Efficient and reliable characterization of the corticospinal system using transcranial magnetic stimulation.

PURPOSE: The purpose of this study is to develop a method to reliably characterize multiple features of the corticospinal system in a more efficient manner than typically done in transcranial magnetic stimulation studies. METHODS: Forty transcranial magnetic stimulation pulses of varying intensity were given over the first dorsal interosseous motor hot spot in 10 healthy adults. The first dorsal interosseous motor-evoked potential size was recorded during rest and activation to create recruitment curves. The Boltzmann sigmoidal function was fit to the data, and parameters relating to maximal motor-evoked potential size, curve slope, and stimulus intensity leading to half-maximal motor-evoked potential size were computed from the curve fit. RESULTS: Good to excellent test-retest reliability was found for all corticospinal parameters at rest and during activation with 40 transcranial magnetic stimulation pulses. CONCLUSIONS: Through the use of curve fitting, important features of the corticospinal system can be determined with fewer stimuli than typically used for the same information. Determining the recruitment curve provides a basis to understand the state of the corticospinal system and select subject-specific parameters for transcranial magnetic stimulation testing quickly and without unnecessary exposure to magnetic stimulation. This method can be useful in individuals who have difficulty in maintaining stillness, including children and patients with motor disorders.

Cortical silent period duration and its implications for surround inhibition of a hand muscle.

Surround inhibition is a neural mechanism that assists in the focusing of excitatory drive to muscles responsible for a given movement (agonist muscles) by suppressing unwanted activity in muscles not relevant to the movement (surround muscles). The purpose of the study was to determine the contribution of γ-aminobutyric acid(B) receptor-mediated intracortical inhibition, as assessed by the cortical silent period (CSP), to the generation of surround inhibition in the motor system. Eight healthy adults (five women and three men, 29.8 ± 9 years) performed isometric contractions with the abductor digiti minimi (ADM) muscle in separate conditions with and without an index finger flexion movement. The ADM motor evoked potential amplitude and CSP duration elicited by transcranial magnetic stimulation were compared between a control condition in which the ADM was activated independently and during conditions involving three phases (pre-motor, phasic, and tonic) of the index finger flexion movement. The motor evoked potential amplitude of the ADM was greater during the control condition compared with the phasic condition. Thus, the presence of surround inhibition was confirmed in the present study. Most critically, the CSP duration of the ADM decreased during the phasic stage of finger flexion compared with the control condition, which indicated a reduction of this type of intracortical inhibition during the phasic condition. These findings indicate that γ-aminobutyric acid(B) receptor-mediated intracortical inhibition, as measured by the duration of the CSP, does not contribute to the generation of surround inhibition in hand muscles.

Achieving "organic compositionality" through self-organization: reviews on brain-inspired robotics experiments.

The current paper examines how compositional structures can self-organize in given neuro-dynamical systems when robot agents are forced to learn multiple goal-directed behaviors simultaneously. Firstly, we propose a basic model accounting for the roles of parietal-premotor interactions for representing skills for goal-directed behaviors. The basic model had been implemented in a set of robotics experiments employing different neural network architectures. The comparative reviews among those experimental results address the issues of local vs distributed representations in representing behavior and the effectiveness of level structures associated with different sensory-motor articulation mechanisms. It is concluded that the compositional structures can be acquired "organically" by achieving generalization in learning and by capturing the contextual nature of skilled behaviors under specific conditions. Furthermore, the paper discusses possible feedback for empirical neuroscience studies in the future.

Motor primitive and sequence self-organization in a hierarchical recurrent neural network.

This study describes how complex goal-directed behavior can be obtained through adaptation processes in a hierarchically organized recurrent neural network using a genetic algorithm (GA). Our experiments, using a simulated Khepera robot, showed that different types of dynamic structures self-organize in the lower and higher levels of the network for the purpose of achieving complex navigation tasks. The parametric bifurcation structures that appear in the lower level explain the mechanism of how behavior primitives are switched in a top-down way. In the higher level, a topologically ordered mapping of initial cell activation states to motor primitive sequences self-organizes by utilizing the initial sensitivity characteristics of non-linear dynamical systems. The biological plausibility of the model's essential principles is discussed.