3D-Video-fMRI: 3D Motion Tracking in a 3T MRI Environment. In: Kamel M, Campilho A, editors. Image Analysis and Recognition. Berlin: Springer Berlin Heidelberg; 2011. pp. 59-67. [DOI: 10.1007/978-3-642-21596-4_7]

A custom MR-compatible dataglove for fMRI of the human motor cortex at 7T

We present a custom-built MR-compatible data glove to capture hand motion during concurrent fMRI experiments at 7 Tesla. Thermal and phantom tests showed our data glove can be used safely and without degradation of image quality. Subject-specific Blood Oxygen Level Dependent (BOLD) signal models, for use in fMRI analysis, were constructed based on recorded kinematic measurements. Experiments revealed the relative fMRI BOLD signal contribution of flexing, extending, and sustained isotonic extension. The ability to evaluate subject performance in real-time and create subject-specific BOLD signal models enables a wide range of experimental paradigms with improved data quality.Clinical Relevance- Using an MR compatible dataglove, subject specific Blood Oxygen Signal Level Dependent (BOLD) signal models can be constructed to study how the brain implements fine motor control.

Monkeys time their pauses of movement and not their movement-kinematics during a synchronization-continuation rhythmic task

A critical question in tapping behavior is to understand whether the temporal control is exerted on the duration and trajectory of the downward-upward hand movement or on the pause between hand movements. In the present study, we determined the duration of both the movement execution and pauses of monkeys performing a synchronization-continuation task (SCT), using the speed profile of their tapping behavior. We found a linear increase in the variance of pause-duration as a function of interval, while the variance of the motor implementation was relatively constant across intervals. In fact, 96% of the variability of the duration of a complete tapping cycle (pause + movement) was due to the variability of the pause duration. In addition, we performed a Bayesian model selection to determine the effect of interval duration (450–1,000 ms), serial-order (1–6 produced intervals), task phase (sensory cued or internally driven), and marker modality (auditory or visual) on the duration of the movement-pause and tapping movement. The results showed that the most important parameter used to successfully perform the SCT was the control of the pause duration. We also found that the kinematics of the tapping movements was concordant with a stereotyped ballistic control of the hand pressing the push-button. The present findings support the idea that monkeys used an explicit timing strategy to perform the SCT, where a dedicated timing mechanism controlled the duration of the pauses of movement, while also triggered the execution of fixed movements across each interval of the rhythmic sequence.