The effects of ketamine and classic hallucinogens on neurotrophic and inflammatory markers in unipolar treatment-resistant depression: a systematic review of clinical trials.

Although results are still preliminary, ketamine and classical hallucinogens have shown promise in recent years as novel, fast-acting antidepressants, especially for the treatment of unipolar treatment-resistant depression (TRD). Depression also seems to be related to abnormal levels of peripheral inflammatory and neurotrophic biomarkers, which may one day help to diagnose of this disorder. In this context, this systematic review of clinical trials evaluated the current evidence that relates the antidepressant effects of ketamine and classical hallucinogens on TRD with changes in inflammatory and neurotrophic biomarkers. Twelve studies were found (n = 587), 2 with oral ayahuasca (1 mL/kg) and 10 with ketamine (mostly intravenous 0.5 mg/kg) administration. Results for all biomarkers assessed were contradictory and thus inconclusive. Randomized controlled trials with bigger samples and higher statistical power are warranted to clarify if peripheral biomarkers can confidently be used to indicate and measure ketamine's and classical hallucinogens' antidepressant effect. The PROSPERO ID for this study is CRD42021249089.

Health resource utilization and cost before versus after initiation of second-generation long-acting injectable antipsychotics among adults with schizophrenia in Alberta, Canada: a retrospective, observational single-arm study.

BACKGROUND: Long-acting injectable (LAI) antipsychotics, along with community treatment orders (CTOs), are used to improve treatment effectiveness through adherence among individuals with schizophrenia. Understanding real-world medication adherence, and healthcare resource utilization (HRU) and costs in individuals with schizophrenia overall and by CTO status before and after second generation antipsychotic (SGA)-LAI initiation may guide strategies to optimize treatment among those with schizophrenia. METHODS: This retrospective observational single-arm study utilized administrative health data from Alberta, Canada. Adults (≥ 18 years) with schizophrenia who initiated a SGA-LAI (no use in the previous 2-years) between April 1, 2014 and March 31, 2016, and had ≥ 1 additional dispensation of a SGA-LAI were included; index date was the date of SGA-LAI initiation. Medication possession ratio (MPR) was determined, and paired t-tests were used to examine mean differences in all-cause and mental health-related HRU and costs (Canadian dollars), comprised of hospitalizations, physician visits, emergency department visits, and total visits, over the 2-year post-index and 2-year pre-index periods. Analyses were stratified by presence or absence of an active CTO during the pre-index and/or post-index periods. RESULTS: Among 1,211 adults with schizophrenia who initiated SGA-LAIs, 64% were males with a mean age of 38 (standard deviation [SD] 14) years. The mean overall antipsychotic MPR was 0.39 (95% confidence interval [CI] 0.36, 0.41) greater during the 2-year post-index period (0.84 [SD 0.26]) compared with the 2-year pre-index period (0.45 [SD 0.40]). All-cause and mental health-related HRU and costs were lower post-index versus pre-index (p < 0.001) for hospitalizations, physician visits, emergency department visits, and total visits; mean total all-cause HRU costs were $33,788 (95% CI -$38,993, -$28,583) lower post- versus pre-index ($40,343 [SD $68,887] versus $74,131 [SD $75,941]), and total mental health-related HRU costs were $34,198 (95%CI -$39,098, -$29,297) lower post- versus pre-index ($34,205 [SD $63,428] versus $68,403 [SD $72,088]) per-patient. Forty-three percent had ≥ 1 active CTO during the study period; HRU and costs varied according to CTO status. CONCLUSIONS: SGA-LAIs are associated with greater medication adherence, and lower HRU and costs however the latter vary according to CTO status.

Using Machine Learning to Predict Remission in Patients With Major Depressive Disorder Treated With Desvenlafaxine.

