Responding to preconditioned cues is devaluation sensitive and requires orbitofrontal cortex during cue-cue learning

The curious case of dopaminergic prediction errors and learning associative information beyond value

Transient changes in the firing of midbrain dopamine neurons have been closely tied to the unidimensional value-based prediction error contained in temporal difference reinforcement learning models. However, whereas an abundance of work has now shown how well dopamine responses conform to the predictions of this hypothesis, far fewer studies have challenged its implicit assumption that dopamine is not involved in learning value-neutral features of reward. Here, we review studies in rats and humans that put this assumption to the test, and which suggest that dopamine transients provide a much richer signal that incorporates information that goes beyond integrated value.

Alterations of gray matter asymmetry in internet gaming disorder

Structural asymmetry is a subtle but pervasive property of the human brain, which has been found altered in various psychiatric and neurocognitive disorders. However, little is known regarding potential alterations of structural asymmetry underlying internet gaming disorder (IGD). Therefore, this study aimed to investigate the structural features of gray matter asymmetry in IGD. High-resolution structural magnetic resonance imaging data were collected from 104 individuals with IGD and 104 recreational game users (RGUs). We applied a whole-brain voxel-based asymmetry (VBA) approach to determine the asymmetrical aberrations of gray matter in relation to IGD. Furthermore, the local abnormalities of structural asymmetry were employed as features to examine the effect of classification using a support vector machine (SVM). The results indicated that individuals with IGD as compared to RGUs showed asymmetrical alterations of gray matter in the medial prefrontal cortex (mPFC), orbitofrontal cortex, precuneus, middle temporal gyrus, superior parietal lobule and inferior temporal gyrus, regions implicated in hedonic motivation, self-reflection, information integration and visuospatial attention processing. Moreover, these atypical asymmetrical features can distinguish IGD subjects from RGUs with high accuracy. These results suggested that disrupted structural asymmetry of motivational reward, visuospatial and default mode circuits might be potential biomarkers for identifying pathological gaming dependence. These findings extended our understanding of structural underpinnings of IGD and provided new insights for developing effective interventions to alleviate compulsive gaming usage.

Predictive Representations: Building Blocks of Intelligence

Adaptive behavior often requires predicting future events. The theory of reinforcement learning prescribes what kinds of predictive representations are useful and how to compute them. This review integrates these theoretical ideas with work on cognition and neuroscience. We pay special attention to the successor representation and its generalizations, which have been widely applied as both engineering tools and models of brain function. This convergence suggests that particular kinds of predictive representations may function as versatile building blocks of intelligence.

The selective D3Receptor antagonist VK4-116 reverses loss of insight caused by self-administration of cocaine in rats

Chronic psychostimulant use causes long-lasting changes to neural and cognitive function that persist after long periods of abstinence. As cocaine users transition from drug use to abstinence, a parallel transition from hyperactivity to hypoactivity has been found in orbitofrontal-striatal glucose metabolism and striatal D2/D3-receptor activity. Targeting these changes pharmacologically, using highly selective dopamine D3-receptor (D3R) antagonists and partial agonists, has shown promise in reducing drug-taking, and attenuating relapse in animal models of cocaine and opioid use disorder. However, much less attention has been paid to treating the loss of insight, operationalized as the inability to infer likely outcomes, associated with chronic psychostimulant use. Here we tested the selective D3R antagonist VK4-116 as a treatment for this loss in rats with a prior history of cocaine use. Male and female rats were first trained to self-administer cocaine or a sucrose liquid for 2 weeks. After 4 weeks of abstinence, performance was assessed using a sensory preconditioning (SPC) learning paradigm. Rats were given VK4-116 (15 mg/kg, i.p.) or vehicle 30 min prior to each SPC training session, thus creating four drug-treatment groups: sucrose-vehicle, sucrose-VK4-116, cocaine-vehicle, cocaine-VK4-116. The control groups (sucrose-vehicle, sucrose-VK4-116) showed normal sensory preconditioning, whereas cocaine use (cocaine-vehicle) selectively disrupted responding to the preconditioned cue, an effect that was reversed in the cocaine-VK4-116 group, which demonstrating responding to the preconditioned cue at levels comparable to controls. These preclinical findings demonstrate that highly selective dopamine D3R antagonists, particularly VK4-116, can reverse the long-term negative behavioral consequences of cocaine use.

