infonet-economy

Delayed rewards lose their value for economic decisions and constitute weaker reinforcers for learning. Temporal discounting of reward value already occurs within a few seconds in animals, which allows investigations of the underlying neurophysiological mechanisms. However, it is difficult to relate these mechanisms to human discounting behavior, which is usually studied over days and months and may engage different brain processes. Our study aimed to bridge the gap by using very short delays and measuring human functional magnetic resonance responses in one of the key reward centers of the brain, the ventral striatum. We used psychometric methods to assess subjective timing and valuation of monetary rewards with delays of 4.0-13.5 s. We demonstrated hyperbolic and exponential decreases of striatal responses to reward predicting stimuli within this time range, irrespective of changes in reward rate. Lower reward magnitudes induced steeper behavioral and striatal discounting. By contrast, striatal responses following the delivery of reward reflected the uncertainty in subjective timing associated with delayed rewards rather than value discounting. These data suggest that delays of a few seconds affect the neural processing of predicted reward value in the ventral striatum and engage the temporal sensitivity of reward responses. Comparisons with electrophysiological animal data suggest that ventral striatal reward discounting may involve dopaminergic and orbitofrontal inputs.

When making choices under uncertainty, people usually consider both the expected value and risk of each option, and choose the one with the higher utility. Expected value increases the expected utility of an option for all individuals. Risk increases the utility of an option for risk-seeking individuals, but decreases it for risk averse individuals. In 2 separate experiments, one involving imperative (no-choice), the other choice situations, we investigated how predicted risk and expected value aggregate into a common reward signal in the human brain. Blood oxygen level dependent responses in lateral regions of the prefrontal cortex increased monotonically with increasing reward value in the absence of risk in both experiments. Risk enhanced these responses in risk-seeking participants, but reduced them in risk-averse participants. The aggregate value and risk responses in lateral prefrontal cortex contrasted with pure value signals independent of risk in the striatum. These results demonstrate an aggregate risk and value signal in the prefrontal cortex that would be compatible with basic assumptions underlying the mean-variance approach to utility.

Invasive recording of dopamine neurons in the substantia nigra and ventral tegmental area (SN/VTA) of behaving animals suggests a role for these neurons in reward learning and novelty processing. In humans, functional magnetic resonance imaging (fMRI) is currently the only non-invasive event-related method to measure SN/VTA activity, but it is debated to what extent fMRI enables inference about dopaminergic responses within the SN/VTA. We consider the anatomical and functional parcellation of the primate SN/VTA and find that its homogeneity suggests little variation in the regional specificity of fMRI signals for reward-related dopaminergic responses. Hence, these responses seem to be well captured by the compound fMRI signal from the SN/VTA, which seems quantitatively related to dopamine release in positron emission tomography (PET). We outline how systematic investigation of the functional parcellation of the SN/VTA in animals, new developments in fMRI analysis and combined PET-fMRI studies can narrow the gap between fMRI and dopaminergic neurotransmission.

Decision making under risk is central to human behavior. Economic decision theory suggests that value, risk, and risk aversion influence choice behavior. Although previous studies identified neural correlates of decision parameters, the contribution of these correlates to actual choices is unknown. In two different experiments, participants chose between risky and safe options. We identified discrete blood oxygen level-dependent (BOLD) correlates of value and risk in the ventral striatum and anterior cingulate, respectively. Notably, increasing inferior frontal gyrus activity to low risk and safe options correlated with higher risk aversion. Importantly, the combination of these BOLD responses effectively decoded the behavioral choice. Striatal value and cingulate risk responses increased the probability of a risky choice, whereas inferior frontal gyrus responses showed the inverse relationship. These findings suggest that the BOLD correlates of decision factors are appropriate for an ideal observer to detect behavioral choices. More generally, these biological data contribute to the validity of the theoretical decision parameters for actual decisions under risk.

The dominant view that perceptual learning is accompanied by changes in early sensory representations has recently been challenged. Here we tested the idea that perceptual learning can be accounted for by reinforcement learning involving changes in higher decision-making areas. We trained subjects on an orientation discrimination task involving feedback over 4 days, acquiring fMRI data on the first and last day. Behavioral improvements were well explained by a reinforcement learning model in which learning leads to enhanced readout of sensory information, thereby establishing noise-robust representations of decision variables. We find stimulus orientation encoded in early visual and higher cortical regions such as lateral parietal cortex and anterior cingulate cortex (ACC). However, only activity patterns in the ACC tracked changes in decision variables during learning. These results provide strong evidence for perceptual learning-related changes in higher order areas and suggest that perceptual and reward learning are based on a common neurobiological mechanism.

