Title of Research Output
Faculty
Science
Supervisor Name
Daniel Ansari and Eric D. Wilkey
Keywords
Math cognition, resting-state functional connectivity, intergenerational transmission, reading, math, reading-network, math-network
Description
The scoping review surveyed the existing literature on the topic of resting-state functional connectivity (rsFC) and mathematical cognition. The review revealed that rsFC is indicative of distinct long-term developmental trends in mathematical processing, alluding to individual differences in math abilities. Though there have been multiple studies that investigate individual differences in functional connectivity patterns related to math development and math learning disorders, no study has directly investigated to what degree these neurobiological factors are heritable. To address this topic, the following intergenerational transmission (IT) study is proposed. IT is the transfer of personal values, abilities, behaviours, and traits, from parents to children (Durlauf & Blume, 2016). A recent study conducted by Takagi et al. (2021) investigated the effects of IT via neurobiological substrates. The investigation was primarily concerned with whether identification of a parent-child dyad was possible based on brain similarity, using both structural and functional information. Using a similar method as Takagi et al., we plan to use data from the Parents and Children: Measuring Academic skills using Neuroimaging (PACMAN) project to investigate whether parent-child dyads are identifiable based on brain similarity - specifically using the reading- and math-related networks. Similar to the Takagi et al. (2021) study, we predict that parent-child dyads will be identifiable based on functional connectivity profiles localized in reading- and math-related brain networks.
Acknowledgements
The completion of my project could not have been done without the incredible mentorship of Dr. Eric Wilkey. His contributions to both projects are greatly appreciated. Thank you for your kindness and support throughout this entire process, you are the absolute best mentor.
An additional thank you to Dr. Lien Peters, as her contributions are paramount to the future of the current proposal. Her expertise and guidance have assisted me greatly during the course of the program.
Above all, thank you to my friends and family who have been so supportive throughout this internship program.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Document Type
Poster
Included in
Cognitive Neuroscience Commons, Cognitive Psychology Commons, Developmental Neuroscience Commons
Intergenerational Transmission of Functional Connectivity Profiles in Isolated Reading and Math Networks: A Scoping Review and Study Proposal
The scoping review surveyed the existing literature on the topic of resting-state functional connectivity (rsFC) and mathematical cognition. The review revealed that rsFC is indicative of distinct long-term developmental trends in mathematical processing, alluding to individual differences in math abilities. Though there have been multiple studies that investigate individual differences in functional connectivity patterns related to math development and math learning disorders, no study has directly investigated to what degree these neurobiological factors are heritable. To address this topic, the following intergenerational transmission (IT) study is proposed. IT is the transfer of personal values, abilities, behaviours, and traits, from parents to children (Durlauf & Blume, 2016). A recent study conducted by Takagi et al. (2021) investigated the effects of IT via neurobiological substrates. The investigation was primarily concerned with whether identification of a parent-child dyad was possible based on brain similarity, using both structural and functional information. Using a similar method as Takagi et al., we plan to use data from the Parents and Children: Measuring Academic skills using Neuroimaging (PACMAN) project to investigate whether parent-child dyads are identifiable based on brain similarity - specifically using the reading- and math-related networks. Similar to the Takagi et al. (2021) study, we predict that parent-child dyads will be identifiable based on functional connectivity profiles localized in reading- and math-related brain networks.