Altered spontaneous neuronal activity of visual cortex and medial anterior cingulate cortex in treatment-naïve posttraumatic stress disorder

Exploring the impact of biological sex on intrinsic connectivity networks in PTSD: A data-driven approach

INTRODUCTION

Sex as a biological variable (SABV) may help to account for the differential development and expression of post-traumatic stress disorder (PTSD) symptoms among trauma-exposed males and females. Here, we investigate the impact of SABV on PTSD-related neural alterations in resting-state functional connectivity (rsFC) within three core intrinsic connectivity networks (ICNs): the salience network (SN), central executive network (CEN), and default mode network (DMN).

METHODS

Using an independent component analysis (ICA), we compared rsFC of the SN, CEN, and DMN between males and females, with and without PTSD (n = 47 females with PTSD, n = 34 males with PTSD, n = 36 healthy control females, n = 20 healthy control males) via full factorial ANCOVAs. Additionally, linear regression analyses were conducted with clinical variables (i.e., PTSD and depression symptoms, childhood trauma scores) in order to determine intrinsic network connectivity characteristics specific to SABV. Furthermore, we utilized machine learning classification models to predict the biological sex and PTSD diagnosis of individual participants based on intrinsic network activity patterns.

RESULTS

Our findings revealed differential network connectivity patterns based on SABV and PTSD diagnosis. Males with PTSD exhibited increased intra-SN (i.e., SN-anterior insula) rsFC and increased DMN-right superior parietal lobule/precuneus/superior occipital gyrus rsFC as compared to females with PTSD. There were also differential network connectivity patterns for comparisons between the PTSD and healthy control groups for males and females, separately. We did not observe significant correlations between clinical measures of interest and brain region clusters which displayed significant between group differences as a function of biological sex, thus further reinforcing that SABV analyses are likely not confounded by these variables. Furthermore, machine learning classification models accurately predicted biological sex and PTSD diagnosis among novel/unseen participants based on ICN activation patterns.

CONCLUSION

This study reveals groundbreaking insights surrounding the impact of SABV on PTSD-related ICN alterations using data-driven methods. Our discoveries contribute to further defining neurobiological markers of PTSD among females and males and may offer guidance for differential sex-related treatment needs.

Elucidating trauma-related and disease-related regional cortical activity in post-traumatic stress disorder

Trauma exposure may precipitate a cascade of plastic modifications within the intrinsic activity of brain regions, but it remains unclear which regions could be responsible for the development of post-traumatic stress disorder based on intrinsic activity. To elucidate trauma-related and post-traumatic stress disorder-related alterations in cortical intrinsic activity at the whole-brain level, we recruited 47 survivors diagnosed with post-traumatic stress disorder, 64 trauma-exposed controls from a major earthquake, and 46 age- and sex-matched healthy controls. All subjects were scanned with an echo-planar imaging sequence, and 5 parameters including the amplitude of low-frequency fluctuations, fractional amplitude of low-frequency fluctuations, regional homogeneity, degree centrality, and voxel-mirrored homotopic connectivity were calculated. We found both post-traumatic stress disorder patients and trauma-exposed controls exhibited decreased amplitude of low-frequency fluctuations in the bilateral posterior cerebellum and inferior temporal gyrus, decreased fractional amplitude of low-frequency fluctuation and regional homogeneity in the bilateral anterior cerebellum, and decreased fractional amplitude of low-frequency fluctuation in the middle occipital gyrus and cuneus compared to healthy controls, and these impairments were more severe in post-traumatic stress disorder patients than in trauma-exposed controls. Additionally, fractional amplitude of low-frequency fluctuation in left cerebellum was positively correlated with Clinician-Administered PTSD Scale scores in post-traumatic stress disorder patients. We identified brain regions that might be responsible for the emergence of post-traumatic stress disorder, providing important information for the treatment of this disorder.

The memory trace of an intrusive trauma-analog episode

Intrusive memories are a core symptom of posttraumatic stress disorder. Compared with memories of everyday events, they are characterized by several seemingly contradictory features: intrusive memories contain distinct sensory and emotional details of the traumatic event and can be triggered by various perceptually similar cues, but they are poorly integrated into conceptual memory. Here, we conduct exploratory whole-brain analyses to investigate the neural representations of trauma-analog experiences and how they are reactivated during memory intrusions. We show that trauma-analog movies induce excessive processing and generalized representations in sensory areas but decreased blood-oxygen-level-dependent (BOLD) responses and highly distinct representations in conceptual/semantic areas. Intrusive memories activate generalized representations in sensory areas and reactivate memory traces specific to trauma-analog events in the anterior cingulate cortex. These findings provide the first evidence of how traumatic events could distort memory representations in the human brain, which may form the basis for future confirmatory research on the neural representations of traumatic experiences.