BACKGROUND: Major depressive disorder (MDD) is a common and burdensome condition that has low rates of treatment success for each individual treatment. This means that many patients require several medication switches to achieve remission; selecting an effective antidepressant is typically a sequential trial-and-error process. Machine learning techniques may be able to learn models that can predict whether a specific patient will respond to a given treatment, before it is administered. This study uses baseline clinical data to create a machine-learned model that accurately predicts remission status for a patient after desvenlafaxine (DVS) treatment. METHODS: We applied machine learning algorithms to data from 3,399 MDD patients (90% of the 3,776 subjects in 11 phase-III/IV clinical trials, each described using 92 features), to produce a model that uses 26 of these features to predict symptom remission, defined as an 8-week Hamilton Depression Rating Scale score of 7 or below. We evaluated that learned model on the remaining held-out 10% of the data (n = 377). RESULTS: Our resulting classifier, a trained linear support vector machine, had a holdout set accuracy of 69.0%, significantly greater than the probability of classifying a patient correctly by chance. We demonstrate that this learning process is stable by repeatedly sampling part of the training dataset and running the learner on this sample, then evaluating the learned model on the held-out instances of the training set; these runs had an average accuracy of 67.0% ± 1.8%. CONCLUSIONS: Our model, based on 26 clinical features, proved sufficient to predict DVS remission significantly better than chance. This may allow more accurate use of DVS without waiting 8 weeks to determine treatment outcome, and may serve as a first step toward changing psychiatric care by incorporating clinical assistive technologies using machine-learned models.

Mononitrate Isosorbide as an Adjunctive Therapy in Schizophrenia: A Randomized Controlled Crossover Trial.

BACKGROUND: Schizophrenia is a complex disabling mental disorder, and many patients present poor response to available treatments. Accumulating evidence about the role of the glutamate/nitric oxide pathway in mediating the positive and negative symptoms of schizophrenia suggests potential benefits of drugs that modulate this system. The aim of this study was to test the efficacy of isosorbide mononitrate (ISMN) as an adjunctive therapy for symptomatic outpatients with schizophrenia. METHODS: This was a 2-month randomized, double-blind, placebo-controlled trial with 24 schizophrenia patients. Participants were treated with ISMN 50 mg for 1 month and placebo for another month in a crossover design. The Positive and Negative Syndrome Scale (PANSS), Clinical Global Impression Scale, Global Assessment of Functioning, and MATRICS Cognitive Consensual Battery were used for symptom assessment and arterial spin labeling was used to assess brain activation patterns. RESULTS: We found significant differences in the total, general, and positive subscales of the PANSS, Global Assessment of Functioning scores, and Clinical Global Impression scores during treatment with ISMN relative to placebo. No treatment effects were found comparing scores in the MATRICS Cognitive Consensual Battery and the negative subscale of the PANSS between the active and placebo conditions. A post hoc analysis of neuroimaging data showed reduced activity in the thalamus in subgroup of patients with severe psychopathology. CONCLUSIONS: Schizophrenia patients with persistent symptoms showed significant improvement after 4 weeks of treatment with ISMN 50 mg/d compared with placebo. Isosorbide mononitrate added beneficial effects to antipsychotic treatment in terms of positive symptoms and functioning.

Incubation of neural alcohol cue reactivity after withdrawal and its blockade by naltrexone.

During the first weeks of abstinence, alcohol craving in patients may increase or "incubate." We hypothesize that Naltrexone (NTX) blocks this incubation effect. Here, we compared NTX effects on neural alcohol cue reactivity (CR) over the first weeks of abstinence and on long-term clinical outcomes to standard treatment. Male alcohol-dependent patients (n = 55) and healthy controls (n = 35) were enrolled. Participants underwent baseline psychometric testing and functional magnetic resonance imaging (fMRI) assessment of mesolimbic alcohol CR. Patients participated in a standard treatment program with the option of adjuvant NTX. They received another scan after 2 weeks of treatment. We found higher CR in several brain regions in patients versus healthy controls. CR significantly increased over 2 weeks in the standard treatment group (n = 13) but not in the NTX group (n = 22). NTX significantly attenuated CR in the left putamen and reduced relapse risk to heavy drinking within 3 months of treatment. Additionally, increased CR in the left putamen and its course over time predicted both NTX response and relapse risk. Carrier status for the functional OPRM1 variant rs1799971:A > G was considered but had no effect on NTX efficacy. In conclusion, NTX was most effective in patients with high CR in the left putamen. While the results from our naturalistic study await further confirmation from prospective randomized trials, they support a potential role of neural CR as a biomarker in the development of precision medicine approaches with NTX.

Neuroimmunological antibody-mediated encephalitis and implications for diagnosis and therapy in neuropsychiatry.

