Last December, the Luminous[1] project organized a networking session at the ICT 2018 Exhibition, a central event of R&D activities in the EU. The networking session aimed to open an interdisciplinary discussion on consciousness. Specifically, Prof. Joanna Bryson (Artificial Intelligence expert, Dept. of Computer Science, University of Bath), Prof. Antonio Chella (Machine Consciousness expert, Dept. of […]
The superior performance of deep learning relative to other machine learning methodologies has been commented in several forums and magazines in recent times. I would like to post today on three reasons that, in my opinion, are the basis of this commented superiority. I am not the first to comment on this issue [1], and […]
Last April Starlab kicked-off the H2020 FET Open Luminous[1]. We are very proud to coordinate one of the 11 projects out of 800 selected for funding in last year’s Call of the FET Open[2] program, one of the most competitive programs within the European funding landscape. The project aims to study consciousness by combining the […]
Recently my colleagues Javier Acedo and Marta Castellano posted about ExperienceLab, Neurokai’s platform for characterizing the emotional response of users, and its very last presentation in an art exhibition discussing technology-driven evolution of humans. As you might already know ExperienceLab gathers data of a user when perceiving an external stimulus and associates an arousal and […]
– Neuro… what? What on earth is neuroinformatics… you mean, bioinformatics? Indeed neuroinformatics takes inspiration from bioinformatics, which refers to the combination of omics data (genomic, transcriptomic, proteomic…) and its understanding with machine learning tools (well, and other computer science disciplines). Bioinformatics has brought enormous advances for instance in cancer research, which was itself one […]
My post today will deal with the future. I have recently attended a conference by Pankaj Ghemawat on the World 3.0 (well the conference had a more local component as well but I will try to focus on the more general aspects). As far as I understood the 3.0 world is characterized by the mixing of […]
Today I would like to relate Machine Learning to different concepts like biological psychiatry, stratified medicine, or the “subjectivity gap between neuroscience research and the clinical reality for patients with mental disorders”. Behind all these concepts there is a redefinition of the diagnostic process, which should incorporate more and more objective data. Although this […]
While heading to Petronas Technology University where I will give a course on transcranial current stimulation (tCS) basics I summarized the basics of the technology and particularly on Starstim, the device we envisioned and started to develop within the HIVE project. tCS devices allow the controlled injection of low-amplitude electrical currents into the cerebral cortex […]
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 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 […]