Course Catalogue

Approaches to Neurotechnology (PGT) PSYCH5114

  • Academic Session: 2026-27
  • School: School of Psychology and Neuroscience
  • Credits: 20
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: Yes
  • Collaborative Online International Learning: No
  • Curriculum For Life: No

Short Description

This Master's-level course provides a multidisciplinary foundation in neuroengineering, combining neuroscience, engineering, and computer science to prepare students for emerging careers in the rapidly expanding neurotechnology sector. Students will gain advanced knowledge of neural systems, alongside hands-on skills in neural signal acquisition and processing, with a strong emphasis on real-world application. Reflecting the industry's increasing demand for hybrid skillsets, students will engage with computational modelling environments, as well as signal processing tools relevant to clinical and consumer neurotechnology. Overall, the course serves as a gateway to careers in healthcare technology, neural interfaces, brain-inspired computing, and neuroethics.

Timetable

1 two-hour lecture per week with additional pre-recorded lectures (flipped classes). Additional tutorials and laboratory work to develop practical skills

Requirements of Entry

Standard University entry requirements for Post-graduate courses apply.

Excluded Courses

None

Co-requisites

None

Assessment

60% examination

40% lab portfolio

Main Assessment In: April/May

Course Aims

■ To provide students with an advanced interdisciplinary understanding of neuroengineering as a field, including its foundations, current applications, and future directions.

■ To promote within students critical thinking about the ethical, legal, and societal implications of neurotechnological innovation. 

■ To foster collaborative, research-led learning through student-led group projects that integrate theory, experimentation, and practical application.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ Critically evaluate the principles and applications of neuroengineering technologies, while being receptive to different information and evidence types

■ Perform practical neural data acquisition and implement advanced processing techniques

■ Formulate, create and interpret computational models of neural systems

■ Iteratively design experiments, and implement a neuroengineering applications and concepts

■ Critically evaluate the societal, legal, and ethical dimensions of neurotechnology development

Minimum Requirement for Award of Credits

No exceptions