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Neurohacking - Tutorials
Written by NHA   
Saturday, 17 September 2011 17:30
Article Index
Neurohacking Tutorial 6 - Association, Perception and Learning
The Learning Cycle & Perception
What Happens if Things Go Wrong
COMP & Natural Learning
NHA Guide to Methods & Technology
The Most Important Bits to Remember
Hacks & Exercices
Notes, References & Answers
All Pages





The Learning Cycle – Working with Biology to Make Learning Easy


First, Grab the Basics

First of all, learning depends on our initial response to the input, and this depends on networks 1, 2 and 3. This kind of thinking is largely unconscious, it only gives us the basics but it is very, very fast. It has to be fast because it evolved for human survival; people needed to recognise and avoid predators much faster than they could do using frontal cognitive processes associated with deliberate decision-making.

This kind of thinking takes place literally in the blink of an eye. Your mind takes less than a second to jump to a series of conclusions whenever you have an experience with anything new in it -meet someone for the first time, start to learn something, see a movie you haven’t seen, or run away from a sabre-toothed tiger.


Suppose, for example, in a foreign country on holiday, an unknown insect lands on you. It doesn’t immediately ‘enter’ your consciousness as a fully fleshed out entity. The brain processes the encounter in modules — one for color, one for size and yet another for its location and even for resonance [association] with previous encounters with such insects. We synchronise these sensory bits into a seamless single impression of this insect as either probably or probably not dangerous, which gives it a ‘weighting’ in memory [dangerous things are important to remember]. If it registers as a new kind of moth, we probably won’t squash it. If it registers as a new kind of spider, we might, just to be on the safe side if we know that some foreign spiders are poisonous.

We don’t have to ‘direct’ this kind of thinking; we just have to let it happen. Trying to figure out the details of something too soon gets in the way of our initial assessment.(and bear in mind –this is where we become vulnerable to misinterpretation). Whenever you approach anything new, you should allow your mind to get a grasp of the basics. When it gets bored with its initial assessment and has grabbed enough bits of the basics to be going on with, your mind will move on:


Second, Fill in the Details

Applying the knowledge that “some foreign spiders are poisonous” requires a different kind of thinking; the second kind required for learning. Concentration on the object of enquiry due to its weighting of ‘importance’ causes signals from ‘teams’ or whole populations of neurons that co-operate efficiently to gain sufficient strength to make it to the surface of your active consciousness. (Everything else remains in the unconscious depths of associative perception).

Scientists now know such neuronal net layers or bandings are crucial steps in the process of perception through the different networks that brings order to the inherently chaotic input we receive. The result of this is shown in the curious effect called binocular or perceptual rivalry.




Perceptual Rivalry

Ambiguous figures demonstrate that a single image can result in a percept being compared against more than one concept; for example the famous 'duck or rabbit' illusion or the Rubin Vase which can be interpreted either as a vase or as two faces.



The sudden input of different images hacks the brain’s innate association/synchronisation mechanism. On its part, the brain opts out of this sensory dilemma by favouring the input from one eye and suppressing that from the other for a second or so. So you only manage to see a single image at first even though you are shown two! (You do ‘see’ the other, temporarily ‘censored’ image but after a slight lapse that is usually noticeable.)

What is more intriguing –and useful- is that there is a similar ‘filtering’ or modulation of neuronal banding caused by our natural intent controlling attention. (This is especially evident in research done with acoustic stimuli: that is how in a noisy party you manage to hang on to your partner’s words despite the distracting din of background noise.) 

Concentration and paying attention change our neurochemistry and the attention of our senses in a way that makes it easier to learn, and we slip into the second kind of thinking –conscious, creative and intellectual- using more of the frontal lobe networks as well as those already engaged. This kind of thinking seeks out and fills in the details about the object of our enquiry and enables us to begin to interact with or understand it. We start to search for ‘missing bits’ to make our picture more complete. (This is where we become particularly vulnerable to misinformation).


Third, Copycat Mode.

