The Potential of Magnetic Resonant Therapy in Children with Autism Spectrum Disorder

Review Article

Austin J Autism & Relat Disabil. 2016; 2(4): 1029.

The Potential of Magnetic Resonant Therapy in Children with Autism Spectrum Disorder

Levy ML1,2* and Crawford J¹

¹Department of Psychiatry at the University Hospital, CHUV, Switzerland

²Institute of Psychology, University of Lausanne, Switzerland

*Corresponding author:Fabienne Giuliani, Community Psychiatry Unit, Department of Psychiatry at the University Hospital, CHUV, Cery site, 1008 Prilly, Switzerland

Received: July 16, 2016; Accepted: August 29, 2016; Published: August 30, 2016

Abstract

Autism Spectrum Disorder (ASD) is a neurobehavioral syndrome caused by a dysfunction of the central nervous system that is manifest by impairment in social interaction, reciprocity, and communication. Approximately 1 in 88 American children are considered to be on the autism spectrum representing a 600 percent increase in prevalence over the past two decades. Children with ASD often have comorbid mental health difficulties, including anxiety and depression, which occur at an increased rate compared to the general population. Current clinical care has plateaued and is directed primarily at treating symptoms and modifying behavior. Currently, novel anatomic and functional modalities including MRI, functional MRI, and EEG are reliably documenting abnormalities in children on the spectrum. Functional MRI as documented a disparity in the relationship between cerebral metabolism and cerebral blood flow in these children. Electroencephalography (EEG) studies of children with ASD demonstrate reduced synchronization of frontal brainwave activity and cortical connectivity indicated by altered/abnormal EEG patterns as compared to that in normal children. It is likely that EEG endophenotypes may exist which are predictive of developing cognitive impairment and may identify infants at risk for ASD.

Magnetic Resonant Therapy (MRT) has been cleared by the Food and Drug Administration for neuromodulation treatment of posttraumatic stress disorder and of Major Depressive Disorder. Its use is additionally being explored for the treatment of children with ASD.

Though it is difficult to make definitive conclusions based upon the current literature regarding the success of MRT in this population, the consistent abnormalities in the electrophysiology of children with ASD would suggest that MRT is an appropriate therapeutic option to further pursue, especially given the minimal morbidity associated with such.

Keywords: Magnetic Resonant Therapy; Autism Spectrum Disorder

Introduction

Autism is a neurobehavioral syndrome caused by a dysfunction of the central nervous system that leads to interrupted development. According to the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV, 2000), the onset of symptoms in autism occurs within the first three years of life. However, the composite of symptoms varies in form and severity in each affected child. Management of children with autism is costly and complex and burdens families emotionally, physically, and financially. It costs approximately $3.2 million to take care of an autistic person over his or her lifetime. Currently clinical care is directed primarily at treating symptoms and modifying behavior.

Due to the diversity of clinical symptoms and severity, the illness is often referred to as Autism Spectrum Disorders which include Autism Spectrum Disorder (ASD), Asperger’s Disorder, and Pervasive Developmental Disorder–Not Otherwise Specified. Symptoms are marked by severe impairment in several developmental areas, including social interaction, reciprocity and communication, and the presence of restricted, repetitive and stereotyped patterns.

It is expected that many more children will be diagnosed with autism in the next year than with childhood cancer, juvenile diabetes, and pediatric Acquired Immune Deficiency combined. ASD affects an estimated three million individuals in the U.S. and tens of millions worldwide. Statistics from the U.S. Centers for Disease Control and Prevention identify around 1 in 88 American children as on the autism spectrum-a 600 percent increase in prevalence over the past two decades. It occurs an average of 4 to 5 times more often in boys than in girls. Along with the increase in autism prevalence, the diagnostic criteria for the illness and similar disorders have changed several times since “autism” was first defined over 5 decades ago.

Comorbid Conditions

In addition to these prominent symptoms, it is also found that children with ASD often have comorbid mental health difficulties, particularly anxiety and depression, which occur at a substantially increased rate compared to the general population [1,2], with prevalence rates of anxiety ranging from 13.6 percent [1] to 84 percent [3]. Although it is not considered a phenomenological characteristic of ASD, in the clinical setting, however, anxiety-related concerns are among the most common presenting problems for school age children and adolescents with ASD [4].

