Excessive discounting of future rewards has been related to a variety of risky behaviors and adverse clinical conditions. Prior work examining delay discounting in schizophrenia suggests an elevated discount rate. However, it remains uncertain whether this reflects the disease process itself or an underlying genetic vulnerability, whether it is selective for delay discounting or reflects pervasive changes in decision-making, and whether it is driven by specific clinical dimensions such as cognitive impairment. Here we investigated delay discounting, as well as loss aversion and risk aversion, in three groups: schizophrenia (SZ), unaffected first-degree family members (FM), and controls without a family history of psychosis (NC). SZ had elevated discounting, without changes in loss aversion or risk aversion. Contrary to expectations, the FM group did not show an intermediate phenotype in discounting. Higher discount rates correlated with lower cognitive performance on verbal reasoning, but this did not explain elevated discount rates in SZ. Group differences were driven primarily by the non-smoking majority of the sample. This study provides further evidence for elevated discounting in schizophrenia, and demonstrates that steeper discounting is not necessarily associated with familial risk, cannot be wholly accounted for by cognitive deficits, and is not attributable to smoking-related impulsivity.

People use information flexibly. They often combine multiple sources of relevant information over time in order to inform decisions with little or no interference from intervening irrelevant sources. They adjust the degree to which they use new information over time rationally in accordance with environmental statistics and their own uncertainty. They can even use information gained in one situation to solve a problem in a very different one. Learning flexibly rests on the ability to infer the context at a given time, and therefore knowing which pieces of information to combine and which to separate. We review the psychological and neural mechanisms behind adaptive learning and structure learning to outline how people pool together relevant information, demarcate contexts, prevent interference between information collected in different contexts, and transfer information from one context to another. By examining all of these processes through the lens of optimal inference we bridge concepts from multiple fields to provide a unified multi-system view of how the brain exploits structure in time to optimize learning.

People use information flexibly. They often combine multiple sources of relevant information over time in order to inform decisions with little or no interference from intervening irrelevant sources. They adjust the degree to which they use new information over time rationally in accordance with environmental statistics and their own uncertainty. They can even use information gained in one situation to solve a problem in a very different one. Learning flexibly rests on the ability to infer the context at a given time, and therefore knowing which pieces of information to combine and which to separate. We review the psychological and neural mechanisms behind adaptive learning and structure learning to outline how people pool together relevant information, demarcate contexts, prevent interference between information collected in different contexts, and transfer information from one context to another. By examining all of these processes through the lens of optimal inference we bridge concepts from multiple fields to provide a unified multi-system view of how the brain exploits structure in time to optimize learning.