Translational Neuroscience in Autism: From Neuropathology to Transcranial Magnetic Stimulation Therapies

synopsis

The presence of heterotopias, increased regional density of neurons at the gray white matter junction, and focal cortical dysplasias all suggest an abnormality of neuronal migration in autism spectrum disorder (ASD). The neuronal migration abnormality is borne from a dissonance in timing between radial and tangentially migrating neuroblasts to the developing cortical plate. The uncoupling of excitatory and inhibitory cortical cells disturbs the coordinated interactions of neurons within local networks thus providing for abnormal patterns of brainwave activity in the gamma bandwidth. In ASD, gamma oscillation abnormalities and autonomic markers offer measures of therapeutic progress and help in the identification of subgroups. Low frequency TMS over the dorsolateral prefrontal cortex serves to normalize gamma oscillations, improve repetitive behaviors and treat deficits of executive functions.

Introduction

Autism is generally thought of as a group of complex neurodevelopmental disorders having similar behavioral manifestations. The adjective “neurodevelopmental” serves to characterize a commonality of this group of disorders as to a presumptive insult that happens during brain development. This insult ultimately affects the function of the brain in a manner that unfolds over a prolonged period of time, if not the life of the affected individual. In the case of autism, symptoms are manifested as abnormalities of social interaction and communication across multiple contexts and by restricted and/or repetitive patterns of thoughts and behaviors. These symptoms first appear in childhood but may not be fully manifested until social demands exceed the coping capacity of the patient and affect the daily functioning of the individual. Among patients, some maintain a high quality of life and need little support while others require frequent and intensive therapy. This range of variability has given rise to the idea that autism spans a spectrum of different conditions with symptoms that vary across individuals not only in severity but also in type and onset. Within this spectrum there are atypical and attenuated types (formes frustes) and devastatingly severe forms characteristic of some syndromic types. The clinical variability of manifestations and lack of biomarkers has procreated a diagnostic scheme based on behavioral manifestations. The end result of such a subjective scheme provides for a large amount of heterogeneity within the research literature and for the averaging out of important findings under the rubric of statistical noise or experimental error. It is therefore not surprising that a great deal of the literature in autism proposes disparate causative theories, underlying pathologies, and a plurality of potential biomarkers each seemingly unrelated to one another.

Research into complex and heterogeneous conditions usually gains significance from insightful perspectives obtained when studying outliers. In homogenous populations, outliers do not reflect the general characteristics of the target population. Their inclusion within the statistical analysis of a study may lead to false positive results. In heterogeneous samples; however, outliers occur frequently and serve to indicate that the population is not randomly distributed. These outliers include monogenic (single-gene) chromosomal disorders, like Angelman syndrome and chromosome 15 duplication. In these disorders, severity in terms of clinical presentation may point to an exaggeration of the underlying pathology that is associated with an autism phenotype. In the right context, the exaggerated features of outliers may make it easier to identify distinguishing characteristics (e.g., neuropathological findings) of the studied population.

Autism spectrum disorder (ASD) is predominantly an idiopathic condition. In a minority of cases (~10%), however, autism is secondary to a known environmental or chromosomal abnormality (1). Neuropathological findings in these secondary conditions include irregular gyri, abnormal laminar distribution of neurons, and a variety of cellular aggregates in both cortical and subcortical locations (2,3). Similar, but subtler pathology, has been reported in idiopathic autism wherein multiple authors have reported on the presence of heterotopias, the accumulation of neurons at the gray/white matter junction, and dysplastic changes of the cerebral cortex (4–8). These changes are all suggestive of a congenital abnormality where neuronal progenitors have divided abnormally and/or failed to migrate to their proper location.

Neuropathology

During corticogenesis, neuronal progenitors migrate from a periventricular location to a target destination within the cerebral cortex. The migration of these precursor cells is termed radial or tangential depending on the orientation that the cells take in regard to the pial surface of the neural tube. The process for germinal cell divisions usually begins before the sixth week of gestation (9). The first divisions within the periventricular germinal matrix are symmetrical and serve to increase the original pool of dividing cells. The second wave of germinal cell divisions is asymmetrical and result in cells that have different specification fates. During asymmetrical divisions, one cell remains behind in the original periventricular matrix while the other migrates along a restricted radial path to become either neurons, astrocytes or oligodendrocytes (10–12). Those neuroblasts that migrate to the cortical plate do so along radial glial fibers and detach along multiple strata. Those that arrive the earliest will detach at the deeper cortical layers (closest to the white matter) while later arriving migratory cells detach at progressively more superficial locations.

