45 citations · 45 across the 4 of their papers we have counts for
5 papers
Mutual Information in High-Dimensional Neural Coding
Zimo Li, Yuchang Tian, Matthew P. Leighton +1
Estimating mutual information in large neural populations is limited by the exponential growth of possible neural response patterns. Here we apply a Monte Carlo framework to make t…
Irreversible behavior drives neural flows in the hippocampus
Kaiyue Shi, Christopher W. Lynn
In the brain, neural activity undergoes directed flows between states, thus breaking time-reversal symmetry. At the same time, animals also exhibit irreversible flows between behav…
Tractable Model for Tunable Non-Markovian Dynamics
Matthew P. Leighton, Christopher W. Lynn
Non-Markovian dynamics are ubiquitous across physics, biology, and engineering. Yet our understanding of non-Markovian processes significantly lags that of simpler Markovian proces…
Decomposing Non-Markovian History Dependence
Matthew P. Leighton, Christopher W. Lynn
Non-Markovian stochastic processes are ubiquitous in biology. Nevertheless, we lack a general framework for quantifying historical dependencies. In this Letter, we propose an infor…
Is stochastic thermodynamics the key to understanding the energy costs of computation?
David Wolpert, Jan Korbel, Christopher Lynn +16
The relationship between the thermodynamic and computational characteristics of dynamical physical systems has been a major theoretical interest since at least the 19th century, an…