iLab: From Brain to Machine and Back
iossifidis Lab
Published in Journal of Neurocomputing: Understanding activation patterns in artificial neural networks by exploring stochastic processes: Discriminating generalization from memorization Stephan Johann Lehmler, Muhammad Saif-ur-Rehman, Tobias Glasmachers, Ioannis Iossifidis for more details: https://doi.org/10.1016/j.neucom.2024.128473
The Iossifidis Lab is excited to announce our participation in the Bernstein Conference 2024! Our team contributed five diverse presentations, highlighting our latest advancements in computational neuroscience. From neural network dynamics to brain-inspired algorithms, our research sparked engaging discussions and collaborations. The conference proved to be an incredible platform for knowledge exchange and networking. We … Read More “Iossifidis Lab at Bernstein Conference 2024” »
https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2024.1390714/full Aline Xavier Fidêncio1,2,3*Christian Klaes3Ioannis Iossifidis2 Error-related potentials (ErrPs) are brain signals known to be generated as a reaction to erroneous events. Several works have shown that not only self-made errors but also mistakes generated by external agents can elicit such event-related potentials. The possibility of reliably measuring ErrPs through non-invasive techniques has increased the … Read More “A generic error-related potential classifier based on simulated subjects-Frontiers in Human Neuroscience” »
