Engineering foundational neuroscience discoveries to improve lives

The University of Pittsburgh's Neural Engineering Cross-Translation (NEXT) Institute aims to: 

  • Advance basic science understanding of the nervous system and develop innovative technologies to improve the diagnosis, treatment, and prevention of neurological and psychiatric disorders through forward and reverse translational approaches.
  • Educate the next generation of leaders in neural engineering through a rigorous and collaborative interdisciplinary program that promotes engagement.
  • Foster interdisciplinary collaborations among researchers, clinicians, industry partners, policy makers, humanists, and people with neurological or psychiatric disorders to accelerate the translation of neural engineering research into clinical practice.
  • Engage with the community to gain input from stakeholders,and to promote neuroethics and awareness of the importance of neural engineering research for improving human health and well-being.

What is Neural Engineering? 

Neural engineering involves electronic and mechanical systems, informatics, imaging, prosthetics, biological and artificial circuits, control systems, tissue engineering and regeneration, modeling, and computation pertinent to the nervous system. Neural Engineers at the University of Pittsburgh are using these techniques to transform lives by engineering scientific discoveries of the nervous system that are translated into human impact.

Who are Pitt’s Neural Engineers?

Neural Engineering at the University of Pittsburgh is interdisciplinary and highly collaborative. Faculty studying neural engineering can be found in the departments of Bioengineering, Physical Medicine & Rehabilitation, Radiology, Neurology, Neuroscience, and more, and their research is divided into five broad focus areas:

This cluster focuses on the software and algorithms that drive neurostimulation and neuromodulation devices. By manipulating neural codes, it aims to generate artificial sensations through feedback systems, closed-loop stimulation, and real-time neural data interpretation. The scope includes neurostimulation techniques, neuroplasticity promotion, and neuroprosthetic technologies designed to recreate sensory experiences, enhance perception, and improve patient outcomes.

Key Areas

  • Neural Code Decoding and Encoding
  • Closed-Loop Electrical StimulationSystems
  • Real-Time Neural Data Processing and Feedback
  • Brainwave and Brain Activity Mapping for Stimulation Protocols
  • Advances in Personalized Neuromodulation Algorithms
  • Low-Intensity Pulsed Ultrasound Stimulation

This cluster integrates research on neurodegenerative diseases (e.g., Alzheimer's, Parkinson's, MS) and nervous system injuries (e.g., brain injuries, and spinal cord damage) with clinical innovations in neurosurgery and neurorehabilitation. It focuses on developing therapies to restore function and improve quality of life through molecular, cellular, and technological interventions. Key areas include neuroplasticity-driven recovery and neuroprosthetic technologies for treating neurodegenerative conditions. Emphasis is placed on integrating these approaches into rehabilitation and surgical strategies to enhance both immediate recovery and long-term neurological function.

Key Areas

  • Neurodegenerative Diseases (Alzheimer’s, Parkinson’s, MS)
  • Traumatic Brain Injury (TBI) and Spinal Cord Injury Recovery
  • Neuroplasticity and Regenerative Rehabilitation
  • Neurostimulation and Neuroprosthetic Integration
  • Clinical Trials for Neurological Recovery

Focuses on the integration of advanced neuroimaging technologies, computational tools, and machine learning techniques to map and understand neural circuits, brain functions, and cognitive processes. This cluster leverages big data analytics, AI, and neurocomputational modeling to interpret neural dynamics, predict clinical outcomes, and guide personalized treatment strategies.

Key Areas

  • Functional and Structural Neuroimaging (e.g., fMRI, PET, two-photon microscopy, optogenetics)
  • Big Data Analytics in Neuroscience
  • AI and Machine Learning for Neuroinformatics
  • Neurocomputational Modeling and Simulation
  • Predictive Analytics for Disease Progression, Neuroplasticity, and Treatment Outcomes

This cluster focuses on the engineering and development of neurotechnologies, including biomaterials, implantable devices, and neuroprosthetics, while also investigating the role of the immune system, neuroinflammation, and glial modulation in neurological diseases and recovery. Emphasizing both physical interfaces and biological interactions, research explores strategies to modulate immune responses, restore neural function, and develop therapeutic interventions for neurodegenerative diseases.

Key Areas

  • Neuroprosthetics, Neural Interfaces, and BCIs
  • Implantable and Wearable Neurostimulation Devices
  • Biocompatible Materials for Neural and Immune Modulation
  • Neuroinflammation and Immune Interventions in Neurodegeneration, TBI, and Spinal Cord Injury

Focuses on the ethical, legal, and policy considerations surrounding neurotechnologies, ensuring their responsible development and use. The cluster also explores how Pitt’s expertise can address neurological health disparities and shape global policy on neurotechnologies

Key Areas

  • Neuroethics in Neurotechnology Development
  • Clinical & Regulatory Policy for Neuroprosthetics
  • Global Health Initiatives in Neurology
  • Health Equity in Access to Neurotechnologies
  • Ethical Considerations in AI and Machine Learning for Neuroscience


Studying Neural Engineering

A wide and exciting variety of neural engineering research projects are underway in Pittsburgh, which benefits from a history of leadership in neuroscience as well as close collaborations among neuroscientists, bioengineers, and engineers at the University of Pittsburgh and Carnegie Mellon University.

For rigorous training in this field, the Department of Bioengineering offers two graduate programs: MS in Neural Engineering and PhD in Bioengineering on the Neural Engineering track. Our graduate students are encouraged to interact with faculty on both campuses and to combine the resources of these institutions for their studies and research.