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At least 163 records · Page 9Linked to original sources
PubMed2005

Mesencephalic substrate of reward: lesion effects.

Psychophysical studies suggest that reward-relevant neurons in the posterior mesencephalon (PM) form a caudal extension of the axonal pathway that mediates the rewarding effectiveness of electrical stimulation of the medial forebrain bundle. The present study sought to further characterize the reward-relevant functional link between these two regions by assessing changes to the rewarding effectiveness of caudal medial forebrain bundle stimulation (ventral tegmental area, VTA) subsequent to electrolytic lesions of different PM sites. A total of 13 rats were tested, 11 of these at bilateral VTA stimulation sites. Overall, rewarding effectiveness was reduced in five rats and pontentiated in four. The presence and magnitude of the effects were site-, current- and time-dependent, and ranged from 0.1 to 0.4 log(10) unit shifts in reward magnitude, with most effects falling below 0.3 log(10) units. Generally, these effects became apparent approximately two weeks after the lesion. In addition to these effects, PM lesions placed on or close to the midline also produced small transient reductions in rewarding effectiveness immediately after the lesion, an effect that disappeared within three days. Conversely, lateral PM lesions were associated either with no immediate effects or with small transient potentiations of reward. The finding that lesions of the PM placed on the midline, just off the midline or laterally all altered the rewarding effectiveness of VTA stimulation suggests that the reward-relevant circuitry is distributed diffusely throughout the PM.

Animals↗
PubMed2006

Heterarchical reinforcement-learning model for integration of multiple cortico-striatal loops: fMRI examination in stimulus-action-reward association learning.

The brain's most difficult computation in decision-making learning is searching for essential information related to rewards among vast multimodal inputs and then integrating it into beneficial behaviors. Contextual cues consisting of limbic, cognitive, visual, auditory, somatosensory, and motor signals need to be associated with both rewards and actions by utilizing an internal representation such as reward prediction and reward prediction error. Previous studies have suggested that a suitable brain structure for such integration is the neural circuitry associated with multiple cortico-striatal loops. However, computational exploration still remains into how the information in and around these multiple closed loops can be shared and transferred. Here, we propose a "heterarchical reinforcement learning" model, where reward prediction made by more limbic and cognitive loops is propagated to motor loops by spiral projections between the striatum and substantia nigra, assisted by cortical projections to the pedunculopontine tegmental nucleus, which sends excitatory input to the substantia nigra. The model makes several fMRI-testable predictions of brain activity during stimulus-action-reward association learning. The caudate nucleus and the cognitive cortical areas are correlated with reward prediction error, while the putamen and motor-related areas are correlated with stimulus-action-dependent reward prediction. Furthermore, a heterogeneous activity pattern within the striatum is predicted depending on learning difficulty, i.e., the anterior medial caudate nucleus will be correlated more with reward prediction error when learning becomes difficult, while the posterior putamen will be correlated more with stimulus-action-dependent reward prediction in easy learning. Our fMRI results revealed that different cortico-striatal loops are operating, as suggested by the proposed model.

Association Learning↗
PubMed2006

Prediction error as a linear function of reward probability is coded in human nucleus accumbens.

Reward probability has been shown to be coded by dopamine neurons in monkeys. Phasic neuronal activation not only increased linearly with reward probability upon expectation of reward, but also varied monotonically across the range of probabilities upon omission or receipt of rewards, therefore modeling discrepancies between expected and received rewards. Such a discrete coding of prediction error has been suggested to be one of the basic principles of learning. We used functional magnetic resonance imaging (fMRI) to show that the human dopamine system codes reward probability and prediction error in a similar way. We used a simple delayed incentive task with a discrete range of reward probabilities from 0%-100%. Activity in the nucleus accumbens of human subjects strongly resembled the phasic responses found in monkey neurons. First, during the expectation period of the task, the fMRI signal in the human nucleus accumbens (NAc) increased linearly with the probability of the reward. Second, during the outcome phase, activity in the NAc coded the prediction error as a linear function of reward probabilities. Third, we found that the Nac signal was correlated with individual differences in sensation seeking and novelty seeking, indicating a link between individual fMRI activation of the dopamine system in a probabilistic paradigm and personality traits previously suggested to be linked with reward processing. We therefore identify two different covariates that model activity in the Nac: specific properties of a psychological task and individual character traits.

