4 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…