A Comparison of the Spatial Arrangement Method and the Total-Set Pairwise Rating Method for Obtaining Similarity Data in the Conceptual Domain.

We compare two methods for obtaining similarity data in the conceptual domain. In the Spatial Arrangement Method (SpAM), participants organize stimuli on a computer screen so that the distance between stimuli represents their perceived dissimilarity. In Total-Set Pairwise Rating Method (PRaM), participants rate the (dis)similarity of all pairs of stimuli on a Likert scale. In each of three studies, we had participants indicate the similarity of four sets of conceptual stimuli with either PRaM or SpAM. Studies 1 and 2 confirm two caveats that have been raised for SpAM. (i) While SpAM takes significantly less time to complete than PRaM, it yields less reliable data than PRaM does. (ii) Because of the spatial manner in which similarity is measured in SpAM, the method is biased against feature representations. Despite these differences, averaging SpAM and PRaM dissimilarity data across participants yields comparable aggregate data. Study 3 shows that by having participants only judge half of the pairs in PRaM, its duration can be significantly reduced, without affecting the dissimilarity distribution, but at the cost of a smaller reliability. Having participants arrange multiple subsets of the stimuli does not do away with the spatial bias of SpAM.

Semantic gender: Norms for 24,000 Dutch words and its role in word meaning.

Semantic gender norms are presented for 24,037 Dutch words. Eighty participants rated 6017 words each on a five-point Likert scale ranging from feminine to masculine. Each word was rated by ten male and ten female participants. The collected norms show high reliability and correlate well with similar norms in English. We show that semantic gender is distinct from other lexical dimensions such as valence, arousal, dominance, concreteness, and age of acquisition. Semantic gender is not the same as the grammatical gender of words, either. The collected norms can be predicted accurately using a semantic space based on word association data. A dimension explaining a good amount of variance is present in this space, indicating that semantic gender is an important component of the human meaning system.

Representation of associative and affective semantic similarity of abstract words in the lateral temporal perisylvian language regions.

The examination of semantic cognition has traditionally identified word concreteness as well as valence as two of the principal dimensions in the representation of conceptual knowledge. More recently, corpus-based vector space models as well as graph-theoretical analysis of large-scale task-related behavioural responses have revolutionized our insight into how the meaning of words is structured. In this fMRI study, we apply representational similarity analysis to investigate the conceptual representation of abstract words. Brain activity patterns were related to a cued-association based graph as well as to a vector-based co-occurrence model of word meaning. Twenty-six subjects (19 females and 7 males) performed an overt repetition task during fMRI. First, we performed a searchlight classification procedure to identify regions where activity is discriminable between abstract and concrete words. These regions were left inferior frontal gyrus, the upper and lower bank of the superior temporal sulcus bilaterally, posterior middle temporal gyrus and left fusiform gyrus. Representational Similarity Analysis demonstrated that for abstract words, the similarity of activity patterns in the cortex surrounding the superior temporal sulcus bilaterally and in the left anterior superior temporal gyrus reflects the similarity in word meaning. These effects were strongest for semantic similarity derived from the cued association-based graph and for affective similarity derived from either of the two models. The latter effect was mainly driven by positive valence words. This research highlights the close neurobiological link between the information structure of abstract and affective word content and the similarity in activity pattern in the lateral and anterior temporal language system.

Lexicosemantic, affective, and distributional norms for 1,000 Dutch adjectives.

The research of the word is still very much the research of the noun. Adjectives have been largely overlooked, despite being the second-largest word class in many languages and serving an important communicative function, because of the rich, nuanced qualifications they afford. Adjectives are also ideally suited to study the interface between cognition and emotion, as they naturally cover the entire range of lexicosemantic variables such as imageability (infinite-green), and affective variables such as valence (sad-happy). We illustrate this by showing how the centrality of words in the mental lexicon varies as a function of the words' affective dimensions, using newly collected norms for 1,000 Dutch adjectives. The norms include the lexicosemantic variables age of acquisition, familiarity, concreteness, and imageability; the affective variables valence, arousal, and dominance; and a variety of distributional variables, including network statistics resulting from a large-scale word association study. The norms are freely available from https://osf.io/nyg8v/, for researchers studying adjectives specifically or for whom adjectives constitute convenient stimuli to study other topics, such as vagueness, inference, spatial cognition, or affective word processing.

