# Difference between revisions of "Sean G. Carver's Publications"

From Sean_Carver

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== Baseball == | == Baseball == | ||

− | * <big> Carver S. ''Number of Samples Needed for Model Selection with Confidence''. '''Proceeding of the Joint Statistical Meeting,''' 2018. We show how to compute the number of half-innings that need to be played by model baseball teams to determine with confidence, from the play, which team is at bat. [[Media:CarverJSM2017.pdf|For | + | * <big> Carver S. ''Number of Samples Needed for Model Selection with Confidence''. '''Proceeding of the Joint Statistical Meeting,''' 2018. We show how to compute the number of half-innings that need to be played by model baseball teams to determine with confidence, from the play, which team is at bat. [[Media:CarverJSM2017.pdf|For reprint, click here.]] |

== Cooperative control with noisy clocks == | == Cooperative control with noisy clocks == |

## Latest revision as of 20:50, 24 July 2018

## Contents

- 1 Baseball
- 2 Cooperative control with noisy clocks
- 3 Limitations of closed-loop system identification with noninvasive perturbations
- 4 Modeling and identifying sensorimotor mechanisms at the cellular and network levels
- 5 Modeling and identifying the control system for human running
- 6 Modeling and identifying the human balance/postural control system
- 7 Other Publications

## Baseball

- Carver S.
*Number of Samples Needed for Model Selection with Confidence*.**Proceeding of the Joint Statistical Meeting,**2018. We show how to compute the number of half-innings that need to be played by model baseball teams to determine with confidence, from the play, which team is at bat. For reprint, click here.

## Cooperative control with noisy clocks

- Carver S, Fortune E, Cowan N.
*State estimation and cooperative control with uncertain time*.**Proceedings of the American Control Conference**, June 2013. We model two lumberjacks cooperatively sawing through a log, using a two-person saw. We show how they can stay in sync given that they must rely on noisy internal clocks for timekeeping. For preprint, click here.

## Limitations of closed-loop system identification with noninvasive perturbations

- Carver S, Kiemel T, Cowan N, Jeka J.
*Optimal motor control may mask sensory dynamics*.**Biological Cybernetics**, 101(1):35-42, 2009. We show that under assumptions commonly made about posture control and other sensorimotor stabilization behaviors, sensory dynamics are hidden from closed-loop system identification by pole-zero cancellations. Only by measuring, perturbing, or breaking the loop, between the sensors and the controller can the dynamics of the sensors be unmasked.

## Modeling and identifying sensorimotor mechanisms at the cellular and network levels

- Carver S, Roth E, Cowan N, Fortune S.
*Synaptic plasticity can produce and enhance direction selectivity.***PloS Computational Biology**, vol. 4, no. 2, 2008. We pose a parsimonious model of a directionally selective neuron, together with upstream processing, and test the model against neurophysiological data from the directionally-selective electrosensory midbrain of weakly electric fish.

## Modeling and identifying the control system for human running

- Carver S, Cowan N, Guckenheimer J.
*Lateral stability of the spring-mass hopper suggests a two step control strategy for running.***Chaos**, June 2009. We pose an experimentally falsifiable hypothesis concerning the control of human running: small perturbations from a desired course are corrected exactly in the fewest number of steps theoretically possible. We show that, for a widely used and well supported model of running, all small perturbations that preserve the sagittal plane require only one step to be corrected, whereas generic small lateral perturbations require two steps.

## Modeling and identifying the human balance/postural control system

- Carver S, Kiemel T, van der Kooij H, Jeka JJ.
*Comparing internal models of the dynamics of the visual environment*.**Biological Cybernetics**, 92, 147-163, 2005. We pose a new model of postural adaptation to visual scene motion and favorably compare it to three alternative models based on previously published frequency response data. We later called our new model the*Agnostic Model*because, unlike with its alternatives, it makes no assumptions about the dynamics of the stimulus.

- Carver S, Kiemel T, Jeka J.
*Modeling the dynamics of sensory reweighting*.**Biological Cybernetics**, 95, 123-134, 2006. Based on the Agnostic Model, we predict that adaptation to a changing stimulus will be temporally asymmetric, in the sense that the system will respond quickly to a change in one direction, but slowly to a return to baseline. Our predictions were born out by experiments in the Jeka Lab.

- Jeka J, Carver S, Allison L, Kiemel T.
*Sensory reweighting in healthy and fall prone adults: Time scales, transient and asymptotic dynamics*. In**From Basic Motor Control to Functional Recovery IV**, Gantchev N, ed., Marin Drinov Academic Publishing House, 2005.

- Jeka J, Allison L, Saffer M, Zhang Y, Carver S, Kiemel T.
*Sensory reweighting with translational visual stimuli in young and elderly adults: the role of state dependent noise*.**Experimental Brain Research**, 2006.

## Other Publications

- Easton B, Meiss J, Carver S.
*Exit times and transport for sympletic twist maps*.**Chaos**, vol. 3, no. 2, 1993.