Stephen M. Fiore University of Central Florida Fiore, S. M. (2014). From Neurons to Networks: Examining Interactions between Brains and Bodies over Time and Space. Educational Testing Service Workshop on Innovative Assessment of Collaboration (November 2-4), Washington, DC. - - - This work by Stephen M. Fiore, PhD is licensed under a Creative Commons Attribution-NonCommercial - NoDerivs 3.0 Unported License 2013. Not for commercial use. Approved for redistribution. Attribution required.
Transcript
Stephen M. Fiore University of Central Florida
Fiore, S. M. (2014). From Neurons to Networks: Examining Interactions between Brains and Bodies over Time and Space. Educational Testing Service Workshop on Innovative Assessment of Collaboration (November 2-4), Washington, DC. -
- -This work by Stephen M. Fiore, PhD is licensed under a Creative Commons Attribution-NonCommercial- NoDerivs 3.0 Unported License 2013. Not for commercial use. Approved for redistribution. Attribution required.
From Neurons to Networks Setting the Stage
Part I. Micro-level Research Interactions at the Neural and Physiological Level
Part II. Meso-level Research Interactions at the Group Level
Part III. Macro-level Research Interactions within and Across Networks
Part IV. Interdisciplinary Challenges Addressing Gaps
Study of teams is becoming increasingly sophisticated Many new concepts and methods Helping us study world of interaction within and across multiple levels of
analysis Pressing Challenge for Understanding Collaboration Developing research that crosses levels and disciplines in the study of
interaction
Development of interdisciplinary research teams capable of creating and synthesizing methods and theory
---From Neurons to Networks (Fiore, 2013) - Now discuss representative
studies of interaction in varied collaboration contexts and at varied levels Fiore, S. M. (2013). President’s Essay: From Neurons to Networks: New Technologies for Understanding
Interaction at Multiple Levels. INGRoup Newsletter, January, 3(1), 1, 6-7.
Setting the Stage
Purpose Examine synchrony in EEG activation during complex coordination (guitar duets) Expected PFC involvement given need to monitor teammate (theory of mind)
Methods
Examined coordination within guitar duets by recording electroencephalogram (EEG) from each player in 12 duets
Musical roles of leader and follower were assigned -- - Assessed within -brain and between -brain coherence in time -frequency signals
Findings Synchronous oscillations vary dependent upon leader-follower assignments - - -Within-brain “phase locking” and between -brain “phase coherence” heightened in
PFC when high demands placed on musical coordination Suggested that this facilitated interpersonal action coordination
Sänger, J., Müller, V., & Lindenberger, U. (2012). Intra-- and interbrain synchronization and network properties when playing guitar in duets. Frontiers in Human Neuroscience, 6, 312
Interactions at the Neural and Physiological Level
Purpose Effect of neuropeptide, oxytocin, on trust and cooperation in groups Examine how it alters behaviors across groups and influences competition and
protective behaviors Methods 3 – person groups played Prisoner’s Dilemma game Participants made decisions with financial consequences for themselves, in -group
members, and a competing out-group member -
- Administered oxytocin or placebo (aerosol)
Findings Compared to placebo, oxytocin enhances motivation to defend the in-group
when in-group vulnerability is high rather than low -
- Even when personal vulnerability not threatened, oxytocin influenced a defense-
motivated competitive desire to protect vulnerable group members
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De Dreu, C.K.W., Shalvi, S., Greer, L.L., Van Kleef, G.A., & Handgraaf, M.J.J. (2012). Oxytocin Motivates Non -Cooperation in Intergroup Conflict to Protect Vulnerable In -Group Members. PLoS ONE 7(11), e46751.