Left perirhinal cortex codes for semantic similarity between written words defined from cued word association.

Knowledge of visual and nonvisual attributes of concrete entities is distributed over neocortical uni- and polymodal association cortex. Here we investigated the role of left perirhinal cortex in explicit knowledge retrieval from written words. We examined whether it extended across visual and nonvisual properties, animate and inanimate entities, how this differed from picture input and how specific it was for perirhinal cortex compared to surrounding structures. The semantic similarity between stimuli was determined on the basis of a word association-based model. Eighteen participants participated in this event-related fMRI experiment. During property verification, the left perirhinal cortex coded for the similarity in meaning between written words. No differences were found between visual and nonvisual properties or between animate and inanimate entities. Among the surrounding regions, a semantic similarity effect for written words was also present in the left parahippocampal gyrus, but not in the hippocampus nor in the right perirhinal cortex. Univariate analysis revealed higher activity for visual property verification in visual processing regions and for nonvisual property verification in an extended system encompassing the superior temporal sulcus along its anterior-posterior axis, the inferior and the superior frontal gyrus. The association strength between the concept and the property correlated positively with fMRI response amplitude in visual processing regions, and negatively with response amplitude in left inferior and superior frontal gyrus. The current findings establish that input-modality determines the semantic similarity effect in left perirhinal cortex more than the content of the knowledge retrieved or the semantic control demand do. We propose that left perirhinal cortex codes for the association between a concrete written word and the object it refers to and operates as a connector hub linking written word input to the distributed cortical representation of word meaning.

The "Small World of Words" English word association norms for over 12,000 cue words.

Word associations have been used widely in psychology, but the validity of their application strongly depends on the number of cues included in the study and the extent to which they probe all associations known by an individual. In this work, we address both issues by introducing a new English word association dataset. We describe the collection of word associations for over 12,000 cue words, currently the largest such English-language resource in the world. Our procedure allowed subjects to provide multiple responses for each cue, which permits us to measure weak associations. We evaluate the utility of the dataset in several different contexts, including lexical decision and semantic categorization. We also show that measures based on a mechanism of spreading activation derived from this new resource are highly predictive of direct judgments of similarity. Finally, a comparison with existing English word association sets further highlights systematic improvements provided through these new norms.

The (un)reliability of item-level semantic priming effects.

Many researchers have tried to predict semantic priming effects using a myriad of variables (e.g., prime-target associative strength or co-occurrence frequency). The idea is that relatedness varies across prime-target pairs, which should be reflected in the size of the priming effect (e.g., cat should prime dog more than animal does). However, it is only insightful to predict item-level priming effects if they can be measured reliably. Thus, in the present study we examined the split-half and test-retest reliabilities of item-level priming effects under conditions that should discourage the use of strategies. The resulting priming effects proved extremely unreliable, and reanalyses of three published priming datasets revealed similar cases of low reliability. These results imply that previous attempts to predict semantic priming were unlikely to be successful. However, one study with an unusually large sample size yielded more favorable reliability estimates, suggesting that big data, in terms of items and participants, should be the future for semantic priming research.

Filling the gaps: A speeded word fragment completion megastudy.

