ORIGINAL RESEARCH published: 13 March 2020 doi: 10.3389/fnint.2020.00013 Continuous Theta-Burst Stimulation in Children With High-Functioning Autism Spectrum Disorder and Typically Developing Children Ali Jannati 1,2 *, Gabrielle Block 1,2† , Mary A. Ryan 1,2 , Harper L. Kaye 1 , Fae B. Kayarian 2 , Shahid Bashir 3 , Lindsay M. Oberman 4† , Alvaro Pascual-Leone 2,5 and Alexander Rotenberg 1,2 * 1 Neuromodulation Program and Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Edited by: Children’s Hospital, Harvard Medical School, Boston, MA, United States, 2 Berenson-Allen Center for Noninvasive Brain John A. Sweeney, Stimulation and Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard University of Cincinnati, United States Medical School, Boston, MA, United States, 3 Neuroscience Center, King Fahad Specialist Hospital Dammam, Dammam, Reviewed by: Saudi Arabia, 4 Neuroplasticity and Autism Spectrum Disorder Program, Department of Psychiatry and Human Behavior, E. P. Sara Borgomaneri, Bradley Hospital, Warren Alpert Medical School, Brown University, East Providence, RI, United States, 5 Institut Guttman de University of Bologna, Italy Neurorehabilitació, Universitat Autónoma de Barcelona, Badalona, Spain Ernest Pedapati, Cincinnati Children’s Hospital Medical Center, United States Objectives: A neurophysiologic biomarker for autism spectrum disorder (ASD) is highly *Correspondence: desirable and can improve diagnosis, monitoring, and assessment of therapeutic Ali Jannati response among children with ASD. We investigated the utility of continuous theta-burst ali.jannati@childrens.harvard.edu stimulation (cTBS) applied to the motor cortex (M1) as a biomarker for children and Alexander Rotenberg alexander.rotenberg@childrens. adolescents with high-functioning (HF) ASD compared to their age- and gender-matched harvard.edu typically developing (TD) controls. We also compared the developmental trajectory of † Present address: long-term depression- (LTD-) like plasticity in the two groups. Finally, we explored the Gabrielle Block, influence of a common brain-derived neurotrophic factor (BDNF) polymorphism on cTBS School of Medicine, New York Medical College, Valhalla, NY, aftereffects in a subset of the ASD group. United States Methods: Twenty-nine children and adolescents (age range 10–16) in ASD (n = 11) Lindsay M. Oberman, Center for Neuroscience and and TD (n = 18) groups underwent M1 cTBS. Changes in MEP amplitude at 5–60 min Regenerative Medicine, Department post-cTBS and their cumulative measures in each group were calculated. We also of Medical and Clinical Psychology, Uniformed Services University of the assessed the relationship between age and maximum cTBS-induced MEP suppression Health Sciences, Bethesda, MD, (∆MEPMax ) in each group. Finally, we compared cTBS aftereffects in BDNF Val/Val (n = 4) United States and Val/Met (n = 4) ASD participants. Received: 30 June 2019 Results: Cumulative cTBS aftereffects were significantly more facilitatory in the ASD Accepted: 25 February 2020 group than in the TD group (PFDR ’s < 0.03). ∆MEPMax was negatively correlated with Published: 13 March 2020 age in the ASD group (r = −0.67, P = 0.025), but not in the TD group (r = −0.12, Citation: Jannati A, Block G, Ryan MA, Kaye HL, Kayarian FB, Bashir S, Abbreviations: ADHD, attention-deficit/hyperactivity disorder; AMT, active motor threshold; BDNF, brain-derived Oberman LM, Pascual-Leone A and neurotrophic factor; cTBS, continuous theta-burst stimulation; ∆MEP, natural log-transformed, baseline-corrected Rotenberg A (2020) Continuous amplitude of motor evoked potentials; EEG, electroencephalography; EMG, electromyography; FDR, false discovery rate; Theta-Burst Stimulation in Children fMRI, functional magnetic resonance imaging; GABA, gamma-aminobutyric acid; HF, high-functioning; IQ, intelligence With High-Functioning Autism quotient; iTBS, intermittent theta-burst stimulation; LF, low-functioning; LTD, long-term depression; LTP, long-term Spectrum Disorder and Typically potentiation; MEP, motor evoked potential; Met, metionine; PAS, paired associative stimulation; PCR, polymerase Developing Children. chain reaction; RMT, resting motor threshold; rTMS, repetitive transcranial magnetic stimulation; SICI, short-interval Front. Integr. Neurosci. 14:13. intracortical cortical inhibition; SNP, single-nucleotide polymorphism; TMS, transcranial magnetic stimulation; Tn, at n doi: 10.3389/fnint.2020.00013 minutes post-cTBS; Val, valine; %∆, percent change from the baseline. Frontiers in Integrative Neuroscience | www.frontiersin.org 1 March 2020 | Volume 14 | Article 13 Jannati et al. cTBS in Children With ASD P = 0.65). Cumulative cTBS aftereffects were not significantly different between the two BDNF subgroups (P-values > 0.18). Conclusions: The results support the utility of cTBS measures of cortical plasticity as a biomarker for children and adolescents with HF-ASD and an aberrant developmental trajectory of LTD-like plasticity in ASD. Keywords: transcranial magnetic stimulation, continuous theta-burst stimulation, plasticity, biomarker, autism spectrum disorder, BDNF INTRODUCTION abnormal in patients with ASD (Pascual-Leone et al., 2005, 2011; Oberman et al., 2010). Autism spectrum disorder (ASD) is characterized by social Pursuant to cTBS (Oberman et al., 2012), adults with communication deficits and restricted, repetitive, and high-functioning (HF) ASD have greater and longer-lasting stereotyped behaviors and interests (American Psychiatric MEP suppression as compared to neurotypical (NT) controls, Association, 2013). Due to the large variability in the clinical indicating an exaggerated, hyperplastic, response to patterned phenotype of ASD and manifestation of symptoms over a cortical stimulation. Additionally (Oberman et al., 2014), cTBS range of ages in childhood, a clinical diagnosis of ASD can measures of plasticity among children and adolescents with be challenging and is often not made until 3–5 years of age. HF-ASD demonstrate a positive linear relationship between age For this reason, a neurophysiologic ASD biomarker is highly and the extent of cTBS-induced modulation. These findings desirable, particularly for improving diagnostic specificity reveal an age-related increase in LTD-like plasticity in childhood and for enabling metrics of therapeutic target-engagement and adolescence. and outcomes. We now extend the scope of previous cTBS studies in Aberrant synaptic plasticity in patients with ASD can be 10–16 years old children with high-functioning ASD addressing measured in vivo at the circuit level by transcranial magnetic two questions: (1) are cTBS aftereffects different between stimulation (TMS; Huang et al., 2005; Hallett, 2007; Pascual- ASD and typically developing (TD) groups? (i.e., is the cTBS Leone et al., 2011). TMS enables focal noninvasive brain biomarker adequate to distinguish children and adolescents stimulation by electromagnetic induction (Barker et al., 1985; with HF-ASD from age-matched TD controls?); and (2) does Kobayashi and Pascual-Leone, 2003; Hallett, 2007), to evoke or the developmental trajectory of cortical plasticity, as measured modulate neural activity in a given brain region or network by cTBS aftereffects, differ between the two groups? (i.e., is (Valero-Cabré