NeuroEngineering Research Lab
Approximately 1% of the world’s population (50 million people) suffers from epilepsy, with two thirds of those having recurring symptoms.
Epilepsy is a neurological disorder where seizures occur randomly, caused by chemically and/or electrically driven over-excitation in populations of neurons (brain cells). These seizures can impair consciousness in many ways (the most commonly known being convulsions) depending on the part of the brain that is affected. In any case their apparent randomness can significantly impair the quality of life of sufferers.
While there are many drugs and some surgeries that can be used to control epileptic seizures, 25% of epileptics cannot be treated sufficiently by any available therapy. Moreover, the exact cause of epileptic seizures in the brain is not well understood.
Our research goal is to understand the underlying causes of epilepsy from a mathematical standpoint, where interactions/signalling between neurons are studied. Mathematical modelling, signal processing and physiological experiments are all important tools to help us do this.
In the long term we want to use this understanding to develop technology that can detect, predict and intervene the generation of epileptic seizures. A physical device could then be used to deliver therapy in the form of fast acting drugs, electrical stimulus, or simply as a warning mechanism.
Advanced epileptic seizure warning methods
Researchers: David Grayden, Anthony Burkitt, Levin Kuhlmann
This project will develop epileptic seizure prediction methods, warning patients of the likelihood of an impending seizure, so that precautionary measures can be taken. Seizure prediction will be of great clinical significance as it will improve the lives of 33% of epileptic patients who have drug-resistant epilepsy, by warning of impending seizures and potentially allowing acute therapies to prevent seizures, such as electrical stimulation of the brain or targeted drug delivery.
We have a unique opportunity as a result of the first and only clinical trial of an implantable intracranial EEG monitoring system and seizure predictor developed by NeuroVista Corporation. This trial was completed in Melbourne with CI Cook as a lead investigator. Patients were implanted with the system for periods of up to 2.5 years, providing unprecedented amounts of EEG data per individual. The large amount of data means we can robustly evaluate new and existing seizure prediction methods, and quantify the effects of the diurnal cycle and EEG statistics on seizure prediction. This has not been done before.
The NeuroVista trials showed that seizure prediction is possible and useful, but further research is needed for it to work for everyone.
Our goals are:
1. Evaluate established seizure prediction methods using the unique NeuroVista dataset.
2. Develop new features to better discriminate patient-specific seizure-related time periods.
3. Use the diurnal cycle to improve seizure prediction algorithms.
4. Use iEEG statistics to better quantify long-term epilepsy changes relevant to seizure prediction.
This project will develop robust seizure prediction methods, which will have a resounding impact on the management of drug-refractory epilepsy. Our prediction methods will provide seizure warnings that will greatly reduce the anxiety and stress linked to the uncertainty of when a seizure will occur and greatly enhance the quality of life of patients.
Anticipation of epileptic seizures using electrical probing of the cortex
Researchers: David Grayden, Dean Freestone, Anthony Burkitt, Alan Lai
Epilepsy is a chronic disease of the brain that affects 1-2% of people. Its defining characteristic is recurrent seizures, carrying a risk of injury, brain damage or death. Anti-epileptic drugs are the mainstay of treatment; despite this 1/3 of focal epilepsy patients have uncontrolled seizures. For these people, seizure onset is unpredictable, severely impairing quality of life.
Although seizure occurrence appears to be random, there is evidence that cortical excitability increases prior to attacks. Tracking cortical excitability is challenging. The field of seizure prediction has developed considerably over the last 30 years, yet this important problem is unsolved. We have developed an active strategy to monitor cortical excitability by measuring responses to low-intensity electrical stimulation. This approach is a paradigm shift from conventional passive techniques with the potential to lead to clinically relevant outcomes such as an implantable therapeutic device.
Data is obtained from St. Vincent’s hospitals. The standard preparation process for epilepsy related surgery involves electrode implantation directly on the brain to localise epileptic and functional tissue. These electrodes present a rare opportunity to stimulate and record from the human brain.
Our novel approach overcomes problems with the existing theory for seizure prediction. By actively determining input-output relationships, we have a direct measure of the brain’s excitability compared to passive observations. This provides the opportunity to track excitability.
Optimisation of signal processing and electrical stimulation algorithms for the abatement of epileptic seizures
Researchers: David Grayden, Dragan Nesic, Dean Freestone, Anthony Burkitt
This research will address the complex problem of the interactions between electrical stimuli and excitable neural tissue. Electrical stimulation is finding increasing acceptance as a novel means of providing therapeutic benefit across a wide range of neurological disorders. Despite this increase in application, the understanding of the ways in which electrical stimulation may convey therapeutic benefit is limited. Aspects of computational neuroscience will be employed in order to better characterise the effect that electrical stimuli have when applied to computational models of neural circuits. A greater understanding of these interactions may aid the future development of implant technologies across a broad range of diseases.
Professor David Grayden
T: +61 3 8344 5234