scholarly journals Neurons in cat V1 show significant clustering by degree of tuning

2015 ◽  
Vol 113 (7) ◽  
pp. 2555-2581 ◽  
Author(s):  
Avi J. Ziskind ◽  
Al A. Emondi ◽  
Andrei V. Kurgansky ◽  
Sergei P. Rebrik ◽  
Kenneth D. Miller
Keyword(s):  
Spatial Frequency ◽  
Frequency Tuning ◽  
Direction Selectivity ◽  
Preferred Orientation ◽  
Orientation Tuning ◽  
Complex Cells ◽  
Spatial Frequency Tuning ◽  
Spatial Frequencies ◽  
Tuning Width ◽  
Simple And Complex Cells

Neighboring neurons in cat primary visual cortex (V1) have similar preferred orientation, direction, and spatial frequency. How diverse is their degree of tuning for these properties? To address this, we used single-tetrode recordings to simultaneously isolate multiple cells at single recording sites and record their responses to flashed and drifting gratings of multiple orientations, spatial frequencies, and, for drifting gratings, directions. Orientation tuning width, spatial frequency tuning width, and direction selectivity index (DSI) all showed significant clustering: pairs of neurons recorded at a single site were significantly more similar in each of these properties than pairs of neurons from different recording sites. The strength of the clustering was generally modest. The percent decrease in the median difference between pairs from the same site, relative to pairs from different sites, was as follows: for different measures of orientation tuning width, 29–35% (drifting gratings) or 15–25% (flashed gratings); for DSI, 24%; and for spatial frequency tuning width measured in octaves, 8% (drifting gratings). The clusterings of all of these measures were much weaker than for preferred orientation (68% decrease) but comparable to that seen for preferred spatial frequency in response to drifting gratings (26%). For the above properties, little difference in clustering was seen between simple and complex cells. In studies of spatial frequency tuning to flashed gratings, strong clustering was seen among simple-cell pairs for tuning width (70% decrease) and preferred frequency (71% decrease), whereas no clustering was seen for simple-complex or complex-complex cell pairs.

Spatial-frequency and orientation tuning in psychophysical end-stopping

1998 ◽  
Vol 15 (4) ◽  
pp. 585-595 ◽  
Author(s):  
CONG YU ◽  
DENNIS M. LEVI
Keyword(s):  
Spatial Frequency ◽  
Frequency Tuning ◽  
Spatial Filter ◽  
Orientation Tuning ◽  
Maximal Strength ◽  
Facilitation Effect ◽  
Spatial Filters ◽  
Spatial Frequency Tuning ◽  
Spatial Frequencies ◽  
Wide Range

A psychophysical analog to cortical receptive-field end-stopping has been demonstrated previously in spatial filters tuned to a wide range of spatial frequencies (Yu & Levi, 1997a). The current study investigated tuning characteristics in psychophysical spatial filter end-stopping. When a D6 (the sixth derivative of a Gaussian) target is masked by a center mask (placed in the putative spatial filter center), two end-zone masks (placed in the filter end-zones) reduce thresholds. This “end-stopping” effect (the reduction of masking induced by end-zone masks) was measured at various spatial frequencies and orientations of end-zone masks. End-stopping reached its maximal strength when the spatial frequency and/or orientation of the end-zone masks matched the spatial frequency and/or orientation of the target and center mask, showing spatial-frequency tuning and orientation tuning. The bandwidths of spatial-frequency and orientation tuning functions decreased with increasing target spatial frequency. At larger orientation differences, however, end-zone masks induced a secondary facilitation effect, which was maximal when the spatial frequency of end-zone masks equated the target spatial frequency. This facilitation effect might be related to certain types of contour and texture perception, such as perceptual pop-out.

Temporal and Spatial Frequency Tuning of the Flicker Motion Aftereffect

Perception ◽  
1996 ◽  
Vol 25 (1_suppl) ◽  
pp. 12-12
Author(s):  
P J Bex ◽  
F A J Verstraten ◽  
I Mareschal
Keyword(s):  
Spatial Frequency ◽  
Frequency Tuning ◽  
Temporal Frequency ◽  
Motion Aftereffect ◽  
Sine Wave ◽  
Test Grating ◽  
Spatial Frequency Tuning ◽  
Spatial Frequencies ◽  
Low Pass ◽  
Sine Wave Gratings

