Measuring Real-Time Team Cognition During Team Training

Gorman, Jamie C.; Grimm, David; Stevens, Ronald H.; Galloway, Trysha; Willemsen‐Dunlap, Ann; Halpin, Donald J.

doi:10.1177/0018720819852791

Cited by 53 publications

(75 citation statements)

References 77 publications

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“…Also warranted is a deeper evaluation WMS performance under varying noisy conditions, along with data from social interactions with/without clear transitions and perhaps even, social interactions with controllable virtual partners ( Fairhurst et al , 2013 ; Dumas et al , 2014 ). With such data, wavelet ridge detection ( Jha and Senroy, 2018 ), real-time change detection ( Hoover et al , 2012 ) and/or non-linear prediction error algorithms ( Kantz and Schreiber, 2003 ; Gorman et al , 2019 ) could be utilized for marking critical transitions in the observed coordination values. Applying these in such a multiscale fashion would also be novel and could potentially allow for detecting critical and meaningful changes in interpersonal synchrony.…”

Section: Potential Approaches For Improving and Generalizing Wmsmentioning

confidence: 99%

“…Importantly, during social interactions, as in any dynamical system, patterns of coordination form and dissipate at different spatiotemporal scales ( Schmidt et al , 1998 ; Dale et al , 2013 ; Dumas et al , 2014 ; Gorman et al , 2019 ; Zhang et al , 2019 ). In fact, recent theorizing emphasizes that moving in and out of synch with others is critical to adaptive human behavior ( Mayo and Gordon, 2020 ) and that coordination in biological systems is fundamentally a multiscale phenomenon ( Zhang et al , 2019 , 2020 ).…”

Section: Introductionmentioning

confidence: 99%

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Windowed multiscale synchrony: modeling time-varying and scale-localized interpersonal coordination dynamics

Likens

Wiltshire

2020

Social Cognitive and Affective Neuroscience

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Social interactions are pervasive in human life with varying forms of interpersonal coordination emerging and spanning different modalities (e.g., behaviors, speech/language, and neurophysiology). However, during social interactions, as in any dynamical system, patterns of coordination form and dissipate at different scales. Historically, researchers have used aggregate measures to capture coordination over time. While those measures (e.g., mean relative phase, cross-correlation, coherence) have provided a wealth of information about coordination in social settings, some evidence suggests that multiscale coordination may change over the time course of a typical empirical observation. To address this gap, we demonstrate an underutilized method, windowed multiscale synchrony, that moves beyond quantifying aggregate measures of coordination by focusing on how the relative strength of coordination changes over time and the scales that comprise social interaction. This method involves using a wavelet transform to decompose time series into component frequencies (i.e., scales), preserving temporal information and then quantifying phase synchronization at each of these scales. We apply this method to both simulated and empirical interpersonal physiological and neuromechanical data. We anticipate that demonstrating this method will stimulate new insights on the mechanisms and functions of synchrony in interpersonal contexts using neurophysiological and behavioral measures.

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Section: Potential Approaches For Improving and Generalizing Wmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Windowed multiscale synchrony: modeling time-varying and scale-localized interpersonal coordination dynamics

Likens

Wiltshire

2020

Social Cognitive and Affective Neuroscience

View full text Add to dashboard Cite

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“…They are computed from activity in different frequency bands (i.e., delta, theta, alpha, beta, and gamma; Berka et al, 2007;Prinzel et al, 2000Prinzel et al, , 2003. This existing research has developed EEG-based measures at both the individual and team levels (Gorman et al, 2019) to provide insight into aspects of cognitive processing and will be introduced below. However, these measures are not typically considered or used in the general cognitive neuroscience field.…”

Section: The Current State Of the Interdisciplinary Field: Model-derived Eeg Measuresmentioning

confidence: 99%

“…Managerial cognition at an individual level is often conceptualized as a set of cognitive processes involving deliberate and/or unconscious computational activities that facilitate decision-making concerning a problem or task (Porac, 2015;Walsh, 1995). On the other hand, team cognition is conceptualized as a collective phenomenon emerging from the interaction between individual cognitive processes, communication, and behavioural coordination (Dunbar et al 2020;Gorman et al 2019;.…”

Section: Introductionmentioning

confidence: 99%

Combining neurophysiological and psychological indicators to understand individual and team cognition and decision-making

Sinha¹,

Kyriaki²,

Cross³

et al. 2020

Preprint

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This chapter provides an introduction to neurophysiological methods from the field ofcognitive neuroscience, and how they may be applied to address research questions in the field ofmanagerial and organisational cognition. The chapter focuses on electroencephalography (EEG)as an accessible and useful tool to expand the theoretical horizons for research on organisationalcognitive neuroscience. We briefly review the cognitive neuroscience methods that have beenpreviously applied to investigate individual and team decision-making and cognition. We thendescribe contemporary EEG measures that reflect individual cognition and compare them tocomplementary measures in the field of psychology and management. We also discuss how theseneurobiological measures of cognition relate to and may predict both individual cognitiveperformance and team cognitive performance (decision-making). This chapter aims to assistscholars in the field of managerial and organisational cognition in understanding thecomplementarity between psychological and neurophysiological methods, and how they may becombined to develop new hypotheses in the intersection of these research fields.

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“…Furthermore, interacting individuals may not be in close physical proximity, required for touch-based nonverbal behaviors, yet may still interrupt. The method of defining an interruption which we have described can be used in time-stamped transcripts that do not retain information from speech overlaps, as in the Gorman et al (2019) data, or in data that record overlaps but were not diarized according to the Feldstein and Welkowitz (1987) standard, as is the case for the data used in this study. Thus interruptions represent status conceptually, have demonstrated predictive validity, and may be identified in a variety of recording environments.…”

Section: Status and Behaviormentioning

confidence: 99%

Leader Identification through Networks of Conversational Interruptions

MacLaren¹,

Fj²,

Sd³

et al. 2020

Preprint

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Leaders are often identified in empirical studies by either their position in an organizationally defined hierarchy or by survey responses, yet such methods conflate behavioral antecedents and outcomes with behaviors themselves. Furthermore, without an external standard for comparison, it cannot be known to what extent differences in leader assignment or emergence between demographic or other categories are due to behavioral differences or biases in the assessment, selection, training, or rating processes. In this study, we propose the ``interruption network'' as a model of small group structure that is (a) grounded in social status theory, (b) definable in both lab and field groups, (c) minimally impacted by rater bias, and (d) based on assessed behaviors rather than antecedents or outcomes. We show that analysis of interruption networks suggests that the often-reported male bias in leadership attributions is found in the ratings but not in the behavior of the observed individuals: males and females may engage in leadership behaviors equally as often, but males are attributed leadership significantly more. Use of the interruption network to represent small group social status therefore extends well-established research on non-verbal behaviors to an explicitly group-oriented context, supporting theory-based unobtrusive assessment and new ways to address important questions in applied psychology.

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Measuring Real-Time Team Cognition During Team Training

Cited by 53 publications

References 77 publications

Windowed multiscale synchrony: modeling time-varying and scale-localized interpersonal coordination dynamics

Windowed multiscale synchrony: modeling time-varying and scale-localized interpersonal coordination dynamics

Combining neurophysiological and psychological indicators to understand individual and team cognition and decision-making

Leader Identification through Networks of Conversational Interruptions

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