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Cited by 34Functional Brain Connectivity StudiesAlzheimer's disease research and treatmentsAdvanced Neuroimaging Techniques and Applications

Functional and structural connectome properties in the 5XFAD transgenic mouse model of Alzheimer’s disease

Open access
Kesler, Shelli R., Acton, Paul, Rao, Vikram, Ray, William J.·2018·Network Neuroscience
DOI 10.1162/netn_a_00048PMC PMC6130552
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Abstract

Neurodegeneration in Alzheimer’s disease (AD) is associated with amyloid-beta peptide accumulation into insoluble amyloid plaques. The five-familial AD (5XFAD) transgenic mouse model exhibits accelerated amyloid-beta deposition, neuronal dysfunction, and cognitive impairment. We aimed to determine whether connectome properties of these mice parallel those observed in patients with AD. We obtained diffusion tensor imaging and resting-state functional magnetic resonance imaging data for four transgenic and four nontransgenic male mice. We constructed both structural and functional connectomes and measured their topological properties by applying graph theoretical analysis. We compared connectome properties between groups using both binarized and weighted networks. Transgenic mice showed higher characteristic path length in weighted structural connectomes and functional connectomes at minimum density. Normalized clustering and modularity were lower in transgenic mice across the upper densities of the structural connectome. Transgenic mice also showed lower small-worldness index in higher structural connectome densities and in weighted structural networks. Hyper-correlation of structural and functional connectivity was observed in transgenic mice compared with nontransgenic controls. These preliminary findings suggest that 5XFAD mouse connectomes may provide useful models for investigating the molecular mechanisms of AD pathogenesis and testing the effectiveness of potential treatments.

AI snapshot

Written from the paper’s full text.

TL;DR

This pilot study compared structural and functional connectomes of 5XFAD transgenic mice with nontransgenic controls and found some AD-like network alterations, including higher characteristic path length and lower small-worldness. The authors conclude that 5XFAD connectomes may be useful for investigating AD mechanisms and preclinical treatment effects.

Key findings

  • Weighted structural connectomes in transgenic mice showed significantly higher characteristic path length (F = 15.2, p = 0.01) and lower small-worldness index (F = 9.73, p = 0.03) than controls.
  • In structural connectomes across the second density window (0.34 to maximum density 0.5), transgenic mice had lower normalized clustering coefficient (p = 0.01), small-worldness index (p = 0.02), and modularity (p = 0.03).
  • Functional connectomes at minimum connection density showed significantly higher characteristic path length in transgenic mice (t = 3.64, p = 0.01); weighted functional connectomes showed no significant group differences after excluding two nontransgenic mice lacking small-worldness.
  • Transgenic mice showed poorer power-law fit in weighted functional connectomes (p < 0.001), and structure-function correlation coefficients using default communication measures were higher in transgenic mice (t = 2.92, p = 0.03); no significant regional effects were found via NBS or FDR.

Methods

  • Eight male mice, 23 weeks old: four 5XFAD transgenic and four nontransgenic littermate controls. In vivo resting-state fMRI was acquired at 7 Tesla under isoflurane; ex vivo DTI was acquired at 9.4 Tesla after perfusion and Magnevist treatment.
  • Functional and structural connectomes were constructed with 32 bilateral cortical/subcortical gray matter nodes. Graph theoretical properties were compared across network densities using area under the curve and nonparametric permutation testing (2,000 iterations), and weighted networks were compared with general linear models covarying for density.
  • Additional analyses examined hub degree distributions via power-law fitting, regional effects using the Network-Based Statistic and false discovery rate, and structure-function relationships by predicting functional connectivity from structural communication measures.

Limitations

  • The paper states that it is unclear why functional connectomes failed to show expected small-worldness, possibly due to anesthesia or MRI field strength; fMRI and DTI were acquired at different field strengths; the small sample may have reduced power; there is no standard parcellation scheme; and DTI-based connectomes correspond poorly with neuron tracer data.
  • The text also makes evident that this is a preliminary pilot study with only four mice per group, no molecular assays were available, and functional analyses were limited by excluding subjects or restricting comparisons to minimum density.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1162/netn_a_00048

Cites

93 of 93 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

37 of 66 cited sources checked · 28 supported · 0 flagged · accuracy not yet measured

  • Findingown data

    Structural networks demonstrated expected small-world organization (small-worldness index greater than 1) across multiple densities.

