An Analysis of Human and Monkey Task Learning Dynamics
Abstract/Contents
- Abstract
- A large part of neuroscience research is devoted to investigating how humans learn - particularly with regard to rules for category matching tasks. Though there are many non-invasive methods to gather electrophysiological data during rule-learning experiments, including fMRI, invasive methods present the opportunity to gather data at the level of individual neurons. Because running invasive procedures, such as inserting electrodes into regions of the sub-cortical brain, is both expensive and dangerous to carry out on humans, rhesus macaque monkeys are often used instead. However, is assumption that monkeys are thinking about the experiment task in the same way as humans flawed? This thesis sets out to investigate if the dynamic of task learning is a factor that needs to be more seriously considered when conducting electrophysiological studies on monkeys. To do this, behavioral data was studied to understand the learning dynamics of monkeys and humans. By comparing this behavioral data to simulations of different learning dynamics, this thesis shows that previous task learning experience has a huge impact on the dynamic of learning on monkeys. It also shows that increased data transparency and availability is needed in order to better understand the intricacies of task learning in humans and monkeys. Lastly, it shows that finding different learning dynamics should be a concern for researchers making the claim that the neural representations of tasks in monkeys and humans are similar.
Description
| Type of resource | text |
|---|---|
| Date created | September 15, 2017 |
Creators/Contributors
| Author | Selvan, Aarush |
|---|
Subjects
| Subject | category matching |
|---|---|
| Subject | rule learning |
| Subject | rhesus macaque |
| Subject | learning dynamics |
| Subject | rescorla wagner |
| Subject | transfer learning |
| Subject | jump learning |
| Subject | Symbolic Systems |
| Subject | Stanford University |
| Genre | Thesis |
Bibliographic information
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- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Preferred citation
- Preferred Citation
- Selvan, Aarush. (). An Analysis of Human and Monkey Task Learning Dynamics. Stanford Digital Repository. Available at: https://purl.stanford.edu/fj242hn1684
Collection
Master's Theses, Symbolic Systems Program, Stanford University
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- Contact
- aselvan@stanford.edu
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