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Atypical Semantic Fluency and Recall in Children and Adolescents with Autism Spectrum Disorders Associated with Autism Symptoms and Adaptive Functioning

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Title: Atypical Semantic Fluency and Recall in Children and Adolescents with Autism Spectrum Disorders Associated with Autism Symptoms and Adaptive Functioning
Language: English
Authors: Foldager, Malene, Vestergaard, Martin, Lassen, Jonathan, Petersen, Lea S., Oranje, Bob, Aggernaes, Bodil, Simonsen, Erik
Source: Journal of Autism and Developmental Disorders. Nov 2023 53(11):4280-4292.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 13
Publication Date: 2023
Document Type: Journal Articles
Reports - Research
Descriptors: Autism Spectrum Disorders, Language Fluency, Semantics, Recall (Psychology), Children, Early Adolescents, Symptoms (Individual Disorders), Executive Function
DOI: 10.1007/s10803-022-05677-x
ISSN: 0162-3257
1573-3432
Abstract: It is unclear whether children with autism spectrum disorders have atypical semantic fluency and lower memory for the semantics of words. Therefore, we examined semantic typicality, fluency and recall for the categories of fruits and animals in 60 children with autism aged 7-15 years (boys: 48/girls: 12) compared to 60 typically developing controls. Relative to controls, the autism group had reduced animal fluency, fruit typicality and recall for fruits. Notably, these measures were associated with more autistic-like symptoms and/or lower adaptive functioning across the autism and control groups. In conclusion, atypical semantics of fruits in the autism group may reflect development of idiosyncratic semantic networks while their lower semantic fluency and recall suggest impaired executive language functions.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1394392
Database: ERIC
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  Value: <anid>AN0172396173;aut01nov.23;2023Oct03.05:10;v2.2.500</anid> <title id="AN0172396173-1">Atypical Semantic Fluency and Recall in Children and Adolescents with Autism Spectrum Disorders Associated with Autism Symptoms and Adaptive Functioning </title> <p>It is unclear whether children with autism spectrum disorders have atypical semantic fluency and lower memory for the semantics of words. Therefore, we examined semantic typicality, fluency and recall for the categories of fruits and animals in 60 children with autism aged 7–15 years (boys: 48/girls: 12) compared to 60 typically developing controls. Relative to controls, the autism group had reduced animal fluency, fruit typicality and recall for fruits. Notably, these measures were associated with more autistic-like symptoms and/or lower adaptive functioning across the autism and control groups. In conclusion, atypical semantics of fruits in the autism group may reflect development of idiosyncratic semantic networks while their lower semantic fluency and recall suggest impaired executive language functions.</p> <p>Keywords: Autism; Autism spectrum disorder; Semantic; Verbal fluency; Free recall; Category recall; Typicality; Social functioning.</p> <p>Copyright comment Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</p> <p>Children and adolescents with autism spectrum disorders display atypical verbal communication skills even when delayed language acquisition is absent (Boucher et al., [<reflink idref="bib5" id="ref1">5</reflink>]; Williams et al., [<reflink idref="bib53" id="ref2">53</reflink>]). The idiosyncratic language seen in children with autism may include neologisms, stereotypical language and incorrect use of personal pronouns but may also include more subtle yet systematic differences in how the semantic relationships between words are remembered (Eigsti et al., [<reflink idref="bib14" id="ref3">14</reflink>]). Semantic knowledge of words and their semantic relationships make up the abstract categories and concepts that we use in our everyday language and helps us to organize and retrieve information efficiently and generalize our knowledge to different and novel contexts (Burgoon et al., [<reflink idref="bib7" id="ref4">7</reflink>]). The developing child learns the semantics of words and abstract language through daily social interactions (Gelman & Meyer, [<reflink idref="bib15" id="ref5">15</reflink>]). It has previously been hypothesized that the impairments in reciprocal social interaction seen in autism might result in the development of idiosyncratic language (Bowler et al., [<reflink idref="bib6" id="ref6">6</reflink>]), while others have suggested the opposite relationship (Eigsti et al., [<reflink idref="bib14" id="ref7">14</reflink>]). Despite these speculations however, it remains unclear whether the underlying semantic networks in children and adolescents with autism differ from their typically developing peers and if differences in semantic cognition are coupled to autistic-like traits.</p> <p>The verbal fluency test is widely used to examine semantics cognition by assessing how efficiently subjects can retrieve as many words as possible from a given category, such as animals or fruits, within a limited time interval, usually lasting a minute (Nelson, [<reflink idref="bib34" id="ref8">34</reflink>]). In typically developing children, age-related improvements in semantic fluency peak around 12 years of age (Hurks et al., [<reflink idref="bib22" id="ref9">22</reflink>]; Sauzeon et al., [<reflink idref="bib46" id="ref10">46</reflink>]). This improvement has been linked to the development of more organized semantic knowledge and efficient search strategies and better executive functions (Becker et al., [<reflink idref="bib2" id="ref11">2</reflink>]; Kavé et al., [<reflink idref="bib24" id="ref12">24</reflink>]; Pastor-Cerezuela et al., [<reflink idref="bib37" id="ref13">37</reflink>]). Many studies have reported that children and adolescents with autism display lower semantic fluency compared to typically developing children (Inokuchi & Kamio, [<reflink idref="bib23" id="ref14">23</reflink>]; Mashal & Kasirer, [<reflink idref="bib32" id="ref15">32</reflink>]; Panerai et al., [<reflink idref="bib36" id="ref16">36</reflink>]; Pastor-Cerezuela et al., [<reflink idref="bib37" id="ref17">37</reflink>]; Verté et al., [<reflink idref="bib51" id="ref18">51</reflink>]), although some studies found no apparent group differences (Begeer et al., [<reflink idref="bib3" id="ref19">3</reflink>]; Corbett et al., [<reflink idref="bib10" id="ref20">10</reflink>]; Happe et al., [<reflink idref="bib19" id="ref21">19</reflink>]; Maister et al., [<reflink idref="bib30" id="ref22">30</reflink>]; Robinson et al., [<reflink idref="bib42" id="ref23">42</reflink>]). Others have looked beyond how many words are named on the semantic fluency task and have instead examined whether children with autism differ from typically developing children in the semantic relationship of words within a category (Begeer et al., [<reflink idref="bib3" id="ref24">3</reflink>]; Inokuchi & Kamio, [<reflink idref="bib23" id="ref25">23</reflink>]; Pastor-Cerezuela et al., [<reflink idref="bib37" id="ref26">37</reflink>]). This is done by looking at how words are clustered based on shared semantic properties, such as naming different subcategories of animals, which is thought to reflect the underlying semantic networks (Troyer et al., [<reflink idref="bib49" id="ref27">49</reflink>]). However, the few studies on semantic clustering in children and youths with autism are quite inconsistent and have either reported larger semantic clusters (Begeer et al., [<reflink idref="bib3" id="ref28">3</reflink>]), fewer and smaller semantic clusters (Pastor-Cerezuela et al., [<reflink idref="bib37" id="ref29">37</reflink>]), or no differences in semantic clustering (Inokuchi & Kamio, [<reflink idref="bib23" id="ref30">23</reflink>]). Such discrepancy in findings may relate to the issue that the measurement of semantic clustering lacks objective criteria and clear consensus on how to define a semantic cluster, as previously noted by others (Begeer et al., [<reflink idref="bib3" id="ref31">3</reflink>]).