1
|
Daniels BC, Wang Y, Page RE, Amdam GV. Identifying a developmental transition in honey bees using gene expression data. PLoS Comput Biol 2023; 19:e1010704. [PMID: 37733808 PMCID: PMC10547183 DOI: 10.1371/journal.pcbi.1010704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 10/03/2023] [Accepted: 09/05/2023] [Indexed: 09/23/2023] Open
Abstract
In many organisms, interactions among genes lead to multiple functional states, and changes to interactions can lead to transitions into new states. These transitions can be related to bifurcations (or critical points) in dynamical systems theory. Characterizing these collective transitions is a major challenge for systems biology. Here, we develop a statistical method for identifying bistability near a continuous transition directly from high-dimensional gene expression data. We apply the method to data from honey bees, where a known developmental transition occurs between bees performing tasks in the nest and leaving the nest to forage. Our method, which makes use of the expected shape of the distribution of gene expression levels near a transition, successfully identifies the emergence of bistability and links it to genes that are known to be involved in the behavioral transition. This proof of concept demonstrates that going beyond correlative analysis to infer the shape of gene expression distributions might be used more generally to identify collective transitions from gene expression data.
Collapse
Affiliation(s)
- Bryan C. Daniels
- School of Complex Adaptive Systems, Arizona State University, Tempe, Arizona, United States of America
| | - Ying Wang
- Banner Health Corporation, Phoenix, Arizona, United States of America
| | - Robert E. Page
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
- Department of Entomology and Nematology, University of California Davis, Davis, California, United States of America
| | - Gro V. Amdam
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
- Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, Aas, Norway
| |
Collapse
|
2
|
Shine JM. Neuromodulatory control of complex adaptive dynamics in the brain. Interface Focus 2023; 13:20220079. [PMID: 37065268 PMCID: PMC10102735 DOI: 10.1098/rsfs.2022.0079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 01/23/2023] [Indexed: 04/18/2023] Open
Abstract
How is the massive dimensionality and complexity of the microscopic constituents of the nervous system brought under sufficiently tight control so as to coordinate adaptive behaviour? A powerful means for striking this balance is to poise neurons close to the critical point of a phase transition, at which a small change in neuronal excitability can manifest a nonlinear augmentation in neuronal activity. How the brain could mediate this critical transition is a key open question in neuroscience. Here, I propose that the different arms of the ascending arousal system provide the brain with a diverse set of heterogeneous control parameters that can be used to modulate the excitability and receptivity of target neurons-in other words, to act as control parameters for mediating critical neuronal order. Through a series of worked examples, I demonstrate how the neuromodulatory arousal system can interact with the inherent topological complexity of neuronal subsystems in the brain to mediate complex adaptive behaviour.
Collapse
Affiliation(s)
- James M. Shine
- Brain and Mind Center, The University of Sydney, Sydney, Australia
| |
Collapse
|
3
|
Galesic M, Barkoczi D, Berdahl AM, Biro D, Carbone G, Giannoccaro I, Goldstone RL, Gonzalez C, Kandler A, Kao AB, Kendal R, Kline M, Lee E, Massari GF, Mesoudi A, Olsson H, Pescetelli N, Sloman SJ, Smaldino PE, Stein DL. Beyond collective intelligence: Collective adaptation. J R Soc Interface 2023; 20:20220736. [PMID: 36946092 PMCID: PMC10031425 DOI: 10.1098/rsif.2022.0736] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Accepted: 02/27/2023] [Indexed: 03/23/2023] Open
Abstract
We develop a conceptual framework for studying collective adaptation in complex socio-cognitive systems, driven by dynamic interactions of social integration strategies, social environments and problem structures. Going beyond searching for 'intelligent' collectives, we integrate research from different disciplines and outline modelling approaches that can be used to begin answering questions such as why collectives sometimes fail to reach seemingly obvious solutions, how they change their strategies and network structures in response to different problems and how we can anticipate and perhaps change future harmful societal trajectories. We discuss the importance of considering path dependence, lack of optimization and collective myopia to understand the sometimes counterintuitive outcomes of collective adaptation. We call for a transdisciplinary, quantitative and societally useful social science that can help us to understand our rapidly changing and ever more complex societies, avoid collective disasters and reach the full potential of our ability to organize in adaptive collectives.