The past decade has seen a surge of reports and investigations into cases of autoimmune-mediated encephalitis. The increasing recognition of these disorders is especially of relevance to the fields of neurology and psychiatry. Autoimmune encephalitis involves antibodies against synaptic receptors, neuronal cell surface proteins and intracellular targets. These disorders feature prominent symptoms of cognitive impairment and behavioural changes, often associated with the presence of seizures. Early in the clinical course, autoimmune encephalitis may manifest as psychiatric symptoms of psychosis and involve psychiatry as an initial point of contact. Although commonly associated with malignancy, these disorders can present in the absence of an inciting neoplasm. The identification of autoimmune encephalitis is of clinical importance as a large proportion of individuals experience a response to immunotherapy. This review focuses on the current state of knowledge on n-methyl-d-aspartate (NMDA) receptor-associated encephalitis and limbic encephalitis, the latter predominantly involving antibodies against the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor, the γ-aminobutyric acid (GABA)B receptor and leucine-rich glioma-inactivated 1 (LGI1) protein. In addition, we briefly describe anti-dopamine D2 receptor encephalitis. A summary of the literature will focus on common clinical presentations and course, diagnostic approaches and response to treatment. Since a substantial proportion of patients with autoimmune encephalitis exhibit symptoms of psychosis, the relevance of this disorder to theories of psychosis and schizophrenia will also be discussed.

An Overview of Animal Models Related to Schizophrenia.

Schizophrenia is a heterogeneous psychiatric disorder that is poorly treated with current therapies. In this brief review, we provide an update regarding the use of animal models to study schizophrenia in an attempt to understand its aetiology and develop novel therapeutic strategies. Tremendous progress has been made developing and validating rodent models that replicate the aetiologies, brain pathologies, and behavioural abnormalities associated with schizophrenia in humans. Here, models are grouped into 3 categories-developmental, drug induced, and genetic-to reflect the heterogeneous risk factors associated with schizophrenia. Each of these models is associated with varied but overlapping pathophysiology, endophenotypes, behavioural abnormalities, and cognitive impairments. Studying schizophrenia using multiple models will permit an understanding of the core features of the disease, thereby facilitating preclinical research aimed at the development and validation of better pharmacotherapies to alter the progression of schizophrenia or alleviate its debilitating symptoms.

Deep grey matter iron accumulation in alcohol use disorder.

PURPOSE: Evaluate brain iron accumulation in alcohol use disorder (AUD) patients compared to controls using quantitative susceptibility mapping (QSM). METHODS: QSM was performed retrospectively by using phase images from resting state functional magnetic resonance imaging (fMRI). 20 male AUD patients and 15 matched healthy controls were examined. Susceptibility values were manually traced in deep grey matter regions including caudate nucleus, combined putamen and globus pallidus, combined substantia nigra and red nucleus, dentate nucleus, and a reference white matter region in the internal capsule. Average susceptibility values from each region were compared between the patients and controls. The relationship between age and susceptibility was also explored. RESULTS: The AUD group exhibited increased susceptibility in caudate nucleus (+8.5%, p=0.034), combined putamen and globus pallidus (+10.8%, p=0.006), and dentate nucleus (+14.9%, p=0.022). Susceptibility increased with age in two of the four measured regions - combined putamen and globus pallidus (p=0.013) and combined substantia nigra and red nucleus (p=0.041). AUD did not significantly modulate the rate of susceptibility increase with age in our data. CONCLUSION: Retrospective QSM computed from standard fMRI datasets provides new opportunities for brain iron studies in psychiatry. Substantially elevated brain iron was found in AUD subjects in the basal ganglia and dentate nucleus. This was the first human AUD brain iron study and the first retrospective clinical fMRI QSM study.

Randomized controlled pilot trial of supportive text messages for patients with depression.

