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      The Role of the Prefrontal Cortex and Functional Connectivity during Maritime Operations: An fNIRS study

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          Abstract

          Introduction

          Watchkeeping is a significant activity during maritime operations, and failures of sustained attention and decision‐making can increase the likelihood of a collision.

          Methods

          A study was conducted in a ship bridge simulator where 40 participants (20 experienced/20 inexperienced) performed: (1) a 20‐min period of sustained attention to locate a target vessel and (2) a 10‐min period of decision‐making/action selection to perform an evasive maneuver. Half of the participants also performed an additional task of verbally reporting the position of their vessel. Activation of the prefrontal cortex (PFC) was captured via a 15‐channel functional near‐infrared spectroscopy (fNIRS) montage, and measures of functional connectivity were calculated frontal using graph‐theoretic measures.

          Results

          Neurovascular activation of right lateral area of the PFC decreased during sustained attention and increased during decision‐making. The graph‐theoretic analysis revealed that density declined during decision‐making in comparison with the previous period of sustained attention, while local clustering declined during sustained attention and increased when participants prepared their evasive maneuver. A regression analysis revealed an association between network measures and behavioral outcomes, with respect to spotting the target vessel and making an evasive maneuver.

          Conclusions

          The right lateral area of the PFC is sensitive to watchkeeping and decision‐making during operational performance. Graph‐theoretic measures allow us to quantify patterns of functional connectivity and were predictive of safety‐critical performance.

          Abstract

          fNIRS was used in a ship bridge simulator to study safety‐related performance during watchkeeping and decision‐making. Functional connectivity of the prefrontal cortex was measured. It was found that connection density was reduced during decision‐making while local clustering increased; connectivity measures were also significantly predictive of safety‐related behaviour.

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          Most cited references73

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          Collective dynamics of 'small-world' networks.

          Networks of coupled dynamical systems have been used to model biological oscillators, Josephson junction arrays, excitable media, neural networks, spatial games, genetic control networks and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation. The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.
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            Complex network measures of brain connectivity: uses and interpretations.

            Brain connectivity datasets comprise networks of brain regions connected by anatomical tracts or by functional associations. Complex network analysis-a new multidisciplinary approach to the study of complex systems-aims to characterize these brain networks with a small number of neurobiologically meaningful and easily computable measures. In this article, we discuss construction of brain networks from connectivity data and describe the most commonly used network measures of structural and functional connectivity. We describe measures that variously detect functional integration and segregation, quantify centrality of individual brain regions or pathways, characterize patterns of local anatomical circuitry, and test resilience of networks to insult. We discuss the issues surrounding comparison of structural and functional network connectivity, as well as comparison of networks across subjects. Finally, we describe a Matlab toolbox (http://www.brain-connectivity-toolbox.net) accompanying this article and containing a collection of complex network measures and large-scale neuroanatomical connectivity datasets. Copyright (c) 2009 Elsevier Inc. All rights reserved.
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              A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology.

              This year marks the 20th anniversary of functional near-infrared spectroscopy and imaging (fNIRS/fNIRI). As the vast majority of commercial instruments developed until now are based on continuous wave technology, the aim of this publication is to review the current state of instrumentation and methodology of continuous wave fNIRI. For this purpose we provide an overview of the commercially available instruments and address instrumental aspects such as light sources, detectors and sensor arrangements. Methodological aspects, algorithms to calculate the concentrations of oxy- and deoxyhemoglobin and approaches for data analysis are also reviewed. From the single-location measurements of the early years, instrumentation has progressed to imaging initially in two dimensions (topography) and then three (tomography). The methods of analysis have also changed tremendously, from the simple modified Beer-Lambert law to sophisticated image reconstruction and data analysis methods used today. Due to these advances, fNIRI has become a modality that is widely used in neuroscience research and several manufacturers provide commercial instrumentation. It seems likely that fNIRI will become a clinical tool in the foreseeable future, which will enable diagnosis in single subjects. Copyright © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                S.Fairclough@ljmu.ac.uk
                Journal
                Brain Behav
                Brain Behav
                10.1002/(ISSN)2157-9032
                BRB3
                Brain and Behavior
                John Wiley and Sons Inc. (Hoboken )
                2162-3279
                04 November 2020
                January 2021
                : 11
                : 1 ( doiID: 10.1002/brb3.v11.1 )
                : e01910
                Affiliations
                [ 1 ] Intelligent Transport Systems Research Centre Wuhan University of Technology Wuhan China
                [ 2 ] National Engineering Research Centre for Water Transport Safety (WTSC) MOST Wuhan China
                [ 3 ] Liverpool Logistics Offshore and Marine (LOOM) Research Institute Liverpool John Moores University Liverpool UK
                [ 4 ] School of Psychology Liverpool John Moores University Liverpool UK
                Author notes
                [*] [* ] Correspondence

                Stephen Fairclough, School of Psychology, Liverpool John Moores University, Liverpool, UK.

                Email: S.Fairclough@ 123456ljmu.ac.uk

                Author information
                https://orcid.org/0000-0003-3714-7201
                https://orcid.org/0000-0001-8080-4997
                https://orcid.org/0000-0002-7850-5688
                Article
                BRB31910
                10.1002/brb3.1910
                7821565
                33151030
                1d11bb19-2358-44d5-a3a7-12186a42df0a
                © 2020 The Authors. Brain and Behavior published by Wiley Periodicals LLC

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 23 May 2020
                : 08 September 2020
                : 04 October 2020
                Page count
                Figures: 12, Tables: 5, Pages: 18, Words: 12323
                Funding
                Funded by: National Natural Science Foundation of China , open-funder-registry 10.13039/501100001809;
                Award ID: 51920105014
                Funded by: H2020 Transport , open-funder-registry 10.13039/100010680;
                Award ID: ENHANCE/MSCA‐RISE 823904
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                January 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.6 mode:remove_FC converted:22.01.2021

                Neurosciences
                functional neuroimaging,neurovascular coupling,occupational safety,prefrontal cortex,spectroscopy,near‐infrared

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