Recognition memory and featural similarity between concepts: The pupil's point of view

lmeEEG: Mass linear mixed-effects modeling of EEG data with crossed random effects

BACKGROUND

Mixed-effects models are the current standard for the analysis of behavioral studies in psycholinguistics and related fields, given their ability to simultaneously model crossed random effects for subjects and items. However, they are hardly applied in neuroimaging and psychophysiology, where the use of mass univariate analyses in combination with permutation testing would be too computationally demanding to be practicable with mixed models.

NEW METHOD

Here, we propose and validate an analytical strategy that enables the use of linear mixed models (LMM) with crossed random intercepts in mass univariate analyses of EEG data (lmeEEG). It avoids the unfeasible computational costs that would arise from massive permutation testing with LMM using a simple solution: removing random-effects contributions from EEG data and performing mass univariate linear analysis and permutations on the obtained marginal EEG.

RESULTS

lmeEEG showed excellent performance properties in terms of power and false positive rate.

COMPARISON WITH EXISTING METHODS

lmeEEG overcomes the computational costs of standard available approaches (our method was indeed more than 300 times faster).

CONCLUSIONS

lmeEEG allows researchers to use mixed models with EEG mass univariate analyses. Thanks to the possibility offered by the method described here, we anticipate that LMM will become increasingly important in neuroscience. Data and codes are available at osf.io/kw87a. The codes and a tutorial are also available at github.com/antovis86/lmeEEG.

Pupil size tracks cue-trace interactions during episodic memory retrieval

Our ability to remember past events requires not only storing enduring engrams or memory traces of these events, but also successfully reactivating these latent traces in response to appropriate cues at the time of retrieval-a process that has been termed ecphory. However, relatively little is known about the processes that facilitate the dynamic interactions between retrieval cues and stored memory traces that are critical for successful recognition and recollection. Recently, an intriguing link between pupil dilation and recognition memory has been identified, with studied items eliciting greater pupil dilation than unstudied items during retrieval. However, the processes contributing to this "pupillary old/new effect" remain unresolved, with current explanations suggesting that it reflects the strength of the underlying memory trace. Here, we explore the novel hypothesis that the pupillary old/new effect does not index memory strength alone, but rather reflects the facilitation of cue-trace interactions during episodic memory retrieval that may be supported by activity within the pupil-linked locus coeruleus-noradrenergic (LC-NA) arousal system. First, we show that the magnitude of pupil dilation is influenced by the degree of overlap between cue and trace information. Second, we find that the magnitude of pupil dilation reflects the amount of study contextual information reinstated during retrieval. These findings provide a novel framework for understanding the pupillary old/new effect, and identify a potential role for the LC-NA system in recognition memory retrieval.

CONcreTEXT norms: Concreteness ratings for Italian and English words in context

Concreteness is a fundamental dimension of word semantic representation that has attracted more and more interest to become one of the most studied variables in the psycholinguistic and cognitive neuroscience literature in the last decade. Concreteness effects have been found at both the brain and the behavioral levels, but they may vary depending on the constraints of the context and task demands. In this study, we collected concreteness norms for English and Italian words presented in different context sentences to allow better control and manipulation of concreteness in future psycholinguistic research. First, we observed high split-half correlations and Cronbach's alpha coefficients, suggesting that our ratings were highly reliable and can be used in Italian- and English-speaking populations. Second, our data indicate that the concreteness ratings are related to the lexical density and accessibility of the sentence in both English and Italian. We also found that the concreteness of words in isolation was highly correlated with that of words in context. Finally, we analyzed differences between nouns and verbs in concreteness ratings without significant effects. Our new concreteness norms of words in context are a valuable source of information for future research in both the English and Italian language. The complete database is available on the Open Science Framework (doi: 10.17605/OSF.IO/U3PC4).

Brain Signatures of Embodied Semantics and Language: A Consensus Paper

According to embodied theories (including embodied, embedded, extended, enacted, situated, and grounded approaches to cognition), language representation is intrinsically linked to our interactions with the world around us, which is reflected in specific brain signatures during language processing and learning. Moving on from the original rivalry of embodied vs. amodal theories, this consensus paper addresses a series of carefully selected questions that aim at determining when and how rather than whether motor and perceptual processes are involved in language processes. We cover a wide range of research areas, from the neurophysiological signatures of embodied semantics, e.g., event-related potentials and fields as well as neural oscillations, to semantic processing and semantic priming effects on concrete and abstract words, to first and second language learning and, finally, the use of virtual reality for examining embodied semantics. Our common aim is to better understand the role of motor and perceptual processes in language representation as indexed by language comprehension and learning. We come to the consensus that, based on seminal research conducted in the field, future directions now call for enhancing the external validity of findings by acknowledging the multimodality, multidimensionality, flexibility and idiosyncrasy of embodied and situated language and semantic processes.