Third, we need to use our ability to mimic and copy things (another well known animal behavior). This needs the third kind of thinking, imagination and creativity, that utilises the mirror neuron system. This kind of thinking goes on partly consciously and partly unconsciously. Consciously one is paying a particular kind of attention to the object of enquiry –the kind of attention that includes imagining oneself interacting as a participator rather than just an observer. It is, for example, the difference between watching someone performing a task and watching it while imagining that we are doing it ourselves. The latter kind of watching is this third kind of thinking when we are awake [and it’s where we become vulnerable to following bad examples]. When we are asleep, this kind of thinking becomes the jumbled content of our dreams, as we unconsciously associate new ideas and look for patterns. This is an important part of making memories long-term.


Fourth, Practice & Variation

Finally, we need to play with information in a different way –in context as a strategy. This is the fourth kind of thinking, and it uses all the brain’s networks [or it should]. It involves putting ideas into action and skills into context. It is the moment when we have just learned how to ride a bicycle and now we want to learn things like how to do hand signals without losing balance, and later how to do cool tricks. It’s the moment when we can play most of the notes in the song but not quite fast enough or with exactly the right rhythm. Self assessment and direct biofeedback between brain and musculature fine tune the performance as imagination compares the attempts, merges and repeats the more successful algorithms. The behavioral program evolves; it emerges from trial and error self-evolving subroutines, and all we have to do is play.

Variation uses imagination too –we think of new and different ways to play with our newfound skills and knowledge. Practice and variation hone our skills and we improve still further with time and experience until our responses become automatic.


How Perception Happens

Input data is binary, but imagination (essential for perception) likes working with graphics. It has to imagine accurately and assemble a constant picture of 'what's going on out there' for us every second of our waking time, after all. Hard wired concepts are stored in graphic format, and if new input is to be compared against the known, it must end up in a form that renders it comparable.

The very nature of cells makes them a digital to analog converter (DAC). They turn binary input into a continually varying physical signal (physical pressure and/or cell voltage). This can be graphed, and is mapped by the mind onto a 2D and then 3D 'inner model' as sets of coordinates that associate with one or more of the locations of the main hard wired concepts in eidetic memory. Information from all senses plus memory data is usually sufficient for an instant classification that happens so fast it can get us right up a tree before we even know what's chasing us consciously.

If associations in the inner model are wrong (incongruous), the output will be less than optimal and our perception will be faulty. The eidetic cores are hard wired to be aligned with the scientific laws of the real world, and the experientially-programmed rest of the model must match up, or incongruity will result and wiring will be incompatible and things will go wrong and we will get confused.


The initial stages of perceptual input sensory processing are well documented and can be confirmed with EEG and fMRI studies and cellular biology. [1]

Our input (the proximal stimulus) and it consists of simple patterns of on/off signals transmitted for processing. All proximal stimuli are in sensorimotor format; mechanical signals (mechanical micromovements of proteins), processed as individual events.

Multiple nanosensors on individual cells also transform detected signals (the 'distal stimulus') into electrochemical activity automatically—this is called transduction.

Population voting and coincidence detection associate parallel input events together and present 'whole patterns' for each microsecond of processing time. The resulting patterns of data are compared against previously experienced patterns and associated with those they most closely resemble, forming a recreation of the distal stimuli in an inner model; this recreation/representation is called the percept [2] and this is the preface to perception of input.

A percept is a packet of information forming one 'bit' or unit of input. All percepts are in spatio-temporal format (viewed, represented and stored as patterns of events within a context of spacetime.)

Percepts are compared against preexisting patterns on an inner model of associated concepts. A concept is a unit of meaning; an abstracted feature or characteristic that binds individual things by association into sets. “Red” is a concept.

Our hard wired concepts are core concepts. A core concept is a basic feature of all reality such as energy, time, space or matter. In the inner model, all concepts are in graphic format (viewed, represented and stored as imagery.) The images are graphic representations of the concepts.

The system experiences proximal stimuli as 'events' and percepts as having an 'address' -they are all 'events @ locations'. All input is represented in the model as associated with certain locations and those locations remain constant in relation to one another on the inner model. Everything that exists or occurs can then be associated with coordinates related to these locations, and any new input can be compared with previous experience and allocated to whatever location it seems to associate with most.

