Specialisation in Neural Engineering

At Trinity College we offer a specialization in Neural engineering, the design and application of quantitative engineering approaches to understand, repair, replace, enhance, or exploit the properties of neural systems. Trinity College is extending the state of the art in neural engineering by designing, developing and evaluating neural prostheses, neuromodulation devices, therapeutic electrical stimulation, and neurodiagnostics. Our research aims to derive a quantitative understanding of precognitive and cognitive abilities and thus build a technical basis for a quantum leap in the fields of neurorehabilitation.

Neural Specialisation Handbook 2011-2012

The Neural Specialisation Handbook 2011-2012 containing information on module details, class dates and contents, module coordinators & guest lectureres, regulations and thesis guidelines for the academic year 2011-2012 can be found here.

Course Objectives and Learning Outcomes

This programme aims to give a sound and broad basis in neural engineering. In particular, we aim to provide engineers and scientists with the education needed to practice neural engineering in the international medical devices industry.
Specifically the learning outcomes are:

• To give students a broad understanding of the key subjects of neural engineering, viz., neural signal analysis, neuroimaging technology, implantable neural systems and current research topics and techniques in neural engineering.
• To develop students ability to critically analyse the scientific literature in the field of biomedical engineering through interactive discussion (including student presentations) and through grounding in the fundamentals of data analysis and modern neurotechnology.
• By way of case studies and assignments, to give students a familiarity with bioengineering applied in the main neurological disciplines.
• To give students a sound understanding of how to apply the scientific method to research in an industrial context.
• To give students the ability to exploit information technology for monitoring the performance of neural systems and related devices.
• To give students a knowledge of how the neural engineering and neurotechnology industry is regulated and of how to obtain acceptance of new products onto the market.

Required Classwork

To lay the foundation for their cutting-edge neural research, our students take the following courses:

[*This module also forms part of the MSc. in Neuroscience.]

Module Description

Neural Signal Analysis (Course coordinator: Dr. Edmund Lalor) The purpose of this course is to equip students with basic and sophisticated mathematical tools for the analysis of neural data including EEG, MEG, fMRI and intracranial data. The tools will include harmonic analysis, filtering, independent component analysis and wavelets. All methods will be developed to answer specific question on real data sets and the lectures will be accompanied by MATLAB-based data analysis assignments throughout the semester. The scoring of the course will encourage this practical application of the methods by an even weighting of scores between the exam and the MATLAB-based assignments.

Form and Function of the Nervous System (Course coordinator: Dr. Daniel Ulrich) This is an introductory module that will deal with the structure and function of the nervous system. The course will primarily focus on neuroanatomy and neurophysiology. Lectures will focus on gross anatomy and functions of the central and peripheral nervous systems, ventricles and CSF, vasculature of the brain, sense organs, ion channels, synaptic transmission, the somatosensory system, motor systems, auditory system, vision, plasticity, memory and learning.

Neuroimaging Technology (Course coordinator: Prof. Richard Reilly) This module will deal with the theory of imaging techniques such as MRI, PET and SPECT and application of these imaging techniques in the neurosciences. Applications in clinical diagnosis, and in neuroimaging of cognitive functions will also be covered in this module.

Implantable Neural Systems (Course coordinator: Dr. Arun Bokde) The objective of this module is to provide a quantitative background to implanted neural systems. It will consider subcomponents with a special emphasis placed on the neural electrode interface for recording and stimulation. Focus will also be on the neuromodulation effects of electrical stimulation and on the goals of real time, closed loop control of implanted systems. Matlab based assignments for the analysis of real recorded data will form part of this module.

Current Research topics & Methods in Neural Engineering This weekly module will introduce MSc students to cutting-edge research in neural engineering and to many of the skills required to engage in such research. The meetings will typically take place on the Trinity College Campus, however, a number of the meetings will be hosted by our clinical collaborators at hospitals around Dublin. The module will take two forms: Journal Club & Data Club. Each journal club session consists of a 20 minute presentation of a relevant cutting-edge neural engineering research paper(s). This will take the form of a structured PowerPoint presentation given by an MSc student, a Neural Engineering PhD student, or a faculty member. Data club sessions consist of a presentation of new research results and will rotate between MSc students, PhD students, and the faculty. The object of the data club sessions is to critically analyse the research results and to attempt to provide constructive feedback to the presenter on their work.

Master’s Thesis

All students are required to conduct individual research leading to a dissertation during their second year. These projects usually follow an interdisciplinary approach and are carried out in cooperation with medical doctors, engineers and neuroscientists. Topics currently being researched by our CEMACUBE students are:

• Neuroimaging study of primary reading epilepsy
• Improving the specificity of responses from human visual cortex
• Quantitative EEG Analysis following Acute Brain Injury
• Early Predictors of speech perception performance in cochlear implant users
• What role does long-term synaptic plasticity play in the mechanisms of neurocognitive function?
• Modelling the Sustained Sense of Head-Direction during Theta Sleep in Rodents
  

Further Research Opportunities

The Neural Engineering Group is a constituent laboratory of the Trinity Centre of Bioengineering and the Trinity Institute of Neuroscience.
Our research groups cover the following themes in Neural Engineering:

Electrophysiology
Our research is focused on three specific objectives:

• Enhancing algorithmic methods for analysing physiological signals and reducing the influence of signal degradation and interference. We have developed FASTER for fully automated, unsupervised processing of high-density EEG data.
• Building core research skills, algorithms and systems for modelling the human physiological state leading to skills necessary for implanted neuroprosthetic devices.
• Developing systems for neural prostheses, neuromodulation devices, therapeutic electrical stimulation, and neurodiagnostics.
  

Speech Processing
Our research in speech is focused on

• speech processing and classification that provides objective analysis in psychiatry.
• speech processing and classification of cognitive function in older people.
  

Biomedical Signal Processing
Our research in biomedical signal processing is focused on

• Multimodal signal analysis and classification
• Locomotion and cognitive function
  

Longitudinal Multi-Dimensional Multiple Sclerosis Study
Cognitive impairment (CI) may occur in up to 65% of multiple sclerosis (MS) patients. The aim of the longitudinal multi-dimensional multiple sclerosis study is to determine the factors that result in cognitive impairment in MS. Each year, data are collected from MS patients across a variety of dimensions, such as psychological, neurological, electrophysiological, and radiological.