Difference between revisions of "Project 2014"

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Motor control often depends on accurate timing of motor commands, but animals succeed with amazing motor feats despite the obvious fact that biological timekeeping falls well short of perfection.  While all known clocks keep time imperfectly, engineered clocks are good enough that their imperfections can be usually be ignored.  For this reason, perhaps it is not surprising that until very recently, nearly all formulations of control theory assumed that control agents had access to perfect clocks.  With this classical control theory, it remained impossible to understand how animals, with substantial imperfections in internal timing, perform as they do.  Over the last few years, my collaborators (at Johns Hopkins and elsewhere) and I have been working to extend control theory to apply when clocks remain substantially inaccurate.  I contributed to this effort by publishing a paper (coauthored by Noah Cowan and Eric Fortune) considering cooperative control of a two-person saw.  We showed that lumberjacks could stay synchronized, despite substantially imperfect timing, if one (a follower) updated their clock by observing the other's (leader's) performance, knowing (or successfully learning) the leader's desired trajectory of the saw.     The demonstration required that I assume a statistical model for the internal clocks.  In the absence of data to constrain this choice, I chose an inverse Gaussian process, but preliminary work with data (during the summer of 2013) showed this simplest formulation to be a bad choice.  During the summer of 2013, I collaborated with two student researchers at Johns Hopkins (Alexander Spinos, undergraduate, and Robert Nickl, Ph.D. candidate).  This summer (2014), I am looking to extend this work using biological time series to search for a better (parsimonious) model of the internal clock.
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== Sean Carver's Summer 2014 Research Plans ==
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Motor control often depends on accurate timing of motor commands, but animals succeed with amazing motor feats despite the obvious fact that biological timekeeping falls well short of perfection.  While all known clocks keep time imperfectly, engineered clocks are good enough that their imperfections can usually be ignored.  For this reason, perhaps it is not surprising that until very recently, nearly all formulations of control theory assumed that control agents had access to perfect clocks.  With this classical control theory, it remained impossible to understand how animals, with substantial imperfections in internal timing, perform as well as they do.  Over the last few years, my collaborators (at Johns Hopkins and elsewhere) and I have been working to extend control theory to apply when clocks remain substantially inaccurate.  I contributed to this effort by publishing a paper [Carver, Fortune and Cowan, 2013] considering cooperative control of a two-person saw.  We showed that lumberjacks could stay synchronized, despite substantially imperfect timing.  In our model, a follower updated its clock by observing the saw and knowing (or successfully learning) the saw's nominal trajectory. Our demonstration required that we assume a statistical model for the internal clocks.  In the absence of data to constrain this choice, we chose an inverse Gaussian process.  More recently, preliminary work with data showed this simplest formulation to be a bad choice for parsimoniously describing reality [accomplished in collaboration with two Johns Hopkins students: Alexander Spinos, undergraduate, and Robert Nickl, Ph.D. candidate].  This summer (2014), I am looking to extend these results using biological time series to search for a better model of the internal clock.

Latest revision as of 21:39, 30 December 2013


Sean Carver's Summer 2014 Research Plans

Motor control often depends on accurate timing of motor commands, but animals succeed with amazing motor feats despite the obvious fact that biological timekeeping falls well short of perfection. While all known clocks keep time imperfectly, engineered clocks are good enough that their imperfections can usually be ignored. For this reason, perhaps it is not surprising that until very recently, nearly all formulations of control theory assumed that control agents had access to perfect clocks. With this classical control theory, it remained impossible to understand how animals, with substantial imperfections in internal timing, perform as well as they do. Over the last few years, my collaborators (at Johns Hopkins and elsewhere) and I have been working to extend control theory to apply when clocks remain substantially inaccurate. I contributed to this effort by publishing a paper [Carver, Fortune and Cowan, 2013] considering cooperative control of a two-person saw. We showed that lumberjacks could stay synchronized, despite substantially imperfect timing. In our model, a follower updated its clock by observing the saw and knowing (or successfully learning) the saw's nominal trajectory. Our demonstration required that we assume a statistical model for the internal clocks. In the absence of data to constrain this choice, we chose an inverse Gaussian process. More recently, preliminary work with data showed this simplest formulation to be a bad choice for parsimoniously describing reality [accomplished in collaboration with two Johns Hopkins students: Alexander Spinos, undergraduate, and Robert Nickl, Ph.D. candidate]. This summer (2014), I am looking to extend these results using biological time series to search for a better model of the internal clock.