Collapse
Affiliation(s)
- Mirta Galesic
- Santa Fe Institute, Santa Fe, NM 87501, USA
- Complexity Science Hub Vienna, 1080 Vienna, Austria
- Vermont Complex Systems Center, University of Vermont, Burlington, VM 05405, USA
| | | | - Andrew M. Berdahl
- School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195, USA
| | - Dora Biro
- Department of Zoology, University of Oxford, Oxford OX1 3PS, UK
| | - Giuseppe Carbone
- Department of Mechanics, Mathematics and Management, Politecnico di Bari, Bari 70125, Italy
| | - Ilaria Giannoccaro
- Department of Mechanics, Mathematics and Management, Politecnico di Bari, Bari 70125, Italy
| | - Robert L. Goldstone
- Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA
| | - Cleotilde Gonzalez
- Department of Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Anne Kandler
- Department of Mathematics, Max-Planck-Institute for Evolutionary Anthropology, Leipzig 04103, Germany
| | - Albert B. Kao
- Santa Fe Institute, Santa Fe, NM 87501, USA
- Biology Department, University of Massachusetts Boston, Boston, MA 02125, USA
| | - Rachel Kendal
- Centre for Coevolution of Biology and Culture, Durham University, Anthropology Department, Durham, DH1 3LE, UK
| | - Michelle Kline
- Centre for Culture and Evolution, Division of Psychology, Brunel University London, Uxbridge, UB8 3PH, UK
| | - Eun Lee
- Department of Scientific Computing, Pukyong National University, 45 Yongso-ro, Nam-gu, Busan, 48513, Republic of Korea
| | | | - Alex Mesoudi
- Department of Ecology and Conservation, University of Exeter, Penryn TR10 9FE, UK
| | | | | | - Sabina J. Sloman
- Department of Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Computer Science, University of Manchester, Manchester, M13 9PL, UK
| | - Paul E. Smaldino
- Santa Fe Institute, Santa Fe, NM 87501, USA
- Department of Cognitive and Information Sciences, University of California, Merced, CA 95343, USA
| | - Daniel L. Stein
- Santa Fe Institute, Santa Fe, NM 87501, USA
- Department of Physics and Courant Institute of Mathematical Sciences, New York University, New York, NY 10012, USA
| |
Collapse
|
4
|
Warnky DM, Diebolt JH, Ho BV, Brake AD, French EL, Villwock MR, Sykes KJ, Villwock JA. Investigation of a Novel Activity-Based Checks (ABC) Functional Pain Scale in the Post-Operative Urologic Surgery Patient. Kans J Med 2023; 16:35-40. [PMID: 36845261 PMCID: PMC9957595 DOI: 10.17161/kjm.vol16.18742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Accepted: 01/09/2023] [Indexed: 02/24/2023] Open
Abstract
Introduction The authors investigated a novel functional pain scale, the Activity-Based Checks (ABCs) of Pain, following open urologic surgery. The primary objectives were to establish the strength of the correlation between the ABCs and the numeric rating scale (NRS) and determine the impact of functional pain on the patient's opioid requirements. We hypothesized that ABC score would correlate strongly with NRS and that the ABC score during hospitalization would be more closely correlated with the number of opioids prescribed and used. Methods This prospective study included patients at a tertiary academic hospital undergoing nephrectomy and cystectomy. The NRS and ABCs were collected pre-operatively, during the inpatient stay, and at the one-week follow-up. Milligrams of morphine equivalents (MMEs) prescribed at discharge and the MME reportedly taken during the first post-operative week were recorded. Spearman's Rho was used to assess the correlation between scale variables. Results Fifty-seven patients were enrolled. The ABCs correlated strongly with the NRS at baseline and post-operative appointments (r = 0.716, p < 0.001 and 0.643, p < 0.001). Neither the NRS nor the composite ABCs score was predictive of outpatient MME requirements; the ABCs function, "Walking outside the room" significantly correlated to MMEs taken after discharge (r = 0.471, p = 0.011). The greatest predictor of MMEs taken was the number of MMEs prescribed (0.493, p = 0.001). Conclusions This study highlighted the importance of post-operative pain assessment that takes functional pain into consideration to evaluate pain, inform management decisions, and reduce opiate reliance. It also emphasized the strong relationship between opioids prescribed and opioids consumed.
