Modulation of hippocampal activity in schizophrenia with levetiracetam: a randomized, double-blind, cross-over, placebo-controlled trial

Hippocampal hyperactivity is a novel pharmacological target in the treatment of schizophrenia. We hypothesized that levetiracetam (LEV), a drug binding to the synaptic vesicle glycoprotein 2 A, normalizes hippocampal activity in persons with schizophrenia and can be measured using neuroimaging methods. Thirty healthy control participants and 30 patients with schizophrenia (28 treated with antipsychotic drugs), were randomly assigned to a double-blind, cross-over trial to receive a single administration of 500 mg oral LEV or placebo during two study visits. At each visit, we assessed hippocampal function using resting state fractional amplitude of low frequency fluctuations (fALFF), cerebral blood flow (CBF) with arterial spin labeling, and hippocampal blood-oxygen-level-dependent (BOLD) signal during a scene processing task. After placebo treatment, we found significant elevations in hippocampal fALFF in patients with schizophrenia, consistent with hippocampal hyperactivity. Additionally, hippocampal fALFF in patients with schizophrenia after LEV treatment did not significantly differ from healthy control participants receiving placebo, suggesting that LEV may normalize hippocampal hyperactivity. In contrast to our fALFF findings, we did not detect significant group differences or an effect of LEV treatment on hippocampal CBF. In the context of no significant group difference in BOLD signal, we found that hippocampal recruitment during scene processing is enhanced by LEV more significantly in schizophrenia. We conclude that pharmacological modulation of hippocampal hyperactivity in schizophrenia can be studied with some neuroimaging methods, but not others. Additional studies in different cohorts, employing alternate neuroimaging methods and study designs, are needed to establish levetiracetam as a treatment for schizophrenia.

Smaller anterior hippocampal subfields in the early stage of psychosis

Hippocampal volume is smaller in schizophrenia, but it is unclear when in the illness the changes appear and whether specific regions (anterior, posterior) and subfields (CA1, CA2/3, dentate gyrus, subiculum) are affected. Here, we used a high-resolution T2-weighted sequence specialized for imaging hippocampal subfields to test the hypothesis that anterior CA1 volume is lower in early psychosis. We measured subfield volumes across hippocampal regions in a group of 90 individuals in the early stage of a non-affective psychotic disorder and 70 demographically similar healthy individuals. We observed smaller volume in the anterior CA1 and dentate gyrus subfields in the early psychosis group. Our findings support models that implicate anterior CA1 and dentate gyrus subfield deficits in the mechanism of psychosis.

Evaluation of resampling-based inference for topological features of neuroimages

Many recent studies have demonstrated the inflated type 1 error rate of the original Gaussian random field (GRF) methods for inference of neuroimages and identified resampling (permutation and bootstrapping) methods that have better performance. There has been no evaluation of resampling procedures when using robust (sandwich) statistical images with different topological features (TF) used for neuroimaging inference. Here, we consider estimation of distributions TFs of a statistical image and evaluate resampling procedures that can be used when exchangeability is violated. We compare the methods using realistic simulations and study sex differences in life-span age-related changes in gray matter volume in the Nathan Kline Institute Rockland sample. We find that our proposed wild bootstrap and the commonly used permutation procedure perform well in sample sizes above 50 under realistic simulations with heteroskedasticity. The Rademacher wild bootstrap has fewer assumptions than the permutation and performs similarly in samples of 100 or more, so is valid in a broader range of conditions. We also evaluate the GRF-based pTFCE method and show that it has inflated error rates in samples less than 200. Our R package, pbj , is available on Github and allows the user to reproducibly implement various resampling-based group level neuroimage analyses.

Hippocampal Network Dysfunction in Early Psychosis: A 2-Year Longitudinal Study

Background

Hippocampal abnormalities are among the most consistent findings in schizophrenia. Numerous studies have reported deficits in hippocampal volume, function, and connectivity in the chronic stage of illness. While hippocampal volume and function deficits are also present in the early stage of illness, there is mixed evidence of both higher and lower functional connectivity. Here, we use graph theory to test the hypothesis that hippocampal network connectivity is broadly lowered in early psychosis and progressively worsens over 2 years.

Methods

We examined longitudinal resting-state functional connectivity in 140 participants (68 individuals in the early stage of psychosis, 72 demographically similar healthy control individuals). We used an anatomically driven approach to quantify hippocampal network connectivity at 2 levels: 1) a core hippocampal-medial temporal lobe cortex (MTLC) network; and 2) an extended hippocampal-cortical network. Group and time effects were tested in a linear mixed effects model.

Results

Early psychosis patients showed elevated functional connectivity in the core hippocampal-MTLC network, but contrary to our hypothesis, did not show alterations within the broader hippocampal-cortical network. Hippocampal-MTLC network hyperconnectivity normalized longitudinally and predicted improvement in positive symptoms but was not associated with increasing illness duration.

Conclusions

These results show abnormally elevated functional connectivity in a core hippocampal-MTLC network in early psychosis, suggesting that selectively increased hippocampal signaling within a localized cortical circuit may be a marker of the early stage of psychosis. Hippocampal-MTLC hyperconnectivity could have prognostic and therapeutic implications.

