Fermín Moscoso del Prado Martín

On the origin of the cumulative semantic inhibition effect

We investigated whether the cumulative semantic inhibition effect found by Howard, Nickels, Coltheart, and Cole-Virtue (2006) provides information about semantic representations. By applying more sensitive statistical analyses to the original data set, we found a significant variation in the magnitude of the effect across categories. This variation cannot be explained by the naming speed of each category. In addition, using a subsample of the data, a second cumulative effect arouse for newly defined supracategories, over and above the effect of the original ones. We discuss these findings in terms of the representations that drive lexical access and show that they favor featural or distributed hypotheses.

Semantic similarity influences early morphological priming in Serbian: A challenge to form-then-meaning accounts of word recognition

Semantically similar (e.g., coolant–COOL) primes have produced greater facilitation than have form-similar but semantically dissimilar (e.g., rampant–RAMP) primes when English words have appeared in the forward-masked primed lexical decision task (Feldman, O’Connor, & Moscoso del Prado Martín, Psychonomic Bulletin & Review 16: 684–691, 2009). These results challenge claims that form-based, semantically blind activation underlies early morphological facilitation. Some have argued that the English materials in previous studies were not ideally constructed, insofar as the types of spelling changes to affixed stems differed in the semantically similar and dissimilar pairs. The present study exploited Serbian’s bialphabetism, rich morphology, and homographic (form-identical) stems to replicate early effects of semantic similarity. Furthermore, it incorporated within-target manipulations of prime type and of alphabet, such that the alphabets of the prime–target pairs matched in Experiment 1a and alternated in Experiment 1b. Importantly, no letter or phoneme changes occurred between the stems of the primes and targets. These results revealed significant effects of semantic similarity that are comparable with and without alphabet alternation. The semantic effects in Serbian replicated almost exactly those in English (Feldman et al., Psychonomic Bulletin & Review 16: 684–691, 2009), which suggests that even early in the course of processing, morphemes are units of meaning as well as of form. The results failed to support models of lexical processing that postulate sequential access, first to the morphological form, and then to the semantic aspects of words.

Information content versus word length in random typing

Recently, it has been claimed that a linear relationship between a measure of information content and word length is expected from word length optimization and it has been shown that this linearity is supported by a strong correlation between information content and word length in many languages (Piantadosi et al 2011 Proc. Nat. Acad. Sci. 108 3825). Here, we study in detail some connections between this measure and standard information theory. The relationship between the measure and word length is studied for the popular random typing process where a text is constructed by pressing keys at random from a keyboard containing letters and a space behaving as a word delimiter. Although this random process does not optimize word lengths according to information content, it exhibits a linear relationship between information content and word length. The exact slope and intercept are presented for three major variants of the random typing process. A strong correlation between information content and word length can simply arise from the units making a word (e.g., letters) and not necessarily from the interplay between a word and its context as proposed by Piantadosi and co-workers. In itself, the linear relation does not entail the results of any optimization process.

Constant conditional entropy and related hypotheses

Constant entropy rate (conditional entropies must remain constant as the sequence length increases) and uniform information density (conditional probabilities must remain constant as the sequence length increases) are two information theoretic principles that are argued to underlie a wide range of linguistic phenomena. Here we revise the predictions of these principles in the light of Hilbergs law on the scaling of conditional entropy in language and related laws. We show that constant entropy rate (CER) and two interpretations for uniform information density (UID), full UID and strong UID, are inconsistent with these laws. Strong UID implies CER but the reverse is not true. Full UID, a particular case of UID, leads to costly uncorrelated sequences that are totally unrealistic. We conclude that CER and its particular cases are incomplete hypotheses about the scaling of conditional entropies.

Vocabulary, Grammar, Sex, and Aging

Understanding the changes in our language abilities along the lifespan is a crucial step for understanding the aging process both in normal and in abnormal circumstances. Besides controlled experimental tasks, it is equally crucial to investigate language in unconstrained conversation. I present an information-theoretical analysis of a corpus of dyadic conversations investigating how the richness of the vocabulary, the word-internal structure (inflectional morphology), and the syntax of the utterances evolves as a function of the speakers age and sex. Although vocabulary diversity increases throughout the lifetime, grammatical diversities follow a different pattern, which also differs between women and men. Women use increasingly diverse syntactic structures at least up to their late fifties, and they do not deteriorate in terms of fluency through their lifespan. However, from age 45 onward, men exhibit a decrease in the diversity of the syntactic structures they use, coupled with an increased number of speech disfluencies.

Case and Cause in Icelandic: Reconstructing Causal Networks of Cascaded Language Changes

Linguistic drift is a process that produces slow irreversible changes in the grammar and function of a language’s constructions. Importantly, changes in a part of a language can have trickle down effects, triggering changes elsewhere in that language. Although such causally triggered chains of changes have long been hypothesized by historical linguists, no explicit demonstration of the actual causality has been provided. In this study, we use cooccurrence statistics and machine learning to demonstrate that the functions of morphological cases experience a slow, irreversible drift along history, even in a language as conservative as is Icelandic. Crucially, we then move on to demonstrate ‐using the notion of Granger-causality‐ that there are explicit causal connections between the changes in the functions of the different cases, which are consistent with documented processes in the history of Icelandic. Our technique provides a means for the quantitative reconstruction of connected networks of subtle linguistic changes.

Does a focus on universals represent a new trend in word recognition

Comparisons across languages have long been a means to investigate universal properties of the cognitive system. Although differences between languages may be salient, it is the underlying similarities that have advanced our understanding of language processing. Frost is not unique in emphasizing that the interaction among linguistic codes reinforces the inadequacy of constructing a model of word recognition where orthographic processes operate in isolation.

Explicit Causal Connections between the Acquisition of Linguistic Tiers: Evidence from Dynamical Systems Modeling

In this study, we model the causal links between the complexities of different macroscopic aspects of child language. We consider pairs of sequences of measurements of the quantity and diversity of the lexical and grammatical properties. Each pair of sequences is taken as the trajectory of a high-dimensional dynamical system, some of whose dimensions are unknown. We use Multispatial Convergent Cross Mapping to ascertain the directions of causality between the pairs of sequences. Our results provide support for the hypothesis that children learn grammar through distributional learning, where the generalization of smaller structures enables generalizations at higher levels, consistent with the proposals of construction-based approaches to language.