Adaptation to Binocular Anticorrelation Results in Increased Neural Excitability

Distinct early and late neural mechanisms regulate feature-specific sensory adaptation in the human visual system

A canonical feature of sensory systems is that they adapt to prolonged or repeated inputs, suggesting the brain encodes the temporal context in which stimuli are embedded. Sensory adaptation has been observed in the central nervous systems of many animal species, using techniques sensitive to a broad range of spatiotemporal scales of neural activity. Two competing models have been proposed to account for the phenomenon. One assumes that adaptation reflects reduced neuronal sensitivity to sensory inputs over time (the "fatigue" account); the other posits that adaptation arises due to increased neuronal selectivity (the "sharpening" account). To adjudicate between these accounts, we exploited the well-known "tilt aftereffect", which reflects adaptation to orientation information in visual stimuli. We recorded whole-brain activity with millisecond precision from human observers as they viewed oriented gratings before and after adaptation, and used inverted encoding modeling to characterize feature-specific neural responses. We found that both fatigue and sharpening mechanisms contribute to the tilt aftereffect, but that they operate at different points in the sensory processing cascade to produce qualitatively distinct outcomes. Specifically, fatigue operates during the initial stages of processing, consistent with tonic inhibition of feedforward responses, whereas sharpening occurs ~200 ms later, consistent with feedback or local recurrent activity. Our findings reconcile two major accounts of sensory adaptation, and reveal how this canonical process optimizes the detection of change in sensory inputs through efficient neural coding.

Image statistics determine the integration of visual cues to motion-in-depth

Motion-in-depth perception is critical in enabling animals to avoid hazards and respond to potential threats. For humans, important visual cues for motion-in-depth include changing disparity (CD) and changing image size (CS). The interpretation and integration of these cues depends upon multiple scene parameters, such as distance moved, object size and viewing distance, posing a significant computational challenge. We show that motion-in-depth cue integration depends upon sensitivity to the joint probabilities of the scene parameters determining these signals, and on the probability of CD and CS signals co-occurring. Models that took these factors into account predicted human performance in speed-in-depth and cue conflict discrimination tasks, where standard linear integration models could not. These results suggest that cue integration is affected by both the uncertainty of sensory signals and the mapping of those signals to real-world properties. Evidence of a role for such mappings demonstrates the importance of scene and image statistics to the processes underpinning cue integration and the perception of motion-in-depth.

Optimal Approach for Signal Detection in Steady-State Visual Evoked Potentials in Humans Using Single-Channel EEG and Stereoscopic Stimuli

In EEG studies, one of the most common ways to detect a weak periodic signal in the steady-state visual evoked potential (SSVEP) is spectral evaluation, a process that detects peaks of power present at notable temporal frequencies. However, the presence of noise decreases the signal-to-noise ratio (SNR), which in turn lowers the probability of successful detection of these spectral peaks. In this paper, using a single EEG channel, we compare the detection performance of four different metrics to analyse the SSVEP: two metrics that use spectral power density, and two other metrics that use phase coherency. We employ these metrics find weak signals with a known temporal frequency hidden in the SSVEP, using both simulation and real data from a stereoscopic apparent depth movement perception task. We demonstrate that out of these metrics, the phase coherency analysis is the most sensitive way to find weak signals in the SSVEP, provided that the phase information of the stimulus eliciting the SSVEP is preserved.

Dichoptic Spatial Contrast Sensitivity Reflects Binocular Balance in Normal and Stereoanomalous Subjects

Purpose

To study binocular balance by comparing dichoptic and standard monocular contrast sensitivity function (CSF) in stereonormal and stereoanomalous/stereoblind amblyopic subjects.

Methods

Sixteen amblyopes and 17 controls participated. Using the capability of the passive three-dimensional display, we measured their CSF both monocularly and dichoptically at spatial frequencies 0.5, 1, 2, 4, and 8 cpds using achromatic Gabor patches on a luminance noise background. During monocular stimulation, the untested eye was covered, while for the dichoptic stimulation the untested eye viewed background noise. Dichoptic CSF of both eyes was acquired within one block.

Results

In patients with central fixation, dichoptic viewing had a large negative impact on the CSF of the amblyopic eye, although it hardly affected that of the dominant eye. In contrast, dichoptic viewing had a small but significant effect on both eyes for controls. In addition, all participants lay along a continuum in terms of how much their two eyes were affected by dichoptic stimulation: by using two predefined contrast sensitivity ratios, namely, amblyopic sensitivity decrement and dichoptic sensitivity decrement, not only did we find a significant correlation between these variables among all participants, but also the two groups were identified with minimum error using a cluster analysis.

Conclusions

Dichoptic CSF may be considered to measure visual performance in patients with altered binocular vision, because it better reflects the visual capacity of the amblyopic eye than the standard monocular examinations. It may also be a more reliable parameter to assess the efficacy of modern approaches to treat amblyopia.