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Inference of Causal Information Flow in Collective Animal Behavior

Warren M. Lord, Jie Sun, Nicholas T. Ouellette, Erik M. Bollt
2016 IEEE Transactions on Molecular, Biological and Multi-Scale Communications  
The collection of channels inferred by oCSE describes a network of information flow within the swarm.  ...  A different approach is to define coordinated motions in terms of an information theoretic channel of direct causal information flow.  ...  Further we have noted that contrary to standard models of swarming and group behaviors, these information flow networks allow that the influential animals for each individual animal may not necessarily  ... 
doi:10.1109/tmbmc.2016.2632099 dblp:journals/tmbmc/Lord0OB16 fatcat:5xqjrzifonaapmzxu7p5hzdt3q

Introduction to Focus Issue: Causation inference and information flow in dynamical systems: Theory and applications

Erik M. Bollt, Jie Sun, Jakob Runge
2018 Chaos  
In nonlinear dynamics and complex systems science, causation inference and information flow are closely related concepts, whereby "information" or knowledge of certain states can be thought of as coupling  ...  While causation inference and information flow are by now classical topics, incorporating methods from statistics and time series analysis, information theory, dynamical systems, and statistical mechanics  ...  Bollt (this focus issue, Chaos 28, 075308 (2018)), "Anatomy of leadership in collective behaviour," studies causality and information flow in the form of leadership in collective behaviour of mobile animal  ... 
doi:10.1063/1.5046848 pmid:30070534 fatcat:knznx3nigjfgxewhywkqn6u5by

Anatomy of leadership in collective behaviour

Joshua Garland, Andrew M. Berdahl, Jie Sun, Erik M. Bollt
2018 Chaos  
Due to the broad interpretation of leadership, many different measures and mathematical tools are used to describe and infer "leadership", e.g., position, causality, influence, information flow.  ...  The ability to infer this differential influence, or leadership, is critical to understanding group functioning in these collective animal systems.  ...  of collective animal behavior is understanding how groups of organisms make decisions as a whole, 4 for example, about where 5 or when 6, 7 to go.  ... 
doi:10.1063/1.5024395 pmid:30070518 fatcat:pzorsolbuzca3ner24lmqwd2ue

Inferring causal relationships in zebrafish-robot interactions through transfer entropy: a small lure to catch a big fish

Maurizio Porfiri
2018 Animal Behavior and Cognition  
Inferring causal relationships in zebrafish-robot interactions through transfer entropy: A small lure to catch a big fish. Animal Behavior and Cognition, 5(4), 341-367.  ...  Abstract -In the field of animal behavior, effective methods to apprehend causal relationships that underlie the interactions between animals are in dire need.  ...  However, other sources of support should be acknowledged for complementing the main line of inquiry on causality in zebrafish-robot interactions, including National Science Foundation under grant nos.  ... 
doi:10.26451/abc.05.04.03.2018 fatcat:o4xzgerkebhmjgohkhee6okaja

Editorial Comment on the Special Issue of "Information in Dynamical Systems and Complex Systems"

Erik Bollt, Jie Sun
2014 Entropy  
The contributions include theoretical characterization and understanding of the different types of information flow and causality in general stochastic processes, inference and identification of coupling  ...  This special issue collects contributions from the participants of the "Information in Dynamical Systems and Complex Systems" workshop, which cover a wide range of important problems and new approaches  ...  Conflicts of Interest The authors declare no conflict of interest. Entropy 2014, 16  ... 
doi:10.3390/e16095068 fatcat:sfxqeheru5ei7h2l3zb5wcrn3q

The Roles of Mental Animations and External Animations in Understanding Mechanical Systems

Mary Hegarty, Sarah Kriz, Christina Cate
2003 Cognition and Instruction  
Verbal instruction provides information that is not easily communicated in graphics and directs students' attention to the relevant information in static and animated diagrams.  ...  Comprehension of diagrams was enhanced by asking students questions that required them to predict the behavior of the machine from static diagrams and by providing them with a verbal description of the  ...  ACKNOWLEDGMENTS The authors wish to thank Pam Freitas, Narisa Hoevetanaku, Naomi Shimozawa, and Tijana Vujovic for assistance in data collection and scoring, and Rich Mayer and Hari Naryanan for fruitful  ... 
doi:10.1207/s1532690xci2104_1 fatcat:zavzmfiwwbe7bjxejkzgjb7kde

On designing comprehensible interactive hypermedia manuals

N.HARI NARAYANAN, MARY HEGARTY
1998 International Journal of Human-Computer Studies  
Since the development of this model draws heavily upon research in both cognitive science and computational modeling, a second contribution is that it contains a detailed review of literature in these  ...  Third, it illustrates how cognitive and computational modeling are being used to inform the design of hypermedia information presentation systems about machines.  ...  The authors acknowledge financial support for this research from the Office of Naval Research through contract N00014-96-1-0525 to Mary Hegarty and contract N00014-96-11187 to Hari Narayanan.  ... 
doi:10.1006/ijhc.1997.0169 fatcat:szg6jab37rajhefuiuybudh2mq