Transcriptional signal and cell specificity of genes related to cortical structural differences of post-traumatic stress disorder

Due to the diversity of traumatic events, the diagnosis of Post-traumatic Stress Disorder is heterogeneous. The pathogenesis has been explored in the fields of brain imaging and genomics separately, but the results are inconsistent. Previous research evidenced that there existed structural differences between PTSD and healthy controls in multiple brain regions. This study further looked into the differences of brain structure in PTSD at the whole brain level and analyzed the difference-related genomes. The brain structure imaging data of 36 patients and 32 healthy controls were taken as morphological indexes. Partial least squares regression and transcriptome data were used to extract genomes related to structural differences. Additional data sets were used to study transcription characteristics of genome. Morphological differences were found in cingulate gyrus between patients and control group. Differentially expressed genes related to Morphometric similarity networks difference space were also observed. The obtained genes (i.e., RORA, PRKG1 and FKBP5) were proved to be related to the disorder with no significant correlation with other mental illnesses. In the subsequent cell type analysis, astrocytes, excitatory neurons and inhibitory neurons were evidenced to have the most significant correlation with these genes. This study found morphologically different brain regions related to PTSD. The related genome transcription analysis connects the structural differences and molecular mechanisms.

Childhood sexual abuse related to brain activity abnormalities in right inferior temporal gyrus among major depressive disorder

Regional brain activity abnormalities have been reported in major depressive disorder (MDD) with childhood trauma (CT). However, these findings were variable and equivocal. The present study aims to explore further the correlation between CT and the amplitude of low-frequency fluctuations (ALFF) alteration in MDD. In this study, we recruited 60 healthy controls (HCs) and 66 MDD patients to complete resting-state fMRI scans. All MDD patients were evaluated clinical symptoms and childhood trauma experience using the Hamilton Depression Rating Scale-17 (HDRS-17), the Hamilton Anxiety Scale (HAMA), and the Childhood Trauma Questionnaire (CTQ). Compared to HCs, MDD patients demonstrated significantly altered ALFF in the right middle occipital gyrus (MOG), bilateral inferior temporal gyrus (ITG), bilateral cerebellum posterior lobe, bilateral anterior cingulate gyrus (ACC), and bilateral superior frontal gyrus (SFG). More importantly, we found negative correlation between childhood sexual abuse (CSA) scores and ALFF value appeared mainly in the right ITG among MDD patients. After adjusting for covariates (age, gender, mean framewise displacement (FD), HRDS-17, and HAMA scores), this correlation remained significant. Meanwhile, ALFF in the right ITG could distinguish MDD patients with or without CSA (area under the curve (AUC) = 0.713). Our findings revealed that the regional brain activity abnormalities in the right ITG might be a potential biomarker for MDD patients with CSA.

Involvement of the intrinsic functional network of the red nucleus in complex behavioral processing

Previous studies suggested the possibility that the red nucleus (RN) is involved in other cognitive functions than motion per se, even though such functions have yet to be clarified. We investigated the activation of RN during several tasks and its intrinsic functional network associated with social cognition and musical practice. The tasks included finger tapping, n-back, and memory recall tasks. Region of interest for RN was identified through those tasks, anatomical information of RN, and a brain atlas. The intrinsic functional network was identified for RN by an analysis of connectivity between RN and other regions typically involved in seven known resting state functional networks with RN used as the seed region. Association of the RN network with a psychological trait of the interpersonal reactivity index and musical training years revealed subnetworks that included empathy related regions or music practice related regions. These social or highly coordinated motor activity represent the most complex functions ever known to involve the RN, adding further evidence for the multifunctional roles of RN. These discoveries may lead to a new direction of investigations to clarify probable novel roles for RN in high-level human behavior.

An exploratory study of resting-state functional connectivity of amygdala subregions in posttraumatic stress disorder following trauma in adulthood

We carried out an exploratory study aimed at identifying differences in resting-state functional connectivity for the amygdala and its subregions, right and left basolateral, centromedial and superficial nuclei, in patients with Posttraumatic Stress Disorder (PTSD), relative to controls. The study included 10 participants with PTSD following trauma in adulthood (9 females), and 10 controls (9 females). The results suggest PTSD was associated with a decreased (negative) functional connectivity between the superficial amygdala and posterior brain regions relative to controls. The differences were observed between right superficial amygdala and right fusiform gyrus, and between left superficial amygdala and left lingual and left middle occipital gyri. The results suggest that among PTSD patients, the worse the PTSD symptoms, the lower the connectivity. The results corroborate the fMRI literature that shows PTSD is associated with weaker amygdala functional connectivity with areas of the brain involved in sensory and perceptual processes. The results also suggest that though the patients traumatic experience occured in adulthood, the presence of early traumatic experiences were associated with negative connectivity between the centromedial amygdala and sensory and perceptual regions. We argue that the understanding of the mechanisms of PTSD symptoms, its behaviors and the effects on quality of life of patients may benefit from the investigation of brain function that underpins sensory and perceptual symptoms associated with the disorder.

