title: Population coding of reward magnitude in the orbitofrontal cortex of the rat.
abstract: Although single-cell coding of reward-related information in the orbitofrontal cortex (OFC) has been characterized to some extent, much less is known about the coding properties of orbitofrontal ensembles. We examined population coding of reward magnitude by performing ensemble recordings in rat OFC while animals learned an olfactory discrimination task in which various reinforcers were associated with predictive odor stimuli. Ensemble activity was found to represent information about reward magnitude during several trial phases, namely when animals moved to the reward site, anticipated reward during an immobile period, and received it. During the anticipation phase, Bayesian and template-matching reconstruction algorithms decoded reward size correctly from the population activity significantly above chance level (highest value of 43 and 48%, respectively; chance level, 33.3%), whereas decoding performance for the reward delivery phase was 76 and 79%, respectively. In the anticipation phase, the decoding score was only weakly dependent on the size of the neuronal group participating in reconstruction, consistent with a redundant, distributed representation of reward information. In contrast, decoding was specific for temporal segments within the structure of a trial. Decoding performance steeply increased across the first few trials for every rewarded odor, an effect that could not be explained by a nonspecific drift in response strength across trials. Finally, when population responses to a negative reinforcer (quinine) were compared with sucrose reinforcement, coding in the delivery phase appeared to be related to reward quality, and thus was not based on ingested liquid volume.
authors: Cognitive and Systems Neuroscience Group, Center for Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 SM Amsterdam, The Netherlands.
authors: Esther
authors: E
authors: van Duuren
authors: Jan
authors: J
authors: Lankelma
authors: Cyriel M A
authors: CM
authors: Pennartz
mesh_terms: D000465:Algorithms; D000818:Animals; D001066:Appetite; D001362:Avoidance Learning / Q000502:physiology; D001499:Bayes Theorem; D001522:Behavior, Animal; D004192:Discrimination, Psychological / Q000502:physiology; D004326:Drinking; D004594:Electrophysiology; D005625:Frontal Lobe / Q000502:physiology*; D008297:Male; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D009812:Odorants; D011237:Predictive Value of Tests; D011803:Quinine; D051381:Rats; D017208:Rats, Wistar; D012054:Reinforcement, Psychology; D012201:Reward; D012903:Smell / Q000502:physiology; D012996:Solutions; D013395:Sucrose; D013997:Time Factors
chemical_list: D012996:Solutions; D013395:Sucrose; D011803:Quinine