Comparative Effects of BCI-Based Attention Training, Methylphenidate, and Citicoline on Attention and Executive Function in School-Age Children: A Quasi-Experimental Study
Abstract
1. Introduction
2. Materials and Methods
2.1. Participants
2.2. Intervention Procedures
2.3. Pharmacological Interventions
- Methylphenidate (Mph): Administered in clinically appropriate doses based on pediatric guidelines and clinical judgment.
- Citicoline: Delivered in standardized age-appropriate dosing as an adjunctive neurocognitive enhancer.
2.4. Other Medications and Confounding Factors
2.5. Outcome Measures
2.6. Statistical Analysis
3. Results
3.1. Participant Characteristics
3.2. Primary Outcomes
3.3. Secondary Outcomes
3.4. Graphical Representation
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- da Silva, B.S.; Grevet, E.H.; Silva, L.C.F.; Ramos, J.K.N.; Rovaris, D.L.; Bau, C.H.D. An overview on neurobiology and therapeutics of attention-deficit/hyperactivity disorder. Discov. Ment. Health 2023, 3, 2. [Google Scholar] [CrossRef]
- Hwang, S.; Meffert, H.; Parsley, I.; Tyler, P.M.; Erway, A.K.; Botkin, M.L.; Pope, K.; Blair, R.J.R. Segregating sustained attention from response inhibition in ADHD: An fMRI study. NeuroImage Clin. 2019, 21, 101677. [Google Scholar] [CrossRef]
- Noah, A.A.; Sedky, H.E. New frontiers in pharmacological treatment of attention-deficit hyperactivity disorder. Naunyn-Schmiedeberg’s Arch. Pharmacol. 2025, 398, 15025–15035. [Google Scholar] [CrossRef]
- Fredriksen, M.; Halmøy, A.; Faraone, S.V.; Haavik, J. Long-term efficacy and safety of treatment with stimulants and atomoxetine in adult ADHD: A review of controlled and naturalistic studies. Eur. Neuropsychopharmacol. J. Eur. Coll. Neuropsychopharmacol. 2013, 23, 508–527. [Google Scholar] [CrossRef]
- Tuncturk, M.; Ermis, C.; Buyuktaskin, D.; Halac, E.; Sut, E.; Ozkan, O.; Gundogan, N.; Unutmaz, G.; Ciray, R.O.; Turan, S.; et al. Investigating the effects of age, IQ, dosing, and anthropometric measures on the treatment persistence in long-term methylphenidate use. Nord. J. Psychiatry 2023, 77, 345–351. [Google Scholar] [CrossRef]
- Levy, F.; Pipingas, A.; Harris, E.V.; Farrow, M.; Silberstein, R.B. Continuous performance task in ADHD: Is reaction time variability a key measure? Neuropsychiatr. Dis. Treat. 2018, 14, 781–786. [Google Scholar] [CrossRef]
- Reza-Zaldívar, E.E.; Jacobo-Velázquez, D.A. Comprehensive Review of Nutraceuticals against Cognitive Decline Associated with Alzheimer’s Disease. ACS Omega 2023, 8, 35499–35522. [Google Scholar] [CrossRef] [PubMed]
- Kansakar, U.; Trimarco, V.; Mone, P.; Varzideh, F.; Lombardi, A.; Santulli, G. Choline supplements: An update. Front. Endocrinol. 2023, 14, 1148166. [Google Scholar] [CrossRef]
