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The dual-process theory of action control postulates that there are two competitive and complementary mechanisms that control our behavior: a goal-directed system that executes deliberate actions, explicitly aimed toward a particular outcome, and a habitual system that autonomously execute well-learned actions, typically following an encounter with a previously associated cue. In line with dual-process theory, animal studies have provided convincing evidence for dissociable neural mechanisms, mainly manifested in cortico-striatal regions, involved in goal-directed and habitual action control. While substantial progress has been made in characterizing the neural mechanism underlying habit learning in animals, we still lack knowledge on how habits are formed and maintained in the human brain. Thus far only one study, conducted more than a decade ago by Tricomi et al. (2009), has been able to induce habitual behavior in humans via extensive training. This study also implicated the posterior putamen in the process, using functional magnetic resonance imaging (fMRI). However, recent attempts to replicate the behavioral results of this study were not successful. This leaves the research of human habits, and particularly the research of their formation through extensive repetition, as well as their neural basis, limited and far behind the animal research in the field. This motivated us to (1) attempt to replicate the behavioral and imaging main findings of Tricomi et al., (2) identify further functional and microstructural neural modifications associated with habit formation and manifestation, and (3) investigate the relationships between functional and structural plasticity and individual differences in habit expression. To this end, in this registered report we used Tricomi et al.’s free-operant task along with multi-modal MRI methods in a well-powered sample (n=123). In this task participants’ sensitivity to outcome devaluation (an index of goal-directed/habitual action control) is tested following either short or extensive training. In contrast to our hypothesis, we were not able to demonstrate habit formation as a function of training duration nor were we able to relate any functional or microstructural plasticity in the putamen with individual habit expression. We found that a pattern of increased activations in the left head of caudate that re-occurred across each day’s training is associated with goal directed behavior and that increased processing of devalued cues in low-level visual regions was indicative of goal-directed behavior (and vice versa). In a follow-up exploratory analysis comparing habitual and goal-directed subgroups within each experimental group, we found that elevated activations in frontoparietal regions during early stages of training, as well as increased reactivity towards still-valued cues in somatosensory and superior parietal regions were found in individuals that were more inclined to perform goal-directed behavior (compared with more habitual individuals). Taken together, regions commonly implicated in goal-directed behavior were most predictive of individual habit expression. Finally, we also found that differential patterns of training-related microstructural plasticity, as measured with diffusion MRI, in midbrain dopaminergic regions were associated with habit expression. This work provides new insights into the neural dynamics involved in individual habit formation/expression and encourages the development and testing of new, more sensitive, procedures for experimental habit induction in humans.

It has been suggested that there are two distinct and parallel mechanisms for controlling instrumental behavior in mammals: goal-directed actions and habits. To gain an understanding of how these two systems interact to control behavior, it is essential to characterize the mechanisms by which the balance between these systems is influenced by experience. Studies in rodents have shown that the amount of training governs the relative expression of these two systems: behavior is goal-directed following moderate training, but the more extensively an instrumental action is trained, the more it becomes habitual. It is less clear whether humans exhibit similar training effects on the expression of goal-directed and habitual behavior, as human studies have reported contradictory findings. To tackle these contradictory findings, we formed a consortium, where four laboratories undertook a pre-registered experimental induction of habits by manipulating the amount of training. There was no statistical evidence for a main effect of the amount of training on the formation and expression of habits. However, exploratory analyses suggest a moderating effect of the affective component of stress on the impact of training over habit expression. Participants who were lower in affective stress appeared to be initially goal-directed, but became habitual with increased training, whereas participants who were high in affective stress were already habitual even after moderate training, thereby manifesting insensitivity to overtraining effects. Our findings highlight the importance of the role of moderating variables such as individual differences in stress and anxiety when studying the experimental induction of habits in humans.

