NEURAL SELECTIVITY

ASSIGNMENT NO LESS THAN 300 WORDS

Many people wear glasses to compensate for the fact that the optical system of their eye does not focus a sharp image on the retinas.  Once you have reviewed the videos below, discuss at least three of the disorders of focusing.  Be sure that you are discussing the complete epigenetic origin which should include a discussion of the genetic/biological origin and the environment influence related to these disorders of focusing. Include in your discussion the impact of culture in the development of the optical system at various stages of the lifespan. Support your belief and use specific examples.

https://www.youtube.com/watch?v=o0DYP-u1rNM

https://www.youtube.com/watch?v=6YxffFmi4Eo

READING

PSYC304| LESSON 3: VISUAL PERCEPTION: NEURAL SELECTIVITY

Introduction

Topics to be covered include:

  • Lateral inhibition
  • Single fibers of an optic nerve
  • The role of feature detectors in visual information processing and perception
  • Where information goes when it is processed and sent to the brain
  • How forms of visual agnosia show us the importance of parts of the brain
  • Why it is important to understand distributed representation

In this lesson, we will look at how the visual systems identify and process information in greater depth. Light is processed and changed as it moves through visual systems to reach the brain. The information is then interpreted by the brain, meaning the exact visual stimulus initially encountered as a distal stimulus is not completely the same once it is processed by the brain. This lesson will explain the different processes that occur and move the information from the eye to the brain.

Electrical Signals

A brain neuron

For this lesson, let us take a trip to the store. When you go grocery shopping, think about how you accomplish the goal of getting everything on your list. Is it a straight line, or do you weave in and out of aisles as you put different types of groceries in your cart? If you only go to the store for one item, a straight line might work, but I’m not sure anyone could exist on just one item to eat for the entire week. The point is that the straight line would be fairly one dimensional and would not provide you with the variety of foods you need.

This is true for electrical signals too. Signals sent to the brain from receptors do not go directly to the brain from the receptor in a straight line. The information that is sent to the brain gets there via the signals of many neurons responsible for different aspects of the initial sensory image. This interaction of the signals of multiple neurons is called neural processing (Goldstein & Brockmole, 2017).

Now, imagine you are in the middle of the store when an end cap full of potato chips falls over leaving mess everywhere. At the time of this incident, 20 people were clustered together nearby. Each one saw something different about this incident. You were in this cluster and caught this incident out of the corner of your eye. You did not directly see it, but did see some and had a good idea of what else happened. By the time you think about it later, the image you pull up seems more complete somehow. Your brain added some details to create a complete picture for you.

Inhibitory Processes in the Retina

When an image is transmitted to the retina, it is processed through a layer of photoreceptors, or neurons that measure light intensity, and alter this information into something that can be processed by the rest of the nervous system. Different photoreceptors correspond to different light points in the observed stimulus. Photoreceptors that correspond to brighter areas of a stimulus process an increased amount of light, which results in larger signals when compared to photoreceptors that correspond to darker areas of a stimulus. This information is then processed in different ways in different interactions with different neurons within the retina. The photoreceptors generate signals based on the amount of light they are receiving, which means signals will be different based on different amounts of light (Grobstein, 2017).

LATERAL INHIBITION

Lateral Inhibition refers to the inhibition that neurons have on one another and how this inhibition is transmitted across the retina in order to increase contrast between dark and light areas to produce a sharper image for the brain (Goldstein & Brockmole, 2017). Think about the endcap of potato chips falling over. If the manager asks what happened and everyone speaks at once, the message becomes blurred as too many people provide information. If only a couple of people speak – preferably people who saw the event from different angles, the picture becomes clearer and more defined. So, how does this work with vision? Output neurons point out to the brain the areas of contrast where light intensity changes quickly, like the light and dark patterns of a checkerboard (Grobstein, 2017).

