Partial Adaptation of Obtained and Observed Value Signals Preserves Information about Gains and Losses.
Given that the range of rewarding and punishing outcomes of actions is large but neural coding capacity is limited, efficient processing of outcomes by the brain is necessary. One mechanism to increase efficiency is to rescale neural output to the range of outcomes expected in the current context, and process only experienced deviations from this expectation. However, this mechanism comes at the cost of not being able to discriminate between unexpectedly low losses when times are bad versus unexpectedly high gains when times are good. Thus, too much adaptation would result in disregarding information about the nature and absolute magnitude of outcomes, preventing learning about the longer-term value structure of the environment. Here we investigate the degree of adaptation in outcome coding brain regions in humans, for directly experienced outcomes and observed outcomes. We scanned participants while they performed a social learning task in gain and loss blocks. Multivariate pattern analysis showed two distinct networks of brain regions adapt to the most likely outcomes within a block. Frontostriatal areas adapted to directly experienced outcomes, whereas lateral frontal and temporoparietal regions adapted to observed social outcomes. Critically, in both cases, adaptation was incomplete and information about whether the outcomes arose in a gain block or a loss block was retained. Univariate analysis confirmed incomplete adaptive coding in these regions but also detected nonadapting outcome signals. Thus, although neural areas rescale their responses to outcomes for efficient coding, they adapt incompletely and keep track of the longer-term incentives available in the environment.



Optimal value-based choice requires that the brain precisely and efficiently represents positive and negative outcomes. One way to increase efficiency is to adapt responding to the most likely outcomes in a given context. However, too strong adaptation would result in loss of precise representation (e.g., when the avoidance of a loss in a loss-context is coded the same as receipt of a gain in a gain-context). We investigated an intermediate form of adaptation that is efficient while maintaining information about received gains and avoided losses. We found that frontostriatal areas adapted to directly experienced outcomes, whereas lateral frontal and temporoparietal regions adapted to observed social outcomes. Importantly, adaptation was intermediate, in line with influential models of reference dependence in behavioral economics.
Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3DY, United Kingdom, Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich, 8006 Zurich, Switzerland, and christopher.burke@econ.uzh.ch.
Christopher J
CJ
Burke
University College London, London WC1E 7HB, United Kingdom.
Michelle
0000-0001-7884-0374
M
Baddeley
Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3DY, United Kingdom, Laboratory for Social and Neural Systems Research, Department of Economics, University of Zurich, 8006 Zurich, Switzerland, and.
Philippe N
0000-0002-4915-9448
PN
Tobler
Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3DY, United Kingdom.
Wolfram
0000-0002-8530-4518
W
Schultz
D000222:Adaptation, Physiological / Q000502:physiology*; D000293:Adolescent; D000328:Adult; D002540:Cerebral Cortex / Q000502:physiology*; D002755:Choice Behavior / Q000502:physiology*; D004193:Discrimination Learning / Q000502:physiology*; D005108:Extinction, Psychological / Q000502:physiology; D005260:Female; D006801:Humans; D008297:Male; D008568:Memory / Q000502:physiology; D009415:Nerve Net / Q000502:physiology; D012201:Reward; D000067570:Social Learning / Q000502:physiology*; D055815:Young Adult
adaptive coding; context; reference dependence; reward
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