Associate Professor Andrew Zalesky

While medical scientists can view a patient’s neural circuitry using MRI technology, accurately identifying faulty circuits is challenging due to the sheer size and complexity of brain networks.

To solve this problem, Professor Andrew Zalesky, an electrical engineer, applied his expertise in transmission networks to develop an innovative tool: a network-based statistic (NBS) that would enable medical scientists to accurately and rapidly pinpoint the location of damaged nerve fibres in patients.

NBS is an internationally recognised and widely used tool that allows medical scientists to pinpoint the location of faulty brain circuits.

The innovation translates principles that govern cascading failures in high-voltage power grids to brain networks.

This establishes a fundamental cross-disciplinary link between fault propagation in engineered and biological networks.

In power networks, when one substation fails, its load shifts to nearby substations, which potentially causes those substations to become overloaded and fail. This failure process can cascade through the network until the network collapses.

Zalesky established that neural circuit failures in diseased brain networks often cascade in the same way.

He capitalised on this discovery by developing an innovative tool to identify damaged circuitry in a patient’s brain network.

“The tool that I have developed provides medical scientists with a new capability to accurately identify faulty circuits from a patient’s brain scan,” he said.

“My tool is a necessary capability to enable treatments that specifically target diseased brain circuits. A clinical trial is underway in which my tool is being used to identify brain targets for a novel trans-cranial magnetic stimulation therapy for obsessive-compulsive disorder.”