Primate Orbitofrontal Cortex Codes Information Relevant for Managing Explore-Exploit Tradeoffs

Reward monitoring in the frontopolar cortex of macaques

Reward processing involves several prefrontal cortex areas, enabling individuals to learn from behavioral outcomes and shape decisions. However, the role of the frontopolar cortex (FPC) in these processes remains unclear due to limited single-neuron research. In this study, we recorded neural activity from the FPC of two macaques performing a fast-learning task, the object-in-place reward task, which examined how reward size affects learning. Results showed that FPC feedback monitoring activity extends to the value of specific choices. Moreover, once the association between scenes and reward had been learned, FPC neural activity before choice reflected the future animal's behavior to stay or to switch on their previous behavioral strategy, i.e., to choose the same target or the other one. These results suggest that FPC neurons integrated information for action monitoring and later reprocessed it to decide the best behavioral strategy to adopt, determining whether to maintain or change the action plan.

Home-Cage Training for Non-Human Primates: An Opportunity to Reduce Stress and Study Natural Behavior in Neurophysiology Experiments

Research involving non-human primates remains a cornerstone in fields such as biomedical research and systems neuroscience. However, the daily routines of laboratory work can induce stress in these animals, potentially compromising their well-being and the reliability of experimental outcomes. To address this, many laboratories have adopted home-cage training protocols to mitigate stress caused by routine procedures such as transport and restraint-a factor that can impact both macaque physiology and experimental validity. This review explores the primary methods and experimental setups employed in home-cage training, highlighting their potential not only to address ethical concerns surrounding animal welfare but also to reduce training time and risks for the researchers. Furthermore, by combining home-cage training with wireless recordings, it becomes possible to expand research opportunities in behavioral neurophysiology with non-human primates. This approach enables the study of various cognitive processes in more naturalistic settings, thereby increasing the ecological validity of scientific findings through innovative experimental designs that thoroughly investigate the complexity of the animals' natural behavior.

A subcortical switchboard for perseverative, exploratory and disengaged states

To survive in dynamic environments with uncertain resources, animals must adapt their behaviour flexibly, choosing strategies such as persevering with a current choice, exploring alternatives or disengaging altogether. Previous studies have mainly investigated how forebrain regions represent choice costs and values as well as optimal strategies during such decisions1-5. However, the neural mechanisms by which the brain implements alternative behavioural strategies such as persevering, exploring or disengaging remain poorly understood. Here we identify a neural hub that is critical for flexible switching between behavioural strategies, the median raphe nucleus (MRN). Using cell-type-specific optogenetic manipulations, fibre photometry and circuit tracing in mice performing diverse instinctive and learnt behaviours, we found that the main cell types of the MRN-GABAergic (γ-aminobutyric acid-expressing), glutamatergic (VGluT2+) and serotonergic neurons-have complementary functions and regulate perseverance, exploration and disengagement, respectively. Suppression of MRN GABAergic neurons-for instance, through inhibitory input from lateral hypothalamus, which conveys strong positive valence to the MRN-leads to perseverative behaviour. By contrast, activation of MRN VGluT2+ neurons drives exploration. Activity of serotonergic MRN neurons is necessary for general task engagement. Input from the lateral habenula that conveys negative valence suppresses serotonergic MRN neurons, leading to disengagement. These findings establish the MRN as a central behavioural switchboard that is uniquely positioned to flexibly control behavioural strategies. These circuits thus may also have an important role in the aetiology of major mental pathologies such as depressive or obsessive-compulsive disorders.

Neural dynamics of semantic control underlying generative storytelling

Storytelling has been pivotal for the transmission of knowledge across human history, yet the role of semantic control and its associated neural dynamics has been poorly investigated. Here, human participants generated stories that were either appropriate (ordinary), novel (random), or balanced (creative), while recording functional magnetic resonance imaging (fMRI). Deep language models confirmed participants adherence to task instructions. At the neural level, linguistic and visual areas exhibited neural synchrony across participants regardless of the semantic control level, with parietal and frontal regions being more synchronized during random ideation. Importantly, creative stories were differentiated by a multivariate pattern of neural activity in frontal and fronto-temporo-parietal cortices compared to ordinary and random stories. Crucially, similar brain regions were also encoding the features that distinguished the stories. Moreover, we found specific spatial frequency patterns underlying the modulation of semantic control during story generation, while functional coupling in default, salience, and control networks differentiated creative stories with their controls. Remarkably, the temporal irreversibility between visual and high-level areas was higher during creative ideation, suggesting the enhanced hierarchical structure of causal interactions as a neural signature of creative storytelling. Together, our findings highlight the neural mechanisms underlying the regulation of semantic exploration during narrative ideation.

Preferences reveal dissociable encoding across prefrontal-limbic circuits

Individual preferences for the flavor of different foods and fluids exert a strong influence on behavior. Most current theories posit that preferences are integrated with other state variables in the orbitofrontal cortex (OFC), which is thought to derive the relative subjective value of available options to guide choice behavior. Here, we report that instead of a single integrated valuation system in the OFC, another complementary one is centered in the ventrolateral prefrontal cortex (vlPFC) in macaques. Specifically, we found that the OFC and vlPFC preferentially represent outcome flavor and outcome probability, respectively, and that preferences are separately integrated into value representations in these areas. In addition, the vlPFC, but not the OFC, represented the probability of receiving the available outcome flavors separately, with the difference between these representations reflecting the degree of preference for each flavor. Thus, both the vlPFC and OFC exhibit dissociable but complementary representations of subjective value, both of which are necessary for decision-making.