Does surprise enhance infant memory? Assessing the impact of the encoding context on subsequent object recognition

A discrepancy between what was predicted and what is observed has been linked to increased looking times, changes in brain electrical activity, and increased pupil dilation in infants. These processes associated with heightened attention and readiness to learn might enhance the encoding and memory consolidation of the surprising object, as suggested by both the infant and the adult literature. We therefore investigated whether the presence of surprise during the encoding context enhances subsequent encoding and recognition memory processes for the items that violated infants' expectations. Seventeen-month-olds viewed 20 familiar objects, half of which were labeled correctly, while the other half were mislabeled. Subsequently, infants were presented with a silent recognition memory test where the previously labeled objects appeared along with new images. Pupil dilation was measured, with more dilated pupils indicating (1) surprise during those labeling events where the item was mislabeled and (2) successful retrieval processes during the memory test. Infants responded with more pupil dilation to mislabeling compared to correct labeling. Importantly, despite the presence of a surprise response during mislabeling, infants only differentiated between the previously seen and unseen items at the memory test, offering no evidence that surprise had facilitated the encoding of the mislabeled items.

Inferior parietal lobule is sensitive to different semantic similarity relations for concrete and abstract words

Similarity measures, the extent to which two concepts have similar meanings, are the key to understand how concepts are represented, with different theoretical perspectives relying on very different sources of data from which similarity can be calculated. While there is some commonality in similarity measures, the extent of their correlation is limited. Previous studies also suggested that the relative performance of different similarity measures may also vary depending on concept concreteness and that the inferior parietal lobule (IPL) may be involved in the integration of conceptual features in a multimodal system for the semantic categorization. Here, we tested for the first time whether theory-based similarity measures predict the pattern of brain activity in the IPL differently for abstract and concrete concepts. English speakers performed a semantic decision task, while we recorded their brain activity in IPL through fNIRS. Using representational similarity analysis, results indicated that the neural representational similarity in IPL conformed to the lexical co-occurrence among concrete concepts (regardless of the hemisphere) and to the affective similarity among abstract concepts in the left hemisphere only, implying that semantic representations of abstract and concrete concepts are characterized along different organizational principles in the IPL. We observed null results for the decoding accuracy. Our study suggests that the use of the representational similarity analysis as a complementary analysis to the decoding accuracy is a promising tool to reveal similarity patterns between theoretical models and brain activity recorded through fNIRS.

Pupil size changes signal hippocampus-related memory functions

A major task of episodic memory is to create unique, distinguishable representations of highly overlapping perceptual inputs. Several studies on this basic function have shown that it is based on the intact functioning of certain subregions of the hippocampus and is among the most sensitive behavioral indicators of mild cognitive impairment (MCI) and dementia. Here we assessed pupil dilation associated with performance in a widely used recognition paradigm that aims to uncover the intactness of fine-graded mnemonic discrimination. A sample of healthy undergraduate students was used. First, we showed that the correct discrimination between highly similar lure items and target items elicit larger pupil response than correct target identification. Second, we found that mnemonic discrimination is associated with larger pupil response in general as compared to target identification, regardless of whether the response was correct or not. These results suggest the pupil changes differentiate mnemonic discrimination and memory identification processes in recognition performance.

Core features: measures and characterization for different languages

According to the feature-based view of semantic representation, concepts can be represented as distributed networks of semantic features, which contribute with different weights to determine the overall meaning of a concept. The study of semantic features, typically collected in property generation tasks, is enriched with measures indicating the informativeness and distinctiveness of a given feature for the related concepts. However, while these measures have been provided in several languages (e.g. Italian, Spanish and English), they have hardly been applied comparatively across languages. The purpose of this paper is to investigate language-related differences and similarities emerging from the semantic representation of aggregated core features. Features with higher salience for a set of concrete concepts are identified and described in terms of their feature type. Then, comparisons are made between domains (natural vs. artefacts) and languages (Italian, Spanish and English) and descriptive statistics are provided. These results show that the characterization of concrete concepts is overall fairly stable across languages, although interesting cross-linguistic differences emerged. We will discuss the implications of our findings in relation to the theoretical paradigm of semantic feature norms, as well as in relation to speakers' mutual understanding in multilingual settings.

Feature distinctiveness effects in language acquisition and lexical processing: Insights from megastudies

Semantic features are central to many influential theories of word meaning and semantic memory, but new methods of quantifying the information embedded in feature production norms are needed to advance our understanding of semantic processing and language acquisition. This paper capitalized on databases of semantic feature production norms and age-of-acquisition ratings, and megastudies including the English Lexicon Project and the Calgary Semantic Decision Project, to examine the influence of feature distinctiveness on language acquisition, visual lexical decision, and semantic decision. A feature network of English words was constructed such that edges in the network represented feature distance, or dissimilarity, between words (i.e., Jaccard and Manhattan distances of probability distributions of features elicited for each pair of words), enabling us to quantify the relative feature distinctiveness of individual words relative to other words in the network. Words with greater feature distinctiveness tended to be acquired earlier. Regression analyses of megastudy data revealed that Manhattan feature distinctiveness inhibited performance on the visual lexical decision task, facilitated semantic decision performance for concrete concepts, and inhibited semantic decision performance for abstract concepts. These results demonstrate the importance of considering the structural properties of words embedded in a semantic feature space in order to increase our understanding of semantic processing and language acquisition.

A practical primer on processing semantic property norm data

Semantic property listing tasks require participants to generate short propositions (e.g., [Formula: see text], [Formula: see text]) for a specific concept (e.g., DOG). This task is the cornerstone of the creation of semantic property norms which are essential for modeling, stimuli creation, and understanding similarity between concepts. Despite the wide applicability of semantic property norms for a large variety of concepts across different groups of people, the methodological aspects of the property listing task have received less attention, even though the procedure and processing of the data can substantially affect the nature and quality of the measures derived from them. The goal of this paper is to provide a practical primer on how to collect and process semantic property norms. We will discuss the key methods to elicit semantic properties and compare different methods to derive meaningful representations from them. This will cover the role of instructions and test context, property preprocessing (e.g., lemmatization), property weighting, and relationship encoding using ontologies. With these choices in mind, we propose and demonstrate a processing pipeline that transparently documents these steps, resulting in improved comparability across different studies. The impact of these choices will be demonstrated using intrinsic (e.g., reliability, number of properties) and extrinsic measures (e.g., categorization, semantic similarity, lexical processing). This practical primer will offer potential solutions to several long-standing problems and allow researchers to develop new property listing norms overcoming the constraints of previous studies.

The interplay between control processes and feature relevance: Evidence from dual-task methodology

Neuropsychological studies suggest a distinction between (a) semantic knowledge and (b) control processes that shape the retrieval of conceptual information to suit the task or context. These aspects of semantic cognition are specifically impaired in patients with semantic dementia and semantic aphasia, respectively. However, interactions between the structure of knowledge and control processes that are expected during semantic retrieval have not been fully characterised. In particular, domain-general executive resources may not have equal relevance for the capacity to promote weak yet task relevant features (i.e., "controlled retrieval) and to ignore or suppress distracting information (i.e., "selection"). Here, using a feature selection task, we tested the contribution of featural relevance to semantic performance in healthy participants under conditions of divided attention. Healthy participants showed greater dual-task disruption as the relevance value of the distractor feature linearly increased, supporting the emerging view that semantic relevance is one of the organising principles of the structure of semantic representation. Moreover, word frequency, and inter-correlational strength affected overall performance, but they did not show an interaction with dual-task conditions. These results suggest that domain-general control processes, disrupted by divided attention, are more important to the capacity to efficiently avoid distracting information during semantic decision-making than to the promotion of weak target features. The present study therefore provides novel information about the nature of the interaction between structured conceptual knowledge and control processes that support the retrieval of appropriate information and relates these results to a new theoretical framework, termed controlled semantic cognition.

Semantic representation of abstract and concrete words: a minireview of neural evidence

Evidence from both behavioral and neuropsychological studies suggest that different types of organizational principles govern semantic representations of abstract and concrete words. The reviewed neuroimaging studies provide new evidence about the role of brain areas of the semantic network involved in the encoding of some types of information during processing of abstract and concrete concepts, better characterizing the neural underpinnings and the organizational principles of semantic representation of these types of word.