Chennai: Data from the neurophysiological test, electroencephalography (EEG), used to measure and record the brain’s electrical activity, can predict if treatment such as stimulation or anti-depression medication given to a patient with depression has an effect in the first week.The early prediction could help patients access the right treatment method quickly, researchers from the IIT Madras (IIT-M) said.IIT-M scientists collaborated with scientists at Czech Academy of Sciences to study brain wave data (EEG) from 176 people with serious depression. Combining EEG with advanced machine learning, scientists looked for measurable signals or characteristics, such as electrical activity patterns or chemical levels, that indicate normal brain function in presence of psychiatric conditions in first week of taking antidepressants and used computers to find patterns.They found that subtle shifts in brain activity captured in these initial days could offer a crucial early signal, potentially sparing patients weeks of ineffective therapy and accelerating treatment outcomes. A machine learning algorithm achieved accuracy of 73% in identifying patients who responded to treatment based on early EEG changes.Their findings, published in the peer-reviewed journal Biomedical Signal Processing and Control, point to the potential of EEG as a non-invasive tool for personalised psychiatry. “Now, determining right antidepressant involves a period of trial and error, lasting several weeks,” said IIT-M assistant professor Dr Aditi Kathpalia from department of applied mechanics and biomedical engineering, who was a part of the study.“This can be emotionally taxing and could delay relief for patients. Our study suggests that these early brain scans might show who will benefit from the medication and who won’t. This ability could revolutionise clinical practice, allowing for quicker adjustments to treatment and a more targeted approach to mental healthcare,” she said.More research is needed with larger groups, but the study offers hope for a future where doctors can use technology to quickly figure out best way to help each person struggling with depression, she said.