It has been suggested that there are two distinct and parallel mechanisms for controlling instrumental behavior in mammals: goal-directed actions and habits. To gain an understanding of how these two systems interact to control behavior, it is essential to characterize the mechanisms by which the balance between these systems is influenced by experience. Studies in rodents have shown that the amount of training governs the relative expression of these two systems: Behavior is goal-directed following moderate training, but the more extensively an instrumental action is trained, the more it becomes habitual. It is less clear whether humans exhibit similar training effects on the expression of goal-directed and habitual behavior, as human studies have reported contradictory findings. To tackle these contradictory findings, we formed a consortium, where four laboratories undertook a preregistered experimental induction of habits by manipulating the amount of training. There was no statistical evidence for a main effect of the amount of training on the formation and expression of habits. However, exploratory analyses suggest a moderating effect of the affective component of stress on the impact of training over habit expression. Participants who were lower in affective stress appeared to be initially goal-directed, but became habitual with increased training, whereas participants who were high in affective stress were already habitual even after moderate training, thereby manifesting insensitivity to overtraining effects. Our findings highlight the importance of the role of moderating variables such as individual differences in stress and anxiety when studying the experimental induction of habits in humans.

Researchers have exerted tremendous efforts to empirically study how habits form and dominate at the expense of deliberation, yet we know very little about breaking these rigid habits to restore goal-directed control. In a three-experiment study, we first illustrate a novel approach of studying well-learned habits, in order to effectively demonstrate habit disruption. In Experiment 1, we use a Go/NoGo task with familiar color-response associations to demonstrate outcome-insensitivity when compared to novel, more flexible associations. Specifically, subjects perform more accurately when the required mapping is the familiar association of green–Go/red–NoGo than when it is red–Go/green–NoGo, confirming outcome-insensitive, habitual control. As a control condition, subjects show equivalent performance with unfamiliar color-response mappings (using the colors blue and purple mapped to Go and NoGo responses). Next, in Experiments 2 and 3, we test a motivation-based feedback manipulation in varying magnitudes (i.e., performance feedback with and without monetary incentives) to break the well-established habits elicited by our familiar stimuli. We find that although performance feedback prior to the contingency reversal test is insufficient to disrupt outcome-insensitivity in Experiment 2, a combination of performance feedback and monetary incentive is able to restore goal-directed control in Experiment 3, effectively breaking the habits. As the first successful demonstration of well-learned habit disruption in the laboratory, these findings provide new insights into how we execute and modify habits, while fostering new and translational research avenues that may be applicable to treating habit-based pathologies.

Research at the intersection of social neuroscience and cognitive effort is an interesting new area for exploration. There is great potential to broaden our understanding of how social context and cognitive effort processes, currently addressed in disparate literatures, interact with one another. In this paper, we briefly review the literature on cognitive effort, focusing on effort-linked valuation and the gap in the literature regarding cognitive effort in the social domain. Next, we present a study designed to explore valuation processes linked to cognitive effort within the social context of an inequality manipulation. More specifically, we created monetary inequality among the participant (SELF, endowed with $50) and two confederates: one also endowed with $50 (OTHER HIGH) and another with only $5 (OTHER LOW). We then scanned participants using fMRI as they attempted to earn bonus payments for themselves and others through a cognitively effortful feedback-based learning task. Positive feedback produced significantly greater activation than negative feedback in key valuation regions, the ventral striatum (VS) and ventromedial prefrontal cortex (vmPFC), both when participants were performing the task on their own behalf and when earning rewards for others. While reward-related activity in the VS was exaggerated for SELF compared to OTHER HIGH for both positive and negative feedback, activity in the vmPFC did not distinguish between recipients in the group-level results. Furthermore, participants naturally fell into two groups: those most engaged when playing for themselves and those who reported engagement for others. While Self-Engaged participants showed differences between the SELF and both OTHER conditions in the VS and vmPFC, Other-Engaged participants only showed an attenuated response to negative feedback for OTHER HIGH compared to SELF in the VS and no differences between recipient conditions in the vmPFC. Together, this work shows the importance of individual differences and the fragility of advantageous inequality aversion in the face of cognitive effort, highlighting the need to study cognitive effort in the social domain.

Two distinct systems govern the motivational control of action: first, cue-driven, outcome-insensitive habits, and second, value-based, goal-directed behaviors. These separate but interactive systems are based in distinct neural circuits — habitual behaviors are driven by a circuit of putamen-thalamic-motor regions, whereas value-based decision making relies on a top-down PFC-caudate network. This review highlights the recent advancements in behavioral science that investigate the motivational underpinnings of habits, situates contemporary behavioral methods into a framework of motivation, and identifies motivational aspects of habit-based pathologies. We also contextualize the recent literature on habits to highlight the necessity of improving our methods and promoting future research attempts to yield translational value (e.g. restoring flexibility in rigid habits).