</p> <p>Another more objective way to examine the semantic properties of words is to measure whether subjects with autism name the same category words as their typically developing peers. Population studies have found a high similarity in the frequency distributions of the category words that children and adolescents spontaneously name and that some words are much more common to a category than others (Carneiro et al., [<reflink idref="bib8" id="ref32">8</reflink>]; Price & Connolly, [<reflink idref="bib39" id="ref33">39</reflink>]). The semantic typicality of words on the fluency task can be measured simply by calculating the named frequency of each word across subjects. Earlier studies in adults have provided convincing evidence that semantic word typicality on the fluency task is related to atypical semantic language in elderly with Alzheimer's (Quaranta et al., [<reflink idref="bib40" id="ref34">40</reflink>]; Sailor et al., [<reflink idref="bib45" id="ref35">45</reflink>]) and adults with schizotypal traits (Kiang & Kutas, [<reflink idref="bib25" id="ref36">25</reflink>]; Rodríguez-Ferreiro & Aguilera, [<reflink idref="bib43" id="ref37">43</reflink>]). Using a somewhat related measure, Dunn et al., ([<reflink idref="bib13" id="ref38">13</reflink>]) showed that a small group of ten 4 to 9-year-old children with autism named less representative words than controls on an animal fluency task. However, their measure of the representative quality of animal words was based on predefined subjective ratings made by undergraduate university students and not objective age-equivalent frequency distributions. To our knowledge, no studies have yet assessed semantic word typicality on the verbal fluency task in children with autism compared to their typically developing peers based on the participants' frequency distributions of words.</p> <p>While semantic fluency captures the ability to rapidly name semantically associated words, a test of verbal recall can be used to examine how semantic relationships between words affect memory and learning rates of a predefined word list (Cole et al., [<reflink idref="bib9" id="ref39">9</reflink>]). In typically developing children, verbal recall is better for semantically related than semantically unrelated words (Boucher et al., [<reflink idref="bib5" id="ref40">5</reflink>]). The limited evidence suggests that children with autism may not intuitively use the semantic relationship between words to guide their recall compared to typically developing controls. Recall performance was shown to be lower for animal words but not unrelated words in a group of 15 intellectually disabled children with autism with a mean age of 11.2 years compared to a group of intellectually disabled age-matched children and a group of typically gifted children with a mean age of 4.7 years (Tager-Flusberg, [<reflink idref="bib48" id="ref41">48</reflink>]). A later study similarly showed that autistic children with intellectual ability well below average on group level had lower recall for animals but not vehicles or unrelated words compared to typically developing controls (Lopez & Leekam, [<reflink idref="bib28" id="ref42">28</reflink>]). More recently, it was shown that children with autism and without intellectual disabilities had impaired semantic recall compared to a group of typically developing controls on a word list including different categories, while groups did not differ in recall for unrelated words (Maister et al., [<reflink idref="bib30" id="ref43">30</reflink>]). However, findings are mixed as other studies have reported that children with autism display intact immediate and long-term semantic recall across five recall trials (Phelan et al., [<reflink idref="bib38" id="ref44">38</reflink>]; Tyson et al., [<reflink idref="bib50" id="ref45">50</reflink>]). Interestingly, a few studies have observed that children with autism initially showed similar recall for category words as controls on the first recall trial but had a slower learning rate on the later recall trials (Bennetto et al., [<reflink idref="bib4" id="ref46">4</reflink>]; Solomon et al., [<reflink idref="bib47" id="ref47">47</reflink>]). Furthermore, it is unresolved if autism is associated with global verbal memory impairments, as a recent meta-analysis concluded that children, adolescents and adults with autism tend to show deficits in verbal recall, regardless of whether words were semantically related or not (Desaunay et al., [<reflink idref="bib11" id="ref48">11</reflink>]).</p> <p>In summary, it remains unclear if children and adolescents with autism have trouble using the semantics of words to guide their fluency and memory. The present study aimed to examine whether semantic fluency, typicality and recall differed in a group of children with autism compared to a group of typically developing controls. We used the categories fruit and animal as outcome measures on both the fluency test and a novel semantic recall task. Because it is unclear if children with autism show atypical semantic cognition for just some categories, fruits and animals were tested as separate variables. We hypothesized that children with autism would show lower semantic fluency and typicality on the fluency task and reduced recall for semantically related compared to unrelated words relative to the control group. Deficits in pragmatic and general language skills have previously been coupled to impaired social functioning in autism (Levinson et al., [<reflink idref="bib26" id="ref49">26</reflink>]), and tentative evidence has indicated that decreased adaptive functioning in children with autism is correlated with lower category recall (Liss et al., [<reflink idref="bib27" id="ref50">27</reflink>]) and semantic fluency (Panerai et al., [<reflink idref="bib36" id="ref51">36</reflink>]). Thus, we furthermore aimed to explore if observed group differences in semantic fluency and/or semantic recall were coupled to lower levels of adaptive functioning and/or severity of autism symptoms.</p> <hd id="AN0172396173-2">Methods</hd> <p></p> <hd id="AN0172396173-3">Recruitment of autistic subjects and controls</hd> <p>The present study included sixty children and adolescents aged 7–14 years (48 boys; 12 girls), diagnosed with an autism spectrum disorder (WHO, [<reflink idref="bib54" id="ref52">54</reflink>]: International Classification of Diseases – 10th Edition: F84.0-F84.12) and sixty typically developing controls. Subjects with autism were recruited from outpatient child and adolescent psychiatric clinics in Region Zealand, Denmark, and via online advertisement. Typically developing children were recruited via schools in Region Zealand and through online advertisement. Thorough information about the study was given to participants and their parents, and written consent was obtained before study initiation. The study protocol was approved by the Regional Medical Ethics Committee and the Danish Data Council (SJ-620).</p> <p>Subjects were excluded if they were diagnosed with intellectual disability or hearing disorder, were prematurely born, or had a serious neurological illness. Controls were further excluded if they had a psychiatric disorder or received psychopharmacological treatment. Initially, sixty-four subjects with autism were recruited to the study, but two children with autism were excluded due to non-compliance and two due to intellectual disability. Controls were matched with the autism group on age, sex and parent education (see Results section). Information on paternal education was missing for one child with autism. Seventeen children with autism had psychiatric comorbidities (Anxiety and stress-related disorder = 9; Attention deficit hyperactivity disorder (ADHD)/Attention Deficit Disorder (ADD) = 8; depression = 2, eating disorder = 1), and seven children of these received psychopharmacological treatment (central stimulant medication = 4, selective serotonin reuptake inhibitor = 2, noradrenaline reuptake inhibitor = 1). The matching variables are displayed in Table 1.</p> <p>Table 1 Matching, clinical and cognitive variables for children with autism and controls</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" /><th align="left"><p>Autism subjects (N = 60)</p></th><th align="left"><p>Controls (N = 60)</p></th></tr></thead><tbody><tr><td align="left" /><td align="left" colspan="2"><p><bold>Matching variables</bold></p></td></tr><tr><td align="left"><p>Age</p></td><td align="left"><p>11.95 ± 1.95</p></td><td align="left"><p>11.70 ± 2.00</p></td></tr><tr><td align="left"><p>Sex (female/male)</p></td><td align="left"><p>12/48</p></td><td align="left"><p>13/47</p></td></tr><tr><td align="left"><p>Parent education</p></td><td align="left"><p>N (%)</p></td><td align="left"><p>N (%)</p></td></tr><tr><td align="left"><p>Elementary school</p></td><td align="left"><p>7 (5.9%)</p></td><td align="left"><p>1 (0.8%)</p></td></tr><tr><td align="left"><p>Skilled worker</p></td><td align="left"><p>26 (21.8%)</p></td><td align="left"><p>29 (24.2%)</p></td></tr><tr><td align="left"><p>High school</p></td><td align="left"><p>8 (6.7%)</p></td><td align="left"><p>12 (10.0%)</p></td></tr><tr><td align="left"><p>Short higher education of two years or less</p></td><td align="left"><p>18 (15.1%)</p></td><td align="left"><p>17 (14.2%)</p></td></tr><tr><td align="left"><p>Medium higher education from 2.5 to 4.5 years</p></td><td align="left"><p>38 (31.9%)</p></td><td align="left"><p>45 (37.5%)</p></td></tr><tr><td align="left"><p>Long parent education</p></td><td align="left"><p>22 (18.5%)</p></td><td align="left"><p>16 (13.3%)</p></td></tr><tr><td align="left" /><td align="left" colspan="2"><p><bold>Clinical variables</bold></p></td></tr><tr><td align="left"><p>ADOS-2 CSS</p></td><td align="left"><p>6.0 ± 