A Network Analysis of Digital Clock Drawing for Command and Copy Conditions

Brandon Frank, Sabyasachi Bandyopadhyay, Catherine Dion, Erin Formanski, Emily Matusz, Dana Penney, Randall Davis, Maureen K. O’Connor, Rhoda Au, Shawna Amini, Parisa Rashidi, Patrick Tighe, David J. Libon, Catherine C. Price

Research output: Contribution to journalArticlepeer-review


Graphomotor and time-based variables from the digital Clock Drawing Test (dCDT) characterize cognitive functions. However, no prior publications have quantified the strength of the associations between digital clock variables as they are produced. We hypothesized that analysis of the production of clock features and their interrelationships, as suggested, will differ between the command and copy test conditions. Older adults aged 65+ completed a digital clock drawing to command and copy conditions. Using a Bayesian hill-climbing algorithm and bootstrapping (10,000 samples), we derived directed acyclic graphs (DAGs) to examine network structure for command and copy dCDT variables. Although the command condition showed moderate associations between variables ((Formula presented.) = 0.34) relative to the copy condition ((Formula presented.) = 0.25), the copy condition network had more connections (18/18 versus 15/18 command). Network connectivity across command and copy was most influenced by five of the 18 variables. The direction of dependencies followed the order of instructions better in the command condition network. Digitally acquired clock variables relate to one another but differ in network structure when derived from command or copy conditions. Continued analyses of clock drawing production should improve understanding of quintessential normal features to aid in early neurodegenerative disease detection.

Original languageEnglish (US)
StateAccepted/In press - 2024

All Science Journal Classification (ASJC) codes

  • Clinical Psychology
  • Applied Psychology


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