Neural mechanisms of information seeking

We ubiquitously seek information to make better decisions. Particularly in the modern age, when more information is available at our fingertips than ever, the information we choose to collect determines the quality of our decisions. Decision neuroscience has long adopted empirical approaches where the information available to decision-makers is fully controlled by the researchers, leaving neural mechanisms of information seeking less understood. Although information seeking has long been studied in the context of the exploration-exploitation trade-off, recent studies have widened the scope to investigate more overt information seeking in a way distinct from other decision processes. Insights gained from these studies, accumulated over the last few years, raise the possibility that information seeking is driven by the reward system signaling the subjective value of information. In this piece, we review findings from the recent studies, highlighting the conceptual and empirical relationships between distinct literatures, and discuss future research directions necessary to establish a more comprehensive understanding of how individuals seek information as a part of value-based decision-making.

Ventral frontostriatal circuitry mediates the computation of reinforcement from symbolic gains and losses

Reinforcement learning (RL), particularly in primates, is often driven by symbolic outcomes. However, it is usually studied with primary reinforcers. To examine the neural mechanisms underlying learning from symbolic outcomes, we trained monkeys on a task in which they learned to choose options that led to gains of tokens and avoid choosing options that led to losses of tokens. We then recorded simultaneously from the orbitofrontal cortex (OFC), ventral striatum (VS), amygdala (AMY), and the mediodorsal thalamus (MDt). We found that the OFC played a dominant role in coding token outcomes and token prediction errors. The other areas contributed complementary functions with the VS coding appetitive outcomes and the AMY coding the salience of outcomes. The MDt coded actions and relayed information about tokens between the OFC and VS. Thus, OFC leads the process of symbolic reinforcement learning in the ventral frontostriatal circuitry.

Curiosity: primate neural circuits for novelty and information seeking

For many years, neuroscientists have investigated the behavioural, computational and neurobiological mechanisms that support value-based decisions, revealing how humans and animals make choices to obtain rewards. However, many decisions are influenced by factors other than the value of physical rewards or second-order reinforcers (such as money). For instance, animals (including humans) frequently explore novel objects that have no intrinsic value solely because they are novel and they exhibit the desire to gain information to reduce their uncertainties about the future, even if this information cannot lead to reward or assist them in accomplishing upcoming tasks. In this Review, I discuss how circuits in the primate brain responsible for detecting, predicting and assessing novelty and uncertainty regulate behaviour and give rise to these behavioural components of curiosity. I also briefly discuss how curiosity-related behaviours arise during postnatal development and point out some important reasons for the persistence of curiosity across generations.

Neurons in the monkey frontopolar cortex encode learning stage and goal during a fast learning task

The frontopolar cortex (FPC) is, to date, one of the least understood regions of the prefrontal cortex. The current understanding of its function suggests that it plays a role in the control of exploratory behaviors by coordinating the activities of other prefrontal cortex areas involved in decision-making and exploiting actions based on their outcomes. Based on this hypothesis, FPC would drive fast-learning processes through a valuation of the different alternatives. In our study, we used a modified version of a well-known paradigm, the object-in-place (OIP) task, to test this hypothesis in electrophysiology. This paradigm is designed to maximize learning, enabling monkeys to learn in one trial, which is an ability specifically impaired after a lesion of the FPC. We showed that FPC neurons presented an extremely specific pattern of activity by representing the learning stage, exploration versus exploitation, and the goal of the action. However, our results do not support the hypothesis that neurons in the frontal pole compute an evaluation of different alternatives. Indeed, the position of the chosen target was strongly encoded at its acquisition, but the position of the unchosen target was not. Once learned, this representation was also found at the problem presentation, suggesting a monitoring activity of the synthetic goal preceding its acquisition. Our results highlight important features of FPC neurons in fast-learning processes without confirming their role in the disengagement of cognitive control from the current goals.

Motor System-Dependent Effects of Amygdala and Ventral Striatum Lesions on Explore-Exploit Behaviors

Deciding whether to forego immediate rewards or explore new opportunities is a key component of flexible behavior and is critical for the survival of the species. Although previous studies have shown that different cortical and subcortical areas, including the amygdala and ventral striatum (VS), are implicated in representing the immediate (exploitative) and future (explorative) value of choices, the effect of the motor system used to make choices has not been examined. Here, we tested male rhesus macaques with amygdala or VS lesions on two versions of a three-arm bandit task where choices were registered with either a saccade or an arm movement. In both tasks we presented the monkeys with explore-exploit tradeoffs by periodically replacing familiar options with novel options that had unknown reward probabilities. We found that monkeys explored more with saccades but showed better learning with arm movements. VS lesions caused the monkeys to be more explorative with arm movements and less explorative with saccades, although this may have been due to an overall decrease in performance. VS lesions affected the monkeys' ability to learn novel stimulus-reward associations in both tasks, while after amygdala lesions this effect was stronger when choices were made with saccades. Further, on average, VS and amygdala lesions reduced the monkeys' ability to choose better options only when choices were made with a saccade. These results show that learning reward value associations to manage explore-exploit behaviors is motor system dependent and they further define the contributions of amygdala and VS to reinforcement learning.

