So-Called "Brain Computer Interfaces" Do Nothing to Show That Mind Uploading Is Possible

The concept of "mind uploading" is the entirely fallacious notion that a human might achieve a radically different form of existence by some process in which his mind and memories are transferred into a computer or robot. The concept is completely erroneous because your brain is not the source of your mind, and the brain is not the storage place of human memories. So there is nothing in a brain that could be transferred to some machine to transfer your mind to a machine. 

You should not have an ounce of regret after reading of facts about brains that debunk the idea of mind uploading. The very reasons why it is will always be impossible to upload your mind into a computer or a robot are the same reasons why you won't ever need to do any such thing.  Your mind and memory cannot be explained by anything in the brain, and that means you must have a mind and memory because you have something like a soul. Having such a soul that is not a product of your brain, you need not worry about your existence ending when your brain dies. Bodies and brains die, but souls do not.  The massive evidence for paranormal phenomena such as out-of-body experiences, deathbed visions and near-death experiences provide independent reasons for thinking your mind will survive death. 

There is a rather recent paper on this topic of mind uploading, a paper with some false claims. The paper is published by something called "The World Journal of Advanced Research and Reviews," which does not seem to be an established and respected scientific journal, but one of the many "scientific journals" that make money from authors paying to get their papers published. Entitled "The Digital Afterlife: AI Cloud Consciousness as the New Immortality," the paper is by someone named Dhruvitkumar V. Talati, who seems to have no higher academic credentials such as a master's degree or a PhD.  Looking at Talati's achievements, as listed on the page here, we seem to see lots of good  experience with computers and technology. But the page says nothing about any training in neuroscience or psychology, nor does it mention any writings on such topics. Based on this page and the articles of Talati I see on Google Scholar, Talati does not seem like a very deep and serious scholar of either brains or minds; and his paper makes some false statements on these topics. 

Before discussing his misstatements, let me discuss the "brain-computer interfaces" which Talati frequently appeals to. Such things are unimpressive affairs, which do nothing to raise any hopes of mind uploading. The simplest thing that could be called a "brain computer interface" is simply an EEG device connected to a computer. Such a thing looks rather like this:

All that is going on in such an affair is that brain waves from a person are being read by use of an EEG head cap, with the brain wave data going to some computer. The data is extremely noisy data consisting of squiggly lines with lots of ups and downs. It looks like what we see below:

By analyzing such data, nothing can be understood about what a person is thinking or remembering. No one has ever been able to discover any "neural code" allowing someone to figure out what a person is thinking or remembering from analyzing such lines. Traces of muscle movements sometimes show up in such lines, and detection of such muscle movements may be misleadingly depicted as "thought reading." 

There is another type of "brain-computer interface" that is more invasive.  Electrodes may be implanted inside someone's brain. That does not offer much of anything more than what you get from an EEG cap that does not require opening up someone's skull. 

Recently some organizations have gone one step further, by implanting into someone's brain some tiny chip. Such a thing does nothing to create any real connection between a brain and a computer. Still the only thing that is occurring is the reading of electrical activity from the brain. 

It is important to clarify what is NOT occurring under these so-called "brain computer interfaces":

• No one is actually reading thoughts. A paralyzed person with such an invasive "brain computer interface" may be able to control a cursor (a little symbol on a computer screen) by moving such a cursor in different directions. But this occurs not by the reading of thoughts from the brain, but by the system picking up indications of muscle movements. Typically such systems include eye readers that can pick up tiny movements of the eye and eye focus, and cause a screen cursor to move in a corresponding way. And even if the eye is not directly tracked, because muscle movements cause blips in the lines of brain waves, it is rather easy to analyze brain waves and pick up things corresponding to tiny muscle movements or intended muscle movements. 
• No actual thought-deciphering of brain waves is occurring.  You cannot pick up what a person is thinking from brain waves. So if I silently think "Abraham Lincoln was a good leader," you can never pick up any such thought from analyzing brain waves. 
• There is no reading whatsoever of synapse states. 
• There is no reading whatsoever of neuron states. 
• There is no reading whatsoever of memories stored in a brain. Microscopic examination of brain tissue has never revealed any trace of learned knowledge or episodic memories by examining brain tissue. Microscopic examination has occurred abundantly with electron microscopes very many times larger than anything going on in a so-called brain-computer interface.  

Now lets look at some of the misstatements in Talati's paper. 

Talati: "The rapid advancements in neuroscience and brain mapping, coupled with the development of brain-computer interfaces, have paved the way for the potential transfer of human cognition into a digital medium." 

Reality: There has been no such progress -- no such way has been paved.  Claims of "mind reading" by insertion of brain chips are misleading. No actual "mind reading" is occurring, and the very meager results come from tricks such as eye-tracking, in which eye movements are used to guide a cursor.  The primitive "brain-computer interfaces" created thus far (described above) offer no reason for hoping that there could ever occur a "potential transfer of human cognition into a digital medium." 

Talati: "At the core of the concept of AI cloud consciousness lies the idea of transferring human cognition, thoughts, memories, and personality into a digital medium. This process involves the use of brain-computer interfaces and advanced neuroscience techniques to map and replicate an individual's neural patterns and cognitive processes (Campbell et al., 2002). With the proliferation of cloud computing and the ever-increasing capabilities of artificial intelligence, the storage and simulation of human consciousness within a virtual realm have become a tangible possibility."

Reality:  No one has done any work making the idea of mind uploading anything like a "tangible possibility." The progress of cloud computing and artificial intelligence is merely progress in computer programming and data processing.  There has been no neuroscience progress that should make anyone believe in the possibility of mind uploading. To the contrary, the more we learn about the physical shortfalls of brains, the less confidence we should have in the possibility of mind uploading. As discussed above, the "brain-computer interfaces" developed thus far are crude affairs offering no sound basis for suspecting a possibility of mind uploading. 

