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SwitchBoard is an In Innovative Training Network (ITN) funded by the European Commission's Horizon 2020 programme under the Marie Curie Actions. The duration of the project is 48 months, starting on November 01, 2015.

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Monday 18 November 2019

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Retinal side of optical illusions


Optical illusions are artifacts of sensory processing.  Though misperceptions, they highlight principles and objectives that govern normal neural processing. Therefore, a comprehensive theory of vision should be able to account for optical illusions. Here I will tell about retinal mechanisms hacked by such types of stimuli.
I strongly recommend arming yourself with a plan of the retina from a Figure 1.





The retina has to provide the rest of the body with sufficient information about the visual environment. On the other hand, we would like it to consume as little energy as possible. To achieve both of these goals, the retina has to be efficient and transmit only important information.  

The visual environment is an aggregate of figures and backgrounds. We are interested in their separation i.e. evaluating differences between them. A way to perform this task efficiently is to transmit information about contrast instead of an absolute light intensity. Contrast characterizes how objects differ in a reflecting light. This is an internal property of an object, thus it allows discriminating objects regardless of the absolute intensity of the incident light. Hence, there is no need to send information about it and this optimizes retinal performance.

How to estimate contrast? Figures are surrounded by other figures and background, so we estimate contrast by subtracting the signal of a given photoreceptor from the signals collected by its neighbors. This process is mediated by horizontal and amacrine cells and called “lateral inhibition”. Consequentially, bipolar cells, which collect signals from photoreceptors, and ganglion cells, which transmit it further to the brain, exhibit antagonistic center-surround receptive field arrangements. That is, these cells are excited by stimuli in their centers, and inhibited by ones in their surround. So essentially they transmit difference between center and surround.

The illusion shown in Figure 2 exploits this processing strategy. Although painted uniformly throughout, the rectangle shown appears lighter on the left and darker on the right. As we know now, the illusion occurs because instead of perceiving an objects absolute brightness we perceive how it differs from its surroundings. As the background is dimmer on the left and lighter on the right, the contrast between background and rectangle is higher leftwards. Thus, object appears brighter.



Another illusion based on this principle - perceiving not intensity, but contrast, is Hermann grid. In Figure 3, with a quick glance we can note grey blobs on the intersections of the grid.
There is a sudden increase in background luminance when we shift our gaze to an interception.
So excitation of the receptive field center remains the same, whereas inhibitory signals from the background suddenly become stronger, thereby darkening the perceived shade of the interception.
It is notable that is even simplest retina-inspired neuromorphic devices (Mahowland and Mead 1991) are susceptible to Herman grid illusion. It highlights that illusory effects arise from the very basics, almost nuts and bolts, of retinal processing. 




Light Adaptation

Although lateral inhibition removes information about absolute light intensities from the photoreceptor outputs, they still need to deal with huge variations in the level of their inputs. The reason for this is very simple: light intensity can vary over 7 orders of magnitude, but the response range of photoreceptors is quite limited. To overcome this issue photoreceptors decrease their sensitivity upon stimulation. This process underlies afterimage illusions.

Let’s consider the image in Figure 4. If you look at it for 30 seconds to 1 minute and then direct your gaze to a white object, you will perceive cyan inscription over a magenta background. This is called an “afterimage”. It is a retinal effect, so if you will move your eyes along a white object, the cyan inscription will move as well. Humans possess three types of photoreceptors for color vision: red, green and blue. When you stare at a red inscription, red-sensitive photoreceptors gradually decrease their sensitivity. That’s why white objects stimulate them to a lesser extent than it does with green and blue-sensitive photoreceptors. We perceive color as a relative activation of opponent channels: red versus green, yellow versus blue, and white versus black. So decreased activation of red channel shifts the overall color picture to its complementary color, that is - cyan. The magenta color of the background can be explained by similar logic.



Dress & Color Constancy

Back in a day, the dress in figure 5 caused a lot of dispute about its color on the internet.
Despite the true color of the dress being blue and black, roughly 40% of people perceive it as white and gold or blue and gold (Lafer-Sousa et al. 2015). This photo highlights stunning and bizarre individual differences in color perception.



Spectral composition of a light reflected by an object, also known as color, is one of its internal properties. Thus, it can help with object identification. Hence, we would like to minimize the influence of illumination on its perception. Indeed, even though evening illumination is quite red compared to midday light, the perceived colors of your car or of tree leaves remain unchanged. This phenomenon is called color constancy, and it is this mechanism that is confused by the dress.
To have the colors of an object constant under various illuminations we simply need to discard illumination. According to experimental data, that is where differences in the dress color perception arises. First of all (Aston and Hurlbert 2017), people who see the dress as blue and black have a tendency to estimate illumination as yellowish, and those who perceive the dress as white and gold think that illumination is blue. Moreover, when the cues to the illumination are enhanced (Lafer-Souza et al. 2015) ambiguity in a dress perception disappears.
Although color constancy engages various cortical mechanisms, essentially it is a figure-background segregation task. Hence, it roots lay in a lateral inhibition, which initiates within the retina and is repeated at the various levels in the visual cortex.