2.1</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>ADI-R A Reciprocal social interaction</p></td><td align="left"><p>12.8 ± 5.5</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>ADI-R B Communication</p></td><td align="left"><p>11.0 ± 5.2</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>ADI-R C Repetitive stereotype behavior <sup>a</sup></p></td><td align="left"><p>3.00 (1–4.47)</p></td><td align="left"><p>-</p></td></tr><tr><td align="left"><p>ABAS-GAC *<sup>a</sup></p></td><td align="left"><p>64.5 (56.0–78.0)</p></td><td align="left"><p>94.5 (85.0-107.0)</p></td></tr><tr><td align="left"><p>ASRS Social Communication *</p></td><td align="left"><p>63.95 ± 7.04</p></td><td align="left"><p>45.10 ± 8.13</p></td></tr><tr><td align="left"><p>ASRS Unusual Behavior *</p></td><td align="left"><p>64.08 ± 8.75</p></td><td align="left"><p>46.08 ± 6.94</p></td></tr><tr><td align="left" /><td align="left" colspan="2"><p><bold>Cognitive assessment</bold></p></td></tr><tr><td align="left"><p>WISC-V Full-scale IQ</p></td><td align="left"><p>98.22 ± 14.78</p></td><td align="left"><p>101.67 ± 10.97</p></td></tr></tbody></table> </ephtml> </p> <p>Data are reported with mean ± standard deviations or with medians and lower and upper quartiles (<sups>a</sups>) if the variable significantly deviated from the normal distribution. WISC-V = Wechsler Intelligence Scale for Children, ADOS-2 = The Autism Diagnostic Observation Schedule, 2nd edition, Module 3; ADI-R = The Autism Diagnostic Interview-Revised; ABAS-GAC = Adaptive Behavior Assessment System, General Adaptive Composite; ASRS = Autism Spectrum Rating Scale. * Significant group difference at p <.05 tested with two-tailed t-tests</p> <hd id="AN0172396173-4">Clinical and cognitive assessment</hd> <p>Clinical and cognitive variables are shown in Table 1.</p> <hd id="AN0172396173-5">The Autism Diagnostic Observation schedule, 2nd edition (ADOS-2)</hd> <p>Children with autism, but not controls, were examined with the ADOS-2 Module 3, a standardized semi-structured assessment tool that measures the quality and frequency of social interaction, communication, play and restricted and repetitive behaviors (Lord et al., [<reflink idref="bib29" id="ref53">29</reflink>]). The severity of autism symptoms is measured using the total score (range 0–28).</p> <hd id="AN0172396173-6">The Autism Diagnostic interview-revised (ADI-R)</hd> <p>Parents to children with autism were interviewed with the semi-structured ADI-R by trained clinicians (JL and MF). The ADI-R assesses the developmental history and autism symptoms of the child (Rutter et al., [<reflink idref="bib44" id="ref54">44</reflink>]). ADI-R is scored using the Diagnostic Algorithm, which provides a differentiated assessment on three domains: reciprocal social interaction (15 items; range 0–30, communication (13 items; range 0–26) and repetitive and stereotyped behaviors (6 items; range 0–12).</p> <hd id="AN0172396173-7">The Autism Spectrum Rating Scale (ASRS)</hd> <p>All parents answered the ASRS questionnaire, a measure of severity of autistic-like symptoms within the last four weeks for children and adolescents aged 6–18 years (Goldstein, [<reflink idref="bib17" id="ref55">17</reflink>]). The ASRS measures autistic-like symptoms with the Social-Communication scale, including problems with Peer socialization, Adult socialization and Social-Emotional Reciprocity, and symptoms related to Atypical language, Behavioral Rigidity, Stereotypy, and Sensory Sensitivity with the scale Unusual Behaviors. Symptom severity is rated on a 4-point Likert scale.</p> <hd id="AN0172396173-8">Adaptive Behavior Assessment System - Second Edition (ABAS-II)</hd> <p>All parents answered questions about the child's functional daily adaptive skills assessed using the ABAS II (Harrison, [<reflink idref="bib20" id="ref56">20</reflink>]). Adaptive functioning is assessed with nine domains, including Communication, Community Use, Functional Academics, Home Living, Health and Safety, Leisure, Self-Care, Self-Direction and Social, which are summed to a General Adaptive Composite (ABAS-GAC) score. Questions are answered on a 4-point Likert scale.</p> <hd id="AN0172396173-9">Wechsler Intelligence Scale for Children – Fifth Edition WISC-V</hd> <p>All participants were assessed with the WISC-V. The WISC-V measures general intellectual ability in children and adolescents aged 6–16 years (Wechsler, [<reflink idref="bib52" id="ref57">52</reflink>]). We used the Full-scale intelligence quotient (IQ) score based on seven of the primary subtests. The Full-scale IQ has a mean of 100 and a standard deviation of 15.</p> <hd id="AN0172396173-10">Semantic fluency</hd> <p>On the semantic fluency test, the child is instructed to name as many words as possible in 1 min from the category fruits and subsequently from the category animals without repetitions. The number of correct and unique answers for each category was summed and used to calculate the fluency score. Answers for fruits were scored as correct answers if the word was commonly defined as fruits, including legumes, berries and nuts. Answers for animals were scored as correct answers if the word was commonly defined as an animal, including prehistoric but not fictional animals. Within-species animal words that differed only in sex or young and adult, such as cow, bull and calf, were coded as correct responses. Verbal responses were recorded and transcribed. Animals and fruits were written in the singular form to standardize the calculation of typicality. The norms for the typicality index were based on the control group by dividing the number of controls saying a word by the total number of controls, similar to Quaranta et al., ([<reflink idref="bib40" id="ref58">40</reflink>]). Thus, a word mentioned by all controls (N = 60) would get a word typicality score of 60/60 = 1, while a word mentioned by only one control would get a word typicality score of 1/60 = 0.017. Words only mentioned by children with autism received a typicality score of 0.017. The typicality score for each child was calculated as the mean typicality of that child's valid answers for animals and fruits, respectively. The 60 control children named 203 different animals and a total of 1083 animals, while they named 57 different fruits for a total of 575 fruits. The ratio of different/total animals was therefore 203/1083 = 0.187, while the ratio of different/total fruits was 57/575 = 0.099, which clearly shows more diversity in naming animals than fruits. Levene's test of equality of variance confirmed that the typicality index for fruits had smaller variance compared to animals (F(<reflink idref="bib1" id="ref59">1</reflink>,<reflink idref="bib258" id="ref60">258</reflink>) = 19.951, p <.001). Figure 1 shows the frequency distributions for fruits and animals, respectively, and the outcome measures for animal fluency, fruit fluency, animal typicality and fruit typicality are displayed in Table 2.</p> <p>Graph: Fig. 1The graph shows the distribution of the typicality scores for each of the 57 different fruits coded in black and 203 different animals coded in gray named by the 60 controls. Typicality scores are shown in descending order. As clearly illustrated by the graph, fruits had significantly smaller variance compared to animals</p> <p>Table 2 Outcome measures for semantic fluency, semantic typicality and semantic recall for children with autism and controls</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" /><th align="left"><p>Autism subjects (N = 60)</p></th><th align="left"><p>Controls (N = 60)</p></th></tr></thead><tbody><tr><td align="left" /><td align="left" colspan="2"><p><bold>Outcome measures</bold></p></td></tr><tr><td align="left"><p>Fluency animals *</p></td><td align="left"><p>15.58 ± 4.56</p></td><td align="left"><p>18.02 ± 4.46</p></td></tr><tr><td align="left"><p>Fluency fruits</p></td><td align="left"><p>8.62 ± 3.130</p></td><td align="left"><p>9.58 ± 3.41</p></td></tr><tr><td align="left"><p>Typicality animals</p></td><td align="left"><p>0.297 ± 0.060</p></td><td align="left"><p>0.290 ± 0.061</p></td></tr><tr><td align="left"><p>Typicality fruits * <sup>a</sup></p></td><td align="left"><p>0.476 (0.40-0.56)</p></td><td align="left"><p>0.489 (0.41-0.55)</p></td></tr><tr><td align="left"><p>Fruits recall 1st trial</p></td><td align="left"><p>3.97 ± 1.76</p></td><td align="left"><p>4.10 ± 1.82</p></td></tr><tr><td align="left"><p>Fruits recall 2nd trial</p></td><td align="left"><p>4.64 ± 1.77</p></td><td align="left"><p>5.28 ± 2.10</p></td></tr><tr><td align="left"><p>Fruits recall 3rd trial *</p></td><td align="left"><p>4.95 ± 2.32</p></td><td align="left"><p>6.17 ± 2.05</p></td></tr><tr><td align="left"><p>Fruits recall 4th trial *</p></td><td align="left"><p>5.09 ± 2.25</p></td><td align="left"><p>5.90 ± 1.98</p></td></tr><tr><td align="left"><p>Animals recall 1st trial</p></td><td align="left"><p>3.90 ± 1.71</p></td><td align="left"><p>4.00 ± 