No, Brains Have Nothing Like a Large Language Model (LLM)

Quanta Magazine is a widely-read online magazine with slick graphics. On topics of science the magazine again and again is guilty of the most glaring failures. Quanta Magazine often assigns its online articles about great biology mysteries (involving riddles a thousand miles over the heads of PhDs) to writers who lack even a bachelor's degree in biology, and who may also lack any history of writing very much about biology. Often it will assign such articles to be written by people identified as "writing interns."  The articles at Quanta Magazine often contain misleading prose, groundless boasts or glaring falsehoods. I discuss some examples of such poor journalism in my posts here and here and here and here.

The writers at Quanta Magazine often sound like the most credulous pushovers for scientists making dubious boasts. They often seem like the science journalists depicted below:

A recent  example of a puff-piece article in Quanta Magazine is its fawning article entitled "The Polyglot Neuroscientist Resolving How the Brain Parses Language." The article title is a very misleading one. It is not brains that parse language. It is people who parse language. Parsing language (interpreting what someone meant upon hearing or reading something) is an example of a very high-level mental faculty.  Neuroscientists have no credible tale to tell of how a brain could produce such a faculty. 

The puff piece article is written by someone identified as a "writer and filmmaker," who has written many articles at the Quanta Magazine dealing with topics related to AI and technology, but almost no articles at the site relating to psychology or neuroscience.  What we get is an article devoted to glorifying neuroscientist Ev Fedorenko. You can tell what a "going gaga" scientist glorification affair is occurring by the fact that the article has five huge photos of Fedorenko, each of which fills up my computer monitor. 

We have this extremely misleading statement by the neuroscientist, not matching anything ever found in a brain:

" 'You can think of the language network as a set of pointers,'  Fedorenko said. 'It’s like a map, and it tells you where in the brain you can find different kinds of meaning. It’s basically a glorified parser that helps us put the pieces together — and then all the thinking and interesting stuff happens outside of [its] boundaries.' ”

The brain has no maps, and it has no pointers. I know pointers well, having used them extensively when I was a C programmer early in my programming career. A pointer is a variable that stores the address where some data is stored. Brains have no addresses, and nothing corresponding to a programming variable. So in a brain there can be nothing like a pointer. 

The article has a reference to a scientific paper by Fedorenko, one entitled "The language network as a natural kind within the broader landscape of the human brain." The paper says, "In this Review, we discuss brain areas that are specific to language —what we refer to as the language network — and position them in relation to perception, motor planning and cognition (Fig. 1)." There are no regions in the brain "specific to language" in the sense of being able to parse language. 

The paper announces that it will back up such claims largely by appealing to brain scan studies, saying, "We primarily draw on fMRI data from studies that have relied on the individual-subject functional localization approach14,19 (Box 1), which was essential in clarifying the distinctions discussed.." We then have in Figure 1 an extremely dubious visual showing five brains. We have some "function localization" claims:

• One brain visual has a small fraction of it colored blue, and this is labeled as the "perception" area of the brain. 
• Another brain visual has a very small fraction of it colored red, and we are told that is the "motor planning" area of the brain. 
• Another brain visual has five parts of it colored purple, and we are told that this is the "language" areas of the brain. 
• Another brain visual has quite a few parts of it colored green, and we are told that this is the "knowledge and reasoning" areas of the brain. 
• Another brain visual has quite a few parts of it colored green, and we are told that this is the "intended meaning" areas of the brain. 

People have been making these kind of functional localization claims about the brain for almost 200 years, and almost always the claims have been very dubious. For example, below is an illustration from the beginning of the 1834 book A System of Phrenology by George Combe. Notice how the brain areas have little numbers next to them, with the bottom legend explaining the claims made about localization of function in the brain. 

What basis does Fedorenko have for the brain function area maps in her paper, Figure 2, one rather reminding you of the phrenology image above? She says her basis is brain scan data.  The Supplementary Data part of the paper promises that if you click on a link you will get the data that was used to generate the brain function area maps. Following the links takes you to a little page that is almost worthless for inspecting data, as it involves a .zip file consisting of files in an .nii format that the average person will be unable to load or read. Consequently it is all but impossible for anyone to check the evidence basis for Fedorenko's brain function area maps, which should not be regarded as reliable. Neuroscientists dramatically disagree with each other when they produce such brain function area maps, which typically fail to have a sound evidence basis. 

A figure on page 294 of the paper  gives us the bar chart below: 

The purple bars at left are probably incorrect

The scale on the left shows us that the bars refer to fMRI percent signal changes in different regions of the brain during different activities. You should note well that the largest bars show a variation of only 2%. For almost all of the activities listed, the percent signal change is less than 1%. On average the change in brain signal strength is merely about 1 part in 200. A change that small is no real sign of brains working harder during some cognitive activity. We might expect that mere chance variations would produce differences that small. 

Except for the two purple bars on the left-most edge, the diagram is consistent with what I have often stated on this blog. For example, in my post "Brain Imaging Shows No Appreciable Neural Correlates of Memory Activity," I quoted quite a few studies showing a variation of only  1 part in 200 when people had their brains scanned by fMRI scanners while they were doing various memory-related activities. I noted that so small a change fails to provide any good evidence of brains causing mental activities, as we might expect a 1 in 200 fluctuation in brain activity to occur by chance, even if brains don't make minds. 

