It is often said that we know the meaning of a word by the company it keeps. But what happens when the “company” is an object? How does the rate of co-occurrence between a word (bark) and a picture (dog) influence how fast the concept is accessed? We investigated this question by modeling data from three sources: (1) norming data obtained from a dataset of 78,000 features to a set of pictures; (2) accuracy and response time data from a picture-word masked congruency task with stimuli presented for 60 and 200 milliseconds; and (3) cosine-similarities between an object (dog) and lexical items labeling superordinate (animal), high-salient (bark), and low-salient (fur) properties of the referent object using word2vec. Results show a superordinate effect: words labeling object categories were most affected by cosine similarity. Our results suggest that the co-occurrence between an object and a superordinate label facilitate object concept tokening.

A sentence such as ”We finished the paper” is indeterminate regarding what we finished doing with the paper. Thesesentences constitute a test case for two major issues regarding the nature of language comprehension: (1) whether ornot semantic composition is simple (classical) or enriched with intended or implicit constituents; and (2) the nature ofthe linguistic and cognitive resources that help us interpret the event the sentence conveys. We conducted an eye-trackingstudy to investigate whether indeterminate sentences embedded within biasing contexts would trigger event interpretations,using a long-term memory paradigm. In each trial, participants were presented with one of three recognition probe typesfor reading while having their eyes monitored. Recognition probes were presented 0 seconds (s) after having read theindeterminate sentence, or following an additional 25s of neutral discourse. Results suggest that abductive processes,relying on the propositional content of supporting context, drive indeterminate sentence interpretation.

Word recognition models such as Cohort have long relied on the gating paradigm to investigate how acoustic-phonetic information maps onto lexical representations. We report on a methodological study investigating (a) whether the recognition point of a spoken word is affected by the speech variables employed in the gating paradigm, and (b) which distributional properties of a words’ linguistic and social usage pattern affect its recognition point. We addressed the first question by contrasting the traditional “brute-force” gating paradigm (i.e., employing incremental segments of 50 ms) to “phonetically-driven” gating paradigms. Three methodologies were employed for determining phonemic segments: (1) articulatory measures, relying on the peak velocity of articulatory gestures, (2) acoustic measures, relying on the acoustic energy of consonants and vowels, and (3) brute-force measures, relying on 50 ms increments. We addressed the second question by relying on four social measures of lexical strength, which were attained from a corpus of 57 billion words from Reddit: word frequency (WF), contextual diversity (CD), discourse contextual diversity (DCD), and user contextual diversity (UCD). Results showed that the traditional brute-force gating method yielded significantly faster word recognition times, in comparison to articulatory and acoustically driven gating methods. Our results also showed that CD is a superior measure of lexical strength than WF, UCD, and DCD. Overall, our results suggest that the traditional gating paradigm is a reliable method for investigating spoken word recognition, given that spoken word recognition may rely on the gradual accumulation of phonetic information over time, rather than relying solely on the recovery of categorical phonetic features that are distributed non-linearly in time. We also suggest that the lexical system may be organized as a function of usage-based contextual measures of lexical items.

Is the visual word recognition system sensitive to compound (e.g., SNOWBALL) and pseudocompound (e.g., CARPET) constituents? To answer this question, we employed red-blue anaglyphs glasses to parse red-blue colored (pseudo)compounds at the fovea—by hypothesis split along the vertical meridian—and allowing for the independent processing of word segments in the visual word form area. Seventy-one participants performed a visual masked lexical decision task with 133 millisecond stimuli presentations. Compounds and pseudocompounds were either split at the (pseudo)morpheme boundary (legally-split) or within a (pseudo)morpheme (illegally-split). We found a statistically significant interaction effect between word type and legality. Planned comparisons revealed an advantage in accuracy for legally-split compounds and pseudocompounds over their respective illegal splits. Furthermore, legally-split compounds elicited more accurate responses than legally-split pseudocompounds. In line with previous findings supporting a purely morpho-orthographic prelexical process with faster presentation times, these findings suggest a temporally distinct mechanism during visual word recognition.