Once we have identified the 'location' of something on the mind's inner model, we can understand it by association with stuff that we know already.

Simple overall rules like 'add more of the same @ location x' or 'if locations x and y are active at the same time, link them together' lie behind plasticity; development is promoted by input signals (use) and constrained by density (availability of materials/ finite volume of space available) and power (energy availability/time in which signals can be processed.)

The locations most regularly active quickly become become permanently established with multiple connections in the 'network hubs'. These will be main communication nexuses where inputs converge, processing can take place and comparisons for association can be made.

Experiential input should confirm, not conflict with, eidetic core concepts, giving our inner model the ability to portray reality accurately, and imagination the correct data to reproduce a model of whatever's detected and start 'making sense of the world'.

We took for an example learning to speak a particular language. Although we are programmed to learn any language or several, as associations build up from experience a specific language will be recognized, and finally the words will be understood as associated with meanings both from experience and from the inner model. Once we've developed association nets to that level, appropriate interactive responses are always ready and waiting.

We'll learn more about this when you move on to intermediate NH (next tutorial). For now we just need to remember that the mind associates everything with animal behaviors and they in turn associate with core concepts that are hard wired. Animal behaviors are flexible and adaptable, core concepts are not.

The minds goal is the pursuit of entelechy (Rogers' “actualization tendency”, the organism thriving) and its required output is a series of interactions that will lead to the best possible outcome. To provide these, the mind must predict the best behaviors for every interaction and constantly improve its repertoire; it's own ability to interact, by learning. It is no surprise then that all intelligent creatures are both keen to learn and tempted by the unknown.

Prediction relies on a mixture of imagination, memory and current perception. Our mind brings together the lessons of the past and probabilities of the future with the here and now, all the time. That's exactly how you know what the end of this sentence is likely t.........


Following the pattern that biology works with is the way you learned to walk and talk, and it’s the fast, easy way to learn. If you didn’t understand all the sciency bits don’t worry, -just follow the white rabbit.


The Process of Perception


The development of intelligence goes through clear stages, and so does the process of learning anything. If we work with the natural process instead of against it, results are much faster.

Learning depends on dynamic changes in brain chemicals to achieve each stage. Remember how different networks use different transmitters? They’re doing different kinds of thinking based on animal behaviors that rely on those chemicals. And the long and the short of it is, if your brain releases the right chemicals in the right order, you learn faster and you remember better.

You can get this to happen on purpose by following a simple formula we will explain shortly.


The brain associates anything your intent follows with 'important stuff', so you have an automatic advantage in natural learning because it then does everything for you, even while you're sleeping!


Summary example of the process of perception:

Someone says 'hello world'. This is the distal stimulus.

The sound and light waves impacting on system sensors are the proximal stimulus.

The brain's reproduction of this input pattern accurately as speaking sounds is the percept.

“Language” is a hard wired concept, compared against which the percept is given meaning.






How Perception Happens -do you get it?

Identify the distal stimulus, proximal stimulus, percepts and concepts in the following scenarios:

A person is looking at a flower. The flower itself is the ---------------------- When light reflected from the flower enters the person's eye and stimulates their retina, that stimulation is the -------------------------. The image of the flower reconstructed by the brain of the person is the ---------------------. Similar images already stored in the brain are ----------------------.


A bird is singing. “Birds Singing” is a --------------------- already in memory. The singing of the bird is the -----------------------------. The sound stimulating your auditory receptors is the -------------------------------, and the brain's interpretation of this as the singing of a bird is the -------------------------------.

Someone passes you a new food to try at a party. The new food is the ------------------------. The registration of the taste and texture of the food on your tastebuds is the -------------------------. Your recognition of it as 'tastes like chicken' is a -------------------------. “Chicken Taste” is a -------------- from your memory.


You meet the Crab People from a distant world. The crab people are the --------------------------. The light waves reflected from the crab people hitting your retina and the odor molecules from the crab people signaling your nasal receptors are the ---------------------------------. Your observations, “Smells like crab, looks like people” are ---------------------------. “Crabs” and “People” are -------------------.

(answers at end of tutorial)



Last Updated on Monday, 29 May 2017 13:07