Dopamine Release in the Nucleus Accumbens Core Encodes the General Excitatory Components of Learning

Dopamine release in the nucleus accumbens core (NAcC) is generally considered to be a proxy for phasic firing of the ventral tegmental area dopamine (VTADA) neurons. Thus, dopamine release in NAcC is hypothesized to reflect a unitary role in reward prediction error signaling. However, recent studies reveal more diverse roles of dopamine neurons, which support an emerging idea that dopamine regulates learning differently in distinct circuits. To understand whether the NAcC might regulate a unique component of learning, we recorded dopamine release in NAcC while male rats performed a backward conditioning task where a reward is followed by a neutral cue. We used this task because we can delineate different components of learning, which include sensory-specific inhibitory and general excitatory components. Furthermore, we have shown that VTADA neurons are necessary for both the specific and general components of backward associations. Here, we found that dopamine release in NAcC increased to the reward across learning while reducing to the cue that followed as it became more expected. This mirrors the dopamine prediction error signal seen during forward conditioning and cannot be accounted for temporal-difference reinforcement learning. Subsequent tests allowed us to dissociate these learning components and revealed that dopamine release in NAcC reflects the general excitatory component of backward associations, but not their sensory-specific component. These results emphasize the importance of examining distinct functions of different dopamine projections in reinforcement learning.

Modeling impaired insight after drug use in rodents

Impaired insight in substance use disorder has been argued to reflect a global deficit in using cognitive models to mentally simulate possible future outcomes. The process of mentally simulating outcomes allows us to understand our beliefs about their causes, that is, to have insight and thereby avoid potentially negative outcomes. However, work in humans cannot address whether impaired insight and its neural/neurochemical sequalae are present prior to the development of a substance use disorder, a consequence of substance use, or a combination of both. This is because baseline measurements prior to drug use are not possible in humans. However, if these changes can be directly caused by drug use, then in animal models, a history of drug use should cause impairments in behavioral tasks designed to assess such inferences. Focusing on cocaine use, here we will review several lines of research from our laboratory that have tested this question using learning-theory tasks designed to isolate insight. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Hippocampal and orbitofrontal neurons contribute to complementary aspects of associative structure

The ability to establish associations between environmental stimuli is fundamental for higher-order brain functions like state inference and generalization. Both the hippocampus and orbitofrontal cortex (OFC) play pivotal roles in this, demonstrating complex neural activity changes after associative learning. However, how precisely they contribute to representing learned associations remains unclear. Here, we train head-restrained mice to learn four 'odor-outcome' sequence pairs composed of several task variables-the past and current odor cues, sequence structure of 'cue-outcome' arrangement, and the expected outcome; and perform calcium imaging from these mice throughout learning. Sequence-splitting signals that distinguish between paired sequences are detected in both brain regions, reflecting associative memory formation. Critically, we uncover differential contents in represented associations by examining, in each area, how these task variables affect splitting signal generalization between sequence pairs. Specifically, the hippocampal splitting signals are influenced by the combination of past and current cues that define a particular sensory experience. In contrast, the OFC splitting signals are similar between sequence pairs that share the same sequence structure and expected outcome. These findings suggest that the hippocampus and OFC uniquely and complementarily organize the acquired associative structure.