In fact, recognition of anxiety in this population is not new. In his original description of children with “classic” autism, Kanner (1943) noted that a number of them had substantial anxiety [5]. However, the evaluation and treatment of anxiety in this population have only recently received the empirical attention it deserves. Part of the reasons for the difficulties recognizing the problem lies in our diagnostic system. Anxiety disorders in both DSM-IV and ICD-10 cite autism spectrum disorder as exclusion criteria. The implication is that an anxious processing style is a feature rather than the cause of the autism spectrum presentation. It is thus difficult to distinguish between comorbid anxiety and the core symptoms of ASD or to distinguish between repetitive behaviors and obsessive-compulsive rituals. Regardless of the debate in phenomenology, prior studies have shown that frontal lobe abnormalities in ASD patients have substantial resemblance to those with clinical anxiety disorder.

Effective treatment for anxiety has demonstrated remarkable effects on other behavioral abnormalities. While some patients have immediate improvement in attention, language, and communication, others show much greater response to behavioral treatment after an effective treatment for anxiety. Thus, neural abnormalities associated with anxiety may play a critical role in the pathophysiology of ASD. Currently there is an urgent need for the development of an effective system to assess and treat anxiety in children with ASD [6] in combination with other behavioral treatments.

Current Treatment Modalities

Clinical services are frequently called upon to treat anxietyrelated problems in ASD. However, there is limited evidence for the effectiveness of treatments, although recent studies have yielded some promising results [7-9].

Current interventions may include medications (that have adverse effects), individual counseling, and the provision of advice to parents. Increasingly, some form of Cognitive Behavior Therapy (CBT) or applied behavior analysis is included with these interventions. However, the ability of young people with ASD to access many of the integral components of CBT and ABA treatments can be limited by their specific neuropsychological deficits. These neuropsychological deficits may include difficulties with communication, social understanding and imagination, problems of motivation, impaired theory of mind, and abnormal emotional responses. They may also include unusual ways of demonstrating or reporting anxiety or distress, difficulties in modulating emotional responses and selfcontrol; rigidity of thought processes/beliefs, and poor generalization to non-therapy settings. More recent studies, in conjunction with other neural imaging measures, have shown that EEG may predict the state energy metabolism in the brain as well as how the cognitive information is processed.

Functional Imaging

Whereas magnetic resonance imaging studies have documented increased white matter in children with ASD [10,11], functional imaging has demonstrated abnormal neural connections as manifested by a lack of relationship between cerebral metabolism and cerebral blood flow [12,13].

EEG

Electroencephalography (EEG) is a gross measure of neural electric activity at the scalp with the amplitude of such reflecting the degree of neuronal synchronization under the recording lead. EEG signals are believed to derive from pyramidal cells aligned in parallel in the cerebral cortex and the hippocampus. The broad frequency bands identified may help to identify abnormal or damped processing circuit characteristics in children with ASD.

The recorded magnitude of frequency distribution reflects the brain status at the time of recording. As we will discuss, often the dominant alpha EEG (approximately 10 Hz) is reduced in both amplitude and coherence, particularly in the frontal lobe in ASD children. Additionally, EEG studies of individuals with ASD demonstrate that these individuals tend to have a reduced synchronization of brainwave activity and cortical connectivity indicated by altered/abnormal EEG patterns as compared to that which would be considered optimal. This phenomenon is prevalent particularly in the frontal area [14].

Additionally, ASD patients usually have lower cortical coherence or synchronization. We believe that future studies need to be directed at evaluating the potential impact of normalizing the EEG and the relationship of such to clinical improvement in autistic symptoms. We will discuss the treatment potential of magnetic resonant therapy (MRT) in children with ASD.

Coherence

EEG coherence represents the consistency of the phase difference between two EEG signals or frequencies when compared over time. These signals may have different phases but remain coherent if the phase difference remains constant. High coherence values are indicative of strong connectivity between disparate cortical regions. The underlying substrate resulting in the behavioral presentation of ASD remains poorly understood, but likely is much more complex than simple states of under or over connectivity and indicative of connections between cortical regions that varies in both extent and location. Additionally, it is likely that these electrical phenomena change as the brain matures in an individual and become more salient when compared to clinical manifestations. Many have suggested that the determination of changes in neural connectivity might be an effective diagnostic marker for atypical connectivity development in children with ASD.

