scholarly journals Predicting the partition of behavioral variability in speed perception with naturalistic stimuli

2019 ◽  
Author(s):  
Benjamin M. Chin ◽  
Johannes Burge
Keyword(s):  
Human Performance ◽  
Internal Noise ◽  
Ideal Observer ◽  
Limiting Factor ◽  
Behavioral Variability ◽  
Visual Neuroscience ◽  
Stimulus Variability ◽  
Critical Experiment ◽  
Perceptual Performance ◽  
Ideal Observer Analysis

AbstractA core goal of visual neuroscience is to predict human perceptual performance from natural signals. Performance in any natural task can be impacted by at least three sources of uncertainty: stimulus variability, internal noise, and sub-optimal computations. Determining the relative importance of these factors has been a focus of interest for decades, but most successes have been achieved with simple tasks and simple stimuli. Drawing quantitative links directly from natural signals to perceptual performance has proven a substantial challenge. Here, we develop an image-computable (pixels in, estimates out) Bayesian ideal observer that makes optimal use of the statistics relating image movies to speed. The optimal computations bear striking resemblance to descriptive models proposed to account for neural activity in area MT. We develop a model based on the ideal, stimulate it with naturalistic signals, predict the behavioral signatures of each performance-limiting factor, and test the predictions in an interlocking series of speed discrimination experiments. The critical experiment collects human responses to repeated presentations of each unique image movie. The model, highly constrained by the earlier experiments, tightly predicts human response consistency without free parameters. This result implies that human observers use near-optimal computations to estimate speed, and that human performance is near-exclusively limited by natural stimulus variability and internal noise. The results demonstrate that human performance can be predicted from a task-specific statistical analysis of naturalistic stimuli, show that image-computable ideal observer analysis can be generalized from simple to natural stimuli, and encourage similar analyses in other domains.

scholarly journals Tactile orientation perception: an ideal observer analysis of human psychophysical performance in relation to macaque area 3b receptive fields

2015 ◽  
Vol 114 (6) ◽  
pp. 3076-3096 ◽  
Author(s):  
Ryan M. Peters ◽  
Phillip Staibano ◽  
Daniel Goldreich
Keyword(s):  
Cortical Neurons ◽  
Human Performance ◽  
Spatial Perception ◽  
Receptive Fields ◽  
Human Perception ◽  
Ideal Observer ◽  
Orientation Discrimination ◽  
Orientation Perception ◽  
Area 3B ◽  
The Ideal

The ability to resolve the orientation of edges is crucial to daily tactile and sensorimotor function, yet the means by which edge perception occurs is not well understood. Primate cortical area 3b neurons have diverse receptive field (RF) spatial structures that may participate in edge orientation perception. We evaluated five candidate RF models for macaque area 3b neurons, previously recorded while an oriented bar contacted the monkey's fingertip. We used a Bayesian classifier to assign each neuron a best-fit RF structure. We generated predictions for human performance by implementing an ideal observer that optimally decoded stimulus-evoked spike counts in the model neurons. The ideal observer predicted a saturating reduction in bar orientation discrimination threshold with increasing bar length. We tested 24 humans on an automated, precision-controlled bar orientation discrimination task and observed performance consistent with that predicted. We next queried the ideal observer to discover the RF structure and number of cortical neurons that best matched each participant's performance. Human perception was matched with a median of 24 model neurons firing throughout a 1-s period. The 10 lowest-performing participants were fit with RFs lacking inhibitory sidebands, whereas 12 of the 14 higher-performing participants were fit with RFs containing inhibitory sidebands. Participants whose discrimination improved as bar length increased to 10 mm were fit with longer RFs; those who performed well on the 2-mm bar, with narrower RFs. These results suggest plausible RF features and computational strategies underlying tactile spatial perception and may have implications for perceptual learning.

scholarly journals Ideal Observer Analysis of Overt Attention

2010 ◽  
Vol 10 (7) ◽  
pp. 12-12 ◽  
Author(s):  
W. S. Geisler
Keyword(s):  
Ideal Observer ◽  
Overt Attention ◽  
Ideal Observer Analysis

scholarly journals Cross inhibition from ON to OFF pathway improves the efficiency of contrast encoding in the mammalian retina

2012 ◽  
Vol 108 (10) ◽  
pp. 2679-2688 ◽  
Author(s):  
Zhiyin Liang ◽  
Michael A. Freed
Keyword(s):  
Spike Train ◽  
Ganglion Cells ◽  
Ideal Observer ◽  
Detection Accuracy ◽  
Low Contrast ◽  
Mammalian Retina ◽  
Ideal Observer Analysis ◽  
On And Off Pathways ◽  
Cross Inhibition

The retina is divided into parallel and mostly independent ON and OFF pathways, but the ON pathway “cross” inhibits the OFF pathway. Cross inhibition was thought to improve signal processing by the OFF pathway, but its effect on contrast encoding had not been tested experimentally. To quantify the effect of cross inhibition on the encoding of contrast, we presented a dark flash to an in vitro preparation of the mammalian retina. We then recorded excitatory currents, inhibitory currents, membrane voltages, and spikes from OFF α-ganglion cells. The recordings were subjected to an ideal observer analysis that used Bayesian methods to determine how accurately the recordings detected the dark flash. We found that cross inhibition increases the detection accuracy of currents and membrane voltages. Yet these improvements in encoding do not fully reach the spike train, because cross inhibition also hyperpolarizes the OFF α-cell below spike threshold, preventing small signals in the membrane voltages at low contrast from reaching the spike train. The ultimate effect of cross inhibition is to increase the accuracy with which the spike train detects moderate contrast, but reduce the accuracy with which it detects low contrast. In apparent compensation for the loss of accuracy at low contrast, cross inhibition, by hyperpolarizing the OFF α-cell, reduces the number of spikes required to detect the dark flash and thereby increases encoding efficiency.

