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Stronger Neural Modulation by Visual Motion Intensity in Autism Spectrum Disorders.

Peiker I, Schneider TR, Milne E, Schöttle D, Vogeley K, Münchau A, Schunke O, Siegel M, Engel AK, David N - PLoS ONE (2015)

Bottom Line: A polynomial regression analysis revealed that gamma-band power increased significantly stronger with motion coherence in ASD compared to controls, suggesting excessive visual activation with increasing stimulus intensity originating from motion-responsive visual areas V3, V6 and hMT/V5.Enhanced neural responses with increasing stimulus intensity suggest an enhanced response gain in ASD.Thus, our data suggest that a disturbed excitatory-inhibitory balance underlies enhanced neural responses to coherent motion in ASD.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

ABSTRACT
Theories of autism spectrum disorders (ASD) have focused on altered perceptual integration of sensory features as a possible core deficit. Yet, there is little understanding of the neuronal processing of elementary sensory features in ASD. For typically developed individuals, we previously established a direct link between frequency-specific neural activity and the intensity of a specific sensory feature: Gamma-band activity in the visual cortex increased approximately linearly with the strength of visual motion. Using magnetoencephalography (MEG), we investigated whether in individuals with ASD neural activity reflect the coherence, and thus intensity, of visual motion in a similar fashion. Thirteen adult participants with ASD and 14 control participants performed a motion direction discrimination task with increasing levels of motion coherence. A polynomial regression analysis revealed that gamma-band power increased significantly stronger with motion coherence in ASD compared to controls, suggesting excessive visual activation with increasing stimulus intensity originating from motion-responsive visual areas V3, V6 and hMT/V5. Enhanced neural responses with increasing stimulus intensity suggest an enhanced response gain in ASD. Response gain is controlled by excitatory-inhibitory interactions, which also drive high-frequency oscillations in the gamma-band. Thus, our data suggest that a disturbed excitatory-inhibitory balance underlies enhanced neural responses to coherent motion in ASD.

No MeSH data available.


Related in: MedlinePlus

Time-frequency representation.The MEG signal was averaged across posterior sensors (highlighted on the schematic head) and all levels of motion coherence, for both groups (left: ASD, right: Control). All responses were quantified as the percentage of change in signal amplitude relative to a blank prestimulus baseline interval (400 ms before up to stimulus onset).
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pone.0132531.g002: Time-frequency representation.The MEG signal was averaged across posterior sensors (highlighted on the schematic head) and all levels of motion coherence, for both groups (left: ASD, right: Control). All responses were quantified as the percentage of change in signal amplitude relative to a blank prestimulus baseline interval (400 ms before up to stimulus onset).

Mentions: Data were transformed from axial to planar gradient configuration. Therefore, the planar gradient at a given sensor location were approximated by comparing the field at that sensor with its neighbors. Two orthogonal gradients in both the horizontal and the vertical direction were computed separately and then combined. After that, all spectral estimates were computed using the multi-taper method [43] based on discrete prolate spheroidal (Slepian) sequences. We computed spectral estimates across equally scaled frequencies f from 5 to 150 Hz (in 5 Hz steps) and time t from -400 to 650 ms (in 50 ms steps). A sliding window method was used with fixed taper length (200 ms) and fixed frequency smoothing (± 10 Hz). All transformations to the frequency domain were performed on the single trial level prior to averaging across trials. Thus, spectral estimates contained signal components phase-locked and non-phase-locked to the stimulus onset. The resulting total power is reported (e.g., in Fig 2) as percentage of change at frequency f relative to the pre-stimulus baseline (400 ms before up to stimulus onset) according to:Ppoststimulus(t,f)=100⋅(Ppoststimulus(t,f)−Pprestimulus(f))/Pprestimulus(f)Thus, the average baseline power was first subtracted from the power of the poststimulus interval and the difference was then divided by the average baseline power.


Stronger Neural Modulation by Visual Motion Intensity in Autism Spectrum Disorders.

Peiker I, Schneider TR, Milne E, Schöttle D, Vogeley K, Münchau A, Schunke O, Siegel M, Engel AK, David N - PLoS ONE (2015)

Time-frequency representation.The MEG signal was averaged across posterior sensors (highlighted on the schematic head) and all levels of motion coherence, for both groups (left: ASD, right: Control). All responses were quantified as the percentage of change in signal amplitude relative to a blank prestimulus baseline interval (400 ms before up to stimulus onset).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4492621&req=5

pone.0132531.g002: Time-frequency representation.The MEG signal was averaged across posterior sensors (highlighted on the schematic head) and all levels of motion coherence, for both groups (left: ASD, right: Control). All responses were quantified as the percentage of change in signal amplitude relative to a blank prestimulus baseline interval (400 ms before up to stimulus onset).
Mentions: Data were transformed from axial to planar gradient configuration. Therefore, the planar gradient at a given sensor location were approximated by comparing the field at that sensor with its neighbors. Two orthogonal gradients in both the horizontal and the vertical direction were computed separately and then combined. After that, all spectral estimates were computed using the multi-taper method [43] based on discrete prolate spheroidal (Slepian) sequences. We computed spectral estimates across equally scaled frequencies f from 5 to 150 Hz (in 5 Hz steps) and time t from -400 to 650 ms (in 50 ms steps). A sliding window method was used with fixed taper length (200 ms) and fixed frequency smoothing (± 10 Hz). All transformations to the frequency domain were performed on the single trial level prior to averaging across trials. Thus, spectral estimates contained signal components phase-locked and non-phase-locked to the stimulus onset. The resulting total power is reported (e.g., in Fig 2) as percentage of change at frequency f relative to the pre-stimulus baseline (400 ms before up to stimulus onset) according to:Ppoststimulus(t,f)=100⋅(Ppoststimulus(t,f)−Pprestimulus(f))/Pprestimulus(f)Thus, the average baseline power was first subtracted from the power of the poststimulus interval and the difference was then divided by the average baseline power.

Bottom Line: A polynomial regression analysis revealed that gamma-band power increased significantly stronger with motion coherence in ASD compared to controls, suggesting excessive visual activation with increasing stimulus intensity originating from motion-responsive visual areas V3, V6 and hMT/V5.Enhanced neural responses with increasing stimulus intensity suggest an enhanced response gain in ASD.Thus, our data suggest that a disturbed excitatory-inhibitory balance underlies enhanced neural responses to coherent motion in ASD.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

ABSTRACT
Theories of autism spectrum disorders (ASD) have focused on altered perceptual integration of sensory features as a possible core deficit. Yet, there is little understanding of the neuronal processing of elementary sensory features in ASD. For typically developed individuals, we previously established a direct link between frequency-specific neural activity and the intensity of a specific sensory feature: Gamma-band activity in the visual cortex increased approximately linearly with the strength of visual motion. Using magnetoencephalography (MEG), we investigated whether in individuals with ASD neural activity reflect the coherence, and thus intensity, of visual motion in a similar fashion. Thirteen adult participants with ASD and 14 control participants performed a motion direction discrimination task with increasing levels of motion coherence. A polynomial regression analysis revealed that gamma-band power increased significantly stronger with motion coherence in ASD compared to controls, suggesting excessive visual activation with increasing stimulus intensity originating from motion-responsive visual areas V3, V6 and hMT/V5. Enhanced neural responses with increasing stimulus intensity suggest an enhanced response gain in ASD. Response gain is controlled by excitatory-inhibitory interactions, which also drive high-frequency oscillations in the gamma-band. Thus, our data suggest that a disturbed excitatory-inhibitory balance underlies enhanced neural responses to coherent motion in ASD.

No MeSH data available.


Related in: MedlinePlus