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Characterisation of a computationally defined treatment target for anxiety and depression

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Conference abstract
Abstract:

Preferential learning from negative at the expense of positive events, has been causally linked to anxiety and depression. This suggests that interventions which target such negative learning bias may reduce symptoms of the illness, although the best way to achieve this is not clear. Recent computational work suggests that people preferentially learn from outcomes with high information content (i.e. which improve prediction of the future), and that central norepinephrine acts to report the in...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted Manuscript

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Publisher copy:
10.1016/j.biopsych.2017.02.927

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Institution:
University of Oxford
Department:
Psychiatry
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Institution:
University of Oxford
Department:
Psychiatry
Publisher:
Elsevier Publisher's website
Volume:
81
Issue:
10
Pages:
S181
Publication date:
2017-05-15
Acceptance date:
2017
DOI:
ISSN:
0006-3223
Pubs id:
pubs:715243
URN:
uri:e2f50f78-7c20-417b-9d98-b8abebcccbb6
UUID:
uuid:e2f50f78-7c20-417b-9d98-b8abebcccbb6
Local pid:
pubs:715243

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