Separate amygdala subregions signal surprise and predictiveness during associative fear learning in humans

TY - JOUR

T1 - Separate amygdala subregions signal surprise and predictiveness during associative fear learning in humans

AU - Boll, Sabrina

AU - Gamer, Matthias

AU - Gluth, Sebastian

AU - Finsterbusch, Jürgen

AU - Büchel, Christian

N1 - © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

PY - 2013/3/1

Y1 - 2013/3/1

N2 - It has recently been suggested that learning signals in the amygdala might be best characterized by attentional theories of associative learning [such as Pearce-Hall (PH)] and more recent hybrid variants that combine Rescorla-Wagner and PH learning models. In these models, unsigned prediction errors (PEs) determine the associability of a cue, which is used in turn to control learning of outcome expectations dynamically and reflects a function of the reliability of prior outcome predictions. Here, we employed an aversive Pavlovian reversal-learning task to investigate computational signals derived from such a hybrid model. Unlike previous accounts, our paradigm allowed for the separate assessment of associability at the time of cue presentation and PEs at the time of outcome. We combined this approach with high-resolution functional magnetic resonance imaging to understand how different subregions of the human amygdala contribute to associative learning. Signal changes in the corticomedial amygdala and in the midbrain represented unsigned PEs at the time of outcome showing increased responses irrespective of whether a shock was unexpectedly administered or omitted. In contrast, activity in basolateral amygdala regions correlated negatively with associability at the time of cue presentation. Thus, whereas the corticomedial amygdala and the midbrain reflected immediate surprise, the basolateral amygdala represented predictiveness and displayed increased responses when outcome predictions became more reliable. These results extend previous findings on PH-like mechanisms in the amygdala and provide unique insights into human amygdala circuits during associative learning.

AB - It has recently been suggested that learning signals in the amygdala might be best characterized by attentional theories of associative learning [such as Pearce-Hall (PH)] and more recent hybrid variants that combine Rescorla-Wagner and PH learning models. In these models, unsigned prediction errors (PEs) determine the associability of a cue, which is used in turn to control learning of outcome expectations dynamically and reflects a function of the reliability of prior outcome predictions. Here, we employed an aversive Pavlovian reversal-learning task to investigate computational signals derived from such a hybrid model. Unlike previous accounts, our paradigm allowed for the separate assessment of associability at the time of cue presentation and PEs at the time of outcome. We combined this approach with high-resolution functional magnetic resonance imaging to understand how different subregions of the human amygdala contribute to associative learning. Signal changes in the corticomedial amygdala and in the midbrain represented unsigned PEs at the time of outcome showing increased responses irrespective of whether a shock was unexpectedly administered or omitted. In contrast, activity in basolateral amygdala regions correlated negatively with associability at the time of cue presentation. Thus, whereas the corticomedial amygdala and the midbrain reflected immediate surprise, the basolateral amygdala represented predictiveness and displayed increased responses when outcome predictions became more reliable. These results extend previous findings on PH-like mechanisms in the amygdala and provide unique insights into human amygdala circuits during associative learning.

KW - Adult

KW - Amygdala

KW - Association Learning

KW - Conditioning, Classical

KW - Cues

KW - Fear

KW - Humans

KW - Magnetic Resonance Imaging

KW - Male

KW - Mesencephalon

KW - Models, Neurological

U2 - 10.1111/ejn.12094

DO - 10.1111/ejn.12094

M3 - SCORING: Journal article

C2 - 23278978

VL - 37

SP - 758

EP - 767

JO - EUR J NEUROSCI

JF - EUR J NEUROSCI

SN - 0953-816X

IS - 5

ER -