scholarly journals Orthogonal Representations of Reward Magnitude, Certainty, and Volatility in the Macaque Orbitofrontal Cortex

2018 ◽  
Author(s):  
Tianming Yang ◽  
Elisabeth A. Murray
Keyword(s):  
Reward Magnitude ◽  
Orbitofrontal Cortex ◽  
Stimulus Presentation ◽  
Two Dimensions ◽  
Foraging Strategies ◽  
General Role ◽  
Decision Variables ◽  
Categorical Knowledge ◽  
Reward Information ◽  
The Brain

AbstractCategorical knowledge about the probabilistic and volatile nature of resource availability can improve foraging strategies, yet we have little understanding of how the brain represents such knowledge. Neurons in the orbitofrontal cortex (OFC) of macaques encode several decision variables (e.g., reward magnitude, probability) that could influence choice behavior. Here we investigated whether OFC neurons also represent two aspects of reward predictability: certainty and volatility. Rhesus monkeys performed a visual stimulus-reward association task in which a set of simple shapes preceded the delivery of reward, and they learned the nature of each shape’s reward association along two dimensions. One involved the certainty of a reward outcome; rewards can be either deterministic (and therefore certain) or probabilistic (uncertain). A second dimension reflected the volatility of an outcome; reward schedules can be either stable over time or volatile. During stimulus presentation, the activity of OFC neurons reflected both categorical certainty and categorical volatility, in addition to reward magnitude. These three characteristics were represented orthogonally by three distinct neural populations of similar size. These findings point to a more general role for OFC in processing reward information than one restricted to encoding parametric valuations such as reward magnitude and probability.

scholarly journals Value Representations in the Rodent Orbitofrontal Cortex Drive Learning, not Choice

2018 ◽  
Author(s):  
Kevin J. Miller ◽  
Matthew M. Botvinick ◽  
Carlos D. Brody
Keyword(s):  
Orbitofrontal Cortex ◽  
Future Expectations ◽  
Neural Representations ◽  
Electrophysiological Recordings ◽  
Expected Values ◽  
Open Question ◽  
Reward Information ◽  
To Receive ◽  
The Brain

AbstractHumans 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.

Sensory evidence integration and action initiation occur in parallel during perceptual decisions

2020 ◽  
Author(s):  
Lluís Hernández-Navarro ◽  
Ainhoa Hermoso-Mendizabal ◽  
Daniel Duque ◽  
Alexandre Hyafil ◽  
Jaime de la Rocha
Keyword(s):  
Time Pressure ◽  
Reaction Times ◽  
Stimulus Presentation ◽  
Perceptual Decision Making ◽  
Evidence Accumulation ◽  
Action Preparation ◽  
Action Model ◽  
The Brain ◽  
Evidence Integration ◽  
Action Initiation

It is commonly assumed that, during perceptual decisions, the brain integrates stimulus evidence until reaching a decision, and then performs the response. There are conditions, however (e.g. time pressure), in which the initiation of the response must be prepared in anticipation of the stimulus presentation. It is therefore not clear when the timing and the choice of perceptual responses depend exclusively on evidence accumulation, or when preparatory motor signals may interfere with this process. Here, we find that, in a free reaction time auditory discrimination task in rats, the timing of fast responses does not depend on the stimulus, although the choices do, suggesting a decoupling of the mechanisms of action initiation and choice selection. This behavior is captured by a novel model, the Parallel Sensory Integration and Action Model (PSIAM), in which response execution is triggered whenever one of two processes, Action Initiation or Evidence Accumulation, reaches a bound, while choice category is always set by the latter. Based on this separation, the model accurately predicts the distribution of reaction times when the stimulus is omitted, advanced or delayed. Furthermore, we show that changes in Action Initiation mediates both post-error slowing and a gradual slowing of the responses within each session. Overall, these results extend the standard models of perceptual decision-making, and shed a new light on the interaction between action preparation and evidence accumulation.