Optogenetic Inhibition of Rat Anterior Cingulate Cortex Impairs the Ability to Initiate and Stay on Task

Our prior research has identified neural correlates of cognitive control in the anterior cingulate cortex (ACC), leading us to hypothesize that the ACC is necessary for increasing attention as rats flexibly learn new contingencies during a complex reward-guided decision-making task. Here, we tested this hypothesis by using optogenetics to transiently inhibit the ACC, while rats of either sex performed the same two-choice task. ACC inhibition had a profound impact on behavior that extended beyond deficits in attention during learning when expected outcomes were uncertain. We found that ACC inactivation slowed and reduced the number of trials rats initiated and impaired both their accuracy and their ability to complete sessions. Furthermore, drift-diffusion model analysis suggested that free-choice performance and evidence accumulation (i.e., reduced drift rates) were degraded during initial learning-leading to weaker associations that were more easily overridden in later trial blocks (i.e., stronger bias). Together, these results suggest that in addition to attention-related functions, the ACC contributes to the ability to initiate trials and generally stay on task.

Optogenetic Inhibition of the Orbitofrontal Cortex Disrupts Inhibitory Control during Stop-Change Performance in Male Rats

Historically, the orbitofrontal cortex (OFC) has been implicated in a variety of behaviors ranging from reversal learning and inhibitory control to more complex representations of reward value and task space. While modern interpretations of the OFC's function have focused on a role in outcome evaluation, these cognitive processes often require an organism to inhibit a maladaptive response or strategy. Single-unit recordings from the OFC in rats performing a stop-change task show that the OFC responds strongly to STOP trials. To investigate the role that the OFC plays in stop-change performance, we expressed halorhodopsin (eNpHR3.0) in excitatory neurons in the OFC and tested rats on the stop-change task. Previous work suggests that the OFC differentiates between STOP trials based on trial sequence (i.e., gS trials: STOP trials preceded by a GO vs sS trials: STOP trials preceded by a STOP). We found that yellow light activation of the eNpHR3.0-expressing neurons significantly decreased accuracy only on STOP trials that followed GO trials (gS trials). Further, optogenetic inhibition of the OFC speeded reaction times on error trials. This suggests that the OFC plays a role in inhibitory control processes and that this role needs to be accounted for in modern interpretations of OFC function.

The cognitive (lateral) hypothalamus

Despite the physiological complexity of the hypothalamus, its role is typically restricted to initiation or cessation of innate behaviors. For example, theories of lateral hypothalamus argue that it is a switch to turn feeding 'on' and 'off' as dictated by higher-order structures that render when feeding is appropriate. However, recent data demonstrate that the lateral hypothalamus is critical for learning about food-related cues. Furthermore, the lateral hypothalamus opposes learning about information that is neutral or distal to food. This reveals the lateral hypothalamus as a unique arbitrator of learning capable of shifting behavior toward or away from important events. This has relevance for disorders characterized by changes in this balance, including addiction and schizophrenia. Generally, this suggests that hypothalamic function is more complex than increasing or decreasing innate behaviors.

Lateral orbitofrontal cortex integrates predictive information across multiple cues to guide behavior

Individuals are often faced with multiple cues that concurrently predict the same outcome, and combining these predictions may benefit behavior. Previous work has studied the neural basis of decision-making, predominantly using isolated sensory stimuli, and so the mechanisms that allow us to leverage multiple cues remain unclear. In two experiments, we used neuroimaging and network-targeted brain stimulation to probe how the brain integrates outcome predictions to guide adaptive behavior. We identified neural signatures of outcome integration in the lateral orbitofrontal cortex (OFC), where concurrently presented cues evoke stronger pattern-based representations of expected outcomes. Moreover, perturbing lateral OFC network activity impairs subjects' ability to leverage predictions from multiple cues to facilitate responding. Intriguingly, we found similar behavioral and brain mechanisms for reward-predicting cues and for cues predicting the absence of reward. These findings highlight a causal role for the lateral OFC in utilizing outcome predictions from multiple cues to guide behavior.

