RESUMEN
Every decision we make is accompanied by a sense of confidence about its likely outcome. This sense informs subsequent behavior, such as investing more-whether time, effort, or money-when reward is more certain. A neural representation of confidence should originate from a statistical computation and predict confidence-guided behavior. An additional requirement for confidence representations to support metacognition is abstraction: they should emerge irrespective of the source of information and inform multiple confidence-guided behaviors. It is unknown whether neural confidence signals meet these criteria. Here, we show that single orbitofrontal cortex neurons in rats encode statistical decision confidence irrespective of the sensory modality, olfactory or auditory, used to make a choice. The activity of these neurons also predicts two confidence-guided behaviors: trial-by-trial time investment and cross-trial choice strategy updating. Orbitofrontal cortex thus represents decision confidence consistent with a metacognitive process that is useful for mediating confidence-guided economic decisions.
Asunto(s)
Conducta/fisiología , Corteza Prefrontal/fisiología , Animales , Conducta de Elección/fisiología , Toma de Decisiones , Modelos Biológicos , Neuronas/fisiología , Ratas Long-Evans , Sensación/fisiología , Análisis y Desempeño de Tareas , Factores de TiempoRESUMEN
By observing their social partners, primates learn about reward values of objects. Here, we show that monkeys' amygdala neurons derive object values from observation and use these values to simulate a partner monkey's decision process. While monkeys alternated making reward-based choices, amygdala neurons encoded object-specific values learned from observation. Dynamic activities converted these values to representations of the recorded monkey's own choices. Surprisingly, the same activity patterns unfolded spontaneously before partner's choices in separate neurons, as if these neurons simulated the partner's decision-making. These "simulation neurons" encoded signatures of mutual-inhibitory decision computation, including value comparisons and value-to-choice conversions, resulting in accurate predictions of partner's choices. Population decoding identified differential contributions of amygdala subnuclei. Biophysical modeling of amygdala circuits showed that simulation neurons emerge naturally from convergence between object-value neurons and self-other neurons. By simulating decision computations during observation, these neurons could allow primates to reconstruct their social partners' mental states.
Asunto(s)
Amígdala del Cerebelo/metabolismo , Amígdala del Cerebelo/fisiología , Toma de Decisiones/fisiología , Animales , Conducta Animal/fisiología , Conducta de Elección/fisiología , Relaciones Interpersonales , Aprendizaje/fisiología , Macaca mulatta/fisiología , Masculino , Neuronas/metabolismo , Neuronas/fisiología , RecompensaRESUMEN
In the natural world, animals make decisions on an ongoing basis, continuously selecting which action to undertake next. In the lab, however, the neural bases of decision processes have mostly been studied using artificial trial structures. New experimental tools based on the genetic toolkit of model organisms now make it experimentally feasible to monitor and manipulate neural activity in small subsets of neurons during naturalistic behaviors. We thus propose a new approach to investigating decision processes, termed reverse neuroethology. In this approach, experimenters select animal models based on experimental accessibility and then utilize cutting-edge tools such as connectomes and genetically encoded reagents to analyze the flow of information through an animal's nervous system during naturalistic choice behaviors. We describe how the reverse neuroethology strategy has been applied to understand the neural underpinnings of innate, rapid decision making, with a focus on defensive behavioral choices in the vinegar fly Drosophila melanogaster.
Asunto(s)
Conducta de Elección , Drosophila melanogaster , Animales , Conducta de Elección/fisiología , Drosophila melanogaster/fisiología , Conducta Animal/fisiología , Neuronas/fisiología , Toma de Decisiones/fisiología , Encéfalo/fisiologíaRESUMEN
Even a simple sensory stimulus can elicit distinct innate behaviors and sequences. During sensorimotor decisions, competitive interactions among neurons that promote distinct behaviors must ensure the selection and maintenance of one behavior, while suppressing others. The circuit implementation of these competitive interactions is still an open question. By combining comprehensive electron microscopy reconstruction of inhibitory interneuron networks, modeling, electrophysiology, and behavioral studies, we determined the circuit mechanisms that contribute to the Drosophila larval sensorimotor decision to startle, explore, or perform a sequence of the two in response to a mechanosensory stimulus. Together, these studies reveal that, early in sensory processing, (1) reciprocally connected feedforward inhibitory interneurons implement behavioral choice, (2) local feedback disinhibition provides positive feedback that consolidates and maintains the chosen behavior, and (3) lateral disinhibition promotes sequence transitions. The combination of these interconnected circuit motifs can implement both behavior selection and the serial organization of behaviors into a sequence.
