Abstract：
:Effective error-driven learning benefits from scaling of prediction errors to reward variability. Such behavioral adaptation may be facilitated by neurons coding prediction errors relative to the standard deviation (SD) of reward distributions. To investigate this hypothesis, we required participants to predict the magnitude of upcoming reward drawn from distributions with different SDs. After each prediction, participants received a reward, yielding trial-by-trial prediction errors. In line with the notion of adaptive coding, BOLD response slopes in the Substantia Nigra/Ventral Tegmental Area (SN/VTA) and ventral striatum were steeper for prediction errors occurring in distributions with smaller SDs. SN/VTA adaptation was not instantaneous but developed across trials. Adaptive prediction error coding was paralleled by behavioral adaptation, as reflected by SD-dependent changes in learning rate. Crucially, increased SN/VTA and ventral striatal adaptation was related to improved task performance. These results suggest that adaptive coding facilitates behavioral adaptation and supports efficient learning.
journal_name
Neuronjournal_title
Neuronauthors
Diederen KM,Spencer T,Vestergaard MD,Fletcher PC,Schultz Wdoi
10.1016/j.neuron.2016.04.019subject
Has Abstractpub_date
2016-06-01 00:00:00pages
1127-38issue
5eissn
0896-6273issn
1097-4199pii
S0896-6273(16)30078-2journal_volume
90pub_type
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