Leading pharmacologist and nutrition research leader Professor Richard Head commenced as Deputy Vice Chancellor and Vice President Research and Innovation in March 2013. His substantive position is as Director of the Sansom Institute for Health Research which he commenced in August 2012.

Prior to his appointment at the Institute, Professor Head was Director of the CSIRO’s Preventative Health National Flagship (2002-2012) where he led a national research program to advance early detection and intervention of chronic diseases; some of his notable achievement in that role included establishing AIBL (the Australian Imaging, Biomarkers and Lifestyle Flagship study of ageing) and founding Australia’s largest research grouping into early detection of colorectal cancer.

Dr Simon Oldfield was appointed the first Chief of the newly formed Land Division (LD) in July 2013. Land Division brings together the science and technology capabilities of DSTO that are focused on delivering outcomes of particular relevance to the Land Domain of Defence. Key capabilities of the Division include Chemical, Biological and Radiological Defence, Systems Engineering, Materials for Personnel Protection, Modeling & Experimentation and a broad range of Human System sciences. Under Simon’s direction, Land Division provides dedicated support to the key Defence stakeholders in Land Capability delivering to programs including Army Modernisation, Future Combat Vehicle acquisition, Diggerworks for the Close Combatant, and CBR Defence.

The formation and nurturing of productive partnerships has been central to Simon’s approach to S&T leadership. Examples of productive relationships at the centre of Land Division’s program include: the CBR MOU with our international partners, the Diggerworks partnership with the ADF’s stakeholders in the Soldier Combat System, the Centre for Food Innovation with CSIRO and the University of Tasmania, and the Physical Employment Standards Centre for Expertise with the University of Wollongong.

Simon’s previous responsibility was as the Chief of the Human Protection and Performance Division (HPPD) which he led since its formation in January 2006.  Prior to the formation of HPPD, Simon led the Chemical, Biological, Radiological and Nuclear Defence Centre (CBRNDC) which managed DSTO’s CBR capabilities, the Defence Nutrition Laboratory at in Scottsdale, and a small Human Sciences capability.   

Simon has a PhD in Psychology from ANU and was a Senior Lecturer at DeakinUniversity and undertook a research fellowship at CambridgeUniversity in the UK before joining DSTO in 1992. His personal research covered areas including auditory perception and its applications to cockpit displays. In 1998 he was promoted to the position of Research Leader of Simulation and Human Factors in Air Operations Division.

jmanton@unimelb.edu.au

Professor Jonathan Manton holds a Distinguished Chair at the University of Melbourne with the title Future Generation Professor. He is also an Adjunct Professor in the Mathematical Sciences Institute at the Australian National University.

He received his Bachelor of Science (mathematics) and Bachelor of Engineering (electrical) degrees in 1995 and his Ph.D. degree in 1998, all from the University of Melbourne, Australia. From 1998 to 2004, he was with the Department of Electrical and Electronic Engineering at the University of Melbourne. During that time, he held a Postdoctoral Research Fellowship then subsequently a Queen Elizabeth II Fellowship, both from the Australian Research Council. In 2005 he became a full Professor in the Department of Information Engineering, Research School of Information Sciences and Engineering (RSISE) at the Australian National University. From July 2006 till May 2008, he was on secondment to the Australian Research Council as Executive Director, Mathematics, Information and Communication Sciences.  His traditional research interests range from pure mathematics (e.g. commutative algebra, algebraic geometry, differential geometry) to engineering (e.g. signal processing, wireless communications, systems theory). More recently, he has become interested in systems biology and systems neuroscience.

“Transdisciplinary Research Involving Systems Engineering and Computational Neuroscience --- Opportunities and Challenges

Transdisciplinary research is considerably more involved than collaborating with others across disciplines. Understanding the brain will require a true transdisciplinary approach with systems engineering as equally important as the biology.  In addition to sketching past history, including the Macy conferences, this talk will discuss the opportunities and challenges that lie ahead at the intersection of systems engineering and computational neuroscience.

janetw@itee.uq.edu.au

Janet Wiles holds a Ph.D. from the University of Sydney, and is Professor of Complex and Intelligent Systems at the University of Queensland. She recently completed a five-year ARC Special Research Initiative on Thinking Systems, leading a cross-disciplinary team studying fundamental issues in how information is transmitted, received, processed and understood in biological and artificial systems. Her research interests include complex systems biology, computational neuroscience, computational modeling methods, artificial intelligence and artificial life, language and cognition.

