellar volume, and between recognition memory of positive words and primary visual cortex volume. The findings indicate that the neural areas subserving memory for emotion-laden information encompass posterior brain areas, including the cerebellum, and that memory for emotion-laden information may be driven by cognitive control functions.

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

The amygdala is composed of multiple nuclei with unique functions and connections in the limbic system and to the rest of the brain. However, standard in vivo neuroimaging tools to automatically delineate the amygdala into its multiple nuclei are still rare. By scanning postmortem specimens at high resolution (100-150µm) at 7T field strength (n = 10), we were able to visualize and label nine amygdala nuclei (anterior amygdaloid, cortico-amygdaloid transition area; basal, lateral, accessory basal, central, cortical medial, paralaminar nuclei). We created an atlas from these labels using a recently developed atlas building algorithm based on Bayesian inference. This atlas, which will be released as part of FreeSurfer, can be used to automatically segment nine amygdala nuclei from a standard resolution structural MR image. We applied this atlas to two publicly available datasets (ADNI and ABIDE) with standard resolution T1 data, used individual volumetric data of the amygdala nuclei as the measure and found that our atlas i) discriminates between Alzheimer's disease participants and age-matched control participants with 84% accuracy (AUC=0.915), and ii) discriminates between individuals with autism and age-, sex- and IQ-matched neurotypically developed control participants with 59.5% accuracy (AUC=0.59). For both datasets, the new ex vivo atlas significantly outperformed (all p < .05) estimations of the whole amygdala derived from the segmentation in FreeSurfer 5.1 (ADNI: 75%, ABIDE: 54% accuracy), as well as classification based on whole amygdala volume (using the sum of all amygdala nuclei volumes; ADNI: 81%, ABIDE: 55% accuracy). This new atlas and the segmentation tools that utilize it will provide neuroimaging researchers with the ability to explore the function and connectivity of the human amygdala nuclei with unprecedented detail in healthy adults as well as those with neurodevelopmental and neurodegenerative disorders.

Investigation of random walks knee cartilage segmentation model using inter-observer reproducibility: Data from the osteoarthritis initiative

BACKGROUND

Existing knee cartilage segmentation methods have reported several technical drawbacks. In essence, graph cuts remains highly susceptible to image noise despite extended research interest; active shape model is often constraint by the selection of training data while shortest path have demonstrated shortcut problem in the presence of weak boundary, which is a common problem in medical images.

OBJECTIVES

The aims of this study is to investigate the capability of random walks as knee cartilage segmentation method.

METHODS

Experts would scribble on knee cartilage image to initialize random walks segmentation. Then, reproducibility of the method is assessed against manual segmentation by using Dice Similarity Index. The evaluation consists of normal cartilage and diseased cartilage sections which is divided into whole and single cartilage categories.

RESULTS

A total of 15 normal images and 10 osteoarthritic images were included. The results showed that random walks method has demonstrated high reproducibility in both normal cartilage (observer 1: 0.83±0.028 and observer 2: 0.82±0.026) and osteoarthritic cartilage (observer 1: 0.80±0.069 and observer 2: 0.83±0.029). Besides, results from both experts were found to be consistent with each other, suggesting the inter-observer variation is insignificant (Normal: P=0.21; Diseased: P=0.15).

CONCLUSION

The proposed segmentation model has overcame technical problems reported by existing semi-automated techniques and demonstrated highly reproducible and consistent results against manual segmentation method.

Elucidation of White Matter Tracts of the Human Amygdala by Detailed Comparison between High-Resolution Postmortem Magnetic Resonance Imaging and Histology

The amygdala has attracted considerable research interest because of its potential involvement in various neuropsychiatric disorders. Recently, attempts have been made using magnetic resonance imaging (MRI) to evaluate the integrity of the axonal connections to and from the amygdala under pathological conditions. Although amygdalar pathways have been studied extensively in animal models, anatomical references for the human brain are limited to histology-based resources from a small number of slice locations, orientations and annotations. In the present study, we performed high-resolution (250 μm) MRI of postmortem human brains followed by serial histology sectioning. The histology data were used to identify amygdalar pathways, and the anatomical delineation of the assigned structures was extended into 3D using the MRI data. We were able to define the detailed anatomy of the stria terminalis and amygdalofugal pathway, as well as the anatomy of the nearby basal forebrain areas, including the substantia innominata. The present results will help us understand in detail the white matter structures associated with the amygdala, and will serve as an anatomical reference for the design of in vivo MRI studies and interpretation of their data.