The potential understanding of synchrony between neural networks can be gleaned from EEG coherence measurements (coherence) which reflect the signal relationship between regionally disparate cortices. Whereas high coherence is indicative of neuronal synchrony, which is functional, low coherence is indicative of neuronal asynchrony, which is less functional and suggestive of multifocal cortical regions of varying signal [15]. Murias et al. reported elevated theta (3-6 Hz) coherence in the left hemispheric, frontal and temporal regions. Children with ASD also demonstrated reduced alpha range (8-10 Hz) coherence both within the frontal region and between frontal regional connections. They concluded that ASD subjects in the eyes closed resting state demonstrated Robust patterns of over- and under-connectivity [16]. Cerebral coherence has also been reported to be altered in children with ASD. Focal elevations of left hemispheric theta coherence in conjunction with reduced frontal lobe alpha coherence have been described [16]. Diffuse cortical decreases in intrahemispheric delta and theta have also been reported [17]. Increased coherence of the left hemisphere as opposed to the right has been described following stimulation in children with ASD but not at rest [18]. Isler described diminished connectivity between the right and left visual cortex during visual stimulation [19]. Greater coherence between the left occipital region with both proximal and distal cortical regions during Rapid Eye Movement (REM) sleep has been reported. They also reported right frontal coherence [20]. Increased bilateral temporal lobe gamma coherence has also been reported [21].

Neuronal Networks

Neuronal networks are notable for the significant downstream connectivity resultant from a progressive branching of synaptic connections [22]. This scale free network is modified with age [23- 25]. The more complex Neuronal networks consist of dense clusters of local synaptic connections with decreased downstream synaptic connections [23]. There are numerous physiologic variables that are specific to each region that potentially can be quantified by assays such as functional magnetic resonance imaging. FMRI has demonstrated global scale-free synaptic networks, which differ from the more hierarchical networks and interregional connectivity found in normal children [26].

MRI tractography of white matter tracts has demonstrated progressive changes in connectivity as a child’s brain develops with continuous synaptogenesis and network modification at both the local and disparate cortical regions [26]. Thus, abnormal network connectivity may be a key to understanding developmental disabilities.

Predictive Electrophysiology

Bosl et al. described the potential of EEG endophenotypes, namely cognitive findings which may predict subsequent cognitive impairments. They proposed that modified multiscale entropy (mMSE) computed on the basis of resting state EEG data can be used as a biomarker of normal brain development and potentially identify infants at risk for ASD [27].

Changes in EEG in Patients with Neurological Dysfunction

Duffy evaluated 1,304 subjects (1 to 18 years), 463 diagnosed with autism spectrum disorder. Utilizing principal components analysis they identified EEG spectral coherence factors with corresponding loading patterns. Loading patterns on the Discriminant function analysis described ASD-specific coherence differences when compared to controls. The authors concluded that the classification success could support a stable coherence loading pattern that differentiates ASD- from Controls which could be indicative of an EEG coherence-based phenotype of children on the spectrum. Whereas reduced short-distance coherences may suggest suboptimal local network function, associated long-distance coherences may represent a compensatory phenomenon in these children. The wide average spectral range of factor loadings may suggest over-damped neural networks [28]. Altered neuronal connectivity (coherence) is a potential contributor to the characteristics noted in children with ASD. Numerous studies have evaluated differences in EEG coherence findings between children with ASD and controls [3,17-21,29].

This study identified no evidence for consistent lateralization among the factor loading patterns and no overriding regional involvement. Furthermore, this study identified no clear interrelationships among spectral bands, number of coherences per factor, nor increased or decreased coherence. A primary spectral finding was the dominance of slow beta across all conditions with the majority of factors manifesting peak loadings in the slow beta range and far fewer in the fast beta, theta, alpha and delta ranges, a finding of uncertain clinical significance. Earlier studies which demonstrated findings specific to differing scalp regions and spectral ranges may largely reflect methodological differences as discussed in the Background. Most significantly, the authors identified that the ASD population coherence patterns tended to be unusually stable across broad spectral ranges (>10 Hz wide) which may be specific for this populations abnormal neurophysiology.

Approved Uses

To date, a number of systems have been cleared by the Food and Drug Administration (FDA) for neuromodulation purposes, including treatment of Major Depressive Disorder and other off label uses of MRT technology. Taghva et al. prospectively reviewed 16 veterans consecutively treated for Post-Traumatic Stress Disorder (PTSD). Following magnetic resonance therapy (MRT) patients were evaluated on the PTSD checklist (PCL-M) and the comparison of pre- and post-treatment EEGs. Significant Clinical improvements on the PCL-M were noted (p < 0.0001) and global EEG alpha-band power increased and delta-band power decreased following MRT (p < 0.05). This study documented trends toward normalization of EEG and concomitant clinical improvement using following MRT for PTSD [30].

