Lateral Orbitofrontal Inactivation Dissociates Devaluation-Sensitive Behavior and Economic Choice

The representation of decision variables in orbitofrontal cortex is longitudinally stable

The computation and comparison of subjective values underlying economic choices rely on the orbitofrontal cortex (OFC). In this area, distinct groups of neurons encode the value of individual options, the binary choice outcome, and the chosen value. These variables capture both the choice input and the choice output, suggesting that the cell groups found in the OFC constitute the building blocks of a decision circuit. Here, we show that this neural circuit is longitudinally stable. Using two-photon calcium imaging, we record from the OFC of mice engaged in a juice-choice task. Imaging of individual cells continues for up to 40 weeks. For each cell and each session pair, we compare activity profiles using cosine similarity, and we assess whether the neuron encodes the same variable in both sessions. We find a high degree of stability and a modest representational drift. Quantitative estimates indicate that this drift would not randomize the circuit within the animal's lifetime.

Predictive filtering of sensory response via orbitofrontal top-down input

Habituation is a crucial sensory filtering mechanism whose dysregulation can lead to a continuously intense world in disorders with sensory overload. While habituation is considered to require top-down predictive signaling to suppress irrelevant inputs, the exact brain loci storing the internal predictive model and the circuit mechanisms of sensory filtering remain unclear. We found that daily neural habituation in the primary auditory cortex (A1) was reversed by inactivation of the orbitofrontal cortex (OFC). Top-down projections from the ventrolateral OFC, but not other frontal areas, carried predictive signals that grew with daily sound experience and suppressed A1 via somatostatin-expressing inhibitory neurons. Thus, prediction signals from the OFC cancel out behaviorally irrelevant anticipated stimuli by generating their "negative images" in sensory cortices.

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.

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.

Lateral Orbitofrontal Cortex Encodes Presence of Risk and Subjective Risk Preference During Decision-Making

Adaptive decision-making requires consideration of objective risks and rewards associated with each option, as well as subjective preference for risky/safe alternatives. Inaccurate risk/reward estimations can engender excessive risk-taking, a central trait in many psychiatric disorders. The lateral orbitofrontal cortex (lOFC) has been linked to many disorders associated with excessively risky behavior and is ideally situated to mediate risky decision-making. Here, we used single-unit electrophysiology to measure neuronal activity from lOFC of freely moving rats performing in a punishment-based risky decision-making task. Subjects chose between a small, safe reward and a large reward associated with either 0% or 50% risk of concurrent punishment. lOFC activity repeatedly encoded current risk in the environment throughout the decision-making sequence, signaling risk before, during, and after a choice. In addition, lOFC encoded reward magnitude, although this information was only evident during action selection. A Random Forest classifier successfully used neural data accurately to predict the risk of punishment in any given trial, and the ability to predict choice via lOFC activity differentiated between and risk-preferring and risk-averse rats. Finally, risk preferring subjects demonstrated reduced lOFC encoding of risk and increased encoding of reward magnitude. These findings suggest lOFC may serve as a central decision-making hub in which external, environmental information converges with internal, subjective information to guide decision-making in the face of punishment risk.

Event-specific and persistent representations for contextual states in orbitofrontal neurons

Flexible and context-dependent behaviors require animals, including humans, to identify their current contextual state for proper rules to apply, especially when information that defines these states is partially observable. Depending on behavioral needs, contextual states usually persist for prolonged periods and across other events, including sensory stimuli, actions, and rewards, highlighting prominent challenges of holding a reliable state representation. The orbitofrontal cortex (OFC) is crucial in behaviors requiring the identification of the current context (e.g., reversal learning); however, how single units in the OFC accomplish this function has not been assessed. Do they maintain such information persistently, in separate populations from those responding phasically to events within a task, or is contextual information dynamic and embedded in these phasic responses? Here, we investigated this question by recording single units from OFC in rats performing a task that required them to identify the current contextual state related to estimated proximity to future reward with distracting olfactory cues. We found that while some OFC neurons encode contextual states, most change their selectivity upon the transition of task events. Nevertheless, despite dynamic activities in single neurons, the neural populations maintain persistent representations regarding current contextual states within particular neural subspaces.

Orbitofrontal cortex control of striatum leads economic decision-making

Animals must continually evaluate stimuli in their environment to decide which opportunities to pursue, and in many cases these decisions can be understood in fundamentally economic terms. Although several brain regions have been individually implicated in these processes, the brain-wide mechanisms relating these regions in decision-making are unclear. Using an economic decision-making task adapted for rats, we find that neural activity in both of two connected brain regions, the ventrolateral orbitofrontal cortex (OFC) and the dorsomedial striatum (DMS), was required for economic decision-making. Relevant neural activity in both brain regions was strikingly similar, dominated by the spatial features of the decision-making process. However, the neural encoding of choice direction in OFC preceded that of DMS, and this temporal relationship was strongly correlated with choice accuracy. Furthermore, activity specifically in the OFC projection to the DMS was required for appropriate economic decision-making. These results demonstrate that choice information in the OFC is relayed to the DMS to lead accurate economic decision-making.

