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 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 the aNMT will influence adaptive brain strategies in young girls.

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. The BNA test is basically divided to 3 phases - first EEG data is collected from subjects using an EEG system and while the subject is performing a computerized cognitive task. The EEG data is then analyzed using the advanced BNA™ technology and last a report of the BNA™ test is generated. Neuroimaging, specifically functional magnetic resonance imaging provides improved spatial data relative to EEG and provides another measure of neuroplasticity to gain the full pictures of training effects on the brain. Previous literature supporting its ability to detect differences in those with ACL injury strengthens the use of fMRI. We will be assessing the full brain response during a knee extension task using previously established methods ACL deficient and reconstructed knees. Recent investigations into gait retraining with fMRI pre-post testing have created the neural correlates of gait training based on ankle dorsiflexion. In the same way, this study will apply a similar paradigm utilizing knee extension to understand the neuroplasticity associated with lower extremity neuromuscular training.

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 novel training program with real-time biofeedback added consists of 2 sets of 10 repetitions per session with a progression in exercise intensity (Squat: 40 repetitions during week 1; Squat Jump: 80 repetitions during weeks 2-3; Tuck Jumps: 120 repetitions during weeks 3-6) over the 6-week training period.

Inclusion Criteria: Healthy female athlete Exclusion Criteria: Any psychiatric disorder, e.g., depression, bipolar disorder, schizophrenic disorder, etc. as determined by clinical evaluation and the Mini International Neuropsychiatric Interview Kid (MINI-Kid) Any CNS neurologic disorder, e.g., epilepsy, seizures, etc. as determined by clinical evaluation Any neuropsychological disorders, e.g.: ADHD, Autistic Spectrum Disorder (ASD), etc. as determined by ASRS 1.0 questionnaire History of Special education, e.g., reading disorder (dyslexia), writing disorder (dysgraphia), math disorder (dyscalculia), nonverbal learning disorder. History of any medication affecting CNS within the last 3 months, e.g., antidepressants, anticonvulsants, psychostimulants, first generation antihistamines, etc. History of any clinically significant brain trauma as previously diagnosed by a physician