Calculating the cost of acting in frontal cortex

Major depression symptom severity associations with willingness to exert effort and patch foraging strategy

Individuals with major depressive disorder (MDD) can experience reduced motivation and cognitive function, leading to challenges with goal-directed behavior. When selecting goals, people maximize 'expected value' by selecting actions that maximize potential reward while minimizing associated costs, including effort 'costs' and the opportunity cost of time. In MDD, differential weighing of costs and benefits are theorized mechanisms underlying changes in goal-directed cognition and may contribute to symptom heterogeneity. We used the Effort Foraging Task to quantify cognitive and physical effort costs, and patch leaving thresholds in low effort conditions (hypothesized to reflect perceived opportunity cost of time) and investigated their shared versus distinct relationships to clinical features in participants with MDD (N=52, 43 in-episode) and comparisons (N=27). Contrary to our predictions, none of the decision-making measures differed with MDD diagnosis. However, each of the measures were related to symptom severity, over and above effects of ability (i.e., performance). Greater anxiety symptoms were selectively associated with lower cognitive effort cost (i.e. greater willingness to exert effort). Anhedonia symptoms were associated with increased physical effort costs. Finally, greater physical anergia was related to decreased patch leaving thresholds. Markers of effort-based decision-making may inform understanding of MDD heterogeneity. Increased willingness to exert cognitive effort may contribute to anxiety symptoms such as rumination and worry. The association of decreased leaving thresholds with symptom severity is consistent with reward rate-based accounts of reduced vigor in MDD. Future research should address subtypes of depression with or without anxiety, which may relate differentially to cognitive effort decisions.

Neural basis of cognitive control signals in anterior cingulate cortex during delay discounting

Cognitive control involves allocating cognitive effort according to internal needs and task demands and the Anterior Cingulate Cortex (ACC) is hypothesized to play a central role in this process. We investigated the neural basis of cognitive control in the ACC of rats performing an adjusting-amount delay discounting task. Decision-making in this this task can be guided by using either a lever-value tracking strategy, requiring a 'resource-based' form of cognitive effort or a lever-biased strategy requiring a 'resistance-based' form of cognitive effort. We found that ACC ensembles always tightly tracked lever value on each trial, indicative of a resource-based control signal. These signals were prevalent in the neural recordings and were influenced by the delay. A shorter delay was associated with devaluing of the immediate option and a longer delay was associated with overvaluing of the immediate option. In addition, ACC theta (6-12Hz) oscillations were observed at the choice point of rats exhibiting a resistance-based strategy. These data provide candidates of neural activity patterns in the ACC that underlie the use of 'resource-based' and 'resistance-based' cognitive effort. Furthermore, these data illustrate how strategies can be engaged under different conditions in individual subjects.

Effort Foraging Task reveals positive correlation between individual differences in the cost of cognitive and physical effort in humans

Effort-based decisions, in which people weigh potential future rewards against effort costs required to achieve those rewards involve both cognitive and physical effort, though the mechanistic relationship between them is not yet understood. Here, we use an individual differences approach to isolate and measure the computational processes underlying effort-based decisions and test the association between cognitive and physical domains. Patch foraging is an ecologically valid reward rate maximization problem with well-developed theoretical tools. We developed the Effort Foraging Task, which embedded cognitive or physical effort into patch foraging, to quantify the cost of both cognitive and physical effort indirectly, by their effects on foraging choices. Participants chose between harvesting a depleting patch, or traveling to a new patch that was costly in time and effort. Participants' exit thresholds (reflecting the reward they expected to receive by harvesting when they chose to travel to a new patch) were sensitive to cognitive and physical effort demands, allowing us to quantify the perceived effort cost in monetary terms. The indirect sequential choice style revealed effort-seeking behavior in a minority of participants (preferring high over low effort) that has apparently been missed by many previous approaches. Individual differences in cognitive and physical effort costs were positively correlated, suggesting that these are perceived and processed in common. We used canonical correlation analysis to probe the relationship of task measures to self-reported affect and motivation, and found correlations of cognitive effort with anxiety, cognitive function, behavioral activation, and self-efficacy, but no similar correlations with physical effort.

Gains and Losses Affect Learning Differentially at Low and High Attentional Load

Prospective gains and losses influence cognitive processing, but it is unresolved how they modulate flexible learning in changing environments. The prospect of gains might enhance flexible learning through prioritized processing of reward-predicting stimuli, but it is unclear how far this learning benefit extends when task demands increase. Similarly, experiencing losses might facilitate learning when they trigger attentional reorienting away from loss-inducing stimuli, but losses may also impair learning by increasing motivational costs or when negative outcomes are overgeneralized. To clarify these divergent views, we tested how varying magnitudes of gains and losses affect the flexible learning of feature values in environments that varied attentional load by increasing the number of interfering object features. With this task design, we found that larger prospective gains improved learning efficacy and learning speed, but only when attentional load was low. In contrast, expecting losses impaired learning efficacy, and this impairment was larger at higher attentional load. These findings functionally dissociate the contributions of gains and losses on flexible learning, suggesting they operate via separate control mechanisms. One mechanism is triggered by experiencing loss and reduces the ability to reduce distractor interference, impairs assigning credit to specific loss-inducing features, and decreases efficient exploration during learning. The second mechanism is triggered by experiencing gains, which enhances prioritizing reward-predicting stimulus features as long as the interference of distracting features is limited. Taken together, these results support a rational theory of cognitive control during learning, suggesting that experiencing losses and experiencing distractor interference impose costs for learning.

Choice history effects in mice and humans improve reward harvesting efficiency

Choice history effects describe how future choices depend on the history of past choices. In experimental tasks this is typically framed as a bias because it often diminishes the experienced reward rates. However, in natural habitats, choices made in the past constrain choices that can be made in the future. For foraging animals, the probability of earning a reward in a given patch depends on the degree to which the animals have exploited the patch in the past. One problem with many experimental tasks that show choice history effects is that such tasks artificially decouple choice history from its consequences on reward availability over time. To circumvent this, we use a variable interval (VI) reward schedule that reinstates a more natural contingency between past choices and future reward availability. By examining the behavior of optimal agents in the VI task we discover that choice history effects observed in animals serve to maximize reward harvesting efficiency. We further distil the function of choice history effects by manipulating first- and second-order statistics of the environment. We find that choice history effects primarily reflect the growth rate of the reward probability of the unchosen option, whereas reward history effects primarily reflect environmental volatility. Based on observed choice history effects in animals, we develop a reinforcement learning model that explicitly incorporates choice history over multiple time scales into the decision process, and we assess its predictive adequacy in accounting for the associated behavior. We show that this new variant, known as the double trace model, has a higher performance in predicting choice data, and shows near optimal reward harvesting efficiency in simulated environments. These results suggests that choice history effects may be adaptive for natural contingencies between consumption and reward availability. This concept lends credence to a normative account of choice history effects that extends beyond its description as a bias.

