Patients with schizophrenia demonstrate deficits in motivation and learning that suggest impairment in different aspects of the reward system. In this article, we present the results of 8 converging experiments that address subjective reward experience, the impact of rewards on decision making, and the role of rewards in guiding both rapid and long-term learning. All experiments compared the performance of stably treated outpatients with schizophrenia and demographically matched healthy volunteers. Results to date suggest (1) that patients have surprisingly normal experiences of positive emotion when presented with evocative stimuli, (2) that patients show reduced correlation, compared with controls, between their own subjective valuation of stimuli and action selection, (3) that decision making in patients appears to be compromised by deficits in the ability to fully represent the value of different choices and response options, and (4) that rapid learning on the basis of trial-to-trial feedback is severely impaired whereas more gradual learning may be surprisingly preserved in many paradigms. The overall pattern of findings suggests compromises in the orbital and dorsal prefrontal structures that play a critical role in the ability to represent the value of outcomes and plans. In contrast, patients often (but not always) approach normal performance levels on the slow learning achieved by the integration of reinforcement signals over many trials, thought to be mediated by the basal ganglia.

Background Decision-making studies show that response selection is influenced by the “effort cost” associated with response alternatives. These effort-cost calculations seem to be mediated by a distributed neural circuit including the anterior cingulate cortex and subcortical targets of dopamine neurons. On the basis of evidence of dysfunction in these systems in schizophrenia (SZ), we examined whether effort-cost computations were impaired in SZ patients and whether these deficits were associated with negative symptoms. Methods Effort-cost decision-making performance was evaluated in 44 patients with SZ and 36 demographically matched control subjects. Subjects performed a computerized task where they were presented with a series of 30 trials in which they could choose between making 20 button presses for $1 or 100 button presses for higher amounts (varying from $3 to $7 across trials). Probability of reward receipt was also manipulated to determine whether certain (100%) or uncertain (50%) reward affected effort-based decision-making. Results Patients were less likely than control subjects to select the high-effort response alternative during the 100% probability condition, particularly when the value payoff was highest (i.e., $6 and $7). Patients were also less likely to select the high-effort option on trials after reward in the 50% probability condition. Furthermore, these impairments in effort-cost computations were greatest among patients with elevated negative symptoms. There was no association with haloperidol equivalent dosage. Conclusions The motivational impairments of SZ might be associated with abnormalities in estimating the “cost” of effortful behavior. This increased effort cost might undermine volition.

Synchronized low-frequency spontaneous fluctuations of the functional MRI (fMRI) signal have recently been applied to investigate large-scale neuronal networks of the brain in the absence of specific task instructions. However, the underlying neural mechanisms of these fluctuations remain largely unknown. To this end, electrophysiological recordings and resting-state fMRI measurements were conducted in ␣-chloralose-anesthetized rats. Using a seed-voxel analysis strategy, region-specific, anesthetic dosedependent fMRI resting-state functional connectivity was detected in bilateral primary somatosensory cortex (S1FL) of the resting brain. Cortical electroencephalographic signals were also recorded from bilateral S1FL; a visual cortex locus served as a control site. Results demonstrate that, unlike the evoked fMRI response that correlates with power changes in the ␥ bands, the resting-state fMRI signal correlates with the power coherence in low-frequency bands, particularly the ␦ band. These data indicate that hemodynamic fMRI signal differentially registers specific electrical oscillatory frequency band activity, suggesting that fMRI may be able to distinguish the ongoing from the evoked activity of the brain.electroencephalogram ͉ spontaneous fluctuations ͉ functional connectivity T he human brain is thought to be composed of multiple coherent neuronal networks of variable scales that support sensory, motor, and cognitive functions (1). The traditional approach to studying such networks has been to use specific tasks to probe neurobiological responses. In contrast, recent studies have demonstrated the existence of spontaneous, low-frequency (i.e., Ͻ0.1 Hz) fluctuations in the functional MRI (fMRI) signal of the resting brain that exhibit coherence patterns within specific neuronal networks in the absence of overt task performance or explicit attentional demands (2-4). Such precisely patterned spontaneous activity has been reported in both awake human and anesthetized nonhuman primates (5). Recently, ''resting-state'' fMRI has been applied to study alterations in brain networks under such pathological conditions as Alzheimer's disease (6), multiple sclerosis (7), and spatial neglect syndrome (8). These studies collectively suggest that, rather than simple physiological artifacts induced by cardiac pulsations or respiration, as was originally suspected, these widely distributed coherent low-frequency fMRI fluctuations have a direct neural basis (9, 10). However, more than a decade since they were first identified, the linkage between neuronal activity and restingstate fMRI signal remains largely unknown, underscoring the clear and critical need for well controlled animal models to investigate this phenomenon.Across various states of vigilance, the electrical activity of neuronal networks is known to oscillate at various frequencies and amplitudes, with high-frequency oscillations confined to local networks, whereas large networks are recruited during slow oscillations (11,12). Imposed tasks alter local field potent...