In vivo quantification of amygdala subnuclei using 4.7 T fast spin echo imaging

The amygdala (AG) is an almond-shaped heterogeneous structure located in the medial temporal lobe. The majority of previous structural Magnetic Resonance Imaging (MRI) volumetric methods for AG measurement have so far only been able to examine this region as a whole. In order to understand the role of the AG in different neuropsychiatric disorders, it is necessary to understand the functional role of its subnuclei. The main goal of the present study was to develop a reliable volumetric method to delineate major AG subnuclei groups using ultra-high resolution high field MRI. 38 healthy volunteers (15 males and 23 females, 21-60 years of age) without any history of medical or neuropsychiatric disorders were recruited for this study. Structural MRI datasets were acquired at 4.7 T Varian Inova MRI system using a fast spin echo (FSE) sequence. The AG was manually segmented into its five major anatomical subdivisions: lateral (La), basal (B), accessory basal (AB) nuclei, and cortical (Co) and centromedial (CeM) groups. Inter-(intra-) rater reliability of our novel volumetric method was assessed using intra-class correlation coefficient (ICC) and Dice's Kappa. Our results suggest that reliable measurements of the AG subnuclei can be obtained by image analysts with experience in AG anatomy. We provided a step-by-step segmentation protocol and reported absolute and relative volumes for the AG subnuclei. Our results showed that the basolateral (BLA) complex occupies seventy-eight percent of the total AG volume, while CeM and Co groups occupy twenty-two percent of the total AG volume. Finally, we observed no hemispheric effects and no gender differences in the total AG volume and the volumes of its subnuclei. Future applications of this method will help to understand the selective vulnerability of the AG subnuclei in neurological and psychiatric disorders.

Amygdala-hippocampal dynamics during salient information processing

Recognizing motivationally salient information is critical to guiding behaviour. The amygdala and hippocampus are thought to support this operation, but the circuit-level mechanism of this interaction is unclear. We used direct recordings in the amygdala and hippocampus from human epilepsy patients to examine oscillatory activity during processing of fearful faces compared with neutral landscapes. We report high gamma (70–180 Hz) activation for fearful faces with earlier stimulus evoked onset in the amygdala compared with the hippocampus. Attending to fearful faces compared with neutral landscape stimuli enhances low-frequency coupling between the amygdala and the hippocampus. The interaction between the amygdala and hippocampus is largely unidirectional, with theta/alpha oscillations in the amygdala modulating hippocampal gamma activity. Granger prediction, phase slope index and phase lag analysis corroborate this directional coupling. These results demonstrate that processing emotionally salient events in humans engages an amygdala-hippocampal network, with the amygdala influencing hippocampal dynamics during fear processing.

Amygdala and hippocampus are involved in processing motivationally salient stimuli but the precise circuit dynamics of the interaction is not understood. Here the authors show that in response to fearful faces in humans, theta/alpha oscillations in the amygdala modulate hippocampal activity dynamics.

Disruption of amygdala-entorhinal-hippocampal network in late-life depression

Episodic memory deficits are evident in late-life depression (LLD) and are associated with subtle synaptic and neurochemical changes in the medial temporal lobes (MTL). However, the particular mechanisms by which memory impairment occurs in LLD are currently unknown. We tested older adults with (DS+) and without (DS-) depressive symptoms using high-resolution fMRI that is capable of discerning signals in hippocampal subfields and amygdala nuclei. Scanning was conducted during performance of an emotional discrimination task used previously to examine the relationship between depressive symptoms and amygdala-mediated emotional modulation of hippocampal pattern separation in young adults. We found that hippocampal dentate gyrus (DG)/CA3 activity was reduced during correct discrimination of negative stimuli and increased during correct discrimination of neutral items in DS+ compared to DS- adults. The extent of the latter increase was correlated with symptom severity. Furthermore, DG/CA3 and basolateral amygdala (BLA) activity predicted discrimination performance on negative trials, a relationship that depended on symptom severity. The impact of the BLA on depressive symptom severity was mediated by the DG/CA3 during discrimination of neutral items, and by the lateral entorhinal cortex (LEC) during false recognition of positive items. These results shed light on a novel mechanistic account for amygdala-hippocampal network changes and concurrent alterations in emotional episodic memory in LLD. The BLA-LEC-DG/CA3 network, which comprises a key pathway by which emotion modulates memory, is specifically implicated in LLD. © 2017 Wiley Periodicals, Inc.