In a classical study conducted by Keffer Hartline, Henry Wagner, and Floyd Ratcliff, researchers used the Limulus Polyphemus, the horseshoe crab to demonstrate how lateral inhibition can affect the response of neurons in a circuit. The limulus is a favorite specimen to use because its retinal neurons are large and easy accessible. Their eyes, which have many tiny structures called ommatidia, have provided a significant amount of research about the physiological processes of human vision. Each ommatidia has a small lens on the eye’s surface that is located directly over a single receptor. What makes the limulus eye interesting to study is that light shown on a single receptor led to rapid firing rate of nerve fiber, yet as additional light promoted neighboring receptors, this inhibited the firing of the initial single receptor (Goldstein & Brockmole, 2017). Thus, lateral inhibition reduced the firing intensity of neighboring receptors. As this reduction occurs, contrast and definition of the stimulus increase.

The Lateral Inhibition Explanation of the Chevreul (Staircase) Illusion

Contrast seems a bit less defined when you look at an array of rectangles with the same color ranging from lighter to darker. This can bring illusions to light. French chemist Michel-Eugene Chevreul’s illusion provided research on brightness illusion by placing gray rectangles side by side. They ranged from light to dark gray from left to right. When you look at these rectangles, you can see an illusion of brightness and color due to the adjacent rectangles. When you look at the rectangles, you can see that they are consistent between the borders, but when you look at the borders, you will notice that it seems like the line becomes darker on the left and lighter on the right as you transition to the next hue of gray (Goldstein & Brockmole, 2017). This illusion is the result of lateral inhibition as neural output varies when the amount of light varies.

Along the boundary between adjacent shades of grey in the Mach bands illusion, lateral inhibition makes the darker area falsely appear even darker and the lighter area falsely appear even lighter.

The Lateral Inhibition Explanation of the Hermann Grid Illusion

The Hermann Grid

Another perceptual phenomenon explained by lateral inhibition is the Hermann Grid. Each intersection contains gray images in between the white “paths” and black squares. Yet when you look directly at the gray zones they vanish. Lateral inhibition can help to explain why this occurs. Signals from bipolar cells create the illusion of gray squares at each intersection. Lateral inhibition creates a slower response to the perception of gray squares and explains why perception doesn’t match the actual physical stimulus (Goldstein & Brockmole, 2017). In a sense, the brain fills in the intensity between the intensity of the two darker squares.

If you think about it, we live in a world of constantly changing light. We encounter intense light, and then we encounter less intense light in varying shades as we move throughout our day. Yet, we do not really notice this. What we see is not really the visual stimulus as it truly appears, but something processed through neural networks as the light is prepared for analysis by the brain.

Problems with the Lateral Inhibition Explanations of the Chevreul Illusion and the Hermann Grid

Of course, lateral inhibition is not the only explanation for the visual illusions that occur. Researchers have conducted studies that challenge the use of lateral inhibition as an explanation of the Chevreul illusion as well as the Hermann Gird. First, for the Chevreul illusion, researchers changed the background ramp from light on the left, dark on the right to the opposite. In so doing, one’s perception of the top and bottom changes, while lateral inhibition between the rectangles stays the same (Goldstein & Brockmole, 2017). The effect is thus impacted by the top and bottom in addition to changes in light to dark.

With regard to the Hermann Grid, problems with lateral inhibition explanations arise when the grid is made with curvy squares rather than straight. Using curvy squares should have little effect on the dark spots, but when the squares are curved, the dark spots vanish. While this calls to question the lateral inhibition theory to an extent, it does not completely discount it (Goldstein & Brockmole, 2017). Perception of changes in the stimuli in these illusions opens up the door for additional research to determine the extent of the influence of lateral inhibition, or, perhaps the change in how we see this influence.

Responding of Single Fibers in the Optic Nerve

On center and off center retinal ganglion cells respond oppositely to light in the center and surround of their receptive fields. A strong response means high frequency firing, a weak response is firing at a low frequency, and no response means no action potential is fired.