But what about the purple bars on the left of the chart? What is the basis for the claim being made in the graph that during sentence comprehension there is up to a 2% change in brain signal strength? We fail to get a justification for the data shown. The references in the paper include some papers referring to sentence comprehension. But none of them seem to back up the claim above. Specifically:

• We have a reference to a paper "Cognitive control and parsing: Reexamining the role of Broca’s area in sentence comprehension." It makes no claim about percent signal changes during sentence comprehension. 
• There's a reference to a paper "Retrieval and Unification of Syntactic Structure in Sentence Comprehension: an fMRI Study Using Word-Category Ambiguity." It's behind a paywall, and its abstract makes no claim about percent signal changes. 
• There's a reference to a paper "The cortical language circuit: from auditory perception to sentence comprehension."  It's behind a paywall, and its abstract makes no claim about percent signal changes. 
• There's a reference to a paper "fMRI reveals language-specific predictive coding during naturalistic sentence comprehension." The paper does not make any claim about a percent signal change during sentence comprehension. 
• There's a reference to the paper "Sentence complexity and input modality effects in sentence comprehension: an fMRI study." It's a study involving only 20 subjects, and does not claim in the main body of its text to have detected any percent signal change of 1% of higher. But there is a footnote in which the authors say that after doing some dubious-sounding fiddling with the data they got some kind of 1% difference of some type. We cannot have much confidence in such claim, as it stated only in a footnote. 
• There's a reference to the paper "Form and Content: Dissociating Syntax and Semantics in Sentence Comprehension." It does not make a claim about a percent signal change. 
• There's a reference to a paper "Location of lesions in stroke patients with deficits in syntactic processing in sentence comprehension." We can ignore it, because the issue is how much normal brain signals change during sentence comprehension.
• There's a reference to a paper "Time course of semantic processes during sentence comprehension: an fMRI study." It does not make a claim about a percent signal change. 

Rather than relying on the references Fedorenko has given, we can follow the alternate approach of doing a Google image search using the phrase " 'percent signal change' + ' sentence comprehension' ." This gives us papers such as these:

• The paper here involving sentence comprehension indicates a percent signal change of less than 1 part in 200 (less than half of a percent). 
• The paper here ("Neural correlates of syntactic movement: converging evidence from two fMRI experiments") reports a relatively large percent signal change of about 1 part in 100 for people listening to sentences. But the study group sizes are so small (involving only 11 subjects for one experiments, and 10 subjects for another experiment) that the paper cannot be counted as good evidence for anything. 
• The very low-quality paper here ("Neural correlate of the construction of sentence meaning") co-authored by Fedorenko must be disregarded because it reported a "percent signal change" based on EEG readings rather than fMRI readings, because it used a sample size of only 6 epilepsy patients with implanted electrodes, and also because of the unreliability of looking for percent signal changes in the brain waves of seizure-prone patients, whose brains produce all kinds of unpredictable EEG spikes. 
• The paper here ("Top-down and bottom-up contributions to understanding sentences describing objects in motion")  used an almost equally poor study group size of 12 subjects, and found a percent signal change of .05 percent, 1 part in 2000. 
• The paper here ("Language processing in the occipital cortex of congenitally blind adults") used one too-small study group size of 9 blind adults and another possibly halfway-adequate study group size of 22 control subjects with normal vision. Its Experiment 1 involving language processing found a percent signal change of less than .1 (less than 1 part in 1000) for the 22 control subjects. Another experiment involve language processing found a percent signal change of less than .5 (less than 1 part in 200) for the 22 control subjects.
• The paper here ("Brain activity associated with selective attention, divided attention and distraction") finds about a 1% percent signal change in the auditory cortex during language processing. But the study group size is an unimpressive 15 subjects. This auditory cortex region of the brain is not part of the "language processing" area claimed by Fedorenko. In her paper she refers to some regions of the brain and says, "These areas are distinct from the language network as well as from general-purpose sensory and motor areas, such as the primary auditory or primary motor cortex," apparently indicating that what she thinks is a "language network" in the brain is something outside of the auditory cortex. 

Typically there is no test/retest reliability when doing these little studies involving only 15 or 20 or 25 subjects. Robust evidence would only come from a much larger study group size. The New Scientist story below tells us that thousands of participants are needed for studies like these:

The purple bars on the graph shown above are very probably incorrect. Scientific papers documenting brain scanning during language comprehension do not show any robust evidence of a 1% or 2% change in brain activity during sentence comprehension. And there is no sound evidential basis for Fedorenko's diagram claiming to show the location of five language areas of the brain. 

As discussed here, a recent study indicated that 40% of MRI signals do not even correspond to brain activity, which further undermines the knowledge boasts that  Fedorenko has made, and provides another reason for disbelieving in the accuracy of her brain activity maps.  We read this: "Researchers at the Technical University of Munich (TUM) and the Friedrich-Alexander-University Erlangen-Nuremberg (FAU) have found that an increased fMRI signal is associated with reduced brain activity in around 40% of cases. At the same time, they observed decreased fMRI signals in regions with elevated activity." This is the kind of finding that should make us disbelieve Fedorenko's fMRI-based claims of a brain "language network." 

