Executive control and decision-making in the prefrontal cortex

The prefrontal cortex (PFC) subserves decision-making and executive control. Here we review recent empirical and modeling works with a focus on neuroimaging studies, which start unifying these two conceptual approaches of PFC function. We propose that the PFC comprises two arbitration systems: (1) a peripheral system comprising premotor/caudal PFC regions and orbitofrontal regions involved in the selection of actions based on perceptual cues and reward values, respectively, and embedded in behavioral sets associated with external contingencies inferred as being stable; (2) a core system comprising ventromedial, dorsomedial, lateral and polar PFC regions involved in superordinate probabilistic reasoning for arbitrating online between exploiting/adjusting previously learned behavioral sets and exploring/creating new ones for efficient adaptive behavior in variable and open-ended environments

A Neural Representation of Prior Information during Perceptual Inference

SummaryPerceptual inference is biased by foreknowledge about what is probable or possible. How prior expectations are neurally represented during visual perception, however, remains unknown. We used functional magnetic resonance imaging to measure brain activity in humans judging simple visual stimuli. Perceptual decisions were either biased in favor of a single alternative (A/∼A decisions) or taken without bias toward either choice (A/B decisions). Extrastriate and anterior temporal lobe regions were more active during A/∼A than A/B decisions, suggesting multiple representations of prior expectations within the visual hierarchy. Forward connectivity was increased when expected and observed perception diverged (“prediction error” signals), whereas prior expectations fed backward from higher to lower regions. Finally, the coincidence between expected and observed perception activated orbital prefrontal regions, perhaps reflecting the reinforcement of prior expectations. These data support computational and quantitative models proposing that a visual percept emerges from converging bottom-up and top-down signals

Reasoning, Learning, and Creativity: Frontal Lobe Function and Human Decision-Making

Computational modeling and behavioral experimentation suggest that human frontal lobe function is capable of monitoring three or four concurrent behavioral strategies in order to select the most suitable one during decision-making

Economic Value Biases Uncertain Perceptual Choices in the Parietal and Prefrontal Cortices

An observer detecting a noisy sensory signal is biased by the costs and benefits associated with its presence or absence. When these costs and benefits are asymmetric, sensory, and economic information must be integrated to inform the final choice. However, it remains unknown how this information is combined at the neural or computational levels. To address this question, we asked healthy human observers to judge the presence or absence of a noisy sensory signal under economic conditions that favored yes responses (liberal blocks), no responses (conservative blocks), or neither response (neutral blocks). Economic information biased fast choices more than slow choices, suggesting that value and sensory information are integrated early in the decision epoch. More formal simulation analyses using an Ornstein–Uhlenbeck process demonstrated that the influence of economic information was best captured by shifting the origin of evidence accumulation toward the more valuable bound. We then used the computational model to generate trial-by-trial estimates of decision-related evidence that were based on combined sensory and economic information (the decision variable or DV), and regressed these against fMRI activity recorded whilst participants performed the task. Extrastriate visual regions responded to the level of sensory input (momentary evidence), but fMRI signals in the parietal and prefrontal cortices responded to the decision variable. These findings support recent single-neuron data suggesting that economic information biases decision-related signals in higher cortical regions

Impulsivity modulates pilot decision making under uncertainty

Little is known whether intensive training and a highly-procedural environment can alleviate the influence of personality on decision making. Here, we address this issue by investigating the influence of impulsivity as personality factor on decision making among airline pilots. We showed that impulsivity modulated pilots’ indecisiveness in uncertain decision scenarios as well as pilots’ self-reported compliance to airline guidelines in real life. This result suggests that the personality factor impulsivity is a profound trait that continues to have an influence through intensive training and highly-procedural decision situations

The dual-path hypothesis for the emergence of anosognosia in Alzheimer's disease

Although neurocognitive models have been proposed to explain anosognosia in Alzheimer's disease (AD), the neural cascade responsible for its origin in the human brain remains unknown. Here, we build on a mechanistic dual-path hypothesis that brings error-monitoring and emotional processing systems as key elements for self-awareness, with distinct impacts on the emergence of anosognosia in AD. Proceeding from the notion of anosognosia as a dimensional syndrome, ranging from the lack of concern about one's own deficits (i.e., anosodiaphoria) to the complete lack of awareness of deficits, our hypothesis states that (i) unawareness of deficits would result from a failure in the error-monitoring system, whereas (ii) anosodiaphoria would more likely result from an imbalance between emotional processing and error-monitoring systems. In the first case, a synaptic failure in the error-monitoring system, in which the cingulate cortex plays a major role, would have a negative impact on error (or deficits) awareness, preventing patients from becoming aware of their condition. In the second case, an impairment in the emotional processing system, in which the amygdala and orbitofrontal cortex play a major role, would prevent patients from monitoring the internal milieu for relevant errors (or deficits) and assigning appropriate value to them, thus biasing their impact on the error-monitoring system. Our hypothesis stems from two scientific premises. One comes from preliminary results in AD patients showing a synaptic failure in the error-monitoring system and decline of awareness at the time of diagnosis. Another comes from the somatic marker hypothesis, which proposes that emotional signals are critical to adaptive behavior. Further exploration will be of great interest to illuminate the foundations of self-awareness and improve our understanding of the underlying mechanisms of anosognosia in AD

Spatial Learning and Action Planning in a Prefrontal Cortical Network Model

The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive “insight” capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates

Bases neurales de la cognition séquentielle chez l'homme (étude IRMf et MEG)

