Attention-deficit hyperactivity disorder (ADHD) is a heterogeneous neuropsychiatric disorder highly prevalent in children, characterized by impairments in attention and/or hyperactivity-impulsivity (Faraone et al., 2015; Tsai, 2017). Psychostimulants, such as amphetamine and methylphenidate (MPH) that work by increasing central dopamine and norepinephrine activity in the brain, are recommended as first-line pharmacological therapy for patients with ADHD (Faraone, 2018). Although these drugs impact executive and attentional functions, some patients fail to respond or experience adverse effects including cardiovascular effects, and discontinue the treatment (Faraone, 2018; Tsai, 2017).

The pathogenesis of ADHD is not fully understood, but genetic factors play a significant role in its development (Kent, 2004). Most therapeutic candidates have focused on modulating the dopaminergic neurotransmission system, with additional candidates involving the noradrenergic and serotonergic systems (Banaschewski et al., 2010; Kent, 2004). In particular, the neurotransmitter dopamine plays an important role in behavioral processes such as cognition and emotional processing; therefore, its dysfunction is involved in several neuropsychiatric disorders including ADHD (Faraone and Biederman, 1998; Leo et al., 2018). Alterations in dopaminergic neurotransmission within the mesocorticolimbic system are involved in the pathophysiology of ADHD, with functional abnormalities in fronto-basal ganglia networks (Biederman and Faraone, 2002; Hart et al., 2013).

Genes associated with neuronal development and plasticity are considered another important target in the clinical manifestation and pathogenesis of ADHD (Banaschewski et al., 2010; Galvez-Contreras et al., 2017; Tsai, 2017). Neurotrophic factors (NTFs) are essential for neural development of the brain and plasticity in adults and are involved in the pathogenesis of ADHD (Bilgiç et al., 2017; Tsai, 2017). In particular, brain-derived neurotrophic factor (BDNF) has been identified in the pathophysiology of ADHD and represents a biological target for treatments of this disorder (Conner et al., 2008; Kent et al., 2005; Tsai, 2017).

Transcranial direct current stimulation (tDCS) has been extensively investigated in children with a variety of diagnoses, including neuropsychiatric disorders, and has shown no serious adverse effects (Bikson et al., 2016). tDCS improves short- and long-term memory deficits and is associated with altered dopamine levels and enhanced synaptic activity, respectively, as shown in an ADHD animal model (Leffa et al., 2018; Leffa et al., 2016). Anodal tDCS exerts beneficial effects on higher order cognitive functions, such as working memory, attention, and perception, in patients with diabetes and animal models through the augmentation of synaptic plasticity, thus requiring BDNF secretion (Coffman et al., 2014; Wu et al., 2017). Because ADHD has comorbid cognitive dysfunction disorders (Faraone et al., 2015; Tsai, 2017), tDCS has been proposed as a possible therapeutic option for treating patients with ADHD (Leffa et al., 2018; Leffa et al., 2016).

Conventional tDCS using saline sponge-based rectangular pads stimulates a large scalp area; thus, the current flow is not concentrated on targeted neuronal populations (Brunoni et al., 2012). However, high-definition tDCS (HD-tDCS) uses small ring-based electrodes to facilitate stimulation and target current delivery, thereby overcoming the lack of specificity (Datta et al., 2009). As HD-tDCS is a potential tool for brain stimulation in the treatment of cognitive deficits, we hypothesized that the regulation of dopaminergic neurotransmission and NTFs using an HD-tDCS approach would contribute to the recovery from cognitive symptoms in patients with ADHD. We therefore modified anodal HD-tDCS for rodents using a small ring-based electrode to optimize focality and intensity. The aim of this study was to identify the therapeutic effects of modified HD-tDCS in a preclinical model of ADHD and to investigate the underlying mechanisms related to these effects. We evaluated the therapeutic effects of HD-tDCS using behavioral assessments of cognitive functions, and performed biochemical and immunofluorescence assays to investigate alterations in dopaminergic neurotransmission and NTFs at the core sites of dopaminergic pathways.

We investigated the therapeutic effects of multi-day sessions of HD-tDCS on recovery from cognitive symptoms observed in a rat model of ADHD. The main findings of the present study are the following: (1) application of anodal HD-tDCS over the prefrontal cortex was associated with beneficial effects on cognition; (2) application of anodal HD-tDCS increased dopaminergic signaling factors TH and VMAT2, and significantly decreased DAT; (3) application of anodal HD-tDCS led to an increase in several NTFs, such as BDNF, TGF-β1, and GDNF. In particular, BDNF showed the most significant increase and was associated with hippocampal neurogenesis. Taken together, our findings suggest that anodal HD-tDCS over the prefrontal cortex regulates dopaminergic neurotransmission and NTFs and that it therefore provides a potential therapeutic tool for cognitive dysfunction in patients with ADHD.

