Dependence of the threshold of sinusoidal grating displacement on its spatial frequency characteristics

2000 ◽  
Vol 26 (4) ◽  
pp. 405-411
Author(s):  
G. A. Kuraev ◽  
V. V. Babenko
Keyword(s):  
Spatial Frequency ◽  
Frequency Characteristics ◽  
Sinusoidal Grating

Temporal-Discontinuity Detection with Contrast-Modulated Gratings

Perception ◽  
1995 ◽  
Vol 24 (11) ◽  
pp. 1257-1264
Author(s):  
Shigeru Ichihara ◽  
Kenji Susami
Keyword(s):  
Spatial Frequency ◽  
Modulation Frequency ◽  
Sinusoidal Grating ◽  
Local Contrast ◽  
Staircase Method ◽  
Low Contrast ◽  
Discontinuity Detection ◽  
Temporal Discontinuity ◽  
Sinusoidal Gratings ◽  
The Subject

Three experiments on temporal-discontinuity detection were carried out. In experiment 1, temporal-discontinuity thresholds were measured for sinusoidal gratings by the use of the double-staircase method. A sinusoidal grating was presented twice successively. The subject judged whether or not an interval was present. The temporal-discontinuity threshold increased as the spatial frequency of the grating increased, but decreased as the contrast of the grating increased. In experiment 2, contrast-modulated gratings were used instead of the sinusoidal grating. The temporal-discontinuity threshold increased as the carrier frequency increased, and the threshold for each contrast-modulated grating was similar to that for the no-modulation (sinusoidal) grating whose contrast was the same as the maximum local contrast of the contrast-modulated grating. In experiment 3, temporal-discontinuity thresholds were measured for low-contrast (3%) sinusoidal gratings. The thresholds were very low, even for such low-contrast gratings. These results suggest that the low-spatial-frequency channels are not involved in detecting the modulation frequency of the contrast-modulated grating. Rather, the local contrast seems to be the determinant of the detection of the contrast-modulated grating itself.

An investigation of spatial frequency characteristics of the complex receptive fields in the visual cortex of the cat

1976 ◽  
Vol 16 (8) ◽  
pp. 789-797 ◽  
Author(s):  
V.D. Glezer ◽  
A.M. Cooperman ◽  
V.A. Ivanov ◽  
T.A. Tsherbach
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Receptive Fields ◽  
Frequency Characteristics

Evoked Magnetic Field Elicited by Motion and Motion Aftereffect

Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 113-113
Author(s):  
N Osaka ◽  
H Ashida ◽  
M Osaka ◽  
S Koyama ◽  
R Kakigi
Keyword(s):  
Magnetic Field ◽  
Spatial Frequency ◽  
Human Subject ◽  
Visual Motion ◽  
Motion Aftereffect ◽  
Sinusoidal Grating ◽  
Negative Aftereffect ◽  
Motion Condition ◽  
Clear Increase ◽  
Good Agreement

Motion aftereffect (MAE) is a negative aftereffect caused by prolonged viewing of visual motion: after gazing at a moving grating for a while, a stationary image will appear to move in the opposite direction (Ashida and Osaka, 1995 Vision Research35 1825). Evoked magnetic field (magnetoencephalogram: MEG) was measured on a human subject observing visual motion and MAE. Magnetic evoked field (80 averagings) was measured from 37 points over occipital and parietal areas (Magnes SQUID biomagnetometer, BTi) during watching a horizontally moving sinusoidal grating with low spatial frequency (2 cycles deg−1 with 5 Hz: motion condition) and immediately after stopping the moving grating (MAE condition). Dipole estimates based on equal magnetic field contour suggest that the main loci subserving visual motion and MAE appear to be the surrounding region over occipital and parietal areas in the human brain. Further analysis is now underway. In general, this appears to be in good agreement with another study using fMRI-based MAE measures [Tootell et al, 1995 Nature (London)375 139] in which a clear increase in activity in these areas was observed when subjects viewed MAE.

