scholarly journals A Neurodynamic Model of Saliency Prediction in V1

2021 ◽  
pp. 1-36
Author(s):  
David Berga ◽  
Xavier Otazu

Lateral connections in the primary visual cortex (V1) have long been hypothesized to be responsible for several visual processing mechanisms such as brightness induction, chromatic induction, visual discomfort, and bottom-up visual attention (also named saliency). Many computational models have been developed to independently predict these and other visual processes, but no computational model has been able to reproduce all of them simultaneously. In this work, we show that a biologically plausible computational model of lateral interactions of V1 is able to simultaneously predict saliency and all the aforementioned visual processes. Our model's architecture (NSWAM) is based on Penacchio's neurodynamic model of lateral connections of V1. It is defined as a network of firing rate neurons, sensitive to visual features such as brightness, color, orientation, and scale. We tested NSWAM saliency predictions using images from several eye tracking data sets. We show that the accuracy of predictions obtained by our architecture, using shuffled metrics, is similar to other state-of-the-art computational methods, particularly with synthetic images (CAT2000-Pattern and SID4VAM) that mainly contain low-level features. Moreover, we outperform other biologically inspired saliency models that are specifically designed to exclusively reproduce saliency. We show that our biologically plausible model of lateral connections can simultaneously explain different visual processes present in V1 (without applying any type of training or optimization and keeping the same parameterization for all the visual processes). This can be useful for the definition of a unified architecture of the primary visual cortex.

NeuroImage ◽  
2012 ◽  
Vol 63 (3) ◽  
pp. 1464-1477 ◽  
Author(s):  
Andreas A. Ioannides ◽  
Vahe Poghosyan ◽  
Lichan Liu ◽  
George A. Saridis ◽  
Marco Tamietto ◽  
...  

2018 ◽  
Author(s):  
Andreea Lazar ◽  
Chris Lewis ◽  
Pascal Fries ◽  
Wolf Singer ◽  
Danko Nikolić

SummarySensory exposure alters the response properties of individual neurons in primary sensory cortices. However, it remains unclear how these changes affect stimulus encoding by populations of sensory cells. Here, recording from populations of neurons in cat primary visual cortex, we demonstrate that visual exposure enhances stimulus encoding and discrimination. We find that repeated presentation of brief, high-contrast shapes results in a stereotyped, biphasic population response consisting of a short-latency transient, followed by a late and extended period of reverberatory activity. Visual exposure selectively improves the stimulus specificity of the reverberatory activity, by increasing the magnitude and decreasing the trial-to-trial variability of the neuronal response. Critically, this improved stimulus encoding is distributed across the population and depends on precise temporal coordination. Our findings provide evidence for the existence of an exposure-driven optimization process that enhances the encoding power of neuronal populations in early visual cortex, thus potentially benefiting simple readouts at higher stages of visual processing.


2004 ◽  
Vol 92 (5) ◽  
pp. 2947-2959 ◽  
Author(s):  
Miguel Á. Carreira-Perpiñán ◽  
Geoffrey J. Goodhill

Maps of ocular dominance and orientation in primary visual cortex have a highly characteristic structure. The factors that determine this structure are still largely unknown. In particular, it is unclear how short-range excitatory and inhibitory connections between nearby neurons influence structure both within and between maps. Using a generalized version of a well-known computational model of visual cortical map development, we show that the number of excitatory and inhibitory oscillations in this interaction function critically influences map structure. Specifically, we demonstrate that functions that oscillate more than once do not produce maps closely resembling those seen biologically. This strongly suggests that local lateral connections in visual cortex oscillate only once and have the form of a Mexican hat.


2005 ◽  
Vol 94 (2) ◽  
pp. 1336-1345 ◽  
Author(s):  
Bartlett D. Moore ◽  
Henry J. Alitto ◽  
W. Martin Usrey

The activity of neurons in primary visual cortex is influenced by the orientation, contrast, and temporal frequency of a visual stimulus. This raises the question of how these stimulus properties interact to shape neuronal responses. While past studies have shown that the bandwidth of orientation tuning is invariant to stimulus contrast, the influence of temporal frequency on orientation-tuning bandwidth is unknown. Here, we investigate the influence of temporal frequency on orientation tuning and direction selectivity in area 17 of ferret visual cortex. For both simple cells and complex cells, measures of orientation-tuning bandwidth (half-width at half-maximum response) are ∼20–25° across a wide range of temporal frequencies. Thus cortical neurons display temporal-frequency invariant orientation tuning. In contrast, direction selectivity is typically reduced, and occasionally reverses, at nonpreferred temporal frequencies. These results show that the mechanisms contributing to the generation of orientation tuning and direction selectivity are differentially affected by the temporal frequency of a visual stimulus and support the notion that stability of orientation tuning is an important aspect of visual processing.


2008 ◽  
Vol 31 (2) ◽  
pp. 209-210 ◽  
Author(s):  
Zhicheng Lin

AbstractThe extent to which visual processing can proceed in the visual hierarchy without awareness determines the magnitude of perceptual delay. Increasing data demonstrate that primary visual cortex (V1) is involved in consciousness, constraining the magnitude of visual delay. This makes it possible that visual delay is actually within the optimal lengths to allow sufficient computation; thus it might be unnecessary to compensate for visual delay.The time delay problem – that perception lives slightly in the past as a result of neural conduction – has recently attracted a considerate amount of attention in the context of the flash-lag effect. The effect refers to a visual illusion wherein a brief flash of light and a continuously moving object that physically align in space and time are perceived to be displaced from one another – the flashed stimulus appears to lag behind the moving object (Krekelberg & Lappe 2001). In the target article, Nijhawan compellingly argues that delay compensation could be undertaken by a predictive process in the feedforward pathways in the vision system. Before jumping into the quest for the mechanism of delay compensation, however, I would like to argue that the magnitude of delay has been overestimated, and that it might even be unnecessary to compensate for such a delay.


PLoS ONE ◽  
2015 ◽  
Vol 10 (7) ◽  
pp. e0130569 ◽  
Author(s):  
Na Shu ◽  
Zhiyong Gao ◽  
Xiangan Chen ◽  
Haihua Liu

Author(s):  
R. Oz ◽  
H. Edelman-Klapper ◽  
S. Nivinsky-Margalit ◽  
H. Slovin

AbstractIntra cortical microstimulation (ICMS) in the primary visual cortex (V1) can generate the visual perception of phosphenes and evoke saccades directed to the stimulated location in the retinotopic map. Although ICMS is widely used, little is known about the evoked spatio-temporal patterns of neural activity and their relation to neural responses evoked by visual stimuli or saccade generation. To investigate this, we combined ICMS with Voltage Sensitive Dye Imaging in V1 of behaving monkeys and measured neural activity at high spatial (meso-scale) and temporal resolution. Small visual stimuli and ICMS evoked population activity spreading over few mm that propagated to extrastriate areas. The population responses evoked by ICMS showed faster dynamics and different spatial propagation patterns. Neural activity was higher in trials w/saccades compared with trials w/o saccades. In conclusion, our results uncover the spatio-temporal patterns evoked by ICMS and their relation to visual processing and saccade generation.


2020 ◽  
Author(s):  
Ali Almasi ◽  
Hamish Meffin ◽  
Shaun L. Cloherty ◽  
Yan Wong ◽  
Molis Yunzab ◽  
...  

AbstractVisual object identification requires both selectivity for specific visual features that are important to the object’s identity and invariance to feature manipulations. For example, a hand can be shifted in position, rotated, or contracted but still be recognised as a hand. How are the competing requirements of selectivity and invariance built into the early stages of visual processing? Typically, cells in the primary visual cortex are classified as either simple or complex. They both show selectivity for edge-orientation but complex cells develop invariance to edge position within the receptive field (spatial phase). Using a data-driven model that extracts the spatial structures and nonlinearities associated with neuronal computation, we show that the balance between selectivity and invariance in complex cells is more diverse than thought. Phase invariance is frequently partial, thus retaining sensitivity to brightness polarity, while invariance to orientation and spatial frequency are more extensive than expected. The invariance arises due to two independent factors: (1) the structure and number of filters and (2) the form of nonlinearities that act upon the filter outputs. Both vary more than previously considered, so primary visual cortex forms an elaborate set of generic feature sensitivities, providing the foundation for more sophisticated object processing.


2020 ◽  
Author(s):  
Chrysa Retsa ◽  
Ana Hernando Ariza ◽  
Nathanael W. Noordanus ◽  
Lorenzo Ruffoni ◽  
Micah M. Murray ◽  
...  

AbstractGeometrical optical illusion (GOIs) are mismatches between physical stimuli and perception. GOIs provide an access point to study the interplay between sensation and perception, yet there is scant quantitative investigation of the extent to which different GOIs rely on similar or distinct brain mechanisms. We addressed this knowledge gap. First, 30 healthy adults reported quantitatively their perceptual biases with three GOIs, whose physical properties parametrically varied on a trial-by-trial basis. Biases observed with one GOI were unrelated to those observed with another GOI, suggestive of (partially) distinct underlying mechanisms. Next, we used these psychophysical results to tune a computational model of primary visual cortex that combines parameters of orientation, selectivity, intra-cortical connectivity, and long-range interactions. We showed that similar biases could be generated in-silico, mirroring those observed in humans. Such results provide a roadmap whereby computational modelling, informed by human psychophysics, can reveal likely mechanistic underpinnings of perception.


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