Assessing and remediating altered reinforcement learning in depression

Major depressive disorder is a common, impairing disease, but current treatments are only moderately effective. Understanding how processes such as reward and punishment learning are disrupted in depression and how these disruptions are remediated through treatment is vital to improving outcomes for people with this disorder. In the present set of studies, computational reinforcement learning models and neuroimaging were used to understand how symptom clusters of depression (anhedonia and negative affect) were related to neural and behavioral measures of learning (Study 1, in Paper 1), how these alterations changed with improvement in symptoms after cognitive behavioral therapy (Study 2, in Paper 1), and how learning parameters could be directly altered in a learning retraining paradigm (Study 3, in Paper 2). Results showed that anhedonia and negative affect were uniquely related to changes in learning and that improvement in these symptoms correlated with changes in learning parameters; these parameters could also be changed through targeted queries based on reinforcement learning theory. These findings add important information to how learning is disrupted in depression and how current and novel treatments can remediate learning and improve symptoms.

Name thesis:degree_name

Ph. D.

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Psychology

Department dc:contributor.department

Psychology

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2018

Author dc:creator

• Brown, Vanessa

Chair dc:contributor.committeechair

• Chiu, Pearl H.

Committee members dc:contributor.committeemember

• Casas, Brooks
• Ollendick, Thomas H.
• Richey, John A.

• Depression
• Reinforcement Learning
• fMRI
• Cognitive Behavioral Therapy
• Computational Modeling
• Computational Psychiatry

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:14404

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/96227