1.83</p></td></tr><tr><td align="left"><p>Animals recall 2nd trial</p></td><td align="left"><p>4.97 ± 2.33</p></td><td align="left"><p>5.62 ± 2.16</p></td></tr><tr><td align="left"><p>Animals recall 3rd trial</p></td><td align="left"><p>5.95 ± 2.31</p></td><td align="left"><p>6.33 ± 2.36</p></td></tr><tr><td align="left"><p>Animals recall 4th trial</p></td><td align="left"><p>5.88 ± 2.45</p></td><td align="left"><p>6.05 ± 2.17</p></td></tr><tr><td align="left"><p>Unrelated recall 1st trial <sup>a</sup></p></td><td align="left"><p>2.53 (1.75-3.0)</p></td><td align="left"><p>2.5 (2.0–3.0)</p></td></tr><tr><td align="left"><p>Unrelated recall 2nd trial <sup>a</sup></p></td><td align="left"><p>3.67 (2.0–5.0)</p></td><td align="left"><p>4.42 (3.0–5.0)</p></td></tr><tr><td align="left"><p>Unrelated recall 3rd trial</p></td><td align="left"><p>4.88 ± 2.623</p></td><td align="left"><p>5.4 ± 2.30</p></td></tr><tr><td align="left"><p>Unrelated recall 4th trial <sup>a</sup></p></td><td align="left"><p>4.34 (2.25-5)</p></td><td align="left"><p>4.65 (3–6)</p></td></tr></tbody></table> </ephtml> </p> <p>Data are reported with mean ± standard deviations or with medians and lower and upper quartiles (<sups>a</sups>) if the variable significantly deviated from the normal distribution. Significant group difference are shown with *</p> <hd id="AN0172396173-11">Semantic recall</hd> <p>Our semantic free recall task was based on similar principles used by previous studies (Maister et al., [<reflink idref="bib30" id="ref61">30</reflink>]; Tager-Flusberg, [<reflink idref="bib48" id="ref62">48</reflink>]). However, while these studies used separate tasks to test differences in the recall of semantic and semantically unrelated words, we combined the semantic and semantically unrelated words into one task to avoid potential bias in the order of presentation. The recall task included 36 words, specifically 12 fruits, 12 animals and 12 semantically unrelated words. The three word lists containing animals, fruits and unrelated words, respectively, were carefully matched on frequency based on previously published norms from 448 children and adolescents aged 3–12 years (Price & Connolly, [<reflink idref="bib39" id="ref63">39</reflink>]). The recall task was made of 12 blocks of 3 words, one from each list. Words within each block were matched on frequency to ensure they were evenly distributed across the total word list.</p> <p>The words were read aloud at a steady pace over a 90-second interval. The child was instructed to listen carefully and remember as many words as possible before each of three immediate recall trials. Delayed recall was assessed by asking the subject to recall as many words from the list following a time interval of approximately 30 min (autism group: mean interval = 34:13 min (SD = 04:18 min), control group: mean interval = 32:53 min (SD = 04:09)). The answers were recorded and transcribed. Intrusions were scored as errors. Two children with autism were unable to participate in the category recall task. Two additional children with autism were unable to participate in the delayed recall trial due to non-compliance. The outcome measures for the fruit, animal and unrelated word lists across the four recall trials are displayed in Table 2.</p> <hd id="AN0172396173-12">Statistical analyses</hd> <p>Statistical analyses were conducted using SPSS 27. A p-value < 0.05 was considered significant. Continuous variables were determined to have a significantly non-normal distribution if the standard errors for the skewness were above or below Z ± 1.96 (two-sided <emph>p <</emph>.05) in the children with autism and/or controls. If not otherwise specified, non-normally distributed variables were normalized using the Rankit transformation, and the normalized values were used in the statistical analyses. Significantly non-normally distributed variables are displayed in Tables 1 and 2 with medians and quartiles. Group differences in age, Full-scale IQ, ASRS Social Communication and ASRS Unusual Behaviors were tested with two-tailed t-tests, while group differences in sex and parent education were tested with the Chi-square test.</p> <p>Group differences on rule-breaking errors and repetition errors on the animal and fruit fluency tasks were tested with Chi-square to assure that the control and autism groups did not differ in test compliance. Group differences in semantic fluency and typicality for animals and fruits, respectively, were tested with multiple linear regression models. Group differences in semantic recall were examined using repeated-measures ANCOVA. If significant group differences were observed, the linear regression and ANCOVA models were controlled for age, sex, parent education and Full-scale IQ. Because linear regression analysis and ANOVA are not able to properly model ordinal covariates with more than two categories, parent education was recoded into a binary variable, used in the following analyses, classifying parents on lower education (elementary school, skilled worker, high school or short higher education of two years or less) or higher education (medium to long higher education) based on the parent with the highest education. All multiple linear regression models were visually inspected to ensure normal distribution of the residuals and that the model covariates fulfilled criteria of noncollinearity defined as a Tolerance > 0.3.</p> <p>The outcome measures for animal fluency, fruit fluency, animal typicality and fruit typicality were entered as the dependent variables in separate linear regression models, while group was entered as the predictor of interest. As it has previously been shown that typicality is highly dependent on fluency (Carneiro et al., [<reflink idref="bib8" id="ref64">8</reflink>]; Sailor et al., [<reflink idref="bib45" id="ref65">45</reflink>]), the corresponding fluency score was further entered as a covariate when the typicality score was used as the dependent variable. We used a two-way repeated-measures ANCOVA to test our hypothesis that children with autism have reduced recall for semantically related relative to unrelated words compared to controls. Group was entered as the between-subject factor while the animal, fruit and unrelated word lists were entered as the first within-subject factor, and the four recall trials were entered as the second within-subject factor in the ANCOVA model. Although the recall scores for the unrelated word list on 1st, 2nd and 4th trials were significantly non-normally distributed, we initially used the raw scores in the repeated measures ANCOVA to assess the effect of list and time, but in the case that significant group differences were observed, the potential effect of skewness for unrelated words was carefully assessed. Multiple linear regression models were used to test the directionality of group differences.</p> <p>Subsequently, multiple linear regression models were used to further explore the nature of significant group differences, always controlling for age, sex, parent education and Full-scale IQ. Initially, we examined if group differences on the fluency and recall measures were independent of each other. Therefore, group differences on the fluency test were controlled for group differences in recall and the other way around. An interaction term for group by recall or correspondingly group by fluency or typicality was then added to the model. If the interaction term was not significant whole-group analyses were performed.</p> <p>Next, we tested if group differences persisted when controlling for either the ASRS Social Communication or Unusual Behavior score or the ABAS-GAC score in separate linear regression models. Then, we included an interaction term for group by the ASRS Social Communication score, the ASRS Unusual Behavior score and the ABAS-GAC score, respectively, to examine if associations differed in the autism group compared to controls. If the interaction term was not significant whole-group analyses were performed excluding group as covariate.</p> <hd id="AN0172396173-13">Results</hd> <p>The children with autism and the typically developing controls were successfully matched and did not differ significantly on age (t(<reflink idref="bib118" id="ref66">118</reflink>)=-0.708; p =.480), sex (Chi-square (<reflink idref="bib1" id="ref67">1</reflink>, N = 120) = 0.054; p =.817), parent education (Chi-square (<reflink idref="bib5" id="ref68">5</reflink>, N = 239) = 6.005; p =.306). Children with autism did not differ from controls on Full-scale IQ (t(<reflink idref="bib118" id="ref69">118</reflink>) = 1.452; p =.149) but had significantly lower ABAS-GAC scores (t(<reflink idref="bib118" id="ref70">118</reflink>) = 10.358; p <.001), higher ASRS Social Communication scores (t(<reflink idref="bib118" id="ref71">118</reflink>)=-9.976; p <.001) and ASRS Unusual Behavior scores (t(<reflink idref="bib118" id="ref72">118</reflink>)=-12.972; p <.001) compared to controls.