Animals foraging for food in natural habitats compete to obtain better quality food patches. To achieve this goal, animals can rely on memory and choose the same patches that have provided higher quality of food in the past. However, in natural habitats simply identifying better food patches may not be sufficient to successfully compete with their conspecifics, as food resources can grow over time. Therefore, it makes sense to visit from time to time those patches that were associated with lower food quality in the past. This demands optimal foraging animals to keep in memory not only which food patches provided the best food quality, but also which food patches they visited recently. To see if animals track their history of visits and use it to maximize the food harvesting efficiency, we subjected them to experimental conditions that mimicked natural foraging behavior. In our behavioral tasks, we replaced food foraging behavior with a two choice task that provided rewards to mice and humans. By developing a new computational model and subjecting animals to various behavioral manipulations, we demonstrate that keeping a memory of past visits helps the animals to optimize the efficiency with which they can harvest rewards.

Neural correlates of visual attention during risky decision evidence integration

Value-based decision-making is presumed to involve a dynamic integration process that supports assessing the potential outcomes of different choice options. Decision frameworks assume the value of a decision rests on both the desirability and risk surrounding an outcome. Previous work has highlighted neural representations of risk in the human brain, and their relation to decision choice. Key neural regions including the insula and anterior cingulate cortex (ACC) have been implicated in encoding the effects of risk on decision outcomes, including approach and avoidance. Yet, it remains unknown whether these regions are involved in the dynamic integration processes that precede and drive choice, and their relationship with ongoing attention. Here, we used concurrent fMRI and eye-tracking to discern neural activation related to visual attention preceding choice between sure-thing (i.e. safe) and risky gamble options. We found activation in both dorsal ACC (dACC) and posterior insula (PI) scaled in opposite directions with the difference in attention to risky rewards relative to risky losses. PI activation also differentiated foveations on both risky options (rewards and losses) relative to a sure-thing option. These findings point to ACC involvement in ongoing evaluation of risky but higher value options. The role of PI in risky outcomes points to a more general evaluative role in the decision-making that compares both safe and risky outcomes, irrespective of potential for gains or losses.

Effort-reward balance and work motivation in rats: Effects of context and order of experience

Being motivated means exerting effort toward a goal. The 'law of least work' emphasizes a preference for exerting relatively less effort. The law crosses boundaries among species and between physical and mental work. Organisms should be highly sensitive to shifts in effort-reward balance (ERB) in order to make optimal choices. We used a free operant-foraging task to investigate changes in ERB on choice between options requiring more or less effort. Results showed a consistent preference for the option with less effort and insensitivity to shifts in ERB. A second aim explored the influence of order of experience on effort choice. Choice for the more effortful option significantly increased after experiencing an equal effort-reward relationship during the initial free operant-foraging session. This relative increase in choice for the effortful option persisted even after effort-reward imbalance. The findings highlight the importance of contextual factors such as order of experience when examining the impact of shifting effort-reward associations. Instead of ignoring or reducing order effects, the sequence of experience (e.g. for shifts in ERB) could be manipulated to enhance or reduce value of outcomes or effort itself.

The tenacious brain: How the anterior mid-cingulate contributes to achieving goals

Tenacity-persistence in the face of challenge-has received increasing attention, particularly because it contributes to better academic achievement, career opportunities and health outcomes. We review evidence from non-human primate neuroanatomy and structural and functional neuroimaging in humans suggesting that the anterior mid cingulate cortex (aMCC) is an important network hub in the brain that performs the cost/benefit computations necessary for tenacity. Specifically, we propose that its position as a structural and functional hub allows the aMCC to integrate signals from diverse brain systems to predict energy requirements that are needed for attention allocation, encoding of new information, and physical movement, all in the service of goal attainment. We review and integrate research findings from studies of attention, reward, memory, affect, multimodal sensory integration, and motor control to support this hypothesis. We close by discussing the implications of our framework for educational achievement, exercise and eating disorders, successful aging, and neuropsychiatric disorders such as depression and dementia.

Anterior cingulate cortex encoding of effortful behavior

An animal’s ability to assess the value of their behaviors to minimize energy use while maximizing goal achievement is critical to its survival. The anterior cingulate cortex (ACC) has been previously shown to play a critical role in this behavioral optimization process, especially when animals are faced with effortful behaviors. In the present study, we designed a novel task to investigate the role of the ACC in evaluating behaviors that varied in effort but all resulted in the same outcome. We recorded single unit activity from the ACC as rats ran back and forth in a shuttle box that could be tilted to different tilt angles (0, 15, and 25°) to manipulate effort. Overall, a majority of ACC neurons showed selective firing to specific effort conditions. During effort expenditure, ACC units showed a consistent firing rate bias toward the downhill route compared with the more difficult uphill route, regardless of the tilt angle of the apparatus. Once rats completed a run and received their fixed reward, ACC units also showed a clear firing rate preference for the single condition with the highest relative value (25° downhill). To assess effort preferences, we used a choice version of our task and confirmed that rats prefer downhill routes to uphill routes when given the choice. Overall, these results help to elucidate the functional role of the ACC in monitoring and evaluating effortful behaviors that may then bias decision-making toward behaviors with the highest utility.

NEW & NOTEWORTHY We developed a novel effort paradigm to investigate how the anterior cingulate cortex (ACC) responds to behaviors with varied degrees of physical effort and how changes in effort influence the ACC’s evaluation of behavioral outcomes. Our results provide evidence for a wider role of the ACC in its ability to motivate effortful behaviors and evaluate the outcome of multiple behaviors within an environment.