Link

The puff piece article in Quanta has a "softball questions only" interview with Fedorenko in which she states this:

"There’s a core set of areas in adult brains that acts as an interconnected system for computing linguistic structure. They store the mappings between words and meanings, and rules for how to put words together. When you learn a language, that’s what you learn: You learn these mappings and the rules. And that allows us to use this 'code' in incredibly flexible ways."

There is no robust scientific basis for these imaginative claims. To the contrary, the most powerful microscopes have examined very much brain tissue from very many still-living people and very many very recently deceased people, and no one has found the slightest trace of any sentence, word or letter stored in a brain. 

Later on Fedorenko states, " Then the language network parses that, finding familiar chunks in the utterance and using them as pointers to stored representations of meaning." Excluding the merely genetic chemical representations in DNA, there is zero evidence for any such "stored representations of meaning" anywhere in the brain.  Later she kind of gives away the speculative nature of her claims, by saying "there may well be cells that respond to particular aspects of language."  Note the use of "there may well be" rather than "there are."   

Fedorenko offers as evidence for this claim the preprint "Modality-Specific and Amodal Language Processing by Single Neurons."  It is a "Jesus in my toast" exercise in noise-mining. Recordings of neuron firings were taken after 1400 invasive microwire electrodes had been implanted in the brains of 21 very sick patients with the worst types of epilepsy. The authors tried to find some neurons that fired more often when certain words were spoken. Because neurons fire between 1 and 200 times per second, any such exercise will always be able to find some neurons that fired more often when certain words were spoken. It is misleading to call such a thing "selectivity" as the paper did. Similarly, if I set up a computer program to try to correlate the passing of cars outside my house and the speaking of words on my TV set, and let the program run long enough, I will probably be able to find that certain words were spoken more commonly on my TV set when a car passed in front of my house.  That would be mere silly noise-mining, and that is all that is going on in this preprint, which fails to provide any decent evidence of any neuron responses to language different from what we would expect from chance variations, giving 1400 microwires implanted in brains. 

Noise-mining studies like this raise grave moral concerns about the reckless research endangerment of very sick epilepsy patients.  The sickest of epilepsy patients often have electrodes implanted for evaluation of where surgery should be done to reduce their symptoms. But such electrodes are usually not the microwire electrodes used for experiments like this. The deep implanting of such microwire electrodes in brains (70 microwires per patient for this study) has serious risks that are not medically justified, such as a risk of brain bleeding.  We should doubt any claim to have got any adequate degree of "informed consent" from the seizure-racked people who have these kind of deep microwire electrode implants. 

A scientific paper tells us, "Sixty-five years after single units were first recorded in the human brain, there remain no established clinical indications for microelectrode recordings in the presurgical evaluation of patients with epilepsy (Cash and Hochberg, 2015)." In other words, there is no medical justification for implanting microelectrodes or microwires in the brains of epilepsy patients. Complications from the insertions of such electrodes may include death, with two deaths reported here. I consider the exploitation and endangerment of sickest epilepsy patients in these type of poorly designed noise-mining experiments to be a serious moral scandal. 

Does it work like this?

For much more on the topic of why most subjects in neuroscience experiments do not understand the risks they are taking, read my post here. Epilepsy patients requiring surgery are often those who cannot read well (because of learning delays caused by their very frequent seizures), and who will not well-understand any jargon-filled form they are asked to sign. Typically neuroscientists doing electrode implant experiments with epilepsy patients fail to provide in their papers the informed consent form used, and also fail to describe whether special measures were taken to make sure those getting the microwire electrode implants really understood the risks of participating in an experiment of this type. 

We should laugh at Fedorenko's answer when she is asked whether there is an LLM (Large-Language Model) inside the brain, and she replies "pretty much." Nothing like that exists in the brain. An LLM or Large Language Model is a gigantic structure of data, computer programming software and data processing software built after some big server farm (consisting of very many individual computers) crunches data gobbled up by crawling the Internet, scooping up the contents of millions of web pages. That does not correspond to anything in a human brain. 

The idea of a language-parsing ability in a brain seems implausible when you consider that human brain anatomy has not changed in more than 20,000 years, but the main human languages (such as English) are less than 3000 years old. 

It is commonly claimed that the left half of the brain is needed for language. But if you read my series of posts labeled "loss of left half of brain," using the link here, you will find many cases that defy such a dogma.  For example, you will read of a case described like this: "He exhibited no lack of intelligence, yet after his death it was discovered that his left brain was practically destroyed and replaced by a watery substance." And you will read of how Beth Usher could still tell all of her "knock-knock" jokes just after the left  half of her brain had been removed to treat intractable seizures. You will read that on page 109 of a paper we read of three other cases of the removal of the left half of the brain, and we read that "speech and verbal comprehension were present immediately after left hemispherectomy in all three cases." The same post describes good verbal comprehension in patient E.C. after the left half of his brain was surgically removed. 

In a scientific paper ("Why Would You Remove Half a Brain? The Outcome of 58 Children After Hemispherectomy −−The Johns Hopkins Experience: 1968 to 1996") we read about how surgeons at Johns Hopkins Medical School performed fifty-eight hemispherectomy operations on children over a thirty-year period. Eleven of these children had the left hemisphere of their brains removed; most of the rest had the right hemisphere of their brains removed.  The paper states this:

"Despite removal of one hemisphere  [i.e. one half of the brain], the intellect of all but one of the children seems either unchanged or improved....Although there have been major concerns about loss of language after left hemispherectomy, all eleven of these children have regained virtually normal language....It is tempting to speculate, that the continuous electrical activity of these severely dysfunctional hemispheres interferes with the function of the other, more normal hemisphere. This might explain why motor function improves after hemispherectomy and why language recovers after removal of the dysfunctional left hemisphere, but does not seem to fully transfer before surgery. Perhaps it also partially explains intellectual improvement in these children after removal of half of the cortex. We are awed by the apparent retention of memory after removal of half of the brain, either half, and by the retention of the child’s personality and sense of humor."