Asunto(s)
Conducta de Elección/fisiología , Drosophila melanogaster/fisiología , Retroalimentación Sensorial/fisiología , Mecanotransducción Celular/fisiología , Células de Renshaw/fisiología , Animales , Larva/fisiología , OptogenéticaRESUMEN
Optogenetic studies in mice have revealed new relationships between well-defined neurons and brain functions. However, there are currently no means to achieve the same cell-type specificity in monkeys, which possess an expanded behavioral repertoire and closer anatomical homology to humans. Here, we present a resource for cell-type-specific channelrhodopsin expression in Rhesus monkeys and apply this technique to modulate dopamine activity and monkey choice behavior. These data show that two viral vectors label dopamine neurons with greater than 95% specificity. Infected neurons were activated by light pulses, indicating functional expression. The addition of optical stimulation to reward outcomes promoted the learning of reward-predicting stimuli at the neuronal and behavioral level. Together, these results demonstrate the feasibility of effective and selective stimulation of dopamine neurons in non-human primates and a resource that could be applied to other cell types in the monkey brain.
Asunto(s)
Conducta de Elección/fisiología , Neuronas Dopaminérgicas/metabolismo , Optogenética/métodos , Animales , Dependovirus/genética , Dopamina/metabolismo , Regulación de la Expresión Génica , Vectores Genéticos/genética , Macaca mulatta , Regiones Promotoras Genéticas/genética , Rodopsina/genéticaRESUMEN
Working memory, the process through which information is transiently maintained and manipulated over a brief period, is essential for most cognitive functions1-4. However, the mechanisms underlying the generation and evolution of working-memory neuronal representations at the population level over long timescales remain unclear. Here, to identify these mechanisms, we trained head-fixed mice to perform an olfactory delayed-association task in which the mice made decisions depending on the sequential identity of two odours separated by a 5 s delay. Optogenetic inhibition of secondary motor neurons during the late-delay and choice epochs strongly impaired the task performance of the mice. Mesoscopic calcium imaging of large neuronal populations of the secondary motor cortex (M2), retrosplenial cortex (RSA) and primary motor cortex (M1) showed that many late-delay-epoch-selective neurons emerged in M2 as the mice learned the task. Working-memory late-delay decoding accuracy substantially improved in the M2, but not in the M1 or RSA, as the mice became experts. During the early expert phase, working-memory representations during the late-delay epoch drifted across days, while the stimulus and choice representations stabilized. In contrast to single-plane layer 2/3 (L2/3) imaging, simultaneous volumetric calcium imaging of up to 73,307 M2 neurons, which included superficial L5 neurons, also revealed stabilization of late-delay working-memory representations with continued practice. Thus, delay- and choice-related activities that are essential for working-memory performance drift during learning and stabilize only after several days of expert performance.
Asunto(s)
Consolidación de la Memoria , Memoria a Corto Plazo , Práctica Psicológica , Animales , Femenino , Masculino , Ratones , Calcio/metabolismo , Conducta de Elección/fisiología , Consolidación de la Memoria/fisiología , Memoria a Corto Plazo/fisiología , Ratones Endogámicos C57BL , Corteza Motora/fisiología , Corteza Motora/citología , Neuronas Motoras/fisiología , Odorantes/análisis , Optogenética , Desempeño Psicomotor/fisiología , Olfato/fisiología , Factores de TiempoRESUMEN
Animals perform flexible goal-directed behaviours to satisfy their basic physiological needs1-12. However, little is known about how unitary behaviours are chosen under conflicting needs. Here we reveal principles by which the brain resolves such conflicts between needs across time. We developed an experimental paradigm in which a hungry and thirsty mouse is given free choices between equidistant food and water. We found that mice collect need-appropriate rewards by structuring their choices into persistent bouts with stochastic transitions. High-density electrophysiological recordings during this behaviour revealed distributed single neuron and neuronal population correlates of a persistent internal goal state guiding future choices of the mouse. We captured these phenomena with a mathematical model describing a global need state that noisily diffuses across a shifting energy landscape. Model simulations successfully predicted behavioural and neural data, including population neural dynamics before choice transitions and in response to optogenetic thirst stimulation. These results provide a general framework for resolving conflicts between needs across time, rooted in the emergent properties of need-dependent state persistence and noise-driven shifts between behavioural goals.
