Objective To explore the prefrontal cortex (PFC) activation levels in children with attention deficit hyperactivity disorder (ADHD) during task states using functional near-infrared spectroscopy (fNIRS), and to evaluate the diagnostic value of combining PFC activation with behavioral assessments for distinguishing ADHD, so as to provide a basis for early diagnosis. Methods A total of 40 children diagnosed with ADHD and 30 healthy children undergoing routine health check-ups atthe Children's Health Department of Xi'an People's Hospital (Xi'an Fourth Hospital) from July 2023 to July 2024 were recruited. A 22-channel fNIRS device was used to measure changes in oxygenated hemoglobin (HbO2) concentration in the PFC during a verbal fluency task (VFT). The Conners Parent Symptom Questionnaire (PSQ) was administered, and correlations between PSQ scores and PFC HbO2 levels were analyzed. Receiver operating characteristic (ROC) curve analysis was performed to assess the sensitivity and specificity of combining HbO2 levels with PSQ scores for ADHD diagnosis. Results Compared to healthy children, ADHD children exhibited significantly lower HbO2 levels in the right dorsolateral prefrontal cortex (rDLPFC), left dorsolateral prefrontal cortex (lDLPFC), right frontopolar cortex (rFPC), medial prefrontal cortex (mFPC), and Brodmann area 8 (BA8) (Z＝4.115, 2.363, 3.591, 2.578, 2.936, P<0.05). ADHD children also scored higher on the PSQ subscales for conduct problems, learning problems, impulsivity-hyperactivity, and hyperactivity index (Z＝3.827, 4.065, 5.531, 4.827, P<0.05). Negative correlations were observed between learning problems and HbO2 levels in the rDLPFC, rFPC, and mFPC (r＝-0.336,-0.412,-0.310, P<0.05), between impulsivity-hyperactivity and HbO2 levels in the mFPC (r＝-0.382, P<0.05), and between the hyperactivity index and HbO2 levels in the rDLPFC, rFPC, mFPC, and BA8 (r＝-0.393,-0.445,-0.431,-0.339, P<0.05). The area under the ROC curve (AUC) for the combined prediction of ADHD using HbO2 levels in the rDLPFC, lDLPFC, rFPC, lFPC, mFPC, and BA8 along with the hyperactivity index was 0.884, 0.877, 0.883, 0.900, 0.896, and 0.884, respectively, all of which were higher than the AUCs for HbO2 levels or the hyperactivity index alone. Conclusion Children with ADHD exhibit impaired PFC function, and the combination of PFC HbO2 levels and PSQ scores demonstrates significant diagnostic value for ADHD.
Key words
attention-deficit hyperactivity disorder /
near-infrared spectroscopic imaging /
prefrontal cortex /
oxygenated haemoglobin /
behavioral assessment
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References
[1] Posner J, Polanczyk GV, Sonuga-Barke E. Attention-deficit hyperactivity disorder[J]. Lancet, 2020, 395(10222): 450-462.
[2] Haber SN, Robbins T. The prefrontal cortex[J]. Neuropsychopharmacol, 2022, 47(1): 1-2.
[3] Rubia K, Westwood S, Aggensteiner PM, et al. Neurotherapeutics for attention deficit/hyperactivity disorder (ADHD): A review[J]. Cells, 2021, 10(8): 2156.
[4] Carey C. DSM- 5® Guidebook: The essential companion to the diagnostic and statistical manual of mental disorders[J]. Ir J Psychol Med, 2016, 33(2):133 - 134.
[5] Yeung MK. An optical window into brain function in children and adolescents: A systematic review of functional near-infrared spectroscopy studies[J]. NeuroImage, 2021, 227: 117672.
[6] Pereira-Sanchez V, Castellanos FX. Neuroimaging in attention-deficit/hyperactivity disorder[J]. Curr Opin Psychiatry, 2021, 34(2): 105-111.
[7] Gu Y, Miao S, Han J, et al. Complexity analysis of fNIRS signals in ADHD children during working memory task[J]. Sci Rep, 2017, 7(1): 829.