Talati: "Researchers in the field of neuroscience have made significant strides in mapping and understanding the complex neural patterns and cognitive processes that underlie human consciousness. (Campbell et al., 2002) (Goh, 2021) Through the use of advanced neuroimaging techniques, such as functional magnetic resonance imaging (fMRI) and electroencephalography, scientists have been able to identify and analyze the neural correlates of various cognitive functions, including memory, decision-making, and self-awareness."

Reality: The description of a human mind as mere "consciousness" is a profoundly misleading word trick of many modern writers, a trick I call "consciousness shadow speaking," in which something of oceanic depth (the human mind) is made to look like the faintest shadow of what it is. Human minds, human mental capabilities, and human mental experiences are a million times more complex than mere "consciousness." No progress has been made in explaining brain causes of the main facets of human mental activity. Scientists are utterly unable to explain how a brain could produce any such things as thinking, personhood, imagination, insight, learning, or recall. When scientists try to explain such things, they give us only the most vacuous hand-waving, such as incoherently trying to explain the formation of memories as "synapse strengthening."  

Excluding all of the "lying with colors" diagrams that mislead us by depicting tiny "1 part in 200" differences as if they were big differences, the search for neural correlates of mental functions has done nothing to substantiate claims that mental functions such as thinking, imagination, learning and recall are brain processes. As discussed here, here, and here, such studies typically show only tiny differences such as 1 part in 200 between resting brains and the brains of people engaging in mental activities.  As such differences are merely the type of differences we would expect from chance variations, they do nothing to support claims that mental activities are brain functions. 

Talati: "The field of brain-computer interfaces continues to evolve, with researchers working to overcome the complexities of neural dynamics and the potential impact of psycho-neurophysiological fluctuations on brain signals (Saha et al., 2021) (Maiseli et al., 2023) (Mak & Wolpaw, 2009). The advancement in neuroscience and the development of brain-computer interfaces form the scientific foundation of AI cloud consciousness (Mak & Wolpaw, 2009) (Rao et al., 2012) (Saha et al., 2021). BCI [brain-computer interfaces] serve as a critical bridge, enabling the translation of neural signals into digital commands that can be used to transfer and simulate human consciousness within a virtual environment."

It is rather obvious what is going on in the statement above. Talati is just repeating over and over again the phrase "brain-computer interfaces" or BCI, a phrase he uses 16 different times in his paper.  The references do nothing to establish any possibility of mind-uploading, because all so-called "brain computer interfaces" are very crude affairs which do little other than than analyze the noisy ups and downs of brain wave lines. While continuing again and again to appeal to "brain-computer interfaces,"  Talati is making some false statements. Specifically:

• It is very false that "the advancement in neuroscience and the development of brain-computer interfaces form the scientific foundation of AI cloud consciousness."  No work in these fields provide any basis for thinking that computers or artificial intelligence will ever be conscious. 
• It is utterly false that "BCI [so-called brain computer interfaces] serve as a critical bridge, enabling the translation of neural signals into digital commands that can be used to transfer and simulate human consciousness within a virtual environment."
• It is utterly false that "brain-computer interfaces...which serve as a critical enabler for mind uploading."  None of the work done in so-called brain-computer interfaces provide any realistic hope that a mind could ever be uploaded into a computer. 

We can tell the lack of any theoretical foundation for mind uploading by how infrequently Taliti refers to memory.  He makes no substantive references to memory. His paper's two uses of the word "memory" are both vacuous passing references, mere statements in which he claims that there are "neural correlates of various cognitive functions, including memory, decision-making, and self-awareness."  There is actually no good evidence that brains look or behave any different when you are learning, deciding or recalling.  Taliti's paper also makes no uses of the word "synapse" or "synaptic," and its only reference to neurons is the incorrect statement that humans have trillions of neurons (the actual number is something like 86 billion). It rather seems that when he wrote this paper on mind uploading, Taliti was neither a very deep and serious scholar of human brains, nor a very deep and serious scholar of human minds.  An excellent knowledge of computer technology does not qualify you to write a paper claiming that mind uploading will be possible. The more you objectively study brains and their many physical shortfalls which exclude them as a source of the human mind, the less you will tend to believe in the possibility of human minds being  uploaded into computers. And the more deeply and thoroughly you study human minds and human mental experiences and human mental capabilities in all their strange and spooky diversity, and the best examples of human mental performances, the less you will tend to believe in the possibility of human minds being  uploaded into computers.

No one should take seriously the notion of uploading minds into computers unless there is ever announced the electronic reading or microscopic reading of memories from human brains.  Such a thing has never occurred, and it never will occur. If human memories existed in human brains, scientists would have been able to read such memories around the year 1960, when microscopic technology advanced far enough to scan the tiniest components in brains. Around that same year of 1960, scientists were able to discover that there is genetic information in DNA, and were able to figure out the coding system by which such information is represented. 

Postscript: The paper "Long-term independent use of an intracortical brain-computer interface for speech and cursor control" is one that was promoted by news stories claiming progress in so-called "brain-computer interfaces." A look at the paper reveals that what is going on is a lot more than just analysis of brain waves.  The paper confesses, "The system independently using neural decoding, supplemented by eye gaze tracking to facilitate user-interface control." The next sentence confesses, "The speech decoder software ran continuously in the background and displayed decoded words on-screen in real time (Fig. 1C, left)." This involved specialized software for decoding garbled speech, something much different from brain wave analysis. There was also hand movement analysis, because we read this of the disabled person using the system: "He could also control his computer by attempting to move or squeeze his hand." So we have here at least three different ways in which the system was getting data from the user other than picking up his brain waves. It is misleading to use the term "brain-computer interfaces" for systems like this that involve so much more than just inputs from brains. 

