New Perspectives on the Aging Lexicon

Finding the Words: How Does the Aging Brain Process Language? A Focused Review of Brain Connectivity and Compensatory Pathways

As people age, there is a natural decline in cognitive functioning and brain structure. However, the relationship between brain function and cognition in older adults is neither straightforward nor uniform. Instead, it is complex, influenced by multiple factors, and can vary considerably from one person to another. Reserve, compensation, and maintenance mechanisms may help explain why some older adults can maintain high levels of performance while others struggle. These mechanisms are often studied concerning memory and executive functions that are particularly sensitive to the effects of aging. However, language abilities can also be affected by age, with changes in production fluency. The impact of brain changes on language abilities needs to be further investigated to understand the dynamics and patterns of aging, especially successful aging. We previously modeled several compensatory profiles of language production and lexical access/retrieval in aging within the Lexical Access and Retrieval in Aging (LARA) model. In the present paper, we propose an extended version of the LARA model, called LARA-Connectivity (LARA-C), incorporating recent evidence on brain connectivity. Finally, we discuss factors that may influence the strategies implemented with aging. The LARA-C model can serve as a framework to understand individual performance and open avenues for possible personalized interventions.

Asynchronous behavioral and neurophysiological changes in word production in the adult lifespan

Behavioral and brain-related changes in word production have been claimed to predominantly occur after 70 years of age. Most studies investigating age-related changes in adulthood only compared young to older adults, failing to determine whether neural processes underlying word production change at an earlier age than observed in behavior. This study aims to fill this gap by investigating whether changes in neurophysiological processes underlying word production are aligned with behavioral changes. Behavior and the electrophysiological event-related potential patterns of word production were assessed during a picture naming task in 95 participants across five adult lifespan age groups (ranging from 16 to 80 years old). While behavioral performance decreased starting from 70 years of age, significant neurophysiological changes were present at the age of 40 years old, in a time window (between 150 and 220 ms) likely associated with lexical-semantic processes underlying referential word production. These results show that neurophysiological modifications precede the behavioral changes in language production; they can be interpreted in line with the suggestion that the lexical-semantic reorganization in mid-adulthood influences the maintenance of language skills longer than for other cognitive functions.

Cognitive modelling of concepts in the mental lexicon with multilayer networks: Insights, advancements, and future challenges

The mental lexicon is a complex cognitive system representing information about the words/concepts that one knows. Over decades psychological experiments have shown that conceptual associations across multiple, interactive cognitive levels can greatly influence word acquisition, storage, and processing. How can semantic, phonological, syntactic, and other types of conceptual associations be mapped within a coherent mathematical framework to study how the mental lexicon works? Here we review cognitive multilayer networks as a promising quantitative and interpretative framework for investigating the mental lexicon. Cognitive multilayer networks can map multiple types of information at once, thus capturing how different layers of associations might co-exist within the mental lexicon and influence cognitive processing. This review starts with a gentle introduction to the structure and formalism of multilayer networks. We then discuss quantitative mechanisms of psychological phenomena that could not be observed in single-layer networks and were only unveiled by combining multiple layers of the lexicon: (i) multiplex viability highlights language kernels and facilitative effects of knowledge processing in healthy and clinical populations; (ii) multilayer community detection enables contextual meaning reconstruction depending on psycholinguistic features; (iii) layer analysis can mediate latent interactions of mediation, suppression, and facilitation for lexical access. By outlining novel quantitative perspectives where multilayer networks can shed light on cognitive knowledge representations, including in next-generation brain/mind models, we discuss key limitations and promising directions for cutting-edge future research.

Age-related differences in the interplay of fluency and complexity in Chinese-speaking seniors' oral narratives

BACKGROUND

Previous studies on language production in normal ageing have primarily focused on distinct dimensions of older adults' spoken language performance, such as fluency and complexity. However, little attention has been paid to the complex, interconnected relations between these dimensions. Additionally, older adults have been treated as a homogeneous group, with little consideration for the differential characteristics of language performance across different stages of ageing.

AIMS

This study aims to investigate how increasing age impacts Chinese seniors' oral language performance, focusing on fluency (articulation rate and dysfluency rate), complexity (lexical and syntactic) and the potential interactions between these dimensions.

METHODS & PROCEDURES

Spontaneous oral narratives were collected from 60 normally ageing individuals, who were categorised into three groups: young-old (60-69 years old), middle-old (70-79 years old) and old-old (≥80 years old). Four measures for assessing language performance, namely, articulation rate, dysfluency rate, lexical complexity and syntactic complexity, were derived from the oral narratives. Dynamic systems techniques, including moving correlations, locally estimated scatterplot smoothing and Monte Carlo simulations, were employed for data analysis.

OUTCOMES & RESULTS

This study revealed two major findings. First, across different age groups, the seniors' oral narratives significantly differed in the aspect of articulation rate and syntactic complexity. Specifically, both the young-old and the middle-old groups exhibited significantly higher articulation rates than the old-old group; the middle-old group also demonstrated significantly higher syntactic complexity compared to the old-old group. Second, the distinct subsystems (i.e., articulation rate, dysfluency rate, lexical and syntactic complexity) of seniors' oral narratives demonstrated varying interactions across different stages of ageing. While these subsystems tended to coordinate with each other in young-old individuals, they exhibited a greater tendency to compete in middle-old and old-old individuals.

CONCLUSIONS & IMPLICATIONS

The findings reveal that subsystems of older adults' oral narratives display varying interactions with the increase of age, indicating that focusing solely on one dimension of language performance may result in inaccurate or misleading conclusions. Therefore, a multi-index comprehensive assessment should be employed for the enhancement of clinical evaluations of language performance in older adults. Additionally, it is vital to consider the interactional patterns (i.e., support or competition) between language subsystems when assessing language performance in normal ageing.

WHAT THIS PAPER ADDS

What is already known on the subject Previous research on language production in normal ageing has primarily focused on distinct dimensions of older adults' spoken language performance, such as fluency, vocabulary richness and grammatical complexity, overlooking the intricate interconnections between these dimensions. However, investigating these connections is significant for a thorough and in-depth understanding of language production in late adulthood, which operates as a system comprising interconnected components. Furthermore, existing studies have predominantly treated older adults as a homogeneous group, comparing their language use to that of young people. This approach lacks justification, given the substantial variations in language use among seniors at different stages of ageing. What this paper adds to existing knowledge The present findings illuminate the dynamic nature of language production in normal ageing. Not only do the distinct dimensions or subsystems of older adults' oral narratives (e.g., articulation rate, dysfluency rate, syntactic complexity) change with age, but more important, the ways in which these subsystems interact with each other also evolve with age, resulting in changing states of spoken language production in the ageing process. More specifically, our study provides evidence that the interactions among subsystems of older adults' oral narratives predominately transition from supportive relationships in earlier stages to competitive ones at later stages of ageing. What are the potential or actual clinical implications of this work? The present study suggests the use of multiple linguistic indices related to various aspects of language performance to assess the spoken language production of older adults. This is highlighted by the observation that various dimensions of older adults' oral narratives continuously interact with one another across different stages of ageing, and hence focusing solely on one dimension of language performance tends to lead to inaccurate or misleading results. Additionally, the patterns of interaction (i.e., support or competition) between different dimensions of language performance may reflect older adults' capacity to coordinate and control attentional resources and therefore should be taken into consideration in clinical evaluations of language performance in older adults.