Adult↗
PubMed2006

Neuronal responses to a delayed-response delayed-reward go/nogo task in the monkey posterior insular cortex.

Anatomical connections of the insular cortex suggest its involvement in cognition, emotion, memory, and behavioral manifestation. However, there have been few neurophysiological studies on the insular cortex in primates, in relation to such higher cognitive functions. In the present study, neural activity was recorded from the monkey insular cortex during performance of a delayed-response delayed-reward go/nogo task. In this task, visual stimuli indicating go or nogo responses associated with reward (reward trials) and with no reward (no-reward trials) were presented after eye fixation. In the reward trials, the monkey was required to release a button during presentation of the 2nd visual stimuli after a delay period (delay 1). Then, a juice reward was delivered after another delay (delay 2). The results indicated that the neurons responding in each epoch of the task were topographically localized within the insular cortex, consistent with the previous anatomical studies indicating topographical distributions of afferent inputs from other subcortical and cortical sensory areas. Furthermore, some insular neurons 1) nonspecifically responded to the visual cues and during fixation; 2) responded to the visual cues predicting reward and during the delay period before reward delivery; 3) responded differentially in go/nogo trials during the delay 2; and 4) responded around button manipulation. The observed patterns of insular-neuron responses and the correspondence of their topographical localization to those in previous anatomical studies suggest that the insular cortex is involved in attention- and reward-related functions and might monitor and integrate activities of other brain regions during cognition and behavioral manifestation.

Analysis of Variance↗
PubMed1998

Electrophysiological evidence that a subset of midbrain dopamine neurons integrate the reward signal induced by electrical stimulation of the posterior mesencephalon.

This study was aimed at determining whether midbrain dopamine (DA) neurons are trans-synaptically activated by rewarding electrical stimulation applied near the midline in the posterior mesencephalon (PM), and in the affirmative, whether the increase in firing was proportional to the rewarding effectiveness of the stimulation. Experiments were performed on male Long-Evans rats trained to lever press to obtain 400 ms trains of cathodal rectangular pulses. Following the training period, curves relating the rates of responding to the stimulation frequencies were determined at two current intensities and reward thresholds were calculated for each animal. Each animal was then anesthetized with urethane (1.2 g/kg, i.p.) and firing rate of DA neurons were recorded before, during, and after each of 50 trains (1 train/3 s) of stimulation to the PM using stimulation parameters that either sustained near threshold responding (rewarding), or failed to sustain responding (non-rewarding), in the behavioral tests. A total of 24 DA cells were recorded from 13 behaviorally trained animals, and of these, 17 (71%) responded to rewarding stimulation by an increase in firing, five (21%) were unresponsive and two (8%) were inhibited. In 12 of the 17 cells that were activated, the increase in firing was proportional to the rewarding effectiveness of the stimulation rather than the total strength of the stimulation. These results provide evidence that a subset of midbrain DA neurons are trans-synaptically activated by rewarding PM stimulation and constitute a second, or subsequent, stage of the reward-relevant pathway that integrates the PM reward signal.

Action Potentials↗
PubMed2000

Reward-dependent learning in neuronal networks for planning and decision making.

