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Event structure in sign languages is reflected in the manual dynamics of verb production. As signed event structure is visible (iconic), non-signers are able to recognize it, despite having no sign lexicon. In this EEG study, hearing non-signers were presented with telic and atelic verb signs, followed by a lexical classification task in their native language. Behavioral data confirmed that non-signers classified both telic and atelic signs with above-chance accuracy. ERP waveforms indicated that non-signers identified the perceptual differences in motion features when viewing telic/atelic signs, and used different processing mechanisms when integrating the perceptual information with linguistic concepts in their native language. Non-signers appeared to segment visual sign language input into discrete events, as they attempted to map the observed visual forms to concepts, and label them linguistically. This mechanism suggests a potential evolutionary pathway for co-optation of perceptual features into the linguistic structure of sign languages.

We present the first analysis of multi-frequency neural entrainment to dynamic visual features which drives sign language comprehension. Using the measure of EEG coherence to optical flow in video stimuli, we are able to classify fluent signers’ brain states as denoting online language comprehension, or non-comprehension during watching of non-linguistic videos that are equivalent in low-level spatiotemporal features and high-level scene parameters. The data also indicates that lower frequencies, such as 1 Hz and 4 Hz, contribute substantially to brain state classification, indicating relevance of neural coherence to the signal at these frequencies to language comprehension. These findings suggest that fluent signers rely on predictive processing during online comprehension.

This is the first kinematic investigation of articulator motion in Austrian Sign Language, which connects kinesiology of sign production and linguistic markers of Aktionsart in the native language of the Deaf community in Austria. Our work used a 3D motion capture approach to sign language analysis to investigate the relationship between the semantics (event structure) of signed verbs, and kinematics of hand articulator movement. The data indicates that the underlying semantics of events in verb signs is reflected in sign duration and acceleration of the dominant hand during sign production. The finding that articulator dynamics (acceleration and deceleration of hand motion) characterizes the event structure in verb signs has significance for linguistic theory of visual communication, and understanding of the relationship between iconicity in sign language, and perceptual biases in meaning construction based on visual input.