ADHD is a heterogeneous neuropsychiatric disorder associated with impaired cognitive function, including problems with behavioral flexibility (Cui et al., 2018; Faraone et al., 2015; Tsai, 2017). Recent studies suggest that non-invasive brain stimulation with tDCS may have therapeutic potential for improving cognitive impairments in patients with ADHD (Coffman et al., 2014; Leffa et al., 2018; Leffa et al., 2016; Wu et al., 2017). The major concerns associated with tDCS treatment are related to its safeness as well as to cortical excitability. Two generalized safety parameters for dosing, electrode current, and charge density have been suggested (Jackson et al., 2017; Liebetanz et al., 2009), and our electrode montage provides an additional safety margin (Jackson et al., 2017; Liebetanz et al., 2009). More than 80% of the applied current is lost in the rat; enough current flowing from the electrode is, however, essential to elicit cortical electric fields (Vöröslakos et al., 2018). Our computational models predicted that values for both electric field intensity and current density would peak at the prefrontal or primary motor cortex according to the electrode position. Electric fields as low as ~1 V/m can affect the timing of action potentials; however, higher intensities (~2 V/m) are required to measurably affect local field potential and the associated brain networks (Liu et al., 2018; Vöröslakos et al., 2018). Our predicted peak electric field intensity was slightly lower than the values in previous rodent experiments, which reported an average intracranial field intensity of 6.8 ± 3.8 V/m (Liu et al., 2018). It also predicted the absence of brain lesions, in line with animal models indicating that brain injury occurs at values of 6.3–13 A/m² (Antal et al., 2017; Bikson et al., 2016).

We first investigated whether HD-tDCS improves cognitive function and flexibility in our rat model of ADHD. We found that HD-tDCS application over the prefrontal cortex exerted a greater beneficial effect than HD-tDCS over the primary motor cortex. HD-tDCS over the prefrontal cortex reduced hyperactivity and alleviated cognitive dysfunctions in spatial learning and working memory, behavioral flexibility, and discrimination and exploratory behavior. These effects were similar to those in the positive control group receiving MPH treatment, with even greater benefits with respect to discrimination ability.

According to the ‘compartment concept’ of dopamine action, extracellular space is considered a site of potential action; thus inhibition of intracellular uptake (or enhancement of vesicular transporters) has been regarded as a target for therapeutic trials (Uhl, 1998). In the dopaminergic neurotransmission system, DAT modulates levels of extracellular and intracellular dopamine stores by controlling reuptake from the extracellular space (Jones et al., 1998; Leo et al., 2018). VMAT2 is a transporter protein expressed on vesicular membranes for monoamines such as dopamine and modulates dopamine release dynamics (Sandoval et al., 2002; Uhl, 1998). DAT and VMAT2 are main regulators of dopamine homeostasis and signaling dynamics between extra- and intracellular compartments in the brain (Guillot and Miller, 2009).

We analyzed gene and protein expression for dopaminergic neurotransmission factors in the core regions of the mesocorticolimbic dopamine pathway. HD-tDCS application induced increases in TH and VMAT2 gene and protein expression and a decrease in DAT expression, a pattern that was most pronounced following HD-tDCS application over the prefrontal cortex. DAT is considered the main target for stimulant drugs used to treat ADHD, such as methylphenidate, a DAT antagonist that works by elevating extracellular dopamine levels (Bonvicini et al., 2016). The ratio between DAT and VMAT2, key regulators of dopaminergic neurotransmission, is a useful molecular marker for dopamine homeostasis; that is, elevated levels of VMAT2 relative to DAT protein translate to higher extracellular levels and, presumably, decreased cytosolic levels of dopamine (Guillot and Miller, 2009; Lohr et al., 2014; Uhl, 1998). HD-tDCS application over the prefrontal cortex showed significant changes in VMAT2 relative to DAT in the prefrontal cortex, striatum, and hippocampus, suggesting possible higher extracellular levels of dopamine in these regions.

NTFs related to neuronal development and plasticity are believed to be involved in the clinical manifestation of ADHD (Banaschewski et al., 2010; Galvez-Contreras et al., 2017; Tsai, 2017). One strong candidate that may play a role in the pathogenesis of ADHD is BDNF (Kent et al., 2005). Bdnf knockout mice exhibit fundamental behavioral characteristics of ADHD (Kernie et al., 2000), and drugs that can activate BDNF signaling have shown therapeutic potential for ADHD (Tsai, 2017). HD-tDCS application induced the upregulation of several NTF genes, including a significant upregulation of BDNF, TGF-β1, and GDNF. In particular, HD-tDCS application over the prefrontal cortex generally induced an increase in BDNF gene and protein expression in all brain regions examined except the hippocampus. Significant induction of BDNF protein was also observed in the SN/VTA of HD-tDCS-treated mice. ADHD rats exhibited decreased BDNF expression in the hippocampus, and impaired spatial learning ability (Jeong et al., 2014). BDNF secretion is essential for learning and memory in tDCS application (Fritsch et al., 2010; Podda et al., 2016). Similarly, our study found that BDNF expression was more markedly increased by HD-tDCS application compared to changes in the other examined NTFs. We confirmed TH and BDNF protein content by ELISA and found that HD-tDCS application induced a significant and continuous increase, not observed in the WKY control stain, in TH levels in the prefrontal cortex and in mBDNF levels in the prefrontal cortex, striatum, and SN/VTA.

Finally, we performed immunofluorescence to observe the distribution of TH/DAT-positive cells, the main target for therapeutic drugs for ADHD (Bonvicini et al., 2016; Uhl, 1998), and of BDNF/pTrkB-positive cells, which have shown therapeutic potential in learning and memory in ADHD (Fritsch et al., 2010; Tsai, 2017). Similar to the results on gene and protein expressions, HD-tDCS application over the prefrontal cortex induced a significant increase in TH-positive cells in the medial prefrontal cortex and the striatum. A marked decrease in DAT-positive cells was observed in the medial prefrontal cortex, dorsal striatum, and SN/VTA. Dopaminergic innervations from the VTA mainly target the prefrontal cortex and ventral striatum (NAc), and also innervate other regions such as the hippocampus. Thus, dopamine signaling represents a crucial factor modulating executive functions including cognitive flexibility, incentive motivation, and reward processing (Russo and Nestler, 2013). Midbrain dopaminergic neurons also project to the striatum and NAc topographically along the mediolateral axis; thus, lateral VTA neurons that project to the NAc core influence motor responses related to reward stimuli (Nobili et al., 2017). There were significantly fewer DAT-positive cells in the prefrontal cortex and striatum and TH/DAT double-positive cells in the lateral region of the VTA following HD-tDCS application, suggesting that HD-tDCS affects executive functions through the regulation of dopaminergic neurotransmission in the prefrontal cortex and the NAc.