Altered Metabolic Interrelationships in the Cortico-Limbic Circuitry in Military Service Members with Persistent Post-Traumatic Stress Disorder Symptoms Following Mild Traumatic Brain Injury

Introduction: Comorbid mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD) are common in military service members. The aim of this study is to investigate brain metabolic interrelationships in service members with and without persistent PTSD symptoms after mTBI by using ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography. Methods: Service members (n = 408) diagnosed with mTBI were studied retrospectively. Principal component analysis was applied to identify latent metabolic systems, and the associations between metabolic latent systems and self-report measures of post-concussive and PTSD symptoms were evaluated. Participants were divided into two groups based on DSM-IV-TR (Diagnostic and Statistical Manual of Mental Disorders, fourth edition-Text Revision) criteria for PTSD, and structural equation modeling was performed to test a priori hypotheses on metabolic interrelationships among the brain regions in the cortico-limbic circuitry responsible for top-down control and bottom-up emotional processing. The differences in metabolic interrelationships between age-matched PTSD-absent (n = 204) and PTSD-present (n = 204) groups were evaluated. Results: FDG uptake in the temporo-limbic system was positively correlated with post-concussive and hyperarousal symptoms. For the bottom-up emotional processing, the insula and amygdala-hippocampal complex in the PTSD-present group had stronger metabolic interrelationships with the bilateral rostral anterior cingulate, left lingual, right lateral occipital, and left superior temporal cortices, but a weaker relationship with the right precuneus cortex, compared with the PTSD-absent group. For the top-down control, the PTSD-present group had decreased metabolic engagements of the dorsolateral prefrontal cortex on the amygdala. Discussion: Our results suggest altered metabolic interrelationships in the cortico-limbic circuitry in mTBI subjects with persistent PTSD symptoms, which may underlie the pathophysiological mechanisms of comorbid mTBI and PTSD. Impact statement This is the first ¹⁸F-fluorodeoxyglucose positron emission tomography study to investigate brain metabolic interrelationships in service members with persistent post-traumatic stress disorder (PTSD) symptoms after mild traumatic brain injury (mTBI). We identified that the temporo-limbic metabolic system was associated with post-concussive and hyperarousal symptoms. Further, brain metabolic interrelationships in the cortico-limbic circuitry were altered in mTBI subjects with significant PTSD symptoms compared with those without them.

Decreased functional connectivity of hippocampal subregions and methylation of the NR3C1 gene in Han Chinese adults who lost their only child

BACKGROUND

Losing one's only child is a major traumatic life event that may lead to post-traumatic stress disorder (PTSD); however, the underlying mechanisms of its psychological consequences remain poorly understood. Here, we investigated subregional hippocampal functional connectivity (FC) networks based on resting-state functional magnetic resonance imaging and the deoxyribonucleic acid methylation of the human glucocorticoid receptor gene (NR3C1) in adults who had lost their only child.

METHODS

A total of 144 Han Chinese adults who had lost their only child (51 adults with PTSD and 93 non-PTSD adults [trauma-exposed controls]) and 50 controls without trauma exposure were included in this fMRI study (age: 40-67 years). FCs between hippocampal subdivisions (four regions in each hemisphere: cornu ammonis1 [CA1], CA2, CA3, and dentate gyrus [DG]) and methylation levels of the NR3C1 gene were compared among the three groups.

RESULTS

Trauma-exposed adults, regardless of PTSD diagnosis, had weaker positive FC between the left hippocampal CA1, left DG, and the posterior cingulate cortex, and weaker negative FC between the right CA1, right DG, and several frontal gyri, relative to healthy controls. Compared to non-PTSD adults, PTSD adults showed decreased negative FC between the right CA1 region and the right middle/inferior frontal gyri (MFG/IFG), and decreased negative FC between the right DG and the right superior frontal gyrus and left MFG. Both trauma-exposed groups showed lower methylation levels of the NR3C1 gene.

CONCLUSIONS

Adults who had lost their only child may experience disrupted hippocampal network connectivity and NR3C1 methylation status, regardless of whether they have developed PTSD.

Distinct patterns of resting-state connectivity in U.S. service members with mild traumatic brain injury versus posttraumatic stress disorder

Mild traumatic brain injury (mTBI) is highly prevalent in military populations, with many service members suffering from long-term symptoms. Posttraumatic stress disorder (PTSD) often co-occurs with mTBI and predicts worse clinical outcomes. Functional neuroimaging research suggests there are both overlapping and distinct patterns of resting-state functional connectivity (rsFC) in mTBI versus PTSD. However, few studies have directly compared rsFC of cortical networks in military service members with these two conditions. In the present study, U.S. service members (n = 137; ages 19-59; 120 male) underwent resting-state fMRI scans. Participants were divided into three study groups: mTBI only, PTSD only, and orthopedically injured (OI) controls. Analyses investigated group differences in rsFC for cortical networks: default mode (DMN), frontoparietal (FPN), salience, somatosensory, motor, auditory, and visual. Analyses were family-wise error (FWE) cluster-corrected and Bonferroni-corrected for number of network seeds regions at the whole brain level (p_FWE < 0.002). Both mTBI and PTSD groups had reduced rsFC for DMN and FPN regions compared with OI controls. These group differences were largely driven by diminished connectivity in the PTSD group. rsFC with the middle frontal gyrus of the FPN was increased in mTBI, but decreased in PTSD. Overall, these results suggest that PTSD symptoms may have a more consistent signal than mTBI. Our novel findings of opposite patterns of connectivity with lateral prefrontal cortex highlight a potential biomarker that could be used to differentiate between these conditions.