Electrophysiological Markers of Aberrant Cue-Specific Exploration in Hazardous Drinkers

Background

Hazardous drinking is associated with maladaptive alcohol-related decision-making. Existing studies have often focused on how participants learn to exploit familiar cues based on prior reinforcement, but little is known about the mechanisms that drive hazardous drinkers to explore novel alcohol cues when their value is not known.

Methods

We investigated exploration of novel alcohol and non-alcohol cues in hazardous drinkers (N = 27) and control participants (N = 26) during electroencephalography (EEG). A normative computational model with two free parameters was fit to estimate participants' weighting of the future value of exploration and immediate value of exploitation.

Results

Hazardous drinkers demonstrated increased exploration of novel alcohol cues, and conversely, increased probability of exploiting familiar alternatives instead of exploring novel non-alcohol cues. The motivation to explore novel alcohol stimuli in hazardous drinkers was driven by an elevated relative future valuation of uncertain alcohol cues. P3a predicted more exploratory decision policies driven by an enhanced relative future valuation of novel alcohol cues. P3b did not predict choice behavior, but computational parameter estimates suggested that hazardous drinkers with enhanced P3b to alcohol cues were likely to learn to exploit their immediate expected value.

Conclusions

Hazardous drinkers did not display atypical choice behavior, different P3a/P3b amplitudes, or computational estimates to novel non-alcohol cues-diverging from previous studies in addiction showing atypical generalized explore-exploit decisions with non-drug-related cues. These findings reveal that cue-specific neural computations may drive aberrant alcohol-related decision-making in hazardous drinkers-highlighting the importance of drug-relevant cues in studies of decision-making in addiction.

Pupil size predicts the onset of exploration in brain and behavior

In uncertain environments, intelligent decision-makers exploit actions that have been rewarding in the past, but also explore actions that could be even better. Several neuromodulatory systems are implicated in exploration, based, in part, on work linking exploration to pupil size-a peripheral correlate of neuromodulatory tone and index of arousal. However, pupil size could instead track variables that make exploration more likely, like volatility or reward, without directly predicting either exploration or its neural bases. Here, we simultaneously measured pupil size, exploration, and neural population activity in the prefrontal cortex while two rhesus macaques explored and exploited in a dynamic environment. We found that pupil size under constant luminance specifically predicted the onset of exploration, beyond what could be explained by reward history. Pupil size also predicted disorganized patterns of prefrontal neural activity at both the single neuron and population levels, even within periods of exploitation. Ultimately, our results support a model in which pupil-linked mechanisms promote the onset of exploration via driving the prefrontal cortex through a critical tipping point where prefrontal control dynamics become disorganized and exploratory decisions are possible.

Preferences reveal separable valuation systems in prefrontal-limbic circuits

Individual preferences for the flavor of different foods and fluids exert a strong influence on behavior. Most current theories posit that preferences are integrated with other state variables in orbitofrontal cortex (OFC), which is thought to derive the relative subjective value of available options to drive choice behavior. Here we report that instead of a single integrated valuation system in OFC, another separate one is centered in ventrolateral prefrontal cortex (vlPFC) in macaque monkeys. Specifically, we found that OFC and vlPFC preferentially represent outcome flavor and outcome probability, respectively, and that preferences are separately integrated into these two aspects of subjective valuation. In addition, vlPFC, but not OFC, represented the outcome probability for the two options separately, with the difference between these representations reflecting the degree of preference. Thus, there are at least two separable valuation systems that work in concert to guide choices and that both are biased by preferences.

Local and global reward learning in the lateral frontal cortex show differential development during human adolescence

Reward-guided choice is fundamental for adaptive behaviour and depends on several component processes supported by prefrontal cortex. Here, across three studies, we show that two such component processes, linking reward to specific choices and estimating the global reward state, develop during human adolescence and are linked to the lateral portions of the prefrontal cortex. These processes reflect the assignment of rewards contingently to local choices, or noncontingently, to choices that make up the global reward history. Using matched experimental tasks and analysis platforms, we show the influence of both mechanisms increase during adolescence (study 1) and that lesions to lateral frontal cortex (that included and/or disconnected both orbitofrontal and insula cortex) in human adult patients (study 2) and macaque monkeys (study 3) impair both local and global reward learning. Developmental effects were distinguishable from the influence of a decision bias on choice behaviour, known to depend on medial prefrontal cortex. Differences in local and global assignments of reward to choices across adolescence, in the context of delayed grey matter maturation of the lateral orbitofrontal and anterior insula cortex, may underlie changes in adaptive behaviour.

Neural responses in macaque prefrontal cortex are linked to strategic exploration

Humans have been shown to strategically explore. They can identify situations in which gathering information about distant and uncertain options is beneficial for the future. Because primates rely on scarce resources when they forage, they are also thought to strategically explore, but whether they use the same strategies as humans and the neural bases of strategic exploration in monkeys are largely unknown. We designed a sequential choice task to investigate whether monkeys mobilize strategic exploration based on whether information can improve subsequent choice, but also to ask the novel question about whether monkeys adjust their exploratory choices based on the contingency between choice and information, by sometimes providing the counterfactual feedback about the unchosen option. We show that monkeys decreased their reliance on expected value when exploration could be beneficial, but this was not mediated by changes in the effect of uncertainty on choices. We found strategic exploratory signals in anterior and mid-cingulate cortex (ACC/MCC) and dorsolateral prefrontal cortex (dlPFC). This network was most active when a low value option was chosen, which suggests a role in counteracting expected value signals, when exploration away from value should to be considered. Such strategic exploration was abolished when the counterfactual feedback was available. Learning from counterfactual outcome was associated with the recruitment of a different circuit centered on the medial orbitofrontal cortex (OFC), where we showed that monkeys represent chosen and unchosen reward prediction errors. Overall, our study shows how ACC/MCC-dlPFC and OFC circuits together could support exploitation of available information to the fullest and drive behavior towards finding more information through exploration when it is beneficial.