Asunto(s)
Encéfalo , Conducta de Elección , Hambre , Neuronas , Sed , Animales , Ratones , Encéfalo/citología , Encéfalo/fisiología , Conducta de Elección/fisiología , Alimentos , Objetivos , Hambre/fisiología , Neuronas/fisiología , Optogenética , Recompensa , Procesos Estocásticos , Sed/fisiología , Factores de Tiempo , Agua , Modelos NeurológicosRESUMEN
People with damage to the orbitofrontal cortex (OFC) have specific problems making decisions, whereas their other cognitive functions are spared. Neurophysiological studies have shown that OFC neurons fire in proportion to the value of anticipated outcomes. Thus, a central role of the OFC is to guide optimal decision-making by signalling values associated with different choices. Until recently, this view of OFC function dominated the field. New data, however, suggest that the OFC may have a much broader role in cognition by representing cognitive maps that can be used to guide behaviour and that value is just one of many variables that are important for behavioural control. In this Review, we critically evaluate these two alternative accounts of OFC function and examine how they might be reconciled.
Asunto(s)
Conducta de Elección , Corteza Prefrontal , Conducta de Elección/fisiología , Toma de Decisiones/fisiología , Humanos , Neuronas/fisiología , Corteza Prefrontal/fisiología , RecompensaRESUMEN
In dynamic environments, subjects often integrate multiple samples of a signal and combine them to reach a categorical judgment1. The process of deliberation can be described by a time-varying decision variable (DV), decoded from neural population activity, that predicts a subject's upcoming decision2. Within single trials, however, there are large moment-to-moment fluctuations in the DV, the behavioural significance of which is unclear. Here, using real-time, neural feedback control of stimulus duration, we show that within-trial DV fluctuations, decoded from motor cortex, are tightly linked to decision state in macaques, predicting behavioural choices substantially better than the condition-averaged DV or the visual stimulus alone. Furthermore, robust changes in DV sign have the statistical regularities expected from behavioural studies of changes of mind3. Probing the decision process on single trials with weak stimulus pulses, we find evidence for time-varying absorbing decision bounds, enabling us to distinguish between specific models of decision making.
Asunto(s)
Toma de Decisiones/fisiología , Modelos Neurológicos , Animales , Conducta de Elección/fisiología , Discriminación en Psicología , Juicio , Macaca/fisiología , Movimiento (Física) , Percepción de Movimiento , Estimulación Luminosa , Factores de TiempoRESUMEN
Neural mechanisms that mediate the ability to make value-guided decisions have received substantial attention in humans and animals1-6. Experiments in animals typically involve long training periods. By contrast, choices in the real world often need to be made between new options spontaneously. It is therefore possible that the neural mechanisms targeted in animal studies differ from those required for new decisions, which are typical of human imaging studies. Here we show that the primate medial frontal cortex (MFC)7 is involved in making new inferential choices when the options have not been previously experienced. Macaques spontaneously inferred the values of new options via similarities with the component parts of previously encountered options. Functional magnetic resonance imaging (fMRI) suggested that this ability was mediated by the MFC, which is rarely investigated in monkeys3; MFC activity reflected different processes of comparison for unfamiliar and familiar options. Multidimensional representations of options in the MFC used a coding scheme resembling that of grid cells, which is well known in spatial navigation8,9, to integrate dimensions in this non-physical space10 during novel decision-making. By contrast, the orbitofrontal cortex held specific object-based value representations1,11. In addition, minimally invasive ultrasonic disruption12 of MFC, but not adjacent tissue, altered the estimation of novel choice values.
