Sometimes when a choice is made, the outcome is not guaranteed and there is only a probability of its occurrence. Each individual’s attitude to probability, sometimes called risk proneness or aversion, has been assumed to be static. Behavioral ecological studies, however, suggest such attitudes are dynamically modulated by the context an organism finds itself in; in some cases, it may be optimal to pursue actions with a low probability of success but which are associated with potentially large gains. We show that human subjects rapidly adapt their use of probability as a function of current resources, goals, and opportunities for further foraging. We demonstrate that dorsal anterior cingulate cortex (dACC) carries signals indexing the pressure to pursue unlikely choices and signals related to the taking of such choices. We show that dACC exerts this control over behavior when it, rather than ventromedial prefrontal cortex, interacts with posterior cingulate cortex.
•Against common belief, risk preference is not fixed but is dynamically updated•Environments exert varying “risk pressure” tracked by ACC•Risk-related values and behavior are then regulated by ACC•Two mechanisms regulate competition for control of behavior between ACC and vmPFC
The propensity to take risks has been considered a fixed personality trait. By contrast, Kolling et al. show that people modulate their degree of risk taking from moment to moment and that this ability is related to a suite of signals in the anterior cingulate cortex.
Despite the prominence of parietal activity in human neuromaging investigations of sensorimotor and cognitive processes there remains uncertainty about basic aspects of parietal cortical anatomical organization. Descriptions of human parietal cortex draw heavily on anatomical schemes developed in other primate species but the validity of such comparisons has been questioned by claims that there are fundamental differences between the parietal cortex in humans and other primates. A scheme is presented for parcellation of human lateral parietal cortex into component regions on the basis of anatomical connectivity and the functional interactions of the resulting clusters with other brain regions. Anatomical connectivity was estimated using diffusion-weighted magnetic resonance image (MRI) based tractography and functional interactions were assessed by correlations in activity measured with functional MRI (fMRI) at rest. Resting state functional connectivity was also assessed directly in the rhesus macaque lateral parietal cortex in an additional experiment and the patterns found reflected known neuroanatomical connections. Cross-correlation in the tractography-based connectivity patterns of parietal voxels reliably parcellated human lateral parietal cortex into ten component clusters. The resting state functional connectivity of human superior parietal and intraparietal clusters with frontal and extrastriate cortex suggested correspondences with areas in macaque superior and intraparietal sulcus. Functional connectivity patterns with parahippocampal cortex and premotor cortex again suggested fundamental correspondences between inferior parietal cortex in humans and macaques. In contrast, the human parietal cortex differs in the strength of its interactions between the central inferior parietal lobule region and the anterior prefrontal cortex.
AIP; MIP; LIP; VIP; IPL; SPL
Studies in monkeys show clear anatomical and functional distinctions among networks connecting with subregions within the prefrontal cortex. Three such networks are centered on lateral orbitofrontal cortex, medial frontal and cingulate cortex, and lateral prefrontal cortex and all have been identified with distinct cognitive roles. Although these areas differ in a number of their cortical connections, some of the first anatomical evidence for these networks came from tracer studies demonstrating their distinct patterns of connectivity with the mediodorsal (MD) nucleus of the thalamus. Here, we present evidence for a similar topography of MD thalamus prefrontal connections, using non-invasive imaging and diffusion tractography (DWI–DT) in human and macaque. DWI–DT suggested that there was a high probability of interconnection between medial MD and lateral orbitofrontal cortex, between caudodorsal MD and medial frontal/cingulate cortex, and between lateral MD and lateral prefrontal cortex, in both species. Within the lateral prefrontal cortex a dorsolateral region (the principal sulcus in the macaque and middle frontal gyrus in the human) was found to have a high probability of interconnection with the MD region between the regions with a high probability of interconnection with other parts of the lateral prefrontal cortex and with the lateral orbitofrontal cortex. In addition to suggesting that the thalamic connectivity in the macaque is a good guide to human prefrontal cortex, and therefore that there are likely to be similarities in the cognitive roles played by the prefrontal areas in both species, the present results are also the first to provide insight into the topography of projections of an individual thalamic nucleus in the human brain.
