Sensorimotor integration refers to the process of combining incoming sensory information with outgoing motor commands to control movement. Short-Latency Afferent Inhibition (SAI), Long-Latency Afferent Inhibition (LAI) and Afferent Facilitation (AF) are three neurophysiological measures collected using Transcranial Magnetic Stimulation (TMS) to assess sensorimotor integration in humans. No studies to date have investigated the influence of tactile discrimination training on these measures. This study aimed to determine whether SAI, LAI, and AF are modulated following training on a custom-designed sensorimotor task which required participants to use their sense of touch to successfully navigate 3D printed maze with interchangeable paths. The maze training was separated into “high difficulty” and “low difficult” conditions which reflected the tactile challenge embedded within the maze. On an additional visit, no maze training was performed to serve as a control condition. Despite evidence of performance improvements during training, there were no significant changes in SAI, LAI or AF following training in either condition. Further, there was no correlation between the % change in SAI/LAI and improvements in total dwell time on the maze. As the functional significance of these measures is still unclear, these findings suggest that changes in SAI, LAI or AF may not be a valid metric to measure meaningful or functional changes related to skills or performance improvements induced by training. / Thesis / Master of Science in Kinesiology / Sensorimotor integration refers to the combination of incoming sensory information with outgoing motor commands in the nervous system to control movement. Short- Latency Afferent Inhibition, Long-Latency Afferent Inhibition and Afferent Facilitation are three measures that probe sensorimotor integration in humans using Transcranial Magnetic Stimulation. Although these measures have been well studied in both healthy and clinical populations in a variety of contexts, the influence of sensorimotor training on these measures remains unclear. This thesis aimed to determine if SAI, LAI and AF change following training on a novel tactile discrimination maze task. Further, the relationship between changes in sensorimotor integration and improvements in maze performance was explored. SAI, LAI and AF were not shown to be influenced by training, and there was no association between the changes in these measures and improvements in maze performance.

Title of diploma thesis: Tactile discrimination and excitability of alpha motoneurons Objectives: The aim of this thesis is to detect whether tactile discrimination tasks affect the excitability of the alpha motoneurons. Methods: Seven volunteers aged between 20 and 26 years participated in this study. The H reflex, (M wave) were recorded during three control and three experimental conditions. The control conditions preceded each experimental condition. By stimulating the tibialis nerve in the popliteal fossa the H reflex was elicited and its amplitude and latency measured at rest (control) and during tactile discrimination tasks (experimental). As tactile discrimination tasks, three separate tasks were chosen-tactile stimulation, escape reaction to tactile stimulation, and two-point discrimination. We used an EMG stimulator with a constant voltage output and monophasic squared pulses, with a 0,5 ms interval. The stimulation was switched on manually every 3-5 seconds. To detect the electrical potential of the soleus muscle, we used a surface EMG device, a GrassTelefactor, with galvanic isolation complying with EU standards. The parameters measured were the latency and amplitude of the H reflex and M wave during the tactile discrimination tasks and these were then compared to the values at rest. The...

Recent experimental studies point to the notion that the brain is a complex dynamical system whose behaviors relating to brain functions and dysfunctions can be described by the physics of network phenomena. The brain consists of anatomical axonal connections among neurons and neuronal populations in various spatial scales. Neuronal interactions and synchrony of neuronal oscillations are central to normal brain functions. Breakdowns in interactions and modifications in synchronization behaviors are usual hallmarks of brain dysfunctions. Here, in this dissertation for PhD degree in physics, we report discoveries of brain oscillatory network activity from two separate studies. These studies investigated the large-scale brain activity during tactile perceptual decision-making and epileptic seizures. In the perceptual decision-making study, using scalp electroencephalography (EEG) recordings of brain potentials, we investigated how oscillatory activity functionally organizes different neocortical regions as a network during a tactile discrimination task. While undergoing EEG recordings, blindfolded healthy participants felt a linear three-dot array presented electromechanically, under computer control, and reported whether the central dot was offset to the left or right. Based on the current dipole modeling in the brain, we found that the source-level peak activity appeared in the left primary somatosensory cortex (SI), right lateral occipital complex (LOC), right posterior intraparietal sulcus (pIPS) and finally left dorsolateral prefrontal cortex (dlPFC) at 45, 130, 160 and 175 ms respectively. Spectral interdependency analysis showed that fine tactile discrimination is mediated by distinct but overlapping ~15 Hz beta and ~80 Hz gamma band large-scale oscillatory networks. The beta-network that included all four nodes was dominantly feedforward, similar to the propagation of peak cortical activity, implying its role in accumulating and maintaining relevant sensory information and mapping to action. The gamma-network activity, occurring in a recurrent loop linked SI, pIPS and dlPFC, likely carrying out attentional selection of task-relevant sensory signals. Behavioral measure of task performance was correlated with the network activity in both bands. In the study of epileptic seizures, we investigated high-frequency (> 50 Hz) oscillatory network activity from intracranial EEG (IEEG) recordings of patients who were the candidates for epilepsy surgery. The traditional approach of identifying brain regions for epilepsy surgery usually referred as seizure onset zones (SOZs) has not always produced clarity on SOZs. Here, we investigated directed network activity in the frequency domain and found that the high frequency (>80 Hz) network activities occur before the onset of any visible ictal activity, andcausal relationships involve the recording electrodes where clinically identifiable seizures later develop. These findings suggest that high-frequency network activities and their causal relationships can assist in precise delineation of SOZs for surgical resection.