Carefully designed devices can pick up a wealth of information from scanning human eyes. For example, given the right type of computer screen viewed by a paralyzed person or a person not using his hands, a carefully designed device can pick up direction indicators from eye movements alone.  Imagine a computer screen showing a scene like the one below:

Through the right technical setup (such as something with a camera looking from this screen to the viewer), you can get a "drive without touching anything" effect displaying on the screen, in which a viewer's gaze at position A causes the screen car to turn to the left, a viewer's gaze at position B causes the screen car to drive straight ahead, and a gaze at position C causes the screen car to turn to the right. If such a system is combined with some EEG apparatus reading brain waves, someone can make a claim that "thoughts in the brain are being read to move the car in 3D space," even though the brain waves are superfluous, and the system is really working based on eye movements. 

There are endless similar variations that might leverage eye movements or eye focus. For example, a screen might show three rows of choices: Choice 1, Choice 2 and Choice 3.  A system might be able to pick up a person focusing his eyes on any of these choices, with a corresponding action occurring. If combined with some EEG reading of brain waves, a neuroscientist might pass this system off as something that is "reading your brain's decisions," even though all that is happening is that eye focus on a particular screen position is being picked up, with the reading of brain waves being superfluous. 

Misleading Tricks of Those Claiming to Decode "Inner Speech"

You can tell when a person is engaging in muscle activity by analyzing the squiggly lines of EEG readings obtained when someone puts on his head a device containing electrodes. Muscle movements of every type (including speech) produce deviations or disturbances in the wavy lines produced by EEG devices picking up brain waves. Because different types of visual images may produce different types of muscle movements (as illustrated in the visual below), it may be possible to predict above chance which of three photos a person is shown. Different photos may produce different types of muscle movements and different durations of muscle movements. So a computer program analyzing the squiggly lines of EEG readings may score above chance, by considering blips in EEG readings that may have different characteristics when different types of photos are shown. Such an ability is no evidence that brains produce minds, but merely evidence that different visual stimuli may produce different types of reactive muscle movements. 

There is no brain-related technology that allows any person or computer program to figure out what a person is thinking by looking at MRI scans of a brain or EEG electrode readings of brain waves. But there are various tricks and cheats that can be used by someone trying to persuade you that he has decoded a person's thoughts or "inner speech" by analyzing brain states or brain waves. Below are some of these cheats and tricks. 

Trick #1: The leveraging of failures of follow fast-paced hard-to-follow instructions. I have noticed this sleazy trick in some neuroscience papers. It is the trick of doing an experiment that requires an experimental subject to very rapidly switch between speaking a word and merely thinking of a word. So, for example, there may be a computer program that flashes instructions like this, with the instructions appearing on the screen for the times shown below:

Say "hippopotamus" (3 seconds)

Pause (2 seconds)

Say "asparagus" (3 seconds)

Pause (2 seconds)

Think "perfect"  (2 seconds)

Pause (2 seconds)

Say "principle" (3 seconds)

Pause (2 seconds)

Say "asparagus" (3 seconds)

Pause (2 seconds)

Think "inventiveness"  (3 seconds)

Pause (2 seconds)

When instructions like this appear on a computer screen, with a very fast pace, and rapid switches between the type of instruction, there is a good chance that a subject will sometimes fail to follow the instructions exactly. So during some percentage of the time that the subject was supposed to be only thinking of a word, the subject may be speaking a word, in audible speech or all-but-silent speech or silent speech involving lip movement. This may allow a neuroscientist to brag about "above chance" results during intervals when supposed "inner speech" occurred.  What is going on is that the instructions have been almost designed in a way to produce a fair amount of audible speech or all-but-silent speech or silent speech involving lip movement during intervals when subjects were supposed to be engaging in only mouth-motionless "inner speech."  And if you are using very sick patients with speech difficulties (as the main paper discussed below did), and  using a very fast rapidly-switching pace, then it is all-but-certain that a large fraction of the brain waves recorded during intervals that are supposed to be only "inner speech" will instead be audible speech, near-audible speech or mouthed speech, an effect that basically invalidates any boasts experimenters may make about decoding "inner speech."

Trick #2: Failing to prevent mouth-movement during intervals supposed to be "inner speech."  There is a simple way to prevent or minimize muscle movement from the mouth during testing intervals that are supposed to be thought-only "inner speech."  One way is to have a test subject wear something in his mouth designed to prevent any movement of the lips or tongue, with the subject wearing such a device during any test interval in which he is supposed to be engaging in speechless "inner speech."  Another way is to make use of some specialized motion detector that will sound an alarm whenever the subject moves his lips or tongue. No such devices are used by neuroscientists doing experiments claiming to decode "inner speech." So whenever they claim that something involved only "inner speech" we should distrust such claims, and suspect that there was a lot of actual speech or muscle movement (audible or not) going on during the recorded periods of supposed "inner speech."  

Trick #3: The word length cheat.  I have noticed this sleazy trick in some neuroscience papers. It is the cheat of doing an experiment that attempts to predict which of a small set of words a person is thinking about, while leveraging the fact that some of the words have longer lengths than others. So, for example, in some quick-paced instructions appearing on a screen, a user may be asked to think (without speaking) one of these words: dog, chameleon, apple, hippopotamus, triangle. If the pace is fast enough, with enough tricky switches between "say this" and "think this,"  some little traces of muscle movement may show up in the EEG readings, even during intervals when the subject is only supposed to be speaking; and from the length of such muscle movement it may be rather easy to predict which word the user was asked to think of.

Trick #4: No exact specification of the experimental procedure. This is a very bad defect of most papers claiming to decode inner speech from brain scans or EEG readings. Such papers will typically offer some sketchy outline of the experiment that went on, without specifying the exact procedure. The rule of thumb we should follow is: regard as worthless any paper claiming successful experimental results which fails to specify in sufficient detail the exact experience that subjects underwent, in a way sufficient for someone to attempt a replication of the reported results. 