- Hübner, I.B.; Scheibe, D.B.; Marchezan, J.; Bücker, J. Use of Citicoline in Attention-Deficit/Hyperactivity Disorder: A Pilot Study. Clin. Neuropharmacol. 2024, 47, 146–149. [Google Scholar] [CrossRef] [PubMed]
- Ölçüoğlu, R. Neurofeedback for ADHD: Exploring the Role of Quantitative EEG and Brainwave Modulation. Brain Behav. 2025, 15, e70714. [Google Scholar] [CrossRef] [PubMed]
- Jeunet, C.; Glize, B.; McGonigal, A.; Batail, J.M.; Micoulaud-Franchi, J.A. Using EEG-based brain computer interface and neurofeedback targeting sensorimotor rhythms to improve motor skills: Theoretical background, applications and prospects. Neurophysiol. Clin. 2019, 49, 125–136. [Google Scholar] [CrossRef]
- Yan, L.; Zhang, J.; Yuan, Y.; Cortese, S. Effects of neurofeedback versus methylphenidate for the treatment of attention-deficit/hyperactivity disorder protocol for a systematic review and meta-analysis of head-to-head trials. Medicine 2018, 97, e12623. [Google Scholar] [CrossRef] [PubMed]
- Van Doren, J.; Arns, M.; Heinrich, H.; Vollebregt, M.A.; Strehl, U.; Loo, S.K. Sustained effects of neurofeedback in ADHD: A systematic review and meta-analysis. Eur. Child Adolesc. Psychiatry 2019, 28, 293–305. [Google Scholar] [CrossRef]
- Liu, X.Y.; Wang, W.L.; Liu, M.; Chen, M.Y.; Pereira, T.; Doda, D.Y.; Ke, Y.F.; Wang, S.Y.; Wen, D.; Tong, X.G.; et al. Recent applications of EEG-based brain-computer-interface in the medical field. Mil. Med. Res. 2025, 12, 14. [Google Scholar] [CrossRef]
- Lim, C.G.; Lee, T.S.; Guan, C.; Fung, D.S.; Zhao, Y.; Teng, S.S.; Zhang, H.; Krishnan, K.R. A brain-computer interface based attention training program for treating attention deficit hyperactivity disorder. PLoS ONE 2012, 7, e46692. [Google Scholar] [CrossRef] [PubMed]
- Hai, T.; Duffy, H.A.; Lemay, J.A.; Lemay, J.F. Impact of stimulant medication on behaviour and executive functions in children with attention-deficit/hyperactivity disorder. World J. Clin. Pediatr. 2022, 11, 48–60. [Google Scholar] [CrossRef] [PubMed]
- Raza, M.Z.; Omais, M.; Arshad, H.M.E.; Maqsood, M.; Nadeem, A.A. Effectiveness of brain computer interface (BCI) based attention training game system for symptom reduction, behavioral enhancement, and brain function modulation in children with ADHD: A systematic review and single-arm meta-analysis. NeuroRegulation 2025, 12, 51–78. [Google Scholar] [CrossRef]
- Oh, H.K.; Cho, Y.J.; Kim, J.J.; Shin, B.; Kim, S.J.; Park, S.; Seok, J.H.; Kim, S.; Kim, E. Advancing ecological validity and clinical utility in virtual reality-based continuous performance test: Exploring the effects of task difficulty and environmental distractors. Front. Psychiatry 2024, 14, 1329221. [Google Scholar] [CrossRef]
- Zeng, X.W.; Hu, L.F.; Cao, X.L.; Yang, B.R.; Wu, Z.M. Fluctuating course of attention-deficit/hyperactivity disorder across development: Multifactorial influences. World J. Psychiatry 2025, 15, 107780. [Google Scholar] [CrossRef]