One of the main challenges in working memory research has been to understand the degree of separation and overlap between the neural systems involved in encoding and maintenance. In the current study we used a variable load version of the Sternberg item recognition test (two, four, six, or eight letters) and a functional connectivity method based on constrained principal component analysis to extract load-dependent neural systems underlying encoding and maintenance, and to characterize their anatomical overlap and functional interaction. Based on the pattern of functional connectivity, constrained principal component analysis identified a load-dependent encoding system comprising bilateral occipital (Brodmann's area (BA) 17, 18), bilateral superior parietal (BA 7), bilateral dorsolateral prefrontal (BA 46), and dorsal anterior cingulate (BA 24, 32) regions. For maintenance, in contrast, constrained principal component analysis identified a system that was characterized by both load-dependent increases and decreases in activation. The structures in this system jointly activated by maintenance load involved left posterior parietal (BA 40), left inferior prefrontal (BA 44), left premotor and supplementary motor areas (BA 6), and dorsal cingulate regions (BA 24, 32), while the regions displaying maintenance-load-dependent activity decreases involved bilateral occipital (BA 17, 18), posterior cingulate (BA 23) and rostral anterior cingulate/orbitofrontal (BA 10, 11, 32) regions. The correlation between the encoding and maintenance systems was strong and negative (Pearson's r = -.55), indicting that some regions important for visual processing during encoding displayed reduced activity during maintenance, while subvocal rehearsal and phonological storage regions important for maintenance showed a reduction in activity during encoding. In summary, our analyses suggest that separable and complementary subsystems underlie encoding and maintenance in verbal working memory, and they demonstrate how constrained principal component analysis can be employed to characterize neuronal systems and their functional contributions to higher-level cognition.

Alternating between task sets involves detection that the current task set is unfavorable, initiation of a change in set, and application of the new task set while fine-tuning to optimally adjust to the demands of the environment. Functional magnetic resonance imaging (fMRI) studies of cognitive flexibility consistently report activation of the anterior cingulate cortex and/or adjacent pre-supplementary motor regions (ACC/pre-SMA, medial Brodmann's areas 24/32/6), suggesting that these cortical regions are involved in switching task set. In the current study, our objective was to probe whether ACC/pre-SMA activation would decrease for a number of trials following a switch in task set, implying longer-term involvement in fine-tuning adjustments. By measuring activation when switching between word reading and color naming in response to Stroop stimuli, ACC/pre-SMA activation was observed when actively countering the influence of the irrelevant task set, and this activation decreased as a function of the number of trials since a task switch. Basal ganglia and thalamic regions also displayed a decreased response over successive trials after task switches. These findings suggest that the ACC/pre-SMA are not only involved in generating a new course of action, but are also involved (along with subcortical regions) in fine-tuning operations that resolve competition between task sets over subsequent repetitions of the same task.

Repetitive transcranial magnetic stimulation (rTMS) is an established technique for non-invasive stimulation of human cortex. Although studies have shown an influence of rTMS on single cortical regions and on simple behavioral response patterns, its influences on the dynamics of task-related activity in cortical networks have not been characterized. We provide such a characterization by showing that 5 Hz rTMS over primary somatosensory cortex (SI) induces a reconfiguration of activity patterns in a sensorimotor network, comprising the stimulated region and ipsilateral primary motor cortex (MI). These plastic changes endure for up to 120 min and are correlated with behavioral improvement in discrimination. Dynamic causal modeling showed that this reconfiguration could be explained by an rTMS-induced increase in SI excitability (self-connection) and an increase in the effective connectivity from SI to MI. Thus, our data demonstrate that rTMS can temporarily induce behaviorally relevant reorganization within a complex cortical network underlying human somatosensory experience.

We used functional magnetic resonance imaging (fMRI) to study neural correlates of a robust somatosensory illusion that can dissociate tactile perception from physical stimulation. Repeated rapid stimulation at the wrist, then near the elbow, can create the illusion of touches at intervening locations along the arm, as if a rabbit hopped along it. We examined brain activity in humans using fMRI, with improved spatial resolution, during this version of the classic cutaneous rabbit illusion. As compared with control stimulation at the same skin sites (but in a different order that did not induce the illusion), illusory sequences activated contralateral primary somatosensory cortex, at a somatotopic location corresponding to the filled-in illusory perception on the forearm. Moreover, the amplitude of this somatosensory activation was comparable to that for veridical stimulation including the intervening position on the arm. The illusion additionally activated areas of premotor and prefrontal cortex. These results provide direct evidence that illusory somatosensory percepts can affect primary somatosensory cortex in a manner that corresponds somatotopically to the illusory percept.