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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Data-driven modeling of collective behavior in sch
 ooling fish - Guy Theraulaz (CNRS (Centre national
  de la recherche scientifique))
DTSTART;TZID=Europe/London:20230809T090000
DTEND;TZID=Europe/London:20230809T100000
UID:TALK201454AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/201454
DESCRIPTION:Swarms of insects\, schools of fish and flocks of 
 birds display an impressive variety of collective 
 movements that emerge from local interactions amon
 g group members. To understand the mechanisms that
  govern these phenomena\, we need to decipher the 
 interactions between individuals\, to identify the
  information exchanged during these interactions a
 nd\, finally\, to characterize and quantify the ef
 fects of these interactions on the behavior of ind
 ividuals. We have recently introduced a general me
 thod to extract from individuals&rsquo\; trajector
 ies the social interaction functions between two i
 ndividuals that are required to achieve coordinate
 d motion. Using large sets of tracking data\, we u
 sed this method to reconstruct and model the inter
 actions between individuals in rummy-nose tetra (H
 . rhodostomus). This species performs a burst-and-
 coast type of swimming characterized by sequences 
 of sudden increase in speed followed by a mostly p
 assive gliding period. The effect of social intera
 ctions on a fish heading can then be precisely mea
 sured. In particular\, one can quantify the streng
 th of attraction\, repulsion\, and alignment behav
 ior resulting from these interactions as a functio
 n of the distance between fish and their relative 
 positions and orientations. Our results show that 
 both attraction and alignment behaviors control th
 e reaction of fish to a neighbor. We used these re
 sults to build a model of spontaneous burst-and-co
 ast swimming and social interactions of fish\, wit
 h all parameters being estimated or directly measu
 red from experiments. Then we have extended our ap
 proach to analyze collective behavior in larger gr
 oups of fish and showed that individuals typically
  interact with their two most influential neighbor
 s. Overall\, our results suggest that fish have to
  acquire only a minimal amount of information abou
 t their environment to coordinate their movements 
 when swimming in groups.
LOCATION:Seminar Room 1\, Newton Institute
CONTACT:
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