Computational Inference of Neural Information Flow Networks

V. Anne Smith, Jing Yu, Tom V. Smulders, Alexander J. Hartemink, Erich D. Jarvis
2006 PLoS Computational Biology  
of reciprocal feedback in auditory processing and greater information flow to higher-order auditory areas when birds hear natural as opposed to synthetic sounds.  ...  is also successful at inferring nonlinear neural information flow networks from electrophysiology data collected with microelectrode arrays.  ...  Baccalá and Sameshima of the University of Sã o Paulo, Brazil, for assistance and instruction in the use of their PDC algorithm, Shih-Chieh Lin for additional assistance in the use of PDC, and Joshua Robinson  ... 
doi:10.1371/journal.pcbi.0020161 pmid:17121460 pmcid:PMC1664702 fatcat:pudwll7sx5dk3jr5khrblgehxu

Computational Inference of Neural Information Flow Networks

V Anne Smith, Jing Yu, Tom Smulders, Alexander J. Hartemink, Erich David Jarvis
2005 PLoS Computational Biology  
of reciprocal feedback in auditory processing and greater information flow to higher-order auditory areas when birds hear natural as opposed to synthetic sounds.  ...  is also successful at inferring nonlinear neural information flow networks from electrophysiology data collected with microelectrode arrays.  ...  Baccalá and Sameshima of the University of Sã o Paulo, Brazil, for assistance and instruction in the use of their PDC algorithm, Shih-Chieh Lin for additional assistance in the use of PDC, and Joshua Robinson  ... 
doi:10.1371/journal.pcbi.0020161.eor fatcat:2ydvpcybizdxdctdtuji6efuv4

A Bayesian Belief Network to Infer Incentive Mechanisms to Reduce Antibiotic Use in Livestock Production

Lan Ge, Marcel A.P.M. van Asseldonk, Natalia I. Valeeva, Wil H.G.J. Hennen, Ron H.M. Bergevoet
2014 NJAS - Wageningen Journal of Life Sciences  
Information on these two factors is therefore crucial in designing incentive mechanisms.  ...  Animal health status and management quality are considered the two most important factors that influence farmers' decision-making concerning antibiotic use.  ...  The BBN allows information to flow in the opposite direction of the causality (Jensen, 1996) .  ... 
doi:10.1016/j.njas.2014.01.001 fatcat:zcoceygn5fbajapbd74vcremge

Improving human understanding and design of complex multi-level systems with animation and parametric relationship supports

Paul Egan, Christian Schunn, Jonathan Cagan, Philip LeDuc
2015 Design Science  
All users were then presented contrasting animations of systems with opposing emergent behaviors, resulting in many more participants demonstrating an understanding of inter-level causal behaviors.  ...  with agent-based animations that emphasized inter-level causality learning.  ...  Early iterations of this work were accepted to the 2014 Cognitive Science Society Conference and 2015 ASME Computers and Information Engineering Conference.  ... 
doi:10.1017/dsj.2015.3 fatcat:ntqxkbtvhbbqllte3qif7m5lzi

Transfer entropy dependent on distance among agents in quantifying leader-follower relationships [article]

Udoy S. Basak, Sulimon Sattari, Md. Motaleb Hossain, Kazuki Horikawa, Tamiki Komatsuzaki
2021 arXiv   pre-print
Understanding of how organisms are regulated to synchronized behavior is one of the challenging issues in the field of collective motion.  ...  It is hypothesized that one or a few agents in a group regulate(s) the dynamics of the whole collective, known as leader(s). The identification of the leader (influential) agent(s) is very crucial.  ...  There, causal inference is an essential aspect of determining leadership and its role in collective systems.  ... 
arXiv:2105.05662v1 fatcat:iz2wykpn4zes3jtshfqlxtsonq

Predicting perturbation effects from resting state activity using functional causal flow [article]

Amin Nejatbakhsh, Francesco Fumarola, Saleh Esteki, Taro Toyoizumi, Roozbeh Kiani, Luca Mazzucato
2020 bioRxiv   pre-print
Here, we introduce a novel statistical method to infer a network's "functional causal flow" (FCF) from ensemble neural recordings.  ...  Critically, FCF is robust to noise and can be inferred from the activity of even a small fraction of neurons in the circuit.  ...  LM was supported by National Institute of Neurological Disorders and Stroke grant R01-NS118461 (BRAIN Initiative) and by National Institute of Deafness and Communication Disorders grant K25-DC013557.  ... 
doi:10.1101/2020.11.23.394916 fatcat:3k4ihqyfuzdlffhww62brkxc6m

Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data

Willem Coetzer, Deshendran Moodley, Aurona Gerber, Julia A. Jones
2016 PLoS ONE  
Observations of individual organisms (data) can be combined with expert ecological knowledge of species, especially causal knowledge, to model and extract from flower-visiting data useful information about  ...  We describe and evaluate a method to elicit and represent such expert causal knowledge of behavioral ecology, and discuss the potential for wider application of this method to the design of knowledge-based  ...  processes e.g. the flow of information (DNA) or energy, or flow of a substance such as a nutrient or pollutant [1, 17] , or an interaction between species.  ... 
doi:10.1371/journal.pone.0166559 pmid:27851814 pmcid:PMC5113002 fatcat:xfmqrwhjavhrtnvr4bjzfsiwwm

Network Structure Inference, A Survey: Motivations, Methods, and Applications [article]

Ivan Brugere and Brian Gallagher and Tanya Y. Berger-Wolf
2018 arXiv   pre-print
Do two animals who physically co-locate have a social bond? Who infected whom in a disease outbreak in a population?  ...  strategies for measuring the inferred network's capability of answering questions on the system of interest.  ...  ACKNOWLEDGEMENTS This work was performed under the auspices of the U.S.  ... 
arXiv:1610.00782v4 fatcat:neu7tyamijhixbjv6rasksyasu
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