Bibliometric Analysis of Academic Journal Articles Reporting Results of Psychedelic Clinical Studies

Following a decades long period of investigational dormancy, there is renewed interest in employing psychedelics as psychiatric treatments. The academic journals, institutions, and countries that have helped sustain clinical psychedelic research and the evolution of the literature on clinical studies of psychedelics have only recently begun to be investigated. To expand upon this work, we conducted a bibliometric analysis of clinical studies of 5-methoxy-N, N-dimethyltryptamine (5-MeO-DMT), ayahuasca, dimethyltryptamine (DMT), lysergic acid diethylamide (LSD), ibogaine, mescaline, 3,4-methylenedioxymethamphetamine (MDMA), and psilocybin published from 1965-2021. Our search revealed 394 relevant articles. After a lull from the 1970s-1990s, publications in this area have resurged. Studies most frequently focused on MDMA (49%), LSD (19%), psilocybin (18%), and ayahuasca (7%). A subanalysis of studies from 1965 to 2009 ("Older cohort") compared to 2010-2021 ("Recent cohort") revealed that the Recent cohort had a higher proportion of studies investigating psychedelics' therapeutic applications and a lower proportion of studies investigating the effects of psychedelics on people using them in non-research settings. Compared to the Older cohort, psilocybin studies increased proportionally in the Recent cohort, while DMT and mescaline studies decreased. Network analyses of inter-country collaborations suggested that psychedelic researchers in the United Kingdom have the most diverse international collaborations.

The State of the Catatonia Literature: Employing Bibliometric Analysis of Articles From 1965-2020 to Identify Current Research Gaps

BACKGROUND

Since Kahlbaum's classic 19th-century description of catatonia, our conceptualization of this syndrome, as well treatment options for it, has advanced considerably. However, little is known about the current state of the catatonia literature since a comprehensive bibliometric analysis of it has not yet been undertaken.

OBJECTIVE

The purpose of this study was to conduct a bibliometric analysis, along with a content analysis of articles reporting new findings, to better understand the catatonia literature and how catatonia research is changing.

METHODS

Using the search term "Title(catatoni∗)" in Web of Science Core Collection for all available years (1965-2020), all available publications (articles, proceeding papers, reviews) pertaining directly to catatonia were identified, and metadata extracted. Semantic and coauthorship network analyses were conducted. A content analysis was also conducted on all available case reports, case series, and research articles written in English.

RESULTS

A total of 1015 articles were identified representing 2861 authors, 346 journals, and 15,639 references. The average number of publications per year over the last 20 years (31.3) more than doubled in comparison to that in the 20 years prior (12.8). The top 3 most common journals were Psychosomatics/Journal of the Academy of Consultation-Liaison Psychiatry, Journal of ECT, and Schizophrenia Research, which represented 12.6% of all publications. Content analysis revealed that catatonia articles are increasingly published in nonpsychiatric journals. There was a notable paucity of clinical trials throughout the study period. Since 2003, articles on catatonia secondary to a general medical condition, as well as articles including child/adolescent patients and patients with autism spectrum disorder or intellectual disability, have made up increasing shares of the literature, with a smaller proportion of articles reporting periodic or recurrent catatonia. We noted a decrease in the proportion of articles detailing animal/in vitro studies, genetic/heredity studies, and clinical trials, along with stagnation in the proportion of neuroimaging studies.

CONCLUSIONS

The catatonia literature is growing through contributions from authors and institutions across multiple countries. However, recent growth has largely been driven by increased case reports, with significant downturns observed in both clinical and basic science research articles. A dearth of clinical trials evaluating potential treatments remain a critical gap in the catatonia literature.