“Of Rats and Robots”

This talk will review recent results in the study of a bio-inspired robot called the iRat developed at the University of Queensland for research at the intersection of neurorobotics, neuroscience and embodied cognition. Biorobotics has the potential to provide an integrated understanding from neural systems to behaviour that is neither ethical nor technically feasible with living systems. Robots that can interact with animals in their natural environment open new possibilities for empirical studies that include temporal, spatial and social factors intrinsic to mammalian biology. Designing a robot that can interact with a rodent requires considerations that span a range of disciplines, starting with the initial safety and social interactions of both rat and robot. Bio-inspired robots are also useful for embodying neural systems. Multidisciplinary teams have developed spiking models of a range of neural systems used in navigation, including cell birth and maturation, the hippocampal circuit, head direction cells, and grid cells. Recent results include a spiking model that incorporates explicit temporal delays to study sequence learning. The talk will overview the current capabilities of the iRat and its neural models and laboratory behaviours.

steven.wiederman@adelaide.edu.au

Dr Wiederman is an interdisciplinary scientist and engineer with a research focus on electrophysiology, computational neuroscience and neuromorphic engineering. He received his Bachelor of Medical Science and Bachelor of Engineering at the University of Technology, Sydney (UTS) in 2005. He was awarded a Graduate Certificate in Education in 2007 and a PhD (Neuroscience) in 2009.

He is currently an ARC Senior Research Associate at the Adelaide Centre for Neuroscience Research, The University of Adelaide, working in the Visual Physiology laboratory with Associate Professor David O'Carroll. Dr Wiederman's research involves recording intracellularly from neurons in the invertebrate brain that underlie feature discrimination in background clutter and their competitive selection within multiple feature environments (i.e. selective attention). He develops models of neuronal processing for applications in robotics and neural prosthetics.

 “Biologically-inspired feature detection, selection and pursuit from a moving platform”

Consider the fast-flying dragonfly, an aerial predator rapidly capturing prey amidst a swarm of potential targets. This task requires 1) the discrimination of moving futures against complex, textured backgrounds, 2) the competitive selection of a single feature amongst distracting stimuli and 3) a pursuit algorithm that maintains feature discriminability whilst minimising flight duration. Even though many animals (including ourselves) can accomplish such 'feature selection and interaction', little is known about the neuronal mechanisms underlying these control systems. Here I describe recordings of the electrophysiological properties of neurons underlying such behaviour and how these recordings subserve computational models that we are currently translating into hardware for use in autonomous ground vehicles.   

rvpsgtech@gmail.com

A/Prof Vijayalakshmi has over 17 years of academic experience and currently holds the position of A/Professor, Department of Applied Mathematics and Computational Sciences at PSG College of Technology, India.  She received her Bachelor in Science (BSc), Masters of Computer Applications (MCA) and Master of Philosophy (MPhil) in Computer Science from Bharathiar University and PhD in Graph Mining Algorithms from Anna University.  Her research interest includes graph based data mining, especially in complex network systems, and social network analysis. Her research publications include about 15 journal and conference papers. She has been a reviewer in the Journal of Pattern Recognition Letters, Elsevier, and the International Journal of Knowledge Engineering and Soft Data Paradigms. She has also delivered special lectures on ‘Efficient Data Structures and Algorithms for Graph based Data Mining’, Database management systems, Problem solving and C programming, and Object oriented Programming in various workshops, conferences and faculty development programme. She has undergone research training in Cognitive Neuroengineering Laboratory (CNEL) in the acquisition and analysis of brain wave data for cognitive modelling, pattern identification and visualization using graph-theoretic approaches and has established a Computational Neuroscience Laboratory at PSG College of Technology in association with Prof. Nanda Nandagopal, UniSA. 

"Computational Techniques for Characterizing Cognition using EEG Data - New Approaches"

Identifying the integrative aspects of brain structure and function, specifically how the connections and interactions among neuronal elements (neurons, brain regions) result in cognition and behaviour, is one of the last great frontiers for scientific research. Unravelling the activity of the brain’s billions of neurons and how they combine to form functional networks, has been and remains restricted by both technological and ethical constraints, thus researchers are now increasingly turning to sophisticated data search techniques such as complex network clustering and graph mining algorithms to further delve into the hidden workings of the human mind. By combining such techniques with more traditional inferential statistics and then applying these to multi-channel Electroencephalography (EEG) data, it is believed that it is possible to both identify and accurately describe hidden patterns and correlations in functional brain networks which would otherwise remain undetected.  This talk provides an overview of the application of such approaches to EEG data, bringing together a variety of techniques including complex network analysis, Pearson's correlation coefficient, coherence, mutual information, approximate entropy, computer visualization and signal processing techniques.

bernie.cocks@unisa.edu.au

Ms. Cocks is a Research Assistant to Prof. Nanda Nandagopal and Lab Manager/Cognitive Psychologist for the UniSA Cognitive Neuroengineering Laboratory (CNEL).  She received a Bachelor of Psychology (1st Class Hons) from the University of New England in 2009 (Psychology/Linguistics) and is nearing completion of her PhD on the neural substrates of spoken language perception.  Prior to returning to study Bernie worked extensively in electronic media (radio and television) in a variety of roles including on-air, production, research and marketing, and received a national industry award for copywriting in 2001. She also holds formal professional writing qualifications, and has extensive experience in writing and editing a variety of genres. 