The motion aftereffect (MAE) was used to study the temporal-frequency and spatial-frequency selectivity of the visual system at suprathreshold contrasts. Observers adapted to drifting sine-wave gratings of a range of spatial and temporal frequencies. The magnitude of the MAE induced by the adaptation was measured with counterphasing test gratings of a variety of spatial and temporal frequencies. Independently of the spatial or temporal frequency of the adapting grating, the largest MAE was found with slowly counterphasing test gratings (∼0.125 – 0.25 Hz). For slowly counterphasing test gratings (<∼2 Hz), the largest MAEs were found when the test grating was of similar spatial frequency to that of the adapting grating, even at very low spatial frequencies (0.125 cycle deg−1). However, such narrow spatial frequency tuning was lost when the temporal frequency of the test grating was increased. The data suggest that MAEs are dominated by a single, low-pass temporal-frequency mechanism and by a series of band-pass spatial-frequency mechanisms at low temporal frequencies. At higher test temporal frequencies, the loss of spatial-frequency tuning implicates separate mechanisms with broader spatial frequency tuning.

scholarly journals Spatial and Temporal Features of Synaptic to Discharge Receptive Field Transformation in Cat Area 17

2010 ◽  
Vol 103 (2) ◽  
pp. 677-697 ◽  
Author(s):  
Lionel G. Nowak ◽  
Maria V. Sanchez-Vives ◽  
David A. McCormick
Keyword(s):  
Spatial Frequency ◽  
Response Latency ◽  
Frequency Tuning ◽  
Receptive Fields ◽  
Width Ratio ◽  
Area 17 ◽  
Simple Cells ◽  
Complex Cells ◽  
Temporal Features ◽  
Simple And Complex Cells

The aim of the present study was to characterize the spatial and temporal features of synaptic and discharge receptive fields (RFs), and to quantify their relationships, in cat area 17. For this purpose, neurons were recorded intracellularly while high-frequency flashing bars were used to generate RFs maps for synaptic and spiking responses. Comparison of the maps shows that some features of the discharge RFs depended strongly on those of the synaptic RFs, whereas others were less dependent. Spiking RF duration depended poorly and spiking RF amplitude depended moderately on those of the underlying synaptic RFs. At the other extreme, the optimal spatial frequency and phase of the discharge RFs in simple cells were almost entirely inherited from those of the synaptic RFs. Subfield width, in both simple and complex cells, was less for spiking responses compared with synaptic responses, but synaptic to discharge width ratio was relatively variable from cell to cell. When considering the whole RF of simple cells, additional variability in width ratio resulted from the presence of additional synaptic subfields that remained subthreshold. Due to these additional, subthreshold subfields, spatial frequency tuning predicted from synaptic RFs appears sharper than that predicted from spiking RFs. Excitatory subfield overlap in spiking RFs was well predicted by subfield overlap at the synaptic level. When examined in different regions of the RF, latencies appeared to be quite variable, but this variability showed negligible dependence on distance from the RF center. Nevertheless, spiking response latency faithfully reflected synaptic response latency.

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.

scholarly journals Dynamics of spatial frequency tuning in mouse visual cortex

2012 ◽  
Vol 107 (11) ◽  
pp. 2937-2949 ◽  
Author(s):  
Samme Vreysen ◽  
Bin Zhang ◽  
Yuzo M. Chino ◽  
Lutgarde Arckens ◽  
Gert Van den Bergh
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Visual Information ◽  
Frequency Tuning ◽  
Neuronal Response ◽  
Correlation Technique ◽  
Low Frequencies ◽  
Temporal Shift ◽  
Spatial Frequency Tuning ◽  
Spatial Frequencies

Neuronal spatial frequency tuning in primary visual cortex (V1) substantially changes over time. In both primates and cats, a shift of the neuron's preferred spatial frequency has been observed from low frequencies early in the response to higher frequencies later in the response. In most cases, this shift is accompanied by a decreased tuning bandwidth. Recently, the mouse has gained attention as a suitable animal model to study the basic mechanisms of visual information processing, demonstrating similarities in basic neuronal response properties between rodents and highly visual mammals. Here we report the results of extracellular single-unit recordings in the anesthetized mouse where we analyzed the dynamics of spatial frequency tuning in V1 and the lateromedial area LM within the lateral extrastriate area V2L. We used a reverse-correlation technique to demonstrate that, as in monkeys and cats, the preferred spatial frequency of mouse V1 neurons shifted from low to higher frequencies later in the response. However, this was not correlated with a clear selectivity increase or enhanced suppression of responses to low spatial frequencies. These results suggest that the neuronal connections responsible for the temporal shift in spatial frequency tuning may considerably differ between mice and monkeys.