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.

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.

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.

Mediodorsal Thalamus Is Critical for Updating during Extradimensional Shifts But Not Reversals in the Attentional Set-Shifting Task

Cognitive flexibility, attributed to frontal cortex, is vital for navigating the complexities of everyday life. The mediodorsal thalamus (MD), interconnected to frontal cortex, may influence cognitive flexibility. Here, male rats performed an attentional set-shifting task measuring intradimensional (ID) and extradimensional (ED) shifts in sensory discriminations. MD lesion rats needed more trials to learn the rewarded sensory dimension. However, once the choice response strategy was established, learning further two-choice discriminations in the same sensory dimension, and reversals of the reward contingencies in the same dimension, were unimpaired. Critically though, MD lesion rats were impaired during the ED shift, when they must rapidly update the optimal choice response strategy. Behavioral analyses showed MD lesion rats had significantly reduced correct within-trial second choice responses. This evidence shows that transfer of information via the MD is critical when rapid within-trial updates in established choice response strategies are required after a rule change.

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'.

The Neural Instantiation of an Abstract Cognitive Map for Economic Choice

Since the discovery of cognitive maps in rodent hippocampus (HC), the cognitive map has evolved from originally referring to spatial representations encoding locations and objects in Euclidean spaces to a general low-dimensional organization of information along selected feature dimensions. A cognitive map includes hypothetical constructs that bridge between environmental stimuli and the final overt behavior. To neuroeconomists, utility and utility functions are such constructs with neurobiological basis that drive choice behavior. Emergence of distinct functional neuron groups in the primate orbitofrontal cortex (OFC) during simple economic choice indicates the formation of an abstract cognitive map for organizing information of goods for value computation. Experimental evidence suggests that organization of neuronal activity in such cognitive map reflects the abstraction of core task features. Thus, such map can be adapted to accommodate economic choices under various task contexts.

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.

Hypothalamic control of interoceptive hunger

While energy balance is critical to survival, many factors influence food intake beyond caloric need or "hunger." Despite this, some neurons that drive feeding in mice are routinely referred to as "hunger neurons," whereas others are not. To understand how specific hypothalamic circuits control interoceptive hunger, we trained mice to discriminate fasted from sated periods. We then manipulated three hypothalamic neuronal populations with well-known effects on feeding while mice performed this task. While activation of ARC^AGRP neurons in sated mice caused mice to report being food-restricted, LH^VGAT neuron activation or LH^VGLUT2 neuron inhibition did not. In contrast, LH^VGAT neuron inhibition or LH^VGLUT2 neuron activation in fasted mice attenuated natural hunger, whereas ARC^AGRP neuron inhibition did not. Each neuronal population evoked distinct effects on food consumption and reward. After satiety- or sickness-induced devaluation, ARC^AGRP neurons drove calorie-specific feeding, while LH^VGAT neurons drove calorie-indiscriminate food intake. Our data support a role for ARC^AGRP neurons in homeostatic feeding and implicate them in driving a hunger-like internal state that directs behavior toward caloric food sources. Moreover, manipulations of LH circuits did not evoke hunger-like effects in sated mice, suggesting that they may govern feeding more related to reward, compulsion, or generalized consumption than to energy balance, but also that these LH circuits can be powerful negative appetite modulators in fasted mice. This study highlights the complexity of hypothalamic feeding regulation and can be used as a framework to characterize how other neuronal circuits affect hunger and identify potential therapeutic targets for eating disorders.

A cortical circuit mechanism for structural knowledge-based flexible sensorimotor decision-making

Making flexible decisions based on prior knowledge about causal environmental structures is a hallmark of goal-directed cognition in mammalian brains. Although several association brain regions, including the orbitofrontal cortex (OFC), have been implicated, the precise neuronal circuit mechanisms underlying knowledge-based decision-making remain elusive. Here, we established an inference-based auditory categorization task where mice performed within-session flexible stimulus re-categorization by inferring the changing task rules. We constructed a reinforcement learning model to recapitulate the inference-based flexible behavior and quantify the hidden variables associated with task structural knowledge. Combining two-photon population imaging and projection-specific optogenetics, we found that auditory cortex (ACx) neurons encoded the hidden task rule variable, which requires feedback input from the OFC. Silencing OFC-ACx input specifically disrupted re-categorization behavior. Direct imaging from OFC axons in the ACx revealed task state-related feedback signals, supporting the knowledge-based updating mechanism. Our data reveal a cortical circuit mechanism underlying structural knowledge-based flexible decision-making.

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).