Neuronal network models have been proposed for the organization of evaluation and decision processes in prefrontal circuitry and their putative neuronal and molecular bases. The models all include an implementation and simulation of an elementary reward mechanism. Their central hypothesis is that tentative rules of behavior, which are coded by clusters of active neurons in prefrontal cortex, are selected or rejected based on an evaluation by this reward signal, which may be conveyed, for instance, by the mesencephalic dopaminergic neurons with which the prefrontal cortex is densely interconnected. At the molecular level, the reward signal is postulated to be a neurotransmitter such as dopamine, which exerts a global modulatory action on prefrontal synaptic efficacies, either via volume transmission or via targeted synaptic triads. Negative reinforcement has the effect of destabilizing the currently active rule-coding clusters; subsequently, spontaneous activity varies again from one cluster to another, giving the organism the chance to discover and learn a new rule. Thus, reward signals function as effective selection signals that either maintain or suppress currently active prefrontal representations as a function of their current adequacy. Simulations of this variation-selection have successfully accounted for the main features of several major tasks that depend on prefrontal cortex integrity, such as the delayed-response test, the Wisconsin card sorting test, the Tower of London test and the Stroop test. For the more complex tasks, we have found it necessary to supplement the external reward input with a second mechanism that supplies an internal reward; it consists of an auto-evaluation loop which short-circuits the reward input from the exterior. This allows for an internal evaluation of covert motor intentions without actualizing them as behaviors, by simply testing them covertly by comparison with memorized former experiences. This element of architecture gives access to enhanced rates of learning via an elementary process of internal or covert mental simulation. We have recently applied these ideas to a new model, developed with M. Kerszberg, which hypothesizes that prefrontal cortex and its reward-related connections contribute crucially to conscious effortful tasks. This model distinguishes two main computational spaces within the human brain: a unique global workspace composed of distributed and heavily interconnected neurons with long-range axons, and a set of specialized and modular perceptual, motor, memory, evaluative and attentional processors. We postulate that workspace neurons are mobilized in effortful tasks for which the specialized processors do not suffice; they selectively mobilize or suppress, through descending connections, the contribution of specific processor neurons. In the course of task performance, workspace neurons become spontaneously co-activated, forming discrete though variable spatio-temporal patterns subject to modulation by vigilance signals and to selection by reward signals. A computer simulation of the Stroop task shows workspace activation to increase during acquisition of a novel task, effortful execution, and after errors. This model makes predictions concerning the spatio-temporal activation patterns during brain imaging of cognitive tasks, particularly concerning the conditions of activation of dorsolateral prefrontal cortex and anterior cingulate, their relation to reward mechanisms, and their specific reaction during error processing.

Animals↗
PubMed1997

Glucocorticoids as a biological substrate of reward: physiological and pathophysiological implications.

The observations presented in this review suggest that glucocorticoids are one of the biological substrates of reward. These hormones are secreted in response to rewarding stimuli, such as food, a receptive sexual partner or drugs of abuse. Furthermore, manipulations of the secretion of glucocorticoids modify reward-related behaviours, and administration of these hormones, in the range of physiological stress levels, has positive reinforcing effects. The rewarding effects of glucocorticoids are probably mediated by a glucocorticoid-induced stimulation of the mesencephalic dopaminergic transmission, one of the principal neural substrates of reward. It is proposed that the rewarding effects of glucocorticoids play the role of counteracting the aversive effects of external aggressions, allowing a better coping with threatening situations. However, a sustained increase in the secretion of these hormones, or an hypersensitivity to their rewarding effects, could determine reward-related pathologies, such as a predisposed state to develop drug-abuse. In conclusion, through their reward-related effects, glucocorticoids may play a key role in tuning adaptation to stress and in determining reward-related behavioral pathologies.

Animals↗
PubMed2002

Exposure to chronic mild stress alters thresholds for lateral hypothalamic stimulation reward and subsequent responsiveness to amphetamine.

Chronic mild stress in rodents has been proposed to model some of the environmental factors that contribute to the induction of depressive disorders in humans. This model is based on the hypothesis that chronic mild stress induces a change in brain reward function that resembles the symptomatology of major depression, namely, a decrease in responsiveness to rewarding stimuli. The purpose of the first experiment was to investigate whether chronic mild stress affects brain reward function as measured by alterations in lateral hypothalamic self-stimulation behavior in rats. Exposure to chronic mild stress induces a reduction in body weight which might affect brain reward function on its own. Therefore, the potential contribution of a reduction in body weight to the chronic mild stress-induced alterations in brain reward function was examined in a separate group of food-restricted rats. Thresholds for lateral hypothalamic self-stimulation were slightly but significantly lowered in animals exposed to chronic mild stress, indicating an enhancement of stimulation reward efficacy. Food restriction had no effect on brain reward function. The second experiment examined the interaction between prior exposure to chronic mild stress or food restriction and responsiveness to a pharmacological challenge, amphetamine, that enhances brain reward function. Acute administration of amphetamine produced a greater enhancement of lateral hypothalamic self-stimulation reward in animals exposed to chronic stress relative to non-stressed and food-restricted animals. Taken together, the present findings indicate that chronic mild stress sensitizes the neural substrates that mediate both lateral hypothalamic stimulation and psychostimulant drug reward. These findings support the hypothesis that prior exposure to stress affects the vulnerability for drug-taking behavior by increasing the positive reinforcing properties of drug of abuse.

