Information learning bias in depression
Saved in:
| Title: | Information learning bias in depression |
|---|---|
| Authors: | Lin, Wanjun |
| Committee Members: | Browning, Michael; Hunt, Laurence; Pulcu, Erdem |
| Summary: | Major depressive disorder is a mood and emotional disorder characterized by persistent low mood and lack of interest. Both reward and punishment learning deficits have been associated with depression. In this thesis, we aim to examine whether biases in reward and punishment learning adaptations to the volatility level of the environments could also be associated with depression disorders. We developed a task in which we independently manipulated the volatility of win and loss outcomes and systematically examined the underlying mechanisms of adaptive learning in depression using computational modelling, fMRI, pharmacological manipulation and pupillometry recordings. We first showed that currently depressed patients had lower loss learning rate volatility adaptations, estimated using a volatility adaptation model, compared to remitted depressed patients and healthy controls. This might be associated with reduced norepinephrine responsibility to loss outcomes, evidenced by reduced loss volatility modulation of pupil responses to loss outcomes in the currently depressed group compared to the other two groups. Using a similar volatility adaptation model, we then showed that loss learning rate adaptation estimates negatively correlated with individual differences in overall negativity levels (depression and anxiety), with might be associated with decreased segregation of win and loss volatility signals in a distributed brain network of outcome sensitive regions, especially in the ACC. Finally, we showed that manipulating norepinephrine level using an antidepressant, reboxetine, a norepinephrine reuptake inhibitor (NRIs), could increase loss learning rate adaptations to volatility. This was also associated with a reduced volatility effect on the pupil responses to loss outcomes, particularly when wins were volatile. Together, the results have provided some consistent evidence that link depression with inadequate learning adaptation to the volatility of loss outcomes which might be caused by maladaptive norepinephrine responsibility to loss outcomes. |
| URL: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.851066 |
| Database: | OpenDissertations |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: ddu DbLabel: OpenDissertations An: ddu.oai.ethos.bl.uk.851066 AccessLevel: 6 PubType: Dissertation/ Thesis PubTypeId: dissertation PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Information learning bias in depression – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Lin%2C+Wanjun%22">Lin, Wanjun</searchLink> – Name: Author Label: Committee Members Group: Au Data: <searchLink fieldCode="CO" term="%22Browning%2C+Michael%22">Browning, Michael</searchLink>; <searchLink fieldCode="CO" term="%22Hunt%2C+Laurence%22">Hunt, Laurence</searchLink>; <searchLink fieldCode="CO" term="%22Pulcu%2C+Erdem%22">Pulcu, Erdem</searchLink> – Name: Abstract Label: Summary Group: Ab Data: Major depressive disorder is a mood and emotional disorder characterized by persistent low mood and lack of interest. Both reward and punishment learning deficits have been associated with depression. In this thesis, we aim to examine whether biases in reward and punishment learning adaptations to the volatility level of the environments could also be associated with depression disorders. We developed a task in which we independently manipulated the volatility of win and loss outcomes and systematically examined the underlying mechanisms of adaptive learning in depression using computational modelling, fMRI, pharmacological manipulation and pupillometry recordings. We first showed that currently depressed patients had lower loss learning rate volatility adaptations, estimated using a volatility adaptation model, compared to remitted depressed patients and healthy controls. This might be associated with reduced norepinephrine responsibility to loss outcomes, evidenced by reduced loss volatility modulation of pupil responses to loss outcomes in the currently depressed group compared to the other two groups. Using a similar volatility adaptation model, we then showed that loss learning rate adaptation estimates negatively correlated with individual differences in overall negativity levels (depression and anxiety), with might be associated with decreased segregation of win and loss volatility signals in a distributed brain network of outcome sensitive regions, especially in the ACC. Finally, we showed that manipulating norepinephrine level using an antidepressant, reboxetine, a norepinephrine reuptake inhibitor (NRIs), could increase loss learning rate adaptations to volatility. This was also associated with a reduced volatility effect on the pupil responses to loss outcomes, particularly when wins were volatile. Together, the results have provided some consistent evidence that link depression with inadequate learning adaptation to the volatility of loss outcomes which might be caused by maladaptive norepinephrine responsibility to loss outcomes. – Name: URL Label: URL Group: URL Data: <link linkTarget="URL" linkTerm="https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.851066" linkWindow="_blank">https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.851066</link> |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ddu&AN=ddu.oai.ethos.bl.uk.851066 |
| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English Subjects: – SubjectFull: Psychiatry ; Cognitive neuroscience Type: general Titles: – TitleFull: Information learning bias in depression Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Lin, Wanjun IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2021 |
| ResultId | 1 |
