Characterisation of a computationally defined treatment target for anxiety and depression
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 computat...
Main Authors: | Browning, M, Pulcu, E |
---|---|
格式: | Conference item |
出版: |
Elsevier
2017
|
相似書籍
-
Using computational psychiatry to rule out the hidden causes of depression
由: Pulcu, E, et al.
出版: (2017) -
Depression is associated with reduced outcome sensitivity in a dual valence, magnitude learning task
由: Pulcu, E, et al.
出版: (2023) -
Affective bias as a rational response to the statistics of rewards and punishments
由: Pulcu, E, et al.
出版: (2017) -
The misestimation of uncertainty in affective disorders
由: Pulcu, E, et al.
出版: (2019) -
Affective bias as a rational response to the statistics of rewards and punishments
由: Erdem Pulcu, et al.
出版: (2017-10-01)