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Different brain areas analyze sight, sound, and smell data that other areas use in thoughts, feelings, and actions but how does all this activity bind together in one experience? Descartes explanation was that all sense data clears through the pituitary gland, that passes it to the mind, which is like a little man in the brain watching a movie. Yet by that logic, that little man would need another little man inside his head to also observe, and so on, in an infinite regress (Dennett, 1991) (Figure 6.34). That there is a little man in the brain is illogical, but physical realism isn’t much better, as it concludes that each neuron in the brain:

“… doesn’t ‘know’ it is creating you in the process, but there you are, emerging from its frantic activity almost magically.” (Hofstadter & Dennett, 1981) p352.

That nerves that can’t observe magically act and “there you are” is weaker than dualism. The mind-body problem of centuries ago lives on in neuroscience today as the binding problem:

“One of the most famous continuing questions in computational neuroscience is called ‘The Binding Problem’. In its most general form, ‘The Binding Problem’ concerns how items that are encoded by distinct brain circuits can be combined for perception, decision, and action.” (Feldman, 2013) p1.

The binding problem arises because distant processing hierarchies can’t just exchange data. They can’t “talk”, as global workspace theory claims (6.1.6), because when a visual cortex nerve fires to register a line, it doesn’t say “I saw a line” like a little person. It just fires a yes-no response like any other neuron. To bind that response to another feature like redness needs higher processing in the same hierarchy. At each step in the hierarchy, a nerve can fire to trigger a motor response, but it isn’t an experience because the nerve doesn’t know why it fired. The six-layered visual cortex can process lines, shapes, colors, and textures but the last nerve to fire in a sequence knows no more than the first. To integrate vision and smell needs a higher area to process both outputs but according to brain studies, this doesn’t happen.

Different areas evolved to process sight, smell, sound, thoughts, feelings, touch, and memory but no area evolved to integrate them all. If it had, the brain would be wired like a computer motherboard, with many lines to a central processor, but it isn’t. Each brain area is encapsulated, so smell, sight and sound brain areas can’t exchange any experiences they have with each other:

“Because of the principle of encapsulation, conscious contents cannot influence each other either at the same time nor across time, which counters the everyday notion that one conscious thought can lead to another conscious thought … content generators cannot communicate the content they generate to another content generator. For example, the generator charged with generating the color orange cannot communicate ‘orange’ to any other content generator because only this generator (a perceptual module) can, in a sense, understand and instantiate ‘orange’.” (Morsella et al., 2016) p12.

And even if higher processing tried to integrate all brain areas, it would be too slow, just as complex thought usually comes up with a witty retort after a conversation is over. Our brain can integrate perceptions with memory to drive motor acts in less than a second but if one hierarchy did this, it would take much longer. The binding problem is that brain activities combine in a way that its wiring doesn’t support, so our unified experience of senses, feelings, thoughts, and actions should be impossible.

Encapsulation predicts that the hemispheres can’t exchange data, so each only sees half the visual field. Yet cutting the nerves between the hemispheres doesn’t give a sense of loss:

“… despite the dramatic effects of callosotomy, W.J. and other patients never reported feeling anything less than whole. As Gazzaniga wrote many times: the hemispheres didn’t miss each other.” (Wolman, 2012).

   Why don’t split-brain patients know that the corpus callosum is cut? If the optic nerve is cut, we know we are blind, as no data comes from the eyes. If an injury cuts the spinal cord, we know we are paralyzed, as no data comes from the legs. But when the millions of nerves joining the hemispheres are cut, both carry on as before! Why doesn’t the verbal hemisphere report a loss of data? If it normally sees the entire field using the other hemisphere, it should report being half blind, but it doesn’t. It follows that it doesn’t report any missing data because there is none.

Instead of data loss, dividing the hemispheres just divides consciousness. One patient couldn’t smoke because when the right hand put a lit cigarette in his mouth, the left hand removed it, and another found her left hand slapping her awake if she overslept (Dimond, 1980) p434. Conflicts made simple tasks take longer – one patient found his left hand unbuttoning a shirt as the right tried to button it. Another found that when shopping, one hand put back on the shelf items the other had put in the basket. One patient struggled to walk home as one half of his body tried to visit his ex-wife while the other wanted to walk home. These extraordinary but well documented cases show that cutting the corpus callosum gives two hemispheres with different experiences and opinions about what the body should do.

   If the left hemisphere only analyzes data from the left visual field, our experience of a single visual field must arise in some other way. It is now proposed that the hemispheres synchronize their electromagnetic fields into one consciousness by means of the eight million nerves linking them (Pockett, 2017). The answer to the binding problem is then that consciousness causes integration not the reverse, where consciousness is the ability to integrate information to yield adaptive action (Morsella, 2005). 

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The human brain doesn’t have an instruction manual but if it did, it might stress that having many ways to control the feedback loop is a feature not a bug. Brains have to analyze sense input, body state and muscle output anyway, so three specialists survive better than one (Figure 6.33). If the brain had only one control center, it would be the hindbrain that matured first not the cortex that came later. This division lets the movement center manage movement details, the emotional center manage feelings, and the intellectual center manage thoughts. But our brains must use the right specialist for the job to succeed.