Expressive writing about past negative events has been shown to lead to a slew of positive outcomes. However, little is known about why writing about something negative would have positive effects. While some have posited that telling a narrative of a past negative event or current anxiety “frees up” cognitive resources, allowing individuals to focus more on the task at hand, there is little neural evidence suggesting that expressive writing has an effect on cognitive load. Moreover, little is known about how individual differences in the content of expressive writing could affect neural processing and the cognitive benefits writing confers. In our experiment, we compared brain activity in a group that had engaged in expressive writing vs. a control group, during performance on a feedback-based paired-associate word-learning task. We found that across groups, differential activation in the dorsal striatum in response to positive vs. negative feedback significantly predicted better later memory. Moreover, writing about a past failure resulted in more activation relative to the control group during the learning task in the mid-cingulate cortex (MCC), an area of the brain crucial to processing negative emotion. While our results do not provide support for the assertion that expressive writing alters attentional processing, our findings suggest that choosing to write about particularly intense past negative experiences like a difficult past failure may have resulted in changes in neural activation during task processing.

Attention-deficit/hyperactivity disorder (ADHD) is associated with neurobehavioral reward system dysfunctions that pose debilitating impairments in adaptive decision-making. A candidate mechanism for such anomalies in ADHD may be a compromise in the control of motivated behaviors. Thus, demonstrating and restoring potential motivational control irregularities may serve significant clinical benefit. The motivational control of action guides goal-directed behaviors that are driven by outcome value, and habits that are inflexibly cue-triggered. We examined whether ADHD symptomology within the general population is linked to habitual control, and whether a motivation-based manipulation can break well-learned habits. We obtained symptom severity scores from 106 participants and administered a Go/NoGo task that capitalizes on familiar, well-learned associations (green-Go and red-NoGo) to demonstrate outcome-insensitivity when compared to newly learned Go/NoGo associations. We tested for outcome-insensitive habits by changing the Go and NoGo contingencies, such that Go signals became NoGo signals and vice versa. We found that generally, participants responded less accurately when green and red stimuli were mapped to color-response contingencies that were incongruent with daily experiences, whereas novel Go/NoGo stimuli evoked similar accuracy regardless of color-response mappings. Thus, our Go/NoGo task successfully elicited outcome-insensitive habits (i.e., persistent responses to familiar stimuli without regard for consequences); however, this effect was independent of ADHD symptomology. Nevertheless, we found an association between hyperactivity and congruent Go response latency, suggesting heightened pre-potency to perform habitual Go actions as hyperactivity increases. To examine habit disruption, participants returned to the lab and underwent the familiar version of the Go/NoGo task, but were given mid-experiment performance tracking information and a monetary incentive prior to contingency change. We found that this motivational boost via dual feedback prevented the incongruency-related accuracy impairment, effectively breaking the habit, albeit independent of ADHD symptomology. Our findings present only a modest link between ADHD symptomology and motivational control, which may be due to compensatory mechanisms in ADHD driving goal-directed control, or our task’s potential insensitivity to individual differences in ADHD symptomology. Further investigations may be crucial for determining whether ADHD is related to motivational impairments.

Attention-deficit/hyperactivity disorder (ADHD) poses debilitating impairments in the neurobehavioral systems governing reward-related processes-key to the control of motivated behaviors. Individuals with ADHD may rely on a motivational control system that favors cue-driven habits-rooted in the posterior putamen-over caudate and prefrontal cortex-driven goal-directed behaviors. We examined the neurobehavioral correlates of motivational control in ADHD. Twenty-five adults with ADHD and 25 neurotypicals underwent fMRI while training on two stimulus-response-outcome associations. A devaluation procedure followed, whereby they were selectively satiated on one of the snack outcomes, decreasing its value. A subsequent extinction test determined outcome-sensitivity (i.e., whether responses towards devalued snack diminished). Despite behavioral similarities, the ADHD group displayed a distinct neural signature marked by enhanced posterior putamen activation as a function of training. This region also displayed diminished functional connectivity with the dorsal anterior cingulate cortex, which is associated with top-down control. Our whole-brain analysis yielded ADHD-specific posterior putamen and opercular/insular cortex activity over the course of training-regions associated with stimulus-sensitivity and maladaptively rigid behaviors, respectively. Neural comparisons also identified hyper-recruitment of the hippocampus in the ADHD group. These results highlight corticostriatal discrepancies in ADHD, possibly serving as a biomarker of the disorder.

