Deficient brainstem encoding of pitch in children with Autism Spectrum Disorders

Russo, Nicole; Skoe, Erika; Trommer, Barbara L.; Nicol, Trent; Zecker, Steven G.; Bradlow, Ann R.; Kraus, Nina

doi:10.1016/j.clinph.2008.01.108

Cited by 194 publications

(185 citation statements)

References 60 publications

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“…As such, the test decouples higher cognitive abilities and functions (e.g., deficits in attention or linguistic abilities) from the expression of the basic temporal cues at the earlier auditory stages, thus pointing to the possible origin of the observed impairments. Finally, an attractive aspect of the ABR test is its suitability for infants and other noncooperative subjects, because it requires no feedback or even conscious listening (14). The implications of the Ruggles et al study (8) are numerous and important.…”

Section: The Author Declares No Conflict Of Interestmentioning

confidence: 99%

Hearing impairments hidden in normal listeners

Shamma

2011

Proc. Natl. Acad. Sci. U.S.A.

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Section: The Author Declares No Conflict Of Interestmentioning

confidence: 99%

Hearing impairments hidden in normal listeners

Shamma

2011

Proc. Natl. Acad. Sci. U.S.A.

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“…Before averaging, data were filtered off-line with a bandpass filter from 70 to 1500 Hz and epoched in 196 ms bins. Epochs with any activity exceeding a range of 35 V were rejected off-line (Russo et al, 2008). A minimum of 1604 trials was averaged in each condition.…”

Section: Methodsmentioning

confidence: 99%

Novelty Detection in the Human Auditory Brainstem

Slabu¹,

Grimm²,

Escera³

2012

J. Neurosci.

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Auditory deviance detection has been associated with a human auditory-evoked potential (AEP), the mismatch negativity, generated in the auditory cortex 100 -200 ms from sound change onset. Yet, single-unit recordings in animals suggest much earlier (ϳ20 -40 ms), and anatomically lower (i.e., thalamus and midbrain) deviance detection. In humans, recordings of the scalp middle-latency AEPs have confirmed early (ϳ30 -40 ms) deviance detection. However, involvement of the human auditory brainstem in deviance detection has not yet been demonstrated. Here we recorded the auditory brainstem frequency-following response (FFR) to consonant-vowel stimuli (/ba/, /wa/) in young adults, with stimuli arranged in oddball and reversed oddball blocks (deviant probability, p ϭ 0.2), allowing for the comparison of FFRs to the same physical stimuli presented in different contextual roles. Whereas no effect was observed for the /wa/ syllable, we found for the /ba/ syllable a reduction in the brainstem FFR to deviant stimuli compared with standard ones and to similar stimuli arranged in a control block, with five equiprobable, rarely occurring sounds. These findings demonstrate that the human auditory brainstem is able to encode regularities in the recent auditory past to detect novel events, and confirm the multiple anatomical and temporal scales of human deviance detection.

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“…For example, in the auditory system, enhanced performance is reported in autism when a discrimination task is performed using pure tones, but no difference or deficits are observed when the stimuli are more complex (65)(66)(67). Consider that the amount of processing, and thus the number of processing stages (e.g., hierarchically organized brain regions), required to analyze sensory information is linked to the complexity of the stimulus.…”

Section: Simple Vs Complex Stimulimentioning

confidence: 99%

A computational perspective on autism

Rosenberg

Patterson

Angelaki

2015

Proc. Natl. Acad. Sci. U.S.A.

149

151

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Autism is a neurodevelopmental disorder that manifests as a heterogeneous set of social, cognitive, motor, and perceptual symptoms. This system-wide pervasiveness suggests that, rather than narrowly impacting individual systems such as affection or vision, autism may broadly alter neural computation. Here, we propose that alterations in nonlinear, canonical computations occurring throughout the brain may underlie the behavioral characteristics of autism. One such computation, called divisive normalization, balances a neuron's net excitation with inhibition reflecting the overall activity of the neuronal population. Through neural network simulations, we investigate how alterations in divisive normalization may give rise to autism symptomatology. Our findings show that a reduction in the amount of inhibition that occurs through divisive normalization can account for perceptual consequences of autism, consistent with the hypothesis of an increased ratio of neural excitation to inhibition (E/I) in the disorder. These results thus establish a bridge between an E/I imbalance and behavioral data on autism that is currently absent. Interestingly, our findings implicate the context-dependent, neuronal milieu as a key factor in autism symptomatology, with autism reflecting a less "social" neuronal population. Through a broader discussion of perceptual data, we further examine how altered divisive normalization may contribute to a wide array of the disorder's behavioral consequences. These analyses show how a computational framework can provide insights into the neural basis of autism and facilitate the generation of falsifiable hypotheses. A computational perspective on autism may help resolve debates within the field and aid in identifying physiological pathways to target in the treatment of the disorder.A utism is a neurodevelopmental disorder that is dramatically increasing in prevalence (Fig. 1). Recent data place the number of children being diagnosed with autism in the United States at 1 in 68, more than doubling in the last decade (1-4). The disorder is highly pervasive, affecting individuals at cognitive, motor, and perceptual levels. It is furthermore a "spectrum disorder," with symptoms that manifest in varying degrees across individuals. This heterogeneity presents significant challenges to establishing a comprehensive characterization of the disorder.Research investigating the genetic and molecular basis of autism implicates over 100 genes (5), many of which are involved in synaptic development and function (6-8). As such, one prominent hypothesis is that autism arises from a neurophysiological excitation-to-inhibition (E/I) imbalance (9, 10). However, the connection between an E/I imbalance and the behavioral characteristics of the disorder remains unclear. Considering the pervasive nature of autism, and the covariance of loosely related symptoms (11-14), one possibility is that an E/I imbalance widely affects neural computation, in turn giving rise to the broad behavioral symptoms recognized as autism.Here,...

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Deficient brainstem encoding of pitch in children with Autism Spectrum Disorders

Abstract: Our findings may have implications for diagnostic and remediation strategies in a subset of children with ASD and open up an avenue for future investigations.

Cited by 194 publications

References 60 publications

Hearing impairments hidden in normal listeners

Hearing impairments hidden in normal listeners

Novelty Detection in the Human Auditory Brainstem

A computational perspective on autism

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