Collapse
Affiliation(s)
- David M. Warnky
- Department of Otolaryngology, University of Kansas School of Medicine, Kansas City, KS
| | - Jennifer H. Diebolt
- Department of Otolaryngology, University of Kansas School of Medicine, Kansas City, KS
| | - Bao V. Ho
- Department of Otolaryngology, University of Kansas School of Medicine, Kansas City, KS
| | - Aaron D. Brake
- Department of Otolaryngology, University of Kansas School of Medicine, Kansas City, KS
| | - Emilie L. French
- Department of Otolaryngology, University of Kansas School of Medicine, Kansas City, KS
| | - Mark R. Villwock
- Department of Otolaryngology, University of Kansas Medical Center, Kansas City, KS
| | - Kevin J. Sykes
- Department of Otolaryngology, University of Kansas Medical Center, Kansas City, KS
| | - Jennifer A. Villwock
- Department of Otolaryngology, University of Kansas Medical Center, Kansas City, KS
| |
Collapse
|
5
|
Stevens R, Galloway TL. Exploring how healthcare teams balance the neurodynamics of autonomous and collaborative behaviors: a proof of concept. Front Hum Neurosci 2022; 16:932468. [PMID: 35966993 PMCID: PMC9365959 DOI: 10.3389/fnhum.2022.932468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 07/04/2022] [Indexed: 11/13/2022] Open
Abstract
Team members co-regulate their activities and move together at the collective level of behavior while coordinating their actions toward shared goals. In parallel with team processes, team members need to resolve uncertainties arising from the changing task and environment. In this exploratory study we have measured the differential neurodynamics of seven two-person healthcare teams across time and brain regions during autonomous (taskwork) and collaborative (teamwork) segments of simulation training. The questions posed were: (1) whether these abstract and mostly integrated constructs could be separated neurodynamically; and, (2) what could be learned about taskwork and teamwork by trying to do so? The taskwork and teamwork frameworks used were Neurodynamic Information (NI), an electroencephalography (EEG) derived measure shown to be a neurodynamic proxy for the pauses and hesitations associated with individual uncertainty, and inter-brain EEG coherence (IBC) which is a required component of social interactions. No interdependency was observed between NI and IBC, and second-by-second dynamic comparisons suggested mutual exclusivity. These studies show that proxies for fundamental properties of teamwork and taskwork can be separated neurodynamically during team performances of ecologically valid tasks. The persistent expression of NI and IBC were not simultaneous suggesting that it may be difficult for team members to maintain inter-brain coherence while simultaneously reducing their individual uncertainties. Lastly, these separate dynamics occur over time frames of 15–30 s providing time for real-time detection and mitigation of individual and collaborative complications during training or live patient encounters.