The "Small World of Words" free association norms for Rioplatense Spanish

Large-scale word association datasets are both important tools used in psycholinguistics and used as models that capture meaning when considered as semantic networks. Here, we present word association norms for Rioplatense Spanish, a variant spoken in Argentina and Uruguay. The norms were derived through a large-scale crowd-sourced continued word association task in which participants give three associations to a list of cue words. Covering over 13,000 words and +3.6 M responses, it is currently the most extensive dataset available for Spanish. We compare the obtained dataset with previous studies in Dutch and English to investigate the role of grammatical gender and studies that used Iberian Spanish to test generalizability to other Spanish variants. Finally, we evaluated the validity of our data in word processing (lexical decision reaction times) and semantic (similarity judgment) tasks. Our results demonstrate that network measures such as in-degree provide a good prediction of lexical decision response times. Analyzing semantic similarity judgments showed that results replicate and extend previous findings demonstrating that semantic similarity derived using spreading activation or spectral methods outperform word embeddings trained on text corpora.

Natural language processing techniques for studying language in pathological ageing: A scoping review

BACKGROUND

In the past few years there has been a growing interest in the employment of verbal productions as digital biomarkers, namely objective, quantifiable behavioural data that can be collected and measured by means of digital devices, allowing for a low-cost pathology detection, classification and monitoring. Numerous research papers have been published on the automatic detection of subtle verbal alteration, starting from written texts, raw speech recordings and transcripts, and such linguistic analysis has been singled out as a cost-effective method for diagnosing dementia and other medical conditions common among elderly patients (e.g., cognitive dysfunctions associated with metabolic disorders, dysarthria).

AIMS

To provide a critical appraisal and synthesis of evidence concerning the application of natural language processing (NLP) techniques for clinical purposes in the geriatric population. In particular, we discuss the state of the art on studying language in healthy and pathological ageing, focusing on the latest research efforts to build non-intrusive language-based tools for the early identification of cognitive frailty due to dementia. We also discuss some challenges and open problems raised by this approach.

METHODS & PROCEDURES

We performed a scoping review to examine emerging evidence about this novel domain. Potentially relevant studies published up to November 2021 were identified from the databases of MEDLINE, Cochrane and Web of Science. We also browsed the proceedings of leading international conferences (e.g., ACL, COLING, Interspeech, LREC) from 2017 to 2021, and checked the reference lists of relevant studies and reviews.

MAIN CONTRIBUTION

The paper provides an introductory, but complete, overview of the application of NLP techniques for studying language disruption due to dementia. We also suggest that this technique can be fruitfully applied to other medical conditions (e.g., cognitive dysfunctions associated with dysarthria, cerebrovascular disease and mood disorders).

CONCLUSIONS & IMPLICATIONS

Despite several critical points need to be addressed by the scientific community, a growing body of empirical evidence shows that NLP techniques can represent a promising tool for studying language changes in pathological aging, with a high potential to lead a significant shift in clinical practice.

WHAT THIS PAPER ADDS

What is already known on this subject Speech and languages abilities change due to non-pathological neurocognitive ageing and neurodegenerative processes. These subtle verbal modifications can be measured through NLP techniques and used as biomarkers for screening/diagnostic purposes in the geriatric population (i.e., digital linguistic biomarkers-DLBs). What this paper adds to existing knowledge The review shows that DLBs can represent a promising clinical tool, with a high potential to spark a major shift to dementia assessment in the elderly. Some challenges and open problems are also discussed. What are the potential or actual clinical implications of this work? This methodological review represents a starting point for clinicians approaching the DLB research field for studying language in healthy and pathological ageing. It summarizes the state of the art and future research directions of this novel approach.

Using Complex Networks in the Hearing Sciences

In this Point of View, we review a number of recent discoveries from the emerging, interdisciplinary field of Network Science , which uses graph theoretic techniques to understand complex systems. In the network science approach, nodes represent entities in a system, and connections are placed between nodes that are related to each other to form a web-like network . We discuss several studies that demonstrate how the micro-, meso-, and macro-level structure of a network of phonological word-forms influence spoken word recognition in listeners with normal hearing and in listeners with hearing loss. Given the discoveries made possible by this new approach and the influence of several complex network measures on spoken word recognition performance we argue that speech recognition measures-originally developed in the late 1940s and routinely used in clinical audiometry-should be revised to reflect our current understanding of spoken word recognition. We also discuss other ways in which the tools of network science can be used in Speech and Hearing Sciences and Audiology more broadly.

Evidence for optimal semantic search throughout adulthood

As people age, they learn and store new knowledge in their semantic memory. Despite learning a tremendous amount of information, people can still recall information relevant to the current situation with ease. To accomplish this, the mind must efficiently organize and search a vast store of information. It also must continue to retrieve information effectively despite changes in cognitive mechanisms due to healthy aging, including a general slowing in information processing and a decline in executive functioning. How effectively does the mind of an individual adjust its search to account for changes due to aging? We tested 746 people ages 25 through 69 on a semantic fluency task (free listing animals) and found that, on average, retrieval follows an optimal path through semantic memory. Participants tended to list a sequence of semantically related animals (e.g., lion, tiger, puma) before switching to a semantically unrelated animal (e.g., whale). We found that the timing of these transitions to semantically unrelated animals was remarkably consistent with an optimal strategy for maximizing the overall rate of retrieval (i.e., the number of animals listed per unit time). Age did not affect an individual's deviation from the optimal strategy given their general performance, suggesting that people adapt and continue to search memory optimally throughout their lives. We argue that this result is more likely due to compensating for a general slowing than a decline in executive functioning.

