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Rigidity of thought is considered a main characteristic of persons with Asperger syndrome (AS). This rigidity may explain the poor comprehension of unusual semantic relations, frequently exhibited by persons with AS. Research indicates that such deficiency is related to altered mental lexicon organization, but has never been directly examined. The...
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ABSTRACT
The present study aimed to investigate the possibility of vocabulary acquisition in a context of
reading of two short stories in English. In order to get to our experimental research, we have
started our study writing about cognition, language, reading comprehension and lexical
knowledge. In relation to teaching and learning of vocabulary...
Citations
... Q measures the degree to which a network breaks apart into smaller clusters or communities, with a higher Q denoting more distinct and separate communities in a network (Fortunato, 2010;Newman, 2006); thus, communities will often represent specific semantic categories (e.g., fruits and vegetables, animals, buildings). In semantic memory networks, higher Q has been related to higher structure and rigidity (Kenett, Beaty, et al., 2016;Kenett, Gold, & Faust, 2016). Critically, the larger the CC, and the smaller the Q and ASPL, the more flexible and efficient the semantic memory network is, which facilitates information processing and cognitive operations in the network (Kenett et al., 2014;Kenett, Beaty, et al., 2016;Kenett & Faust, 2019). ...
Crystallized intelligence (Gc)-knowledge acquired through education and experience-supports creativity. Yet whether Gc contributes to creativity beyond providing access to more knowledge, remains unclear. We explore the role of a "flexible" semantic memory network structure as a potential shared mechanism of Gc and creativity. Across two studies (N = 506 and N = 161) participants completed Gc tests of vocabulary knowledge and were divided into low, medium, and high Gc groups. They also completed two alternate uses task, to assess verbal creativity, and a semantic fluency task, to estimate semantic memory networks. Across both studies, the semantic memory network structure of the high Gc group was more flexible-less structured, more clustered, and more interconnected-than that of the low Gc group. The high Gc group also outperformed the low Gc group on the creativity tasks. Our results suggest that flexible access to semantic memory supports both verbal intelligence and creativity. Educational relevance statement: Crystallized intelligence (Gc)-knowledge acquired through education and experience-supports creativity, yet whether Gc contributes to creativity beyond providing access to more knowledge (semantic memory), remains unclear. In this two-part study, we find that individuals with higher Gc tended to have a more flexible semantic memory structure, which in turn supported greater verbal creativity. This finding suggests that building students' vocabulary knowledge and verbal skills may not just expand their knowledge base, but also increase creativity through enabling more flexible access to that knowledge. If supported by further research, this could mean educational interventions targeting growth in Gc and semantic flexibility may foster students' creative capacities beyond just improving content mastery. Overall, this research highlights the interplay between building domain knowledge and cultivating creative thinking, suggesting educators should aim to develop both abilities in tandem rather than treating them separately.
... This finding aligns with the increased creative abilities linked to less modular networks observed in Kenett et al. (2014). Further complicating this picture, EXTREME modularity has been associated with rigidity of thought in individuals with Asperger syndrome (Kenett et al., 2016b). ...
... However, it is important to emphasise that these are raw averages that might not capture the full extent of variability within each group. To address this question, we next performed a bootstrap analysis to test the significance of the differences in the participants' networks across the two groups (Christensen & Kenett, 2021;Kenett et al., 2016b). This method allowed us to explore the distribution of these metrics within our actual data, providing a robust statistical framework to detect subtle changes in the lexicon due to language immersion. ...
... We repeated this process 1000 times for subsets containing 50%, 60%, 70%, 80%, and 90% of the nodes in the original networks, thus creating a sampling distribution for each measure and network. The logic behind this approach is that if two networks differ, the partial networks derived from them should also differ (Kenett et al., 2016b). We used analysis of covariance (ANCOVA) to test for the differences between the groups, with the percentage of nodes and edges as covariates to control for potential confounds related to the number of nodes and edges. ...
L1 lexical attrition is the decline of L1 lexical-semantic abilities due to reduced L1 exposure and/or L2 interference. Semantic fluency tasks are central in this research, but traditional analyses are often inconclusive.
To address this, we employed an innovative network science approach to investigate the bilingual lexicon's structural properties. Semantic fluency data were collected from immersed/non-immersed late bilinguals with comparable L2 proficiencies.