Defining an orbitofrontal compass: Functional and anatomical heterogeneity across anterior-posterior and medial-lateral axes

The orbitofrontal cortex (OFC) plays a critical role in the flexible control of behaviors and has been the focus of increasing research interest. However, there have been a number of controversies around the exact theoretical role of the OFC. One potential source of these issues is the comparison of evidence from different studies, particularly across species, which focus on different specific sub-regions within the OFC. Furthermore, there is emerging evidence that there may be functional diversity across the OFC which may account for these theoretical differences. Therefore, in this review we consider evidence supporting functional heterogeneity within the OFC and how it relates to underlying anatomical heterogeneity. We highlight the importance of anatomical and functional distinctions within the traditionally defined OFC subregions across the medial-lateral axis, which are often not differentiated for practical and historical reasons. We then consider emerging evidence of even finer-grained distinctions within these defined subregions along the anterior-posterior axis. These fine-grained anatomical considerations reveal a pattern of dissociable, but often complementary functions within the OFC. (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).

Causal investigations into orbitofrontal control of human decision making

Although it is widely accepted that the orbitofrontal cortex (OFC) is important for decision making, its precise contribution to behavior remains a topic of debate. While many loss of function experiments have been conducted in animals, causal studies of human OFC function are relatively scarce. This review discusses recent causal investigations into the human OFC, with an emphasis on advances in network-based brain stimulation approaches to indirectly perturb OFC function. Findings show that disruption of human OFC impairs decisions that require mental simulation of outcomes. Taken together, these results support the idea that human OFC contributes to decision making by representing a cognitive map of the task environment, facilitating inference of outcomes not yet experienced. Future work may utilize similar non-invasive approaches in clinical settings to mitigate decision making deficits in neuropsychiatric disorders.

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).

To be specific: The role of orbitofrontal cortex in signaling reward identity

The orbitofrontal cortex (OFC) plays a prominent role in signaling reward expectations. Two important features of rewards are their value (how good they are) and their specific identity (what they are). Whereas research on OFC has traditionally focused on reward value, recent findings point toward a pivotal role of reward identity in understanding OFC signaling and its contribution to behavior. Here, we review work in rodents, nonhuman primates, and humans on how the OFC represents expectations about the identity of rewards, and how these signals contribute to outcome-guided behavior. Moreover, we summarize recent findings suggesting that specific reward expectations in OFC are learned and updated by means of identity errors in the dopaminergic midbrain. We conclude by discussing how OFC encoding of specific rewards complements recent proposals that this region represents a cognitive map of relevant task states, which forms the basis for model-based behavior. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Altered Activity of Lateral Orbitofrontal Cortex Neurons in Mice following Chronic Intermittent Ethanol Exposure

The lateral orbitofrontal cortex (LOFC) is thought to encode information associated with consumption of rewarding substances and is essential for flexible decision-making. Indeed, firing patterns of LOFC neurons are modulated following changes in reward value associated with an action outcome relationship. Damage to the LOFC impairs behavioral flexibility in humans and is associated with suboptimal performance in reward devaluation protocols in rodents. As chronic intermittent ethanol (CIE) exposure also impairs OFC-dependent behaviors, we hypothesized that CIE exposure would alter LOFC neuronal activity during alcohol drinking, especially under conditions when the reward value of ethanol was modulated by aversive or appetitive tastants. To test this hypothesis, we monitored LOFC activity using GCaMP6f fiber photometry in mice receiving acute injections of ethanol and in those trained in operant ethanol self-administration. In naive mice, an acute injection of ethanol caused a dose-dependent decrease in the frequency but not amplitude of GCaMP6f transients. In operant studies, mice were trained on a fixed ratio one schedule of reinforcement and were then separated into CIE or Air groups. Following four cycles of CIE exposure, GCaMP6f activity was recorded during self-administration of alcohol, alcohol+quinine (aversive), or alcohol+sucrose (appetitive) solutions. LOFC neurons showed discrete patterns of activity surrounding lever presses and surrounding drinking bouts. Responding for and consumption of ethanol was greatly enhanced by CIE exposure, was aversion resistant, and was associated with signs of LOFC hyperexcitability. CIE-exposed mice also showed altered patterns of LOFC activity that varied with the ethanol solution consumed.

The Role of the Rodent Lateral Orbitofrontal Cortex in Simple Pavlovian Cue-Outcome Learning Depends on Training Experience

The orbitofrontal cortex (OFC) is a critical structure in the flexible control of value-based behaviors. OFC dysfunction is typically only detected when task or environmental contingencies change, against a backdrop of apparently intact initial acquisition and behavior. While intact acquisition following OFC lesions in simple Pavlovian cue-outcome conditioning is often predicted by models of OFC function, this predicted null effect has not been thoroughly investigated. Here, we test the effects of lesions and temporary muscimol inactivation of the rodent lateral OFC on the acquisition of a simple single cue-outcome relationship. Surprisingly, pretraining lesions significantly enhanced acquisition after overtraining, whereas post-training lesions and inactivation significantly impaired acquisition. This impaired acquisition to the cue reflects a disruption of behavioral control and not learning since the cue could also act as an effective blocking stimulus in an associative blocking procedure. These findings suggest that even simple cue-outcome representations acquired in the absence of OFC function are impoverished. Therefore, while OFC function is often associated with flexible behavioral control in complex environments, it is also involved in very simple Pavlovian acquisition where complex cue-outcome relationships are irrelevant to task performance.

