The prefrontal cortex (PFC) contains a dense network of serotonergic [serotonin, 5-hydroxytryptamine (5-HT)] axons, and endogenous 5-HT markedly modulates PFC neuronal function via several postsynaptic receptors. The therapeutic action of atypical antipsychotic drugs, acting mainly via 5-HT receptors, also suggests a role for serotonergic neurotransmission in cognitive functions. However, psychopharmacological studies have failed to find a consistent relationship between serotonergic transmission and cognitive functions of the PFC, including spatial working memory (SWM). Here, we built a computational network model to investigate 5-HT modulation of SWM in the PFC. We found that 5-HT modulates network's SWM performance nonmonotonically via 5-HT1A and 5-HT2A receptors, following an inverted U-shape. This relationship may contribute to blur the effects of serotonergic agents in previous SWM group-based behavioral studies. Our simulations also showed that errors occurring at low and high 5-HT concentrations are due to different network dynamics instabilities, suggesting that these 2 conditions can be distinguished experimentally based on their distinct dependency on experimental variables. We inferred specific predictions regarding the expected behavioral effects of serotonergic agents in 2 classic working-memory tasks. Our results underscore the relevance of identifying different error types in SWM tasks in order to reveal the association between neuromodulatory systems and SWM.

The orbitofrontal cortex (OFC), located in the ventral surface of the prefrontal cortex (PFC), plays a key role in emotion, reinforcement learning, and certain forms of behavioral flexibility (Kringelbach & Rolls

A Computational Model for Spatial Working Memory Defi cits in Schizophreniaindividuals, a similar network of areas, pivoting around the DLPFC, are identifi ed by neuroimaging studies as supporting working memory function [ 12 ] . Also the DLPFC has been singled out in neurophysiological experiments in non-human primates as the locus of persistent activity, the substrate of working memory maintenance in delayed response tasks [ 13 , 14 ] . The convergent evidence from neuroimaging and neurophysiological studies that links circuit dynamics in the DLPFC to working memory has motivated computational eff orts to formulate explicit biological models of the mechanisms that support working memory in DLPFC. In the last 2 decades, several biophysical computational models have been proposed to explain persistent prefrontal neural activity in monkeys performing a working memory task [ 15 -18 ] . One particularly infl uential family of such models is based on attractor dynamics [ 19 -22 ] . Attractor models are characterized by internal dynamics such that the system evolves with time approaching and stabi-

Serotonin (5-HT) receptors of types 1A and 2A are strongly expressed in prefrontal cortex (PFC) neurons, an area associated with cognitive function. Hence, 5-HT could be effective in modulating prefrontal-dependent cognitive functions, such as spatial working memory (SWM). However, a direct association between 5-HT and SWM has proved elusive in psycho-pharmacological studies. Recently, a computational network model of the PFC microcircuit was used to explore the relationship between 5-HT and SWM (Cano-Colino et al., 2013). This study found that both excessive and insufficient 5-HT levels lead to impaired SWM performance in the network, and it concluded that analyzing behavioral responses based on confidence reports could facilitate the experimental identification of SWM behavioral effects of 5-HT neuromodulation. Such analyses may have confounds based on our limited understanding of metacognitive processes. Here, we extend these results by deriving three additional predictions from the model that do not rely on confidence reports. Firstly, only excessive levels of 5-HT should result in SWM deficits that increase with delay duration. Secondly, excessive 5-HT baseline concentration makes the network vulnerable to distractors at distances that were robust to distraction in control conditions, while the network still ignores distractors efficiently for low 5-HT levels that impair SWM. Finally, 5-HT modulates neuronal memory fields in neurophysiological experiments: Neurons should be better tuned to the cued stimulus than to the behavioral report for excessive 5-HT levels, while the reverse should happen for low 5-HT concentrations. In all our simulations agonists of 5-HT1A receptors and antagonists of 5-HT2A receptors produced behavioral and physiological effects in line with global 5-HT level increases. Our model makes specific predictions to be tested experimentally and advance our understanding of the neural basis of SWM and its neuromodulation by 5-HT receptors.

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