Amphetamine↗
PubMed1999

A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation.

A meta-analysis of 128 studies examined the effects of extrinsic rewards on intrinsic motivation. As predicted, engagement-contingent, completion-contingent, and performance-contingent rewards significantly undermined free-choice intrinsic motivation (d = -0.40, -0.36, and -0.28, respectively), as did all rewards, all tangible rewards, and all expected rewards. Engagement-contingent and completion-contingent rewards also significantly undermined self-reported interest (d = -0.15, and -0.17), as did all tangible rewards and all expected rewards. Positive feedback enhanced both free-choice behavior (d = 0.33) and self-reported interest (d = 0.31). Tangible rewards tended to be more detrimental for children than college students, and verbal rewards tended to be less enhancing for children than college students. The authors review 4 previous meta-analyses of this literature and detail how this study's methods, analyses, and results differed from the previous ones.

Behavior Therapy↗
PubMed2003

Neuronal activity in primate dorsolateral and orbital prefrontal cortex during performance of a reward preference task.

An important function of the prefrontal cortex (PFC) is the control of goal-directed behaviour. This requires information as to whether actions were successful in obtaining desired outcomes such as rewards. While lesion studies implicate a particular PFC region, the orbitofrontal cortex (OFC), in reward processing, neurons encoding reward have been reported in both the OFC and the dorsolateral prefrontal cortex (DLPFC). To compare and contrast their roles, we recorded simultaneously from both areas while two rhesus monkeys (Macaca mulatta) performed a reward preference task. The monkeys had to choose between pictures associated with different amounts of a juice reward. Neuronal activity in both areas reflected the reward amount. However, neurons in the DLPFC encoded both the reward amount and the monkeys' forthcoming response, while neurons in the OFC more often encoded the reward amount alone. Further, reward selectivity arose more rapidly in the OFC than the DLPFC. These results are consistent with reward information entering the PFC via the OFC, where it is passed to the DLPFC and used to control behaviour.

Action Potentials↗
PubMed2005

Immediate changes in anticipatory activity of caudate neurons associated with reversal of position-reward contingency.

The primate caudate nucleus plays a crucial role in transforming cognitive/motivational information into eye movement signals. A subset of caudate projection neurons fire before a visual target's onset. This anticipatory activity is sensitive to position-reward contingencies and correlates with saccade latency, which is shorter toward a rewarded position. We recorded single-unit activity of caudate projection neurons to examine the dynamics of change in anticipatory activity immediately after switches of the position-reward contingency. Two monkeys performed a visually guided saccade task where only one position was associated with reward. The position-reward mapping remained constant within a block, but was reversed frequently between blocks without any indication to the monkey. Therefore the switch could be detected only by unexpected reward delivery or unexpected lack of reward. After the switch, both saccade latency and anticipatory activity showed reliable changes already in the second trial, whether or not the first trial was rewarded. However, anticipatory activity in the second trial was generally higher if the first trial was rewarded, and the measured saccade latencies could be better explained by the difference in anticipatory activity between the two caudate nuclei. We suggest that anticipatory activity of caudate neurons reflects the reversal set of reward-position contingency.

Action Potentials↗
PubMed2000

Modifications of reward expectation-related neuronal activity during learning in primate orbitofrontal cortex.

