Sign language encodes event structure through neuromotor dynamics: motion, muscle, and meaning

Area of Science:

• Linguistic research
• Neuroscience
• Biomechanics

Background:

• Sign languages encode grammatical information through complex movements.
• Embodied cognition theories suggest language processing involves sensorimotor systems.
• Understanding the neuromotor basis of sign language grammar is crucial for linguistic and cognitive science.

Purpose of the Study:

• To provide neuromotor evidence for the embodied kinematic encoding of grammatical event structure in Austrian Sign Language (ÖGS).
• To investigate how ÖGS distinguishes telic (bounded) and atelic (unbounded) verbs using kinematic and muscle activation patterns.
• To explore the role of motor control schemas in producing grammatical contrasts in sign language.

Main Methods:

• Utilized time-locked motion capture and surface electromyography (EMG) to record signers.
• Analyzed kinematic parameters like movement duration, deceleration, and variability.
• Examined muscle activation patterns, including co-contraction and cross-correlation, in forearm and upper-arm muscles.

Main Results:

• Telic signs exhibited shorter duration, later deceleration, and lower movement variability compared to atelic signs.
• Distinct spectral activation patterns were observed in forearm and upper-arm muscles for telic versus atelic verbs.
• Telic signs showed greater EMG co-contraction but lower cross-correlation, indicating precise antagonistic muscle coordination.

Conclusions:

• Grammatical distinctions in ÖGS are produced through finely tuned motor control schemas.
• Neuromotor correlates of linguistic structure in a visual-manual modality are replicable and interpretable.
• Results support the linguistic interpretation of morphological marking differences between telic and atelic verb signs.