David Dobbs
Contributing writer
The Transmitter
From this contributor
Remembering Mark Hallett, leader in transcranial magnetic stimulation
The long-time NINDS researcher, best known for studying movement disorders, has died at age 82.
Remembering Mark Hallett, leader in transcranial magnetic stimulation
The new history of autism, part III
For decades, two figures have dominated the history of autism studies. Today, newly excavated documents are calling into question the primacy of these men as founders of the field.
The new history of autism, part II
For decades, two figures have dominated the history of autism studies. Today, newly excavated documents are calling into question the primacy of these men as founders of the field.
The new history of autism, part I
For decades, two figures have dominated the history of autism studies. Today, newly excavated documents are calling into question the primacy of these men as founders of the field.
Rethinking regression in autism
The loss of abilities that besets some toddlers with autism is probably less sudden and more common than anyone thought.
Explore more from The Transmitter
Why neural foundation models work, and what they might—and might not—teach us about the brain
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?
Why neural foundation models work, and what they might—and might not—teach us about the brain
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?
Error equation predicts brain’s ability to generalize
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.
Error equation predicts brain’s ability to generalize
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.
Embrace complexity to improve the translatability of basic neuroscience
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.
Embrace complexity to improve the translatability of basic neuroscience
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.