Interneurons (inhibitory cells) primarily arise from the medial and caudal ganglionic eminences and migrate tangentially in order to reach their final destination in the cortical plate. These inhibitory neurons first settle in the lower cortical layers and mature along ascending strata besides pyramidal cells with whom they establish contacts (13). The distance traveled by the tangentially migrating neuroblasts is much longer than the radial pathway pursued by other precursor cells. In this way, tangential migration allows future interneurons to achieve destinations far removed from their site of origin. This rather circuitous route expands the time window of opportunity during which the migration of neuroblasts may be imperiled. In some neurodevelopmental disorders, the predisposition to pathology caused by the winding tangential migration of interneurons may procreate a deficit of inhibition manifested as cortical hyperexcitability.

The confluence of the tangential and radial migratory streams upon the cortical plate results in a series of distinct cellular partnerships characterized by dyads of interacting excitatory and inhibitory neurons (13,14). The stacked superimposition and interdependence of these cellular dyads, along with their projections, gives rise to a vertical unit of function called the “minicolumn”. Lorente de Nó first discussed the functional role of these “vertical cylinders” when he stated, “All the elements of the cortex are represented in it, and therefore it may be called an elementary unit, in which theoretically, the whole process of transmission of impulses from the afferent fibre to the efferent axon may be accomplished” (15). It is thought that minicolumns contain a canonical circuit that is iterated throughout the cerebral cortex thus providing a basic similarity of internal design and operation (16).

The scale and spatial boundaries of minicolumns are defined by their interconnections. Neurons within a minicolumn, performing a shared function, implement an economy of wiring when kept in close apposition to each other (17). The underlying organizational scheme provides for increased intracolumnar connectivity as compared to the looser connectivity arrangement observed between minicolumns (18). Selective pressures have required the clustering of these connections into a small world network; a topology that optimizes connectedness while minimizing wiring costs (19,20). The resultant community structure or clustering provides a frame of reference that ties together both connectivity and the excitatory-inhibitory balance of the cerebral cortex. Indeed, anthropometric indices of anatomical connectivity (e.g., area of corpus callosum, gyral window, cortical complexity) in autism all seem to be altered and suggest a bias favoring short connections over longer projections (21,22).

Postmortem studies of minicolumnar morphometry in ASD indicate salient differences when compared to neurotypicals. These studies indicate compartmentalization of the minicolumns with a significant areal reduction of its peripheral neuropil space, while its core compartment is relatively preserved(10). The periphery of the minicolumn is populated by inhibitory cells that help establish lateral or surround inhibition. Mountcastle described this compartment as imparting upon the minicolumn a strong flow of vertical inhibition (23). Having a similar idea in mind, Szentágothai described the function of the peripheral minicolumnar compartment as a shower curtain of inhibition (24). In autism, a faulty shower of inhibition (i.e., diminished peripheral neuropil space of minicolumns) allows for stimulation to spread from its core into adjacent minicolumns. The end result is to diminish signal contrast and procreate a cascade of excitation. At present, both EEG and studies of tactile processing indicate abnormalities of lateral inhibition in ASD individuals (25,26).

In ASD, several lines of evidence suggest a deficit of cortical inhibition. Postmortem studies have shown a reduction of GABA(A) receptors in the cerebral cortex and cerebellum of ASD individuals when compared to neurotypicals (27,28). In vivo magnetic resonance spectroscopy studies show that reductions of GABA levels correlate with the severity of the ASD phenotype (e.g., social cognition, motor stereotypies) (29,30). Computerized image analysis studies of the cerebral cortex have revealed the presence of dysplastic areas, predominantly in the frontal lobes (31). The co-occurrence of focal cortical dysplasias and heterotopias serves to emphasize the developmental nature of autism and the presence of a neuronal migratory deficit. Within dysplastic areas, spatial statistics indicate a reduction in size of occupant pyramidal cells and a concomitant reduction in the total number of interneurons (31). Immunocytochemical studies have localized this inhibitory deficit to a subset of cells containing the calcium-binding protein parvalbumin (PV) (32).

