Convolutional Neural Networks: Brain Computer Simulations for Potential Non-Invasive Schizophrenia and Psychiatric Treatment as Alternative to Medication

Deep Learning Neural Networks (DLNN), drawing inspiration from the brain's learning capabilities, may potentially provide treatment solutions alternative to medication. Recent advancements in Convolutional Neural Networks (CNN) and Electroencephalography (EEG) have shown promise in accurately diagnosing conditions like depression, anxiety, and schizophrenia. Additionally, DLNN could be applied to identify brain regions suitable for electrical stimulation or suppression including Electroconvulsive Therapy (ECT) as non-invasive treatments for psychiatric disorders, minimizing side effects of medication. The paper evaluates current progress in DLNN for psychiatric diagnosis and proposes a novel approach to treatment for schizophrenia.