- Martín-Rodríguez, A.; Herrero-Roldán, S.; Clemente-Suárez, V.J. The Role of Physical Activity in ADHD Management: Diagnostic, Digital and Non-Digital Interventions, and Lifespan Considerations. Children 2025, 12, 338. [Google Scholar] [CrossRef]
- Mizuno, Y.; Cai, W.; Supekar, K.; Makita, K.; Takiguchi, S.; Silk, T.J.; Tomoda, A.; Menon, V. Methylphenidate Enhances Spontaneous Fluctuations in Reward and Cognitive Control Networks in Children with Attention-Deficit/Hyperactivity Disorder. Biological psychiatry. Cogn. Neurosci. Neuroimaging 2023, 8, 271–280. [Google Scholar] [CrossRef]
- Wu, F.; Zhang, W.; Ji, W.; Zhang, Y.; Jiang, F.; Li, G.; Hu, Y.; Wei, X.; Wang, H.; Wang, S.A.; et al. Stimulant medications in children with ADHD normalize the structure of brain regions associated with attention and reward. Neuropsychopharmacol. Off. Publ. Am. Coll. Neuropsychopharmacol. 2024, 49, 1330–1340. [Google Scholar] [CrossRef]
- Gruber, S.A.; Sagar, K.A.; Dahlgren, M.K.; Gonenç, A.; Conn, N.A.; Winer, J.P.; Penetar, D.; Lukas, S.E. Citicoline Treatment Improves Measures of Impulsivity and Task Performance in Chronic Marijuana Smokers: A Pilot BOLD fMRI Study. Int. J. Neurol. Neurother. 2015, 2, 1–8. [Google Scholar] [CrossRef]
- Derbyshire, E.; Obeid, R. Choline, Neurological Development and Brain Function: A Systematic Review Focusing on the First 1000 Days. Nutrients 2020, 12, 1731. [Google Scholar] [CrossRef]
- Picciotto, M.R.; Lewis, A.S.; van Schalkwyk, G.I.; Mineur, Y.S. Mood and anxiety regulation by nicotinic acetylcholine receptors: A potential pathway to modulate aggression and related behavioral states. Neuropharmacology 2015, 96, 235–243. [Google Scholar] [CrossRef] [PubMed]
- Yeh, W.H.; Ju, Y.J.; Liu, Y.T.; Wang, T.Y. Systematic Review and Meta-Analysis on the Effects of Neurofeedback Training of Theta Activity on Working Memory and Episodic Memory in Healthy Population. Int. J. Environ. Res. Public Health 2022, 19, 11037. [Google Scholar] [CrossRef]
- Esteves, I.; Nan, W.; Alves, C.; Calapez, A.; Melício, F.; Rosa, A. An Exploratory Study of Training Intensity in EEG Neurofeedback. Neural Plast. 2021, 2021, 8881059. [Google Scholar] [CrossRef] [PubMed]
- Gareri, P.; Castagna, A.; Cotroneo, A.M.; Putignano, S.; De Sarro, G.; Bruni, A.C. The role of citicoline in cognitive impairment: Pharmacological characteristics, possible advantages, and doubts for an old drug with new perspectives. Clin. Interv. Aging 2015, 10, 1421–1429. [Google Scholar] [CrossRef]
- Diarra, M.; Theurel, J.; Paty, B. Systematic review of neurophysiological assessment techniques and metrics for mental workload evaluation in real-world settings. Front. Neuroergon. 2025, 6, 1584736. [Google Scholar] [CrossRef]
