Traumatic Brain Injury Research

About the Research

Background Traumatic brain injury (TBI) is a leading cause of death and disability worldwide and its incidence continues to rise. Over 1.4 million TBI patients are treated in UK hospitals every year and in the US the societal and healthcare annual costs of TBI exceed $60 billion. In addition, TBI has been dubbed the signature injury of recent conflicts in Afghanistan and Iraq, and there is growing concern about the short- and long-term effects of concussion in sports.


The aim of this collaboration is to set up a pipeline for clinical translation of the Beckman Institute’s cutting-edge basic science research in bioengineering, cognitive neurosciences, neuroimaging and nutrition through the expertise and resources of University of Birmingham’s Neurobiology group and of the National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre (NIHR SRMRC) in the following areas:

  • Machine-learning techniques to analyse the data collected as part of ongoing SRMRC studies on major trauma and sport concussion in predicting TBI outcomes and recovery of function.
  • Examining the relationship between lifestyle and recovery of function in harmonising our neuropsychology assessment batteries to provide the evaluation of different cognitive constructs
  • Testing personalised medical devices to provide new ways to measure impacts related to TBI and track subsequent changes
  • Develop implantable devices to integrate monitoring functions in bioactive membranes

Early outputs:

  • Professors Barbey, Belli and Logan have co-written and published a joint paper (Network Topology and Dynamics in Traumatic Brain Injury in Current Opinion in Behavioral Sciences)
  • £1.2 million grant submitted to the Health Innovation Challenge Fund (Near Infrared Spectroscopic imaging solutions to guide resuscitation in Traumatic Brain Injury)
  • IT platform for common data sharing and analysis under development Incorporation of lifestyle and metabolic data collection tools in TBI clinical data collection protocols


Professor Belli
Professor Logan

Professor Barbey
Professor Cohen
Professor Rogers
Professor Kramer