[8] Kruppa JA, Reindl V, Gerloff C, et al. Brain and motor synchrony in children and adolescents with ASD-a fNIRS hyperscanning study[J]. Soc Cogn Affect Neurosci, 2021, 16(1-2): 103-116.
[9] 范娟,杜亚松,王立伟.Conners父母用症状问卷的中国城市常模和信度研究[J].上海精神医学,2005,17(6): 321-323.
Fan J, Du YS, Wang LW. The norm and reliability of the Conners Parent Symptom Questionnaire in Chinese urban children[J]. Shanghai Arch Psychiatry, 2005,17(6): 321-323. (in Chinese)
[10] Hou X, Zhang Z, Zhao C, et al. NIRS-KIT: A MATLAB toolbox for both resting-state and task fNIRS data analysis[J]. Neurophotonics, 2021, 8(1):010802.
[11] Kocsis L, Herman P, Eke A. The modified Beer-Lambert law revisited[J]. Phys Med Biol, 2006, 51(5): N91-98.
[12] Eggebrecht AT, White BR, Ferradal SL, et al. A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping[J]. NeuroImage, 2012, 61(4): 1120-1128.
[13] Zhang H, Xu L, Yu J, et al. Identification of autism spectrum disorder based on functional near-infrared spectroscopy using adaptive spatiotemporal graph convolution network[J]. Front Neurosci, 2023, 17: 1132231.
[14] Wu T, Liu X, Cheng F, et al. Dorsolateral prefrontal cortex dysfunction caused by a go/no-go task in children with attention-deficit hyperactivity disorder: A functional near-infrared spectroscopy study[J]. Front Neurosci, 2023,17: 1145485.
[15] Miao S, Han J, Gu Y, et al. Reduced prefrontal cortex activation in children with attention-deficit/hyperactivity disorder during go/no-go task: A functional near-infrared spectroscopy study[J]. Front Neurosci, 2017, 11: 367.
[16] Wagner S, Sebastian A, Lieb K, et al. A coordinate-based ALE functional MRI meta-analysis of brain activation during verbal fluency tasks in healthy control subjects[J]. BMC Neurosci, 2014, 15: 19.
[17] Li Y, Ma S, Zhang X, et al. ASD and ADHD: Divergent activating patterns of prefrontal cortex in executive function tasks?[J]. J Psychiatr Res, 2024, 172: 187-196.
[18] Sripada CS, Kessler D, Angstadt M. Lag in maturation of the brain's intrinsic functional architecture in attention-deficit/hyperactivity disorder[J]. Proc Natl Acad Sci USA, 2014, 111(39):14259-14264.
[19] Dadario NB, Tanglay O, Sughrue ME. Deconvoluting human Brodmann area 8 based on its unique structural and functional connectivity[J]. Front Neuroanat, 2023, 17: 1127143.
[20] Wu J, Xiao H, Sun H, et al. Role of Dopamine receptors in ADHD: A systematic Meta-analysis[J]. Mol Neurobiol, 2012, 45(3): 605-620.
[21] Wu ZM, Llera A, Hoogman M, et al. Linked anatomical and functional brain alterations in children with attention-deficit/hyperactivity disorder[J]. NeuroImage Clin, 2019, 23: 101851.
[22] Chiang HL, Wu CS, Chen CL, et al. Machine-learning-based feature selection to identify attention-deficit hyperactivity disorder using whole-brain white matter microstructure: A longitudinal study[J]. Asian J Psychiatry, 2024, 97: 104087.
[23] Chen Y, Huang X, Wu M, et al. Disrupted brain functional networks in drug-naïve children with attention deficit hyperactivity disorder assessed using graph theory analysis[J]. Hum Brain Mapp, 2019, 40(17): 4877-4887.
[24] Høberg A, Solberg BS, Hegvik TA, et al. Using polygenic scores in combination with Symptom Rating Scales to identify attention-deficit/hyperactivity disorder[J]. BMC Psychiatry, 2024, 24(1): 471.
[25] Hong SB. Thalamocortical functional connectivity in youth with attention-deficit/hyperactivity disorder[J].J Psychiatry Neurosci, 2023, 48(1): E50-E60.
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