Our large neocortex is the crux of intelligence and gives humans an innate ability to recognize patterns. Hawkins (2004) introduces his view on consciousness as "what it feels like to have a neocortex." Vernon Mountcastle (1978) proposed a fascinating hypothesis in the late 1970s, which stated that "there is a common algorithm that is performed by all the cortical regions." This algorithm has the ability to replicate itself and in a sense organize itself. The same types of layers, cell types, and connections exist in the entire cortex. Mountcastle explains that the “differences between areas of the neocortex reflect differences in their patterns of extrinsic connections” (p. 15). Therefore, there is nothing intrinsically different in the structure or function of various areas of the neocortex. Although there is a fissure separating the two cerebral hemispheres and a sulcus dividing the front and back, there are no clear delineations of certain areas constrained to certain functions. There is major overlap between the senses as well as between the senses and motor mechanisms.
Jeff Hawkins attempts to outline a framework for understanding intelligence in his book On Intelligence. He discusses many topics and uses logic to deduce how the brain may work. His definition of intelligence is most interesting. He defines intelligence as the ability to predict and remember. He creates what he calls a memory-prediction framework to understand the brain and its capacities.
Within this framework, there are many important aspects. To begin, Hawkins argues to steer away from our intuitive sense that intelligence is based on output behavior. Instead, he believes that intelligence is a process centered on successful prediction, experience, memory and understanding. Hawkins’ focus is on the neocortex, which is most pronounced in humans, and he focuses on four major capabilities of the cortex.
First, he describes that the cortex stores sequences of patterns, as well as, sequences of sequences. The best example would be our memory of the alphabet. It is not something recalled all together in an instant. Rather, our memory conveniently stores the information as a sequence of patterns.
Second, the cortex recalls “auto-associative” memories. He is referring to our ability to recognize patterns when only given a part of the pattern. For example, if we hear half a melody of a song we know, we can often recognize the entire song and complete the melody. Essentially, each functional region is waiting for familiar patterns or pattern-fragments to be processed. The inputs to the brain are linking to themselves auto-associatively, filling in the present and what normally flows next (Hawkins, 2004).
Third, patterns are stored in an invariant form. This idea of storing ideas in an invariant form can be traced back to ancient philosophers such as Plato and Aristotle. However, Hawkins steers away from most philosophical implications and focuses on our ability to store a belief or an idea of an object regardless of its current context. For example, an object such as a table is stored in our brains in an invariant form. Although there are many individual instances of a table, i.e. coffee tables, kitchen tables, restaurant tables, we know that an object with four legs and a top is most often a table regardless of context and individual differences. We have the ability to identify a novel table without ever seeing one that looked exactly like the one being viewed. This system allows knowledge of past events to be applied to new situations that are similar but not identical to the past (Hawkins, 2004).
Fourth, Hawkins explains that the cortex stores patterns in a hierarchy. The neocortex, if stretched flat, is about the size of a large table napkin and 2mm and consists of six layers that are roughly the thickness of a playing card (Hawkins). These six layers are separated mostly by cell type and neuronal connections. Among these layers there is a branching hierarchy. In a certain sense, raw sensory data is being sent “up” the hierarchy, as more and more abstract and generalized versions of information are sent “down” the hierarchical layers and compared with known patterns. While reading words on a page, the higher levels of the cortical hierarchy are sending more signals down to the primary visual cortex than your eyes are receiving from the page (Hawkins, 2004).
This hierarchical structure gives us our ability to store patterns of patterns. He often uses music as a metaphor and describes how a song is understood. A song is made up of melodies, which are made up of a sequence of notes that are certain intervals away from one another. The nested structure of the world can be seen in our model of the world. Another great example is a piece of writing such as a book. From the simplest element lines make up letters, letters make up words, words make up sentences, sentences make up paragraphs, paragraphs make up chapters, and multiple chapters combine to form a book. Hawkins (2004) describes in great detail how this hierarchical structure seen in the world is actually similar to how the brain processes and stores information.