HD-tDCS application induced the activation of BDNF/TrkB, even more than MPH treatment, in all target regions except the SN. Enhancing adult hippocampal neurogenesis improves cognitive function and is closely related to BDNF expression (Choi et al., 2018). Thus, we quantified neurogenesis in the dentate gyrus of the hippocampus and found a significant increase in newly formed neurons following HD-tDCS application. A comparison of the HD-tDCS group with the positive control group receiving DAT antagonist MPH revealed similar therapeutic effects. Indeed, HD-tDCS application over the prefrontal cortex had a more significant effect on BDNF expression than MPH. This suggests that long-term application of tDCS may mediate N-methyl-D-aspartate (NMDA) receptors and increase intracellular calcium levels that link to the downstream molecular cascades, leading to the secretion of activity-dependent growth factors such as BDNF (Liebetanz et al., 2002; Nitsche et al., 2003; Wu et al., 2017). BDNF also enhances dopamine release in the NAc through the activation of TrkB receptors on dopaminergic nerve terminals, and is thus considered a key regulator of the mesolimbic dopamine pathway linking cognitive processes (Berton et al., 2006; Goggi et al., 2003). Our results shed light on the possibility that the activation of the BDNF/TrkB pathway may be involved in dopamine release at the core sites of dopaminergic pathways.

Non-invasive brain stimulators generate neuronal activation at the primary target site and then spread to subcortical sites of the mesocorticolimbic dopamine system via mediating NMDA receptors that induce intracellular calcium cascades (Diana et al., 2017; Ferenczi and Deisseroth, 2016; Liebetanz et al., 2002; Nitsche et al., 2003; Wu et al., 2017). The observed connectivity-based spread from the prefrontal cortex to subcortical sites following HD-tDCS may be related to the therapeutic effects on cognitive deficits in patients with ADHD. Our results show that similar therapeutic effects in the tDCS-PFC and the tDCS-M1 groups, potentially due to connectivity-based spread from the prefrontal cortex to subcortical sites (Liebetanz et al., 2002; Nitsche et al., 2003; Wu et al., 2017) and direct electrical stimulation of subcortical structures (Hadar et al., 2020; Thibaut et al., 2015). However, other possible mechanisms should be considered that the stimulation of HD-tDCS may partially induce cortical excitability via transcutaneous peripheral nerve stimulation, depending on the location of the active and reference electrode (Asamoah et al., 2019; Tsuiki et al., 2019).

While our study suggests that tDCS application provides a potential adjuvant therapy for ADHD, our findings have some limitations regarding their transfer to the clinical practice. The charge density and predicted current density was much higher than what is currently applied in patients, which makes it difficult to directly transfer our approach to clinical situations (Bikson et al., 2016; Liebetanz et al., 2009). However, head size needs to be considered regarding the transfer of stimulation parameters and dose regimes need to be adapted to achieve comparable conditions in animal and clinical studies. The relative difference in electric field strength between the mouse and humans is 100 times, with a typical transcranial electric stimulation intensity of 1–2 mA in humans approximately translating to 10–20 μA in mice (Alekseichuk et al., 2019). Compared to the intensity of <1 V/m measured in conventional human studies (Liu et al., 2018), rodent studies typically employ stronger intensities. The human brain also requires a higher field intensity than that used in conventional tDCS to reliably affect local field potential (Liu et al., 2018; Vöröslakos et al., 2018). Our results encourage the development of intensified tDCS protocols to induce more stable or more potent, that is, therapeutically longer-lasting, benefits of neuromodulation in psychiatric disorders (Antal et al., 2017; Jackson et al., 2016; Liebetanz et al., 2009).

Consequently, our results present evidence of the therapeutic potential of anodal HD-tDCS over the prefrontal cortex in the treatment of ADHD. This treatment regulated dopaminergic neurotransmission factors (especially DAT) and BDNF signaling in the core dopaminergic pathways, subsequently ameliorating cognitive dysfunction. The results of our gene and protein expression analysis, that is, TGF-β1 protein in the striatum and GDNF protein in the hippocampus indicate that NTFs such as TGF-β1 and GDNF are also activated; future research that aims to clarify these mechanisms is warranted. In summary anodal HD-tDCS application offers a potential adjuvant therapy for psychiatric disorders such as ADHD and may improve recovery of cognitive dysfunctions.

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures and Tables.