Trick #5: Cherry-picking best results. Using multiple subjects and many different electrodes reading from different regions of the brain, a researcher can cherry-pick a best result from the many results (a result that might easily be obtainable by pure chance), and then try to give the impression that such a result was a typical result. Something similar would be going on if you had 20 people try to guess 50 five-digit numbers, and then had some visual graph heading bragging about "60% accuracy" with the fine print revealing that this was for guess target number 35 and guesser number 17 (when the target was 44392 and the guesser guessed 44291). 

Trick #6: Leveraging data backdoors in a sneaky way. This trick goes on when some researcher claims that they got an impressive result "from brain scans" or "EEG readings" when brain scans or EEG readings were only part of the inputs used, with the success mainly coming from some data backdoor. An example is when researchers have subjects look at images obtained from the COCO image dataset. That dataset includes text annotations corresponding to each of the images, an example being that a picture of an apple may be labeled as "apple" or "fruit."  So a computer program analyzing EEG readings while test subjects saw particular images can find out words corresponding to the observed image, by using the data backdoor of the text annotation corresponding to each image. With a little obfuscation and "clouding the waters," a success so unimpressive might be passed off as "mind reading" even though what is powering the success is 98% simply looking up the text annotations corresponding to the images, a feat no more impressive than looking up the definition of a word. 

Trick #7: Leveraging sound inputs. Some people with speech problems have the ability to produce sounds when trying to speak, sounds that an average person is unable to understand. This may sound like someone trying to speak with his mouth filled with food. Some scientist may connect such a person to some EEG device, either one that is invasive (involving brain-implanted electrodes) or not invasive. Some computer program may then train on the person's speech while he is reading something or trying to read something. The computer may get a good idea about correlations between sounds that a human listener cannot understand, and words that a person is attempting to speak.  Then the computer program may report success at "decoding" something that may be called "inner speech" or "brain states" or "brain outputs," even though the success is coming mainly from sound inputs rather than brain states. The effort may be wrongly called "brain-to-text" or a "decoding of brain speech" although such terms are inappropriate under such circumstances. 

Trick #8:  Leveraging phoneme or attempted phoneme EEG correlates. I noted before that muscle movements of every type (including speech) produce deviations or disturbances in the wavy lines produced by EEG devices picking up brain waves. There may be particular EEG correlates for particular phonemes or attempted phenomes that a person may make. So when someone makes the sound at the beginning of "achoo" and "apple," that may tend to produce a particular type of EEG blip; and when someone makes the sound in the middle of the words "cheese" and "sneeze," that may tend to produce some other type of EEG blip. So if you have a computer program that is trained to recognize such characteristic EEG blips, by training after someone connected to an EEG device tries to read some long body of text, that program may gain some ability to pick up lots of what a person is saying from his EEG brain wave readings. This may be described as "brain reading" although it is more accurately described as muscle movement EEG correlation reading. A program trained to recognize particular type of EEG correlates of phoneme pronunciation or attempted phoneme pronunciation may use some fancy AI "fill in the blanks" algorithm (possibly involving frequentist word-guessing or syllable guessing or phoneme guessing) to enhance some limited success it has at picking up EEG correlates of attempted syllable pronunciations. None of what I describe in this paragraph is correctly described as "decoding inner speech," although it may be described as that, particularly under some fast-pace hurry-up methodology in which a good deal of actual speech or attempted speech is occurring during two-second intervals in which someone is supposed to be only thinking of a word, because of a study design that almost guarantees there will be a large amount of this spillover "talking or trying to talk when you were supposed to only think."

Trick #9: The "as high as X percent accurate" trick. This trick is as old as the hills. You slice and dice the prediction results into something like 100 different portions, and pick the portion with the highest predictive accuracy. You then say something like "my method is up to 75% accurate," mentioning the accuracy of the most successful little portion, rather than the overall results. 

Trick #10: Leveraging AI and large language models. An AI system that has trained on very many web pages and online books may be able to fill in lots of blanks in sentences, using guesswork based on word frequencies and the frequency of words used in a particular type of sentence or sentence fragment. So for example, if you have a fragment of a sentence such as "I'm hungry so __ ____ __ ____ ______," the AI system might be able to predict "I'm going to make some food" or some similar phrase as the missing part. Leveraging such AI systems, an experiment might produce some success level at "decoding inner speech" much higher than it would get without using such an AI system, particularly if some experiment uses carefully chosen test sentences of a type that allow an AI system to predict the full sentence from only half of the sentence.  

The latest example of a misspeaking neuroscience paper boasting about decoding inner speech is the paper "Inner speech in motor cortex and implications for speech neuroprostheses" which you can read here.  We get in the paper various boast soundbites that are not backed up by anything reported in the paper. The paper starts out by making the false claim that "Attempted, inner, and perceived speech have a shared representation in motor cortex."  Speech is not represented in the cortex or any other part of the brain. The beginning of the paper contains quite a few untrue statements about the previous results of researchers, statements that are untrue because of various defects in the results published by such researchers. 

Many of today's neuroscientists misspeak like crazy when they use the words "represent," "representations," "decode" and "decoding."  Misstatements by neuroscientists using these words are extremely abundant. As a general rule you should never trust a neuroscientist using the words "represent," "representations," "decode" and "decoding." When it comes to "representations" neuroscientists are often guilty of very bad pareidolia and noise-mining, which involves a kind of seeing things that are not really there. Nowadays it easy for a scientist to kind of see things that are not there, by using "keep torturing the data until it confesses" tactics that often involve shady manipulations of data by dubious custom-written computer programs. We also should have a default distrust over any neuroscientist statement made by a neuroscientist about a decoding percentage accuracy. Such statements are typically extremely dubious, involving very dubious or easy-to-discredit calculation methods, or claims in which no calculation method is ever adequately specified. Often in a paper some impressive "decoding accuracy" figure is stated, but never justified. 

Our first reason for distrusting the "Inner speech in motor cortex and implications for speech neuroprostheses" paper comes when we read that it involved only four subjects. As a general rule, correlation-seeking neuroscience experiments have no value unless they use a study group size of at least 15 or 20 subjects; and usually the required study group size is much larger. 