Collapse
Affiliation(s)
- Ronald Stevens
- UCLA School of Medicine, Brain Research Institute, Los Angeles, CA, United States
- The Learning Chameleon, Inc., Culver City, CA, United States
- *Correspondence: Ronald Stevens
| | | |
Collapse
|
6
|
Discovering sparse control strategies in neural activity. PLoS Comput Biol 2022; 18:e1010072. [PMID: 35622828 PMCID: PMC9140285 DOI: 10.1371/journal.pcbi.1010072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 04/01/2022] [Indexed: 11/19/2022] Open
Abstract
Biological circuits such as neural or gene regulation networks use internal states to map sensory input to an adaptive repertoire of behavior. Characterizing this mapping is a major challenge for systems biology. Though experiments that probe internal states are developing rapidly, organismal complexity presents a fundamental obstacle given the many possible ways internal states could map to behavior. Using C. elegans as an example, we propose a protocol for systematic perturbation of neural states that limits experimental complexity and could eventually help characterize collective aspects of the neural-behavioral map. We consider experimentally motivated small perturbations—ones that are most likely to preserve natural dynamics and are closer to internal control mechanisms—to neural states and their impact on collective neural activity. Then, we connect such perturbations to the local information geometry of collective statistics, which can be fully characterized using pairwise perturbations. Applying the protocol to a minimal model of C. elegans neural activity, we find that collective neural statistics are most sensitive to a few principal perturbative modes. Dominant eigenvalues decay initially as a power law, unveiling a hierarchy that arises from variation in individual neural activity and pairwise interactions. Highest-ranking modes tend to be dominated by a few, “pivotal” neurons that account for most of the system’s sensitivity, suggesting a sparse mechanism of collective control.
Collapse
|
7
|
Ebitz RB, Hayden BY. The population doctrine in cognitive neuroscience. Neuron 2021; 109:3055-3068. [PMID: 34416170 PMCID: PMC8725976 DOI: 10.1016/j.neuron.2021.07.011] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 07/02/2021] [Accepted: 07/13/2021] [Indexed: 01/08/2023]
Abstract
A major shift is happening within neurophysiology: a population doctrine is drawing level with the single-neuron doctrine that has long dominated the field. Population-level ideas have so far had their greatest impact in motor neuroscience, but they hold great promise for resolving open questions in cognition as well. Here, we codify the population doctrine and survey recent work that leverages this view to specifically probe cognition. Our discussion is organized around five core concepts that provide a foundation for population-level thinking: (1) state spaces, (2) manifolds, (3) coding dimensions, (4) subspaces, and (5) dynamics. The work we review illustrates the progress and promise that population-level thinking holds for cognitive neuroscience-for delivering new insight into attention, working memory, decision-making, executive function, learning, and reward processing.
Collapse
Affiliation(s)
- R Becket Ebitz
- Department of Neurosciences, Faculté de médecine, Université de Montréal, Montréal, QC, Canada.
| | - Benjamin Y Hayden
- Department of Neuroscience, Center for Magnetic Resonance Research, and Center for Neuroengineering, University of Minnesota, Minneapolis, MN, USA
| |
Collapse
|
8
|
Stevens RH, Galloway TL. Parsing Neurodynamic Information Streams to Estimate the Frequency, Magnitude and Duration of Team Uncertainty. Front Syst Neurosci 2021; 15:606823. [PMID: 33597850 PMCID: PMC7882625 DOI: 10.3389/fnsys.2021.606823] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 01/04/2021] [Indexed: 11/30/2022] Open
Abstract
Neurodynamic organizations are information-based abstractions, expressed in bits, of the structure of long duration EEG amplitude levels. Neurodynamic information (NI, the variable of neurodynamic organization) is thought to continually accumulate as EEG amplitudes cycle through periods of persistent activation and deactivation in response to the activities and uncertainties of teamwork. Here we show that (1) Neurodynamic information levels were a better predictor of uncertainty and novice and expert behaviors than were the EEG power levels from which NI was derived. (2) Spatial and temporal parsing of team NI from experienced submarine navigation and healthcare teams showed that it was composed of discrete peaks with durations up to 20–60 s, and identified the involvement of activated delta waves when precise motor control was needed. (3) The relationship between NI and EEG power was complex varying by brain regions, EEG frequencies, and global vs. local brain interactions. The presence of an organizational system of information that parallels the amplitude of EEG rhythms is important as it provides a greatly reduced data dimension while retaining the essential system features, i.e., linkages to higher scale behaviors that span temporal and spatial scales of teamwork. In this way the combinatorial explosion of EEG rhythmic variables at micro levels become compressed into an intermediate system of information and organization which links to macro-scale team and team member behaviors. These studies provide an avenue for understanding how complex organizations arise from the dynamics of underlying micro-scale variables. The study also has practical implications for how micro-scale variables might be better represented, both conceptually and in terms of parsimony, for training machines to recognize human behaviors that span scales of teams.
