When probes are inserted into the brain for research or clinical purposes, the electrical activity of neurons is recorded. These signals can be used to understand how the brain performs certain computations or even to identify pathological states. However, brains are composed of cell types that perform different roles in computation and are differentially affected by certain psychiatric disorders or drugs. Without a deep understanding of how cell types orchestrate the overall activity patterns, we cannot develop the next generation of therapies.

Researchers from Boston University’s Chobanian & Avedisian School of Medicine, College of Arts & Sciences, College of Engineering and Faculty of Computing & Data Sciences have developed a tool called PhysMAP to separate the “voices” of individual cell types within a crowd of electrical noise by combining several complementary features of each type's electrical signature. This machine learning algorithm could open up the study of how cell types shape both the healthy computations and the pathological states that electrical recordings have long been able to detect but never fully understood.

Geoengineering could protect the Amazon rainforest from climate change, new research shows.

The development of batteries for electric vehicles has progressed much faster than experts and policymakers had anticipated. New research shows that the market is well equipped to cope with both raw material shortages and price increases. This raises questions about which materials are actually critical to the energy transition, according to the researchers.