Efficiency of spoken word recognition slows across the adult lifespan

Spoken word recognition is a critical hub during language processing, linking hearing and perception to meaning and syntax. Words must be recognized quickly and efficiently as speech unfolds to be successfully integrated into conversation. This makes word recognition a computationally challenging process even for young, normal hearing adults. Older adults often experience declines in hearing and cognition, which could be linked by age-related declines in the cognitive processes specific to word recognition. However, it is unclear whether changes in word recognition across the lifespan can be accounted for by hearing or domain-general cognition. Participants (N = 107) responded to spoken words in a Visual World Paradigm task while their eyes were tracked to assess the real-time dynamics of word recognition. We examined several indices of word recognition from early adolescence through older adulthood (ages 11-78). The timing and proportion of eye fixations to target and competitor images reveals that spoken word recognition became more efficient through age 25 and began to slow in middle age, accompanied by declines in the ability to resolve competition (e.g., suppressing sandwich to recognize sandal). There was a unique effect of age even after accounting for differences in inhibitory control, processing speed, and hearing thresholds. This suggests a limited age range where listeners are peak performers.

Referential and inferential production across the lifespan: different patterns and different predictive cognitive factors

Introduction

The ability to speak is grounded in general memory and control processes and likely changes across the lifespan. However, our knowledge on how word production abilities naturally evolve from childhood to old age remains marginally investigated. Our aim was to shed further light on this issue by exploiting the contrast between two ways to elicit word production: referential picture naming and inferential naming from definition.

Methods

We collected accuracy and production latencies in a picture naming task and in a naming from definition task from 130 participants ranging from 10 to 80 years old. Measures of vocabulary size, digit span memory, semantic and phonemic fluencies and processing speed were also collected. We used multivariate adaptative regression splines and regression models to characterize lifespan patterns of the two tasks.

Results

Patterns of increase in performance were similar for picture naming and naming from definition only from childhood to young adulthood. In the second half of the lifespan, significant decrease of performance was found in older adults for picture naming (from around 60 years-old) but not for naming from definition. Clearly, word production elicited with an inferential task (naming from definition) yields different age-related patterns than usually described in the literature with a referential task (picture naming).

Discussion

We discuss how cognitive processes such as visual-conceptual processes and lexical prediction may explain the differential pattern of results in aging in referential and inferential production tasks. We argue for more lifespan studies and the need to investigate language production beyond picture naming, in particular with respect to aging.

Consensus Paper: Current Perspectives on Abstract Concepts and Future Research Directions

concepts are relevant to a wide range of disciplines, including cognitive science, linguistics, psychology, cognitive, social, and affective neuroscience, and philosophy. This consensus paper synthesizes the work and views of researchers in the field, discussing current perspectives on theoretical and methodological issues, and recommendations for future research. In this paper, we urge researchers to go beyond the traditional abstract-concrete dichotomy and consider the multiple dimensions that characterize concepts (e.g., sensorimotor experience, social interaction, conceptual metaphor), as well as the mediating influence of linguistic and cultural context on conceptual representations. We also promote the use of interactive methods to investigate both the comprehension and production of abstract concepts, while also focusing on individual differences in conceptual representations. Overall, we argue that abstract concepts should be studied in a more nuanced way that takes into account their complexity and diversity, which should permit us a fuller, more holistic understanding of abstract cognition.

Lexical Access Restrictions after the Age of 80

BACKGROUND

During the fourth age (80+ years), cognitive difficulties increase. Although language seems to resist the advancement of age, an older person without pathological developments in cognition may exhibit deficits in lexical access. This study examines the restrictions on lexical access in people aged 80 and older in word recognition and retrieval modalities through four lexical tasks.

METHOD

The effect of aging on response time and accuracy was measured using recognition (lexical decision/naming/priming) and retrieval (picture naming) tasks. A fourth age group (>80) and two third age groups (60-69/70-79) were compared according to lexical access modality and type of task employed through linear regression models.

RESULTS

People aged 80 and older exhibit a strong lexical access constraint, as they are slower and less accurate in recognizing and retrieving words than both third age groups. These restrictions are more profound for the word retrieval modality, especially in the picture naming task.

CONCLUSION

Impaired fluid intelligence and internode transmission deficits during advanced aging could further reduce the ability to recognize and/or retrieve words, having an impact on access speed and accuracy. Furthermore, the idea that crystallized intelligence could strengthen the accuracy of lexical access during aging is supported, specifically in word recognition modality.

Contextual dynamics in lexical encoding across the ageing spectrum: A simulation study

The field of psycholinguistics has recently questioned the primacy of word frequency (WF) in influencing word recognition and production, instead focusing on the importance of a word's contextual diversity (CD). WF is operationalised by counting the number of occurrences of a word in a corpus, while a word's CD is a count of the number of contexts that a word occurs in, with repetitions within a context being ignored. Numerous studies have converged on the conclusion that CD is a better predictor of word recognition latency and accuracy than frequency. These findings support a cognitive mechanism based on the principle of likely need over the principle of repetition in lexical organisation. In the current study, we trained the semantic distinctiveness model on communication patterns in social media platforms consisting of over 55-billion-word tokens and examined the ability of theoretically distinct models to explain word recognition latency and accuracy data from over 1 million participants from the Mandera et al. English Crowdsourding Project norms, consisting of approximately 59,000 words across six age bands ranging from ages 10 to 60 years. There was a clear quantitative trend across the age bands, where there is a shift from a social environment-based attention mechanism in the "younger" models, to a clear dominance for a discourse-based attention mechanism as models "aged." This pattern suggests that there is a dynamical interaction between the cognitive mechanisms of lexical organisation and environmental information that emerges across ageing.

Investigating the network structure of domain-specific knowledge using the semantic fluency task

Cognitive scientists have a long-standing interest in quantifying the structure of semantic memory. Here, we investigate whether a commonly used paradigm to study the structure of semantic memory, the semantic fluency task, as well as computational methods from network science could be leveraged to explore the underlying knowledge structures of academic disciplines such as psychology or biology. To compare the knowledge representations of individuals with relatively different levels of expertise in academic subjects, undergraduate students (i.e., experts) and preuniversity high school students (i.e., novices) completed a semantic fluency task with cue words corresponding to general semantic categories (i.e., animals, fruits) and specific academic domains (e.g., psychology, biology). Network analyses of their fluency networks found that both domain-general and domain-specific semantic networks of undergraduates were more efficiently connected and less modular than the semantic networks of high school students. Our results provide an initial proof-of-concept that the semantic fluency task could be used by educators and cognitive scientists to study the representation of more specific domains of knowledge, potentially providing new ways of quantifying the nature of expert cognitive representations.

Representing melodic relationships using network science

Music is a complex system consisting of many dimensions and hierarchically organized information-the organization of which, to date, we do not fully understand. Network science provides a powerful approach to representing such complex systems, from the social networks of people to modelling the underlying network structures of different cognitive mechanisms. In the present research, we explored whether network science methodology can be extended to model the melodic patterns underlying expert improvised music. Using a large corpus of transcribed improvisations, we constructed a network model in which 5-pitch sequences were linked depending on consecutive occurrences, constituting 116,403 nodes (sequences) and 157,429 edges connecting them. We then investigated whether mathematical graph modelling relates to musical characteristics in real-world listening situations via a behavioral experiment paralleling those used to examine language. We found that as melodic distance within the network increased, participants judged melodic sequences as less related. Moreover, the relationship between distance and reaction time (RT) judgements was quadratic: participants slowed in RT up to distance four, then accelerated; a parallel finding to research in language networks. This study offers insights into the hidden network structure of improvised tonal music and suggests that humans are sensitive to the property of melodic distance in this network. More generally, our work demonstrates the similarity between music and language as complex systems, and how network science methods can be used to quantify different aspects of its complexity.

Semantic cognition in healthy ageing: Neural signatures of representation and control mechanisms in naming typical and atypical objects

Effective use of conceptual knowledge engages semantic representation and control processes to access information in a goal-driven manner. Neuropsychological findings of patients presenting either degraded knowledge (e.g., semantic dementia) or disrupted control (e.g., semantic aphasia) converge with neuroimaging evidence from young adults, and delineate the neural segregation of representation and control mechanisms. However, there is still scarce research on the neurofunctional underpinnings of such mechanisms in healthy ageing. To address this, we conducted an fMRI study, wherein young and older adults performed a covert naming task of typical and atypical objects. Three main age-related differences were found. As shown by age group and typicality interactions, older adults exhibited overactivation during naming of atypical (e.g., avocado) relative to typical concepts in brain regions associated to semantic representation, including anterior and medial portions of left temporal lobe (respectively, ATL and MTG). This provides evidence for the reorganization of neural activity in these brain regions contingent to the enrichment of semantic repositories in older ages. The medial orbitofrontal gyrus was also overactivated, indicating that the processing of atypical concepts (relative to typical items) taxes additional control resources in the elderly. Increased activation in the inferior frontal gyrus (IFG) was observed in naming typical items (relative to atypical ones), but only for young adults. This suggests that naming typical items (e.g., strawberry) taxes more on control processes in younger ages, presumably due to the semantic competition set by other items that share multiple features with the target (e.g., raspberry, blackberry, cherry). Together, these results reveal the dynamic nature of semantic control interplaying with conceptual representations as people grow older, by indicating that distinct neural bases uphold semantic performance from young to older ages. These findings may be explained by neural compensation mechanisms coming into play to support neurocognitive changes in healthy ageing.

The Resilience of the Phonological Network May Have Implications for Developmental and Acquired Disorders

A central tenet of network science states that the structure of the network influences processing. In this study of a phonological network of English words we asked: how does damage alter the network structure (Study 1)? How does the damaged structure influence lexical processing (Study 2)? How does the structure of the intact network "protect" processing with a less efficient algorithm (Study 3)? In Study 1, connections in the network were randomly removed to increasingly damage the network. Various measures showed the network remained well-connected (i.e., it is resilient to damage) until ~90% of the connections were removed. In Study 2, computer simulations examined the retrieval of a set of words. The performance of the model was positively correlated with naming accuracy by people with aphasia (PWA) on the Philadelphia Naming Test (PNT) across four types of aphasia. In Study 3, we demonstrated another way to model developmental or acquired disorders by manipulating how efficiently activation spread through the network. We found that the structure of the network "protects" word retrieval despite decreases in processing efficiency; words that are relatively easy to retrieve with efficient transmission of priming remain relatively easy to retrieve with less efficient transmission of priming. Cognitive network science and computer simulations may provide insight to a wide range of speech, language, hearing, and cognitive disorders.

Structural differences in the semantic networks of younger and older adults

Cognitive science invokes semantic networks to explain diverse phenomena, from memory retrieval to creativity. Research in these areas often assumes a single underlying semantic network that is shared across individuals. Yet, recent evidence suggests that content, size, and connectivity of semantic networks are experience-dependent, implying sizable individual and age-related differences. Here, we investigate individual and age differences in the semantic networks of younger and older adults by deriving semantic networks from both fluency and similarity rating tasks. Crucially, we use a megastudy approach to obtain thousands of similarity ratings per individual to allow us to capture the characteristics of individual semantic networks. We find that older adults possess lexical networks with smaller average degree and longer path lengths relative to those of younger adults, with older adults showing less interindividual agreement and thus more unique lexical representations relative to younger adults. Furthermore, this approach shows that individual and age differences are not evenly distributed but, rather, are related to weakly connected, peripheral parts of the networks. All in all, these results reveal the interindividual differences in both the content and the structure of semantic networks that may accumulate across the life span as a function of idiosyncratic experiences.

Balancing novelty and appropriateness leads to creative associations in children

Creative problem solving is a fundamental skill of human cognition and is conceived as a search process whereby a novel and appropriate solution is generated. However, it is unclear whether children are able to balance novelty and appropriateness to generate creative solutions and what are the underlying computational mechanisms. Here, we asked children, ranging from 10 to 11 years old, to perform a word association task according to three instructions, which triggered a more appropriate (ordinary), novel (random), or balanced (creative) response. Results revealed that children exhibited greater cognitive flexibility in the creative condition compared to the control conditions, as revealed by the structure and resiliency of the semantic networks. Moreover, responses' word embeddings extracted from pretrained deep neural networks showed that semantic distance and category switching index increased in the creative condition with respect to the ordinary condition and decreased compared to the random condition. Critically, we showed how children efficiently solved the exploration/exploitation trade-off to generate creative associations by fitting a computational reinforcement learning (RL) model that simulates semantic search strategies. Our findings provide compelling evidence that children balance novelty and appropriateness to generate creative associations by optimally regulating the level of exploration in the semantic search. This corroborates previous findings on the adult population and highlights the crucial contribution of both components to the overall creative process. In conclusion, these results shed light on the connections between theoretical concepts such as bottom-up/top-down modes of thinking in creativity research and the exploration/exploitation trade-off in human RL research.