In our fMRI experiment, participants completed a learning task in both a noncompetitive and a socially competitive learning environment. Despite reporting a preference for completing the task while competing, participants remembered significantly more during the task and later recalled more from the noncompetitive learning environment. Furthermore, during working memory maintenance, there was performance‐related deactivation in the medial prefrontal cortex (mPFC) and the precuneus/PCC. During feedback presentation, there was greater activation in the mPFC and the precuneus/PCC while competing. Differential activation in the precuneus/PCC predicted worse later recall for information learned competitively. Since previous research suggests that the mPFC is involved in social‐referencing, while the precuneus/PCC is implicated in off‐task thoughts, our results suggest that receiving feedback regarding competition produces more activation in brain regions implicated in social interaction, as well as task distraction. While competition may make a task more enjoyable, the goal of winning may distract from maximizing performance. Hum Brain Mapp 38:457–471, 2017. © 2016 Wiley Periodicals, Inc.

Intelligence mindset, which denotes individual beliefs about whether intelligence is fixed versus malleable, shapes academic success, but the neural mechanisms underlying mindset-related differences in learning are unknown. Here, we probe the effects of individual differences in mindset on neural responses to negative feedback after a competence threat manipulation. We hypothesized that when their competence was threatened, participants with fixed mindsets would interpret further negative feedback as punishing. After receiving either no score or a competence-threatening IQ score, participants performed a learning task with feedback that emphasized either the evaluative or informational weight of negative feedback. Participants who experienced the competence threat had the strongest predictive relationships between mindset, performance, and caudate activation. The competence threat may have compounded the subjective punishment of negative feedback for fixed mindsets relative to growth mindsets, causing poorer learning from negative feedback in the evaluative context and inflexible striatal responses to negative feedback across feedback contexts.

Performance feedback about whether responses are correct or incorrect provides valuable information to help guide learning. Although feedback itself has no extrinsic value, it can produce subjective feelings similar to “rewards” and “punishments.” Therefore, feedback can play both an informative and a motivational role. Over the past decade, researchers have identified a neural circuit that processes reward value and promotes reinforcement learning, involving target regions of dopaminergic input (e.g., striatum and ventromedial prefrontal cortex). Importantly, this circuit is engaged by performance feedback even in the absence of reward. Recent research suggests that feedback-related brain activity can be modulated by motivational context, such as whether feedback reflects goal achievement, whether learners are oriented toward the informative versus evaluative aspect of feedback, and whether individual learners are motivated to perform well relative to their peers. This body of research suggests that the brain responds flexibly to feedback, based on the learner’s goals.

Adolescence is a time of tumultuous behavior that may result, in part, from brain circuitry that enhances reward seeking. In this issue of Neuron, Davidow et al. (2016) present a convincing argument that adolescent brain functionality can be adaptive in certain contexts, particularly probabilistic learning environments.

Habits are characterized by an insensitivity to their consequences and, as such, can be distinguished from goal-directed actions. The neural basis of the development of demonstrably outcome insensitive habitual actions in humans has not been previously characterized. In this experiment, we show that extensive training on a free-operant task reduces the sensitivity of participants’ behavior to a reduction in outcome value. Analysis of functional magnetic resonance imagine (fMRI) data acquired during training revealed a significant increase in task-related cue sensitivity in a right posterior putamen/globus pallidus region as training progressed. These results provide evidence for a shift from goal-directed to habit-based control of instrumental actions in humans, and suggest that cue-driven activation in a specific region of dorsolateral posterior putamen may contribute to the habitual control of behavior in humans.

