Visual Evoked Potential Abnormalities in Phelan-McDermid Syndrome

Siper, Paige M.; Rowe, Mikaela; Guillory, Sylvia; Rouhandeh, Audrey; George-Jones, Julia; Tavassoli, Teresa; Lurie, Stacey; Zweifach, Jessica; Weissman, Jordana; Foss‐Feig, Jennifer H.; Halpern, Danielle; Trelles, M. Pilar; Mulhern, Maureen; Brittenham, Chloe; Gordon, James; Zemon, Vance; Buxbaum, Joseph D.; Kolevzon, Alexander

doi:10.1016/j.jaac.2021.07.006

Cited by 6 publications

(4 citation statements)

References 40 publications

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“…This observed preservation of early auditory habituation parallels pre-clinical findings in at least one Shank3 mouse model that found no disruption of sensory gating ( Drapeau et al, 2018 ). These results serve as a contrast to findings of reduced electrophysiological amplitude in response to visual stimuli in individuals with PMS ( Siper et al, 2021 ), suggesting dissociation of cortical processing across at least these two sensory domains. Future research should also assess whether cortical responses to somatosensory stimulation resemble vision and parallel the behavioral tactile hyposensitivity found in PMS or if they are incongruent as with audition.…”

Section: Discussioncontrasting

confidence: 99%

Neural Markers of Auditory Response and Habituation in Phelan-McDermid Syndrome

et al. 2022

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Phelan-McDermid Syndrome (PMS) is a rare genetic disorder caused by deletion or sequence variation in the SHANK3 gene at terminal chromosome 22 that confers high likelihood of comorbid autism spectrum disorder (ASD). Whereas individuals with idiopathic ASD (iASD) can demonstrate diverse patterns of sensory differences, PMS is mainly characterized by sensory hyporesponsiveness. This study used electrophysiology and a passive auditory habituation paradigm to test for neural markers of hyporesponsiveness. EEG was recorded from 15 individuals with PMS, 15 with iASD, and 16 with neurotypical development (NT) while a series of four consecutive 1,000 Hz tones was repeatedly presented. We found intact N1, P2, and N2 event-related potentials (ERPs) and habituation to simple auditory stimuli, both in individuals with iASD and in those with PMS. Both iASD and PMS groups showed robust responses to the initial tone and decaying responses to each subsequent tone, at levels comparable to the NT control group. However, in PMS greater initial N1 amplitude and habituation were associated with auditory hypersensitivity, and P2 habituation correlated with ASD symptomatology. Additionally, further classification of the PMS cohort into genetic groupings revealed dissociation of initial P2 amplitude and habituation of N1 based on whether the deletions included additional genes beyond solely SHANK3 and those not thought to contribute to phenotype. These results provide preliminary insight into early auditory processing in PMS and suggest that while neural response and habituation is generally preserved in PMS, genotypic and phenotypic characteristics may drive some variability. These initial findings provide early evidence that the robust pattern of behavioral hyporesponsiveness in PMS may be due, at least in audition, to higher order factors.

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Section: Discussioncontrasting

confidence: 99%

Neural Markers of Auditory Response and Habituation in Phelan-McDermid Syndrome

et al. 2022

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“…Given overlap with the sample used in the previous study (Siper et al, 2016), the current study included additional useable data from 12 nonautistic and 41 autistic children with the long condition, and 13 nonautistic and 40 autistic children with the short condition. (Since this work was submitted, an article is now in press with a focus on Phelan‐McDermid syndrome using a similar sample, analysis of MSC values, and amplitudes of time‐domain deflections [P 60 ‐N 75 and N 75 ‐P 100 , but not P 100 ‐N 135 ], but it does not include the novel measures and techniques introduced here [analysis of total power, signal power, noise power within each frequency band, and correlations of time‐domain and frequency‐domain measures] (Siper et al, 2021). When possible, monocular and binocular visual acuities were measured using an optotype chart at 114 cm from the screen.…”

