Paper Info
Title
Detailed temporal structure of communication networks in groups of songbirds.
Abstract
Animals in groups often exchange calls, in patterns whose temporal structure may be influenced by contextual factors such as physical location and the social network structure of the group. We introduce a model-based analysis for temporal patterns of animal call timing, originally developed for networks of firing neurons. This has advantages over cross-correlation analysis in that it can correctly handle common-cause confounds and provides a generative model of call patterns with explicit parameters for the influences between individuals. It also has advantages over standard Markovian analysis in that it incorporates detailed temporal interactions which affect timing as well as sequencing of calls. Further, a fitted model can be used to generate novel synthetic call sequences. We apply the method to calls recorded from groups of domesticated zebra finch (Taeniopygia guttata) individuals. We find that the communication network in these groups has stable structure that persists from one day to the next, and that 'kernels' reflecting the temporal range of influence have a characteristic structure for a calling individual's effect on itself, its partner and on others in the group. We further find characteristic patterns of influences by call type as well as by individual.
Year
DOI
Venue
2016
10.1098/rsif.2016.0296
JOURNAL OF THE ROYAL SOCIETY INTERFACE
Keywords
Field
DocType
animal communication,Poisson process,point process,linear-nonlinear Poisson,communication network,social network analysis
Telecommunications network,Social network,Markov process,Computer science,Social network analysis,Point process,Artificial intelligence,Animal communication,Taeniopygia,Machine learning,Generative model
Journal
Volume
Issue
ISSN
13
119
1742-5689
Citations 
PageRank 
References 
0
0.34
4
Authors
3
Name
Order
Citations
PageRank
Dan Stowell120921.84
Lisa F. Gill210.71
David Clayton300.34