Anatomy; DTI; Human; Macaque; Thalamus
Orbitofrontal cortex (OFC) is widely held to be critical for flexibility in decision-making when established choice values change. OFC's role in such decision making was investigated in macaques performing dynamically changing three-armed bandit tasks. After selective OFC lesions, animals were impaired at discovering the identity of the highest value stimulus following reversals. However, this was not caused either by diminished behavioral flexibility or by insensitivity to reinforcement changes, but instead by paradoxical increases in switching between all stimuli. This pattern of choice behavior could be explained by a causal role for OFC in appropriate contingent learning, the process by which causal responsibility for a particular reward is assigned to a particular choice. After OFC lesions, animals' choice behavior no longer reflected the history of precise conjoint relationships between particular choices and particular rewards. Nonetheless, OFC-lesioned animals could still approximate choice-outcome associations using a recency-weighted history of choices and rewards.
► OFC lesions can impair decision making in both changeable and fixed environments ► OFC is critical for assigning credit for a particular reward to a particular choice ► OFC lesions spare system to approximate learning based on choice and reward history ► Role in contingent learning underlies impairments in flexible decision making
A neural circuit that covaries with social hierarchy A neuroimaging study reveals that individual variation in brain circuits in structures below the cerebral cortex of macaques is associated with experience at different ends of the social hierarchy.
Despite widespread interest in social dominance, little is known of its neural correlates in primates. We hypothesized that social status in primates might be related to individual variation in subcortical brain regions implicated in other aspects of social and emotional behavior in other mammals. To examine this possibility we used magnetic resonance imaging (MRI), which affords the taking of quantitative measurements noninvasively, both of brain structure and of brain function, across many regions simultaneously. We carried out a series of tests of structural and functional MRI (fMRI) data in 25 group-living macaques. First, a deformation-based morphometric (DBM) approach was used to show that gray matter in the amygdala, brainstem in the vicinity of the raphe nucleus, and reticular formation, hypothalamus, and septum/striatum of the left hemisphere was correlated with social status. Second, similar correlations were found in the same areas in the other hemisphere. Third, similar correlations were found in a second data set acquired several months later from a subset of the same animals. Fourth, the strength of coupling between fMRI-measured activity in the same areas was correlated with social status. The network of subcortical areas, however, had no relationship with the sizes of individuals' social networks, suggesting the areas had a simple and direct relationship with social status. By contrast a second circuit in cortex, comprising the midsuperior temporal sulcus and anterior and dorsal prefrontal cortex, covaried with both individuals' social statuses and the social network sizes they experienced. This cortical circuit may be linked to the social cognitive processes that are taxed by life in more complex social networks and that must also be used if an animal is to achieve a high social status.
Social status is an important feature of group life in many primates. Position in the dominance hierarchy influences access to food and mates and is correlated with both general and mental health. Discovering how the brain is organized with respect to individual social status is an important first step for understanding the neural mechanisms that might drive social status and mediate its consequences. We performed a neuroimaging study in non-human primates and our findings suggest that brain organization reflects at least two aspects of dominance. First, we identified neural circuits in brain regions that appear to have a relatively simple and direct relationship with social status—one circuit in which gray matter volume tended to be greater in socially dominant individuals and another in which gray matter volume was greater in those with a more subordinate social position. We also showed that the degree of connectivity within each circuit was associated with experiences at each end of the social hierarchy. Second, given that social status in male macaques depends not only on successful engagement in agonistic behavior but also on success in forming social bonds that promote coalitions, we explored regions where gray matter relates to both social status and social network size. This second neural circuit may mediate the way in which dominance is dependent on social bond formation, which is in turn dependent on social cognition.