Section: Methodsmentioning

confidence: 99%

Objective frequency analysis of transient visual evoked potentials in autistic children

et al. 2021

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Visual evoked potentials (VEPs) provide a means to examine neural mechanisms in autism with high temporal resolution. Conventional VEP analysis relies on subjective inspection of a few points (peaks and troughs) in the time‐domain waveform. The current study applied power spectral analysis and magnitude‐squared coherence (MSC) statistics (frequency‐domain measures) to VEPs recorded during 1‐minute runs and with a recently developed short‐duration technique that allow for objective examination of the responses (Zemon & Gordon, European Journal of Neuroscience, 2018, 48, 1765–1788) from nonautistic and autistic children. Results indicate that, for both groups, early time‐domain measures (P60, N75, P100) are highly correlated with middle‐ and high‐frequency (14–28 and 30–48 Hz, respectively) mechanisms, and late measures are highly correlated with a low‐frequency (6–12 Hz) mechanism. One frequency‐domain measure (power in the middle‐frequency band) is capable of predicting the key amplitude measure (N75‐P100) with high accuracy. MSC and power measures were combined to yield separate measures of signal and noise strength to evaluate alternate hypotheses in autism. Linear mixed‐effects modeling demonstrated selective differences in early time‐domain and middle‐to‐high frequency‐domain measures in autistic children as compared to nonautistic children given both recording techniques, implicating weaker excitatory input to the cortex. Receiver‐operating‐characteristic curve analysis showed predictive diagnostic accuracy for middle‐ and high‐frequency bands based on MSC. These findings support the value of frequency analysis measures (power spectral analysis and MSC) in the objective examination of neural differences in autism. Lay Summary Visual evoked potentials (VEPs) are used to assess neural mechanisms. Typically, VEPs are analyzed by subjective examination of time‐series waveforms; but here objective techniques were applied to quantify VEP frequency components to investigate neural differences between autistic and nonautistic children. The objective measures demonstrate group differences in brain function that point to weaker excitatory input to the cortex in autism.

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“…Reports from ASD in humans and, recently, in different animal models of neurodevelopmental disorders associated with ASD showed alterations in visual processing 58 , 64 , 71 . Recently, evidence of an increased sensitivity of V1 neurons to stimuli with high spatial frequency and low contrast was reported in a mouse model of MeCP2 duplication syndrome 74 .…”

Section: Introductionmentioning

confidence: 98%

“…Similarly, people with ASD showed enhancement activity in areas related to visual perception when they were exposed to objects, faces, and words in a visual perception task 58 . Importantly, quantification of visual attention showed that ASD individuals had a more robust image center bias regardless of object distributions and reduced saliency for faces 71 , besides an EEG study performed in children with ASD (Phelan–McDermid syndrome and idiopathic ASD) displayed abnormal waveforms of visual evoked potentials 64 . All these data strongly suggest that ASD individuals exhibit atypical visual processing.…”

Section: Introductionmentioning

confidence: 98%

Haploinsufficiency of Shank3 increases the orientation selectivity of V1 neurons

Ortiz-Cruz

Marquez

Linares-García

et al. 2022

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Autism spectrum disorder (ASD) is a neurodevelopmental disorder whose hallmarks are social deficits, language impairment, repetitive behaviors, and sensory alterations. It has been reported that patients with ASD show differential activity in cortical regions, for instance, increased neuronal activity in visual processing brain areas and atypical visual perception compared with healthy subjects. The causes of these alterations remain unclear, although many studies demonstrate that ASD has a strong genetic correlation. An example is Phelan–McDermid syndrome, caused by a deletion of the Shank3 gene in one allele of chromosome 22. However, the neuronal consequences relating to the haploinsufficiency of Shank3 in the brain remain unknown. Given that sensory abnormalities are often present along with the core symptoms of ASD, our goal was to study the tuning properties of the primary visual cortex to orientation and direction in awake, head-fixed Shank3+/− mice. We recorded neural activity in vivo in response to visual gratings in the primary visual cortex from a mouse model of ASD (Shank3+/− mice) using the genetically encoded calcium indicator GCaMP6f, imaged with a two-photon microscope through a cranial window. We found that Shank3+/− mice showed a higher proportion of neurons responsive to drifting gratings stimuli than wild-type mice. Shank3+/− mice also show increased responses to some specific stimuli. Furthermore, analyzing the distributions of neurons for the tuning width, we found that Shank3+/− mice have narrower tuning widths, which was corroborated by analyzing the orientation selectivity. Regarding this, Shank3+/− mice have a higher proportion of selective neurons, specifically neurons showing increased selectivity to orientation but not direction. Thus, the haploinsufficiency of Shank3 modified the neuronal response of the primary visual cortex.

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Visual Evoked Potential Abnormalities in Phelan-McDermid Syndrome

Cited by 6 publications

References 40 publications

Neural Markers of Auditory Response and Habituation in Phelan-McDermid Syndrome

Neural Markers of Auditory Response and Habituation in Phelan-McDermid Syndrome

Objective frequency analysis of transient visual evoked potentials in autistic children

Haploinsufficiency of Shank3 increases the orientation selectivity of V1 neurons

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