Pretreatment Brain Connectome Fingerprint Predicts Treatment Response in Major Depressive Disorder

Background

Major depressive disorder (MDD) treatment is characterized by low remission rate and often involves weeks to months of treatment. Identification of pretreatment biomarkers of response may play a critical role in novel drug development, in enhanced prognostic predictions, and perhaps in providing more personalized medicine. Using a network restricted strength predictive modeling (NRS-PM) approach, the goal of the current study was to identify pretreatment functional connectome fingerprints (CFPs) that (1) predict symptom improvement regardless of treatment modality and (2) predict treatment specific improvement.

Methods

Functional magnetic resonance imaging and behavioral data from unmedicated patients with MDD (n = 200) were investigated. Participants were randomized to daily treatment of sertraline or placebo for 8 weeks. NRS-PM with 1000 iterations of 10 cross-validation were implemented to identify brain connectivity signatures that predict percent improvement in depression severity at week-8.

Results

The study identified a pretreatment CFP that significantly predicts symptom improvement independent of treatment modality but failed to identify a treatment specific CFP. Regardless of treatment modality, improved antidepressant response was predicted by high pretreatment connectivity between modules in the default mode network and the rest of the brain, but low external connectivity in the executive network. Moreover, high pretreatment internal nodal connectivity in the bilateral caudate predicted better response.

Conclusions

The identified CFP may contribute to drug development and ultimately to enhanced prognostic predictions. However, the results do not assist with providing personalized medicine, as pretreatment functional connectivity failed to predict treatment specific response.

A Unique Brain Connectome Fingerprint Predates and Predicts Response to Antidepressants

More than six decades have passed since the discovery of monoaminergic antidepressants. Yet, it remains a mystery why these drugs take weeks to months to achieve therapeutic effects, although their monoaminergic actions are present rapidly after treatment. In an attempt to solve this mystery, rather than studying the acute neurochemical effects of antidepressants, here we propose focusing on the early changes in the brain functional connectome using traditional statistics and machine learning approaches. Capitalizing on three independent datasets (n = 1,261) and recent developments in data and network science, we identified a specific connectome fingerprint that predates and predicts response to monoaminergic antidepressants. The discovered fingerprint appears to generalize to antidepressants with differing mechanism of action. We also established a consensus whole-brain hierarchical connectivity architecture and provided a set of model-based features engineering approaches suitable for identifying connectomic signatures of brain function in health and disease.

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Machine learning methods were used to fully investigate the brain connectome

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Network-informed features engineering approaches were proposed

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A cortical-subcortical hierarchical brain atlas was established

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A specific connectome signature was found to predict response to antidepressants

Determining the Hierarchical Architecture of the Human Brain Using Subject-Level Clustering of Functional Networks

Optimal integration and segregation of neuronal connections are necessary for efficient large-scale network communication between distributed cortical regions while allowing for modular specialization. This dynamic in the cortex is enabled at the network mesoscale by the organization of nodes into communities. Previous in vivo efforts to map the mesoscale architecture in humans had several limitations. Here we characterize a consensus multiscale community organization of the functional cortical network. We derive this consensus from the clustering of subject-level networks. We applied this analysis to magnetic resonance imaging data from 1003 healthy individuals part of the Human Connectome Project. The hierarchical atlas and code will be made publicly available for future investigators.

The Neurobiology and Pharmacotherapy of Posttraumatic Stress Disorder

New approaches to the neurobiology of posttraumatic stress disorder (PTSD) are needed to address the reported crisis in PTSD drug development. These new approaches may require the field to move beyond a narrow fear-based perspective, as fear-based medications have not yet demonstrated compelling efficacy. Antidepressants, particularly recent rapid-acting antidepressants, exert complex effects on brain function and structure that build on novel aspects of the biology of PTSD, including a role for stress-related synaptic dysconnectivity in the neurobiology and treatment of PTSD. Here, we integrate this perspective within a broader framework-in other words, a dual pathology model of ( a) stress-related synaptic loss arising from amino acid-based pathology and ( b) stress-related synaptic gain related to monoamine-based pathology. Then, we summarize the standard and experimental (e.g., ketamine) pharmacotherapeutic options for PTSD and discuss their putative mechanism of action and clinical efficacy.