Individualized Prediction of PTSD Symptom Severity in Trauma Survivors From Whole-Brain Resting-State Functional Connectivity

Previous studies have demonstrated relations between spontaneous neural activity evaluated by resting-state functional magnetic resonance imaging (fMRI) and symptom severity in post-traumatic stress disorder. However, few studies have used brain-based measures to identify imaging associations with illness severity at the level of individual patients. This study applied connectome-based predictive modeling (CPM), a recently developed data-driven and subject-level method, to identify brain function features that are related to symptom severity of trauma survivors. Resting-state fMRI scans and clinical ratings were obtained 10-15 months after the earthquake from 122 earthquake survivors. Symptom severity of post-traumatic stress disorder features for each survivor was evaluated using the Clinician Administered Post-traumatic Stress Disorder Scale (CAPS-IV). A functionally pre-defined atlas was applied to divide the human brain into 268 regions. Each individual's functional connectivity 268 × 268 matrix was created to reflect correlations of functional time series data across each pair of nodes. The relationship between CAPS-IV scores and brain functional connectivity was explored in a CPM linear model. Using a leave-one-out cross-validation (LOOCV) procedure, findings showed that the positive network model predicted the left-out individual's CAPS-IV scores from resting-state functional connectivity. CPM predicted CAPS-IV scores, as indicated by a significant correspondence between predicted and actual values (r = 0.30, P = 0.001) utilizing primarily functional connectivity between visual cortex, subcortical-cerebellum, limbic, and motor systems. The current study provides data-driven evidence regarding the functional brain features that predict symptom severity based on the organization of intrinsic brain networks and highlights its potential application in making clinical evaluation of symptom severity at the individual level.

Supervised machine learning for diagnostic classification from large-scale neuroimaging datasets

There are growing concerns about the generalizability of machine learning classifiers in neuroimaging. In order to evaluate this aspect across relatively large heterogeneous populations, we investigated four disorders: Autism spectrum disorder (N = 988), Attention deficit hyperactivity disorder (N = 930), Post-traumatic stress disorder (N = 87) and Alzheimer's disease (N = 132). We applied 18 different machine learning classifiers (based on diverse principles) wherein the training/validation and the hold-out test data belonged to samples with the same diagnosis but differing in either the age range or the acquisition site. Our results indicate that overfitting can be a huge problem in heterogeneous datasets, especially with fewer samples, leading to inflated measures of accuracy that fail to generalize well to the general clinical population. Further, different classifiers tended to perform well on different datasets. In order to address this, we propose a consensus-classifier by combining the predictive power of all 18 classifiers. The consensus-classifier was less sensitive to unmatched training/validation and holdout test data. Finally, we combined feature importance scores obtained from all classifiers to infer the discriminative ability of connectivity features. The functional connectivity patterns thus identified were robust to the classification algorithm used, age and acquisition site differences, and had diagnostic predictive ability in addition to univariate statistically significant group differences between the groups. A MATLAB toolbox called Machine Learning in NeuroImaging (MALINI), which implements all the 18 different classifiers along with the consensus classifier is available from Lanka et al. (2019) The toolbox can also be found at the following URL: https://github.com/pradlanka/malini .

Multivariate classification of earthquake survivors with post-traumatic stress disorder based on large-scale brain networks

OBJECTIVE

The identification of post-traumatic stress disorder (PTSD) among natural disaster survivors is remarkably challenging, and there are no reliable objective signatures that can be used to assist clinical diagnosis and optimize treatment. The current study aimed to establish a neurobiological signature of PTSD from the connectivity of large-scale brain networks and clarify the brain network mechanisms of PTSD.

METHODS

We examined fifty-seven unmedicated survivors with chronic PTSD and 59 matched trauma-exposed healthy controls (TEHCs) using resting-state functional magnetic resonance imaging (rs-fMRI). We extracted the node-to-network connectivity and obtained a feature vector with a dimensionality of 864 (108 nodes × 8 networks) to represent each subject's functional connectivity (FC) profile. Multivariate pattern analysis with a relevance vector machine was then used to distinguish PTSD patients from TEHCs.

RESULTS

We achieved a promising diagnostic accuracy of 89.2% in distinguishing PTSD patients from TEHCs. The most heavily weighted connections for PTSD classification were among the default mode network (DMN), visual network (VIS), somatomotor network, limbic network, and dorsal attention network (DAN). The strength of the anticorrelation of FC between the ventral medial prefrontal cortex (vMPFC) in DMN and the VIS and DAN was associated with the severity of PTSD.

