Elucidating the neuropathological and molecular heterogeneity of amyloid-beta and tau in Alzheimer's disease through machine learning and transcriptomic integration.

Discerning functional brain network variations related to neuropathological aggregates in Alzheimer's disease (AD), including amyloid-beta (Abeta) and phosphorylated tau (p-tau), is crucial for understanding their link to cognitive decline and underlying molecular mechanisms. However, these variations are often confounded by normal aging-related changes, complicating interpretation. To address this challenge, we first defined Alzheimer's continuum cases (Abeta positive (A+), n = 129) and normal elderly (Abeta negative (A-), n = 160) using cerebral spinal fluid amyloid levels, and then applied a novel deep learning approach to resting-state connectivity using functional magnetic resonance imaging (fMRI) of the 289 subjects to disentangle A+-specific dimensions in brain network alterations from those shared with A- individuals.

How Psychedelics Modulate Multiple Memory Mechanisms in Posttraumatic Stress Disorder.

Posttraumatic stress disorder (PTSD) is a psychiatric disorder with defining abnormalities in memory, and psychedelics may be promising candidates for the treatment of PTSD given their effects on multiple memory systems. Most PTSD and psychedelic research has investigated memory with fear conditioning and extinction. While fruitful, conditioning and extinction provide a limited model of the complexity of PTSD and phenomenology of psychedelics, thereby limiting the refinement of therapies.

Contrastive Functional Connectivity Defines Neurophysiology-informed Symptom Dimensions in Major Depression.

Background: Major depressive disorder (MDD) is a prevalent psychiatric disorder characterized by substantial clinical and neurobiological heterogeneity. Conventional studies that solely focus on clinical symptoms or neuroimaging metrics often fail to capture the intricate relationship between these modalities, limiting their ability to disentangle the complexity in MDD. Moreover, patient neuroimaging data typically contains normal sources of variance shared with healthy controls, which can obscure disorder-specific variance and complicate the delineation of disease heterogeneity.

Discriminative functional connectivity signature of cocaine use disorder links to rTMS treatment response.

Cocaine use disorder (CUD) is prevalent, and repetitive transcranial magnetic stimulation (rTMS) shows promise in reducing cravings. However, the association between a consistent CUD-specific functional connectivity signature and treatment response remains unclear. Here we identify a validated functional connectivity signature from functional magnetic resonance imaging to discriminate CUD, with successful independent replication.

Symptom dimensions of resting-state electroencephalographic functional connectivity in autism.

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by social and communication deficits (SCDs), restricted and repetitive behaviors (RRBs) and fixated interests. Despite its prevalence, development of effective therapy for ASD is hindered by its symptomatic and neurophysiological heterogeneities. To comprehensively explore these heterogeneities, we developed a new analytical framework combining contrastive learning and sparse canonical correlation analysis that identifies symptom-linked resting-state electroencephalographic connectivity dimensions within 392 ASD samples.

Dementia Subtypes Defined Through Neuropsychiatric Symptom-Associated Brain Connectivity Patterns.

Importance: Understanding the heterogeneity of neuropsychiatric symptoms (NPSs) and associated brain abnormalities is essential for effective management and treatment of dementia.

Objective: To identify dementia subtypes with distinct functional connectivity associated with neuropsychiatric subsyndromes.

Design, Setting, And Participants: Using data from the Open Access Series of Imaging Studies-3 (OASIS-3; recruitment began in 2005) and Alzheimer Disease Neuroimaging Initiative (ADNI; recruitment began in 2004) databases, this cross-sectional study analyzed resting-state functional magnetic resonance imaging (fMRI) scans, clinical assessments, and neuropsychological measures of participants aged 42 to 95 years.

Psychedelics and Evidence-based Psychotherapy: A Systematic Review with Recommendations for Advancing Psychedelic Therapy Research.

Administration of psychedelics for mental health treatment, typically referred to as "psychedelic-assisted therapy," is a broad term with a very heterogeneous implementation. Despite increasing interest in the clinical application of psychedelic compounds for psychiatric disorders, there is no consensus on how to best integrate the psychedelic experience with evidence-based psychotherapeutic treatment. This systematic review provides a timely appraisal of existing approaches to combining psychotherapy with psychedelics and provides clear recommendations to best develop, optimize, and integrate evidence-based psychotherapy with psychedelic administration for straightforward scientific inference and maximal therapeutic benefit.

Optimizing Antidepressant Efficacy: Generalizable Multimodal Neuroimaging Biomarkers for Prediction of Treatment Response.

Major depressive disorder (MDD) is a common and often severe condition that profoundly diminishes quality of life for individuals across ages and demographic groups. Unfortunately, current antidepressant and psychotherapeutic treatments exhibit limited efficacy and unsatisfactory response rates in a substantial number of patients. The development of effective therapies for MDD is hindered by the insufficiently understood heterogeneity within the disorder and its elusive underlying mechanisms.

Delineating Transdiagnostic Subtypes in Neurodevelopmental Disorders via Contrastive Graph Machine Learning of Brain Connectivity Patterns.

Neurodevelopmental disorders, such as Attention Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD), are characterized by comorbidity and heterogeneity. Identifying distinct subtypes within these disorders can illuminate the underlying neurobiological and clinical characteristics, paving the way for more tailored treatments. We adopted a novel transdiagnostic approach across ADHD and ASD, using cutting-edge contrastive graph machine learning to determine subtypes based on brain network connectivity as revealed by resting-state functional magnetic resonance imaging.