1. 1. Alekseichuk I
   2. Mantell K
   3. Shirinpour S
   4. Opitz A

   (2019) Comparative modeling of transcranial magnetic and electric stimulation in mouse, monkey, and human

   NeuroImage 194:136–148.

   https://doi.org/10.1016/j.neuroimage.2019.03.044

   • PubMed
   • Google Scholar
2. 1. Antal A
   2. Alekseichuk I
   3. Bikson M
   4. Brockmöller J
   5. Brunoni AR
   6. Chen R
   7. Cohen LG
   8. Dowthwaite G
   9. Ellrich J
   10. Flöel A
   11. Fregni F
   12. George MS
   13. Hamilton R
   14. Haueisen J
   15. Herrmann CS
   16. Hummel FC
   17. Lefaucheur JP
   18. Liebetanz D
   19. Loo CK
   20. McCaig CD
   21. Miniussi C
   22. Miranda PC
   23. Moliadze V
   24. Nitsche MA
   25. Nowak R
   26. Padberg F
   27. Pascual-Leone A
   28. Poppendieck W
   29. Priori A
   30. Rossi S
   31. Rossini PM
   32. Rothwell J
   33. Rueger MA
   34. Ruffini G
   35. Schellhorn K
   36. Siebner HR
   37. Ugawa Y
   38. Wexler A
   39. Ziemann U
   40. Hallett M
   41. Paulus W

   (2017) Low intensity transcranial electric stimulation: safety, ethical, legal regulatory and application guidelines

   Clinical Neurophysiology 128:1774–1809.

   https://doi.org/10.1016/j.clinph.2017.06.001

   • PubMed
   • Google Scholar
3. 1. Asamoah B
   2. Khatoun A
   3. Mc Laughlin M

   (2019) tACS motor system effects can be caused by transcutaneous stimulation of peripheral nerves

   Nature Communications 10:266.

   https://doi.org/10.1038/s41467-018-08183-w

   • PubMed
   • Google Scholar
4. 1. Banaschewski T
   2. Becker K
   3. Scherag S
   4. Franke B
   5. Coghill D

   (2010) Molecular genetics of attention-deficit/hyperactivity disorder: an overview

   European Child & Adolescent Psychiatry 19:237–257.

   https://doi.org/10.1007/s00787-010-0090-z

   • PubMed
   • Google Scholar
5. 1. Berton O
   2. McClung CA
   3. Dileone RJ
   4. Krishnan V
   5. Renthal W
   6. Russo SJ
   7. Graham D
   8. Tsankova NM
   9. Bolanos CA
   10. Rios M
   11. Monteggia LM
   12. Self DW
   13. Nestler EJ

   (2006) Essential role of BDNF in the mesolimbic dopamine pathway in social defeat stress

   Science 311:864–868.

   https://doi.org/10.1126/science.1120972

   • PubMed
   • Google Scholar
6. 1. Biederman J
   2. Faraone SV

   (2002) Current concepts on the neurobiology of Attention-Deficit/Hyperactivity disorder

   Journal of Attention Disorders 6:7–16.

   https://doi.org/10.1177/070674370200601S03

   • Google Scholar
7. 1. Bikson M
   2. Grossman P
   3. Thomas C
   4. Zannou AL
   5. Jiang J
   6. Adnan T
   7. Mourdoukoutas AP
   8. Kronberg G
   9. Truong D
   10. Boggio P
   11. Brunoni AR
   12. Charvet L
   13. Fregni F
   14. Fritsch B
   15. Gillick B
   16. Hamilton RH
   17. Hampstead BM
   18. Jankord R
   19. Kirton A
   20. Knotkova H
   21. Liebetanz D
   22. Liu A
   23. Loo C
   24. Nitsche MA
   25. Reis J
   26. Richardson JD
   27. Rotenberg A
   28. Turkeltaub PE
   29. Woods AJ

   (2016) Safety of transcranial direct current stimulation: evidence based update 2016

   Brain Stimulation 9:641–661.

   https://doi.org/10.1016/j.brs.2016.06.004

   • PubMed
   • Google Scholar
8. 1. Bilgiç A
   2. Toker A
   3. Işık Ü
   4. Kılınç İ

   (2017) Serum brain-derived neurotrophic factor, glial-derived neurotrophic factor, nerve growth factor, and neurotrophin-3 levels in children with attention-deficit/hyperactivity disorder

   European Child & Adolescent Psychiatry 26:355–363.

   https://doi.org/10.1007/s00787-016-0898-2

   • PubMed
   • Google Scholar
9. 1. Bonvicini C
   2. Faraone SV
   3. Scassellati C

   (2016) Attention-deficit hyperactivity disorder in adults: a systematic review and meta-analysis of genetic, pharmacogenetic and biochemical studies

   Molecular Psychiatry 21:872–884.

   https://doi.org/10.1038/mp.2016.74

   • PubMed
   • Google Scholar
10. 1. Brunoni AR
    2. Nitsche MA
    3. Bolognini N
    4. Bikson M
    5. Wagner T
    6. Merabet L
    7. Edwards DJ
    8. Valero-Cabre A
    9. Rotenberg A
    10. Pascual-Leone A
    11. Ferrucci R
    12. Priori A
    13. Boggio PS
    14. Fregni F

    (2012) Clinical research with transcranial direct current stimulation (tDCS): challenges and future directions

    Brain Stimulation 5:175–195.

    https://doi.org/10.1016/j.brs.2011.03.002

    • PubMed
    • Google Scholar
11. 1. Choi SH
    2. Bylykbashi E
    3. Chatila ZK
    4. Lee SW
    5. Pulli B
    6. Clemenson GD
    7. Kim E
    8. Rompala A
    9. Oram MK
    10. Asselin C
    11. Aronson J
    12. Zhang C
    13. Miller SJ
    14. Lesinski A
    15. Chen JW
    16. Kim DY
    17. van Praag H
    18. Spiegelman BM
    19. Gage FH
    20. Tanzi RE