The human dorsal frontal cortex has been associated with the most sophisticated aspects of cognition, including those that are thought to be especially refined in humans. Here we used diffusion-weighted magnetic resonance imaging (DW-MRI) and functional MRI (fMRI) in humans and macaques to infer and compare the organization of dorsal frontal cortex in the two species. Using DW-MRI tractography-based parcellation, we identified 10 dorsal frontal regions lying between the human inferior frontal sulcus and cingulate cortex. Patterns of functional coupling between each area and the rest of the brain were then estimated with fMRI and compared with functional coupling patterns in macaques. Areas in human medial frontal cortex, including areas associated with high-level social cognitive processes such as theory of mind, showed a surprising degree of similarity in their functional coupling patterns with the frontal pole, medial prefrontal, and dorsal prefrontal convexity in the macaque. We failed to find evidence for “new” regions in human medial frontal cortex. On the lateral surface, comparison of functional coupling patterns suggested correspondences in anatomical organization distinct from those that are widely assumed. A human region sometimes referred to as lateral frontal pole more closely resembled area 46, rather than the frontal pole, of the macaque. Overall the pattern of results suggest important similarities in frontal cortex organization in humans and other primates, even in the case of regions thought to carry out uniquely human functions. The patterns of interspecies correspondences are not, however, always those that are widely assumed.
Using multivoxel pattern analysis (MVPA), we studied how distributed visual representations in human occipitotemporal cortex are modulated by attention and link their modulation to concurrent activity in frontal and parietal cortex. We detected similar occipitotemporal patterns during a simple visuoperceptual task and an attention-to-working-memory task in which one or two stimuli were cued before being presented among other pictures. Pattern strength varied from highest to lowest when the stimulus was the exclusive focus of attention, a conjoint focus, and when it was potentially distracting. Although qualitatively similar effects were seen inside regions relatively specialized for the stimulus category and outside, the former were quantitatively stronger. By regressing occipitotemporal pattern strength against activity elsewhere in the brain, we identified frontal and parietal areas exerting top-down control over, or reading information out from, distributed patterns in occipitotemporal cortex. Their interactions with patterns inside regions relatively specialized for that stimulus category were higher than those with patterns outside those regions and varied in strength as a function of the attentional condition. One area, the frontal operculum, was distinguished by selectively interacting with occipitotemporal patterns only when they were the focus of attention. There was no evidence that any frontal or parietal area actively inhibited occipitotemporal representations even when they should be ignored and were suppressed. Using MVPA to decode information within these frontal and parietal areas showed that they contained information about attentional context and/or readout information from occipitotemporal cortex to guide behavior but that frontal regions lacked information about category identity.
Using computational modelling and neuroimaging, two distinct brain systems are shown to use distinct algorithms to make parallel predictions about the environment. The predictions are then optimally combined to control behavior.
A computational approach to functional specialization suggests that brain systems can be characterized in terms of the types of computations they perform, rather than their sensory or behavioral domains. We contrasted the neural systems associated with two computationally distinct forms of predictive model: a reinforcement-learning model of the environment obtained through experience with discrete events, and continuous dynamic forward modeling. By manipulating the precision with which each type of prediction could be used, we caused participants to shift computational strategies within a single spatial prediction task. Hence (using fMRI) we showed that activity in two brain systems (typically associated with reward learning and motor control) could be dissociated in terms of the forms of computations that were performed there, even when both systems were used to make parallel predictions of the same event. A region in parietal cortex, which was sensitive to the divergence between the predictions of the models and anatomically connected to both computational networks, is proposed to mediate integration of the two predictive modes to produce a single behavioral output.
To interact effectively with the environment, brains must predict future events based on past and current experience. Predictions associated with different behavioural domains of the brain are often associated with different algorithmic forms. For example, whereas the motor system makes dynamic moment-by-moment predictions based on physical world models, the reward system is more typically associated with statistical predictions learned over discrete events. However, in perceptually rich natural environments, behaviour is not neatly segmented into tasks like “reward learning” and “motor control.” Instead, many different types of information are available in parallel. The brain must both select behaviourally relevant information and arbitrate between conflicting predictions. To investigate how the brain balances and integrates different types of predictive information, we set up a task in which humans predicted an object's flight trajectory by using one of two strategies: either a statistical model (based on where objects had often landed in the past) or dynamic calculation of the current flight trajectory. Using fMRI, we show that brain activity switches between different regions of the brain, depending on which predictive strategy was used, even though behavioural output remained the same. Furthermore, we found that brain regions involved in selecting actions took into account the predictions from both competing algorithms, weighting each algorithm optimally in terms of the precision with which it could predict the event of interest. Thus, these distinct brain systems compete to control predictive behaviour.
