Preserved navigation abilities and spatio‐temporal memory in individuals with autism spectrum disorder

Laidi, Charles; Neu, Nathan; Watilliaux, Aurélie; Martinez-Teruel, Axelle; Razafinimanana, Mihoby; Boisgontier, Jennifer; Hotier, S.; d’Albis, Marc-Antoine; Delorme, Richard; Amestoy, Anouck; Holiga, Štefan; Le-Moal, Myriam Ly; Coupé, Pierrick; Leboyer, Marion; Houenou, Josselin; Rondi-Reig, Laure; Paradis, Anne‐Lise

doi:10.1002/aur.2865

Cited by 2 publications

(2 citation statements)

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“…Among them, the heschl and superior frontal gyrus areas both play an important role in the classification based on two types of FC. We also find that both have a certain proportion in the cerebellum region [ 48 , 49 ]. Previous classification models or physiological studies also have some similar conclusions that differences exist in these brain areas [ 50 – 53 ].…”

Section: Resultsmentioning

confidence: 98%

A hybrid CNN-SVM model for enhanced autism diagnosis

Qiu,

Zhai

2024

PLoS ONE

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Autism is a representative disorder of pervasive developmental disorder. It exerts influence upon an individual’s behavior and performance, potentially co-occurring with other mental illnesses. Consequently, an effective diagnostic approach proves to be invaluable in both therapeutic interventions and the timely provision of medical support. Currently, most scholars’ research primarily relies on neuroimaging techniques for auxiliary diagnosis and does not take into account the distinctive features of autism’s social impediments. In order to address this deficiency, this paper introduces a novel convolutional neural network-support vector machine model that integrates resting state functional magnetic resonance imaging data with the social responsiveness scale metrics for the diagnostic assessment of autism. We selected 821 subjects containing the social responsiveness scale measure from the publicly available Autism Brain Imaging Data Exchange dataset, including 379 subjects with autism spectrum disorder and 442 typical controls. After preprocessing of fMRI data, we compute the static and dynamic functional connectivity for each subject. Subsequently, convolutional neural networks and attention mechanisms are utilized to extracts their respective features. The extracted features, combined with the social responsiveness scale features, are then employed as novel inputs for the support vector machine to categorize autistic patients and typical controls. The proposed model identifies salient features within the static and dynamic functional connectivity, offering a possible biological foundation for clinical diagnosis. By incorporating the behavioral assessments, the model achieves a remarkable classification accuracy of 94.30%, providing a more reliable support for auxiliary diagnosis.

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Section: Resultsmentioning

confidence: 98%

A hybrid CNN-SVM model for enhanced autism diagnosis

Qiu,

Zhai

2024

PLoS ONE

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“…The neurobiological basis of the cognitive change associated with ASD are not well understood (Bauman & Kemper, 2005). Nevertheless, autistic children have reduced function parts of the brain in cortical regions, such as the superior temporal sulcus (STS) and inferior frontal gyrus (IFG) (Laidi et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

The Effect of Family-Oriented Organized Motivational Program on Working Memory in the Children with Autism Spectrum Disorder

Afshari,

Afshari

2023

Preprint

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Working memory plays an important role in learning. In this study, we are looking for motivational ways to stimulate memory. The participants (8 girls and 10 boys) were divided into experimental and control groups. They are selected from among 28 subjects after primary tests to be matched. The design of the study is semi-experimental including an independent variable, a pretest and a posttest. After considering the research hypotheses, using descriptive statistics and one-way Analysis of Covariance (ANCOVA), the results suggested a significant difference in posttest scores of experimental and control groups after independent variable being applied. The results show that a motivational program including math assignments and naming shapes assignments that it has coincided with children's motivations can has a positive effect on working memory in children with autism spectrum disorders. Due to increase in brain cognitive functions which control motivation and memory, memory experienced a high level of performance which can lead to more learning.

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Preserved navigation abilities and spatio‐temporal memory in individuals with autism spectrum disorder

Cited by 2 publications

References 54 publications

A hybrid CNN-SVM model for enhanced autism diagnosis

A hybrid CNN-SVM model for enhanced autism diagnosis

The Effect of Family-Oriented Organized Motivational Program on Working Memory in the Children with Autism Spectrum Disorder

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