Our brains use stored memories to constantly make predictions about everything we see, feel and hear. Prediction is so pervasive that the way we “perceive” the world does not come solely from our senses. We perceive a combination of what we sense and of our brain’s memory-derived prediction. In this predictive process, neurons involved in sensing become active in advance of them actually receiving sensory input. These predictions are not always perfect, but the probabilistic predictions are often reliable. This concept is understood at some level to be intuition (Hawkins, 2004).
A large area of our neocortex expanded dramatically only a couple millions years ago. The neocortex is built using a common repeated element so evolution led to the rapid copying of an existing structure. As the cortex got larger over evolutionary time it was able to remember more and more about the world, form memories and the ability to make more predictions. Through time, the complexity of the memories and predictions increased (Hawkins, 2004).
By adding a memory system to the sensory paths of the primitive brain, an animal gains an ability to predict the future. Memory and prediction provide an animal a way to use its existing “old brain” behavior more intelligently. These capabilities of the neocortex allow an animal to use its existing hardware more effectively and compliments Ornstein’s and Allman’s view of the retrofitted brain. This ability creates a better adapted species. At a future time when the animal encounters the same or a similar situation the memory recognizes the input as similar and recalls what happened in the past. Recalled memory is compared with the sensory input streams and it “fills in” the current input and predicts what will be sensed next. In a certain sense, this allows an animal to see into the future (Hawkins, 2004).
As we interact with the environment, whether consciously or unconsciously, we are constantly predicting what is going to happen next. For example, as you read this sentence you are predicting what the next word will be in the sentence. While a stream of sensory information is coming into our brains we have a significant amount of more information flowing back down the hierarchical memory system. This feedback is sending predictions of what to expect next (Hawkins, 2004).
Multiple regions of the neocortex are simultaneously trying to predict what their next experience will be. Visual areas make predictions about edges, shapes, objects, locations and motions. Auditory areas make predictions about tones, directions to sources and patterns of sound. Somatosensory areas make predictions about touch, texture, contour and temperature (Hawkins, 2004). When the sensory input does arrive, it is compared with what was expected. When your predictions are met, you’ll continue without consciously knowing that your predictions were verified. For example, our auditory areas predict that background noise will continue, in continuation, moment after moment, and as long as the noise does not change our expectations are not violated. However, when a background noise ceases, this violates our prediction and attracts our attention.
Another great example of this memory-prediction framework is of our mind predicting and filling in the small blind spot in each eye where the optic nerve exits each retina. Even with one eye open, our visual system “fills in” missing information to make one coherent vision. The visual cortex is drawing on memories of similar patterns and makes a continuous stream of predictions that fill in for any missing input. We perceive clear lines and boundaries separating objects when we look at the world, but the raw data entering our eyes is often noisy and ambiguous. Our eyes saccade about three times every second. A saccade is when eyes fixate on one point and then suddenly jump to another point. We are not aware of these movements, and do not consciously control them. Each time our eyes fixate on a new point, the pattern entering your brain from the eyes changes completely from the last fixation. Yet, we are only aware of a continuous view of the world.
Jeff Hawkins attempts to outline a framework for understanding intelligence in his book On Intelligence. He discusses many topics and uses logic to deduce how the brain may work. His definition of intelligence is most interesting. He defines intelligence as the ability to predict and remember. He creates what he calls a memory-prediction framework to understand the brain and its capacities.
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| Jeff Hawkins and his book On Intelligence (Picture Link) |
First, he describes that the cortex stores sequences of patterns, as well as, sequences of sequences. The best example would be our memory of the alphabet. It is not something recalled all together in an instant. Rather, our memory conveniently stores the information as a sequence of patterns.
Second, the cortex recalls “auto-associative” memories. He is referring to our ability to recognize patterns when only given a part of the pattern. For example, if we hear half a melody of a song we know, we can often recognize the entire song and complete the melody. Essentially, each functional region is waiting for familiar patterns or pattern-fragments to be processed. The inputs to the brain are linking to themselves auto-associatively, filling in the present and what normally flows next (Hawkins, 2004).
