scholarly journals Spectral receptive fields do not explain tuning for boundary curvature in V4

2014 ◽  
Vol 112 (9) ◽  
pp. 2114-2122 ◽  
Author(s):  
Timothy D. Oleskiw ◽  
Anitha Pasupathy ◽  
Wyeth Bair
Keyword(s):  
Shape Representation ◽  
Angular Position ◽  
Receptive Fields ◽  
Shape Selectivity ◽  
Neural Representation ◽  
Phase Information ◽  
Area V4 ◽  
Visual Cortical Area ◽  
V4 Neurons ◽  
Contour Curvature

The midlevel visual cortical area V4 in the primate is thought to be critical for the neural representation of visual shape. Several studies agree that V4 neurons respond to contour features, e.g., convexities and concavities along a shape boundary, that are more complex than the oriented segments encoded by neurons in the primary visual cortex. Here we compare two distinct approaches to modeling V4 shape selectivity: one based on a spectral receptive field (SRF) map in the orientation and spatial frequency domain and the other based on a map in an object-centered angular position and contour curvature space. We test the ability of these two characterizations to account for the responses of V4 neurons to a set of parametrically designed two-dimensional shapes recorded previously in the awake macaque. We report two lines of evidence suggesting that the SRF model does not capture the contour sensitivity of V4 neurons. First, the SRF model discards spatial phase information, which is inconsistent with the neuronal data. Second, the amount of variance explained by the SRF model was significantly less than that explained by the contour curvature model. Notably, cells best fit by the curvature model were poorly fit by the SRF model, the latter being appropriate for a subset of V4 neurons that appear to be orientation tuned. These limitations of the SRF model suggest that a full understanding of midlevel shape representation requires more complicated models that preserve phase information and perhaps deal with object segmentation.

Processing of Kinetic Boundaries in Macaque V4

2006 ◽  
Vol 95 (3) ◽  
pp. 1864-1880 ◽  
Author(s):  
Santosh G. Mysore ◽  
Rufin Vogels ◽  
Steve E. Raiguel ◽  
Guy A. Orban
Keyword(s):  
Relative Motion ◽  
Receptive Fields ◽  
Shape Selectivity ◽  
Luminance Contrast ◽  
Motion Cues ◽  
Form Processing ◽  
Similar Shape ◽  
Shape Selective ◽  
Sizeable Fraction ◽  
V4 Neurons

We used gratings and shapes defined by relative motion to study selectivity for static kinetic boundaries in macaque V4 neurons. Kinetic gratings were generated by random pixels moving in opposite directions in the neighboring bars, either parallel to the orientation of the boundary (parallel kinetic grating) or perpendicular to the boundary (orthogonal kinetic grating). Neurons were also tested with static, luminance defined gratings to establish cue invariance. In addition, we used eight shapes defined either by relative motion or by luminance contrast, as used previously to test cue invariance in the infero-temporal (IT) cortex. A sizeable fraction (10–20%) of the V4 neurons responded selectively to kinetic patterns. Most neurons selective for kinetic contours had receptive fields (RFs) within the central 10° of the visual field. Neurons selective for the orientation of kinetic gratings were defined as having similar orientation preferences for the two types of kinetic gratings, and the vast majority of these neurons also retained the same orientation preference for luminance defined gratings. Also, kinetic shape selective neurons had similar shape preferences when the shape was defined by relative motion or by luminance contrast, showing a cue-invariant form processing in V4. Although shape selectivity was weaker in V4 than what has been reported in the IT cortex, cue invariance was similar in the two areas, suggesting that invariance for luminance and motion cues of IT originates in V4. The neurons selective for kinetic patterns tended to be clustered within dorsal V4.

scholarly journals Rhythmic neural spiking and attentional sampling arising from cortical receptive field interactions

2018 ◽  
Author(s):  
Ricardo Kienitz ◽  
Joscha T. Schmiedt ◽  
Katharine A. Shapcott ◽  
Kleopatra Kouroupaki ◽  
Richard C. Saunders ◽  
...  
Keyword(s):  
Eye Movements ◽  
Receptive Field ◽  
Spatial Attention ◽  
Receptive Fields ◽  
Reaction Times ◽  
List Type ◽  
Attention Task ◽  
Area V4 ◽  
Fixational Eye Movements ◽  
Visual Cortical Area