scholarly journals Contralateral Bias of High Spatial Frequency Tuning and Cardinal Direction Selectivity in Mouse Visual Cortex

2017 ◽  
Vol 37 (42) ◽  
pp. 10125-10138 ◽  
Author(s):  
Kirstie J. Salinas ◽  
Dario X. Figueroa Velez ◽  
Jack H. Zeitoun ◽  
Hyungtae Kim ◽  
Sunil P. Gandhi
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Frequency Tuning ◽  
High Spatial Frequency ◽  
Direction Selectivity ◽  
Spatial Frequency Tuning ◽  
Cardinal Direction ◽  
Mouse Visual Cortex

Monocular and binocular response properties of cells in the striate-recipient zone of the cat's lateral posterior-pulvinar complex

1989 ◽  
Vol 62 (2) ◽  
pp. 544-557 ◽  
Author(s):  
C. Casanova ◽  
R. D. Freeman ◽  
J. P. Nordmann
Keyword(s):  
Spatial Frequency ◽  
Frequency Tuning ◽  
Single Cells ◽  
Temporal Frequency ◽  
Orientation Tuning ◽  
Low Frequencies ◽  
Response Properties ◽  
Spatial Frequencies ◽  
Lateral Posterior ◽  
The Mean

1. We have studied response properties of single cells in the striate-recipient zone of the cat's lateral posterior-pulvinar (LP-P) complex. This zone is in the lateral section of the lateral posterior nucleus (LP1). Our purpose was to determine basic response characteristics of these cells and to investigate the possibility that the LP-P complex is a center of integration that is dominated by input from visual cortex. 2. The majority (72%) of cells in the striate-recipient zone respond to drifting sinusoidal gratings with unmodulated discharge. 3. Cells in the LP1 are selective to the orientation of gratings, and tuning functions have a mean bandwidth of 31 degrees. More than one-half of these units are direction-selective. The preferred orientation and the tuning widths for the two eyes are generally well matched. However, a few cells exhibited the interesting property of opposite preferred directions for the two eyes. Orientation tuning for a small group of cells was different for the mean discharge and first harmonic components, suggesting a convergence from different inputs to these cells. 4. Two-thirds of LP1 cells are tuned to low spatial frequencies (less than 0.5 c/deg). The tuning is broad with a mean bandwidth of 2.2 octaves. The remaining one-third of the units are low-pass because they show no attenuation of their responses to low spatial frequencies. Both eyes exhibit the same spatial frequency preference and the same spatial frequency tuning. There is a high correlation between spatial frequency and orientation selectivities. 5. All cells tested are tuned for temporal frequency with a sharp attenuation for low frequencies. The optimal values range between 4 and 8 Hz, and the mean bandwidth is 2.2 octaves. 6. Cells in LP1 are mostly binocular. When monocular, cells are almost always contralaterally driven. Dichoptic presentation of gratings reveals the presence of strong binocular interaction. In almost all cases, these interactions are phase specific. The cell's discharge is facilitated at particular phases and inhibited at phases 180 degrees away. These binocular interactions are orientation dependent. 7. Twenty-five percent of the cells with phase-specific binocular facilitation appear to be monocular when each eye is tested separately. For three cells, we observed a non-phase-specific inhibitory effect of the silent eye. 8. Our findings indicate that LP1 cells form a relatively homogeneous group, suggesting a high degree of integration of multiple cortical inputs.(ABSTRACT TRUNCATED AT 400 WORDS)

Noisy Template Matching: A Model for Detection and Discrimination

Perception ◽  
1997 ◽  
Vol 26 (1_suppl) ◽  
pp. 263-263 ◽  
Author(s):  
W McIlhagga ◽  
A Pääkkönen
Keyword(s):  
Simple Model ◽  
Spatial Frequency ◽  
Template Matching ◽  
Additive Noise ◽  
Frequency Tuning ◽  
Central Place ◽  
Orientation Tuning ◽  
Decision Variable ◽  
Backward Masking ◽  
Spatial Frequency Tuning

The detection and discrimination of simple patterns occupies a central place in visual psychophysics. A wide variety of phenomena have been observed in this paradigm, such as: Weber's law; masking (simultaneous, forward, and backward); masking by noise; spatial frequency tuning; orientation tuning; and area summation. We suggest that many of these phenomena can be explained by a simple model which we call ‘noisy template matching’. In this model, the encoded stimulus is matched to a memorised template. Both stimulus and template are corrupted by additive noise. The template matching operation yields a decision variable, to which more noise is added. This model is very simple, but it has many interesting consequences. It provides qualitative explanations for many of the phenomena mentioned above, and with additional (but we think reasonable) assumptions about lens blur, contrast nonlinearity (Whittle, 1986 Vision Research26 1677 – 1691), uncertainty (Pelli, 1985 Journal of the Optical Society of America2 1508 – 1532), and suboptimal templates, the model also provides good quantitative accounts of these phenomena.

