Sean G. Carver's Research Interests
Broadly, my interests involve system identification (SysID) applied to biological systems, especially:
- developing methods of SyID,
- applying methods of SysID to understand biological processes, and
- advancing methods for teaching SysID (pedagogy).
By system identification, I mean using statistics, derived from experimental data, to constrain dynamical models of a system. Typically, SysID involves parameter estimation, model selection, and model validation.
System Identification of Cooperative Control
When people cooperate to perform a task that requires that they stay in sync (e.g. salsa dancing, or chamber music), how do they maintain synchrony given that their biological clocks are noisy? I am currently involved in designing experiments (in collaboration with the LIMBS lab, Johns Hopkins) to collect and analyze data from humans performing simple sensorimotor tasks where they must cooperate to stay in sync. We plan to analyze the data with SysID. Please see a preprint of a relevant paper (click here).
Control Theory Where Agent(s) Rely on Noisy Clocks
No clock tells time perfectly [1], but in the past, when timekeeping was not good enough for a particular engineering application, the engineers invariably solved the problem by building better clocks. Indeed, engineered clocks achieve remarkable precision. But in solving the problem in this way, engineers avoided needing to create better control algorithms that could rely on noisy clocks. Invariably, they managed to get away with assuming perfection in timekeeping. Biological evolution has different constraints. Apparently, nature has made better neural control algorithms as well as making better clocks. To understand the sensorimotor control of behaviors such as dance, we need to extend control theory to handle with the case that internal clocks are noisy. To date, surprisingly little has been done in this regard, but the models I pose for the SysID of cooperative synchrony do involve noisy internal clocks.