In Figure 6.33, the forebrain that receives muscle input is next to the motor nerves for those muscles, like a single input-output gate. In fish, the cerebellum used this gate to run the brain-world feedback loop, with data from the still evolving forebrain and midbrain. In birds and mammals, limbic control can override the cerebellum, which still managed fine motor control. In later mammals like us, the neocortex became independent, but its control of emotions and instincts is often quite limited.

The result is a brain with not one control-center but three. Each center monitors body and sense input with its own neural connections, and does what it decides is best. Evolution has given us a brain with super-fast movement, powerful emotions, and complex thoughts, because different situations need all three. This isn’t easy because the centers can’t “talk” to each other as people do. They all speak different “languages” because millions of years of evolution separate them.

For example, people with a spider phobia can discuss their fear intellectually and accept that a little harmless spider isn’t a threat. They have all the data needed for a non-fear response, but putting that spider on the table still makes them jump up in fear! The emotional center ignores talk but an actual spider makes it press the red danger button. And if during the conversation an object fell from a shelf above, the moving center might catch it before the intellect can recognize it. Different brain centers are too busy constantly analyzing external events to talk internally.

Each center must learn independently. For example, falling on a hard surface is a common cause of injury in old people. It happens so fast that what the brain does in a fraction of second decides whether we end up injured or just get back up. The intellect is too slow to act in time and an emotional center panic isn’t much use, as a muscle spasm can injure bones or joints more than the fall itself. In most cases, its best to relax and let the movement center manage the fall, as parachutists do. This is easy to say but it takes a lot of practice to learn. 

The three-in-one answer that evolved from the early forebrain-midbrain-hindbrain division gives us fast responses, powerful emotions, and complex thoughts. The traditional idea of human nature as intellect, emotions and will derives from this early neural division of labor. The three-center approach to the brain can be illustrated by a story:

Once upon a time there were three brothers who flew a tiny plane. Elder brother handled the flight controls, middle brother monitored the cockpit knobs, and baby brother looked out the window to see what was out there. Eventually, by delivering goods in the city to earn money, they managed to buy a jet plane for intercity travel that had knobs to automate landing, takeoff, and flight among other things. This meant that middle brother was more often in charge but elder brother still monitored the controls to make fine adjustments and took over in emergencies. Middle brother had a thrust button for more power but he had to use it at the right time. As little brother grew older, he used what he called ‘symbols’ to record events on bits of paper but the others just used his spotting ability.

Intercity travel made more money, so one day they bought an intercontinental jet with state-of-the-art computer controls. Elder brother preferred his manual controls and middle brother liked his dials and knobs but younger brother preferred the computer screen to paper. It took longer but he could control the plane with it and even send messages to other planes. His older brothers were too busy to talk in flight, so he would demo a new flight technique by computer control and they picked it up if useful. 

Their plane was constantly being upgraded. At first, elder brother used a simple dot radar to avoid colliding with other planes. When a radar with pictures instead of dots was installed, he found it too complex for manual flying but middle brother used it to identify friend from foe. When computer radar arrived, the first two found it complex and slow but little brother used it to analyze trends and causes. Over time, the brother’s plane dominated the airways because three pilots are better than one if each does what they are good at.

Our brain has three centers just as cars have different gears for different situations, but why do we experience one driver? All that neuroscience knows about the brain, from blindsight to the split-brain, suggests many “I”s not one. Our sense of “I” implies that nerve input goes to a center that then directs all motor nerves, but neuroscience assures us that this isn’t so:

“In contrast to this first-person experience of a unified self, modern neuroscience reveals that each brain has hundreds of parts, each of which has evolved to do specific jobs – some recognize faces, others tell muscles to execute actions, some formulate goals and plans, and yet others store memories for later integration with sensory input and subsequent action.” (Nunez, 2016) p55.

This issue, of how different brain areas work together, is called the binding problem.

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The human cortex handles higher abilities like language that set us apart from other species. While the cerebellum packs 80% of the brain’s neurons into 10% of its mass, the cortex needs 80% of the brain’s mass to support 20% of its neurons, because they are larger and have more support cells. It is a folded sheet, 2-5mm thick, with six layers, while the midbrain hippocampus only has three layers. It was the last part of the brain to evolve and is the last to mature in children. If other centers ran the feedback loop before it, how can it take control? The answer, it seems, is with difficulty.

Piaget concluded that the human intellect develops in four distinct stages:

1.               Sensorimotor (0 to 2): Babies and toddlers think in sensorimotor terms.

2.               Preoperational (2 to 7): Children begin to think symbolically and learn language.

3.               Concrete operations (7 to 11): Children think logically about concrete events.

4.               Formal operations (12+): Abstract thought emerges.

The cortex can’t act independently until over 12 years old and it continues to mature into the mid-twenties, as the ability to think increases.

In the sensorimotor stage (0 to 2), the moving center controls activities like reaching so it also tries to speak. Hence, language begins as babbling, as babies form sounds to match the speech that they hear in the first year. Babble can sound just like speech, although no words are known yet. The moving center tries to talk as it learns to walk – by just doing it. Before an infant says its first word, at about one year, it knows all the phonemes needed for speech, including intonations. The midbrain isn’t mature enough to lay down memories until two or later, so before that we have childhood amnesia, a period we can’t remember because the midbrain couldn’t lay down long-term memories. The same occurs in animals for the same reason (Feigley & Spear, 1970).