Our results indicate that L2 immersion led to more integrated and efficient L2 networks. Crucially, immersion also resulted in L1 attrition (only evident in the network analysis). Immersed participants exhibited less densely connected and sparser L1 networks. Furthermore, network measures suggest that L1 lexical attrition occurs gradually, initially impacting network interconnectivity, while information flow and community structure remain more stable.
Drawing from these insights, we introduce the Lexical Attrition Foundation (LeAF) framework, offering a network-based perspective on lexical attrition development and laying the groundwork for future research.
... It is also possible to evaluate the number of communities and the categories that comprise these communities within the larger network (e.g., "pets" and "farm animals" communities within a network of "animals"). How a network divides into communities may also relate to how resilient a network may be (e.g., Cosgrove et al., 2021;Kenett et al., 2016Kenett et al., , 2018, and to the properties of the words themselves (e.g., Siew, 2013). Significant community structure has been found in a variety of semantic as well as phonological networks (e.g., Castro & Vitevitch, 2023). ...
Objective: Although language is often considered to be largely intact in multiple sclerosis (MS), word-finding difficulties are a common complaint. Recent work suggests that declines in language are not solely the result of motoric and cognitive slowing that is most strongly associated with MS. Network science approaches have been effectively used to examine network structure as it relates to clinical conditions, aging, and language. The present study utilizes a network science approach to investigate whether individuals with MS exhibit less interconnected and resilient semantic networks compared to age-matched neurotypical peers. Method: We used semantic fluency data from 89 participants with MS and 88 neurotypical participants to estimate and analyze the semantic network structure for each participant group. Additionally, we conducted a percolation analysis to examine the resilience of each network. Results: Network measures showed that individuals with MS had lower local and global clustering coefficients, longer average shortest path lengths, and higher modularity values compared to neurotypical peers. Small-worldness, network portrait divergence measures, and community detection analyses were consistent with these results and indicated that macroscopic properties of the two networks differed and that the semantic network for individuals with MS was more fractured than the neurotypical peer network. Moreover, a spreading activation simulation and percolation analysis suggested that the semantic networks of individuals with MS are less flexible and activation degrades faster than those of age-matched neurotypical participants. Conclusions: These differing semantic network structures suggest that language retrieval difficulties in MS partially result from decline in language-specific factors.
... avoiding intrusions and repetitions), leading to the inhibition of ordinary associations and shifting towards meaningful solutions (46,31,50). Yet, verbal tasks, such as the verbal fluency or word association tasks (WATs), are frequently used in clinical assessments whose executive functions are impaired (1,51,52). ...
... More often, networks with higher ASPL and Q tend to reflect an impairment in the efficiency of the search process (1, 51). For instance, individuals with high-functioning autism have been found to have a more modular semantic network than neurotypical controls (51). A possible explanation proposed by the authors is that higher levels of segregation could make it more difficult to integrate information since the network breaks apart into smaller subparts. ...
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 pre-trained 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 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 reinforcement learning research.
... Such networks consist of nodes representing concepts or words in the semantic system, and edges representing the semantic similarity between nodes (Siew et al., 2019;Collins & Loftus, 1975). SemNets have been used to show structural differences in the semantic organization of several neurological populations, including people with AD, Asperger syndrome, and schizophrenia, as well as late talker children (Stam et al., 2007;Kenett et al., 2016;Zeev-Wolf et al., 2014, Beckage et al., 2011. ...
People with brain tumours in eloquent brain areas may be left with mild semantic impairments following awake brain surgery. Semantic assessments traditionally used in this population may be insufficient for the detection of such deficits. To fill this gap in the literature, in this study we proposed a novel methodology which makes use of graph theory metrics.
Twenty-nine French speaking participants who had undergone awake brain surgery took part in this study. Participants underwent five traditional pen-and-paper tasks (category fluency, letter fluency, PPTT, DO80, PASAT), followed by a novel associative judgement task (AJT). To investigate the presence and quality of semantic deficits, graph theory metrics (D, ASPL, CC, Q, S) obtained from this group (N=29) were compared to those of healthy controls (N=94). For validation purposes, the metrics were then correlated with scores on traditional pen-and-paper tasks, including total scores on both category and letter fluency. To better understand the linguistic nature of these metrics, they were correlated with sequence-level metrics (average cluster size, number of switches, switch rate) extracted from category fluency. It was predicted that significant differences would exist between the metrics of each group, that these differences would correlate strictly with measures of linguistic processing, and that both network metrics and sequence-level fluency metrics would reflect the same underlying organization of semantic memory.