    “As shown in Figure 1, structural networks demonstrated expected small-world organization defined as a small-worldness index greater than 1 (Humphries & Gurney, 2008) across multiple densities.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Humphries & Gurney, 2008 source
  • Premisecitation

    5XFAD mice at 23 weeks of age have been shown to have cognitive deficits that are prior to significant neuronal or synaptic loss.

    “5XFAD mice at 23 weeks of age have been shown to have cognitive deficits that are prior to significant neuronal or synaptic loss (Eimer & Vassar, 2013; Oakley et al., 2006).”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites Eimer & Vassar, 2013 source

      The Results section reports no significant neuron loss at 4 months and a variable onset around 6 months, supporting the neuronal-loss portion of the claim for an age between those measurements. The paper does not establish cognitive deficits specifically at 23 weeks or show that they precede significant synaptic loss; those parts are not supported by the eligible passages (page numbers unavailable). (LLM, conf=0.83)

      Experimental — accuracy not yet measured
    • cites Oakley et al., 2006 source

      The section “5XFAD mice develop spatial memory deficits” reports significant Y-maze impairment at 4–5 months, but does not test mice specifically at 23 weeks. The “Memory impairment and intraneuronal Aβ” section says that this deficit coincides with the initial decline in synaptophysin, a synaptic marker; thus the paper does not support saying the deficit preceded synaptic loss. Neuron loss was documented in 9-month-old mice. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
  • Premisecitation

    5XFAD mice are particularly useful for investigating the effects of amyloid-beta deposition on neuronal loss.

    “They are particularly useful for investigating the effects of amyloid-beta deposition on neuronal loss (Eimer & Vassar, 2013).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Eimer & Vassar, 2013 source
  • Premisecitation

    Previous DTI and fMRI connectome studies of patients with AD have also demonstrated lower normalized clustering, small-worldness, and modularity.

    “Previous DTI and fMRI connectome studies of patients with AD have also demonstrated lower normalized clustering, small-worldness, and modularity (Brier et al., 2014; Sun et al., 2014; Supekar, Menon, Rubin, Musen, & Greicius, 2008).”
    Quote in the paperNot a substantial claim2 of 3 sources checked
    • cites Brier et al., 2014

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Sun et al., 2014 source
    • cites Supekar et al., 2008 source

      The Results section, “Comparison of small-world metrics in the AD and control groups” (page unavailable), reports significantly lower normalized clustering (γ) and small-worldness (σ) in the AD group. This study used fMRI, not DTI, and the retrieved passages do not report a modularity result. It therefore supports only part of the combined claim attributed to the three citations. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
  • Premisecitation

    Clinical studies of patients with AD have demonstrated higher characteristic path lengths of DTI- or fMRI-based connectomes.

    “Clinical studies of patients with AD have demonstrated higher characteristic path lengths of DTI- or fMRI-based connectomes (Lo et al., 2010; Wang et al., 2012; Zhao et al., 2012).”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites Lo et al., 2010

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Wang et al., 2012 source
    • cites Zhao et al., 2012 source
  • Classified as probably not a substantial claim. 29
  • May combine two claims. 13

  • Classified as probably not a substantial claim.

    Premisecitation

    Studies suggest that AD pathogenesis targets high-traffic hub regions in the brain, spreading from epicenters to secondary networks as the disease progresses.

    “Additionally, studies suggest that AD pathogenesis targets high-traffic hub regions in the brain, spreading from epicenters to secondary networks as the disease progresses (Buckner et al., 2009; Dai et al., 2015; Mallio et al., 2015; Stam et al., 2009; Zhou, Gennatas, Kramer, Miller, & Seeley, 2012; Zhou & Seeley, 2014).”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites Buckner et al., 2009 source

      The Results section, “Aβ Deposition in Alzheimer’s Disease Occurs Preferentially in the Locations of Cortical Hubs” (page unavailable), reports a strong overlap between cortical hubs and amyloid deposition in AD. The paper supports the proposed vulnerability of hubs, but its comparison of hub and amyloid maps does not show pathology spreading from epicenters to secondary networks as disease progresses. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
    • cites Dai et al., 2015

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Mallio et al., 2015 source

      The Summary (p. 1) and Conclusion (pp. 6–7) support disruption spreading outward from entorhinal and hippocampal epicenters as AD severity increases. But the Conclusion (p. 8) reports that testing high-traffic hub regions as alternative epicenters did not reproduce this pattern; the authors say total connectional flow did not explain their results. Thus this paper does not support the high-traffic-hub part of the claim. (LLM, conf=0.90)

      Experimental — accuracy not yet measured

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Thresholding connectomes is necessary for removing false-positive edges and facilitating between-group comparisons but can remove potentially valid information regarding differences in network topology.

