Word Type and Frequency Effects on Lexical Decisions Are Process-dependent and Start Early.

When encountering letter strings, we rapidly determine whether they are words. The speed of such lexical decisions (LDs) is affected by word frequency. Apart from influencing late, decision-related, processing stages, frequency has also been shown to affect very early stages, and even the processing of nonwords.

The impact of mood-induction on maladaptive thinking in the vulnerability for depression.

Background And Objectives: Mind-wandering, and specifically the frequency and content of mind-wandering, plays an important role in the psychological well-being of individuals. Repetitive negative thinking has been associated with a high risk to develop and maintain Major Depressive Disorder. We here combined paradigms and techniques from cognitive sciences and experimental clinical psychology to study the transdiagnostic psychiatric phenomenon of repetitive negative thinking.

A cognitive modeling approach to learning and using reference biases in language.

During real-time language processing, people rely on linguistic and non-linguistic biases to anticipate upcoming linguistic input. One of these linguistic biases is known as the , wherein language users anticipate that certain entities will be rementioned in the discourse based on the entity's particular role in an expressed causal event. For example, when language users encounter a sentence like "Elizabeth congratulated Tina…" during real-time language processing, they seemingly anticipate that the discourse will continue about Tina, the object referent, rather than Elizabeth, the subject referent.

An exploration of error-driven learning in simple two-layer networks from a discriminative learning perspective.

Error-driven learning algorithms, which iteratively adjust expectations based on prediction error, are the basis for a vast array of computational models in the brain and cognitive sciences that often differ widely in their precise form and application: they range from simple models in psychology and cybernetics to current complex deep learning models dominating discussions in machine learning and artificial intelligence. However, despite the ubiquity of this mechanism, detailed analyses of its basic workings uninfluenced by existing theories or specific research goals are rare in the literature. To address this, we present an exposition of error-driven learning - focusing on its simplest form for clarity - and relate this to the historical development of error-driven learning models in the cognitive sciences.

Online Processing of Temporal Agreement in a Grammatical Tone Language: An ERP Study.

Previous electrophysiological studies that have examined temporal agreement violations in (Indo-European) languages that use grammatical affixes to mark time reference, have found a Left Anterior Negativity (LAN) and/or P600 ERP components, reflecting morpho-syntactic and syntactic processing, respectively. The current study investigates the electrophysiological processing of temporal relations in an African language (Akan) that uses grammatical tone, rather than morphological inflection, for time reference. Twenty-four native speakers of Akan listened to sentences with time reference violations.

Order Matters! Influences of Linear Order on Linguistic Category Learning.

Linguistic category learning has been shown to be highly sensitive to linear order, and depending on the task, differentially sensitive to the information provided by preceding category markers (premarkers, e.g., gendered articles) or succeeding category markers (postmarkers, e.

Analyzing the Time Course of Pupillometric Data.

This article provides a tutorial for analyzing pupillometric data. Pupil dilation has become increasingly popular in psychological and psycholinguistic research as a measure to trace language processing. However, there is no general consensus about procedures to analyze the data, with most studies analyzing extracted features from the pupil dilation data instead of analyzing the pupil dilation trajectories directly.

Perception of spectrally degraded reflexives and pronouns by children.

Speech perception skills in cochlear-implant users are often measured with simple speech materials. In children, it is crucial to fully characterize linguistic development, and this requires linguistically more meaningful materials. The authors propose using the comprehension of reflexives and pronouns, as these specific skills are acquired at different ages.

How WM load influences linguistic processing in adults: a computational model of pronoun interpretation in discourse.

This paper presents a study of the effect of working memory load on the interpretation of pronouns in different discourse contexts: stories with and without a topic shift. We discuss a computational model (in ACT-R, Anderson, 2007) to explain how referring expressions are acquired and used. On the basis of simulations of this model, it is predicted that WM constraints only affect adults' pronoun resolution in stories with a topic shift, but not in stories without a topic shift.

Cognitive architectures and language acquisition: a case study in pronoun comprehension.

In this paper we discuss a computational cognitive model of children's poor performance on pronoun interpretation (the so-called Delay of Principle B Effect, or DPBE). This cognitive model is based on a theoretical account that attributes the DPBE to children's inability as hearers to also take into account the speaker's perspective. The cognitive model predicts that child hearers are unable to do so because their speed of linguistic processing is too limited to perform this second step in interpretation.