Rodent Models of Adaptive Value Learning and Decision-Making

Real-world decisions are rarely as straightforward as choosing between clearly "good" vs. "bad" options. More often, options must be evaluated carefully because they differ in relative value. For example, we typically learn about (and make decisions between) options in comparison, where one outcome may be more costly or risky than the other. Several neuropsychiatric conditions are characterized by atypical evaluation of effort and risk costs, including major depression, schizophrenia, autism, obsessive-compulsive disorder, and substance use disorders. Aberrant value learning and decision-making have long been considered a cognitive-behavioral endophenotype of these disorders and can be modeled in rodents. This chapter presents two general methodological domains that the experimenter can manipulate in animal decision-making tasks: risk and effort. Here, we present detailed methods of rodent tasks frequently employed within these domains: probabilistic reversal learning (PRL) and effort choice. These tasks recruit regions within rodent frontal cortex, the amygdala, and the striatum, and performance is heavily modulated by dopamine, making these assays highly valid measures in the study of behavioral and substance addictions, in particular.

The roles of the anterior cingulate cortex and its dopamine receptors in self-paced cost-benefit decision making in rats

It has been shown that the anterior cingulate cortex (ACC) and its dopamine system are crucial for decision making that requires physical/emotional effort, but not for all forms of cost-benefit decision making. Previous studies had mostly employed behavioral tasks with two competing cost-reward options that were preset by the experimenters. However, few studies have been conducted using scenarios in which the subjects have full control over the energy/time expenditure required to obtain a proportional reward. Here, we assessed the roles of the ACC and its dopamine system in cost-benefit decision making by utilizing a "do more get more" (DMGM) task and a time-reward trade-off (TRTO) task, wherein the animals were able to self-determine how much effort or time to expend at a nosepoke operandum for a proportional reward. Our results showed that (1) ACC inactivation severely impaired DMGM task performance, with a reduction in the rate of correct responses and a decrease in the effort expended, but did not affect the TRTO task; and (2) blocking ACC D2 receptors had no impact on DMGM task performance in the baseline cost-benefit scenario, but it significantly reduced the attempts to invest increased effort for a large reward when the benefit-cost ratio was reduced by half. In contrast, blocking ACC D1 receptors had no effect on DMGM task performance. These findings suggest that the ACC is required for self-paced effort-based but not for time-reward trade-off decision making. Furthermore, ACC dopamine D2 but not D1 receptors are involved in DMGM decision making.

Neuropsychiatric Phenotypes Produced by GABA Reduction in Mouse Cortex and Hippocampus

Whereas cortical GAD67 reduction and subsequent GABA level decrease are consistently observed in schizophrenia and depression, it remains unclear how these GABAergic abnormalities contribute to specific symptoms. We modeled cortical GAD67 reduction in mice, in which the Gad1 gene is genetically ablated from ~50% of cortical and hippocampal interneurons. Mutant mice showed a reduction of tissue GABA in the hippocampus and cortex including mPFC, and exhibited a cluster of effort-based behavior deficits including decreased home-cage wheel running and increased immobility in both tail suspension and forced swim tests. Since saccharine preference, progressive ratio responding to food, and learned helplessness task were normal, such avolition-like behavior could not be explained by anhedonia or behavioral despair. In line with the prevailing view that dopamine in anterior cingulate cortex (ACC) plays a role in evaluating effort cost for engaging in actions, we found that tail-suspension triggered dopamine release in ACC of controls, which was severely attenuated in the mutant mice. Conversely, ACC dopamine release by progressive ratio responding to reward, during which animals were allowed to effortlessly perform the nose-poking, was not affected in mutants. These results suggest that cortical GABA reduction preferentially impairs the effort-based behavior which requires much effort with little benefit, through a deficit of ACC dopamine release triggered by high-effort cost behavior, but not by reward-seeking behavior. Collectively, a subset of negative symptoms with a reduced willingness to expend costly effort, often observed in patients with schizophrenia and depression, may be attributed to cortical GABA level reduction.

Orbitofrontal Cortex: A Neural Circuit for Economic Decisions

Economic choice behavior entails the computation and comparison of subjective values. A central contribution of neuroeconomics has been to show that subjective values are represented explicitly at the neuronal level. With this result at hand, the field has increasingly focused on the difficult question of where in the brain and how exactly subjective values are compared to make a decision. Here, we review a broad range of experimental and theoretical results suggesting that good-based decisions are generated in a neural circuit within the orbitofrontal cortex (OFC). The main lines of evidence supporting this proposal include the fact that goal-directed behavior is specifically disrupted by OFC lesions, the fact that different groups of neurons in this area encode the input and the output of the decision process, the fact that activity fluctuations in each of these cell groups correlate with choice variability, and the fact that these groups of neurons are computationally sufficient to generate decisions. Results from other brain regions are consistent with the idea that good-based decisions take place in OFC and indicate that value signals inform a variety of mental functions. We also contrast the present proposal with other leading models for the neural mechanisms of economic decisions. Finally, we indicate open questions and suggest possible directions for future research.

Predicting Motivation: Computational Models of PFC Can Explain Neural Coding of Motivation and Effort-based Decision-making in Health and Disease

Human behavior is strongly driven by the pursuit of rewards. In daily life, however, benefits mostly come at a cost, often requiring that effort be exerted to obtain potential benefits. Medial PFC (MPFC) and dorsolateral PFC (DLPFC) are frequently implicated in the expectation of effortful control, showing increased activity as a function of predicted task difficulty. Such activity partially overlaps with expectation of reward and has been observed both during decision-making and during task preparation. Recently, novel computational frameworks have been developed to explain activity in these regions during cognitive control, based on the principle of prediction and prediction error (predicted response-outcome [PRO] model [Alexander, W. H., & Brown, J. W. Medial prefrontal cortex as an action-outcome predictor. Nature Neuroscience, 14, 1338-1344, 2011], hierarchical error representation [HER] model [Alexander, W. H., & Brown, J. W. Hierarchical error representation: A computational model of anterior cingulate and dorsolateral prefrontal cortex. Neural Computation, 27, 2354-2410, 2015]). Despite the broad explanatory power of these models, it is not clear whether they can also accommodate effects related to the expectation of effort observed in MPFC and DLPFC. Here, we propose a translation of these computational frameworks to the domain of effort-based behavior. First, we discuss how the PRO model, based on prediction error, can explain effort-related activity in MPFC, by reframing effort-based behavior in a predictive context. We propose that MPFC activity reflects monitoring of motivationally relevant variables (such as effort and reward), by coding expectations and discrepancies from such expectations. Moreover, we derive behavioral and neural model-based predictions for healthy controls and clinical populations with impairments of motivation. Second, we illustrate the possible translation to effort-based behavior of the HER model, an extended version of PRO model based on hierarchical error prediction, developed to explain MPFC-DLPFC interactions. We derive behavioral predictions that describe how effort and reward information is coded in PFC and how changing the configuration of such environmental information might affect decision-making and task performance involving motivation.

