Matías Goldin PhD in Physics

Course and current status

1. 2020 – present : Institut de la Vision, Inserm/Sorbonne Université, Paris, France.    
Team of Retinal Information Processing.

2. 2019 – 2020 : Institute of Neuroscience Paris-Saclay (Neuro-PSI), CNRS, Gif-sur-Yvette, France. Team of Sensori-motor Integration & Plasticity.   

3. 2009 – 2015: Dynamical Systems Laboratory. Physics Dept, School of Science, Univ of Buenos Aires, Argentina.

4. 2009 : Systems Biology Laboratory. Inst of Phys, Mol Biol and Neurosc (IFIByNE) CONICET, School of Science, Univ of Buenos Aires, Argentina.

5. 2006 – 2008: Image Processing Laboratory. Physics Dept, School of Science, Univ of Buenos Aires, Argentina.

Scientific summary

My purpose is to understand how biological neurons implement together specific computations in the brain. For this I have designed and used tools from physics to perform experiments where I can perturb neural circuits in a controlled manner, and I have combined them with quantitative modeling to exploit these results, and built models explaining how neural computations are implemented. I did my PhD on the neural mechanisms of temperature manipulations in the motor pathway of birds, both experimentally and computationally, developing a cooling device and average neuronal models. In a first short postdoc, I modeled the effect of temperature control on single cells in the bird. In a second postdoc, I focused on sensory coding of complex stimuli in the rodent whisker system, on developing models of sensory processing, and of the corresponding neural circuits. In my third postdoc, I am studying retinal coding under complex natural stimuli, modeling neuronal units and populations with deep neural networks in order to understand the retinal circuits. During my Physics Master I worked 3 years in optics developing a method with a foundational concept for holography, a technique used in neuroscience. I have a solid background in optics, computational modeling at diverse scales and systems neuroscience, as well as experience in analyzing and modeling neural data.

Image d’exemple