Purpose Examine movement patterns related to leadership in orchestras. Aimed to
investigate: ▪ (1) the driving force of the conductor on the players ▪ (2) the sensorimotor communication among musicians
Methods Used infrared optical systems and passive markers for kinematic data capture during
group interaction between violinists’ and conductors Passive marker placed on end of players’ bows and tip of the conductor’s baton Analysis of causal relations between conductor wand and violinists’ elbow movement Uncover leadership dynamics related to the aesthetic quality of music
Findings Conductors modulated average inter-musician interaction strength - Musical experts determined that quality of execution related to increase of conductor-
to-muscians of influence and decrease of musician-to-musician coordination - --
D'Ausilio A., Badino, L., Li , Y., Tokay, S., Craighero, L., et al. (2012). Leadership in Orchestra Emerges from the Causal Relationships of Movement Kinematics. PLoS ONE 7(5), e35757
Interactions at the Group Level
Purpose Examine relationship between individual and team creativity “in the wild” Study how team member movements and face-t0-face interaction were related
to productivity Methods Studied creativity in teams using electronic “Experience Sampling Methods” (social
interaction via network data, body movements, audio) and expert creativity assessment
Creativity scale assessed work they did on assigned projects and outcomes evaluated by expert judge
Findings Days coded as more creative showed higher daily movement along with more
face-to-face interaction of team members when compared to non -creative days -
Tripathi, P. & Burleson, W. (2012). Predicting creativity in the wild: experience sample and sociometric modeling of teams. Proceedings of CSCW '12 Computer Supported Cooperative Work, February 11–15, 2012, Seattle, WA, USA
Purpose Examine patterns of effective team interaction in highly coordinated
sport Methods Studied nearly 300K passes between professional soccer players Used metrics such as network intensity (passing rate) and network
centrality Findings Links between the level of interaction in teams and performance Higher passing rate leads to increased team performance Centralized interaction patterns lead to decreased team performance.
Grund, T.U. (2012). Network structure and team performance: The case of English Premier League soccer
teams. Social Networks, 34(4), 682–690.
Interactions within and Across Networks
Purpose Use MMORPG to study performance, teamwork, and success Examine player potential to survive, accomplish goals, and win along with team’s
probability of success and individual’s centrality in the network Methods SNA on data collected over 3.5 months and 7,406 players Considered in- game messages, strength and resources, alliances and cooperation,
trades, and diplomacy status -
Findings In initial weeks, teaming behaviors (alliances) by survivors but not by winners In middle of game play winners predicted by SNA statistics (closeness centrality) Social network information measured via in-game messages equally predict player
potential as well as direct game variables (resource amount, trade, and population development)
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Wigand, R. T., Agarwal, N., Osesina, I., Hering, W., Korsgaard, A., Picot, A. & Drescher, M. (2012). Social Network Indices as Performance Predictors in a Virtual Organization. Proceedings of the 4th International Conference on Computational Aspects of Social Networks (CASoN 2012). November 21 -23, 2012. Sao Carlos, Brazil
Studying Collaboration Across Levels Variety of disciplines studying interaction Numerous contexts for being studied Innovative methods for studying interactions
Need to leverage complementarity Develop new theories that transcend disciplines integrate methods to
provide fuller understanding of collaboration Next discuss contextual factors Need to be considered to bring about more sophisticated
understanding of collaboration – From Neurons to Networks (Fiore, 2013; 2014)
Fiore, S. M. (2013). President’s Essay: From Neurons to Networks: New Technologies for Understanding Interaction at Multiple Levels. INGRoup Newsletter, January, 3(1), 1, 6-7.
Fiore, S. M. (2014). From Neurons to Networks: Understanding Interaction at Multiple Levels. The National Academies Keck Futures Initiative, Collective Behavior: From Cells to Societies, Irvine, CA.
-Consideration of interdependencies – who relies on whom for task completion and how does that alter collaboration (Fiore, 2008; Saavedra et al., 1993).
Pooled interdependence, each person performs his/her own task, and the team result is the sum of each person's output.
Sequential interdependence occurs when one person's output is necessary for another person's input (i.e., B cannot act without output from A).
Reciprocal interdependence, one person's output becomes another person's input and vice versa
Intensive interdependence is the highest form of coordinated activity - "group members jointly diagnose, problem solve, and collaborate to complete a task”
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Fiore, S. M. (2008). Interdisciplinarity as Teamwork: How the Science of Teams can inform Team Science. Small Group Research, 39(3), 251-277.