- Shi, X.; Ji, Y.; Cai, S.; Wu, Y.; Zhang, L.; Shen, L.; Jiang, Z.; Chen, Y. Comorbidities and functional impairments in children with attention deficit hyperactivity disorder in China: A hospital-based retrospective cross-sectional study. BMJ Open 2021, 11, e042196. [Google Scholar] [CrossRef]
- Moggia, D.; Lutz, W.; Brakemeier, E.L.; Bickman, L. Treatment Personalization and Precision Mental Health Care: Where are we and where do we want to go? Adm. Policy Ment. Health 2024, 51, 611–616. [Google Scholar] [CrossRef] [PubMed]


| Variables | COGO + Mph | n | COGO + Citicoline | n | COGO | n | Citicoline | n | X2/F | p |
|---|---|---|---|---|---|---|---|---|---|---|
| Age | 9.7 ± 2.4 | 44 | 10.4 ± 2.5 | 44 | 11.3 ± 2.8 | 44 | 11.3 ± 3.1 | 42 | 3.3 | 0.023 a |
| Gender, n (%) | 44 | 44 | 44 | 42 | 0.2 | 0.971 | ||||
| Female | 15 (34.1) | 14 (31.8) | 16 (36.4) | 15 (35.7) | ||||||
| Male | 29 (65.9) | 30 (68.2) | 28 (63.6) | 27 (64.3) | ||||||
| Grade | 4.4 ± 2.6 | 38 | 4.8 ± 2.7 | 39 | 6.1 ± 3.1 | 40 | 6.2 ± 3.3 | 33 | 3.5 | 0.018 a |
| RCADS b | 30.8 ± 19.6 | 38 | 24.4 ± 12.9 | 39 | 32.7 ± 16.8 | 40 | 32.2 ± 17.4 | 33 | 2.4 | 0.075 |
| SNAP-IV b | ||||||||||
| Inattention | 14.8 ± 5.3 | 38 | 13.6 ± 5.2 | 39 | 14.7 ± 4.6 | 40 | 13.3 ± 5.9 | 33 | 0.8 | 0.485 |
| Hyperactivity | 12.4 ± 5.1 | 38 | 12.3 ± 6.2 | 39 | 12.5 ± 6.0 | 40 | 11.8 ± 6.4 | 33 | 0.2 | 0.914 |
| SCT Scale b | 21.4 ± 6.7 | 38 | 18.5 ± 5.4 | 39 | 22.1 ± 8.3 | 40 | 19.7 ± 6.4 | 33 | 2.3 | 0.076 |
| SDQ b | ||||||||||
| Emotional | 3.7 ± 2.9 | 38 | 3.2 ± 2.3 | 39 | 4.1 ± 2.6 | 40 | 3.9 ± 2.4 | 33 | 1.2 | 0.311 |
| Conduct | 2.4 ± 1.8 | 38 | 3.1 ± 2.0 | 39 | 3.4 ± 2.1 | 40 | 2.3 ± 1.5 | 33 | 2.8 | 0.043 |
| Hyperactivity | 6.2 ± 2.0 | 38 | 5.7 ± 2.5 | 39 | 6.0 ± 2.0 | 40 | 6.0 ± 2.4 | 33 | 0.3 | 0.849 |
| Peer Problems | 3.8 ± 2.2 | 38 | 2.8 ± 1.9 | 39 | 3.3 ± 2.1 | 40 | 3.2 ± 2.2 | 33 | 1.1 | 0.346 |
| Prosocial Behavior | 8.3 ± 1.6 a | 38 | 7.2 ± 1.9 b | 39 | 7.1 ± 1.8 b | 40 | 7.2 ± 2.1b | 33 | 4.4 | 0.005 |
| Total Difficulty | 16.1 ± 6.3 | 38 | 14.8 ± 5.7 | 39 | 16.8 ± 6.0 | 40 | 15.3 ± 5.7 | 33 | 0.8 | 0.475 |
| BRIEF b | ||||||||||
| Inhibition | 28.8 ± 5.6 | 38 | 28.7 ± 7.4 | 39 | 29.6 ± 6.8 | 40 | 29.4 ± 6.3 | 33 | 0.1 | 0.960 |
| Shifting | 21.9 ± 4.1 | 38 | 22.0 ± 4.7 | 39 | 22.7 ± 4.2 | 40 | 22.8 ± 5.0 | 33 | 0.7 | 0.551 |
| Emotional | 20.1 ± 4.9 | 38 | 20.0 ± 5.2 | 39 | 21.8 ± 5.1 | 40 | 19.6 ± 4.6 | 33 | 1.4 | 0.244 |
| Initiation | 17.1 ± 3.9 | 38 | 16.9 ± 3.6 | 39 | 17.8 ± 2.8 | 40 | 16.6 ± 3.4 | 33 | 0.7 | 0.526 |
| Working Memory | 23.7 ± 4.6 | 38 | 23.3 ± 4.6 | 39 | 24.1 ± 4.2 | 40 | 23.6 ± 4.8 | 33 | 0.2 | 0.908 |
| Planning | 33.1 ± 1.3 | 38 | 32.0 ± 6.6 | 39 | 33.4 ± 6.2 | 40 | 32.2 ± 7.1 | 33 | 0.4 | 0.749 |
| Organization | 16.7 ± 4.8 | 38 | 17.3 ± 4.6 | 39 | 18.1 ± 3.9 | 40 | 16.4 ± 4.3 | 33 | 1.0 | 0.414 |
