When someone in a family begins to forget familiar names, develops a tremor, or suddenly has trouble speaking after a stroke, questions arise quickly. What is happening inside the brain? Could this have been noticed earlier? And if it had been, could the outcome have been different? For a long time, neuroscience has tried to answer these questions by observing patients, studying brain scans, and linking symptoms to damaged areas of the brain. Today, a new tool is slowly changing this work. Artificial intelligence, often talked about in relation to machines or job loss, is becoming a helpful partner in brain research. It is not meant to replace doctors or scientists, but to help spot patterns that are too small or complex for the human eye to see. The human brain is extremely complex. Billions of nerve cells send signals to one another to control movement, memory, emotions, and thinking. Since the early 2000s, new tools in brain imaging, genetics, and behaviour research have created huge amounts of information. Much of this data is simply too large for traditional methods to handle. Artificial intelligence is useful here because it can sort through large datasets and find important signals that might otherwise be missed. Over the past decade, research groups at places such as the Mayo Clinic, the University of California San Francisco, USA, and the international Alzheimer's Disease Neuroimaging Initiative have shown that artificial intelligence can help detect early brain changes linked to Alzheimer's disease. Their work suggests that small changes in brain scans can appear years before clear memory problems begin. This creates opportunities for earlier care and better planning for patients and families. Similar progress has been seen in Parkinson's disease. Studies from research teams at University College London and King's College London, UK, published between 2018 and 2023, show that computer programmes can detect small changes in movement and brain structure before common symptoms like tremor and stiffness become obvious. Doctors involved in this work stress that the goal is earlier support and monitoring, not replacing medical decision making. Artificial intelligence is also helping researchers better understand how brain disorders differ from person to person. In recent years, scientists at Harvard Medical School and Stanford University, USA have shown that combining brain scans with sleep data, movement patterns, and medical records can help group patients into clearer subtypes. This approach supports more personalised care for conditions such as depression, epilepsy, and Parkinson's disease, recognising that each person's brain is unique. These advances are especially important for Nepal. According to the Global Burden of Disease 2021 study, stroke is one of the leading causes of death and long-term disability in the country. Mental health conditions, including depression and anxiety, are also increasing, especially among younger and working aged people. Nepal has fewer than seven neurologists per 100,000 people, and most specialists are based in cities. For many families in rural areas, reaching expert care can still take days. In this setting, artificial intelligence could offer practical help. Since around 2020, artificial intelligence tools used alongside telemedicine have been tested. This can help doctors read brain scans, spot early warning signs of stroke, and recognise patterns linked to Parkinson's disease or dementia. In district hospitals, where specialists are often unavailable, these tools could act as an extra layer of support. Pilot programmes in nearby countries, including India, between 2021 and 2024, suggest that artificial intelligence assisted imaging can improve decisions, especially in urgent stroke care. At the same time, caution is necessary. Public health experts at the World Health Organisation have warned in reports published since 2022 that technology alone cannot solve these problems. Artificial intelligence systems learn from data, and most brain research data still comes from Western countries. Without testing in local populations, these tools may not reflect Nepal's genetics, environment, or health care conditions. Clear rules, transparency, and active involvement of Nepali doctors and researchers are essential. Artificial intelligence should support medical judgment, not replace it. Perhaps, the most important lesson artificial intelligence offers neuroscience is not about technology, but about people. These systems show that the brain often sends quiet warning signs long before illness becomes clear. In Nepal, those signs are often missed because care comes too late or is out of reach. As people across Nepal and South Asia live longer, brain health will become an even greater public health concern in the years ahead. Investing now in neuroscience education, digital health systems, and regional research partnerships can help ensure that new tools truly benefit people. Artificial intelligence cannot heal the brain on its own, but when used carefully, it can help us understand it better. And understanding is often the first step toward better care, empathy, and lasting change. Pokharel is a Ph.D. candidate in Neuroscience and Neurological Disorders specializing in Parkinson's disease research at The University of Toledo, USA