In the preoperational stage (2 to 7), the emotional center increases control of behavior, to make us emotional beings who think everyone sees the world as we do. A five-year-old asked what is in a chocolate box will say “chocolates” until shown it contains pencils. If then asked what another child will think is in the box, they say pencils not chocolates. They can’t imagine how others see the world yet and so have no empathy.

While the emotional center is in charge, the developing intellect produces egocentric speech, where the child keeps up a running commentary on what they do, even when alone. At first they comment after an action, so a four-year-old child may stroke a teddy bear then say “Good boy”, but at five the same child says “Good boy” as they stroke it, and at six they say it first then stroke it. It is as if a part of the brain is first observing what is happening and making after-the-fact comments, then making current comments, and finally predicting what will happen. Egocentric speech is the child’s growing intellect expressing itself out-loud to the rest:

“One area of the brain and mind may initiate a behavior, which is witnessed or experienced by other (disconnected) brain areas, only as it occurs outside the brain and body.” (Joseph, 2017a) p442.

In the concrete operations stage (7 to 11), the intellect learns to apply thought to concrete things. A child under 7 may think that spacing out checkers in a line increases their number, but by 9 they know that number is still conserved (Figure 6.30). Yet they still struggle to reason abstractly.

Not until the formal operations stage at about twelve does the intellect manage to think abstract ideas. Prior to this, we learn in a formatory way, by memory associations not logic. Children under 12 can rote learn dates for a history exam but struggle with abstract mathematics. As the intellect matures, it can change from backward thinking to forward thinking, from finding reasons to justify conclusions already held to forming new conclusions by analyzing agreed facts.

Backward thinking is people cherry-picking the Internet for facts to confirm preconceptions while forward thinking is the scientific method. Formal operations let children think scientifically, but it still takes another decade to do it routinely. Western science began when Socrates started to think forwards but two thousand years later, we still struggle to follow his example because thought hurts! For example:

Bob rides his bicycle to pick up his motorbike from the repair shop at 10 mph. How fast must he ride his motorbike back to average 20 mph for the whole trip?

Emotional thinking suggests 30mph but using the intellect shows that is impossible.

Does the cortex control the feedback loop as it matures? It has the nerve links to do so as the sensorimotor cortex (Figure 6.31) maps to body muscles based on importance (Figure 6.32)

A voluntary act, like raising the hand, occurs when the frontal lobe directs the supplementary motor area (SMA) to prepare the movement and tell the motor cortex to do it. The SMA activates even at the thought of moving, long before muscles move (Nachev et al., 2008), suggesting to some that:

“… the “will” to move begins in the SMA and medial frontal lobes and exerts executive control over the secondary, primary and subcortical motor areas which then perform these “willed” actions.” (Joseph, 2017b) p151

The author concludes that: “The frontal lobes serve as the ‘Senior Executive’ of the brain …” (Joseph, 2017b) p138, but how can two frontal lobes have one will? The brutal fact of neural science is that multiple systems drive bodily actions:

 “Figuratively speaking, the skeletomotor output system is akin to a single steering wheel that is controlled by multiple drivers …” (Morsella et al., 2016) p6.

The frontal lobes can initiate muscle movement but so can other brain centers. The cortex has voluntary muscle control but its ability to coordinate a successful golf swing is close to zero. It also struggles with emotional urges, as when we plan to eat less by dieting, we can deny one cake but to always do so takes more than intellectual “will”. Like the triumvirate of Rome, at least two of the three control centers must agree for a long-term plan to work. The ideal for our brain isn’t some sort of neural dictatorship but for its centers to share control in a balanced way.

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Muscle memory is a sensorimotor schema stored in the cerebellum that is activated by sensory triggers, so to know if you know how to ride a bike, you must get on one again. In contrast, midbrain memories let us re-experience past events, like whether we left the stove on. Episodic memory provides a past event timeline that can be analyzed to link cause and effect. It allows organisms to survive by emotional learning, of good or bad consequences.

The emotional center of the brain is the limbic system (Figure 6.28), which includes the:

·      Thalamus. A relay station to pass on sight, sound, and touch input.

·      Hypothalamus. Connects to the peripheral nervous system that controls body states.

·      Hippocampus. Acts to lay down memories.

·      Amygdala. Analyzes sense and body state input to generate emotions.

·      Cingulate gyrus. Links to the cerebral cortex.

Hippocampus damage can result in amnesia, the inability to lay down new memories. Cingulate gyrus damage is involved in depression and schizophrenia. Amygdala damage reduces the ability to process emotions in facial expressions and is a neural marker of autism. The hypothalamus links to the peripheral nervous system, a second brain of a 100 million nerves outside the skull that handles body hormones and digestion. According to three-center theory, the limbic system is a control center, with its own sensory, visceral and memory input, whose role is to generate emotions that activate body states.

The amygdala can react to facial data in under a tenth of a second, before cortical awareness, by a subcortical visual path (Adolphs, 2008). Sense data from the thalamus goes direct to the amygdala by a short route and takes a long route via the cortex (Figure 6.29), so the amygdala can initiate emotional responses like sweaty hands, dry mouth and tense muscles before the visual cortex even recognizes what is seen. The thalamus still passes data to the cortex, to allow a better but slower decision. Like the movement center, the emotional center uses links that existed when it evolved, so it can act by visceral and sense links acquired before the cortex began to think.

