Matthew Boggess
Papers
1
Total Citations
17
H-Index
1
About
Matthew Boggess is a researcher at the forefront of motor control and motor learning, with a particular focus on developing accessible, high-resolution tools for experimental research. His most-cited work, "OnPoint: A package for online experiments in motor control and motor learning" (2020, 17 citations), addresses a critical bottleneck in the field: the reliance on expensive, in-person laboratory setups. By creating a software package that enables rigorous online experiments, Boggess has helped democratize motor learning research, allowing scientists to collect high-quality data remotely without sacrificing temporal or spatial precision. This contribution is especially significant for scaling studies and reaching broader participant populations. His work reflects a commitment to methodological innovation, bridging the gap between traditional lab-based paradigms and the growing need for flexible, remote experimentation. Boggess’s efforts are paving the way for more inclusive and efficient research practices in motor neuroscience, making him a key figure in the modernization of experimental design in the field.
Research Focus
Key Achievements
Top Papers
- 1