Whereas positive feedback is both rewarding and informative, negative feedback can be construed as either punishing (because it is indicative of poor performance) or informative (because it may lead to goal attainment). In this neuroimaging experiment, we highlighted the informational value of negative feedback by intermixing trials with and without feedback. When performance feedback is expected, positive feedback triggers an increase in striatal activity, whereas negative feedback elicits a decrease in striatal activity. We predicted that, in contrast, when feedback receipt is unpredictable, the striatal response to negative feedback would increase. Participants performed a paired-associate learning task during fMRI scanning. In one condition (“blocked feedback”), the receipt of feedback was predictable—participants knew whether or not they would receive feedback for their responses. In another condition (“mixed feedback”), the receipt of feedback was unpredictable—on a random 50% of trials, participants received feedback, and they otherwise received no feedback. Negative feedback in the mixed feedback condition elicited more striatal activity than negative feedback in the blocked feedback condition. In contrast, feedback omission evoked more striatal activity when feedback delivery was expected, compared to when it was unpredictable. This pattern emerged from an increase in caudate activity in response to negative feedback in the mixed feedback condition and a decrease in ventral striatal activity in response to no feedback in this condition. These results suggest that, by emphasizing the informational value of negative feedback, an unpredictable feedback context alters the striatal response to negative feedback and to the omission of feedback.

Competition has often been implicated as a means to improve effort-based learning and attention. Two experiments examined the effects of competition on effort and memory. In Experiment 1, participants completed a physical effort task in which they were rewarded for winning an overall percentage, or for winning a competition they believed was against another player. In Experiment 2, participants completed a memory task in which they were rewarded for remembering an overall percentage of shapes, or more shapes than a competitor. We found that, in the physical effort task, participants demonstrated faster reaction times—a previous indicator of increased attention— in the competitive environment. Moreover, individual differences predicted the salience of competition’s effect. Furthermore, male participants showed faster reaction times and greater sustained effort as a result of a competitive environment, suggesting that males may be more affected by competition in physical effort tasks. However, in Experiment 2, participants remembered fewer shapes when competing, and later recalled less of these shapes during a post-test, suggesting that competition was harmful in our memory task. The different results from these two experiments suggest that competition can improve attention in a physical effort task, yet caution the use of competition in memory tasks.

Research has increasingly implicated the striatum in the processing of reward-related information in both animals and humans. However, it is unclear whether human striatal activation is driven solely by the hedonic properties of rewards or whether such activation is reliant on other factors, such as anticipation of upcoming reward or performance of an action to earn a reward. We used event-related functional magnetic resonance imaging to investigate hemodynamic responses to monetary rewards and punishments in three experiments that made use of an oddball paradigm. We presented reward and punishment displays randomly in time, following an anticipatory cue, or following a button press response. Robust and differential activation of the caudate nucleus occurred only when a perception of contingency existed between the button press response and the outcome. This finding suggests that the caudate is involved in reinforcement of action potentially leading to reward, rather than in processing reward per se.

For the consequences of our actions to guide behavior, the brain must represent different types of outcome-related information. For example, an outcome can be construed as negative because an expected reward was not delivered or because an outcome of low value was delivered. Thus behavioral consequences can differ in terms of the information they provide about outcome probability and value. We investigated the role of the striatum in processing probability-based and value-based negative feedback by training participants to associate cues with food rewards and then employing a selective satiety procedure to devalue one food outcome. Using functional magnetic resonance imaging, we examined brain activity related to receipt of expected rewards, receipt of devalued outcomes, omission of expected rewards, omission of devalued outcomes, and expected omissions of an outcome. Nucleus accumbens activation was greater for rewarding outcomes than devalued outcomes, but activity in this region did not correlate with the probability of reward receipt. Activation of the right caudate and putamen, however, was largest in response to rewarding outcomes relative to expected omissions of reward. The dorsal striatum (caudate and putamen) at the time of feedback also showed a parametric increase correlating with the trialwise probability of reward receipt. Our results suggest that the ventral striatum is sensitive to the motivational relevance, or subjective value, of the outcome, while the dorsal striatum codes for a more complex signal that incorporates reward probability. Value and probability information may be integrated in the dorsal striatum, to facilitate action planning and allocation of effort.

A popular hypothesis in the social sciences is that humans have social preferences to reduce inequality in outcome distributions because it has a negative impact on their experienced reward. Although there is a large body of behavioural and anthropological evidence consistent with the predictions of these theories, there is no direct neural evidence for the existence of inequality-averse preferences. Such evidence would be especially useful because some behaviours that are consistent with a dislike for unequal outcomes could also be explained by concerns for social image or reciprocity, which do not require a direct aversion towards inequality. Here we use functional MRI to test directly for the existence of inequality-averse social preferences in the human brain. Inequality was created by recruiting pairs of subjects and giving one of them a large monetary endowment. While both subjects evaluated further monetary transfers from the experimenter to themselves and to the other participant, we measured neural responses in the ventral striatum and ventromedial prefrontal cortex, two areas that have been shown to be involved in the valuation of monetary and primary rewards in both social and non-social contexts. Consistent with inequality-averse models of social preferences, we find that activity in these areas was more responsive to transfers to others than to self in the 'high-pay' subject, whereas the activity of the 'low-pay' subject showed the opposite pattern. These results provide direct evidence for the validity of this class of models, and also show that the brain's reward circuitry is sensitive to both advantageous and disadvantageous inequality.