A central question in cognitive neuroscience regards the means by which options are compared and decisions are resolved during value-guided choice. It is clear that several component processes are needed; these include identifying options, a value-based comparison, and implementation of actions to execute the decision. What is less clear is the temporal precedence and functional organisation of these component processes in the brain. Competing models of decision making have proposed that value comparison may occur in the space of alternative actions, or in the space of abstract goods. We hypothesized that the signals observed might in fact depend upon the framing of the decision. We recorded magnetoencephalographic data from humans performing value-guided choices in which two closely related trial types were interleaved. In the first trial type, each option was revealed separately, potentially causing subjects to estimate each action's value as it was revealed and perform comparison in action-space. In the second trial type, both options were presented simultaneously, potentially leading to comparison in abstract goods-space prior to commitment to a specific action. Distinct activity patterns (in distinct brain regions) on the two trial types demonstrated that the observed frame of reference used for decision making indeed differed, despite the information presented being formally identical, between the two trial types. This provides a potential reconciliation of conflicting accounts of value-guided choice.
There are several competing theories of how the primate brain supports the ability to choose between different opportunities to obtain rewards – such as food, shelter, or more abstract goods (e.g. money). These theories suggest that the comparison of different options is either fundamentally dependent upon regions in prefrontal cortex (in which representations of abstract goods are often found), or upon motoric areas such as pre-motor and motor cortices (in which representations of specific actions are found). Evidence has been provided in support of both theories, derived largely from studies using different behavioural tasks. In this study, we show that a subtle manipulation in the behavioural task can have profound consequences for which brain regions appear to support value comparison. We recorded whole-brain magnetoencephalography data whilst subjects performed a decision task. Value comparison-related 13–30 Hz oscillations were found in ‘goods space’ in ventromedial prefrontal cortex in one trial type, but in ‘action space’ in pre-motor and primary motor cortices in another trial type - despite information presented being identical across trial types. This suggests both decision mechanisms are available in the brain, and that the brain adopts the most appropriate mechanism depending upon the current context.
Although damage to medial frontal cortex causes profound decision-making impairments, it has been difficult to pinpoint the relative contributions of key anatomical subdivisions. Here we use fMRI to examine the contributions of human ventromedial prefrontal cortex (vmPFC) and dorsal anterior cingulate cortex (dACC) during sequential choices between multiple alternatives – two key features of choices made in ecological settings. By carefully constructing options whose current value at any given decision was dissociable from their longer-term value, we were able to examine choices in current and long-term frames of reference. We present evidence showing that activity at choice and feedback in vmPFC and dACC was tied to the current choice and the best long-term option, respectively. vmPFC, mid-cingulate, and PCC encoded the relative value between the chosen and next-best option at each sequential decision, whereas dACC encoded the relative value of adapting choices from the option with the highest value in the longer-term. Furthermore, at feedback we identify temporally dissociable effects that predict repetition of the current choice and adaptation away from the long-term best option in vmPFC and dACC, respectively. These functional dissociations at choice and feedback suggest that sequential choices are subject to competing cortical mechanisms.
To decide effectively, information must not only be integrated from multiple sources but it must be distributed across the brain if it is to influence structures such as motor cortex that execute choices. Human participants integrated information from multiple, but only partially informative, cues in a probabilistic reasoning task in an optimal manner. We tested whether lateralization of alpha- and beta-band oscillatory brain activity over sensorimotor cortex reflected decision variables such as the sum of the evidence provided by observed cues - a key quantity for decision making - and whether this could be dissociated from an update signal reflecting processing of the most recent cue stimulus. Alpha- and beta-band activity in the electroencephalogram reflected the logarithm of the likelihood ratio associated with the each piece of information witnessed, and the same quantity associated with the previous cues. Only the beta-band, however, reflected the most recent cue in a manner that suggested it reflected updating processes associated with cue processing. In a second experiment, transcranial magnetic stimulation (TMS)-induced disruption was used to demonstrate that the intraparietal sulcus played a causal role both in decision making and in the appearance of sensorimotor beta-band activity.