| Monitoring | 18.4 ± 3.3 | 38 | 17.5 ± 3.4 | 39 | 18.7 ± 2.8 | 40 | 18.0 ± 3.9 | 33 | 0.9 | 0.463 |
| Behavioral Regulation | 70.8 ± 12.5 | 38 | 70.8 ± 17.4 | 39 | 74.1 ± 13.6 | 40 | 71.8 ± 15.9 | 33 | 0.5 | 0.661 |
| Metacognition Index | 109.2 ±20.3 | 38 | 106.9± 20.2 | 39 | 112.0 ± 16.2 | 40 | 106.7 ± 20.6 | 33 | 0.6 | 0.626 |
| Global Executive | 180.0 ± 28.9 | 38 | 177.7 ± 32.6 | 39 | 186.1 ± 25.3 | 40 | 178.5 ± 34.2 | 33 | 0.6 | 0.643 |
| Intervention | CPT-3 (T Score) | Mean ± SD | Std. Error Mean | t | p | Cohen’s d |
|---|---|---|---|---|---|---|
| COGO + Mph | ||||||
| Omissions | 9.91 ± 20.22 | 4.31 | 2.3 | 0.032 | 0.49 | |
| Commissions | 3.86 ± 10.4 | 2.22 | 1.74 | 0.096 | 0.37 | |
| Perseverations | 1.68 ± 16.8 | 3.58 | 0.47 | 0.641 | 0.1 | |
| HRT | 4.68 ± 8.6 | 1.83 | 2.55 | 0.643 | 0.54 | |
| HRT SD | 6.85 ± 20.5 | 4.37 | 1.59 | 0.126 | 0.34 | |
| Variability | 0.91 ± 18.1 | 3.85 | 0.24 | 0.816 | 0.05 | |
| HRT ISI Change | 11.41 ± 16.5 | 3.52 | 3.24 | 0.004 | 0.69 | |
| COGO + Citicoline | ||||||
| Omissions | 4.86 ± 17.5 | 3.72 | 1.31 | 0.205 | 0.28 | |
| Commissions | 3.68 ± 6.7 | 1.42 | 2.59 | 0.017 | 0.55 | |
| Perseverations | 5.59 ± 13.4 | 2.93 | 1.91 | 0.07 | 0.41 | |
| HRT | −2.41 ± 7.3 | 1.56 | −1.54 | 0.138 | −0.33 | |
| HRT SD | 2.0 ± 10.8 | 2.3 | 0.87 | 0.394 | 0.19 | |
| Variability | 1.64 ± 14.9 | 3.17 | 0.52 | 0.661 | 0.11 | |
| HRT ISI Change | 0.0 ± 12.0 | 2.56 | 0.0 | 1.0 | 0.0 | |
| COGO | ||||||
| Omissions | 4.46 ± 10.6 | 2.25 | 1.2 | 0.61 | 0.42 | |
| Commissions | −1.45 ± 7.3 | 1.55 | −0.93 | 0.36 | −0.20 | |
| Perseverations | −0.09 ± 16.1 | 3.44 | −0.26 | 0.979 | −0.006 | |
| HRT | 1.18 ± 8.15 | 1.74 | 1.05 | 0.307 | 0.22 | |
| HRT SD | 1.18 ± 11.04 | 2.4 | 0.50 | 0.621 | 0.11 | |
| Variability | −2.05 ± 14.2 | 3.03 | −0.67 | 0.507 | −0.14 | |
| HRT ISI Change | 1.68 ± 13.2 | 2.82 | 0.6 | 0.557 | 0.13 | |
| Citicoline | ||||||
| Omissions | 4.71 ± 14.03 | 3.1 | 1.54 | 0.139 | 0.34 | |
| Commissions | 0.33 ± 8.5 | 1.85 | 0.18 | 0.859 | 0.04 | |
| Perseverations | 4.95 ± 14.8 | 3.32 | 1.53 | 0.142 | 0.33 | |
| HRT | 0.24 ± 6.77 | 1.5 | 0.16 | 0.874 | 0.35 | |
| HRT SD | 2.95 ± 11.4 | 2.49 | 1.18 | 0.25 | 0.26 | |
| Variability | 2.81 ± 9.7 | 2.11 | 1.33 | 0.198 | 0.29 | |
| HRT ISI Change | 3.3 ± 14.2 | 3.1 | 1.1 | 0.301 | 0.23 |
| Variable | Sum of Squares | df | Mean Square | F | p | Partial η2 |
|---|---|---|---|---|---|---|
| Omission | 164.31 | 3 | 54.77 | 0.31 | 0.816 | 0.01 |
| Commission | 122.48 | 3 | 40.83 | 0.48 | 0.694 | 0.02 |
| Perseveration | 830.68 | 3 | 276.89 | 1.78 | 0.158 | 0.06 |
| HRT | 68.12 | 3 | 22.71 | 0.21 | 0.891 | 0.01 |
| HRT SD | 463.29 | 3 | 154.43 | 0.86 | 0.464 | 0.03 |
| Variability | 694.28 | 3 | 231.43 | 1.55 | 0.209 | 0.05 |
| HRT Block Change | 444.70 | 3 | 148.23 | 1.25 | 0.297 | 0.04 |