Another strong reason for distrusting the "Inner speech in motor cortex and implications for speech neuroprostheses" paper comes when we consider the endangerment-of-the-sickest procedure that its researchers engaged in.  The study involves invasively inserting microelectrodes into the brains of four very sick patients.  This was not done for any medical benefit for these patients.  The very sick patients had diseases such as the muscle-wasting disease ALS, sometimes called Lou Gehrig's disease. The insertion of microelectrodes into brains involves very serious medical hazards, and when used on very sick patients it may worsen their difficulties. In this case the very sick patients were used as "experimental guinea pigs," without any medical benefits coming to them from the medical risks they were enduring. 

Whenever such shady business is going on, we should all-the-more tend to distrust any statements made by the people engaging in the shady business. We should nowhere be giving "the benefit of the doubt" when such researchers make grand boasts, but demand the clearest evidence that such boasts are justified. 

In the case of the paper "Inner speech in motor cortex and implications for speech neuroprostheses" no such clear evidence is given. The paper fails to give any very exact specification of the experimental procedures it followed. But from its Supplemental Information document we should have the strongest suspicion that some of the tricks listed above were used.  

When asked to produce "inner speech," instructions were given that seem designed to produce muscle movement rather than pure thought. According to Table S1, the instructions were these:""

• "Imagine mouthing the word. Focus on what your mouth, tongue, lips, jaw and throat would be doing and how they would feel."
• "Imagine uttering the word aloud. Focus on the sound you would be producing."
•  "Imagine hearing me (or someone’s voice you know well) say the word, focus on the sound of my (their) voice."

The same table tells us that instructions such as these were alternated with instructions like these:

• "Say the word aloud (to the best of your ability.'
• "Mouth the word as if you were mouthing to someone across a room, without sound."

How fast were these instructions switched? We cannot tell exactly, because the paper authors have failed to describe their exact test procedure in a way that would allow anyone to reproduce it exactly.  But from Table S4 in the Supplemental Information, we have every reason to suspect that the authors were guilty of Trick #1 described above. We have some table suggesting that very fast, rapidly switching time intervals were used. The table makes it sound as if the subjects were required to do some super-hurried affair in which they had to very rapidly switch between "speak the word" instructions and "think the word" instructions. 

Now let us look at some of the unwarranted and dubious statements made in the paper:

(1) The caption of Figure 1F refers to a "T16-i6v Decoding Accuracy of 92.1%."  This gives an impression of high accuracy, until you figure out that this referring to only a single subject (subject T16) and a single electrode location (corresponding to the name i6V). The figure seems to have been cherry-picked from Figure 1E, which shows a grid of 63 percentages ranging from 11 to 97.9. We may note how misleading this is. A casual viewer of the paper, looking at the figures, may get the idea that some high decoding accuracy was achieved, when no such thing occurred.  Something shady as this should deepen our distrust of this paper. We have no decent explanation of how these numbers in Figure 1E were obtained, and the whole grid should be regarded with suspicion. What little explanation is given (some mention of a "Gaussian naive Bayes" with a 500 millisecond window)  is something that does not inspire confidence. Figure 1D graphs a suspiciously hurried-up affair that seems to involve a trick like described in Trick #1 above. 

(2) The careful critical reader of the paper will tend to suspect that what is going on is noise-mining and cherry-picking from electrode data corresponding to many different reading locations in the brain. Each of the four patients had multiple electrodes inserted into their brains. So when Figure 1F refers to a "T16-i6v Decoding Accuracy of 92.1%,"  this is referring to only a single subject (subject T16) and a single electrode location (corresponding to the name i6V). It is not at all the average accuracy of decoding attempts using this subject. Do we have here any reason for thinking that the results are better than chance, when you consider the results from each patient's electrodes?  There seems to be no such reason. 

Each of the four subjects had about 6 electrode arrays in their brains. So with 24 or more possible areas to check, it is hardly surprising that some researcher might be able to report a relatively high "decoding accuracy" involving one of those areas and one of these subjects. Similarly, if I ask 24 people to pick the score and teams of the next Super Bowl, I will probably have one that I can claim as having a high predictive accuracy, even if mere chance is involved. 

We also have some insinuations in the paper ""Inner speech in motor cortex and implications for speech neuroprostheses" that some  relatively high accuracy was achieved in experiments involving a 125,000 word vocabulary. None of the claims should be trusted, because the procedure involved is not described in adequate detail.  We have a link to a video showing a woman (subject T16)  seeing a computer screen that displays some text. The video says, "In this task the target sentence appears at the top of the screen, and the inner speech BCI [brain computer interface] is shown below, generated in real time."  First, the computer displays the sentence "That's probably a good idea." Then we see below that a line slowly appearing; "That's probably a good idea."

We should treat with the greatest skepticism any claim that this is a "decoding" of what the very sick subject was thinking. Some computer program already knew the target sentence. We don't know what tricks are going on for the computer program to go from this known target to a supposed "decoding" matching the target, because the testing procedure and programming is nowhere decently described in the paper or its Supplemental Information. Were the sentences randomly selected from some very large set such as a group of 100,000 sentences? Or were the sentences only a very limited number of sentences that some AI program had trained on, which would tend to create a vastly higher chance of success? We don't know, because the authors haven't explained their method decently. We have no idea of what kind of tricks and cheats may have helped produced this impressive-looking result.  Part of what is going on seems to be AI prediction based on phrase frequencies in sentences starting a particular way. An AI system can predict "a good idea" as one of the most likely endings of a sentence beginning "That's probably..."

Seeing the video you might assume that there was some "Chinese wall" affair in which one part of the software knew that the target sentence was "That's probably a good idea," and some other part of the software (a decoding part) did not know that this sentence was the target, and figured out the target from brain waves. But you should not make any such assumption, because it is never made explicitly in the paper; and what was going on when you see that video clip is never adequately explained. The paper authors have given us reasons for distrusting their work, and our default attitude should be distrust, rather than making generous assumptions the authors are trying to suggest. 