Environmental uncertainty and the advantage of impulsive choice strategies

Choice impulsivity is characterized by the choice of immediate, smaller reward options over future, larger reward options, and is often thought to be associated with negative life outcomes. However, some environments make future rewards more uncertain, and in these environments impulsive choices can be beneficial. Here we examined the conditions under which impulsive vs. non-impulsive decision strategies would be advantageous. We used Markov Decision Processes (MDPs) to model three common decision-making tasks: Temporal Discounting, Information Sampling, and an Explore-Exploit task. We manipulated environmental variables to create circumstances where future outcomes were relatively uncertain. We then manipulated the discount factor of an MDP agent, which affects the value of immediate versus future rewards, to model impulsive and non-impulsive behavior. This allowed us to examine the performance of impulsive and non-impulsive agents in more or less predictable environments. In Temporal Discounting, we manipulated the transition probability to delayed rewards and found that the agent with the lower discount factor (i.e. the impulsive agent) collected more average reward than the agent with a higher discount factor (the non-impulsive agent) by selecting immediate reward options when the probability of receiving the future reward was low. In the Information Sampling task, we manipulated the amount of information obtained with each sample. When sampling led to small information gains, the impulsive MDP agent collected more average reward than the non-impulsive agent. Third, in the Explore-Exploit task, we manipulated the substitution rate for novel options. When the substitution rate was high, the impulsive agent again performed better than the non-impulsive agent, as it explored the novel options less and instead exploited options with known reward values. The results of these analyses show that impulsivity can be advantageous in environments that are unexpectedly uncertain.

Active inference and the two-step task

Sequential decision problems distill important challenges frequently faced by humans. Through repeated interactions with an uncertain world, unknown statistics need to be learned while balancing exploration and exploitation. Reinforcement learning is a prominent method for modeling such behaviour, with a prevalent application being the two-step task. However, recent studies indicate that the standard reinforcement learning model sometimes describes features of human task behaviour inaccurately and incompletely. We investigated whether active inference, a framework proposing a trade-off to the exploration-exploitation dilemma, could better describe human behaviour. Therefore, we re-analysed four publicly available datasets of the two-step task, performed Bayesian model selection, and compared behavioural model predictions. Two datasets, which revealed more model-based inference and behaviour indicative of directed exploration, were better described by active inference, while the models scored similarly for the remaining datasets. Learning using probability distributions appears to contribute to the improved model fits. Further, approximately half of all participants showed sensitivity to information gain as formulated under active inference, although behavioural exploration effects were not fully captured. These results contribute to the empirical validation of active inference as a model of human behaviour and the study of alternative models for the influential two-step task.

Value representations in the rodent orbitofrontal cortex drive learning, not choice

Humans and animals make predictions about the rewards they expect to receive in different situations. In formal models of behavior, these predictions are known as value representations, and they play two very different roles. Firstly, they drive choice: the expected values of available options are compared to one another, and the best option is selected. Secondly, they support learning: expected values are compared to rewards actually received, and future expectations are updated accordingly. Whether these different functions are mediated by different neural representations remains an open question. Here, we employ a recently developed multi-step task for rats that computationally separates learning from choosing. We investigate the role of value representations in the rodent orbitofrontal cortex, a key structure for value-based cognition. Electrophysiological recordings and optogenetic perturbations indicate that these representations do not directly drive choice. Instead, they signal expected reward information to a learning process elsewhere in the brain that updates choice mechanisms.

Shared mechanisms mediate the explore-exploit tradeoff in macaques and humans

Ancestors of macaques and humans separated into distinct lineages 25 million years ago. Despite this long separation, Hogeveen et al. (2022) show, in this issue of Neuron, that they mediate the explore-exploit tradeoff, which must be managed by any agent adapting to a dynamic environment, using similar computational and neural mechanisms.

The neurocomputational bases of explore-exploit decision-making

Flexible decision-making requires animals to forego immediate rewards (exploitation) and try novel choice options (exploration) to discover if they are preferable to familiar alternatives. Using the same task and a partially observable Markov decision process (POMDP) model to quantify the value of choices, we first determined that the computational basis for managing explore-exploit tradeoffs is conserved across monkeys and humans. We then used fMRI to identify where in the human brain the immediate value of exploitative choices and relative uncertainty about the value of exploratory choices were encoded. Consistent with prior neurophysiological evidence in monkeys, we observed divergent encoding of reward value and uncertainty in prefrontal and parietal regions, including frontopolar cortex, and parallel encoding of these computations in motivational regions including the amygdala, ventral striatum, and orbitofrontal cortex. These results clarify the interplay between prefrontal and motivational circuits that supports adaptive explore-exploit decisions in humans and nonhuman primates.