Pareidolia Progress: Neuroscientists Get Better and Better at Seeing Things in the Brain That Are Not There

 Our neuroscientists are getting nowhere in trying to show that there is a neural basis for human memory or human thinking. But they have something they can rely on to help hide their lack of progress:  pareidolia. Pareidolia is when you see patterns that aren't really there, like some guy examining his toast every day for years, and then one day saying, "I finally see the face of Jesus in my toast."  A scientist conjuring up some pareidolia can make a nice-sounding progress report when no real progress has been made. I describe some examples of this in my post "Scientists Have a Hundred Ways to Conjure Up Phantasms That Don't Exist." 

There are several factors driving an increase in the ability of neuroscientists to make these pareidolia reports of seeing things in a brain that are not there. They include the following:

(1) Technological improvements have made it more and more easy for neuroscientists to use microelectrodes to record activity from individual neurons. This type of invasive brain intervention yields much more data than you get from the non-invasive technique of reading brain waves by having someone wear an EEG cap with electrodes. Neurons fire randomly at a rate between about 1 time per second and about 300 times per second. Being able to get data from all the individual firings of a large set of neurons randomly firing is almost the perfect seed bed for pareidolia.  The more random, rapidly changing data you get, the easier it is to do noise-mining pareidolia in which you seek for patterns you are eagerly hoping to find. 

(2) Advances in computer programming and AI make it easier-than-ever to create computer programs that manipulate gathered brain data in arbitrary ways. Easy-to-use languages such as Python make it easier for neuroscientists who are not professional programmers to write such programs. AI tools such as ChatGPT allow the creation of artificially generated code that can be used as part of such programs. The easier it is to produce such computer programs, the easier it is to do the kind of "keep torturing the data until it confesses" work that is often the basis of pareidolia, or a pillar of pareidolia. 

(3) Advances in so-called artificial intelligence (AI) and the public accessibility of such techniques make it easier than ever to do noise mining or data mining to extract or construct patterns or claimed patterns that a human might night never be able to find or that humans would never say existed if the humans made a simple, straightforward examination of the data. 

We have a recent example of neuroscientists seeing things that are not really there is the paper "Dynamic coding and sequential integration of multiple reward attributes by primate amygdala neurons" which you can read here. We have two neuroscientists claiming to have found that "neurons frequently signalled reward probability in an abstract, stimulus-independent code." They provide no robust evidence for this claim. To qualify as decent evidence, a study like theirs would have required a study group size of at least 15 subjects. The study group size they used was the way-too-small size of only two subjects, both monkeys. 

Below from Figure 4 of the paper is some of the data gathered from monitoring several hundred neurons of the two monkeys, as they were either resting or presented with some kind of cue. 

The little blips are neuron firing or neuron firing spikes going on while these cues were presented. A human looking at this data will see no pattern. But the authors played around with what we might charitably call "analysis techniques," trying to find some way to squeeze some evidence of a pattern or a code out of this neural noise. In the paper these are called "general linear models" and are given names of GLM 1, GLM 2, GLM 3, GLM 4 and GLM 5. Describing each of these "models," the authors groundlessly claimed that each of them identified a particular neuron encoding in some different way. The claims are never justified, and seem like pure imagination. 

Procedures like this almost invariably involve computer programming code that passes the data through programming loops. It's kind of like what's depicted in the visuals below. 

Normally you get an idea of how objectionable the data processing was by looking at the programming code used by the scientists. There is no excuse for any study of this failing to publish its code, as there are nowadays various platforms and web sites that make it very easy for someone to make their code publicly available online.  Typically in affairs such as this you can examine the programming code, and find some convoluted poorly documented mess that will demonstrate that the data was being monkeyed with in wild and weird ways. If, on the other hand, you were to find some clean, straightforward, well-documented code, it might be a sign of a respectable methodology. 

But often the scientists will not make their programming code publicly available. This is a strong reason for suspecting that the programming code involved is something that the scientists were embarrassed by, some programming horror they were too embarrassed to publish.  In the case of the paper discussed here ("Dynamic coding and sequential integration of multiple reward attributes by primate amygdala neurons" which you can read here), the authors have failed to make their programming code public.  We should have no confidence in any of the author's claims to have found "probability-coding neurons." but we can assume that the authors were not proud of their own coding. 

The authors are just engaging in the most groundless "Jesus in my toast" pareidolia when they make these claims:

"Amygdala neurons frequently signalled reward probability in an abstract, stimulus-independent code that generalized across cue formats. While some probability-coding neurons were insensitive to magnitude, signalling ‘pure’ probability rather than value, many neurons showed biphasic responses that signalled probability and magnitude in a dynamic (temporally-patterned) and flexible (reversible) value code. Specific neurons integrated these reward attributes into risk signals that quantified the uncertainty of expected rewards, distinct from value."