et al., 2017). When the recommended guidelines there cortical dysmaturity in children with HF-ASD associated are followed (Rossi et al., 2009; Rossini et al., 2015), TMS is with delayed or aberrant maturation of LTD-like plasticity safe and well-tolerated, even in pediatric populations (Garvey as measured by cTBS?). We also conduct pilot analysis on and Gilbert, 2004; Rajapakse and Kirton, 2013; Hameed a subset of the ASD group, to test whether cTBS measures et al., 2017). TMS, when combined with electromyography of plasticity were affected by a common single-nucleotide (EMG), electroencephalography (EEG), or neuroimaging such polymorphism (SNP) in the brain-derived neurotrophic factor as functional magnetic resonance imaging (fMRI) can quantify (BDNF) gene, Val66Met, which has influences on rTMS the extent of modulation of cortical reactivity induced by an measures of cortical plasticity in healthy subjects (Cheeran et al., intervention, providing an index of brain plasticity (Pascual- 2008; Antal et al., 2010; Lee et al., 2013; Chang et al., 2014; Leone et al., 2011). Di Lazzaro et al., 2015; Fried et al., 2017; Jannati et al., 2017; Patterned repetitive TMS (rTMS) protocols in humans Jannati et al., 2019). approximate experimental protocols that predictably induce long-term depression (LTD) and long-term potentiation (LTP) of synaptic strength in animal models (Huang et al., 2005, 2008). MATERIALS AND METHODS A form of rTMS termed continuous theta-burst stimulation (cTBS) consists of 50 Hz bursts of three TMS pulses repeated Participants at 5 Hz for a total of 600 pulses over 40 s (Huang et al., Twenty-nine individuals participated in this study, which 2005). Following cTBS of the primary motor cortex (M1), the was approved by the local Institutional Review Board in average amplitude of motor evoked potentials (MEPs) induced accordance with the Declaration of Helsinki. All participants by single TMS pulses is typically reduced by 25% for up to or their parents/legal guardians provided written informed 50 min, before returning to pre-cTBS baseline (Wischnewski consent/assent prior to enrollment and received age-appropriate and Schutter, 2015). The cTBS-induced neuromodulatory effect monetary compensation in the form of a gift card upon has LTD-like characteristics (Cárdenas-Morales et al., 2011) completion. No participants endorsed TMS-specific and involves mechanisms of GABAergic and glutamatergic contraindications (Rossi et al., 2009), and neurological plasticity (Stagg et al., 2009; Trippe et al., 2009; Benali et al., examination was unremarkable for all participants enrolled. 2011). Thus, cTBS aftereffects provide a neurophysiologic The two study populations were as follows: (1) high-functioning index of the mechanism of LTD-like cortical plasticity that is children with idiopathic ASD (n = 11; ASD group); and Frontiers in Integrative Neuroscience | www.frontiersin.org 2 March 2020 | Volume 14 | Article 13 Jannati et al. cTBS in Children With ASD (2) neurotypical age- and gender-matched controls (n = 18; chain reaction (PCR) amplification and a pair of fluorescent dye TD group). The TD group were originally recruited as detectors that target the SNP. One fluorescent dye is attached part of a separate and unrelated study, and not for the to the detector that is a perfect match to the first allele and purpose of comparing cTBS responses between TD and a different fluorescent dye is attached to the detector that is a ASD children. Participants were recruited through local perfect match to the second allele. During PCR, the polymerase community advertisements, and local autism associations releases the fluorescent probe into solution where it is detected and clinics. All participants in the ASD group carried a using endpoint analysis in an Applied Biosystems Inc. (Foster prior clinical diagnosis made by a psychiatrist or clinical City, CA, USA) 7900HT Real-Time instrument. Primers and psychologist, met diagnostic criteria for ASD as defined by probes were also obtained through Applied Biosystems. the Diagnostic and Statistical Manual of Mental Disorders, 5th Because DNA samples were not available for the TD group, edition (DSM-5© ; American Psychiatric Association, 2013), and a difference in rs6265 SNP prevalence in the ASD and and underwent independent neuropsychological assessment TD groups could give rise to a difference in cTBS responses via the Autism Diagnostic Observation Schedule (ADOS; exhibited by the two groups, we estimated the probability mean score = 10.82; SD = 3.28). Participants in the ASD that two hypothetical ASD and TD groups with sample sizes group underwent a comprehensive neurological exam by a of 11 and 18, respectively, would have significantly different board-certified pediatric neurologist (Alexander Rotenberg, BDNF Met−:Met+ ratios. The minor allele frequency of the study M.D.) to confirm the absence of impaired gross or rs6265 SNP in the admixed American population in The 1000 fine motor function. Participants in the TD group had no Genomes Project Consortium et al. (2015) is approximately neurological or psychological disorder. Lastly, all participants 0.153, which translates to 71.79%, 25.88%, and 2.33% for were screened following published recommendations endorsed the prevalence of BDNF Val/Val, Val/Met, and Met/Met by the International Federation of Clinical Neurophysiology (see genotypes, respectively. Based on a 0.718:0.282 prevalence ratio Table 1 for detailed demographic information). of Met−:Met+ genotypes, we then conducted separate Monte Carlo simulations (Rubinstein and Kroese, 2016), each with Neuropsychological Testing 10,000 iterations, to estimate the probability that either 1, 2, The ADOS (Lord et al., 2000), and the Abbreviated Battery of . . ., or 11 subjects in the ASD group, and either 1, 2, . . ., or Stanford–Binet IV intelligence scale (Thorndike et al., 1986) were 18 subjects in the TD group would have a BDNF Met− genotype. completed for the ASD group. IQ scores were obtained prior to We then conducted separate Fisher’s exact tests for all possible enrollment only for children with ASD to ensure patients with combinations of numbers of BDNF Met− subjects in the two intellectual disability or low-functioning ASD were excluded groups and identified the scenarios in which the Met−:Met+ from enrollment. IQ testing was not performed for TD children, ratio would be significantly different between the two groups. For with the assumption that the IQ of TD children falls within the each of those scenarios, we then calculated the joint probability of normal limits of the general pediatric population. the two relevant events in the two groups. Finally, we summated We limited the enrollment of our ASD participants to HF the probabilities of all those mutually exclusive scenarios to children for two reasons: (1) lack of established feasibility of obtain an estimate of the overall probability that two groups TMS/cTBS procedures in children with LF ASD; and (2) to of 11 and 18 subjects randomly sampled from the admixed reduce the heterogeneity of our pool of children with ASD, American population would be significantly different from one which are by nature, a heterogeneous population. As such, the another in BDNF Met−:Met+ ratio. findings reported