Quantitative relations between electrical brain activity and upper limb torque generation in human subjects. - Ricamato AL (Quantitative Relations Between Electrical Brain Activity & Upper Limb Torque Generation in Human Subjects, 2000)
The objective of this study was to use high-resolution electroencephalography (EEG) to examine the functional organization of the human sensorimotor cortex during voluntary muscle activation of the upper limb. Two hypotheses are proposed. First, that separate centers of cortical activation would be responsible for generating joint torques in different directions. Second, that the magnitude of the electrical brain activity scales with joint torque level, while preserving the location of brain activity, which depends on direction in which a torque is generated.A secondary goal was to develop a new analysis technique to rigorously quantify electrical brain activity. A novel quantitative analysis technique incorporating a realistic, subject-specific Boundary Element Method (BEM) head model was devised to create a 3D spatial resultant vector representation of the cortical region(s) of activation.This new signal analysis technique combined with six degrees of freedom torque recordings revealed monotonic increases in the EEG resultant vector magnitude as a function of static joint torque level at both the elbow and the shoulder. Results indicate that a clear spatioternporal relationship exists between the location of cortical activity and the magnitude of joint torque generation. Findings also demonstrate a strong spatioternporal correlation between the location of centers of electrical brain activity and elbow/shoulder static joint torque direction.The methods developed as part of this thesis provide the ability to distinguish separate locations of centers of cortical activity not only as a function of joint but more importantly as a function of joint torque direction and the associated muscle activation patterns at a given joint.In conclusion, subject-specific quantitative spatial resultant vector analysis combined with innovative load cell controlled behavioral paradigms may prove helpful in identifying cortical regions responsible for generating specific muscle activation patterns. This work may also prove useful for evaluating potentially contrasting motor encoding schemes for cortical neuronal systems; thus distinguishing torque direction/magnitude coding from muscle activation based encoding approaches.