Making these claims the authors are like someone staring at 1000 photos of clouds in the sky, and finally declaring that he sees angel castles and animal ghosts. Among their procedural sins:

(1) They have not done a study with even one seventh of the study group size needed for a study like this to be taken seriously. 

(2) They have not revealed the exact details of their procedural method, because they failed to publish the programming code that their claims are dependent on. 

(3) Instead of testing a single hypothesis and declaring that it either succeeded or failed, they kept playing around with different ways of analyzing data until they found something they thought produced a publishable result. 

All claims that the authors make about finding neurons "encoding" something are spurious and groundless. Their description of the analysis algorithms they fooled around with is a description of a  tangled, tortured gobbledygook rigamarole, some "witches brew" of statistical spaghetti code shenanigans that the authors give no justification for. You could give the data they recorded to 100 neuroscientists and ask them whether they saw anything in the data; and not one of them would claim that they saw any evidence of "probability encoding neurons" unless you primed the pump by mentioning such a notion to them. 

Suspect Malarkey When Someone Theorizes About a "Universal Consciousness Field"

 Neuroscience does a crappy job of explaining human minds. The explanations of neuroscientists lack very many things. For example, they lack:

• Any coherent or credible theory of how a brain could convert experience into brain states or synapse states when a memory is created;
• any coherent or credible theory of how a brain could convert brain states or synapse states into thoughts or recollections when a memory is recalled;
• any coherent or credible theory of how a brain could instantly create new memories, something that humans routinely do; 
• any coherent or credible theory of how a brain could instantly retrieve a memory, such as instantly getting just the right answer when someone is asked to identify some person or object or technical term or historical event;
• any coherent or credible theory of how a brain could create an abstract idea such as the idea of a child or the idea of a dog or the idea of a nation;  
• any coherent or credible theory of how a brain could imagine something such as some invention no one ever built yet;
• any coherent or credible theory as to how there could occur any of the types of anomalous or paranormal things that humans experience -- things such as near-death experiences, out-of-body experiences, apparition sightings and extrasensory perception (ESP). 

Faced with such a shortfall, some try to turn to physics. This is a mistake. Physics does nothing to explain why consciousness or minds exist. We might make a relational claim looking rather like this:

Physics --> Chemistry --> Biology --> Psychology

But in such a claim the "-->" should not be viewed as "explains" but as "is a prerequisite for." The right type of physics (by which I mean a universe with extremely fine-tuned fundamental constants and laws) is a prerequisite for chemistry; and just the right type of chemistry (involving an information-rich wealth of many types of protein molecules) is a prerequisite for biology; and just the right type of biology (such as the vast organization of a human body) is a prerequisite for physical people having psychology or minds like humans have. 

Physics is far-removed from psychology, and does nothing to directly explain human minds or any aspect of human minds. The study of brains involves a little bit of physics when someone may track the electricity of neurons firing in the brain. But neuron firings do nothing to explain mind or memory, contrary to the claims of neuroscientists.  And during near-death experiences occurring during cardiac arrest,  people often have vivid near-death experiences when their brains are electrically shut down.

But in our culture physics has a great deal of prestige. So it is not surprising that some people might try to explain human minds by appealing to physics or using jargon borrowed from physicists. Such attempts are usually dismal failures. The latest such dismal failure is the recent paper "Universal consciousness as foundational field: A theoretical bridge between quantum physics and non-dual philosophy" by materials scientist Maria Strømme.

We should always start out with very great distrust of any document claiming to be advancing something the document describes as a theory of consciousness. Why is that? It is because a human mind is something almost infinitely greater and richer than mere consciousness. Mentally you are not "some consciousness." You are a thinking, knowing, believing, loving, caring, planning, questioning, seeing, hearing, creating, imagining, willing, speaking, reading, aspiring, instantly learning, striving, enjoying, suffering and comprehending unified self, a person capable of insight, compassion, morality, self-introspection, instant recall, philosophical inquiry, appreciation and spirituality. And you are actually much, much more than the things listed in the previous sentence.  

So any attempt to describe you or a human like you as "consciousness" is an example of what I call shadow-speaking, which is when people describe things as if they mere shadows of what they are.  What kind of person engages in this type of shadow-speaking? It is typically a person who lacks any decent explanation for a human mind. People who lack decent explanations for some reality tend to describe that reality in very diminutive terms, trying to make that reality seem a million times less impressive than it is. 

Strømme is just such a shadow-speaker. Her failure to decently describe human minds is shown by her failure to use the word "memory" in her paper. 

Strømme presents the unbelievable idea of a "universal consciousness field," saying, "Consciousness interacts with physical processes as a fundamental field." She says that "awareness arises from localized perturbations.... that propagate and interact dynamically, analogous to the emergence of structure in quantum field fluctuations."

To get some inkling of what is being theorized, you may do a Google search for "in physics what is a fundamental field?" We are told this:

"According to quantum field theory, the universe is not made of particles, but of fields that fill all of space and time. Particles like electrons and photons are simply localized disturbances or 'vibrations' in these underlying fields."