in this study may be specific only to children and adolescents with HF-ASD. Transcranial Magnetic Stimulation Genetic Testing Participants were seated in a comfortable reclining chair with Saliva samples from participants in the ASD group (n = 8) the right arm and hand in a natural pronated position. They were used to assess BDNF Val66Met SNP. The remaining three were instructed to keep their right hand as still and relaxed as participants in the ASD group did not provide consent for DNA possible throughout the experiment. They were also monitored sampling and were thus not included in this subset. for drowsiness and were asked to keep their eyes open during the Aliquot (700 µl) extraction of genomic DNA was performed TMS application. on saliva samples collected using the Oragene Discover OGR-250 All TMS procedures followed the recommended guidelines Kit (DNA Genotek Inc., Ottawa, ON, Canada). DNA was endorsed by the International Federation of Clinical extracted from samples using standard methodology and the Neurophysiology (Rossi et al., 2009; Rossini et al., 2015). prepIT•L2P reagent (DNA Genotek Inc, 2015). The following Single TMS pulses and cTBS were applied to the left M1 at quality control metrics were performed on each sample: 120% of individual resting motor threshold (RMT) and 80% of PicoGreen fluorometry for double-stranded DNA quantification, active motor threshold (AMT), respectively, as biphasic pulses Nanodrop spectrophotometry as an estimate of sample purity with an anteroposterior–posteroanterior (AP-PA) induced using A260/A280 ratios and agarose gel electrophoresis for current direction in the brain. All stimulation was delivered visualization of DNA integrity. using a hand-held figure-of-eight coil (outer diameter: 70 mm) The rs6265 SNP of the BDNF gene was analyzed using a attached to a Magstim Rapid2 Plus1 (Magstim Company Limited, TaqMan single-tube genotyping assay, which uses polymerase Whitland, UK) stimulator. Frontiers in Integrative Neuroscience | www.frontiersin.org 3 March 2020 | Volume 14 | Article 13 Frontiers in Integrative Neuroscience | www.frontiersin.org Jannati et al. TABLE 1 | Demographics, neuropsychological measures, and medications for individual participants. Group Participant No. Age IQ BDNF Neuroactive medication Comorbidities ADOS score ASD M = 13.09 M = 103.55 4 Val/Val; 10 Yes; 9 Yes; M = 10.82 (n = 11) (SD = 1.97) (SD = 12.43) 4 Val/Met 1 None 2 None (SD = 3.28) AS1 10–15 106 Val/Val Dexmethylphenidate; Sertraline ADHD; Anxiety 11 AS2 10–15 82 Val/Val None None 13 AS3 10–15 100 Val/Met Flouxetine Depression 15 AS4 10–15 100 Val/Met Adderall ADHD; Asthma 7 AS5 10–15 121 Val/Val Clonidine; Melatonin; Sertraline Anxiety; Depression; 10 Asthma AS6 10–15 100 Val/Met Dexmethylphenidate; Melatonin; Anxiety; Depression 9 Fluoxetine AS7 10–15 100 Val/Met Clonidine; Methylphenidate ADHD 10 AS8 15–20 124 Val/Val Melatonin; Methylphenidate ADHD; PTSD; Asthma 16 AS9 10–15 91 - Melatonin None 14 AS10 10–15 100 - Flouxetine; Thyroid tablets Depression; 7 Hypothyroidism AS11 10–15 115 - Dexmethylphenidate ADHD 7 TD M = 13.44 0 Yes; 0 Yes; - (n = 18) (SD = 1.85) 18 None 18 None 4 TD1 10–15 None None N/A TD2 15–20 None None N/A TD3 10–15 None None N/A TD4 10–15 None None N/A TD5 10–15 None None N/A TD6 10–15 None None N/A TD7 15–20 None None N/A TD8 10–15 None None N/A TD9 10–15 None None N/A TD10 15–20 None None N/A TD11 10–15 None None N/A TD12 10–15 None None N/A TD13 10–15 None None N/A TD14 10–15 None None N/A March 2020 | Volume 14 | Article 13 TD15 10–15 None None N/A TD16 10–15 None None N/A TD17 10–15 None None N/A TD18 15–20 None None N/A cTBS in Children With ASD Group averages are presented as means and standard deviations (in parentheses). IQ scores were estimated using the Abbreviated Battery of Stanford-Binet IV intelligence scale. IQ, BDNF, and handedness data were not available for the TD group. Age range (instead of individual age) and no individual gender information are provided to avoid the possibility of publishing personally identifiable data. Three participants in the ASD group did not complete BDNF genotyping. ADHD; attention-deficit/hyperactivity disorder; ADOS, Autism Diagnostic Observation Schedule; ASD, autism spectrum disorder; BDNF, brain- derived neurotrophic factor; Met, metionine; PTSD, posttraumatic stress disorder; TD, typically developing; Val, Valine. Jannati et al. cTBS in Children With ASD The coil was held tangentially to the participant’s head in at least five of 10 pulses with the FDI slightly contracted. surface, with the handle pointing occipitally and positioned Live EMG was monitored during the AMT assessment to at 45◦ relative to the mid-sagittal axis of the participant’s ensure consistent contraction between ∼100–200 µV. After head. The optimal spot for the maximal TMS-induced motor a 5-min break, during which participants were instructed to responses of the right first dorsal interosseous (FDI) muscle maintain hand relaxation to control the effects of voluntary (‘‘motor hotspot’’) was localized. A Polaris infrared-optical hand movements on cTBS responses (Iezzi et al., 2008), cTBS tracking system (Northern Digital Inc., Waterloo, ON, Canada) was applied as 200 bursts of three pulses at 50 Hz, repeated at and a frameless stereotactic neuronavigation system (Brainsight, 200-ms intervals for 40 s (for a total of 600 pulses). Cortico- Rogue Research Inc., Montreal, QC, Canada) with a brain MRI motor reactivity was reassessed at 5, 10, 20, 30, 40, 50, and 60 min template were used to ensure consistent targeting throughout post-cTBS (T5–T60). the experiment. Each participant’s head was registered to the MRI template using defined cranial landmarks to ensure the coil Statistical Analyses position and orientation was consistent with the MRI template Study data were collected and managed using Research (Ruohonen and Karhu, 2010). Electronic Data Capture (REDCap) electronic data capture tools Surface EMG electrodes were placed over the FDI belly hosted at Beth Israel Deaconess Medical Center (Harris et al., (negative) and the first interphalangeal joint of the second finger 2009, 2019). MATLAB R2016b (The MathWorks, Natick, MA, (positive). The ground electrode was placed over the ipsilateral USA) and Stata 13.1 (StataCorp., College Station, TX, USA) were ulnar styloid process. The TMS system delivered triggered pulses used for data analyses and simulations. G∗ Power 3.1.9 (Faul et al., that synchronized the TMS and EMG systems. 2007) was used for power and sample-size calculations. At the start of each TMS session the FDI motor hotspot was Data from each TMS visit included: (a) RMT and AMT, located per patient and individual RMT, defined as the lowest expressed as percentage of maximum stimulator output (MSO); stimulation intensity necessary to elicit an MEP of ≥50 µV in at (b) baseline MEP amplitude, calculated as the average of baseline least five of 10 pulses from the relaxed right FDI, was obtained. MEP amplitude in three blocks of 30 single TMS pulses; and To assess pre-cTBS cortico-motor reactivity, three blocks of (c) percent change in the average amplitude of 30 MEPs at 30 single TMS pulses in the ASD group, and two blocks of T5–T60 relative to baseline (%∆) for each participant. 