Research in the Cognitive Neural Systems Lab is focused on measuring and characterizing perceptual and cognitive brain signals that relate to behavior. We are particularly interested in linking non-invasively recorded electrical brain signals (EEG) in humans to specific neural computations involved in perception, attention and decision making.
In our research we use psychophysics, electrophysiology, functional imaging and computational modeling to understand the mechanisms by which the brain makes simple decisions. Major questions we are pursuing include how value, prior information, urgency, perceptual ambiguity, temporal uncertainty and competition among information sources are accounted for in the decision making process through adaptive changes in sensory, decision and motor signals, and selective attention.
Our focus is on paradigm development and basic research findings, but we continually deploy our paradigms and dependent measures to studies of neurological and psychiatric disorders through several active clinical collaborations.
Biomedical Engineering
Biomedical Engineering involves the application of engineering principles and methods to problems in medicine and healthcare. Through the application of engineering techniques we can gain a greater understanding of the human body, from the single cell up to the system level. Sophisticated engineering methods can be used to extract information from biological signals that
help understand healthy physiological systems and the changes that occur in disease, thereby improving early diagnosis and intervention strategies.
Electronic and Electrical engineering is also fundamental to the development of new technologies that can interact with the human body including neuromodulation therapies based on electrical stimulation of the nervous and cardiovascular systems, neuroprostheses and wireless monitoring of physiological signals. Advancements in communication systems and sensor technologies are opening up new ways of monitoring and interpreting patient data.
Biomedical Engineering has long been associated with the School of Electrical & Electronic Engineering in UCD. Current areas of Biomedical Engineering research in the School include Neuromuscular Systems and Neural Engineering, Cognitive Neuroscience, Cardiovascular Systems and Respiration, Sleep Monitoring, Biomedical Optics, Rehabilitation Engineering and Robotics.
These research groups are also members of the multidisciplinary UCD Centre for Biomedical Engineering Research and contribute to the undergraduate and graduate BE and ME Biomedical Engineering programmes.
Faculty
- Dr. Simon Kelly - Cognitive Neural Systems
- Dr. Madeleine Lowery - Neuromuscular Systems and Neural Engineering
- Prof. John. T. Sheridan – Biomedical Optics
- Prof. Annraoi de Paor (Emeritus) - Neuromuscular Systems and Neural Engineering
- Dr. Giacomo Severini – Rehabilitation Engineering and Robotics
- Dr. Stephen Redmond
- Dr. Emer Doheny
- Dr. Sigrid Dupan
- Dr. Elaine Corbett
Our research In the Neuromuscular Systems and Neural Engineering Lab involves the application of engineering principles, in particular mathematical modelling and signal processing, to understand how the nervous system controls muscle in healthy and diseased states. Through this research we aim to improve our understanding of the neuromuscular system both to address fundamental questions in the control of human movement and to develop improved therapeutic and rehabilitation strategies.
Specific areas of interest include mathematical modelling and analysis of bioelectric signals, electromyography (EMG), electrical stimulation of the nervous system, myoelectric prosthetics and motor control. Examples of research projects that our group are currently involved in include computational modelling of deep brain stimulation (DBS) in Parkinson's Disease, adaption of motor control in fatigue and disease, modelling of motoneuron activity and EMG, and understanding the role of oscillatory neural activity in the neuromuscular system.
Supported by a recent ERC Consolidator Grant, our group are developing computer models of the central and peripheral nervous system to better understand how DBS affects the activity of networks of neurons within the brain and neuromuscular system. Using these models we can explore the mechanisms by which DBS exerts its therapeutic effects and design optimal stimulation patterns that can ultimately be applied in patients to obtain better clinical outcomes.
The application of modern optics technology to the field of biomedical research and healthcare has advanced rapidly in recent years, with new application areas continuing to emerge. The Optical Engineering Lab at UCD is involved in research across a range of biomedical applications including the use of optics for advanced imaging of biological and physiological systems, examining the physiological effects of different types of light and light-therapy, and the design of optical systems for analyzing and interacting with the human body. Research areas in which we are currently involved include recording and analysis of oculo-microtremor, monitoring of cells using digital holography, LED based lighting and light therapy (bio-optics).
The adoption throughout across the world of LED light sources will truly bring about an energy revolution and may go a long way towards addressing projected energy crises. While the advantages of such sources appear obvious, their widespread raises serious issues regarding their optical effects on humans and animals. On example is that the installation of blue LED in Tokyo subway system which has been reported as producing a significant decrease (80%) in the number of suicides. The research team at University College Dublin (UCD) working in close collaboration with colleagues in Equilume(www.equilume.com) have been applying LEDs to a range of topics related to the use of LEDS. Work related to this has been published in reviewed international journals as diverse as Optik (LED Based Solar Simulators for testing Organisc Solar Cells) and The Journal of Veterinary Science (Light Therapy for Horses).
The Rehabilitation Engineering and Robotics Lab is a research entity shared between the Schools of Mechanical and Material Engineering and Electrical and Electronic Engineering. The Lab has been co-founded by Dr. Donal Holland and Dr. Giacomo Severini.
Our research focuses on the application of Engineering principles to the development of novel solutions aiming at facilitating the administration and understanding of Neuromuscular Rehabilitation in the impaired population, with a specific interest in robotics.
Our research follows two major streams: a) the study of motor control and motor learning in intact and impaired individuals, as a mean to fully understand the processes by which the central nervous system can re-learn movement after an injury/disease; b) the development of novel technical solutions and assistive/rehabilitative devices that would facilitate the administration of therapy, including robots.
Specific areas of interest include: soft robotics, wearable sensors, active orthoses and exoskeletons for assistance and rehabilitation, passive orthoses to assist human motion and prevent injury, medical device design, biomedical signal processing and neurophysiology.
Examples of research projects within our group include the design of soft robots for hand rehabilitation, the development of a wearable soft active knee brace, the study of the bi-lateral contributions to human locomotion and the development of novel data analysis approaches for the identification of biomarkers of impairment and recovery.
The Biomedical Sensors & Signals Group laboratory is a vibrant research team led by Stephen Redmond. The group explores fundamental and applied aspects of existing and novel biomedical sensors, with strong fundamentals in electronic circuit design, digital signal processing, and machine learning. The group currently has interests and expertise in tactile physiology and artificial tactile sensing, intelligent robotic manipulation, medical image analysis, human movement analysis, and connected health.