Awesome, we are finally down to a few things I need to answer - again I might answer more than once - just a heads up. I am not going to go too in depth here because there are so many things I want to get off my chest - we were talking about an article I read but this post does have some relation to this thread which is why I have placed it here. Yeah - I am not a huge fan of QM. I have also read some data that points to correlation implying causation - that tells me that there is something up with QM. To which you responded:
I should be able to dig the source up quite easily gib - no problem.
I might be very surprised as a matter of fact but nothing would surprise me these days Oh, you are probably better at statistics than I - that might be an important tidbit - I guess we might find out later - it does not bother me if I make errors only that I do not know about them.
Very, very interesting, and to think a good sense of intuition picks up these things in an instant(not literally) when traversing the world and interacting with people. Correlations are just as useful as causation when it comes to modelling the brain as we have seen.
Yeah, this is a great way to explain it. I will dig that article up so you can read it.
OK - I have a lot of other stuff to cover so I will be back later.
Before I started taking my medications, my mind was so full of thoughts I am not even sure whether I was making sense to myself - it felt like I was at the time. This post is just my thoughts from a while back - when my mind was a lot more muddled - I am not sure how much this will be worth but I am going to put it here and see what I can pick out from it that may be useful - I will pick it apart over time.
This might be encouraging of dialog. I will try my best to reverse engineer what I mean by the concept of meaning(this was a first pass attempt):
The whole is greater than the sum of its parts. {Being able to see similarity in otherwise unrelated topics} Using the knowledge acquired throughout life to compare with newfound knowledge to either instantly get some meaning or with thought, work it out. The total sum of experience from birth to the present. {Just a tool to perform step one} By asking something abstract and only using the accumulated information in ones memory it is possible to derive meaning from anything. {accumulated information being the total sum plus the newfound}
abstract impression = total sum[derivativeSimilarities]/newfound
integrated answer = meaning
I imagine this being a driver to our imagination which may lead to the ultimate question/s and answer/s. I am guessing that seeds of meaning initiate when the quotient is obtained from derivativeSimilarities and newfound. Skipping a step or two we can use an integrated impression to drive a question for further knowledge. The propagation of meaning can then be drawn from the answer and question laterally. It also looks like this reverse engineers itself; in some obscure fashion. So that covers the stuff that is kind of baffling me and I think I am making some sort of mistake and that is why I am not getting the result I want.
Classically:
When an equal amount is taken from equals, an equal amount results.
meaning = meaning
Analogy on the other hand is just confusing; how we can somehow end up with an invention based upon some partial derivative knowledge.
If on the other hand I go with my mixing of concepts here, then it would possibly be where the concepts intersect or correlate.
Right on with the ambiguity in that we seem to use a lot of interpretation to derive meaning. So if interpretation is where meaning lies then there seems to be more than one version of truth. The direction on the other hand may arrive at the definite like 1 + 1 = 2. Mathematically I think it is like a system of equations where each equation or part of the system has the flexibility to be just a little different from its counterpart peers ending with some sort of normalization in the system.
The resulting normalization being the derivative meaning. Do you think that there is a limit to the representations anyway? ; for each individual? ; Meaningful ones I mean! I am thinking that meaning is derived in some purely mental manner but I can see how this could be different depending on the factors involved ending up at such conceptual states like; did the tree in the woods really fall if no-one was there to witness it?
I am guessing that meaning is somehow intertwined with the driving forces of life itself; possibly a bunch of quanta that somehow link. Apparently in the “quantum world” - correlation can imply causation. The question is intended to be of the open type(ambiguous). Maybe I don’t even understand the meaning of the question that I seek the answer to. My attempt at some poorly delivered humor. Maybe the question and answer are circular dependencies.
I am not even sure how much of these thoughts I agree with anymore but I needed to post it so that when I read through this thread again I might interpolate the information into a useful place in my mind. Yes, it is related to meaning as opposed to brain and mind - but meaning is related to brain and mind too.
Do not start with that premise because that is not true and that would lead you towards a wrong direction. Both are different entities and execute different works too.