We discuss a recent approach to investigating cognitive control, which has the potential to deal with some of the challenges inherent in this endeavour. In a model-based approach, the researcher defines a formal, computational model that performs the task at hand and whose performance matches that of a research participant. The internal variables in such a model might then be taken as proxies for latent variables computed in the brain. We discuss the potential advantages of such an approach for the study of the neural underpinnings of cognitive control and its pitfalls, and we make explicit the assumptions underlying the interpretation of data obtained using this approach.
Cognitive control; Model-based approach; Model; Reinforcement learning; Action regulation
The default mode network (DMN) of the brain consists of areas that are typically more active during rest than during active task performance. Recently however, this network has been shown to be activated by certain types of tasks. Social cognition, particularly higher-order tasks such as attributing mental states to others, has been suggested to activate a network of areas at least partly overlapping with the DMN. Here, we explore this claim, drawing on evidence from meta-analyses of functional MRI data and recent studies investigating the structural and functional connectivity of the social brain. In addition, we discuss recent evidence for the existence of a DMN in non-human primates. We conclude by discussing some of the implications of these observations.
default mode network; mentalizing; social cognition; fMRI; theory of mind; TPJ; posterior cingulate; medial frontal cortex
Decision making and learning in a real-world context require organisms to track not only the choices they make and the outcomes that follow but also other untaken, or counterfactual, choices and their outcomes. Although the neural system responsible for tracking the value of choices actually taken is increasingly well understood, whether a neural system tracks counterfactual information is currently unclear. Using a three-alternative decision-making task, a Bayesian reinforcement-learning algorithm, and fMRI, we investigated the coding of counterfactual choices and prediction errors in the human brain. Rather than representing evidence favoring multiple counterfactual choices, lateral frontal polar cortex (lFPC), dorsomedial frontal cortex (DMFC), and posteromedial cortex (PMC) encode the reward-based evidence favoring the best counterfactual option at future decisions. In addition to encoding counterfactual reward expectations, the network carries a signal for learning about counterfactual options when feedback is available—a counterfactual prediction error. Unlike other brain regions that have been associated with the processing of counterfactual outcomes, counterfactual prediction errors within the identified network cannot be related to regret theory. Furthermore, individual variation in counterfactual choice-related activity and prediction error-related activity, respectively, predicts variation in the propensity to switch to profitable choices in the future and the ability to learn from hypothetical feedback. Taken together, these data provide both neural and behavioral evidence to support the existence of a previously unidentified neural system responsible for tracking both counterfactual choice options and their outcomes.
Reinforcement learning (RL) models, which formally describe how we learn from direct experience, can explain a diverse array of animal behavior. Considering alternative outcomes that could have been obtained but were not falls outside the purview of traditional RL models. However, such counterfactual thinking can considerably accelerate learning in real-world contexts, ranging from foraging in the wild to investing in financial markets. In this study, we show that three brain regions in humans (frontopolar, dorsomedial frontal, and posteromedial cortex) play a special role in tracking “what might have been”, and whether it is worth choosing such foregone options in the future. These regions encode the net benefit of choosing the next-best alternative in the future, suggesting that the next-best alternative may be privileged over inferior alternatives in the human brain. When people subsequently witness feedback indicating what would have happened had they made a different choice, these same regions encode a key learning signal—a prediction error that signals the discrepancy between what would have happened and what people believed could have happened. Further analysis indicates these brain regions exploit counterfactual information to guide future changes in behavior. Such functions may be compromised in addiction and psychiatric conditions characterized by an inability to alter maladaptive behavior.
Lateralization in the desynchronization of anticipatory occipitoparietal alpha (8–12 Hz) oscillations has been implicated in the allocation of selective visuospatial attention. Previous studies have demonstrated that small changes in the lateralization of alpha-band activity are predictive of behavioral performance but have not directly investigated how flexibly alpha lateralization is linked to top-down attentional goals. To address this question, we presented participants with cues providing varying degrees of spatial certainty about the location at which a target would appear. Time-frequency analysis of EEG data demonstrated that manipulating spatial certainty led to graded changes in the extent to which alpha oscillations were lateralized over the occipitoparietal cortex during the cue-target interval. We found that individual differences in alpha desynchronization contralateral to attention predicted reaction times, event-related potential measures of perceptual processing of targets, and beta-band (15–25 Hz) activity typically associated with response preparation. These results support the hypothesis that anticipatory alpha modulation is a plausible neural mechanism underlying the allocation of visuospatial attention and is under flexible top-down control.