</p> <hd id="AN0172396173-14">Group differences in semantic fluency and typicality</hd> <p>Chi-square showed no significant group differences in rule-breaking errors for animals ((<reflink idref="bib1" id="ref73">1</reflink>, N = 120) = 0.152; p =.697; controls = 3; autism group = 4) or fruits ((<reflink idref="bib4" id="ref74">4</reflink>, N = 120) = 4.156; p =.385; controls = 8; autism group = 11) nor in repetition errors for animals ((<reflink idref="bib4" id="ref75">4</reflink>, N = 120) = 5.175; p =.270; controls = 15; autism group = 9) or fruits ((<reflink idref="bib2" id="ref76">2</reflink>, N = 120) = 0.840; p =.657; controls = 14; autism group = 10). Descriptive inspection of the individual frequency distributions indicated that it was quite normal for children to name unique words in both the control group and autism group. Of the 57 different fruits named by control children, 19 were named by only one child, and similarly of the 54 fruits named by children with autism 15 were named one time. Of the 203 different animals named by the controls, 84 words were named just once, while for the 197 animals named by children with autism 97 were named one time.</p> <p>The autism group displayed significantly lower animal fluency (t(<reflink idref="bib118" id="ref77">118</reflink>)=-2.956; β=-0.263; p =.004) and fruit typicality (t(<reflink idref="bib117" id="ref78">117</reflink>)=-2.557; β=-0.175; p =.012) while no group differences were seen for fruit fluency (t(<reflink idref="bib118" id="ref79">118</reflink>)=-1-617; β=-0.147; p =.108) or animal typicality (t(<reflink idref="bib117" id="ref80">117</reflink>)=-0.594; β=-0.052; p =.553). Controlling for age, sex, parent education and Full-scale IQ increased the effect sizes of the observed group differences in animal fluency (t(<reflink idref="bib114" id="ref81">114</reflink>)=-3.586; β=-0.274; p <.001; Fig. 2A) and fruit typicality (t(<reflink idref="bib113" id="ref82">113</reflink>)=-2.822; β=-0.195; p =.006). Even though the Rankit-transformed score for fruit typicality was normally distributed, visual inspection of the partial regression plot indicated one extreme outlier in the autism group with extremely low typicality. To ensure that group difference was not driven by this outlier, the regression analysis was rerun excluding the subject, which did not affect the group difference (<emph>t</emph>(<reflink idref="bib112" id="ref83">112</reflink>)=-2.788; β=-0.174; p =.006; Fig. 2B). As a precautionary measure, this child was excluded in all further analyses for fruits typicality.</p> <p>Graph: Fig. 2The partial regression plots display group differences in fluency for Animals (A), typicality for Fruits (B) and recall fruits at 3rd recall (F). The horizontal lines represent the group means, and the values displayed on the y-axes and x-axes are the regression model residuals. The line plots display the group difference in recall performance across the four trials for Fruits (C), Unrelated word (D) and Animals (E) shown with estimated marginal means and 0.5 standard deviations. The * indicates significant group differences (p <.05). All models are corrected for age, sex, parent education and Full-scale IQ. The Fruits typicality plot is further corrected for fruits fluency</p> <hd id="AN0172396173-15">Group differences in semantic recall</hd> <p>The repeated measures ANCOVA showed a significant main effect of word list (F(<reflink idref="bib2" id="ref84">2</reflink>, 228) = 43.155; p <.001), time (F(<reflink idref="bib3" id="ref85">3</reflink>, 342) = 128.849; p <.001), time by list (F(<reflink idref="bib6" id="ref86">6</reflink>, 684) = 4.870; p <.001), and a significant time by group effect (F(<reflink idref="bib3" id="ref87">3</reflink>, 342) = 2.777; p =.041), but no main effect of group (F(<reflink idref="bib1" id="ref88">1</reflink>, 114) = 2.609; p =.109), word list by group (F(<reflink idref="bib2" id="ref89">2</reflink>, 228) = 0.947; p =.389) or word list by time by group (F(<reflink idref="bib6" id="ref90">6</reflink>, 684) = 1.135; p =.341). The group by time interaction (F(<reflink idref="bib3" id="ref91">3</reflink>, 342) = 3.112; p =.027) survived correction for age, sex, parent education and Full-scale IQ. Subsequently, we explored whether recall for animals, fruits or unrelated words drove the significant group-by-time interaction. One-way repeated measures ANCOVA analyses controlled for age, sex, parent education and Full-scale IQ showed a significant main effect of group in recall for fruits (F(<reflink idref="bib1" id="ref92">1</reflink>, 110) = 6.007; p =.016 Fig. 2C) and a significant interaction for group by time for recall of fruits (F(<reflink idref="bib3" id="ref93">3</reflink>, 330) = 3.501; p =.020), while no main effect of group was found for animals (F(<reflink idref="bib1" id="ref94">1</reflink>, 110) = 1.637; p =.203 Fig. 2E) or unrelated words (F(<reflink idref="bib1" id="ref95">1</reflink>, 110) = 2.286; p =.133 Fig. 2D), and no group by time interaction was observed for neither animals (F(<reflink idref="bib3" id="ref96">3</reflink>, 33) = 0.837; p =.474) nor unrelated words (F(<reflink idref="bib3" id="ref97">3</reflink>, 33) = 1.483; p =.219). Multiple linear regression analyses showed that compared to controls, the autism group had similar recall for fruits in the 1st recall trial, a trend for lower recall at the 2nd trial (t(<reflink idref="bib112" id="ref98">112</reflink>)=-1.775; β=-0.146; p =.079) and significantly lower recall at the 3rd trial (t(<reflink idref="bib112" id="ref99">112</reflink>)=-3.280; β=-0.255; p =.001; Fig. 2F) and 4th trial (t(<reflink idref="bib110" id="ref100">110</reflink>)=-2.264; β=-0.189; p =.026), which indicate that the children with autism had a slower learning curve for fruits.</p> <p>Group difference in animal fluency and fruits typicality survived correction for fruits recall on the 3rd and 4th trial (p <.05), and differences in recall for fruits persisted controlling for animal fluency and fruits typicality, although group differences for fruits on the 4th trial turned near-significant when correcting for animal fluency (p =.069). No apparent interaction effects were observed (p >.05), and animal fluency and fruits typicality did not appear to be associated with either the 3rd or 4th recall trial for fruits across groups (p >.05).</p> <hd id="AN0172396173-16">Semantic fluency and recall associated with autism symptoms and adaptive functioning</hd> <p>The group differences in animal fluency and typicality for fruits persisted when additionally correcting for either of the ASRS or the ABAS-GAC scales (p <.05), although group differences in fruits typicality turned near-significant controlling for ASRS Unusual Behavior (<emph>t</emph>(<reflink idref="bib112" id="ref101">112</reflink>)=-1.829; β=-0.387; p =.070). Group difference for fruits 3rd recall remained significant when correcting for ASRS Unusual Behavior (p =.004), marginally so for ABAS-GAC (p =.051) but not ASRS Social Communication (p =.2), while group difference in fruits 4th recall did not survive correcting for the ASRS or ABAS-GAC scales (p >.05). We did not observe significant group interactions (p >.05).</p> <p>Results of whole-group analyses for animal fluency, fruit typicality and recall for fruits on the 3rd and 4th trial are shown in Table 3 and significant associations with the largest effect sizes for animal fluency, fruit typicality and recall for fruits on the 3rd trial, respectively, are displayed in Fig. 3.</p> <p>Table 3 Whole-group multiple linear regression models across children with autism and their typically developing peers</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" colspan="6"><p>Dependent variable: Fruits typicality</p></th></tr></thead><tbody><tr><td align="left" /><td align="left"><p>B</p></td><td align="left"><p>SE</p></td><td align="left"><p>t</p></td><td align="left"><p>β</p></td><td align="left"><p>p</p></td></tr><tr><td align="left"><p>ABAS-GAC</p></td><td align="left"><p>0.102</p></td><td align="left"><p>0.064</p></td><td align="left"><p>1.597</p></td><td align="left"><p>0.104</p></td><td align="left"><p>0.113</p></td></tr><tr><td align="left"><p>ASRS Social Communication</p></td><td align="left"><p>− 0.008</p></td><td align="left"><p>0.005</p></td><td align="left"><p>-1.601</p></td><td align="left"><p>− 0.104</p></td><td align="left"><p>0.112</p></td></tr><tr><td align="left"><p>ASRS Unusual Behavior</p></td><td align="left"><p>− 0.011</p></td><td align="left"><p>0.005</p></td><td align="left"><p>-2.142</p></td><td align="left"><p>− 0.755</p></td><td align="left"><p>0.034 * <sup>A</sup></p></td></tr><tr><td align="left" colspan="6"><p>Dependent variable: Animal fluency</p></td></tr><tr><td align="left"><p>ABAS-GAC</p></td><td align="left"><p>1.103</p></td><td align="left"><p>0.376</p></td><td align="left"><p>2.931</p></td><td align="left"><p>0.235</p></td><td align="left"><p>0.004 * <sup>B</sup></p></td></tr><tr><td align="left"><p>ASRS Social