Reverse engineering the brain
The brain creates a coherent interpretation of the external world based on input from its sensory system. Yet data from the senses are unreliable and confused. How does the brain synthesise its percepts? Recent psychophysical experiments indicate that humans perform near-optimal Bayesian Inference in a wide variety of cognitive tasks, such as motion perception, decision making, or motor control. In Bayesian Inference – a powerful mathematical framework – the likelihood of a particular state of the world being true is calculated based not only on sensory input signals but also on prior knowledge about the external world that the system has already learned. The Bayesian framework has also been shown to be ideal for fusing information from different sensory modalities and is robust to errors in individual sensors. If we could understand, in an engineering sense, how the brain accomplishes this, then we could apply this knowledge to the electronic sensors we build.
Neurones in the brain use action potentials (spikes) to communicate with each other. From calculations based on the energy consumption of the brain, it has been estimated that, on average, each neurone fires only one spike per second, although individual sensory neurones can fire close to 1000 spikes per second. The question of how Bayesian Inference can be implemented using spiking neurones with such slow communication rates is intriguing. In the past five years a dozen of papers have been published showing glimpses of how this could be achieved. Taking a similar approach to electronic sensor networks would minimise the bandwidth needed for communication and therefore minimise power consumption.
The delay between the firing of a spike by one neurone to the reception of that spike by another neurone is typically in the range of one to forty milliseconds. These propagation delays have been largely ignored by both the neurophysiology and the neural computation communities. It has only very recently been recognised that the incorporation of delays enables a whole new class of computational systems, termed reservoir computing. Reservoir computing underlies quite possibly the computational architecture by which the brain performs Bayesian Inference.
To read out such reservoirs of neurones, propagation delays from neurones in the reservoir to the read-out neurone have to be precisely tuned. Some very limited evidence from neurophysiology for adaptive delays has begun to emerge, but in general delay adaptation in the brain has hardly been studied. The demonstration of a learning rule for adaptive delays in the brain would constitute a break-through discovery in neuroscience.
At BENS we study the neurophysiological and computational neuroscience implications of the Bayesian Inference framework and aim to discover how it is implemented in the brain.
"Read this aloud and your inner ear, by itself, will be carrying out at least the equivalent of a billion floating-point operations per second, about the workload of a typical game console. The inner ear together with the brain can distinguish sounds that have intensities ranging over 120 decibels, from the roar of a jet engine to the rustle of a leaf, and it can pick out one conversation from among dozens in a crowded room. It is a feat no artificial system comes close to matching. But what's truly amazing is the neural system's efficiency. Consuming about 50 watts, that game console throws off enough heat to bake a cookie, whereas the inner ear uses just 14 microwatts and could run for 15 years on one AA battery. If engineers could borrow nature's tricks, maybe they could build faster, better and smaller devices that don't literally burn holes in our pockets." – R. Sarpeshkar, IEEE Spectrum, May 2006
Efficient, parallel, low-power computation is a hallmark of brain computation and the goal of neuromorphic engineering. The focus of this project is to design, implement and test the most accurate, electronic, very large scale integrated (VLSI) circuit model of the cochlea and its associated auditory signal processing. In creating this electronic model, we will develop new schemes for parallel, low-power, auditory signal processing that would be impossible to study in any other way. The cochlea model will accurately simulate the fluid dynamic properties of the biological cochlea and will now include active gain control and active quality factor control of the cochlea partition. It will also implement the processing performed by the sensory transducers and the spiking neurons of the auditory nerve. We will design, implement, and test a spiking neuron chip capable of simulating the response properties of many of the types found in biology and its parameters will be programmable.
Neuromorphic Engineering now is capable of interfacing all neuromorphic circuits that adhere to the, now standard, Address Event Representation protocol to each other or a computer. This will not only include our circuits, but also those designed by other neuromorphic engineers. The interface is furthermore programmable, enabling it to perform computation on the spike trains as they pass through the interface from one chip to another. This tool enables advanced spike based signal processing systems. We will develop models and circuits that demonstrate the advantages of spike based processing over conventional analogue and digital signal processing for certain applications. We will use the auditory pathway as our inspiration for these systems.
We are currently developing several electronic devices for medical purposes. Some of these devices measure intrinsic body properties such as blood flow and respiration. Other devices actively interact with the user with the aim of improving human functions such as balance and sensory perception. Some examples are given below.
The ability to accurately quantify human body functions is directly linked to our ability to diagnose and treat disease, ultimately extending our life expectancy. While we have made great advances with technologies such as X-Ray, CT, MRI etc. they are still limited. It is still a normal requirement that a patient goes to hospital where the medical device and personnel are located and be placed in a machine or at least be in a fixed pose when the measurement is taken. Ideally, medical devices would conform to the body, would move as the body moves and be wearable 24/7 if required. It is with these ideals in mind that we developed some exciting new technologies.