beta; electroencephalography; spatial certainty
Both the anterior cingulate cortex (ACC) and mesolimbic dopamine, particularly in the nucleus accumbens (NAc), have been implicated in allowing an animal to overcome effort constraints to obtain greater benefits. However, their exact contribution to such decisions has, to date, never been directly compared. To investigate this issue we tested rats on an operant effort-related cost–benefit decision-making task where animals selected between two response alternatives, one of which involved investing effort by lever pressing on a high fixed-ratio (FR) schedule to gain high reward [four food pellets (HR)], whereas the other led to a small amount of food on an FR schedule entailing less energetic cost [two food pellets, low reward (LR)]. All animals initially preferred to put in work to gain the HR. Systemic administration of a D2 antagonist caused a significant switch in choices towards the LR option. Similarly, post-operatively, excitotoxic ACC lesions caused a significant bias away from HR choices compared with sham-lesioned animals. There was no slowing in the speed of lever pressing and no correlation between time to complete the FR requirement and choice performance. Unexpectedly, no such alteration in choice allocation was observed in animals following 6-hydroxydopamine NAc lesions. However, these rats were consistently slower to initiate responding when cued to commence each trial and also showed a reduction in food hoarding on a species-typical foraging task. Taken together, this implies that only ACC lesions, and not 6-hydroxydopamine NAc lesions as performed here, cause a bias away from investing effort for greater reward when choosing between competing options.
6-hydroxydopamine; choice behaviour; cost–benefit; dopamine; lesion; rat
Choosing an appropriate response in an uncertain and varying world is central to adaptive behaviour. The frequent activation of the anterior cingulate cortex (ACC) in a diverse range of tasks has lead to intense interest in and debate over its role in the guidance and control of performance. Here, we consider how this issue can be informed by a series of studies considering the ACC's role in more naturalistic situations where there is no single certain correct response and the relationships between choices and their consequences vary. A neuroimaging study of response switching demonstrates that dorsal ACC is not simply concerned with self-generated responses or error monitoring in isolation, but is instead involved in evaluating the outcome of choices, positive or negative, that have been voluntarily chosen. By contrast, an interconnected part of the orbitofrontal cortex is shown to be more active when attending to consequences of actions instructed by the experimenter. This dissociation is explained with reference to the anatomy of these regions in humans as demonstrated by diffusion weighted imaging. Lesions to a corresponding ACC region in monkeys has no effect on animals' ability to detect or immediately correct errors when response contingencies reverse, but renders them unable to sustain appropriate behaviour due to an impairment in the ability to integrate over time their recent history of choices and outcomes. Taken together, this implies a prominent role for the ACC within a distributed network of regions that determine the dynamic value of actions and guide decision making appropriately.
To investigate how we orient our spatial attention, previous studies have recorded neural activity while participants are instructed where to attend. Here we contrast this classical instructed attention condition with a novel condition in which the focus of voluntary attention is not specified by the experimenter but rather is freely chosen by the participant. Central cues prompted fixating participants either to choose which of two peripheral spatial locations to covertly attend or formed an instruction. Either type of cueing initiated selective attention demonstrated behaviorally by enhanced performance at a visual detection task in comparison to a separate divided attention condition. We used functional magnetic resonance imaging to measure which areas were more active during choice than instruction. Choosing where to attend activated a large cluster of medial frontal cortical regions similar to those that have been previously implicated in the free selection of overt action. We then addressed a potential confound in contrasting choice with instruction: participants may remember their behavior more when choosing. In a separate block, and interleaved with choice trials, “memory” trials were introduced in which participants were instructed to remember where they had attended on the previous trial. The presupplementary eye fields and lateral frontal eye fields were specialized for choice-guided attentional orienting over and above any memory confound. This evidence suggests a common mechanism may underlie free selection, whether for covert attention or overt saccades.