The Rapid Naming Test: Development and initial validation in typically aging adults

ObjectiveProgressive word-finding difficulty is a primary cognitive complaint among healthy older adults and a symptom of pathological aging. Classic measures of visual confrontation naming, however, show ceiling effects among healthy older adults. To address the need for a naming test that is sensitive to subtle, age-related word-finding decline, we developed the Rapid Naming Test (RNT), a computerized, one-minute, speeded visual naming test.MethodFunctionally intact older (n = 145) and younger (n = 69) adults completed the RNT. Subsets of older adults also completed neuropsychological tests, a self-report scale of functional decline, amyloid-β PET imaging, and repeat RNT administration to determine test-retest reliability.ResultsRNT scores were normally distributed and exhibited good test-retest reliability. Younger adults performed better than older adults. Within older adults, lower scores were associated with older age. Higher scores correlated with measures of language, processing speed, and episodic learning and memory. Scores were not correlated with visuospatial or working memory tests. Worse performance was related to subjective language decline, even after controlling for a classic naming test and speed. The RNT was also negatively associated with amyloid-β burden.ConclusionsThe RNT appears to be a reliable test that is sensitive to subtle, age-related word-finding decline. Convergent and divergent validity are supported by its specific associations with measures relying on visual naming processes. Ecological validity is supported by its relationship with subjective real-world language difficulties. Lastly, worse performance was related to amyloid-β deposition, an Alzheimer's disease biomarker. This study represents a key step toward validating a novel, sensitive naming test in typically aging adults.

Phantom smells: a prevalent COVID-19 symptom that progressively sets in

PURPOSE

One of the long-term symptoms of COVID-19 is phantosmia, a type of Olfactory Disorder (OD) that has deleterious impacts on patients' quality of life. The aim of this article was to study how this poorly understood qualitative OD manifests itself in the COVID-19.

METHODS

4691 patients with COVID-19 responded to our online questionnaire focusing on COVID-19-related OD. We first analyzed the prevalence of phantosmia in this population. Then, with the help of Natural Language Processing techniques, we investigated the qualitative descriptions of phantom smells by the 1723 respondents who reported phantosmia.

RESULTS

The prevalence of phantosmia was of 37%. Women were more likely to report phantosmia than men, as well as respondents for whom OD was described as fluctuating rather than permanent, lasted longer, was partial rather than total and appeared progressively rather than suddenly. The relationship between OD duration and phantosmia followed a logarithmic function, with a prevalence of phantosmia increasing strongly during the first 2 months of the disease before reaching a plateau and no decrease over the 15 months considered in this study. Qualitative analyses of phantosmia descriptions with a sentiment analysis revealed that the descriptions were negatively valenced for 78% of the respondents. Reference to "tobacco" was more frequent in non-smokers. Source names and odor characteristics were used differently according to age and OD duration.

CONCLUSION

The results of this descriptive study of phantosmia contribute to the current efforts of the medical community to better understand and treat this rapidly increasing COVID-19-related OD.

Comparing the semantic networks of children with cochlear implants and children with typical hearing: Effects of length of language access

PURPOSE

Kenett et al. (2013) report that the sematic networks, measured by using an oral semantic fluency task, of children with cochlear implants (CI) are less structured compared to the sematic networks of children with typical hearing (TH). This study aims to evaluate if such differences are only evident if children with CI are compared to children with TH matched on chronological age, or also if they are compared to children with TH matched on hearing age.

METHOD

The performance of a group of children with CI on a verbal fluency task was compared to the performance of a group of chronological-age matched children with TH. Subsequently, computational network analysis was used to compare the semantic network structure of the groups. The same procedure was applied to compare a group of children with CI to a group of hearing-age matched children with TH.

RESULTS

The children with CI perform on the same level on an oral semantic verbal fluency task as the children with TH matched on hearing age. There are significant differences in terms of the structure of the semantic network between the groups. The magnitude of these differences is very small and they are non-significant for a proportion of nodes included in the bootstrap analysis. This indicates that there is no true difference between the networks. Hearing age, but not age at implantation was found to be significantly positively correlated with semantic verbal fluency performance for the children with CI.

CONCLUSIONS

The results from the current study indicate that length of exposure to the tested language is an important factor for the structure of the semantic network and the performance on a semantic verbal fluency task for children with CI. Further studies are needed to explore the role of the accessibility of the language input for the development of semantic networks of children with CI.

Categorical Perception of Lexical Tones in Mandarin-Speaking Seniors

PURPOSE

This study aims to investigate the different degeneration processes of categorical perception (CP) of Mandarin lexical tones in the normal aging population and the pathological aging population with mild cognitive impairment (MCI).

METHOD

In Experiment I, we compared the identification and discrimination of Tone 1 and Tone 2 across young adults, seniors aged 60-65 years, and older seniors aged 75-80 years with normal cognitive abilities. In Experiment II, we compared lexical tone identification and discrimination across young adults, healthy seniors, and age-matched seniors with MCI.

RESULTS

In Experiment I, tone perception was intact in seniors aged below 65 years. Those aged above 75 years could also maintain normal tone identification, whereas they showed poorer tone discrimination correlated with age-related poorer hearing level. In Experiment II, healthy seniors showed normal CP of Mandarin tones. Tone identification was also normal in those with MCI, whereas their tone discrimination had significantly degenerated.

CONCLUSIONS

In the normal aging population, age-related hearing loss decreased signal audibility, accounting for poorer discrimination of Mandarin lexical tones in seniors above 75 years. In the pathological aging population with MCI, the poorer discrimination of lexical tones may be attributed to the additive effect of age, hearing loss, and cognitive impairment (e.g., impaired working memory and long-term phonological memory). This study uncovered the roles of low-level sensory processing and high-level cognitive processing in lexical tone perception in the Chinese aging population.

On the semantic representation of risk

What are the defining features of lay people's semantic representation of risk? We contribute to mapping the semantics of risk based on word associations to provide insight into both universal and individual differences in the representation of risk. Specifically, we introduce a mini-snowball word association paradigm and use the tools of network and sentiment analysis to characterize the semantics of risk. We find that association-based representations not only corroborate but also extend those extracted from past survey- and text-based approaches. Crucially, we find that the semantics of risk show universal properties and individual and group differences. Most notably, while semantic clusters generalize across languages, their frequency varies systematically across demographic groups, with older and female respondents showing more negative connotations and mentioning more often certain types of activities (e.g., recreational activities) relative to younger adults and males, respectively. Our work has general implications for the measurement of risk-related constructs by suggesting that "risk" can mean different things to different individuals.

Editors' Introduction to Networks of the Mind: How Can Network Science Elucidate Our Understanding of Cognition?

Thinking is complex. Over the years, several types of methods and paradigms have developed across the psychological, cognitive, and neural sciences to study such complexity. A rapidly growing multidisciplinary quantitative field of network science offers quantitative methods to represent complex systems as networks, or graphs, and study the network properties of these systems. While the application of network science to study the brain has greatly advanced our understanding of the brains structure and function, the application of these tools to study cognition has been done to a much lesser account. This topic is a collection of papers that discuss the fruitfulness of applying network science to study cognition across a wide scope of research areas from generalist accounts of memory and encoding, to individual differences, to communities, and finally to cultural and individual change.

