Cortical Response

Cortical response research aims to understand how brain regions process sensory information, focusing on how artificial neural network models can predict and explain these responses. Current studies heavily utilize convolutional and transformer-based architectures, including self-supervised models like Wav2vec 2.0, to analyze responses to visual and auditory stimuli, comparing single-image versus video processing and exploring the role of attention. These investigations reveal insights into the hierarchical nature of cortical processing and the effectiveness of different model architectures in capturing neural activity, potentially informing the design of improved neuroprosthetics and advancing our understanding of brain computation.