Asunto(s)
Conducta de Elección/fisiología , Lóbulo Frontal/citología , Lóbulo Frontal/fisiología , Macaca mulatta/fisiología , Neuronas/fisiología , Adulto , Animales , Femenino , Células de Red/fisiología , Humanos , Imagen por Resonancia Magnética , Masculino , Corteza Prefrontal/citología , Corteza Prefrontal/fisiología , Navegación Espacial/fisiología , Adulto JovenRESUMEN
AI is now an integral part of everyday decision-making, assisting us in both routine and high-stakes choices. These AI models often learn from human behavior, assuming this training data is unbiased. However, we report five studies that show that people change their behavior to instill desired routines into AI, indicating this assumption is invalid. To show this behavioral shift, we recruited participants to play the ultimatum game, where they were asked to decide whether to accept proposals of monetary splits made by either other human participants or AI. Some participants were informed their choices would be used to train an AI proposer, while others did not receive this information. Across five experiments, we found that people modified their behavior to train AI to make fair proposals, regardless of whether they could directly benefit from the AI training. After completing this task once, participants were invited to complete this task again but were told their responses would not be used for AI training. People who had previously trained AI persisted with this behavioral shift, indicating that the new behavioral routine had become habitual. This work demonstrates that using human behavior as training data has more consequences than previously thought since it can engender AI to perpetuate human biases and cause people to form habits that deviate from how they would normally act. Therefore, this work underscores a problem for AI algorithms that aim to learn unbiased representations of human preferences.
Asunto(s)
Inteligencia Artificial , Toma de Decisiones , Humanos , Toma de Decisiones/fisiología , Masculino , Femenino , Adulto , Conducta de Elección/fisiología , Adulto JovenRESUMEN
Humans can make abstract choices independent of motor actions. However, in laboratory tasks, choices are typically reported with an associated action. Consequentially, knowledge about the neural representation of abstract choices is sparse, and choices are often thought to evolve as motor intentions. Here, we show that in the human brain, perceptual choices are represented in an abstract, motor-independent manner, even when they are directly linked to an action. We measured MEG signals while participants made choices with known or unknown motor response mapping. Using multivariate decoding, we quantified stimulus, perceptual choice, and motor response information with distinct cortical distributions. Choice representations were invariant to whether the response mapping was known during stimulus presentation, and they occupied a distinct representational space from motor signals. As expected from an internal decision variable, they were informed by the stimuli, and their strength predicted decision confidence and accuracy. Our results demonstrate abstract neural choice signals that generalize to action-linked decisions, suggesting a general role of an abstract choice stage in human decision-making.
Asunto(s)
Encéfalo , Toma de Decisiones , Humanos , Toma de Decisiones/fisiología , Encéfalo/fisiología , Mapeo Encefálico , Conducta de Elección/fisiologíaRESUMEN
Humans have been shown to strategically explore. They can identify situations in which gathering information about distant and uncertain options is beneficial for the future. Because primates rely on scarce resources when they forage, they are also thought to strategically explore, but whether they use the same strategies as humans and the neural bases of strategic exploration in monkeys are largely unknown. We designed a sequential choice task to investigate whether monkeys mobilize strategic exploration based on whether information can improve subsequent choice, but also to ask the novel question about whether monkeys adjust their exploratory choices based on the contingency between choice and information, by sometimes providing the counterfactual feedback about the unchosen option. We show that monkeys decreased their reliance on expected value when exploration could be beneficial, but this was not mediated by changes in the effect of uncertainty on choices. We found strategic exploratory signals in anterior and mid-cingulate cortex (ACC/MCC) and dorsolateral prefrontal cortex (dlPFC). This network was most active when a low value option was chosen, which suggests a role in counteracting expected value signals, when exploration away from value should to be considered. Such strategic exploration was abolished when the counterfactual feedback was available. Learning from counterfactual outcome was associated with the recruitment of a different circuit centered on the medial orbitofrontal cortex (OFC), where we showed that monkeys represent chosen and unchosen reward prediction errors. Overall, our study shows how ACC/MCC-dlPFC and OFC circuits together could support exploitation of available information to the fullest and drive behavior towards finding more information through exploration when it is beneficial.