20 single TMS pulses in the TD group, were applied to M1 with The Shapiro–Wilk found significant deviations in MEP a 5–10-min inter-block interval, at a random 4–6-s inter-pulse amplitudes from the normal distribution. Thus, we first baseline- interval, as done in previous studies (Pechmann et al., 2012; corrected each post-cTBS amplitude by dividing it by the Gomes-Osman and Field-Fote, 2015; Davila-Pérez et al., 2018). average baseline MEP amplitude in that individual participant. The different number of single TMS pulses administered We then natural log-transformed the baseline-corrected MEP at baseline (90 vs. 40) and in each post-cTBS block (30 vs. amplitudes at each post-cTBS time point (∆MEP, Nielsen, 20) in the two groups was due to site-specific approval of 1996a,b; Pasqualetti and Ferreri, 2011) and averaged them the experimental protocol utilized at each research site. This over participants separately for each group. The following difference was unlikely, however, to give rise to differing baseline measures were also calculated: maximum suppression of MEPs MEP amplitude estimates between the two groups, as recent during 60 min post-cTBS (∆MEPMax ) and the signed area- studies have found applying at least 20 single TMS pulses yields a under-the-curve (AUC) of ∆MEPs over T5–T10, T5–T20,. . ., reliable estimate of MEP amplitude at a given time point (Chang and T5–T60 intervals. To calculate the ∆MEPMax for each et al., 2016; Goldsworthy et al., 2016). In each block, individual participant, we chose the post-cTBS block (T5–T60) in which MEPs >2.5 SD from the mean were excluded. The mean (±SD) the ∆MEP showed the maximum suppression relative to the number of MEPs in total excluded from all blocks in each subject baseline MEP amplitude. Cumulative AUCs of the ∆MEPs was 4.63 (± 1.6) and 2.22 (±1.4) in the ASD and TD groups, enable numerical integration of cTBS-induced changes in MEP respectively. This means that even in occasional post-cTBS blocks amplitude over successively larger intervals following cTBS. Such in the ASD group in which one (or, rarely, two) MEPs were measures are more robust to the large inter-and intra-individual excluded, there were 19 (or, rarely, 18) pulses remaining in each variability of MEP amplitudes typically observed at individual block, which has been shown to yield estimates of MEP amplitude time points post-cTBS (López-Alonso et al., 2014; Vernet et al., with excellent internal consistency (Chang et al., 2016). To ensure 2014; Vallence et al., 2015; Hordacre et al., 2017; Jannati et al., hand relaxation was maintained throughout the experiment, 2017, 2019) and can be advantageous in studies with smaller real-time EMG was monitored to ensure the pre-TMS EMG sample sizes. activity did not exceed ∼100 µV, which is the amplitude typically Grand-average values for all cTBS measures were calculated considered to be discernible activity from background EMG separately for each time point in each group and were compared (Stinear and Byblow, 2002; Sartori et al., 2013; Benussi et al., between the two groups using independent-samples t-tests. 2018). Participants were also monitored for drowsiness and Similar analyses were conducted for the two small BDNF were asked to keep their eyes open for the duration of the subgroups (n = 4 per subgroup) of the ASD group. We conducted stimulation session. a sample-size analysis based on the preliminary results from the Baseline MEP amplitude was calculated as the average of the BDNF subgroups in order to estimate the number of participants peak-to-peak amplitude of MEPs in the three blocks. AMT was per BDNF subgroup required to detect a significant difference then assessed as the lowest intensity that elicited MEPs ≥200 µV between the cumulative AUC measures of cTBS aftereffects Frontiers in Integrative Neuroscience | www.frontiersin.org 5 March 2020 | Volume 14 | Article 13 Jannati et al. cTBS in Children With ASD over each interval. Comparisons of proportions were conducted in mood, or to report any other change or side effect they using Fisher’s exact test. Pearson product-moment correlation experienced. The experimenter also noted whether the coefficient was used to assess the relationship between ∆MEPMax participant experienced a syncopal event or seizure. If the and age in each group. All analyses were two-tailed, and α and β participant reported any side effects following the stimulation, levels were set to 0.05 and 0.80, respectively. False discovery rate the severity and duration were documented. (FDR; Benjamini and Yekutieli, 2001) was used to adjust the P- values for multiple testing. RESULTS To obtain a rough estimate on the extent to which our small sample sizes—combined with the interindividual variability of The ASD and TD groups were comparable in age and sex ratio MEP changes in response to cTBS—resulted in reduced power, (P-values > 0.61). Demographics, neuropsychological measures, we conducted a post hoc power calculation for the whole and medications for individual participants are presented in sample over each post-cTBS interval (but see Hoenig and Table 1. Heisey, 2001 for the limited usefulness of this approach) and a pre-hoc sample-size calculation for the analyses comparing cTBS cTBS Is Safe and Tolerable in Children responses in the two BDNF subgroups of the ASD group. All participants tolerated cTBS and single-pulse stimulation To control for the number of pre- and post-cTBS MEPs in without any serious adverse event. One participant reported the two groups, we selected a subset of data from the ASD group mild scalp irritation (on the forehead underneath the headband such that both the number of baseline MEPs and the number of holding the subject tracker of the neuronavigation system), MEPs in each post-cTBS block included in the analysis would which was resolved quickly without medication. No other be equal in the two groups. Out of the 90 baseline MEPs, we adverse events were reported. selected the last 40 MEPs before cTBS to calculate the baseline MEP amplitude for each subject in the ASD group. We also cTBS Measures of Plasticity Differentiate selected the 20 MEPs out of 30 MEPs in each post-cTBS block Between ASD and TD Children that centered around the time point of interest (10, 20,. . ., The difference in cumulative AUC measures of cTBS aftereffects and 60 min post-cTBS), and then log-transformed the baseline- between the two groups was significant over all the intervals corrected MEPs and recalculated the cumulative AUC measures (PFDR ’s < 0.03), indicating greater facilitatory response to cTBS of cTBS aftereffects for the ASD group. To account for the in the ASD group relative to the TD group. Post-cTBS data from occasional MEP amplitudes excluded from each block in the TD one participant in the ASD group were not obtained beyond group that was >2.5 SD, we continued to exclude any MEP that T10 due to technical difficulties. Grand-average ∆MEPs at had been excluded from each block in the original, larger ASD individual post-cTBS time points in the two groups are presented dataset. Finally, we compared those cumulative measures of cTBS in Figure 1A. Cumulative AUCs of the ∆MEPs and their aftereffects with the corresponding measures in the TD group, as 95% confidence intervals (CI) over T5–T10, T5–T20,. . ., and described