Transdermal Electrical Neuromodulation for Anxiety and Sleep Problems in High-Functioning Autism Spectrum Disorder: Feasibility and Preliminary Findings.

BACKGROUND: Autism spectrum disorder (ASD) is associated with anxiety and sleep problems. We investigated transdermal electrical neuromodulation (TEN) of the cervical nerves in the neck as a safe, effective, comfortable and non-pharmacological therapy for decreasing anxiety and enhancing sleep quality in ASD. METHODS: In this blinded, sham-controlled study, seven adolescents and young adults with high-functioning ASD underwent five consecutive treatment days, one day of the sham followed by four days of subthreshold TEN for 20 min. Anxiety-provoking cognitive tasks were performed after the sham/TEN. Measures of autonomic nervous system activity, including saliva α-amylase and cortisol, electrodermal activity, and heart rate variability, were collected from six participants. RESULTS: Self-rated and caretaker-rated measures of anxiety were significantly improved with TEN treatment as compared to the sham, with effect sizes ranging from medium to large depending on the rating scale. Sleep scores from caretaker questionnaires also improved, but not significantly. Performance on two of the three anxiety-provoking cognitive tasks and heart rate variability significantly improved with TEN stimulation as compared to the sham. Four of the seven (57%) participants were responders, defined as a ≥ 30% improvement in self-reported anxiety. Salivary α-amylase decreased with more TEN sessions and decreased from the beginning to the end of the session on TEN days for responders. TEN was well-tolerated without significant adverse events. CONCLUSIONS: This study provides preliminary evidence that TEN is well-tolerated in individuals with ASD and can improve anxiety.

Visual Influences on Auditory Behavioral, Neural, and Perceptual Processes: A Review.

In a naturalistic environment, auditory cues are often accompanied by information from other senses, which can be redundant with or complementary to the auditory information. Although the multisensory interactions derived from this combination of information and that shape auditory function are seen across all sensory modalities, our greatest body of knowledge to date centers on how vision influences audition. In this review, we attempt to capture the state of our understanding at this point in time regarding this topic. Following a general introduction, the review is divided into 5 sections. In the first section, we review the psychophysical evidence in humans regarding vision's influence in audition, making the distinction between vision's ability to enhance versus alter auditory performance and perception. Three examples are then described that serve to highlight vision's ability to modulate auditory processes: spatial ventriloquism, cross-modal dynamic capture, and the McGurk effect. The final part of this section discusses models that have been built based on available psychophysical data and that seek to provide greater mechanistic insights into how vision can impact audition. The second section reviews the extant neuroimaging and far-field imaging work on this topic, with a strong emphasis on the roles of feedforward and feedback processes, on imaging insights into the causal nature of audiovisual interactions, and on the limitations of current imaging-based approaches. These limitations point to a greater need for machine-learning-based decoding approaches toward understanding how auditory representations are shaped by vision. The third section reviews the wealth of neuroanatomical and neurophysiological data from animal models that highlights audiovisual interactions at the neuronal and circuit level in both subcortical and cortical structures. It also speaks to the functional significance of audiovisual interactions for two critically important facets of auditory perception-scene analysis and communication. The fourth section presents current evidence for alterations in audiovisual processes in three clinical conditions: autism, schizophrenia, and sensorineural hearing loss. These changes in audiovisual interactions are postulated to have cascading effects on higher-order domains of dysfunction in these conditions. The final section highlights ongoing work seeking to leverage our knowledge of audiovisual interactions to develop better remediation approaches to these sensory-based disorders, founded in concepts of perceptual plasticity in which vision has been shown to have the capacity to facilitate auditory learning.

Emerging biomarkers in autism spectrum disorder: a systematic review.

Autism spectrum disorder (ASD) affects approximately 2% of children in the United States (US) yet its etiology is unclear and effective treatments are lacking. Therapeutic interventions are most effective if started early in life, yet diagnosis often remains delayed, partly because the diagnosis of ASD is based on identifying abnormal behaviors that may not emerge until the disorder is well established. Biomarkers that identify children at risk during the pre-symptomatic period, assist with early diagnosis, confirm behavioral observations, stratify patients into subgroups, and predict therapeutic response would be a great advance. Here we underwent a systematic review of the literature on ASD to identify promising biomarkers and rated the biomarkers in regards to a Level of Evidence and Grade of Recommendation using the Oxford Centre for Evidence-Based Medicine scale. Biomarkers identified by our review included physiological biomarkers that identify neuroimmune and metabolic abnormalities, neurological biomarkers including abnormalities in brain structure, function and neurophysiology, subtle behavioral biomarkers including atypical development of visual attention, genetic biomarkers and gastrointestinal biomarkers. Biomarkers of ASD may be found prior to birth and after diagnosis and some may predict response to specific treatments. Many promising biomarkers have been developed for ASD. However, many biomarkers are preliminary and need to be validated and their role in the diagnosis and treatment of ASD needs to be defined. It is likely that biomarkers will need to be combined to be effective to identify ASD early and guide treatment.