Artificial Intelligence’s Involvement in Neurology
- Julia Pelanne
- 3 days ago
- 3 min read
Artificial intelligence’s involvement in neurology has made for revolutionary progress in neuroimaging, neurocognitive disorder research, and personalized treatment over the last decade. Since the 1970s, AI has been integrated into a multitude of topics in neuroscience, ranging from genetic mapping and modelling of the human brain, to patient treatment analysis, to advanced research in neurological disorders. Its contributions to the fields of neuroscience, neurology, and psychological research have improved the lives of millions suffering from formerly understudied conditions.
Neuroscience has become integral to comprehensive research in neural systems and their communicational functions, proving to be the perfect modelling tool in this space. Utilizing AI, scientists can imitate the neural signals sent by the brains, and by portraying neural pathways on a greater scale, they can effectively look for complex patterns and/or malformations.
An example of this is known as a “BCI”, or brain-computer interface. BCIs interpret brain signals to then control external devices, and have been used for individuals with neurological or physical disabilities. Artificial intelligence’s incorporation to BCI’s enhanced user and collection experience, erases the stress of inexperience learning models, and allows the focus to be on personal customization and comfort.
The incorporation of AI in BCI’s has also led to increased efficiency and precision in their data processing, meaning it can catalog information gathered at groundbreaking speeds compared to several years ago. Sorting out inessential data (oftentimes referring to excess brain-noise) and organizing the brain signals connected are just a few of the jobs that AI accomplishes for neurologists. Artificial intelligence gives people with neurological or physical disabilities opportunities for modern independence.
The brain is an intricate control center, and neuroscientists are a long way from understanding all there is to know about all of its systems. Applying AI in neurology has brought clarity to structures and functions in the brain that scientists were previously oblivious to.
In early November 2025, scientists used AI to analyze over 50,000 MRI scans, revealing a communication bridge between the left and right hemispheres of the brain for the first time ever. The function of AI in this study was in the analysis of the genetic architecture of the brain’s communication bridge, and how the genetic overlap of the structures correlate to other neurological or mental disorders, such as ADHD or bipolar disorder. This also warranted the creation of the first large-scale map of the corpus callosum, the fiber network connecting the halves of the brain. By observing the connection between the brain’s communication pathways and how they affect brain function, scientists have gained a deeper understanding of the link between mental health disorders and neuroscience.
Additionally, a wide spectrum of medical professionals have been using AI as an impartial viewpoint assessing patient treatment. For instance, neurologists can feed AI a patient’s medical files and ask questions on the best form of treatment, based on factors such as genetic history, medical images, and previous records. Using this information, AI can lay out various paths a patient’s treatment options, including medication recommendations, simulating end results, and estimating timeframes. AI’s ability to detect subtle abnormalities and genetic errors helps it detect patterns of disease early on, which could have otherwise been missed.
The use of artificial intelligence for diagnosis and treatment can raise ethical and credibility concerns, as it can misinterpret or hallucinate. Issues may also arise concerning confidentiality, reliability, and currency in dealing with AI-driven systems. Together, healthcare and AI are a collaborative effort, with trust being a slow-building portion of that relationship. Ultimately, decisions regarding treatment plans should be left up to medical professionals and their patients.
Artificial intelligence has become an integral component of neuroscience, and its capabilities will only continue to expand as it evolves. The abundance of studies and articles produced daily clearly indicate the progress underway in the realms of neuroimaging, neurological disorders, and medicine. Conflicts around factuality, privacy, and moral values bring perspective to debates revolving around AI use in healthcare. However, the advances made as a direct result of AI’s involvement in neurobiology tend to outweigh discourse to rid AI entirely. In the end, the benefits arising from AI in neuroscience will continue impacting diagnosis accuracy, growth in experimental research, and custom treatment plans.
Works Cited:
“The Evolution of AI in Healthcare” XSolis
Accessed: Nov 13 2025
“Revolutionizing Neurology: The Role of Artificial Intelligence in Advancing Diagnosis and Treatment” PMC
Accessed: Nov 11 2025
“AI Maps the Brain’s Hidden Bridge, Revealing Genetic Links to Mental Health” Neuroscience News
Accessed Nov 11 2025
