A Plausible Mechanism for Drosophila
Larva Intermittent Behavior
Panagiotis Sakagiannis
1(B) , Miguel Aguilera
2 , and Martin Paul Nawrot
1
1 Computational Systems Neuroscience, Institute of Zoology, University of Cologne,
Cologne, Germany
p.sakagiannis@uni-koeln.de
2 IAS-Research Center for Life, Mind, and Society,
University of the Basque Country, Donostia, Spain
http://computational-systems-neuroscience.de/
Abstract. The behavior of many living organisms is not continuous.
Rather, activity emerges in bouts that are separated by epochs of rest, a
phenomenon known as intermittent behavior. Although intermittency is
ubiquitous across phyla, empirical studies are scarce and the underlying
neural mechanisms remain unknown. Here we present the first empirical evidence of intermittency during Drosophila larva free exploration.
We report power-law distributed rest-bout and log-normal distributed
activity-bout durations. We show that a stochastic network model can
transition between power-law and non-power-law distributed states and
we suggest a plausible neural mechanism for the alternating rest and
activity in the larva. Finally, we discuss possible implementations in
behavioral simulations extending spatial Levy-walk or coupled-oscillator
models with temporal intermittency.
Keywords: Larva crawling · Levy-walks · Neuronal avalanches
1 Introduction
The search for statistical regularities in animal movement is a predominant
focus of motion ecology. Random walks form a broad range of models that
assume discrete steps of displacement obeying defined statistical rules and acute
reorientations. A Levy walk is a random walk where the displacement lengths
and the respective displacement durations are drawn from a heavy-tailed, most
often a power-law distribution. When considered in a 2D space reorientation
angles are drawn from a uniform distribution. This initial basic Levy walk has
Supported by the Research Training Group ‘Neural Circuit Analysis’ (DFG-RTG 1960,
grant no. 233886668) and the Research Unit ‘Structure, Plasticity and Behavioral Function of the Drosophila mushroom body’ (DFG-FOR 2705, grant no. 403329959), funded
by the German Research Foundation. M.A. was funded by the UPV/EHU post-doctoral
training program ESPDOC17/17 and H2020 Marie Skk lodowska-Curie grant 892715,
and supported in part from the Basque Government (IT1228-19).
c
Springer Nature Switzerland AG 2020
V. Vouloutsi et al. (Eds.): Living Machines 2020, LNAI 12413, pp. 288–299, 2020.
https://doi.org/10.1007/978-3-030-64313-3_28
Larva Intermittent Behavior
Panagiotis Sakagiannis
1(B) , Miguel Aguilera
2 , and Martin Paul Nawrot
1
1 Computational Systems Neuroscience, Institute of Zoology, University of Cologne,
Cologne, Germany
p.sakagiannis@uni-koeln.de
2 IAS-Research Center for Life, Mind, and Society,
University of the Basque Country, Donostia, Spain
http://computational-systems-neuroscience.de/
Abstract. The behavior of many living organisms is not continuous.
Rather, activity emerges in bouts that are separated by epochs of rest, a
phenomenon known as intermittent behavior. Although intermittency is
ubiquitous across phyla, empirical studies are scarce and the underlying
neural mechanisms remain unknown. Here we present the first empirical evidence of intermittency during Drosophila larva free exploration.
We report power-law distributed rest-bout and log-normal distributed
activity-bout durations. We show that a stochastic network model can
transition between power-law and non-power-law distributed states and
we suggest a plausible neural mechanism for the alternating rest and
activity in the larva. Finally, we discuss possible implementations in
behavioral simulations extending spatial Levy-walk or coupled-oscillator
models with temporal intermittency.
Keywords: Larva crawling · Levy-walks · Neuronal avalanches
1 Introduction
The search for statistical regularities in animal movement is a predominant
focus of motion ecology. Random walks form a broad range of models that
assume discrete steps of displacement obeying defined statistical rules and acute
reorientations. A Levy walk is a random walk where the displacement lengths
and the respective displacement durations are drawn from a heavy-tailed, most
often a power-law distribution. When considered in a 2D space reorientation
angles are drawn from a uniform distribution. This initial basic Levy walk has
Supported by the Research Training Group ‘Neural Circuit Analysis’ (DFG-RTG 1960,
grant no. 233886668) and the Research Unit ‘Structure, Plasticity and Behavioral Function of the Drosophila mushroom body’ (DFG-FOR 2705, grant no. 403329959), funded
by the German Research Foundation. M.A. was funded by the UPV/EHU post-doctoral
training program ESPDOC17/17 and H2020 Marie Skk lodowska-Curie grant 892715,
and supported in part from the Basque Government (IT1228-19).
c
Springer Nature Switzerland AG 2020
V. Vouloutsi et al. (Eds.): Living Machines 2020, LNAI 12413, pp. 288–299, 2020.
https://doi.org/10.1007/978-3-030-64313-3_28