#autism

In the second of two director’s messages on RDoC, Dr. Gordon talks about the role of computational psychiatry in the effort to understand the brain processes underlying behavior and mental disorders. Read more

Functional connectivity magnetic resonance imaging (fcMRI) may predict which high-risk, 6-month old infants will develop autism spectrum disorder (ASD) by age 2 years. Read more

For the first time, neuroscientists have boosted a female rodent’s partnering with a male by stimulating connectivity of a brain reward circuit. Understanding the circuitry of such affiliative behavio ... Read more

In the first of two messages, Dr. Gordon shares his thoughts on NIMH’s Research Domain Criteria (RDoC), and discusses how we might be able to use big data approaches to enhance this research framework ... Read more

A streamlined behavioral therapy delivered in a pediatrics practice offered much greater benefit to youth with anxiety and depression than a more standard referral to mental health care with follow-up ... Read more

NIMH grantee Karl Deisseroth, M.D., Ph.D., of Stanford University, has been awarded one of science’s most generous prizes. A German foundation presented the inventor of technologies that are transform ... Read more

The goal of this initiative is to solicit applications in the area of eXplainable Artificial Intelligence (XAI) applied to NIMH’s mental health priorities. Current machine learning approaches focus on ... Read more

The purpose of this initiative is to support projects that implement creative and robust molecular epidemiologic approaches that leverage existing electronic medical records (EMR) from large, populati ... Read more

The goal of the NIMH PDSP is to provide the research community with access to broad screening capabilities in the form of pharmacological and functional assays. Read more

Pediatric clinical trials that investigate drug candidates in psychiatry are rare. Yet these trials are critical for evaluating safety, tolerance, efficacy, and optimal dosing in developing children. ... Read more

The goal of this initiative is to support a practice-based research network to transform the development, delivery, and sustainability of evidence-based mental health practices and services. Read more

The goal of this initiative is to rapidly increase the capacity of the NIMH investigator workforce to develop and test the effectiveness of a broad range of services that address the needs of adults a ... Read more

The goal of this initiative is to solicit applications in the area of eXplainable Artificial Intelligence (XAI) applied to NIMH’s mental health priorities. Current machine learning approaches focus on ... Read more

The purpose of this initiative is to support projects that implement creative and robust molecular epidemiologic approaches that leverage existing electronic medical records (EMR) from large, populati ... Read more