Accurate Confidence and Bayesian Interval Estimation for Non-centrality Parameters and Effect Size Indices

Reporting effect size index estimates with their confidence intervals (CIs) can be an excellent way to simultaneously communicate the strength and precision of the observed evidence. We recently proposed a robust effect size index (RESI) that is advantageous over common indices because it's widely applicable to different types of data. Here, we use statistical theory and simulations to develop and evaluate RESI estimators and confidence/credible intervals that rely on different covariance estimators. Our results show (1) counter to intuition, the randomness of covariates reduces coverage for Chi-squared and F CIs; (2) when the variance of the estimators is estimated, the non-central Chi-squared and F CIs using the parametric and robust RESI estimators fail to cover the true effect size at the nominal level. Using the robust estimator along with the proposed nonparametric bootstrap or Bayesian (credible) intervals provides valid inference for the RESI, even when model assumptions may be violated. This work forms a unified effect size reporting procedure, such that effect sizes with confidence/credible intervals can be easily reported in an analysis of variance (ANOVA) table format.

Anterior hippocampal dysfunction in early psychosis: a 2-year follow-up study

BACKGROUND

Cross-sectional studies indicate that hippocampal function is abnormal across stages of psychosis. Neural theories of psychosis pathophysiology suggest that dysfunction worsens with illness stage. Here, we test the hypothesis that hippocampal function is impaired in the early stage of psychosis and declines further over the next 2 years.

METHODS

We measured hippocampal function over 2 years using a scene processing task in 147 participants (76 individuals in the early stage of a non-affective psychotic disorder and 71 demographically similar healthy control individuals). Two-year follow-up was completed in 97 individuals (50 early psychosis, 47 healthy control). Voxelwise longitudinal analysis of activation in response to scenes was carried out within a hippocampal region of interest to test for group differences at baseline and a group by time interaction.

RESULTS

At baseline, we observed lower anterior hippocampal activation in the early psychosis group relative to the healthy control group. Contrary to our hypothesis, hippocampal activation remained consistent and did not show the predicted decline over 2 years in the early psychosis group. Healthy controls showed a modest reduction in hippocampal activation after 2 years.

CONCLUSIONS

The results of this study suggest that hippocampal dysfunction in early psychosis does not worsen over 2 years and highlight the need for longer-term longitudinal studies.

Incomplete Hippocampal Inversion: A Neurodevelopmental Mechanism for Hippocampal Shape Deformation in Schizophrenia

BACKGROUND

Shape analyses of patients with schizophrenia have revealed bilateral deformations of the anterolateral hippocampus, primarily localized to the CA1 subfield. Incomplete hippocampal inversion (IHI), an anatomical variant of the human hippocampus resulting from an arrest during neurodevelopment, is more prevalent and severe in patients with schizophrenia. We hypothesized that IHI would affect the shape of the hippocampus and contribute to hippocampal shape differences in schizophrenia.

METHODS

We studied 199 patients with schizophrenia and 161 healthy control participants with structural magnetic resonance imaging to measure the prevalence and severity of IHI. High-fidelity hippocampal surface reconstructions were generated with the SPHARM-PDM toolkit. We used general linear models in SurfStat to test for group shape differences, the impact of IHI on hippocampal shape variation, and whether IHI contributes to hippocampal shape abnormalities in schizophrenia.

RESULTS

Not including IHI as a main effect in our between-group comparison replicated well-established hippocampal shape differences in patients with schizophrenia localized to the CA1 subfield in the anterolateral hippocampus. Shape differences were also observed near the uncus and hippocampal tail. IHI was associated with outward displacements of the dorsal and ventral surfaces of the hippocampus and inward displacements of the medial and lateral surfaces. Including IHI as a main effect in our between-group comparison eliminated the bilateral shape differences in the CA1 subfield. Shape differences in the uncus persisted after including IHI.

CONCLUSIONS

IHI impacts hippocampal shape. Our results suggest IHI as a neurodevelopmental mechanism for the well-known shape differences, particularly in the CA1 subfield, in schizophrenia.

Increased amplitude of hippocampal low frequency fluctuations in early psychosis: A two-year follow-up study

Neuroimaging studies have revealed hippocampal hyperactivity in schizophrenia. In the early stage of the illness, hyperactivity is present in the anterior hippocampus and is thought to spread to other regions as the illness progresses. However, there is limited evidence for changes in basal hippocampal function following the onset of psychosis. Resting state functional MRI signal amplitude may be a proxy measure for increased metabolism and disrupted oscillatory activity, both consequences of an excitation/inhibition imbalance underlying hippocampal hyperactivity. Here, we used fractional amplitude of low frequency fluctuations (fALFF) to test the hypothesis of progressive hippocampal hyperactivity in a two-year longitudinal case-control study. We found higher fALFF in the anterior and posterior hippocampus of individuals in the early stage of non-affective psychosis at study entry. Contrary to our hypothesis of progressive hippocampal dysfunction, we found evidence for normalization of fALFF over time in psychosis. Our findings support a model in which hippocampal fALFF is a marker of psychosis vulnerability or acute illness state rather than an enduring feature of the illness.

Automated, open-source segmentation of the Hippocampus and amygdala with the open Vanderbilt archive of the temporal lobe

Examining volumetric differences of the amygdala and anterior-posterior regions of the hippocampus is important for understanding cognition and clinical disorders. However, the gold standard manual segmentation of these structures is time and labor-intensive. Automated, accurate, and reproducible techniques to segment the hippocampus and amygdala are desirable. Here, we present a hierarchical approach to multi-atlas segmentation of the hippocampus head, body and tail and the amygdala based on atlases from 195 individuals. The Open Vanderbilt Archive of the temporal Lobe (OVAL) segmentation technique outperforms the commonly used FreeSurfer, FSL FIRST, and whole-brain multi-atlas segmentation approaches for the full hippocampus and amygdala and nears or exceeds inter-rater reproducibility for segmentation of the hippocampus head, body and tail. OVAL has been released in open-source and is freely available.