Cell fate specification studies have shown how interneurons develop into an abundance of cells that vary on the basis of their morphological, neurochemical, and electrophysiological characteristics. In neuropathology, subtyping of interneurons has been primarily done based on their surface markers (i.e., calcium-binding proteins)¹. When comparing brain tissue specimens of autistics and control subjects, immunohistochemistry reveals a significant reduction in the total number of PV-positive cells in all cortical areas examined (BA46, BA47, BA9) (32).

The PV-positive cells account for approximately 40% of all interneurons and include fast spiking basket and chandelier cells². The function of PV-positive cells is significantly diminished in the prefrontal cortex of numerous psychiatric conditions (e.g., schizophrenia, Alzheimer disease, bipolar disorder) (37,38). Animal models have shown a correlation between decreased PV expression and those behavioral deficits characteristic of the ASD phenotype (39,40). According to Wöhr and associates (2015), downregulation of PV-positive cells represents one point of convergence that provides a “common link between apparently unrelated ASD-associated synapse structure/function phenotypes” (40, p.1).

Fast forward inhibition by PV-positive cells helps regulate pyramidal cell activity, prevent runaway excitation, refine receptive fields and synchronize the firing rhythms of neuronal populations responsible for fast cortical oscillations. Among PV-positive neurons, basket cells are highly interconnected through chemical synapses and gap junctions. The ensuing web of synchronously interconnected cells (41,42) triggers and maintains high-frequency gamma oscillations within ensembles of cortical pyramidal cells (41, 43–48). These oscillations modulate a large variety of behavioral responses (38). It is therefore unsurprising that some researchers have gone as far as proposing the use of gamma-band based metrics both as a possible mean for subtyping the autism endophenotype and as a surrogate marker for treatment response to interventions (49).

Gamma oscillations are generated locally as a result of reciprocal interactions between excitatory pyramidal cells and the rhythmic perisomatic inhibition of PV interneurons (50). A pathological increase of gamma activity, as in autism, reflects an imbalance in the excitatory-inhibitory homeostasis of the cortex. Similarly, in schizophrenia, loss of PV interneurons has been postulated to underlie reported abnormalities of gamma oscillations as a way of explaining commonly observed symptoms of executive dysfunction (e.g., conceptualization, cognitive flexibility, planning) (50–53). These electrophysiological and neuropathological findings reported in ASD can’t therefore be regarded as specific to the disorder but do provide mechanistic explanations to core symptomatology and to possible targets for intervention.

Gamma Oscillations

In modern systems of communication, data transmission is dependent on both the bandwidth and frequency of the transceived signal. The broader the bandwidth and the faster the frequency, the higher the capacity for data transfer. The brain shares these properties as a communication system. Pyramidal cells in the cerebral cortex summate the dipoles of postsynaptic potentials. The resultant potential difference, expressed as volts, can be detected by scalp electrodes and electrophysiological monitoring. These voltages (brainwaves) can be divided according to frequency (slowest to fastest) as delta, theta, alpha, beta, and gamma. The different brainwave bands reflect distinct behavioral and cognitive states. Delta waves, for example, are characteristic of deep sleep while higher frequency bands reflect increased alertness and focus.

The fastest frequencies and broadest bandwidth of brainwaves is seen with gamma oscillations, typically defined as between 30 and 120 Hz and characterized by a low amplitude of 10–20 μV. It is in this gamma bandwidth that the brain can most efficiently process multimodal information stemming from disparate anatomical locations. Gamma oscillations help regulate maintenance of attention, working memory, face processing, and refinement of executive functions, as well as the integration of perceptual features of individual objects into a whole (54–58). Being involved in so many fundamental aspects of cortical functions, gamma oscillations may serve as a fingerprint of typical and atypical behaviors. It is therefore unsurprising that gamma oscillations, as a measure of temporal binding, was proposed as the causative agent for the atypical perceptual processing symptoms observed in ASD (59). According to this hypothesis abnormalities in gamma oscillations reflect a failure in the integration of sensory information at the cortical level. By increasing the efficiency of local fine-grained analysis while simultaneously taxing those tasks requiring configural strategies (e.g., face discrimination), gamma oscillation abnormalities help explain the autistic characteristic of focusing on local details at the expense of global processing. This appears to be a severity-dependent measure wherein an excess of high-frequency electroencephalogram oscillations provides an index of developmental delay in autistic children (60).

