Humans routinely formulate plans in domains so complex that even the most powerful computers are taxed. To do so, they seem to avail themselves of many strategies and heuristics that efficiently simplify, approximate, and hierarchically decompose hard tasks into simpler subtasks. Theoretical and cognitive research has revealed several such strategies; however, little is known about their establishment, interaction, and efficiency. Here, we use modelbased behavioral analysis to provide a detailed examination of the performance of human subjects in a moderately deep planning task. We find that subjects exploit the structure of the domain to establish subgoals in a way that achieves a nearly maximal reduction in the cost of computing values of choices, but then combine partial searches with greedy local steps to solve subtasks, and maladaptively prune the decision trees of subtasks in a reflexive manner upon encountering salient losses. Subjects come idiosyncratically to favor particular sequences of actions to achieve subgoals, creating novel complex actions or "options."planning | hierarchical reinforcement learning | memoization | pruning H umans and other animals often face complex tasks and environments in which they have to plan and execute long sequences of appropriate actions to achieve distant goals. One can represent the space of future actions and outcomes as a tree; such trees grow inordinately (often exponentially) large as a function of the length of the sequence (i.e., the depth of the tree). Rather little is definitively known about how this computational complexity is addressed. Work in the fields of reinforcement learning and artificial intelligence has suggested a number of heuristics that we describe below, namely, hacking, hierarchies, hoarding, and habitization (1-4). Various tasks have been designed to highlight individual heuristics; though how subjects generate and combine them without clear instruction has not been well characterized (however, see refs. 5 and 6).We previously designed a moderately deep planning problem to elicit a specific heuristic, in this case hacking or pruning of the decision tree (4). However, the task contains many of the elements that make choosing appropriately tricky in general. Thus, we closely examined the nature of, and individual differences between, the performance of subjects, shedding light on the interaction of heuristics in the self-generation of adaptive control when faced with a complex planning problem.Subjects had to plan a path through a maze so as to maximize their cumulative earnings. On each trial, they were placed in a random state and were asked to plan to a depth of 3, 4, or 5 moves ( Fig. 1 A and B). Because each depth involved a binary choice, planning to depths 3, 4, and 5 corresponded to choosing among a set of 8, 16, or 32 possible sequences. We previously found that the large immediate losses at particular branch points in the tree (the red transitions) encouraged subjects to eliminate possibly lucrative subbranches beneath those points ...
Recent evidence suggests that a state of good mental health is associated with biased processing of information that supports a positively skewed view of the future. Depression, on the other hand, is associated with unbiased processing of such information. Here, we use brain imaging in conjunction with a belief update task administered to clinically depressed patients and healthy controls to characterize brain activity that supports unbiased belief updating in clinically depressed individuals. Our results reveal that unbiased belief updating in depression is mediated by strong neural coding of estimation errors in response to both good news (in left inferior frontal gyrus and bilateral superior frontal gyrus) and bad news (in right inferior parietal lobule and right inferior frontal gyrus) regarding the future. In contrast, intact mental health was linked to a relatively attenuated neural coding of bad news about the future. These findings identify a neural substrate mediating the breakdown of biased updating in major depression disorder, which may be essential for mental health.
No abstract
Serotonin (5-HT) neurotransmission is implicated in cognitive and emotional processes and a number of neuropsychiatric disorders. The use of positron emission tomography (PET) to measure ligand displacement has allowed estimation of endogenous dopamine release in the human brain; however, applying this methodology to assess central 5-HT release has proved more challenging. The aim of this study was to assess the sensitivity of a highly selective 5-HT(1A) partial agonist radioligand [(11)C]CUMI-101 to changes in endogenous 5-HT levels induced by an intravenous challenge with the selective 5-HT re-uptake inhibitor (SSRI), citalopram, in healthy human participants. We studied 15 healthy participants who underwent PET scanning in conjunction with [(11)C]CUMI-101 after receiving an intravenous infusion of citalopram 10 mg or placebo in a double-blind, crossover, randomized design. Regional estimates of binding potential (BP(ND)) were obtained by calculating total volumes of distribution (V(T)) for presynaptic dorsal raphe nucleus (DRN) and postsynaptic cortical regions. Relative to placebo, citalopram infusion significantly increased [(11)C]CUMI-101 BP(ND) at postsynaptic 5-HT(1A) receptors in several cortical regions, but there was no change in binding at 5-HT(1A) autoreceptors in the DRN. Across the postsynaptic brain regions, citalopram treatment induced a mean 7% in [(11)C]CUMI-101 BP(ND) (placebo 1.3 (0.2); citalopram 1.4 (0.2); paired t-test P=0.003). The observed increase in postsynaptic [(11)C]CUMI-101 availability identified following acute citalopram administration could be attributable to a decrease in endogenous 5-HT availability in cortical terminal regions, consistent with preclinical animal studies, in which acute administration of SSRIs decreases DRN cell firing through activation of 5-HT(1A) autoreceptors to reduce 5-HT levels in postsynaptic regions. We conclude that [(11)C]CUMI-101 may be sensitive to changes in endogenous 5-HT release in humans.
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