@phdthesis{Akhrif2023,
  author    = {Akhrif, Atae},
  title     = {The BOLD Signal is more than a Brain Activation Index},
  doi       = {10.25972/OPUS-32287},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-322879},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2023},
  abstract  = {In the recent years, translational studies comparing imaging data of animals and humans have gained increasing scientific interests with crucial findings stemming from both, human and animal work. In order to harmonize statistical analyses of data from different species and to optimize the transfer of knowledge between them, shared data acquisition protocols and combined statistical approaches have to be identified. Following this idea, methods of data analysis, which have until now mainly been used to model neural responses of electrophysiological recordings from rodent data, were applied on human hemodynamic responses (i.e. Blood-Oxygen-Level- Dependent BOLD signal) as measured via functional magnetic resonance imaging (fMRI). At the example of two attention and impulsivity networks, timing dynamics and amplitude of the fMRI signal were determined (study 1). Study 2 described the same parameters frequency-specifically, and in study 3, the complexity of neural processing was quantified in terms of fractality. Determined parameters were compared with regard to the subjects' task performance / impulsivity to validate findings with regard to reports of the current scientific debate. In a general discussion, overlapping as well as additional information of methodological approaches were discussed with regard to its potential for biomarkers in the context of neuropsychiatric disorders.},
  subject      = {funktionelle Kernspintomographie},
  language  = {en}
}
@phdthesis{Akhrif2020,
  author    = {Akhrif, Atae},
  title     = {The BOLD Signal is more than a Brain Activation Index},
  doi       = {10.25972/OPUS-20729},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-207299},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2020},
  abstract  = {In the recent years, translational studies comparing imaging data of animals and humans have gained increasing scientific interests with crucial findings stemming from both, human and animal work. In order to harmonize statistical analyses of data from different species and to optimize the transfer of knowledge between them, shared data acquisition protocols and combined statistical approaches have to be identified. Following this idea, methods of data analysis, which have until now mainly been used to model neural responses of electrophysiological recordings from rodent data, were applied on human hemodynamic responses (i.e. Blood-Oxygen-Level-Dependent BOLD signal) as measured via functional magnetic resonance imaging (fMRI). At the example of two attention and impulsivity networks, timing dynamics and amplitude of the fMRI signal were determined (study 1). Study 2 described the same parameters frequency-specifically, and in study 3, the complexity of neural processing was quantified in terms of fractality. Determined parameters were compared with regard to the subjects' task performance / impulsivity to validate findings with regard to reports of the current scientific debate. In a general discussion, overlapping as well as additional information of methodological approaches were discussed with regard to its potential for biomarkers in the context of neuropsychiatric disorders.},
  subject      = {funktionelle Kernspintomographie},
  language  = {en}
}