Collapse
Affiliation(s)
- Ronald H Stevens
- University of California Los Angeles (UCLA) School of Medicine, Brain Research Institute, Culver City, CA, United States.,The Learning Chameleon, Inc., Culver City, CA, United States
| | | |
Collapse
|
9
|
Stramaglia S, Scagliarini T, Daniels BC, Marinazzo D. Quantifying Dynamical High-Order Interdependencies From the O-Information: An Application to Neural Spiking Dynamics. Front Physiol 2021; 11:595736. [PMID: 33519503 PMCID: PMC7841410 DOI: 10.3389/fphys.2020.595736] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 12/16/2020] [Indexed: 11/23/2022] Open
Abstract
We address the problem of efficiently and informatively quantifying how multiplets of variables carry information about the future of the dynamical system they belong to. In particular we want to identify groups of variables carrying redundant or synergistic information, and track how the size and the composition of these multiplets changes as the collective behavior of the system evolves. In order to afford a parsimonious expansion of shared information, and at the same time control for lagged interactions and common effect, we develop a dynamical, conditioned version of the O-information, a framework recently proposed to quantify high-order interdependencies via multivariate extension of the mutual information. The dynamic O-information, here introduced, allows to separate multiplets of variables which influence synergistically the future of the system from redundant multiplets. We apply this framework to a dataset of spiking neurons from a monkey performing a perceptual discrimination task. The method identifies synergistic multiplets that include neurons previously categorized as containing little relevant information individually.
Collapse
Affiliation(s)
- Sebastiano Stramaglia
- Dipartimento Interateneo di Fisica, Universitá degli Studi Aldo Moro, Bari and INFN, Bari, Italy
- Center of Innovative Technologies for Signal Detection and Processing (TIRES), Universitá degli Studi Aldo Moro, Bari, Italy
| | - Tomas Scagliarini
- Dipartimento Interateneo di Fisica, Universitá degli Studi Aldo Moro, Bari and INFN, Bari, Italy
| | - Bryan C. Daniels
- Arizona State University and Santa Fe Institute Center for Biosocial Complex Systems, Arizona State University, Tempe, AZ, United States
| | | |
Collapse
|
10
|
Winklmayr C, Kao AB, Bak-Coleman JB, Romanczuk P. The wisdom of stalemates: consensus and clustering as filtering mechanisms for improving collective accuracy. Proc Biol Sci 2020; 287:20201802. [PMID: 33143576 PMCID: PMC7735266 DOI: 10.1098/rspb.2020.1802] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Groups of organisms, from bacteria to fish schools to human societies, depend on their ability to make accurate decisions in an uncertain world. Most models of collective decision-making assume that groups reach a consensus during a decision-making bout, often through simple majority rule. In many natural and sociological systems, however, groups may fail to reach consensus, resulting in stalemates. Here, we build on opinion dynamics and collective wisdom models to examine how stalemates may affect the wisdom of crowds. For simple environments, where individuals have access to independent sources of information, we find that stalemates improve collective accuracy by selectively filtering out incorrect decisions (an effect we call stalemate filtering). In complex environments, where individuals have access to both shared and independent information, this effect is even more pronounced, restoring the wisdom of crowds in regions of parameter space where large groups perform poorly when making decisions using majority rule. We identify network properties that tune the system between consensus and accuracy, providing mechanisms by which animals, or evolution, could dynamically adjust the collective decision-making process in response to the reward structure of the possible outcomes. Overall, these results highlight the adaptive potential of stalemate filtering for improving the decision-making abilities of group-living animals.