Neurobiological studies of trauma-related psychopathology: a public health perspective

The societal burden of psychiatric disorders that result after exposure to psychological trauma is enormous. The study of trauma-related disorders using neurobiological and public health approaches is often disjointed. It is critical to emphasize the translational potential of neurobiological work and its relevance to the public health burden of psychological trauma. Applying a public health model to traumatology that includes primary, secondary, and tertiary levels, we highlight ways in which advancing the field of neurobiology can pave the way for scalable interventions that can improve outcomes and help to address the public health problem.

Topology of brain functional connectivity networks in posttraumatic stress disorder

Here we present functional neuroimaging-based network data (focused on the default mode network) collected from a cohort of US Veterans with history of combat exposure, combined with clinical assessments for PTSD and other psychiatric comorbidities. The data has been processed and analyzed using several network construction methods (signed, thresholded, normalized to phase-randomized and rewired surrogates, functional and multimodal parcellation). An interpretation and discussion of the data can be found in the main NeuroImage article by Akiki et al. [51].

Altered White Matter Diffusivity of the Cingulum Angular Bundle in Posttraumatic Stress Disorder

Purpose of the Study

Prior studies showed posttraumatic stress disorder (PTSD)-related alterations in white matter integrity, but most of these studies have used region-based approaches. We address this limitation by investigating the relationship between PTSD severity and fractional anisotropy (FA) using a tract-based approach.

Procedures

Structural and diffusion magnetic resonance imaging were acquired from 67 combat-exposed US Veterans and processed using FSL/FreeSurfer TRActs Constrained by UnderLying Anatomy. Partial correlations were conducted between PTSD severity and FA of the cingulum and uncinate fasciculi covarying for age, sex, and head motion.

Results

Only FA of the left cingulum angular bundle (CAB) was positively correlated with PTSD symptom severity (r = 0.433, p = 0.001, df = 57) and remained significant after Bonferroni correction.

Conclusions

This finding may imply greater organization of the CAB with increasing PTSD severity. The CAB connects directly to the cingulate cortex and the hippocampal subiculum, critical nodes of the default mode network, as well as being implicated in neurodegeneration pathology, decision-making, and executive functions, which may help explain previously shown alterations in this network in PTSD.

Message of the Paper

Further study of white matter tract integrity in PTSD is warranted, particularly to investigate whether the CAB connections with both higher-order cognitive functioning and emotion processing regions contribute to the pathophysiology and comorbidity of PTSD.

Default mode network abnormalities in posttraumatic stress disorder: A novel network-restricted topology approach

Disruption in the default mode network (DMN) has been implicated in numerous neuropsychiatric disorders, including posttraumatic stress disorder (PTSD). However, studies have largely been limited to seed-based methods and involved inconsistent definitions of the DMN. Recent advances in neuroimaging and graph theory now permit the systematic exploration of intrinsic brain networks. In this study, we used resting-state functional magnetic resonance imaging (fMRI), diffusion MRI, and graph theoretical analyses to systematically examine the DMN connectivity and its relationship with PTSD symptom severity in a cohort of 65 combat-exposed US Veterans. We employed metrics that index overall connectivity strength, network integration (global efficiency), and network segregation (clustering coefficient). Then, we conducted a modularity and network-based statistical analysis to identify DMN regions of particular importance in PTSD. Finally, structural connectivity analyses were used to probe whether white matter abnormalities are associated with the identified functional DMN changes. We found decreased DMN functional connectivity strength to be associated with increased PTSD symptom severity. Further topological characterization suggests decreased functional integration and increased segregation in subjects with severe PTSD. Modularity analyses suggest a spared connectivity in the posterior DMN community (posterior cingulate, precuneus, angular gyrus) despite overall DMN weakened connections with increasing PTSD severity. Edge-wise network-based statistical analyses revealed a prefrontal dysconnectivity. Analysis of the diffusion networks revealed no alterations in overall strength or prefrontal structural connectivity. DMN abnormalities in patients with severe PTSD symptoms are characterized by decreased overall interconnections. On a finer scale, we found a pattern of prefrontal dysconnectivity, but increased cohesiveness in the posterior DMN community and relative sparing of connectivity in this region. The DMN measures established in this study may serve as a biomarker of disease severity and could have potential utility in developing circuit-based therapeutics.