above. T5–T60 intervals for the two groups are presented in Figure 1B. Even though our post-cTBS MEP measures are already The baseline MEP amplitude (mean ± SD) in the ASD group, baseline-corrected, it is still possible that a difference in the 0.37 mV ± 0.27, was significantly smaller than in the TD group, absolute baseline MEP amplitude between the two groups 1.19 mV ± 0.41, t (27) = 5.96, P < 0.001. The largest ASD and contributes to a difference in cTBS aftereffects. Because, as TD subgroups that would have a comparable baseline MEP reported below, we found a significant difference in baseline MEP amplitude consist of only five participants per subgroup. The amplitude between the two groups, we set out to create the largest baseline MEP amplitude [mean ± (SD)] in the two resulting ASD and TD subgroups that would have comparable baseline subgroups with n = 5 are comparable: 0.62 mV (±0.17) in MEP amplitude, and then compared the cTBS aftereffects the ASD subgroup and 0.72 mV (±0.17) in the TD subgroup, between those subgroups. t (8) = 0.91, P = 0.39. There is no significant difference in Because several subjects in the ASD group had comorbid cumulative AUC ∆MEP measures between the two subgroups attention-deficit/hyperactivity disorder (ADHD; Table 1), and over any of the post-cTBS intervals (P-values > 0.58). in pediatric ADHD there is impaired GABA-mediated plasticity The effect sizes based on the difference in cumulative as measured by paired-pulse TMS (Dutra et al., 2016; Gilbert AUC measure of cTBS aftereffects between the ASD and TD et al., 2019), we repeated the calculation of cumulative AUC groups over T5–T10, T5–T20,. . ., and T5–T60 intervals are measures of cTBS aftereffects and their comparison between the 0.85, 0.84, 0.79, 0.70, 0.65, and 0.65, respectively. Assuming ASD and TD groups after excluding the five ASD subjects with a two-tailed, independent-samples t-tests with α = 0.05, the post documented clinical diagnosis of ADHD. hoc power to detect a significant difference between the two groups are estimated as 57.2%, 56.2%, 51.2%, 42.2%, 37.4%, and Side-Effect Monitoring 37.4%, respectively. Immediately following the TMS session, a side-effects The Monte Carlo simulations find in a group of 11 subjects, questionnaire was completed by the experimenter. Participants the estimated probability that either 1, 2,. . ., or 11 subjects would were asked to report whether they experienced any of the have a BDNF Met—genotype is < 0.0001, 0.0002, 0.003, 0.012, following side effects: headache, neck pain, scalp pain or 0.043, 0.115, 0.198, 0.266, 0.218, 0.113, and 0.027, respectively. irritation, difficulty hearing, thinking or concentrating, change In a group of 18 subjects, the estimated probability that either Frontiers in Integrative Neuroscience | www.frontiersin.org 6 March 2020 | Volume 14 | Article 13 Jannati et al. cTBS in Children With ASD FIGURE 1 | (A) Individual and grand-average change from baseline in MEP amplitude recorded from the right FDI muscle at 5–60 min following cTBS of the left motor cortex in ASD and TD groups. Error bars represent standard error of the mean. (B) Cumulative AUCs of the ∆MEPs and their 95% CI over T5–T10, T5–T20, . . ., and T5–T60 intervals for the two groups (the end time-point of each interval is labeled on the abscissa). The cumulative AUC measures were significantly more positive in the ASD group than in the TD group over all the T5–T10 to T5–T60 intervals (PFDR ’s < 0.03). ASD, autism spectrum disorder; AUC, area-under-the-curve; CI, confidence interval; cTBS, continuous theta-burst stimulation; ∆MEP, natural log-transformed, baseline-corrected amplitude of motor evoked potentials; FDI, first dorsal interosseous; FDR, false discovery rate; MEP, motor evoked potential; TD, typically developing; Tm–Tn, over m to n minutes following cTBS. 1, 2,. . ., or 18 subjects would have a BDNF Met—genotype The relationship between age and the maximum cTBS-induced is <0.0001 (for 1–5 such subjects), 0.001, 0.003, 0.010, 0.031, suppression of MEPs (∆MEPMax ) during the first 60 min 0.064, 0.120, 0.177, 0.208, 0.185, 0.127, 0.062, 0.019, and 0.002, post-cTBS in the two groups are illustrated in Figure 2. respectively. After summating the probability of all scenarios in which a two-tailed Fisher’s exact test would find a significant BDNF and cTBS Measures of Plasticity in difference in BDNF Met−:Met+ ratio between the ASD and TD ASD groups, we obtain an overall probability of 0.0426. The difference in cumulative AUC measures of cTBS aftereffects After equalizing the number of pre- and post-cTBS MEPs between the two BDNF subgroups (Val/Val and Val/Met) of in the two groups, the cumulative AUC measures of cTBS the ASD group is not statistically significant (P-values > 0.08). aftereffects do not change substantially compared to the Grand-average ∆MEPs at individual post-cTBS time points in measures obtained with the complete ASD dataset. The mean the two BDNF subgroups are presented in Figure 3A. Cumulative (±SD) cumulative AUC of ∆MEP over T5–T10, T5–T20,. . ., AUCs of the ∆MEPs and their 95% CI over T0–T10, T0–T20, . . ., and T5–T60 intervals in this subset of data from the ASD and T0–T60 intervals for the two BDNF subgroups are presented group is 0.085 (±0.24), 0.18 (±0.45), 0.22 (±0.67), 0.24 (±0.80), in Figure 3B. 0.20 (± 0.92), and 0.14 (±1.06), respectively. These measures Based on the results from eight participants with available remain significantly more facilitatory in the ASD group than BDNF data, the effect size based on the difference in cumulative in the TD group over all the intervals from T5–T10 to T5–T50 AUC measure of cTBS aftereffects over each interval ranges (PFDR ’s < 0.047), but not over T5–T60 (PFDR = 0.053). from 0.78 to 0.87. Assuming a 1:1 ratio between the two After excluding the five subjects in the ASD group who subgroups, the sample size in each BDNF subgroup required had comorbid ADHD, the cumulative AUC measures of to detect those effect sizes with 80% power ranges from cTBS aftereffects remain significantly more facilitatory in the 27 to 22, respectively. ASD group compared to the TD group over all intervals (PFDR ’s < 0.001). DISCUSSION cTBS Aftereffects Have a Developmental We find, considering the caveats and confounders discussed Trajectory in Children with ASD below, the responses to M1 cTBS can differentiate between ∆MEPMax is correlated with age in the ASD group (r = –0.67, 10–16 years old children with HF-ASD and their age-, gender, P = 0.025), but not in the TD group (r = –0.12, P = 0.65). and IQ-matched TD children. This is due to more-facilitatory Frontiers in Integrative Neuroscience | www.frontiersin.org 7 March 2020 | Volume 14 | Article 13 Jannati et al. cTBS in Children With ASD FIGURE 2 | The relationship between the maximum cTBS-induced suppression in the natural log-transformed, baseline-corrected MEP amplitude (Max. MEP suppression) and age in ASD (A) and TD (B) groups. Max. MEP suppression was negatively correlated with age in the ASD group (r = –0.67, P = 0.025), but not in the TD group (r = –0.12, P = 0.65). Dashed lines represent the slopes of the linear regression fit. ASD, autism spectrum disorder; cTBS, continuous theta-burst stimulation; MEP, motor evoked potential; TD, typically developing. FIGURE 3 | (A) Changes in individual and grand-average MEPs recorded from the right FDI muscle at 5–60 min following cTBS of the left primary motor cortex in BDNF Met− (Val/Val) and Met+ (Val/Met) subgroups of participants with ASD. Error bars represent standard error of the mean. (B) Cumulative AUCs of the ∆MEPs and their 95% CI over T5–T10, T5–T20, . . ., and T5–T60 intervals for the two BDNF subgroups (the end time-point of each interval is labeled on the abscissa). The cumulative AUC measures were not significantly different between the two BDNF subgroups over any of the intervals (P-values > 0.18). ASD, autism spectrum disorder; AUC, area-under-the-curve; BDNF, brain-derived neurotrophic factor; CI, confidence interval; cTBS, continuous theta-burst stimulation; ∆MEP, natural log-transformed, baseline-corrected amplitude of motor evoked potentials; FDI, first dorsal interosseous; FDR, false discovery rate; MEP, motor evoked potential; Met, methionine; TD, typically developing; Tm–Tn, over m to n minutes following cTBS; Val, valine. cTBS aftereffects in MEPs in the ASD group relative to the maximum cTBS-induced suppression of MEPs in the ASD TD group. We argue this difference is not likely to be due group, but not in the TD group, suggesting a dysmaturity in to potential confounds such as differences in the number LTD-like plasticity in children with ASD. These results indicate of pre- and post-cTBS MEPs, BDNF Val66Met SNP, ADHD the importance of further investigations of the utility of M1 cTBS comorbidity, or neuroactive medications between the two as a potential physiologic biomarker for children and adolescents groups. Moreover, we report an age-related increase in the with HF-ASD. Frontiers in Integrative Neuroscience | www.frontiersin.org 8 March 2020 | Volume 14 | Article 13 Jannati et al. cTBS in Children With ASD TMS Safety and Tolerability in Children that employ other TMS-derived biomarkers. For instance, All participants tolerated the stimulation, and only one GABAA ergic activity, as measured by short-interval intracortical participant reported a minor scalp irritation that resolved quickly cortical inhibition (SICI), was associated with a delay in language without medication. The present study adds to the growing acquisition in adults with ASD (Enticott et al., 2013). literature documenting the safety and tolerability of rTMS in children and in individuals with ASD (Garvey and Gilbert, 2004; Frye et al., 2008; Croarkin et al., 2011; Oberman et al., 2012, 2014, Present and Anticipated Confounders 2016; Wu et al., 2012; Rajapakse and Kirton, 2013; Hong et al., Although the post-cTBS measures reported in the present study 2015; Pedapati et al., 2015; Hameed et al., 2017). are already adjusted for baseline MEP amplitude at the individual level, it is possible that a difference in the baseline MEP amplitude cTBS as a Biomarker for Children and at the group level contributes to the observed differences in Adolescents With ASD cTBS aftereffects between ASD and TD groups. The finding We find that the pattern of cTBS aftereffects during the first that the baseline MEP amplitude is significantly smaller in 60 min post-cTBS successfully differentiates between the ASD the ASD group than in the TD group can be either due to and TD groups. Namely, the ASD group shows significantly more chance because of the small sample sizes or because of a real facilitatory responses to cTBS than the TD group throughout the difference in input-output characteristics of MEPs in the two assessed post-cTBS interval (Figure 1). Notably, this pattern of groups (Goetz et al., 2014). Because the largest ASD and TD results is not driven by one or two particular post-cTBS time subgroups with a comparable baseline MEP amplitude consist points, which can be prone to the large inter- and intra-individual of only five participants, the present sample does not allow for variability in cTBS responses observed in adults (López-Alonso a robust assessment of the effect of group-level baseline MEP et al., 2014; Vernet et al., 2014; Vallence et al., 2015; Hordacre amplitude on cTBS aftereffects in the two groups. Larger samples et al., 2017; Jannati et al., 2017, 2019). in future studies aimed at comparing rTMS responses between The finding that the ASD group exhibits a distinct pattern of ASD and control populations can address this limitation by cTBS from their TD counterparts indicates the potential utility ensuring comparable baseline MEP amplitudes at the group level of M1 cTBS as a biomarker for children and adolescents with between the two groups. HF-ASD. Moreover, considering the involvement of GABAergic Our analysis controlling for the number of baseline and synaptic transmission in cTBS aftereffects (Stagg et al., 2009; post-cTBS MEPs shows that the differences in cumulative Trippe et al., 2009), the facilitatory (rather than inhibitory) measures of cTBS aftereffects, at least from T5–T10 to T5–T50, responses to cTBS in the ASD group further supports the are not due to differences in the number of baseline MEPs (90 vs. notion of GABAergic dysfunction in ASD (LeBlanc and Fagiolini, 40) or the number of MEPs in each post-cTBS block (30 vs. 20) 2011; Ben-Ari et al., 2012; Coghlan et al., 2012). The effect of between the ASD and TD groups. GABAergic transmission during typical development shifts from One issue that needs to be considered in comparing cTBS excitatory to inhibitory through sequential activation of chloride responses between the ASD and TD groups is the potential effects (Cl− ) cotransporters NKCC1 and KCC2 and via age-dependent of neuroactive medications on cTBS responses. It is plausible that reduction of intracellular Cl− concentration (Yamada et al., 2004; at least some of those medications influence the pattern of cTBS Ben-Ari et al., 2007). Rodent ASD models indicate a delayed aftereffects in ASD participants and thus the difference between shift of GABA activity from excitatory to inhibitory, which can the two groups. There is, however, considerable variability in be restored behaviorally and electrophysiologically by in utero the type of those medications received by our ASD participants, administration of the NKCC1 inhibitor bumetanide (Tyzio et al., which makes it unlikely that all or a majority of them have 2014). Similarly, bumetanide treatment may mitigate core ASD a similar effect on the plasticity mechanisms indexed by cTBS symptoms in children and adolescents (Lemonnier et al., 2017). aftereffects. To maintain the external validity of the findings of We thus suggest that cTBS measures of M1 plasticity in ASD can studies aimed at developing biomarkers or therapeutics for the be used to assess baseline cortico-motor reactivity, probe-target ASD population, it is necessary to include patients who are under engagement, and monitor therapeutic response to experimental treatment by neuroactive medications prescribed for common pharmacotherapy (e.g., bumetanide; Lemonnier et al., 2017) comorbidities such as depression, anxiety, and ADHD. and, potentially, future rTMS treatments for ASD (Cole et al., Another issue in comparing cTBS responses between the 2019). Moreover, differential cTBS responses within the pediatric ASD and TD groups is the possibility that there is a significant ASD population can form the