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CATEGORIES:Computational Neuroscience
SUMMARY:Mapping affective decisions in depression using re
 inforcement learning tools - Quentin Huys (Gatsby 
 Computational Neuroscience Unit\, UCL)
DTSTART;TZID=Europe/London:20100505T163000
DTEND;TZID=Europe/London:20100505T173000
UID:TALK24760AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/24760
DESCRIPTION:Most decision problems the brain faces are fantast
 ically hard. I will describe three different gener
 al solution strategies that are well described at 
 neural\, behavioural and computational level\, and
  show how each of these can elucidate important as
 pects of decision making in depression. First\, co
 ncentrating on habitual learning\, we will apply a
  simple TD-like learning model to a large dataset 
 of 392 subjects in a simple asymmetrically rewarde
 d decision making task (due to Diego Pizzagalli). 
 This allows for a detailed analysis relating the e
 ffect of dopamine\, stress and depression to the p
 rocessing of rewards. Second\, we will present a B
 ayesian model of learned helplessness. We show tha
 t the prior belief about the extent to which the e
 nvironment is controllable has profound impacts on
  goal-directed choice behaviour\, and that this is
  related specifically to psychometric measures of 
 hopelessness in subjects suffering from recurrent 
 depression. Finally\, we will discuss the role of 
 serotonin in behavioural inhibition. Computational
 ly	separating the effects of behavioural inhibitio
 n during learning and later during behaviour allow
 s for insights into the prozac paradox: the fact t
 hat	5HTTLPR polymorphisms and SSRIs seem to do the
  same yet have opposite effects on depression. Fur
 thermore\, considering the relationship between se
 rotonin and innate\, evolutionarily acquired Pavlo
 vian responses hints at a possible reason for the 
 co-morbidities between mood and anxiety disorders.
LOCATION:Cambridge University Engineering Department\, CBL 
 Rm #438 (http://learning.eng.cam.ac.uk/Public/Dire
 ctions)
CONTACT:Prof Máté Lengyel
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