The methodology of working out is very difficult. There are some certain means of actual physical verification but very demanding in nature, and certainly not within everyone’s reach. Yes, one can get somewhat closer the reality by philosophy, yet not exactly there.
As far as their work is concerned, brain provide collective inputs of all the sense organs to the mind, mind analyze that provided information and if necessary, it asks brain to give command to some body parts as to suit mind.
I am absolutely in no hurry and have no expectations at all - my suggestion is to only respond to that which talks to you - if that is all of it then so be it. If it is none of it then so be it. I am certain that you will respond to some of it though.
I was just so damn inspired that I really went crazy with it.
I do try my best to exhaust as many pathways as possible . . .
Goodness no, that is not my stance - I firmly believe the mind and body are two different things - to me they are connected. That was an invitation for those that believe otherwise - to which they still do not have good proof. The proof that I see is that the brain responds to the mind.
Exactly.
Thank you zinnat. Do we call you zinnat or sanjay?
Sanjay!!! I haven’t seen you in these parts for ages. I was told you couldn’t stand Turd so you left. Well, I haven’t seen him around these parts in a while, so welcome back.
He is just a naughty and silly child to me who thinks very high of himself. I took a pause because of some personal reasons. I had some serious disagreements with my employer thus quit his job. As i have to earn money so i stared trading in stock market as i am familiar with it since long. So, i was busy in all that stuff. Posting at a philosophy forum is a serious thing to me, not a time pass. And, I am not a kind of multitasker by nature and cannot focus on many things at one time thus stopped posting. That is all. Even now i would have to very selective.
For the sake of brevity, I’m going to respond with summarized responses to whole posts.
^ This post here–good intro–but it does not yet get into how to answer the question: how do we scan the brain to find pattern recognition? By pattern recognition, we are talking about how the mind recognizes objects or properties or events based on how well it matches similar patterns from past experience. What would we be looking at in the brain–via an fMRI scan, for example–such that we could say: ah, the brain is recognizing a pattern in its sensory input.
Absolutely! I believe the brain is a physical system subject to the laws of cause and effect like any other system. Some would like to say that quantum indeterminism is at work in the brain, and that special mechanisms in the neurons of the brain are able to take this indeterminism and amplify it to the level of whole neurons… so instead of only being able to observe quantum indeterminism at the level of particles, we should be able to observe it at the level of neurons… and since neurons are like amplifiers of behavior (i.e. a few neurons firing can determine the actuality or suppression of a specific behavior), they say that this quantum indeterminism can account for behavior as well; the idea they are aiming for in the end is to explain free will. If it feels like we choose our behavior out of free will, it’s because it is free–that is, non-deterministic–and that indeterminism starts at the sub-atomic level with particles inside neurons.
But until the science is out on this, I’m placing my bets on ordinary mechanics as the best account for the functions of the brain. I have no problem with the idea of indeterminism at the level of particles, but I’m holding by breath on quantum consciousness.
Well, that’s more or less what I was getting at when I said we figure out the algorithms computers are to run based on introspecting our minds. If we look at the history of the development of computers and the history of the development of the brain sciences, we see that they go hand in hand; the 50s were the golden decade for the brain sciences, and only a decade later we saw the emergence of computers. The key principle that was carried over from the brain science to computer design was the way in which the brain seemed to process information as electric signals travelling down the axons of neurons and either being propagated to other neurons or being blocked by inhibiting neurons. From this, we got wires with electric signals travelling down their length and being propagated to other wires through logic gates or being blocked by different logic gates. (The brain also has chemical signals that allow the signal to jump across the synaptic gap, but that wasn’t carried over to computers). That seems to be the general principle underlying more or less all circuit design. However, when it comes to designing specific circuits which are to carry out specific functions, we fall back on introspection. Adders, for example, are based on the principle “long addition” (I think it’s called). It’s the principle of adding two large numbers by adding consecutively each digit in each number. So the units get added first, then tens, then the hundreds, and for each addition, we carry the 1 if we have to. We didn’t get this method by studying the brain under a microscope, we simply took a moment out to think (i.e. introspect) and imagined doing addition in the way. Since we are satisfied that this method is algorithmic (i.e. it works flawlessly), we figure: let’s apply it to design a computer circuit that carries out addition. So now computers all over the world have a little circuit inside them that gets recruited any time we need to do addition. It even has a component for carrying the 1. Who knows if this circuit looks anything remotely like the neural circuitry in the brain that comes into play when we do long addition in our heads–it might be completely different–so I would agree that we model computer circuitry after the algorithms we construct in our minds rather than the neural designs the brain is built on. Not that the latter are wrong or substandard, but it seems to me that if the brain is design to (at least as one of its functions) come up with algorithms for solving certain kinds of problems (and these algorithms we arrive at consciously via introspection), it is the results of this process that we want to apply to computer design, not the machinery used to produce those results. The machinery is built to come up with algorithm, but that doesn’t mean it is running algorithms when coming up with those algorithms (certainly not necessarily the most optimal algorithms). The brain is more often based on heuristics than algorithms, so we have to be careful when we attempt to model computers after the brain. The general principle of neurons being used to process information is a good one to model circuit design after, but when it comes to which specific algorithms to build into the circuit, we are better off modeling that after what we come up with using our imaginations and intelligence.
What does it take to form an opinion? You mean, what are the steps in building one? Like a recipe for baking a cake? God, how am I supposed to know?! But I do think a motive is required, a desire for some kind of outcome that serves your own interests. If I work for the military, my livelihood depends on war. It keeps me in business. So my opinion may be that war is sometimes necessary. If I were a school teacher or a stay home dad, on the other hand, fearing for the lives of the children I oversee, I may be steadfast against war. I think that our personal interests and biases dictate our opinions far more than logic and rationality. We build the logic and rationality underlying our opinions after the fact. Before that, we (unconsciously) assess what would be the best and most closely within reach outcome and decide right then and there what opinions to hold. Then we go to work forming arguments and justifications for them.
About evolutionary and configuration emotions: if I understand it correctly, an example of an evolutionary emotion might be fear of snakes. Is this right? We may be born with the neural wiring already in place to feel fear upon seeing a snake. ← We inherit that from our evolution. But configuration emotions would be more like emotions that are built within us by some kind of conditioning or socialization, something that could be wholly new and unique to a particular culture (kind of like abstract concepts, like wormholes for example, which we aren’t born with and require teaching). Is this what you mean? And if so, what would be an example?
Waaay over my head.
Don’t really have much to say about this one, except that I’d make a terrible statistician.
I’m afraid this one’s over my head too, encode. But I do sense that this is at the core:
It reminds me of the Hegelian dialect: thesis → antithesis → synthesis. The synthesis will always derive newer higher meaning. ← Is this within the ball park?
Which of course with the help of other available data be transformed even more. As you can see this system allows for concurrent formation and recognition in the parsers and on to semantics. Any system this complex needs to build itself.
FFRL allows for harmony between formations and recognition by using the self building K Parser and self building Semantic Analysis.
The first bot can help me build the K Parser and a lot of Semantics. The first bot may be able to help me with a lot of other stuff. What I need the first bot to generate is a whole bunch of sets for the K Parser . . .
Words in this BOT have heirarchies as follows:
Incept → Known - > Actual Type → [Abstraction Starts Here]
When the bot chooses the structure it wants to work from it goes something like this:
Level 1 - Incept, Incept, Incept . . .
Level 2 - Known, Incept, Known . . .
Level 3 - Noun, Verb, Known . . . or Incept, Verb, Known . . . so still with Incepts and Knowns but has some types.
Level 4 - Noun, Verb, Noun . . . or some other fully typed convention.
Level 5 - One of the S-V-O-Adj-Adv-N conventions.
Level 6 - Some form of higher abstraction.
Level 7 - Preferably the ultimate level of abstraction.
So with the mind intro out of the way let us focus on a scan. No need to respond to this post because I need to tie a few things together in a simpler way.
It might seem strange to be looking at intermediate information before the simple explanations but it is the best way for me to explain it . . .
That is a great idea actually gib.
Sneak preview . . .
DTI Color Map
OK . . . this will take a few passes to get right. The mind and brain work differently - that is the truth for this pass.