In the speeded word fragment completion task, participants have to complete fragments such as tom_to as quickly and accurately as possible. Previous work has shown that this paradigm can successfully capture subtle priming effects (Heyman, De Deyne, Hutchison, & Storms Behavior Research Methods, 47, 580-606, 2015). In addition, it has several advantages over the widely used lexical decision task. That is, the speeded word fragment completion task is more efficient, more engaging, and easier. Given its potential, we conducted a study to gather speeded word fragment completion norms. The goal of this megastudy was twofold. On the one hand, it provides a rich database of over 8,000 stimuli, which can, for instance, be used in future research to equate stimuli on baseline response times. On the other hand, the aim was to gain insight into the underlying processes of the speeded word fragment completion task. To this end, item-level regression and mixed-effects analyses were performed on the response latencies using 23 predictor variables. Since all items were selected from the Dutch Lexicon Project (Keuleers, Diependaele, & Brysbaert Frontiers in Psychology, 1, 174, 2010), we ran the same analyses on lexical decision latencies to compare the two tasks. Overall, the results revealed many similarities, but also some remarkable differences, which are discussed. We propose that both tasks are complementary when examining visual word recognition. The article ends with a discussion of potential process models of the speeded word fragment completion task.

Estimating affective word covariates using word association data.

Word ratings on affective dimensions are an important tool in psycholinguistic research. Traditionally, they are obtained by asking participants to rate words on each dimension, a time-consuming procedure. As such, there has been some interest in computationally generating norms, by extrapolating words' affective ratings using their semantic similarity to words for which these values are already known. So far, most attempts have derived similarity from word co-occurrence in text corpora. In the current paper, we obtain similarity from word association data. We use these similarity ratings to predict the valence, arousal, and dominance of 14,000 Dutch words with the help of two extrapolation methods: Orientation towards Paradigm Words and k-Nearest Neighbors. The resulting estimates show very high correlations with human ratings when using Orientation towards Paradigm Words, and even higher correlations when using k-Nearest Neighbors. We discuss possible theoretical accounts of our results and compare our findings with previous attempts at computationally generating affective norms.

How do people learn from negative evidence? Non-monotonic generalizations and sampling assumptions in inductive reasoning.

A robust finding in category-based induction tasks is for positive observations to raise the willingness to generalize to other categories while negative observations lower the willingness to generalize. This pattern is referred to as monotonic generalization. Across three experiments we find systematic non-monotonicity effects, in which negative observations raise the willingness to generalize. Experiments 1 and 2 show that this effect emerges in hierarchically structured domains when a negative observation from a different category is added to a positive observation. They also demonstrate that this is related to a specific kind of shift in the reasoner's hypothesis space. Experiment 3 shows that the effect depends on the assumptions that the reasoner makes about how inductive arguments are constructed. Non-monotonic reasoning occurs when people believe the facts were put together by a helpful communicator, but monotonicity is restored when they believe the observations were sampled randomly from the environment.

Using the speeded word fragment completion task to examine semantic priming.

The present research investigates semantic priming with an adapted version of the word fragment completion task. In this task, which we refer to as the speeded word fragment completion task, participants need to complete words such as lett_ce (lettuce), from which one letter was omitted, as quickly as possible. This paradigm has some interesting qualities in comparison with the traditionally used lexical decision task. That is, it requires no pseudowords, it is more engaging for participants, and most importantly, it allows for a more fine-grained investigation of semantic activation. In two studies, we found that words were completed faster when the preceding trial comprised a semantically related fragment such as tom_to (tomato) than when it comprised an unrelated fragment such as guit_r (guitar). A third experiment involved a lexical decision task, to compare both paradigms. The results showed that the magnitude of the priming effect was similar, but item-level priming effects were inconsistent over tasks. Crucially, the speeded word fragment completion task obtained strong priming effects for highly frequent, central words, such as work, money, and warm, whereas the lexical decision task did not. In a final experiment featuring only short, highly frequent words, the lexical decision task failed to find a priming effect, whereas the fragment completion task did obtain a robust effect. Taken together, these results suggest that the speeded word fragment completion task may prove a viable alternative for examining semantic priming.

If My Memory Serves Me Well: Investigating My Memory for the Past 24 Years.