Communication</p></td><td align="left"><p>− 0.076</p></td><td align="left"><p>0.031</p></td><td align="left"><p>0.2.488</p></td><td align="left"><p>− 0.198</p></td><td align="left"><p>0.014 *</p></td></tr><tr><td align="left"><p>ASRS Unusual Behavior</p></td><td align="left"><p>− 0.084</p></td><td align="left"><p>0.030</p></td><td align="left"><p>-2.822</p></td><td align="left"><p>− 0.222</p></td><td align="left"><p>0.006 *</p></td></tr><tr><td align="left" colspan="6"><p>Dependent variable: Fruits recall 3rd trial</p></td></tr><tr><td align="left"><p>ABAS-GAC</p></td><td align="left"><p>0.495</p></td><td align="left"><p>0.187</p></td><td align="left"><p>2.654</p></td><td align="left"><p>0.214</p></td><td align="left"><p>0.009 *</p></td></tr><tr><td align="left"><p>ASRS Social Communication</p></td><td align="left"><p>− 0.046</p></td><td align="left"><p>0.015</p></td><td align="left"><p>-3.139</p></td><td align="left"><p>− 0.249</p></td><td align="left"><p>0.002 * <sup>C</sup></p></td></tr><tr><td align="left"><p>ASRS Unusual Behavior</p></td><td align="left"><p>− 0.026</p></td><td align="left"><p>0.015</p></td><td align="left"><p>-1.758</p></td><td align="left"><p>− 0.143</p></td><td align="left"><p>0.081</p></td></tr><tr><td align="left" colspan="6"><p>Dependent variable: Fruits recall 4rd trial</p></td></tr><tr><td align="left"><p>ABAS-GAC</p></td><td align="left"><p>0.280</p></td><td align="left"><p>0.188</p></td><td align="left"><p>1.488</p></td><td align="left"><p>0.129</p></td><td align="left"><p>0.140</p></td></tr><tr><td align="left"><p>ASRS Social Communication</p></td><td align="left"><p>− 0.035</p></td><td align="left"><p>0.015</p></td><td align="left"><p>-2.398</p></td><td align="left"><p>− 0.209</p></td><td align="left"><p>0.018 *</p></td></tr><tr><td align="left"><p>ASRS Unusual Behavior</p></td><td align="left"><p>− 0.028</p></td><td align="left"><p>0.015</p></td><td align="left"><p>-1.878</p></td><td align="left"><p>− 0.160</p></td><td align="left"><p>0.063</p></td></tr></tbody></table> </ephtml> </p> <p>All multiple linear models were adjusted for age, sex, Full-scale IQ and parental education. The ASRS and ABAS-GAC scales were entered as covariates of interest in separate multiple linear regression analyses. ABAS-GAC = Adaptive Behavior Assessment System, General Adaptive Composite; ASRS = Autism Spectrum Rating Scale. Significant group difference are shown with *. <sups>A, B & C</sups> are displayed in Figure 3.</p> <p>Graph: Fig. 3The partial regression plots display whole-group analyses of the relationship between typicality for fruits and ASRS Unusual behavior (A), Fluency for Animals and ABAS-GAC score (B), Fruits 3rd recall and ASRS Social Communication (C). The straight lines represent the linear fits. The values displayed on the y-axes and x-axes are the regression model residuals. All models were corrected for age, sex, parent education and Full-scale IQ</p> <hd id="AN0172396173-17">Discussion</hd> <p>The present study examined the hypothesis that children with autism differ from typically developing controls in their semantic fluency and recall of words. We used the categories fruit and animal as outcome measures on both the fluency test and the semantic recall task to ease appraisal of the findings on the two tests. Our hypotheses were partially supported as children with autism compared to controls named more atypical fruits and had lower fluency for animals. On the novel semantic recall task, children with autism initially recalled a similar number of words as controls, but the autism group had a flatter learning curve for fruits, which persisted on the delayed recall. Across the children with and without autism, lower typicality for fruits was coupled with more autistic-like unusual behaviors, including atypical language, rigidity, stereotypy and sensory sensitivity while reduced recall for fruits were related to more social communication problems and lower adaptive functions. Lastly, lower fluency for animals was associated with more social communication problems, unusual behaviors, and lower adaptive functioning. These associations appear dimensional as they were evident across the entire sample of children and adolescents and not unique to the autism group.</p> <p>Previous studies that examined whether children with autism differ from their typically developing peers in the semantic clustering of words have provided conflicting results (Begeer et al., [<reflink idref="bib3" id="ref102">3</reflink>]; Inokuchi & Kamio, [<reflink idref="bib23" id="ref103">23</reflink>]; Pastor-Cerezuela et al., [<reflink idref="bib37" id="ref104">37</reflink>]). Therefore, we used a simple but unbiased method to estimate word typicality based on how frequent category words were named by control participants. Here, we present novel evidence that children with autism name more atypical fruits than controls. Our results indicate that word typicality is a valid way to assess verbal idiosyncrasy in children and adolescents with autism thereby expanding its usability to a broader age range as earlier studies have examined word typicality in adults with Alzheimer's disease (Quaranta et al., [<reflink idref="bib40" id="ref105">40</reflink>]; Sailor et al., [<reflink idref="bib45" id="ref106">45</reflink>]) or schizotypal traits (Kiang & Kutas, [<reflink idref="bib25" id="ref107">25</reflink>]; Rodríguez-Ferreiro & Aguilera, [<reflink idref="bib43" id="ref108">43</reflink>]). It is unclear whether semantic word typicality reflects inter-individual variations in the underlying semantic networks and/or executive language functions. The Controlled Semantic Cognition (CSC) framework assumes that semantic cognition relies on the representation and control of semantic networks. Semantic representations of concepts are underpinned by a multimodal 'hub' and modality-specific 'spokes' while semantic control supports executive functions that constrain and modulate semantic representations of concepts. Semantic control is more needed when representations are weakly encoded, and context-dependent whereas robustly encoded semantic knowledge needs little guidance from the semantic control system (Ralph et al., [<reflink idref="bib41" id="ref109">41</reflink>]). Because semantic typicality reflects how common a word is to a category, typicality may rely more on the hub-and-spokes system than semantic control. In support of this view, elderly people with Alzheimer's disease name more typical words than controls (Quaranta et al., [<reflink idref="bib40" id="ref110">40</reflink>]; Sailor et al., [<reflink idref="bib45" id="ref111">45</reflink>]), maybe because their semantic networks are slowly breaking down, resulting in a weakening of the semantic connections of those words least representative to a category. Lower fruit typicality but not fruit fluency has been associated with increased schizotypal-like traits in community adults, mainly with more disorganized/odd speech and behavior (Kiang & Kutas, [<reflink idref="bib25" id="ref112">25</reflink>]). These findings are in line with our results as naming more atypical fruits across the autism group and controls were associated with more parent-reported autistic-like unusual behaviors, including atypical language, rigidity, stereotypy, and sensory sensitivity. However, while semantic atypicality in the children with autism likely reflects the developmental trajectories in semantic knowledge, the semantic hyper-typicality in the elderly with Alzheimer's probably occurs later in life as a consequence of the acquired disease. The time course of semantic atypicality in people high on schizotypal traits is more uncertain as many individuals on the schizophrenia spectrum display cognitive deficits already in childhood (Murray et al., [<reflink idref="bib33" id="ref113">33</reflink>]). In any case, the lower fruit typicality in the autism group does not appear trivial as it was coupled with severity of autistic-like symptoms.</p> <p>Evidence furthermore suggests that the semantic networks for fruits are rooted in early childhood. Semantic clustering is believed to reflect the underlying architecture of semantic networks. Studies have consistently shown that the size of semantic clusters on the fluency task already reaches a developmental plateau in the early school-aged years (Becker et al., [<reflink idref="bib2" id="ref114">2</reflink>]; Gonçalves et al., [<reflink idref="bib18" id="ref115">18</reflink>]; Hurks et al., [<reflink idref="bib22" id="ref116">22</reflink>]; Kavé et al., [<reflink idref="bib24" id="ref117">24</reflink>]). Moreover, the frequency responses for fruits are strikingly similar across the age range 3 to 12 years (Carneiro et al., [<reflink idref="bib8" id="ref118">8</reflink>]; Price & Connolly, [<reflink idref="bib39" id="ref119">39</reflink>]). Thus, it seems plausible that the atypical naming of fruits observed in the autism group originates as early as in preschool years and reflects an idiosyncratic development in the semantic networks for fruits. This may likewise partly explain why we did not observe a group difference in animal typicality because the normative frequency responses for animals seem to change considerably from early childhood to adolescence (Carneiro et al., [<reflink idref="bib8" id="ref120">8</reflink>]; Price & Connolly, [<reflink idref="bib39" id="ref121">39</reflink>]). In line with previous findings (Kiang & Kutas, [<reflink idref="bib25" id="ref122">25</reflink>]; Nelson, [<reflink idref="bib34" id="ref123">34</reflink>]), we observed that the frequency responses for animals showed significantly more variance than the category of fruits. This indicates that animals are a more heterogeneous category relative to fruits, which is a smaller and more uniform category. The fact that the category of animals appears to be very heterogeneous as well as less stable in childhood may make animals unsuitable as a measure of semantic typicality, at least in children.