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@ARTICLE{Omidvarnia:909906,
      author       = {Omidvarnia, Amir and Liégeois, Raphaël and Amico, Enrico
                      and Preti, Maria Giulia and Zalesky, Andrew and Van De
                      Ville, Dimitri},
      title        = {{O}n the {S}patial {D}istribution of {T}emporal
                      {C}omplexity in {R}esting {S}tate and {T}ask {F}unctional
                      {MRI}},
      journal      = {Entropy},
      volume       = {24},
      number       = {8},
      issn         = {1099-4300},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2022-03509},
      pages        = {1148},
      year         = {2022},
      abstract     = {Measuring the temporal complexity of functional MRI (fMRI)
                      time series is one approach to assess how brain activity
                      changes over time. In fact, hemodynamic response of the
                      brain is known to exhibit critical behaviour at the edge
                      between order and disorder. In this study, we aimed to
                      revisit the spatial distribution of temporal complexity in
                      resting state and task fMRI of 100 unrelated subjects from
                      the Human Connectome Project (HCP). First, we compared two
                      common choices of complexity measures, i.e., Hurst exponent
                      and multiscale entropy, and observed a high spatial
                      similarity between them. Second, we considered four tasks in
                      the HCP dataset (Language, Motor, Social, and Working
                      Memory) and found high task-specific complexity, even when
                      the task design was regressed out. For the significance
                      thresholding of brain complexity maps, we used a statistical
                      framework based on graph signal processing that incorporates
                      the structural connectome to develop the null distributions
                      of fMRI complexity. The results suggest that the
                      frontoparietal, dorsal attention, visual, and default mode
                      networks represent stronger complex behaviour than the rest
                      of the brain, irrespective of the task engagement. In sum,
                      the findings support the hypothesis of fMRI temporal
                      complexity as a marker of cognition},
      cin          = {INM-7},
      ddc          = {510},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5253 - Neuroimaging (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5253},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {36010812},
      UT           = {WOS:000847156900001},
      doi          = {10.3390/e24081148},
      url          = {https://juser.fz-juelich.de/record/909906},
}