In this pass let us briefly cover a few things.
The Synapse
In the brain we need to look at synaptic connections. It is widely accepted that the synapse plays a role in the formation of memory.
As neurotransmitters activate receptors across the synaptic cleft, the connection between the two neurons is strengthened when both neurons are active at the same time, as a result of the receptor’s signaling mechanisms.
fMRI
Functional magnetic resonance imaging or functional MRI (fMRI) measures brain activity by detecting changes associated with blood flow. This technique relies on the fact that cerebral blood flow and neuronal activation are coupled. When an area of the brain is in use, blood flow to that region also increases.
The primary form of fMRI uses the blood-oxygen-level dependent (BOLD) contrast, discovered by Seiji Ogawa.
As we can now tell there are different forms of fMRI - we start at a low resolution:
These fMRI images are from a study showing parts of the brain lighting up on seeing houses and other
parts on seeing faces. The ‘r’ values are correlations, with higher positive or negative values
indicating a better match.
Statistics
Now we wonder how we can get higher resolution and mathematics holds the key as usual: Statistical inference uses mathematics to draw conclusions in the presence of uncertainty. There is much uncertainty in low resolution imaging.
Tensors
When using Diffusion MRI as opposed to fMRI we can apply Diffusion tensor imaging (DTI) which is an MRI technique that enables the measurement of the restricted diffusion of water in tissue in order to produce neural tract images instead of using this data solely for the purpose of assigning contrast or colors to pixels in a cross sectional image.
Lets start with low resolution DTI:
Visualization of DTI data with ellipsoids.
A more precise statement of the image acquisition process is that the image-intensities at each position are attenuated, depending on the strength (b-value) and direction of the so-called magnetic diffusion gradient, as well as on the local microstructure in which the water molecules diffuse.
The principal application is in the imaging of white matter where the location, orientation, and anisotropy of the tracts can be measured. The architecture of the axons in parallel bundles, and their myelin sheaths, facilitate the diffusion of the water molecules preferentially along their main direction. Such preferentially oriented diffusion is called anisotropic diffusion.
Tractographic reconstruction of neural connections via DTI
Diffusion MRI relies on the mathematics and physical
interpretations of the geometric quantities known as tensors.
Only a special case of the general mathematical notion is relevant to imaging, which is based on the concept of a symmetric matrix. Diffusion itself is tensorial, but in many cases the objective is not really about trying to study brain diffusion per se, but rather just trying to take advantage of diffusion anisotropy in white matter for the purpose of finding the orientation of the axons and the magnitude or degree of anisotropy.
Matrices
The following matrix displays the components of the diffusion tensor:
Positron-emission tomography (PET) is a nuclear medicine functional imaging technique that is used to observe metabolic processes in the body. The system detects pairs of gamma rays emitted indirectly by a positron-emitting radionuclide (tracer), which is introduced into the body on a biologically active molecule. Three-dimensional images of tracer concentration within the body are then constructed by computer analysis. In modern PET-CT scanners, three-dimensional imaging is often accomplished with the aid of a CT X-ray scan performed on the patient during the same session, in the same machine.
Brain PET-MRI fusion image
PET scans are increasingly read alongside CT or magnetic resonance imaging (MRI) scans, with the combination (called “co-registration”) giving both anatomic and metabolic information (i.e., what the structure is, and what it is doing biochemically). Because PET imaging is most useful in combination with anatomical imaging, such as CT, modern PET scanners are now available with integrated high-end multi-detector-row CT scanners (so-called “PET-CT”).
Oh, you are probably better at statistics than I - that might be an important tidbit - I guess we might find out later - it does not bother me if I make errors only that I do not know about them.
But I do think a motive is required, a desire for some kind of outcome that serves your own interests. If I work for the military, my livelihood depends on war. It keeps me in business. So my opinion may be that war is sometimes necessary. If I were a school teacher or a stay home dad, on the other hand, fearing for the lives of the children I oversee, I may be steadfast against war. I think that our personal interests and biases dictate our opinions far more than logic and rationality. We build the logic and rationality underlying our opinions 
