Graph-theoretic connectivity measures: what do they tell us about connectivity?

被引:0
|
作者
A. Laita
J. S. Kotiaho
M. Mönkkönen
机构
[1] University of Jyväskylä,Department of Biological and Environmental Science
来源
Landscape Ecology | 2011年 / 26卷
关键词
Functional connectivity; Graph theory; Reserve network; Component; Patch prioritisation;
D O I
暂无
中图分类号
学科分类号
摘要
Graph-theoretic connectivity analyses have received much attention in connectivity evaluation during the last few years. Here, we explore the underlying conceptual differences of various graph-theoretic connectivity measures. Based on connectivity analyses from three reserve networks in forested landscapes in Central Finland, we illustrate how these conceptual differences cause inconsistent connectivity evaluations at both the landscape and patch level. Our results also illustrate how the characteristics of the networks (patch density) may affect the performance of the different measures. Many of the connectivity measures react to changes in habitat connectivity in an ecologically undesirable manner. Patch prioritisations based on a node removal analysis were sensitive to the connectivity measure they were based on. The patch prioritisations derived from different measures showed a disparity in terms of how much weight they put on patch size versus patch location and how they value patch location. Although graphs operate at the interface of structure and function, there is still much to do for incorporating the inferred ecological process into graph structures and analyses. If graph analyses are going to be used for real-world management and conservation purposes, a more thorough understanding of the caveats and justifications of the graph-theoretic connectivity measures will be needed.
引用
收藏
页码:951 / 967
页数:16
相关论文
共 45 条
  • [21] What electrophysiology tells us about Alzheimer's disease: a window into the synchronization and connectivity of brain neurons
    Babiloni, Claudio
    Blinowska, Katarzyna
    Bonanni, Laura
    Cichocki, Andrej
    De Haan, Willem
    Del Percio, Claudio
    Dubois, Bruno
    Escudero, Javier
    Fernandez, Alberto
    Frisoni, Giovanni
    Guntekin, Bahar
    Hajos, Mihaly
    Hampel, Harald
    Ifeachor, Emmanuel
    Kilborn, Kerry
    Kumar, Sanjeev
    Johnsen, Kristinn
    Johannsson, Magnus
    Jeong, Jaeseung
    LeBeau, Fiona
    Lizio, Roberta
    da Silva, Fernando Lopes
    Maestu, Fernando
    McGeown, William J.
    McKeith, Ian
    Moretti, Davide Vito
    Nobili, Flavio
    Olichney, John
    Onofrj, Marco
    Palop, Jorge J.
    Rowan, Michael
    Stocchi, Fabrizio
    Struzik, Zbigniew M.
    Tanila, Heikki
    Teipel, Stefan
    Taylor, John Paul
    Weiergraeber, Marco
    Yener, Gorsev
    Young-Pearse, Tracy
    Drinkenburg, Wilhelmus H.
    Randall, Fiona
    NEUROBIOLOGY OF AGING, 2020, 85 : 58 - 73
  • [22] Functional near infrared spectroscopy for brain functional connectivity analysis: A graph theoretic approach
    Akila, V.
    Johnvictor, Anita Christaline
    HELIYON, 2023, 9 (04)
  • [23] Higher levels of trait emotional awareness are associated with more efficient global information integration throughout the brain: a graph-theoretic analysis of resting state functional connectivity
    Smith, Ryan
    Sanova, Anna
    Alkozei, Anna
    Lane, Richard D.
    Killgore, William D. S.
    SOCIAL COGNITIVE AND AFFECTIVE NEUROSCIENCE, 2018, 13 (07) : 665 - 675
  • [24] What functional connectivity can do: Software driven neural networks
    Watanabe, M
    Aihara, K
    ICONIP'98: THE FIFTH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING JOINTLY WITH JNNS'98: THE 1998 ANNUAL CONFERENCE OF THE JAPANESE NEURAL NETWORK SOCIETY - PROCEEDINGS, VOLS 1-3, 1998, : 1370 - 1373
  • [25] Two measures of landscape-graph connectivity: assessment across gradients in area and configuration
    Ferrari, Joseph R.
    Lookingbill, Todd R.
    Neel, Maile C.
    LANDSCAPE ECOLOGY, 2007, 22 (09) : 1315 - 1323
  • [26] Two measures of landscape-graph connectivity: assessment across gradients in area and configuration
    Joseph R. Ferrari
    Todd R. Lookingbill
    Maile C. Neel
    Landscape Ecology, 2007, 22 : 1315 - 1323
  • [27] What Can Neuroscience Tell Us about the Hard Problem of Consciousness?
    Brogaard, Berit
    Gatzia, Dimitria Electra
    FRONTIERS IN NEUROSCIENCE, 2016, 10
  • [28] Investigations on the brain connectivity patterns in progression of Alzheimer's disease using functional MR imaging and graph theoretical measures
    Bhuvaneshwari, B.
    Kavitha, A.
    2017 IEEE 16TH INTERNATIONAL CONFERENCE ON COGNITIVE INFORMATICS & COGNITIVE COMPUTING (ICCI*CC), 2017, : 151 - 160
  • [29] Reproducibility of graph measures derived from resting-state MEG functional connectivity metrics in sensor and source spaces
    Pourmotabbed, Haatef
    Curry, Amy L. de Jongh
    Clarke, Dave F.
    Tyler-Kabara, Elizabeth C.
    Babajani-Feremi, Abbas
    HUMAN BRAIN MAPPING, 2022, 43 (04) : 1342 - 1357
  • [30] Reliable evaluation of functional connectivity and graph theory measures in source-level EEG: How many electrodes are enough?
    Hatlestad-Hall, Christoffer
    Bruna, Ricardo
    Liljestrom, Mia
    Renvall, Hanna
    Heuser, Kjell
    Tauboll, Erik
    Maestu, Fernando
    Haraldsen, Ira H.
    CLINICAL NEUROPHYSIOLOGY, 2023, 150 : 1 - 16