The selective D3-Receptor antagonist VK4-116 effectively treats behavioral inflexibility in rats caused by self-administration and withdrawal from cocaine

Chronic psychostimulant use can cause long lasting changes to neural and cognitive function that persist even after long periods of abstinence. As cocaine users transition from drug use to abstinence, a parallel transition from hyperactivity to hypoactivity has been found in orbitofrontal-striatal glucose metabolism, and striatal D2/D3 receptor activity. Targeting these changes pharmacologically, using highly selective dopamine D3 receptor (D3R) antagonists and partial agonists, has shown significant promise in reducing drug-taking, and attenuating relapse in animal models of cocaine and opioid use disorder. However, much less attention has been focused on treating inflexible and potentially maladaptive non-drug behaviors following chronic psychostimulant use. Here we tested the selective D3R antagonist VK4-116 as a treatment for the long-term behavioral inflexibility in abstinent male and female rats with a prior history of chronic cocaine use. Rats were first trained to self-administer cocaine (0.75 mg/kg/reinforcer) or a sucrose liquid (10%, .04 mL/reinforcer) for 2 weeks (FR1 schedule, max 60 reinforcers in 3 hrs/ day), followed by 4 weeks of abstinence. Cognitive and behavioral flexibilities were then assessed using a sensory preconditioning (SPC) learning paradigm. Rats were given an VK4-116 (15 mg/kg, i.p.) or vehicle 30 mins prior to each SPC training session, thus creating four drug-treatment groups: sucrose-vehicle, sucrose-VK4-116, cocaine-vehicle, cocaine-VK4-116. The control groups (sucrose-vehicle, sucrose-VK4-116) demonstrated significant evidence of flexible SPC behavior, whereas cocaine use (cocaine-vehicle) disrupted SPC behavior. Remarkably, the D3R antagonist VK4-116 mitigated this cocaine deficit in the cocaine-VK4-116 group, demonstrating flexible SPC to levels comparable to the control groups. These preclinical findings demonstrate that highly selective dopamine D3R antagonists, particularly VK4-116, show significant promise as a pharmacological treatment for the long-term negative behavioral consequences of cocaine use disorder.

Computationally Informed Interventions for Targeting Compulsive Behaviors

Compulsive behaviors are central to addiction and obsessive-compulsive disorder and can be understood as a failure of adaptive decision making. Particularly, they can be conceptualized as an imbalance in behavioral control, such that behavior is guided predominantly by learned rather than inferred outcome expectations. Inference is a computational process required for adaptive behavior, and recent work across species has identified the neural circuitry that supports inference-based decision making. This includes the orbitofrontal cortex, which has long been implicated in disorders of compulsive behavior. Inspired by evidence that modulating orbitofrontal cortex activity can alter inference-based behaviors, here we discuss noninvasive approaches to target these circuits in humans. Specifically, we discuss the potential of network-targeted transcranial magnetic stimulation and real-time neurofeedback to modulate the neural underpinnings of inference. Both interventions leverage recent advances in our understanding of the neurocomputational mechanisms of inference-based behavior and may be used to complement current treatment approaches for behavioral disorders.

The role of the lateral orbitofrontal cortex in creating cognitive maps

We use mental models of the world-cognitive maps-to guide behavior. The lateral orbitofrontal cortex (lOFC) is typically thought to support behavior by deploying these maps to simulate outcomes, but recent evidence suggests that it may instead support behavior by underlying map creation. We tested between these two alternatives using outcome-specific devaluation and a high-potency chemogenetic approach. Selectively inactivating lOFC principal neurons when male rats learned distinct cue-outcome associations, but before outcome devaluation, disrupted subsequent inference, confirming a role for the lOFC in creating new maps. However, lOFC inactivation surprisingly led to generalized devaluation, a result that is inconsistent with a complete mapping failure. Using a reinforcement learning framework, we show that this effect is best explained by a circumscribed deficit in credit assignment precision during map construction, suggesting that the lOFC has a selective role in defining the specificity of associations that comprise cognitive maps.