    (2018) Combined adult neurogenesis and BDNF mimic exercise effects on cognition in an Alzheimer's mouse model

    Science 361:eaan8821.

    https://doi.org/10.1126/science.aan8821

    • PubMed
    • Google Scholar
12. 1. Coffman BA
    2. Clark VP
    3. Parasuraman R

    (2014) Battery powered thought: enhancement of attention, learning, and memory in healthy adults using transcranial direct current stimulation

    NeuroImage 85:895–908.

    https://doi.org/10.1016/j.neuroimage.2013.07.083

    • PubMed
    • Google Scholar
13. 1. Conner AC
    2. Kissling C
    3. Hodges E
    4. Hünnerkopf R
    5. Clement RM
    6. Dudley E
    7. Freitag CM
    8. Rösler M
    9. Retz W
    10. Thome J

    (2008) Neurotrophic factor-related gene polymorphisms and adult attention deficit hyperactivity disorder (ADHD) score in a high-risk male population

    American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 147B:1476–1480.

    https://doi.org/10.1002/ajmg.b.30632

    • Google Scholar
14. 1. Cui Q
    2. Li Q
    3. Geng H
    4. Chen L
    5. Ip NY
    6. Ke Y
    7. Yung WH

    (2018) Dopamine receptors mediate strategy abandoning via modulation of a specific prelimbic cortex-nucleus accumbens pathway in mice

    PNAS 115:E4890–E4899.

    https://doi.org/10.1073/pnas.1717106115

    • PubMed
    • Google Scholar
15. 1. Datta A
    2. Bansal V
    3. Diaz J
    4. Patel J
    5. Reato D
    6. Bikson M

    (2009) Gyri-precise head model of transcranial direct current stimulation: improved spatial focality using a ring electrode versus conventional rectangular pad

    Brain Stimulation 2:201–207.

    https://doi.org/10.1016/j.brs.2009.03.005

    • Google Scholar
16. 1. Diana M
    2. Raij T
    3. Melis M
    4. Nummenmaa A
    5. Leggio L
    6. Bonci A

    (2017) Rehabilitating the addicted brain with transcranial magnetic stimulation

    Nature Reviews Neuroscience 18:685–693.

    https://doi.org/10.1038/nrn.2017.113

    • PubMed
    • Google Scholar
17. 1. Faraone SV
    2. Asherson P
    3. Banaschewski T
    4. Biederman J
    5. Buitelaar JK
    6. Ramos-Quiroga JA
    7. Rohde LA
    8. Sonuga-Barke EJ
    9. Tannock R
    10. Franke B

    (2015) Attention-deficit/hyperactivity disorder

    Nature Reviews Disease Primers 1:15020.

    https://doi.org/10.1038/nrdp.2015.20

    • PubMed
    • Google Scholar
18. 1. Faraone SV

    (2018) The pharmacology of amphetamine and methylphenidate: relevance to the neurobiology of attention-deficit/hyperactivity disorder and other psychiatric comorbidities

    Neuroscience & Biobehavioral Reviews 87:255–270.

    https://doi.org/10.1016/j.neubiorev.2018.02.001

    • PubMed
    • Google Scholar
19. 1. Faraone SV
    2. Biederman J

    (1998) Neurobiology of attention-deficit hyperactivity disorder

    Biological Psychiatry 44:951–958.

    https://doi.org/10.1016/S0006-3223(98)00240-6

    • PubMed
    • Google Scholar
20. 1. Ferenczi E
    2. Deisseroth K

    (2016) Illuminating next-generation brain therapies

    Nature Neuroscience 19:414–416.

    https://doi.org/10.1038/nn.4232

    • Google Scholar
21. 1. Fritsch B
    2. Reis J
    3. Martinowich K
    4. Schambra HM
    5. Ji Y
    6. Cohen LG
    7. Lu B

    (2010) Direct current stimulation promotes BDNF-dependent synaptic plasticity: potential implications for motor learning

    Neuron 66:198–204.

    https://doi.org/10.1016/j.neuron.2010.03.035

    • PubMed
    • Google Scholar
22. 1. Galvez-Contreras AY
    2. Campos-Ordonez T
    3. Gonzalez-Castaneda RE
    4. Gonzalez-Perez O

    (2017) Alterations of growth factors in autism and Attention-Deficit/Hyperactivity disorder

    Frontiers in Psychiatry 8:126.

    https://doi.org/10.3389/fpsyt.2017.00126

    • PubMed
    • Google Scholar
23. 1. Goggi J
    2. Pullar IA
    3. Carney SL
    4. Bradford HF

    (2003) Signalling pathways involved in the short-term potentiation of dopamine release by BDNF

    Brain Research 968:156–161.

    https://doi.org/10.1016/S0006-8993(03)02234-0

    • PubMed
    • Google Scholar
24. 1. Guillot TS
    2. Miller GW

    (2009) Protective actions of the vesicular monoamine transporter 2 (VMAT2) in monoaminergic neurons

    Molecular Neurobiology 39:149–170.

    https://doi.org/10.1007/s12035-009-8059-y

    • PubMed
    • Google Scholar
25. 1. Hadar R
    2. Winter R
    3. Edemann-Callesen H
    4. Wieske F
    5. Habelt B
    6. Khadka N
    7. Felgel-Farnholz V
    8. Barroeta-Hlusicka E
    9. Reis J
    10. Tatarau CA
    11. Funke K
    12. Fritsch B
    13. Bernhardt N
    14. Bikson M
    15. Nitsche MA
    16. Winter C

    (2020) Prevention of schizophrenia deficits via non-invasive adolescent frontal cortex stimulation in rats

    Molecular Psychiatry 25:896–905.

    https://doi.org/10.1038/s41380-019-0356-x

    • PubMed
    • Google Scholar
26. 1. Hart H
    2. Radua J
    3. Nakao T
    4. Mataix-Cols D
    5. Rubia K

    (2013) Meta-analysis of functional magnetic resonance imaging studies of inhibition and attention in attention-deficit/hyperactivity disorder: exploring task-specific, stimulant medication, and age effects

    JAMA Psychiatry 70:185–198.

    https://doi.org/10.1001/jamapsychiatry.2013.277

    • PubMed
    • Google Scholar
27. 1. Jackson MP
    2. Rahman A
    3. Lafon B
    4. Kronberg G
    5. Ling D
    6. Parra LC
    7. Bikson M

    (2016) Animal models of transcranial direct current stimulation: methods and mechanisms

    Clinical Neurophysiology 127:3425–3454.

    https://doi.org/10.1016/j.clinph.2016.08.016

    • PubMed
    • Google Scholar
28. 1. Jackson MP
    2. Truong D
    3. Brownlow ML
    4. Wagner JA
    5. McKinley RA
    6. Bikson M
    7. Jankord R

    (2017) Safety parameter considerations of anodal transcranial direct current stimulation in rats

    Brain, Behavior, and Immunity 64:152–161.

    https://doi.org/10.1016/j.bbi.2017.04.008

    • PubMed
    • Google Scholar
29. 1. Jeong HI
    2. Ji ES
    3. Kim SH
    4. Kim TW
    5. Baek SB
    6. Choi SW

    (2014) Treadmill exercise improves spatial learning ability by enhancing brain-derived neurotrophic factor expression in the attention-deficit/hyperactivity disorder rats

    Journal of Exercise Rehabilitation 10:162–167.

    https://doi.org/10.12965/jer.140111

    • PubMed
    • Google Scholar
30. 1. Jones SR
    2. Gainetdinov RR
    3. Jaber M
    4. Giros B
    5. Wightman RM
    6. Caron MG

    (1998) Profound neuronal plasticity in response to inactivation of the dopamine transporter

    PNAS 95:4029–4034.

    https://doi.org/10.1073/pnas.95.7.4029

    • PubMed
    • Google Scholar
31. 1. Jung Y-J
    2. Kim J-H
    3. Im C-H

    (2013) COMETS: a MATLAB toolbox for simulating local electric fields generated by transcranial direct current stimulation (tDCS)

    Biomedical Engineering Letters 3:39–46.

    https://doi.org/10.1007/s13534-013-0087-x

    • Google Scholar
32. 1. Kent L

    (2004) Recent advances in the genetics of attention deficit hyperactivity disorder

    Current Psychiatry Reports 6:143–148.

    https://doi.org/10.1007/s11920-004-0054-4

    • PubMed
    • Google Scholar
33. 1. Kent L
    2. Green E
    3. Hawi Z
    4. Kirley A
    5. Dudbridge F
    6. Lowe N
    7. Raybould R
    8. Langley K
    9. Bray N
    10. Fitzgerald M
    11. Owen MJ
    12. O'Donovan MC
    13. Gill M
    14. Thapar A
    15. Craddock N

    (2005) Association of the paternally transmitted copy of common Valine allele of the Val66Met polymorphism of the brain-derived neurotrophic factor (BDNF) gene with susceptibility to ADHD

    Molecular Psychiatry 10:939–943.

    https://doi.org/10.1038/sj.mp.4001696

    • PubMed
    • Google Scholar
34. 1. Kernie SG
    2. Liebl DJ
    3. Parada LF

    (2000) BDNF regulates eating behavior and locomotor activity in mice

    The EMBO Journal 19:1290–1300.

    https://doi.org/10.1093/emboj/19.6.1290

    • PubMed
    • Google Scholar
35. Conference

    1. Kronberg G
    2. Bikson M

    (2012) Electrode assembly design for transcranial direct current stimulation: a FEM modeling study

    Conference Proceedings : . Annual International Conference of the IEEE Engineering in Medicine and Biology Society Annual Conference. pp. 891–895.

    https://doi.org/10.1109/EMBC.2012.6346075

    • Google Scholar
36. 1. Lee C
    2. Jung YJ
    3. Lee SJ
    4. Im CH

    (2017) COMETS2: an advanced MATLAB toolbox for the numerical analysis of electric fields generated by transcranial direct current stimulation

    Journal of Neuroscience Methods 277:56–62.

    https://doi.org/10.1016/j.jneumeth.2016.12.008

    • PubMed
    • Google Scholar
37. 1. Leffa DT
    2. de Souza A
    3. Scarabelot VL
    4. Medeiros LF
    5. de Oliveira C
    6. Grevet EH
    7. Caumo W
    8. de Souza DO
    9. Rohde LAP
    10. Torres ILS

    (2016) Transcranial direct current stimulation improves short-term memory in an animal model of attention-deficit/hyperactivity disorder

    European Neuropsychopharmacology 26:368–377.

    https://doi.org/10.1016/j.euroneuro.2015.11.012

    • PubMed
    • Google Scholar
38. 1. Leffa DT
    2. Bellaver B
    3. Salvi AA
    4. de Oliveira C
    5. Caumo W
    6. Grevet EH
    7. Fregni F
    8. Quincozes-Santos A
    9. Rohde LA
    10. Torres ILS

    (2018) Transcranial direct current stimulation improves long-term memory deficits in an animal model of attention-deficit/hyperactivity disorder and modulates oxidative and inflammatory parameters

    Brain Stimulation 11:743–751.

    https://doi.org/10.1016/j.brs.2018.04.001

    • PubMed
    • Google Scholar
39. 1. Leo D
    2. Sukhanov I
    3. Zoratto F
    4. Illiano P
    5. Caffino L
    6. Sanna F
    7. Messa G
    8. Emanuele M
    9. Esposito A
    10. Dorofeikova M
    11. Budygin EA
    12. Mus L
    13. Efimova EV
    14. Niello M
    15. Espinoza S
    16. Sotnikova TD
    17. Hoener MC
    18. Laviola G
    19. Fumagalli F
    20. Adriani W
    21. Gainetdinov RR

    (2018) Pronounced hyperactivity, cognitive dysfunctions, and BDNF dysregulation in dopamine transporter Knock-out rats

    The Journal of Neuroscience 38:1959–1972.

    https://doi.org/10.1523/JNEUROSCI.1931-17.2018

    • PubMed
    • Google Scholar
40. 1. Liebetanz D
    2. Nitsche MA
    3. Tergau F
    4. Paulus W

    (2002) Pharmacological approach to the mechanisms of transcranial DC-stimulation-induced after-effects of human motor cortex excitability

    Brain 125:2238–2247.

    https://doi.org/10.1093/brain/awf238

    • PubMed
    • Google Scholar
41. 1. Liebetanz D
    2. Koch R
    3. Mayenfels S
    4. König F
    5. Paulus W
    6. Nitsche MA

    (2009) Safety limits of cathodal transcranial direct current stimulation in rats

    Clinical Neurophysiology 120:1161–1167.

    https://doi.org/10.1016/j.clinph.2009.01.022

    • PubMed
    • Google Scholar
42. 1. Liu A
    2. Vöröslakos M
    3. Kronberg G
    4. Henin S
    5. Krause MR
    6. Huang Y
    7. Opitz A
    8. Mehta A
    9. Pack CC
    10. Krekelberg B
    11. Berényi A
    12. Parra LC
    13. Melloni L
    14. Devinsky O
    15. Buzsáki G

    (2018) Immediate neurophysiological effects of transcranial electrical stimulation

    Nature Communications 9:5092.

    https://doi.org/10.1038/s41467-018-07233-7

    • PubMed
    • Google Scholar
43. 1. Lohr KM
    2. Bernstein AI
    3. Stout KA
    4. Dunn AR
    5. Lazo CR
    6. Alter SP
    7. Wang M
    8. Li Y
    9. Fan X
    10. Hess EJ
    11. Yi H
    12. Vecchio LM
    13. Goldstein DS
    14. Guillot TS
    15. Salahpour A
    16. Miller GW

    (2014) Increased vesicular monoamine transporter enhances dopamine release and opposes parkinson disease-related neurodegeneration in vivo

    PNAS 111:9977–9982.

    https://doi.org/10.1073/pnas.1402134111

    • PubMed
    • Google Scholar
44. 1. Nitsche MA
    2. Fricke K
    3. Henschke U
    4. Schlitterlau A
    5. Liebetanz D
    6. Lang N
    7. Henning S
    8. Tergau F
    9. Paulus W

    (2003) Pharmacological modulation of cortical excitability shifts induced by transcranial direct current stimulation in humans

    The Journal of Physiology 553:293–301.

    https://doi.org/10.1113/jphysiol.2003.049916

    • PubMed
    • Google Scholar
45. 1. Nobili A
    2. Latagliata EC
    3. Viscomi MT
    4. Cavallucci V
    5. Cutuli D
    6. Giacovazzo G
    7. Krashia P
    8. Rizzo FR
    9. Marino R
    10. Federici M
    11. De Bartolo P
    12. Aversa D
    13. Dell'Acqua MC
    14. Cordella A
    15. Sancandi M
    16. Keller F
    17. Petrosini L
    18. Puglisi-Allegra S
    19. Mercuri NB
    20. Coccurello R
    21. Berretta N
    22. D'Amelio M

    (2017) Dopamine neuronal loss contributes to memory and reward dysfunction in a model of alzheimer's disease

    Nature Communications 8:14727.

    https://doi.org/10.1038/ncomms14727

    • PubMed
    • Google Scholar
46. 1. Podda MV
    2. Cocco S
    3. Mastrodonato A
    4. Fusco S
    5. Leone L
    6. Barbati SA
    7. Colussi C
    8. Ripoli C
    9. Grassi C

    (2016) Anodal transcranial direct current stimulation boosts synaptic plasticity and memory in mice via epigenetic regulation of bdnf expression

    Scientific Reports 6:22180.

    https://doi.org/10.1038/srep22180

    • PubMed
    • Google Scholar
47. 1. Russo SJ
    2. Nestler EJ

    (2013) The brain reward circuitry in mood disorders

    Nature Reviews Neuroscience 14:609–625.

    https://doi.org/10.1038/nrn3381

    • PubMed
    • Google Scholar
48. 1. Sandoval V
    2. Riddle EL
    3. Hanson GR
    4. Fleckenstein AE

    (2002) Methylphenidate redistributes vesicular monoamine transporter-2: role of dopamine receptors

    The Journal of Neuroscience 22:8705–8710.

