A Computational Model for Recovery from Brain Injury

A computational simulation model calculates recovery trajectories following traumatic brain injury (TBI). Prior publications include a multi-scale framework for studying concussion and a systems-level causal loop diagram (CLD) and discussion of feedback processes. The scope of the computational model goes beyond concussion to include all severities of TBI. A set of first order ordinary differential equations and their associated parameters determines recovery trajectories. While highly speculative, the model serves to demonstrate the potential utility of computational models in this context. Much more research will be needed to create a properly supported research model that could be used for clinical trial design or precision medicine. The model contains 15 state variables, 73 auxiliary variables, and 50 parameters describing TBI pathology in an aggregate fashion at the cellular, network, cognitive and social levels. There are 1200 feedback loops, which gives rise to a variety of behavior modes, many of which are highly nonlinear. Exogenous parameters include patient and injury characteristics, treatments, and time constants for recovery processes. Model testing has focused on reviewing the model structure with subject matter experts and determining sensitivity of model results to injury severity and patient characteristics, especially the time constants associated with healing/recovery processes. The model produces outcome trajectories that represent quick or slow recovery with no deficits, partial recovery, or remaining indefinitely in a pathological state. See Also:A Computational Model for Recovery from Traumatic Brain Injury, Presented at the International Conference of the Society for Systems Sciences, Corvallis, Oregon, USAhttps://pdxscholar.library.pdx.edu/systems_science_seminar_series/1003/thumbnail.jp