Ketamine, but Not the NMDAR Antagonist Lanicemine, Increases Prefrontal Global Connectivity in Depressed Patients

BACKGROUND

Identifying the neural correlates of ketamine treatment may facilitate and expedite the development of novel, robust, and safe rapid-acting antidepressants. Prefrontal cortex (PFC) global brain connectivity with global signal regression (GBCr) was recently identified as a putative biomarker of major depressive disorder (MDD). Accumulating evidence have repeatedly shown reduced PFC GBCr in MDD, an abnormality which appears to normalize following ketamine treatment.

METHODS

Fifty-six unmedicated participants with MDD were randomized to intravenous placebo (normal saline; n = 18), ketamine (0.5mg/kg; n = 19) or lanicemine (100mg; n = 19). PFC GBCr was computed using time series from functional magnetic resonance imaging (fMRI) scans that were completed at baseline, during infusion, and 24h post-treatment.

RESULTS

Compared to placebo, ketamine significantly increased average PFC GBCr during infusion (p = 0.01) and 24h post-treatment (p = 0.02). Lanicemine had no significant effects on GBCr during infusion (p = 0.45) and 24h post-treatment (p = 0.23), compared to placebo. Average delta PFC GBCr (during minus baseline) showed a pattern of positively predicting depression improvement in participants receiving ketamine (r = 0.44; p = 0.06; d = 1.0) or lanicemine (r = 0.55; p = 0.01; d = 1.3), but not those receiving placebo (r = -0.1; p = 0.69; d = 0.02). Follow-up vertex-wise analyses showed ketamine-induced GBCr increases in the dorsolateral, dorsomedial, and frontomedial PFC during infusion, and in the dorsolateral and dorsomedial PFC 24h post-treatment (corrected p < 0.05). Exploratory vertex-wise analyses examining the relationship with depression improvement showed positive correlation with GBCr in the dorsal PFC during infusion and 24h post-treatment, but negative correlation with GBCr in the ventral PFC during infusion (uncorrected p < 0.01).

CONCLUSIONS

In a randomized placebo-controlled approach, the results provide the first evidence in MDD of ketamine-induced increases in PFC GBCr during infusion, and suggests that ketamine's rapid-acting antidepressant properties are related to its acute effects on prefrontal connectivity. Overall, the study findings underscore the similarity and differences between ketamine and another N-methyl-D-aspartate receptor (NMDAR) antagonist, while proposing a pharmacoimaging paradigm for optimization of novel rapid-acting antidepressants prior to testing in costly clinical trials.

Posttraumatic Stress Disorder and Depression Symptom Severities Are Differentially Associated With Hippocampal Subfield Volume Loss in Combat Veterans

Background

Two decades of human neuroimaging research have associated volume reductions in the hippocampus with posttraumatic stress disorder. However, little is known about the distribution of volume loss across hippocampal subfields. Recent advances in neuroimaging methods have made it possible to accurately delineate 10 gray matter hippocampal subfields. Here, we apply a volumetric analysis of hippocampal subfields to data from a group of combat-exposed Veterans.

Method

Veterans (total, n = 68, posttraumatic stress disorder, n = 36; combat control, n = 32) completed high-resolution structural magnetic resonance imaging. Based on previously validated methods, hippocampal subfield volume measurements were conducted using FreeSurfer 6.0. The Clinician-Administered PTSD Scale assessed posttraumatic stress disorder symptom severity; Beck Depression Inventory assessed depressive symptom severity. Controlling for age and intracranial volume, partial correlation analysis examined the relationship between hippocampal subfields and symptom severity. Correction for multiple comparisons was performed using false discovery rate. Gender, intelligence, combat severity, comorbid anxiety, alcohol/substance use disorder, and medication status were investigated as potential confounds.