physiologic basis for a clinical difference in BDNF Met−:Met+ ratio between the two groups. endophenotype that improves classification and understanding Such difference can give rise to an observed difference in cTBS of the pathophysiology of ASD. responses between the two groups that are not necessarily The more-facilitatory response to cTBS in the ASD group associated with an ASD diagnosis but with the composition of relative to the TD group is consistent with the results of previous BDNF genotypes in the two groups. Our simulations, however, studies that have found impaired LTP-like changes in MEPs in do not find such a possibility to be very likely in the present individuals with ASD by paired associative stimulation (PAS; study. We find, assuming random sampling from the admixed Jung et al., 2013) and iTBS (Oberman et al., 2012; Pedapati American population, there is a ∼4.3% chance that two groups et al., 2016). Given that cTBS also likely engages GABAergic of 11 and 18 subjects are significantly different from one another mechanisms, our results are also consistent with related findings in the BDNF Met−:Met+ ratio. Frontiers in Integrative Neuroscience | www.frontiersin.org 9 March 2020 | Volume 14 | Article 13 Jannati et al. cTBS in Children With ASD Potential confound due to psychiatric comorbidities in the to overcome, or control for, some of these factors. Another ASD group is another factor that can mediate the difference important reason for replicating the present findings is to assess in cTBS responses between the two groups. One common the test-retest reliability of M1 cTBS aftereffects in both HF-ASD comorbidity in ASD is ADHD (Craig et al., 2015), in which and TD children. This is underscored by the recent findings in abnormal GABA-mediated plasticity measured by paired-pulse healthy adults that indicate low-to-moderate reliability of most TMS has been observed (Dutra et al., 2016; Gilbert et al., cTBS aftereffects (Jannati et al., 2019). 2019). After excluding five subjects in the ASD group with Regarding potential selection and outcome biases in documented ADHD comorbidity, we still find significantly recruiting the participants in the TD group, it should be greater cumulative facilitatory aftereffects of cTBS in the ASD- noted that because the TD subjects were recruited as part of an without-ADHD subgroup than in the TD group across all unrelated study—and not for the purpose of comparing their post-cTBS intervals. These results show that the observed cTBS responses with those of ASD children—such biases did not differences between the whole ASD group and the TD group play a role in recruiting the TD subjects. cannot not be due to the effects of ADHD comorbidity on cTBS responses. In general, nonetheless, in studies comparing Developmental Trajectory of cTBS plasticity responses of ASD and control populations, the Responses in ASD potential effects of common psychiatric comorbidities such as Consistent with the previously reported age-related increase depression, anxiety, and ADHD on TMS measures of plasticity, in the duration of cTBS-induced modulation in children and should be considered. adolescents with ASD (Oberman et al., 2014), we find an Interestingly, the overall pattern of cTBS responses in the ASD age-related increase in the maximum cTBS-induced suppression group in the present study is not necessarily what one would of MEP during 60 min post-cTBS in the ASD group, but not expect based on previous results. Namely, a previous cTBS study in the TD group. Namely, older participants with ASD tend to from our group (Oberman et al., 2014) found only one-third of exhibit greater cTBS-induced LTD-like plasticity than younger children and adolescents with ASD showed facilitatory responses participants with ASD, whereas there is no such developmental to cTBS. This difference in results can be due to several factors: trajectory in the TD group (at least in the age range of 11–16). Caution should be exercised in interpreting these correlations, (1) The large inter-individual variability in response to cTBS however, because of the short dynamic range of age in the among healthy adults is now well-established (Hamada et al., two groups. Assuming these results are confirmed in larger 2013; Goldsworthy et al., 2014; López-Alonso et al., 2014; studies in the future and over wider age ranges, they suggest Nettekoven et al., 2015; Vallence et al., 2015; Hordacre et al., a dysmaturity in LTD-like plasticity as measured by cTBS in 2017; Jannati et al., 2017). A similar degree of variability in children with ASD, perhaps arising from a dysfunction in cTBS responses in TD children and among clinical pediatric the shift of GABAergic activity from excitatory to inhibitory. populations such as children with ASD is reasonable to Since GABAA -receptor activity is involved in generating the expect. By mere virtue of random sampling from a large cTBS aftereffects, such dysfunction would cause the ASD spectrum of responses, such variability can give rise to participants to achieve greater inhibitory cTBS responses as seemingly inconsistent results in small sample sizes that may they grow older. In contrast, because the GABAergic shift not capture the entire gamut of cTBS responses in healthy and presumably occurs earlier in TD children, they may achieve clinical populations. In fact, our post hoc power calculation greater cTBS-induced inhibition at a younger age and then for the whole sample indicates that the present study is plateau at older ages. These results hint at the utility of cTBS underpowered, especially beyond the T5–T20 interval. Larger measures of plasticity as longitudinal tools for monitoring sample sizes would perhaps have resulted in more-robust the development of cortical plasticity and/or gradual response differences, and/or over longer intervals, between the two to potential treatments among children and adolescents with groups. We thus anticipate that this power analysis will enable ASD. Because the slope of such developmental trajectory the design of future studies with larger sample sizes that are is likely to vary across individuals with ASD, a substantial required to confirm and extend the present results. number of subjects at any given age may be necessary to (2) The difference in the proportion of participants with BDNF obtain robust ‘‘growth curves’’ for cortical plasticity in pediatric Val/Met genotype, which has been shown to influence cTBS ASD populations. and other rTMS measures of neuroplasticity (Cheeran et al., 2008; Antal et al., 2010; Lee et al., 2013; Chang et al., 2014; Di BDNF Polymorphism and cTBS Lazzaro et al., 2015; Fried et al., 2017; Jannati et al., 2017, 2019) may have contributed to the different results. Aftereffects in ASD The role of BDNF Val66Met SNP in influencing rTMS plasticity (3) Differences in other demographic, neuropsychological, and measures in adults has been investigated in several studies genetic factors as well as neuroactive medications received by (Cheeran et al., 2008; Antal et al., 2010; Lee et al., 2013; the participants in the ASD group could have given rise to the Chang et al., 2014; Di Lazzaro et al., 2015; Fried et al., 2017; different patterns of cTBS response in the two studies. Jannati et al., 2017, 2019). BDNF Met carrier status is known These potential confounds underscore the need for to be associated with impaired N-Methyl-D-aspartate-(NMDA)- replication of present findings in future cTBS studies with dependent LTD (Woo et al., 2005), aberrant GABAergic synaptic large samples of children and adolescents with ASD in order transmission (Abidin et al., 2008), reduced cTBS-induced Frontiers in Integrative Neuroscience | www.frontiersin.org 10 March 2020 | Volume 14 | Article 13 Jannati et al. cTBS in Children With ASD inhibition of MEPs (Chung et al., 2016), and, in some cases, informed consent/assent prior to enrollment and received paradoxical cTBS-induced facilitation of MEPs (Gentner et al., monetary compensation upon completion. 2008; Goldsworthy et al., 2012; Hellriegel et al., 2012; Brownjohn et al., 2014; Jannati et al., 2017, 2019). In contrast with these AUTHOR CONTRIBUTIONS results, the BDNF Met+ children with ASD in the present study exhibit a numerically more-inhibitory response than the BDNF AJ, LO, AP-L, and AR conceived and designed the study. AJ, Met− children at all individual post-cTBS time points, even GB, MR, HK, FK, SB, and LO collected the data. AJ analyzed the though the difference between two subgroups is not statistically data and drafted the manuscript. AJ, AP-L, and AR interpreted significant. Because of the small sample sizes, it is difficult to infer the data. All authors revised the manuscript, approved the final whether the seemingly opposite effect of BDNF Met carrier status version, and agreed to be accountable for the content of the work. on cTBS response in children with ASD compared to adults is due to: (1) sampling error arising from small sample sizes; or (2) a FUNDING dysfunction in GABAergic shift that causes the BDNF SNP to have an opposite influence on cTBS aftereffects in children with This study was primarily funded by the National Institutes ASD compared to healthy individuals. of Health (NIH R01 MH100186). AJ was further supported by postdoctoral fellowships from the Natural Sciences and CONCLUSION Engineering Research Council of Canada (NSERC 454617) and the Canadian Institutes of Health Research (CIHR 41791). Considering the discussed limitations and potential confounders, LO was further supported by the Simons Foundation Autism cTBS-derived metrics may enable practical and safe physiologic Research Initiative (SFARI) and the Nancy Lurie Marks Family biomarkers in pediatric ASD. Given that such measures can Foundation. AP-L was further supported by the Sidney R. be applied repeatedly to individuals, our data also point to Baer Jr. Foundation, the NIH (R01 HD069776, R01 NS073601, prospects for probing developmentally regulated features of R21 MH099196, R21 NS085491, R21 HD07616), the Football cortical plasticity in ASD and perhaps other neurodevelopmental Players Health Study at Harvard University, and Harvard disorders. Because of its high tolerability by patients with Catalyst | The Harvard Clinical and Translational Science ASD, cTBS offers an opportunity to study the mechanisms and Center (NCRR and the NCATS NIH, UL1 RR025758). AR was alterations of neural plasticity in the ASD population. These further supported by the NIH (R01 NS088583), The Boston proof-of-principle findings in the motor cortex can be followed Children’s Hospital Translational Research Program, Autism in future studies through extra motor stimulation in TMS-EEG Speaks, Massachusetts Life Sciences, The Assimon Family, or similar protocols. Brainsway, CRE Medical, Eisai, Neuroelectrics, Roche, Sage Therapeutics, and Takeda Medical. The content is solely the responsibility of the authors and does not necessarily represent DATA AVAILABILITY STATEMENT the official views of Harvard Catalyst, Harvard University and its affiliated academic health care centers, the National Institutes of The datasets generated for this study are available on request to Health, or any of the other listed granting agencies. the corresponding author. ACKNOWLEDGMENTS ETHICS STATEMENT We thank the Neurodevelopmental and Behavioral Core This study was approved by the Institutional Review Boards at Boston Children’s Hospital for conducting the Autism at Boston Children’s Hospital and King Saud University, Diagnostic Observation Schedule (ADOS), and Ann Connor where the research took place, in accordance with the and Joanna Macone (Beth Israel Deaconess Medical Center) for Declaration of Helsinki. All participants provided written assistance with regulatory oversight and compliance. REFERENCES Barker, A. T., Jalinous, R., and Freeston, I. L. (1985). Non-invasive magnetic stimulation of human motor cortex. Lancet 325, 1106–1107. Abidin, I., Eysel, U. T., Lessmann, V., and Mittmann, T. (2008). 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G., Conflict of Interest: AR is a founder and advisor for Neuromotion, serves on Pitcher, J. B., and Ridding, M. C. (2015). Inter- and intra-subject the medical advisory board or has consulted for Cavion, Epihunter, Gamify, variability of motor cortex plasticity following continuous theta-burst NeuroRex, Roche, Otsuka, and is listed as an inventor on a patent related to stimulation. Neuroscience 304, 266–278. doi: 10.1016/j.neuroscience.2015. the integration of TMS and EEG. AP-L serves on the scientific advisory boards 07.043 for Neuronix, Starlab Neuroscience, Neuroelectrics, Constant Therapy, Cognito, Vernet, M., Bashir, S., Yoo, W.-K., Oberman, L. M., Mizrahi, I., Ifert-Miller, F., NovaVision, and Neosync; and is listed as an inventor on several issued and et al. (2014). Reproducibility of the effects of theta burst stimulation on motor pending patents on the real-time integration of TMS with EEG and MRI. cortical plasticity in healthy participants. Clin. Neurophysiol. 125, 320–326. doi: 10.1016/j.clinph.2013.07.004 The remaining authors declare that the research was conducted in the absence of Wischnewski, M., and Schutter, D. J. L. G. (2015). Efficacy and time course of theta any commercial or financial relationships that could be construed as a potential burst stimulation in healthy humans. Brain Stimul. 8, 685–692. doi: 10.1016/j. conflict of interest. brs.2015.03.004 Woo, N. H., Teng, H. K., Siao, C.-J., Chiaruttini, C., Pang, P. T., Milner, T. A., et al. Copyright © 2020 Jannati, Block, Ryan, Kaye, Kayarian, Bashir, Oberman, Pascual- (2005). Activation of p75NTR by proBDNF facilitates hippocampal long-term Leone and Rotenberg. This is an open-access article distributed under the terms depression. Nat. Neurosci. 8, 1069–1077. doi: 10.1038/nn1510 of the Creative Commons Attribution License (CC BY). The use, distribution or Wu, S. W., Shahana, N., Huddleston, D. A., Lewis, A. N., and Gilbert, D. L. reproduction in other forums is permitted, provided the original author(s) and the (2012). Safety and tolerability of theta-burst transcranial magnetic stimulation copyright owner(s) are credited and that the original publication in this journal in children. Dev. Med. Child Neurol. 54, 636–639. doi: 10.1111/j.1469-8749. is cited, in accordance with accepted academic practice. No use, distribution or 2012.04300.x reproduction is permitted which does not comply with these terms. Frontiers in Integrative Neuroscience | www.frontiersin.org 14 March 2020 | Volume 14 | Article 13