1 citations · 2 across the 5 of their papers we have counts for
5 papers
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…
Optimization and variability can coexist
Marianne Bauer, William Bialek, Chase Goddard +6
Many biological systems perform close to their physical limits, but promoting this optimality to a general principle seems to require implausibly fine tuning of parameters. Using e…
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…
Statistical mechanics for networks of real neurons
Leenoy Meshulam, William Bialek
Perceptions and actions, thoughts and memories result from coordinated activity in hundreds or even thousands of neurons in the brain. It is an old dream of the physics community t…