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Item Combining functional near-infrared spectroscopy and EEG measurements for the diagnosis of attention-deficit hyperactivity disorder(2020) Guven, Aysegul; Altinkaynak, Miray; Dolu, Nazan; Izzetoglu, Meltem; Pektas, Ferhat; Ozmen, Sevgi; Demirci, Esra; Batbat, Turgay; 0000-0002-3104-7587; AAG-4494-2019Recently multimodal neuroimaging which combines signals from different brain modalities has started to be considered as a potential to improve the accuracy of diagnosis. The current study aimed to explore a new method for discriminating attention-deficit hyperactivity disorder (ADHD) patients and control group by means of simultaneous measurement of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Twenty-three pre-medicated combined type ADHD children and 21 healthy children were included in the study. Nonlinear brain dynamics of subjects were obtained from EEG signal using Higuchi fractal dimensions and Lempel-Ziv complexity, latency and amplitude values of P3 wave obtained from auditory evoked potentials and frontal cortex hemodynamic responses calculated from fNIRS. Lower complexity values, prolonged P3 latency and reduced P3 amplitude values were found in ADHD children. fNIRS indicated that the control subjects exhibited higher right prefrontal activation than ADHD children. Features are analyzed, looking for the best classification accuracy and finally machine learning techniques, namely Support Vector Machines, Naive Bayes and Multilayer Perception Neural Network, are introduced for EEG signals alone and for combination of fNIRS and EEG signals. Naive Bayes provided the best classification with an accuracy rate of 79.54% and 93.18%, using EEG and EEG-fNIRS systems, respectively. Our findings demonstrate that utilization of information by combining features obtained from fNIRS and EEG improves the classification accuracy. As a conclusion, our method has indicated that EEG-fNIRS multimodal neuroimaging is a promising method for ADHD objective diagnosis.Item Prefrontal Brain Activation in Subtypes of Attention Deficit Hyperactivity Disorder: A Functional Near-Infrared Spectroscopy Study(2018) Dolu, Nazan; Altinkaynak, Miray; Guven, Aysegul; Izzetoglu, Meltem; Demirci, Esra; Ozmen, Sevgi; Pektas, Ferhat; 0000-0002-3104-7587; AAG-4494-2019According to clinical symptoms, attention deficit and hyperactivity disorder (ADHD) is categorized into three groups: the predominantly inattentive subtype (ADHD-I),the predominantly hyperactive-impulsive subtype (ADHD-HI), and the combined subtype (ADHD-C). Recent advances in neuroimaging have demonstrated new approaches for assessing the ADHD subtypes with underlying pathophysiology.This study aims to examine the hemodynamic response and reaction time (RT) in healthy children and the ADHD subtypes as measured by functional near-infrared spectroscopy (fNIRS) during an auditory oddball attention task. The sample was made up of 40 children divided into four groups: control group (n=14), ADHD-I group (n=9), ADHD-HI group (n=6), and ADHD-C group (n=11). The target responses were identified and were grand-averaged for each participant. Right prefrontal cortex hemodynamic responses and groups performances on RT were compared between subtypes and between controls and subtypes. Functional near-infrared spectroscopy indicated that while control subjects exhibited higher activation than all ADHD subtypes, the ADHD subtypes did not differ from one another. Relative to control subjects, a longer RT was observed in all ADHD subtypes. The ADHD-I group showed significantly longer RTs compared to the ADHD-HI and ADHD-C groups.This study can bring a new perspective to the continuing controversy about ADHD subtypes, and the findings may help in the evaluation of fNIRS, RT, and RT variability studies in ADHD.