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As a fellow at the Dana Foundation, she merged two familiar passions and discovered a new one: science philanthropy.

Complex, multidimensional tasks that unfold over time could reveal how different brain areas work together to support decisions.

Estropipate, paclitaxel and levocarnitine altered behaviors tied to SCN2A and DYRK1A variants specifically, a new open-source platform revealed.

The findings could influence how researchers interpret signals from techniques that use blood flow as a surrogate for neuronal activity.

A 1960s study by Kelleher and Morse found that lever pressing in squirrel monkeys depended not on whether they received a reward or shock, but on the rules of the task. This taught Calipari to think deeply about factors that influence how behavior is generated and maintained.

These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?

Four statistical measurements of neural network geometry capture how well brains and artificial networks use what they already know to solve new problems, a study suggests.

Researchers must learn to view heterogeneity as an essential feature of the systems they study and a central consideration in experimental design, not a variable to control for or reduce.

Her favorite part of research was talking about it. So she left academia and turned that passion into a successful company.

Senescence presents differently depending on the cell type, toxic trigger and neighboring cells, two new studies find.

The changes would restrict the sharing of human neuroimaging, transcriptomic and genetic data.

Addressing this gap will require collecting widespread data on pregnancy, menopause and other life events women experience—and could bring us closer to the “holy grail” of linking brain and behavior.

The “intuitive” neuropharmacologist pushed against the status quo.

Adjusting genetic analyses could help plug autism’s heritability gap, according to a new preprint.

In a 2011 Neuron study, Stephan Lammel and his colleagues showed that dopamine neurons with different projections have different physiological properties. The work inspired Lerner to think about how to challenge widely held assumptions in the field.