 “Measuring cognitive load: Can a last straw really break a camel’s back?”

Reductionism lies at the heart of science, yet this pre-occupation with the fine print of cognition may mean that cognitive science is missing the bigger picture.  To this end, the current pilot study sought to identify if interactions between lower and higher order cognitive and perceptual processes create bottle-necks of neural processing which can be directly associated with human performance degradation.  More practically, it sought to establish cortical locations where cognitive load could be objectively dissociated from cognitive overload through the use of EEG. Graph analysis and pattern identification identified three such areas which, as predicted, were considered likely to reflect anterior cingulate cortex (ACC) activity.  On-going research is now examining degrees of cognitive load to more clearly delineate where load stops and overload begins and to identify the most accurate metric for measuring such load.  It is envisaged that the results of this on-going research will lay the foundations for developing simple devices capable of measuring cognitive load in real time.

naga.dasari@mymail.unisa.edu.au

Naga Dasari is a PhD candidate with the UniSA CNEL investigating ways to visualise real-time EEG data.  Before moving to Adelaide Naga completed a Bachelor of Technology (Electronics and Communication Engineering) and Master of Technology (Digital Systems and Computer Electronics) in India and taught extensively as an academic staff member.  He has previously worked as a software engineer.  His current research interests include cognitive neuroengineering and computer networks which have led, thus far, to the publication of one peer reviewed journal article and eight conference papers.

“Visualization of Complex Functional Brain Networks during Cognitive Load”

Analysis of multi-channel EEG data to visualize functional brain networks and identify the cognitive activity has been a challenge to the research community. High temporal resolution data collected by electroencephalograph (EEG) has enormous amounts of hidden information about neuronal transactions in the underlying brain network.  Statistical measures such as magnitude squared coherence and Pearson product moment correlation coefficient have been used to analyse the EEG data to identify the cognitive activity and visualize the functional brain networks.  These results have been compared with eyes open condition. We would be investigating nonlinear statistical measures for underlying neuronal interactions better.

nabaraj.dahal@unisa.edu.au

Nabaraj Dahal is a PhD candidate with the UniSA CNEL using EEG to investigate the computational modelling of cognitive functions in simulated driving environments.  Nab also received his Masters in Telecommunication Engineering from UniSA’s  Institute of Telecommunication Research in 2008, based upon his minor thesis “Location Tracking System Using Sensor Nodes for Aged-Care Application”.  Prior to this he received his Bachelors in Electronics and Communication from Tribhuwan University, Kathmandu, Nepal in 2005. Nab’s current research interests include Cognition, Brain and Engineering; Augmented   Cognition; Computational   Neuroscience; and Pattern Recognition Techniques. 

“Modeling of Cognitive Functions using EEG”

There is an increased interest in the field of cognitive modelling based upon the study of behavioural data such as analysis of latency and error rate. The advances in brain imaging techniques such as Electroencephalogram (EEG), Magneto encephalogram (MEG), functional Magnetic Resonance Imaging (fMRI) along with robust and advanced signal analysis and computational techniques during the last three decades have enabled the emergence of new cognitive modelling approaches.

Accurately identifying cognitive activity from multi-channel EEG data continues to be a challenging task for cognition researchers. Although brain impairments such as epilepsy and ADHD tend to display relatively easy to identify EEG data features, delineating clear patterns of normal cognitive activity within the healthy brain has not yet been satisfactorily achieved. In the current study, the EEG features associated with distraction have been examined. Continuous EEG has been recorded from eight participants as they performed normal and auditory-distraction virtual driving.  All pole analysis using the autoregressive model of the EEG data in both conditions has been then carried out, producing interesting and anatomically feasible patterns in temporal lobe regions. Event related synchronization and desynchronization patterns have also been observed at specific brain locations within the alpha, beta and gamma band frequencies. These results clearly distinguish audio-distracted driving from normal driving, suggesting that the techniques used here may provide a new analysis method for brain computer interface research.