One of these devices, VitalCore, is essentially an instrumented t-shirt embedded with electroresistive polymer bands, polarized by a very low and safe DC current. When paired with a bespoke amplifier it can translate minute changes in the expansion/contraction of the body into a recordable electrical signal. Not only can this be used to visualize the movement of the chest and abdomen during breathing, it is sensitive enough to capture the expansion/contraction of heart. Importantly, all of these measurements are made in millilitres, which allows comparative measurement to be made over time and uniquely allows direct measurement of cardiac output without the inserting a catheter into the heart. Another technology, HeMo, applies these bands to the arm or leg. In a similar manner we may see blood flow due to general shift in blood e.g. when we stand up, blood wells in our legs. We can also see the arterial flow into our limbs and watch as it changes during and following exercise.
To complete the health assessment of the cardiovascular system, and to fit it into the paradigm of wearable and unobtrusive monitoring, we 'rethought' electrocardiography (ECG). Since its introduction into clinical practice, ECG has been recognised as one of the principal tools for the screening and diagnosis of cardiovascular diseases. However, despite its clear benefits, clinicians and engineers alike have largely ignored an underlying limitation that has existed since its inception. ECG makes an assumption that the torso is a sphere and that precordial leads are equally related to a singular "virtual" ground at the centre of this sphere. Clearly neither assumption is true, a fact that impacts on the ability to interpret the ECG signals. A new technology, True-Unipolar ECG, developed at BENS seeks to directly address these assumptions, fixing a problem that has existed for over 100 years. This system allows a more precise characterisation of the phenomena behind the signals, reducing the uncertainty of interpretation in critical scenarios. Currently we are extending this research to a number of cardiac conditions with the cooperation of cardiologists at Campbelltown, Camden and Westmead Hospitals in NSW.
Advanced Electrical impedance Tomography (EIT)
The ability to correctly diagnose diseases and illnesses particularly in emergency scenarios rely in the correct interpretation of symptoms and/or direct measurement of physiological signals. Unfortunately, a number of illnesses have common traits and without the aid of suitable medical diagnostics, it is difficult to determine what problem exists and decide on the best treatment. For example, there are two different kinds of stroke or brain ischemia. One is linked to bleeding inside the brain while the other relates to an obstructed vessel. Correct and prompt diagnosis leads to the prescription of the correct drugs that may save the patients life and improve recovery outcomes. However, imaging devices like MRI or CT are not always available when needed and often too slow for this purpose. This research uses a newly developed advance tomography scanner that creates images of the brain using electrodes placed upon the patient skull. This can be performed at the patient bed in a timely manner and will be capable of distinguish between the two types of ischemia. This device uses the principle of the electrical impedance variations of tissues that are particularly pronounced at interfaces such as the brain-blood barrier and organ boundaries. Impedance changes are measured through the detection of the faint voltage drops elicited by injection of safe small currents into the body and transformed into surfaces with a technique similar to standard computer tomography.
Restoring Neural Function
There are more than 100 different conditions that can lead to nerve damage. These include physical trauma, kidney disorders, liver disease, vitamin deficiencies, alcoholism, vascular damage, blood diseases, cancers and benign tumors, toxins, viruses, bacterial diseases and other inherited forms. Typically these conditions will lead to partial damage to nerves, reducing the feeling of touch, protective sensation and our ability to balance among many other detrimental effects. Currently, there is no treatment available that can restore these lost functions.
In one application we use externally applied subsensory electrical noise stimulation to amplify residual neural signals. To date we have shown that our technology improves sensation in healthy younger adults, older adults with clinically significant loss of sensory perception and patients with diabetic neuropathy. We have seen, from human nerve recordings, how our device changes the existing neural code, amplifying it without changing the meaning of the code. This technology has also been used to stimulate the otoliths of older adults and individuals suffering from traumatic brain injury producing enhanced vestibular function and balance.
This research is now expanding in three directions. First, we are continuing our efforts to establish the most effective means of delivering this stimulus for maximum benefit in the context of specific conditions. Secondly, the number of patient cohorts that could potentially use this technology is very large. As a result we are extending this research to these other groups to determine if they may also benefit. Finally, we need to go beyond the laboratory and clinical experiments and establish the real world benefits of this technology. To the end we are now planning long-term use trials and determining the benefits to gait stability and driving performance.
If the nerve is instead "pinched" or severed, it will often require surgical intervention e.g. a nerve graft to reconnect the nerve. However, the outcome from surgical nerve restoration is too often poor and recovery times are measured in years. We have developed a fully flexible biocompatible nerve graft sheet that avoids the need of sutures that alone promotes re-innervation. We are also investigating the use of a bespoke version with inbuilt electrodes that aims to simultaneously stimulate and preserve the distal conductive pathway (reducing muscle wasting) and promote nerve cell regrowth via active targeted stimulation. This technology is now being used in animal models to test the basic hypotheses.
Open Source Devices
The development of biomedical devices carries often requires the development of a safe medical grade data acquisition system. To save fellow researchers time and effort, we have developed an open source BIOADC that can work either stand-alone (saving data onto a memory card) or connected to a standard PC via a medical grade isolated embedded USB 2.0 connection. Our latest implementation of the device includes an ultra-high impedance front-end and is fully wearable when assembled on a flexible printed circuit board.
Current Postgraduate Research Projects
Please see our current PhD projects page for a list of projects.