The neural substrates of higher-order conditioning: A review

Sensory preconditioned and second-order conditioned responding are each well-documented. The former occurs in subjects (typically rats) exposed to pairings of two relatively neutral stimuli, S2 and S1, and then to pairings of S1 and a motivationally significant event [an unconditioned stimulus (US)]; the latter occurs when the order of these experiences is reversed with rats being exposed to S1-US pairings and then to S2-S1 pairings. In both cases, rats respond when tested with S2 in a manner appropriate to the affective nature of the US, e.g., approach when the US is appetitive and withdrawal when it is aversive. This paper reviews the neural substrates of sensory preconditioning and second-order conditioning. It identifies commonalities and differences in the substrates of these so-called higher-order conditioning protocols and discusses these commonalities/differences in relation to what is learned. In so doing, the review highlights ways in which these types of conditioning enhance our understanding of how the brain encodes and retrieves different types of information to generate appropriate behavior.

Understanding Associative Learning Through Higher-Order Conditioning

Associative learning is often considered to require the physical presence of stimuli in the environment in order for them to be linked. This, however, is not a necessary condition for learning. Indeed, associative relationships can form between events that are never directly paired. That is, associative learning can occur by integrating information across different phases of training. Higher-order conditioning provides evidence for such learning through two deceptively similar designs - sensory preconditioning and second-order conditioning. In this review, we detail the procedures and factors that influence learning in these designs, describe the associative relationships that can be acquired, and argue for the importance of this knowledge in studying brain function.

Anterior cingulate neurons signal neutral cue pairings during sensory preconditioning

Of all frontocortical subregions, the anterior cingulate cortex (ACC) has perhaps the most overlapping theories of function.1-3 Recording studies in rats, humans, and other primates have reported diverse neural responses that support many theories,4-12 yet nearly all these studies have in common tasks in which one event reliably predicts another. This leaves open the possibility that ACC represents associative pairing of events, independent of their overt biological significance. Sensory preconditioning13 provides an opportunity to test this. In the first phase, preconditioning, value-neutral sensory stimuli are paired (A→B). To test whether this was learned, subjects are given standard conditioning during which one of the previously neutral sensory cues is paired with a biologically meaningful outcome (B→outcome). During the final probe test, the neutral cue which was never paired with a biologically meaningful outcome is presented alone (A→) and will elicit a conditional response, suggesting that subjects had learned the associative structure during preconditioning and use that knowledge to infer presentation of the biologically relevant outcome (A→B→outcome). Inference-based responding demonstrates a fundamental property of model-based reasoning14,15 and requires learning of the associations between neutral stimuli before rewards are introduced.16-19 ACC neurons developed firing patterns that reflected the learning of sensory associations during preconditioning, even though no rewards were present. The strength of these correlates predicted rats' ability to later mobilize and use that associative information during the probe test. These results demonstrate that clear biological significance is not necessary to produce correlates of learning in ACC.

The prediction-error hypothesis of schizophrenia: new data point to circuit-specific changes in dopamine activity

Schizophrenia is a severe psychiatric disorder affecting 21 million people worldwide. People with schizophrenia suffer from symptoms including psychosis and delusions, apathy, anhedonia, and cognitive deficits. Strikingly, schizophrenia is characterised by a learning paradox involving difficulties learning from rewarding events, whilst simultaneously 'overlearning' about irrelevant or neutral information. While dysfunction in dopaminergic signalling has long been linked to the pathophysiology of schizophrenia, a cohesive framework that accounts for this learning paradox remains elusive. Recently, there has been an explosion of new research investigating how dopamine contributes to reinforcement learning, which illustrates that midbrain dopamine contributes in complex ways to reinforcement learning, not previously envisioned. This new data brings new possibilities for how dopamine signalling contributes to the symptomatology of schizophrenia. Building on recent work, we present a new neural framework for how we might envision specific dopamine circuits contributing to this learning paradox in schizophrenia in the context of models of reinforcement learning. Further, we discuss avenues of preclinical research with the use of cutting-edge neuroscience techniques where aspects of this model may be tested. Ultimately, it is hoped that this review will spur to action more research utilising specific reinforcement learning paradigms in preclinical models of schizophrenia, to reconcile seemingly disparate symptomatology and develop more efficient therapeutics.