The video is attempting to give us the impression that some randomly generated sentence (created from a vocabulary list of 125,000 words) is being decoded by brain signal analysis. But nowhere in the text do we actually have a claim that any of the sentences were randomly generated from such a vocabulary list; and nowhere in the text do we have an assertion that the sentence was randomly chosen from a very large set of sentences such as a set of 100,000 sentences.  For all we know there may be only a very small number of sentences, each of which was previously given to the subjects. So the impressive-looking "decoding" might actually be something a thousand times less impressive, something easily obtainable by a few statistical or programing tricks, even if it is utterly impossible to decode what word someone is thinking of by gathering EEG signals from someone whose mouth is immobile.  

Referring to the subject T16 shown in their little video clip, the paper says, "T16 had online retraining only for the 125,000-word vocabulary evaluation blocks, in which the cued sentences were used as ground truth to retrain the model, but only after those sentences had been decoded online." Although obscure, that sentence should be enough to make us suspect that the video involving subject T16 is just some smoke-and-mirrors affair, not any real decoding of what someone was thinking from the person's brain states or brain waves. 

As the paper lacks adequate documentation on what was going on, we should have no confidence in the results.  The authors of the paper help create a fog of mystery about what they did by having the paper document about five different experiments, none of which is clearly and consistently named, and none of which is very well documented in regard to the exact procedure followed. This is not how to do a persuasive experiment showing an ability to decode "inner speech" from brain waves. Instead, do a single experiment in which everything that went on is so well-documented that someone else might be able to reproduce the result.  

Whenever a completely silent person's lips and tongue are motionless, and he is not moving any of his muscles,  it is impossible to decode what a person is thinking or imagining (or a sentence he is trying to speak) using only brain scans produced by MRI machines or the brain waves picked up by EEG readings. But using a variety of misleading tricks such as the ones listed above and many other possible misleading tricks, researchers can create misleading impressions that they are making progress at a task that is impossible. 

Postscript: The paper "Long-term independent use of an intracortical brain-computer interface for speech and cursor control" is one that was promoted by news stories claiming progress in so-called "brain-computer interfaces." A look at the paper reveals that what is going on is a lot more than just analysis of brain waves.  The paper confesses, "The system independently using neural decoding, supplemented by eye gaze tracking to facilitate user-interface control." The next sentence confesses, "The speech decoder software ran continuously in the background and displayed decoded words on-screen in real time (Fig. 1C, left)." This involved specialized software for decoding garbled speech, something much different from brain wave analysis. There was also hand movement analysis, because we read this of the disabled person using the system: "He could also control his computer by attempting to move or squeeze his hand." So we have here at least three different ways in which the system was getting data from the user other than picking up his brain waves. It is misleading to use the term "brain-computer interfaces" for systems like this that involve so much more than just inputs from brains. 

Carefully designed devices can pick up a wealth of information from scanning human eyes. For example, given the right type of computer screen viewed by a paralyzed person or a person not using his hands, a carefully designed device can pick up direction indicators from eye movements alone.  Imagine a computer screen showing a scene like the one below:

Through the right technical setup (such as something with a camera looking from this screen to the viewer), you can get a "drive without touching anything" effect displaying on the screen, in which a viewer's gaze at position A causes the screen car to turn to the left, a viewer's gaze at position B causes the screen car to drive straight ahead, and a gaze at position C causes the screen car to turn to the right. If such a system is combined with some EEG apparatus reading brain waves, someone can make a claim that "thoughts in the brain are being read to move the car in 3D space," even though the brain waves are superfluous, and the system is really working based on eye movements. 

There are endless similar variations that might leverage eye movements or eye focus. For example, a screen might show three rows of choices: Choice 1, Choice 2 and Choice 3.  A system might be able to pick up a person focusing his eyes on any of these choices, with a corresponding action occurring. If combined with some EEG reading of brain waves, a neuroscientist might pass this system off as something that is "reading your brain's decisions," even though all that is happening is that eye focus on a particular screen position is being picked up, with the reading of brain waves being superfluous. 

No One Is Actually Doing Thought-Reading by Scanning Brains or Reading Brain Signals

Elon Musk's company Neuralink has recently announced that it has implanted a chip in a human brain. The press has many an untrue headline about this, such as headlines talking about mind-reading brain chips. No one has done any such thing as reading thoughts by scanning brains. 

You might expect to get the real scoop on this topic by reading an article on it in the prestigious journal Nature. But a recent article in that journal misinforms us on this topic. The article is entitled  "Elon Musk’s Neuralink brain chip: what scientists think of first human trial." We read this:

"Neuroscientists have long argued that data from individual neurons are needed for sophisticated thought-decoding. But research indicates that averaged signals can allow decoding of complex cognitive processes, such as inner speech."

No, that isn't true. It is impossible to figure out what a person is thinking by scanning his brain signals or brain states.  The quote above has a link to the paper "A high-performance neuroprosthesis for speech decoding and avatar control." The paper describes a device that helps decode what a paralyzed woman is trying to say. But that paper states this:

"For speech decoding, the participant was presented with a sentence as a text prompt on a screen and was instructed to silently attempt to say the sentence after a visual go cue. Specifically, she attempted to silently speak the sentence without vocalizing any sounds. This differs from imagined or inner speech because she was trying to engage her articulators to the best of her ability, although substantial orofacial weakness prevents her from naturally mouthing words."

The paper describes a woman paralyzed so badly that she is unable to make intelligible speech. What the device was doing was responding to muscle signals that occur when a person is trying to speak. Picking up such signals is not an example of reading thoughts from brain signals. As the quote above confesses, it is not an example of "inner speech."

The Nature article has misled us by claiming that some decoding of brain signals can "allow decoding of complex cognitive processes, such as inner speech." The first paper it cites in support of this claim denies that claim, as the quote above shows. 