Collapse
Affiliation(s)
- Claudia Winklmayr
- Bernstein Center for Computational Neuroscience, Berlin, Germany.,Max Planck Institut für Mathematik in den Naturwissenschaften, Leipzig, Germany
| | | | - Joseph B Bak-Coleman
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.,Center for an Informed public, University of Washington, Seattle, WA, USA.,eScience Institute, University of Washington, Seattle, WA, USA
| | - Pawel Romanczuk
- Bernstein Center for Computational Neuroscience, Berlin, Germany.,Institute for Theoretical Biology, Department of Biology, Humboldt Universität zu Berlin, Germany
| |
Collapse
|
11
|
Ramos-Fernandez G, Smith Aguilar SE, Krakauer DC, Flack JC. Collective Computation in Animal Fission-Fusion Dynamics. Front Robot AI 2020; 7:90. [PMID: 33501257 PMCID: PMC7805913 DOI: 10.3389/frobt.2020.00090] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 06/05/2020] [Indexed: 11/15/2022] Open
Abstract
Recent work suggests that collective computation of social structure can minimize uncertainty about the social and physical environment, facilitating adaptation. We explore these ideas by studying how fission-fusion social structure arises in spider monkey (Ateles geoffroyi) groups, exploring whether monkeys use social knowledge to collectively compute subgroup size distributions adaptive for foraging in variable environments. We assess whether individual decisions to stay in or leave subgroups are conditioned on strategies based on the presence or absence of others. We search for this evidence in a time series of subgroup membership. We find that individuals have multiple strategies, suggesting that the social knowledge of different individuals is important. These stay-leave strategies provide microscopic inputs to a stochastic model of collective computation encoded in a family of circuits. Each circuit represents an hypothesis for how collectives combine strategies to make decisions, and how these produce various subgroup size distributions. By running these circuits forward in simulation we generate new subgroup size distributions and measure how well they match food abundance in the environment using transfer entropies. We find that spider monkeys decide to stay or go using information from multiple individuals and that they can collectively compute a distribution of subgroup size that makes efficient use of ephemeral sources of nutrition. We are able to artificially tune circuits with subgroup size distributions that are a better fit to the environment than the observed. This suggests that a combination of measurement error, constraint, and adaptive lag are diminishing the power of collective computation in this system. These results are relevant for a more general understanding of the emergence of ordered states in multi-scale social systems with adaptive properties-both natural and engineered.
Collapse
Affiliation(s)
- Gabriel Ramos-Fernandez
- Departamento de Modelación Matemática de Sistemas Sociales, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Ciudad de México, Mexico
- Unidad Profesional Interdisciplinaria en Ingeniería y Tecnologías Avanzadas, Instituto Politécnico Nacional, Ciudad de México, Mexico
| | | | | | | |
Collapse
|
12
|
Stevens RH, Galloway TL, Willemsen-Dunlap A. Neuroergonomics: Quantitative Modeling of Individual, Shared, and Team Neurodynamic Information. HUMAN FACTORS 2018; 60:1022-1034. [PMID: 29906201 DOI: 10.1177/0018720818781623] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
OBJECTIVE The aim of this study was to use the same quantitative measure and scale to directly compare the neurodynamic information/organizations of individual team members with those of the team. BACKGROUND Team processes are difficult to separate from those of individual team members due to the lack of quantitative measures that can be applied to both process sets. METHOD Second-by-second symbolic representations were created of each team member's electroencephalographic power, and quantitative estimates of their neurodynamic organizations were calculated from the Shannon entropy of the symbolic data streams. The information in the neurodynamic data streams of health care ( n = 24), submarine navigation ( n = 12), and high school problem-solving ( n = 13) dyads was separated into the information of each team member, the information shared by team members, and the overall team information. RESULTS Most of the team information was the sum of each individual's neurodynamic information. The remaining team information was shared among the team members. This shared information averaged ~15% of the individual information, with momentary levels of 1% to 80%. CONCLUSION Continuous quantitative estimates can be made from the shared, individual, and team neurodynamic information about the contributions of different team members to the overall neurodynamic organization of a team and the neurodynamic interdependencies among the team members. APPLICATION Information models provide a generalizable quantitative method for separating a team's neurodynamic organization into that of individual team members and that shared among team members.
