1Department of Cognitive Neuroscience, Faculty of Educational Sciences and Psychology, University of Tabriz, Tabriz, Iran.
2Department of Mathematics, Institute for Advanced Studies in Basic Sciences, Zanjan, Iran.
3Department of Biomedical Engineering, Faculty of Engineering, Shahed University, Tehran, Iran.
چکیده
Background: Autism Spectrum Disorders (ASD) are a group of developmental conditions that impair social communication and often involve repetitive behaviors. Among the core features of ASD, verbal impairments are prominent. Verbal fluency tests are widely used neuropsychological tasks to assess language skills in children with ASD. Recently, speech graphs, derived from graph theory, have been employed to analyze verbal fluency performance more comprehensively. Methods: This study aimed to compare speech graph features from phonemic and semantic verbal fluency tasks between children with ASD and typically developing (TD) peers. Participants included 25 children with ASD (ages 7–12 years; IQ 70–85 based on the Goodenough Test) from an autism school in Tabriz, and 30 age-matched TD children from regular schools. Verbal fluency was assessed using the Kormi Nouri fluency task with phonemic cues (A, N, M) and semantic categories (boy names, girl names, body parts, fruits, colors, kitchen utensils). Spoken words were represented as nodes, and temporal links between them as edges, to construct speech graphs. Standard verbal fluency scores and graph features were analyzed using independent t-tests and Mann–Whitney U tests. Results: Children with ASD produced fewer words in both phonemic and semantic fluency tasks compared to TD children. Their speech graphs also displayed fewer nodes and edges, smaller largest connected components, lower average shortest paths and diameters, higher graph density, and reduced average total degree in comparison to TD peers. Conclusion: Speech graph analysis offers a novel computational approach for characterizing verbal fluency deficits in children with ASD. The findings suggest potential applications for developing computer-based rehabilitation tools for individuals with speech and language impairments. Future studies may expand these approaches to other cognitive domains.
Sternberg RJ. Cognitive Psychology. Kharazi SK, Hejazi E, translators. Tehran: SAMT Publications; 2015. [In Persian]
Baars B, Gage N. Fundamentals of Cognitive Neuroscience. Kharazi SK, translator. Tehran: SAMT Publications; 2015.
Fredenburg J, Silverman G. Cognitive Science: An Introduction to the Study of Mind. Eftadehal M, et al., translators. Tehran: Defense Industries Education and Research Institute Press; 2016 [In Persian].
Lindgren KA, Folstein SE, Tomblin JB, Tager‐Flusberg H. Language and reading abilities of children with autism spectrum disorders and specific language impairment and their first‐degree relatives. Autism Research. 2009 Feb;2(1):22-38.
Grange CN. A Literature Review: How Language Parameter Deficits Impact Social Interaction in Children with Autism Spectrum Disorders during Middle Childhood, and Intervention Strategies. McNair Scholars Research Journal. 2012;5(1):7.
Fanid LM, Shahrokhi H, Amiri S. Verbal Fluency is Related to Theory of Mind: Comparison in Control Children and with Autism Spectrum Disorder. International Neuropsychiatric Disease Journal. 2017;9(3):1-9.
Dockrell J, McShane J. Children's learning difficulties: A cognitive approach. Tehran: Roshd Publications; 1993 [In Persian].
Karami-Nouri R, Moradi A, Akbari-Zardkhaneh S, Gholami A. Development of phonemic and semantic verbal fluency in Persian-speaking children. Educational Innovations Quarterly. 2008;7(25):97–118 [In Persian].
Lezak MD. Neuropsychological assessment. Oxford University Press, USA; 2004.
Zarean M, Bahalouei Z, Ekhtiari H. Theoretical and Applied Considerations in Persian Verbal Fluency Task: A Systematic Review. Journal of Modern Psychological Researches. 2020 Dec 21;15(59):49-71.
Bahrami H, Nejati V, Pour-Etemad HR, Fath-Abadi J. A comparison of verbal fluency in individuals with developmental stuttering and healthy subjects. Zahedan Journal of Research in Medical Sciences. 2012;14(1):13-20 [In Persian].
Tan EJ, Neill E, Tomlinson K, Rossell SL. Semantic memory impairment across the schizophrenia continuum: a meta-analysis of category fluency performance. Schizophrenia bulletin open. 2020 Jan;1(1):sgaa054.
Bertola L, Mota NB, Copelli M, Rivero T, Diniz BS, Romano-Silva MA, et al. Graph analysis of verbal fluency test discriminate between patients with Alzheimer's disease, mild cognitive impairment and normal elderly controls. Frontiers in aging neuroscience. 2014 Jul 29;6:185.
Babelian E. Topics in Discrete Mathematics. Tehran: Mobtakeran Publications; 2010 [In Persian].
Nazari S, Sayahi H. Comparison of phonemic and semantic verbal fluency in dyslexic and non-dyslexic students. Journal of Exceptional Education. 2014;14(2):18–24 [In Persian].
Zhang G, Ma J, Chan P, Ye Z. Graph theoretical analysis of semantic fluency in patients with Parkinson’s disease. Behavioural Neurology. 2022;2022(1):6935263.