Anterior cingulate cortex supports effort allocation towards a qualitatively preferred option

The anterior cingulate cortex (ACC) is known to be involved in effortful choice, yet its role in cost-benefit evaluation of qualitatively different rewards (more/less preferred), beyond magnitude differences (larger/smaller), is poorly understood. Selecting between qualitatively different options is a decision type commonly faced by humans. Here, we assessed the role of ACC on a task that has primarily been used to probe striatal function in motivation. Rats were trained to stable performance on a progressive ratio schedule for sucrose pellets and were then given sham surgeries (control) or excitotoxic NMDA lesions of ACC. Subsequently, a choice was introduced: chow was concurrently available while animals could work for the preferred sucrose pellets. ACC lesions produced a significant decrease in lever presses for sucrose pellets compared to control, whereas chow consumption was unaffected. Lesions had no effect on sucrose pellet preference when both options were freely available. When laboratory chow was not concurrently available, ACC-lesioned rats exhibited similar lever pressing as controls. During a test under specific satiety for sucrose pellets, ACC-lesioned rats also showed intact devaluation effects. The effects of ACC lesions in our task are not mediated by decreased appetite, a change in food preference, a failure to update value or a learning deficit. Taken together, we found that ACC lesions decreased effort for a qualitatively preferred option. These results are discussed with reference to effects of striatal manipulations and our recent report of a role for basolateral amygdala in effortful choice.

Computational Models of Anterior Cingulate Cortex: At the Crossroads between Prediction and Effort

In the last two decades the anterior cingulate cortex (ACC) has become one of the most investigated areas of the brain. Extensive neuroimaging evidence suggests countless functions for this region, ranging from conflict and error coding, to social cognition, pain and effortful control. In response to this burgeoning amount of data, a proliferation of computational models has tried to characterize the neurocognitive architecture of ACC. Early seminal models provided a computational explanation for a relatively circumscribed set of empirical findings, mainly accounting for EEG and fMRI evidence. More recent models have focused on ACC's contribution to effortful control. In parallel to these developments, several proposals attempted to explain within a single computational framework a wider variety of empirical findings that span different cognitive processes and experimental modalities. Here we critically evaluate these modeling attempts, highlighting the continued need to reconcile the array of disparate ACC observations within a coherent, unifying framework.

Repeated threat (without direct harm) alters metabolic capacity in select regions that drive defensive behavior

To understand the behavioral consequences of intermittent anticipatory stress resulting from threats without accompanying physiological challenges, we developed a semi-naturalistic rodent housing and foraging environment that can include threats that are unpredictable in timing. Behavior is automatically recorded while rats forage for food or water. Over three weeks, the threats have been shown to elicit risk assessment behaviors, increase defensive burying and increase adrenal gland weight. To identify brain regions activated by this manipulation, we measured cytochrome c oxidase (COX), which is tightly coupled to neural activity. Adolescent male Sprague-Dawley rats were randomly assigned to control (CT) or unpredictable threat/stress (ST) housing conditions consisting of two tub cages, one with food and another with water, separated by a tunnel. Over three weeks (P31-P52), the ST group received randomly timed (probability of 0.25), simultaneous presentations of ferret odor, an abrupt light, and sound at the center of the tunnel. The ST group had consistently fewer tunnel crossings than the CT group, but similar body weights. Group differences in COX activity were detected in regions implicated in the control of defensive burying. There was an increase in COX activity in the hypothalamic premammillary dorsal nucleus (PMD) and lateral septum (LS), whereas a decrease was observed in the periaqueductal gray (PAG) and CA3 region of the hippocampus. There were no significant differences in the anterior cingulate cortex, prefrontal cortex, striatum or motor cortex. The sites with changes in metabolic capacity are candidates for the sites of plasticity that may underlie the behavioral adaptations to intermittent threats.

Dissociation of reward and effort sensitivity in methcathinone-induced Parkinsonism

Methcathinone‐induced Parkinsonism is a recently described extrapyramidal syndrome characterized by globus pallidus and substantia nigra lesions, which provides a unique model of basal ganglia dysfunction. We assessed motivated behaviour in this condition using a novel cost‐benefit decision‐making task, in which participants decided whether it was worth investing effort for reward. Patients showed a dissociation between reward and effort sensitivity, such that pallidonigral complex dysfunction caused them to become less sensitive to rewards, while normal sensitivity to effort costs was maintained.

A Quantitative Relationship between Signal Detection in Attention and Approach/Avoidance Behavior

This study examines how the domains of reward and attention, which are often studied as independent processes, in fact interact at a systems level. We operationalize divided attention with a continuous performance task and variables from signal detection theory (SDT), and reward/aversion with a keypress task measuring approach/avoidance in the framework of relative preference theory (RPT). Independent experiments with the same subjects showed a significant association between one SDT and two RPT variables, visualized as a three-dimensional structure. Holding one of these three variables constant, further showed a significant relationship between a loss aversion-like metric from the approach/avoidance task, and the response bias observed during the divided attention task. These results indicate that a more liberal response bias under signal detection (i.e., a higher tolerance for noise, resulting in a greater proportion of false alarms) is associated with higher "loss aversion." Furthermore, our functional model suggests a mechanism for processing constraints with divided attention and reward/aversion. Together, our results argue for a systematic relationship between divided attention and reward/aversion processing in humans.

Emotional and cognitive dysregulation in schizophrenia and depression: understanding common and distinct behavioral and neural mechanisms

Emerging behavioral and neuroimaging studies in schizophrenia (SCZ) and major depressive disorder (MD) are mapping mechanisms of co-occurring and distinct affective disturbances across these disorders. This constitutes a critical goal towards developing rationally guided therapies for upstream neural pathways that contribute to comorbid symptoms across disorders. We highlight the current state of the art in our understanding of emotional dysregulation in SCZ versus MD by focusing on broad domains of behavioral function that can map onto underlying neural systems, namely deficits in hedonics, anticipatory behaviors, computations underlying value and effort, and effortful goal-directed behaviors needed to pursue rewarding outcomes. We highlight unique disturbances in each disorder that may involve dissociable neural systems, but also possible interactions between affect and cognition in MD versus SCZ. Finally, we review computational and translational approaches that offer mechanistic insight into how cellular-level disruptions can lead to complex affective disturbances, informing development of therapies across MD and SCZ.