La facultŽ dÕexŽcuter des sŽquences dÕactions est essentielle lÕhomme, mais lÕimplŽmentation neurale de leur reprŽsentation reste mal comprise. Nous avons crŽŽ un protocole expŽrimental permettant de sŽparer les reprŽsentations ordinales (position relatives des pas de la sŽquence) et hiŽrarchiques (relations entre les segments autonomes des sŽquences) impliquŽes lors de lÕexŽcution des sŽquences. En utilisant lÕIRMf, nous avons mis en ŽvidenceÊ: 1. Un rŽseau frontal bilatŽral hiŽrachique, impliquŽ dans la sŽlection des actes moteurs simples (BA 6), des chunks dO action (ensemble dÕactes moteurs ordonnŽs ou associŽs des stimuli, BA 44) et des chunks superordinŽs (ensemble de chunks ordonnŽs ou associŽs des stimuli, BA 45). 2. Un rŽseau pariŽtal maintenant la composante ordinale des sŽquences (IPS gauche) et le chunk dÕaction moteur courant (IPS droit) associŽ chaque pas. Le protocole expŽrimental a ŽtŽ adaptŽ la MEG afin de dŽterminer la dynamique temporelle de ce rŽseau.PARIS-BIUSJ-Thèses (751052125) / SudocPARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF

Apprentissage et contrôle cognitif (une théorie computationnelle de la fonction exécutive préfontale humaine)

Le contrôle cognitif (CC) est la capacité à réagir à des stimuli en fonction du contexte présent, d indices passés, de nos buts internes. Le CC et l apprentissage entretiennent des liens profonds et réciproques : si le CC requiert que nous ayons appris un répertoire de comportements et leur valeur dans différentes conditions, l apprentissage de ce répertoire nécessite du CC, pour différentes décisions de haut niveau. Le CC et l apprentissage sont donc indissociablement liés dans la flexibilité qui caractérise la fonction exécutive préfrontale humaine. Cependant, ce lien est actuellement mal compris et peu de travaux de psychologie cognitive ou de modélisation intègrent ces deux aspects et tentent de rendre compte de leur interaction. Nous proposons une théorie mathématique reposant sur l apprentissage par renforcement et l inférence bayésienne, qui intègre l apprentissage de répertoires de comportements (task-sets) dans un milieu incertain et le CC avec ou sans information contextuelle. Cette théorie permet de faire des prédictions spécifiques que nous avons validées par deux expériences comportementales, au détriment d autres modèles existants. Elle rend compte des différences qualitatives de stratégies observées. Notre théorie caractérise de façon intrinsèque les notions essentielles de comportement par défaut, de switch et d exploration, et fait émerger naturellement un contrôle du compromis exploitation exploration. Les résultats empiriques valident les prédictions et confirment les hypothèses du modèle. Il pourra être utilisé pour étudier en IRMf les rôles fonctionnels de régions du cortex préfrontal, des ganglions de la base, et de la dopamine et la noradrénaline.Cognitive control enables appropriate action selection according to stimuli, but also present context or past cues, while taking our internal goals into account. Cognitive control and learning are profoundly and reciprocally linked. On one side, cognitive control requires that a repertoire of behaviors be learnt, as well as their values in different conditions, for appropriate use. On the other side, cognitive control is needed for learning of a repertoire of behaviors, notably to regulate the exploration-exploitation trade-off, but also to generalize, decide to switch, infer a structure in a problem, etc. . ..Thus, cognitive control and learning are strongly linked in the flexibility that characterizes human prefrontal executive function. However, this link is presently poorly understood and few psychological or cognitive neuroscience studies include both aspects. Moreover, existing computational models of learning and decision do not account for their interaction. In this PhD thesis, we propose a mathematical theory combining reinforcement learning and Bayesian inference mechanisms. This model includes learning of repertoires of behaviors (task-sets) in an uncertain environment as well as cognitive control (task-switching) in presence or absence of contextual information. This model makes specific predictions that we tested in two behavioral experiments. They validate the predictions of the theory against other existing models. Moreover, the theory proposes an explanatory factor for qualitative differences in exploratory strategies that we observed across individuals. The proposed theory intrinsically characterizes essential notions such as default behavior, switch and exploration. It allows for the natural emergence of a control mechanism of the exploitationexploration trade-off, as well as its weighing factor. Lastly, empirical results validate the predictions and confirm the hypotheses of the model. The model may be used in functional imaging studies to understand computations executed in the brain, with prefrontal cortex, basal ganglia and neurotransmitters such as dopamine and norepinephrine as main points of interestPARIS-BIUP (751062107) / SudocPARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF

Du lien entre flexibilité cognitive et motivation dans le cortex préfrontal humain

Le cortex préfrontal latéral (CPFL) sélectionne et maintient une représentation qui guide le comportement en accord avec les buts internes et le contexte externe, depuis la formation d une intention jusqu à sa réalisation. Divers mécanismes, fondées sur des représentations liant actions et conséquences dans le cortex préfrontal médian (CPFM), complètent ce modèle. Ces représentations d une part guident la sélection de l action vers la poursuite d un objectif ; d autre part actualisent les représentations du CPFL par la mise en rapport de l action réalisée et de sa conséquence observée. Nous intégrons ces principes dans un modèle computationnel qui met en lumière les contributions relatives du CFPL et du CPFM à la flexiblité cognitive. Une expérience d imagerie illustre ces principes. Enfin, nous proposons un mécanisme spécifique qui permet de mettre une tâche en attente pendant l exécution d une autre. Cette fonction est implémentée dans un modèle par l interaction du CPFM, du CPFL et du cortex frontopolaire. Nos travaux suggèrent une architecture cognitive globale du cortex préfrontal humain qui dirige l action vers la réalisation des intentions.PARIS-BIUSJ-Thèses (751052125) / SudocPARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF