---
res:
  bibo_abstract:
  - 'Recent developments in automated tracking allow uninterrupted, high-resolution
    recording of animal trajectories, sometimes coupled with the identification of
    stereotyped changes of body pose or other behaviors of interest. Analysis and
    interpretation of such data represents a challenge: the timing of animal behaviors
    may be stochastic and modulated by kinematic variables, by the interaction with
    the environment or with the conspecifics within the animal group, and dependent
    on internal cognitive or behavioral state of the individual. Existing models for
    collective motion typically fail to incorporate the discrete, stochastic, and
    internal-state-dependent aspects of behavior, while models focusing on individual
    animal behavior typically ignore the spatial aspects of the problem. Here we propose
    a probabilistic modeling framework to address this gap. Each animal can switch
    stochastically between different behavioral states, with each state resulting
    in a possibly different law of motion through space. Switching rates for behavioral
    transitions can depend in a very general way, which we seek to identify from data,
    on the effects of the environment as well as the interaction between the animals.
    We represent the switching dynamics as a Generalized Linear Model and show that:
    (i) forward simulation of multiple interacting animals is possible using a variant
    of the Gillespie’s Stochastic Simulation Algorithm; (ii) formulated properly,
    the maximum likelihood inference of switching rate functions is tractably solvable
    by gradient descent; (iii) model selection can be used to identify factors that
    modulate behavioral state switching and to appropriately adjust model complexity
    to data. To illustrate our framework, we apply it to two synthetic models of animal
    motion and to real zebrafish tracking data. @eng'
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Katarína
      foaf_name: Bod’Ová, Katarína
      foaf_surname: Bod’Ová
  - foaf_Person:
      foaf_givenName: Gabriel
      foaf_name: Mitchell, Gabriel
      foaf_surname: Mitchell
      foaf_workInfoHomepage: http://www.librecat.org/personId=315BCD80-F248-11E8-B48F-1D18A9856A87
  - foaf_Person:
      foaf_givenName: Roy
      foaf_name: Harpaz, Roy
      foaf_surname: Harpaz
  - foaf_Person:
      foaf_givenName: Elad
      foaf_name: Schneidman, Elad
      foaf_surname: Schneidman
  - foaf_Person:
      foaf_givenName: Gasper
      foaf_name: Tkacik, Gasper
      foaf_surname: Tkacik
      foaf_workInfoHomepage: http://www.librecat.org/personId=3D494DCA-F248-11E8-B48F-1D18A9856A87
    orcid: 0000-0002-6699-1455
  bibo_doi: 10.1371/journal.pone.0193049
  bibo_issue: '3'
  bibo_volume: 13
  dct_date: 2018^xs_gYear
  dct_identifier:
  - UT:000426896800032
  dct_language: eng
  dct_publisher: Public Library of Science@
  dct_title: Probabilistic models of individual and collective animal behavior@
...