The "perturbations " Strømme appeals to are similar to the disturbances or vibrations mentioned above.  The same "quantum field theory" is famous for making what is called "the worst prediction in the history of physics."  Quantum field theory allows us to calculate how much energy there should be in the vacuum of space because of quantum fluctuations in the fundamental fields it postulates. The problem is that when scientists do the calculations, they get a number that is ridiculously wrong. According to this page of a UCLA astronomer, quantum field theory gives a prediction that every cubic centimeter of the vacuum should have an energy density of 10⁹¹ grams.  This number is 10 followed by 90 zeroes. That is an amount trillions of times greater than the mass of the entire observable universe, which is estimated to be only about 10⁵⁶ grams.

This means that according to quantum field theory every cubic centimeter of empty space should have more mass-energy than all the mass-energy in the entire observable universe.

How far off is this calculation? It varies on how you do the calculations. According to one type of calculation, the prediction of quantum field theory is wrong by a factor of 10⁶⁰, which is a factor of a trillion trillion trillion trillion trillion times. According to a different way of estimating it, the prediction of quantum field theory is wrong by a factor of 10¹²⁰, which is a factor of a million billion quadrillion quintillion sextillion septillion octillion times.

This prediction has been repeatedly referred to as the worst prediction in the history of physics. It could just as well be called the most wrong prediction in the history of human thought. No zealous apocalyptic doomer ever made a prediction more wrong, not even the preacher who predicted the end of the world would occur in 1844.

The matter is discussed in this well-written post by physicist Matt Strassler, which includes some nice graphics. Scientists don't talk about this matter very much, as it is something of a skeleton in their closet. But when they do discuss the matter, they refer to it as the vacuum catastrophe or the cosmological constant problem. Scientists think that the vacuum does have a very slight energy density (believed to be the main driver of what is called the cosmological constant, which is causing the universe's expansion to accelerate). But that energy density is less than .00000000000000000000000000000000001 percent of the amount predicted by quantum field theory.

So we have a Big Reason #1 for why we should have no confidence in anyone claiming the idea of a "universal consciousness field" and claiming that you and I are vibrations or perturbations of such a field, an idea inspired by the quantum field theory idea that individual particles are vibrations of a fundamental field. It is the reason that we should not be making a theory of consciousness or mind inspired by a physics theory that fails so enormously to correctly predict the reality we observe. 

Then there's a Big Reason #2 why we should have no confidence in anyone claiming the idea of a "universal consciousness field" and claiming that you and I are vibrations of such a field. It is the reason that we should not be treating mind as if were like a physical reality, which it is not. Since consciousness is a non-physical thing, the idea of a vibration of a consciousness field makes no sense, and is like the idea of the weight in kilograms of an idea, or an idea of the cubic volume of a comprehension. 

Then there's Big Reason #3 why we should have no confidence in anyone claiming the idea of a "universal consciousness field" and claiming that you and I are vibrations of such a field. This is simply the idea that the human mind is a reality enormously more complex and diverse than mere consciousness. You are not some consciousness. You are a  thinking, knowing, believing, loving, caring, planning, questioning, seeing, hearing, creating, imagining, willing, speaking, reading, aspiring, instantly learning, striving, enjoying, suffering and comprehending unified self, a person capable of insight, compassion, morality, self-introspection, instant recall, philosophical inquiry, appreciation and spirituality. So the idea that your mental reality could arise by some vibration of a "consciousness field" is nonsensical. Such an idea is like claiming that a library of intelligible well-written books might arise from vibrations in a warehouse storing stacks of blank paper and buckets of ink. Just as it is enormously misleading nonsense to describe a large library of books as merely "some paper with ink marks," it is enormously misleading nonsense to describe a human mind and human mental experience as mere "consciousness." 

As mentioned above, I did a Google search for "in physics what is a fundamental field?" I are told this:

"According to quantum field theory, the universe is not made of particles, but of fields that fill all of space and time. Particles like electrons and photons are simply localized disturbances or 'vibrations' in these underlying fields."

That does not sound like something impossible, because electrons are very simple things, and so are photons.  Each electron has exactly the same electrical charge (the very exact opposite of the electrical charge on each proton); and each electron has the same rest mass (1/1836 of the rest mass of each proton). Because electrons are so simple and so alike, it does not sound all that farfetched that all electrons might result from tiny vibrations or perturbations in some "fundamental field." But for human minds, the situation is completely different. Every human mind and every human life of mental experience is a very complex thing, consisting of a great wealth and diversity of experiences and characteristics and capabilities. It is nonsensical to suggest that a human mind could arise from some mere "perturbation" or "vibration" of a featureless "universal consciousness field." 

When I do a search for "physics definition of a field" I get an answer of "a physical quantity that has a value at every point in space and time." I am told that a scalar field is one in which each point in space has a single number. Two examples are temperature (which can be measured at any point in space) and air pressure (which can be measured at any point in space). The concept of a "universal consciousness field" seems to make no sense, because consciousness is not a physical quantity, and cannot be measured. You cannot take consciousness readings at different points in space.  

We have as a Figure 1 of the paper a diagram looking like the one below, but with slicker graphics. 

The diagram does not make sense. "Consciousness" is an aspect of mind, or a very diminutive, weak, and minimal way of describing  a mind, which is a huge wealth of capabilities and complexities vastly more than just "consciousness"  (just as "solidity" is an aspect of a human body, or a weak, minimal way of describing a human body, a state of vast organization vastly more than just solidity).  Thought is not a separate thing from mind, but something that minds sometimes produce. A diagram with separate circles for "mind" and "consciousness" and "thought" makes no sense. Conversely, it might make some sense to have a diagram with a large circle labeled "mind" and many smaller circles inside it, with each of the smaller circles having labels such as "consciousness," "recall," "recognition," "learning ability," "insight." and so forth. 