</p> <p>Although we do not know what underlies the observed atypical semantics for fruits in autism, differences in the daily experiences of children with autism may provide some explanation. For instance, the special interests frequently seen in children with autism (Nowell et al., [<reflink idref="bib35" id="ref124">35</reflink>]) could affect what type of words they pick up on. Children with autism furthermore display a high occurrence of sensory processing challenges including taste and smell sensitivity, and they often show food selectivity related to insistence on sameness and restricted eating habits (Marí-Bauset et al., [<reflink idref="bib31" id="ref125">31</reflink>]).This is perhaps why naming more atypical fruits in the present study was associated with increased unusual behaviors, which includes heightened sensory sensitivity, rigidity, stereotypy and atypical language.</p> <p>In line with some studies (Inokuchi & Kamio, [<reflink idref="bib23" id="ref126">23</reflink>]; Mashal & Kasirer, [<reflink idref="bib32" id="ref127">32</reflink>]; Panerai et al., [<reflink idref="bib36" id="ref128">36</reflink>]; Pastor-Cerezuela et al., [<reflink idref="bib37" id="ref129">37</reflink>]; Verté et al., [<reflink idref="bib51" id="ref130">51</reflink>]), but in contrast to others (Begeer et al., [<reflink idref="bib3" id="ref131">3</reflink>]; Corbett et al., [<reflink idref="bib10" id="ref132">10</reflink>]; Goddard et al., [<reflink idref="bib16" id="ref133">16</reflink>]; Happe et al., [<reflink idref="bib19" id="ref134">19</reflink>]; Maister et al., [<reflink idref="bib30" id="ref135">30</reflink>]; Robinson et al., [<reflink idref="bib42" id="ref136">42</reflink>]), we observed that the autism group had lower animal fluency and a marginally lower fruit fluency (p =.052) compared to controls. It is still unclear why findings on semantic fluency in childhood autism are so inconsistent. However, matching of autism and control groups on verbal abilities or global intelligence may play a critical role for the outcome of results. Those studies that have examined children with average or well below average intellectual ability on group level and matched the autism and control groups on verbal abilities or full-scale intelligence found no group differences in semantic fluency (Begeer et al., [<reflink idref="bib3" id="ref137">3</reflink>]; Goddard et al., [<reflink idref="bib16" id="ref138">16</reflink>]; Happe et al., [<reflink idref="bib19" id="ref139">19</reflink>]; Maister et al., [<reflink idref="bib30" id="ref140">30</reflink>]; Robinson et al., [<reflink idref="bib42" id="ref141">42</reflink>]). In contrast, some studies reporting lower semantic fluency in children with autism did not match groups on verbal abilities but solely on non-verbal intelligence (Panerai et al., [<reflink idref="bib36" id="ref142">36</reflink>]; Pastor-Cerezuela et al., [<reflink idref="bib37" id="ref143">37</reflink>]). In one of these studies, the autism group had a verbal intelligence below 70 on group average but was compared to typically verbal intelligent children (Pastor-Cerezuela et al., [<reflink idref="bib37" id="ref144">37</reflink>]). Furthermore, other studies observing lower semantic fluency in children with autism neither assessed verbal nor non-verbal intellectual abilities (Mashal & Kasirer, [<reflink idref="bib32" id="ref145">32</reflink>]; Verté et al., [<reflink idref="bib51" id="ref146">51</reflink>]). Thus, it appears that the discrepancies between studies on semantic fluency in childhood autism are to some extent explained by whether or not the autism group was matched to the control group on measures of verbal abilities or full-scale intelligence. Therefore, we assured to carefully match and control for likely confounders, including age, sex, parent education and Full-scale IQ, which includes assessment of verbal and non-verbal intellectual abilities. Lower animal fluency showed robust associations with more autistic-like unusual behaviors and social-communication problems and with lower levels in adaptive functioning across the children with autism and controls. This indicates that the lower animal fluency in the autism group is not simply a spurious or trivial finding, and reduced semantic fluency has previously been associated with decreased adaptive functioning in children with autism (Panerai et al., [<reflink idref="bib36" id="ref147">36</reflink>]). While typicality may tap more into the representational part of semantic networks, a higher animal fluency likely relies somewhat more on semantic control as specified by the CSC framework (Ralph et al., [<reflink idref="bib41" id="ref148">41</reflink>]). This is supported by findings showing that better semantic fluency is positively associated with executive functions in children and adolescents (Ardila et al., [<reflink idref="bib1" id="ref149">1</reflink>]; Dias & Seabra, [<reflink idref="bib12" id="ref150">12</reflink>]; Henry et al., [<reflink idref="bib21" id="ref151">21</reflink>]). In summary, the reduced semantic typicality and fluency in the autism group may reflect differences in the underlying semantic networks and semantic control functions, respectively.</p> <p>Our finding that children with autism had a slower learning rate for fruits but not animals or unrelated words partially agrees with some studies but not others. We could not replicate previous reports that children with autism had lower recall for semantically related words relative to unrelated words on the first immediate recall trial (Lopez & Leekam, [<reflink idref="bib28" id="ref152">28</reflink>]; Maister et al., [<reflink idref="bib30" id="ref153">30</reflink>]; Tager-Flusberg, [<reflink idref="bib48" id="ref154">48</reflink>]). Our results, however, are in agreement with other studies that observed children with autism to have similar semantic recall as controls on the first recall trial but a slower learning rate for semantic recall on later trials (Bennetto et al., [<reflink idref="bib4" id="ref155">4</reflink>]; Solomon et al., [<reflink idref="bib47" id="ref156">47</reflink>]), although others found no group differences across semantic recall trials (Phelan et al., [<reflink idref="bib38" id="ref157">38</reflink>]; Tyson et al., [<reflink idref="bib50" id="ref158">50</reflink>]). Some of the inconsistencies between studies may be due to methodological differences, such as the categories used to test semantic recall. For instance, Lopez & Leekam ([<reflink idref="bib28" id="ref159">28</reflink>])found that children with autism had lower recall for animals but not vehicles. Although, even those studies that used the same semantic word list, some have found impaired learning rates (Bennetto et al., [<reflink idref="bib4" id="ref160">4</reflink>]; Solomon et al., [<reflink idref="bib47" id="ref161">47</reflink>]) while others have not (Phelan et al., [<reflink idref="bib38" id="ref162">38</reflink>]; Tyson et al., [<reflink idref="bib50" id="ref163">50</reflink>]). The inclusion of children with either typical or lowered intellectual abilities might also influence results. Our autism group and controls were on average intellectually typical, while some of the studies that observed lower semantic recall on the first trial in children with autism examined autistic subjects with either intellectual disabilities (Tager-Flusberg, [<reflink idref="bib48" id="ref164">48</reflink>]) or intellectual abilities well below average on group average (Lopez & Leekam, [<reflink idref="bib28" id="ref165">28</reflink>]). Therefore, the autism group in our study may have been able to employ cognitive resources or strategies on the first recall trial that may not be accessible to children with intellectual disabilities. It has previously been speculated that the weakened semantic memory associated with autism is linked to inefficient memory strategies (Bennetto et al., [<reflink idref="bib4" id="ref166">4</reflink>]; Maister et al., [<reflink idref="bib30" id="ref167">30</reflink>]; Solomon et al., [<reflink idref="bib47" id="ref168">47</reflink>]). Impaired strategic recall could indicate problems with more context-dependent semantic control in line with the CSC framework (Ralph et al., [<reflink idref="bib41" id="ref169">41</reflink>]). In the present study, the slower learning rate for fruits observed in the autism group does not appear to be explained by general memory or executive deficits. Otherwise, the children with autism would be expected to display a slower learning rate on all three word lists, which they did not. Moreover, the lower recall for fruits in children with autism was not explained by their more idiosyncratic fluency for fruits as the two measures were not associated with each other. Decreased recall for fruits was related to more autistic-like social communication problems and reduced levels in adaptive functioning in the present study. Lower semantic recall has earlier been associated with social communication problems and reduced daily living skills in typically gifted children with autism (Liss et al., [<reflink idref="bib27" id="ref170">27</reflink>]). Therefore, efficient use of the semantics of words for context-dependent memory encoding and retrieval may have implications for the child's ability to function in daily situations and routines.