Context Negative symptoms are a core feature of schizophrenia, but their pathophysiology remains unclear. Objective Negative symptoms are defined by the absence of normal function. However, there must be a productive mechanism that leads to this absence. Here, we test a reinforcement learning account suggesting that negative symptoms result from a failure to represent the expected value of rewards coupled with preserved loss avoidance learning. Design Subjects performed a probabilistic reinforcement learning paradigm involving stimulus pairs in which choices resulted in either reward or avoidance of loss. Following training, subjects indicated their valuation of the stimuli in a transfer task. Computational modeling was used to distinguish between alternative accounts of the data. Setting A tertiary care research outpatient clinic. Patients A total of 47 clinically stable patients with a diagnosis of schizophrenia or schizoaffective disorder and 28 healthy volunteers participated. Patients were divided into high and low negative symptom groups. Main Outcome measures 1) The number of choices leading to reward or loss avoidance and 2) performance in the transfer phase. Quantitative fits from three different models were examined. Results High negative symptom patients demonstrated impaired learning from rewards but intact loss avoidance learning, and failed to distinguish rewarding stimuli from loss-avoiding stimuli in the transfer phase. Model fits revealed that high negative symptom patients were better characterized by an “actor-critic” model, learning stimulus-response associations, whereas controls and low negative symptom patients incorporated expected value of their actions (“Q-learning”) into the selection process. Conclusions Negative symptoms are associated with a specific reinforcement learning abnormality: High negative symptoms patients do not represent the expected value of rewards when making decisions but learn to avoid punishments through the use of prediction errors. This computational framework offers the potential to understand negative symptoms at a mechanistic level.

Background: Rewards and punishments may make distinct contributions to learning via separate striato-cortical pathways. We investigated whether fronto-striatal dysfunction in schizophrenia (SZ) is characterized by selective impairment in either reward-(Go) or punishment-driven (NoGo) learning.

The integration of multiple relations between mental representations is critical for higher level cognition. For both deductiveand inductive-reasoning tasks, patients with prefrontal damage exhibited a selective and catastrophic deficit in the integration of relations, whereas patients with anterior temporal lobe damage, matched for overall IQ but with intact prefrontal cortex, exhibited normal relational integration. In contrast, prefrontal patients performed more accurately than temporal patients on tests of both episodic memory and semantic knowledge. These double dissociations suggest that integration of relations is a specific source of cognitive complexity for which intact prefrontal cortex is essential. The integration of relations may be the fundamental common factor linking the diverse abilities that depend on prefrontal function, such as planning, problem solving, and fluid intelligence.Reasoning depends on the ability to form and manipulate mental representations of relations between objects and events. For example, transitive inference (a type of deductive reasoning, in which the truth of the premises ensures the truth of the conclusion) requires the ability to integrate two relations that share an element (e.g., given that Bill is taller than Charles and Abe is taller than Bill, it follows that Abe is taller than Charles). Similarly, in drawing analogies (a type of inductive reasoning, in which the initial premises determine the plausibility of the conclusion), relational reasoning is also essential (e.g., in the problem "person is to house as bear is to what?" the shared roles, dweller and dwelling, constrain the inferred answer, "cave"). Problem solving and planning also necessarily depend on relational integration. For example, using the elementary problem-solving strategy of difference reduction (Newell & Simon, 1972) requires integration of a difference between the present state and the goal state (a relation, such as "this wall lacks a coat of paint") with the expected change that would be produced by an operator applied to the present state (a second relation, such as "painting the wall will add a coat of paint"). Forming subgoals by means-ends analysis also requires integration of multiple relations (e.g.