CONCLUSIONS

This study achieved relatively high accuracy in classifying PTSD patients vs. TEHCs at the individual level. This performance demonstrates that rs-fMRI-derived multivariate classification based on large-scale brain networks can provide potential signatures both to facilitate clinical diagnosis and to clarify the underlying brain network mechanisms of PTSD caused by natural disasters.

Exploring memory function in earthquake trauma survivors with resting-state fMRI and machine learning

BACKGROUND

Traumatized earthquake survivors may develop poor memory function. Resting-state functional magnetic resonance imaging (rs-fMRI) and machine learning techniques may one day aid the clinical assessment of individual psychiatric patients. This study aims to use machine learning with Rs-fMRI from the perspectives of neurophysiology and neuroimaging to explore the association between it and the individual memory function of trauma survivors.

METHODS

Rs-fMRI data was acquired for eighty-nine survivors (male (33%), average age (SD):45.18(6.31) years) of Wenchuan earthquakes in 2008 each of whom was screened by experienced psychiatrists based on the clinician-administered post-traumatic stress disorder (PTSD) scale (CAPS), and their memory function scores were determined by the Wechsler Memory Scale-IV (WMS-IV). We explored which memory function scores were significantly associated with CAPS scores. Using simple multiple kernel learning (MKL), Rs-fMRI was used to predict the memory function scores that were associated with CAPS scores. A support vector machine (SVM) was also used to make classifications in trauma survivors with or without PTSD.

RESULTS

Spatial addition (SA), which is defined by spatial working memory function, was negatively correlated with the total CAPS score (r = - 0.22, P = 0.04). The use of simple MKL allowed quantitative association of SA scores with statistically significant accuracy (correlation = 0.28, P = 0.03; mean squared error = 8.36; P = 0.04). The left middle frontal gyrus and the left precuneus contributed the largest proportion to the simple MKL association frame. The SVM could not make a quantitative classification of diagnosis with statistically significant accuracy.

LIMITATIONS

The use of the cross-sectional study design after exposure to an earthquake and the leave-one-out cross-validation (LOOCV) increases the risk of overfitting.

CONCLUSION

Spontaneous brain activity of the left middle frontal gyrus and the left precuneus acquired by rs-fMRI may be a brain mechanism of visual working memory that is related to PTSD symptoms. Machine learning may be a useful tool in the identification of brain mechanisms of memory impairment in trauma survivors.

Psychological and Brain Connectivity Changes Following Trauma-Focused CBT and EMDR Treatment in Single-Episode PTSD Patients

Among the different therapeutic alternatives for post-traumatic stress disorder (PTSD), Trauma-Focused Cognitive-Behavioral Therapy (TF-CBT) and Eye Movement Desensitization and Reprocessing (EMDR) Therapy have shown promising results in helping patients cope with PTSD symptoms. However, given the different theoretical and methodological substrate of TF-CBT and EMDR, a potentially different impact on the brain for the two interventions could be hypothesized, as well as an interaction between trauma-specific PTSD symptomatology and response to a given psychotherapy. In this study, we monitored psychological and spontaneous functional connectivity fMRI patterns in two groups of PTSD patients who suffered by the same traumatic event (i.e., natural disaster), before and after a cycle of psychotherapy sessions based on TF-CBT and EMDR. Thirty-seven (37) PTSD patients were enrolled from a larger sample of people exposed to a single, acute psychological stress (i.e., 2002 earthquake in San Giuliano di Puglia, Italy). Patients were randomly assigned to TF-CBT (n = 14) or EMDR (n = 17) psychotherapy. Clinical assessment was performed using the Clinician-Administered PTSD Scale (CAPS), the Davidson Trauma Scale (DTS) and the Work and Social Adjustment Scale (WSAS), both at baseline and after treatment. All patients underwent a fMRI data acquisition session before and after treatment, aimed at characterizing their functional connectivity (FC) profile at rest, as well as potential connectivity changes associated with the clinical impact of psychotherapy. Both EMDR and TF-CBT induced statistically significant changes in clinical scores, with no difference in the clinical impact of the two treatments. Specific changes in FC correlated with the improvement at the different clinical scores, and differently for EMDR and TF-CBT. However, a similarity in the connectivity changes associated with changes in CAPS in both groups was also observed. Specifically, changes at CAPS in the entire sample correlated with an (i) increase in connectivity between the bilateral superior medial frontal gyrus and right temporal pole, and a (ii) decrease in connectivity between left cuneus and left temporal pole. Results point to a similar, beneficial psychological impact of EMDR and TF-CBT for treatment of natural-disaster PTSD patients. Neuroimaging data suggest a similar neurophysiological substrate for clinical improvement following EMDR and TF-CBT, involving changes affecting bilateral temporal pole connectivity.

