Artificial Intelligence (AI) has been part of our imaginations and simmering in research labs since a group of computer scientists rallied around this topic at the Dartmouth Conference in 1956. They would give birth to the field of AI. In the decades since, AI has exploded, especially since 2015. Much of that has to do with […]
On 11th November 2012, I successfully defended my PhD at the University of Barcelona. I will never forget that date and I still vividly remember all the emotions I felt that day. After 5 years of intense research, I had 45 minutes to brief the jury about the motivation, methods and results of my research. […]
As most of you may know P300 is one of the most studied and used event related potentials (ERP) in brain computer interfaces (BCI). This potential is usually elicited by the oddball paradigm in which series of low-probability target items are mixed with high-probability non-target ones. The person carrying out the BCI task is asked […]
With our previous posts, we have been trying to provide our readers with a complete set of knowledge and tools for working with EEG and other physiological signals. We presented the basics of EEG signal processing, the practical usage of EEG signal processing related to emotions or Alzheimer, useful technologies like machine learning, practical guidelines for […]
One of the most interesting theories of brain function in recent years is that of surprise minimisation. This theory was born of computational neuroscience which brings together aspects of physics, information theory and machine learning and tells us that your brain spends its time predicting what will happen next and then updating predictions based on […]
As I advanced in my last post I will try to follow up my description of the Machine Learning family by focusing today on Machine Learning itself (the perfect family parent), and the promising family offspring (hybrid systems, and modern AI). Machine Learning fields Machine Learning started out as a way of investigating how to […]
In our last rendezvous on, ‘Affective computing (or how your PC will know how you feel)‘, I introduced different methodologies for emotion detection that configure the state- of- the- art. Methodologies for emotion detection from face expressions and from body gestures were exposed. Also methodologies from physiological signals, including EEG, galvanic skin response, heart rate […]
In former posts I have given a quick-and-dirty overview of Machine Learning and related methodologies: “what most people call machine learning in neuroscience academic texts is known in other research contexts as pattern recognition, data mining, artificial intelligence (AI), computational intelligence (CI), soft computing (SC), or data analytics. All of these refer to more or […]