 johnson.thie@sydney.edu.au

Dr Johnson Thie is currently a professional officer at the School of Electrical & Information Engineering at the University of Sydney. His role includes designing experiments and materials for teaching laboratories and supporting teaching and research in biomedical engineering and embedded systems. His previous role includes research fellow at The Australian School of Advanced Medicine, Macquarie University and research scientist at Emotiv.  He received his Bachelor of Engineering and Masters of Biomedical Engineering from the University of New South Wales in 1999 and PhD (also University of New South Wales) in 2003.  Dr Thie has also worked as an RA for CSIRO Telecommunications and Industrial Physics. His current areas of interest include: Biomedical electronics, Biological signal processing (EEG, VEP) of human and rodents, Wireless applications for medical instruments, Machine learning applications for biomedical signals.

“A wireless marker system to enable evoked potential recordings using a wireless EEG system (EPOC) and a portable computer”

As wireless EEG devices have become affordable at low cost, have a small form factor and quick setup time, they can be deployed at universities and schools for teaching purposes. However they have not been applied for evoked potential recording since they lack an option to receive stimulus markers. Meanwhile evoked potential recording is required for functional assessment of the sensory systems such as auditory and visual. This presentation describes a wireless system that embeds information about the stimulus in the EEG channels. The transmitter unit is connected to the stimulus device to detect the stimulus and transmit the stimulus information to the receiver unit. The receiver unit attached to two of the EEG electrodes decodes the information and generates a pulse across the electrodes. The pulse width conveys the information about the stimulus. Hence the stimuli are synchronised with the EEG data allowing users to evaluate the evoked potentials in the offline processing. The wireless marker system was verified with audio stimuli consisting of 1000Hz and 1200Hz tones and reliably generated pulses with 100ms and 200ms width respectively. The delay between the onset of the tone and the onset of the pulse was 19.3 +/- 0.1ms. Since the variability of the delay was under 1ms and so negligible, the evoked potentials could be evaluated reliably. The evoked potential could be shifted back by 19.3ms to compensate for the delay. The system was also verified with a black-and-white checkerboard pattern stimuli and reliably generated pulses with 100ms width when the pattern reversed. The delay between the onset of the reversal and the onset of the pulse was 6.4ms. Similarly the variability of the delay was negligible.

Rick.VanDerZwan@scu.edu.au

A/Prof. Rick van der Zwan, a behavioural scientist working to understand the neural mechanisms mediating our perceptions of others and of ourselves. Rick leads research projects in behavioural neuroscience, in applied brain sciences, and in healthy aging. He has an international reputation as a behavioural researcher having authored more than 60 scholarly articles and numerous other reports and consultancies. He works also as Director of Research in Coffs Harbour at Southern Cross University. He speaks every week with regional ABC radio to make contemporary research and mental health issues accessible to the general public and to help to popularise and demystify the neurosciences and the brain.

Rick obtained a BSc from the University of Sydney. Majoring in Psychology and Anatomy, he went on to achieve First Class Honours in Psychology. Rick then completed his PhD, also at the University of Sydney. His doctoral research led to his winning a postdoctoral appointment in the Department of Neurology at the University Hospital in Zurich. In 1995 Rick was invited to apply for appointment to the Department of Psychology at the University of Sydney. In 2001 he moved to James Cook University. Rick joined Southern Cross University in 2003 to lead the development of the research programme and set up the University's first research labs in Coffs Harbour. In addition to his work as Director of Research Rick is also Director of the Regional Initiative for Social Innovation Research, also based in Coffs Harbour.

“Human Social-Perceptual Mechanisms, Ambiguity, and Non-verbal Signalling –neural correlates and implications.”

Perceptual systems are for problem solving. They are designed to collect sensory information, to interpret that information, and then to guide actions – the so-called perception-action loop (Gibson 1979). Some interpretation and some action processes are available for conscious inspection. Many are not. Those unconscious processes and their effects on behaviours will be described here. So too will intersensory interactions between processes, particularly in terms of strategies for reducing perceptual ambiguity. In particular, and as the popular media likes to point out, we evaluate others very quickly; a process Ambady & Rosenthal describe as “thin slicing” (1992). Perceptions arising during thin slicing affect behaviours and those effects can be on going. Critical features for manipulating perceptions will be discussed. So to will implications for tool and prosthetic use.

deanrf@unimelb.edu.au

Dr Freestone completed his honours degree in electronic engineering from La Trobe University, Melbourne in 2007. In 2012 he graduated from his PhD studies at the University of Melbourne, where he won the Chancellor's prize for thesis excellence for his research that focused on prediction and control of epileptic seizures. He has continued his research in this area at the University of Melbourne in his post-doc working in the NeuroEngineering Laboratory with projects in collaboration with the Bionics Institute, St. Vincent's Hospital Melbourne and Medtronic Inc. (USA).