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  • Receptive FieldBefore his work on the limulus, Hartline studied fiber responses by dissecting a frog’s eye. This research illuminated how light shown on the retina causes the neuron to fire, this area is labeled as the receptive field. The retina contains areas that must receive illumination in order to receive a response from an optic nerve fiber. These receptive fields overlap, which prompts retinal activation of many ganglion cell fibers by light on an overlapping receptive field. Hartline noted that the receptive field covers a greater area than a single rod or cone, which demonstrates that thousands of signals are converging (Goldstein & Brockmole, 2017).

Hubel and Wiesel’s Rationale for Studying Receptive Fields

Using stimuli from an animal, Hubel and Wiesel’s research showed how cortical neurons at higher levels of the visual system become more specialized to certain types of stimuli. Using a projector instead of direct light on the animal’s eye the researchers were able to determine which areas, excitatory or inhibitory did not respond to screen (Goldstein & Brockmole, 2017).

It is important to understand how signals travel from the retina, following Hubel and Wiesel’s approach; signals leave the eye in the optic nerve, travel to the lateral geniculate nucleus (LGN), and then to the occipital lobe (the visual receiving area). The visual receiving area is the sensory location of the cortex. Interestingly, center-surround receptive fields are present in both the optic nerve fibers and the neurons in the LGN, which calls into question the function of the LGN. It is possible that it acts to regulate neural information based on the reduction in output from the LGN in comparison to the input going into it. Another thought is that it is involved in feedback of information received from the brain (Goldstein & Brockmole, 2017).

Receptive Fields of Neurons in the Visual Cortex

Gabor filter

Hubel and Wiesel also conducted research on receptive fields in the striate cortex. They discovered that instead of the center-surround arrangement, the receptive cells in these fields are arranged side-by-side. These side-by-side cells are called simple cortical cells. These cells respond to specific stimuli orientations, in particular these cells are sensitive to vertical orientation. This is part of the orientation turning curve, which indicates changes in cell firing based on vertical or tilted orientations. As the cells are vertically oriented, the firing response is optimum. As the bar is tilted, the cell response decreases, and begins to show the impact of inhibitory areas (Goldstein & Brockmole, 2017).

Not all cells in the striate cortex responded the same way for Hubel and Wiesel. Some cells did nothing when exposed to small spots of light. This is best defined as the measure between orientation and firing (Goldstein & Brockmole, 2017). They discovered by accident that some cells in the striate cortex respond to other stimuli.

COMPLEX CELLS

END-STOPPED CELLS

Different cells respond to different, specific features, earning the name feature detectors.

Selective Adaptation, Selective Rearing and Sensory Coding

  • SELECTIVE ADAPTATION
  • SELECTIVE REARING
  • SENSORY CODING

Now that we have explored how feature detectors respond to specific stimuli, it is time to see if they have anything to do with perception. One way is through selective adaptation. Selective adaptation occurs as neurons that are firing eventually become fatigued, or they adapt. Selective adaptation causes the neuron firing rate to decrease. Adaptation also causes the neuron firing frequency to decrease with the stimulus is quickly presented again. Adaptation is selective because vertical neurons adapt and non-firing neurons do not. This indicates that the adaptation selectively affects specific orientations, just like neurons selectively respond to specific orientations (Goldstein & Brockmole, 2017).

Cortical Organization

Now that we have explored receptive fields and the response properties of neurons, it is time to look how the visual system is organized.

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  • Spatial OrganizationWhen we look at the fallen display in the store things are organized across the visual field, including the people looking at the display on the floor, and potato chip bags scattered across the floor. Each of these stimuli represent different locations in the environment and specific locations in the visual cortex. This is called spatial organization, or the organization of stimuli in the environment as it is represented by locations in the visual cortex (Goldstein & Brockmole, 2017).

 

Most of what we have been talking about is based on normal function of the parts of the visual system. That, however is not always the case and you can learn as much from what happens when something does not work, as you can when it works properly. The fMRI is also used to study people who have suffered some form of damage to the visual association pathway. Visual agnosia is an inability to properly perceive a stimulus as it should be perceived (Carlson, Miller, Heth, Donahoe, & Martin, 2010). With visual agnosia, an individual is capable of sight, and can see a stimulus with visual sensory organs, but cannot identify the stimulus. Let’s look at a few types of visual agnosia.

