The protective effects of education on simulated brain injury.
Disturbed intellectual function is an important determinant of long-term recovery after head injury. Residual behavioral disability depends largely upon which hemisphere is damaged and the site of injury within the hemisphere. Resulting neurobehavioral syndromes vary with the pattern of brain insult. While this correlation is important, it is still not well understood how damage to single neurons translates into abnormal behavior. In addition, no currently available technology permits in vivo evaluation of such cells in normal or injured states. While research into brain trauma traditionally emphasize single cell pathology, this level of study is insufficient to clarify how individual cell activity contributes to higher cognition. In contrast, neural network simulations may partially fill this void by predicting biological function. Here, we present data generated by a three-layer neural network that employs the ALOPEX algorithm, capable of learning 10 words. The addition of Gaussian distributed noise into connection weights strengths damaged the network's function; interestingly, the rate and extent of network impairment depended upon the level of learning that occurred during the training period, in agreement with human studies that demonstrate a protective effect of education on subsequent brain injury. Damage to input signals resulted in similar effects on network function. Accordingly, such simulations offer powerful evidence that human behavior may be considered in terms of neuronal cell populations and efforts to preserve brain function at the time of injury should emphasize maintaining neural connections.
Powell
A L
AL
Department of Neurology, University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School, New Brunswick 08901, USA.
Zahner
D
D
Micheli-Tzanakou
E
E
D000465:Algorithms; D001930:Brain Injuries / Q000503:physiopathology / Q000523:psychology*; D003198:Computer Simulation; D004493:Education; D006801:Humans; D007858:Learning; D016571:Neural Networks, Computer; D009434:Neural Pathways / Q000502:physiology