Evolving schema representations in orbitofrontal ensembles during learning

How do we learn about what to learn about? Specifically, how do the neural elements in our brain generalize what has been learned in one situation to recognize the common structure of-and speed learning in-other, similar situations? We know this happens because we become better at solving new problems-learning and deploying schemas1-5-through experience. However, we have little insight into this process. Here we show that using prior knowledge to facilitate learning is accompanied by the evolution of a neural schema in the orbitofrontal cortex. Single units were recorded from rats deploying a schema to learn a succession of odour-sequence problems. With learning, orbitofrontal cortex ensembles converged onto a low-dimensional neural code across both problems and subjects; this neural code represented the common structure of the problems and its evolution accelerated across their learning. These results demonstrate the formation and use of a schema in a prefrontal brain region to support a complex cognitive operation. Our results not only reveal a role for the orbitofrontal cortex in learning but also have implications for using ensemble analyses to tap into complex cognitive functions.

A cortical thinning signature to identify World Trade Center responders with possible dementia

Introduction:

World Trade Center (WTC) responders have a high risk of early-onset cognitive impairment (CI), but little is known about the etiology including the extent to which CI in WTC responders is accompanied by cortical atrophy as is common in progressive diseases causing age-related CI such as Alzheimer’s disease and related dementias. In the current study, we entrained an artificial neural network (ANN) to determine the accuracy of cortical thickness (CTX) on magnetic resonance imaging to identify World Trade Center responders at midlife (aged 44–65 years) with possible dementia.

Methods:

A total of 119 WTC responders (57 with CI and 62 with intact cognition) underwent a structural MRI scanning protocol including T1-weighted MPRAGE as part of two imaging studies. The discovery study was divided into training and validation samples, while a second replication sample was used. An ANN was trained using regional CTX measured across 34 unilateral regions of interest (ROIs) using Freesurfer software and ‘Desikan-Killiany’ brain atlas. The discovery sample was used for model development, and the replication sample was used to evaluate predictive accuracy.

Results:

In the WTC responder cohort, the ANN algorithm showed high discrimination performance for CI. The ANN model using regional CTX data from both hemispheres achieved an area under the receiver operating characteristic curve (AUC) of 0.96 95% C.I. = [0.91–1.00] (Accuracy = 96.0%, Precision = 97.8%, Recall = 95.8%, Sensitivity = 95.8%, Specificity = 98.0%, F1 = 96.8%) for the discovery sample and AUC = 0.90 [0.70–1.00] (Accuracy = 90.0%, Precision = 90.0%, Sensitivity = 90.0%, Specificity = 90.0%, F1 = 90.0%) in the replication sample.

Conclusion:

Analysis of bilateral regional CTX data derived from T1-weighted MPRAGE images by ANN analysis demonstrated excellent accuracy in distinguishing WTC responders with early-onset CI.

Processing in Lateral Orbitofrontal Cortex Is Required to Estimate Subjective Preference during Initial, but Not Established, Economic Choice

The orbitofrontal cortex (OFC) is proposed to be critical to economic decision making. Yet one can inactivate OFC without affecting well-practiced choices. One possible explanation of this lack of effect is that well-practiced decisions are codified into habits or configural-based policies not normally thought to require OFC. Here, we tested this idea by training rats to choose between different pellet pairs across a set of standard offers and then inactivating OFC subregions during choices between novel offers of previously experienced pairs or between novel pairs of previously experienced pellets. Contrary to expectations, controls performed as well on novel as experienced offers yet had difficulty initially estimating their subjective preference on novel pairs, difficulty exacerbated by lateral OFC inactivation. This pattern of results indicates that established economic choice reflects the use of an underlying model or goods space and that lateral OFC is only required for normal behavior when the established framework must incorporate new information.

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.