Recent studies suggest the possibility of examining different time windows of frequency or subbands of gamma activity as a way of distinguishing between sensory and cognitive processes (61,62). Although high frequency gamma (>60 Hz) is reflective of the high-level visual-based cognitive processes characteristic of ASD deficits (63), the majority of reported studies have been done in the low frequency range (30–60 Hz). Indeed, early studies focused on a single frequency (40Hz) traditionally related to the “binding”³ of sensory features to form coherent precepts (65,66).

Signal analysis of multi-channel electroencephalographic recordings allows the identification of brainwave’s component frequencies as well as their power. For gamma oscillations, power changes in brainwave activity are termed “evoked” when they are tied (phased-locked) to an eliciting stimulus and persists within the first 100 msec after stimulus onset. The evoked gamma is thought to represent the binding of information within a confined cortical field (63,67). For gamma oscillations, a later component, labelled as “induced”, is believed to represent the binding of feedforward and feedback processing across networks of different cortical regions. This component of the gamma activity has a variable onset (i.e., it is not tied or phase-locked to the eliciting stimulus) usually starting at around 250 msec. The jittering of the induced gamma band activity makes it difficult to extract descriptive measures in the time domain. Given the disparity in how gamma oscillations have been studied and reported by researchers (e.g., single or broader range of different band frequencies, evoked or induced gamma), caution should be exerted when comparing the results of different studies.

Gamma oscillations are usually measured in association with stimulus-driven changes in network activation (68). Bursts of gamma oscillations can be seen over the occipital lobes during visual object processing. When involved in more complex tasks, other areas involved in the undertaking are recruited and synchronized in the same gamma range (e.g., fusiform gyrus for face recognition; 69).

Figures of illusory or subjective contours (Kanizsa figures) that evoke the precept of a shape, produce gamma oscillations during visual cognitive tasks. In autism, EEG recordings during a Kanizsa figure have shown an overall increase in gamma oscillatory activity as compared to neurotypicals (69). The findings have been interpreted to reflect reduced “signal to noise” due to diminished inhibitory processing (69).

Ogawa et al. examined the changes in high frequency oscillations (HFOs) of somato-sensory evoked potentials (SEPs) both before and after slow TMS (0.5 Hz) over the right primary somatosensory cortex (postcentral gyrus) (70). After slow TMS, the HFOs, which represent the localized activity of intracortical inhibitory interneurons, were significantly increased, without a concomitant change in the SEPs. The results suggest the possible therapeutic benefits of slow TMS on cortical excitability by modulating the activity of the intracortical inhibitory neurons beyond the time of the stimulation. According to Cole and associates (71, p. 12), “[The] findings should encourage the psychiatric community to expand research into other applications for which transcranial magnetic stimulation may be used to treat patients with psychiatric disabilit[ies]”.

A recent meta-analysis of post-mortem studies in schizophrenia supports the presence of a deficit of the GABAergic system, in particular a loss of PV-containing interneurons critical to the generation of gamma oscillations (72). Researchers have thus suggested using drugs that modulate Kv3.1/2 channels⁴, as a possible treatment modality for schizophrenia (74–76). Alternatively, transcranial magnetic stimulation (TMS) over the dorsolateral prefrontal cortex (DLPC) has proven to be an effective intervention capable of normalizing gamma oscillations, improving cognitive performance, and in relieving both positive (especially auditory hallucinations) and negative symptoms of schizophrenia (71, 77–80). Although, schizophrenia and autism are distinct conditions, both share an apparent overlap in regards to electrophysiological and neuropathological findings. It is therefore of interest that TMS has been used for research purposes as a therapeutic intervention in both conditions for similar reasons.

Transcranial Magnetic Stimulation

In an open circuit, electrons within a conductor (e.g., wire) have randomly aligned magnetic fields. In this state, with no current flowing through a circuit, the magnetic field associated with the electrons cancel each other out. When current starts to flow through the conductor, the magnetic fields of the electrons tend to align with each other. As we increase the applied voltage and/or diminish the resistance of the conductor, we increase the intensity of current as well as the strength of the resultant magnetic field surrounding the conductor. In a pulsed voltage, the strength of the magnetic field will increase as the current flow increases to its maximal value.

In Transcranial Magnetic Stimulation (TMS) a rapidly discharging bank of capacitors creates a controlled pulse of a large current (up to 10,000 amperes) through a conductor. The capacitors serve to store electrical energy and are efficient at discharging it in short bursts⁵. Wrapping the conductor in a coil summates the magnetic field of each individual coil with that of its neighbors. The resultant magnetic field has polarity, with a north pole at one end and a south pole at the other end of the coil. Adding a core material to the coil helps concentrate the magnetic flux in a well-defined and predictable path. In TMS, the magnetic field stemming from the coil varies between 1.5 to 2.0 Tesla which is approximately equal to the field strength produced by modern magnetic resonance imaging (MRI) equipment. For comparison purposes, the strength of the Earth’s magnetic field ranges from 25 to 65 microteslas.

The geometric shape of the coil will affect how the magnetic field lines are expressed or focused on the brain. Coils shaped like a figure of 8 allow for a targeted stimulation of the cortex while doughnut shaped coils cover a broader area (figure 1). Specially shaped coils, like the H coil, are used for deeper stimulation at the expense of a higher and wider spread of electrical fields in the more superficial cortical regions. This is because the strength of the magnetic field obeys an inverse square law. As you move away from the coil, the intensity of the magnetic field will decrease as the square of the distance.

Figure 1:

A figure of 8 electromagnetic coil is placed near the forehead of a child while she sits comfortably in a reclining chair. Repeatedly activating the electromagnet produces clicking sounds and a slight tapping on the forehead. Earplugs are provided for noise reduction.

In TMS, a pulse generator provides a burst of current through a low resistance pathway. The pulsed current produces an expanding (and later on collapsing) magnetic field which has a relative motion to any stationary conductors crossing its flux lines. In humans, the neuronal soma and its projections serve as membrane-bound “bags” of electrolytes acting as conductors. Axons have passive conduction properties that determine the spread of electrical current. Larger diameter axons will conduct better because there is less resistance to the flow of ions. The voltage created (induced) by the magnetic field on axons will depend on both their length and their orientation relative to the magnetic field’s flux lines. If the axon stands perpendicular to the magnetic lines of force, the maximum voltage is induced. No voltage is induced if the axons hold the same orientation as the direction of the magnetic field.

At low frequencies (<1 Hz) TMS preferentially has an inhibitory effect. This may be due to its action on interneurons. Some of these inhibitory elements have a more favorable geometrical orientation to the magnetic field lines which induce currents along the axons rather than across the same (81). When higher frequencies are used (>5 HZ) all neurons within a targeted cortical area are stimulated regardless of their geometrical orientation. Since pyramidal cells comprise 70 to 90% of all neurons in the cerebral cortex the end result is that TMS becomes excitatory at higher stimulation frequencies (see 82). Higher frequencies also increase the impedance⁶ of the inductor (coil). The increased resistance provides a voltage drop through the coil that dissipates electrical power as heat. In TMS, different cooling systems are available to prevent overheating when using high frequency stimulation.

In TMS, the influence of the magnetic field is restricted to a small area (approximately 3 cm²) within the superficial layers of the cerebral cortex⁷. Selecting an appropriate target area or region of interest is therefore of importance in order to maximize the effectiveness of the intervention. Among the many areas of the cerebral cortex, the dorsolateral prefrontal cortex (DLPC) has been intimately tied to disrupted functioning in ASD. This prefrontal cortical region is involved in the genesis of executive functions that include judgement, planning, sequencing of activity, abstract reasoning, and dividing (cross-modal and set-shifting) attention. Furthermore, the DLPFC is responsible for the inability to inhibit context-inappropriate/inflexible behaviors that impair adaptive responses. Since the DLPC is extensively interconnected with cortical (sensory, motor, association) and subcortical areas, correcting the function of this region could help normalize the function of its multiple interconnected sites⁸.