Parallel inputs from the mediodorsal thalamus to the prefrontal cortex in the rat

There is a growing interest in determining the functional contribution of thalamic inputs to cortical functions. In the context of adaptive behaviours, identifying the precise role of the mediodorsal thalamus (MD) in particular remains difficult despite the large amount of experimental data available. A better understanding of the thalamocortical connectivity of this region may help to capture its functional role. To address this issue, this study focused exclusively on the specific connections from the MD to the prefrontal cortex (PFC) by means of direct comparisons of labelling produced by single and dual injections of retrograde tracers in the different subdivisions of the PFC in the rat. We show that at least three parallel and essentially separate thalamocortical pathways originate from the MD, as follows: projections to the dorsal (1) and the ventral (2) subdivisions of the mPFC follow a mediolateral topography at the thalamic level (i.e. medial thalamic neurons target the mPFC ventrally whereas lateral thalamic neurons project dorsally), whereas a considerable innervation to the OFC (3) includes thalamic cells projecting to both the lateral and the ventral OFC subdivisions. These observations provide new insight on the functions of the MD and suggest a specific focus on each of these pathways for future functional studies.

Neural and neurochemical basis of reinforcement-guided decision making

Decision making is an adaptive behavior that takes into account several internal and external input variables and leads to the choice of a course of action over other available and often competing alternatives. While it has been studied in diverse fields ranging from mathematics, economics, ecology, and ethology to psychology and neuroscience, recent cross talk among perspectives from different fields has yielded novel descriptions of decision processes. Reinforcement-guided decision making models are based on economic and reinforcement learning theories, and their focus is on the maximization of acquired benefit over a defined period of time. Studies based on reinforcement-guided decision making have implicated a large network of neural circuits across the brain. This network includes a wide range of cortical (e.g., orbitofrontal cortex and anterior cingulate cortex) and subcortical (e.g., nucleus accumbens and subthalamic nucleus) brain areas and uses several neurotransmitter systems (e.g., dopaminergic and serotonergic systems) to communicate and process decision-related information. This review discusses distinct as well as overlapping contributions of these networks and neurotransmitter systems to the processing of decision making. We end the review by touching on neural circuitry and neuromodulatory regulation of exploratory decision making.

Does my brain want what my eyes like? - How food liking and choice influence spatio-temporal brain dynamics of food viewing

How food valuation and decision-making influence the perception of food is of major interest to better understand food intake behavior and, by extension, body weight management. Our study investigated behavioral responses and spatio-temporal brain dynamics by means of visual evoked potentials (VEPs) in twenty-two normal-weight participants when viewing pairs of food photographs. Participants rated how much they liked each food item (valuation) and subsequently chose between the two alternative food images. Unsurprisingly, strongly liked foods were also chosen most often. Foods were rated faster as strongly liked than as mildly liked or disliked irrespective of whether they were subsequently chosen over an alternative. Moreover, strongly liked foods were subsequently also chosen faster than the less liked alternatives. Response times during valuation and choice were positively correlated, but only when foods were liked; the faster participants rated foods as strongly liked, the faster they were in choosing the food item over an alternative. VEP modulations by the level of liking attributed as well as the subsequent choice were found as early as 135-180ms after food image onset. Analyses of neural source activity patterns over this time interval revealed an interaction between liking and the subsequent choice within the insula, dorsal frontal and superior parietal regions. The neural responses to food viewing were found to be modulated by the attributed level of liking only when foods were chosen, not when they were dismissed for an alternative. Therein, the responses to disliked foods were generally greater than those to foods that were liked more. Moreover, the responses to disliked but chosen foods were greater than responses to disliked foods which were subsequently dismissed for an alternative offer. Our findings show that the spatio-temporal brain dynamics to food viewing are immediately influenced both by how much foods are liked and by choices taken on them. These valuation and choice processes are subserved by brain regions involved in salience and reward attribution as well as in decision-making processes, which are likely to influence prospective dietary choices in everyday life.

Action-outcome relationships are represented differently by medial prefrontal and orbitofrontal cortex neurons during action execution

Internal representations of action-outcome relationships are necessary for flexible adaptation of motivated behavior in dynamic environments. Prefrontal cortex (PFC) is implicated in flexible planning and execution of goal-directed actions, but little is known about how information about action-outcome relationships is represented across functionally distinct regions of PFC. Here, we observe distinct patterns of action-evoked single unit activity in the medial prefrontal cortex (mPFC) and orbitofrontal cortex (OFC) during a task in which the relationship between outcomes and actions was independently manipulated. The mPFC encoded changes in the number of actions required to earn a reward, but not fluctuations in outcome magnitude. In contrast, OFC neurons decreased firing rates as outcome magnitude was increased, but were insensitive to changes in action requirement. A subset of OFC neurons also tracked outcome availability. Pre-outcome anticipatory activity in both mPFC and OFC was altered when reward expectation was reduced, but did not differ with outcome magnitude. These data provide novel evidence that PFC regions encode distinct information about the relationship between actions and impending outcomes during action execution.

Effort-Based Decision Making: A Novel Approach for Assessing Motivation in Schizophrenia

Because negative symptoms, including motivational deficits, are a critical unmet need in schizophrenia, there are many ongoing efforts to develop new pharmacological and psychosocial interventions for these impairments. A common challenge of these studies involves how to evaluate and select optimal endpoints. Currently, all studies of negative symptoms in schizophrenia depend on ratings from clinician-conducted interviews. Effort-based decision-making tasks may provide a more objective, and perhaps more sensitive, endpoint for trials of motivational negative symptoms. These tasks assess how much effort a person is willing to exert for a given level of reward. This area has been well-studied with animal models of effort and motivation, and effort-based decision-making tasks have been adapted for use in humans. Very recently, several studies have examined physical and cognitive types of effort-based decision-making tasks in cross-sectional studies of schizophrenia, providing evidence for effort-related impairment in this illness. This article covers the theoretical background on effort-based decision-making tasks to provide a context for the subsequent articles in this theme section. In addition, we review the existing literature of studies using these tasks in schizophrenia, consider some practical challenges in adapting them for use in clinical trials in schizophrenia, and discuss interpretive challenges that are central to these types of tasks.