</p> <hd id="AN0172396173-18">Limitations</hd> <p>Because our study was cross-sectional, we cannot determine whether inter-individual variations in semantic fluency and typicality and the lower learning rate for fruits are causally linked to differences in severity of autism symptoms and/or adaptive functioning. We used Canadian norms (Price & Connolly, [<reflink idref="bib39" id="ref171">39</reflink>]) to match our three word lists on frequency as no Danish frequency norms were available and cultural differences in the frequency distributions of category norms may have affected our findings. The choice to assess semantic fluency and recall with the categories fruits and animals may further have influenced the results of the present study as suggested by evidence from studies on fluency (Inokuchi & Kamio, [<reflink idref="bib23" id="ref172">23</reflink>]) and semantic recall (Lopez & Leekam, [<reflink idref="bib28" id="ref173">28</reflink>]). Future research on semantic memory in autism may consider what categories to examine based on the frequency distributions of the category words and how variable the frequency distributions appear across childhood and adolescence. We used the typically developing children and adolescents as the normative group, and it is therefore likely that the group difference in typicality for fruits was simply caused by a trivial comparison of "who said what". However, the observation that lower typicality was coupled to more parent-reported autistic-like unusual behaviors provide some indication that naming more atypical fruits has some relationship to the level of autism symptoms.</p> <hd id="AN0172396173-19">Conclusions</hd> <p>In conclusion, compared to their typically developing peers, children and adolescents with autism name fewer animals, spontaneously name more atypical fruits and display troubles with using the semantics of fruits to guide their memory on repeated verbal recall trials. While the lower fruit typicality in children with autism might reflect an idiosyncratic development of the underlying semantic networks, the lower learning rate for fruits is more likely related to inefficient strategies in using contextual semantic inputs to guide memory. Our findings suggest that even subtle differences in the semantic networks and memory of children with autism are coupled to the wide spectrum of autism symptoms and even the ability to adapt.</p> <hd id="AN0172396173-20">Conflict of interest</hd> <p>None of the authors report any actual or potential conflict of interest, including any financial, personal, or other relationships with other people or organizations within three years of beginning the submitted work that could inappropriately influence, or be perceived to influence, the work.</p> <hd id="AN0172396173-21">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0172396173-22"> <title> References </title> <blist> <bibl id="bib1" idref="ref59" type="bt">1</bibl> <bibtext> Ardila A, Rosselli M, Bateman JR. Factorial structure of cognitive activity using a neuropsychological test battery. 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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Atypical Semantic Fluency and Recall in Children and Adolescents with Autism Spectrum Disorders Associated with Autism Symptoms and Adaptive Functioning
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Foldager%2C+Malene%22">Foldager, Malene</searchLink><br /><searchLink fieldCode="AR" term="%22Vestergaard%2C+Martin%22">Vestergaard, Martin</searchLink><br /><searchLink fieldCode="AR" term="%22Lassen%2C+Jonathan%22">Lassen, Jonathan</searchLink><br /><searchLink fieldCode="AR" term="%22Petersen%2C+Lea+S%2E%22">Petersen, Lea S.</searchLink><br /><searchLink fieldCode="AR" term="%22Oranje%2C+Bob%22">Oranje, Bob</searchLink><br /><searchLink fieldCode="AR" term="%22Aggernaes%2C+Bodil%22">Aggernaes, Bodil</searchLink><br /><searchLink fieldCode="AR" term="%22Simonsen%2C+Erik%22">Simonsen, Erik</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Autism+and+Developmental+Disorders%22"><i>Journal of Autism and Developmental Disorders</i></searchLink>. Nov 2023 53(11):4280-4292.
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  Label: Availability
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 13
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2023
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Autism+Spectrum+Disorders%22">Autism Spectrum Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Fluency%22">Language Fluency</searchLink><br /><searchLink fieldCode="DE" term="%22Semantics%22">Semantics</searchLink><br /><searchLink fieldCode="DE" term="%22Recall+%28Psychology%29%22">Recall (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Children%22">Children</searchLink><br /><searchLink fieldCode="DE" term="%22Early+Adolescents%22">Early Adolescents</searchLink><br /><searchLink fieldCode="DE" term="%22Symptoms+%28Individual+Disorders%29%22">Symptoms (Individual Disorders)</searchLink><br /><searchLink fieldCode="DE" term="%22Executive+Function%22">Executive Function</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/s10803-022-05677-x
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0162-3257<br />1573-3432
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: It is unclear whether children with autism spectrum disorders have atypical semantic fluency and lower memory for the semantics of words. Therefore, we examined semantic typicality, fluency and recall for the categories of fruits and animals in 60 children with autism aged 7-15 years (boys: 48/girls: 12) compared to 60 typically developing controls. Relative to controls, the autism group had reduced animal fluency, fruit typicality and recall for fruits. Notably, these measures were associated with more autistic-like symptoms and/or lower adaptive functioning across the autism and control groups. In conclusion, atypical semantics of fruits in the autism group may reflect development of idiosyncratic semantic networks while their lower semantic fluency and recall suggest impaired executive language functions.
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  Data: 2023
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  Data: EJ1394392
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      – Type: doi
        Value: 10.1007/s10803-022-05677-x
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 13
        StartPage: 4280
    Subjects:
      – SubjectFull: Autism Spectrum Disorders
        Type: general
      – SubjectFull: Language Fluency
        Type: general
      – SubjectFull: Semantics
        Type: general
      – SubjectFull: Recall (Psychology)
        Type: general
      – SubjectFull: Children
        Type: general
      – SubjectFull: Early Adolescents
        Type: general
      – SubjectFull: Symptoms (Individual Disorders)
        Type: general
      – SubjectFull: Executive Function
        Type: general
    Titles:
      – TitleFull: Atypical Semantic Fluency and Recall in Children and Adolescents with Autism Spectrum Disorders Associated with Autism Symptoms and Adaptive Functioning
        Type: main
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            NameFull: Foldager, Malene
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            – D: 01
              M: 11
              Type: published
              Y: 2023
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            – Type: issn-print
              Value: 0162-3257
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              Value: 1573-3432
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