Research Areas

Systems Neuroengineering
Superficially, it might appear that different brain regions are important for different tasks. In reality, different regions in the brain are densely connected through neuronal pathways. Systems Neuroengineering is aimed at understanding the inner workings of the brain at a systems level or whole-brain level through a variety of state-of-the-art experimental and computational techniques.

Brain-computer interface
Research in Brain-computer interface or BCI is aimed at reading signals from the brain through a variety of methods such as surface or implanted electrodes and connects it to a device to carry out a desired action. BCI is a promising solution for many conditions in which the brain is intact but either the connection between brain and body is damaged through accident or neurodegeneration or the musculo-skeletal system is affected.

Neuroergonomics
Neuroergonomics research aims to understand the brain in everyday life contexts, and its relationship to action, behavior, body, and environment. Neuroergonomics research utilizes wearable and noninvasive neuroimaging and neurostimulation to expand our understanding of the neural mechanisms underlying human perceptual, cognitive, and motor functioning with a focus on real-world contexts. Within the last decade, this emerging discipline has demonstrated potential to advances our understanding of brain with practical applications in diverse sectors such as medicine, education/training, aviation, automotive, manufacturing, administration, entertainment, communication and everyday life at large. Neuroergonomics research span from theoretical, and computational to applied and translational focusing on real-world industry challenges with implications in diverse sectors such as healthcare, education, transportation, manufacturing, entertainment, communication, and everyday life at large.

Neurotechnology
Neurotechnology research and development is at the core of Neuroengineering and supports all other investigations. This includes development of new tools and approaches that utilize real-time measures or actuators to create novel forms of reading or writing to brain, enabling animal and human-machine or human-human interaction. This area is devoted to the engineering of neurotechnologies, both neuroimaging and neurostimulation, that are designed to sense body, brain activity, and alter brain activity. Research topics include sensor/stimulator hardware and software development, biomedical signal preprocessing and artifact rejection techniques; feature extraction and machine learning; AI methods; Signal fusion and multimodal approaches.

Neuromorphic Engineering
Neuromorphic engineering is aimed at using “neuron-like” devices and connectivity patterns in biological brains to create synthetic nervous systems. The driving principle is to emulate the low power requirements and unique computing abilities of biological networks.

Comparative Neuroengineering
The nervous systems of different animals have shared architecture as well as differences. By analyzing species similarity and differences in brain sturcture, function, and behavior, comparative neuroengineering uncovers general principles of brain function that helps us understand the short-cuts that evolution has taken and aids in understanding disease.

Computational Neuroengineering
Computational neuroengineering is aimed at building mathematical or computer models from biological data. Computational neuroengineering also provides theoretical framework for interpreting data and for designing better experiments. Computation Neuroengineering involves modeling at multiple scales including modeling of single neurons, neuronal circuits, and the entire brain.

Translational neuroengineering
Translational neuroengineering is concerned with specific disease processes and therapies and the path from basic science and engineering to clinical application. The long term goals are clinically relevant devices and therapies. The research itself can be animal model based, or foundational engineering, or more direct pre-clinical testing processes, but the focus is to move knowledge and technology along the pipeline to clinic.

Human Neuroengineering
Human Neuroengineering ranges from clinical applications to recreational interface devices for games. At Drexel it is generally non-invasive, utilizing FNIR, EEG and other tools. In some instances at Drexel data collected invasively in clinical settings such as during neurosurgery or pre-operative testing may be the focus, but most work is less so.

Neuromechanics
Neuromechanics investigates the neural control and co-adaptations of neural and biomechanics systems throughout motor systems. Neuromechanics topics can range from the human gait lab to the swimming of fish, frog protective reflexes, or the walking and evasion manoevres of fruit flies. The field is a marriage of mechanics and neural control principles and draws from both, interfacing closely with neural circuit analyses.

Neural circuit engineering
Neural circuit engineering investigates the neural control implementation details and their analyses through simulation and recording. The effort is to reverse engineer neural circuitry to understand its organizational and information processing principles, dynamics, and the opportunities for intervention and therapy.

Neural-related Biomaterials
Biomaterials understanding is key to any neural recording or interface systems. Neural tissue is a unique mixture of sophisticated information processing, and its energetics, support requirements, and mechanical fragility or robustness. Managing these in interventions and interfaces through materials understanding is the focus.

Neural Tissue Engineering
Neural tissue engineering seeks to grow, manipulate and repair neural systems using combinations of the intrinsic neural tissues, neural transplanted and modified tissues, novel biomaterials and cellular controls. The major goal is to repair the damages leading to disease through neural manipulations in vivo or in vitro and their combinations.