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About 10,000 papers for “Spatial frequency”

Spatial Frequency

National Cancer Institute · Definitions · 2020

Cited by 0Open access

Storage of spatial-frequency information and spatial-frequency discrimination

D. Regan · Journal of the Optical Society of America A · 1985

The spatial frequencies of two gratings can be discriminated when they differ by about 5%. This discrimination threshold was found to be remarkably independent of interstimulus interval in a temporal two-alternative forced-choice procedure. Discrimination threshold between parallel gratings did not change over a 50:1 range of interstimulus intervals between 0.4 and 20 sec; spatial-frequency information is stored with at least 5% precision without appreciable decay up to 20 sec at least. Spatial-frequency discrimination between orthogonal gratings was the same as spatial-frequency discrimination between parallel gratings and did not change over the 25:1 range of interstimulus intervals investigated (0.4 to 10 sec). It is suggested that, after being encoded to a high degree of precision by a size-opponent mechanism that is tuned to orientation, spatial-frequency information is stored in a form that is independent of orientation.

Cited by 65

spatial-frequency-preferences

Broderick, William F., Simoncelli, Eero P., Winawer, Jonathan · Zenodo (CERN European Organization for Nuclear Research) · 2024

@jiyeongha found a bug in how I was transforming from neuropythy's retinotopic polar angle convention to the standard one. I had been mapping the polar angle such that 0 corresponded to the right horizontal meridian / positive x-axis, and angle increased clockwise, but angle should've increased counter-clockwise. Further investigation led to the realization that I had done this everywhere where I was defining some sort of polar angle or orientation. This is equivalent to a flip over the vertical axes. Fixing this doesn't affect our results at all, because the errors cancelled themselves out. The only difference is that all stimuli actually have a negative w_a compared to our original definitions. That is, whereas we originally said forward spirals had w_r=w_a and negative spirals had w_r=-w_a, the reverse is true; while we said all annuli have w_r=0,w_a>0, they all have w_r=0,w_a<0 (this doesn't affect the local spatial frequency, but does matter for the phase. The equations presented in the paper were all correct, so if anyone was writing an implementation from scratch, this will not affect them. However, the implementations in this code were incorrect. Other changes are to make sure everything still runs (e.g., updating the neuropythy version as discussed in #2). Full Changelog: https://github.com/billbrod/spatial-frequency-preferences/compare/v1.1.1...v2.0.0

Cited by 0Open access

Spatial analysis Frequency

2008

sed nd Pinu investigate the evolution of the forest stand so as (i) to reconstruct past rockfall rates; (ii) to analyze the bounce heights; and (iii) to analyze the spatial comportment of rockfall activity Geomorphology 102 (2008) 522–531 Contents lists available at ScienceDirect

Cited by 0

Spatial frequency tuning.

Phillip A. Romo (577961), Natalie Zeater (577962), Chun Wang (337817) et al. · Figshare · 2015

&lt;p&gt;&lt;b&gt;A&lt;/b&gt; Examples of spatial frequency tuning plots of area 18 cells for stimuli presented via the dominant and non-dominant eyes. The bandwidth represents the spatial frequency range which elicits &gt;50% of maximal firing rate. Scatter plot in &lt;b&gt;Bi&lt;/b&gt; illustrates the interocular matching of optimal spatial frequencies. Black line indicates linear regression line. &lt;b&gt;Bii&lt;/b&gt; Frequency histogram of interocular differences in optimal spatial frequencies. &lt;b&gt;C&lt;/b&gt; Histogram illustrating the mean optimal spatial frequencies of simple and complex cells to optimized drifting gratings presented via the dominant and non-dominant eyes. # Indicates a marginal significant (P&lt;0.05, Mann-Whitney test, one-tailed criterion) difference. &lt;b&gt;D&lt;/b&gt; Histogram showing the mean optimal spatial frequencies for stimuli presented via the dominant or non-dominant eyes for groups of simple (S) and complex (C) based on eccentricity of location of their discharge fields.&lt;/p&gt;

Cited by 0Open access

Spatial frequency filtering

Ajoy Ghatak, K. Thyagarajan · Cambridge University Press eBooks · 1989

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.

Cited by 6

Spatial frequency stimuli

William Ferguson Broderick · OSF Preprints (OSF Preprints) · 2019

See the readme in the corresponding Github repo for a description of this OSF project.

