From cells to systems: multiscale studies of the epileptic brain
It is increasingly recognized that epilepsy affects human brain organization across multiple scales, ranging from cellular alterations in specific regions towards macroscale network imbalances. My talk will overview an emerging paradigm that integrates cellular, neuroimaging, and network modelling approaches to faithful characterize the extent of structural and functional alterations in the common epilepsies. I will also discuss how multiscale framework can help to derive clinically useful biomarkers of dysfunction, and how these methods may guide surgical planning and prognostics.
Emergence of long time scales in data-driven network models of zebrafish activity
How can neural networks exhibit persistent activity on time scales much larger than allowed by cellular properties? We address this question in the context of larval zebrafish, a model vertebrate that is accessible to brain-scale neuronal recording and high-throughput behavioral studies. We study in particular the dynamics of a bilaterally distributed circuit, the so-called ARTR, including hundreds neurons. ARTR exhibits slow antiphasic alternations between its left and right subpopulations, which can be modulated by the water temperature, and drive the coordinated orientation of swim bouts, thus organizing the fish spatial exploration. To elucidate the mechanism leading to the slow self-oscillation, we train a network graphical model (Ising) on neural recordings. Sampling the inferred model allows us to generate synthetic oscillatory activity, whose features correctly capture the observed dynamics. A mean-field analysis of the inferred model reveals the existence several phases; activated crossing of the barriers in between those phases controls the long time scales present in the network oscillations. We show in particular how the barrier heights and the nature of the phases vary with the water temperature.
Is it Autism or Alexithymia? explaining atypical socioemotional processing
Emotion processing is thought to be impaired in autism and linked to atypical visual exploration and arousal modulation to others faces and gaze, yet evidence is equivocal. We propose that, where observed, atypical socioemotional processing is due to alexithymia, a distinct but frequently co-occurring condition which affects emotional self-awareness and Interoception. In study 1 (N = 80), we tested this hypothesis by studying the spatio-temporal dynamics and entropy of eye-gaze during emotion processing tasks. Evidence from traditional and novel methods revealed that atypical eye-gaze and emotion recognition is best predicted by alexithymia in both autistic and non-autistic individuals. In Study 2 (N = 70), we assessed interoceptive and autonomic signals implicated in socioemotional processing, and found evidence for alexithymia (not autism) driven effects on gaze and arousal modulation to emotions. We also conducted two large-scale studies (N = 1300), using confirmatory factor-analytic and network modelling and found evidence that Alexithymia and Autism are distinct at both a latent level and their intercorrelations. We argue that: 1) models of socioemotional processing in autism should conceptualise difficulties as intrinsic to alexithymia, and 2) assessment of alexithymia is crucial for diagnosis and personalised interventions in autism.