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Research ArticleResearch Article: New Research, Sensory and Motor Systems

Functional Connectome Analyses Reveal the Human Olfactory Network Organization

T. Campbell Arnold, Yuqi You, Mingzhou Ding, Xi-Nian Zuo, Ivan de Araujo and Wen Li
eNeuro 29 May 2020, 7 (4) ENEURO.0551-19.2020; DOI: https://doi.org/10.1523/ENEURO.0551-19.2020
T. Campbell Arnold
1Department of Psychology, Florida State University, Tallahassee, FL, 32306
2Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104
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Yuqi You
1Department of Psychology, Florida State University, Tallahassee, FL, 32306
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Mingzhou Ding
3J Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, 32611
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Xi-Nian Zuo
4Developmental Population Neuroscience Research Center, State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China, 100875
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Ivan de Araujo
5Department of Psychiatry, Yale University School of Medicine, The John B. Pierce Laboratory, New Haven, CT, 06519
6Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029
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Wen Li
1Department of Psychology, Florida State University, Tallahassee, FL, 32306
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  • Figure 1.
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    Figure 1.

    Procedures. A, Schematic illustration of analysis pipeline. (i) A total of 28 ROIs were defined. (ii) An automated procedure based on COV removed voxels contaminated with artifacts from the ROIs. (iii) Participant exclusion based on three exclusion criteria. (iv) Timeseries data extraction from the ROIs. (v) A 28 × 28 correlation matrix compiled based on pair-wise correlations across the ROIs. (vi) A binary adjacency matrix constructed with suprathreshold and subthreshold connections. (vii) Suprathreshold connections chosen to form the olfactory network. (viii) Graph-theoretical analyses performed to characterize the organization of this network. B, 3D display of ROIs before (top row) and after (bottom row) voxel removal. Insets illustrate the underlying ROIs in 3D whole-brain images with parts of dorsolateral frontal and temporal lobes removed. Omm, middle medial OFC; Opm, posterior medial OFC; Oc, central OFC; Oapc, anterior-APC OFC; Oml, medial lateral OFC; Oolfl = lateral olfactory OFC.

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    Figure 2.

    The olfactory network. A, A weighted sparse 28 × 28 correlation matrix of group average Pearson’s rs for all suprathreshold pairs. ROIs included in the olfactory network are enclosed in the orange box, with the three identified modules (subnetworks) enclosed in the red boxes. The table lists the region names in correspondence to the ROI/node numbers. B, A transparent brain model (in sagittal and axial views) with ROIs (nodes) for the three modules coded in three respective colors. Gray nodes are ROIs not accepted into the olfactory network. C, A binary connectivity matrix reveals suprathreshold connections (shown in yellow) across the olfactory network nodes (22 parcels, enclosed in the orange box) and occipital visual cortical regions (28 parcels, enclosed in the cyan box) at three cutoff levels (top 5%, 10%, and 15%). The visual regions (Cal = calcarine gyrus; Cun = cuneus gyrus; Occ-I = occipital inferior gyrus; Occ-M = occipital middle gyrus; Occ-S = occipital superior gyrus) were strongly interconnected and relatively disconnected from the olfactory nodes.

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    Figure 3.

    Local network metrics. A, Topology of the olfactory network. The three modules/subnetworks are indicated by the three colors of the circles. Line thickness indicates connection strength (mean correlation coefficients), and node size reflects connection density (number of connections). B, Modularity across a range of connection thresholds. Each row corresponds to one of the 28 ROIs, and columns indicate the connection threshold applied to the network while color indicates the module assignment. In general, nodes were consistently assigned to three modules identified as the limbic (red), sensory (yellow), and frontal (blue) subnetworks. At some connection thresholds, nodes were no longer connected to the network, which is indicated in gray. C, Hubness of a node as reflected by composite hub ranking and composite hub Z-scores. The three centrality indices (node degree, betweenness, and closeness centrality) are also displayed. The AMY and INSa separated from the other nodes as major hubs of the network. Changes in global efficiency of the olfactory network following a node removal were small except for the AMY and INSa nodes, which resulted in 8.5% and 7.3% reductions in global efficiency, respectively.

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    Figure 4.

    Validation and function of the olfactory network. A, Weighted connectivity matrices of the olfactory network based on the HCP dataset and the independent dataset greatly overlapped; Spearman ρ = 0.41, p < 0.001. B, Module assignments across weighted networks of individual subjects. Each row corresponds to one of the 28 ROIs, and columns indicate individual subjects while color indicates the module assignment. The group level module assignment is provided to the far right for reference. Subjects are ordered based on the number of modules detected (left, two module subjects, n = 4; center, three module subjects, n = 21; right, four module subjects, n = 7) and beneath the module assignment matrix a key to module number is provided (purple). C, The global network metric of clustering coefficient was positively correlated with olfactory discrimination performance (d’), ρ = 0.32, *p < 0.05.

Tables

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    Table 1

    ROI centroid coordinates, sizes, and mean (whole-brain) correlation coefficients

    ROIxyzVoxelsR
    Oolf2535–141800.25
    APC2410–201430.22
    PPC244–171370.22
    AMY21–5–203770.30
    aHIP26–14–213120.28
    pHIP28–28–93110.28
    ENT18–4–293090.25
    INSa3521–64490.30
    INSd39864210.27
    INSv432–55130.29
    INSp37–15123680.29
    HYP5–3–121070.22
    THLda11–14132630.25
    THLva10–1322760.27
    THLdp16–24112380.24
    THLvp14–2522800.27
    OTB144–14430.13
    Omm1641–212040.24
    Opm1725–212220.27
    Oa1556–172500.23
    Oc2843–172190.23
    Oal2457–142520.20
    Oml4238–122500.26
    Oolfl3334–151830.24
    Opl3926–152330.25
    Omp3124–211600.22
    Oapc2318–231340.22
    NAcc1011–81160.22
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Functional Connectome Analyses Reveal the Human Olfactory Network Organization
T. Campbell Arnold, Yuqi You, Mingzhou Ding, Xi-Nian Zuo, Ivan de Araujo, Wen Li
eNeuro 29 May 2020, 7 (4) ENEURO.0551-19.2020; DOI: 10.1523/ENEURO.0551-19.2020

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Functional Connectome Analyses Reveal the Human Olfactory Network Organization
T. Campbell Arnold, Yuqi You, Mingzhou Ding, Xi-Nian Zuo, Ivan de Araujo, Wen Li
eNeuro 29 May 2020, 7 (4) ENEURO.0551-19.2020; DOI: 10.1523/ENEURO.0551-19.2020
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Keywords

  • functional neuroanatomy
  • functional segregation
  • functional specialization
  • graph theory
  • network
  • olfaction

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