Spinal cord injury detection and monitoring using spectral coherence.
In this paper, spectral coherence (SC) is used to study the somatosensory evoked potential (SEP) signals in rodent model before and after spinal cord injury (SCI). The SC technique is complemented with the Basso, Beattie, and Bresnahan (BBB) behavior analysis method to help us assess the status of the motor recovery. SC can be used to follow the effects of SCI without any preinjury baseline information. In this study, adult female Fischer rats received contusion injury at T8 level with varying impact heights using the standard New York University impactor. The results show that the average SC between forelimb and hindlimb SEP signals before injury was relatively high ( > or =0.7). Following injury, the SC between the forelimb and hindlimb SEP signals dropped to various levels ( < or =0.7) corresponding to the severity of SCI. The SC analysis gave normalized quantifiable results for the evaluation of SCI and recovery thereafter using the forelimb signals as an effective control, without the need of any baseline data. This technique solves the problems associated with the commonly used time-domain analysis like the need of a trained neurophysiologist to interpret the data and the need for baseline data. We believe that both SC and BBB may provide a comprehensive and complementary picture of the health status of the spinal cord after injury. The presented method is applicable to SCIs not affecting the forelimb SEP signals.
College of Engineering, American University of Sharjah, Sharjah, UAE. hnashash@aus.edu
Hasan
H
Al-Nashash
Noreen A
NA
Fatoo
Nabil N
NN
Mirza
Rabi I
RI
Ahmed
Gracee
G
Agrawal
Nitish V
NV
Thakor
Angelo H
AH
All
D000465:Algorithms; D000704:Analysis of Variance; D000818:Animals; D001522:Behavior, Animal / Q000502:physiology; D004195:Disease Models, Animal; D005073:Evoked Potentials, Somatosensory / Q000502:physiology*; D005121:Extremities / Q000503:physiopathology; D005260:Female; D051381:Rats; D011916:Rats, Inbred F344; D012815:Signal Processing, Computer-Assisted; D013119:Spinal Cord Injuries / Q000175:diagnosis* / Q000503:physiopathology