This emotional center even has its own ability to process space. While the hindbrain maps the vector data needed to track movement in space, the midbrain maps the locations needed to return to a point in space (O’Keefe & Nadel, 1978). It can compare its own dedicated sensory and visceral input to past memories to generate the appropriate emotion, as it did for millennia in birds and mammals.

An emotion is a neural representation of reality in body terms generated by the limbic system. For example, fear is the experience of increased heart rate, breathing, adrenaline, blood pressure and blood sugar that accompanies a fight or flight response. Over millions of years, this response to threat was passed on because a body prepared for threat survives it better.

The amygdala interprets facial expressions like anger by emotional learning (Hooker et al., 2006) but also responds to any sensed danger, so an odd smell or an insect crawling on the skin can create a fear response that prepares the body for action. Just as the hindbrain represents reality by schema, and the cortex by thoughts, so the midbrain represents reality by emotions.

Fear isn’t the only emotion, as limbic states support survival in general. Emotions like lust, anger and greed are now primitive urges to be avoided but even today, anger is useful to fight an enemy, lust helps continue the species and greed ensures that surplus food isn’t wasted. Dependence is inappropriate for an adult but it keeps a child by its parents for protection and even laziness has value, as an injured animal should rest and recover. All emotions have survival value in the right situations, as they relate to biological needs.

Emotions, a body-state tool kit that can be tailored to situations based on experience, were a big evolutionary advance at the time. All the emotions we now call negative were useful in evolution and still are, if used correctly. A toolkit is only negative if the wrong tool is used, as if a carpenter uses a hammer to shorten a plank not a saw, it isn’t the toolkit’s fault. 

Movement center memory knits sensations into a motor schema but emotional memory lets us base present acts on past experience to allow projection, assessing another’s intent based on what I would do. Many birds cache their food to hide it for use later, but when they see another bird watching them hide food, they return later to re-hide it (Clayton et al., 2007). This ability to understand another’s intent allows empathy, the ability to feel what another feels, a vital component of the emotion we call love.

Doing something is usually better than doing nothing but if a predator is nearby, it’s often better to stay still. For the emotional center to respond to threat by keeping still, it must override the tendency to move, so if a mammal sees a predator, the instinct to run away is stopped by the emotion of fear. When fear freezes an animal in its tracks, the amygdala activates its connections to the brainstem and cerebellum (Ressler, 2010). Mammals have this paralysis by fright response but fish don’t. An emotional center that can suppress hindbrain movement sets the stage for the evolution of cortical control, in the next section.

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The human brain grows from a neural tube, whose forebrain, midbrain and hindbrain areas later form the cortex, limbic and cerebellum systems (Figure 6.24). This basic division reflects three basic brain functions:

       1. Input. What is out there?

       2. State. What is the body state?

       3. Output. What actions can be done?

Life involves all three, as animals must sense food or danger, know if the body is hungry or tired, and control actions like biting to survive. The neural tube then evolved to analyze input patterns, evaluate body state and control muscle schema, and this evolution occurred in parallel not in sequence.

An engineer might design a feedback system to analyze input, assess internal state and direct responses in that order, then integrate them (Figure 6.25), but evolution didn’t do that. Given three necessary functions, it developed them all at once in different ways because the brain has no control center.

Three-center theory is that the hindbrain, midbrain, and forebrain evolved as independent feedback control centers for:

1. Sensory control: Based on sensory patterns.

2. State control: Based on body state feelings.

3. Movement control: Based on muscle schema.

 How an animal responds depends on which control center drives the feedback loop at a given moment, as an animal with a chance to bite might do so under movement control, freeze in place from fear under state control, or decide that the threat isn’t really dangerous and ignore it under sensory control.

 The brain evolved motor processing first, perhaps because action is critical to survival. Single-celled life moved before it saw, and embryo motor nerves develop before sensory ones, so babies kick in the womb before their eyes even start working.

Fish brains have forebrain optical and olfactory areas to process sense data, a midbrain amygdala and pituitary to manage endocrine tasks, and a hindbrain to handle movement (Figure 6.26). All three functions exist, but the cerebellum of fish is far more evolved than its cortex (Montgomery et al., 2012), so it probably controlled the feedback loop using data from the primitive forebrain and midbrain.

In fish, the forebrain area that receives muscle data is next to the area that directs movement, as it is for us, perhaps because it is easier to use the same paths for both, and having sensory and motor areas close to each other improves sensorimotor timing. For us, the motor cortex directs movement but for fish, it is probable that the cerebellum controls the motor cortex, as it projects both excitatory and inhibitory nerves to it (Daskalakis et al., 2004).

In humans, the hindbrain bulges out from the base of brain as the cerebellum (Figure 6.27). It may be ancient but the cerebellum has more neurons than the rest of the brain put together! Its two cross-linked hemispheres are known to control complex movement and it was certainly the most advanced part of the brain when reptiles ruled the earth. If the hindbrain was the first brain control center to evolve, can it still control the body using primitive links to the early forebrain and midbrain?

 In infant swimming, babies instinctively hold their breath underwater thanks to a diving reflex and move their arms and legs in parallel to propel them through the water by an amphibian reflex that flexes same-side hip and knee kicks. These instinctive actions disappear later, as the child learns to swim as people do, by moving limbs alternately. That babies swim as reptiles do but lose the ability after four months suggests that the brain retraces its reptilian ancestry as it matures.