Results

In the whole sample, total hippocampal volume negatively correlated with Clinician-Administered PTSD Scale and Beck Depression Inventory scores. Of the 10 hippocampal subfields, Clinician-Administered PTSD Scale symptom severity negatively correlated with the hippocampus–amygdala transition area (HATA). Beck Depression Inventory scores negatively correlated with dentate gyrus, cornu ammonis 4 (CA4), HATA, CA2/3, molecular layer, and CA1. Follow-up analysis limited to the posttraumatic stress disorder group showed a negative correlation between Clinician-Administered PTSD Scale symptom severity and each of HATA, CA2/3, molecular layer, and CA4.

Conclusion

This study provides the first evidence relating posttraumatic stress disorder and depression symptoms to abnormalities in the HATA, an anterior hippocampal region highly connected to prefrontal-amygdala circuitry. Notably, dentate gyrus abnormalities were associated with depression severity but not posttraumatic stress disorder symptoms. Future confirmatory studies should determine the extent to which dentate gyrus volume can differentiate between posttraumatic stress disorder- and depression-related pathophysiology.

A Network-Based Neurobiological Model of PTSD: Evidence From Structural and Functional Neuroimaging Studies

PURPOSE OF REVIEW

Although a fine-grained understanding of the neurobiology of posttraumatic stress disorder (PTSD) is yet to be elucidated, the last two decades have seen a rapid growth in the study of PTSD using neuroimaging techniques. The current review summarizes important findings from functional and structural neuroimaging studies of PTSD, by primarily focusing on their relevance towards an emerging network-based neurobiological model of the disorder.

RECENT FINDINGS

PTSD may be characterized by a weakly connected and hypoactive default mode network (DMN) and central executive network (CEN) that are putatively destabilized by an overactive and hyperconnected salience network (SN), which appears to have a low threshold for perceived saliency, and inefficient DMN-CEN modulation. There is considerable evidence for large-scale functional and structural network dysfunction in PTSD. Nevertheless, several limitations and gaps in the literature need to be addressed in future research.

The Association of PTSD Symptom Severity with Localized Hippocampus and Amygdala Abnormalities

Background

The hippocampus and amygdala have been repeatedly implicated in the psychopathology of posttraumatic stress disorder (PTSD). While numerous structural neuroimaging studies examined these two structures in PTSD, these analyses have largely been limited to volumetric measures. Recent advances in vertex-based neuroimaging methods have made it possible to identify specific locations of subtle morphometric changes within a structure of interest.

Methods

In this cross-sectional study, we used high-resolution magnetic resonance imaging to examine the relationship between PTSD symptomatology, as measured using the Clinician Administered PTSD Scale for the DSM-IV, and structural shape of the hippocampus and amygdala using vertex-wise shape analyses in a group of combat-exposed U.S. Veterans (N = 69).

Results

Following correction for multiple comparisons and controlling for age and cranial volume, we found that participants with more severe PTSD symptoms showed an indentation in the anterior half of the right hippocampus and an indentation in the dorsal region of the right amygdala (corresponding to the centromedial amygdala). Post hoc analysis using stepwise regression suggest that among PTSD symptom clusters, arousal symptoms explain most of the variance in the hippocampal abnormality, whereas reexperiencing symptoms explain most of the variance in the amygdala abnormality.

Conclusion

The results provide evidence of localized abnormalities in the anterior hippocampus and centromedial amygdala in combat-exposed U.S. Veterans suffering from PTSD symptoms. This novel finding provides a more fine-grained analysis of structural abnormalities in PTSD and may be informative for understanding the neurobiology of the disorder.