The orbitofrontal cortex, food intake and obesity

Obesity is a major health challenge facing many people throughout the world. Increased consumption of palatable, high-caloric foods is one of the major drivers of obesity. Both orexigenic and anorexic states have been thoroughly reviewed elsewhere; here, we focus on the cognitive control of feeding in the context of obesity, and how the orbitofrontal cortex (OFC) is implicated, based on data from preclinical and clinical research. The OFC is important in decision-making and has been heavily researched in neuropsychiatric illnesses such as addiction and obsessive–compulsive disorder. However, activity in the OFC has only recently been described in research into food intake, obesity and eating disorders. The OFC integrates sensory modalities such as taste, smell and vision, and it has dense reciprocal projections into thalamic, midbrain and striatal regions to fine-tune decision-making. Thus, the OFC may be anatomically and functionally situated to play a critical role in the etiology and maintenance of excess feeding behaviour. We propose that the OFC serves as an integrative hub for orchestrating motivated feeding behaviour and suggest how its neurobiology and functional output might be altered in the obese state.

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

The orbitofrontal cortex (OFC) is necessary for inferring value in tests of model-based reasoning, including in sensory preconditioning. This involvement could be accounted for by representation of value or by representation of broader associative structure. We recently reported neural correlates of such broader associative structure in OFC during the initial phase of sensory preconditioning (Sadacca et al., 2018). Here, we used optogenetic inhibition of OFC to test whether these correlates might be necessary for value inference during later probe testing. We found that inhibition of OFC during cue-cue learning abolished value inference during the probe test, inference subsequently shown in control rats to be sensitive to devaluation of the expected reward. These results demonstrate that OFC must be online during cue-cue learning, consistent with the argument that the correlates previously observed are not simply downstream readouts of sensory processing and instead contribute to building the associative model supporting later behavior.

Differential encoding of action selection by orbitofrontal and striatal population dynamics

Survival relies on the ability to flexibly choose between different actions according to varying environmental circumstances. Many lines of evidence indicate that action selection involves signaling in corticostriatal circuits, including the orbitofrontal cortex (OFC) and dorsomedial striatum (DMS). While choice-specific responses have been found in individual neurons from both areas, it is unclear whether populations of OFC or DMS neurons are better at encoding an animal's choice. To address this, we trained head-fixed mice to perform an auditory guided two-alternative choice task, which required moving a joystick forward or backward. We then used silicon microprobes to simultaneously measure the spiking activity of OFC and DMS ensembles, allowing us to directly compare population dynamics between these areas within the same animals. Consistent with previous literature, both areas contained neurons that were selective for specific stimulus-action associations. However, analysis of concurrently recorded ensemble activity revealed that the animal's trial-by-trial behavior could be decoded more accurately from DMS dynamics. These results reveal substantial regional differences in encoding action selection, suggesting that DMS neural dynamics are more specialized than OFC at representing an animal's choice of action.NEW & NOTEWORTHY While previous literature shows that both orbitofrontal cortex (OFC) and dorsomedial striatum (DMS) represent information relevant to selecting specific actions, few studies have directly compared neural signals between these areas. Here we compared OFC and DMS dynamics in mice performing a two-alternative choice task. We found that the animal's choice could be decoded more accurately from DMS population activity. This work provides among the first evidence that OFC and DMS differentially represent information about an animal's selected action.

Prefrontal regulation of behavioural control: Evidence from learning theory and translational approaches in rodents

Everyday activities require adaptive decision-making and control over our actions to achieve our goals. Sub-regions within the cortex are widely reported to regulate these choices. Here we review rodent studies from two disparate fields of instrumental action control - goal-directed and habitual responding, and impulsive and compulsive behaviour. Our aim was to compare findings across the spectrum, from precision associative learning to translational studies of action control. The evidence suggests that each cortical sub-region performs different roles depending on task requirements and, within tasks, clear dissociations exist between regions. Rather than synthesizing a single role or function for a given region, we should consider regions to be capable of many different functions. Further investigation of cortico-cortical connections and the pattern of input and output circuitry within each region may be needed to identify unique process-specific pathways. Despite differences in the scope and purpose of these two fields, integrating evidence across tasks provides a broader context for testing hypotheses about the role of cortical regions in adaptive actions and decision-making.

Value and choice as separable and stable representations in orbitofrontal cortex

Value-based decision-making requires different variables-including offer value, choice, expected outcome, and recent history-at different times in the decision process. Orbitofrontal cortex (OFC) is implicated in value-based decision-making, but it is unclear how downstream circuits read out complex OFC responses into separate representations of the relevant variables to support distinct functions at specific times. We recorded from single OFC neurons while macaque monkeys made cost-benefit decisions. Using a novel analysis, we find separable neural dimensions that selectively represent the value, choice, and expected reward of the present and previous offers. The representations are generally stable during periods of behavioral relevance, then transition abruptly at key task events and between trials. Applying new statistical methods, we show that the sensitivity, specificity and stability of the representations are greater than expected from the population's low-level features-dimensionality and temporal smoothness-alone. The separability and stability suggest a mechanism-linear summation over static synaptic weights-by which downstream circuits can select for specific variables at specific times.