Perceiving the Present

In contrast to our eukaryotic brothers, we animals are able to move and movement vastly increases the pace of life. This is why the nervous system emerged: to guide, coordinate and navigate us.  As Pavlov brilliantly demonstrated, the nervous system anticipates rather than reacts. In an ever-changing world, being ready for today means being late because preparation takes time.
Vision is there to create a map of an environment. Signal processing and transmission take time. That leads to a delay of roughly 100ms between stimulus onset and elicited perception.
This is mainly due to the slow transduction processes of photoreceptors that transduce photons into electrical signals. The visual system needs to compensate for this delay somehow if we really want to perceive the present.
According to Changizi et al. (Changizi et al. 2008) confusion of this mechanism leads to a vast number of optical illusions, like the classical geometrical illusions.
A combination of these illusions (Herring, Orbison and Ponzo) are shown in Figure 6. Motion leads to a displacement of the objects. In this case, compensation for the delay is critically important. To compensate, we need to estimate how the scene will look in the following 100 ms. To do so we use some cues to figure out the direction and speed of movement and then to model how it will affect an object.
The optical flow induced by motion engenders radial “smear’’, which is mimicked by the radial display shown in Figure 6.  It makes us think we move forward. What we see is not an actual picture, but how it will look like in the next moment. When you pass through the door, its opening goes sideways. That’s why the vertical lines in Herring illusion appears non-parallel. Surprisingly, we become closer to objects in a direction of motion while moving. As a result, the retinal area on which their image is projected, also known as angular size increases. This causes distortion of the squares shape in Figure 6, a phenomena referred to as an Orbison illusion.  Same reason underpins Ponzo illusion as well.


Figure 6   M. A. Changizi et al./Cognitive Science 32 (2008)

This activity moves at the true location of the object or even along its leading edge (Berry et al. 1999). It means that the delay is already compensated for on the level of retinal output. The underlying mechanism is as follows: Ganglion cell activation reports that an object is passing by. Earlier we discussed receptive fields - areas from which neurons collect their inputs. Receptive fields are extended in space. Therefore, a moving object activates some of the ganglion cells ahead of its motion. It activates ganglion cells when just crosses the edge of the receptive field, but not completely passed by yet.  So in a way, the spatial extension of the ganglion cell receptive fields compensates for the delay.  One might note that such spatial extension alone is not enough for a proper delay cancelation. Since it also implies activity of ganglion cells when object have already passed by. This issue is overcome by using transient cells as they only activate briefly when an object crosses their receptive field, then quickly return to their non-activated state.
Intuitively and based on a personal experience with tracking objects, we might suggest that the quality of extrapolation and delay cancelation should depend upon a contrast, which is indeed the case. While interesting, this is not a very surprising result. We already know that due to lateral inhibition, the signal fed into ganglion cells is simply contrast. Weak signals i.e. weak contrast will just fail to activate ganglion cell in a proper way regardless of the speed, direction or any other parameter of motion.
There are more than 20 different types of ganglion cells. Each type senses its particular feature. However, regardless of those features all ganglion cells inevitably sense contrast and this sometimes creates a mess. For instance, let’s consider the next example, the “Plaid stimulus”. This stimulus consists of two gratings passing through each other. When asked about the direction of plaid motion we Homo sapiens show a bias towards grating with the higher contrast as this contrast causes stronger activation of the corresponding direction-selective cells. This subset of ganglion cells only activate when an object moves in a certain direction along vertical and horizontal axes.
There is also a certain type of retinal ganglion cells, which detect an object approaching.
It is contrast-sensitive as well. I suppose that’s why the left part of a rectangle in Figure 7 appears slightly closer.  Indeed, higher contrast causes stronger activation of approach-sensitive cells in the part of the retina where an image of this object is projected. So in terms of ganglion cell firing rates, it looks like the stimulus on the left is approaching us.
 As you remember, to perceive the present the visual system has to model how a scene will change in the next moment. And, as you might also note, objects which we approach usually becomes closer.  In addition, its angular size increases. That’s why the circle with the higher contrast in Figure 7 looks bigger.


Figure 7  M. A. Changizi et al./Cognitive Science 32 (2008)


Conclusion

Here I discussed some neuronal processes behind optical illusions. Namely light adaptation, lateral inhibition and compensation of neuronal delays.  These are all very general, basic and subliminal mechanism of visual processing. The bottom line here is that optical illusions stem from the organization of the nervous system itself, from its ultimate limitations and concerns. These incorrect-perceptions hack-strategies in most cases are consequences of optimizing neuronal performance. So perception of illusions is a downside of neuronal efficiency, which meanwhile nicely illustrates this efficiency.

Written by: Matthew Yedutenko


References

Aston, S., & Hurlbert, A. (2017). What #theDress reveals about the role of illumination priors in color perception and color constancy. Journal of Vision, 17(9):4, 1–18, doi:10.1167/17.9.4.

Berry, M.J., 2nd, Brivanlou, I.H., Jordan, T.A., and Meister, M. (1999). Anticipation of moving stimuli by the retina. Nature 398, 334–338.

Changizi M.A., Hsieh A., Nijhawan R., Kanai R., Shimojo S. Perceiving the Present and a Systematization of Illusions. Cognitive Science 32 (2008) 459–503 

Lafer-Sousa, R., Hermann, K. L., & Conway, B. R. (2015). Striking individual differences in color perception uncovered by ‘‘the dress’’ photograph. Current Biology, 25(13), R545–R546.

Mahowald Misha, Mead Carver “The Silicon Retina” Scientific American, May 1991


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