Foraging with the frontal cortex: A cross-species evaluation of reward-guided behavior

Efficient foraging is essential to survival and depends on frontal cortex in mammals. Because of its role in psychiatric disorders, frontal cortex and its contributions to reward procurement have been studied extensively in both rodents and non-human primates. How frontal cortex of these animal models compares is a source of intense debate. Here we argue that translating findings from rodents to non-human primates requires an appreciation of both the niche in which each animal forages as well as the similarities in frontal cortex anatomy and function. Consequently, we highlight similarities and differences in behavior and anatomy, before focusing on points of convergence in how parts of frontal cortex contribute to distinct aspects of foraging in rats and macaques, more specifically. In doing so, our aim is to emphasize where translation of frontal cortex function between species is clearer, where there is divergence, and where future work should focus. We finish by highlighting aspects of foraging for which have received less attention but we believe are critical to uncovering how frontal cortex promotes survival in each species.

Higher-Order Conditioning and Dopamine: Charting a Path Forward

Higher-order conditioning involves learning causal links between multiple events, which then allows one to make novel inferences. For example, observing a correlation between two events (e.g., a neighbor wearing a particular sports jersey), later helps one make new predictions based on this knowledge (e.g., the neighbor's wife's favorite sports team). This type of learning is important because it allows one to benefit maximally from previous experiences and perform adaptively in complex environments where many things are ambiguous or uncertain. Two procedures in the lab are often used to probe this kind of learning, second-order conditioning (SOC) and sensory preconditioning (SPC). In second-order conditioning (SOC), we first teach subjects that there is a relationship between a stimulus and an outcome (e.g., a tone that predicts food). Then, an additional stimulus is taught to precede the predictive stimulus (e.g., a light leads to the food-predictive tone). In sensory preconditioning (SPC), this order of training is reversed. Specifically, the two neutral stimuli (i.e., light and tone) are first paired together and then the tone is paired separately with food. Interestingly, in both SPC and SOC, humans, rodents, and even insects, and other invertebrates will later predict that both the light and tone are likely to lead to food, even though they only experienced the tone directly paired with food. While these processes are procedurally similar, a wealth of research suggests they are associatively and neurobiologically distinct. However, midbrain dopamine, a neurotransmitter long thought to facilitate basic Pavlovian conditioning in a relatively simplistic manner, appears critical for both SOC and SPC. These findings suggest dopamine may contribute to learning in ways that transcend differences in associative and neurological structure. We discuss how research demonstrating that dopamine is critical to both SOC and SPC places it at the center of more complex forms of cognition (e.g., spatial navigation and causal reasoning). Further, we suggest that these more sophisticated learning procedures, coupled with recent advances in recording and manipulating dopamine neurons, represent a new path forward in understanding dopamine's contribution to learning and cognition.

Is the core function of orbitofrontal cortex to signal values or make predictions?

One dominant hypothesis about the function of the orbitofrontal cortex (OFC) is that the OFC signals the subjective values of possible outcomes to other brain areas for learning and decision making. This popular view generally neglects the fact that OFC is not necessary for simple value-based behavior (i.e., when values have been directly experienced). An alternative, emerging view suggests that OFC plays a more general role in representing structural information about the task or environment, derived from prior experience, and relevant to predicting behavioral outcomes, such as value. From this perspective, value signaling is simply one derivative of the core underlying function of OFC. New data in favor of both views have been accumulating rapidly. Here we review these new data in discussing the relative merits of these two ideas.

