Dynamical information processing in bacteria

In spite of their seeming simplicity, prokaryotic organisms such as the bacteria Escherichia coli and Bacillus subtilis are able to exhibit nontrivial dynamical responses to complex environmental conditions. We monitor this behavior using fluorescence proteins as reporters of gene expression, which are measured via time-lapse microscopy. This technique provides time-resolved information about the activity of desired DNA promoters at the single-cell level, which in combination with theoretical modeling allows us to unravel the molecular mechanism of diverse cellular processes, such as stress responses and natural and synthetic gene oscillations. We also study the spatiotemporal organization of large cellular populations such as bacterial biofilms.

Decision making in development

Multicellular organisms, in particular mammals, have an astonishing ability to self-organize in space and time. Starting from a single cell, embryos use a large variety of biochemical and mechanical cues, both intrisic and maternal, to define when and where myriads of proliferating cells reach a specific fate. This intricately choreographed division of labor eventually leads to a fully functional organism. While much is known about the details of the different developmental processes involved, much remains to be learned still about the fundamental mechanisms of multicellular self-organization. We use theoretical and computational approaches, in combination with both live imaging and single-cell transcriptomics data, to search for these fundamental mechanisms.

Signaling in the immune response

The immune system must be ready to respond quickly to pathogens in order to organize a rapid response. When the system goes awry, the body runs the risk of responding too weakly to external insults (immunodeficiency) or, in the other extreme, to respond too much and attack its own cells (autoimmunity). In order to face these disorders, we need to understand how immune cells respond to external triggers. We study these questions using a variety of approaches and data, involving different processes ranging from the antiviral response of single mammalian cells in culture to the interaction between multiple biological layers in patients suffering from autoimmune disorders.

Mesoscopic brain dynamics

Brain activity is naturally dynamical. EEG measures reveal a variety of rhythms (alpha, beta, gamma, etc) each of which have been associated with a distinct physiological function. One of the challenges in this field is to relate the functional measures of brain activity, routinely obtained not only by EEG but also by other techniques such as fMRI and MEG, with the underlying structure of brain connectivity. We adress this question with mesoscopic neural mass models that allow us to describe theoretically the activity of the full brain, and use these models to understand the dynamical correlates of neurodegenerative diseases.

Collective oscillations in neuronal populations

Brain rhythms are generated by populations of neurons, even though the individual neurons do not necessarily fire in synchrony with these global oscillations. We are investigating how the dynamical properties of the individual neurons impact the nature of the population oscillations, and how these oscillations are affected by noise, and are used to communicate information in an effective manner across distant brain areas.