Improving Our Understanding of Impaired Social Problem-Solving in Children and Adolescents with Conduct Problems: Implications for Cognitive Behavioral Therapy

In cognitive behavioral therapy (CBT) children and adolescents with conduct problems learn social problem-solving skills that enable them to behave in more independent and situation appropriate ways. Empirical studies on psychological functions show that the effectiveness of CBT may be further improved by putting more emphasis on (1) recognition of the type of social situations that are problematic, (2) recognition of facial expressions in view of initiating social problem-solving, (3) effortful emotion regulation and emotion awareness, (4) behavioral inhibition and working memory, (5) interpretation of the social problem, (6) affective empathy, (7) generation of appropriate solutions, (8) outcome expectations and moral beliefs, and (9) decision-making. To improve effectiveness, CBT could be tailored to the individual child's or adolescent's impairments of these psychological functions which may depend on the type of conduct problems and their associated problems.

The whole prefrontal cortex is premotor cortex

We propose that the entirety of the prefrontal cortex (PFC) can be seen as fundamentally premotor in nature. By this, we mean that the PFC consists of an action abstraction hierarchy whose core function is the potentiation and depotentiation of possible action plans at different levels of granularity. We argue that the apex of the hierarchy should revolve around the process of goal-selection, which we posit is inherently a form of optimization over action abstraction. Anatomical and functional evidence supports the idea that this hierarchy originates on the orbital surface of the brain and extends dorsally to motor cortex. Accordingly, our viewpoint positions the orbitofrontal cortex in a key role in the optimization of goal-selection policies, and suggests that its other proposed roles are aspects of this more general function. Our proposed perspective will reframe outstanding questions, open up new areas of inquiry and align theories of prefrontal function with evolutionary principles. This article is part of the theme issue 'Systems neuroscience through the lens of evolutionary theory'.

Differential coding of goals and actions in ventral and dorsal corticostriatal circuits during goal-directed behavior

Goal-directed behavior requires identifying objects in the environment that can satisfy internal needs and executing actions to obtain those objects. The current study examines ventral and dorsal corticostriatal circuits that support complementary aspects of goal-directed behavior. We analyze activity from the amygdala, ventral striatum, orbitofrontal cortex, and lateral prefrontal cortex (LPFC) while monkeys perform a three-armed bandit task. Information about chosen stimuli and their value is primarily encoded in the amygdala, ventral striatum, and orbitofrontal cortex, while the spatial information is primarily encoded in the LPFC. Before the options are presented, information about the to-be-chosen stimulus is represented in the amygdala, ventral striatum, and orbitofrontal cortex; at the time of choice, the information is passed to the LPFC to direct a saccade. Thus, learned value information specifying behavioral goals is maintained throughout the ventral corticostriatal circuit, and it is routed through the dorsal circuit at the time actions are selected.

Reinforcement-learning in fronto-striatal circuits

We review the current state of knowledge on the computational and neural mechanisms of reinforcement-learning with a particular focus on fronto-striatal circuits. We divide the literature in this area into five broad research themes: the target of the learning-whether it be learning about the value of stimuli or about the value of actions; the nature and complexity of the algorithm used to drive the learning and inference process; how learned values get converted into choices and associated actions; the nature of state representations, and of other cognitive machinery that support the implementation of various reinforcement-learning operations. An emerging fifth area focuses on how the brain allocates or arbitrates control over different reinforcement-learning sub-systems or "experts". We will outline what is known about the role of the prefrontal cortex and striatum in implementing each of these functions. We then conclude by arguing that it will be necessary to build bridges from algorithmic level descriptions of computational reinforcement-learning to implementational level models to better understand how reinforcement-learning emerges from multiple distributed neural networks in the brain.

Interactions between ventrolateral prefrontal and anterior cingulate cortex during learning and behavioural change

Hypotheses and beliefs guide credit assignment - the process of determining which previous events or actions caused an outcome. Adaptive hypothesis formation and testing are crucial in uncertain and changing environments in which associations and meanings are volatile. Despite primates' abilities to form and test hypotheses, establishing what is causally responsible for the occurrence of particular outcomes remains a fundamental challenge for credit assignment and learning. Hypotheses about what surprises are due to stochasticity inherent in an environment as opposed to real, systematic changes are necessary for identifying the environment's predictive features, but are often hard to test. We review evidence that two highly interconnected frontal cortical regions, anterior cingulate cortex and ventrolateral prefrontal area 47/12o, provide a biological substrate for linking two crucial components of hypothesis-formation and testing: the control of information seeking and credit assignment. Neuroimaging, targeted disruptions, and neurophysiological studies link an anterior cingulate - 47/12o circuit to generation of exploratory behaviour, non-instrumental information seeking, and interpretation of subsequent feedback in the service of credit assignment. Our observations support the idea that information seeking and credit assignment are linked at the level of neural circuits and explain why this circuit is important for ensuring behaviour is flexible and adaptive.

Relative salience signaling within a thalamo-orbitofrontal circuit governs learning rate

Learning to predict rewards is essential for the sustained fitness of animals. Contemporary views suggest that such learning is driven by a reward prediction error (RPE)-the difference between received and predicted rewards. The magnitude of learning induced by an RPE is proportional to the product of the RPE and a learning rate. Here we demonstrate using two-photon calcium imaging and optogenetics in mice that certain functionally distinct subpopulations of ventral/medial orbitofrontal cortex (vmOFC) neurons signal learning rate control. Consistent with learning rate control, trial-by-trial fluctuations in vmOFC activity positively correlate with behavioral updating when the RPE is positive, and negatively correlates with behavioral updating when the RPE is negative. Learning rate is affected by many variables including the salience of a reward. We found that the average reward response of these neurons signals the relative salience of a reward, because it decreases after reward prediction learning or the introduction of another highly salient aversive stimulus. The relative salience signaling in vmOFC is sculpted by medial thalamic inputs. These results support emerging theoretical views that prefrontal cortex encodes and controls learning parameters.

