The book is an insightful journey into contemporary understanding of human brain and how scientists are trying to replicate it.
Major takeaways from the book are listed below.
Thought experiments on the world
- Charles Lyell was the first person to propose that steady movement of water carves out gorges and canyons.
- This became inspiration for Charles Darwin‘s theory of evolution.
- Both of them engaged in thought experiments looking for how things around them attained their states and discovered underlying phenomena.
- Similarly, Einstein after reading about the experiments which concluded that relative speed of light is always constant engaged in thought experiments which eventually lead to “Theory of relativity”.
- Human brain is remarkably amazing in its ability to identify such patterns and discover underlying phenomena just by thinking.
Thought experiments on thinking
- Experiment 1: Its easy to recite alphabets going from A to Z, difficult to do the reverse (same experiment can be done for things like rhymes and poems) => Our memories are stored in a sequential order. They can be accessed only in that sequential order.
- Experiment 2: Try visualizing a person/situation which was encountered only once or twice, it is very difficult to visualize the details => Our memories are stored as sequence of patterns, there are no images, videos or sound recordings. Memories which are not accessed dim over time.
- We can recognize even partial patterns with alterations, our recognition ability detects patterns which survive real world variations.
- Our conscious experience of our perceptions is changed by our interpretations, we continuously predict the future and hypothesize what we will experience and this influences the actual perception.
- Routine procedures are stored as organized hierarchies in human brain, same ability is used for recognizing objects and situations.
A model of the neocortex
- Neocortex is responsible for hierarchical patterns of information and hierarchical thinking (some scientists call it “new brain” as oppose to reptilian “old brain” which is more tuned towards short term things like getting food, avoid becoming someone’s food and sex).
- Humans have really large forehead (and large neocortex) compared to other mammals. It has roughly 300 million pattern recognizers.
- A human master in a particular field knows about 100, 000 chunks of knowledge.
- Pattern recognition theory of mind – Neocortex has multiple layers of neurons, based on sensory inputs, some of the first layer neurons are triggered, those who trigger beyond a certain threshold, fire the second layer of neurons (second layer matches higher level patterns then first layer), the higher layer can send a back signal and reduce or increase the triggering threshold of the previous layers (this is the prediction and hypothesis part).
- Memory is effectively a list of patterns (they will trigger with appropriate input leading to recall of that memory). Since we capture patterns, our memory is only an approximation of events happened in the past.
- Learning – its difficult to learn too many conceptual levels simultaneously (It is difficult to train multiple layers simultaneously), we learn a level and as it stabilizes, we move to the next one.
- Misunderstanding – A person tries to convey patterns in his neocortex to another person’s neocortex using “language” which itself is a set of patterns in neocortex, these differences in patterns cause misunderstanding.
- Directed thinking – where we consciously try to direct our thoughts towards understanding or solving a certain problem
- Undirected thinking – where we experience sudden recollection of memories (triggers of which appears to non logical).
- Confabulation – We subconsciously make up stories to justify our actions which cannot be explained logically (this is more pronounced in split brain patients where left and right hemisphere are not connected – leading to one part of brain reacting and other one confabulating to justify the action).
- Culture, society and profession predicts certain norms, this trains our neocortex to think in certain ways, this ensures social order but at the same time makes it difficult to think differently (which Darwin or Einstein did). In dreams, these norms are usually a bit relaxed.
The biological neocortex
- Human brain is unusually large, its a cause of higher maternal mortality rate among humans (compared to mammals) and requires a pivoting gait which makes women biomechanically less efficient walker than men.
- Neocortex is repetitive structure consisting of “assembly of neurons” where each assembly is ~100 neurons and connections inside each assembly are similar. The connections between assemblies are dynamic, new ones are formed as needed and old unneeded ones are pruned away.
- Neocortex is highly “plastic” – meaning if a part which deals with say, vision is damaged, slowly another part develops the lost set of patterns.
- A genome has about 25 million bytes (after lossless compression) while total connections in neocortex are ~ 10^15 => most connections are not determined genetically but built over time.
- Over the time, field of AI (Artificial Intelligence) has developed the same set of techniques (which are believe to exist in neocortex) to process real world information like human speech and written language.
The old brain
- Optic nerves have 12 output channels – one recognizes edges, another recognize large areas of uniform color, another focuses on background => effectively we only see patterns rather than exact details.
