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| Name | Class |
|---|---|
| Xi'an TCM Hospital of Encephalopathy | UNKNOWN |
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Research background and project basis
Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder characterized by social disorders and repetitive stereotypical behavior. Social memory impairment is a significant feature of ASD patients, and the specific pathogenesis of social memory impairment in ASD patients is currently unclear, and there are no objective indicators to measure social memory levels. Sleep spindle wave is a special brain wave in sleep that is closely related to memory consolidation. However, no one has yet studied the impact of sleep spindles on social memory.
Research purpose
Exploring the correlation between sleep spindles and social memory in the population, providing reference for the auxiliary diagnosis of social memory disorders in children with ASD.
The goal of this observational study is to exploring the correlation between sleep spindles and social memory in the population, providing reference for the auxiliary diagnosis of social memory disorders in children with autism spectrum disorders(ASD). The main question it aims to answer is the effect of sleep spindles on social memory. The study clinically recruited 30 children with ASD and 30 normal children. Participants will be asked to take face and car recognition memory tests which car recognition memory test as a control. After the two tasks, nighttime EEG recordings and subsequent spindle analysis will be recorded and performed.Then the correlation analysis between social memory levels and spindle levels would be conducted by machine learning model, so that researchers can infer the individual's social memory level through the level of spindles in the EEG.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| ASD group | Diagnosed as ASD based on DSM-V diagnostic criteria and combined with clinical manifestations. |
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| Control group | Healthy children |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| social memory levels and spindle levels | Diagnostic Test | Take a face recognition memory test, and a car recognition memory test as a control . Then record nighttime EEG recordings after the two tasks and performed subsequent spindle analysis.So conduct the correlation between social memory levels and the level of spindles in the EEG by using machine learning to model. |
| Measure | Description | Time Frame |
|---|---|---|
| Recognition accuracy | Recognition accuracy as an evaluation indicator for cars and facial recognition. The car and face recognition task included a learning phase on the first night (approximately 30 minutes before going to bed) and a recognition test phase on the second morning (approximately 30 minutes after waking up). The learning phase included 11 pictures of adult faces (319 × 432 pixel). During the learning phase, pictures were randomly presented for 3s with an inter-stimulus interval of 2s. During the test phase, two pictures were presented simultaneously, with the picture from the study list (called "old") paired with an unseen picture (called "new"), in random left-right order. Participants were asked to select a picture they had seen previously by pressing the left and right buttons. And the next stimulus was presented immediately after the participant answered. Recognition accuracy was computed as the number of correct responses (hits). | Through face & car recognition task completion, an average of 2-4 days. |
| Response delay time | Reaction time is commonly used to evaluate cognitive abilities. Mean reaction times (ms) were calculated for correct responses (hits), which is the response delay time. | Through face & car recognition task completion, an average of 2-4 days. |
| Sleep spindle density | Sleep spindle wave recognition and data processing use the YASA (Yet Another Spindle Algorithm) toolbox based on Python to stage EEG sleep automatic recognition of sleep spindle waves. Calculate the density (N/min) of sleep spindles. | Through the 12 hour EEG recording completion, an average of 5-12 days. |
| Sleep spindle average duration | Calculate the average duration (s) of single spindle. | Through the 12 hour EEG recording completion, an average of 5-12 days. |
| Sleep spindle amplitude |
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Inclusion Criteria:
Exclusion Criteria:
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It is expected to recruit 60 participants aged 6-18, of which 30 in the case group are all inpatient and outpatient cases from Xi'an Traditional Chinese Medicine Brain Disease Hospital, and are designated as ASD according to unified diagnostic standards; The healthy control group consists of 30 individuals from nearby community kindergartens and primary schools at Xi'an Traditional Chinese Medicine Brain Disease Hospital, who have not suffered from ASD or other diseases related to ASD research factors.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Dongqi Cui, PhD | Contact | 18501059233 | 18501059233@163.com | |
| Xiaodan Wang, PhD | Contact | 13720418610 | m19834513386@163.com |
| Name | Affiliation | Role |
|---|---|---|
| Yan Li, PhD | First Afflicated Hospital of Xian Jiaotong University | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| First Afflicated Hospital Xian Jiaotong University | Recruiting | Xi'an | Shaanxi | 710061 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 33294809 | Background | Lai M, Lee J, Chiu S, Charm J, So WY, Yuen FP, Kwok C, Tsoi J, Lin Y, Zee B. A machine learning approach for retinal images analysis as an objective screening method for children with autism spectrum disorder. EClinicalMedicine. 2020 Nov 5;28:100588. doi: 10.1016/j.eclinm.2020.100588. eCollection 2020 Nov. | |
| 33501147 | Background |
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| ID | Term |
|---|---|
| D000067877 | Autism Spectrum Disorder |
| D004194 | Disease |
| ID | Term |
|---|---|
| D002659 | Child Development Disorders, Pervasive |
| D065886 | Neurodevelopmental Disorders |
| D001523 | Mental Disorders |
| D010335 | Pathologic Processes |
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The observational study does not involve biological sample collection, only collects and analyzes participants' memory test data and EEG recording data.
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Amplitude (μV) refers to the maximum energy value possessed by the spindle wave. |
| Through the 12 hour EEG recording completion, an average of 5-12 days. |
| Sleep spindle frequency | Frequency (Hz) refers to the number of times the spindle wave vibrates repeatedly per second. | Through the 12 hour EEG recording completion, an average of 5-12 days. |
| Georgescu AL, Koehler JC, Weiske J, Vogeley K, Koutsouleris N, Falter-Wagner C. Machine Learning to Study Social Interaction Difficulties in ASD. Front Robot AI. 2019 Nov 29;6:132. doi: 10.3389/frobt.2019.00132. eCollection 2019. |
| 36574922 | Background | Das S, Zomorrodi R, Mirjalili M, Kirkovski M, Blumberger DM, Rajji TK, Desarkar P. Machine learning approaches for electroencephalography and magnetoencephalography analyses in autism spectrum disorder: A systematic review. Prog Neuropsychopharmacol Biol Psychiatry. 2023 Apr 20;123:110705. doi: 10.1016/j.pnpbp.2022.110705. Epub 2022 Dec 24. |
| D013568 | Pathological Conditions, Signs and Symptoms |