This study investigated how neuronal activity in orbitofrontal cortex related to the expectation of reward changed while monkeys repeatedly learned to associate new instruction pictures with known behavioral reactions and reinforcers. In a delayed go-nogo task with several trial types, an initial picture instructed the animal to execute or withhold a reaching movement and to expect a liquid reward or a conditioned auditory reinforcer. When novel instruction pictures were presented, animals learned according to a trial-and-error strategy. After experience with a large number of novel pictures, learning occurred in a few trials, and correct performance usually exceeded 70% in the first 60-90 trials. About 150 task-related neurons in orbitofrontal cortex were studied in both familiar and learning conditions and showed two major forms of changes during learning. Quantitative changes of responses to the initial instruction were seen as appearance of new responses, increase of existing responses, or decrease or complete disappearance of responses. The changes usually outlasted initial learning trials and persisted during subsequent consolidation. They often modified the trial selectivities of activations. Increases might reflect the increased attention during learning and induce neuronal changes underlying the behavioral adaptations. Decreases might be related to the unreliable reward-predicting value of frequently changing learning instructions. The second form of changes reflected the adaptation of reward expectations during learning. In initial learning trials, animals reacted as if they expected liquid reward in every trial type, although only two of the three trial types were rewarded with liquid. In close correspondence, neuronal activations related to the expectation of reward occurred initially in every trial type. The behavioral indices for reward expectation and their neuronal correlates adapted in parallel during the course of learning and became restricted to rewarded trials. In conclusion, these data support the notion that neurons in orbitofrontal cortex code reward information in a flexible and adaptive manner during behavioral changes after novel stimuli.

Adaptation, Psychological↗
PubMed2001

Reward signaling by dopamine neurons.

Dopamine projections from the midbrain to the striatum and frontal cortex are involved in behavioral reactions controlled by rewards, as inferred from deficits in parkinsonism, schizophrenia, and drug addiction. Recent experiments have shown that dopamine neurons are not directly modulated in relation to movements. Rather, they appear to code the rewarding aspects of environmental stimuli. They show short, phasic increases of activity following primary food and liquid rewards ("unconditioned stimuli") and conditioned, reward-predicting stimuli of visual, auditory, and somatosensory modalities. They also display smaller activation-depression sequences after stimuli resembling rewards and after novel or particularly intense stimuli. Rewards are only reported as far as they occur differently than predicted. According to learning theories, a "prediction error" message may constitute a powerful teaching signal for behavior and learning. The phasic reward message is different from the more tonic enabling function of dopamine that is deficient in Parkinson's disease, indicating that dopamine neurons subserve different functions at different time scales. Neurons in other brain structures, such as the striatum, orbitofrontal cortex, and amygdala, code the quality, quantity, and preference of rewards. The dopamine reward prediction error signal may cooperate with these reward perception signals during the learning and performance of behavioral reactions to motivating environmental stimuli.

Animals↗
PubMed2004

The neural substrates of reward processing in humans: the modern role of FMRI.

Experimental work in animals has identified numerous neural structures involved in reward processing and reward-dependent learning. Until recently, this work provided the primary basis for speculations about the neural substrates of human reward processing. The widespread use of neuroimaging technology has changed this situation dramatically over the past decade through the use of PET and fMRI. Here, the authors focus on the role played by fMRI studies, where recent work has replicated the animal results in human subjects and has extended the view of putative reward-processing neural structures. In particular, fMRI work has identified a set of reward-related brain structures including the orbitofrontal cortex, amygdala, ventral striatum, and medial prefrontal cortex. Moreover, the human experiments have probed the dependence of human reward responses on learned expectations, context, timing, and the reward dimension. Current experiments aim to assess the function of human reward-processing structures to determine how they allow us to predict, assess, and act in response to rewards. The authors review current accomplishments in the study of human reward processing and focus their discussion on explanations directed particularly at the role played by the ventral striatum. They discuss how these findings may contribute to a better understanding of deficits associated with Parkinson's disease.

Algorithms↗
PubMed2026

Targeting distinct facets of anhedonia via transcutaneous auricular vagus nerve stimulation: Effects on heart rate variability and reward-based behavior.