Effects of Experience on Spatial Frequency Tuning in the Visual System: Behavioral, Visuocortical, and Alpha-band Responses

2020 ◽  
Vol 32 (6) ◽  
pp. 1153-1169 ◽  
Author(s):  
Wendel M. Friedl ◽  
Andreas Keil
Keyword(s):  
Spatial Frequency ◽  
Undergraduate Students ◽  
Frequency Tuning ◽  
Temporal Frequency ◽  
Alpha Power ◽  
Alpha Band ◽  
Conditioning Paradigm ◽  
Spatial Frequency Tuning ◽  
Spatial Frequencies ◽  
Time Courses

Using electrophysiology and a classic fear conditioning paradigm, this work examined adaptive visuocortical changes in spatial frequency tuning in a sample of 50 undergraduate students. High-density EEG was recorded while participants viewed 400 total trials of individually presented Gabor patches of 10 different spatial frequencies. Patches were flickered to produce sweep steady-state visual evoked potentials (ssVEPs) at a temporal frequency of 13.33 Hz, with stimulus contrast ramping up from 0% to 41% Michelson over the course of each 2800-msec trial. During the final 200 trials, a selected range of Gabor stimuli (either the lowest or highest spatial frequencies, manipulated between participants) were paired with an aversive 90-dB white noise auditory stimulus. Changes in spatial frequency tuning from before to after conditioning for paired and unpaired gratings were evaluated at the behavioral and electrophysiological level. Specifically, ssVEP amplitude changes were evaluated for lateral inhibition and generalization trends, whereas change in alpha band (8–12 Hz) activity was tested for a generalization trend across spatial frequencies, using permutation-controlled F contrasts. Overall time courses of the sweep ssVEP amplitude envelope and alpha-band power were orthogonal, and ssVEPs proved insensitive to spatial frequency conditioning. Alpha reduction (blocking) was most pronounced when viewing fear-conditioned spatial frequencies, with blocking decreasing along the gradient of spatial frequencies preceding conditioned frequencies, indicating generalization across spatial frequencies. Results suggest that alpha power reduction—conceptually linked to engagement of attention and alertness/arousal mechanisms—to fear-conditioned stimuli operates independently of low-level spatial frequency processing (indexed by ssVEPs) in primary visual cortex.

On the variety of spatial frequency selectivities shown by neurons in area 17 of the cat

1981 ◽  
Vol 213 (1191) ◽  
pp. 183-199 ◽  
Keyword(s):  
Spatial Frequency ◽  
Visual Analysis ◽  
Frequency Tuning ◽  
Spatial Summation ◽  
Orientation Tuning ◽  
Area 17 ◽  
Tuning Curves ◽  
Spatial Frequencies ◽  
Functional Classes ◽  
Y Cells

The amplitudes of the responses of over 300 neurons in area 17 of the cat were examined as a function of the spatial frequency of moving sinusoidal gratings. The optimal spatial frequency and the bandwidth of the tuning curves were determined. The bandwidth varied considerably from neuron to neuron. Neurons optimally responsive to high spatial frequencies tended to have narrower tuning curves than those responsive to lower frequencies. Neurons with narrow spatial frequency tuning curves also tended to have narrow orientation tuning curves. These observations suggest that linear spatial summation tends to occur over a relatively constant area of visual field despite marked differences in each neuron’s optimal spatial frequency, a prediction of one model of visual analysis. There was little difference in either the optimal spatial frequencies or the bandwidths of tuning for different functional classes of neuron. Neurons with broad tuning curves tended to be restricted to lamina IV and its environs, being concentrated in the deep part of lamina II–III and the upper part of lamina IV ab. Neurons with very low optimal spatial frequencies were uncommon and tended to be found either at the border of laminae II–III and IV or in lamina V. These laminar distributions are discussed with respect to the laminar differences in the projection of l. g. n. X- and Y- cells to the visual cortex.

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