In general, parameters for our TMS studies have used a figure of 8 coil with low frequency stimulation (inhibitory) over the DLPC. Most studies have excluded patients with seizures or brain trauma in the study population. Participation has been limited to higher functioning (IQ>70) individuals in order to maximize successful completion of tested paradigms, maintain alertness/attention, and provide adequate behavioral responses (e.g., pressing a button in response to deviants). For the same reasons, age range was usually restricted to 8–18 years. Outcome measures have included gamma oscillations, event related potentials (often using an oddball paradigm⁹), behavioral screening, and autonomic measures. In our own studies, we thought that the best control group would be a series of IQ, socioeconomic, age- and sex matched autistic individuals not subjected to active TMS treatment. After finishing the study and breaking the blind, participants in the wait list group were offered the active treatment.

Transcranial Magnetic Stimulation in Autism Spectrum Disorder

Gamma Oscillations

The first clinical trial using TMS in ASD was reported a decade ago by Sokhadze and associates (83; for reviews of TMS studies in autism see 84–91). The authors justified the trial and choice of an intervention based on a series of postmortem studies which were suggestive of an excitatory-inhibitory imbalance in widely distributed regions of the cerebral cortex. Given the nature of the described deficits, the researchers decided on using low frequency TMS (0.5 Hz; trying to build inhibition) over DLPC. Thirteen patients (ADOS and ADI-R diagnosed) and equal number of controls participated in the study. Repetitive TMS was delivered 2 times per week for 3 weeks. Kanizsa figures were used in an oddball paradigm in order to investigate the effects of target classification and discrimination between illusory stimulus features. Gamma power and behavioral screening were used as an outcome measure. Behavioral screening showed decreased irritability and hyperactivity scores on the Aberrant Behavior Checklist (ABC) and a reduction in repetitive and stereotype behaviors on the Repetitive Behavior Scale (RBS-R). Also, at baseline the gamma power was higher and of shorter latency in the ASD group as compared to controls. After treatmen,t the active group, similar to controls, showed a wider difference in gamma power when comparing target and non-target stimuli (figure 2). Results were highly significant (p<0.001) when comparing Stimulus (target, nontarget) × Group (autism, control) for all recording sites. The findings on both gamma oscillations and behavioral screening were reproduced in later studies using different populations of patients and number of TMS sessions (figure 3) (92–95).

Figure 2:

Induced gamma oscillations to target stimuli increased post-TMS as compared to baseline.

From Sokhadze EM, Casanova MF, El-Baz AS, et al. TMS-based neuromodulation of evoked and induced gamma oscillations and event-related potentials in children with autism. NeuroRegulation 2016;3(3):115; with permission.

Figure 3:

Ritualistic/Sameness behavior (left) and Stereotype behavior (right) rating scores of RBS-R questionnaire at baseline, post waiting period, and post 12 and 18 sessions of rTMS. Most dramatic decrease of scores was observed in the 18 TSM group.

Adapted from Sokhadze EM, Lamina EV, Casanova EL, et al. Exploratory study of rTMS neuromodulation effects on electrocortical functional measures of performance in an oddball test and behavioral symptoms in autism. Front Syst Neurosci 2018;12(20):10; with permission.

Our group also examined the effects of TMS applied bilaterally over the DLPC on both gamma phase coherence (i.e., a measure of synchronization and communication among different cortical areas) and event-related potentials (ERP). One study consisted of 18 TMS sessions in 54 ASD children equally divided into an active and a control group. The results indicated a significant posttreatment increase in latency and reduction in amplitude of frontal and fronto-central ERP components to non-targets in the treatment group as compared to the control group (figure 4) (95). In another study, 18 sessions of bilateral DLPC TMS was used to examine EEG gamma phase coherence between frontal and parietal sites (96) in 32 participants (TMS and wait list controls, 16 subjects each). TMS had its most significant effect on induced gamma in the frontal region of our active treatment group as indicated by increased gamma phase coherence in response to target stimuli. These variations in induced gamma activity happened during the same time window as the P300, an ERP component elicited during decision making, thus suggesting a possible relation to higher cognitive processes.

Figure 4:

At baseline P300 responses were similar to all 3 stimuli (target Kanizsa, nontarget Kanizsa, standard). Post-TMS responses to non-target stimuli decreased.