Initial Studies

Preliminary Data communicated from Peking University in China is optimistic. Over 5 year duration, more than 60 patients with ASD were treated using quantitative EEG/ECG-guided transcranial magnetic stimulation (MeRTSM). Forty-two percent of patients who completed treatment for 4 weeks or longer showed clinically significant responses with a greater than 30% reduction from baseline measure in total CARS score at the end of the treatment. MRT Stimulation is an individualized TMS treatment protocol, which utilizes individual’s intrinsic alpha EEG frequency and its closest frequency relationship with the higher harmonic of heartbeat to determine the magnetic stimulus rate. Stimulus location was set at the most apparent abnormal EEG site revealed by quantitative EEG mapping, and the magnetic output intensity was set at 80% of the individual’s motor threshold. Each patient was treated 6 sec / min, 30 min / day for 5 days / week. Treatment was delivered with the MagVenture TMS generator (MagPro R30) coupled with a diffused and static cooled coil (MCF-B65 Butterfly). 39 patients who completed the study.

They found that the average 41% symptom reduction to be statistically significant (p < 0.05). No adverse effects were noticed in any patients either after acute or chronic treatment. Two patients with severe comorbid epileptic seizure (180 episodes/day and 600 episodes/day, respectively) showed significant improvement (1 episode/week and 40 episodes/day, respectively) after the treatment. The minimal side effect may be explained by the individualized and low intensity stimulation protocol. Compared to 120% motor threshold stimulation intensity in the FDA approved protocol, MRT intensity is only 80% motor threshold. This sub-threshold stimulation will not trigger the neuronal firing and therefore is unlikely to cause seizure.

Conclusion

It is difficult to make definitive conclusions based upon the current peer review literature given that throughout the multiple studies there are differences in experimental design, choice of spectral bands and choice of analysis used, the potential for electrical artifact given the patient population, and the anatomic location of recording which may be institution specific. Additionally, current studies are plagued by small sample sizes, variations in age, and level of impairment. These issues clutter our understanding as to whether the findings are indicative of aberrant brain function in children with ASD or rather variability in study design. At the cellular level, the EEG likely records activity of cortical pyramidal cells, which are aligned in parallel in the cerebral cortex and hippocampus. These pyramidal cells act as interconnected nonlinear oscillators. Given the scale free organization of neurons, EEG recordings of these complex, non-linear signals may be indicative of asynchrony and lack of coherence and not only indicative of aberrant neuronal networks but may also represent a potential avenue for therapeutic intervention. Despite this, given our understanding of the EEG and the consistent abnormalities in the electrophysiology of children with ASD, we would suggest that MRT is an appropriate therapeutic option to further pursue. The existing literature in depression and posttraumatic stress disorder in addition to preliminary studies in children with ASD all support its potential impact as a therapeutic option.