Brain atrophy in the visual cortex and thalamus induced by severe stress in animal model

Psychological stress induces many diseases including post-traumatic stress disorder (PTSD); however, the causal relationship between stress and brain atrophy has not been clarified. Applying single-prolonged stress (SPS) to explore the global effect of severe stress, we performed brain magnetic resonance imaging (MRI) acquisition and Voxel-based morphometry (VBM). Significant atrophy was detected in the bilateral thalamus and right visual cortex. Fluorescent immunohistochemistry for Iba-1 as the marker of activated microglia indicates regional microglial activation as stress-reaction in these atrophic areas. These data certify the impact of severe psychological stress on the atrophy of the visual cortex and the thalamus. Unexpectedly, these results are similar to chronic neuropathic pain rather than PTSD clinical research. We believe that some sensitisation mechanism from severe stress-induced atrophy in the visual cortex and thalamus, and the functional defect of the visual system may be a potential therapeutic target for stress-related diseases.

Psychoradiology: The Frontier of Neuroimaging in Psychiatry

Unlike neurologic conditions, such as brain tumors, dementia, and stroke, the neural mechanisms for all psychiatric disorders remain unclear. A large body of research obtained with structural and functional magnetic resonance imaging, positron emission tomography/single photon emission computed tomography, and optical imaging has demonstrated regional and illness-specific brain changes at the onset of psychiatric disorders and in individuals at risk for such disorders. Many studies have shown that psychiatric medications induce specific measurable changes in brain anatomy and function that are related to clinical outcomes. As a result, a new field of radiology, termed psychoradiology, seems primed to play a major clinical role in guiding diagnostic and treatment planning decisions in patients with psychiatric disorders. This article will present the state of the art in this area, as well as perspectives regarding preparations in the field of radiology for its evolution. Furthermore, this article will (a) give an overview of the imaging and analysis methods for psychoradiology; (b) review the most robust and important radiologic findings and their potential clinical value from studies of major psychiatric disorders, such as depression and schizophrenia; and (c) describe the main challenges and future directions in this field. An ongoing and iterative process of developing biologically based nomenclatures with which to delineate psychiatric disorders and translational research to predict and track response to different therapeutic drugs is laying the foundation for a shift in diagnostic practice in psychiatry from a psychologic symptom-based approach to an imaging-based approach over the next generation. This shift will require considerable innovations for the acquisition, analysis, and interpretation of brain images, all of which will undoubtedly require the active involvement of radiologists. ^© RSNA, 2016 Online supplemental material is available for this article.

Altered Topological Properties of Brain Networks in Social Anxiety Disorder: A Resting-state Functional MRI Study

Recent studies involving connectome analysis including graph theory have yielded potential biomarkers for mental disorders. In this study, we aimed to investigate the differences of resting-state network between patients with social anxiety disorder (SAD) and healthy controls (HCs), as well as to distinguish between individual subjects using topological properties. In total, 42 SAD patients and the same number of HCs underwent resting functional MRI, and the topological organization of the whole-brain functional network was calculated using graph theory. Compared with the controls, the patients showed a decrease in 49 positive connections. In the topological analysis, the patients showed an increase in the area under the curve (AUC) of the global shortest path length of the network (L_p) and a decrease in the AUC of the global clustering coefficient of the network (C_p). Furthermore, the AUCs of L_p and C_p were used to effectively discriminate the individual SAD patients from the HCs with high accuracy. This study revealed that the neural networks of the SAD patients showed changes in topological characteristics, and these changes were prominent not only in both groups but also at the individual level. This study provides a new perspective for the identification of patients with SAD.

Altered spontaneous brain activity in Cushing's disease: a resting-state functional MRI study

CONTEXT AND OBJECTIVE

Cushing's disease (CD) provides a unique and naturalist model for studying the influence of hypercortisolism on the human brain and the reversibility of these effects after resolution of the condition. This cross-sectional study used resting-state fMRI (rs-fMRI) to investigate the altered spontaneous brain activity in CD patients and the trends for potential reversibility after the resolution of the hypercortisolism. We also aim to determine the relationship of these changes with clinical characteristics and cortisol levels.

SUBJECTS AND METHODS

Active CD patients (n = 18), remitted CD patients (n = 14) and healthy control subjects (n = 22) were included in this study. Amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) values were calculated to represent spontaneous brain activity.

RESULTS

Our study resulted in three major findings: (i) active CD patients showed significantly altered spontaneous brain activity in the posterior cingulate cortex (PCC)/precuneus (PCu), occipital lobe (OC)/cerebellum, thalamus, right postcentral gyrus (PoCG) and left prefrontal cortex (PFC); (ii) trends for partial restoration of altered spontaneous brain activity after the resolution hypercortisolism were found in several brain regions; and (iii) active CD patients showed a significant correlation between cortisol levels and ALFF/ReHo values in the PCC/PCu, a small cluster in the OC and the right IPL.

CONCLUSIONS

This study provides a new approach to investigating brain function abnormalities in patients with CD and enhances our understanding of the effect of hypercortisolism on the human brain. Furthermore, our explorative potential reversibility study of patients with CD may facilitate the development of future longitudinal studies.

