Scientists from the National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, and the Indian Institute of Technology (IIT) Bhubaneswar have discovered a novel approach to studying schizophrenia by analyzing how brain signals evolve over time. Leveraging principles of Chaos Theory, the research provides new insights into the progression of the disorder and how treatments may affect patients differently.
Understanding Schizophrenia Through Brain Dynamics
Schizophrenia is one of the most severe mental health disorders, affecting approximately 15% of the global population. It typically emerges in late adolescence or early adulthood, often disrupting the most productive years of life. The scientists emphasize that comprehending brain function in such conditions is essential for developing more effective treatments.
Methodology and Tools
The team employed functional MRI (fMRI), a brain imaging technique that tracks changes in blood oxygen levels to map brain activity. They concentrated on resting-state signals, which capture brain activity when a person is not engaged in any specific task, to understand how different brain regions communicate in schizophrenia patients.
To analyze these signals, the researchers designed a system based on Chaos Theory, treating schizophrenia as a dynamical disease where brain activity, behavior, and thought processes exhibit chaotic, non-linear patterns instead of ordered ones. This system enables tracking of how brain activity changes over time and how it responds to treatments such as medication, transcranial magnetic stimulation (TMS), and electroconvulsive therapy (ECT).
Key Innovation: Chaotic Dynamics Marker
A significant outcome of the study is the development of the Chaotic Dynamics Marker (CDM). This tool allows doctors to measure patient recovery and guide treatment decisions. The study also revealed that certain treatments may have different effects if applied beyond specific thresholds, underscoring the need for personalized therapeutic approaches, according to Brahma Deo, MGM Chair Professor at IIT Bhubaneswar.
Visual Pattern and Portable Device
Researchers from IIT and NIMHANS have also created a unique model named U-KBBC, which generates a visual pattern called 'Sudarshan'. This pattern changes shape based on a patient's brain signals, aiding in tracking disease progression and recovery. The variations produce patient-specific markers, including CDM and a synchronization measure (SyncSZ), enabling detailed monitoring of disease assessment, progression, and recovery.
Additionally, IIT has developed a portable electronic device named Chinmoy, embedded with the U-KBBC system, enhancing its potential for real-world clinical applications. A joint patent has been filed by NIMHANS Bengaluru and IIT Bhubaneswar to protect this innovation. The researchers aim to expand this work across medical institutions.
The study team includes Urvakhsh Meherwan Mehta from NIMHANS, and IIT Bhubaneswar professors Kousik Samanta, Barathram Ramkumar, PhD research scholar Chinmoy Raj Hota, and Brahma Deo.