Anhedonia, a core feature of major depressive disorder, is associated with disrupted reward processing and may represent a mechanistically relevant target for neuromodulation. This study examined the effects of transcutaneous auricular vagus nerve stimulation (taVNS) on reward-related behavior and autonomic regulation in individuals with higher (n = 34) and lower (n = 34) depressive symptomatology. In a randomized, within-subject crossover design, participants received active taVNS and sham stimulation on two separate days. During each session, incentive motivation and reward learning were assessed using the Effort Expenditure for Rewards Task and the Probabilistic Reward Task (PRT), respectively, with stimulation condition and task order counterbalanced. Findings revealed that taVNS effects on heart rate variability (HRV) were modulated by baseline HRV levels and depressive status; specifically, they enhanced HRV at low baseline levels and reduced it at high baseline levels in participants with lower depressive symptomatology, with opposite patterns in individuals with higher symptoms. Moreover, compared to sham, taVNS enhanced the willingness to exert effort for rewards, particularly at low reward probabilities, with a more pronounced effect in the group characterized by higher depressive symptoms. No significant effects were observed on reward learning, as indexed by the PRT. Additionally, taVNS reduced self-reported anxiety across groups. Despite the limitation of a single stimulation session, these findings suggest that taVNS modulates motivational effort allocation in individuals with higher depressive symptoms, supporting its potential relevance for targeting reward-related dysfunctions in mood disorders.

Anhedonia↗
PubMed2005

Individual differences in reward sensitivity are related to food craving and relative body weight in healthy women.

According to the theory of J.A. Gray, a strongly reactive approach system is highly sensitive to reward or to cues that signal reward. This implies that intake driven by the rewarding properties of food should be affected by individual differences in reactivity of the approach system. The present study examined whether reward sensitivity is associated with food craving and relative body weight in a sample of female college students. Participants completed the Sensitivity to Punishment and Sensitivity to Reward Questionnaire and the trait version of the Food Craving Questionnaire and also reported their weight and height in order to compute Body Mass Index (BMI). Sensitivity to reward was significantly related to food craving and BMI. Furthermore, the correlation between reward sensitivity and BMI was not attenuated when the influence of food craving was partialled out, indicating that the relation between sensitivity to reward and BMI was not mediated by food craving. This is the first study demonstrating a relation between the personality trait of sensitivity to reward and BMI. These findings are discussed in the context of the involvement of dopaminergic reward circuitry in overeating.

Adolescent↗
PubMed2002

Effects of isolation-rearing on intracranial self-stimulation reward of the lateral hypothalamus: baseline assessment and drug challenges.

There is evidence that isolation rearing produces down-regulation of the dopamine D2 receptor. Therefore, isolation rearing should also modify the effects of D2 antagonists on intracranial self-stimulation (ICSS) reward. This study investigated the effect of isolation rearing on ICSS reward, and modulation of that reward by SCH23390, Raclopride and MK-801. Sprague-Dawley rats were reared alone (isolates) or in pairs from day 21 postnatal to day 75 postnatal. At this time, all rats were implanted with monopolar stimulating electrodes in the lateral hypothalamus. The ICSS rate-frequency curve-shift method was used to assess reward and operant motor function at baseline and after administration of SCH-23390 (D1 antagonist: 0.02, 0.06, 0.2 mg/kg), Raclopride (D2 antagonist: 0.01, 0.025, 0.06 mg/kg), and MK-801 (non-competitive NMDA receptor antagonist: 0.1, 0.2 mk/kg). Isolation-reared rats displayed similar measures of both basal reward and motor function when compared to socially reared controls. Isolation-reared rats were subsensitive to the reward decreasing effects of Raclopride. Socially reared rats were observed to have more variant baseline reward measures, and could be divided into distinctly different groups with different basal reward function. Isolation-rearing down-regulates D2 function but does not affect basal reward function, but some unknown factor in the social rearing environment did have a substantial effect on basal reward function.

Animals↗
PubMed2006

Role of dopamine in the primate caudate nucleus in reward modulation of saccades.

Expected reward impacts behavior and neuronal activity in brain areas involved in sensorimotor processes. However, where and how reward signals affect sensorimotor signals is unclear. Here, we show evidence that reward-dependent modulation of behavior depends on normal dopamine transmission in the striatum. Monkeys performed a visually guided saccade task in which expected reward gain was different depending on the position of the target. Saccadic reaction times were reliably shorter on large-reward trials than on small-reward trials. When position-reward contingency was switched, the reaction time difference changed rapidly. Injecting dopamine D1 antagonist into the caudate significantly attenuated the reward-dependent saccadic reaction time changes. Conversely, injecting D2 antagonist into the same region enhanced the reward-dependent changes. These results suggest that reward-dependent changes in saccadic eye movements depend partly on dopaminergic modulation of neuronal activity in the caudate nucleus.

Animals↗