BACKGROUND: Depression is projected to be the primary cause of disability worldwide by 2030. In a recent survey, the most commonly cited unmet need among 42.4% of depressed Albertans was the lack of sufficient, accessible, and affordable counselling. Our aim was to test the efficacy of a supportive text messaging mobile health intervention in improving treatment outcomes in depressed patients. METHODS: We performed a single-rater-blinded randomized trial involving 73 patients with Major Depressive Disorder. Patients in the intervention group (n = 35) received twice-daily supportive text messages for 3 months while those in the control group (n = 38) received a single text message every fortnight thanking them for participating in the study. The primary outcome of this study was: "Mean changes in the BDI scores from baseline". RESULTS: After adjusting for baseline BDI scores, a significant difference remained in the 3 month mean BDI scores between the intervention and control groups: (20.8 (SD = 11.7) vs. 24.9 (SD = 11.5), F (1, 60) = 4.83, p = 0.03, ηp2 = 0.07). The mean difference in the BDI scores change was significant with an effect size (Cohen's d) of 0.67. Furthermore, after adjusting for baseline scores, a significant difference remained in the 3 month mean self-rated VAS scores (EQ-5D-5 L scale) between the intervention and control groups, 65.7 (SD = 15.3) vs. 57.4 (SD = 22.9), F (1, 60) =4.16, p = 0.05, ηp2 = 0.065. The mean difference in change mean self-rated VAS scores was also statistically significant with an effect size (Cohen's d) of 0.51. CONCLUSIONS: Our findings suggest that supportive text messages are a potentially useful psychological intervention for depression, especially in underserved populations. Further studies are needed to explore the implications of our findings in larger clinical samples. TRIAL REGISTRATION: ClinicalTrials.gov NCT02327858 . Registered 24 December 2014.

Cross-sectional survey evaluating Text4Mood: mobile health program to reduce psychological treatment gap in mental healthcare in Alberta through daily supportive text messages.

BACKGROUND: To complement the oversubscribed counselling services in Alberta, the Text4Mood program which delivers daily supportive text messages to subscribers was launched on the 18th of January, 2016. This report presents an evaluation of self-reports of the impact of the program on the mental wellbeing of subscribers. METHODS: An online link to a survey questionnaire was created by an expert group and delivered via text messages to mobile phones of all 4111 active subscribers of the Text4Mood program as of April 11, 2016. RESULTS: Overall, 894 subscribers answered the survey (overall response rate 21.7 %). The response rate for individual questions varied and is reported alongside the results. Most respondents were female (83 %, n = 668), Caucasian (83 %, n = 679), and diagnosed with a psychiatric disorder (38 %, n = 307), including Depression (25.4 %, n = 227) and Anxiety (20 %, n = 177). Overall, 52 % (n = 461) signed up for Text4Mood to help elevate their mood and 24.5 % (n = 219) signed up to help them worry less. Most respondents felt the text messages made them more hopeful about managing issues in their lives (81.7 %, n = 588), feel in charge of managing depression and anxiety (76.7 %, n = 552), and feel connected to a support system (75.2 %, n = 542). The majority of respondents felt Text4Mood improved their overall mental well-being (83.1 %, n = 598). CONCLUSION: Supportive text messages are a feasible and acceptable way of delivering adjunctive psychological interventions to the general public with mental health problems. Given that text messages are affordable, readily available, and can be delivered to thousands of people simultaneously, they present an opportunity to help close the psychological treatment gap for mental health patients in Alberta and elsewhere.

The Gut-Brain Axis and the Microbiome in Anxiety Disorders, Post-Traumatic Stress Disorder and Obsessive-Compulsive Disorder.

A large body of research supports the role of stress in several psychiatric disorders in which anxiety is a prominent symptom. Other research has indicated that the gut microbiome-immune system- brain axis is involved in a large number of disorders and that this axis is affected by various stressors. The focus of the current review is on the following stress-related disorders: generalized anxiety disorder, panic disorder, social anxiety disorder, post-traumatic stress disorder and obsessivecompulsive disorder. Descriptions of systems interacting in the gut-brain axis, microbiome-derived molecules and of pro- and prebiotics are given. Preclinical and clinical studies on the relationship of the gut microbiome to the psychiatric disorders mentioned above are reviewed. Many studies support the role of the gut microbiome in the production of symptoms in these disorders and suggest the potential for pro- and prebiotics for their treatment, but there are also contradictory findings and concerns about the limitations of some of the research that has been done. Matters to be considered in future research include longer-term studies with factors such as sex of the subjects, drug use, comorbidity, ethnicity/ race, environmental effects, diet, and exercise taken into account; appropriate compositions of pro- and prebiotics; the translatability of studies on animal models to clinical situations; and the effects on the gut microbiome of drugs currently used to treat these disorders. Despite these challenges, this is a very active area of research that holds promise for more effective, precision treatment of these stressrelated disorders in the future.

