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1.
Cogn Affect Behav Neurosci ; 23(1): 142-161, 2023 02.
Article in English | MEDLINE | ID: mdl-36289181

ABSTRACT

Mood is an important ingredient of decision-making. Human beings are immersed into a sea of ​​emotions where episodes of high mood alternate with episodes of low mood. While changes in mood are well characterized, little is known about how these fluctuations interact with metacognition, and in particular with confidence about our decisions. We evaluated how implicit measurements of confidence are related with mood states of human participants through two online longitudinal experiments involving mood self-reports and visual discrimination decision-making tasks. Implicit confidence was assessed on each session by monitoring the proportion of opt-out trials when an opt-out option was available, as well as the median reaction time on standard correct trials as a secondary proxy of confidence. We first report a strong coupling between mood, stress, food enjoyment, and quality of sleep reported by participants in the same session. Second, we confirmed that the proportion of opt-out responses as well as reaction times in non-opt-out trials provided reliable indices of confidence in each session. We introduce a normative measure of overconfidence based on the pattern of opt-out selection and the signal-detection-theory framework. Finally and crucially, we found that mood, sleep quality, food enjoyment, and stress level are not consistently coupled with these implicit confidence markers, but rather they fluctuate at different time scales: mood-related states display faster fluctuations (over one day or half-a-day) than confidence level (two-and-a-half days). Therefore, our findings suggest that spontaneous fluctuations of mood and confidence in decision making are independent in the healthy adult population.


Subject(s)
Metacognition , Adult , Humans , Metacognition/physiology , Reaction Time , Visual Perception , Discrimination, Psychological , Affect , Decision Making/physiology
2.
Front Hum Neurosci ; 14: 559793, 2020.
Article in English | MEDLINE | ID: mdl-33132875

ABSTRACT

This paper addresses how impairments in prediction in young adults with autism spectrum disorder (ASD) relate to their behavior during collaboration. To assess it, we developed a task where participants play in collaboration with a synthetic agent to maximize their score. The agent's behavior changes during the different phases of the game, requiring participants to model the agent's sensorimotor contingencies to play collaboratively. Our results (n = 30, 15 per group) show differences between autistic and neurotypical individuals in their behavioral adaptation to the other partner. Contrarily, there are no differences in the self-reports of that collaboration.

3.
Addict Biol ; 24(6): 1121-1137, 2019 11.
Article in English | MEDLINE | ID: mdl-30811097

ABSTRACT

Cannabis is the most used illicit substance in the world. As many countries are moving towards decriminalization, it is crucial to determine whether and how cannabis use affects human brain and behavior. The role of the cerebellum in cognition, emotion, learning, and addiction is increasingly recognized. Because of its high density in CB1 receptors, it is expected to be highly affected by cannabis use. The aim of this systematic review is to investigate how cannabis use affects cerebellar structure and function, as well as cerebellar-dependent behavioral tasks. Three databases were searched for peer-reviewed literature published until March 2018. We included studies that focused on cannabis effects on cerebellar structure, function, or cerebellar-dependent behavioral tasks. A total of 348 unique records were screened, and 40 studies were included in the qualitative synthesis. The most consistent findings include (1) increases in cerebellar gray matter volume after chronic cannabis use, (2) alteration of cerebellar resting state activity after acute or chronic use, and (3) deficits in memory, decision making, and associative learning. Age of onset and higher exposure to cannabis use were frequently associated with increased cannabis-induced alterations. Chronic cannabis use is associated with alterations in cerebellar structure and function, as well as with deficits in behavioral paradigms that involve the cerebellum (eg, eyeblink conditioning, memory, and decision making). Future studies should consider tobacco as confounding factor and use standardized methods for assessing cannabis use. Paradigms exploring the functional activity of the cerebellum may prove useful as monitoring tools of cannabis-induced impairment.


