Sleep EEG for TBI

Novel computation and acquisition of sleep EEG as a biomarker of traumatic brain injury (TBI)

Novel computation and acquisition of sleep EEG as a biomarker of traumatic brain injury (TBI) Contact Person:

Hung Cao

Other PIs/Investigators/PhD students:

Nikil Dutt
Amir M. Rahmani
Miranda Lim
Manoj Vishwanath
Ikhwan Shin
Salar Jafarlou

Project Summary:

The central goal of this collaborative project is to innovate novel computational approaches in order to understand persistently disrupted brain physiology sustained after mild traumatic brain injury (mTBI). Unique translational approaches will utilize massive electroencephalography (EEG) data during sleep and wakefulness in mice with TBI, in direct comparison with massive data collected from overnight polysomnography (PSG – EEG and other physiological signals) from human subjects with TBI. The investigative team will test novel approaches to EEG data preprocessing and normalization and apply transfer learning from mouse to human EEG data, in order to generate the most relevant, cross-species brain biomarkers of TBI.

Publications:

– Manoj Vishwanath, Salar Jafarlou, Ikhwan Shin, Miranda M. Lim, Nikil Dutt, Amir M. Rahmani, Hung Cao, “Investigation of Machine Learning Approaches for Traumatic Brain Injury Classification via EEG Assessment in Mice”, MDPI Sensors 2020, 2020.
– Manoj Vishwanath, Salar Jafarlou, Ikhwan Shin, Nikil Dutt, Amir M. Rahmani, Miranda Lim, Hung Cao, “Classification of Mild Traumatic Brain Injury in a Mouse Model Using Machine Learning Approaches”, 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2020.