title: Synchrony can destabilize reward-sensitive networks.
abstract: When exposed to rewarding stimuli, only some animals develop persistent craving. Others are resilient and do not. How the activity of neural populations relates to the development of persistent craving behavior is not fully understood. Previous computational studies suggest that synchrony helps a network embed certain patterns of activity, although the role of synchrony in reward-dependent learning has been less studied. Increased synchrony has been reported as a marker for both susceptibility and resilience to developing persistent craving. Here we use computational simulations to study the effect of reward salience on the ability of synchronous input to embed a new pattern of activity into a neural population. Our main finding is that weak stimulus-reward correlations can facilitate the short-term repetition of a pattern of neural activity, while blocking long-term embedding of that pattern. Interestingly, synchrony did not have this dual effect on all patterns, which suggests that synchrony is more effective at embedding some patterns of activity than others. Our results demonstrate that synchrony can have opposing effects in networks sensitive to the correlation structure of their inputs, in this case the correlation between stimulus and reward. This work contributes to an understanding of the interplay between synchrony and reward-dependent plasticity.
authors.affiliation: Department of Neuroscience, Icahn School of Medicine Mount Sinai, Friedman Brain Institute New York, NY, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Chary
authors.affiliation: Department of Neuroscience, Icahn School of Medicine Mount Sinai, Friedman Brain Institute New York, NY, USA.
authors.forename: Ehud
authors.initials: E
authors.lastname: Kaplan
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D003198:Computer Simulation; D007858:Learning / Q000502:physiology; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009473:Neuronal Plasticity / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D012201:Reward
keywords: computational models in psychiatry; cortical networks and systems; plasticity and learning; substance abuse; synchrony code