Les fondements génétiques de la représentation des actions d'autrui

Au cours des dernières années, plusieurs questions furent soulevées par la découverte d’un système neuronal permettant la mise en correspondance des représentations visuelles et motrices d’une même action lors de l’observation d’actions. Plus particulièrement, de quelle façon ce système acquiert-il cette intrigante propriété et quelle fonction remplie-t-il? Les perspectives théoriques actuelles proposent que le développement de ce système, appelé le système des neurones miroirs (SNM), soit régulé à la fois par des facteurs génétiques et par l’apprentissage associatif afin de faciliter des processus de cognition sociale de plus haut niveau, tel que l’empathie. Notons que jusqu’à présent, aucun facteur génétique n’a pu être associé au développement et au fonctionnement de ce système. La présente thèse propose d’évaluer l’influence d’une variation génétique sur l’activité et le fonctionnement du SNM, le polymorphisme Val66Met du Facteur neurotrophique dérivé du cerveau (Brain-derived Neurotrophic Factor; BDNF). Ce facteur génétique fut notamment associé à l’apprentissage moteur et à l’adaptation visuomotrice dans certaine région du système. Les résultats de la présente thèse indiquent que le polymorphisme Val66Met du BDNF influence la réponse du SNM lors de l’observation d’actions. Cette influence serait possiblement opérée par l’action du polymorphisme sur l’apprentissage associatif, lui-même influencé par ce facteur génétique (Article 1). De plus, les résultats obtenus indiquent une association entre ce polymorphisme et l’empathie autorapportée qui ne peut être attribuable à d’autres facteurs génétiques préalablement associés à cette mesure (Article 2). Ces observations ont inspiré la proposition d’une nouvelle approche psychophysique permettant d’offrir une alternative aux méthodes actuelles visant l’étude des interactions gène-gène et gène-environnement en neuroimagerie génétique (Article 3). Les résultats présentés constituent la première démonstration empirique de l’influence d’un facteur génétique sur l’apprentissage et le fonctionnement du SNM. Bien que ce facteur génétique puisse moduler le SNM et l’empathie autorapportée, les résultats obtenus ne permettent toutefois pas de statuer sur le lien direct entre ces deux phénotypes fréquemment associés dans la littérature. Cette contribution scientifique permet l’avancée de la compréhension du système des neurones miroirs, un système ayant été grandement étudié pour son rôle dans des psychopathologies associées à des symptômes sociaux cognitifs telles que la schizophrénie.Many questions were raised by the discovery of the mirror neuron system (MNS), a neural system involves in the transformation of visual representations of action into fined-grained changes in the motor system during action observation. Notably, how does this system acquire this property and what is its function? Contemporary perspectives propose that the MNS might be regulated both by genetics and associative learning in order to facilitate higher-order social cognitive processes, such as empathy. Although, so far, no genetic variant was directly or indirectly associated to the development or to the function of this system. This dissertation aims at determining the influence of a specific genetic variant, the polymorphism Val66Met of the Brain-derived Neurotrophic factor (BDNF), on the activity and the function of the system. This genetic variant has previously been associated to motor learning and to visuomotor adaptation in regions of the mirror system. The results indicate that the BDNF val66Met polymorphism influences the response of the MNS during action observation. More precisely, this effect might be confered throught the action of the polymorphism on visuomotor associative learning (Article 1). Moreover, the results indicate an association between this polymorphism and self-reported empathy that cannot be explained by two other genetic variants commonly associated with this measure (Article 2). These observations led to the propostion of a new psychophysical conceptualisation of the effect of genetic variants in genetic neuroimaging that could facilitate the study of the complex gene-by-gene and gene-by-environement interactions in the field (Article 3). These results represent the first empirical evidence suggesting an influence of a specific genetic variant on the activity and function of the MNS. Our results do not indicate a direct link between the MNS and self-reported empathy, but indicate independent influences of the BDNF Val66Met on both phenotypes. This scientific contribution furthers our understanding of the mirror neuron system, a system widely studied for its role in psychopathologies linked to social cognitive symptoms such as schizophrenia

Les distances entre les attributs internes du visage humain

La zeitgesit contemporaine sur la reconnaissance des visages suggère que le processus de reconnaissance reposerait essentiellement sur le traitement des distances entre les attributs internes du visage. Il est toutefois surprenant de noter que cette hypothèse n’a jamais été évaluée directement dans la littérature. Pour ce faire, 515 photographies de visages ont été annotées afin d’évaluer l’information véhiculée par de telles distances. Les résultats obtenus suggèrent que les études précédentes ayant utilisé des modifications de ces distances ont présenté 4 fois plus d’informations que les distances inter-attributs du monde réel. De plus, il semblerait que les observateurs humains utilisent difficilement les distances inter-attributs issues de visages réels pour reconnaître leurs semblables à plusieurs distances de visionnement (pourcentage correct maximal de 65%). Qui plus est, la performance des observateurs est presque parfaitement restaurée lorsque l’information des distances inter-attributs n’est pas utilisable mais que les observateurs peuvent utiliser les autres sources d’information de visages réels. Nous concluons que des indices faciaux autre que les distances inter-attributs tel que la forme des attributs et les propriétés de la peau véhiculent l’information utilisée par le système visuel pour opérer la reconnaissance des visages.According to an influential view, based on studies of development and of the face inversion effect, human face recognition relies mainly on the treatment of the distances among internal facial features. However, there is surprisingly little evidence supporting this claim. Here, we first use a sample of 515 face photographs to estimate the face recognition information available in interattribute distances. We demonstrate that previous studies of interattribute distances generated faces that exaggerated 4 times this information compared to real-world faces. When interattribute distances are sampled from a real-world distribution, we show that human observers recognize faces poorly across a broad range of viewing distances (with a maximum accuracy of 65%). In contrast, recognition performance is restored when observers only use facial cues of real-world faces other than interattribute distances. We conclude that facial cues other than interattribute distances such as attribute shapes and skin properties are the dominant information of face recognition mechanisms

