neuroscientist @HHMIJanelia, thinking about thinking, 
#suite2p | diversity and open-science for better science | Ⓥ | she/her
U tweetove putem weba ili aplikacija drugih proizvođača možete dodati podatke o lokaciji, kao što su grad ili točna lokacija. Povijest lokacija tweetova uvijek možete izbrisati. Saznajte više
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
We conclude that mice have a lot of information in their brains, which are 1000x smaller than ours.pic.twitter.com/xVxz0TW5cB
They can’t communicate this information to us, but that does not mean they don’t use it, for example as a first step to another computation.pic.twitter.com/9xxfVQ7nPW
We hope to find out in the future what these other computations might be.
We publicly shared the data and code from this paper if anyone wants to dig further. data:https://figshare.com/articles/Recordings_of_20_000_neurons_from_V1_in_response_to_oriented_stimuli/8279387 … code:https://github.com/MouseLand/stringer-et-al-2019 …
1) Is this equivalent to considering each neuron as an agent in an ensemble? 2) Is there any reason to believe this "super neuron" receives and processes it's inputs linearly?
3) when you say super neuron, are you actually implying the results end up at a specific neuron for use in later calculation or are you referring to the state of the system?
Twitter je možda preopterećen ili ima kratkotrajnih poteškoća u radu. Pokušajte ponovno ili potražite dodatne informacije u odjeljku Status Twittera.