ABERRANT RESTING-STATE BRAIN ACTIVITY IN POSTTRAUMATIC STRESS DISORDER: A META-ANALYSIS AND SYSTEMATIC REVIEW

BACKGROUND

About 10% of trauma-exposed individuals develop PTSD. Although a growing number of studies have investigated resting-state abnormalities in PTSD, inconsistent results suggest a need for a meta-analysis and a systematic review.

METHODS

We conducted a systematic literature search in four online databases using keywords for PTSD, functional neuroimaging, and resting-state. In total, 23 studies matched our eligibility criteria. For the meta-analysis, we included 14 whole-brain resting-state studies, reporting data on 663 participants (298 PTSD patients and 365 controls). We used the activation likelihood estimation approach to identify concurrence of whole-brain hypo- and hyperactivations in PTSD patients during rest. Seed-based studies could not be included in the quantitative meta-analysis. Therefore, a separate qualitative systematic review was conducted on nine seed-based functional connectivity studies.

RESULTS

The meta-analysis showed consistent hyperactivity in the ventral anterior cingulate cortex and the parahippocampus/amygdala, but hypoactivity in the (posterior) insula, cerebellar pyramis and middle frontal gyrus in PTSD patients, compared to healthy controls. Partly concordant with these findings, the systematic review on seed-based functional connectivity studies showed enhanced salience network (SN) connectivity, but decreased default mode network (DMN) connectivity in PTSD.

CONCLUSIONS

Combined, these altered resting-state connectivity and activity patterns could represent neurobiological correlates of increased salience processing and hypervigilance (SN), at the cost of awareness of internal thoughts and autobiographical memory (DMN) in PTSD. However, several discrepancies between findings of the meta-analysis and systematic review were observed, stressing the need for future studies on resting-state abnormalities in PTSD patients.

Multimodal MRI-Based Classification of Trauma Survivors with and without Post-Traumatic Stress Disorder

Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder. It can be difficult to discern the symptoms of PTSD and obtain an accurate diagnosis. Different magnetic resonance imaging (MRI) modalities focus on different aspects, which may provide complementary information for PTSD discrimination. However, none of the published studies assessed the diagnostic potential of multimodal MRI in identifying individuals with and without PTSD. In the current study, we investigated whether the complementary information conveyed by multimodal MRI scans could be combined to improve PTSD classification performance. Structural and resting-state functional MRI (rs-fMRI) scans were conducted on 17 PTSD patients, 20 trauma-exposed controls without PTSD (TEC) and 20 non-traumatized healthy controls (HC). Gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and regional homogeneity were extracted as classification features, and in order to integrate the information of structural and functional MRI data, the extracted features were combined by a multi-kernel combination strategy. Then a support vector machine (SVM) classifier was trained to distinguish the subjects at individual level. The performance of the classifier was evaluated using the leave-one-out cross-validation (LOOCV) method. In the pairwise comparison of PTSD, TEC, and HC groups, classification accuracies obtained by the proposed approach were 2.70, 2.50, and 2.71% higher than the best single feature way, with the accuracies of 89.19, 90.00, and 67.57% for PTSD vs. HC, TEC vs. HC, and PTSD vs. TEC respectively. The proposed approach could improve PTSD identification at individual level. Additionally, it provides preliminary support to develop the multimodal MRI method as a clinical diagnostic aid.

Altered resting-state functional activity in posttraumatic stress disorder: A quantitative meta-analysis

Many functional neuroimaging studies have reported differential patterns of spontaneous brain activity in posttraumatic stress disorder (PTSD), but the findings are inconsistent and have not so far been quantitatively reviewed. The present study set out to determine consistent, specific regional brain activity alterations in PTSD, using the Effect Size Signed Differential Mapping technique to conduct a quantitative meta-analysis of resting-state functional neuroimaging studies of PTSD that used either a non-trauma (NTC) or a trauma-exposed (TEC) comparison control group. Fifteen functional neuroimaging studies were included, comparing 286 PTSDs, 203 TECs and 155 NTCs. Compared with NTC, PTSD patients showed hyperactivity in the right anterior insula and bilateral cerebellum, and hypoactivity in the dorsal medial prefrontal cortex (mPFC); compared with TEC, PTSD showed hyperactivity in the ventral mPFC. The pooled meta-analysis showed hypoactivity in the posterior insula, superior temporal, and Heschl’s gyrus in PTSD. Additionally, subgroup meta-analysis (non-medicated subjects vs. NTC) identified abnormal activation in the prefrontal-limbic system. In meta-regression analyses, mean illness duration was positively associated with activity in the right cerebellum (PTSD vs. NTC), and illness severity was negatively associated with activity in the right lingual gyrus (PTSD vs. TEC).