Asunto(s)
Conducta de Elección , Corteza Prefrontal , Humanos , Animales , Conducta de Elección/fisiología , Corteza Prefrontal/fisiología , Lóbulo Frontal/fisiología , Recompensa , Macaca mulattaRESUMEN
The taste of sugar is one of the most basic sensory percepts for humans and other animals. Animals can develop a strong preference for sugar even if they lack sweet taste receptors, indicating a mechanism independent of taste1-3. Here we examined the neural basis for sugar preference and demonstrate that a population of neurons in the vagal ganglia and brainstem are activated via the gut-brain axis to create preference for sugar. These neurons are stimulated in response to sugar but not artificial sweeteners, and are activated by direct delivery of sugar to the gut. Using functional imaging we monitored activity of the gut-brain axis, and identified the vagal neurons activated by intestinal delivery of glucose. Next, we engineered mice in which synaptic activity in this gut-to-brain circuit was genetically silenced, and prevented the development of behavioural preference for sugar. Moreover, we show that co-opting this circuit by chemogenetic activation can create preferences to otherwise less-preferred stimuli. Together, these findings reveal a gut-to-brain post-ingestive sugar-sensing pathway critical for the development of sugar preference. In addition, they explain the neural basis for differences in the behavioural effects of sweeteners versus sugar, and uncover an essential circuit underlying the highly appetitive effects of sugar.
Asunto(s)
Encéfalo/fisiología , Conducta de Elección/fisiología , Azúcares de la Dieta/metabolismo , Preferencias Alimentarias/fisiología , Glucosa/metabolismo , Intestinos/fisiología , Animales , Encéfalo/citología , Azúcares de la Dieta/química , Glucosa/análogos & derivados , Glucosa/química , Masculino , Metilglucósidos/química , Metilglucósidos/metabolismo , Ratones , Ratones Endogámicos C57BL , Neuronas/fisiología , Gusto/fisiología , Tiazinas/metabolismo , Agua/metabolismoRESUMEN
An economic choice entails computing and comparing the values of individual offers. Offer values are represented in the orbitofrontal cortex (OFC)-an area that participates in value comparison-but it is unknown where offer values are computed in the first place. One possibility is that this computation takes place in OFC. Alternatively, offer values might be computed upstream of OFC. For choices between edible goods, a primary candidate is the gustatory region of the anterior insula (gustatory cortex, GC). Here we recorded from the GC of male rhesus monkeys choosing between different juice types. As a population, neurons in GC represented the flavor, the quantity, and the subjective value of the juice chosen by the animal. These variables were represented by distinct groups of cells and with different time courses. Specifically, chosen value signals emerged shortly after offer presentation, while neurons encoding the chosen juice and the chosen quantity peaked after juice delivery. Surprisingly, neurons in GC did not represent individual offer values in a systematic way. In a computational sense, the variables encoded in GC follow the process of value comparison. Thus our results argue against the hypothesis that offer values are computed in GC. At the same time, signals representing the subjective value of the expected reward indicate that responses in GC are not purely sensory. Thus neuronal responses in GC appear consummatory in nature.
Asunto(s)
Conducta de Elección , Macaca mulatta , Neuronas , Animales , Masculino , Conducta de Elección/fisiología , Neuronas/fisiología , RecompensaRESUMEN
Interspecies comparisons are key to deriving an understanding of the behavioral and neural correlates of human cognition from animal models. We perform a detailed comparison of the strategies of female macaque monkeys to male and female humans on a variant of the Wisconsin Card Sorting Test (WCST), a widely studied and applied task that provides a multiattribute measure of cognitive function and depends on the frontal lobe. WCST performance requires the inference of a rule change given ambiguous feedback. We found that well-trained monkeys infer new rules three times more slowly than minimally instructed humans. Input-dependent hidden Markov model-generalized linear models were fit to their choices, revealing hidden states akin to feature-based attention in both species. Decision processes resembled a win-stay, lose-shift strategy with interspecies similarities as well as key differences. Monkeys and humans both test multiple rule hypotheses over a series of rule-search trials and perform inference-like computations to exclude candidate choice options. We quantitatively show that perseveration, random exploration, and poor sensitivity to negative feedback account for the slower task-switching performance in monkeys.