In parasomnia, sleepwalkers can get up, walk, eat, cook dinner or ride a motorbike while asleep and wake up later with no recall. With the cortex and midbrain dormant, the hindbrain moves the body by itself and there is no recall because the midbrain isn’t laying down memories. Sleepwalking behavior isn’t just reflexes, as cooking a meal is a purposeful act that requires constant situational adaptation. It follows that the hindbrain can control the body entirely, like a brain in itself, without the cortical intellect or episodic memory.

Hindbrain control also explains blindsight, where people with visual cortex damage report seeing nothing but can still catch a ball or insert an object into a tilted slot whose orientation they say they can’t see (Goodale & Milner, 2004). When cortical systems that identify objects fail, the hindbrain can use older subcortical paths to handle spatial location and direct motor acts by implicit perception (Hannula et al., 2005). Primitive circuitry that evolved when the cortex was still in its infancy is used to direct motor output.

When later systems fail, older ones take their place, so aphasic subjects who can’t speak due to cortical damage can still swear and sing. Amnesic patients given the same jigsaw every day say: “I have never seen this before” but still solve it faster each day. Research confirms that a monkey with no visual cortex can’t discern a circle from a triangle but can still move under visual guidance like a normal monkey (Humphrey, 1992). Brain systems that evolved millions of years ago still operate in our brain and can take over if the systems that evolved after them fail.

If the brain was built in a factory, then put to work, the cortex might run the brain but nature didn’t have that luxury, as some center had to run the feedback loop at every stage of evolution. In fish, the hindbrain, as the first brain center to evolve, is in control, because the cortex isn’t ready yet.

By some estimates, the cerebellum or “little brain” contains about 80% of the nerves of adult brains so despite its ancient origin, its role today isn’t just backup. People with cerebellar damage struggle with movement in a wide range of activities, like walking, reaching, speaking, gaze and balance. They have staggered walking, inability to maintain eye-gaze, slurred speech and other features associated with being drunk. What is lost is the ability to relate moment-to-moment muscle actions to sense input, because that is what the hindbrain does.    

The cerebellum once acted independently of the cortex that came later, and it still can. For a gymnast to back-flip on a balance beam takes super-fast processing that the cortex just can’t do. Even simple tasks like riding a bike are done badly by the cortex until the hindbrain takes over as we automate the task, when the cerebellum develops a schema for it.

   Hence, the cortex doesn’t control the cerebellum, it just triggers it to act. The cerebellum learns a schema, like riding a bike, by itself. When the senses trigger a schema, the cerebellum acts as needed without direction, just as a car’s automatic transmission monitors events and changes gear as needed. To ride a bike, we just push off and let our movement center take over to handle balance as only it can. It can act by itself because it was once the senior brain system and it retains that ability in us today. Other parts of the brain can interfere with it, but they can’t do what it does.

   To call the hindbrain primitive because it can’t speak is like calling a jet engine primitive because it has no video feed, when given what it does, that’s impossible. Just as modern jets have the latest engines, our brain has the latest movement control that evolution can provide. We don’t have an old reptile brain but a state-of-the-art movement center. It acts implicitly without fuss, so it’s easy to ignore, but the midbrain emotions of the next section are anything but unseen.

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A brain that analyzes input but doesn’t control output doesn’t help survival. It needs access to both input and output, so that when the eyes see danger, the muscles can run from it. The brain must control the basic feedback loop (Figure 6.20) to evolve, but what initiates this loop? Last century, psychology split into two camps on this issue:

a. Behaviorism argued that people are machines driven by outside events, so stimuli and responses entirely define the loop and what the brain does.

b. Constructivism argued that the brain controls the loop by actively constructing reality, as it can produce more sentences than we could ever learn from stimulus-response associations (Chomsky, 2006).

They differed on what initiated the feedback loop, as behaviorism was input-driven but constructivism was brain-driven (Figure 6.21). Since a circular process can be initiated at any point, today we accept that both can be true. The brain can be driven by outside events but it can also be driven by a brain intent. The second is needed because a brain must initiate the feedback loop to learn or evolve.

Yet updating a running system isn’t easy. When Microsoft upgraded the DOS operating system to Windows, it just replaced it, making it obsolete along with all the time users spent learning it. If nature worked this way, the mammal brain would make the reptile brain obsolete, losing hundreds of millions of years of evolution! Obviously, that is not efficient.

That nature doesn’t discard things led an American neuro-physiologist at the National Institute of Mental Health to argue that our brain is a reptile brain overlaid by a mammal brain overlaid by a human brain (MacLean, 1990) (Figure 6.22), where the reptile brain is hind brain structures like the cerebellum, the mammal brain is the mid-brain limbic system, and the human brain is the neocortex of higher thinking. This explained autism as an out-of-control reptile brain and anxiety as an out-of-control mammal brain. In this view, evolution evolved a reptile brain to handle movement, a mammal brain to handle emotions, and finally a neocortex for human thought. MacLean proposed that the human brain is three brains in one, each overlaying the last.

This model then became a popular way to explain autism and animals. Temple Grandin, an authority on animal psychology, who is autistic, wrote:

“To understand why animals seem so different from normal human beings, yet so familiar at the same time, you need to know that the human brain is really three different brains, each one built on top of the previous at three different times in evolutionary history. And here’s the really interesting part: each one of those brains has its own kind of intelligence, its own sense of time and space, its own memory, and its own subjectivity. It’s almost as if we have three different identities inside our heads, not just one.” (Johnson & Grandin, 2006).