| HRT ISI Change | 353.73 | 3 | 117.91 | 0.88 | 0.456 | 0.03 |
| Variable | Sum of Squares | df | Mean Square | F | p | Partial η2 |
|---|---|---|---|---|---|---|
| SNAP-IV | ||||||
| Attention Subscale | 5.60 | 3 | 1.87 | 0.2 | 0.926 | 0.01 |
| Hyperactivity Subscale | 15.32 | 3 | 5.11 | 0.4 | 0.788 | 0.02 |
| SCT-Scale | 59.86 | 3 | 19.95 | 0.7 | 0.574 | 0.02 |
| RCADS | 888.78 | 3 | 296.26 | 1.8 | 0.145 | 0.06 |
| SDQ | ||||||
| Emotional | 11.23 | 3 | 3.74 | 1.4 | 0.244 | 0.05 |
| Conduct | 2.84 | 3 | 0.95 | 0.5 | 0.659 | 0.02 |
| Hyperactivity | 8.37 | 3 | 2.79 | 1.2 | 0.327 | 0.04 |
| Peer Problems | 2.13 | 3 | 0.71 | 0.4 | 0.774 | 0.01 |
| Prosocial Behavior | 1.85 | 3 | 0.61 | 0.3 | 0.790 | 0.01 |
| Total Difficulty | 7.93 | 3 | 2.64 | 0.2 | 0.928 | 0.01 |
| BRIEF | ||||||
| Inhibition | 119.81 | 3 | 39.94 | 1.9 | 0.137 | 0.06 |
| Shifting | 23.00 | 3 | 7.67 | 0.5 | 0.671 | 0.02 |
| Emotional | 31.82 | 3 | 10.61 | 0.9 | 0.452 | 0.03 |
| Initiation | 29.96 | 3 | 9.99 | 1.9 | 0.131 | 0.07 |
| Working Memory | 26.81 | 3 | 8.94 | 0.8 | 0.476 | 0.03 |
| Planning | 69.49 | 3 | 23.16 | 1.2 | 0.310 | 0.04 |
| Organization of Materials | 14.46 | 3 | 4.82 | 0.7 | 0.579 | 0.02 |
| Monitoring | 37.97 | 3 | 12.66 | 1.7 | 0.184 | 0.06 |
| Behavioral Regulation Index | 331.03 | 3 | 110.34 | 1.0 | 0.376 | 0.04 |
| Metacognition Index | 646.92 | 3 | 215.64 | 1.3 | 0.294 | 0.04 |
| Global Executive Composite | 1626.74 | 3 | 542.25 | 1.1 | 0.350 | 0.04 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2026 by the authors. Published by MDPI on behalf of the Lithuanian University of Health Sciences. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Share and Cite
Turan, S.; Çıray, R.O. Comparative Effects of BCI-Based Attention Training, Methylphenidate, and Citicoline on Attention and Executive Function in School-Age Children: A Quasi-Experimental Study. Medicina 2026, 62, 448. https://doi.org/10.3390/medicina62030448
Turan S, Çıray RO. Comparative Effects of BCI-Based Attention Training, Methylphenidate, and Citicoline on Attention and Executive Function in School-Age Children: A Quasi-Experimental Study. Medicina. 2026; 62(3):448. https://doi.org/10.3390/medicina62030448
Chicago/Turabian StyleTuran, Serkan, and Remzi Oğulcan Çıray. 2026. "Comparative Effects of BCI-Based Attention Training, Methylphenidate, and Citicoline on Attention and Executive Function in School-Age Children: A Quasi-Experimental Study" Medicina 62, no. 3: 448. https://doi.org/10.3390/medicina62030448
APA StyleTuran, S., & Çıray, R. O. (2026). Comparative Effects of BCI-Based Attention Training, Methylphenidate, and Citicoline on Attention and Executive Function in School-Age Children: A Quasi-Experimental Study. Medicina, 62(3), 448. https://doi.org/10.3390/medicina62030448