Brain structure, working memory and response inhibition in childhood leukemia survivors

INTRODUCTION

Survival rates for children with acute lymphoblastic leukemia (ALL) approach 95%. At the same time, there is growing concern that chemotherapy causes alterations in brain development and cognitive abilities. We performed MRI measurements of white and gray matter volume to explore how variation in brain structure may be related to cognitive abilities in ALL survivors and healthy controls.

METHODS

The sample included 24 male ALL survivors who had completed contemporary treatment 3-11 years prior, and 21 age- and sex-matched controls. Participants were between 8 and 18 years old. Working memory and motor response inhibition were measured with the N-Back and Stop Signal Tasks (SST), respectively. Participants underwent 3T structural MRI to assess white and gray matter volumes overall, lobe-wise, and in cortical and atlas-identified subcortical structures. Mental health was assessed with the Child Behavioral Checklist.

RESULTS

ALL survivors performed more poorly on measures of working memory and response inhibition than controls. Frontal and parietal white matter, temporal and occipital gray matter volume, and volumes of subcortical white and gray matter structures were significantly reduced in ALL survivors compared with controls. Significant structure-function correlations were observed between working memory performance and volume of the amygdala, thalamus, striatum, and corpus callosum. Response inhibition was correlated with frontal white matter volume. No differences were found in psychopathology.

CONCLUSIONS

Compared with controls, a reduction in volume across brain regions and tissue types, was detectable in ALL survivors years after completion of therapy. These structural alterations were correlated with neurocognitive performance, particularly in working memory. Confirming these observations in a larger, more representative sample of the population is necessary. Additionally, establishing the time course of these changes-and the treatment, genetic, and environmental factors that influence them-may provide opportunities to identify at-risk patients, inform the design of treatment modifications, and minimize adverse cognitive outcomes.

Manual segmentation of the human bed nucleus of the stria terminalis using 3T MRI

The bed nucleus of the stria terminalis (BNST)-a small gray matter region located in the basal forebrain-has been implicated in both anxiety and addiction based on compelling evidence from rodent and non-human primate studies. However, the BNST's small size and proximity to other gray matter regions has hindered non-invasive study in human subjects using standard neuroimaging methods. While initial studies have benefitted from a BNST mask created from a single human subject using a 7T scanner, individual variability is likely-especially in patient populations-thus a manual segmentation protocol is needed. Here we report on the development of a reliable manual segmentation protocol performed on 3T MRI images using a scanning sequence that provides high gray matter/white matter/cerebrospinal fluid contrast. Inter- and intra-rater reliabilities, measured in 10 healthy individuals, demonstrate that the protocol can be reliably implemented (intra-rater Dice similarity coefficient≥0.85, inter-rater≥0.77). This BNST tracing protocol provides the necessary foundation for future 3T MRI studies of the BNST in healthy controls and patient populations.

In vivo delineation of subdivisions of the human amygdaloid complex in a high-resolution group template

The nuclei of the human amygdala remain difficult to distinguish in individual subject structural magnetic resonance images. However, interpretation of the amygdala's role in whole brain networks requires accurate localization of functional activity to a particular nucleus or subgroup of nuclei. To address this, high spatial resolution, three-dimensional templates, using joint high accuracy diffeomorphic registration of T1- and T2-weighted structural images from 168 typical adults between 22 and 35 years old released by the Human Connectome Project were constructed. Several internuclear boundaries are clearly visible in these templates, which would otherwise be impossible to delineate in individual subject data. A probabilistic atlas of major nuclei and nuclear groups was constructed in this template space and mapped back to individual spaces by inversion of the individual diffeomorphisms. Group level analyses revealed a slight (∼2%) bias toward larger total amygdala and nuclear volumes in the right hemisphere. No substantial sex or age differences were found in amygdala volumes normalized to total intracranial volume, or subdivision volumes normalized to amygdala volume. The current delineation provides a finer parcellation of the amygdala with more accurate external boundary definition than current histology-based atlases when used in conjunction with high accuracy registration methods, such as diffeomorphic warping. These templates and delineation are intended to be an open and evolving resource for future functional and structural imaging studies of the human amygdala. Hum Brain Mapp 37:3979-3998, 2016. © 2016 Wiley Periodicals, Inc.