References

  1. Kim JA, Szatmari P, Bryson SE, Streiner DL, Wilson FJ. The prevalence of anxiety and mood problems among children with autism and Asperger syndrome. Autism. 2000; 4: 117-132.
  2. Simonoff E, Pickles A, Charman T, Loucas T, Chandler S, Baird G. Psychiatric disorders in children with autism spectrum disorders: Prevalence, comorbidity, and associated factors in a population-derived sample. Journal of the American Academy of Child and Adolescent Psychiatry. 2008; 47: 921-929.
  3. Muris P, Steerneman P, Merckelbach H, Holdrinet I, Meesters C. Comorbid anxiety symptoms in children with pervasive developmental disorders. Journal of Anxiety Disorders. 1998; 12: 387-393.
  4. Ghaziuddin M. Asperger syndrome: Associated psychiatric and medical conditions. Focus on Autism and Other Developmental Disabilities. 2002; 17: 138-144.
  5. Kanner L. Autistic disturbances of affective contact. Nervous Child. 1943; 2: 217-250.
  6. Lord C, Wagner A, Rogers S, Szatmari P, Aman M, Charman T, et al. Challenges in Evaluating Psychosocial Interventions for Autistic Spectrum Disorders. Journal of Autism and Developmental Disorders. 2005; 35: 695-708.
  7. Chalfant A, Rapee R, Carroll L. Treating anxiety disorders in children with high functioning autism spectrum disorders: A controlled trial. Journal of Autism and Developmental Disorder. 2007; 37: 1842-1857.
  8. Sofronoff K, Attwood T, Hinton S. A randomized controlled trial of CBT intervention for anxiety in children with Asperger syndrome. Journal of Child Psychology and Psychiatry. 2005; 46: 1152-1160.
  9. Sofronoff K, Attwood T, Hinton S, Levin I. A randomized controlled trial of a cognitive behavioural intervention for anger management in children diagnosed with Asperger syndrome. Journal of Autism and Developmental Disorders. 2007; 37: 1203-1214.
  10. Courchesne E, Karns CM, Davis HR, Ziccardi R, Carper RA, Tigue ZD, et al. Unusual brain growth patterns in early life in patients with autistic disorder: An MRI study. Neurology. 2001; 57: 245-254.
  11. Herbert MR, Ziegler DA, Makris N, Filipek PA, Kemper TL, Normandin JJ, et al. Localization of white matter volume increase in autism and developmental language disorder. Ann Neurol. 2004; 55(4): 530-540.
  12. Just MA, Cherkassky VL, Keller TA, Kana RK, Minshew NJ. Functional and anatomical cortical under connectivity in autism: Evidence from an fMRI study of an executive function task and corpus callosum morphometry. Cerebral Cortex. 2006; 17: 951-961.
  13. Koshino H, Carpenter PA, Minshew NJ, Cherkassky VL, Keller TA, Just MA. Functional connectivity in an fMRI working memory task in high-functioning autism. NeuroImage. 2005; 24: 810-821.
  14. Wang J, Barstein J, Ethridge LE, Mosconi MW, Takarae, Sweeney JA. Resting state EEG abnormalities in autism spectrum disorder. J Neurodev Disord. 2013; 5: 24.
  15. Nunez PL, Srinivasan R. Electric fields of the brain: The neurophysics of EEG. New York: Oxford University Press. 2006.
  16. Murias M, Webb SJ, Greenson J, Dawson G. Resting State Cortical Connectivity Reflected in EEG Coherence in Individuals with Autism. Biol Psych. 2007; 62: 270-273.
  17. Coben R, Clarke AR, Hudspeth W, Barry RJ. EEG power and coherence in autistic spectrum disorder. Clin Neurophysiol. 2008; 119: 1002-1009.
  18. Lazarev VV, Pontes A, Mitrofanov AA, deAzevedo LC. Interhemispheric asymmetry in EEG photic driving coherence in childhood autism. Clin Neurophysiol. 2009; 121: 145-152.
  19. Isler JR, Martien KM, Grieve PG, Stark RI, Herbert MR. Reduced functional connectivity in visual evoked potentials in children with autism spectrum disorder. Clin Neurophysiol. 2010; 121: 2035-2043.
  20. Leveille C, Barbeau EB, Bolduc C, Limoges E, Berthiaume C, Chevrier E, et al. Enhanced connectivity between visual cortex and other regions of the brain in autism: A REM sleep EEG coherence study. Autism Res. 2010; 3: 280-285.
  21. Sheikhani A, Behnam H, Mohammadi MR, Noroozian M, Mohammadi M. Detection of abnormalities for diagnosing of children with autism disorders using of quantitative electroencephalography analysis. J Med Syst. 2010; 36: 957-963.
  22. Buzsáki G. Rhythms of the Brain. New York: Oxford University Press. 2006.
  23. Barabasi AL. Scale-free networks: a decade and beyond. Science. 2009; 325: 412-413.
  24. Bassett DS, Bullmore E. Small-world brain networks. Neuroscientist. 2006; 12: 512-523.
  25. Ravasz E, Barabási AL. Hierarchical organization in complex networks. Phys Rev E. 2003; 67: 1-7.
  26. Supekar K, Musen M, Menon V. Development of large-scale functional brain networks in children. PLoS Biol. 2009; 7.
  27. Bosl W, Tierney A, Tager-Flusberg H, Nelson C. EEG complexity as a biomarker for autism spectrum disorder risks. BMC Medicine. 2011; 9: 18.
  28. H Duffy FH, Als H. A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study. BMC Medicine. 2012; 10: 64.
  29. Barttfeld P, Wicker B, Cukier S, Navarta S, Lew S, Sigman M. A big-world network in ASD: dynamical connectivity analysis reflects a deficit in long-range connections and an excess of short-range connections. Neuropsychologia. 2010; 49: 254-263.
  30. Taghva A, Silvetz R, Ring A, Kim KA, Murphy KT, Liu CY, et al. Magnetic Resonance Therapy Improves Clinical Phenotype and EEG Alpha Power in Posttraumatic Stress Disorder. Trauma Mon. 201; 20: 27360.

Download PDF

Citation: Levy ML and Crawford J. The Potential of Magnetic Resonant Therapy in Children with Autism Spectrum Disorder. Austin J Autism & Relat Disabil. 2016; 2(4): 1029.

Home
Journal Scope
Online First
Current Issue
Editorial Board
Instruction for Authors
Submit Your Article
Contact Us