Semantic processing with and without awareness. Insights from computational linguistics and semantic priming.

During my PhD, I’ve explored how native speakers access semantic information from lexical stimuli, and weather consciousness plays a role in the process of meaning construction. In a first study, I exploited the metaphor linking time and space to assess the specific contribution of linguistically–coded information to the emergence of priming. In fact, time is metaphorically arranged on either the horizontal or the sagittal axis in space (Clark, 1973), but only the latter comes up in language (e.g., "a bright future in front of you"). In a semantic categorization task, temporal target words (e.g., earlier, later) were primed by spatial words that were processed either consciously (unmasked) or unconsciously (masked). With visible primes, priming was observed for both lateral and sagittal words; yet, only the latter ones led to a significant effect when the primes were masked. Thus, unconscious word processing may be limited to those aspects of meaning that emerge in language use. In a second series of experiments, I tried to better characterize these aspects by taking advantage of Distributional Semantic Models (DSMs; Marelli, 2017), which represent word meaning as vectors built upon word co–occurrences in large textual database. I compared state–of–the–art DSMs with Pointwise Mutual Information (PMI; Church & Hanks, 1990), a measure of local association between words that is merely based on their surface co–occurrence. In particular, I tested how the two indexes perform on a semantic priming dataset comprising visible and masked primes, and different stimulus onset asynchronies between the two stimuli. Subliminally, none of the predictor alone elicited significant priming, although participants who showed some residual prime visibility showed larger effect. Post-hoc analyses showed that for subliminal priming to emerge, the additive contribution of both PMI and DSM was required. Supraliminally, PMI outperforms DSM in the fit to the behavioral data. According to these results, what has been traditionally thought of as unconscious semantic priming may mostly rely on local associations based on shallow word cooccurrence. Of course, masked priming is only one possible way to model unconscious perception. In an attempt to provide converging evidence, I also tested overt and covert semantic facilitation by presenting prime words in the unattended vs. attended visual hemifield of brain–injured patients suffering from neglect. In seven sub–acute cases, data show more solid PMI–based than DSM–based priming in the unattended hemifield, confirming the results obtained from healthy participants. Finally, in a fourth work package, I explored the neural underpinnings of semantic processing as revealed by EEG (Kutas & Federmeier, 2011). As the behavioral results of the previous study were much clearer when the primes were visible, I focused on this condition only. Semantic congruency was dichotomized in order to compare the ERP evoked by related and unrelated pairs. Three different types of semantic similarity were taken into account: in a first category, primes and targets were often co–occurring but far in the DSM (e.g., cheese-mouse), while in a second category the two words were closed in the DSM, but not likely to co-occur (e.g., lamp-torch). As a control condition, we added a third category with pairs that were both high in PMI and close in DSMs (e.g., lemon-orange). Mirroring the behavioral results, we observed a significant PMI effect in the N400 time window; no such effect emerged for DSM. References Church, K. W., & Hanks, P. (1990). Word association norms, mutual information, and lexicography. Computational linguistics, 16(1), 22-29. Clark, H. H. (1973). Space, time, semantics, and the child. In Cognitive development and acquisition of language (pp. 27-63). Academic Press. Kutas, M., & Federmeier, K. D. (2011). Thirty years and counting: finding meaning in the N400 component of the event-related brain potential (ERP). Annual review of psychology, 62, 621-647. Marelli, M. (2017). Word-Embeddings Italian Semantic Spaces: a semantic model for psycholinguistic research. Psihologija, 50(4), 503-520. Commentato