Collapse
|
13
|
Mazurek KA, Berger M, Bollu T, Chowdhury RH, Elangovan N, Kuling IA, Sohn MH. Highlights from the 28th Annual Meeting of the Society for the Neural Control of Movement. J Neurophysiol 2018; 120:1671-1679. [PMID: 30020841 PMCID: PMC6230782 DOI: 10.1152/jn.00475.2018] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Accepted: 07/15/2018] [Indexed: 01/04/2023] Open
Affiliation(s)
- Kevin A Mazurek
- Department of Neuroscience, University of Rochester , Rochester, New York
- Del Monte Institute for Neuroscience, University of Rochester , Rochester, New York
| | - Michael Berger
- Cognitive Neuroscience Laboratory, German Primate Center-Leibniz-Institute for Primate Research, Göttingen , Germany
- Faculty of Biology and Psychology, University of Göttingen , Göttingen , Germany
| | - Tejapratap Bollu
- Department of Neurobiology and Behavior, Cornell University , Ithaca, New York
| | - Raeed H Chowdhury
- Department of Biomedical Engineering, Northwestern University , Evanston, Illinois
- Department of Physiology, Northwestern University , Chicago, Illinois
| | - Naveen Elangovan
- Human Sensorimotor Control Lab, University of Minnesota , Minneapolis, Minnesota
| | - Irene A Kuling
- Department of Human Movement Sciences, VU University , Amsterdam , The Netherlands
| | - M Hongchul Sohn
- Department of Biomedical Engineering, Northwestern University , Evanston, Illinois
- Shirley Ryan AbilityLab, Chicago, Illinois
| |
Collapse
|
14
|
Brush ER, Krakauer DC, Flack JC. Conflicts of interest improve collective computation of adaptive social structures. SCIENCE ADVANCES 2018; 4:e1603311. [PMID: 29376116 PMCID: PMC5777398 DOI: 10.1126/sciadv.1603311] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Accepted: 12/14/2017] [Indexed: 05/31/2023]
Abstract
In many biological systems, the functional behavior of a group is collectively computed by the system's individual components. An example is the brain's ability to make decisions via the activity of billions of neurons. A long-standing puzzle is how the components' decisions combine to produce beneficial group-level outputs, despite conflicts of interest and imperfect information. We derive a theoretical model of collective computation from mechanistic first principles, using results from previous work on the computation of power structure in a primate model system. Collective computation has two phases: an information accumulation phase, in which (in this study) pairs of individuals gather information about their fighting abilities and make decisions about their dominance relationships, and an information aggregation phase, in which these decisions are combined to produce a collective computation. To model information accumulation, we extend a stochastic decision-making model-the leaky integrator model used to study neural decision-making-to a multiagent game-theoretic framework. We then test alternative algorithms for aggregating information-in this study, decisions about dominance resulting from the stochastic model-and measure the mutual information between the resultant power structure and the "true" fighting abilities. We find that conflicts of interest can improve accuracy to the benefit of all agents. We also find that the computation can be tuned to produce different power structures by changing the cost of waiting for a decision. The successful application of a similar stochastic decision-making model in neural and social contexts suggests general principles of collective computation across substrates and scales.