Utility-free heuristic models of two-option choice can mimic predictions of utility-stage models under many conditions

Economists often model choices as if decision-makers assign each option a scalar value variable, known as utility, and then select the option with the highest utility. It remains unclear whether as-if utility models describe real mental and neural steps in choice. Although choices alone cannot prove the existence of a utility stage, utility transformations are often taken to provide the most parsimonious or psychologically plausible explanation for choice data. Here, we show that it is possible to mathematically transform a large set of common utility-stage two-option choice models (specifically ones in which dimensions are can be decomposed into additive functions) into a heuristic model (specifically, a dimensional prioritization heuristic) that has no utility computation stage. We then show that under a range of plausible assumptions, both classes of model predict similar neural responses. These results highlight the difficulties in using neuroeconomic data to infer the existence of a value stage in choice.

The evolutionary roots of human decision making

Humans exhibit a suite of biases when making economic decisions. We review recent research on the origins of human decision making by examining whether similar choice biases are seen in nonhuman primates, our closest phylogenetic relatives. We propose that comparative studies can provide insight into four major questions about the nature of human choice biases that cannot be addressed by studies of our species alone. First, research with other primates can address the evolution of human choice biases and identify shared versus human-unique tendencies in decision making. Second, primate studies can constrain hypotheses about the psychological mechanisms underlying such biases. Third, comparisons of closely related species can identify when distinct mechanisms underlie related biases by examining evolutionary dissociations in choice strategies. Finally, comparative work can provide insight into the biological rationality of economically irrational preferences.

Mechanisms Underlying Motivational Deficits in Psychopathology: Similarities and Differences in Depression and Schizophrenia

Motivational and hedonic impairments are core aspects of a variety of types of psychopathology. These impairments cut across diagnostic categories and may be critical to understanding major aspects of the functional impairments accompanying psychopathology. Given the centrality of motivational and hedonic systems to psychopathology, the Research Domain Criteria (RDoC) initiative includes a "positive valence" systems domain that outlines a number of constructs that may be key to understanding the nature and mechanisms of motivational and hedonic impairments in psychopathology. These component constructs include initial responsiveness to reward, reward anticipation or expectancy, incentive or reinforcement learning, effort valuation, and action selection. Here, we review behavioral and neuroimaging studies providing evidence for impairments in these constructs in individuals with psychosis versus in individuals with depressive pathology. There are important differences in the nature of reward-related and hedonic deficits associated with psychosis versus depression that have major implications for our understanding of etiology and treatment development. In particular, the literature strongly suggests the presence of impairments in in-the-moment hedonics or "liking" in individuals with depressive pathology, particularly among those who experience anhedonia. Such deficits may propagate forward and contribute to impairments in other constructs that are dependent on hedonic responses, such as anticipation, learning, effort, and action selection. Such hedonic impairments could reflect alterations in dopamine and/or opioid signaling in the striatum related to depression or specifically to anhedonia in depressed populations. In contrast, the literature points to relatively intact in-the-moment hedonic processing in psychosis, but provides much evidence for impairments in other components involved in translating reward to action selection. Particularly, individuals with schizophrenia exhibit altered reward prediction and associated striatal and prefrontal activation, impaired reward learning, and impaired reward-modulated action selection.

Cognitive control and the anterior cingulate cortex: how conflicting stimuli affect attentional control in the rat

Converging evidence supports the hypothesis that the prefrontal cortex is critical for cognitive control. One prefrontal subregion, the anterior cingulate cortex, is hypothesized to be necessary to resolve response conflicts, disregard salient distractors and alter behavior in response to the generation of an error. These situations all involve goal-oriented monitoring of performance in order to effectively adjust cognitive processes. Several neuropsychological disorders, e.g., schizophrenia, attention deficit hyperactivity and obsessive compulsive disorder, are accompanied by morphological changes in the anterior cingulate cortex. These changes are hypothesized to underlie the impairments on tasks that require cognitive control found in these subjects. A novel conflict monitoring task was used to assess the effects on cognitive control of excitotoxic lesions to anterior cingulate cortex in rats. Prior to surgery all subjects showed improved accuracy on the second of two consecutive, incongruent trials. Lesions to the anterior cingulate cortex abolished this. Lesioned animals had difficulty in adjusting cognitive control on a trial-by-trial basis regardless of whether cognitive changes were increased or decreased. These results support a role for the anterior cingulate cortex in adjustments in cognitive control.

Précis on The Cognitive-Emotional Brain

In The Cognitive-Emotional Brain (Pessoa 2013), I describe the many ways that emotion and cognition interact and are integrated in the brain. The book summarizes five areas of research that support this integrative view and makes four arguments to organize each area. (1) Based on rodent and human data, I propose that the amygdala's functions go beyond emotion as traditionally conceived. Furthermore, the processing of emotion-laden information is capacity limited, thus not independent of attention and awareness. (2) Cognitive-emotional interactions in the human prefrontal cortex (PFC) assume diverse forms and are not limited to mutual suppression. Particularly, the lateral PFC is a focal point for cognitive-emotional interactions. (3) Interactions between motivation and cognition can be seen across a range of perceptual and cognitive tasks. Motivation shapes behavior in specific ways – for example, by reducing response conflict or via selective effects on working memory. Traditional accounts, by contrast, typically describe motivation as a global activation independent of particular control demands. (4) Perception and cognition are directly influenced by information with affective or motivational content in powerful ways. A dual competition model outlines a framework for such interactions at the perceptual and executive levels. A specific neural architecture is proposed that embeds emotional and motivational signals into perception and cognition through multiple channels. (5) A network perspective should supplant the strategy of understanding the brain in terms of individual regions. More broadly, in a network view of brain architecture, “emotion” and “cognition” may be used as labels of certain behaviors, but will not map cleanly into compartmentalized pieces of the brain.