Asunto(s)
Macaca mulatta , Animales , Femenino , Masculino , Humanos , Adulto , Aprendizaje/fisiología , Adulto Joven , Especificidad de la Especie , Conducta de Elección/fisiología , Tiempo de Reacción/fisiologíaRESUMEN
It remains a pressing concern to understand how neural computations relate to risky decisions. However, most observations of brain-behavior relationships in the risk-taking domain lack a rigorous computational basis or fail to emulate of the dynamic, sequential nature of real-life risky decision-making. Recent advances emphasize the role of neural prediction error (PE) signals. We modeled, according to prospect theory, the choices of n = 43 human participants (33 females, 10 males) performing an EEG version of the hot Columbia Card Task, featuring rounds of sequential decisions between stopping (safe option) and continuing with increasing odds of a high loss (risky option). Single-trial regression EEG analyses yielded a subjective value signal at centroparietal (300-700â ms) and frontocentral (>800â ms) electrodes and in the delta band, as well as PE signals tied to the feedback-related negativity, P3a, and P3b, and in the theta band. Higher risk preference (total number of risky choices) was linked to attenuated subjective value signals but increased PE signals. Higher P3-like activity associated with the most positive PE in each round predicted stopping in the present round but not risk-taking in the subsequent round. Our findings indicate that decreased representation of decision values and increased sensitivity to winning despite low odds (positive PE) facilitate risky choices at the subject level. Strong neural responses when gains are least expected (the most positive PE on each round) adaptively contribute to safer choices at the trial-by-trial level but do not affect risky choice at the round-by-round level.
Asunto(s)
Toma de Decisiones , Electroencefalografía , Asunción de Riesgos , Humanos , Masculino , Femenino , Adulto , Adulto Joven , Toma de Decisiones/fisiología , Conducta de Elección/fisiología , AdolescenteRESUMEN
Reinforcement learning is a theoretical framework that describes how agents learn to select options that maximize rewards and minimize punishments over time. We often make choices, however, to obtain symbolic reinforcers (e.g., money, points) that are later exchanged for primary reinforcers (e.g., food, drink). Although symbolic reinforcers are ubiquitous in our daily lives, widely used in laboratory tasks because they can be motivating, mechanisms by which they become motivating are less understood. In the present study, we examined how monkeys learn to make choices that maximize fluid rewards through reinforcement with tokens. The question addressed here is how the value of a state, which is a function of multiple task features (e.g., the current number of accumulated tokens, choice options, task epoch, trials since the last delivery of primary reinforcer, etc.), drives value and affects motivation. We constructed a Markov decision process model that computes the value of task states given task features to then correlate with the motivational state of the animal. Fixation times, choice reaction times, and abort frequency were all significantly related to values of task states during the tokens task (n = 5 monkeys, three males and two females). Furthermore, the model makes predictions for how neural responses could change on a moment-by-moment basis relative to changes in the state value. Together, this task and model allow us to capture learning and behavior related to symbolic reinforcement.
Asunto(s)
Conducta de Elección , Macaca mulatta , Motivación , Refuerzo en Psicología , Recompensa , Animales , Motivación/fisiología , Masculino , Conducta de Elección/fisiología , Tiempo de Reacción/fisiología , Cadenas de Markov , FemeninoRESUMEN
From deciding which meal to prepare for our guests to trading off the proenvironmental effects of climate protection measures against their economic costs, we often must consider the consequences of our actions for the well-being of others (welfare). Vexingly, the tastes and views of others can vary widely. To maximize welfare according to the utilitarian philosophical tradition, decision-makers facing conflicting preferences of others should choose the option that maximizes the sum of the subjective value (utility) of the entire group. This notion requires comparing the intensities of preferences across individuals. However, it remains unclear whether such comparisons are possible at all and (if they are possible) how they might be implemented in the brain. Here, we show that female and male participants can both learn the preferences of others by observing their choices and represent these preferences on a common scale to make utilitarian welfare decisions. On the neural level, multivariate support vector regressions revealed that a distributed activity pattern in the ventromedial prefrontal cortex (VMPFC), a brain region previously associated with reward processing, represented the preference strength of others. Strikingly, also the utilitarian welfare of others was represented in the VMPFC and relied on the same neural code as the estimated preferences of others. Together, our findings reveal that humans can behave as if they maximized utilitarian welfare using a specific utility representation and that the brain enables such choices by repurposing neural machinery processing the reward others receive.
Asunto(s)
Recompensa , Humanos , Masculino , Femenino , Adulto , Adulto Joven , Conducta de Elección/fisiología , Corteza Prefrontal/fisiología , Toma de Decisiones/fisiología , Imagen por Resonancia Magnética , Mapeo EncefálicoRESUMEN
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.