From Neptune to Mercury

Neptune, Uranus, out rocks. Saturn, and Jupiter the gas giants. Then, Mars, rocky, arid. A condensate of dust compacted into deserts and grit. No water in the air, yet. Perhaps ice. Then, earth. Then Venus. Dense clouds of carbon dioxide and sulphur. Then Mercury, crystalline surface? 

Planets spinning towards the heat and gravity of the Sun.

See a pattern?

Brain World

Beginning work on converting brain indices into operations.

Billions of black and white holes

Billions of Schwartzchild radii on the surface of a gravitational well with sufficient complexity. Quantum  entangled super positions interacting to quantum causality.

The Speed of Light

What if the speed of light as a constant, being associated with Planck frequency, is what keeps different universes apart? That is, if something travelled faster, we would be in different universes, i.e., break the phase boundary of Planck frequency. 

Love

Love does not care about distance,
It does not care about time.
Love does not care about if you are good,
Or bad,
It does not care if you are dead,
Or alive.
If you are real,
Or imaginary.
It only cares to be in the same dimension as you.
If not,
It will do all things to bring you to it,
Or it will move to you.
If it cannot,
It will create new dimensions.
The greatest of these is love.

Cycling through thoughts

 We seek to maximize our minimizational (maximinal). This has individual differences. Those who's maximinal is small essentially prefer low stimulation, or boredom. Those who's maximinal is big prefer stimulation, or excitement.

Wednesday August 31 2022: Phases of learning

About neural learning, neural systems should have different phases of learning. I would argue that the first phase has to be one where the energy (or information, or prediction error) imposes itself onto the energy state of the neural system. At this point, the neural system's encoding of this novel information is still only in terms of thermodynamics or flows of the received energy. We might observe this in the form of the neural system's post-synaptic potential and axonal spike activity. It is critical to note that changes in activity are by definition a dynamic concept. Thus, the information is not encoded in one static activity state. Rather, the complete information packet as it were must be represented by a window of dynamic activity fluctuations. Sustaining such a non-homeostatic state of activity is untenable in the long run. Therefore, this dynamic activity must be resolved in the neural system's architecture. Here, the novel information graduates from thermodynamics to physical structures. We might observe short- or long-term potentiation or depression, directed shaping of short and long-range connections characteristic of pruning and neural development. All these consume energy, and likely in a way that reflects the dynamic activity that is the packet of information received.

A necessary question is then what sort of information is received, and what sort of information is bypassed by neural systems. This consideration stems from the fact that the neural system cannot possibly encode all encountered fluctuations of energy in the environment. I would argue that the information received and not bypassed might be construed as information that is meaningful to the system. By meaningful, I mean that the information is auto-encoded or auto-regressive. That is, meaningful information is information that sufficiently maximizes the match between the prior state and the information.

Here, we can then formulate the problem as one in which there exists a prior state, novel information, and the posterior state which is the cross product of the two.

Engines in the brain

Motor actuation works via a pulse transferred to momentum force that is smeared over time. Efficient motors have a significant proportion of this smeared force extending the influence of the pulse by having a large part of the momentum dynamically adding to subsequent pulses. A dampening sine. A collection of dampening sines. A fractal collection of dampening sines.

The driver? Temperature and its local fluctuations establishing sufficient gradient crossings for stability. If entropy has increased for all temperatures, what happens?

Life and Least Action

 Intelligence: the shortest time for energy to transition between states.

Nuclear tug of war

 If you constrain the environment around an object such that the constraints threaten the object's integrity, the object (if it is to maintain its integrity) will find the path of least resistance to create an alternative route out of the constraints that will maintain its integrity. This is a tug-of-war of the nuclear forces. This involves the creation of dimensions in spactime.

The evolution of humans

This is a postulate. The next stage of human evolution begins when someone, somewhere truly sheds of his or her humanity to embrace the next form of ego consciousness.

2 Science Projects to Receive Billion-Euro Award

2 Science Projects to Receive Billion-Euro Award: The winners of the European Commission’s awards are a project to imitate the brain and one to develop new materials for information technology.

Studies Suggest Potential Approaches for Early Detection of Alzheimer Disease

Studies Suggest Potential Approaches for Early Detection of Alzheimer Disease: New Orleans— By the time a patient is diagnosed with even mild Alzheimer disease (AD), evidence suggests that the abnormal accumulation of amyloid and tau proteins in the brain, 2 hallmarks of the disorder, has been under way for 10 to 20 years.

New brain gene gives us edge over apes, study suggests

New brain gene gives us edge over apes, study suggests: Scientists have taken a step forward in helping to solve one of life's greatest mysteries -- what makes us human?

Running too far, too fast, and too long speeds progress 'to finish line of life'

Running too far, too fast, and too long speeds progress 'to finish line of life': Vigorous exercise is good for health, but only if it's limited to a maximum daily dose of between 30 and 50 minutes, say researchers.

[Report] A Large-Scale Model of the Functioning Brain

[Report] A Large-Scale Model of the Functioning Brain: Two-and-a-half million model neurons recognize images, learn via reinforcement, and display fluid intelligence.