Representation of foreseeable choice outcomes in orbitofrontal cortex triplet-wise interactions

Shared neuronal variability has been shown to modulate cognitive processing. However, the relationship between shared variability and behavioral performance is heterogeneous and complex in frontal areas such as the orbitofrontal cortex (OFC). Mounting evidence shows that single-units in OFC encode a detailed cognitive map of task-space events, but the existence of a robust neuronal ensemble coding for the predictability of choice outcome is less established. Here, we hypothesize that the coding of foreseeable outcomes is potentially unclear from the analysis of units activity and their pairwise correlations. However, this code might be established more conclusively when higher-order neuronal interactions are mapped to the choice outcome. As a case study, we investigated the trial-to-trial shared variability of neuronal ensemble activity during a two-choice interval-discrimination task in rodent OFC, specifically designed such that a lose-switch strategy is optimal by repeating the rewarded stimulus in the upcoming trial. Results show that correlations among triplets are higher during correct choices with respect to incorrect ones, and that this is sustained during the entire trial. This effect is not observed for pairwise nor for higher than third-order correlations. This scenario is compatible with constellations of up to three interacting units assembled during trials in which the task is performed correctly. More interestingly, a state-space spanned by such constellations shows that only correct outcome states that can be successfully predicted are robust over 100 trials of the task, and thus they can be accurately decoded. However, both incorrect and unpredictable outcome representations were unstable and thus non-decodeable, due to spurious negative correlations. Our results suggest that predictability of successful outcomes, and hence the optimal behavioral strategy, can be mapped out in OFC ensemble states reliable over trials of the task, and revealed by sufficiency complex neuronal interactions.

Neuronal responses can differ substantially during repetitions of the same tasks; however, they are often coordinated (shared) across multiple neighboring neurons. Such correlation between neurons has been related to the capacity of the brain to take decisions, but specifically how this relation is established is still under study. In this work, we address this question by focusing on an intriguing case study, the orbitofrontal cortex, since this brain area has been found in various studies to be useful for decision-making. Here, we question whether orchestrated groups of neurons encode sufficient information for optimizing their decision strategy; that is, whether the outcome of a choice can be predicted or not on the basis of previous experience. We thus designed a decision-making task for a rat in which some of the correct choices can be predicted. We found that only successful outcomes that can actually be predicted were robustly encoded over time. This finding was shown by analyzing sufficiently complex interactions between three neurons, whilst more complex orchestrations did not add further insights. Thus, we propose that coordinated responses of up to three neurons in the OFC could contribute to the capacity of the animal to take the optimal decision.

Habitual Preference for the Nondrug Reward in a Drug Choice Setting

For adaptive and efficient decision making, it must be possible to select between habitual alternative courses of action. However, research in rodents suggests that, even in the context of simple decision-making, choice behavior remains goal-directed. In contrast, we recently found that during discrete trial choice between cocaine and water, water-restricted rats preferred water and this preference was habitual and inflexible (i.e., resistant to water devaluation by satiation). Here we sought to test the reproducibility and generality of this surprising finding by assessing habitual control of preference for saccharin over cocaine in non-restricted rats. Specifically, after the acquisition of preference for saccharin, saccharin was devalued and concurrent responding for both options was measured under extinction. As expected, rats responded more for saccharin than for cocaine during extinction, but this difference was unaffected by saccharin devaluation. Together with our previous research, this result indicates that preference for nondrug alternatives over cocaine is under habitual control, even under conditions that normally support goal-directed control of choice between nondrug options. The possible reasons for this difference are discussed.

Glutamatergic fast-spiking parvalbumin neurons in the lateral hypothalamus: Electrophysiological properties to behavior

Throughout the central nervous system, neurons expressing the calcium-binding protein parvalbumin have been typically classified as GABAergic with fast-spiking characteristics. However, new methods that allow systematic characterization of the cytoarchitectural organization, connectivity, activity patterns, neurotransmitter nature, and function of genetically-distinct cell types have revealed populations of parvalbumin-positive neurons that are glutamatergic. Remarkably, such findings challenge longstanding concepts that fast-spiking neurons are exclusively GABAergic, suggesting conservation of the fast-spiking phenotype across at least two neurotransmitter systems. This review focuses on the recent advancements that have begun to reveal the functional roles of lateral hypothalamic parvalbumin-positive neurons in regulating behaviors essential for survival.

Neural mechanisms of economic choices in mice

Economic choices entail computing and comparing subjective values. Evidence from primates indicates that this behavior relies on the orbitofrontal cortex. Conversely, previous work in rodents provided conflicting results. Here we present a mouse model of economic choice behavior, and we show that the lateral orbital (LO) area is intimately related to the decision process. In the experiments, mice chose between different juices offered in variable amounts. Choice patterns closely resembled those measured in primates. Optogenetic inactivation of LO dramatically disrupted choices by inducing erratic changes of relative value and by increasing choice variability. Neuronal recordings revealed that different groups of cells encoded the values of individual options, the binary choice outcome and the chosen value. These groups match those previously identified in primates, except that the neuronal representation in mice is spatial (in monkeys it is good-based). Our results lay the foundations for a circuit-level analysis of economic decisions.

