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Study connects neural gene expression differences to functional distinctions

The Picower Institute for Learning and Memory found that the two closely related neuronal subtypes differed from each other in how they expressed more than 800 genes. By manipulating genes whose expression differed most prominently, the scientists were then able to show how they produced several of the observable differences between the cells.
Charles Whittaker Nicole Aponte Troy Littleton Karen Cunningham Yulia Akbergenova Suresh Jetti
Source: mit.edu

Cracking the code that relates brain and behavior in a simple animal

An MIT team has produced an atlas of how most cells, and the circuits they take part in, encode a worm's actions. The atlas reveals the underlying โ€œlogicโ€ of how an animal brain produces a sophisticated and flexible repertoire of behaviors, even as its environmental circumstances change.
Matthew Gomes Ziyu Wang Netta Cohen Saba Baskoylu Steven Flavell Eric Bueno
Source: mit.edu

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AI models are powerful, but are they biologically plausible?

Researchers hypothesize that a powerful type of AI model known as a transformer could be implemented in the brain through networks of neuron and astrocyte cells. The work could offer insights into how the brain works and help scientists understand why transformers are so effective at machine-learning tasks.
United States Konstantinos Michmizos Kseniav Kastanenka Dmitry Krotov Leo Kozachkov Research Institute
Source: mit.edu

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