Off-campus UMass Amherst users: To download campus access dissertations, please use the following link to log into our proxy server with your UMass Amherst user name and password.
Non-UMass Amherst users: Please talk to your librarian about requesting this dissertation through interlibrary loan.
Dissertations that have an embargo placed on them will not be available to anyone until the embargo expires.
Author ORCID Identifier
https://orcid.org/0000-0001-9200-9923
AccessType
Open Access Dissertation
Document Type
dissertation
Degree Name
Doctor of Philosophy (PhD)
Degree Program
Neuroscience and Behavior
Year Degree Awarded
2023
Month Degree Awarded
May
First Advisor
Rebecca Spencer
Second Advisor
Agnes Lacreuse
Third Advisor
Ilia Karatsoreos
Fourth Advisor
Stephanie Padillas
Subject Categories
Behavioral Neurobiology | Cognitive Neuroscience | Computational Neuroscience
Abstract
Creating memories is a fundamental challenge for the human brain. To create memories, defining features of experiences must be stored distinguishably without forgetting other memories. Memory associations represent co-occurring features and defining features across experiences. Memory associations are represented as networks of information that are stored in the brain. New memory associations are encoded during experiences and can be used to update existing memory associations during offline intervals. However, the mechanisms that underlie how encoded memory associations are stored within existing networks during offline intervals remains unclear. The experiments in this dissertation address a significant theoretical gap in understanding the mechanisms that underlie how encoded memory associations strengthen, weaken, or otherwise modify existing memory associations during offline consolidation intervals spent asleep and awake.
Two experiments were conducted. For both experiments, strong and weaker memory associations were selected using normative strength metrics. Changes in memories were compared between items with strong and weaker memory associations. Following offline consolidation intervals spent asleep or awake at home, Experiment 1 examined changes in recognition performance and perceived relatedness. Since memory associations constantly undergo changes, Experiment 2 further compared behavioral changes prior to and following a period of sleep monitored in the lab. The results from Experiment 1 provide evidence that encoded memory associations modify unencoded memory associations following offline intervals spent asleep and awake. After both offline intervals, encoded and unencoded strong memory associations were more easily recognized than weaker associations. Perceived relatedness decreased significantly less for strong compared to weaker memory associations. Strong associations with stronger competitors were rated as less closely related to their respective themes. Likewise, the results from Experiment 2 demonstrate that before sleeping, individuals correctly recognized encoded memory associations and falsely recognized unencoded memory associations more often for strong compared to weaker associates. After sleeping, unencoded strong memory associations were also strengthened more than unencoded weaker and other memory associations. Unexpectedly, sleep physiology did not predict consolidation. Taken together, these results demonstrate that encoded memory associations modify the strength of unencoded memory associations proportionally to the strength of other memory associations in the same memory networks offline.
DOI
https://doi.org/10.7275/34760003
Recommended Citation
Kainec, Kyle A., "The Consolidation of Memory Associations" (2023). Doctoral Dissertations. 2822.
https://doi.org/10.7275/34760003
https://scholarworks.umass.edu/dissertations_2/2822
Included in
Behavioral Neurobiology Commons, Cognitive Neuroscience Commons, Computational Neuroscience Commons