Age-related changes in sleep-dependent novel word consolidation

Learning new words is a vital, life-long process that benefits from memory consolidation during sleep in young adults. In aging populations, promoting vocabulary learning is an attractive strategy to improve quality of life and workplace longevity by improving the integration of new technology and the associated terminology. Decreases in sleep quality and quantity with aging may diminish sleep-dependent memory consolidation for word learning. Alternatively, given that older adults outperform young adults on vocabulary-based tasks, and that strength of memory encoding (how well older adults learn) predicts sleep-dependent memory consolidation, word learning may uniquely benefit from sleep in older adults. We assessed age-related changes in memory for novel English word-definition pairs recalled following intervals spent asleep and awake. While sleep was shown to fully preserve memory for word/definition pairs in young adults (N = 53, asleep = 32, awake = 21, 18-30 years), older adults (N = 45, asleep = 21, awake = 24, 58-75 years) forgot items equally over wake and sleep intervals but preserved the accuracy of typed responses better following sleep. However, this was modulated by the strength of encoded memories: the proportion of high strength items consolidated increased for older adults following sleep compared to wake. Older adults consolidated a lower proportion of medium strength items across both sleep and wake intervals compared to young adults. Our results contribute to growing evidence that encoding strength is crucially important to understand the expression of sleep-dependent benefits in older adults and assert the need for sufficiently sensitive performance metrics in aging research.

Phonological and semantic similarity of misperceived words in babble: Effects of sentence context, age, and hearing loss

This study investigated how age and hearing loss influence the misperceptions made when listening to sentences in babble. Open-set responses to final words in sentences with low and high context were analyzed for younger adults with normal hearing and older adults with normal or impaired hearing. All groups performed similarly in overall accuracy but differed in error type. Misperceptions for all groups were analyzed according to phonological and semantic properties. Comparisons between groups indicated that misperceptions for older adults were more influenced by phonological factors. Furthermore, older adults with hearing loss omitted more responses. Overall, across all groups, results suggest that phonological confusions most explain misperceptions in low context sentences. In high context sentences, the meaningful sentence context appears to provide predictive cues that reduce misperceptions. When misperceptions do occur, responses tend to have greater semantic similarity and lesser phonological similarity to the target, compared to low context sentences. In this way, semantic similarity may index a postdictive process by which ambiguities due to phonological confusions are resolved to conform to the semantic context of the sentence. These patterns demonstrate that context, age, and hearing loss affect the misperceptions, and potential sentence interpretation, made when listening to sentences in babble.

The Value of Statistical Learning to Cognitive Network Science

To study the human mind is to consider the nature of associations-how are they learned, what are their constituent parts, and how can they be severed or adjusted? The manipulation of associations stands as a pillar of statistical learning (SL) research, which strongly suggests that processes as diverse as word segmentation, learning of grammatical patterns, and event perception can be explained by the learner's sensitivity to simple temporal dependencies (among other regularities). Used to determine the edges of a network, associations are similarly crucial to consider when quantifying the graph-theoretical properties of various cognitive systems. With this point of convergence in mind, the present work reaffirms the unique value of network science in illuminating the broad-level architectures of complex cognitive systems. However, I also describe how insights from the SL literature, coupled with insights from psycholinguistics more broadly, offer a strong theoretical backbone upon which we can develop and study networks that reflect, as closely as possible, the psychological realities of learning.

Using Network Science to Understand the Aging Lexicon: Linking Individuals' Experience, Semantic Networks, and Cognitive Performance

People undergo many idiosyncratic experiences throughout their lives that may contribute to individual differences in the size and structure of their knowledge representations. Ultimately, these can have important implications for individuals' cognitive performance. We review evidence that suggests a relationship between individual experiences, the size and structure of semantic representations, as well as individual and age differences in cognitive performance. We conclude that the extent to which experience-dependent changes in semantic representations contribute to individual differences in cognitive aging remains unclear. To help fill this gap, we outline an empirical agenda that utilizes network analysis and involves the concurrent assessment of large-scale semantic networks and cognitive performance in younger and older adults. We present preliminary data to establish the feasibility and limitations of such empirical, network-analytical approaches.

Depressive symptoms may be associated with semantic memory decline in elderly adults

Depressive symptoms are associated with a decline of episodic memory, but the relationship with semantic memory remains unclear.

The effect of aging on facial attractiveness: An empirical and computational investigation

How does aging affect facial attractiveness? We tested the hypothesis that people find older faces less attractive than younger faces, and furthermore, that these aging effects are modulated by the age and sex of the perceiver and by the specific kind of attractiveness judgment being made. Using empirical and computational network science methods, we confirmed that with increasing age, faces are perceived as less attractive. This effect was less pronounced in judgments made by older than younger and middle-aged perceivers, and more pronounced by men (especially for female faces) than women. Attractive older faces were perceived as elegant more than beautiful or gorgeous. Furthermore, network analyses revealed that older faces were more similar in attractiveness and were segregated from younger faces. These results indicate that perceivers tend to process older faces categorically when making attractiveness judgments. Attractiveness is not a monolithic construct. It varies by age, sex, and the dimensions of attractiveness being judged.

Is the Mind a Network? Maps, Vehicles, and Skyhooks in Cognitive Network Science

Cognitive researchers often carve cognition up into structures and processes. Cognitive processes operate on structures, like vehicles driving over a map. Language alongside semantic and episodic memory are proposed to have structure, as are perceptual systems. Over these structures, processes operate to construct memory and solve problems by retrieving and manipulating information. Network science offers an approach to representing cognitive structures and has made tremendous inroads into understanding the nature of cognitive structure and process. But is the mind a network? If so, what kind? In this article, we briefly review the main metaphors, assumptions, and pitfalls prevalent in cognitive network science (maps and vehicles; one network/process to rule them all), highlight the need for new metaphors that elaborate on the map-and-vehicle framework (wormholes, skyhooks, and generators), and present open questions in studying the mind as a network (the challenge of capturing network change, what should the edges of cognitive networks be made of, and aggregated vs. individual-based networks). One critical lesson of this exercise is that the richness of the mind as network approach makes it a powerful tool in its own right; it has helped to make our assumptions more visible, generating new and fascinating questions, and enriching the prospects for future research. A second lesson is that the mind as a network-though useful-is incomplete. The mind is not a network, but it may contain them.