Parcellation of the primary cerebral cortices based on local connectivity profiles

Connectivity-based parcellation using diffusion MRI has been extensively used to parcellate subcortical areas and the association cortex. Connectivity profiles are vital for connectivity-based parcellation. Two categories of connectivity profiles are generally utilized, including global connectivity profiles, in which the connectivity information is from the seed to the whole brain, and long connectivity profiles, in which the connectivity information is from the seed to other brain regions after excluding the seed. However, whether global or long connectivity profiles should be applied in parcellating the primary cortex utilizing connectivity-based parcellation is unclear. Many sources of evidence have indicated that the primary cerebral cortices are composed of structurally and functionally distinct subregions. Because the primary cerebral cortices are rich in local anatomic hierarchical connections and possess high degree of local functional connectivity profiles, we proposed that local connectivity profiles, that is the connectivity information within a seed region of interest, might be used for parcellating the primary cerebral cortices. In this study, the global, long, and local connectivity profiles were separately used to parcellate the bilateral M1, A1, S1, and V1. We found that results using the three profiles were all quite consistent with reported cytoarchitectonic evidence. More importantly, the results using local connectivity profiles showed less inter-subject variability than the results using the other two, a finding which suggests that local connectivity profiles are superior to global and long connectivity profiles for parcellating the primary cerebral cortices. This also implies that, depending on the characteristics of specific areas of the cerebral cortex, different connectivity profiles may need to be adopted to parcellate different areas.

Altered spontaneous neuronal activity in chronic posttraumatic stress disorder patients before and after a 12-week paroxetine treatment

BACKGROUND

Abnormal functional brain activity has been revealed in patients with Posttraumatic Stress Disorder (PTSD) in recent years, while the recovery neuromechanism of PTSD has not yet been elucidated. The aim of this study was to investigate the altered spontaneous brain activity in treatment-naïve chronic PTSD patients before and after 12 weeks׳ treatment with paroxetine.

METHODS

Twenty-one earthquake-related PTSD patients and seventeen traumatized controls underwent a resting functional magnetic resonance imaging (Rs-fMRI) scan at baseline. Amplitude of low-frequency fluctuation (ALFF) was calculated and compared between PTSD patients and controls. Then, the PTSD group completed 12 weeks of treatment with paroxetine, and Rs-fMRI was repeated to compare with the baseline. Lastly, correlation analyses of ALFF values within altered brain areas were conducted.

RESULTS

Hyperactive function of visual cortex was observed in PTSD patients before and after treatment. After treatment, significantly increased ALFF values were observed in the left orbitofrontal cortex (OFC), while decreased ALFF values were found in the precuneus. Interestingly, a negative correlation between the mean ALFF values of OFC and those of precuneus and visual cortex was only observed in controls, but not in PTSD patients pre- or post-treatment.

LIMITATIONS

A corresponding control condition was absent in this study.

CONCLUSION

The findings showed that manipulating regional spontaneous activity of precuneus and OFC could be a potential prognostic indicator of PTSD. However, hyperactive function of visual cortex and disrupted connections between OFC, precuneus and visual cortex did not reverse after treatment, which could be a potential target for further treatment.

Altered blood oxygen level-dependent signal variability in chronic post-traumatic stress disorder during symptom provocation

BACKGROUND

Recent research suggests that variability in brain signal provides important information about brain function in health and disease. However, it is unknown whether blood oxygen level-dependent (BOLD) signal variability is altered in post-traumatic stress disorder (PTSD). We aimed to identify the BOLD signal variability changes of PTSD patients during symptom provocation and compare the brain patterns of BOLD signal variability with those of brain activation.

METHODS

Twelve PTSD patients and 14 age-matched controls, who all experienced a mining accident, underwent clinical assessment as well as fMRI scanning while viewing trauma-related and neutral pictures. BOLD signal variability and brain activation were respectively examined with standard deviation (SD) and general linear model analysis, and compared between the PTSD and control groups. Multiple regression analyses were conducted to explore the association between PTSD symptom severity and these two brain measures across all subjects as well as in the PTSD group.

RESULTS

PTSD patients showed increased activation in the middle occipital gyrus compared with controls, and an inverse correlation was found between PTSD symptom severity and brain activation in the hippocampus and anterior cingulate cortex/medial prefrontal cortex. Brain variability analysis revealed increased SD in the insula, anterior cingulate cortex/medial prefrontal cortex, and vermis, and decreased SD in the parahippocapal gyrus, dorsolateral prefrontal cortex, somatosensory cortex, and striatum. Importantly, SD alterations in several regions were found in both traumatic and neutral conditions and were stratified by PTSD symptom severity.

CONCLUSION

BOLD signal variability may be a reliable and sensitive biomarker of PTSD, and combining brain activation and brain variability analysis may provide complementary insight into the neural basis of this disorder.

Contributions of cortical feedback to sensory processing in primary visual cortex

Closing the structure-function divide is more challenging in the brain than in any other organ (Lichtman and Denk, 2011). For example, in early visual cortex, feedback projections to V1 can be quantified (e.g., Budd, 1998) but the understanding of feedback function is comparatively rudimentary (Muckli and Petro, 2013). Focusing on the function of feedback, we discuss how textbook descriptions mask the complexity of V1 responses, and how feedback and local activity reflects not only sensory processing but internal brain states.