The reception of the three-brain model among neuroscientists wasn’t as positive, because evolution doesn’t work by adding layers one after another, like geological structures. As one critic put it: Your brain isn’t an onion with a tiny reptile inside. Evolution didn’t build a reptile brain, then a mammal brain, then a human cortex because it isn’t a linear production line. Nor did it add new things without precedent, as bat wings are modified forelimbs that existed before. And even reptiles have a primitive cortex that lets them care for their young and solve problems (Patton, 2008).

Triune theory also didn’t account for birds. Over millions of years, reptiles evolved into dinosaurs whose descendants today are birds. Birdbrain is a term of ridicule but they are quite smart, as crows can bend a wire into a hook to get food their beak can’t reach (Weir et al., 2002) (Figure 6.23). Children can’t use tools like this until about eight and even then, only half succeed (Cutting et al., 2014). Birds like nutcrackers can hide 30,000 seeds over a 200 square mile area and recover them six months later. Birds are more like feathered apes than reptiles, and urban crows are especially smart:

 “On a university campus in Japan, crows and humans line up patiently, waiting for the traffic to halt. When the lights change, the birds hop in front of the cars and place walnuts, which they picked from the adjoining trees, on the road. After the lights turn green again, the birds fly away and vehicles drive over the nuts, cracking them open. The birds wait patiently with human pedestrians for a red light before retrieving their prize. If the cars miss the nuts, the birds sometimes hop back and put them somewhere else on the road.” (Earthfire Institute)

 Birds share many cognitive abilities with advanced mammals but their brains evolved differently (Jarvis & et al., 2005), as the bird cortex is smooth while the mammal cortex is folded. The current view is that as bird and mammal brains evolved from the basic reptile design, nature tried both options and converged to equivalent functions (Lefebvre et al., 2004). Triune theory doesn’t predict this evolution, but an alternative that does is now explored.

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A neuron is a cell whose body receives electrical input from dendrites and projects electric pulses down an axon to others, as a tree sends water from roots to leaves (Figure 6.10). Dendrites have to pass an input threshold to fire a neuron so input from neurons B and D in Figure 6.11 fire neuron A, but B and C don’t, as they don’t reach its threshold of four. Neurons selectively pass on electrical impulses.

In embryos, nerves grow out from the brain to form the retina, so light entering the eye touches the brain directly. If the retina was a photoelectric cell, it would pass on pixel data if say 1 is black and 0 is white. It works equally well if 0 is black and 1 is white, as long as the definition is absolute, but a designer would have to set that.

Brains had no designer so evolution took both options, as it always does. One type of retinal cell responds to light above the background level and another type responds to light below that level. In Figure 6.12, cell 1 responds to white and cell 2 to black. Instead of defining data absolutely, retinal cells respond relative to background light by interacting to excite or inhibit each other to amplify the borders that later allow object shapes.

Vision identifies an object by making one side figure and the other ground. In Figure 6.13, making black the figure just gives blobs but making it background lets you read “MAIL BOX”. The brain uses figure-ground context to unravel visual data ambiguity, as one must choose the right figure-ground context to see an object.

The human cortex is a nested hierarchy that processes data in six layers labelled I to VI, as lower units feed higher ones. The first step after the nerve is a hundred or so nerves about the thickness of a hair called a microcolumn:

“… current data on the microcolumn indicate that the neurons within the microcolumn receive common inputs, have common outputs, are interconnected, and may well constitute a fundamental computational unit of the cerebral cortex …” (Cruz, 2005)

About a hundred microcolumns then form a cortico-cortical column that sends axons to nerves nearby. They then form into a macrocolumn of about a million nerves, about 3mm wide, with cortical links. Macrocolumns then form about 32 Brodmann areas (Figure 6.14) of maybe a hundred million nerves for functions like language.

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The cortical processing layers are (Nunez, 2016) p91:

1. Microcolumns. A hundred or so nerves about .03mm wide.

2. Cortico-cortical columns. A thousand or so nerves about .3mm wide.

3. Macrocolumns. A million or so nerves about 3mm wide.

4. Brain areas. A hundred million or so nerves of various sizes

Brain areas then form four lobes about 50mm wide separated by deep fissures (Figure 6.15). The occipital lobe handles visual data, the parietal lobe handles body image and space relations, the temporal lobe handles sound and memory and the frontal lobe handles plans and intentions. It can stop other parts doing socially improper acts, so a person with frontal lobe damage may know how to behave but can’t stop inappropriate acts like touching. Four lobes together form a hemisphere that with the other is the cortical brain.

The visual hierarchy starts when the eye detects photons. This data is then subject to layer upon layer of processing to detect relevant features. For example, some nerves in layer IV fire for different line angles (Figure 6.16) and others for other features.

Scientists estimate that each eye inputs about 8.75 Megabits a second and the brain in total receives over 20 Mbps. As James said in 1892, our first impression was probably information overload:

“The baby, assailed by eyes, ears, nose, skin, and entrails at once, feels it all as one great blooming, buzzing confusion”

Computers handle information overload by compression that reduces the data in a video but keeps the key features. The brain does the same by reducing sense data to features that represent borders, shapes or objects. When a baby’s brain transforms data from millions of optic nerves to see an object is a cup, it handles the world better. The brain helps us survive by reducing sense data to key features.   