Targeted Stimulation of Human Orbitofrontal Networks Disrupts Outcome-Guided Behavior

Outcome-guided behavior requires knowledge about the current value of expected outcomes. Such behavior can be isolated in the reinforcer devaluation task, which assesses the ability to infer the current value of specific rewards after devaluation. Animal lesion studies demonstrate that orbitofrontal cortex (OFC) is necessary for normal behavior in this task, but a causal role for human OFC in outcome-guided behavior has not been established. Here, we used sham-controlled, non-invasive, continuous theta-burst stimulation (cTBS) to temporarily disrupt human OFC network activity by stimulating a site in the lateral prefrontal cortex that is strongly connected to OFC prior to devaluation of food odor rewards. Subjects in the sham group appropriately avoided Pavlovian cues associated with devalued food odors. However, subjects in the stimulation group persistently chose those cues, even though devaluation of food odors themselves was unaffected by cTBS. This behavioral impairment was mirrored in changes in resting-state functional magnetic resonance imaging (rs-fMRI) activity such that subjects in the stimulation group exhibited reduced OFC network connectivity after cTBS, and the magnitude of this reduction was correlated with choices after devaluation. These findings demonstrate the feasibility of indirectly targeting the human OFC with non-invasive cTBS and indicate that OFC is specifically required for inferring the value of expected outcomes.

Interactions between human orbitofrontal cortex and hippocampus support model-based inference

Internal representations of relationships between events in the external world can be utilized to infer outcomes when direct experience is lacking. This process is thought to involve the orbitofrontal cortex (OFC) and hippocampus (HPC), but there is little evidence regarding the relative role of these areas and their interactions in inference. Here, we used a sensory preconditioning task and pattern-based neuroimaging to study this question. We found that associations among value-neutral cues were acquired in both regions during preconditioning but that value-related information was only represented in the OFC at the time of the probe test. Importantly, inference was accompanied by representations of associated cues and inferred outcomes in the OFC, as well as by increased HPC-OFC connectivity. These findings suggest that the OFC and HPC represent only partially overlapping information and that interactions between the two regions support model-based inference.

Real-Time Value Integration during Economic Choice Is Regulated by Orbitofrontal Cortex

Neural correlates implicate the orbitofrontal cortex (OFC) in value-based or economic decision making [1-3]. Yet inactivation of OFC in rats performing a rodent version of the standard economic choice task is without effect [4, 5], a finding more in accord with ideas that the OFC is primarily necessary for behavior when new information must be taken into account [6-9]. Neural activity in the OFC spontaneously updates to reflect new information, particularly about outcomes [10-16], and the OFC is necessary for adjustments to learned behavior only under these conditions [4, 16-26]. Here, we merge these two independent lines of research by inactivating lateral OFC during an economic choice that requires new information about the value of the predicted outcomes to be incorporated into an already established choice. Outcome value was changed by pre-feeding the rats one of two food options before testing. In control rats, this pre-feeding resulted in divergent changes in choice behavior that depended on the rats' prior preference for the pre-fed food. Optogenetic inactivation of the OFC disrupted this bi-directional effect of pre-feeding without affecting other measures that describe the underlying choice behavior. This finding unifies the role of the OFC in economic choice with its role in a host of other behaviors, causally demonstrating that the OFC is not necessary for economic choice per se-unless that choice incorporates new information about the outcomes.

Neuroscience: Reevaluating the Role of Orbitofrontal Cortex

A new optogenetic lesion study shows that the orbitofrontal cortex is essential for integrating information about recent rewards - which may either increase or decrease demand for more - with learned preferences to drive behavior.

Reward-driven changes in striatal pathway competition shape evidence evaluation in decision-making

Cortico-basal-ganglia-thalamic (CBGT) networks are critical for adaptive decision-making, yet how changes to circuit-level properties impact cognitive algorithms remains unclear. Here we explore how dopaminergic plasticity at corticostriatal synapses alters competition between striatal pathways, impacting the evidence accumulation process during decision-making. Spike-timing dependent plasticity simulations showed that dopaminergic feedback based on rewards modified the ratio of direct and indirect corticostriatal weights within opposing action channels. Using the learned weight ratios in a full spiking CBGT network model, we simulated neural dynamics and decision outcomes in a reward-driven decision task and fit them with a drift diffusion model. Fits revealed that the rate of evidence accumulation varied with inter-channel differences in direct pathway activity while boundary height varied with overall indirect pathway activity. This multi-level modeling approach demonstrates how complementary learning and decision computations can emerge from corticostriatal plasticity.

