Organizers of a leading neuroscience conference are trying to allay concerns after a policy that bars submissions from researchers based at institutions sanctioned by the United States government attracted intense scrutiny online.
By Dalmeet Singh Chawla
Last week, the NIH announced an influx of $150 million to develop infrastructure for the testing of novel alternative methods, following the administration’s push to move away from animal research.
By Claudia López Lloreda
Trainees need to learn how to identify a paper’s major takeaways and integrate them into their understanding. In her essay, Nora Bradford argues that this skill doesn’t come from outsourcing the work to large language models.
Explore “Brainstorming,” @thetransmitter's new LinkedIn newsletter that looks at how neuroscientists are solving research challenges. The first edition features nontraditional model organisms that are well suited for studying certain behaviors or neurological conditions.
Each month, The Transmitter explores creative approaches neuroscientists are taking to solve problems that arise in their research. In this installment, we see how researchers work backward from specific phenomena they want to study to find nature’s ready-made behavioral and physiological examples.
A mouse’s head direction cells, which support navigation, maintain stable tuning over the course of weeks, a new study shows.
By @avaskham
On the latest episode, of the Brain Inspired podcast, Paul Middlebrooks talks with Juan Gallego about the wealth of evidence that supports the view that neural manifolds are real and useful, even if they may not completely solve the age-old mind-body problem.
“Based on astrocytic activity alone, you can tell whether a mouse is in its comfort zone,” a new study suggests.
By Holly Barker
Two studies looking at the link between the microbiome and the brain contain data duplications, casting doubt on the findings, says researcher Dorothy Bishop.
By Claudia López Lloreda
Neuroscience has become increasingly concerned with prediction, and machine learning with causal explanation, with each field adopting methods from the other, writes Sam Gershman. Will this bring us closer to understanding neural systems?
