Graduate

Neuroengineering Focus Area Curriculum Requirements

 

 

 

 

 

 

 

 

 

 

 

Neuroengineering is an emerging and fast growing basic and translational research avenue within today’s biomedical and bioengineering fields. The main focus of neuroengineering is to use engineering tools to modulate central, peripheral and autonomic nervous system (CNS, PNS & ANS) function. It aims at developing new engineering oriented technologies within the medical field for screening, diagnosis, prognosis, rehabilitation, repair, and regeneration. Brain computer interface, deep brain stimulation, and cell replacement therapy are exemplar disciplines developed by utilizing core engineering approaches to understand pathologies and treat patients with neurological disorders.

Although neuroengineering is not a new field and has been known under different names, it has undergone a revolution in the last two decades due to rapid advancement in the fields of engineering and computer science. Neuroengineering encompasses modulation of individual neurons and their sub-cell components to regulate their networks and function in nervous tissue and the organ as whole, which eventually control the functioning of the entire human body. This allows engineers to develop means and tools to define, control, enhance, or inhibit their function selectively, precisely, and in spatial and temporal domains. 

Additional information about the neuroengineering track can be found here

Neuroengineering focus area students are expected to complete at least two of the following “core” courses:
  • Models of the Neuron (EN.580.639)
  • Neuro Data Design I (EN.580.697)
  • Neuro Data Design II (EN.580.638)
  • Neural Implants and Interfaces (EN.580.742)
  • Representations of Choice (EN.580.462)
  • Structure and Function of the Auditory and Vestibular Systems (EN.580.625)
Neuroengineering focus area students will complete additional electives selected from the following list (choose at least three of these courses):
  • Artificial Intelligence (EN.601.664)
  • Biomedical Photonics I (EN.580.678)
  • Biomedical Photonics II (EN.580.788)
  • Introduction to Biomedical Rodent Surgery Laboratory and Granstsmanship (EN.580.706)
  • Introduction to Computational Medicine I (EN.580.631)
  • Imaging Instrumentation (EN.580.693)
  • Machine Learning (EN.601.675)
  • Machine Learning: Data to Models (EN.601.476)
  • Machine Learning: Deep Learning (EN.601.682)
  • Principles of the Design of Biomedical Instrumentation (EN.580.771)
  • Probabilistic Models in the Visual Cortex (EN.601.685)
  • Sensory Information Processing (EN.520.735)
  • Structure and Function of the Auditory and Vestibular Brian (EN.580.626)
  • Theoretical Neuroscience (EN.580.630)
  • Topics in Systems Neuroscience (EN.580.628)
Students will select additional graduate level science, technology, engineering, or math courses with the consent of their advisor to complete the total of 30 credits required for graduation.