Interattribute Distances do not Represent the Identity of Real World Faces

According to an influential view, based on studies of development and of the face inversion effect, human face recognition relies mainly on the treatment of the distances among internal facial features. However, there is surprisingly little evidence supporting this claim. Here, we first use a sample of 515 face photographs to estimate the face recognition information available in interattribute distances. We demonstrate that previous studies of interattribute distances generated faces that exaggerated by 376% this information compared to real-world faces. When human observers are required to recognize faces solely on the basis of real-world interattribute distances, they perform poorly across a broad range of viewing distances (equivalent to 2 to more than 16 m in the real-world). In contrast, recognition is almost perfect when observers recognize faces on the basis of real-world information other than interattribute distances such as attribute shapes and skin properties. We conclude that facial cues other than interattribute distances such as attribute shapes and skin properties are the dominant information of face recognition mechanisms

Measuring away an attentional confound?

A recent fMRI study by Webb et al. (Cortical networks involved in visual awareness independent of visual attention, Proc Natl Acad Sci U S A 2016;113:13923–28) proposes a new method for finding the neural correlates of awareness by matching atten- tion across awareness conditions. The experimental design, however, seems at odds with known features of attention. We highlight logical and methodological points that are critical when trying to disentangle attention and awareness

BDNF Val66Met polymorphism is associated with self-reported empathy

Empathy is an important driver of human social behaviors and presents genetic roots that have been studied in neuroimaging using the intermediate phenotype approach. Notably, the Val66Met polymorphism of the Brain-derived neurotrophic factor (BDNF) gene has been identified as a potential target in neuroimaging studies based on its influence on emotion perception and social cognition, but its impact on self-reported empathy has never been documented. Using a neurogenetic approach, we investigated the association between the BDNF Val66Met polymorphism and self-reported empathy (Davis’ Interpersonal Reactivity Index; IRI) in a sample of 110 young adults. Our results indicate that the BDNF genotype is significantly associated with the linear combination of the four facets of the IRI, one of the most widely used self-reported empathy questionnaire. Crucially, the effect of BDNF Val66Met goes beyond the variance explained by two polymorphisms of the oxytocin transporter gene previously associated with empathy and its neural underpinnings (OXTR rs53576 and rs2254298). These results represent the first evidence suggesting a link between the BDNF gene and self-reported empathy and warrant further studies of this polymorphism due to its potential clinical significance

"Task-relevant autoencoding" enhances machine learning for human neuroscience

In human neuroscience, machine learning can help reveal lower-dimensional neural representations relevant to subjects' behavior. However, state-of-the-art models typically require large datasets to train, so are prone to overfitting on human neuroimaging data that often possess few samples but many input dimensions. Here, we capitalized on the fact that the features we seek in human neuroscience are precisely those relevant to subjects' behavior. We thus developed a Task-Relevant Autoencoder via Classifier Enhancement (TRACE), and tested its ability to extract behaviorally-relevant, separable representations compared to a standard autoencoder, a variational autoencoder, and principal component analysis for two severely truncated machine learning datasets. We then evaluated all models on fMRI data from 59 subjects who observed animals and objects. TRACE outperformed all models nearly unilaterally, showing up to 12% increased classification accuracy and up to 56% improvement in discovering "cleaner", task-relevant representations. These results showcase TRACE's potential for a wide variety of data related to human behavior.Comment: 41 pages, 11 figures, 5 tables including supplemental materia

The Union Threat *

Abstract This paper studies the impact of labor unions on wage inequality, output and unemployment. To do so, it proposes a search and matching model of union formation in which unions arise endogenously through a voting process within firms. In a union firm, workers bargain their wages collectively. In a nonunion firm, each worker bargains individually with the firm. Because of this wage setting asymmetry, a union lowers the profit of a firm and compresses the wage distribution of the workers. Furthermore, to prevent unionization, nonunion firms distort their hiring decisions in a way that also lowers the dispersion of wages. After being calibrated on the United States, the model shows that, even though a standard empirical estimate would predict a small impact of unions on wage inequality, removing the threat of unionization increases the variance of wages substantially. It also increases output and reduces unemployment. Completely outlawing unions increases wage inequality further while forcing all firms to be unionized lowers inequality considerably. These results suggest that, even with a small membership, unions might have a significant impact on the economy through general equilibrium mechanisms and the way they distort firms' decisions

Financial Risk and Unemployment

Abstract There is a strong correlation between the corporate interest rate (BAA rated), and its spread relative to Treasuries, and the unemployment rate. We model how interest rates and potential default rates impact equilibrium unemployment in a Diamond-Mortesen-Pissarides model. We calibrate the model using US data without targeting business cycle statistics. Volatility in the corporate interest rate can explain about 80% of the volatility of unemployment, vacancies, and market tightness. Simulating the Great Recession shows the model can account for much of the rise in unemployment. Without Fed action, unemployment would have been 6% higher. JEL Classification:E22, E24, E32, E44, J41, J63, J6