This paper reports on a study of my autobiographical memory for 2691 notes recorded over 24 years in my diary, without any intention to ever use the notes as test material. I never read any of the notes again until the start of the memory study. I remembered less than two thirds of the recorded events and the retention curve showed a curvilinear shape. I dated 2% of the described events correctly but misdated on average about one and a half year, with an equal number of over and underestimations of the event age. Retention correlated significantly with ratings of salience, emotional involvement, pleasantness, event rehearsal and self-relatedness, but not with intimacy. Dating accuracy correlated with salience, pleasantness, intimacy and event rehearsal, but not with emotional involvement or self-relatedness. Regression analyses showed that event rehearsal was the best predictor of retention and dating, but the predictive value of other ratings was dependent on the content of the recorded events.

Idealness and similarity in goal-derived categories: a computational examination.

The finding that the typicality gradient in goal-derived categories is mainly driven by ideals rather than by exemplar similarity has stood uncontested for nearly three decades. Due to the rather rigid earlier implementations of similarity, a key question has remained--that is, whether a more flexible approach to similarity would alter the conclusions. In the present study, we evaluated whether a similarity-based approach that allows for dimensional weighting could account for findings in goal-derived categories. To this end, we compared a computational model of exemplar similarity (the generalized context model; Nosofsky, Journal of Experimental Psychology. General 115:39-57, 1986) and a computational model of ideal representation (the ideal-dimension model; Voorspoels, Vanpaemel, & Storms, Psychonomic Bulletin & Review 18:1006-114, 2011) in their accounts of exemplar typicality in ten goal-derived categories. In terms of both goodness-of-fit and generalizability, we found strong evidence for an ideal approach in nearly all categories. We conclude that focusing on a limited set of features is necessary but not sufficient to account for the observed typicality gradient. A second aspect of ideal representations--that is, that extreme rather than common, central-tendency values drive typicality--seems to be crucial.

Better explanations of lexical and semantic cognition using networks derived from continued rather than single-word associations.

In this article, we describe the most extensive set of word associations collected to date. The database contains over 12,000 cue words for which more than 70,000 participants generated three responses in a multiple-response free association task. The goal of this study was (1) to create a semantic network that covers a large part of the human lexicon, (2) to investigate the implications of a multiple-response procedure by deriving a weighted directed network, and (3) to show how measures of centrality and relatedness derived from this network predict both lexical access in a lexical decision task and semantic relatedness in similarity judgment tasks. First, our results show that the multiple-response procedure results in a more heterogeneous set of responses, which lead to better predictions of lexical access and semantic relatedness than do single-response procedures. Second, the directed nature of the network leads to a decomposition of centrality that primarily depends on the number of incoming links or in-degree of each node, rather than its set size or number of outgoing links. Both studies indicate that adequate representation formats and sufficiently rich data derived from word associations represent a valuable type of information in both lexical and semantic processing.

On domain differences in categorization and context variety.

Membership in many natural categories is considered all-or-none, while membership in most artifact categories is found to be graded. We introduce an alternative for the prevailing view that this domain difference in categorization results from representational differences. The context variety account posits that an item's gradedness reflects the variety of contexts it appears in. Items that feature in a variety of contexts are assumed to be more likely to elicit a graded categorization response, since the suggested target category only provides one of many solutions to the question of the item's identity. We review earlier work that suggested a domain difference in context variety, with artifactual items appearing in a greater variety of contexts than natural ones. The context variety domain difference is established in two separate experiments but is shown not to explain the domain difference in categorization. A selection of artifactual and natural items, for which the domain difference in context variety is reversed, is presented for categorization in a third experiment. This selection, too, fails to provide evidence for the context variety account of categorization differences. The domain difference in categorization is shown to be robust against this manipulation. Context variety appears to have no bearing on categorization, so the context variety account is not a sustainable alternative to accounts that posit representational differences between natural and artifact categories.

Raising argument strength using negative evidence: a constraint on models of induction.

