Author Archives: Jorge Mejías

<span property="name">Jorge Mejías</span>
Jorge Mejías received his MSc in Physics and PhD in Computational neuroscience from the University of Granada. After working as a postdoc at the Centre for Neural Dynamics of the University of Ottawa (Canada) he is currently at the Center for Neural Science of New York University.

The term reinforcement learning is well known among researchers in the areas of machine learning and artificial intelligence. It refers to a type of algorithms which are designed to solve a task by maximizing some kind of reward. In […]

When contemplating a high-technology device, one can often realize how much the design and the different pieces have been optimized for the goal they try to achieve. It does not have to be a modern-day technological device; think for example […]

Neurons in your brain are interconnected through synapses, thus constituting the so-called neural networks. Following a simplified but conceptually useful view, each synapse can be seen as a “link” between two given neurons, and it has a certain associated strength. […]

Neurons are known to display irregular behavior in many areas of the brain. When recording the evolution of the membrane potential of a given neuron in the prefrontal cortex (for instance, during in vivo electrophysiology), we can observe its erratic […]