SummaryGrowing evidence suggests that distributed spatial attention may invoke theta (3-9 Hz) rhythmic sampling processes. The neuronal basis of such attentional sampling is however not fully understood. Here we show using array recordings in visual cortical area V4 of two awake macaques that presenting separate visual stimuli to the excitatory center and suppressive surround of neuronal receptive fields elicits rhythmic multi-unit activity (MUA) at 3-6 Hz. This neuronal rhythm did not depend on small fixational eye movements. In the context of a distributed spatial attention task, during which the monkeys detected a spatially and temporally uncertain target, reaction times (RT) exhibited similar rhythmic fluctuations. RTs were fast or slow depending on the target occurrence during high or low MUA, resulting in rhythmic MUA-RT cross-correlations at at theta frequencies. These findings suggest that theta-rhythmic neuronal activity arises from competitive receptive field interactions and that this rhythm may subserve attentional sampling.HighlightsCenter-surround interactions induce theta-rhythmic MUA of visual cortex neuronsThe MUA rhythm does not depend on small fixational eye movementsReaction time fluctuations lock to the neuronal rhythm under distributed attention

scholarly journals Shape encoding consistency across colors in primate V4

2012 ◽  
Vol 108 (5) ◽  
pp. 1299-1308 ◽  
Author(s):  
Brittany N. Bushnell ◽  
Anitha Pasupathy
Keyword(s):  
Correlation Coefficients ◽  
Shape Selectivity ◽  
Shape Information ◽  
Area V4 ◽  
Neuronal Populations ◽  
Shape Encoding ◽  
Shape Selective ◽  
Different Shapes ◽  
V4 Neurons ◽  
Response Consistency

Neurons in primate cortical area V4 are sensitive to the form and color of visual stimuli. To determine whether form selectivity remains consistent across colors, we studied the responses of single V4 neurons in awake monkeys to a set of two-dimensional shapes presented in two different colors. For each neuron, we chose two colors that were visually distinct and that evoked reliable and different responses. Across neurons, the correlation coefficient between responses in the two colors ranged from −0.03 to 0.93 (median 0.54). Neurons with highly consistent shape responses, i.e., high correlation coefficients, showed greater dispersion in their responses to the different shapes, i.e., greater shape selectivity, and also tended to have less eccentric receptive field locations; among shape-selective neurons, shape consistency ranged from 0.16 to 0.93 (median 0.63). Consistency of shape responses was independent of the physical difference between the stimulus colors used and the strength of neuronal color tuning. Finally, we found that our measurement of shape response consistency was strongly influenced by the number of stimulus repeats: consistency estimates based on fewer than 10 repeats were substantially underestimated. In conclusion, our results suggest that neurons that are likely to contribute to shape perception and discrimination exhibit shape responses that are largely consistent across colors, facilitating the use of simpler algorithms for decoding shape information from V4 neuronal populations.

Spectral Receptive Field Properties Explain Shape Selectivity in Area V4

2006 ◽  
Vol 96 (6) ◽  
pp. 3492-3505 ◽  
Author(s):  
Stephen V. David ◽  
Benjamin Y. Hayden ◽  
Jack L. Gallant
Keyword(s):  
Receptive Field ◽  
Spatial Frequency ◽  
Functional Model ◽  
Shape Selectivity ◽  
Second Order ◽  
Natural Images ◽  
Orientation Tuning ◽  
Large Set ◽  
Area V4 ◽  
V4 Neurons

Neurons in cortical area V4 respond selectively to complex visual patterns such as curved contours and non-Cartesian gratings. Most previous experiments in V4 have measured responses to small, idiosyncratic stimulus sets and no single functional model yet accounts for all of the disparate results. We propose that one model, the spectral receptive field (SRF), can explain many observations of selectivity in V4. The SRF describes tuning in terms of the orientation and spatial frequency spectrum and can, in principle, predict the response to any visual stimulus. We estimated SRFs for neurons in V4 of awake primates by linearized reverse correlation of responses to a large set of natural images. We find that V4 neurons have large orientation and spatial frequency bandwidth and often bimodal orientation tuning. For comparison, we estimated SRFs for neurons in primary visual cortex (V1). Consistent with previous observations, we find that V1 neurons have narrower bandwidth than that of V4. To determine whether estimated SRFs can account for previous observations of selectivity, we used them to predict responses to Cartesian gratings, non-Cartesian gratings, natural images, and curved contours. Based on these predictions, we find that the majority of neurons in V1 are selective for Cartesian gratings, whereas the majority of V4 neurons are selective for non-Cartesian gratings or natural images. The SRF describes visual tuning properties with a second-order nonlinear model. These results support the hypothesis that a second-order model is sufficient to describe the general mechanisms mediating shape selectivity in area V4.

scholarly journals A Model of V4 Shape Selectivity and Invariance

2007 ◽  
Vol 98 (3) ◽  
pp. 1733-1750 ◽  
Author(s):  
Charles Cadieu ◽  
Minjoon Kouh ◽  
Anitha Pasupathy ◽  
Charles E. Connor ◽  
Maximilian Riesenhuber ◽  
...  
Keyword(s):  
Object Recognition ◽  
Shape Representation ◽  
Intermediate Stage ◽  
Shape Selectivity ◽  
Quantitative Model ◽  
Translation Invariance ◽  
Translation Invariant ◽  
Hierarchical Processing ◽  
Area V4 ◽  
Ventral Pathway