Both intuitively, and according to similarity-based theories of induction, relevant evidence raises argument strength when it is positive and lowers it when it is negative. In three experiments, we tested the hypothesis that argument strength can actually increase when negative evidence is introduced. Two kinds of argument were compared through forced choice or sequential evaluation: single positive arguments (e.g., "Shostakovich's music causes alpha waves in the brain; therefore, Bach's music causes alpha waves in the brain") and double mixed arguments (e.g., "Shostakovich's music causes alpha waves in the brain, X's music DOES NOT; therefore, Bach's music causes alpha waves in the brain"). Negative evidence in the second premise lowered credence when it applied to an item X from the same subcategory (e.g., Haydn) and raised it when it applied to a different subcategory (e.g., AC/DC). The results constitute a new constraint on models of induction.

The generalized polymorphous concept account of graded structure in abstract categories.

Abstract categories present with graded structure. The extent to which feature commonality between exemplars and category provides a satisfying account of this graded structure varies from one abstract category to the other (Hampton, 1981). We investigate whether the incorporation of features that exemplars share with external categories yields an improved account of abstract categories' graded structures. In doing so, we follow the suggestion that abstract categories are relational in nature (Goldstone, 1996; Wiemer-Hastings & Xu, 2005). The generalized polymorphous concept model, which incorporates both types of features, is found to improve the account of typicality and category membership in three of seven studied abstract categories. These three categories are found to be the most abstract, suggesting that it is appropriate to think of abstract categories as varying along a continuum of abstractness/interrelatedness rather than as a distinct type of category altogether.

Geometric and featural representations in semantic concepts.

We explore the adequacy of two types of similarity representation in the context of semantic concepts. To this end, we evaluate different categorization models, assuming either a geometric or a featural representation, using categorization decisions involving familiar and unfamiliar foods and animals. The study aims to assess the optimal stimulus representation as a function of the familiarity of the stimuli. For the unfamiliar stimuli, the geometric categorization models provide the best account of the categorization data, whereas for the familiar stimuli, the featural categorization models provide the best account. This pattern of results suggests that people rely on perceptual information to assign an unfamiliar stimulus to a category but rely on more elaborate conceptual knowledge when assigning a familiar stimulus.

Abstraction and model evaluation in category learning.

Thirty previously published data sets, from seminal category learning tasks, are reanalyzed using the varying abstraction model (VAM). Unlike a prototype-versus-exemplar analysis, which focuses on extreme levels of abstraction only, a VAM analysis also considers the possibility of partial abstraction. Whereas most data sets support no abstraction when only the extreme possibilities are considered, we show that evidence for abstraction can be provided using the broader view on abstraction provided by the VAM. The present results generalize earlier demonstrations of partial abstraction (Vanpaemel & Storms, 2008), in which only a small number of data sets was analyzed. Following the dominant modus operandi in category learning research, Vanpaemel and Storms evaluated the models on their best fit, a practice known to ignore the complexity of the models under consideration. In the present study, in contrast, model evaluation not only relies on the maximal likelihood, but also on the marginal likelihood, which is sensitive to model complexity. Finally, using a large recovery study, it is demonstrated that, across the 30 data sets, complexity differences between the models in the VAM family are small. This indicates that a (computationally challenging) complexity-sensitive model evaluation method is uncalled for, and that the use of a (computationally straightforward) complexity-insensitive model evaluation method is justified.

Perception of self and other in psychosis: a method for analyzing the structure of the phenomenology.

Although the phenomenology accompanying psychoses is fascinating, hitherto empirical examinations have been qualitative and thus limited in their clinical conclusions regarding the actual underlying cognitive mechanisms responsible for the formation and maintenance of the delusion, which is often distressing to the patient. We investigated the internal cognitive structure (i.e., connections) of some delusions pertaining to self and others in a patient with psychosis who was very fluent and thus able to provide a lucid account of his phenomenological experiences. To this end we employed a clustering method (HICLAS disjunctive model) in conjunction with standard neuropsychological tests. A well-fitting, but parsimonious solution revealed the absence of unique feature sets associated with certain persons, findings that provide a compelling case underlying the confusion in certain instances between real and delusional people. We illustrate the methodology in one patient and suggest that it is sensitive enough to explore the structure of delusions, which in conjunction with standard neuropsychological and clinical assessments promises to be useful in uncovering the mechanisms underlying delusions in psychosis.