Welch two-sample t-tests showed that D and ASPL values were significantly lower in participants who had undergone awake brain surgery relative to healthy controls. Total letter fluency scores were negatively correlated with Q, and positively correlated with CC. Q was positively correlated with average cluster size in category fluency, and negatively correlated with switch rate.
Results suggested increased network efficiency among those who had undergone surgery. That is, the structure of the semantic networks in these individuals reflect more cost-effective travel between nodes in the network, consistent with semantic systems where associations between concepts are more easily made. Results further suggested total letter fluency as an indicator of overall network efficiency, and category fluency structure as a correlate of semantic network organization. Considerations for future research are suggested.
Key words: awake brain surgery, graph theory, brain tumours, semantic system, verbal fluency
... For example, family chaos has been found to covary with problem behavior in youths (Evans and Wachs, 2010), and functional brain network analysis has determined that chaos and randomness are central aspects of schizophrenia and ADHD (van Straaten & Stam, 2013). Likewise, "rigidity" has been a staple of psychological and psychiatric research for at least a century (Schultz & Searleman, 2002); to mention one recent interesting example, rigidity has been found to characterize the thinking of persons with autism spectrum disorder (Aspergers syndrome), who display more compartmentalization of their mental lexicon than controls (Kenett et al., 2016). ...
Chaos and rigidity are often used to describe problematic psychological states. If they are to be avoided, how does one conceive of a normative alternative? A midway compromise between chaos and rigidity seems unsatisfactory. This paper proposes that underlying chaos and rigidity are two dimensions of healthy human experience, those of stability (focus, routine, unity) and flexibility (exploration, novelty, diversity). Their union is possible, the optimal state of “flexstability”, a state in which individuals experience flexibility and stability simultaneously. Chaos can be now understood as flexibility without stability, and rigidity as stability without flexibility. These concepts may be arranged in a two-by-two “flexstability matrix” that suggests that normative psychological development navigates the extremes of chaos and rigidity and pursues the state of flexstability. The concepts of the matrix are applied to seven research areas in psychology: parenting styles, identity formation, development of mind, flow, creativity, emotional regulation and self-determination.
... This makes compactness a candidate for studies of modular, possibly disconnected networks. In [40], for example, the authors examine the graph representations of the semantic memories of persons with Asperger syndrome, which reveal a so-called hyper-modular lexicon structure different from that of the control group. The compactness measure here opens a perspective on distance structure analysis beyond L in particular when the modules are disconnected. ...
The average geodesic distance L Newman (2003) and the compactness C B Botafogo (1992) are important graph indices in applications of complex network theory to real-world problems. Here, for simple connected undirected graphs G of order n , we study the behavior of L ( G ) and C B ( G ), subject to the condition that their order | V ( G )| approaches infinity. We prove that the limit of L ( G )/ n and C B ( G ) lies within the interval [0;1/3] and [2/3;1], respectively. Moreover, for any not necessarily rational number β ∈ [0;1/3] ( α ∈ [2/3;1]) we show how to construct the sequence of graphs { G }, | V ( G )| = n → ∞, for which the limit of L ( G )/ n ( C B ( G )) is exactly β ( α ) (Theorems 1 and 2). Based on these results, our work points to novel classification possibilities of graphs at the node level as well as to the information-theoretic classification of the structural complexity of graph indices.
... These findings, although crosssectional in nature, are consistent with the idea of aging being associated with changes in the structure of the semantic system, providing insight into the structure of the lexicon across the lifespan. However, while additional studies related highly structured, segregated semantic memory structure to higher intelligence (Kenett, Beaty, et al., 2016), network segregation has also been related to decreased flexible thinking among younger adults Kenett, Gold, & Faust, 2016;Siew, 2013). In relation to typical aging, it is yet to be determined how these changes in semantic memory structure relate to changes in flexible thinking. ...