scholarly journals Cultural variation in the gray matter volume of the prefrontal cortex is moderated by the dopamine D4 receptor gene (DRD4)

2018 ◽  
Vol 29 (9) ◽  
pp. 3922-3931 ◽  
Author(s):  
Qinggang Yu ◽  
Nobuhito Abe ◽  
Anthony King ◽  
Carolyn Yoon ◽  
Israel Liberzon ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Orbitofrontal Cortex ◽  
Receptor Gene ◽  
Cultural Influences ◽  
Dopamine D4 Receptor ◽  
East Asians ◽  
European Americans ◽  
The Difference ◽  
D4 Receptor ◽  
The Brain

Abstract Recent evidence suggests a systematic cultural difference in the volume/thickness of prefrontal regions of the brain. However, origins of this difference remain unclear. Here, we addressed this gap by adopting a unique genetic approach. People who carry the 7- or 2-repeat (7/2-R) allele of the dopamine D4 receptor gene (DRD4) are more sensitive to environmental influences, including cultural influences. Therefore, if the difference in brain structure is due to cultural influences, it should be moderated by DRD4. We recruited 132 young adults (both European Americans and Asian-born East Asians). Voxel-based morphometry showed that gray matter (GM) volume of the medial prefrontal cortex and the orbitofrontal cortex was significantly greater among European Americans than among East Asians. Moreover, the difference in GM volume was significantly more pronounced among carriers of the 7/2-R allele of DRD4 than among non-carriers. This pattern was robust in an alternative measure assessing cortical thickness. A further exploratory analysis showed that among East Asian carriers, the number of years spent in the U.S. predicted increased GM volume in the orbitofrontal cortex. The present evidence is consistent with a view that culture shapes the brain by mobilizing epigenetic pathways that are gradually established through socialization and enculturation.

scholarly journals Primate prefrontal neurons signal economic risk derived from the statistics of recent reward experience

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Fabian Grabenhorst ◽  
Ken-Ichiro Tsutsui ◽  
Shunsuke Kobayashi ◽  
Wolfram Schultz
Keyword(s):  
Dorsolateral Prefrontal Cortex ◽  
Choice Task ◽  
Support Vector ◽  
Probabilistic Choice ◽  
Economic Decisions ◽  
Decision Variables ◽  
Dorsolateral Prefrontal ◽  
Process Risk ◽  
The Brain ◽  
Statistical Variance

Risk derives from the variation of rewards and governs economic decisions, yet how the brain calculates risk from the frequency of experienced events, rather than from explicit risk-descriptive cues, remains unclear. Here, we investigated whether neurons in dorsolateral prefrontal cortex process risk derived from reward experience. Monkeys performed in a probabilistic choice task in which the statistical variance of experienced rewards evolved continually. During these choices, prefrontal neurons signaled the reward-variance associated with specific objects (‘object risk’) or actions (‘action risk’). Crucially, risk was not derived from explicit, risk-descriptive cues but calculated internally from the variance of recently experienced rewards. Support-vector-machine decoding demonstrated accurate neuronal risk discrimination. Within trials, neuronal signals transitioned from experienced reward to risk (risk updating) and from risk to upcoming choice (choice computation). Thus, prefrontal neurons encode the statistical variance of recently experienced rewards, complying with formal decision variables of object risk and action risk.

scholarly journals Salience-driven value construction for adaptive choice under risk

2018 ◽  
Author(s):  
Mehran Spitmaan ◽  
Emily Chu ◽  
Alireza Soltani
Keyword(s):  
Reward Magnitude ◽  
Human Subjects ◽  
Real Life ◽  
Individual Outcomes ◽  
Single Piece ◽  
Differential Weighting ◽  
Adaptive Choice ◽  
Plausible Mechanism ◽  
Reward Information ◽  
Adaptive Decision Making