    “Thresholding connectomes is necessary for removing false-positive edges and facilitating between-group comparisons but can remove potentially valid information regarding differences in network topology (Fornito, Zalesky, & Breakspear, 2013; van Wijk, Stam, & Daffertshofer, 2010).”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites Fornito, Zalesky, & Breakspear, 2013 source
    • cites van Wijk, Stam, & Daffertshofer, 2010 source

      In Analysis > Defining graphs from data, the paper describes thresholding to omit connectivity values expected by chance and warns that a fixed average degree can exclude important connections and modify topology. It also says thresholding can hide information that differs between conditions. The claim overstates its necessity for between-group comparisons: the paper says threshold choice can make comparisons inaccurate and discusses weighted analysis as an alternative that avoids selecting a threshold. (LLM, conf=0.86)

      Experimental — accuracy not yet measured

  • Classified as probably not a substantial claim.

    Premisecitation

    Previous studies of APP/PS1 and ArcBeta transgenic mice have demonstrated deficits in the functional connectivity of multiple brain regions that is associated with amyloid deposition.

    “Previous studies of APP/PS1 and ArcBeta transgenic mice have demonstrated deficits in the functional connectivity of multiple brain regions that is associated with amyloid deposition (Bero et al., 2012; Grandjean et al., 2014; Shah et al., 2013).”
    Quote in the paperSubstantial claim3 of 3 sources checked
    • cites Bero et al., 2012 source
    • cites Grandjean et al., 2014 source

      The Discussion reports reduced functional connectivity in ArcAβ mice, particularly early in life, so the deficit portion is supported. But those changes appeared before amyloid deposition, and the paper says it could not correlate them with plaque burden. The cited paper discusses APP/PS1 findings from another study rather than demonstrating APP/PS1 deficits itself. (LLM, conf=0.90)

      Experimental — accuracy not yet measured
    • cites Shah et al., 2013 source

  • May combine two claims.

    Premisecitation

    Connectome properties have been shown to be preserved across species and therefore provide a unique translational bridge between preclinical and clinical studies.

    “Connectome properties have been shown to be preserved across species and therefore provide a unique translational bridge between preclinical and clinical studies (Gorges et al., 2017; Oh et al., 2014; Stafford et al., 2014; van den Heuvel, Bullmore, & Sporns, 2016).”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites Gorges et al., 2017 source
    • cites Oh et al., 2014

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Stafford et al., 2014 source

  • May combine two claims.

    Premisecitation

    Inconsistencies in connectome findings are a well-known issue in the literature and often reflect differences in methodology such as imaging modality and/or choice of thresholding method.

    “Inconsistencies in connectome findings are a well-known issue in the literature (for reviews, see Dai & He, 2014; Tijms, Wink et al., 2013) and often reflect differences in methodology such as imaging modality and/or choice of thresholding method.”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites Dai & He, 2014 source
    • cites Tijms, Wink et al., 2013 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Efficiency and path length are related measures.

    “Efficiency and path length are related measures (Achard & Bullmore, 2007).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Achard & Bullmore, 2007 source

  • Classified as probably not a substantial claim.

    Premisecitation

    Both amyloid-beta and tau are believed to synergistically drive neurodegenerative processes involved in AD.

    “Both amyloid-beta and tau are believed to synergistically drive neurodegenerative processes involved in AD (Bloom, 2014; Lloret et al., 2015; Stancu, Vasconcelos, Terwel, & Dewachter, 2014).”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites Bloom, 2014 source
    • cites Lloret et al., 2015 source
    • cites Stancu, Vasconcelos, Terwel, & Dewachter, 2014 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Negative functional edges were zeroed given evidence that properties of negative correlation networks are different than those of positive correlation networks.

    “Negative functional edges were zeroed given evidence that properties of negative correlation networks are different than those of positive correlation networks (Hosseini & Kesler, 2013; Schwarz & McGonigle, 2011).”
    Quote in the paperNot a substantial claim1 of 2 sources checked
    • cites Hosseini & Kesler, 2013 source
    • cites Schwarz & McGonigle, 2011

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    In a small-world network, clustering coefficient is greater than that of random networks, while the path length is comparable to that of random networks.