... Such subcommunities can be thought of as subcategories in a semantic network (e.g., farm animals in the 'animals' category). Previous research has shown that modularity in semantic networks is inversely related to a network's flexibility (Kenett, Gold, et al., 2016;Kenett et al., 2018). ...
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.
... Recent research utilising network theory approach has suggested that semantic network connectivity influences adaptive knowledge deployment as well as the structure and dynamism of thinking (Marupaka et al., 2012;Siew et al., 2019;Wulff et al., 2019). For instance, Kenett and colleagues (Kenett et al., 2011 proposed that the structure of semantic network constrains spreading, search, and retrieval of semantic information and so delimits high-order cognition, such as idea generation, mental flexibility (also see Collins & Loftus, 1975;Marko & Riečanský, 2018;Schilling, 2005;Vitevitch et al., 2014), as well as the robustness of semantic system to deterioration and dysfunctions Kenett, Gold, et al., 2016). Importantly, cognitive models of semantic memory organisation are grounded on the idea that habitual structure of semantic representation establishes "cognitive economy", enabling rapid and effortless processing of semantic information, which has been referred to as automatic semantic processing. ...
... This would critically depend on whether an individual has sufficient executive capacity to regulate the unconstrained semantic activation spreading (Benedek et al., 2017;Fisher et al., 2013;Nelson & Rawlings, 2010). On the other hand, low-connectivity semantic organisation (i.e., ↓CC, ↑Q and ↑ASPL) can contribute to analytical thinking and reasoning skills (adaptive functioning), if accompanied with sufficient executive resources to counteract the relatively inelastic semantic structure, or otherwise (maladaptive functioning) result in mental rigidity (e.g., perseverations, repetitive thoughts, content poverty) and impaired linguistic processing (i.e., low metaphor comprehension, lack of humour), which is typical e.g., for obsessive, negative or autistic symptomatology (Craig & Baron-Cohen, 1999;Kenett, Beaty, et al., 2016;Kenett, Gold, et al., 2016;Turner, 1999). Notably, a similar model assuming that semantic network structure grounds the balance between "rigid" and "chaotic" mode of cognition has previously been proposed by Faust and Kenett (2014), but also others (Mohr et al., 2001;Rawlings & Locarnini, 2008). ...
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.
... Higher modularity indicates that there are more subcommunities, more dense connections between the nodes within these sub-communities, and fewer connections between nodes across different sub-communities (Newman, 2006). Higher Q has been related to rigidity of thought by blunting spreading activation within subcommunities, evidenced by studies in phonological processing (Siew, 2013) and in clinical populations, such as Asperger syndrome (Kenett, Gold, & Faust, 2016). Taken together, the shorter the ASPL, the larger the CC, and the smaller the Q, the more flexible and efficient the semantic network association is (Kenett et al., 2014;Kenett & Faust, 2019). ...
... So, the high the Q is, the more sub-networks the structure has. For example, people with Asperger syndrome have shown hyper-modular semantic networks, which may hinder their ability to break apart from a specific module in the network and spread into other modules, thus resulting in rigidity of thought (Kenett, Gold, et al., 2016). Similarly, the community structure of the phonological network found that the densely connected phonological modules (high Q) could "trap" spreading activation of phonological processing (Siew, 2013). ...
Metaphors are a common way to express creative language, yet the cognitive basis of figurative language production remains poorly understood. Previous studies found that higher creative individuals can better comprehend novel metaphors, potentially due to a more flexible semantic memory network structure conducive to remote conceptual combination. The present study extends this domain to creative metaphor production and examined whether the ability to produce creative metaphors is related to variation in the structure of semantic memory. Participants completed a creative metaphor production task and two verbal fluency tasks. They were divided into two equal groups based on their creative metaphor production score. The semantic networks of these two groups were estimated and analyzed based on their verbal fluency responses using a computational network science approach. Results revealed that the semantic networks of high-metaphor producing individuals were more flexible, clustered, and less rigid than that of the low-metaphor producing individuals. Importantly, these results replicated across both semantic categories. The findings provide the first evidence that a flexible, clustered, and less rigid semantic memory structure relates to people’s ability to produce figurative language, extending the growing literature on the role of semantic networks in creativity to the domain of metaphor production.
