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Neurobiol Aging. 2018 Jan;61:36-43. doi: 10.1016/j.neurobiolaging.2017.08.026. Epub 2017 Sep 5.

Aging and a genetic KIBRA polymorphism interactively affect feedback- and observation-based probabilistic classification learning.

Author information

1
Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA; Max Planck Research Group NeuroCode and Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany. Electronic address: schuck@mpib-berlin.mpg.de.
2
Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, Newark, NJ, USA; Department of Psychology, Saint Olaf College, Northfield, MN, USA. Electronic address: petok@stolaf.edu.
3
Department of Cognitive Psychology, VU University, Amsterdam, the Netherlands.
4
Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Neuropsychiatric Genetics Group, Berlin, Germany.
5
Max Planck Research Group NeuroCode and Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Neuropsychiatric Genetics Group, Berlin, Germany.
6
Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Neuropsychiatric Genetics Group, Berlin, Germany; Platform for Genome Analytics, Institutes of Neurogenetics and Integrative & Experimental Genomics, University of Lübeck, Lübeck, Germany; Neuroepidemiology and Ageing Research Unit, School of Public Health, Faculty of Medicine, The Imperial College of Science, Technology, and Medicine, London, UK.
7
Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, Newark, NJ, USA.
8
Max Planck Research Group NeuroCode and Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany; Technische Universität Dresden, Department of Psychology, Chair of Lifespan Developmental Neuroscience, Dresden, Germany.

Abstract

Probabilistic category learning involves complex interactions between the hippocampus and striatum that may depend on whether acquisition occurs via feedback or observation. Little is known about how healthy aging affects these processes. We tested whether age-related behavioral differences in probabilistic category learning from feedback or observation depend on a genetic factor known to influence individual differences in hippocampal function, the KIBRA gene (single nucleotide polymorphism rs17070145). Results showed comparable age-related performance impairments in observational as well as feedback-based learning. Moreover, genetic analyses indicated an age-related interactive effect of KIBRA on learning: among older adults, the beneficial T-allele was positively associated with learning from feedback, but negatively with learning from observation. In younger adults, no effects of KIBRA were found. Our results add behavioral genetic evidence to emerging data showing age-related differences in how neural resources relate to memory functions, namely that hippocampal and striatal contributions to probabilistic category learning may vary with age. Our findings highlight the effects genetic factors can have on differential age-related decline of different memory functions.

KEYWORDS:

Aging; Hippocampus; KIBRA; Probabilistic classification; Striatum; Weather prediction task

PMID:
29032191
PMCID:
PMC5705462
[Available on 2019-01-01]
DOI:
10.1016/j.neurobiolaging.2017.08.026
[Indexed for MEDLINE]

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