BNST and amygdala connectivity are altered during threat anticipation in schizophrenia

In schizophrenia, impairments in affect are prominent and anxiety disorders are prevalent. Neuroimaging studies of fear and anxiety in schizophrenia have focused on the amygdala and show alterations in connectivity. Emerging evidence suggests that the bed nucleus of the stria terminalis (BNST) also plays a critical role in anxiety, especially during anticipation of an unpredictable threat; however, previous studies have not examined the BNST in schizophrenia. In the present study, we examined BNST function and connectivity in people with schizophrenia (n = 31; n = 15 with comorbid anxiety) and controls (n = 15) during anticipation of unpredictable and predictable threat. A secondary analysis tested for differences in activation and connectivity of the central nucleus of the amygdala (CeA), which has also been implicated in threat anticipation. Analyses tested for group differences in both activation and connectivity during anticipation of unpredictable threat and predictable threat (p < .05). Relative to controls, individuals with schizophrenia showed stronger BNST-middle temporal gyrus (MTG) connectivity during unpredictable threat anticipation and stronger BNST-MTG and BNST-dorsolateral prefrontal connectivity during predictable threat anticipation. Comparing subgroups of individuals with schizophrenia and a comorbid anxiety disorder (SZ+ANX) to those without an anxiety disorder (SZ-ANX) revealed broader patterns of altered connectivity. During unpredictable threat anticipation, the SZ+ANX group had stronger BNST connectivity with regions of the salience network (insula, dorsal anterior cingulate cortex). During predictable threat anticipation, the SZ+ANX group had stronger BNST connectivity with regions associated with fear processing (insula, extended amygdala, prefrontal cortex). A secondary CeA analysis revealed a different pattern; the SZ+ANX group had weaker CeA connectivity across multiple brain regions during threat anticipation compared to the SZ-ANX group. These findings provide novel evidence for altered functional connectivity during threat anticipation in schizophrenia, especially in individuals with comorbid anxiety.

Stable habituation deficits in the early stage of psychosis: a 2-year follow-up study

Neural habituation, the decrease in brain response to repeated stimuli, is a fundamental, highly conserved mechanism that acts as an essential filter for our complex sensory environment. Convergent evidence indicates neural habituation is disrupted in both early and chronic stages of schizophrenia, with deficits co-occurring in brain regions that show inhibitory dysfunction. As inhibitory deficits have been proposed to contribute to the onset and progression of illness, habituation may be an important treatment target. However, a crucial first step is clarifying whether habituation deficits progress with illness. In the present study, we measured neural habituation in 138 participants (70 early psychosis patients (<2 years of illness), 68 healthy controls), with 108 participants assessed longitudinally at both baseline and 2-year follow-up. At follow-up, all early psychosis patients met criteria for a schizophrenia spectrum disorder (i.e., schizophreniform disorder, schizophrenia, schizoaffective disorder). Habituation slopes (i.e., rate of fMRI signal change) to repeated images were computed for the anterior hippocampus, occipital cortex, and the fusiform face area. Habituation slopes were entered into a linear mixed model to test for effects of group and time by region. We found that early psychosis patients showed habituation deficits relative to healthy control participants across brain regions, and that these deficits were maintained, but did not worsen, over two years. These results suggest a stable period of habituation deficits in the early stage of schizophrenia.

Incomplete hippocampal inversion in schizophrenia: prevalence, severity, and impact on hippocampal structure

Incomplete hippocampal inversion (IHI) is an anatomical variant of the human brain resulting from an arrest in brain development, especially prevalent in the left hemisphere. We hypothesized that IHI is more common in schizophrenia and contributes to the well-known hippocampal structural differences. We studied 199 schizophrenia patients and 161 healthy control participants with 3 T MRI to establish IHI prevalence and the relationship of IHI with hippocampal volume and asymmetry. IHI was more prevalent (left hemisphere: 15% of healthy control participants, 27% of schizophrenia patients; right hemisphere: 4% of healthy control participants, 10% of schizophrenia patients) and more severe in schizophrenia patients compared to healthy control participants. Severe IHI cases were associated with a higher rate of automated segmentation failure. IHI contributed to smaller hippocampal volume and increased R > L volume asymmetry in schizophrenia. The increased prevalence and severity of IHI supports the neurodevelopmental model of schizophrenia. The impact of this developmental variant deserves further exploration in studies of the hippocampus in schizophrenia.

Medial temporal lobe volumes in late-life depression: effects of age and vascular risk factors

Substantial work associates late-life depression with hippocampal pathology. However, there is less information about differences in hippocampal subfields and other connected temporal lobe regions and how these regions may be influenced by vascular factors. Individuals aged 60 years or older with and without a DSM-IV diagnosis of Major Depressive Disorder completed clinical assessments and 3 T cranial MRI using a protocol allowing for automated measurement of medial temporal lobe subfield volumes. A subset also completed pseudo-continuous arterial spin labeling, allowing for the measurement of hippocampal cerebral blood flow. In 59 depressed and 21 never-depressed elders (mean age = 66.4 years, SD = 5.8y, range 60-86y), the depressed group did not exhibit statistically significant volumetric differences for the total hippocampus or hippocampal subfields but did exhibit significantly smaller volumes of the perirhinal cortex, specifically in the BA36 region. Additionally, age had a greater effect in the depressed group on volumes of the cornu ammonis, entorhinal cortex, and BA36 region. Finally, both clinical and radiological markers of vascular risk were associated with smaller BA36 volumes, while reduced hippocampal blood flow was associated with smaller hippocampal and cornu ammonis volumes. In conclusion, while we did not observe group differences in hippocampal regions, we observed group differences and an effect of vascular pathology on the BA36 region, part of the perirhinal cortex. This is a critical region exhibiting atrophy in prodromal Alzheimer's disease. Moreover, the observed greater effect of age in the depressed groups is concordant with past longitudinal studies reporting greater hippocampal atrophy in late-life depression.

