April 6, 2018
11:30AM - 12:30PM
Psych Bldg 035
Add to Calendar
2018-04-06 11:30:00
2018-04-06 12:30:00
Colloquium - Nicholas Turk-Browne, PhD, Yale University
Rethinking memory systems for statistical learning
Dogma states that memory can be divided into distinct types, based on whether conscious
or not, one-shot or statistical, autobiographical or factual, sensory or motor, etc.
These distinctions have been supported by dissociations in brain localization, task performance,
developmental trajectories, and pharmacological interventions, among other
techniques. A natural consequence is the assumption of a one-to-one mapping between
brain systems and memory behaviors. Aside from theoretical concerns about dissociation
logic, there have also now been several empirical demonstrations of where these
boundaries break down, from contributions of the hippocampus to reward learning and
motor behavior to rapid episodic-like learning in frontal cortex. These considerations
suggest that behavior is overdetermined by multiple memory systems. As a case study, I
will describe a series of neuroimaging, neuropsychological, and computational studies
implicating the hippocampal system in statistical learning, a function more traditionally
ascribed to cortical systems. I will end by considering some open questions that arise
from this perspective, including about how the function and balance of memory systems
changes over development and how multiple memory signals are integrated to guide
behavior.
Psych Bldg 035
OSU ASC Drupal 8
ascwebservices@osu.edu
America/New_York
public
Date Range
Add to Calendar
2018-04-06 11:30:00
2018-04-06 12:30:00
Colloquium - Nicholas Turk-Browne, PhD, Yale University
Rethinking memory systems for statistical learning
Dogma states that memory can be divided into distinct types, based on whether conscious
or not, one-shot or statistical, autobiographical or factual, sensory or motor, etc.
These distinctions have been supported by dissociations in brain localization, task performance,
developmental trajectories, and pharmacological interventions, among other
techniques. A natural consequence is the assumption of a one-to-one mapping between
brain systems and memory behaviors. Aside from theoretical concerns about dissociation
logic, there have also now been several empirical demonstrations of where these
boundaries break down, from contributions of the hippocampus to reward learning and
motor behavior to rapid episodic-like learning in frontal cortex. These considerations
suggest that behavior is overdetermined by multiple memory systems. As a case study, I
will describe a series of neuroimaging, neuropsychological, and computational studies
implicating the hippocampal system in statistical learning, a function more traditionally
ascribed to cortical systems. I will end by considering some open questions that arise
from this perspective, including about how the function and balance of memory systems
changes over development and how multiple memory signals are integrated to guide
behavior.
Psych Bldg 035
Department of Psychology
ASC-psychmainoffice@osu.edu
America/New_York
public
Rethinking memory systems for statistical learning
Dogma states that memory can be divided into distinct types, based on whether conscious
or not, one-shot or statistical, autobiographical or factual, sensory or motor, etc.
These distinctions have been supported by dissociations in brain localization, task performance,
developmental trajectories, and pharmacological interventions, among other
techniques. A natural consequence is the assumption of a one-to-one mapping between
brain systems and memory behaviors. Aside from theoretical concerns about dissociation
logic, there have also now been several empirical demonstrations of where these
boundaries break down, from contributions of the hippocampus to reward learning and
motor behavior to rapid episodic-like learning in frontal cortex. These considerations
suggest that behavior is overdetermined by multiple memory systems. As a case study, I
will describe a series of neuroimaging, neuropsychological, and computational studies
implicating the hippocampal system in statistical learning, a function more traditionally
ascribed to cortical systems. I will end by considering some open questions that arise
from this perspective, including about how the function and balance of memory systems
changes over development and how multiple memory signals are integrated to guide
behavior.