Saavedra, R., Early, P. & Van Dyne, L. (1993). Complex Interdependence in Task-Performing Groups. Journal of Applied Psychology, 78(1), 61-72.
Low Virtuality Teams experience higher degree of co-location and/or synchronous
interaction with information rich technology (e.g., videoconferencing) High Virtuality Teams experience lower degree of co-location and more
asynchronous interaction information poor technology (e.g., email)
Fiore, S. M., Salas, E., Cuevas, H. M. & Bowers, C. A. (2003). Distributed coordination space: Toward a theory of distributed team process and performance. Theoretical Issues in Ergonomic Science, 4, 3-4, 340-363.
Mesmer-Magnus, J. R., DeChurch, L. A., Jimenez-Rodriguez, M., Wildman, J., & Shuffler, M. (2011). A meta-analytic investigation of virtuality and information sharing in teams. Organizational Behavior and Human Decision Processes, 115(2), 214-225.
Consideration of virtuality – the form and location of the collaboration (Fiore et al., 2003).
Consideration of scale – collaborations range in size from two members to large teams with complex and varied goals at different levels (Fiore et al., 2012).
Teams Context “two or more individuals who must interact and adapt to achieve specified,
shared, and valued objectives” (p. 4, Salas, Dickinson, Converse, & Tannenbaum, 1992).
Multiteam System Context “two or more teams that interface directly and interdependently in
response to environmental contingencies toward the accomplishment of collective goals” (Marks, Mathieu, & Zaccaro, 2001, p. 290).
Fiore, S. M., Rosen, M. A., Pavlas, D., & Jentsch, F. (2012). Conceptualizing Cognition at Multiple Levels in Support of Training Team Cognitive Readiness. Proceedings of 56th Annual Meeting of the Human Factors and Ergonomics Society (pp. 448-452). Santa Monica, CA: Human Factors and Ergonomics Society.
Marks, M. A., Zaccaro, S. J., & Mathieu, J. E. (2000). Performance implications of leader briefings and team-interaction training for team adaptation to novel environments. Journal of Applied Psychology, 85, 971-986.
Salas, E., Dickinson, T., Converse, S., & Tannenbaum, S. (1992). Towards an understanding of team performance and training. In R. W. Swezey & E. Salas (Eds.), Teams: Their training and performance (pp. 3-29). Norwood, NJ: Ablex.
Interdependence
Virt
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High Low
Low
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Fiore, S. M. (2014). From Neurons to Networks: Understanding Interaction at Multiple Levels. The National Academies Keck Futures Initiative, Collective Behavior: From Cells to Societies, Irvine, CA.
Consideration of these contextual factors enables study of interactions across multiple levels (Fiore, 2014; Hackman, 2003).
Provides means through which to apply methods of measuring processes applicable within or across levels.
May improve theory testing and measurement development. May improve diagnosis of causal factors of team process and performance (Hackman, 2003)
Moving up or down levels of analysis can add explanatory power
▪ Shifting focus to a higher or a lower level can lead to new insights into causal mechanisms in shaping team process and performance
▪ “explanatory power of bracketing lies in crossing levels of analysis, not blurring them” (p. 919).
To improve understanding and measurement of collaboration, need to develop theory that captures, not only micro- and macro-level issues, but also the inter -relations among these levels – from Neurons to Networks (Fiore, 2014).
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Fiore, S. M. (2014). From Neurons to Networks: Understanding Interaction at Multiple Levels. The National Academies Keck Futures Initiative, Collective Behavior: From Cells to Societies, Irvine, CA.
Hackman, J. R. (2003). Learning more by crossing levels: Evidence from airplanes, hospitals, and orchestras. Journal of Organizational Behavior, 24(8), 905-922.
Stephen M. Fiore, Ph.D. University of Central Florida Cognitive Sciences, Department of Philosophy and Institute for Simulation & Training [email protected]
