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Despite a rise in the use of "learning by doing" pedagogical methods in praxis, little is known as to how the brain benefits from these methods. Learning by doing strategies that utilize complementary information ("enrichment") such as gestures have been shown to optimize learning outcomes in several domains including foreign language (L2) training. Here we tested the hypothesis that behavioral benefits of gesture-based enrichment are critically supported by integrity of the biological motion visual cortices (bmSTS). Prior functional neuroimaging work has implicated the visual motion cortices in L2 translation following sensorimotor-enriched training; the current study is the first to investigate the causal relevance of these structures in learning by doing contexts. Using neuronavigated transcranial magnetic stimulation and a gesture-enriched L2 vocabulary learning paradigm, we found that the bmSTS causally contributed to behavioral benefits of gesture-enriched learning. Visual motion cortex integrity benefitted both short- and long-term learning outcomes, as well as the learning of concrete and abstract words. These results adjudicate between opposing predictions of two neuroscientific learning theories: While reactivation-based theories predict no functional role of specialized sensory cortices in vocabulary learning outcomes, the current study supports the predictive coding theory view that these cortices precipitate sensorimotor-based learning benefits.
Pubmed ID: 32959878
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Software package for analysis of brain imaging data sequences. Sequences can be a series of images from different cohorts, or time-series from same subject. Current release is designed for analysis of fMRI, PET, SPECT, EEG and MEG.
View all literature mentionsA sweep-based data acquisition and analysis software package. Its uses range from a simple storage oscilloscope to complex applications requiring stimulus generation, data capture, control of external equipment and custom analysis. A built-in script language automates tasks and provides additional tools for custom analyses and applications. Signal includes functions for specific application areas, including dynamic clamp, whole cell and patch clamp electrophysiology, and evoked response including control of magnetic and other stimulus devices. Video tutorials and a demo version of Signal is available on the main page.
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