The findings of these studies bear clinical significance. Abnormalities of gamma oscillations provide the basis for observed deficits in the functional integration of widely distributed networks¹⁰. The resultant deficit provides for reduced connectivity in local neural networks and over-connectivity within isolated neural assemblies (63,67, 97). In ASD, the uninhibited gamma activity observed at baseline may be related to an inability to focus attention. From an electrophysiological perspective, this may mean that no single circuit comes to dominance because too many of them are active simultaneously (69). According to Casanova and associates, “In a network that is over-activated and “noisy”, local cortical connectivity may be enhanced at the expense of long-range cortical connections, and individuals with ASD may have difficulty focusing their attention. It may not be possible for them to selectively activate specific perceptual systems based on the relevance of a stimuli (e.g., target vs. non-target)” (98). The findings are explanatory of previous results reported by Grice et al., (2001) showing lack of significant difference in frontal gamma activity when comparing upright and inverted faces in ASD as opposed to clear differences in the control subjects (99).

Executive Functions

Executive functions control goal-oriented behaviors, such as the online maintenance and manipulation of information (i.e., working memory), mental flexibility, and task switching. Individuals with ASD manifest restricted and repetitive behaviors related to daily cognitive flexibility deficits, especially in those undertakings that have an emotional component (100). In a review of 26 studies examining executive functions among children with ASD and/or attention deficit hyperactivity disorder (ADHD), impairment in flexibility and planning and deficits in response inhibition differentiated between the groups (ASD, ASD+ADHD, ADHD) (101). In contrast, other executive functions, including deficit in attention, working memory, preparatory processing, fluency and concept formation, did not appear to discriminate between the groups.

Children who have problems in task monitoring experience difficulties in achieving their daily chores. Task monitoring entails focusing on the chore at hand, recalling and following multi-step directions, and being able to detect errors and institute corrective behaviors. The ability to institute certain corrective actions, allow us to avoid further errors and help us adapt to our everchanging environment (102). It is for these reasons that the first studies on TMS in autism that targeted executive functions focused on error monitoring and correction. In this study, 28 individuals (n=14 each for ASD and control groups) participated; the active group receiving 12 sessions of bilateral low frequency TMS over the DLPC (103). Results showed significant improvements in error detection and correction in the active intervention group. Performance in task monitoring was also indexed by changes in error-related brain activity (ERN). The magnitude of this ERP component is associated with self-correction and post-error slowing responses, the latter usually interpreted as a biomarker of error processing (104). In ASD, TMS leads to decreased latency and increase amplitude for the error-related negativity component during commission errors manifested behaviorally as improved motor reaction accuracy (105). The results suggest that TMS treatment (low frequency over the DLPC) in ASD may improve both executive functions (related to error monitoring) and behavioral performance.

Autonomic Measures

The autonomic nervous system (ANS) innervates our internal organs and regulates those bodily functions that are carried out automatically, without conscious awareness. Signs of autonomic disturbances are common in ASD and include baseline (tonic) pupillary dilation, altered skin conductance, and lack of heart rate regulation to potentially stressful stimuli (e.g., social cognitive tasks) (106). Our studies used heart rate variability and skin conductance activity/level (SCL) as noninvasive measures of autonomic nervous system activity during TMS therapy in autism (107–109). The results showed that, at baseline, ASD individuals have an accelerated heart rate in association with lower heart rate variability (HRV) indexed by a low frequency (LF) to high frequency (HF) ratio (LF/HF, so-called cardiac autonomic balance index) and a reduction in the standard deviation of HR (SDHR) along with high SCL. These autonomic indicators were normalized by TMS treatment (figure 5) (109). Behavioral evaluations serving as outcome measures for these studies showed decreased irritability, hyperactivity, and stereotypical and compulsive behaviors, whose improvement correlated with several of the autonomic variables.

Figure 5:

Skin conductance level (SCL) showed statistically significant linear regression over 18 sessions of r The LF/HF ratio of HRV (cardiac autonomic balance index) showed a linear regression that was statistically significant (R=0.79, R²=0.62, adjusted R²=0.59, observed power=0.97, Fig.5.1).TMS (R=0.63, R² = 0.40, adjusted R²=0.36, F=10.70, p=0.004, power=0.94, Fig.5.2).