    “In a small-world network, clustering coefficient is greater than that of random networks, while the path length is comparable to that of random networks (Bassett & Bullmore, 2006; Humphries & Gurney, 2008; Watts & Strogatz, 1998).”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites Bassett & Bullmore, 2006

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Humphries & Gurney, 2008 source
    • cites Watts & Strogatz, 1998 source

  • Classified as probably not a substantial claim.

    Premisecitation

    Previous research has demonstrated lower connectivity among regions involved in specific brain networks of patients with AD, including the default mode network.

    “Previous research has demonstrated lower connectivity among regions involved in specific brain networks of patients with AD, including the default mode network (Bai et al., 2011; Damoiseaux, Prater, Miller, & Greicius, 2012; Lehmann et al., 2013; Simic, Babic, Borovecki, & Hof, 2014).”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites Bai et al., 2011 source

      The Introduction (page unavailable) reports prior findings of default mode network abnormalities in patients with AD, and the Discussion links AD to changes in functional connectivity. It does not establish that connectivity is specifically lower in AD patients; this paper’s measured connectivity changes concern amnestic mild cognitive impairment. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites Damoiseaux, Prater, Miller, & Greicius, 2012

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Lehmann et al., 2013 source

  • Classified as probably not a substantial claim.

    Premisecitation

    Some studies have observed conflicting results, including lower characteristic path length in DTI, gray matter, fMRI, EEG, and MEG connectomes in patients with AD.

    “However, some studies have observed conflicting results, including lower characteristic path length in DTI (Daianu et al., 2013), gray matter (Tijms, Moller et al., 2013), fMRI (Sanz-Arigita et al., 2010), EEG (de Haan et al., 2009), and magneto-encephalogram (MEG; Stam et al., 2009) connectomes in patients with AD.”
    Quote in the paperSubstantial claim3 of 3 sources checked
    • cites Daianu et al., 2013 source
    • cites Tijms, Moller et al., 2013 source
    • cites Sanz-Arigita et al., 2010 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    DTI-based connectomes correspond poorly with neuron tracer data.

    “DTI-based connectomes have particular limitations, as they have been shown to correspond poorly with neuron tracer data (Calabrese, Badea, Cofer, Qi, & Johnson, 2015).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Calabrese, Badea, Cofer, Qi, & Johnson, 2015 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Relevant subnetworks have been shown to be present in mice both structurally and functionally.

    “Relevant subnetworks have been shown to be present in mice both structurally and functionally (Liska, Galbusera, Schwarz, & Gozzi, 2015; Stafford et al., 2014)”
    Quote in the paperNot a substantial claim1 of 2 sources checked
    • cites Liska, Galbusera, Schwarz, & Gozzi, 2015 source
    • cites Stafford et al., 2014 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Such hyper-correlation has been noted in patients with neurologic disorders.

    “Such hyper-correlation has been noted in patients with neurologic disorders (Kesler et al., 2017; Rudie et al., 2012; Wirsich et al., 2016).”
    Quote in the paperNot a substantial claim3 of 3 sources checked
    • cites Kesler et al., 2017 source
    • cites Rudie et al., 2012 source
    • cites Wirsich et al., 2016 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Sun et al. (2014) observed lower structure-function coupling in connectomes of patients with AD.

    “However, Sun et al. (2014) observed lower structure-function coupling in connectomes of patients with AD.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Sun et al. (2014) source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The power-law fit is believed to reflect the brain network's hub organization wherein the majority of information processing is handled by a small number of core regions.

    “The power-law fit is believed to reflect the brain network’s hub organization wherein the majority of information processing is handled by a small number of core regions (Achard et al., 2006).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Achard et al., 2006 source

      The “Degree distribution and hubs” section identifies highly connected association-cortical hubs, supporting the claim's hub-organization component. But it finds that an exponentially truncated power law fits better than a pure power law, and the paper does not establish that a small number of regions handle most information processing (page numbers unavailable in our copy). (LLM, conf=0.88)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Findingown data

    For weighted functional networks, the transgenic group showed poor fit with the power-law, and this was significantly lower than that of the control group (p < 0.001).

    “For weighted functional networks, the transgenic group showed poor fit with the power-law (Figure 6), and this was significantly lower than that of the control group (p < 0.001).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Both groups showed goodness of fit with the power-law with no between-group difference (p = 0.68).