The motivation and pleasure dimension of negative symptoms: neural substrates and behavioral outputs

A range of emotional and motivation impairments have long been clinically documented in people with schizophrenia, and there has been a resurgence of interest in understanding the psychological and neural mechanisms of the so-called "negative symptoms" in schizophrenia, given their lack of treatment responsiveness and their role in constraining function and life satisfaction in this illness. Negative symptoms comprise two domains, with the first covering diminished motivation and pleasure across a range of life domains and the second covering diminished verbal and non-verbal expression and communicative output. In this review, we focus on four aspects of the motivation/pleasure domain, providing a brief review of the behavioral and neural underpinnings of this domain. First, we cover liking or in-the-moment pleasure: immediate responses to pleasurable stimuli. Second, we cover anticipatory pleasure or wanting, which involves prediction of a forthcoming enjoyable outcome (reward) and feeling pleasure in anticipation of that outcome. Third, we address motivation, which comprises effort computation, which involves figuring out how much effort is needed to achieve a desired outcome, planning, and behavioral response. Finally, we cover the maintenance emotional states and behavioral responses. Throughout, we consider the behavioral manifestations and brain representations of these four aspects of motivation/pleasure deficits in schizophrenia. We conclude with directions for future research as well as implications for treatment.

Overlapping neural systems represent cognitive effort and reward anticipation

Anticipating a potential benefit and how difficult it will be to obtain it are valuable skills in a constantly changing environment. In the human brain, the anticipation of reward is encoded by the Anterior Cingulate Cortex (ACC) and Striatum. Naturally, potential rewards have an incentive quality, resulting in a motivational effect improving performance. Recently it has been proposed that an upcoming task requiring effort induces a similar anticipation mechanism as reward, relying on the same cortico-limbic network. However, this overlapping anticipatory activity for reward and effort has only been investigated in a perceptual task. Whether this generalizes to high-level cognitive tasks remains to be investigated. To this end, an fMRI experiment was designed to investigate anticipation of reward and effort in cognitive tasks. A mental arithmetic task was implemented, manipulating effort (difficulty), reward, and delay in reward delivery to control for temporal confounds. The goal was to test for the motivational effect induced by the expectation of bigger reward and higher effort. The results showed that the activation elicited by an upcoming difficult task overlapped with higher reward prospect in the ACC and in the striatum, thus highlighting a pivotal role of this circuit in sustaining motivated behavior.

Cost-benefit analysis: the first real rule of fight club?

Competition is ubiquitous among social animals. Vying against a conspecific to achieve a particular outcome often requires one to act aggressively, but this is a costly and inherently risky behavior. So why do we aggressively compete, or at the extreme, fight against others? Early work suggested that competitive aggression might stem from an innate aggressive tendency, emanating from subcortical structures. Later work highlighted key cortical regions that contribute toward an instrumental aggression network, one that is recruited or suppressed as needed to achieve a goal. Recent neuroimaging work hints that competitive aggression is upmost a cost-benefit decision, in that it appears to recruit many components of traditional, non-social decision-making networks. This review provides a historical glimpse into the neuroscience of competitive aggression, and proposes a conceptual advancement for studying competitive behavior by outlining how utility calculations of contested-for resources are skewed, pre- and post-competition. A basic multi-factorial model of utility assessment is proposed to account for competitive endowment effects that stem from the presence of peers, peer salience and disposition, and the tactical effort required for victory. In part, competitive aggression is a learned behavior that should only be repeated if positive outcomes are achieved. However, due to skewed utility assessments, deviations of associative learning occur. Hence truly careful cost-benefit analysis is warranted before choosing to vie against another.

The expected value of control: an integrative theory of anterior cingulate cortex function

The dorsal anterior cingulate cortex (dACC) has a near-ubiquitous presence in the neuroscience of cognitive control. It has been implicated in a diversity of functions, from reward processing and performance monitoring to the execution of control and action selection. Here, we propose that this diversity can be understood in terms of a single underlying function: allocation of control based on an evaluation of the expected value of control (EVC). We present a normative model of EVC that integrates three critical factors: the expected payoff from a controlled process, the amount of control that must be invested to achieve that payoff, and the cost in terms of cognitive effort. We propose that dACC integrates this information, using it to determine whether, where and how much control to allocate. We then consider how the EVC model can explain the diverse array of findings concerning dACC function.

Neural substrates underlying effort computation in schizophrenia

The lack of initiative, drive or effort in patients with schizophrenia is linked to marked functional impairments. However, our assessment of effort and motivation is crude, relying on clinical rating scales based largely on patient recall. In order to better understand the neurobiology of effort in schizophrenia, we need more rigorous measurements of this construct. In the behavioural neuroscience literature, decades of work has been carried out developing various paradigms to examine the neural underpinnings of an animal's willingness to expend effort for a reward. Here, we shall review this literature on the nature of paradigms used in rodents to assess effort, as well as those used in humans. Next, the neurobiology of these effort-based decisions will be discussed. We shall then review what is known about effort in schizophrenia, and what might be inferred from experiments done in other human populations. Lastly, we shall discuss future directions of research that may assist in shedding light on the neurobiology of effort cost computations in schizophrenia.

Motivated action: new light on prefrontal-neuromodulatory circuits

A new study has used optogenetic methods to stimulate prefrontal-brainstem neuromodulatory pathways while animals face environmental stressors, the results providing further compelling evidence that prefrontal control of neuromodulatory function can have a dramatic effect on motivated behavior.

Effort increases sensitivity to reward and loss magnitude in the human brain

It is ecologically adaptive that the amount of effort invested to achieve a reward increases the relevance of the resulting outcome. Here, we investigated the effect of effort on activity in reward and loss processing brain areas by using functional magnetic resonance imaging. In total, 28 subjects were endowed with monetary rewards of randomly varying magnitude after performing arithmetic calculations that were either difficult (high effort), easy (low effort) or already solved (no effort). Subsequently, a forced donation took place, where a varying part of the endowment was transferred to a charity organization, causing a loss for the subject. Results show that reward magnitude positively modulates activity in reward-processing brain areas (subgenual anterior cingulate cortex and nucleus accumbens) only in the high effort condition. Furthermore, anterior insular activity was positively modulated by loss magnitude only after high effort. The results strongly suggest an increasing relevance of outcomes with increasing previous effort.

What if I Get Busted? Deception, Choice, and Decision-Making in Social Interaction

Deception is an essentially social act, yet little is known about how social consequences affect the decision to deceive. In this study, participants played a computerized game of deception without constraints on whether or when to attempt to deceive their opponent. Participants were questioned by an opponent outside the scanner about their knowledge of the content of a display. Importantly, questions were posed so that, in some conditions, it was possible to be deceptive, while in other conditions it was not. To simulate a realistic interaction, participants could be confronted about their claims by the opponent. This design, therefore, creates a context in which a deceptive participant runs the risk of being punished if their deception is detected. Our results show that participants were slower to give honest than to give deceptive responses when they knew more about the display and could use this knowledge for their own benefit. The condition in which confrontation was not possible was associated with increased activity in subgenual anterior cingulate cortex. The processing of a question which allows a deceptive response was associated with activation in right caudate and inferior frontal gyrus. Our findings suggest the decision to deceive is affected by the potential risk of social confrontation rather than the claim itself.

