Past events

Neurodevelopmental disorders encompass a wide range of childhood-onset medical conditions caused by different genetic mutations and interaction with environmental factors, affect ~2% of the population, and are a leading cause of intellectual disability and autism spectrum disorder. Evidence is accumulating that either loss or gain in dosage of proteins involved in cognitive and behavioural processes can be deleterious to the nervous system by causing a failure in the ability to maintain neuronal homeostasis. My studies are focused on the MECP2 duplication syndrome, one of the most common genomic rearrangements in males, characterized by autism, intellectual disability, motor dysfunction, anxiety, epilepsy, recurrent respiratory tract infections and early death. To determine whether the phenotypes of MECP2 duplication are reversible upon normalization of MeCP2 levels, I first generated and characterized a new mouse model that over-expresses a conditional allele of Mecp2 that could be deleted in the adult animal (Nature 2015). Upon normalization of MeCP2 in adult symptomatic mice, several phenotypes were rescued at the behavioral, physiological, and molecular levels. Next, I reduced MeCP2 using an antisense oligonucleotide (ASO) strategy, which has greater translational potential. I found that ASO treatment induced a broad phenotypic rescue in adult symptomatic MECP2 duplication mice, abolished abnormal EEG discharges and behavioral seizures, and corrected abnormal gene expression in the hippocampus. I am currently characterizing a novel “humanized” mouse model of MECP2 duplication syndrome that will precisely mimic the human condition by having two copies of human MECP2 and no copies of the mouse gene. These mice will serve as the ideal model for preclinical tests as they represent the closest construct validity model for the human condition. In addition, I am generating and characterizing neurons and cortical spheroids induced from patients’ derived pluripotent stem cells (iPSCs).

Understanding the Self has fascinated artists, writers, philosophers and psychologist for generation. In the past two decades cognitive and neurocognitive tools have been applied to the study of the Self. The talk will present research on the Self and the Friend. Not surprisingly, it is consistently found that our brain prioritize the Self. For example, deciding whether a face looks to the left or right is faster on one’s own face than on a face of a friend. This prioritization transcend time, showing similar prioritization to one’s face in the past as in the present. Lesions to the fusiform gyrus hinders Self facilitation, while lesions to lateral frontal cortices amplifies it. Associating a simple geometric shape to oneself is done much more efficiently than to a stranger an effect that is mediated via the left STS, medial and lateral frontal cortices. Participants are also better at judging a perspective of an avatar if it is tagged as them than as a stranger. But in all these studies the Friend is also prioritized relative to a stranger. Why is the friend prioritized, is it because it is relevant, or because it is liked? In a simple shape-identity matching task, we manipulated orthogonally the valence and relevance of familiar identities. We found that prioritization is given based on relevance and valence in Western culture, but primarily based on valance in Asian cultures. Using spatial maps to represent the social space, we observed consistent representation of social relations as physical distances. Physical distance between identities was affected by the valence and relevance factors, though this was modulated by the participants’ culture. Finally, presenting participants with incongruent spatial maps of their social relations, resulted in increase and decrease responses in a large network of regions including the Amygdala and superior temporal structure known to play a rule in social cognition. Taken together this body of work highlight neurocognitive mechanism by which our brain prioritize information based on social rules.

The cortical system for processing faces is a model system for studying the functional neuroanatomy of ventral temporal cortex and its role in perception for two reasons. First, the functional organization of the cortical face system is well understood. Second, activations in ventral face-selective regions are causally related to face perception. Here, I will describe recent results from our research elucidating the computations performed by population receptive field (pRFs) in the cortical system for face perception. In contrast to predictions of classical theories, recent data from my lab reveals that computations in face-selective regions in human ventral temporal cortex can be characterized with a computational pRF model, which predicts the location and spatial extent of the visual field that is processed by the neural population in a voxel. Our research characterizes pRF properties of ventral face-selective regions revealing three main findings. First, pRFs illustrate a hierarchical organization within the face system, whereby pRFs become larger and more foveal across the ventral hierarchy. Second, attention to faces modulates pRFs in face-selective regions, consequently enhancing the representation of faces in the peripheral visual field where visual acuity is the lowest. Third, our research shows that pRF properties in face-selective regions are behaviorally relevant. We find that face perception abilities are correlated with pRF properties: participants with larger pRFs perform better in face recognition than participants with smaller pRFs. These data suggest that computations performed by pRFs in face-selective regions may form a neural basis for holistic processing necessary for face recognition. Overall, these data highlight the importance of elucidating computational properties of neural populations in ventral temporal cortex as they offer a new mechanistic understanding of high-level visual processes such as face perception.