This article reviews and synthesizes research on reward processing in schizophrenia, which has begun to provide important insights into the cognitive and neural mechanisms associated with motivational impairments. Aberrant cortical-striatal interactions may be involved with multiple reward processing abnormalities, including: (1) dopamine-mediated basal ganglia systems that support reinforcement learning and the ability to predict cues that lead to rewarding outcomes; (2) orbitofrontal cortex-driven deficits in generating, updating, and maintaining value representations; (3) aberrant effort-value computations, which may be mediated by disrupted anterior cingulate cortex and midbrain dopamine functioning; and (4) altered activation of the prefrontal cortex, which is important for generating exploratory behaviors in environments where reward outcomes are uncertain. It will be important for psychosocial interventions targeting negative symptoms to account for abnormalities in each of these reward processes, which may also have important interactions; suggestions for novel behavioral intervention strategies that make use of external cues, reinforcers, and mobile technology are discussed.

Impairments in feedback processing and reinforcement learning appear to be prominent aspects of schizophrenia (SZ), which may relate to symptoms of the disorder. Evidence from cognitive neuroscience investigations indicates that disparate brain systems may underlie different kinds of feedback-driven learning. The ability to rapidly shift response tendencies in the face of negative feedback, when reinforcement contingencies are reversed, is an important type of learning thought to depend on ventral prefrontal cortex (PFC). Schizophrenia has long been associated with dysfunction in dorsolateral areas of PFC, but evidence for ventral PFC impairment in more mixed. In order to assess whether SZ patients experience particular difficulty in carrying out a cognitive function commonly linked to ventral PFC function, we administered to 34 patients and 26 controls a modified version of an established probabilistic reversal learning task from the experimental literature (Cools et al. 2002). Although SZ patients and controls performed similarly on the initial acquisition of probabilistic contingencies, patients showed substantial learning impairments when reinforcement contingencies were reversed, achieving significantly fewer reversals [Χ^2(6)=15.717, p=0.008]. Even when analyses were limited to subjects who acquired all probabilistic contingencies initially (22 patients and 20 controls), patients achieved significantly fewer reversals [Χ^2(3)=9.408, p=0.024]. These results support the idea that ventral PFC dysfunction is a prevalent aspect of schizophrenic pathophysiology, which may contribute to deficits in reinforcement learning exhibited by patients. Further studies are required to investigate the roles of dopaminergic systems in these impairments. Keywordsschizophrenia; dopamine; reinforcement; basal ganglia; prefrontal; orbitofrontal One of the most common neuropsychological findings in the schizophrenia (SZ) literature is that of impaired attentional set-shifting, as evidenced by studies using tasks like the Wisconsin Card Sort Test (WCST) and the intradimensional/extradimensional (ID/ED) attentional setshifting task. This deficit has often been linked to dysfunction of dorsolateral prefrontal cortex (DLPFC), one of the most frequently-observed neural correlates of schizophrenia (Weinberger et al. 1986;Berman et al. 1988). One possible source of set-shifting deficits in patients may be set-learning impairments related to limitations in DLPFC-dependent attentional and working memory resources. Another possible source of set-shifting difficulties, however, may be a specific impairment in reversing learned associations. The reversal of learned associations is known to depend on ventral and medial areas of prefrontal cortex (PFC) from a variety of studies involving both human and nonhuman animal subjects, including both lesion studies (Dias et al. 1996;Fellows and Farah 2003;Hornak et al. 2004) and those using physiological Corresponding Author: Dr. James Andrew Waltz, PhD, Maryland Psychiatric Research Center Pu...