Perceptual Classification Images from Vernier Acuity Masked by Noise

Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 2-2 ◽  
Author(s):  
A J Ahumada
Keyword(s):  
Fourier Transforms ◽  
Internal Noise ◽  
Discrimination Performance ◽  
Ideal Observer ◽  
Classification Rule ◽  
Horizontal Line ◽  
Vernier Acuity ◽  
Perceptual Classification ◽  
Classification Images ◽  
The Ideal

Letting external noise rather than internal noise limit discrimination performance allows information to be extracted about the observer's stimulus classification rule. A perceptual classification image is the correlation over trials between the noise amplitude at a spatial location and the observer's responses. If, for example, the observer followed the rule of the ideal observer, the response correlation image would be an estimate of the ideal observer filter, the difference between the two unmasked images being discriminated. Perceptual classification images were estimated for a Vernier discrimination task. The display screen had 48 pixels deg−1 horizontally and vertically. The no-offset image had a dark horizontal line of 4 pixels, a 1 pixel space, and 4 more dark pixels. Classification images were based on 1600 discrimination trials with the line contrast adjusted to keep the error rate near 25%. In the offset image, the second line was one pixel higher. Unlike the ideal observer filter (a horizontal dipole), the observer perceptual classification images are strongly oriented. Fourier transforms of the classification images had a peak amplitude near 1 cycle deg−1 and an orientation near 25 deg. The spatial spread is much more than image blur predicts, and probably indicates the spatial position uncertainty in the task.

Mechanisms of Whole-Body Vibration Effects on Human Performance

1983 ◽  
Vol 27 (6) ◽  
pp. 472-472
Author(s):  
John C. Guignard ◽  
Alvah C. Bittner ◽  
Mary M. Harbeson
Keyword(s):  
Human Performance ◽  
Physiological State ◽  
Whole Body Vibration ◽  
Whole Body ◽  
Future Research ◽  
Limiting Factor ◽  
Body Vibration ◽  
Long Duration ◽  
Performance Effects ◽  
Open Question

Oscillatory ship motion and vibration effects on crews in modern naval air and sea systems can be the limiting factor in mission performance. The mechanisms of these effects, however, have not yet been clearly delineated; nor have a practical taxonomy and standard methodology for distinguishing and evaluating the deleterious action of whole-body vibratory motion on human performance been established. Some effects of vibration on performance appear to be directly attributable to immediate mechanical disruption of input and /or output (i.e., interference at the points of contact—displays or controls—between operator and task). Far more meager is clear evidence for time-dependent disruptive or degrading effects of vibration on central cognitive processes: these of course may also be affected indirectly by changes in the physiological state (including motion sickness and fatigue) induced by the motion or vibration. The distinction between direct and indirect mechanisms of performance decrement in the motion environment has important implications for both protective measures and the focus of future research. This report considers published work on the performance effects of vibration in relation to the etiology of performance change and those implications. A critical review of the methodology of performance studies in motion and vibration environments is under way at the Naval Biodynamics Laboratory; and a series of experiments (some previously published) on whole-body vibration effects on performance is also in progress. While the duality of the mechanisms of action of oscillatory motion on performance remains an open question, the evidence so far adduced for other than direct mechanical effects is sparse, at least in the frequency range of major body resonance phenomena. Further experimentation, including long-duration studies, is needed to resolve this question. Implications both for future research directions and for current national and international standardization efforts in this area are discussed.

scholarly journals An ideal observer analysis of variability in visual-only speech

2005 ◽  
Vol 5 (8) ◽  
pp. 883-883
Author(s):  
B. Conrey ◽  
J. M. Gold
Keyword(s):  
Ideal Observer ◽  
Ideal Observer Analysis

scholarly journals Contour statistics in natural images: Grouping across occlusions

2009 ◽  
Vol 26 (1) ◽  
pp. 109-121 ◽  
Author(s):  
WILSON S. GEISLER ◽  
JEFFREY S. PERRY
Keyword(s):  
Human Performance ◽  
Statistical Properties ◽  
Ideal Observer ◽  
Neural Mechanisms ◽  
Natural Images ◽  
Natural Image ◽  
Edge Element ◽  
Visual Tasks ◽  
Contour Grouping ◽  
The Ideal

AbstractCorrectly interpreting a natural image requires dealing properly with the effects of occlusion, and hence, contour grouping across occlusions is a major component of many natural visual tasks. To better understand the mechanisms of contour grouping across occlusions, we (a) measured the pair-wise statistics of edge elements from contours in natural images, as a function of edge element geometry and contrast polarity, (b) derived the ideal Bayesian observer for a contour occlusion task where the stimuli were extracted directly from natural images, and then (c) measured human performance in the same contour occlusion task. In addition to discovering new statistical properties of natural contours, we found that naïve human observers closely parallel ideal performance in our contour occlusion task. In fact, there was no region of the four-dimensional stimulus space (three geometry dimensions and one contrast dimension) where humans did not closely parallel the performance of the ideal observer (i.e., efficiency was approximately constant over the entire space). These results reject many other contour grouping hypotheses and strongly suggest that the neural mechanisms of contour grouping are tightly related to the statistical properties of contours in natural images.

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