Decisions we face in real life are inherently risky and can result in one of many possible outcomes. However, most of what we know about choice under risk is based on studies that use options with only two possible outcomes (simple gambles), so it remains unclear how the brain constructs reward values for more complex risky options faced in real life. To address this question, we combined experimental and modeling approaches to examine choice between pairs of simple gambles and pairs of three-outcome gambles in male and female human subjects. We found that subjects evaluated individual outcomes of three-outcome gambles by multiplying functions of reward magnitude and probability. To construct the overall value of each gamble, however, most subjects differentially weighted possible outcomes based on either reward magnitude or probability. These results reveal a novel dissociation between how reward information is processed when evaluating complex gambles: valuation of each outcome is based on an integrated value whereas combination of possible outcomes relies on a single piece of reward information. We show that differential weighting of possible outcomes enabled subjects to make decisions more easily and quickly. Together, these findings reveal a plausible mechanism for how salience, in terms of possible reward magnitude or probability, can influence the construction of subjective values for complex gambles. They also point to separable neural mechanisms for how reward value controls choice and attention in order to allow for more adaptive decision making.

scholarly journals I know that I don’t know: Structural and functional connectivity underlying meta-ignorance in pre-schoolers

2018 ◽  
Author(s):  
Elisa Filevich ◽  
Caroline Garcia Forlim ◽  
Carmen Fehrman ◽  
Carina Forster ◽  
Markus Paulus ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Orbitofrontal Cortex ◽  
Cingulate Gyrus ◽  
Partial Knowledge ◽  
Metacognitive Monitoring ◽  
Default Mode ◽  
Posterior Cingulate Gyrus ◽  
Knowledge Condition ◽  
The Brain

Research Highlights[1] Children develop the ability to report that they do not know something at around five years of age.[2] Children who could correctly report their own ignorance in a partial-knowledge task showed thicker cortices within medial orbitofrontal cortex.[3] This region was functionally connected to parts of the default-mode network.[4] The default-mode network might support the development of correct metacognitive monitoring.AbstractMetacognition plays a pivotal role in human development. The ability to realize that we do not know something, or meta-ignorance, emerges after approximately five years of age. We aimed at identifying the brain systems that underlie the developmental emergence of this ability in a preschool sample.Twenty-four children aged between five and six years answered questions under three conditions of a meta-ignorance task twice. In the critical partial knowledge condition, an experimenter first showed two toys to a child, then announced that she would place one of them in a box behind a screen, out of sight from the child. The experimenter then asked the child whether or not she knew which toy was in the box.Children who answered correctly both times to the metacognitive question in the partial knowledge condition (n=9) showed greater cortical thickness in a cluster within left medial orbitofrontal cortex than children who did not (n=15). Further, seed-based functional connectivity analyses of the brain during resting state revealed that this region is functionally connected to the medial orbitofrontal gyrus, posterior cingulate gyrus and precuneus, and mid- and inferior temporal gyri.This finding suggests that the default mode network, critically through its prefrontal regions, supports introspective processing. It leads to the emergence of metacognitive monitoring allowing children to explicitly report their own ignorance.

scholarly journals Values Encoded in Orbitofrontal Cortex Are Causally Related to Economic Choices

2020 ◽  
Author(s):  
Sébastien Ballesta ◽  
Weikang Shi ◽  
Katherine E. Conen ◽  
Camillo Padoa-Schioppa
Keyword(s):  
Electrical Stimulation ◽  
Neuronal Activity ◽  
Orbitofrontal Cortex ◽  
Rhesus Monkeys ◽  
Fundamental Issue ◽  
High Current ◽  
Neural Processes ◽  
Economic Choices ◽  
The Brain