New Spanish semantic feature production norms for older adults

Semantic feature production norms are a useful tool for researchers to have empirically collected data about the semantic representations of a particular population. As older adults have been shown to have certain differences in their semantic knowledge organization in comparison with younger adults, it is relevant for them to have their own normative data. Thus we present here the first Spanish semantic feature production norms for older adults. They contain information about the feature composition of 400 concrete concepts. We also provide information about some feature and concept variables as well as comparisons between young and old adults on these variables.

Beauty and Wellness in the Semantic Memory of the Beholder

Beauty and wellness are terms used often in common parlance, however their meaning and relation to each other is unclear. To probe their meaning, we applied network science methods to estimate and compare the semantic networks associated with beauty and wellness in different age generation cohorts (Generation Z, Millennials, Generation X, and Baby Boomers) and in women and men. These mappings were achieved by estimating group-based semantic networks from free association responses to a list of 47 words, either related to Beauty, Wellness, or Beauty + Wellness. Beauty was consistently related to Elegance, Feminine, Gorgeous, Lovely, Sexy, and Stylish. Wellness was consistently related Aerobics, Fitness, Health, Holistic, Lifestyle, Medical, Nutrition, and Thrive. In addition, older cohorts had semantic networks that were less connected and more segregated from each other. Finally, we found that women compared to men had more segregated and organized concepts of Beauty and Wellness. In contemporary societies that are pre-occupied by the pursuit of beauty and a healthy lifestyle, our findings shed novel light on how people think about beauty and wellness and how they are related across different age generations and by sex.

Emotional Valence Precedes Semantic Maturation of Words: A Longitudinal Computational Study of Early Verbal Emotional Anchoring

We present a longitudinal computational study on the connection between emotional and amodal word representations from a developmental perspective. In this study, children's and adult word representations were generated using the latent semantic analysis (LSA) vector space model and Word Maturity methodology. Some children's word representations were used to set a mapping function between amodal and emotional word representations with a neural network model using ratings from 9-year-old children. The neural network was trained and validated in the child semantic space. Then, the resulting neural network was tested with adult word representations using ratings from an adult data set. Samples of 1210 and 5315 words were used in the child and the adult semantic spaces, respectively. Results suggested that the emotional valence of words can be predicted from amodal vector representations even at the child stage, and accurate emotional propagation was found in the adult word vector representations. In this way, different propagative processes were observed in the adult semantic space. These findings highlight a potential mechanism for early verbal emotional anchoring. Moreover, different multiple linear regression and mixed-effect models revealed moderation effects for the performance of the longitudinal computational model. First, words with early maturation and subsequent semantic definition promoted emotional propagation. Second, an interaction effect between age of acquisition and abstractness was found to explain model performance. The theoretical and methodological implications are discussed.

Global and Local Feature Distinctiveness Effects in Language Acquisition

Various aspects of semantic features drive early vocabulary development, but less is known about how the global and local structure of the overall semantic feature space influences language acquisition. A feature network of English words was constructed from a large database of adult feature production norms such that edges in the network represented feature distances between words (i.e., Manhattan distances of probability distributions of features elicited for each pair of words). A word's global feature distinctiveness is measured with respect to all other words in the network and a word's local feature distinctiveness is measured relative to words in sub-networks derived from clustering analyses. This paper investigates how feature distinctiveness of individual words at local and global scales of the network influences language acquisition. Regression analyses indicate that global feature distinctiveness was associated with earlier age of acquisition ratings, and was a stronger predictor of age of acquisition than local feature distinctiveness. These results suggest that the global structure of the semantic feature network could play an important role in language acquisition, whereby globally distinctive concepts help to structure vocabulary development over the lifespan.

The Primacy of Beauty in Music, Visual Arts and Literature: Not Just a Replication Study in the Greek Language Exploring the Effects of Verbal Fluency, Age and Gender

Research on aesthetic descriptors of art in different languages is scarce. The aim of the present study was to elucidate the conceptual structure of aesthetic experiences of three forms of art (music, visual arts and literature) in the Greek language, which has not been explored so far. It was further aimed to study if biological and cognitive factors such as age and gender might produce differences in art appreciation. A total of 467 younger and older individuals from Greece were asked to generate verbal descriptors (adjectives) in free word-listing conditions in order to collect terms reflecting the aesthetics-related semantic field of art. The capacity of verbal memory was controlled by using a battery of neuropsychological tests. Analysis of generated adjectives’ frequency and salience revealed that ‘beautiful’ was the most prominent descriptor that was selected with a distinctive primacy for all three forms of arts. The primacy of ‘beautiful’ was significantly more pronounced for visual arts relative to music and literature. Although the aging-related decline of verbal capacity was similar for males and females, the primacy of ‘beautiful’ depended on age and gender by being more emphasized for young females than males, and for old males than females. Analysis of secondary descriptors and pairs of adjectives revealed that affective and hedonic experiences are essentially fixed in the semantic field of art reflection. It is concluded that although the concept of the aesthetics seems to be diversified and rich, a clear primacy of beauty is found for the Greek cultural environment and across different forms of art. The results also highlight the presence of complex influences of biological and cognitive factors on aesthetic art experiences.

Age-related evaluations of imageability and subjective frequency for 1286 neutral and emotional French words: ratings by young, middle-aged, and older adults

This study aimed at providing imageability and subjective frequency ratings collected from four adult age groups ranging from 18 to 85 years old (18-25; 26-39; 40-59; and 60 and over) for 1286 neutral and emotional French words available in the EMA database (Gobin et al., 2017). Overall, the older adults rated words as more (subjectively) frequent and more imageable than the younger adults. Furthermore, we examined the relationships between subjective frequency and imageability, as well as those with emotional variables (i.e., valence, arousal) already available for these words, for each age group. For all age groups, more subjective frequent words were more imageable. Emotional words were more imageable and more frequent. Arousal scores were lower for low- and high-imageability words, and higher for more subjective frequent words. The strength of these links between subjective frequency, imageability, and emotional ratings was found to decrease as a function of age. Finally, by using the lexical decision reaction times and accuracy rates of young adults from Megalex (Ferrand et al., 2018), imageability and subjective frequency across age were found to provide an additional contribution to visual word recognition performance as compared to objective lexical variables (i.e., number of letters, syllables, objective frequency, orthographic neighborhood). More importantly, subjective frequency and imageability ratings from the youngest group predicted reaction times and accuracy better than ratings from the oldest group. By providing new age-adapted word characteristics, this norm should be of great use to researchers in the field of cognitive aging who use word materials.