The caption that is given to Figure 1 in the paper (looking like the visual above) is just muddled metaphysical mishmash. It is this: 

"Illustration depicting the integration of mind, consciousness, and thought based on the quantum mechanical concepts described in the paper. Mind represents the universal creative intelligence, the source of all creation. Consciousness represents universal awareness that enables the perception of space, time, and matter. It acts as a substrate, giving structure and form to the formless potential of the mind and bridging the infinite and the physical. Thought represents the creative mechanism converting the infinite potential of the mind and the universal awareness of consciousness into individualized, structured realities."

There may be some language in which a translation of this paragraph makes sense, but the English text above makes no sense. "Mind" is a term referring to the cognitive capabilities and mental experiences of a person. In English the word "mind" does not refer to "the universal creative intelligence, the source of all creation." It is reasonable to postulate a supreme Mind that is the source of all other minds (given the failure of brains to explain minds). But if you do that, you need to introduce some word or phrase more than just the word "mind." The word "consciousness" is a term referring to the awareness of a particular mind that is conscious. The term does not mean "universal awareness." You can speculate about some kind of "universal awareness," but if you do that, you need some word or phrase different from the mere word "consciousness." It makes no sense to say, "Thought represents the creative mechanism converting the infinite potential of the mind and the universal awareness of consciousness into individualized, structured realities." 

The author tries to inject as much physics jargon as she can into her metaphysical speculations. These physics jargon injections mostly sound completely inappropriate. You can get a little taste of the resulting mess in the quote below:

"This analogy reflects how a universal field, initially undifferentiated, can generate stable and diverse structures through the process of symmetry breaking—structures that, in this context, correspond to individual sentient entities. The supplementary material S2 outlines how individual consciousness may emerge as a result of other collapse mechanisms."

This is nonsense. Individual sentient entities such as you and I do not arise by any type of symmetry breaking or any type of "collapse mechanism." Anyone familiar with what a mess is today's swampland of speculation called "quantum gravity" may laugh when the paper makes some gobbledygook statement like the one above, and claims "this resonates with models in quantum gravity." 

Their is a press release describing Strømme's muddled mess, one entitled "Consciousness as the foundation: new theory addresses nature of reality." The press release wrongly describes Strømme's speculations as a "model." In physics a model is something that produces exact numerical outputs from numerical inputs, and no such thing is going on here. Trying to drum up interest, the press release says, "In this model, phenomena that are now perceived as ‘mysterious’ – such as telepathy or near‑death experiences – can be explained as natural consequences of a shared field of consciousness." But, to the contrary, the paper does not mention telepathy or near-death experiences. 

The press release says, "Her theory also suggests that our individual consciousness does not cease at death, but returns to the universal field of consciousness from which it once emerged." That at least mirrors a statement in the paper, the statement "the dissolution of individuality (e.g., through death) does not imply annihilation but rather reintegration into the universal field." Statements like that are basically meaningless, and do not involve an assertion of life after death. Statements like that are no more meaningful than the claim that after death your atoms will be reintegrated into the atom totality of our planet.

Documents such as Strømme's paper are totally dependent upon the trick of shadow-speaking, in which human minds (something enormously more complex than mere consciousness) are described in the most diminutive way possible, using the super-reductive term "consciousness." Once you properly describe a human being and a human mind and its experiences, the idea that a human mind arises as some fluctuation or perturbation from a "universal consciousness field" seems ridiculous, rather like the idea that an encyclopedia could arise from some fluctuation arising from a bathtub of ink. Typically when you examine such metaphysical efforts, you find that they engage in denial of the self or denial of the existence of individuals. What is going on is the grossest dehumanization. When people depict humans as if they were mere animals, that is a grotesque type of dehumanization. When people depict humans as if they were mere "consciousness" or "perturbations of a universal field," that is an equally grotesque type of dehumanization. 

Postscript: An effort similar to  Strømme's, and equally unpersuasive, is the recent paper "Macroscopic quantum effects in the brain: new insights into the fundamental principle underlying conscious processes" by Joachim Keppler. The main difference is that while Strømme's paper has little discussion of neuroscience details, Keppler's paper shows lots of discussion of such details (but not the most relevant details). Keppler's approach seems to be: throw in a whole bunch of discussion of tiny little neuroscience details, and then throw in a whole bunch of discussion of quantum mechanics, and then kind of say, "Voila! Light has been shed on the origin of consciousness!"  Such a paper moves not the tiniest step forward to explaining human minds. There are supposedly quantum effects in everything, including a vacuum, a rock, a ball of gas, and a brain. So describing some quantum effects in the brain does nothing to explain why a brain would produce a mind. The so-called point zero-point field or ZPF is the vacuum of space as described by quantum field theory. We should laugh hard when Keepler states, "A profound new insight takes shape, namely, that the fundamental principle behind the formation of conscious states is the resonant coupling of the brain to the ZPF." I'm reminded of the people who have long-claimed that we will be able to extract limitless energy from the vacuum of space by exploiting the same ZPF or zero-point field. 

They Deified Biological Noise, But Never Decently Studied It

Almost every time you read the word "evolution" in any Darwinist attempt at explanation, you can substitute the word "noise" for the word "evolution," and the meaning will be equivalent. 

Darwinism is a theory all based on appeal to random mutations. Rather than using the two-word phrase "random mutations," you can be more concise by using the single word "noise."  One of the definitions that I get for the word "noise" is the following: "random fluctuations that obscure or do not contain meaningful data or other information." That definition matches the concept of random mutations.  When Darwinists appeal to random mutations as creative agents causing wonders of biological innovation, they are making an extremely unbelievable claim that noise has some creative power. 

So suppose you read some Darwinist paragraph that reads like this:

"The world of life shows us the magnificent power of evolution. Evolution got life started. Evolution built the first large visible organisms. Evolution has yielded all of the amazing life forms on our planet. And as the crowning glory of its creative work, evolution gave us the human species." 

Given that Darwinism is totally dependent on claims of the creative power of random mutations that are concisely described as noise, we can rewrite this paragraph to unveil the ugly truth of the thoughts behind it:

"The world of life shows us the magnificent power of evolution NOISE. NOISE Evolution got life started. NOISE Evolution built the first large visible organisms. NOISE Evolution has yielded all of the amazing life forms on our planet. And as the crowning glory of its creative work, NOISE evolution gave us the human species." 

A careful study of biology will reveal that the biosphere is pervaded everywhere by the most astonishing engineering effects. For example, a human body contains 20,000+ types of protein molecules, each a marvel of engineering consisting of thousands of atoms arranged in just the right way to produce some particular functional effect. Such protein molecules combine together to make thousands of different types of protein complexes, which are so complex in their organization that many biochemists are nowadays referring to them as molecular machines.  An example is shown below. 

Having an unlimited faith in the power of random mutations, Darwinists believe basically that noise has millions of times acted like some super-genius engineer, to produce wonders of innovation so complex and marvelous in their functionality that they are beyond the current understanding of humans.  Darwinists have thereby deified noise.  They have attributed to noise god-like powers of biological engineering beyond anything that human engineers could produce. This is inanity of the worst kind. Noise is not an engineer. 

But while they have been willing to deify noise, our Darwinists have failed to decently study noise. If they were decent students of the noise in our brains, they would not have made the claim that the brain is the source of the human mind. 

Using the previously quoted definition of "noise" as "random fluctuations that obscure or do not contain meaningful data or other information." we can say that brains are extremely noisy. Many neurons fire at unpredictable intervals, just as maple leaves fall from a tree in autumn at unpredictable intervals. A scientific paper tells us, “Neuronal variability (both in and across trials) can exhibit statistical characteristics (such as the mean and variance) that match those of random processes.” Another scientific paper tells us that “Neural activity in the mammalian brain is notoriously variable/noisy over time.” Another paper tells us, "We have confirmed that synaptic transmission at excitatory synapses is generally quite unreliable, with failure rates usually in excess of 0.5 [50%]." A paper tells us that there are two problems in synaptic transmission: (1) the low likelihood of a signal transmitting across a synapse, and (2) a randomness in the strength of the signal that is transmitted if such a signal transmission occurs. As the paper puts it (using more technical language than I just used):

"The probability of vesicle release is known to be generally low (0.1 to 0.4) from in vitro studies in some vertebrate and invertebrate systems (Stevens, 1994). This unreliability is further compounded by the trial-to-trial variability in the amplitude of the post-synaptic response to a vesicular release." 

The 2010 paper "The low synaptic release probability in vivo" by Borst is devoted to the topic of what is the chance that a synapse will transmit a signal that it receives. It tells us, "A precise estimate of the in vivo release probability is difficult," but that "it can be expected to be closer to 0.1 than to the previous estimates of around 0.5."  Slide number 20 of the 2019 Power Point presentation here has a graph showing that this release probability is often around 0.1 or 0.2, and the same page mentions 0.3 as a typical release probability. 

Another paper concurs by also saying that there are two problems (unreliable synaptic transmission and a randomness in the signal strength when the transmission occurs):

"On average most synapses respond to only less than half of the presynaptic spikes, and if they respond, the amplitude of the postsynaptic current varies. This high degree of unreliability has been puzzling as it impairs information transmission."

All of these facts are extremely damaging to all claims that the brain is the storage place of human memories, and the source of human thought. We know that humans can recall large bodies of information with perfect reliability. This happens every time someone plays the role of Hamlet, and correctly speaks every word in the 1480 lines in this role. The same reliability occurs when numerous Muslim scholars correctly recall every word in their holy book, a book of more than 6000 verses. Akira Haraguchi was able to recite correctly from memory 100,000 digits of pi in 16 hours, in a filmed public exhibition. Besides such feats of perfectly accurate retrieval of very large bodies of information, there have also been numerous math calculation savants who could perform very complex calculations "in their heads" with perfect accuracy, without using paper, pencils or digital devices.  No such feats should be possible if they are produced by brains dominated by noise, brains in which signals are transmitted so unreliably.

If our Darwinists had made a decent study of biological noise, they would have found that the most relevant type of biological noise is the vast amount of biological noise in our own brains, an amount great enough to exclude all claims that the brain is the source of human recall and human math calculation that can occur with 100% accuracy. But alas, while our Darwinists deified biological noise, they didn't bother to decently study it.