Our new work “The network structure of scientific revolutions” out in https://t.co/VnoMhwulHC. We use network science to operationalize and test philosophical theories about the development of scientific ideas on growing networks of hyperlinked articles on Wikipedia. 1/
Defended my PhD thesis!
Thanks to my mentor @DaniSBassett, my committee members, the lab, and my program @PennNGG for their support.
Looking forward to researching web3 with @sinanaral at @mit_ide!
From logical reasoning to mental simulation, recurrent neural networks (RNNs) possess an incredible capacity for computation. To fully harness this capacity, we developed a programming language for RNNs https://t.co/gqecBR1QNc. Here is a game of pong programmed inside of an RNN.
Fluctuations in functional connectivity associated with interictal epileptiform discharges (IEDs) in intracranial EEG (in ~140 ppl!) https://t.co/b90ezLcnxP
If you think about how IEDs contribute to FC changes in epilepsy or what to do with IEDs in data, this might be helpful!
Check out our new work - Environmental influences on the pace of brain development w/ @DaniSBassett & @ally_mackey in @NatRevNeurosci!
We suggest that childhood SES affects not only the outcome but also pace of brain dev, w/ implications for plasticity.
https://t.co/kr1ckrve9A
How do recurrent neural networks learn to manipulate memories and predict the future just by observing a few examples? Find out here! https://t.co/MK8oFlJHqM in collaboration with @zhixin_lu@NozariErfan@pappasg69@DaniSBassett