Anterior cingulate is a source of valence-specific information about value and uncertainty

AbstractAnterior cingulate cortex (ACC) is thought to control a wide range of reward, punishment, and uncertainty-related behaviors. However, how it does so is unclear. Here, in a Pavlovian procedure in which monkeys displayed a diverse repertoire of reward-related, punishment-related, and uncertainty-related behaviors, we show that many ACC-neurons represent expected value and uncertainty in a valence-specific manner, signaling value or uncertainty predictions about either rewards or punishments. Other ACC-neurons signal prediction information about rewards and punishments by displaying excitation to both (rather than excitation to one and inhibition to the other). This diversity in valence representations may support the role of ACC in many behavioral states that are either enhanced by reward and punishment (e.g., vigilance) or specific to either reward or punishment (e.g., approach and avoidance). Also, this first demonstration of punishment-uncertainty signals in the brain suggests that ACC could be a target for the treatment of uncertainty-related disorders of mood.</jats:p

Neurons in the primate dorsal striatum signal the uncertainty of object–reward associations

To learn, obtain reward and survive, humans and other animals must monitor, approach and act on objects that are associated with variable or unknown rewards. However, the neuronal mechanisms that mediate behaviours aimed at uncertain objects are poorly understood. Here we demonstrate that a set of neurons in an internal-capsule bordering regions of the primate dorsal striatum, within the putamen and caudate nucleus, signal the uncertainty of object–reward associations. Their uncertainty responses depend on the presence of objects associated with reward uncertainty and evolve rapidly as monkeys learn novel object–reward associations. Therefore, beyond its established role in mediating actions aimed at known or certain rewards, the dorsal striatum also participates in behaviours aimed at reward-uncertain objects

Neurons in the primate medial basal forebrain signal combined information about reward uncertainty, value, and punishment anticipation

It has been suggested that the basal forebrain (BF) exerts strong influences on the formation of memory and behavior. However, what information is used for the memory-behavior formation is unclear. We found that a population of neurons in the medial BF (medial septum and diagonal band of Broca) of macaque monkeys encodes a unique combination of information: reward uncertainty, expected reward value, anticipation of punishment, and unexpected reward and punishment. The results were obtained while the monkeys were expecting (often with uncertainty) a rewarding or punishing outcome during a Pavlovian procedure, or unexpectedly received an outcome outside the procedure. In vivo anterograde tracing using manganese-enhanced MRI suggested that the major recipient of these signals is the intermediate hippocampal formation. Based on these findings, we hypothesize that the medial BF identifies various contexts and outcomes that are critical for memory processing in the hippocampal formation

Multiple mechanisms for processing reward uncertainty in the primate basal forebrain

UNLABELLED: The ability to use information about the uncertainty of future outcomes is critical for adaptive behavior in an uncertain world. We show that the basal forebrain (BF) contains at least two distinct neural-coding strategies to support this capacity. The dorsal-lateral BF, including the ventral pallidum (VP), contains reward-sensitive neurons, some of which are selectively suppressed by uncertain-reward predictions (U(-)). In contrast, the medial BF (mBF) contains reward-sensitive neurons, some of which are selectively enhanced (U(+)) by uncertain-reward predictions. In a two-alternative choice-task, U(-) neurons were selectively suppressed while monkeys chose uncertain options over certain options. During the same choice-epoch, U(+) neurons signaled the subjective reward value of the choice options. Additionally, after the choice was reported, U(+) neurons signaled reward uncertainty until the choice outcome. We suggest that uncertainty-related suppression of VP may participate in the mediation of uncertainty-seeking actions, whereas uncertainty-related enhancement of the mBF may direct cognitive resources to monitor and learn from uncertain-outcomes. SIGNIFICANCE STATEMENT: To survive in an uncertain world, we must approach uncertainty and learn from it. Here we provide evidence for two mostly distinct mechanisms for processing uncertainty about rewards within different subregions of the primate basal forebrain (BF). We found that uncertainty suppressed the representation of certain (or safe) reward values by some neurons in the dorsal-lateral BF, in regions occupied by the ventral pallidum. This uncertainty-related suppression was evident as monkeys made risky choices. We also found that uncertainty-enhanced the activity of many medial BF neurons, most prominently after the monkeys\u27 choices were completed (as they awaited uncertain outcomes). Based on these findings, we propose that different subregions of the BF could support action and learning under uncertainty in distinct but complimentary manners

