Biology subjects

Geisler, W. S.

Publications and source records attributed to Geisler, W. S..

3 recordsLinked to original sources

bioRxiv2021

Stereo Slant Discrimination of Planar 3D Surfaces: Standard vs. Planar Cross-Correlation

Binocular stereo cues are important for discriminating 3D surface orientation, especially at near distances. We devised a single-interval task where observers discriminated the slant of a densely textured planar test surface relative to a textured planar surround reference surface. Although surfaces were rendered with correct perspective, the stimuli were designed so that the binocular cues dominated performance. Slant discrimination performance was measured as a function of the reference slant and the level of uncorrelated white noise added to the test-plane images in the left and right eye. We compared human performance with an approximate ideal observer (planar cross correlation, PCC) and two sub-ideal observers. The PCC observer uses the image in one eye and back projection to predict the test image in the other eye for all possible slants, tilts, and distances. The estimated slant, tilt, and distance are determined by the prediction that most closely matches the measured image in the other eye. The first sub-ideal observer (local PCC, LPCC) applies planar cross correlation over local neighborhoods and then pools estimates across the test plane. The second sub-optimal observer (standard cross correlation, SCC), uses only positional disparity information. We find that the ideal observer (PCC) and the first sub-ideal observer (LPCC) outperform the second sub-ideal observer (SCC), demonstrating the benefits of structural disparities. We also find that all three model observers can account for human performance, if two free parameters are included: a fixed small level of internal estimation noise, and a fixed overall efficiency scalar on slant discriminability. PrecisWe measured human stereo slant discrimination thresholds for accurately-rendered textured surfaces designed so that performance is dominated by binocular-disparity cues. We compared human performance with an approximate ideal observer and two sub-ideal observers.

animal behavior and cognition↗

bioRxiv2021

Similar neural and perceptual masking effects of low-power optogenetic stimulation in primate V1

Can direct stimulation of primate V1 substitute for a visual stimulus and mimic its perceptual effect? To address this question, we developed an optical-genetic toolkit to "read" neural population responses using widefield calcium imaging, while simultaneously using optogenetics to "write" neural responses into V1 of behaving macaques. We focused on the phenomenon of visual masking, where detection of a dim target is significantly reduced by a co-localized medium-brightness pedestal. Using our toolkit, we tested whether V1 optogenetic stimulation can recapitulate the perceptual masking effect of a visual pedestal. We find that, similar to a visual pedestal, low-power optostimulation can significantly reduce visual detection sensitivity, that a sublinear interaction between visual and optogenetic evoked V1 responses could account for this perceptual effect, and that these neural and behavioral effects are spatially selective. Our toolkit and results open the door for further exploration of perceptual substitutions by direct stimulation of sensory cortex.

neuroscience↗

bioRxiv2020

Similar masking effects of natural backgrounds on detection performances in humans, macaques, and macaque-V1 population responses

Visual systems evolve to process the stimuli that arise in the organisms natural environment and hence to fully understand the neural computations in the visual system it is important to measure behavioral and neural responses to natural visual stimuli. Here we measured psychometric and neurometric functions and thresholds in the macaque monkey for detection of a windowed sine-wave target in uniform backgrounds and in natural backgrounds of various contrasts. The neurometric functions and neurometric thresholds were obtained by near-optimal decoding of voltage-sensitive-dye-imaging (VSDI) responses at the retinotopic scale in primary visual cortex (V1). The results were compared with previous human psychophysical measurements made under the same conditions. We found that human and macaque behavioral thresholds followed the generalized Webers law as function of contrast, and that both the slopes and the intercepts of the threshold functions match each other up to a single scale factor. We also found that the neurometric thresholds followed the generalized Webers law and that the neurometric slopes and intercepts matched the behavioral slopes and intercepts up to a single scale factor. We conclude that human and macaque ability to detect targets in natural backgrounds are affected in the same way by background contrast, that these effects are consistent with population decoding at the retinotopic scale by down-stream circuits, and that the macaque monkey is an appropriate animal model for gaining an understanding of the neural mechanisms in humans for detecting targets in natural backgrounds. Finally, we discuss limitations of the current study and potential next steps. New & NoteworthyWe measured macaque detection performance in natural images and compared their performance to the detection sensitivity of neurophysiological responses recorded in the primary visual cortex (V1), and to the performance of human subjects. We found that (i) human and macaque behavioral performances are in quantitative agreement, (ii) are consistent with near-optimal decoding of V1 population responses. SignificanceNatural selection guarantees that neural computations will be matched to the task-relevant natural stimuli in the organisms environment, and thus it is crucial to measure behavioral and neural responses to natural stimuli. We measured the ability of macaque monkeys to detect targets in natural images and compared their performance to neurophysiological responses recorded in the macaques primary visual cortex (V1), and to the performance of humans under the same conditions. We found that (i) human and macaque behavioral performance are in quantitative agreement, (ii) are consistent with near-optimal population decoding of V1 neural responses, and (iii) that the macaque monkey is an appropriate animal model for gaining understanding of the neural mechanisms in humans for detecting targets in natural backgrounds.

neuroscience↗