Third, patterns are stored in an invariant form. This idea of storing ideas in an invariant form can be traced back to ancient philosophers such as Plato and Aristotle. However, Hawkins steers away from most philosophical implications and focuses on our ability to store a belief or an idea of an object regardless of its current context. For example, an object such as a table is stored in our brains in an invariant form. Although there are many individual instances of a table, i.e. coffee tables, kitchen tables, restaurant tables, we know that an object with four legs and a top is most often a table regardless of context and individual differences. We have the ability to identify a novel table without ever seeing one that looked exactly like the one being viewed. This system allows knowledge of past events to be applied to new situations that are similar but not identical to the past (Hawkins, 2004).
Fourth, Hawkins explains that the cortex stores patterns in a hierarchy. The neocortex, if stretched flat, is about the size of a large table napkin and 2mm and consists of six layers that are roughly the thickness of a playing card (Hawkins). These six layers are separated mostly by cell type and neuronal connections. Among these layers there is a branching hierarchy. In a certain sense, raw sensory data is being sent “up” the hierarchy, as more and more abstract and generalized versions of information are sent “down” the hierarchical layers and compared with known patterns. While reading words on a page, the higher levels of the cortical hierarchy are sending more signals down to the primary visual cortex than your eyes are receiving from the page (Hawkins, 2004).
This hierarchical structure gives us our ability to store patterns of patterns. He often uses music as a metaphor and describes how a song is understood. A song is made up of melodies, which are made up of a sequence of notes that are certain intervals away from one another. The nested structure of the world can be seen in our model of the world. Another great example is a piece of writing such as a book. From the simplest element lines make up letters, letters make up words, words make up sentences, sentences make up paragraphs, paragraphs make up chapters, and multiple chapters combine to form a book. Hawkins (2004) describes in great detail how this hierarchical structure seen in the world is actually similar to how the brain processes and stores information.
Our brains use stored memories to constantly make predictions about everything we see, feel and hear. Prediction is so pervasive that the way we “perceive” the world does not come solely from our senses. We perceive a combination of what we sense and of our brain’s memory-derived prediction. In this predictive process, neurons involved in sensing become active in advance of them actually receiving sensory input. These predictions are not always perfect, but the probabilistic predictions are often reliable. This concept is understood at some level to be intuition (Hawkins, 2004).
A large area of our neocortex expanded dramatically only a couple millions years ago. The neocortex is built using a common repeated element so evolution led to the rapid copying of an existing structure. As the cortex got larger over evolutionary time it was able to remember more and more about the world, form memories and the ability to make more predictions. Through time, the complexity of the memories and predictions increased (Hawkins, 2004).
As we interact with the environment, whether consciously or unconsciously, we are constantly predicting what is going to happen next. For example, as you read this sentence you are predicting what the next word will be in the sentence. While a stream of sensory information is coming into our brains we have a significant amount of more information flowing back down the hierarchical memory system. This feedback is sending predictions of what to expect next (Hawkins, 2004).
Multiple regions of the neocortex are simultaneously trying to predict what their next experience will be. Visual areas make predictions about edges, shapes, objects, locations and motions. Auditory areas make predictions about tones, directions to sources and patterns of sound. Somatosensory areas make predictions about touch, texture, contour and temperature (Hawkins, 2004). When the sensory input does arrive, it is compared with what was expected. When your predictions are met, you’ll continue without consciously knowing that your predictions were verified. For example, our auditory areas predict that background noise will continue, in continuation, moment after moment, and as long as the noise does not change our expectations are not violated. However, when a background noise ceases, this violates our prediction and attracts our attention.
Another great example of this memory-prediction framework is of our mind predicting and filling in the small blind spot in each eye where the optic nerve exits each retina. Even with one eye open, our visual system “fills in” missing information to make one coherent vision. The visual cortex is drawing on memories of similar patterns and makes a continuous stream of predictions that fill in for any missing input. We perceive clear lines and boundaries separating objects when we look at the world, but the raw data entering our eyes is often noisy and ambiguous. Our eyes saccade about three times every second. A saccade is when eyes fixate on one point and then suddenly jump to another point. We are not aware of these movements, and do not consciously control them. Each time our eyes fixate on a new point, the pattern entering your brain from the eyes changes completely from the last fixation. Yet, we are only aware of a continuous view of the world.
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