The Underlying Neurobiological Mechanisms of Psychosis: Focus on Neurotransmission Dysregulation, Neuroinflammation, Oxidative Stress, and Mitochondrial Dysfunction.

Psychosis, defined as a set of symptoms that results in a distorted sense of reality, is observed in several psychiatric disorders in addition to schizophrenia. This paper reviews the literature relevant to the underlying neurobiology of psychosis. The dopamine hypothesis has been a major influence in the study of the neurochemistry of psychosis and in development of antipsychotic drugs. However, it became clear early on that other factors must be involved in the dysfunction involved in psychosis. In the current review, it is reported how several of these factors, namely dysregulation of neurotransmitters [dopamine, serotonin, glutamate, and γ-aminobutyric acid (GABA)], neuroinflammation, glia (microglia, astrocytes, and oligodendrocytes), the hypothalamic-pituitary-adrenal axis, the gut microbiome, oxidative stress, and mitochondrial dysfunction contribute to psychosis and interact with one another. Research on psychosis has increased knowledge of the complexity of psychotic disorders. Potential new pharmacotherapies, including combinations of drugs (with pre- and probiotics in some cases) affecting several of the factors mentioned above, have been suggested. Similarly, several putative biomarkers, particularly those related to the immune system, have been proposed. Future research on both pharmacotherapy and biomarkers will require better-designed studies conducted on an all stages of psychotic disorders and must consider confounders such as sex differences and comorbidity.

Preclinical evidence for the use of the atypical antipsychotic, brexpiprazole, for opioid use disorder.

Opioid addiction is characterized by adaptations in the mesolimbic dopamine system that occur during chronic opioid use. Alterations in dopaminergic transmission contribute to pathological drug-seeking behavior and other symptoms associated with opioid withdrawal following drug discontinuation, making drug abstinence challenging and contributing to high rates of relapse among those suffering from substance use disorder. Recently, the use of dopamine partial agonists has been proposed as a potential strategy to restore dopaminergic signalling during drug withdrawal, while avoiding the adverse side effects associated with stronger modulators of dopaminergic transmission. We investigated the effects of the atypical antipsychotic brexpiprazole, which is a partial agonist at dopamine D2 and D3 receptors, in a mouse model of opioid dependence. The development of opioid dependence in mice is characterized by locomotor sensitization, analgesic tolerance, opioid-induced hyperalgesia, and drug-seeking behavior. We set up four paradigms to model the effects of brexpiprazole on each of these adaptations that occur during chronic opioid use in male and female C57BL/6J mice. Concomitant treatment of brexpiprazole during chronic morphine administration attenuated the development of locomotor sensitization. Brexpiprazole treatment abolished morphine place preference and blocked reinstatement of this behavior following extinction. Brexpiprazole treatment did not alter morphine analgesia, nor did it impact the development of morphine tolerance. However, brexpiprazole treatment did prevent the expression of opioid-induced hyperalgesia in a tail-withdrawal assay, while failing to improve somatic withdrawal symptoms. Altogether, these results provide preclinical evidence for the efficacy of brexpiprazole as a modulator of dopamine-dependent behaviors during opioid use and withdrawal.

Effects of Transcranial Direct Current Stimulation on Cognitive Deficits in Depression: A Systematic Review.

Background: Major depressive disorder is the leading cause of mental health-related burden globally and up to one-third of major depressive disorder patients never achieve remission. Transcranial Direct Current Stimulation is a non-invasive intervention used to treat individuals diagnosed with major depressive disorder and bipolar disorder. Since the last transcranial direct current stimulation review specifically focusing on cognitive symptoms in major depressive disorder, twice as many papers have been published. Methods: A systematic review was conducted with 5 electronic databases from database inception until March 21, 2022. Randomized controlled trials with at least 1 arm evaluating transcranial direct current stimulation in adults (diagnosed with major depressive disorder or bipolar disorder using the Diagnostic and Statistical Manual of Mental Disorders or International Classification of Diseases criteria) aged 18 or older were included. Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were adopted. Results: : A total of 972 participants were included across 14 studies (60.5% female; mean age of 47.0 years [SD = 16.8]). Nine studies focused on participants with major depressive disorder and all studies used the Diagnostic and Statistical Manual of Mental Disorders to diagnose the participants. Seven out of the 14 studies showed significant improvements in at least 1 cognitive outcome measure in the active transcranial direct current stimulation group compared to the sham group. Several cognitive measures were used across studies, and 12 of the 14 studies reported mild-to-moderate side effects from treatment. Conclusion: : Current transcranial direct current stimulation literature has shown limited evidence for the treatment of cognitive impairments in major depressive disorder and bipolar disorder. Future research that applies machine learning algorithms may enable us to distinguish responders from non-responders, increasing clinical benefits of transcranial direct current stimulation.