Authors: Chris Eliasmith, Terrence C. Stewart, Xuan Choo, Trevor Bekolay, Travis DeWolf, Charlie Tang, Daniel Rasmussen

Cultivator of Brain Parts

Cultivator of Brain Parts:
Yoshiki Sasai is not just an ordinary tissue engineer who tries to coax stem cells to grow into fully formed bodily structures. It is true that Sasai has made his mark by taking on big projects like using stem cells to whip up a retina, cortical tissue and the cerebellum, involved with balance and movement. But his research has gone deeper by delving into the way stem cells organize themselves into complex structures under the influence of genes and the prenatal environment. Read a profile of Sasai here to accompany “ Grow Your Own Eye ,” Sasai’s own account of growing a retina in the November Scientific American .
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Efficient use of brain space makes the intelligent person

"When you finish playing with your toys, you must put them back. Otherwise next time you want to play with them again, you cannot find them." These are my mother's words that will forever echo through my mind. How remarkably correct she was!

In a limited network, struggling to represent the world, the trick is to clean up after yourself, as quickly as possible, leave a cue, and then you can move on to something else, doing the same thing again. If you do not clean up after yourself, and leave clutter, then you don't have space to handle the new stuff. Then, things get messy. You start to have new stuff mixed with old stuff, you can't tell the two apart, you take more time to find things, if you can find them at all. They are there, but you can't get at them because they were not organized well.

We see this partially in evidence from personality studies. Higher levels of neuroticism, with lower levels of conscientiousness are associated with higher incidence of Alzheimer's dementia. Perhaps higher neuroticism means that the brain is stuck in a certain way of doing things and can't disengage from processes that are unhelpful. And, perhaps lower conscientiousness means that the brain does not process information thoroughly enough before attending to other matters. These hint at the clean-up-after-yourself problem.

We can also project this from simple conceptual developments surrounding neural network and information representation and retrieval. A fixed neural network region can only represent 1 state of information at any one time, even though that state may be a complex one. In order for that network to move on to represent another state effectively, it must settle into a stable representation of the 1st state. Otherwise, the two states will overlap and the representation will be compromised. By this token, subsequent attempts to retrieve a given state will be more difficult or less accurate because the two states simpy do not exist as separate entities.

How does a network stabilize it's state representations? The answer is work. After you are done, clean up. Put it back in a place in order. Plan ahead and project what you need to know to get the stuff back in the future, and organize your stuff right now accordingly. Use placeholders. Don't just leave things lying around. Go deep. Understand the essence of stuff.

An example may easily be seen in spatial representations. It is much more efficient to know the rule that a square consists of 4 sides of equal length, and that the length is X, than to encode that the first side of a square is X length, the second is X length, the third is X length, and the fourth is X length. Working hard to understanding the essence of something helps to clean up brain space.

Another example relates to Hansel and Gretel. You're in a forest of trees. Everything looks the same. Realize that you are going to get lost. Think a little bit and realize that if you drop a trail, or do something out of the ordinary for yourself, you can find your way back later. Don't just jump head into the forest without thinking, hoping that you will somehow come out the right way again. Working hard to do something that insures you in the future also cleans up brain space.

Some will find it harder than others to clean up after themselves. Some stuff are harder to organize and pack up than others too. But in this is the beauty of the human being - that we are all creatures who have habits, and habits can be fostered, and habits make a hard thing easier, or at least help us not to mind doing it. Familiarity feels good.

I may have bad memory, but I make good decisions.

Age and time. They catch up with the best of us. Despite its awesome capabilities, our brains are still finite apprehenders of reality. There is only so much knowledge we can each possess. And therefore, only so much knowledge we can retain or retrieve at any one time. Information that we used to have is changed, and therefore lost.

This is at once a threat to our existence. Loss of important information acquired in the past might cost us a bad choice. Effectively, we might make uninformed choices.

Here's sprinkling more salt on the wound. Losing information is one thing, but having our tuning for what's good or bad for us messed with, now that's something warranting some learned helplessness. At least if we forget, we can Google it now. But if we can't distinguish what's good or bad for us, even if it's staring us in the face, right under our noses, then Googling the most relevant hits will do us no good, pun intended.

So, how do we keep our senses tuned?

Yellowstone 2012: Day 1

It is 12.43am, I am writing a paper. Its been 4 days since my last day at LBN. The weekend was mostly spent on work, shopping, eating, watching TV. Packing up our stuff was at the back of our minds...the 22nd seems so far away at the moment. But we know it is not. It is a stressor.

Today's thoughts included:
1. Tim Minchin's Storm is something I contend with.
2. Higgs-Boson particle.
3. Dang it Apple! -- you stole my eye-glass computer screen idea, and you'll probably make it work too, I so love/hate you.
4. Pho.
5. Classes to teach.
6. Grants to write.
7. Research projects to do.
8. Lumix GX1 wins.
9. The Snow Leopard has not yet appeared at our door.
10. DK is cool, but he does go on.
11. ...

You can hardly tell that in 4 hours, we're leaving for Yellowstone.

What I need is a butler.

Yay to vacations, yay to getting back to reality.