Subject(s)
Cerebellum/physiopathology , Cognitive Dysfunction/physiopathology , Marijuana Abuse/physiopathology , Marijuana Use/psychology , Memory Disorders/physiopathology , Association Learning/physiology , Cerebellum/diagnostic imaging , Cognition , Cognitive Dysfunction/diagnostic imaging , Cognitive Dysfunction/psychology , Decision Making/physiology , Functional Neuroimaging , Gray Matter/diagnostic imaging , Humans , Magnetic Resonance Imaging , Marijuana Abuse/diagnostic imaging , Marijuana Abuse/psychology , Memory Disorders/psychology , Receptor, Cannabinoid, CB1/metabolism
4.
Proc Biol Sci ; 284(1869)2017 Dec 20.
Article in English | MEDLINE | ID: mdl-29263282

ABSTRACT

Humans display anticipatory motor responses to minimize the adverse effects of predictable perturbations. A widely accepted explanation for this behaviour relies on the notion of an inverse model that, learning from motor errors, anticipates corrective responses. Here, we propose and validate the alternative hypothesis that anticipatory control can be realized through a cascade of purely sensory predictions that drive the motor system, reflecting the causal sequence of the perceptual events preceding the error. We compare both hypotheses in a simulated anticipatory postural adjustment task. We observe that adaptation in the sensory domain, but not in the motor one, supports the robust and generalizable anticipatory control characteristic of biological systems. Our proposal unites the neurobiology of the cerebellum with the theory of active inference and provides a concrete implementation of its core tenets with great relevance both to our understanding of biological control systems and, possibly, to their emulation in complex artefacts.


Subject(s)
Anticipation, Psychological , Movement , Posture , Adaptation, Psychological , Humans , Models, Psychological
5.
Sci Rep ; 7(1): 15499, 2017 Nov 10.
Article in English | MEDLINE | ID: mdl-29127416

ABSTRACT

A correction to this article has been published and is linked from the HTML version of this paper. The error has been fixed in the paper.a.

6.
Sci Rep ; 7(1): 3333, 2017 06 13.
Article in English | MEDLINE | ID: mdl-28611387

ABSTRACT

Body ownership is critically dependent on multimodal integration as for instance revealed in the Rubber Hand Illusion (RHI) and a number of studies which have addressed the neural correlates of the processes underlying this phenomenon. Both experimental and clinical research have shown that the structures underlying body ownership seem to significantly overlap with those of motor control including the parietal and ventral premotor cortices, Temporal Parietal Junction (TPJ) and the insula. This raises the question of whether this structural overlap between body ownership and motor control structures is of any functional significance. Here, we investigate the specific question of whether experimentally induced ownership over a virtual limb can modulate the performance of that limb in a simple sensorimotor task. Using a Virtual reality (VR) environment we modulate body ownership in three experimental conditions with respect to the (in)congruence of stimulus configurations. Our results show that the degree of ownership directly modulates motor performance. This implies that body ownership is not exclusively a perceptual and/or subjective multimodal state but that it is tightly coupled to systems for decision-making and motor control.


Subject(s)
Decision Making , Motor Activity , Psychomotor Performance , Sensorimotor Cortex/physiology , Touch Perception , Visual Perception , Adult , Female , Humans , Male , Virtual Reality
7.
Neural Netw ; 72: 88-108, 2015 Dec.
Article in English | MEDLINE | ID: mdl-26585942

ABSTRACT

Animals successfully forage within new environments by learning, simulating and adapting to their surroundings. The functions behind such goal-oriented behavior can be decomposed into 5 top-level objectives: 'how', 'why', 'what', 'where', 'when' (H4W). The paradigms of classical and operant conditioning describe some of the behavioral aspects found in foraging. However, it remains unclear how the organization of their underlying neural principles account for these complex behaviors. We address this problem from the perspective of the Distributed Adaptive Control theory of mind and brain (DAC) that interprets these two paradigms as expressing properties of core functional subsystems of a layered architecture. In particular, we propose DAC-X, a novel cognitive architecture that unifies the theoretical principles of DAC with biologically constrained computational models of several areas of the mammalian brain. DAC-X supports complex foraging strategies through the progressive acquisition, retention and expression of task-dependent information and associated shaping of action, from exploration to goal-oriented deliberation. We benchmark DAC-X using a robot-based hoarding task including the main perceptual and cognitive aspects of animal foraging. We show that efficient goal-oriented behavior results from the interaction of parallel learning mechanisms accounting for motor adaptation, spatial encoding and decision-making. Together, our results suggest that the H4W problem can be solved by DAC-X building on the insights from the study of classical and operant conditioning. Finally, we discuss the advantages and limitations of the proposed biologically constrained and embodied approach towards the study of cognition and the relation of DAC-X to other cognitive architectures.


Subject(s)
Adaptation, Psychological/physiology , Appetitive Behavior/physiology , Behavior, Animal/physiology , Conditioning, Operant/physiology , Models, Biological , Animals , Brain/physiology , Cognition/physiology , Computer Simulation , Decision Making/physiology , Learning/physiology , Problem Solving/physiology
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