Generalizing deep whole-brain segmentation for post-contrast MRI with transfer learning

Purpose: Generalizability is an important problem in deep neural networks, especially with variability of data acquisition in clinical magnetic resonance imaging (MRI). Recently, the spatially localized atlas network tiles (SLANT) can effectively segment whole brain, non-contrast T1w MRI with 132 volumetric labels. Transfer learning (TL) is a commonly used domain adaptation tool to update the neural network weights for local factors, yet risks degradation of performance on the original validation/test cohorts. Approach: We explore TL using unlabeled clinical data to address these concerns in the context of adapting SLANT to scanning protocol variations. We optimize whole-brain segmentation on heterogeneous clinical data by leveraging 480 unlabeled pairs of clinically acquired T1w MRI with and without intravenous contrast. We use labels generated on the pre-contrast image to train on the post-contrast image in a five-fold cross-validation framework. We further validated on a withheld test set of 29 paired scans over a different acquisition domain. Results: Using TL, we improve reproducibility across imaging pairs measured by the reproducibility Dice coefficient (rDSC) between the pre- and post-contrast image. We showed an increase over the original SLANT algorithm (rDSC 0.82 versus 0.72) and the FreeSurfer v6.0.1 segmentation pipeline ( rDSC = 0.53 ). We demonstrate the impact of this work decreasing the root-mean-squared error of volumetric estimates of the hippocampus between paired images of the same subject by 67%. Conclusion: This work demonstrates a pipeline for unlabeled clinical data to translate algorithms optimized for research data to generalize toward heterogeneous clinical acquisitions.

Habituation during encoding: A new approach to the evaluation of memory deficits in schizophrenia

BACKGROUND

Memory is significantly impaired in schizophrenia. However, memory measures are often complex and confounded by additional impairments such as motivation and task comprehension, which can affect behavioral performance and obscure neural function during memory tasks. Neural signatures of memory encoding that are robust to potential confounds may shed additional light on neural deficits contributing to memory impairment in schizophrenia.

METHODS

Here, we investigate a potential neural signature of memory-habituation-and its relationship with healthy and impaired memory function. To limit potential confounds, we used a passive depth of encoding memory task designed to elicit neural responses associated with memory encoding while limiting other cognitive demands. To determine whether habituation during encoding was predictive of intact memory processing, we first compared neural habituation over repeated encoding exposures with subsequent explicit memory in healthy individuals. We then tested whether a similar relationship existed in patients with schizophrenia.

RESULTS

Explicit memory performance was impaired in patients with schizophrenia relative to healthy control subjects. In healthy participants, more habituation over repeated exposures during encoding was associated with greater repetition-related increases in accuracy during testing. However, in patients with schizophrenia, better performance was associated with less habituation, or a more sustained neural response during encoding.

CONCLUSIONS

These results suggest that sustained neural activity is required for normal repetition-related improvements in memory performance in schizophrenia, in line with a neural inefficiency model. Habituation may serve as a valuable index of neural processes that underlie behavioral memory performance.

Cognitive motor impairments and brain structure in schizophrenia spectrum disorder patients with a history of catatonia

There is growing interest in understanding the behavioral and neural mechanisms of catatonia. Here, we examine cognition and brain structure in schizophrenia spectrum disorder (SSD) patients with a history of catatonia. A total of 172 subjects were selected from a data repository; these included SSD patients with (n = 43) and without (n = 43) a history of catatonia and healthy control subjects (n = 86). Cognitive functioning was assessed using the Screen for Cognitive Impairment in Psychiatry (SCIP) and brain structure was assessed using voxel-based morphometry (VBM) in the CAT12 toolbox. SSD patients with a history of catatonia showed worse performance on tests of verbal fluency and processing speed compared to SSD patients without such a history, even after controlling for current antipsychotic and benzodiazepine use. No differences were found between patients with and without a history of catatonia in terms of brain structure. Both patient groups combined showed significantly smaller grey matter volumes compared to healthy control subjects in brain regions consistent with prior studies, including the anterior cingulate, insular, temporal, and medial frontal cortices. The results highlight a cognitive-motor impairment in SSD patients with a history of catatonia. Challenges and limitations of examining brain structure in patients with a history of catatonia are discussed.

Relational Memory in the Early Stage of Psychosis: A 2-Year Follow-up Study

BACKGROUND

Relational memory, the ability to bind information into complex memories, is moderately impaired in early psychosis and severely impaired in chronic schizophrenia, suggesting relational memory may worsen throughout the course of illness.

METHODS

We examined relational memory in 66 early psychosis patients and 64 healthy control subjects, with 59 patients and 52 control subjects assessed longitudinally at baseline and 2-year follow-up. Relational memory was assessed with 2 complementary tasks, to test how individuals learn relationships between items (face-scene binding task) and make inferences about trained relationships (associative inference task).

RESULTS

The early psychosis group showed impaired relational memory in both tasks relative to the healthy control group. The ability to learn relationships between items remained impaired in early psychosis patients, while the ability to make inferences about trained relationships improved, although never reaching the level of healthy control performance. Early psychosis patients who did not progress to schizophrenia at follow-up had better relational memory than patients who did.

CONCLUSIONS

Relational memory impairments, some of which improve and are less severe in patients who do not progress to schizophrenia, are a target for intervention in early psychosis.

Generalizing Deep Whole Brain Segmentation for Pediatric and Post- Contrast MRI with Augmented Transfer Learning

Generalizability is an important problem in deep neural networks, especially in the context of the variability of data acquisition in clinical magnetic resonance imaging (MRI). Recently, the Spatially Localized Atlas Network Tiles (SLANT) approach has been shown to effectively segment whole brain non-contrast T1w MRI with 132 volumetric labels. Enhancing generalizability of SLANT would enable broader application of volumetric assessment in multi-site studies. Transfer learning (TL) is commonly to update neural network weights for local factors; yet, it is commonly recognized to risk degradation of performance on the original validation/test cohorts. Here, we explore TL by data augmentation to address these concerns in the context of adapting SLANT to anatomical variation (e.g., adults versus children) and scanning protocol (e.g., non-contrast research T1w MRI versus contrast-enhanced clinical T1w MRI). We consider two datasets: First, 30 T1w MRI of young children with manually corrected volumetric labels, and accuracy of automated segmentation defined relative to the manually provided truth. Second, 36 paired datasets of pre- and post-contrast clinically acquired T1w MRI, and accuracy of the post-contrast segmentations assessed relative to the pre-contrast automated assessment. For both studies, we augment the original TL step of SLANT with either only the new data or with both original and new data. Over baseline SLANT, both approaches yielded significantly improved performance (pediatric: 0.89 vs. 0.82 DSC, p<0.001; contrast: 0.80 vs 0.76, p<0.001). The performance on the original test set decreased with the new-data only transfer learning approach, so data augmentation was superior to strict transfer learning.

Hyperactivity and Reduced Activation of Anterior Hippocampus in Early Psychosis

OBJECTIVE

In schizophrenia, the anterior hippocampus is hyperactive and shows reduced task-related recruitment, but the relationship between these two findings is unclear. The authors tested the hypothesis that hyperactivity impairs recruitment of the anterior hippocampus during scene processing.

METHODS

Functional MRI data from 45 early-psychosis patients and 35 demographically matched healthy control subjects were analyzed using a block-design 1-back scene-processing task. Hippocampal activation in response to scenes and faces compared with scrambled images was measured. In a subset of 20 early-psychosis patients and 31 healthy control subjects, baseline hippocampal activity using cerebral blood volume (CBV) mapping was measured. Correlation analyses were used to examine the association between baseline hippocampal activity and task-related hippocampal activation.

RESULTS

Activation of the anterior hippocampus was significantly reduced and CBV in the anterior hippocampus was significantly increased in the early stages of psychosis. Increased CBV in early-psychosis patients was inversely correlated with task-related activation during scene processing in the anterior hippocampus.

CONCLUSIONS

Anterior hippocampal hyperactivity in early-psychosis patients appears to limit effective recruitment of this region during task performance. These findings provide novel support for the anterior hippocampus as a therapeutic target in the treatment of cognitive deficits in psychosis.

Improving human cortical sulcal curve labeling in large scale cross-sectional MRI using deep neural networks

BACKGROUND

Human cortical primary sulci are relatively stable landmarks and commonly observed across the population. Despite their stability, the primary sulci exhibit phenotypic variability.

NEW METHOD

We propose a fully automated pipeline that integrates both sulcal curve extraction and labeling. In this study, we use a large normal control population (n = 1424) to train neural networks for accurately labeling the primary sulci. Briefly, we use sulcal curve distance map, surface parcellation, mean curvature and spectral features to delineate their sulcal labels. We evaluate the proposed method with 8 primary sulcal curves in the left and right hemispheres compared to an established multi-atlas curve labeling method.

RESULTS

Sulcal labels by the proposed method reasonably well agree with manual labeling. The proposed method outperforms the existing multi-atlas curve labeling method.

COMPARISON WITH EXISTING METHOD

Significantly improved sulcal labeling results are achieved with over 12.5 and 20.6 percent improvement on labeling accuracy in the left and right hemispheres, respectively compared to that of a multi-atlas curve labeling method in eight curves (p≪0.001, two-sample t-test).

CONCLUSION

The proposed method offers a computationally efficient and robust labeling of major sulci.

Disrupted Habituation in the Early Stage of Psychosis

BACKGROUND

Learning and memory are impaired in schizophrenia. Some theories have proposed that one form of memory, habituation, is particularly impaired. Preliminary evidence suggests that memory impairment is associated with failed hippocampal habituation in patients with chronic schizophrenia. We studied how abnormal habituation of the hippocampus is related to relational memory deficits in the early stage of psychosis.

METHODS

We measured hippocampal activity in 62 patients with early psychosis and 70 healthy individuals using functional magnetic resonance imaging. Habituation was defined as the slope of functional magnetic resonance imaging signal change to repeated presentations of faces and objects. Relational memory ability was measured as the slope of preferential viewing during a face-scene pair eye movement task outside the scanner.

RESULTS

Patients with early psychosis showed impaired relational memory (p < .001) and less hippocampal habituation to objects (p = .01) than healthy control subjects. In the healthy control group, better relational memory was associated with faster anterior hippocampal habituation (faces, r = -.28, p = .03). In contrast, patients with early psychosis showed no brain-behavior relationship (r = .12, p = .40).

CONCLUSIONS

We found evidence for disrupted hippocampal habituation in the early stage of psychosis along with an altered association between hippocampal habituation and relational memory ability. These results suggest that neural habituation may provide a novel target for early cognitive interventions in psychosis.

Registration-based image enhancement improves multi-atlas segmentation of the thalamic nuclei and hippocampal subfields

Magnetic resonance imaging (MRI) is an important tool for analysis of deep brain grey matter structures. However, analysis of these structures is limited due to low intensity contrast typically found in whole brain imaging protocols. Herein, we propose a big data registration-enhancement (BDRE) technique to augment the contrast of deep brain structures using an efficient large-scale non-rigid registration strategy. Direct validation is problematic given a lack of ground truth data. Rather, we validate the usefulness and impact of BDRE for multi-atlas (MA) segmentation on two sets of structures of clinical interest: the thalamic nuclei and hippocampal subfields. The experimental design compares algorithms using T1-weighted 3 T MRI for both structures (and additional 7 T MRI for the thalamic nuclei) with an algorithm using BDRE. As baseline comparisons, a recent denoising (DN) technique and a super-resolution (SR) method are used to preprocess the original 3 T MRI. The performance of each MA segmentation is evaluated by the Dice similarity coefficient (DSC). BDRE significantly improves mean segmentation accuracy over all methods tested for both thalamic nuclei (3 T imaging: 9.1%; 7 T imaging: 15.6%; DN: 6.9%; SR: 16.2%) and hippocampal subfields (3 T T1 only: 8.7%; DN: 8.4%; SR: 8.6%). We also present DSC performance for each thalamic nucleus and hippocampal subfield and show that BDRE can help MA segmentation for individual thalamic nuclei and hippocampal subfields. This work will enable large-scale analysis of clinically relevant deep brain structures from commonly acquired T1 images.

Reproducibility Evaluation of SLANT Whole Brain Segmentation Across Clinical Magnetic Resonance Imaging Protocols

Whole brain segmentation on structural magnetic resonance imaging (MRI) is essential for understanding neuroanatomical-functional relationships. Traditionally, multi-atlas segmentation has been regarded as the standard method for whole brain segmentation. In past few years, deep convolutional neural network (DCNN) segmentation methods have demonstrated their advantages in both accuracy and computational efficiency. Recently, we proposed the spatially localized atlas network tiles (SLANT) method, which is able to segment a 3D MRI brain scan into 132 anatomical regions. Commonly, DCNN segmentation methods yield inferior performance under external validations, especially when the testing patterns were not presented in the training cohorts. Recently, we obtained a clinically acquired, multi-sequence MRI brain cohort with 1480 clinically acquired, de-identified brain MRI scans on 395 patients using seven different MRI protocols. Moreover, each subject has at least two scans from different MRI protocols. Herein, we assess the SLANT method's intra- and inter-protocol reproducibility. SLANT achieved less than 0.05 coefficient of variation (CV) for intra-protocol experiments and less than 0.15 CV for inter-protocol experiments. The results show that the SLANT method achieved high intra- and inter- protocol reproducibility.

Neural correlates of resolving conflict from emotional and nonemotional distracters in obsessive-compulsive disorder

Obsessive compulsive disorder (OCD) is associated with altered processing in brain regions involved in conflict resolution. However, limited research has examined the extent to which conflict from emotional distracters characterizes OCD such that responsiveness to task-irrelevant emotional stimuli is altered compared to controls. In the present study, 16 patients with OCD and 15 healthy controls underwent functional magnetic resonance imaging (fMRI) during resolution of conflict from emotional or nonemotional distracters. Results in healthy controls demonstrated that rostral anterior cingulate cortex (rACC), middle frontal gyrus (MFG), and medial superior frontal gyrus (MSFG) showed greater activation for high conflict versus low conflict. Responses in these regions differed between the emotional and nonemotional distracter tasks, with rACC and MSFG having greater activation for conflict from nonemotional distracters and anterior MFG showing greater activation for conflict from emotional distracters. Furthermore, between-group differences revealed a region in right posterior MFG in which controls similarly exhibited greater activation during high conflict versus low conflict with emotional distracters; however, OCD patients showed the opposite pattern with greater activation during low conflict compared to high conflict. These findings suggest that activity of right posterior MFG may be relevant in better understanding inefficient responding during emotional conflict in OCD.

Impact of substance use disorder on gray matter volume in schizophrenia

Substance use may confound the study of brain structure in schizophrenia. We used voxel-based morphometry (VBM) to examine whether differences in regional gray matter volumes exist between schizophrenia patients with (n = 92) and without (n = 66) clinically significant cannabis and/or alcohol use histories compared to 88 healthy control subjects. Relative to controls, patients with schizophrenia had reduced gray matter volume in the bilateral precentral gyrus, right medial frontal cortex, right visual cortex, right occipital pole, right thalamus, bilateral amygdala, and bilateral cerebellum regardless of substance use history. Within these regions, we found no volume differences between patients with schizophrenia and a history of cannabis and/or alcohol compared to patients with schizophrenia without a clinically significant substance use history. Our data support the idea that a clinically meaningful history of alcohol or cannabis use does not significantly compound the gray matter deficits associated with schizophrenia.

Regionally specific volume deficits along the hippocampal long axis in early and chronic psychosis

Previous studies in psychosis patients have shown hippocampal volume deficits across anterior and posterior regions or across subfields, but subfield specific changes in volume along the hippocampal long axis have not been examined. Here, we tested the hypothesis that volume changes exist across the hippocampus in chronic psychosis but only the anterior CA region is affected in early psychosis patients. We analyzed structural MRI data from 179 patients with a non-affective psychotic disorder (94 chronic psychosis; 85 early psychosis) and 167 heathy individuals demographically matched to the chronic and early psychosis samples respectively (82 matched to chronic patients; 85 matched to early patients). We measured hippocampal volumes using Freesurfer 6-derived automated segmentation of both anterior and posterior regions and the CA, dentate gyrus, and subiculum subfields. We found a hippocampal volume deficit in both anterior and posterior regions in chronic psychosis, but this deficit was limited to the anterior hippocampus in early psychosis patients. This volume change was more pronounced in the anterior CA subfield of early psychosis patients than in the dentate gyrus or subiculum. Our findings support existing models of psychosis implicating initial CA dysfunction with later progression to other hippocampal regions and suggest that the anterior hippocampus may be an important target for early interventions.

