TY - JOUR
T1 - Reversal learning reveals cognitive deficits and altered prediction error encoding in the ventral striatum in Huntington’s disease
AU - Nickchen, Katharina
AU - Boehme, Rebecca
AU - del Mar Amador, Maria
AU - Hälbig, Thomas D.
AU - Dehnicke, Katharina
AU - Panneck, Patricia
AU - Behr, Joachim
AU - Prass, Konstantin
AU - Heinz, Andreas
AU - Deserno, Lorenz
AU - Schlagenhauf, Florian
AU - Priller, Josef
N1 - Publisher Copyright:
© 2016, Springer Science+Business Media New York.
PY - 2017/12/1
Y1 - 2017/12/1
N2 - Huntington’s disease (HD) is an autosomal dominant neurodegenerative condition characterized by a triad of movement disorder, neuropsychiatric symptoms and cognitive deficits. The striatum is particularly vulnerable to the effects of mutant huntingtin, and cell loss can already be found in presymptomatic stages. Since the striatum is well known for its role in reinforcement learning, we hypothesized to find altered behavioral and neural responses in HD patients in a probabilistic reinforcement learning task performed during functional magnetic resonance imaging. We studied 24 HD patients without central nervous system (CNS)-active medication and 25 healthy controls. Twenty HD patients and 24 healthy controls were able to complete the task. Computational modeling was used to calculate prediction error values and estimate individual parameters. We observed that gray matter density and prediction error signals during the learning task were related to disease stage. HD patients in advanced disease stages appear to use a less complex strategy in the reversal learning task. In contrast, HD patients in early disease stages show intact encoding of learning signals in the degenerating left ventral striatum. This effect appears to be lost with disease progression.
AB - Huntington’s disease (HD) is an autosomal dominant neurodegenerative condition characterized by a triad of movement disorder, neuropsychiatric symptoms and cognitive deficits. The striatum is particularly vulnerable to the effects of mutant huntingtin, and cell loss can already be found in presymptomatic stages. Since the striatum is well known for its role in reinforcement learning, we hypothesized to find altered behavioral and neural responses in HD patients in a probabilistic reinforcement learning task performed during functional magnetic resonance imaging. We studied 24 HD patients without central nervous system (CNS)-active medication and 25 healthy controls. Twenty HD patients and 24 healthy controls were able to complete the task. Computational modeling was used to calculate prediction error values and estimate individual parameters. We observed that gray matter density and prediction error signals during the learning task were related to disease stage. HD patients in advanced disease stages appear to use a less complex strategy in the reversal learning task. In contrast, HD patients in early disease stages show intact encoding of learning signals in the degenerating left ventral striatum. This effect appears to be lost with disease progression.
KW - Gray matter density
KW - Huntington’s disease
KW - Reinforcement learning
KW - Ventral striatum
UR - http://www.scopus.com/inward/record.url?scp=85002444247&partnerID=8YFLogxK
U2 - 10.1007/s11682-016-9660-0
DO - 10.1007/s11682-016-9660-0
M3 - Article
C2 - 27917451
AN - SCOPUS:85002444247
SN - 1931-7557
VL - 11
SP - 1862
EP - 1872
JO - Brain Imaging and Behavior
JF - Brain Imaging and Behavior
IS - 6
ER -