The striatum has been shown to play an important role in learning from performance-related feedback that is presented shortly after each response. However, less is known about the neural mechanisms supporting learning from feedback that is substantially delayed from the original response. Since the consequences of one's actions often do not become known until after a delay, it is important to understand whether delayed feedback can produce neural responses similar to those elicited by immediate-feedback presentation. We investigated this issue by using functional magnetic resonance imaging (fMRI) as participants performed a paired-associate learning task with 180 distinct trials. Feedback indicating response accuracy was presented immediately, after a delay of 25 min, or not at all. Both immediate and delayed feedback led to significant gains in accuracy on a posttest, relative to no feedback. Replicating previous work, we found that the caudate nuclei showed greater activation for positive feedback than for negative feedback when the feedback was presented immediately. In addition, delayed feedback also led to differential caudate activity to positive versus negative feedback. Delayed negative feedback also produced significant activation of the putamen and globus pallidus (the lentiform nucleus), relative to no feedback and delayed positive feedback. This suggests that the caudate nucleus is sensitive to the affective nature of feedback, across different time scales, while the lentiform nucleus may be particularly involved in processing the information carried by negative feedback after a substantial delay.

Delay discounting refers to the reduction of the value of a future reward as the delay to that reward increases. The rate at which individuals discount future rewards varies as a function of both individual and contextual differences, and high delay discounting rates have been linked with problematic behaviors, including drug abuse and gambling. The current study investigated the effects of acute anticipatory stress on delay discounting, while considering two important factors: individual perceptions of stress and whether the stressful situation is future-focused or present-focused. Half of the participants experienced acute stress by anticipating giving a videotaped speech. This stress was either future-oriented (speech about future job) or present-oriented (speech about physical appearance). They then performed a delay discounting task, in which they chose between smaller, immediate rewards, and larger, delayed rewards. Their scores on the Perceived Stress Scale were also collected. The way in which one appraises stressful situations interacts with acute stress to influence choices; under stressful conditions, delay discounting rate was highest in individuals with low trait perceived stress and lowest for individuals with high trait perceived stress. This result might be related to individual variation in reward responsiveness under stress. Furthermore, the time orientation of the task interacted with its stressfulness to affect the individual’s propensity to choose immediate rewards. These findings add to our understanding of the intermediary factors between stress and decision-making.

O. Vartanian, D.R. Mandel, Introduction. Part 1. Theoretical Models. M. Sigman, S. Dehaene, Why Does it Take Time to Make a Decision? The Role of a Global Workspace in Simple Decision Making. D.R. Mandel, O.Vartanian, Frames, Brains, and Content Domains: Neural and Behavioral Effects of Descriptive Context on Preferential Choice. Part 2. Risk and Uncertainty. A. Bechara, Human Emotions in Decision Making: Are they Useful or Disruptive? A.J. Yu, Uncertainty and Neuromodulation: Focus on Acetylcholine and Sustained Attention. W. De Neys, V. Goel, Heuristics and Biases in the Brain: Dual Neural Pathways for Decision Making. Part 3. Reward and Loss. M.R. Delgado, E. Tricomi, Reward Processing and Decision Making in the Human Striatum. J.P. O'Doherty, Neural Mechanisms Underlying Reward and Punishment Learning in the Human Brain: Insights from fMRI. D.A. Pizzagalli, D.G. Dillon, R. Bogdan, A.J. Holmes, Reward and Punishment Processing in the Human Brain: Clues from Affective Neuroscience and Implications for Depression Research. Part 4. Cooperation and Trust. A.G. Sanfey, J.K. Rilling, Neural Bases of Social Decision Making. D. Houser, R. Kurzban, E. Xiao, Social and Biological Evidence on Motives for Punishment. Part 5. Goal-directed Decision Making. K. Christoff, A. Gordon, R. Smith, The Role of Spontaneous Thought in Human Cognition. J. Moll, J. Grafman, Well, What Do You Want To Do? A Cognitive Neuroscience View of Plan Decision Making. O. Vartanian, Decision Junctures in the Creative Process.

