Brain and cognitive sciences
Brain and cognitive sciences

Estimating suicide risk from text

A new language-processing tool could help identify the highest-risk individuals from natural language, enabling swifter interventions.

Poitras Center to fuel early careers of 50 young scientists dedicated to psychiatric disorders research

Patricia and James Poitras ’63 provide fellowships for graduate students and postdocs who will shape the future of mental health research.

Alexander Rakhlin named director of the MIT Statistics and Data Science Center

An expert in machine learning, statistics, and computation, Rakhlin succeeds Professor Ankur Moitra.

MIT in the media: Exploring how curiosity-driven science is an essential ingredient in America’s success

“Scientific American” showcases the history and future of America’s scientific engine, highlighting promising young scientists and icons at MIT and beyond.

Beacon Biosignals is mapping the brain during sleep

Founded by Jake Donoghue PhD ’19 and former MIT researcher Jarrett Revels, the company is creating an AI-driven platform to help diagnose and treat disease.

Improving understanding with language

MIT senior Olivia Honeycutt investigates how the ways we communicate can shape our views of the world.

AI algorithm enables tracking of vital white matter pathways

Opening a new window on the brainstem, a new tool reliably and finely resolves distinct nerve bundles in live diffusion MRI scans, revealing signs of injury or disease.

At MIT, a continued commitment to understanding intelligence

With support from the Siegel Family Endowment, the newly renamed MIT Siegel Family Quest for Intelligence investigates how brains produce intelligence and how it can be replicated to solve problems.

A “scientific sandbox” lets researchers explore the evolution of vision systems

The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.

Enabling small language models to solve complex reasoning tasks

The “self-steering” DisCIPL system directs small models to work together on tasks with constraints, like itinerary planning and budgeting.