    https://doi.org/10.1523/JNEUROSCI.22-19-08705.2002

    • PubMed
    • Google Scholar
49. 1. Thibaut A
    2. Di Perri C
    3. Chatelle C
    4. Bruno MA
    5. Bahri MA
    6. Wannez S
    7. Piarulli A
    8. Bernard C
    9. Martial C
    10. Heine L
    11. Hustinx R
    12. Laureys S

    (2015) Clinical response to tDCS depends on residual brain metabolism and Grey Matter Integrity in Patients With Minimally Conscious State

    Brain Stimulation 8:1116–1123.

    https://doi.org/10.1016/j.brs.2015.07.024

    • PubMed
    • Google Scholar
50. 1. Tsai SJ

    (2017) Role of neurotrophic factors in attention deficit hyperactivity disorder

    Cytokine & Growth Factor Reviews 34:35–41.

    https://doi.org/10.1016/j.cytogfr.2016.11.003

    • PubMed
    • Google Scholar
51. 1. Tsuiki S
    2. Sasaki R
    3. Miyaguchi S
    4. Kojima S
    5. Saito K
    6. Inukai Y
    7. Masaki M
    8. Otsuru N
    9. Onishi H

    (2019) The effect of combined transcranial direct current stimulation and peripheral nerve electrical stimulation on corticospinal excitability

    PLOS ONE 14:e0214592.

    https://doi.org/10.1371/journal.pone.0214592

    • PubMed
    • Google Scholar
52. 1. Uhl GR

    (1998) Hypothesis: the role of dopaminergic transporters in selective vulnerability of cells in Parkinson's disease

    Annals of Neurology 43:555–560.

    https://doi.org/10.1002/ana.410430503

    • PubMed
    • Google Scholar
53. 1. Vöröslakos M
    2. Takeuchi Y
    3. Brinyiczki K
    4. Zombori T
    5. Oliva A
    6. Fernández-Ruiz A
    7. Kozák G
    8. Kincses ZT
    9. Iványi B
    10. Buzsáki G
    11. Berényi A

    (2018) Direct effects of transcranial electric stimulation on brain circuits in rats and humans

    Nature Communications 9:483.

    https://doi.org/10.1038/s41467-018-02928-3

    • PubMed
    • Google Scholar
54. 1. Wu YJ
    2. Lin CC
    3. Yeh CM
    4. Chien ME
    5. Tsao MC
    6. Tseng P
    7. Huang CW
    8. Hsu KS

    (2017) Repeated transcranial direct current stimulation improves cognitive dysfunction and synaptic plasticity deficit in the prefrontal cortex of streptozotocin-induced diabetic rats

    Brain Stimulation 10:1079–1087.

    https://doi.org/10.1016/j.brs.2017.08.007

    • PubMed
    • Google Scholar

Author details

1. Da Hee Jung

   1. Department of Korean Medical Science, School of Korean Medicine, Pusan National University, Yangsan, Republic of Korea
   2. Graduate Training Program of Korean Medicine for Healthy Aging, Pusan National University, Yangsan, Republic of Korea

   Contribution

   Conceptualization, Data curation, Formal analysis, Methodology, Writing - original draft

   Competing interests

   No competing interests declared

2. Sung Min Ahn

   Korean Medical Science Research Center for Healthy Aging, Pusan National University, Yangsan, Republic of Korea

   Contribution

   Methodology

   Competing interests

   No competing interests declared

3. Malk Eun Pak

   Korean Medical Science Research Center for Healthy Aging, Pusan National University, Yangsan, Republic of Korea

   Contribution

   Methodology

   Competing interests

   No competing interests declared

4. Hong Ju Lee

   1. Department of Korean Medical Science, School of Korean Medicine, Pusan National University, Yangsan, Republic of Korea
   2. Graduate Training Program of Korean Medicine for Healthy Aging, Pusan National University, Yangsan, Republic of Korea

   Contribution

   Methodology

   Competing interests

   No competing interests declared

5. Young Jin Jung

   Department of Radiological Science, Health Science Division, Dongseo University, Busan, Republic of Korea

   Contribution

   Investigation

   Competing interests

   No competing interests declared

6. Ki Bong Kim

   Department of Korean Pediatrics, School of Korean Medicine, Pusan National University, Yangsan, Republic of Korea

   Contribution

   Data curation

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5724-4653

7. Yong-Il Shin

   Department of Rehabilitation Medicine, School of Medicine, Pusan National University, Yangsan, Republic of Korea

   Contribution

   Data curation

   Competing interests

   No competing interests declared

8. Hwa Kyoung Shin

   1. Department of Korean Medical Science, School of Korean Medicine, Pusan National University, Yangsan, Republic of Korea
   2. Graduate Training Program of Korean Medicine for Healthy Aging, Pusan National University, Yangsan, Republic of Korea
   3. Korean Medical Science Research Center for Healthy Aging, Pusan National University, Yangsan, Republic of Korea

   Contribution

   Data curation, Methodology

   Competing interests

   No competing interests declared

9. Byung Tae Choi

   1. Department of Korean Medical Science, School of Korean Medicine, Pusan National University, Yangsan, Republic of Korea
   2. Graduate Training Program of Korean Medicine for Healthy Aging, Pusan National University, Yangsan, Republic of Korea
   3. Korean Medical Science Research Center for Healthy Aging, Pusan National University, Yangsan, Republic of Korea

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Writing - original draft

   For correspondence

   choibt@pusan.ac.kr

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5965-4346

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