Cited by 0

spatial-frequency-preferences

Broderick, William F., Simoncelli, Eero P., Winawer, Jonathan · Zenodo (CERN European Organization for Nuclear Research) · 2022

Submission of revision to journal. Since <code>v1.0.3</code>: adds info on getting containers from NYU faculty data archive adds CITATION.cff adds <code>behavioral.py</code> and ability to create figures showing behavioral data small figure changes following reviewer suggestions adds behavioral data to the BIDS events.tsv files created supplemental download now includes events.tsv files caught "overbinning" bug in <code>figures.example_voxels</code> updates README

Cited by 0Open access

Spatial frequency mapping

Jonathan Winawer, Yuna Kwak, Marc Himmelberg et al. · OSF Preprints (OSF Preprints) · 2025

covariation between cortical magnification and preferred spatial frequency in human V1 measured using fMRI

Cited by 0

spatial-frequency-preferences

Broderick, William F., Simoncelli, Eero P., Winawer, Jonathan · Zenodo (CERN European Organization for Nuclear Research) · 2022

Acceptance of manuscript from journal. Since <code>v1.1.0</code>, only change is swapping out the <code>einstein.pgm</code> image with <code>tiles.png</code>, since we don't have the rights to use the Einstein image in a publication and the tiles one is from my personal collection.

Cited by 0Open access

spatial-frequency-preferences

Broderick, William F., Simoncelli, Eero P., Winawer, Jonathan · Zenodo (CERN European Organization for Nuclear Research) · 2024

@jiyeongha found a bug in how I was transforming from neuropythy's retinotopic polar angle convention to the standard one. I had been mapping the polar angle such that 0 corresponded to the right horizontal meridian / positive x-axis, and angle increased clockwise, but angle should've increased counter-clockwise. Further investigation led to the realization that I had done this everywhere where I was defining some sort of polar angle or orientation. This is equivalent to a flip over the vertical axes. Fixing this doesn't affect our results at all, because the errors cancelled themselves out. The only difference is that all stimuli actually have a negative w_a compared to our original definitions. That is, whereas we originally said forward spirals had w_r=w_a and negative spirals had w_r=-w_a, the reverse is true; while we said all annuli have w_r=0,w_a>0, they all have w_r=0,w_a<0 (this doesn't affect the local spatial frequency, but does matter for the phase. The equations presented in the paper were all correct, so if anyone was writing an implementation from scratch, this will not affect them. However, the implementations in this code were incorrect. Other changes are to make sure everything still runs (e.g., updating the neuropythy version as discussed in #2). Full Changelog: https://github.com/billbrod/spatial-frequency-preferences/compare/v1.1.1...v2.0.0

Cited by 0Open access

Spatial Frequency and Lightness

Nathan Moroney, Sabine Süsstrunk · Color and Imaging Conference · 2004

A method of adjustment experiment was conducted in which observers matched the lightness of a test stimulus to the lightness of a reference stimulus. The reference stimulus and background were non-uniform and consisted of a blue noise pattern. The test stimulus and background were also non-uniform and consisted of a white noise pattern. In both cases, the background patterns were comprised of black and white pixels. The stimuli consisted of gray and either black or white pixels. Fourteen observers performed the experiment on a CRT in a dark surround. We found that there is an approximately 10 percent difference in the relative luminance for the matches between the white noise and blue noise conditions, and that this difference is statistically significant at a 95% confidence level. In this abstract, we discuss these non-equivalent backgrounds in relation with previous studies and also present some preliminary results for moving test stimuli.

Cited by 0Open access

The spatial frequency and

2015

ct a,* ham, gy, M ceive later visual areas or lateral/feedback modulatory neural vidual neurons (Field, Hayes, &amp;amp; Hess, 1993). In a similar vein, we have recently investigated the rules that underlie the integration of local motion signals across space to help disambiguate the presence of simple spatial contours (Hess &amp;amp; Ledgeway, 2003b; Ledgeway &amp;amp;

Cited by 0

Spatial dimension frequency chart.

Hongxun Xiang (17403860), Yangfan Bu (17403863), Xunhua Wang (10135861) · Figshare · 2023