Neural circuits for inference-based decision-making

In novel situations, where direct experience is lacking or outdated, humans must rely on mental simulations to predict future outcomes. This review discusses recent work on the neural circuits that support such inference-based behavior. We focus on two specific examples: 1) using knowledge about the associative structure of the world to infer outcomes when direct experience is lacking; 2) inferring the current value of options when the desirability of the associated outcome has changed since the original learning experience. These two examples can be studied in the sensory preconditioning and devaluation tasks, respectively. We review results from studies in animals and humans suggesting that the orbitofrontal cortex (OFC), together with the hippocampus and amygdala, is necessary for inference in both of these tasks. Together, these findings suggest that the OFC is a critical hub in the brain network that supports inference-based decision-making.

Neural Substrates of Incidental Associations and Mediated Learning: The Role of Cannabinoid Receptors

The ability to form associations between different stimuli in the environment to guide adaptive behavior is a central element of learning processes, from perceptual learning in humans to Pavlovian conditioning in animals. Like so, classical conditioning paradigms that test direct associations between low salience sensory stimuli and high salience motivational reinforcers are extremely informative. However, a large part of everyday learning cannot be solely explained by direct conditioning mechanisms - this includes to a great extent associations between individual sensory stimuli, carrying low or null immediate motivational value. This type of associative learning is often described as incidental learning and can be captured in animal models through sensory preconditioning procedures. Here we summarize the evolution of research on incidental and mediated learning, overview the brain systems involved and describe evidence for the role of cannabinoid receptors in such higher-order learning tasks. This evidence favors a number of contemporary hypotheses concerning the participation of the endocannabinoid system in psychosis and psychotic experiences and provides a conceptual framework for understanding how the use of cannabinoid drugs can lead to altered perceptive states.

Mechanisms of higher-order learning in the amygdala

Adaptive behaviour is under the potent control of environmental cues. Such cues can acquire value by virtue of their associations with outcomes of motivational significance, be they appetitive or aversive. There are at least two ways through which an environmental cue can acquire value, through first-order and higher-order conditioning. In first-order conditioning, a neutral cue is directly paired with an outcome of motivational significance. In higher-order conditioning, a cue is indirectly associated with motivational events via a directly conditioned first-order stimulus. The present article reviews some of the associations that support learning in first- and higher-order conditioning, as well as the role of the BLA and the molecular mechanisms involved in these two types of learning.

The orbitofrontal cortex is necessary for learning to ignore

Animals learn not only what is potentially useful but also what is meaningless and should be disregarded. How this is accomplished is a key but seldom explored question in psychology and neuroscience. Learning to ignore irrelevant cues is evident in latent inhibition-the ubiquitous phenomenon where presenting a cue several times without consequences leads to retardation of subsequent conditioning to that cue.1,2 Does learning to ignore these cues, because they predict nothing, involve the same neural circuits that are critical to learning to make predictions about other "real world" impending events? If so, the orbitofrontal cortex (OFC), as a key node in such networks, should be important.3 Specifically, the OFC has been hypothesized to participate in the recognition of hidden task states, which are not directly signaled by explicit outcomes.4 Evaluating its involvement in pre-exposure learning during latent inhibition would be an acid test for this hypothesis. Here, we report that selective chemogenetic inactivation of rat orbitofrontal cortex principal neurons during stimulus pre-exposure markedly reduces latent inhibition in subsequent conditioning. Inactivation only during pre-exposure ensured that the observed effects were due to an impact on the acquisition of information prior to its use in any sort of behavior, i.e., during latent learning. Further behavioral tests confirmed this, showing that the impact of OFC inactivation during pre-exposure was limited to the latent inhibition effect. These results demonstrate that the OFC is important for latent learning and the formation of associations even in the absence of explicit outcomes.