The Effect of Deep Brain Stimulation Therapy on Fear-Related Capture of Attention in Parkinson's Disease and Essential Tremor: A Comparison to Healthy Individuals

In addition to motor symptoms, Parkinson’s disease (PD) involves significant non-motor sequelae, including disruptions in cognitive and emotional processing. Fear recognition appears to be affected both by the course of the disease and by a common interventional therapy, deep brain stimulation of the subthalamic nucleus (STN-DBS). Here, we examined if these effects extend to other aspects of emotional processing, such as attentional capture by negative emotional stimuli. Performance on an emotional attentional blink (EAB) paradigm, a common paradigm used to study emotional capture of attention, was examined in a cohort of individuals with PD, both on and off STN-DBS therapy (n=20). To contrast effects of healthy aging and other movement disorder and DBS targets, we also examined performance in a healthy elderly (n=20) and young (n=18) sample on the same task, and a sample diagnosed with Essential Tremor (ET) undergoing therapeutic deep brain stimulation of the ventral-intermediate nucleus (VIM-DBS, n=18). All four groups showed a robust attentional capture of emotional stimuli, irrespective of aging processes, movement disorder diagnosis, or stimulation. PD patients on average had overall worse performance, but this decrement in performance was not related to the emotional capture of attention. PD patients exhibited a robust EAB, indicating that the ability of emotion to direct attention remains intact in PD. Congruent with other recent data, these findings suggest that fear recognition deficits in PD may instead reflect a highly specific problem in recognition, rather than a general deficit in emotional processing of fearful stimuli.

Personality traits predicting quality of life and overall functioning in schizophrenia

INTRODUCTION

Clinical symptoms and sociodemographic variables predict level of functioning and quality of life in patients with schizophrenia. However, few studies have examined the effect of personality traits on quality of life and overall functioning in schizophrenia. Personality traits are premorbid to illness and may predict the way patients experience schizophrenia. The aim of this study was to examine the individual and additive effects of two core personality traits-neuroticism and extraversion-on quality of life and functioning.

METHODS

Patients with schizophrenia-spectrum disorders (n=153) and healthy controls (n=125) completed personality and quality of life questionnaires. Global functioning was assessed during a clinician-administered structured interview. Neuroticism and extraversion scores were analyzed both as continuous variables and as categorical extremes (High versus Normal Neuroticism, Low versus Normal Extraversion).

RESULTS

Quality of life was significantly associated with neuroticism, extraversion, and the neuroticism×diagnosis and extraversion×diagnosis interactions. For patients, a lower neuroticism score (in the normal range) was associated with quality of life scores comparable to controls; whereas high neuroticism scores in patients were associated with the lowest quality of life. For overall functioning, only diagnosis had a significant effect.

CONCLUSION

Neuroticism modulates quality of life and may provide an important key to improving the life of patients with schizophrenia.

Multi-Scale Hippocampal Parcellation Improves Atlas-Based Segmentation Accuracy

Known for its distinct role in memory, the hippocampus is one of the most studied regions of the brain. Recent advances in magnetic resonance imaging have allowed for high-contrast, reproducible imaging of the hippocampus. Typically, a trained rater takes 45 minutes to manually trace the hippocampus and delineate the anterior from the posterior segment at millimeter resolution. As a result, there has been a significant desire for automated and robust segmentation of the hippocampus. In this work we use a population of 195 atlases based on T1-weighted MR images with the left and right hippocampus delineated into the head and body. We initialize the multi-atlas segmentation to a region directly around each lateralized hippocampus to both speed up and improve the accuracy of registration. This initialization allows for incorporation of nearly 200 atlases, an accomplishment which would typically involve hundreds of hours of computation per target image. The proposed segmentation results in a Dice similiarity coefficient over 0.9 for the full hippocampus. This result outperforms a multi-atlas segmentation using the BrainCOLOR atlases (Dice 0.85) and FreeSurfer (Dice 0.75). Furthermore, the head and body delineation resulted in a Dice coefficient over 0.87 for both structures. The head and body volume measurements also show high reproducibility on the Kirby 21 reproducibility population (R2 greater than 0.95, p < 0.05 for all structures). This work signifies the first result in an ongoing work to develop a robust tool for measurement of the hippocampus and other temporal lobe structures.

Increased Amplitude of Low Frequency Fluctuations but Normal Hippocampal-Default Mode Network Connectivity in Schizophrenia

BACKGROUND

Clinical and preclinical studies have established that the hippocampus is hyperactive in schizophrenia, making it a possible biomarker for drug development. Increased hippocampal connectivity, which can be studied conveniently with resting state imaging, has been proposed as a readily accessible corollary of hippocampal hyperactivity. Here, we tested the hypothesis that hippocampal activity and connectivity are increased in patients with schizophrenia.

METHODS

Sixty-three schizophrenia patients and 71 healthy control subjects completed a resting state functional magnetic resonance imaging scan. We assessed hippocampal activity with the amplitude of low frequency fluctuations. We analyzed hippocampal functional connectivity with the default mode network using three common methods: group and single subject level independent component analysis, and seed-based functional connectivity.

RESULTS

In patients with schizophrenia, we observed increased amplitude of low frequency fluctuations but normal hippocampal connectivity using independent component and seed-based analyses.

CONCLUSION

Our results indicate that although intrinsic hippocampal activity may be increased in schizophrenia, this finding does not extend to functional connectivity. Neuroimaging methods that directly assess hippocampal activity may be more promising for the identification of a biomarker for schizophrenia.

