Deep Learning Unveils Health Predictions From EEG and MRI Data

The field of neuroscience and neuroimaging has been revolutionized with the use of artificial intelligence (AI), as it helps in enhancing the detection of brain activities and accurately diagnosing neurological disorders using various modalities. There are different modalities that help in measuring brain activities, but the most common and widely used are functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). The advanced AI approaches, like deep learning (DL) models, give a new opportunity to various fields, including brain research. This research investigates various AI-driven techniques used for the detection and exploration of the human brain using fMRI and EEG. The AI methods include different machine learning (ML) and DL techniques used to interpret neural activities. Basically, the AI-based models, which also include ML and DL, identify the patterns and detect the abnormalities with higher accuracy, which is helpful in many applications, including brain decoding, monitoring cognitive states, brain-computer interface (BCI), and diagnosis of various diseases. This research provides a comprehensive overview of AI applications in neuroimaging, highlights key applications in cognitive neuroscience and medical imaging, along with a discussion of challenges and future directions. The AI impact of the transformation of neuroimaging research is comprehensively discussed with examples to enhance comprehension.