Human Brain
Research on the human brain focuses on understanding its complex information processing mechanisms and applying this knowledge to improve artificial intelligence and medical applications. Current research employs various computational models, including deep neural networks (like transformers and convolutional neural networks), graph neural networks, and spiking neural networks, to analyze brain activity data (fMRI, EEG, MEG) and decode neural representations of visual information, language, and emotions. These efforts aim to improve our understanding of brain function, develop more accurate brain-computer interfaces, and create more human-like AI systems, ultimately impacting fields ranging from neuroscience and psychology to clinical diagnosis and treatment.
Papers
Optimal EEG Electrode Set for Emotion Recognition From Brain Signals: An Empirical Quest
Rumman Ahmed Prodhan, Sumya Akter, Tanmoy Sarkar Pias, Md. Akhtaruzzaman Adnan
Denoising Diffusion Probabilistic Models for Image Inpainting of Cell Distributions in the Human Brain
Jan-Oliver Kropp, Christian Schiffer, Katrin Amunts, Timo Dickscheid