Brain energy metabolism on the link between stress, anxiety and coping behaviors, Carmen SANDI
Stress and anxiety can greatly affect individuals coping strategies, including social behaviors. I will present our recent work that highlights brain energy metabolism, particularly mitochondrial function in the nucleus accumbens, as a key mediating mechanism of the impact of stress and anxiety on social competition and coping behaviors. Our findings have implications to understand individual differences in motivated behaviour and in vulnerability to stress.

12h00-12h30 : Sandrine Humbert, GIN
Does abnormal brain development contribute to late onset neurological conditions?
The bulk of interest in the HTT (HTT) protein has centered on the fact that, when mutated, HTT causes Huntington’s disease (HD), a devastating neurological disorder. The mutation causing HD is an abnormal polyglutamine stretch in HTT. Given the adult onset and dysfunction and death of adult neurons characterizing HD, most studies have focused on the toxic effects elicited by mutant HTT in post-mitotic neurons. However, the protein is ubiquitous and expressed in the developing embryo where it plays an essential role as revealed by the early embryonic lethality at day 7.5 of the complete knockout of the HTT gene in mouse. Anyway, the roles of the wild-type protein during development have been overlooked. I will discuss how HTT regulates several steps of mouse embryonic corticogenesis. HTT is important to maintain the pool of cycling progenitors and also regulates the polarization of newly generated neurons. I will describe the underlying molecular mechanisms by which HTT mediates its effects. Finally, I will also show the consequences of the presence of an abnormal polyglutamine expansion in HTT during cortical neurogenesis and consider the viewing of HD as a developmental disorder.


12h30-13h00 : Sophie Achard, GIPSA-lab
Challenges in measuring brain connectivity networks alterations for clinical applications

Resting state fMRI (rs-fMRI) datasets allow the observation of the functioning brain at rest. rs-fMRI combined with graph theoretical approaches has become popular with the perspective of finding network graph metrics as biomarkers in the context of clinical studies. The acquired data consist in multivariate time series. Each time series corresponds to the recording of a specific parcel of the brain for a finite duration. Each node of the brain graph is one time series and an edge in the network is characterizing an interaction between two brain regions. Clinical application on coma patients is presented. Alterations of brain networks are not found at the global level where global topological properties of complex brain networks may be homeostatically conserved under extremely different clinical conditions. However, in every patient we found evidence for a radical reorganization of high degree or highly efficient ``hub’’ nodes. Cortical regions that were hubs of healthy brain networks had typically become non-hubs of comatose brain networks and vice versa. Thus, Consciousness likely depends on the anatomical location of hub nodes in human brain networks.

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