A Critical Review of Network-Based and Distributional Approaches to Semantic Memory Structure and Processes

Some of the earliest work on understanding how concepts are organized in memory used a network-based approach, where words or concepts are represented as nodes, and relationships between words are represented by links between nodes. Over the past two decades, advances in network science and graph theoretical methods have led to the development of computational semantic networks. This review provides a modern perspective on how computational semantic networks have proven to be useful tools to investigate the structure of semantic memory as well as search and retrieval processes within semantic memory, to ultimately model performance in a wide variety of cognitive tasks. Regarding representation, the review focuses on the distinctions and similarities between network-based (based on behavioral norms) approaches and more recent distributional (based on natural language corpora) semantic models, and the potential overlap between the two approaches. Capturing the type of relation between concepts appears to be particularly important in this modeling endeavor. Regarding processes, the review focuses on random walk models and the degree to which retrieval processes demand attention in pursuit of given task goals, which dovetails with the type of relation retrieved during tasks. Ultimately, this review provides a critical assessment of how the network perspective can be reconciled with distributional and machine-learning-based perspectives to meaning representation, and describes how cognitive network science provides a useful conceptual toolkit to probe both the structure and retrieval processes within semantic memory.

Quantifying flexibility in thought: The resiliency of semantic networks differs across the lifespan

Older adults tend to have a broader vocabulary compared to younger adults - indicating a richer storage of semantic knowledge - but their retrieval abilities decline with age. Recent advances in quantitative methods based on network science have investigated the effect of aging on semantic memory structure. However, it is yet to be determined how this aging effect on semantic memory structure relates to its overall flexibility. Percolation analysis provides a quantitative measure of the flexibility of a semantic network, by examining how a semantic memory network is resistant to "attacks" or breaking apart. In this study, we incorporated percolation analyses to examine how semantic networks of younger and older adults break apart to investigate potential age-related differences in language production. We applied the percolation analysis to 3 independent sets of data (total N = 78 younger, 78 older adults) from which we generated semantic networks based on verbal fluency performance. Across all 3 datasets, the percolation integrals of the younger adults were larger than older adults, indicating that older adults' semantic networks were less flexible and broke down faster than the younger adults'. Our findings provide quantitative evidence for diminished flexibility in older adults' semantic networks, despite the stability of semantic knowledge across the lifespan. This may be one contributing factor to age-related differences in language production.

The structure of semantic representation shapes controlled semantic retrieval

An essential aim in the research on semantic cognition is to understand the interplay between the structure of semantic representation and controlled processes that operate on it to generate flexible behaviours. To evaluate the link between semantic network connectivity and semantic control functions (semantic inhibition and switching), we employed a network theory approach and revealed that controlled semantic processing was reliably associated with connectivity of conceptual representation. In particular, our results show that efficient information flow afforded by high connectivity of semantic network is coupled with superior switching but poor inhibition ability. These findings suggest that the network architectures that facilitate efficient semantic activation spreading aid flexible transitions between semantic clusters but impede inhibition employed to suppress inappropriate or interfering semantic representations. Overall, our study provides a novel insight into the mechanisms underlying controlled semantic processing that is recruited to disentangle from habitual structure of semantic representation.

What Can Network Science Tell Us About Phonology and Language Processing?

Contemporary psycholinguistic models place significant emphasis on the cognitive processes involved in the acquisition, recognition, and production of language but neglect many issues related to the representation of language‐related information in the mental lexicon. In contrast, a central tenet of network science is that the structure of a network influences the processes that operate in that system, making process and representation inextricably connected. Here, we consider how the structure found across phonological networks of several languages from different language families may influence language processing as we age and experience diseases that affect cognition during the typical and atypical acquisition of new words, during typical perception and production of speech in adults, and during language change over time. We conclude that the network science approach may not only provide insights into specific language processes but also provide a way to connect the work from these domains, which are becoming increasingly balkanized.

Methodological Considerations for Incorporating Clinical Data Into a Network Model of Retrieval Failures

Difficulty retrieving information (e.g., words) from memory is prevalent in neurogenic communication disorders (e.g., aphasia and dementia). Theoretical modeling of retrieval failures often relies on clinical data, despite methodological limitations (e.g., locus of retrieval failure, heterogeneity of individuals, and progression of disorder/disease). Techniques from network science are naturally capable of handling these limitations. This paper reviews recent work using a multiplex lexical network to account for word retrieval failures and highlights how network science can address the limitations of clinical data. Critically, any model we employ could impact clinical practice and patient lives, harkening the need for theoretically well-informed network models.

Category norms with a cross-sectional sample of adults in the United States: Consideration of cohort, age, and historical effects on semantic categories

This paper describes normative data for newly collected exemplar responses to 70 semantic categories described in previous norming studies (Battig & Montague, Journal of Experimental Psychology, 80(3, pt.2): 1-46, 1969; Van Overschelde, Rawson, & Dunlosky, Journal of Memory and Language, 50(3): 289-335, 2004; Yoon et al., Psychology and Aging, 19(3), 379-393, 2004). These categories were presented to 246 young (18-39 years), middle (40-59 years), and older (60 years and older) English-speaking adults living in the United States who were asked to generate as many category exemplars as possible for each of the 70 categories. In order to understand differences in normative responses, we analyzed these responses a) between age groups within the current sample and b) in comparison to three previously published sets of norms. Experimental studies using such norms typically assume invariance of normative likelihoods across age and historical time. We replicate previous findings such that exemplar frequency correlations suggest moderate stability in generated category members between age groups and cohorts for many, but not all, categories. Further, analyses of rank-order correlations highlight that the traditional measure of typicality may not capture all aspects of typicality, namely that for some categories there is high consistency in the frequency of exemplars across age groups and/or norms, but the ordering of those exemplars differs significantly. We include a cluster analysis to aid in grouping categories based on relative stability across time, cohort, and age groups. These results emphasize the importance of maintaining and updating age-differentiated category norms.

Scaling laws in natural conversations among elderly people

Language is a result of brain function; thus, impairment in cognitive function can result in language disorders. Understanding the aging of brain functions in terms of language processing is crucial for modern aging societies. Previous studies have shown that language characteristics, such as verbal fluency, are associated with cognitive functions. However, the scaling laws in language in elderly people remain poorly understood. In the current study, we recorded large-scale data of one million words from group conversations among healthy elderly people and analyzed the relationship between spoken language and cognitive functions in terms of scaling laws, namely, Zipf's law and Heaps' law. We found that word patterns followed these scaling laws irrespective of cognitive function, and that the variations in Heaps' exponents were associated with cognitive function. Moreover, variations in Heaps' exponents were associated with the ratio of new words taken from the other participants' speech. These results indicate that the exponents of scaling laws in language are related to cognitive processes.