Cortical Contributions to Higher-Order Conditioning: A Review of Retrosplenial Cortex Function

In higher-order conditioning paradigms, such as sensory preconditioning or second-order conditioning, discrete (e.g., phasic) or contextual (e.g., static) stimuli can gain the ability to elicit learned responses despite never being directly paired with reinforcement. The purpose of this mini-review is to examine the neuroanatomical basis of high-order conditioning, by selectively reviewing research that has examined the role of the retrosplenial cortex (RSC) in sensory preconditioning and second-order conditioning. For both forms of higher-order conditioning, we first discuss the types of associations that may occur and then review findings from RSC lesion/inactivation experiments. These experiments demonstrate a role for the RSC in sensory preconditioning, suggesting that this cortical region might contribute to higher-order conditioning via the encoding of neutral stimulus-stimulus associations. In addition, we address knowledge gaps, avenues for future research, and consider the contribution of the RSC to higher-order conditioning in relation to related brain structures.

Cross-species studies on orbitofrontal control of inference-based behavior

Many decisions are guided by expectations about their outcomes. These expectations can arise from two fundamentally different sources: from direct experience with outcomes and the events and actions that precede them or from mental simulations and inferences when direct experience is missing. Here we discuss four elegant tasks from animal learning theory (devaluation, sensory preconditioning, Pavlovian-to-instrumental transfer, and Pavlovian overexpectation) and how they can be used to isolate behavior that is based on such mental simulations from behavior that can be based solely on experience. We then review findings from studies in rodents, nonhuman primates, and humans that use these tasks in combination with neural recording and loss-of-function experiments to understand the role of the orbitofrontal cortex (OFC) in outcome inference. The results of these studies show that activity in the OFC is correlated with inferred outcome expectations and that an intact OFC is necessary for inference-based behavior and learning. In summary, these findings provide converging cross-species support for the idea that the OFC is critical for behavior that is based on inferred outcomes, whereas it is not required when expectations can be based on direct experience alone. This conclusion may have important implications for our understanding of the role of OFC in psychiatric disorders and how we may be able to treat them. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

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).

Targeted Stimulation of an Orbitofrontal Network Disrupts Decisions Based on Inferred, Not Experienced Outcomes

When direct experience is unavailable, animals and humans can imagine or infer the future to guide decisions. Behavior based on direct experience versus inference may recruit partially distinct brain circuits. In rodents, the orbitofrontal cortex (OFC) contains neural signatures of inferred outcomes, and OFC is necessary for behavior that requires inference but not for responding driven by direct experience. In humans, OFC activity is also correlated with inferred outcomes, but it is unclear whether OFC activity is required for inference-based behavior. To test this, we used noninvasive network-based continuous theta burst stimulation (cTBS) in human subjects (male and female) to target lateral OFC networks in the context of a sensory preconditioning task that was designed to isolate inference-based behavior from responding that can be based on direct experience alone. We show that, relative to sham, cTBS targeting this network impairs reward-related behavior in conditions in which outcome expectations have to be mentally inferred. In contrast, OFC-targeted stimulation does not impair behavior that can be based on previously experienced stimulus–outcome associations. These findings suggest that activity in the targeted OFC network supports decision-making when outcomes have to be mentally simulated, providing converging cross-species evidence for a critical role of OFC in model-based but not model-free control of behavior.

SIGNIFICANCE STATEMENT It is widely accepted that the orbitofrontal cortex (OFC) is important for decision-making. However, it is less clear how exactly this region contributes to behavior. Here we test the hypothesis that the human OFC is only required for decision-making when future outcomes have to be mentally simulated, but not when direct experience with stimulus–outcome associations is available. We show that targeting OFC network activity in humans using network-based continuous theta burst stimulation selectively impairs behavior that requires inference but does not affect responding that can be based solely on direct experience. These results are in line with previous findings in animals and suggest a critical role for human OFC in model-based but not model-free behavior.