The emotional attentional blink: what we know so far

The emotional attentional blink (EAB), also known as emotion-induced blindness, refers to a phenomenon in which the brief appearance of a task-irrelevant, emotionally arousing image captures attention to such an extent that individuals cannot detect target stimuli for several hundred ms after the emotional stimulus. The EAB allows for mental chronometry of stimulus-driven attention and the time needed to disengage and refocus goal-directed attention. In this review, we discuss current evidence for the mechanisms through which the EAB occurs. Although the EAB shares some similarities to both surprise-induced blindness (SiB) and other paradigms for assessing emotion-attention interactions, it possesses features that are distinct from these paradigms, and thus appears to provide a unique measure of the influence of emotion on stimulus-driven attention. The neural substrates of the EAB are not completely understood, but neuroimaging and neuropsychological data suggest some possible neural mechanisms underlying the phenomenon. The importance of understanding the EAB is highlighted by recent evidence indicating that EAB tasks can detect altered sensitivity to disorder relevant stimuli in psychiatric conditions such as post-traumatic stress disorder (PTSD).

Heightened attentional capture by threat in veterans with PTSD

Although an attentional bias for threat-relevant cues has been theorized in posttraumatic stress disorder (PTSD), to date empirical demonstration of this phenomenon has been at best inconsistent. Furthermore, the nature of this bias in PTSD has not been clearly delineated. In the present study, veterans with PTSD (n = 20), trauma-exposed veterans without PTSD (n = 16), and healthy nonveteran controls (n = 22) completed an emotional attentional blink task that measures the extent to which emotional stimuli capture and hold attention. Participants searched for a target embedded within a series of rapidly presented images. Critically, a combat-related, disgust, positive, or neutral distracter image appeared 200 ms, 400 ms, 600 ms, or 800 ms before the target. Impaired target detection was observed among veterans with PTSD relative to both veterans without PTSD and healthy nonveteran controls after only combat-related threat distracters when presented 200 ms, 400 ms, or 600 ms before the target, indicating increased attentional capture by cues of war and difficulty disengaging from such cues for an extended period. Veterans without PTSD and healthy nonveteran controls did not significantly differ from each other in target detection accuracy after combat-related threat distracters. These data support the presence of an attentional bias toward combat related stimuli in PTSD that should be a focus of treatment efforts.

Meta-analytic connectivity modeling reveals differential functional connectivity of the medial and lateral orbitofrontal cortex

The orbitofrontal cortex (OFC) is implicated in a broad range of behaviors and neuropsychiatric disorders. Anatomical tracing studies in nonhuman primates reveal differences in connectivity across subregions of the OFC, but data on the connectivity of the human OFC remain limited. We applied meta-analytic connectivity modeling in order to examine which brain regions are most frequently coactivated with the medial and lateral portions of the OFC in published functional neuroimaging studies. The analysis revealed a clear divergence in the pattern of connectivity for the medial OFC (mOFC) and lateral OFC (lOFC) regions. The lOFC showed coactivations with a network of prefrontal regions and areas involved in cognitive functions including language and memory. In contrast, the mOFC showed connectivity with default mode, autonomic, and limbic regions. Convergent patterns of coactivations were observed in the amygdala, hippocampus, striatum, and thalamus. A small number of regions showed connectivity specific to the anterior or posterior sectors of the OFC. Task domains involving memory, semantic processing, face processing, and reward were additionally analyzed in order to identify the different patterns of OFC functional connectivity associated with specific cognitive and affective processes. These data provide a framework for understanding the human OFC's position within widespread functional networks.

Attentional capture by emotional stimuli is preserved in patients with amygdala lesions

The importance of cues signaling reward, threat or danger would suggest that they receive processing privileges in the neural systems underlying perception and attention. Previous research has documented enhanced processing of motivationally salient cues, and has pointed to the amygdala as a candidate neural structure underlying the enhancements. In the current study, we examined whether the amygdala was necessary for this emotional modulation of attention to occur. Patients with unilateral amygdala lesions and matched controls completed an emotional attentional blink task in which emotional distractors impair the perception of subsequent targets. Emotional images proved more distracting across all participant groups, including those with right or left amygdala lesions. These data argue against a central role for the amygdala in mediating all types of attentional capture by emotional stimuli.

Reprint of: Fear-enhanced visual search persists after amygdala lesions

Previous research has indicated that the amygdala is a critical neural substrate of the emotional modulation of attention. However, a recent case study suggests that the amygdala may not be essential for all types of emotion-attention interactions. In order to test this hypothesis, we assessed the visual-search performance of patients with unilateral amygdala lesions, matched controls, and medication-matched epilepsy patients with intact amygdalae. All participants completed a visual-search task consisting of trials in which (1) an emotional target was embedded among neutral distractors, (2) a neutral target was embedded among emotional distractors, or (3) a neutral target was embedded among neutral distractors. All participant groups, including those with amygdala lesions, detected emotional targets more efficiently than neutral targets. These data indicate that the amygdala is not necessary for emotion-guided visual search and suggest that other mechanisms beyond the amygdala help guide attention toward threatening stimuli.

Fear-enhanced visual search persists after amygdala lesions

Previous research has indicated that the amygdala is a critical neural substrate of the emotional modulation of attention. However, a recent case study suggests that the amygdala may not be essential for all types of emotion-attention interactions. In order to test this hypothesis, we assessed the visual-search performance of patients with unilateral amygdala lesions, matched controls, and medication-matched epilepsy patients with intact amygdalae. All participants completed a visual-search task consisting of trials in which (1) an emotional target was embedded among neutral distractors, (2) a neutral target was embedded among emotional distractors, or (3) a neutral target was embedded among neutral distractors. All participant groups, including those with amygdala lesions, detected emotional targets more efficiently than neutral targets. These data indicate that the amygdala is not necessary for emotion-guided visual search and suggest that other mechanisms beyond the amygdala help guide attention toward threatening stimuli.