Adapted from Sokhadze GE, Casanova MF, Kelly DP, et al. Neuromodulation based on rTMS affects behavioral measures and autonomic nervous system activity in children with autism. NeuroRegulation 2017;4(2):65–78; with permission.

The ANS is directly involved in aspects of affect, emotional expression, facial gestures, vocal communication, and social engagement that are often hypothesized as contributing to the broad autism phenotype. Our results suggest that measures of autonomic arousal, as well as autonomic cardiac responses regulation profiles, could be useful in distinguishing subgroups of autistic individuals and how we treat them. Indeed, there are ongoing clinical trials using beta-blockers (e.g., Inderal) in ASD as a way of treating overactivation of the sympathetic nervous system by blocking its effect on the heart. It has been suggested that propranolol may have beneficial effects for treating the emotional, behavioral and autonomic dysregulation of children and adolescents in the autism spectrum (110). These drug trials may serve to better target the underlying pathology and avoid many of the short- and long-term side effects provided by anxiolytics.

Our group has also examined for possible synergism by combining use of TMS and EEG neurofeedback (NFB) (i.e. the use of brain activity parameters as feedback to regulate a brainwave frequency) (111). The justification for the trials wasthat the use of TMS while simultaneously operantly conditioning EEG changes would prove synergistic when measuring executive functions and behavioral health screening (e.g., ABC, RBS-R) (111). Results of the combined treatment trial (N==20 TMS/NFB 18 sessions, N=22 controls) demonstrated significant improvements in measures of executive functions, positive changes in EEG outcomes of neurofeedback training (e.g., frontal theta-to-beta ratio), and an increase in the relative amplitude or power of gamma activity (111).

In summary, In concert, human postmortem research, electrophysiological investigations, and pathological studies of animal models all provide confluent evidence of an inhibitory cortical deficit in ASD. More specifically, the studies indicate a disruption of cortical fast-spiking inhibitory cells that normally control and synchronize those regional neural circuits that support higher cognitive functions. The gamma and ERP responses reported in these studies indicate that the cortical activity induced by perceptual processes starts earlier and continues for a longer period of time than in controls. The results suggest that the neural networks involved in synchronizing information processing are not functioning normally. These cortical abnormalities disrupt the neural top-down control over the limbic system and ANS. A dysregulated ANS, in turn, increases the risk for metabolic abnormalities, cardiovascular disease and diabetes (112). Normalization of the excitatory/inhibitory cortical imbalance in ASD may therefore lead to systemic benefits and assist in the treatment of related comorbities.

Conclusions

Research studies suggest that TMS may help regulate gamma oscillations, reduce behavioral symptoms, and normalize signs of executive and autonomic dysfunction. These effects are “context dependent” i.e. results will vary according to the state of excitability of the cerebral cortex at the time of stimulation (113). Disturbances in baseline gamma oscillations may help identify a subgroup of ASD patients for which TMS therapy is beneficial. Despite positive results, the use of TMS outside of a research setting is premature. The total number of patients involved in clinical trials thus far has been small and lacking in adequate controls. Further studies are needed to examine the effects of different patterns of TMS stimulation (114), long-term therapeutic effects of TMS, the potential benefits of booster sessions, and the use of ancillary intervention to promote synergism and/or maintain therapeutic benefits (e.g., neurofeedback) (85, 88).

Key Points:

• Neuropathological studies in autism suggest the presence of a neuronal migrational disorder that alters the excitation-inhibition balance of the cerebral cortex.

• Neuropathological studies in both humans and animal models of autism indicate a loss of parvalbumin (PV)-positive interneurons in widespread cortical regions.

• Abnormalities of PV-positive neurons are related to changes in gamma oscillations, neural network instabilities, epileptogenesis, and impaired cognitive functions.

• Atypical gamma oscillations reflect an excitation-inhibition imbalance within the cerebral cortex.

• Low frequency transcranial magnetic stimulation (TMS) over the dorsolateral prefrontal cortex has been proven to normalize gamma oscillation abnormalities, executive functions, and repetitive behaviors in high-functioning ASD individuals.