Category-related brain activations have been reported in the posterior fusiform gyri when people view pictures of tools and animals, but only a single study has observed this pattern when the stimuli were words, rather than pictures. Here we replicate these category effects with words and provide evidence that distinctive patterns of activation are task-specific. The results suggest that category-related activation in the posterior fusiform gyri can be driven either “bottom-up” by visual processing of images or “top-down” by word processing.
category-specificity; written words; visual form processing; posterior fusiform gyri; fMRI
In order to be able to make informed and successful decisions, it is vital to be able to evaluate whether the expected benefits of a course of action make it worth tolerating the costs incurred to obtain them. The frontal lobe has been implicated in several aspects of goal-directed action selection, social interaction and optimal choice behavior. However, its exact contribution has remained elusive. Here, we discuss a series of studies in rats and primates examining the effect of discrete lesions on different aspects of cost-benefit decision making. Rats with excitotoxic lesions of the anterior cingulate cortex became less willing to invest effort for reward but showed no change when having to tolerate delays. Orbitofrontal cortex-lesioned rats, by contrast, became more impulsive, yet were just as prepared as normal animals to expend energy to obtain reward. The sulcal region of primate anterior cingulate cortex was also shown to be essential for dynamically integrating over time the recent history of choices and outcomes. Selecting a particular course of action may also come at the expense of gathering important information about other individuals. Evaluating social information when deciding whether to respond was demonstrated to be a function of the anterior cingulate gyrus. Taken together, this indicates that there may be dissociable pathways in the frontal lobe for managing different types of response cost and for gathering social information.
Anterior cingulate cortex; Orbitofrontal cortex; Decision making; Effort; Delay; Risk; Social
Economic theories of decision making are based on the principle of utility maximization, and reinforcement learning theory provides computational algorithms that can be used to estimate the overall reward expected from alternative choices. These formal models not only account for a large range of behavioral observations in human and animal decision makers, but also provide useful tools for investigating the neural basis of decision making. Nevertheless, in reality, decision makers must combine different types of information about the costs and benefits associated with each available option, such as the quality and quantity of expected reward and required work. In this article, we put forward a hypothesis that different subdivisions of the primate frontal cortex may be specialized to focus on different aspects of dynamic decision-making processes. In this hypothesis, the lateral prefrontal cortex is primarily involved in maintaining the state representation necessary to identify optimal actions in a given environment. By contrast, the orbitofrontal cortex and the anterior cingulate cortex might be largely involved in encoding and updating the utilities associated with different sensory stimuli and alternative actions, respectively. These cortical areas are also likely to contribute to decision making in a social context.
reinforcement learning; reward; cingulate cortex; prefrontal cortex; orbitofrontal cortex; neuroeconomics
Although the lesions of patients with impaired social behaviour encompass both orbitofrontal and anterior cingulate cortex (OFC and ACC), attempts to model such impairments in animals have focused on the OFC. However, recent neuroimaging attempts to identify the neural correlates of social interaction have emphasized the relative importance of ACC. Here we report the effect of circumscribed excitotoxic lesions of either OFC or ACC on ethological, unconditioned tests of emotion and social behaviour in the Lister hooded rat. OFC lesions altered emotional responsiveness to stimuli in non-social, fear-inducing situations (hyponeophagia test), and produced a small but statistically significant increase in aggression to other rats, but did not compromise other aspects of social interaction and appraisal. ACC lesions did, however, affect the utilization of social information. Specifically, ACC lesions diminished interest in other individuals and caused a relative reduction in memory for social stimuli. Whereas normal animals habituated to repeated presentations of the same individual, the poor performance of ACC animals entailed continued higher levels of responsiveness to repeated presentations of the same individual. The ACC impairment cannot simply be attributed to a general reduction in arousal, or a general impairment in recognition memory. Neither lesion affected anxiety per se (successive alleys test). Further analyses were conducted to investigate whether the changes in aggressive and social behaviour were related to different aspects of decision-making. Although the relationship between changes in social interaction and decision-making after ACC lesions is unclear, OFC impairments in emotionality were correlated with increased impulsive choice.
anxiety; behaviour; emotion; rat