We investigated how the properties of lexical items, which label object features, affect concept tokening. We addressed this issue by modeling data from three sources: (1) norms obtained from a dataset of 78,000 features to a set of pictures representing living and nonliving objects; (2) accuracy data from a picture-word priming congruency task with stimuli presented for 50-60 milliseconds; and (3) corpus data on the lexical properties of four different social usage count measures. We conducted two sets of analyses: one relying on sample count-based measures (i.e., measures based on the norming study: sample frequency, cue validity, feature distinctiveness), and a second relying on the social usage count-based measures (i.e., word frequency (WF), contextual diversity (CD), discourse contextual diversity (DCD), and user contextual diversity (UCD). Contrasting count and social usage-based measures allowed us to gain insight into the contribution of diverse semantic and socially oriented contextual measures of lexical items, and how they may affect concept tokening. Our results show that cue validity and feature distinctiveness were negative predictors of participants’ accuracy to congruency decisions—an effect which was more pronounced for distinctive features of living things. There was also a noticeable advantage for the UCD and DCD variables, over CD and WF. Overall, our results suggest that the conceptual system may be organized as a function of both, intrinsic properties of object features and usage based contextual measures of lexical items that label these features.

We investigated the early moments of visual word recognition,when the retinal information—by hypothesis split verticallyalong the fovea—is divided into two visual pathways,projecting the right visual field into the left hemisphere (LH),and the left visual field into the right hemisphere (RH).Wearing red/blue anaglyph glasses, participants performed alexical decision task to compounds (FOOTBALL) andmonomorphemic words that were either pseudo-compounds(CARPET) or unsegmentable (JINGLE). The stimuli werepresented (masked, 60 ms exposure) in three colorcombinations: all black, red/blue (ipsilateral visual pathways),and blue/red (contralateral pathways). For the red/blue andblue/red conditions, the colors were split either at themorpheme boundary (legal split) or at a character to the left orto the right of the split (illegal split). We found an advantage(RT and accuracy) of compounds over non-compounds,independent of pathway, and an advantage of legal vs. illegalconstituent split. Results suggest that the visual wordrecognition system performs parsing analyses that are inconsonant with the morphological objects of the language. Theadvantage of pseudo-compounds over unsegmentablessuggests that at an early—pre-lexical—stage the system ispartially insensitive to the semantic properties of the wholeword.

How are features and categories of objects represented in the brain? While numerous studies have identified category-specific regions for different categories of objects, the nature of the representation for individual objects remains elusive. We investigated this question by employing representational similarity analysis (Kriegskorte et al., 2006) to identify different types of object information reflected in fMRI activation patterns. Relying on Clarke et al's (2014) object naming data, we conducted a searchlight mapping analysis to assess whether the object dissimilarity predicted by various theoretical models of object categories and features corresponded to the dissimilarity defined by fMRI activity patterns. The object feature models we contrasted were based on three different sets of feature norms: (a) norming data we obtained from a dataset of 78,000 features produced by 100 participants for a set of 264 pictures (Antal et al., 2024), (b) the CLSB word feature norms (Devereux et al., 2014), and (c) McRae et al's (2005) word feature norms. Results will address the contribution of feature information to the representation of different object categories.

Numerous studies have found category-specific semantic deficits in Alzheimers disease (AD). Thus far, however, only asmall number of studies have investigated how semantic categories lexicalized by verbs are represented, and how thesecategories might be impaired in AD. We investigated the representation and breakdown of verb knowledge employingdifferent syntactic and semantic classes of verbs in a group of probable AD patients (N=10) and matched controls. Inour main task, we employed movies of events and states depicting verbs belonging to three different classes: causatives,perception/psychological, and movement verbs. These verbs differ with regards to their argument structure, the thematicroles they assign, and their hypothetical semantic templates. Patients had more difficult employing verbs of the percep-tion/psychological class. We suggest that thematic roles play the most important role in verb semantic representations. Wefurther suggest that verbs are not represented by decompositional semantic templates.