Object recognition in primates is mediated by the ventral visual pathway and is classically described as a feedforward hierarchy of increasingly sophisticated representations. Neurons in macaque monkey area V4, an intermediate stage along the ventral pathway, have been shown to exhibit selectivity to complex boundary conformation and invariance to spatial translation. How could such a representation be derived from the signals in lower visual areas such as V1? We show that a quantitative model of hierarchical processing, which is part of a larger model of object recognition in the ventral pathway, provides a plausible mechanism for the translation-invariant shape representation observed in area V4. Simulated model neurons successfully reproduce V4 selectivity and invariance through a nonlinear, translation-invariant combination of locally selective subunits, suggesting that a similar transformation may occur or culminate in area V4. Specifically, this mechanism models the selectivity of individual V4 neurons to boundary conformation stimuli, exhibits the same degree of translation invariance observed in V4, and produces observed V4 population responses to bars and non-Cartesian gratings. This work provides a quantitative model of the widely described shape selectivity and invariance properties of area V4 and points toward a possible canonical mechanism operating throughout the ventral pathway.

Temporal dynamics of 2D and 3D shape representation in macaque visual area V4

2006 ◽  
Vol 23 (5) ◽  
pp. 749-763 ◽  
Author(s):  
JAY HEGDÉ ◽  
DAVID C. VAN ESSEN
Keyword(s):  
Temporal Dynamics ◽  
Shape Representation ◽  
Macaque Monkey ◽  
Large Stimulus ◽  
3D Shape ◽  
Area V4 ◽  
Single Animal ◽  
Distributed Process ◽  
V4 Neurons ◽  
2D And 3D

We studied the temporal dynamics of shape representation in area V4 of the alert macaque monkey. Analyses were based on two large stimulus sets, one equivalent to the 2D shape stimuli used in a previous study of V2, and the other a set of stereoscopic 3D shape stimuli. As in V2, we found that information conveyed by individual V4 neurons about the stimuli tended to be maximal during the initial transient response and generally lower, albeit statistically significant, afterwards. The population response was substantially correlated from one stimulus to the next during the transients, and decorrelated as responses decayed. V4 responses showed significantly longer latencies than in V2, especially for the 3D stimulus set. Recordings from area V1 in a single animal revealed temporal dynamic patterns in response to the 2D shape stimuli that were largely similar to those in V2 and V4. Together with earlier results, these findings provide evidence for a distributed process of coarse-to-fine representation of shape stimuli in the visual cortex.

scholarly journals The DeepTune framework for modeling and characterizing neurons in visual cortex area V4

2018 ◽  
Author(s):  
Reza Abbasi-Asl ◽  
Yuansi Chen ◽  
Adam Bloniarz ◽  
Michael Oliver ◽  
Ben D.B. Willmore ◽  
...  
Keyword(s):  
Neural Network ◽  
Visual Cortex ◽  
Deep Neural Network ◽  
Predictive Accuracy ◽  
Population Analysis ◽  
Receptive Fields ◽  
Network Models ◽  
Neural Network Models ◽  
Area V4 ◽  
V4 Neurons

AbstractDeep neural network models have recently been shown to be effective in predicting single neuron responses in primate visual cortex areas V4. Despite their high predictive accuracy, these models are generally difficult to interpret. This limits their applicability in characterizing V4 neuron function. Here, we propose the DeepTune framework as a way to elicit interpretations of deep neural network-based models of single neurons in area V4. V4 is a midtier visual cortical area in the ventral visual pathway. Its functional role is not yet well understood. Using a dataset of recordings of 71 V4 neurons stimulated with thousands of static natural images, we build an ensemble of 18 neural network-based models per neuron that accurately predict its response given a stimulus image. To interpret and visualize these models, we use a stability criterion to form optimal stimuli (DeepTune images) by pooling the 18 models together. These DeepTune images not only confirm previous findings on the presence of diverse shape and texture tuning in area V4, but also provide rich, concrete and naturalistic characterization of receptive fields of individual V4 neurons. The population analysis of DeepTune images for 71 neurons reveals how different types of curvature tuning are distributed in V4. In addition, it also suggests strong suppressive tuning for nearly half of the V4 neurons. Though we focus exclusively on the area V4, the DeepTune framework could be applied more generally to enhance the understanding of other visual cortex areas.

scholarly journals Modeling diverse responses to filled and outline shapes in macaque V4