- Human cochlea (which catches sound vibrations) extracts about 3000 bands of information.
- Thalamus process information coming from various parts of the body (including eyes and ears) before handing them over to neocortex.
- Neocortex on its own cannot do directed thinking, it requires inputs coming from Thalamus.
- Hippocampus is the area where short term pattern forming happens, these patterns are transferred to neocortex for long term. Alzheimer’s disease attacks hippocampus first.
- Cerebellum controls quick motions like catching a ball.
- Old (premammalian brain) is addicted to pleasures (food and sex), neocortex in mammals allows us to control the primitive desires. Dopamine and Serotonin play a role in feeling of pleasure.
- Amygdala controls “fear” (flight or fight decisions) – on detecting danger, it causes sudden rise of blood pressure, heart rate and respiration rate.
- Feeling happens in both old and new brain while thinking happens only in new brain (“neocortex”).
- Emotional thoughts takes place in spindle neurons – humans have a lot more of them than other animals, newborns don’t have them but they are developed over the age of 4 months to 3 years (this is when child learns emotions and morality).
- Ability of neocortex to master signals of fear from Amygdala plays a role in confidence, organizational skills and ability to influence others.
- Creativity – A key aspect of creativity is finding metaphors which neocortex is good at. Learning new patterns from different fields, help in learning more metaphors, making brain more creative.
- Love – Phenylethylamine (PEA) causes the feeling of “love” (high energy level, focused attention and craving to be with someone), oxytocin encourages long term bonding (monogamous relations), prairie vole are monogamous because of oxytocin receptors while montane vole engage in short term relations because of lack of them.
- Love in humans exist primarily to satisfy need of neocortex (primitive lust was sufficient for reproduction) – a loved one becomes a major part of ones neocortex and after spending decades together, a virtual other exists which can anticipate every move of the loved one. When we lose the person, we are still left with patterns in neocortex which trigger, except triggers change from delight to mourning.
The biologically inspired digital neocortex
- Neocortex replaces the process of (slow) evolution with (fast) learning and that’s one reason of advancement of human race. Since even a single human finds something new, everyone can learn that (rather than that appearing in genetic code).
- A digital neocortex is will provide a factor of thousand to a million speed up over biological cortex.
- Several attempts to do brain simulations (functional level as well as molecular level) are being done, author expects by 2020, there will be sufficient computational power to simulate human brain.
- Techniques being used are neural networks, vector quantization (for sparse coding), HHMM (hierarchical hidden markov models) and evolutionary (genetic) algorithms.
- Watson, Google Translate and Wolfram are some major work done in direction of processing and generating real world information.
The mind as computer
- Brain is slow but massively parallel (300 million pattern recognizers can be fired together) while opposite is true for computers.
Thought experiments on the mind
- Consciousness is a heated topic of debate among philosophers. There are no agreements on “are plants conscious?” or “are babies conscious?”. The general agreement is that “ability to act according to one’s free will” (implying nondeterminism) is consciousness.
- Panprotopsychism says that everything is conscious, “humans are more conscious than light bulb”.
- Author predicts that by 2029, we can expect to see “digital consciousness”.
- Western perspective – consciousness is emergent property of complex system.
- Eastern perspective – consciousness is fundamental property, physical world only comes into existence through the thoughts of conscious beings.
- Existence of “free will” is hotly debated topic – existence of free will requires non-determinism in actions and experts don’t agree on whether humans actually have free will (compared to say Watson) or are the actions predetermined. Some philosophers believe that future is completely deterministic (given present) but complex enough to be unpredictable.
- There are also disagreements on what constitutes identity – author holds the position that a snapshot of neocortex (or brain, in general) is a person’s identity and hence, identity, in principle, is not unique and can be replicated.
The law of accelerating returns applied to the brain
- Most technologies follow S-curve (slow start, rapid growth and then matures) but in the end of its life cycle, its replaced by something else (eg. Transistors replaced vacuum tubes).
- Most technologies (like processing power, storage capacity, brain imaging resolution) etc. are growing at exponential pace and leading to a “Law of accelerating returns”, hence, a digital brain will arrive faster than most people expect.
- This chapter basically talks about objections raised to previous work of author – not much relevant to rest of the book.