Min-Yoon Park

Entering Class - 2013

E-MAIL: park1133@umn.edu

Undergraduate Institution and Major:

  • Yonsei University (South Korea), B.S. in Biology, 2009
  • Yonsei University (South Korea), M.S. in Systems Biology, 2011

Graduate Advisor:

Matthew Chafee, Ph.D., Department of Neuroscience

Thesis Committee Members:

Description of Graduate Research:

Categorization is the ability to classify objects or ideas into certain groups depending on their common properties. Categorization can be a simple object classification depending on their own features, absolute categorization, or can be an abstract concept classification depending on various relationships between objects, relational categorization. Because relational categorization requires understanding relationships between objects based on their absolute features, for instance, location (right/left, above/below) or size(bigger/smaller), it is an essential cognitive function that allows us to predict future status, to infer, to make decisions, and to acquire knowledge. In spite of its fundamental importance, most of categorization studies have focused on absolute categorization. We have little understanding how the brain learns relational categories and how the brain uses the learned relational categories to predict future status or to make decisions. To approach these questions, my research will relate psychometric and neurometric functions in relational categorization to confirm that the neural signals encode the actual relationships between objects. Also, we will contrast categorization representation in prefrontal cortex under passive and active categorization conditions to determine the influence of the requirement for operant response on category representation. Furthermore, we will characterize how feature dimensions relevant to different categorization rules are selectively encoded by prefrontal neurons. Lastly, we will isolate neural correlates to predict sensory changes based on the learned relational categories in prefrontal circuits.

Research Areas:

  • Behavioral and Cognitive Neuroscience
  • Computational Neuroscience
  • Visual Neuroscience

Graduate Level Awards and Honors:

  • 3M Science and Technology Fellowship, 2013

Professional Presentations:

  • Neural correlates of category learning in the prefrontal-parietal network (2017). University of Minnesota Graduate Program in Neuroscience colloquium series, Minneapolis, MN.
  • Neural encoding of spatial relationships in the prefrontal-parietal network (2016). University of Minnesota Graduate Program in Neuroscience colloquium series, Minneapolis, MN.


Why Did You Choose UMN?

The UMN neuroscience program is one of the biggest neuroscience graduate programs. You can do research in various fields, and there is a wide range of choices of laboratories open to you.

What Advice Would You Give A First Year Graduate Student?

The first year is important and very busy because of lab rotations and the amount of studying one has to do. Therefore, time management and prioritization of your to-do list is necessary for success.

Min-Yoon Park