Attention for learning signals in anterior cingulate cortex

Learning theory suggests that animals attend to pertinent environmental cues when reward contingencies unexpectedly change so that learning can occur. We have previously shown that activity in basolateral nucleus of amygdala (ABL) responds to unexpected changes in reward value, consistent with unsigned prediction error signals theorized by Pearce and Hall. However, changes in activity were present only at the time of unexpected reward delivery, not during the time when the animal needed to attend to conditioned stimuli that would come to predict the reward. This suggested that a different brain area must be signaling the need for attention necessary for learning. One likely candidate to fulfill this role is the anterior cingulate cortex (ACC). To test this hypothesis, we recorded from single neurons in ACC as rats performed the same behavioral task that we have used to dissociate signed from unsigned prediction errors in dopamine and ABL neurons. In this task, rats chose between two fluid wells that produced varying magnitudes of and delays to reward. Consistent with previous work, we found that ACC detected errors of commission and reward prediction errors. We also found that activity during cue sampling encoded reward size, but not expected delay to reward. Finally, activity in ACC was elevated during trials in which attention was increased following unexpected upshifts and downshifts in value. We conclude that ACC not only signals errors in reward prediction, as previously reported, but also signals the need for enhanced neural resources during learning on trials subsequent to those errors.

Anterior cingulate neurons in the rat map anticipated effort and reward to their associated action sequences

Goal-directed behaviors require the consideration and expenditure of physical effort. The anterior cingulate cortex (ACC) appears to play an important role in evaluating effort and reward and in organizing goal-directed actions. Despite agreement regarding the involvement of the ACC in these processes, the way in which effort-, reward-, and motor-related information is registered by networks of ACC neurons is poorly understood. To contrast ACC responses to effort, reward, and motor behaviors, we trained rats on a reversal task in which the selected paths on a track determined the level of effort or reward. Effort was presented in the form of an obstacle that was climbed to obtain reward. We used single-unit recordings to identify neural correlates of effort- and reward-guided behaviors. During periods of outcome anticipation, 52% of recorded ACC neurons responded to the specific route taken to the reward while 21% responded prospectively to effort and 12% responded prospectively to reward. In addition, effort- and reward-selective neurons typically responded to the route, suggesting that these cells integrated motor-related activity with expectations of future outcomes. Furthermore, the activity of ACC neurons did not discriminate between choice and forced trials or respond to a more generalized measure of outcome value. Nearly all neural responses to effort and reward occurred after path selection and were restricted to discrete temporal/spatial stages of the task. Together, these findings support a role for the ACC in integrating route-specific actions, effort, and reward in the service of sustaining discrete movements through an effortful series of goal-directed actions.

Can the neuroeconomics revolution revolutionize psychiatry?

Neuroeconomics is a rapidly growing new research discipline aimed at describing the neural substrate of decision-making using incentivized decisions introduced in experimental economics. The novel combination of economic decision theory and neuroscience has the potential to better examine the interactions of social, psychological and neural factors with regard to motivational forces that may underlie psychiatric problems. Game theory will provide psychiatry with computationally principled measures of cognitive dysfunction. Given the relatively high heritability of these measures, they may contribute to improving phenotypic definitions of psychiatric conditions. The game-theoretical concepts of optimal behavior will allow description of psychopathology as deviation from optimal functioning. Neuroeconomists have successfully used normative or near-normative models to interpret the function of neurotransmitters; these models have the potential to significantly improve neurotransmitter theories of psychiatric disorders. This paper will review recent evidence from neuroeconomics and psychiatry in support of applying economic concepts such as risk/uncertainty preference, time preference and social preference to psychiatric research to improve diagnostic classification, prevention and therapy.

Parallel declines in cognition, motivation, and locomotion in aging mice: association with immune gene upregulation in the medial prefrontal cortex

Aging in humans is associated with parallel changes in cognition, motivation, and motoric performance. Based on the human aging literature, we hypothesized that this constellation of age-related changes is mediated by the medial prefrontal cortex and that it would be observed in aging mice. Toward this end, we performed detailed assessments of cognition, motivation, and motoric behavior in aging mice. We assessed behavioral and cognitive performance in C57Bl/6 mice aged 6, 18, and 24 months, and followed this with microarray analysis of tissue from the medial prefrontal cortex and analysis of serum cytokine levels. Multivariate modeling of these data suggested that the age-related changes in cognition, motivation, motor performance, and prefrontal immune gene expression were highly correlated. Peripheral cytokine levels were also correlated with these variables, but less strongly than measures of prefrontal immune gene upregulation. To determine whether the observed immune gene expression changes were due to prefrontal microglial cells, we isolated CD11b-positive cells from the prefrontal cortex and subject them to next-generation RNA sequencing. Many of the immune changes present in whole medial prefrontal cortex were enriched in this cell population. These data suggest that, as in humans, cognition, motivation, and motoric performance in the mouse change together with age and are strongly associated with CNS immune gene upregulation.

The neural basis of intuitive and counterintuitive moral judgment

Neuroimaging studies on moral decision-making have thus far largely focused on differences between moral judgments with opposing utilitarian (well-being maximizing) and deontological (duty-based) content. However, these studies have investigated moral dilemmas involving extreme situations, and did not control for two distinct dimensions of moral judgment: whether or not it is intuitive (immediately compelling to most people) and whether it is utilitarian or deontological in content. By contrasting dilemmas where utilitarian judgments are counterintuitive with dilemmas in which they are intuitive, we were able to use functional magnetic resonance imaging to identify the neural correlates of intuitive and counterintuitive judgments across a range of moral situations. Irrespective of content (utilitarian/deontological), counterintuitive moral judgments were associated with greater difficulty and with activation in the rostral anterior cingulate cortex, suggesting that such judgments may involve emotional conflict; intuitive judgments were linked to activation in the visual and premotor cortex. In addition, we obtained evidence that neural differences in moral judgment in such dilemmas are largely due to whether they are intuitive and not, as previously assumed, to differences between utilitarian and deontological judgments. Our findings therefore do not support theories that have generally associated utilitarian and deontological judgments with distinct neural systems.