Cognitive process models such as reinforcement learning (RL) and the drift diffusion model (DDM) have helped to elucidate the basic algorithms underlying error-corrective learning and the evaluation of accumulating decision evidence leading up to a choice. While these relatively abstract models help to guide experimental and theoretical probes into associated phenomena, they remain uninformative about the actual physical mechanics by which learning and decision algorithms are carried out in a neurobiological substrate during adaptive choice behavior. Here we present an “upwards mapping” approach to bridging neural and cognitive models of value-based decision-making, showing how dopaminergic feedback alters the network-level dynamics of cortico-basal-ganglia-thalamic (CBGT) pathways during learning to bias behavioral choice towards more rewarding actions. By mapping “up” the levels of analysis, this approach yields specific predictions about aspects of neuronal activity that map to the quantities appearing in the cognitive decision-making framework.

Rat Orbitofrontal Ensemble Activity Contains Multiplexed but Dissociable Representations of Value and Task Structure in an Odor Sequence Task

The orbitofrontal cortex (OFC) has long been implicated in signaling information about expected outcomes to facilitate adaptive or flexible behavior. Current proposals focus on signaling of expected value versus the representation of a value-agnostic cognitive map of the task. While often suggested as mutually exclusive, these alternatives may represent extreme ends of a continuum determined by task complexity and experience. As learning proceeds, an initial, detailed cognitive map might be acquired, based largely on external information. With more experience, this hypothesized map can then be tailored to include relevant abstract hidden cognitive constructs. The map would default to an expected value in situations where other attributes are largely irrelevant, but, in richer tasks, a more detailed structure might continue to be represented, at least where relevant to behavior. Here, we examined this by recording single-unit activity from the OFC in rats navigating an odor sequence task analogous to a spatial maze. The odor sequences provided a mappable state space, with 24 unique "positions" defined by sensory information, likelihood of reward, or both. Consistent with the hypothesis that the OFC represents a cognitive map tailored to the subjects' intentions or plans, we found a close correspondence between how subjects were using the sequences and the neural representations of the sequences in OFC ensembles. Multiplexed with this value-invariant representation of the task, we also found a representation of the expected value at each location. Thus, the value and task structure co-existed as dissociable components of the neural code in OFC.

Patients with basal ganglia damage show preserved learning in an economic game

Both basal ganglia (BG) and orbitofrontal cortex (OFC) have been widely implicated in social and non-social decision-making. However, unlike OFC damage, BG pathology is not typically associated with disturbances in social functioning. Here we studied the behavior of patients with focal lesions to either BG or OFC in a multi-strategy competitive game known to engage these regions. We find that whereas OFC patients are significantly impaired, BG patients show intact learning in the economic game. By contrast, when information about the strategic context is absent, both cohorts are significantly impaired. Computational modeling further shows a preserved ability in BG patients to learn by anticipating and responding to the behavior of others using the strategic context. These results suggest that apparently divergent findings on BG contribution to social decision-making may instead reflect a model where higher-order learning processes are dissociable from trial-and-error learning, and can be preserved despite BG damage.

Neuroimaging evidence implicates basal ganglia (BG) in social decision-making, yet causal evidence remains lacking. Here, the authors show that learning in strategic (but not non-strategic) games is spared in patients with BG damage, suggesting social decision making is not fully reliant on the BG.

An Integrated Model of Action Selection: Distinct Modes of Cortical Control of Striatal Decision Making

Making decisions in environments with few choice options is easy. We select the action that results in the most valued outcome. Making decisions in more complex environments, where the same action can produce different outcomes in different conditions, is much harder. In such circumstances, we propose that accurate action selection relies on top-down control from the prelimbic and orbitofrontal cortices over striatal activity through distinct thalamostriatal circuits. We suggest that the prelimbic cortex exerts direct influence over medium spiny neurons in the dorsomedial striatum to represent the state space relevant to the current environment. Conversely, the orbitofrontal cortex is argued to track a subject's position within that state space, likely through modulation of cholinergic interneurons.

Activity of Prefrontal Neurons Predict Future Choices during Gambling

Neuronal signals in the prefrontal cortex have been reported to predict upcoming decisions. Such activity patterns are often coupled to perceptual cues indicating correct choices or values of different options. How does the prefrontal cortex signal future decisions when no cues are present but when decisions are made based on internal valuations of past experiences with stochastic outcomes? We trained rats to perform a two-arm bandit-task, successfully adjusting choices between certain-small or possible-big rewards with changing long-term advantages. We discovered specialized prefrontal neurons, whose firing during the encounter of no-reward predicted the subsequent choice of animals, even for unlikely or uncertain decisions and several seconds before choice execution. Optogenetic silencing of the prelimbic cortex exclusively timed to encounters of no reward, provoked animals to excessive gambling for large rewards. Firing of prefrontal neurons during outcome evaluation signals subsequent choices during gambling and is essential for dynamically adjusting decisions based on internal valuations.