Stronger Neural Modulation by Visual Motion Intensity in Autism Spectrum Disorders

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 excitatoryinhibitory balance underlies enhanced neural responses to coherent motion in ASD

Bifurcation study of a neural field competition model with an application to perceptual switching in motion integration.

Perceptual multistability is a phenomenon in which alternate interpretations of a fixed stimulus are perceived intermittently. Although correlates between activity in specific cortical areas and perception have been found, the complex patterns of activity and the underlying mechanisms that gate multistable perception are little understood. Here, we present a neural field competition model in which competing states are represented in a continuous feature space. Bifurcation analysis is used to describe the different types of complex spatio-temporal dynamics produced by the model in terms of several parameters and for different inputs. The dynamics of the model was then compared to human perception investigated psychophysically during long presentations of an ambiguous, multistable motion pattern known as the barberpole illusion. In order to do this, the model is operated in a parameter range where known physiological response properties are reproduced whilst also working close to bifurcation. The model accounts for characteristic behaviour from the psychophysical experiments in terms of the type of switching observed and changes in the rate of switching with respect to contrast. In this way, the modelling study sheds light on the underlying mechanisms that drive perceptual switching in different contrast regimes. The general approach presented is applicable to a broad range of perceptual competition problems in which spatial interactions play a role

Processing of kinetically defined boundaries in areas V1 and V2 of the macaque monkey

We recorded responses in 107 cells in the primary visual area V1 and 113 cells in the extrastriate visual area V2 while presenting a kinetically defined edge or a luminance contrast edge. Cells meeting statistical criteria for responsiveness and orientation selectivity were classified as selective for the orientation of the kinetic edge if the preferred orientation for a kinetic boundary stimulus remained essentially the same even when the directions of the two motion components defining that boundary were changed by 90 degrees. In area V2, 13 of the 113 cells met all three requirements, whereas in V1, only 4 cells met the criteria of 107 that were tested, and even these demonstrated relatively weak selectivity. Correlation analysis showed that V1 and V2 populations differed greatly (P &lt; 1.0 x 10(-6), Student's t-test) in their selectively for specific orientations of kinetic edge stimuli. Neurons in V2 that were selective for the orientation of a kinetic boundary were further distinguished from their counterparts in V1 in displaying a strong, sharply tuned response to a luminance edge of the same orientation. We concluded that selectivity for the orientation of kinetically defined boundaries first emerges in area V2 rather than in primary visual cortex. An analysis of response onset latencies in V2 revealed that cells selective for the orientation of the motion-defined boundary responded about 40 ms more slowly, on average, to the kinetic edge stimulus than to a luminance edge. In nonselective cells, that is, those presumably responding only to the local motion in the stimulus, this difference was only about 20 ms. Response latencies for the luminance edge were indistinguishable in KE-selective and -nonselective neurons. We infer that while responses to luminance edges or local motion are indigenous to V2, KE-selective responses may involve feedback entering the ventral stream at a point downstream with respect to V2.</p

Response latency of macaque area MT/V5 neurons and its relationship to stimulus parameters

A total of 310 MT/V5 single cells were tested in anesthetized, paralyzed macaque monkeys with moving random-dot stimuli. At optimum stimulus parameters, latencies ranged from 35 to 325 ms with a mean of 87 +/- 45 (SD) ms. By examining the relationship between latency and response levels, stimulus parameters, and stimulus selectivities, we attempted to isolate the contributions of these factors to latency and to identify delays representing intervening synapses (circuitry) and signal processing (flow of information through that circuitry). First, the relationship between stimulus parameters and latency was investigated by varying stimulus speed and direction for individual cells. Resulting changes in latencies were explainable in terms of response levels corresponding to how closely the actual stimulus matched the preferred stimulus of the cell. Second, the relationship between stimulus selectivity and latency across the population of cells was examined using the optimum speed and direction of each neuron. A weak tendency for cells tuned for slow speeds to have longer latencies was explainable by lower response rates among slower-tuned neurons. In contrast, sharper direction tuning was significantly associated with short latencies even after taking response rate into account, (P = 0.002, ANCOVA). Accordingly, even the first 10 ms of the population response fully demonstrates direction tuning. A third study, which examined the relationship between antagonistic surrounds and latency, revealed a significant association between the strength of the surround and the latency that was independent of response levels (P &lt; 0.002, ANCOVA). Neurons having strong surrounds exhibited latencies averaging 20 ms longer than those with little or no surround influence, suggesting that neurons with surrounds represent a later stage in processing with one or more intervening synapses. The laminar distribution of latencies closely followed the average surround antagonism in each layer, increasing with distance from input layer IV but precisely mirroring response levels, which were highest near the input layer and gradually decreased with distance from input layer IV. Layer II proved the exception with unexpectedly shorter latencies (P &lt; 0.02, ANOVA) yet showing only modest response levels. The short latency and lack of strong direction tuning in layer II is consistent with input from the superior colliculus. Finally, experiments with static stimuli showed that latency does not vary with response rate for such stimuli, suggesting a fundamentally different mode of processing than that for a moving stimulus.</p