How the value of the environment controls persistence in visual search

Classic foraging theory predicts that humans and animals aim to gain maximum reward per unit time. However, in standard instrumental conditioning tasks individuals adopt an apparently suboptimal strategy: they respond slowly when the expected value is low. This reward-related bias is often explained as reduced motivation in response to low rewards. Here we present evidence this behavior is associated with a complementary increased motivation to search the environment for alternatives. We trained monkeys to search for reward-related visual targets in environments with different values. We found that the reward-related bias scaled with environment value, was consistent with persistent searching after the target was already found, and was associated with increased exploratory gaze to objects in the environment. A novel computational model of foraging suggests that this search strategy could be adaptive in naturalistic settings where both environments and the objects within them provide partial information about hidden, uncertain rewards

The zona incerta in control of novelty seeking and investigation across species

Many organisms rely on a capacity to rapidly replicate, disperse, and evolve when faced with uncertainty and novelty. But mammals do not evolve and replicate quickly. They rely on a sophisticated nervous system to generate predictions and select responses when confronted with these challenges. An important component of their behavioral repertoire is the adaptive context-dependent seeking or avoiding of perceptually novel objects, even when their values have not yet been learned. Here, we outline recent cross-species breakthroughs that shed light on how the zona incerta (ZI), a relatively evolutionarily conserved brain area, supports novelty-seeking and novelty-related investigations. We then conjecture how the architecture of the ZI\u27s anatomical connectivity - the wide-ranging top-down cortical inputs to the ZI, and its specifically strong outputs to both the brainstem action controllers and to brain areas involved in action value learning - place the ZI in a unique role at the intersection of cognitive control and learning

Surprise and recency in novelty detection in the primate brain

Primates and other animals must detect novel objects. However, the neuronal mechanisms of novelty detection remain unclear. Prominent theories propose that visual object novelty is either derived from the computation of recency (how long ago a stimulus was experienced) or is a form of sensory surprise (stimulus unpredictability). Here, we use high-channel electrophysiology in primates to show that in many primate prefrontal, temporal, and subcortical brain areas, object novelty detection is intertwined with the computations of recency and sensory surprise. Also, distinct circuits could be engaged by expected versus unexpected sensory surprise. Finally, we studied neuronal novelty-to-familiarity transformations during learning across many days. We found a diversity of timescales in neurons\u27 learning rates and between-session forgetting rates, both within and across brain areas, that are well suited to support flexible behavior and learning in response to novelty. Our findings show that novelty sensitivity arises on multiple timescales across single neurons due to diverse but related computations of sensory surprise and recency and shed light on the computational underpinnings of novelty detection in the primate brain

Laser stimulation of the skin for quantitative study of decision-making and motivation

Neuroeconomics studies how decision-making is guided by the value of rewards and punishments. But to date, little is known about how noxious experiences impact decisions. A challenge is the lack of an aversive stimulus that is dynamically adjustable in intensity and location, readily usable over many trials in a single experimental session, and compatible with multiple ways to measure neuronal activity. We show that skin laser stimulation used in human studies of aversion can be used for this purpose in several key animal models. We then use laser stimulation to study how neurons in the orbitofrontal cortex (OFC), an area whose many roles include guiding decisions among different rewards, encode the value of rewards and punishments. We show that some OFC neurons integrated the positive value of rewards with the negative value of aversive laser stimulation, suggesting that the OFC can play a role in more complex choices than previously appreciated

A neural mechanism for conserved value computations integrating information and rewards

Behavioral and economic theory dictate that we decide between options based on their values. However, humans and animals eagerly seek information about uncertain future rewards, even when this does not provide any objective value. This implies that decisions are made by endowing information with subjective value and integrating it with the value of extrinsic rewards, but the mechanism is unknown. Here, we show that human and monkey value judgements obey strikingly conserved computational principles during multi-attribute decisions trading off information and extrinsic reward. We then identify a neural substrate in a highly conserved ancient structure, the lateral habenula (LHb). LHb neurons signal subjective value, integrating information\u27s value with extrinsic rewards, and the LHb predicts and causally influences ongoing decisions. Neurons in key input areas to the LHb largely signal components of these computations, not integrated value signals. Thus, our data uncover neural mechanisms of conserved computations underlying decisions to seek information about the future