From exploration to exploitation: a shifting mental mode in late life development

Changes in cognition, affect, and brain function combine to promote a shift in the nature of mentation in older adulthood, favoring exploitation of prior knowledge over exploratory search as the starting point for thought and action. Age-related exploitation biases result from the accumulation of prior knowledge, reduced cognitive control, and a shift toward affective goals. These are accompanied by changes in cortical networks, as well as attention and reward circuits. By incorporating these factors into a unified account, the exploration-to-exploitation shift offers an integrative model of cognitive, affective, and brain aging. Here, we review evidence for this model, identify determinants and consequences, and survey the challenges and opportunities posed by an exploitation-biased mental mode in later life.

Spatial Representations in Rat Orbitofrontal Cortex

The orbitofrontal cortex (OFC) and hippocampus share striking cognitive and functional similarities. As a result, both structures have been proposed to encode "cognitive maps" that provide useful scaffolds for planning complex behaviors. However, while this function has been exemplified by spatial coding in neurons of hippocampal regions-particularly place and grid cells-spatial representations in the OFC have been investigated far less. Here we sought to address this by recording OFC neurons from male rats engaged in an open-field foraging task like that originally developed to characterize place fields in rodent hippocampal neurons. Single-unit activity was recorded as rats searched for food pellets scattered randomly throughout a large enclosure. In some sessions, particular flavors of food occurred more frequently in particular parts of the enclosure; in others, only a single flavor was used. OFC neurons showed spatially localized firing fields in both conditions, and representations changed between flavored and unflavored foraging periods in a manner reminiscent of remapping in the hippocampus. Compared with hippocampal recordings taken under similar behavioral conditions, OFC spatial representations were less temporally reliable, and there was no significant evidence of grid tuning in OFC neurons. These data confirm that OFC neurons show spatial firing fields in a large, two-dimensional environment in a manner similar to hippocampus. Consistent with the focus of the OFC on biological meaning and goals, spatial coding was weaker than in hippocampus and influenced by outcome identity.SIGNIFICANCE STATEMENT The orbitofrontal cortex (OFC) and hippocampus have both been proposed to encode "cognitive maps" that provide useful scaffolds for planning complex behaviors. This function is exemplified by place and grid cells identified in hippocampus, the activity of which maps spatial environments. The current study directly demonstrates very similar, though not identical, spatial representatives in OFC neurons, confirming that OFC-like hippocampus-can represent a spatial map under the appropriate experimental conditions.

Organization of Parieto-Prefrontal and Temporo-Prefrontal Networks in the Macaque

The connectivity among architectonically defined areas of the frontal, parietal, and temporal cortex of the macaque has been extensively mapped through tract tracing methods. To investigate the statistical organization underlying this connectivity, and identify its underlying architecture, we performed a hierarchical cluster analysis on 69 cortical areas based on their anatomically defined inputs. We identified 10 frontal, 4 parietal, and 5 temporal hierarchically related sets of areas (clusters), defined by unique sets of inputs and typically composed of anatomically contiguous areas. Across cortex, clusters that share functional properties were linked by dominant information processing circuits in a topographically organized manner that reflects the organization of the main fiber bundles in the cortex. This led to a dorsal-ventral subdivision of the frontal cortex, where dorsal and ventral clusters showed privileged connectivity with parietal and temporal areas, respectively. Ventrally, temporo-frontal circuits encode information to discriminate objects in the environment, their value, emotional properties, and functions such as memory and spatial navigation. Dorsal parieto-frontal circuits encode information for selecting, generating, and monitoring appropriate actions based on visual-spatial and somatosensory information. This organization may reflect evolutionary antecedents, in which the vertebrate pallium, which is the ancestral cortex, was defined by a ventral and lateral olfactory region and a medial hippocampal region.

The anterior cingulate cortex directs exploration of alternative strategies

The ability to adjust one's behavioral strategy in complex environments is at the core of cognition. Doing so efficiently requires monitoring the reliability of the ongoing strategy and, when appropriate, switching away from it to evaluate alternatives. Studies in humans and non-human primates have uncovered signals in the anterior cingulate cortex (ACC) that reflect the pressure to switch away from the ongoing strategy, whereas other ACC signals relate to the pursuit of alternatives. However, whether these signals underlie computations that actually underpin strategy switching or merely reflect tracking of related variables remains unclear. Here we provide causal evidence that the rodent ACC actively arbitrates between persisting with the ongoing behavioral strategy and temporarily switching away to re-evaluate alternatives. Furthermore, by individually perturbing distinct output pathways, we establish that the two associated computations-determining whether to switch strategy and committing to the pursuit of a specific alternative-are segregated in the ACC microcircuitry.