    “Both groups showed goodness of fit with the power-law with no between-group difference (p = 0.68).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Functional networks were small-world for all subjects at only one density (0.52), which was one step above the upper density boundary.

    “However, functional networks were small-world for all subjects at only one density (0.52), which was one step above our upper density boundary.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The study protocols were approved by the University of Texas MD Anderson Institutional Animal Care and Use Committee.

    “Our protocols were approved by the University of Texas MD Anderson Institutional Animal Care and Use Committee.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    AD is associated with significant amyloid-beta peptide accumulation, which is produced from APP by PSEN1 and PSEN2, leading to the hypothesis that it is a primary mechanism of neurodegeneration.

    “AD is associated with significant amyloid-beta peptide accumulation, which is produced from APP by PSEN1 and PSEN2, leading to the hypothesis that it is a primary mechanism of neurodegeneration (Hardy & Selkoe, 2002; Lloret, Fuchsberger, Giraldo, & Vina, 2015).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Hardy & Selkoe, 2002 source
    • cites Lloret et al., 2015 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    Higher characteristic path length suggests that the network is less random in terms of path length.

    “It also suggests that the network is less random in terms of path length.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Weighted functional connectomes for two nontransgenic mice did not demonstrate small-worldness, so these were excluded.

    “Weighted functional connectomes for two nontransgenic mice did not demonstrate small-worldness, so these were excluded.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation

    Lower small-worldness index reflects overall similarity to random networks in that segregation and integration are imbalanced.

    “Lower clustering coefficient suggests lower network segregation or specialization, while lower small-worldness index reflects the overall similarity to random networks in that segregation and integration (i.e., path length) are imbalanced (Bassett & Bullmore, 2006; Watts & Strogatz, 1998).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Bassett & Bullmore, 2006

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Watts & Strogatz, 1998 source

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    The preliminary nature of this study may have limited power to detect differences in efficiencies.

    “Since this was a preliminary study, we may have lacked power to detect differences in efficiencies.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.

    Interpretationnone given

    There were several innovative aspects of this study, including connectome measurement in an AD mouse model, multimodal connectome measurement, and the use of different network thresholding methods.

    “There were several innovative aspects of this study, including connectome measurement in an AD mouse model, multimodal connectome measurement, and the use of different network thresholding methods.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    The small sample may have reduced power to detect certain effects.

    “This study is also limited by the small sample, which may have reduced our power to detect certain effects.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationreasoning

    A different parcellation approach may yield alternate results.

    “and therefore a different approach may yield alternate results.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Currently there is no standard regarding the parcellation scheme for connectome analyses.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation

    The presence of hubs in the mouse brain is consistent with other studies.

    “This is consistent with other studies showing presence of hubs in the mouse brain (Liska et al., 2015; Rubinov, Ypma, Watson, & Bullmore, 2015).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites Liska et al., 2015 source
    • cites Rubinov, Ypma, Watson, & Bullmore, 2015 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    fMRI and DTI were acquired at different MRI field strengths.

    “Another drawback is that fMRI and DTI were acquired at different MRI field strengths.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Previous studies have suggested that AD pathogenesis may selectively target certain hub regions.

    “Previous studies have suggested that AD pathogenesis may selectively target certain hub regions (Dai et al., 2015; Stam et al., 2009; Xie & He, 2011; Yao et al., 2010; Zhou et al., 2012).”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites Dai et al., 2015

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Stam et al., 2009

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Xie & He, 2011

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    The study used a conservative statistical approach, including permutation analysis with a large number of permutations and correction for multiple comparisons where appropriate.

    “However, we used a conservative statistical approach, including permutation analysis with a large number of permutations and correction for multiple comparisons where appropriate.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Interpretationnone given

    DTI connectome properties have been shown to differentiate patient groups and therefore seem to provide valuable insights regarding the effects of AD on brain networks.

    “However, as noted above, DTI connectome properties have been shown to differentiate patient groups and therefore seem to provide valuable insights regarding the effects of AD on brain networks.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationown data

    The lack of significant regional connectome differences may reflect limited statistical power and/or may indicate diffuse regional effects.

    “This may again reflect limited statistical power and/or may indicate diffuse regional effects.”
    Quote in the paperNot a substantial claim
34 of 34

  • The paper relies on this without support.

    Few if any studies have examined connectome organization in transgenic AD mice or any disease group.

    “Few if any studies have examined connectome organization in transgenic AD mice or any disease group.”