AbstractIt has long been hypothesized that economic choices rely on the assignment and comparison of subjective values. Indeed, when agents make decisions, neurons in orbitofrontal cortex encode the values of offered and chosen goods. Moreover, neuronal activity in this area suggests the formation of a decision. However, it is unclear whether these neural processes are causally related to choices. More generally, the evidence linking economic choices to value signals in the brain remains correlational. We address this fundamental issue using electrical stimulation in rhesus monkeys. We show that suitable currents bias choices by increasing the value of individual offers. Furthermore, high-current stimulation disrupts both the computation and the comparison of subjective values. These results demonstrate that values encoded in orbitofrontal cortex are causal to economic choices.

scholarly journals Selective enhancement of object representations through multisensory integration

2019 ◽  
Author(s):  
David A. Tovar ◽  
Micah M. Murray ◽  
Mark T. Wallace
Keyword(s):  
Multisensory Integration ◽  
Sensory Information ◽  
Stimulus Presentation ◽  
Building Blocks ◽  
Object Representations ◽  
The Individual ◽  
And Behavior ◽  
Living Objects ◽  
Selective Enhancement ◽  
The Brain

AbstractObjects are the fundamental building blocks of how we create a representation of the external world. One major distinction amongst objects is between those that are animate versus inanimate. Many objects are specified by more than a single sense, yet the nature by which multisensory objects are represented by the brain remains poorly understood. Using representational similarity analysis of human EEG signals, we show enhanced encoding of audiovisual objects when compared to their corresponding visual and auditory objects. Surprisingly, we discovered the often-found processing advantages for animate objects was not evident in a multisensory context due to greater neural enhancement of inanimate objects—the more weakly encoded objects under unisensory conditions. Further analysis showed that the selective enhancement of inanimate audiovisual objects corresponded with an increase in shared representations across brain areas, suggesting that neural enhancement was mediated by multisensory integration. Moreover, a distance-to-bound analysis provided critical links between neural findings and behavior. Improvements in neural decoding at the individual exemplar level for audiovisual inanimate objects predicted reaction time differences between multisensory and unisensory presentations during a go/no-go animate categorization task. Interestingly, links between neural activity and behavioral measures were most prominent 100 to 200ms and 350 to 500ms after stimulus presentation, corresponding to time periods associated with sensory evidence accumulation and decision-making, respectively. Collectively, these findings provide key insights into a fundamental process the brain uses to maximize information it captures across sensory systems to perform object recognition.Significance StatementOur world is filled with an ever-changing milieu of sensory information that we are able to seamlessly transform into meaningful perceptual experience. We accomplish this feat by combining different features from our senses to construct objects. However, despite the fact that our senses do not work in isolation but rather in concert with each other, little is known about how the brain combines the senses together to form object representations. Here, we used EEG and machine learning to study how the brain processes auditory, visual, and audiovisual objects. Surprisingly, we found that non-living objects, the objects which were more difficult to process with one sense alone, benefited the most from engaging multiple senses.

scholarly journals Robust and distributed neural representation of action values

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Eun Ju Shin ◽  
Yunsil Jang ◽  
Soyoun Kim ◽  
Hoseok Kim ◽  
Xinying Cai ◽  
...  
Keyword(s):  
Neural Activity ◽  
Statistical Tests ◽  
Brain Structures ◽  
Surrogate Data ◽  
Neural Representation ◽  
Decision Variables ◽  
Multiple Regions ◽  
Serial Correlations ◽  
Action Value ◽  
The Brain

Studies in rats, monkeys, and humans have found action-value signals in multiple regions of the brain. These findings suggest that action-value signals encoded in these brain structures bias choices toward higher expected rewards. However, previous estimates of action-value signals might have been inflated by serial correlations in neural activity and also by activity related to other decision variables. Here, we applied several statistical tests based on permutation and surrogate data to analyze neural activity recorded from the striatum, frontal cortex, and hippocampus. The results show that previously identified action-value signals in these brain areas cannot be entirely accounted for by concurrent serial correlations in neural activity and action value. We also found that neural activity related to action value is intermixed with signals related to other decision variables. Our findings provide strong evidence for broadly distributed neural signals related to action value throughout the brain.

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