Balancing exploration and exploitation with information and randomization

Explore-exploit decisions require us to trade off the benefits of exploring unknown options to learn more about them, with exploiting known options, for immediate reward. Such decisions are ubiquitous in nature, but from a computational perspective, they are notoriously hard. There is therefore much interest in how humans and animals make these decisions and recently there has been an explosion of research in this area. Here we provide a biased and incomplete snapshot of this field focusing on the major finding that many organisms use two distinct strategies to solve the explore-exploit dilemma: a bias for information ('directed exploration') and the randomization of choice ('random exploration'). We review evidence for the existence of these strategies, their computational properties, their neural implementations, as well as how directed and random exploration vary over the lifespan. We conclude by highlighting open questions in this field that are ripe to both explore and exploit.

The orbitofrontal cartographer

Theories of orbitofrontal cortex (OFC) function have evolved substantially over the last few decades. There is now a general consensus that the OFC is important for predicting aspects of future events and for using these predictions to guide behavior. Yet the precise content of these predictions and the degree to which OFC contributes to agency contingent upon them has become contentious, with several plausible theories advocating different answers to these questions. In this review we will focus on three of these ideas-the economic value, credit assignment, and cognitive map hypotheses-describing both their successes and failures. We will propose that these failures hint at a more nuanced and perhaps unique role for the OFC, particularly the lateral subdivision, in supporting the proposed functions when an underlying model or map of the causal structures in the environment must be constructed or updated. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The orbitofrontal cortex in temporal cognition

One of the most important factors in decision-making is estimating the value of available options. Subregions of the prefrontal cortex, including the orbitofrontal cortex (OFC), have been deemed essential for this process. Value computations require a complex integration across numerous dimensions, including, reward magnitude, effort, internal state, and time. The importance of the temporal dimension is well illustrated by temporal discounting tasks, in which subjects select between smaller-sooner versus larger-later rewards. The specific role of OFC in telling time and integrating temporal information into decision-making remains unclear. Based on the current literature, in this review we reevaluate current theories of OFC function, accounting for the influence of time. Incorporating temporal information into value estimation and decision-making requires distinct, yet interrelated, forms of temporal information including the ability to tell time, represent time, create temporal expectations, and the ability to use this information for optimal decision-making in a wide range of tasks, including temporal discounting and wagering. We use the term "temporal cognition" to refer to the integrated use of these different aspects of temporal information. We suggest that the OFC may be a critical site for the integration of reward magnitude and delay, and thus important for temporal cognition. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Increasing Effectiveness of Cognitive Behavioral Therapy for Conduct Problems in Children and Adolescents: What Can We Learn from Neuroimaging Studies?

Cognitive behavioral therapy (CBT) is particularly relevant for children from 7 years on and adolescents with clinical levels of conduct problems. CBT provides these children and adolescents with anger regulation and social problem-solving skills that enable them to behave in more independent and situation appropriate ways. Typically, CBT is combined with another psychological treatment such as behavioral parent training in childhood or an intervention targeting multiple systems in adolescence. The effectiveness of CBT, however, is in the small to medium range. The aim of this review is to describe how the effectiveness of CBT may be improved by paying more attention to a series of psychological functions that have been shown to be impaired in neuroimaging studies: (1) anger recognition, (2) the ability to generate situation appropriate solutions to social problems, (3) reinforcement-based decision making, (4) response inhibition, and (5) affective empathy. It is suggested that children and adolescents first become familiar with these psychological functions during group CBT sessions. In individual sessions in which the parents (and/or child care workers in day treatment and residential treatment) and the child or adolescent participate, parents then learn to elicit, support, and reinforce their child’s use of these psychological functions in everyday life (in vivo practice). In these individual sessions, working on the psychological functions is tailored to the individual child’s characteristic impairments of these functions. CBT therapists may also share crucial social-learning topics with teachers with a view to creating learning opportunities for children and adolescents at school.

Alexithymia

Humans are highly adept at differentiating, regulating, and responding to their emotions. At the core of all these functions is emotional awareness: the conscious feeling states that are central to human mental life. Disrupted emotional awareness-a subclinical construct commonly referred to as alexithymia-is present in a range of psychiatric and neurological disorders and can have a deleterious impact on functional outcomes and treatment response. This chapter is a selective review of the current state of the science on alexithymia. We focus on two separate but related issues: (i) the functional deficits associated with alexithymia and what they reveal about the importance of emotional awareness for shaping normative human functioning, and (ii) the neural correlates of alexithymia and what they can inform us about the biological bases of emotional awareness. Lastly, we outline challenges and opportunities for alexithymia research, focusing on measurement issues and the potential utility of formal computational models of emotional awareness for advancing the fields of clinical and affective science.

Correlates of Auditory Decision-Making in Prefrontal, Auditory, and Basal Lateral Amygdala Cortical Areas