  • The paper relies on this without support.

    Few if any studies have compared connectomes in rodent models of disease groups.

    “Few if any studies have compared connectomes in rodent models of disease groups.”

  • The paper relies on this without support.

    This is the first study to evaluate connectome organization in an AD mouse model.

    “To our knowledge, this is the first study to evaluate connectome organization in an AD mouse model.”

  • The paper relies on this without support.

    There tends to be a large difference in network densities between rsfMRI- and DTI-derived connectomes.

    “Further, there tends to be a large difference in network densities between rsfMRI- and DTI-derived connectomes.”

  • The paper relies on this without support.

    5XFAD mice demonstrate accelerated amyloid deposition and have an early onset, aggressive disease presentation.

    “These mice demonstrate accelerated amyloid deposition and have an early onset, aggressive disease presentation.”

  • The paper relies on this without support.

    The 5XFAD mouse model used in this study is associated with accelerated amyloid-beta pathology.

    “The 5XFAD mouse model used in this study is associated with accelerated amyloid-beta pathology.”

  • The paper relies on this without support.

    5XFAD mice do not have significant tau pathology.

    “5XFAD do not have significant tau pathology.”

  • The paper relies on this without support.

    The 5XFAD mice were evaluated at an age prior to significant neuronal and synaptic loss.

    “We evaluated the 5XFAD mice at an age prior to significant neuronal and synaptic loss”

  • The paper relies on this without support.

    Currently there is no standard regarding the parcellation scheme for connectome analyses.

    “Currently there is no standard regarding the parcellation scheme for connectome analyses”
9 of 9

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Aβ mouse model of amyloidosis (5XFAD mice) also showed a decreased network efficiency.

    “In addition, Aβ mouse model of amyloidosis (5XFAD mice) also showed a decreased network efficiency (Kesler et al., 2018).”

    From Disrupted structural connectivity in ArcAβ mouse model of Aβ amyloidosis (2020) · cites this paper as Kesler et al., 2018

    The Discussion explicitly says that decreased network efficiency, reported in patients with AD, was not observed in the 5XFAD mice. The paper reports other connectome differences, including higher characteristic path length, but does not equate those findings with decreased efficiency. (LLM, conf=0.95)

    Checked by a reasoning model — may be wrong.

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Discussion attributes a path-length increase to weighted functional networks

    Minor

    The Results report higher functional characteristic path length at minimum connection density after thresholding and excluding one transgenic mouse. They report no significant group differences for weighted functional connectomes, so the Discussion assigns the finding to the wrong network analysis.

1 of 1

Cites

Flagged first, then by citations

2 of the 95 references couldn’t be matched to a known paper.

Research works printed but not linked: 5

  1. Boveroux P., 2010, Journal of the American Society of Anesthesiologists, 113, 1038
  2. Gorges M., 2017, Frontiers in Neurology, 8
  3. Prince M., 2015, World Alzheimer report 2015: The global impact of dementia
  4. Tijms B. M., 2015, Neurobiology of Aging
  5. Xie T., 2011, Frontiers in Psychiatry, 2, 77

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Related

Authors
Kesler, S. R., Acton, P., Rao, V., & Ray, W. J.
Affiliations
The University of Texas MD Anderson Cancer Center (US)
ORCID
Venue
Network Neuroscience
Publisher
MIT Press
Published
2018-06
Volume
2
Issue
2
Pages
241-258
ISSN
2472-1751 (ISSN-L)
DOI
10.1162/netn_a_00048
PMC
PMC6130552
OpenAlex
W2791373153
Semantic Scholar
6bbe04bb8593dacec340e908e32dd8e273b1e90b
Cited by
34
References
95
Citations by year
2026: 1 · 2025: 6 · 2024: 5 · 2023: 4 · 2022: 5 · 2021: 4 · 2020: 2 · 2019: 3 · 2018: 4
FWCI
1.79
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Network Neuroscience (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (submittedVersion, cc-by)
  • PubMed Central (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • The Neurodegeneration Consortium
  • The MD Anderson Foundation
  • National Cancer Institute (1R03CA191559, 1R01CA172145)
  • National Institute of Nursing Research (1R01NR014195)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Keywords
Alzheimer's disease, 5xFAD mice, connectome, structural connectivity, functional connectivity, amyloid-beta, graph theory, small-world networks, network topology, diffusion tensor imaging, resting-state fMRI

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-24.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-24.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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