Individual deviations from normative electroencephalographic connectivity predict antidepressant response.

Background: Antidepressant medications yield unsatisfactory treatment outcomes in patients with major depressive disorder (MDD) with modest advantages over the placebo, partly due to the elusive mechanisms of antidepressant responses and unexplained heterogeneity in patient's response to treatment. Here we develop a novel normative modeling framework to quantify individual deviations in psychopathological dimensions that offers a promising avenue for the personalized treatment for psychiatric disorders.

Methods: We built a normative model with resting-state electroencephalography (EEG) connectivity data from healthy controls of three independent cohorts.

The mechanistic divide in psychedelic neuroscience: An unbridgeable gap?

In recent years, psychedelics have generated considerable excitement and interest as potential novel therapeutics for an array of conditions, with the most advanced evidence base in the treatment of certain severe and/or treatment-resistant psychiatric disorders. An array of clinical and pre-clinical evidence has informed our current understanding of how psychedelics produce profound alterations in consciousness. Mechanisms of psychedelic action include receptor binding and downstream cellular and transcriptional pathways, with long-term impacts on brain structure and function-from the level of single neurons to large-scale circuits.

Latent-state and model-based learning in PTSD.

Post-traumatic stress disorder (PTSD) is characterized by altered emotional and behavioral responding following a traumatic event. In this article, we review the concepts of latent-state and model-based learning (i.e.

Defining Dementia Subtypes Through Neuropsychiatric Symptom-Linked Brain Connectivity Patterns.

Background: Dementia is highly heterogeneous, with pronounced individual differences in neuropsychiatric symptoms (NPS) and neuroimaging findings. Understanding the heterogeneity of NPS and associated brain abnormalities is essential for effective management and treatment of dementia.

Methods: Using large-scale neuroimaging data from the Open Access Series of Imaging Studies (OASIS-3), we conducted a multivariate sparse canonical correlation analysis to identify functional connectivity-informed symptom dimensions.

Individual Deviations from Normative Electroencephalographic Connectivity Predict Antidepressant Response.

Antidepressant medications yield unsatisfactory treatment outcomes in patients with major depressive disorder (MDD) with modest advantages over the placebo. This modest efficacy is partly due to the elusive mechanisms of antidepressant responses and unexplained heterogeneity in patient's response to treatment - the approved antidepressants only benefit a portion of patients, calling for personalized psychiatry based on individual-level prediction of treatment responses. Normative modeling, a framework that quantifies individual deviations in psychopathological dimensions, offers a promising avenue for the personalized treatment for psychiatric disorders.

Dissecting Symptom-linked Dimensions of Resting-State Electroencephalographic Functional Connectivity in Autism with Contrastive Learning.

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by , and . Despite its high prevalence, development of effective therapy for ASD is hindered by its symptomatic and neurophysiological heterogeneities. To collectively dissect the ASD heterogeneity in neurophysiology and symptoms, we develop a new analytical framework combining contrastive learning and sparse canonical correlation analysis to identify resting-state EEG connectivity dimensions linked to ASD behavioral symptoms within 392 ASD samples.

A generalizable functional connectivity signature characterizes brain dysfunction and links to rTMS treatment response in cocaine use disorder.

Cocaine use disorder (CUD) is a prevalent substance abuse disorder, and repetitive transcranial magnetic stimulation (rTMS) has shown potential in reducing cocaine cravings. However, a robust and replicable biomarker for CUD phenotyping is lacking, and the association between CUD brain phenotypes and treatment response remains unclear. Our study successfully established a cross-validated functional connectivity signature for accurate CUD phenotyping, using resting-state functional magnetic resonance imaging from a discovery cohort, and demonstrated its generalizability in an independent replication cohort.

Individualized fMRI connectivity defines signatures of antidepressant and placebo responses in major depression.

Though sertraline is commonly prescribed in patients with major depressive disorder (MDD), its superiority over placebo is only marginal. This is in part due to the neurobiological heterogeneity of the individuals. Characterizing individual-unique functional architecture of the brain may help better dissect the heterogeneity, thereby defining treatment-predictive signatures to guide personalized medication.

Volume of subcortical brain regions in social anxiety disorder: mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group.

There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls.

Transdiagnostic connectome signatures from resting-state fMRI predict individual-level intellectual capacity.

Medication and other therapies for psychiatric disorders show unsatisfying efficacy, in part due to the significant clinical/ biological heterogeneity within each disorder and our over-reliance on categorical clinical diagnoses. Alternatively, dimensional transdiagnostic studies have provided a promising pathway toward realizing personalized medicine and improved treatment outcomes. One factor that may influence response to psychiatric treatments is cognitive function, which is reflected in one's intellectual capacity.

Laboratory models of post-traumatic stress disorder: The elusive bridge to translation.

Post-traumatic stress disorder (PTSD) is a debilitating mental illness composed of a heterogeneous collection of symptom clusters. The unique nature of PTSD as arising from a precipitating traumatic event helps simplify cross-species translational research modeling the neurobehavioral effects of stress and fear. However, the neurobiological progress on these complex neural circuits informed by animal models has yet to produce novel, evidence-based clinical treatment for PTSD.

Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group.

The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis.