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N.Wells



Posts: 1836
Joined: Oct. 2005

(Permalink) Posted: April 28 2015,21:19   

[quote=GaryGaulin,April 28 2015,19:20][/quote]
 
Quote
Please spare us your anti-ID related embellishments to already accepted definitions. The word "designed" is not found (and does not belong) in the following:  
Quote

http://en.wikipedia.org/wiki.......eration

A theory of operation is a description of how a device or system should work. It is often included in documentation, especially maintenance/service documentation, or a user manual. It aids troubleshooting by providing the troubleshooter with a mental model of how the system is supposed to work. The troubleshooter can then more easily identify discrepancies, to aid diagnosis of problem.

This is not "my embellishment" - it is just standard understanding.   The Wikipedia writers probably didn't realize that there would be anyone dense enough to miss the point without adding "designed" after all the talk about devices and maintenance and service documentation and people troubleshooting problems.  Theories of operation are written by people who create (design) devices or systems so that users can gain a better mental model of how something works so they can fix it. Find one example of somebody, other than you, using "theory of operation" for a nondesigned system, and I will publicly apologize.

 
Quote
It's not my fault that Charles Darwin only had a simple outside view of a complex intelligent system (that causes speciation) and did not have enough detail for a working model of it.
Assuming facts not in evidence - you have not yet demonstrated that evolution is an intelligent system.

 
Quote
If he did then he would have possibly like me have reached a point where the model would require a theory of operation (to explain how it works).
 No, that would require a regular scientific theory, not a theory of operation.  Gary, words mean stuff: you can't just make up rubbish whenever you want just so you can feel better about your prior beliefs.  Neither reality nor English work that way.

 
Quote
In my opinion I'm simply following a very useful systems biology approach, you will just have to get used to.

OF COURSE you would claim to be doing systems biology: it's a wonderful buzzword and is very poorly defined, so all sorts of things could qualify.  Your stuff is about a system, right, so surely it has to qualify?  Well, no.

Don't get me wrong, I'm all for systems biology.  In Geology, I love to alternate (A) looking at things from small details and fundamental processes in order to build up to the big picture of how large systems are working, with (B) working down from the big picture of how a system operates to figure out how all its parts contribute and mesh together.  The global climate models that I just mentioned are in effect "Systems Climatology".  

Nonetheless, let's take a look at systems biology approaches, and see where your rubbish falls short.

NIH  
Quote
[from http://irp.nih.gov/catalys....-by-nih ]Systems biology is an approach in biomedical research to understanding the larger picture—be it at the level of the organism, tissue, or cell—by putting its pieces together. It’s in stark contrast to decades of reductionist biology, which involves taking the pieces apart.  .... Start with Computational Modeling ...... models need solid experimental data as input and as a reference to ensure reality checks. Otherwise the biological models are likely to be oversimplified ........
......
And they have a top-down approach that uses inferences from perturbation analyses to probe the large-scale structure of the interactions not only at the cellular level, but also at the tissue and even the organism level.
...............

Ron Germain does have his own definition of systems biology that he’s sticking to: a scientific approach that combines the principles of engineering, mathematics, physics, and computer science with extensive experimental data to develop a quantitative as well as a deep conceptual understanding of biological phenomena, permitting prediction and accurate simulation of complex (emergent) biological behaviors.


From http://sbiaustralia.org/systems....biology
 
Quote
Definition of Systems Biology

"Understanding biomedical systems by data-based mathematical modelling of their dynamical behavior. For the purposes of this study the objective of systems biology has been defined as the understanding of network behavior, and in particular their dynamic aspects, which requires the utilization of mathematical modeling tightly linked to experiment."


From http://blogs.nature.com/sevenst...._3.html
 
Quote

What is systems biology?

23 Jul 2007 | 21:22 BST | Posted by Molecular Systems Biology Team | Category: Publishing

For the fun of it, here are a few examples of definitions:

   To understand complex biological systems requires the integration of experimental and computational research — in other words a systems biology approach. (Kitano, 2002)

   Systems biology studies biological systems by systematically perturbing them (biologically, genetically, or chemically); monitoring the gene, protein, and informational pathway responses; integrating these data; and ultimately, formulating mathematical models that describe the structure of the system and its response to individual perturbations. (Ideker et al, 2001)

   […]the objective of systems biology [can be] defined as the understanding of network behavior, and in particular their dynamic aspects, which requires the utilization of mathematical modeling tightly linked to experiment. (Cassman, 2005)

   By discovering how function arises in dynamic interactions, systems biology addresses the missing links between molecules and physiology. Top-down systems biology identifies molecular interaction networks on the basis of correlated molecular behavior observed in genome-wide “omics” studies. Bottom-up systems biology examines the mechanisms through which functional properties arise in the interactions of known components. (Bruggeman and Westerhoff, 2007)

Why is it so difficult to come up with a concise definition of systems biology? One of the reasons might be that every definition has to respect a delicate balance between “the yin and the yang” of the discipline: the integration of experimental and computational approaches (Kitano, 2002); the balance between genome-wide systematical approaches (Ideker et al, 2001) and smaller-scale quantitative studies (Tyson et al, 2001); top-down versus bottom-up strategies to solve systems architecture and functional properties (Bruggeman and Westerhoff, 2007). But despite the diversity in opinions and views, there might be two main aspects that are conserved across these definitions: a) a system-level approach attempts to consider all the components of a system; b) the properties and interactions of the components are linked with functions performed by the intact system via a computational model.



So, let's see how you stack up.  Are you starting with solid experimental data as input and as a reference to ensure reality checks, lest your biological models become oversimplified for lack of data?  No, you don't start with experimental data as either input or reality checks, and you brag about how your models are excessively simplified.   Are you doing perturbation analysis to see how the system responds to changes?  No.  Are you starting with massive data sets and trying to create a model that yields those results from first principles (exactly as I was describing for regional climate models)?  No.  (Your insect has a hippocampus, FCOL. That's orders of magnitudes of inaccuracy without even leaving the starting gate.)  Are you using "extensive experimental data to develop a quantitative as well as a deep conceptual understanding of biological phenomena, permitting prediction"? - that would "heck, no!!".  Are you using mathematical modelling tightly linked to experimentation?  Again, no.  You would certainly love to discover "how function arises in dynamic interactions" but you are merely asserting this: are you actually addressing "the missing links between molecules and physiology" and  identifying "molecular interaction networks" on the basis of "correlated molecular behavior observed in genome-wide “omics” studies"?  Again, that's a bunch of no's.

Other than your finch beak growth model, your shock zone stuff comes closest to a systems biology approach where you are trying to align experimental results with how your model functions.  With hard work, reworking the model to start with basics that are biologically real, and more ground-truthing to make sure that you are modelling things the way they actually work (rather than "Do: Up = Up  + AngelLift: Loop Until Up > NotYetAirborne"), you might actually get a model of rat navigation.  However, you are claiming that your model is about such things as the emergence of intelligence; molecular intelligence, evolution as an intelligent system; intelligence being fractal, emergent, self-similar, and intelligently designed all at the same time; natural selection not working as advertised, etc., etc., etc.  and navigation around shock zones is none of that.

  
GaryGaulin



Posts: 5385
Joined: Oct. 2012

(Permalink) Posted: April 28 2015,23:16   

Quote (stevestory @ April 28 2015,10:09)
This is kinda like what Gary's program would be, if Gary wasn't a clueless lunatic: Evolution Lab

That is not a computer model, or a theory of operation. Another what (maybe) came from what does not put the phrase "intelligent cause" into scientific context.

I have no need to try competing with what PBS and others already provide. At this point in time it's more like helping to pioneer a relatively new area of science where for all the goal ends up becoming to model living things in molecular level detail, with what can be fairly described as an ID Lab of the future.

My finding the need to stay consistent with existing theory writing procedures for "systems" can be useful information to someone who ends up not knowing where to even begin writing a "theory" for the system they have. This also supports what some of the most famous pioneers of systems biology have been describing about the framework of Darwinian theory not really working for them all that well. They are then accused of being science deniers. From my experience the problem is that system biology needs a theory writing structure designed for working with systems, while evolutionary biology needs what Charles Darwin wrote for theory. It's a "need to use the right tool" sort of thing, where what works is already there to use.

--------------
The theory of intelligent design holds that certain features of the universe and of living things are best explained by an intelligent cause, not an undirected process such as natural selection.

   
GaryGaulin



Posts: 5385
Joined: Oct. 2012

(Permalink) Posted: April 29 2015,01:25   

Quote (N.Wells @ April 28 2015,21:19)
Quote (GaryGaulin @ April 28 2015,19:20)

   
Quote
Please spare us your anti-ID related embellishments to already accepted definitions. The word "designed" is not found (and does not belong) in the following:    
Quote

http://en.wikipedia.org/wiki.......eration

A theory of operation is a description of how a device or system should work. It is often included in documentation, especially maintenance/service documentation, or a user manual. It aids troubleshooting by providing the troubleshooter with a mental model of how the system is supposed to work. The troubleshooter can then more easily identify discrepancies, to aid diagnosis of problem.

This is not "my embellishment" - it is just standard understanding.   The Wikipedia writers probably didn't realize that there would be anyone dense enough to miss the point without adding "designed" after all the talk about devices and maintenance and service documentation and people troubleshooting problems.  Theories of operation are written by people who create (design) devices or systems so that users can gain a better mental model of how something works so they can fix it. Find one example of somebody, other than you, using "theory of operation" for a nondesigned system, and I will publicly apologize.

   
Quote
It's not my fault that Charles Darwin only had a simple outside view of a complex intelligent system (that causes speciation) and did not have enough detail for a working model of it.
Assuming facts not in evidence - you have not yet demonstrated that evolution is an intelligent system.

   
Quote
If he did then he would have possibly like me have reached a point where the model would require a theory of operation (to explain how it works).
 No, that would require a regular scientific theory, not a theory of operation.  Gary, words mean stuff: you can't just make up rubbish whenever you want just so you can feel better about your prior beliefs.  Neither reality nor English work that way.

   
Quote
In my opinion I'm simply following a very useful systems biology approach, you will just have to get used to.

OF COURSE you would claim to be doing systems biology: it's a wonderful buzzword and is very poorly defined, so all sorts of things could qualify.  Your stuff is about a system, right, so surely it has to qualify?  Well, no.

Don't get me wrong, I'm all for systems biology.  In Geology, I love to alternate (A) looking at things from small details and fundamental processes in order to build up to the big picture of how large systems are working, with (B) working down from the big picture of how a system operates to figure out how all its parts contribute and mesh together.  The global climate models that I just mentioned are in effect "Systems Climatology".  

Nonetheless, let's take a look at systems biology approaches, and see where your rubbish falls short.

NIH      
Quote
[from http://irp.nih.gov/catalys....-by-nih ]Systems biology is an approach in biomedical research to understanding the larger picture—be it at the level of the organism, tissue, or cell—by putting its pieces together. It’s in stark contrast to decades of reductionist biology, which involves taking the pieces apart.  .... Start with Computational Modeling ...... models need solid experimental data as input and as a reference to ensure reality checks. Otherwise the biological models are likely to be oversimplified ........
......
And they have a top-down approach that uses inferences from perturbation analyses to probe the large-scale structure of the interactions not only at the cellular level, but also at the tissue and even the organism level.
...............

Ron Germain does have his own definition of systems biology that he’s sticking to: a scientific approach that combines the principles of engineering, mathematics, physics, and computer science with extensive experimental data to develop a quantitative as well as a deep conceptual understanding of biological phenomena, permitting prediction and accurate simulation of complex (emergent) biological behaviors.


From http://sbiaustralia.org/systems....biology
   
Quote
Definition of Systems Biology

"Understanding biomedical systems by data-based mathematical modelling of their dynamical behavior. For the purposes of this study the objective of systems biology has been defined as the understanding of network behavior, and in particular their dynamic aspects, which requires the utilization of mathematical modeling tightly linked to experiment."


From http://blogs.nature.com/sevenst...._3.html
   
Quote

What is systems biology?

23 Jul 2007 | 21:22 BST | Posted by Molecular Systems Biology Team | Category: Publishing

For the fun of it, here are a few examples of definitions:

   To understand complex biological systems requires the integration of experimental and computational research — in other words a systems biology approach. (Kitano, 2002)

   Systems biology studies biological systems by systematically perturbing them (biologically, genetically, or chemically); monitoring the gene, protein, and informational pathway responses; integrating these data; and ultimately, formulating mathematical models that describe the structure of the system and its response to individual perturbations. (Ideker et al, 2001)

   […]the objective of systems biology [can be] defined as the understanding of network behavior, and in particular their dynamic aspects, which requires the utilization of mathematical modeling tightly linked to experiment. (Cassman, 2005)

   By discovering how function arises in dynamic interactions, systems biology addresses the missing links between molecules and physiology. Top-down systems biology identifies molecular interaction networks on the basis of correlated molecular behavior observed in genome-wide “omics” studies. Bottom-up systems biology examines the mechanisms through which functional properties arise in the interactions of known components. (Bruggeman and Westerhoff, 2007)

Why is it so difficult to come up with a concise definition of systems biology? One of the reasons might be that every definition has to respect a delicate balance between “the yin and the yang” of the discipline: the integration of experimental and computational approaches (Kitano, 2002); the balance between genome-wide systematical approaches (Ideker et al, 2001) and smaller-scale quantitative studies (Tyson et al, 2001); top-down versus bottom-up strategies to solve systems architecture and functional properties (Bruggeman and Westerhoff, 2007). But despite the diversity in opinions and views, there might be two main aspects that are conserved across these definitions: a) a system-level approach attempts to consider all the components of a system; b) the properties and interactions of the components are linked with functions performed by the intact system via a computational model.



So, let's see how you stack up.  Are you starting with solid experimental data as input and as a reference to ensure reality checks, lest your biological models become oversimplified for lack of data?  No, you don't start with experimental data as either input or reality checks, and you brag about how your models are excessively simplified.  

That is a very good summary of what "systems biology" is. I have to thank you for the input.

The navigation network's cell population is trained to behave as inhibitory synapse connected neurons. This is how it's done:

Code Sample

~Dimension Random Access Memory to pretrain for behavior from a population of cells with 6 Field sectors of inhibitory In/Out to neighboring fields.
~In biological brains this is from the group behavior from many grid, place, boundary/border cells combined.
~Upper two bits set behavior of entire field for either repel (Bit6) or attract (Bit7, most significat bit).

Dim FieldRAM(255) As Byte


Code Sample

~Train RAM for grid field behavior. Repel locations (128=10nnnnnn binary) are left all zeros.
~For Attractor locations, all outputs are active (63=111111 binary) when Inputs are all inactive.

    FieldRAM(64) = 63          ~64=01000000 binary, Attractor bit + six zeros for inactive neighbors.

~Normally grid locations propagate active signals coming in from neighbors, to all inactive neighbors.

 For N = 1 To 63               ~For all possible Neighbor readings. Above 63 is Attract or Repel mem.
    FieldRAM(N) = 63 - N       ~Example: binary 111111 - 001100 = 110011, bits become exact opposite.
 Next N



It's such a simple and basic signal interaction it's rather silly for you to argue that it cannot happen in biology.

My taking so few lines of code to train a RAM to behave as network elements is from the model and theory for-real making it fast it easy to do so. I had something up and running in around one hour after starting writing code. I then noticed the signal flow went around obstacle network elements that had no signal flow through them. It's more like explaining the properties of a most simple network possible.

What I have been explaining is all that is easily contained in even network behavior as simple as this. And that was made possible by NOT starting with "ANN" type modeling that adjusts synaptic weights of interconnected layers and all that. How it's done in the modeling method I use eliminated all the number crunching math, the result worked surprisingly well. Was the right tool for the job. I have good reasons to stay with the modeling method that keeps on making awesome models possible.

I may have made it all look too easy. But where you carefully examine the code it is still modeling commonly described neural behavior, not something else.

--------------
The theory of intelligent design holds that certain features of the universe and of living things are best explained by an intelligent cause, not an undirected process such as natural selection.

   
k.e..



Posts: 5432
Joined: May 2007

(Permalink) Posted: April 29 2015,02:23   

Gary you must know that that is not Turing complete ?

AND cannot possibly model intelligence ...right.

Fucking moron!

--------------
"I get a strong breeze from my monitor every time k.e. puts on his clown DaveTard suit" dogdidit
"ID is deader than Lenny Flanks granmaws dildo batteries" Erasmus
"I'm busy studying scientist level science papers" Galloping Gary Gaulin

  
ChemiCat



Posts: 532
Joined: Nov. 2013

(Permalink) Posted: April 29 2015,03:27   

Quote
It's not my fault that Charles Darwin only had a simple outside view of a complex intelligent system (that causes speciation) and did not have enough detail for a working model of it. If he did then he would have possibly like me have reached a point where the model would require a theory of operation (to explain how it works).


I'm not sure quite what this is supposed to mean but it appears that Gaulin thinks that a "complex intelligent system" causes speciation.

Quote
At this point in time it's more like helping to pioneer a relatively new area of science where for all the goal ends up becoming to model living things in molecular level detail, with what can be fairly described as an ID Lab of the future.


The problem here, Gaulin, is that you are using a covered wagon and scientists are driving a racing car.

  
GaryGaulin



Posts: 5385
Joined: Oct. 2012

(Permalink) Posted: April 29 2015,07:46   

Navigational networks provide the navigation signals, not the "intelligence".

The simple trick I used to ahead of time train the RAM (as well as no guess or confidence circuits needed) renders it unintelligent, but with all there so it can all by itself wire up the complete brain it's a model of some of the cellular intelligence of neurons.

--------------
The theory of intelligent design holds that certain features of the universe and of living things are best explained by an intelligent cause, not an undirected process such as natural selection.

   
NoName



Posts: 2729
Joined: Mar. 2013

(Permalink) Posted: April 29 2015,08:01   

Quote (GaryGaulin @ April 29 2015,08:46)
Navigational networks provide the navigation signals, not the "intelligence".

The simple trick I used to ahead of time train the RAM (as well as no guess or confidence circuits needed) renders it unintelligent, but with all there so it can all by itself wire up the complete brain it's a model of some of the cellular intelligence of neurons.

No.  It's not.
It's a software emulation of an imaginary construction of a hallucination of what "intelligence" might be.
As relevant as a fart in church, and less useful or informative.

  
N.Wells



Posts: 1836
Joined: Oct. 2005

(Permalink) Posted: April 29 2015,11:38   

Quote (NoName @ April 29 2015,08:01)
 As relevant as a fart in church

I'm not sure about that: flatulence in church might actually be more relevant.  If you could time it to the preacher declaiming Psalm 29,
     
Quote
"The voice of the Lord is upon the waters;
The God of glory thundereth;"

or possibly Exodus 19:16
     
Quote
Thunder and lightning are significant manifestations of the power of God, and emblems of his presence

or Acts 2:2
   
Quote
And suddenly there came a sound from heaven as of a rushing mighty wind, and it filled all the house where they were sitting

then it might at least enliven a boring sermon.
:)
My juvenile contribution for the day.

  
Henry J



Posts: 5786
Joined: Mar. 2005

(Permalink) Posted: April 30 2015,08:27   

Quote
My juvenile contribution for the day.

Maybe, but it was a gas!

  
fnxtr



Posts: 3504
Joined: June 2006

(Permalink) Posted: April 30 2015,08:45   

Quote (Henry J @ April 30 2015,06:27)
Quote
My juvenile contribution for the day.

Maybe, but it was a gas!

We all feel the need to vent occasionally.

--------------
"[A] book said there were 5 trillion witnesses. Who am I supposed to believe, 5 trillion witnesses or you? That shit's, like, ironclad. " -- stevestory

"Wow, you must be retarded. I said that CO2 does not trap heat. If it did then it would not cool down at night."  Joe G

  
jeffox



Posts: 671
Joined: Oct. 2007

(Permalink) Posted: April 30 2015,15:35   

No wonder Jack Flash was jumping!  :)

But, then again, there's that Garth Brooks album, 'Breaking the Wind'.  

'When I was back there in seminary school, there was a person there who put forth the proposition that you can petition the lord with air . . . . '

OK, 'nuff of that, back to GooGoobaiting . . . .

:)  :)  :)

  
fnxtr



Posts: 3504
Joined: June 2006

(Permalink) Posted: April 30 2015,21:06   

Quote (jeffox @ April 30 2015,13:35)
But, then again, there's that Garth Brooks album, 'Breaking the Wind'.  

I thought that was Spinal Tap.

--------------
"[A] book said there were 5 trillion witnesses. Who am I supposed to believe, 5 trillion witnesses or you? That shit's, like, ironclad. " -- stevestory

"Wow, you must be retarded. I said that CO2 does not trap heat. If it did then it would not cool down at night."  Joe G

  
Henry J



Posts: 5786
Joined: Mar. 2005

(Permalink) Posted: April 30 2015,21:45   

Quote (fnxtr @ April 30 2015,20:06)
Quote (jeffox @ April 30 2015,13:35)
But, then again, there's that Garth Brooks album, 'Breaking the Wind'.  

I thought that was Spinal Tap.

Or geese, flying in formation.

  
GaryGaulin



Posts: 5385
Joined: Oct. 2012

(Permalink) Posted: May 01 2015,03:50   

Quote (jeffox @ April 30 2015,15:35)
OK, 'nuff of that, back to GooGoobaiting . . . .

:)  :)  :)

Well wank my chain.....

That helped clear the air.

--------------
The theory of intelligent design holds that certain features of the universe and of living things are best explained by an intelligent cause, not an undirected process such as natural selection.

   
jeffox



Posts: 671
Joined: Oct. 2007

(Permalink) Posted: May 02 2015,09:43   

Well, it certainly cleared the room, anyways.  :O  :)  :)

Yer still a hoot, Goo Goo!

  
N.Wells



Posts: 1836
Joined: Oct. 2005

(Permalink) Posted: May 02 2015,11:22   

Quote (GaryGaulin @ May 01 2015,03:50)
Well wank my chain.....

Umm, no, thank you.

  
GaryGaulin



Posts: 5385
Joined: Oct. 2012

(Permalink) Posted: May 02 2015,18:18   

From:
http://www.antievolution.org/cgi-bin....y244077
   
Quote (Timothy McDougald @ May 01 2015,10:07)
I wonder what the implications of this is for near death experiences.  :O

Very very paradigm changing implications.

Thanks for the link that helped word my latest writing project:
Quote

In this Intelligence Design Lab a place cell self-navigation network provides an "internal world model" for intuitively navigating around obstacles, through tunnels and makes it possible to learn how to slow down ahead of time for a well controlled preplanned landing at a place attracting it, an attractor. In at least humans this network is expected to cause the conscious feeling of being inside (or in the case of Near Death Experiences outside) of one's own body.

HOW IT WORKS

Navigational vectors for two point proprioception (sense of how our bodies are positioned) of a body center and center of mouth are provided by the direction of action potential flow across an inhibitory connected network of room-preferring and arena-preferring place cells. Places to not navigate towards have no place cell discharge. The most attracting places (such as food pellet locations) have the greatest discharge. This signal gradient propagates from highest to lowest activity, around obstacles and places to avoid blocking signal propagation hence navigation through them by becoming completely inactive.

Digital RAM arrays (memory matrices) represent a population of place cells. The room-preferring (but not arena-preferring) place cells are addressed by the room angle by converting the Radian amount to a whole number (such as 0-7 or 0-15) then adding to the serialization by multiplying by power of two for appropriate bit position. The RAM data stored at each memory address contains activity levels (associated bit is 0 or 1) for 6 sectors hexagonally at each place mapped by the place cell memory/network. To these 6 bits are added 1 data bit that is set for behavior to make that place attract and 1 data bit that is set for behavior to make that place repel, avoid. This makes 8 bits of data per RAM address, one data byte per each hexagonally located place on the place cell map. When a food pellet is known to be inside a shock zone the place is set to both attract and avoid, which cancels place cell discharge in the six sectors at that location. The attractor location will resume signaling after the avoid bit is reset to 0, turned off.

Grid cells are expected to be part of the system that provides the rotation (such as to cue card on wall) and translation (distance traveled over time, dead-reckoning deduced position) signals for locating itself on the place cell network map. For computer modeling purposes rotation and translation are here provided by the already program calculated X,Y and rotation of everything in the environment including itself. The computer model then assumes that the in-silico critter has a computer accurate reading of exactly where it is located at any timestep in its lifetime.  This is the starting benchmark for models of the grid cell related system where there is the least amount of biological detail but greatest amount of calculation precision. It is not necessary to be computer precise, "close enough" still makes a useful navigation system. It is here best to start with upstream rotation and translation signals free of errors that would otherwise show up in testing of the place cell memory system alone.

See:
Brain scan reveals out-of-body illusion
http://www.sciencedaily.com/release....107.htm

Dynamic Grouping of Hippocampal Neural Activity During Cognitive Control of Two Spatial Frames.
Eduard Kelemen and André A.Fenton (2010)
PLoS Biol 8(6): e1000403. doi:10.1371/journal.pbio.1000403
http://www.plosbiology.org/article....1000403
Arena video:
http://www.plosbiology.org/article....03.s014


--------------
The theory of intelligent design holds that certain features of the universe and of living things are best explained by an intelligent cause, not an undirected process such as natural selection.

   
Woodbine



Posts: 1218
Joined: June 2007

(Permalink) Posted: May 02 2015,19:05   

Quote (GaryGaulin @ May 03 2015,00:18)
Brain scan reveals out-of-body illusion
http://www.sciencedaily.com/release....107.htm

This must resonate with you, Gary.

You believe yourself to be at the cutting edge of science when in fact you are somewhere else entirely.

  
GaryGaulin



Posts: 5385
Joined: Oct. 2012

(Permalink) Posted: May 02 2015,23:45   

From:
http://www.antievolution.org/cgi-bin....y244100
   
Quote (Acartia_Bogart @ May 02 2015,22:12)
Maybe there is hope for ID after all.


See: How Would You Answer These Questions?

 
Quote
A friend writes to inform me that his son’s high school biology teacher is busily indoctrinating him into Darwinism by writing test questions that force the student to spew back Darwinist party-line answers in order to receive credit. Here are the questions:

1. One argument made against evolution is: evolution is random, so it cannot generate complex, orderly organisms. Explain why this statement is false.

2. Some people argue that evolution cannot be observed today. Explain how natural selection is observable in each of the following professionals (and makes their work more difficult): medical professionals, exterminators, and farmers.

......

Barry’s answers:

1. Neo-Darwinian theory posits that natural selection acts on random changes such as mutations by preserving those changes that create a survival advantage and deleting those changes that do not. As advantageous changes accumulate over countless generations, simple organisms gradually morph into more complex organisms. While it is true that the theory posits that the changes are random, it is not true that the theory posits that the overall process is random, because natural selection is not random. As the law of gravity “directs” a stone to fall to the earth, the law of “natural selection” directs the evolutionary process in a way that is analogous to a dog breeder developing a new dog breed. Therefore, it is false to say that Neo-Darwinian theory posits a purely random process. That said, natural selection has never been observed to actually direct the creation of large scale evolutionary changes such as new body types, and there are good reasons to believe it cannot do so.

2. It is simply false to say that evolution has never been observed. It most certainly has. Scientists have actually observed microbes develop antibiotic resistance through a strictly Darwinian process. Obviously, the work of medical professionals becomes more difficult when the microbes they are trying to eradicate evolve resistance to antibiotics. Similarly, the work of famers and exterminators becomes harder when bugs evolve resistance to pesticides. Thus, Darwinian evolution at this scale has been observed many times, and it is therefore false to say evolution cannot be observed. That said, it is also true that in contrast to small scale changes within a type (such as the development of antibiotic resistance), large scale evolutionary change that result in complex new organs or new body types has not been directly observed. Rather, since Charles Darwin and his finch beaks, theorists have assumed that the same process that results in small changes can be extrapolated to account for large changes. There are, however, very good reasons to believe that assumption is unwarranted.


With all considered, that's not all bad. Or at least I'm OK with Barry's answers. Long live UD....

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The theory of intelligent design holds that certain features of the universe and of living things are best explained by an intelligent cause, not an undirected process such as natural selection.

   
fnxtr



Posts: 3504
Joined: June 2006

(Permalink) Posted: May 03 2015,03:18   

"OK, so.. what "good reasons" would those be?"

"THE BIBLE SEZ SO."

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"[A] book said there were 5 trillion witnesses. Who am I supposed to believe, 5 trillion witnesses or you? That shit's, like, ironclad. " -- stevestory

"Wow, you must be retarded. I said that CO2 does not trap heat. If it did then it would not cool down at night."  Joe G

  
k.e..



Posts: 5432
Joined: May 2007

(Permalink) Posted: May 03 2015,05:56   

Quote (fnxtr @ May 03 2015,11:18)
"OK, so.. what "good reasons" would those be?"

"THE BIBLE SEZ SO."

Not L.A.W but lore. Barry just wants to stone homos and adulterers. He should live in Saudi Arabia under a Theocracy.

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"I get a strong breeze from my monitor every time k.e. puts on his clown DaveTard suit" dogdidit
"ID is deader than Lenny Flanks granmaws dildo batteries" Erasmus
"I'm busy studying scientist level science papers" Galloping Gary Gaulin

  
GaryGaulin



Posts: 5385
Joined: Oct. 2012

(Permalink) Posted: May 03 2015,08:22   

There was another Eureka! moment, after trying out the third of three possible states the network model inherently has but I never experimented with before. It added the bolded part to the How It Works:

 
Quote

In this Intelligence Design Lab a place cell self-navigation network provides an "internal world model" for intuitively navigating around obstacles to avoid and through tunnels. It's then easy to learn how to slow down ahead of time for a well controlled preplanned landing at a place attracting it, an attractor. In at least humans this network system is expected to cause the conscious feeling of being inside (or in the case of Near Death Experiences outside) of one's own body.

HOW IT WORKS

Navigational vectors for two point proprioception (sense of how our bodies are positioned) of a body center and center of mouth are provided by the direction of action potential flow across an inhibitory connected network modeled using digital RAM arrays (memory matrices) that map to room-preferring and arena-preferring place cell discharge.

The cell population has three active states, which are:

State 0, binary 00, Propagate
Places to navigate through (but not towards or away from) have no action potential discharge of their own. They do though propagate any signal received from a neighboring place to the neighboring place opposite to it, such that action potentials travel straight through and in time spread out like a wave.

State 1, binary 01, Attract
The most attracting place (such as location of a food pellet) has the greatest discharge and signals out in all 6 directions whenever no signal in is being received. This signaling to others (whenever it senses quiet) propagates out a signal flowing from highest to lowest activity that goes around places that might be completely inactive, non-propagating, state 3.

State 2, binary 10, Avoid
A place to avoid can cancel signal propagation of a nearby place that is attracting using the in/out pattern that produces a wavefront collision, by making the 6 direction signal out the same as the signal in. The navigation vectors then alternate between two possible frames, where the one added is an 180 degrees out of phase reflection that point the other way, repel instead of attract. At a distance an avoid is not as much an influence, but where the attractor is right next a place to avoid the critter nervously keeps its distance to, though may confidently charge full speed then where avoid signals become predominate it will quickly retreat again.


State 3, binary 11, Inactive, Nonfunctional
A logic state that equals State 1 plus State 2, which are opposites of each other therefore cancel each other out. This sets the attractor location initiating propagation to also repel, which stops all propagation everywhere. Critter is then most confident by staying motionless.

The room-preferring (but not arena-preferring) place cells are addressed by the room angle by converting the Radian amount to a whole number (such as 0-7 or 0-15) then adding to the serialization by multiplying by power of two for appropriate bit position. The RAM data stored at each memory address contains activity levels (associated bit is 0 or 1) for 6 sectors hexagonally at each place mapped by the place cell memory/network. To these 6 bits are added 1 data bit that is set for behavior to make that place attract and 1 data bit that is set for behavior to make that place repel, avoid. This makes 8 bits of data per RAM address, one data byte per each hexagonally located place on the place cell map. When a food pellet is known to be inside a shock zone the place is set to both attract and avoid, which cancels place cell discharge in the six sectors at that location. The attractor location will resume signaling after the avoid bit is reset to 0, turned off.

Grid cells are expected to be part of the system that provides the rotation (such as to cue card on wall) and translation (distance traveled over time, dead-reckoning deduced position) signals for locating itself on the place cell network map. For computer modeling purposes rotation and translation are here provided by the already program calculated X,Y and rotation of everything in the environment including itself. The computer model then assumes that the in-silico critter has a computer accurate reading of exactly where it is located at any timestep in its lifetime.  This is the starting benchmark for models of the grid cell related system where there is the least amount of biological detail but greatest amount of calculation precision. It is not necessary to be computer precise, "close enough" still makes a useful navigation system. It is here best to start with rotation and translation signals free of errors that would otherwise show up in testing of the place cell memory system alone.

See:
Dynamic Grouping of Hippocampal Neural Activity During Cognitive Control of Two Spatial Frames.
Eduard Kelemen and André A.Fenton (2010)
PLoS Biol 8(6): e1000403. doi:10.1371/journal.pbio.1000403
http://www.plosbiology.org/article....1000403

Arena video:
http://www.plosbiology.org/article....03.s014

Brain scan reveals out-of-body illusion
http://www.sciencedaily.com/release....107.htm


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The theory of intelligent design holds that certain features of the universe and of living things are best explained by an intelligent cause, not an undirected process such as natural selection.

   
Jim_Wynne



Posts: 1208
Joined: June 2006

(Permalink) Posted: May 03 2015,10:36   

Quote (GaryGaulin @ May 03 2015,08:22)
State 2, binary 10, Avoid
A place to avoid can cancel signal propagation of a nearby place that is attracting using the in/out pattern that produces a wavefront collision, by making the 6 direction signal out the same as the signal in. The navigation vectors then alternate between two possible frames, where the one added is an 180 degrees out of phase reflection that point the other way, repel instead of attract. At a distance an avoid is not as much an influence, but where the attractor is right next a place to avoid the critter nervously keeps its distance to, though may confidently charge full speed then where avoid signals become predominate it will quickly retreat again.

How does your "theory" account for the fact that you're incapable of learning anything about English composition?

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Evolution is not about laws but about randomness on happanchance.--Robert Byers, at PT

  
GaryGaulin



Posts: 5385
Joined: Oct. 2012

(Permalink) Posted: May 03 2015,18:15   

Quote (Jim_Wynne @ May 03 2015,10:36)
Quote (GaryGaulin @ May 03 2015,08:22)
State 2, binary 10, Avoid
A place to avoid can cancel signal propagation of a nearby place that is attracting using the in/out pattern that produces a wavefront collision, by making the 6 direction signal out the same as the signal in. The navigation vectors then alternate between two possible frames, where the one added is an 180 degrees out of phase reflection that point the other way, repel instead of attract. At a distance an avoid is not as much an influence, but where the attractor is right next a place to avoid the critter nervously keeps its distance to, though may confidently charge full speed then where avoid signals become predominate it will quickly retreat again.

How does your "theory" account for the fact that you're incapable of learning anything about English composition?

I was totally exhausted from going over the writing a few hundred times yesterday, but I was too excited to sleep. Code I thought I would need to add is no longer needed. I did though fix the grammar in that paragraph, shortly after posting it.

I'm now seeing the complex skittish behaviors I observe in wild animals like squirrels, which likewise noticeably alternate between two states/frames that approach and avoid a moving human offering them a treat. There is no circling in orbit around food and other behaviors that would indicate the network added (what's more like) a physics model of gravity or guided missile type feedback. This critter gets noticeably agitated by the two streams of conflicting information. If it had a language center then I would expect it to be swearing up a storm.

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The theory of intelligent design holds that certain features of the universe and of living things are best explained by an intelligent cause, not an undirected process such as natural selection.

   
k.e..



Posts: 5432
Joined: May 2007

(Permalink) Posted: May 04 2015,04:00   

Quote (GaryGaulin @ May 04 2015,02:15)
Quote (Jim_Wynne @ May 03 2015,10:36)
Quote (GaryGaulin @ May 03 2015,08:22)
State 2, binary 10, Avoid
A place to avoid can cancel signal propagation of a nearby place that is attracting using the in/out pattern that produces a wavefront collision, by making the 6 direction signal out the same as the signal in. The navigation vectors then alternate between two possible frames, where the one added is an 180 degrees out of phase reflection that point the other way, repel instead of attract. At a distance an avoid is not as much an influence, but where the attractor is right next a place to avoid the critter nervously keeps its distance to, though may confidently charge full speed then where avoid signals become predominate it will quickly retreat again.

How does your "theory" account for the fact that you're incapable of learning anything about English composition?

I was totally exhausted from going over the writing a few hundred times yesterday, but I was too excited to sleep. Code I thought I would need to add is no longer needed. I did though fix the grammar in that paragraph, shortly after posting it.

I'm now seeing the complex skittish behaviors I observe in wild animals like squirrels, which likewise noticeably alternate between two states/frames that approach and avoid a moving human offering them a treat. There is no circling in orbit around food and other behaviors that would indicate the network added (what's more like) a physics model of gravity or guided missile type feedback. This critter gets noticeably agitated by the two streams of conflicting information. If it had a language center then I would expect it to be swearing up a storm.

Gary what you are "seeing" is the depths of delusion. You are doing yourself no favors by not seeking professional help.

-aside- god help his psychiatrist!

--------------
"I get a strong breeze from my monitor every time k.e. puts on his clown DaveTard suit" dogdidit
"ID is deader than Lenny Flanks granmaws dildo batteries" Erasmus
"I'm busy studying scientist level science papers" Galloping Gary Gaulin

  
Jim_Wynne



Posts: 1208
Joined: June 2006

(Permalink) Posted: May 05 2015,09:29   

Quote (GaryGaulin @ May 03 2015,18:15)
Quote (Jim_Wynne @ May 03 2015,10:36)
Quote (GaryGaulin @ May 03 2015,08:22)
State 2, binary 10, Avoid
A place to avoid can cancel signal propagation of a nearby place that is attracting using the in/out pattern that produces a wavefront collision, by making the 6 direction signal out the same as the signal in. The navigation vectors then alternate between two possible frames, where the one added is an 180 degrees out of phase reflection that point the other way, repel instead of attract. At a distance an avoid is not as much an influence, but where the attractor is right next a place to avoid the critter nervously keeps its distance to, though may confidently charge full speed then where avoid signals become predominate it will quickly retreat again.

How does your "theory" account for the fact that you're incapable of learning anything about English composition?

I was totally exhausted from going over the writing a few hundred times yesterday, but I was too excited to sleep. Code I thought I would need to add is no longer needed. I did though fix the grammar in that paragraph, shortly after posting it.

I'm now seeing the complex skittish behaviors I observe in wild animals like squirrels, which likewise noticeably alternate between two states/frames that approach and avoid a moving human offering them a treat. There is no circling in orbit around food and other behaviors that would indicate the network added (what's more like) a physics model of gravity or guided missile type feedback. This critter gets noticeably agitated by the two streams of conflicting information. If it had a language center then I would expect it to be swearing up a storm.

You didn't answer the question.

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Evolution is not about laws but about randomness on happanchance.--Robert Byers, at PT

  
NoName



Posts: 2729
Joined: Mar. 2013

(Permalink) Posted: May 05 2015,10:34   

Quote (Jim_Wynne @ May 05 2015,10:29)
Quote (GaryGaulin @ May 03 2015,18:15)
 
Quote (Jim_Wynne @ May 03 2015,10:36)
 
Quote (GaryGaulin @ May 03 2015,08:22)
State 2, binary 10, Avoid
A place to avoid can cancel signal propagation of a nearby place that is attracting using the in/out pattern that produces a wavefront collision, by making the 6 direction signal out the same as the signal in. The navigation vectors then alternate between two possible frames, where the one added is an 180 degrees out of phase reflection that point the other way, repel instead of attract. At a distance an avoid is not as much an influence, but where the attractor is right next a place to avoid the critter nervously keeps its distance to, though may confidently charge full speed then where avoid signals become predominate it will quickly retreat again.

How does your "theory" account for the fact that you're incapable of learning anything about English composition?

I was totally exhausted from going over the writing a few hundred times yesterday, but I was too excited to sleep. Code I thought I would need to add is no longer needed. I did though fix the grammar in that paragraph, shortly after posting it.

I'm now seeing the complex skittish behaviors I observe in wild animals like squirrels, which likewise noticeably alternate between two states/frames that approach and avoid a moving human offering them a treat. There is no circling in orbit around food and other behaviors that would indicate the network added (what's more like) a physics model of gravity or guided missile type feedback. This critter gets noticeably agitated by the two streams of conflicting information. If it had a language center then I would expect it to be swearing up a storm.

You didn't answer the question.

That's how we know it's really Gary posting, not someone pretending to be as useless as he himself is.

Of course, given that his 'theory' is incapable of explaining or even demonstrating 'learning' in any standard, let alone Cognitive Science based, definition of the term, it's no surprise he has no ability to account for learning or its absence.

  
Jim_Wynne



Posts: 1208
Joined: June 2006

(Permalink) Posted: May 05 2015,11:16   

Quote
This is the only known Theory of Intelligent Design that provides scientifically testable predictions and models to explain the origin of intelligence and how intelligent cause works.

That's from here, with emphasis added.  

Gary, what is the origin of intelligence? You should be able to answer the question in one sentence and without reference to diagrams we've already seen.

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Evolution is not about laws but about randomness on happanchance.--Robert Byers, at PT

  
N.Wells



Posts: 1836
Joined: Oct. 2005

(Permalink) Posted: May 05 2015,13:51   

Quote (Jim_Wynne @ May 05 2015,11:16)
Quote
This is the only known Theory of Intelligent Design that provides scientifically testable predictions and models to explain the origin of intelligence and how intelligent cause works.

That's from here, with emphasis added.  

Gary, what is the origin of intelligence? You should be able to answer the question in one sentence and without reference to diagrams we've already seen.

You're just yanking his chain trying to get him to post The Diagram again, aren't you?

It's self-similar turtles, all the way down.  :)

I second the question, Gary.  What is the origin, and how is your model relevant to your answer?

  
GaryGaulin



Posts: 5385
Joined: Oct. 2012

(Permalink) Posted: May 05 2015,15:56   

Quote (Jim_Wynne @ May 05 2015,11:16)
Quote
This is the only known Theory of Intelligent Design that provides scientifically testable predictions and models to explain the origin of intelligence and how intelligent cause works.

That's from here, with emphasis added.  

Gary, what is the origin of intelligence? You should be able to answer the question in one sentence and without reference to diagrams we've already seen.

If I find a way to explain all that in one short sentence then I'll let you know, by posting it here. But otherwise I am not interested in oversimplified answers that leave all that and more to the imagination, by stating something like "Intelligence evolved."

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The theory of intelligent design holds that certain features of the universe and of living things are best explained by an intelligent cause, not an undirected process such as natural selection.

   
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