Reaction Time to Gratings: A Re-Examination

Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 16-16 ◽  
Author(s):  
C Bonnet ◽  
J P Thomas ◽  
P Fagerholm
Keyword(s):  
Reaction Time ◽  
Spatial Frequency ◽  
Window Size ◽  
Vertical Axis ◽  
Grating Period ◽  
Sinusoidal Grating ◽  
Choice Procedure ◽  
Frequency Detection ◽  
Forced Choice Procedure ◽  
Number Of Cycles

We have examined the relationship between the reaction time for detecting a sinusoidal grating stimulus and the stimulus variables of spatial frequency, contrast, window size, and uncertainty with respect to spatial frequency. Detection was measured in a two-alternative spatial-forced-choice procedure. The stimuli were horizontal cosine gratings windowed spatially by two-dimensional Gaussians. Spatial frequency was varied from 0.7 to 6.5 cycles deg−1 and contrast was varied from 0.054 to 0.673. The standard deviation of the Gaussian window was fixed in some conditions and the number of cycles presented in each window covaried with spatial frequency. In other conditions, window size was varied, along the vertical axis only, to hold the number of cycles constant. Contrasts were always randomly intermixed, but frequencies were intermixed in some conditions and blocked in others. We confirm previous findings that reaction time increases as spatial frequency increases and decreases as contrast increases. We also confirm and extend the proposal of Rudd that reaction time closely approximates a single function of the product of contrast and the square of the grating period. We consider the implications of these findings for the nature of the physiological mechanisms which govern reaction time.

65. VEPs elicited by sinusoidal grating stimuli with low spatial frequency

2009 ◽  
Vol 120 (5) ◽  
pp. e162
Author(s):  
Yamazaki Hiroko ◽  
Sai Gyokushu ◽  
Yatabe Kiyomi ◽  
Gunji Atsuko ◽  
Kaga Makiko ◽  
...  
Keyword(s):  
Spatial Frequency ◽  
Sinusoidal Grating

Transfer of Learning in Transformed Random-Dot Stereostimuli

Perception ◽  
1982 ◽  
Vol 11 (4) ◽  
pp. 409-414 ◽  
Author(s):  
Nigel R Long
Keyword(s):  
Spatial Frequency ◽  
High Frequency ◽  
Transfer Of Learning ◽  
Low Frequency ◽  
Frequency Characteristics ◽  
Frequency Transformations

The transfer of learning between normal and monocularly-transformed small-disparity, random-dot stereostimuli has been examined under extended viewing conditions. When the disparity value was constant, transfer of learning between normal and monocularly-transformed stereostimuli was disrupted by both low-frequency and high-frequency transformations. These results suggest that stereolearning is restricted to disparity units that are selective to the same spatial-frequency characteristics.

How Reliable is the Pattern Adaptation Technique? A Modeling Study

2009 ◽  
Vol 102 (4) ◽  
pp. 2245-2252 ◽  
Author(s):  
Jay Hegdé
Keyword(s):  
Spatial Frequency ◽  
Frequency Tuning ◽  
Spatial Vision ◽  
Neural Mechanisms ◽  
System Level ◽  
Sinusoidal Grating ◽  
Tuning Parameters ◽  
Neuronal Ensemble ◽  
Spatial Frequency Tuning ◽  
Spatial Frequencies

Upon prolonged viewing of a sinusoidal grating, the visual system is selectively desensitized to the spatial frequency of the grating, while the sensitivity to other spatial frequencies remains largely unaffected. This technique, known as pattern adaptation, has been so central to the psychophysical study of the mechanisms of spatial vision that it is sometimes referred to as the “psychologist's microelectrode.” While this approach implicitly assumes that the adaptation behavior of the system is diagnostic of the corresponding underlying neural mechanisms, this assumption has never been explicitly tested. We tested this assumption using adaptation bandwidth, or the range of spatial frequencies affected by adaptation, as a representative measure of adaptation. We constructed an intentionally simple neuronal ensemble model of spatial frequency processing and examined the extent to which the adaptation bandwidth at the system level reflected the bandwidth at the neuronal level. We find that the adaptation bandwidth could vary widely even when all spatial frequency tuning parameters were held constant. Conversely, different spatial frequency tuning parameters were able to elicit similar adaptation bandwidths from the neuronal ensemble. Thus, the tuning properties of the underlying units did not reliably reflect the adaptation bandwidth at the system level, and vice versa. Furthermore, depending on the noisiness of adaptation at the neural level, the same neuronal ensemble was able to produce selective or nonselective adaptation at the system level, indicating that a lack of selective adaptation at the system level cannot be taken to mean a lack of tuned mechanisms at the neural level. Together, our results indicate that pattern adaptation cannot be used to reliably estimate the tuning properties of the underlying units, and imply, more generally, that pattern adaptation is not a reliable tool for studying the neural mechanisms of pattern analysis.

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