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@INPROCEEDINGS{Amunts:863674,
      author       = {Amunts, Julia and Camilleri, Julia and Eickhoff, Simon and
                      Patil, Kaustubh and Heim, Stefan and Weis, Susanne},
      title        = {{P}redicting verbal fluency performance from executive
                      functions tests: {A} study in healthy subjects},
      reportid     = {FZJ-2019-03680},
      year         = {2019},
      abstract     = {Verbal fluency (VF) tasks are a common diagnostic tool in
                      neuropsychological assessment for testing executive
                      functions (EFs) and are part of several diagnostic batteries
                      in the clinical context. Interindividual differences like
                      age or sex impact performance of EFs leading to ambiguous
                      results concerning the relationship between EFs and VF.
                      Thus, the question of which subdomains of EFs impact on VF
                      tasks remains inconclusive. The present study examines
                      whether VF can be predicted on the basis of EF test
                      performance and aims to find out which variables have most
                      impact on prediction analysis.We tested 235 monolingual
                      German speaking healthy subjects (94 males, aged 20-55) with
                      13 EF tests and 3 VF tasks. These VF tests included two
                      simple and one switching task. Each task was performed for
                      two minutes and the total sum of corrects words was
                      calculated. Additionally, saliva samples were collected to
                      analyze for sex hormone levels and stress. Data were
                      adjusted for sex and age by linear regression and analyses
                      were computed on the residuals. For prediction analysis a
                      Relevance Vector Machine (RVM) approach with 500
                      replications and a 10-fold cross-validation was computed.
                      Prediction performance was assessed by computing the
                      correlation between real and predicted values. Variables
                      that had a non-zero weight in at least $80\%$ of all models
                      are considered to have the most influenced prediction
                      performance.A significant correlation was observed between
                      true and predicted values (r = 0.25; p < 0.001) and 9 EF
                      tests exhibited non-zero weights in more than $80\%$ of the
                      models. Out of these, the Stroop test, WAF-G (divided
                      attention), Raven´s Matrices test, Corsi and Wisconsin Card
                      Sorting test had at least $95\%$ non-zero weights. Stroop
                      contributed 3 features and WAF-G 2 out of the 9 relevant EFs
                      features. With regards to non-EFs features, Cortisol and
                      Estradiol had a high impact on prediction performance
                      $(100\%).Results$ of this study indicate that scores
                      obtained from tasks testing inhibition and updating are
                      representative to reflect VF performance. These findings
                      concur with previous studies which infer that updating
                      ability might be involved in VF when keeping track of
                      already spoken words to avoid errors and repetitions, while
                      inhibition might be needed to suppress repeated or
                      irrelevant responses. Additionally, together with other
                      studies, this study elucidates the impact of hormones on EFs
                      but also on VF performance. Previous studies have shown that
                      the menstrual cycle phase impacts accuracy and processing
                      speed in EFs test while the effects of cortisol are still
                      inconclusive.},
      month         = {Jun},
      date          = {2019-06-25},
      organization  = {INM/ICS retreat 2019, Jülich
                       (Germany), 25 Jun 2019 - 26 Jun 2019},
      subtyp        = {After Call},
      cin          = {INM-7 / INM-1},
      cid          = {I:(DE-Juel1)INM-7-20090406 / I:(DE-Juel1)INM-1-20090406},
      pnm          = {571 - Connectivity and Activity (POF3-571) / 572 -
                      (Dys-)function and Plasticity (POF3-572) / 574 - Theory,
                      modelling and simulation (POF3-574)},
      pid          = {G:(DE-HGF)POF3-571 / G:(DE-HGF)POF3-572 /
                      G:(DE-HGF)POF3-574},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/863674},
}