Effects of emotional context on impulse control.

High risk behaviors such as narcotic use or physical fighting can be caused by impulsive decision making in emotionally-charged situations. Improved neuroscientific understanding of how emotional context interacts with the control of impulsive behaviors may lead to advances in public policy and/or treatment approaches for high risk groups, including some high-risk adolescents or adults with poor impulse control. Inferior frontal gyrus (IFG) is an important contributor to response inhibition (behavioral impulse control). IFG also has a role in processing emotional stimuli and regulating emotional responses. The mechanism(s) whereby response inhibition processes interact with emotion processing in IFG are poorly understood. We used 4.7 T fMRI in 20 healthy young adults performing a rapid event-related emotional Go/NoGo task. This task combined the Go/NoGo task, which is a classic means of recruiting response inhibition processes, with emotionally neutral and aversive distractor images. In IFG, both response inhibition in an emotionally neutral context (neutral NoGo trials) and aversive emotional picture processing (aversive Go trials) evoked activation greater than the simple response baseline (neutral Go trials). These results are consistent with the literature. Activation for response inhibition in aversive contexts (aversive NoGo-neutral Go trials) was approximately the sum of response inhibition activation (neutral NoGo-neutral Go) and aversive emotional distractor activation (aversive Go-neutral Go). We conclude that response inhibition and aversive emotional stimulus processing activities combine additively (linearly) in IFG, rather than interfering with each other (sub-linearly) or mutually-enhancing each other (super-linearly). We also found previously undocumented interaction effects between response inhibition (NoGo vs. Go) and emotional context (aversive vs. neutral distractor pictures) in bilateral posterior middle temporal gyrus and angular gyrus, right frontal eye field, and other brain regions. These results may reflect the interaction of attention processes driven by emotional stimuli with conflict resolution processes related to Go/NoGo performance.

Ayahuasca, a potentially rapid acting antidepressant: focus on safety and tolerability.

INTRODUCTION: Ayahuasca is a psychedelic brew originally used by Amazonian indigenous groups and in religious rituals. Pre-clinical and observational studies have demonstrated its possible potential as an antidepressant, and open- and placebo-controlled clinical trials corroborated these results. For it to become an approved treatment for depression, its safety and tolerability need to be assessed and documented. AREAS COVERED: We have gathered data regarding the occurrence of adverse events (AEs) in all reported randomized, placebo-controlled trials with healthy and clinical populations involving ayahuasca administration (n = 108 ayahuasca administrations). We systematically categorized these results, recorded their prevalence, and discussed the possible mechanisms related to their emergence. EXPERT OPINION: There were no reports of serious AEs, indicating a relative safety of ayahuasca administration in controlled settings. Most common AEs included nausea, vomiting, headaches, and transient increases in cardiovascular measurements. Ayahuasca research is still in its infancy, especially concerning the absence of large and robust clinical trials to verify its antidepressant effects. Dose standardization, legal prohibition of the possession of its alkaloids and how traditional communities will be compensated if ayahuasca becomes an approved medicine are the biggest obstacles to overcome for its future use in the therapeutic context.

Prediction of Obsessive-Compulsive Disorder: Importance of Neurobiology-Aided Feature Design and Cross-Diagnosis Transfer Learning.