   Computer processing is mostly linear but brain hierarchies have bottom-up, lateral and top-down links. Sense data flows up and down the processing hierarchy as a two-way flow. Top-down paths predict, interrogate and check lower processing as higher processing “experts” check for consistency or errors (Dehaene, 2014) p139. Bottom-up paths analyze data as computers do, but lateral paths establish context and top-down links can rerun lower processing.

Is Figure 6.17 an old or young lady? If you see a young lady, can you see an old one or the reverse? To do this you must rerun your visual processing. The visual system makes a best guess, but you can ask for a redo because nerves go down as well as up. Lower processing is “out of sight and out of mind” but it can be redone by top-down control. All perception is a hypothesis of an ambiguous world.

   Subconscious processing might be assumed to be primitive but the spinning ballerina illusion (Figure 6.18) suggests otherwise. Click on the link to see a ballerina spinning but the rotation is ambiguous, so you might see her spin clockwise or anti-clockwise.

 Try to see her spin the other way. If you can’t, pause the video and if you see an extended leg at the front, imagine it at the back, or vice-versa. Restart the video and if she spins the other way, you just reprogrammed some complex unconscious visual processing

The optic nerve has about a million axons but the auditory nerve only has about 50,000, so its processing base is narrower than for vision. In Figure 6.19, the same processing resources applied to a narrow base allows deeper processing. There is a trade-off between processing breadth and depth, so if hemispheres of equal capacity specialize, the narrower base of sound can be processed deeper than the broad base of vision. The hemisphere that specializes in sound can develop language because a narrow base allows the deeper processing that language requires. One hemisphere specializes in the deep processing of language while the other favors the broad processing of spatial analysis.

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We like to control things, so our first networks centralized control, until decentralized networks like Ethernet were found to be ten times faster. They also degrade gradually under load, instead of crashing suddenly, as centralized networks do. When the Internet was first proposed, it was expected to fall into chaos without central control, but it was decentralized control that enabled it to survive.

Early brain theories also expected a central executive. In Schacter’s model (Figure 6.5), an executive decides what to do after a conscious awareness unit accesses sensory knowledge modules, memory and higher reasoning (Schacter, 1989). The executive was assumed to be in the cortex, a folded layer wrapped around the midbrain and hindbrain (Figure 6.6) that handles voluntary acts, thought, planning, and language.

The cortex is the most advanced part of the brain, but its two hemispheres share the work between them. The left one directs the right side of the body and the right one directs the left. One specializes in language and the other in spatial analysis, but how can two hemispheres act as one executive?

   The answer, revealed by a treatment of epilepsy, is that they don’t. In epilepsy, an electrical disturbance in one hemisphere spreads to incapacitate the cortex across an 800 million nerve bridge called the corpus callosum. Cutting it in animals didn’t seem to harm them, so surgeons tried the same in epileptics, to stop the epilepsy spreading. The treatment worked but while serious side effects were expected, split-brain patients spoke and acted normally! So little changed that some thought the corpus callosum was just a structural support. Further studies revealed an unexpected result.

Each hemisphere moves the opposite hand but for vision, the left hemisphere inputs the right side of both eyes and the right one gets input from the left side of both eyes (Figure 6.7). In split-brain studies, each eye saw half a split screen, so with the corpus callosum cut, the left hemisphere saw only the claw and the right hemisphere saw only the snow (Figure 6.8).

When subjects were asked to point to a picture that matched what they saw, the right hand picked a chicken but the left hand picked a shovel! The left hemisphere saw a claw, so it used the right hand to point to a chicken, while the right hemisphere saw snow, so it used the left hand to point to a shovel, and neither was aware of the other’s choice. Both hemispheres could receive and send data as if each was a brain in itself, so there was no central executive.

When asked why his left hand chose a shovel, a subject said “you need a shovel to clean up after chickens”. The verbal left hemisphere had no idea why the shovel was chosen, as it didn’t see the snow, but instead of saying I don’t know, it made up a story. It tried to interpret events as best it could:

“These findings all suggest that the interpretive mechanism of the left hemisphere is always hard at work, seeking the meaning of events. It is constantly looking for order and reason, even when there is none – which leads it continually to make mistakes. It tends to overgeneralize, frequently constructing a potential past as opposed to a true one.” (Gazzaniga, 2002) p30

Interpreter theory is that the cortex, with its language and thought, is more servant than master in the brain. If the brain is a federation of agents (Minsky, 1986), the left cortex is head of human relations not the CEO, as some suggest (Kaku, 2014). It is like a diplomat, whose job is to explain the decisions that others in power make.

Perhaps human intellect expanded when we formed tribes because those who better explain themselves survive to reproduce, as the animal most likely to harm a human is another human. Inventing acceptable reasons after the fact may be the evolutionary basis of our vaunted intellect. Logical thought, building one idea upon another in a rational way to reach an unforeseen conclusion, probably isn’t what our intellect originally evolved to do.

