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SUMMARY:Generalised Langevin dynamics for movement data analysis - Rainer 
 Klages (Queen Mary University of London)
DTSTART:20230719T104500Z
DTEND:20230719T111500Z
UID:TALK201727@talks.cam.ac.uk
DESCRIPTION:I briefly review the concept of Langevin dynamics\, which orig
 inates from modeling the Brownian motion of a passive tracer particle in a
  fluid. However\, for describing active biological motion this equation ha
 s to be suitably modified. I then show how such suggested modifications ar
 e obtained in stochastic models constructed from experimental data. First\
 , I discuss migration of neutrophil cells along a chemical gradient [1]. E
 xtracting moments of the positions\, position probability distributions an
 d velocity autocorrelation functions from experimental data suggests a sim
 ple stochastic model in the form of an overdamped generalised Langevin equ
 ation that well reproduces the data. Notably\, cells move asymmetrically s
 uperdiffusively in both directions. Biological activity is represented by 
 power law correlation decay. Second\, experimental data of bumblebee fligh
 ts is analysed for constructing a Langevin-type generalised correlated ran
 dom walk model\, again well reproducing the data [2]. Biological activity 
 shows up both in the friction coefficient of the speed and in non-trivial 
 correlation decay.\n[1] P.Dieterich et al.\, PLoS Comput Biol 18\, e101008
 9 (2022)[2] F.Lenz\, A.V.Chechkin\, RK\, PLoS ONE 8\, e59036 (2013)
LOCATION:Seminar Room 1\, Newton Institute
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