Effects of Neuromuscular Training on EEG Adaptations in Young Athletes

The purpose of the current project is to determine the effects of augmented neuromuscular training on brain neuroplasticity. Specifically we aim to evaluate the potential of standard augmented NMT (aNMT) to alter brain neural performance as evidenced by EEG and functional brain magnetic resonance imaging (MRI). The changes in EEG and MRI (pre vs. post) will be compared over the same period of time. We hypothesize that aNMT will influence adaptive brain strategies in young girls and simultaneously will improve joint mechanics in evidence-based measures collected in realistic, sport-specific virtual reality scenarios. The human brain is a highly complex multilayered organ composed of many billions of neurons (1 trillion brain cells and 100 billion neurons), organized into very complicated interconnecting neural networks. Typically, each neuron is connected to tens of thousands of other neurons through connections called synapses. Electrochemical signals that are passed between neurons through these synapses allow them to communicate. The connections between neurons are not static, but change over time. The more signals sent between two neurons, the stronger the connection grows, and so, with each new experience, the brain slightly rewires its physical and functional structure.

Unique local physical and functional connections between neurons are called neural networks. Neural networks are typically characterized by preferred signaling pathways, and it is the interactions within and between these networks of neurons that enable us to perform various functions including cognitive functions, such as attention, working memory, pattern recognition and problem-solving. It is this simultaneous cooperative function of brain areas working together as large-scale networks which is at the root of the sophistication and computational power of the human brain.

Event Related Potentials (ERPs), which are temporal reflections of the neural mass electrical activity of cells in specific regions of the brain that occur in response to stimuli, may offer such a measure, as they provide both a noninvasive and portable index of brain function. The ERPs provide excellent temporal information, but spatial resolution for ERPs has traditionally been limited. However, by using high-density electroencephalograph (EEG) recording spatial resolution for ERPs has improved significantly.

Currently, there is no direct, reliable, bed-side, and non-invasive method for assessing changes in brain activity associated with concussion. Event Related Potentials (ERPs), which are temporal reflections of the neural mass electrical activity of cells in specific regions of the brain that occur in response to stimuli, may offer such a method, as they provide both a noninvasive and portable measure of brain function. The ERPs provide excellent temporal information, but spatial resolution for ERPs has traditionally been limited. However, by using high-density electroencephalograph (EEG) recording spatial resolution for ERPs is improved significantly. The paradigm for the current study will combine neurophysiological knowledge with mathematical signal processing and pattern recognition methods (BNA™) to temporally and spatially map brain function, connectivity and synchronization.

The proposed study will provide additional evidence for the utility and contribution of the BNA™ test (reflecting temporal and spatial changes in brain activity as well as brain functional connectivity associated with concussion) in concussion management.