   The left hemisphere usually specializes in language but the right hemisphere isn’t illiterate. One study of a split-brain boy (Wolman, 2012) asked the left hemisphere “Who is your favorite?” but flashed “Who is your favorite girlfriend?” to the right hemisphere. The left hemisphere made no verbal reply, as didn’t see the word girlfriend, but a nervous giggle revealed that the right hemisphere understood. The right hemisphere then used the left hand to select scrabble tiles to spell out L-I-Z, a cute girl in his class. The right hemisphere had no vocal control but it could still read and spell. Both hemispheres are conscious in any way you care to define it:

“Everything we have seen indicates that that the surgery has left these people with two separate minds, that is, two separate spheres of consciousness. What is experienced in the right hemisphere seems to lie entirely outside the realm of awareness of the left hemisphere. This mental division has been demonstrated in regard to perception, volition, learning and memory.” (Sperry, 1966)p299.

Evolution favors decentralization because then if part of the brain is lost, the rest can carry on. In a famous case, an iron rod pierced the middle and left cortical lobes (Figure 6.9) of a railway worker called Phineas Gage, who shortly after walked off, conscious and speaking. He showed disturbed behavior but lived for 13 more years and died of unknown causes. Now imagine banging a nail through a mother-board! The brain duplicates the cortex for the same reason that planes duplicate critical control units – to increase reliability. This answers Von Neumann’s question:

“How could a mechanism composed of some ten billion unreliable components function reliably while computers with ten thousand components regularly fail?”

As information goes into the brain, it makes sense to peel away the layers of processing to find the “I” from which all proceeds, but doing so reveals no central executive. If the body is a ship run by the brain, it has no “Captain”, even at the highest level:

“Studies of the structural and functional organization of the brain have shown that this organ is, to a large extent, decentralized, and processes information in parallel in countless sensory and motor subsystems. In short, there is no single homunculus in our brains that controls and manages all these distributed processes.” (Singer, 2007)

No-one searches the Internet to find its “center”, so why expect a brain network to have a center? Neither neuroscience nor information science support the idea that we have one “I”:

“In contrast to this first-person experience of a unified self, modern neuroscience reveals that each brain has hundreds of parts, each of which has evolved to do specific jobs – some recognize faces, others tell muscles to execute actions, some formulate goals and plans, and yet others store memories for later integration with sensory input and subsequent action.” (Nunez, 2016) p55.

Some argue that this conflict between the fact that we experience one observer and the fact that the brain has no central control area means one fact is wrong (Dennett, 1991), but science doesn’t work by cherry-picking facts. It works by accepting facts, putting questions and finding answers, so part 6.3 will later ask how can a decentralized brain can create one observer?

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A transistor can’t grow a computer but a cell can grow a brain, so building a processor isn’t the same as evolving one. Evolution found a path from a cell to a brain and embryos grow brains by following that path.

Even so, brains and computers have similarities. Both use electricity to power on/off units that process data, so neuron logic gates process data just as computer transistors do (McCulloch & Pitts, 1943). Sensorimotor channels also mirror computer input-output channels so brain-computer theories propose that nerves process the senses to give muscle output as computers process input and output (Churchland & Sejnowski, 1992). Yet the comparison ends there because growing and building processing are different challenges (Whitworth, 2008).

We build a computer at leisure then switch it on, but an evolving brain must always be on because life never stops. Our computers use the Von Neumann design, of a central processing unit (CPU) that processes input to give output (Figure 6.3), because it always knows what to do next, but if the CPU fails, everything does. Biological parts fail regularly so a brain that fails when a part does is too fragile to survive in nature. Evolution needed a reliable processor, so brains don’t have a central processing unit.

To understand the brain, one must understand evolution. Darwin’s natural selection is that traits change gradually over time to select what survives (Figure 6.4). For a brain, this requires variability, change, and survival:

1.  Variability. Nerve autonomy, the ability to act by internal direction, lets brains vary. If nerves didn’t act by their own choice, the brain couldn’t evolve, so neural freedom allows evolution while absolute central control denies it, so brains had to decentralize control.

2.  Change. Evolution occurs in a step-wise manner, so brains had to change in the same way. A brain can’t string processors together in a series of steps that end up giving value, as programmers do, because each step has to give value. As a result, our brain is layer upon layer, where each layer evolved while the previous one was still operating. Each step has to add value and lead to the next, so it is a nested hierarchy. 

3.   Survival. To survive, a brain must add value, say by moving a creature towards light, so a sense like light detection is useless if it isn’t acted upon. To survive, a brain must control the feedback loop between sensory input and muscle output.

Decentralized control, nested hierarchies, and feedback control, as evolutionary principles, explain the brain better than any computer analogy.

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A human brain has more nerves than there are people in the world or devices on the Internet, and it has more connections than the Internet, as one nerve can link to 10,000 others. It also took five hundred million years to evolve, because it had to operate at every step. A bee brain is just a neuron sliver but it lets them fly, form colonies, and even communicate with each other, because brains like ours could only evolve from brains like theirs if they survived. Imagine building a jumbo jet where the first part had to fly and likewise for every part added after that, or writing a program where the first line of code had to work or you didn’t get to write the second. We build information processors but nature had to grow one.

QR6.2.1 Growing Processing

QR6.2.2 Decentralized Control

QR6.2.3 Nested Hierarchies

QR6.2.4 Feedback Loops

QR6.2.5 Three-Center Theory

QR6.2.6 The Emotional Center

QR6.2.7 The Intellectual Center

QR6.2.8 Sharing Control

QR6.2.9 The Binding Problem

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