Keywords: Computational Neuroscience, Dynamical Systems, Machine Learning, Time Series Analysis, Networks.

Below you can find some brief descriptions of current and past research projects and interests.

Neural coding: Information processing in the retina

Decoding

I am currently working on visual information processing in the retina, with a focus on decoding problems: inferring the stimulus seen by the retina from the experimentally recorded neural response. We employ Machine Learning techniques as well as tools from Statistical Physics and Information Theory to decode the visual stimulus and gain valuable biological insight about the organization of the neural code.

Some general questions that guide our research are: to which extent is the visual information linearly decodable? Are noise correlations important for decoding? How does the brain deal with retinal ganglion cells spontaneous firing?

In collaboration with

Adaptive networks

Adaptive network

Adaptive systems give rise to new and interesting dynamical phenomena. For example, we have studied an adaptive network of chaotic maps - where there is an interplay between topology and local dynamics - and found that the network can self-organize in a polysynchronous state with a strongly hierarchical structure.

In collaboration with

Dynamics of neural oscillations

Slow Wave

The sleep slow waves appear as a result of the synchronization of large populations of neurons that alternately agree to fire and turn silent together. These slow waves, which have been linked to learning and memory consolidation processes, propagate through the cortex in a complex way. Making use of human intracranial EEG data we characterized different aspects of their dynamics.

In collaboration with

  • Michel Le Van Quyen (CRICM, Paris)
  • Mario Valderrama (Universidad de los Andes, Bogotá)

Poster: Travelling waves in the brain: a network approach to their propagation. Vienna, 2011.

Non-linear dynamics and chaos

Varley bifurcationsLozi map bifurcations

Part of my research is focused in the study of systems presenting chaotic behaviour. More specifically we work with discrete maps in order to achieve a better understanding of their dynamics. We have mainly studied the dynamical repertoire of one- and two-dimensional piecewise continuous maps.

In collaboration with

Poster: Dynamics of a map with a power-law tail: Description of an order-to-chaos transition. Cargèse, 2010.
Poster: Families of maps with constant Lyapunov exponent. Zaragoza, 2012.