Spatial selective listening and auditory choice underlie important processes including attending to a speaker at a cocktail party and knowing how (or whether) to respond. To examine task encoding and the relative timing of potential neural substrates underlying these behaviors, we developed a spatial selective detection paradigm for monkeys, and recorded activity in primary auditory cortex (AC), dorsolateral prefrontal cortex (dlPFC), and the basolateral amygdala (BLA). A comparison of neural responses among these three areas showed that, as expected, AC encoded the side of the cue and target characteristics before dlPFC and BLA. Interestingly, AC also encoded the choice of the monkey before dlPFC and around the time of BLA. Generally, BLA showed weak responses to all task features except the choice. Decoding analyses suggested that errors followed from a failure to encode the target stimulus in both AC and dlPFC, but again, these differences arose earlier in AC. The similarities between AC and dlPFC responses were abolished during passive sensory stimulation with identical trial conditions, suggesting that the robust sensory encoding in dlPFC is contextually gated. Thus, counter to a strictly PFC-driven decision process, in this spatial selective listening task AC neural activity represents the sensory and decision information before dlPFC. Unlike in the visual domain, in this auditory task, the BLA does not appear to be robustly involved in selective spatial processing.SIGNIFICANCE STATEMENT We examined neural correlates of an auditory spatial selective listening task by recording single-neuron activity in behaving monkeys from the amygdala, dorsolateral prefrontal cortex, and auditory cortex. We found that auditory cortex coded spatial cues and choice-related activity before dorsolateral prefrontal cortex or the amygdala. Auditory cortex also had robust delay period activity. Therefore, we found that auditory cortex could support the neural computations that underlie the behavioral processes in the task.

Rules warp feature encoding in decision-making circuits

We have the capacity to follow arbitrary stimulus-response rules, meaning simple policies that guide our behavior. Rule identity is broadly encoded across decision-making circuits, but there are less data on how rules shape the computations that lead to choices. One idea is that rules could simplify these computations. When we follow a rule, there is no need to encode or compute information that is irrelevant to the current rule, which could reduce the metabolic or energetic demands of decision-making. However, it is not clear if the brain can actually take advantage of this computational simplicity. To test this idea, we recorded from neurons in 3 regions linked to decision-making, the orbitofrontal cortex (OFC), ventral striatum (VS), and dorsal striatum (DS), while macaques performed a rule-based decision-making task. Rule-based decisions were identified via modeling rules as the latent causes of decisions. This left us with a set of physically identical choices that maximized reward and information, but could not be explained by simple stimulus-response rules. Contrasting rule-based choices with these residual choices revealed that following rules (1) decreased the energetic cost of decision-making; and (2) expanded rule-relevant coding dimensions and compressed rule-irrelevant ones. Together, these results suggest that we use rules, in part, because they reduce the costs of decision-making through a distributed representational warping in decision-making circuits.

Hypothalamic Interactions with Large-Scale Neural Circuits Underlying Reinforcement Learning and Motivated Behavior

Biological agents adapt behavior to support the survival needs of the individual and the species. In this review we outline the anatomical, physiological, and computational processes that support reinforcement learning (RL). We describe two circuits in the primate brain that are linked to specific aspects of learning and goal-directed behavior. The ventral circuit, that includes the amygdala, ventral medial prefrontal cortex, and ventral striatum, has substantial connectivity with the hypothalamus. The dorsal circuit, that includes inferior parietal cortex, dorsal lateral prefrontal cortex, and the dorsal striatum, has minimal connectivity with the hypothalamus. The hypothalamic connectivity suggests distinct roles for these circuits. We propose that the ventral circuit defines behavioral goals, and the dorsal circuit orchestrates behavior to achieve those goals.

Reinforcement Learning during Adolescence in Rats

The most dynamic period of postnatal brain development occurs during adolescence, the period between childhood and adulthood. Neuroimaging studies have observed morphologic and functional changes during adolescence, and it is believed that these changes serve to improve the functions of circuits that underlie decision-making. Direct evidence in support of this hypothesis, however, has been limited because most preclinical decision-making paradigms are not readily translated to humans. Here, we developed a reversal-learning protocol for the rapid assessment of adaptive choice behavior in dynamic environments in rats as young as postnatal day 30. A computational framework was used to elucidate the reinforcement-learning mechanisms that change in adolescence and into adulthood. Using a cross-sectional and longitudinal design, we provide the first evidence that value-based choice behavior in a reversal-learning task improves during adolescence in male and female Long-Evans rats and demonstrate that the increase in reversal performance is due to alterations in value updating for positive outcomes. Furthermore, we report that reversal-learning trajectories in adolescence reliably predicted reversal performance in adulthood. This novel behavioral protocol provides a unique platform for conducting biological and systems-level analyses of the neurodevelopmental mechanisms of decision-making.SIGNIFICANCE STATEMENT The neurodevelopmental adaptations that occur during adolescence are hypothesized to underlie age-related improvements in decision-making, but evidence to support this hypothesis has been limited. Here, we describe a novel behavioral protocol for rapidly assessing adaptive choice behavior in adolescent rats with a reversal-learning paradigm. Using a computational approach, we demonstrate that age-related changes in reversal-learning performance in male and female Long-Evans rats are linked to specific reinforcement-learning mechanisms and are predictive of reversal-learning performance in adulthood. Our behavioral protocol provides a unique platform for elucidating key components of adolescent brain function.

Psychotherapy in pain management: New viewpoints and treatment targets based on a brain theory

The current paper provides an explanation of neurophysiological pain processing based the Dimensional Systems Model (DSM), a theory of higher cortical functions in which the cortical column is considered the binary digit for all cortical functions. Within the discussion, novel views on the roles of the basal ganglia, cerebellum, and cingulate cortex are presented. Additionally, an applied Clinical Biopsychological Model (CBM) based on the DSM will be discussed as related to psychological treatment with chronic pain patients. Three specific areas that have not been adequately addressed in the psychological treatment of chronic pain patients will be discussed based on the CBM. The treatment approaches have been effectively used in a clinical setting. Conclusions focus on a call for researchers and clinicians to fully evaluate the value of both the DSM and CBM.