2019 ◽  
Vol 121 (3) ◽  
pp. 1059-1077 ◽  
Author(s):  
Dina V. Popovkina ◽  
Wyeth Bair ◽  
Anitha Pasupathy
Keyword(s):  
Object Recognition ◽  
Response Strength ◽  
Stimulus Category ◽  
Similar Response ◽  
Boundary Edge ◽  
Neuronal Responses ◽  
Area V4 ◽  
Visual Cortical Area ◽  
V4 Neurons ◽  
Visual Cortical

Visual area V4 is an important midlevel cortical processing stage that subserves object recognition in primates. Studies investigating shape coding in V4 have largely probed neuronal responses with filled shapes, i.e., shapes defined by both a boundary and an interior fill. As a result, we do not know whether form-selective V4 responses are dictated by boundary features alone or if interior fill is also important. We studied 43 V4 neurons in two male macaque monkeys ( Macaca mulatta) with a set of 362 filled shapes and their corresponding outlines to determine how interior fill modulates neuronal responses in shape-selective neurons. Only a minority of neurons exhibited similar response strength and shape preferences for filled and outline stimuli. A majority responded preferentially to one stimulus category (either filled or outline shapes) and poorly to the other. Our findings are inconsistent with predictions of the hierarchical-max (HMax) V4 model that builds form selectivity from oriented boundary features and takes little account of attributes related to object surface, such as the phase of the boundary edge. We modified the V4 HMax model to include sensitivity to interior fill by either removing phase-pooling or introducing unoriented units at the V1 level; both modifications better explained our data without increasing the number of free parameters. Overall, our results suggest that boundary orientation and interior surface information are both maintained until at least the midlevel visual representation, consistent with the idea that object fill is important for recognition and perception in natural vision. NEW & NOTEWORTHY The shape of an object’s boundary is critical for identification; consistent with this idea, models of object recognition predict that filled and outline versions of a shape are encoded similarly. We report that many neurons in a midlevel visual cortical area respond differently to filled and outline shapes and modify a biologically plausible model to account for our data. Our results suggest that representations of boundary shape and surface fill are interrelated in visual cortex.

scholarly journals Attention selectively gates afferent signal transmission to area V4

2015 ◽  
Author(s):  
Iris Grothe ◽  
David Rotermund ◽  
Simon D. Neitzel ◽  
Sunita Mandon ◽  
Udo A. Ernst ◽  
...  
Keyword(s):  
Selective Attention ◽  
Cortical Neurons ◽  
Signal Transmission ◽  
Receptive Fields ◽  
Low Frequency ◽  
Area V4 ◽  
Gating Mechanism ◽  
V4 Neurons ◽  
Visual Cortical ◽  
Signal Routing

Selective attention causes visual cortical neurons to act as if only one of multiple stimuli are within their receptive fields. This suggests that attention employs a, yet unknown, neuronal gating mechanism for transmitting only the information that is relevant for the current behavioral context. We introduce an experimental paradigm to causally investigate this putative gating and the mechanism underlying selective attention by determining the signal availability of two time-varying stimuli in local field potentials of V4 neurons. We find transmission of the low frequency (<20Hz) components only from the attended visual input signal and that the higher frequencies from both stimuli are attenuated. A minimal model implementing routing by synchrony replicates the attentional gating effect and explains the spectral transfer characteristics of the signals. It supports the proposal that selective gamma-band synchrony subserves signal routing in cortex and further substantiates our experimental finding that attention selectively gates signals already at the level of afferent synaptic input.

Ultrastructure of developing visual cortical synapses in the cat superior colliculus

1991 ◽  
Vol 49 ◽  
pp. 156-157
Author(s):  
Caroline A. Miller ◽  
Laura L. Bruce
Keyword(s):  
Superior Colliculus ◽  
Phosphate Buffer ◽  
Receptive Fields ◽  
Visual Cortical Area ◽  
Cortical Synapses ◽  
Visual Cortical ◽  
And Function ◽  
Phosphate Buffered Saline ◽  
The Brain ◽  
Cat Superior Colliculus

The first visual cortical axons arrive in the cat superior colliculus by the time of birth. Adultlike receptive fields develop slowly over several weeks following birth. The developing cortical axons go through a sequence of changes before acquiring their adultlike morphology and function. To determine how these axons interact with neurons in the colliculus, cortico-collicular axons were labeled with biocytin (an anterograde neuronal tracer) and studied with electron microscopy.Deeply anesthetized animals received 200-500 nl injections of biocytin (Sigma; 5% in phosphate buffer) in the lateral suprasylvian visual cortical area. After a 24 hr survival time, the animals were deeply anesthetized and perfused with 0.9% phosphate buffered saline followed by fixation with a solution of 1.25% glutaraldehyde and 1.0% paraformaldehyde in 0.1M phosphate buffer. The brain was sectioned transversely on a vibratome at 50 μm. The tissue was processed immediately to visualize the biocytin.

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