Neuropsychopharmacology最新文献

{"title":"Improved patient identification by incorporating symptom severity in deep learning using neuroanatomic images in first episode schizophrenia.","authors":"Wenjing Zhang, Lituan Wang, Xusha Wu, Li Yao, Zhang Yi, Hong Yin, Lei Zhang, Su Lui, Qiyong Gong","doi":"10.1038/s41386-024-02021-y","DOIUrl":"https://doi.org/10.1038/s41386-024-02021-y","url":null,"abstract":"<p><p>Brain alterations associated with illness severity in schizophrenia remain poorly understood. Establishing linkages between imaging biomarkers and symptom expression may enhance mechanistic understanding of acute psychotic illness. Constructing models using MRI and clinical features together to maximize model validity may be particularly useful for these purposes. A multi-task deep learning model for standard case/control recognition incorporated with psychosis symptom severity regression was constructed with anatomic MRI collected from 286 patients with drug-naïve first-episode schizophrenia and 330 healthy controls from two datasets, and validated with an independent dataset including 40 first-episode schizophrenia. To evaluate the contribution of regression to the case/control recognition, a single-task classification model was constructed. Performance of unprocessed anatomical images and of predefined imaging features obtained using voxel-based morphometry (VBM) and surface-based morphometry (SBM), were examined and compared. Brain regions contributing to the symptom severity regression and illness identification were identified. Models developed with unprocessed images achieved greater group separation than either VBM or SBM measurements, differentiating schizophrenia patients from healthy controls with a balanced accuracy of 83.0% with sensitivity = 76.1% and specificity = 89.0%. The multi-task model also showed superior performance to single-task classification model without considering clinical symptoms. These findings showed high replication in the site-split validation and external validation analyses. Measurements in parietal, occipital and medial frontal cortex and bilateral cerebellum had the greatest contribution to the multi-task model. Incorporating illness severity regression in pattern recognition algorithms, our study developed an MRI-based model that was of high diagnostic value in acutely ill schizophrenia patients, highlighting clinical relevance of the model.</p>","PeriodicalId":19143,"journal":{"name":"Neuropsychopharmacology","volume":" ","pages":""},"PeriodicalIF":6.6,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142591193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In memoriam: Klaus A Miczek, PhD.","authors":"Harriet de Wit, Jack Bergman, Linda Dykstra, Chris-Ellyn Johanson","doi":"10.1038/s41386-024-02019-6","DOIUrl":"https://doi.org/10.1038/s41386-024-02019-6","url":null,"abstract":"","PeriodicalId":19143,"journal":{"name":"Neuropsychopharmacology","volume":" ","pages":""},"PeriodicalIF":6.6,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142576495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neuroimaging education in psychiatric training.","authors":"Joseph J Cooper, Victor A Valencia, Kathy Niu","doi":"10.1038/s41386-024-01909-z","DOIUrl":"10.1038/s41386-024-01909-z","url":null,"abstract":"<p><p>As the histories of psychiatry, neurology, and neuroimaging interweave through time, psychiatry has only recently started to recognize the need to embrace neuroimaging like its sibling specialty. While imaging in psychiatric research is well accepted, there is current clinical utility as well. Standards for psychiatry residency and board certification in the USA and abroad have carved out a place for neuroimaging, but the implementation is variable and sparse in the USA. The few publications that describe neuroimaging teaching to psychiatrists have barriers to widespread adoption, and no comprehensive curricular solution has been developed. In this context, we describe some of the barriers and propose solutions to shape the future of neuroimaging education for psychiatrists.</p>","PeriodicalId":19143,"journal":{"name":"Neuropsychopharmacology","volume":" ","pages":"298-304"},"PeriodicalIF":6.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11525630/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141724095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neuroimaging and suicide-specific stimuli.","authors":"Elizabeth D Ballard, Steven J Lamontagne","doi":"10.1038/s41386-024-01936-w","DOIUrl":"10.1038/s41386-024-01936-w","url":null,"abstract":"","PeriodicalId":19143,"journal":{"name":"Neuropsychopharmacology","volume":" ","pages":"308-309"},"PeriodicalIF":6.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11525674/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141760072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human neuroimaging and antipsychotic neurobiology at millisecond temporal resolution.","authors":"Daniel P Eisenberg, Karen F Berman","doi":"10.1038/s41386-024-01933-z","DOIUrl":"10.1038/s41386-024-01933-z","url":null,"abstract":"","PeriodicalId":19143,"journal":{"name":"Neuropsychopharmacology","volume":" ","pages":"306-307"},"PeriodicalIF":6.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11525651/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141766863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measuring neuroplasticity in human development: the potential to inform the type and timing of mental health interventions.","authors":"Max P Herzberg, Ashley N Nielsen, Joan Luby, Chad M Sylvester","doi":"10.1038/s41386-024-01947-7","DOIUrl":"10.1038/s41386-024-01947-7","url":null,"abstract":"<p><p>Neuroplasticity during sensitive periods, the molecular and cellular process of enduring neural change in response to external stimuli during windows of high environmental sensitivity, is crucial for adaptation to expected environments and has implications for psychiatry. Animal research has characterized the developmental sequence and neurobiological mechanisms that govern neuroplasticity, yet gaps in our ability to measure neuroplasticity in humans limit the clinical translation of these principles. Here, we present a roadmap for the development and validation of neuroimaging and electrophysiology measures that index neuroplasticity to begin to address these gaps. We argue that validation of measures to track neuroplasticity in humans will elucidate the etiology of mental illness and inform the type and timing of mental health interventions to optimize effectiveness. We outline criteria for evaluating putative neuroimaging measures of plasticity in humans including links to neurobiological mechanisms shown to govern plasticity in animal models, developmental change that reflects heightened early life plasticity, and prediction of neural and/or behavior change. These criteria are applied to three putative measures of neuroplasticity using electroencephalography (gamma oscillations, aperiodic exponent of power/frequency) or functional magnetic resonance imaging (amplitude of low frequency fluctuations). We discuss the use of these markers in psychiatry, envision future uses for clinical and developmental translation, and suggest steps to address the limitations of the current putative neuroimaging measures of plasticity. With additional work, we expect these markers will significantly impact mental health and be used to characterize mechanisms, devise new interventions, and optimize developmental trajectories to reduce psychopathology risk.