Imagine you are on your shopping trip and your best friend is also there. Unfortunately, when you look at him you see a head with eyes, a nose, a mouth, and cheeks, but they are not where they are supposed to be and you are unable to identify him. You can recognize his voice, which gives his identify away, but your visual system is not translating the information it is processing in a way that allows you to see a complete face as it is truly put together. This is prosopagnosia.

Damage to the temporal lobe can result in prosopagnosia, or a difficulty recognizing the faces of people whose identity is known (Goldstein & Brockmole, 2017). People diagnosed with prosopagnosia understand that they are looking at a face, but cannot identify the owner of the face, even if it is a close loved one. The individual can recognize the parts of the face, but the configuration of the features does not align correctly (Carlson et al., 2010).

 

The parahippocampal gyrus is shown in blue

Faces are not the only topic of specialization in the temporal cortex. We also see specialization for place, specifically pictures of indoor and outdoor scenes, which activate the parahippocampal place area (PPA) in the ventral stream (Goldstein & Brockmole, 2017). An individual with a visual agnosia in this area might be able to recognize the grocery store as a store, but might be unable to recognize the specific objects in the store, such as the displays, the food on the shelves, or other objects. So, it would seem that the spatial layout is intact, but the objects within the layout are not.

One other area of specialization in the region next to the primary visual cortex is the extrastriate body area (EBA), which is activated by the rest of the body parts other than faces (Goldstein & Brockmole, 2017). If visual agnosia occurs in the EBA, an individual might be able to recognize a face, but not a hand or leg. With this form of agnosia, you would be able to recognize your friend’s face in the store, and the shelves and produce, but not your friend’s hand or arm as a hand or arm

So, what about the environment and the types of stimuli encountered on a regular basis? Selective rearing occurs when an animal is raised in a particular environment with limited specific types of stimuli. Due to the limited selection, the neurons respond more to these stimuli. When this happens, the response potential for other stimuli is reduced. This is neural plasticity, or the shaping of neurons through perceptual experiences (Goldstein & Brockmole, 2017). As stimuli are limited, neural plasticity becomes more specialized to the stimuli that the animal has been exposed to. Blakemore and Cooper explored this ‘use it or lose it’ effect of neural plasticity by limiting the stimuli kittens were exposed to. Kittens were limited to viewing either horizontal or vertical stripes for the first five months of life. The kittens were then tested to see the effects of the selective rearing. Results indicated that cats raised in horizontal stimuli responded to horizontal but not vertical stimuli. The same occurred for cats raised in vertical stimuli (Goldstein & Brockmole, 2017).

 

Sensory Coding refers to how neurons represent different characteristics of the environment. When specialized neurons respond to specific stimuli, specificity coding has occurred. However, this idea is likely to be incorrect because the brain would need one different neuron to perceive every different object. Neurons usually respond to more than stimulus. It could be that there are a number of neurons that are involved in representing a stimulus. Another form of coding looks at the different neuronal firing patterns that can occur in the representation of a particular stimulus. Where population coding utilizes larger groups of neurons that can create a greater number of different patterns, sparse coding involves smaller groups of neurons. Sparse coding is in effect when a stimulus is represented by the firing of a smaller group of neurons (Goldstein & Brockmole, 2017).

 

Dorsal and Ventral Pathways

Neurons are also organized through streams, or pathways. The pathway leading from the striate cortex to the parietal lobe is called the dorsal pathway, and the pathway that leads to the parietal lobe is the ventral pathway. The ventral pathway identifies what a stimulus is, and the dorsal pathway identifies where a stimulus is located, and whether or not it is stationary. The dorsal and ventral pathways serve different functions, but they are connected and signals flow both up toward the parietal and temporal lobes and back. Some information is shared between them as what an object is and where it is interact. The dorsal pathway also seems to be linked to the actions of an object, including how an action is carried out (Goldstein & Brockmole, 2017).

