Visual Stimulus

Visual stimulus research investigates how the brain processes visual information, aiming to understand the neural mechanisms underlying perception and cognition. Current research focuses on decoding brain activity to reconstruct visual stimuli using deep learning models, including autoencoders, latent diffusion models, and convolutional neural networks, often incorporating multimodal data (e.g., fMRI, EEG, text descriptions) to improve accuracy and semantic fidelity. These advancements have implications for brain-computer interfaces, diagnosing neurological disorders like Alzheimer's, and improving our understanding of visual perception and attention, potentially leading to more effective treatments and assistive technologies.