“Data-driven Mesoscopic Neural Modelling”

Abstract: This presentation will discuss methods for developing subject-specific mesoscopic neural models. The ability to create subject-specific models will enable estimation of normally hidden aspects of physiology. Imaging physiological parameters will lead to a greater understanding of diseases and provide new targets for novel therapies. The model-data fusion framework in this presentation is based on nonlinear Kalman filtering. In particular, we will demonstrate estimation accuracy using synthetic data before showing results from real intracranial EEG data.

tony.vladusic@unisa.edu.au

Dr Tony Vladusich is a Research Fellow in the Institute for Telecommunications Research at the University of South Australia, Adelaide. Since obtaining his Ph.D. in neuroscience at The Australian National University in 2004, he has conducted both experimental and theoretical research on visual surface perception in Europe, the US and Australia. His current research program involves the development of a general theory of visual surface perception, with applications in computational vision and computer graphics software.

“Gamut relativity:  An innovative computational approach to visual surface perception”

I have recently introduced an innovative mathematical theory of visual surface perception in human vision. The theory, termed gamut relativity, overturns the classical assumption that surface lightness, transparency and gloss constitute perceptual dimensions corresponding to the physical dimensions of diffuse reflectance, transmittance, and specular reflectance, respectively. The theory instead shows how lightness, transparency and gloss are built directly into the fabric of the visual system's representation of surface and illumination properties. Gamut relativity suggests novel solutions to many outstanding problems in the study of visual surface perception, overturns some deeply held assumptions about how the brain represents the physical world, sheds new light on a central organisational feature of the visual brain, and suggests new design constraints for engineered vision systems.

i.hettiarachchi@research.deakin.edu.au

Imali Hettiarachchi is a PhD candidate with the Centre for Intelligent Systems Research (CISR), Deakin University, Australia.  She received a Bachelor of Science in Electrical Engineering with a 1st Class Honours in 2004 and a Master of Philosophy in Electrical Engineering in 2009 from the University of Moratuwa, Sri Lanka. Before starting the PhD she was a lecturer at the Department of Electrical Engineering, University of Moratuwa and a Visiting Lecturer at the Institute of National Diploma in Technology and the Institute of Engineers, Sri Lanka. Her current research interests include Cognitive Neuroscience with a focus on information processing of the brain using event related potentials.

“ Source level Information flow Analysis using Event Related Potential (ERP) data”

Currently, ERP analysis is one of the most widely used methods in cognitive neuroscience research to study the physiological correlates of sensory, perceptual and cognitive activity associated with processing information. The information flow or dynamic effective connectivity analysis applied to ERP data is a vital technique to understand higher cognitive processing under different events.  Among other tools used in effective connectivity analysis, Granger Causality (GC) has found a prominent place. The GC analysis, based on strictly causal multivariate autoregressive (MVAR) models does not account for the instantaneous interactions among the sources. If instantaneous interactions are present, GC-based on strictly causal MVAR will lead to erroneous conclusions on the underlying information flow.  This presentation will focus on the use of extended MVAR (eMVAR) models for GC-based information flow analysis of ERP data. The eMAR model accounts for instantaneous interactions, by including the zero-lag component to the conventional MVAR model. The use of different adaptive estimation procedures for eMVAR model identification will be discussed and the information flow during a visual categorisation task is demonstrated.

Nanda.nandagopal@unisa.edu.au

Professor Nandagopal brings to bear a unique combination of leadership and management in Strategic Science, as well as experience across a broad range of disciplines. His career in research spans three continents (Asia [India], North America and Australia) covering a wide range of areas in Science and Engineering including Defence Science, Electronics, Biomedical Engineering and Sensor Signal and Information Processing. He has significant experience at systems level, especially in high level architectures, mission and combat systems, autonomous systems. He has developed a passion for Systems and the system of Systems research.  Professor Nandagopal joined UniSA after extensive experience with the Australian Department of Defence. He has been with the Defence Science and Technology Organisation (DSTO) for over 23 years, during which time he held various Senior Executive positions including the position of Deputy Chief Defence Scientist. He has also served on various Defence Committees in Canberra. Professor Nandagopal has taken up the position of Dean International and Chair Defence Systems at UniSA after leaving DSTO in August 2012. Professor Nandagopal has held academic positions at the University of Adelaide, McMaster University (Canada) and the University of Melbourne. He has also held Adjunct positions at the University of Adelaide and the Australian National University (ANU).