Adults have difficulty discriminating nonnative phonetic contrasts, but under certain circumstances training can lead to improvement in this ability. Despite the ubiquitous use of performance feedback in training paradigms in this and many other domains, the mechanisms by which feedback affects learning are not well understood. In this event-related functional magnetic resonance imaging study, we examined how performance feedback is processed during perceptual learning. Thirteen Japanese speakers for whom the English phonemes [r] and [l] were nondistinct performed an identification task of the words “road” and “load” that has been shown to be effective in inducing learning only when performance feedback is present. Each subject performed alternating runs of training with and without feedback, followed by performance of a card-guessing task with monetary reward and punishment outcomes. We found that the caudate nucleus was more robustly activated bilaterally when performing the perceptual identification task with feedback than without feedback, and the right caudate nucleus also showed a differential response to positive and negative feedback. Moreover, using a within-subjects design, we found that the caudate nucleus also showed a similar activation pattern to monetary reward and punishment outcomes in the card-guessing task. These results demonstrate that the caudate responds to positive and negative feedback during learning in a manner analogous to its processing of extrinsic affective reinforcers and indicate that this region may be a critical moderator of the influence of feedback on learning. These findings impact our broader understanding of the mechanisms underlying nondeclarative learning and language acquisition.

Most temperate songbird species sing seasonally, and the brain areas involved in producing song (the song system) vary in size alongside the changes in behavior. Black-capped chickadees (Poecile atricapillus) also sing seasonally, and we find that there are changes in the stereotypy and the length of the fee-bee song from the nonbreeding to the breeding season. Yet despite these changes, we fail to find any evidence of seasonal changes in the song system. The song system of males is larger than that of females, as is typical in songbirds, but the ratio between the sexes is small compared to other species. We suggest three hypotheses to explain our failure to find seasonal variation in the chickadee song system.

The distributions of the neuropeptides substance P (SP) and neuropeptide Y (NPY) were investigated in four songbird species that differ in their food-storing behavior. The food-storing black-capped chickadee (Parus atricapillus) was compared to the non-storing blue tit (Parus caeruleus) and great tit (Parus major) within the avian family Paridae, as well as to the non-storing dark-eyed junco (Junco hyemalis). All four species showed a similar distribution of SP throughout the brain with the exception of two areas, the hippocampal complex (including hippocampus (Hp) and parahippocampus (APH)) and the Wulst (including the hyperstriatum accessorium (HA)). SP-like immunoreactivity was found in cells of the Hp in juncos, but not in the three parid species. Two areas within the APH and HA showed SP-like immunoreactivity in all four species. The more medial of these (designated SPm) is a distinctive field of fibers and terminals found throughout the APH and extending into the HA. A positive relationship between SPm and Hp volume was found for all four species with the chickadee having a significantly larger SPm area relative to telencephalon than the other species. The distribution of SP in this region may be related to differences in food-storing behavior. In contrast to substance P, NPY distribution throughout the brain was similar in all four species. Further, NPY-immunoreactive cells were found in the Hp of all four species and no species differences in the number of NPY cells was observed.

Negative feedback can signal poor performance, but it also provides information that can help learners reach the goal of task mastery. The primary aim of this study was to test the hypothesis that the amount of information provided by negative feedback during a paired-associate learning task influences feedback-related processing in the caudate nucleus. To do this, we manipulated the number of response options: With two options, positive and negative feedback provide equal amounts of information, whereas with four options, positive feedback provides more information than does negative feedback. We found that positive and negative feedback activated the caudate similarly when there were two response options. With four options, the caudate’s response to negative feedback was reduced. A secondary goal was to investigate the link between brain-based measures of feedback-related processing and behavioral indices of learning. Analysis of the posttest measures showed that trials with positive feedback were associated with higher posttest confidence ratings. Additionally, when positive feedback was delivered, caudate activity was greater for trials with high than with low posttest confidence. This experiment demonstrated the context sensitivity of feedback processing and provided evidence that feedback processing in the striatum can contribute to the strengthening of the representations available within declarative memory.