The dorsal stream (shown in green) and the ventral stream (shown in purple)

Modularity and Agnosia

  • MODULARITY
  • VISUAL AGNOSIA
  • PARAHIPPOCAMPAL PLACE AREA (PPA)
  • EXTRASTRIATE BODY AREA (EBA)

While the pathways are connected, they do serve different functions. Based on this, different areas of the cortex respond to different stimuli. This is called modularity. The different specialized areas that process information are called modules. One area where specialization to specific stimuli is the face. Researchers have used fMRI brain imaging to identify areas of the brain where neurons respond best to faces when distinguished from other objects. The main area of activity occurs in the fusiform face area (FFA), located at the base of the brain below the IT cortex (Goldstein & Brockmole, 2017).

Computer enhanced fMRI san of a person who has been asked to look at faces. The image shows increased blood flow in the part of the visual cortex that recognizes faces

Distributed Representation

Now that we have looked at specific areas that specialize in faces, body parts, and environmental scenes, we need to understand that these specific areas do not exist in a vacuum. Other areas of the cortex, and the rest of the brain for that matter, are also involved in identification of these stimuli. This is called distributed representation, or activation in multiple different areas of the brain. This is important to know because while research continuously indicates areas of specialization, it also indicates that the activation is distributed to other areas of the brain at the same time (Goldstein & Brockmole, 2017).

So, why might this occur? Well for one, we discussed at the beginning of this lesson that processing does not occur in a straight line. The processing of the stimulus travels around to different areas of the brain. Additionally, a face is not just a face. Each face has different features and movements, all of which must be processed based on a multidimensional approach in different sections (Goldstein & Brockmole, 2017). Let’s relate it to our shopping trip. Think about making spaghetti and meatballs for dinner and shopping for the ingredients. Is it just spaghetti and meatballs? What is the sauce made up of? What about the meatballs?

Now, in addition to using the recipe, you have some understanding about what goes into spaghetti and meatballs stored in your memory. You remember perceptual experiences of cooking and eating spaghetti and meatballs previously. Next, we will look at how research has measured the relationship between memory and perception in the hippocampus, an area of the brain associated with memory formation and storage (Goldstein & Brockmole, 2017).

Perception and Memory

What would happen if you had your hippocampus removed on both sides of your brain? The following case study shows us. Henry Molaison (H.M.) had the hippocampus removed completely as doctors attempted to stop the epileptic seizures he was experiencing. The seizures were eliminated, but so was his ability to store experiences and form long-term memories. Other research showed that there is a connection between visual processes and the hippocampus that respond to our three areas again: faces, bodies and environment scenes (Goldstein & Brockmole, 2017). Where one neuron might respond to one face, another might respond to recognition of another known face. Thus, certain neurons would be responsible for certain categories or types of stimuli.

What has all of this taught us? Can we conclusively connect certain neurons to certain stimuli? Do we have a solid answer to the mind-body problem, or the question of how biological neural processes become our perceptual experience? Well, if we have seen anything with this lesson, it is the fact that each new discovery leads to more questions and potential exceptions to the explanations proposed. Lateral inhibition seems to make sense in some cases, but not all cases. Each person has their own individual experiences based on their own individual perspective and processing of information from a given stimulus.

If I cook a lot, my perception of that plate of spaghetti and meatballs might be a little more detailed as I note the spices mixed in the sauce. This goes along with the expertise hypothesis, which proposes that changes occur via the plasticity of experience that we looked at earlier in this lesson as individuals spend more time with a given stimulus (Goldstein & Brockmole, 2017). Of course, that does not mean that the expertise hypothesis would explain everything. Studies on faces and FFA neurons indicate that there is merit to this hypothesis as experts in a field indicate increased neuronal responses for what is known based on strong experience or expertise. Yet, some researchers argue that this has more to do with neural connections that are already there rather than strengthening and expanding new responses (Goldstein & Brockmole, 2017).

Henry Molaison, also known as H.M.