Collapse
Affiliation(s)
- Eleanor R. Brush
- Program in Quantitative and Computational Biology, Princeton University, Princeton, NJ 08544, USA
- Santa Fe Institute, Santa Fe, NM 87501, USA
| | | | | |
Collapse
|
15
|
Flack JC. Coarse-graining as a downward causation mechanism. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2017; 375:rsta.2016.0338. [PMID: 29133440 PMCID: PMC5686398 DOI: 10.1098/rsta.2016.0338] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/11/2017] [Indexed: 05/25/2023]
Abstract
Downward causation is the controversial idea that 'higher' levels of organization can causally influence behaviour at 'lower' levels of organization. Here I propose that we can gain traction on downward causation by being operational and examining how adaptive systems identify regularities in evolutionary or learning time and use these regularities to guide behaviour. I suggest that in many adaptive systems components collectively compute their macroscopic worlds through coarse-graining. I further suggest we move from simple feedback to downward causation when components tune behaviour in response to estimates of collectively computed macroscopic properties. I introduce a weak and strong notion of downward causation and discuss the role the strong form plays in the origins of new organizational levels. I illustrate these points with examples from the study of biological and social systems and deep neural networks.This article is part of the themed issue 'Reconceptualizing the origins of life'.
Collapse
|
16
|
López Chavira MA, Marcelín-Jiménez R. Distributed rewiring model for complex networking: The effect of local rewiring rules on final structural properties. PLoS One 2017; 12:e0187538. [PMID: 29107986 PMCID: PMC5673200 DOI: 10.1371/journal.pone.0187538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Accepted: 10/20/2017] [Indexed: 11/19/2022] Open
Abstract
The study of complex networks has become an important subject over the last decades. It has been shown that these structures have special features, such as their diameter, or their average path length, which in turn are the explanation of some functional properties in a system such as its fault tolerance, its fragility before attacks, or the ability to support routing procedures. In the present work, we study some of the forces that help a network to evolve to the point where structural properties are settled. Although our work is mainly focused on the possibility of applying our ideas to Information and Communication Technologies systems, we consider that our results may contribute to understanding different scenarios where complex networks have become an important modeling tool. Using a discrete event simulator, we get each node to discover the shortcuts that may connect it with regions away from its local environment. Based on this partial knowledge, each node can rewire some of its links, which allows modifying the topology of the entire underlying graph to achieve new structural properties. We proposed a distributed rewiring model that creates networks with features similar to those found in complex networks. Although each node acts in a distributed way and seeking to reduce only the trajectories of its packets, we observed a decrease of diameter and an increase in clustering coefficient in the global structure compared to the initial graph. Furthermore, we can find different final structures depending on slight changes in the local rewiring rules.
Collapse
Affiliation(s)
| | - Ricardo Marcelín-Jiménez
- Department of Electrical Engineering, Universidad Autónoma Metropolitana, Iztapalapa, Mexico City, Mexico
| |
Collapse
|
17
|
Torday JS, Miller WB. The resolution of ambiguity as the basis for life: A cellular bridge between Western reductionism and Eastern holism. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2017; 131:288-297. [PMID: 28743585 DOI: 10.1016/j.pbiomolbio.2017.07.013] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2017] [Revised: 07/12/2017] [Accepted: 07/21/2017] [Indexed: 01/08/2023]
Abstract
Boundary conditions enable cellular life through negentropy, chemiosmosis, and homeostasis as identifiable First Principles of Physiology. Self-referential awareness of status arises from this organized state to sustain homeostatic imperatives. Preferred homeostatic status is dependent upon the appraisal of information and its communication. However, among living entities, sources of information and their dissemination are always imprecise. Consequently, living systems exist within an innate state of ambiguity. It is presented that cellular life and evolutionary development are a self-organizing cellular response to uncertainty in iterative conformity with its basal initiating parameters. Viewing the life circumstance in this manner permits a reasoned unification between Western rational reductionism and Eastern holism.
Collapse
Affiliation(s)
- John S Torday
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA 90502, USA.
| | | |
Collapse
|