&lt;div&gt;&lt;p&gt;Background&lt;/p&gt;&lt;p&gt;Policy tools embody policy concepts and are essential to achieving policy objectives. The effective allocation of policy tools directly impacts the effectiveness of community governance and determines the modernization process of grassroots governance. We aim to analyze the logic of community governance policy tool selection, and then provide assistance for the modernization of grassroots governance.&lt;/p&gt;&lt;p&gt;Methods&lt;/p&gt;&lt;p&gt;We selected 100 national and provincial government work reports and 63 policy documents related to community governance during China’s “12th Five-Year Plan” to “14th Five-Year Plan” period as analysis samples. And build an analysis framework based on the three dimensions of time, space, and tools. We used Nvivo.20 software for text encoding analysis.&lt;/p&gt;&lt;p&gt;Results&lt;/p&gt;&lt;p&gt;Based on the model framework, we analyze the results as follows. From the perspective of the time dimension, among the five types of policy tools, the proportion of command-type policy tools used showed a downward trend, from 88.16% in the 12th Five-Year Plan to 83.50% in the 14th Five-Year Plan. However, motivation-type and persuasion-type tools showed an upward trend, rising from 1.34% and 5.26% in the 12th Five-Year Plan period to 3.40% and 8.74% in the 14th Five-Year Plan respectively. The system-change-type policy tools decreased from 1.32% in the 12th Five-Year Plan to 0.97% in the 14th Five-Year Plan. The proportion of capacity-building-type policy tools has gradually increased from 2.63% in the 12th Five-Year Plan to 4.85% in the 14th Five-Year Plan. From the perspective of spatial dimension, apart from command and persuasion policy tools, the usage frequency of the other three types of policy tools in the three major regions all display a “growth-decline-growth” trend. From the perspective of tool dimension, command-type policy tools are dominant in China’s community governance, with a cumulative frequency of 1405 times and a high proportion of 81.75%. Apart from command policy tools, persuasive policy tools and capacity-building policy tools have a relatively high proportion, with usage frequencies of 186 and 78 respectively.&lt;/p&gt;&lt;p&gt;Conclusions&lt;/p&gt;&lt;p&gt;We found that current community governance policy tools mainly consist of command tools. However, there is a trend towards combining tools such as command, persuasion, incentive, capacity building, and system change in the future. There is a typical contradiction between instrumental rationality and value rationality, indicating an evolution from instrumental rationality to the integration of instrumental and value rationality. This study addresses the conflict of policy tools through rational guidance of values, the rational guarantee of tools, and cooperation to achieve the goal of high-quality development of community governance.&lt;/p&gt;&lt;/div&gt;

Cited by 0Open access

Spatial frequency decay rates.

Matthew Rinehart (552113), Sheila Grab (552114), Lisa Rohan (552115) et al. · Figshare · 2015

&lt;p&gt;(A) Each characteristic length scale is fit over the time interval of (τ&lt;sub&gt;H&lt;/sub&gt;,20∶00) to an exponential decay, . 95% confidence intervals of the fits are shown as black bars. (B) Average bulk decay rates (Γ) and micron-scale particle decay rates (Λ) of each sample. Black bars show standard deviation (See &lt;a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0095005#pone-0095005-t001" target="_blank"&gt;Table 1&lt;/a&gt; for summary).&lt;/p&gt;

Cited by 0Open access

Spatial frequency and refraction.

John G. Holman (14670911), Winnie W. K. Lai (14670914), Paul Pichler (14670917) et al. · Figshare · 2023

&lt;p&gt;The leftmost bar shows the “nominal” spatial frequency of the grid stimulus that would been perceived in the absence of refraction for all three height conditions. However refractive effects increase the perceived spatial frequency to an extent that depends on the height of the channel above the stimulus (righthand three bars). Following [&lt;a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010924#pcbi.1010924.ref027" target="_blank"&gt;27&lt;/a&gt;] here we treat the bottom of the channel as an air/water interface. The perceived spatial frequency was estimated by calculating the angle subtended at the eye by rays stemming from the limits of a single stimulus period centered directly below. For the values used in these experiments, the three mid-channel heights of 8mm, 32mm and 56mm above the stimulus and a nominal spatial frequency of 0.0156 cycles per degree (cpd), the perceived spatial frequency would have varied from 0.0187 cpd to 0.021 cpd. Given the spatial frequency tuning curve (&lt;a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010924#pcbi.1010924.s010" target="_blank"&gt;S10A Fig&lt;/a&gt;), this degree of uncontrolled variation (± 7.7% relative to midpoint of the range) about a point close to the peak of the curve would not be expected to have much effect on OMR performance, as confirmed empirically by the subsequent experiment (&lt;a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010924#pcbi.1010924.s010" target="_blank"&gt;S10B Fig&lt;/a&gt;). As refractive effects increase towards the periphery this may also suggest that the stimulus region directly below the fish has the strongest influence on the strength of the OMR.&lt;/p&gt; &lt;p&gt;(PDF)&lt;/p&gt;

Cited by 0Open access

Spatial frequency time dynamics.

Matthew Rinehart (552113), Sheila Grab (552114), Lisa Rohan (552115) et al. · Figshare · 2015

&lt;p&gt;Selected characteristic length scales demonstrate early hydration and subsequent dissolution. Blue lines and error bars correspond to the mean and standard deviation of three repeats of each film type.&lt;/p&gt;

Cited by 0Open access