4 papers
Fast deep learning correspondence for neuron tracking and identification in C.elegans using synthetic training
Xinwei Yu, Matthew S. Creamer, Francesco Randi +3
We present an automated method to track and identify neurons in C. elegans, called "fast Deep Learning Correspondence" or fDLC, based on the transformer network architecture. The m…
Nonequilibrium Green's functions for functional connectivity in the brain
Francesco Randi, Andrew M. Leifer
A theoretical framework describing the set of interactions between neurons in the brain, or functional connectivity, should include dynamical functions representing the propagation…
Searching for collective behavior in a small brain
Xiaowen Chen, Francesco Randi, Andrew M. Leifer +1
In large neuronal networks, it is believed that functions emerge through the collective behavior of many interconnected neurons. Recently, the development of experimental technique…
Temporal processing and context dependency in C. elegans mechanosensation
Mochi Liu, Anuj K Sharma, Joshua W Shaevitz +1
A quantitative understanding of how sensory signals are transformed into motor outputs places useful constraints on brain function and helps reveal the brain's underlying computati…