BACKGROUND: Machine learning applications using neuroimaging provide a multidimensional, data-driven approach that captures the level of complexity necessary for objectively aiding diagnosis and prognosis in psychiatry. However, models learned from small training samples often have limited generalizability, which continues to be a problem with automated diagnosis of mental illnesses such as obsessive-compulsive disorder (OCD). Earlier studies have shown that features incorporating prior neurobiological knowledge of brain function and combining brain parcellations from various sources can potentially improve the overall prediction. However, it is unknown whether such knowledge-driven methods can provide a performance that is comparable to state-of-the-art approaches based on neural networks. METHODS: In this study, we apply a transparent and explainable multiparcellation ensemble learning framework EMPaSchiz (Ensemble algorithm with Multiple Parcellations for Schizophrenia prediction) to the task of predicting OCD, based on a resting-state functional magnetic resonance imaging dataset of 350 subjects. Furthermore, we apply transfer learning using the features found effective for schizophrenia to OCD to leverage the commonality in brain alterations across these psychiatric diagnoses. RESULTS: We show that our knowledge-based approach leads to a prediction performance of 80.3% accuracy for OCD diagnosis that is better than domain-agnostic and automated feature design using neural networks. Furthermore, we show that a selection of reduced feature sets can be transferred from schizophrenia to the OCD prediction model without significant loss in prediction performance. CONCLUSIONS: This study presents a machine learning framework for OCD prediction with neurobiology-aided feature design using resting-state functional magnetic resonance imaging that is generalizable and reasonably interpretable.

Superior temporal gyrus functional connectivity predicts transcranial direct current stimulation response in Schizophrenia: A machine learning study.

Transcranial direct current stimulation (tDCS) is a promising adjuvant treatment for persistent auditory verbal hallucinations (AVH) in Schizophrenia (SZ). Nonetheless, there is considerable inter-patient variability in the treatment response of AVH to tDCS in SZ. Machine-learned models have the potential to predict clinical response to tDCS in SZ. This study aims to examine the feasibility of identifying SZ patients with persistent AVH (SZ-AVH) who will respond to tDCS based on resting-state functional connectivity (rs-FC). Thirty-four SZ-AVH patients underwent resting-state functional MRI at baseline followed by add-on, twice-daily, 20-min sessions with tDCS (conventional/high-definition) for 5 days. A machine learning model was developed to identify tDCS treatment responders based on the rs-FC pattern, using the left superior temporal gyrus (LSTG) as the seed region. Functional connectivity between LSTG and brain regions involved in auditory and sensorimotor processing emerged as the important predictors of the tDCS treatment response. L1-regularized logistic regression model had an overall accuracy of 72.5% in classifying responders vs. non-responders. This model outperformed the state-of-the-art convolutional neural networks (CNN) model-both without (59.41%) and with pre-training (68.82%). It also outperformed the L1-logistic regression model trained with baseline demographic features and clinical scores of SZ patients. This study reports the first evidence that rs-fMRI-derived brain connectivity pattern can predict the clinical response of persistent AVH to add-on tDCS in SZ patients with 72.5% accuracy.

Molecular Pathways of the Therapeutic Effects of Ayahuasca, a Botanical Psychedelic and Potential Rapid-Acting Antidepressant.

Ayahuasca is a psychoactive brew traditionally used in indigenous and religious rituals and ceremonies in South America for its therapeutic, psychedelic, and entheogenic effects. It is usually prepared by lengthy boiling of the leaves of the bush Psychotria viridis and the mashed stalks of the vine Banisteriopsis caapi in water. The former contains the classical psychedelic N,N-dimethyltryptamine (DMT), which is thought to be the main psychoactive alkaloid present in the brew. The latter serves as a source for ß-carbolines, known for their monoamine oxidase-inhibiting (MAOI) properties. Recent preliminary research has provided encouraging results investigating ayahuasca's therapeutic potential, especially regarding its antidepressant effects. On a molecular level, pre-clinical and clinical evidence points to a complex pharmacological profile conveyed by the brew, including modulation of serotoninergic, glutamatergic, dopaminergic, and endocannabinoid systems. Its substances also interact with the vesicular monoamine transporter (VMAT), trace amine-associated receptor 1 (TAAR1), and sigma-1 receptors. Furthermore, ayahuasca's components also seem to modulate levels of inflammatory and neurotrophic factors beneficially. On a biological level, this translates into neuroprotective and neuroplastic effects. Here we review the current knowledge regarding these molecular interactions and how they relate to the possible antidepressant effects ayahuasca seems to produce.