activity
20152023
most citedAdaptive, locally-linear models of complex dynamics

83 citations · 132 across the 6 of their papers we have counts for

collaborators

6 papers

q-bio.NC2023★ 1 cited

Statistics of C. elegans turning behavior reveals optimality under biasing constraints

W. Mathijs Rozemuller, Steffen Werner, Antonio Carlos Costa +3

Animal locomotion is often subject to constraints arising from anatomical/physiological asymmetries. We use the nematode C.~elegans as a minimal model system to ask whether such co…

physics.bio-ph2023★ 23 cited

A Markovian dynamics for C. elegans behavior across scales

Antonio C. Costa, Tosif Ahamed, David Jordan +1

How do we capture the breadth of behavior in animal movement, from rapid body twitches to aging? Using high-resolution videos of the nematode worm , we show that a sing…

physics.bio-ph2021★ 22 cited

Maximally predictive states: from partial observations to long timescales

Antonio Carlos Costa, Tosif Ahamed, David Jordan +1

Isolating slower dynamics from fast fluctuations has proven remarkably powerful, but how do we proceed from partial observations of dynamical systems for which we lack underlying e…

q-bio.NC2019★ 2 cited

Capturing the Continuous Complexity of Behavior in C. elegans

Tosif Ahamed, Antonio Carlos Costa, Greg J. Stephens

Animal behavior is often quantified through subjective, incomplete variables that may mask essential dynamics. Here, we develop a behavioral state space in which the full instantan…

q-bio.QM2018★ 83 cited

Adaptive, locally-linear models of complex dynamics

Antonio Carlos Costa, Tosif Ahamed, Greg J. Stephens

The dynamics of complex systems generally include high-dimensional, non-stationary and non-linear behavior, all of which pose fundamental challenges to quantitative understanding.…

q-bio.NC2015★ 1 cited

Modeling the ballistic-to-diffusive transition in nematode motility reveals variation in exploratory behavior across species

Stephen J. Helms, W. Mathijs Rozemuller, Antonio Carlos Costa +3

A quantitative understanding of organism-level behavior requires predictive models that can capture the richness of behavioral phenotypes, yet are simple enough to connect with und…