Conclusion

As we have seen, there are no straight lines in visual processing. A simple shopping trip could involve thousands of neurons acting together to transmute a clear and understandable picture to the brain. Different receptors provide different light perspectives that can cause neurons to fire more or less. We have also seen that this process is regulated by lateral inhibition based on how the light patterns are distributed across the retina. Amazingly, more light over more of the retina increases the activation of lateral inhibition, which decreases the firing of the receptor neurons. Now, this seems like it would hurt our visual processing, but in actuality, it provides clarity.

Imagine going shopping and having hundreds of spaghetti sauce options all crowded together. They look similar and now you have to find the one you want, but there are so many and because there are so many none stand out and provide the contrast you need to recognize the one you want.
We also looked, to some extent, at how the brain fills in blanks and processes the information to make it more understandable and cohesive. Think about filling in the information about the incident with the display falling over. You didn’t see the whole thing, but your brain had some understanding to help it fill in what you did not see and then process it into an experiential memory.

We learned that we have areas that specialize in visual processing of certain types of information, such as faces, and views of our environment. Parts of the brain are responsible for recognizing the faces of the people we encounter at the grocery store, the aisles and products, and the arm of someone reaching for spaghetti sauce. Of course, even though certain neurons specialize and correspond to certain areas of the brain, other neurons and areas of the brain are involved in a distributed representation of the stimulus. We do not process sensory information in just one dimension. We also tend to process information we have a lot of experience with in more detail with more neuronal action.

Of course, we also learned that for everything concluded in one research article, there are exceptions. We might have more questions than answers now that we are really looking at the details of the perceptual process, but that does not mean we have not learned valuable information about how we see what we see. In our next lesson we will look a little more at how we tend to organize what we see.

Sources

Carlson, N. R., Miller, H. L., Heth, D. S., Donahoe, J. W., & Martin, G. N. (2010). Psychology: The science of behavior (7th ed.). Boston, MA: Allyn & Bacon.

Goldstein, E. B. & Brockmole, J. R. (2017). Sensation and perception (10th ed.). Boston, MA: Cengage.

Grobstein, P. (2017). Tricks of the eye, wisdom of the brain. Retrieved from: http://serendip.brynmawr.edu/bb/latinhib.html

Image Citations

“A brain neuron ” by 23684899_ML.

“Along the boundary between adjacent shades of grey in the Mach bands illusion, lateral inhibition makes the darker area falsely appear even darker and the lighter area falsely appear even lighter.” by https://commons.wikimedia.org/wiki/File:Bandes_de_mach.PNG.

“The Hermann Grid” by https://commons.wikimedia.org/wiki/File:HermannGrid.gif.

“On center and off center retinal ganglion cells respond oppositely to light in the center and surround of their receptive fields. A strong response means high frequency firing, a weak response is firing at a low frequency, and no response means no action potential is fired.” by https://commons.wikimedia.org/wiki/File:Receptive_field.png.

“Gabor filter” by https://commons.wikimedia.org/wiki/File:Gabor_filter.png.

“The dorsal stream (shown in green) and the ventral stream (shown in purple)” by https://commons.wikimedia.org/wiki/File:Ventral-dorsal_streams.svg.

“Computer enhanced fMRI san of a person who has been asked to look at faces. The image shows increased blood flow in the part of the visual cortex that recognizes faces” by https://commons.wikimedia.org/wiki/File:Face_recognition.jpg.

“Parts of the brain highlighted in different colors ” by By Allan Ajifo – https://www.flickr.com/photos/125992663@N02/14414604077/, CC BY 2.0, https://commons.wikimedia.org/w/index.php?curid=35380024.

“The parahippocampal gyrus is shown in blue” by https://commons.wikimedia.org/wiki/File:Sobo_1909_630_-_Parahippocampal_gyrus.png.

“The body and arms of a woman in the grocery store” by 50632177_ML.

“Henry Molaison, also known as H.M. ” by https://en.wikipedia.org/wiki/Henry_Molaison#/media/File:Henry_Gustav_1.jpg.

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