Carsen Stringer

This makes our lives as neuroscientists hard. Single measurements of neurons are not reliable (gray dots), and we need to repeat the measurements many times to average out the noise (black line).pic.twitter.com/N7WXNcuix6

Maybe, we thought, the brain uses some kind of averaging over its millions of noisy neurons to get a clean estimate of what it’s looking at.pic.twitter.com/jzTSA9kyK0

Can we find these “magical” combinations by looking at the brain while it’s looking at our images? We used a microscope to record the activity of ~20,000 neurons simultaneously. Here is all of them from one session in random colors.pic.twitter.com/iaNkGRUZCD

We used linear regression to find weights for each neuron that combine their activities into “super-neurons”.pic.twitter.com/Rxepy0oB69

These super-neurons were much less noisy than single neurons. In fact, the super-neurons could tell the difference between 45 and 46 degrees on 95% of the test trials. Can you?pic.twitter.com/wuueSaanHH

Imagine asking a mouse to distinguish such small differences... Our colleagues in @BenucciLab actually tried! The mouse could only tell apart angle differences of 29 degrees, which was about 100 times worse than the neurons.pic.twitter.com/MeXXVeiWma

Even for humans it’s difficult, but I bet you can see the difference if I make the pictures into a movie.pic.twitter.com/S7nfZEpGbP