3 citations · 5 across the 7 of their papers we have counts for
5 papers · 1 filter
When many noisy genes optimize information flow
Nicholas Lawson, William Bialek
It often is emphasized that gene expression is noisy. A seemingly contradictory view is that control mechanisms have been optimized to squeeze as much information as possible out o…
Neural subspaces, minimax entropy, and mean-field theory for networks of neurons
Luca Di Carlo, Francesca Mignacco, Christopher W. Lynn +1
Recent advances in experimental techniques enable the simultaneous recording of activity from thousands of neurons in the brain, presenting both an opportunity and a challenge: to…
Extended mean-field theories for networks of real neurons
Luca Di Carlo, Francesca Mignacco, Christopher W. Lynn +1
If the behavior of a system with many degrees of freedom can be captured by a small number of collective variables, then plausibly there is an underlying mean-field theory. We show…
Exact minimax entropy models of large-scale neuronal activity
Christopher W. Lynn, Qiwei Yu, Rich Pang +2
In the brain, fine-scale correlations combine to produce macroscopic patterns of activity. However, as experiments record from larger and larger populations, we approach a fundamen…
Exactly solvable statistical physics models for large neuronal populations
Christopher W. Lynn, Qiwei Yu, Rich Pang +2
Maximum entropy methods provide a principled path connecting measurements of neural activity directly to statistical physics models, and this approach has been successful for popul…