</p>","PeriodicalId":19143,"journal":{"name":"Neuropsychopharmacology","volume":" ","pages":"124-136"},"PeriodicalIF":6.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11525577/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141893963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Opioid inhalation in mice as a model to investigate biological drivers of the opioid crisis.","authors":"Renata C N Marchette, Leandro F Vendruscolo","doi":"10.1038/s41386-024-01949-5","DOIUrl":"10.1038/s41386-024-01949-5","url":null,"abstract":"","PeriodicalId":19143,"journal":{"name":"Neuropsychopharmacology","volume":" ","pages":"347-348"},"PeriodicalIF":6.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11525815/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141893964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Psychiatric neuroimaging designs for individualised, cohort, and population studies.","authors":"Martin Gell, Stephanie Noble, Timothy O Laumann, Steven M Nelson, Brenden Tervo-Clemmens","doi":"10.1038/s41386-024-01918-y","DOIUrl":"10.1038/s41386-024-01918-y","url":null,"abstract":"<p><p>Psychiatric neuroimaging faces challenges to rigour and reproducibility that prompt reconsideration of the relative strengths and limitations of study designs. Owing to high resource demands and varying inferential goals, current designs differentially emphasise sample size, measurement breadth, and longitudinal assessments. In this overview and perspective, we provide a guide to the current landscape of psychiatric neuroimaging study designs with respect to this balance of scientific goals and resource constraints. Through a heuristic data cube contrasting key design features, we discuss a resulting trade-off among small sample, precision longitudinal studies (e.g., individualised studies and cohorts) and large sample, minimally longitudinal, population studies. Precision studies support tests of within-person mechanisms, via intervention and tracking of longitudinal course. Population studies support tests of generalisation across multifaceted individual differences. A proposed reciprocal validation model (RVM) aims to recursively leverage these complementary designs in sequence to accumulate evidence, optimise relative strengths, and build towards improved long-term clinical utility.</p>","PeriodicalId":19143,"journal":{"name":"Neuropsychopharmacology","volume":" ","pages":"29-36"},"PeriodicalIF":6.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11525483/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141982863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Revisiting the role of computational neuroimaging in the era of integrative neuroscience.","authors":"Alisa M Loosen, Ayaka Kato, Xiaosi Gu","doi":"10.1038/s41386-024-01946-8","DOIUrl":"10.1038/s41386-024-01946-8","url":null,"abstract":"<p><p>Computational models have become integral to human neuroimaging research, providing both mechanistic insights and predictive tools for human cognition and behavior. However, concerns persist regarding the ecological validity of lab-based neuroimaging studies and whether their spatiotemporal resolution is not sufficient for capturing neural dynamics. This review aims to re-examine the utility of computational neuroimaging, particularly in light of the growing prominence of alternative neuroscientific methods and the growing emphasis on more naturalistic behaviors and paradigms. Specifically, we will explore how computational modeling can both enhance the analysis of high-dimensional imaging datasets and, conversely, how neuroimaging, in conjunction with other data modalities, can inform computational models through the lens of neurobiological plausibility. Collectively, this evidence suggests that neuroimaging remains critical for human neuroscience research, and when enhanced by computational models, imaging can serve an important role in bridging levels of analysis and understanding. We conclude by proposing key directions for future research, emphasizing the development of standardized paradigms and the integrative use of computational modeling across neuroimaging techniques.</p>","PeriodicalId":19143,"journal":{"name":"Neuropsychopharmacology","volume":" ","pages":"103-113"},"PeriodicalIF":6.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11525590/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142146043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quality over quantity: powering neuroimaging samples in psychiatry.","authors":"Carolina Makowski, Thomas E Nichols, Anders M Dale","doi":"10.1038/s41386-024-01893-4","DOIUrl":"10.1038/s41386-024-01893-4","url":null,"abstract":"<p><p>Neuroimaging has been widely adopted in psychiatric research, with hopes that these non-invasive methods will provide important clues to the underpinnings and prediction of various mental health symptoms and outcomes. However, the translational impact of neuroimaging has not yet reached its promise, despite the plethora of computational methods, tools, and datasets at our disposal. Some have lamented that too many psychiatric neuroimaging studies have been underpowered with respect to sample size. In this review, we encourage this discourse to shift from a focus on sheer increases in sample size to more thoughtful choices surrounding experimental study designs. We propose considerations at multiple decision points throughout the study design, data modeling and analysis process that may help researchers working in psychiatric neuroimaging boost power for their research questions of interest without necessarily increasing sample size. We also provide suggestions for leveraging multiple datasets to inform each other and strengthen our confidence in the generalization of findings to both population-level and clinical samples. Through a greater emphasis on improving the quality of brain-based and clinical measures rather than merely quantity, meaningful and potentially translational clinical associations with neuroimaging measures can be achieved with more modest sample sizes in psychiatry.</p>","PeriodicalId":19143,"journal":{"name":"Neuropsychopharmacology","volume":" ","pages":"58-66"},"PeriodicalIF":6.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11525971/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141432396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}