Besides having a link to the paper above, the Nature quote above also had a reference to the paper "Generalizable spelling using a speech neuroprosthesis in an individual with severe limb and vocal paralysis." That paper is also a paper that relies on attempted speech in a severely paralyzed person, rather than pure thought that makes no attempt at muscle movement. We read this in the paper: 

"Here, we demonstrate that real-time decoding of silent attempts to say 26 alphabetic code words from the NATO phonetic alphabet can enable highly accurate and rapid spelling in a clinical-trial participant (ClinicalTrials.gov; NCT03698149) with paralysis and anarthria. During training sessions, we cued the participant to attempt to produce individual code words and a hand-motor movement, and we used the simultaneously recorded cortical activity from an implanted 128-channel electrocorticography (ECoG) array to train classification and detection models. After training, the participant performed spelling tasks in which he spelled out sentences in real time with a 1152-word vocabulary using attempts to silently say the corresponding alphabetic code words. A beam-search algorithm used predicted code-word probabilities from a classification model to find the most likely sentence given the neural activity while automatically inserting spaces between decoded words. To initiate spelling, the participant silently attempted to speak, and a speech-detection model identified this start signal directly from ECoG activity.".

The second paper cited by the Nature article also gives no support for the article's claim that some decoding of brain signals can "allow decoding of complex cognitive processes, such as inner speech." To the contrary, what we have is another case of picking up attempted muscle movements. 

The ideologically neutral diagram below may help you understand the situation better:

What the two papers above are doing are picking up brain signals from the motor cortex. Such papers do nothing to show that the Mind Core (thought, recall, will, imagination, self-hood, etc.) comes from the brain. Virtually no one disputes that there can be increased activity in the motor cortex area of the brain when someone is engaging in muscle activity or attempting to move his muscles. 

Real thought-reading using neural devices would require picking up something when no one was attempting to move their muscles. Such a thing has never been done. There have been some misleading "mashup"-technique studies that have included attempts to read brain signals and also the use of computer databases and AI (artificial intelligence). Such a mixture can be an extremely confusing "smoke and mirrors" affair in which results coming not from thought-reading by brain scans are mixed up with some brain scanning activity, with the results misleadingly passed off as some breakthrough in "neural mind reading." For a discussion of some of the resulting misleading studies see my two posts below:  

Misleading Tricks of the Latest Claim of Mind-Reading by Brain Scans

Suspect Shenanigans When You Hear Claims of "Mind Reading" Technology

Elon Musk's company Neuralink may produce something of benefit to paralyzed people, but brain implants will never produce any great benefit to the general public. The brain is not the source of your thoughts or your imagination, and is not the storage place of your memories. The idea that people will be able to enhance their intelligence or learn more quickly by brain implants is an idea based on the incorrect idea that your brain is the source of your mind, and the incorrect idea that the brain is the storage place of human memories. To discover the reasons why those ideas cannot be correct, read the posts on this blog. 

I read that Neuralink is now claiming that a human with a Neuralink chip implant is controlling a mouse "by thoughts alone." To the contrary, all that is occurring is such a chip picking up intended muscle movements, which are not thoughts. Previously we got from Neuralink or one of its chief investors the inaccurate claim that no monkey had died from one of Neuralink's chip implants. A story in Wired showed that the claim was not correct, and details the specifics of how monkeys had died from Neuralink implants. In November the Reuters news agency reported that "Four U.S. lawmakers have asked the Securities and Exchange Commission to investigate whether Elon Musk committed securities fraud by allegedly misleading investors about the safety of a brain implant being developed by the billionaire’s firm Neuralink, according to a letter to the regulator."

In the history of neuroscience there have been endless misstatements. They have included the following:

• The very massive current occurrence of misleading university press releases, very often announcing new research and making claims about such research not matching anything shown by the research (with the press release claims very often not matching anything even claimed in the corresponding scientific paper). 
• The extensive use of deceptive brain scan visuals, which "lie with colors" by using misleading coloring effects in which very tiny brain activity differences are depicted in bright colors, leading people to think that particular regions of the brain "light up" and are much more active during certain cognitive activities, when in reality the difference is only about 1 part in 200 (the type of difference we might expect from random fluctuations, even if brains do not produce minds and do not store memories). 
• The massive occurrence in scientific papers of inaccurate citations, claiming that some paper showed or supported some claim that it never showed or supported, typically made by scientists who never read the paper they are citing (a scientific paper estimated that only 20% of people citing a scientific paper actually read the paper they are citing). 
• Inaccurate descriptions of what was stated by people who were brain zapped to try to produce an out-of-body experience, in which the subjects hesitating and ambiguous responses (often in response to "leading" questions) are described as reports of an out-of-body experience, when such a report was not given by the subject. 
• Deceptive papers in which purely software implementations are passed off as things that help to explain human memory, by means of outrageous language abuses in which sections or layers of software code are improperly given anatomical names corresponding to parts of the human brain, and in which tricky equivocation occurs involving mixing up the human definition of memory (involving mental experiences) and the computer definition of memory (not involving mental experiences). 
• A very large number of misstatements and misrepresentations by psychiatrists, very carefully documented in Peter Gøtzsche’s "Critical Psychiatry Textbook" that can be read here, with the misstatements often occurring to try to bolster weakly supported or unfounded claims that various types of mental illness are caused by brain states rather than life histories or socioeconomic conditions or personal life conditions. 
• The massive current occurrence of both misleading titles in scientific papers and misleading claims in scientific paper abstracts, with paper titles very commonly making claims not matching anything established by the research in the main body of the paper, and abstracts also frequently claiming the research showed something it failed to show. 
• Extremely misleading statements about the quality of evidence for spiritual and psychical phenomena that tend to contradict neuroscientist dogmas, typically made by people who have never seriously studied such evidence, often claiming very large bodies of solid evidence gathered over decades or centuries are "no evidence," combined with misleading stereotypical, mudslinging or gaslighting characterizations of the people who have reported such phenomena.
• Many decades of poor research practices in neuroscience, such as the use of way-too-small sample sizes of fewer than ten subjects, failure to follow blinding protocols, lack of pre-registration, and the use of an unreliable "see-whatever-you-want-to-see" method for trying to measure animal recollection ("freezing behavior" estimation) rather than the reliable measurement techniques discussed here.  
• The repetition by neuroscientists of utterly absurd claims that it takes hours for a human to form a long-lasting memory, claims that are contrary to every person's experience, which is that permanent memories can form instantly, with the claims being made because the people making such claims want us to believe that memories are formed through synapse strengthening known to take at least hours.  
• The frequent appearance of highly speculative "brain functional map" charts suggesting some knowledge that particular parts of the brain produce cognitive functions, suggestions that are unwarranted (see here for evidence against one of the standard elements of such charts). 
• The extremely severe lie by materialists that a split-brain operation (severing the nerve fibers connecting the two hemispheres of the brain) results in two separate human minds, contrary to the facts that no such thing occurs, and that such an operation leaves people with a single self.   
• The use in neuroscience experiments of tortuous extremely convoluted analysis pathways in which brain scan data or biological data is passed through a series of programming iterations, often involving poorly documented gobbledygook code that no one but the original programmer could have ever understood, with the effect of the rigmarole iterations being some "black box" manipulation that not even the original programmer can now understand, and the resulting mess (perhaps having some desired pattern) being passed off as some enhancement of the original data, even though there is every season to suspect the result is a corruption, distortion or contortion of the original data. 

In general, you should be suspicious about some neuroscientist trumpeting his own research, because that person is a vested interest who stands to gain financially and career-wise the more you believe his or her claims. And when corporations issue  neuroscience-related claims that are controlled by the desire of such corporations to maintain high stock prices and the desire to attract more investors, then perhaps you should be suspicious to the second power. 

The erring Nature article I quoted above is not the only erroneous article Nature has published making the false claim that minds are being read by brain devices.  A recent Nature article has the misleading title "Mind-reading devices are revealing the brain’s secrets," a claim it provides no evidence to support.  The article starts out like this:

"Moving a prosthetic arm. Controlling a speaking avatar. Typing at speed. These are all things that people with paralysis have learnt to do using brain–computer interfaces (BCIs) — implanted devices that are powered by thought alone."

No, none of these things is "powered by thought alone." They are all devices reading brain signals to detect muscle movement attempts rather than pure thoughts. 

We hear that the Broca's region supposedly involved in speech contains no actual information about words:

"They also found that Broca’s area, a brain region thought to have a role in speech production and articulation, contained little to no information about words, facial movements or units of sound called phonemes. 'It seems surprising that it’s not really involved in speech production per se,' says Willett."

The article makes this claim, which is not backed up any good research:

"His team developed a BCI implant capable of generating speech in real time when participants either whisper or imagine speaking without moving their lips or making a sound. The brain signals picked up by the BCI device in both whispered and imagined speech were similar to those for spoken speech. They share areas and patterns of activity, but are not the same, explains Herff."

In the quote above we have a reference to the paper here which has the misleading title "Real-time synthesis of imagined speech processes from minimally invasive recordings of neural activity." We have a study involving a single subject who was not paralyzed. The study has got brain wave readings of the subject while she was told to speak, whisper, and just imagine. From the combination of all three readings, some better-than-chance prediction is made about the words spoken or whispered or imagined.  But since data is being gathered in all three ways, no claim can be made to have read pure thoughts. And we don't know whether the subject kind of halfway-mouthed some of the words during the cases of supposedly "just imagining."  The authors refer to "the inherent difficulty of knowing how the participant internally performed imagined speaking,"  Exactly: we don't know whether the claimed "imagined speaking" really was pure thought.  

The Nature article's claim that the "BCI implant" was "capable of generating speech in real time when  participants either whisper or imagine speaking without moving their lips" is not correct. The study merely guessed about the words its single subject had spoken, whispered or imagined, and made guesses with a success rate slightly above chance,  a result we might expect to get by chance given 100 experiments trying such a thing.  You can plausibly explain the reported results easily without supposing any actual reading of thoughts, by simply imagining that the single subject faintly vocalized a few of the small number of words she was asked to imagine.  

Since the experiment was a rapid-fire affair, with very quick responses required, an experiment requiring responses to 100 random words in a period of only five minutes, it would have been very plausible that a subject might have done such a thing, despite being told to only imagine the displayed word. Reliable neuroscience experiments involving correlation effects require at least 15 subjects, and an experiment based on data from a single subject should not be taken very seriously. The authors claim that their one-subject experiment "demonstrates real-time speech synthesis from imagined neural activity" is unfounded.

What kind of design would a study like this need to have to provide credible evidence of thought-reading by a neural device? For one thing, you would need to test at least 15 subjects. Also, steps could be taken to prevent subjects from doing something like attempts at muscle movements in tests in which pure thought was required. You could have the subjects wear a mouthpiece that would prevent muscle movement in the mouth. Or you could have subjects wear in their mouth a device that would detect faint muscle movements or attempted muscle movements when a subject was supposed to be engaging in pure thought. Whenever such a detection was made, that response would be removed from the data, with a warning flashed not to whisper the displayed word. You would also make sure to have a decent time interval between each word test, such as 30 seconds. You might have the display of each word preceded by a warning such as "Now make sure not to speak the next word -- just THINK it."

Don't be fooled by claims of mind-reading technology in the science news. Today's "Science News" pages and sites are a boastful cesspool of glitzy goofy semi-true clickbait-infected razzle-dazzle razzmatazz that largely serve to promote the vested interests of corporations, elitist institutions, click miners and glory  seekers. 

Postscript: In an article we learn about the person who has received the first Neuralink chip. He is a person paralyzed from the shoulders down, who can speak and move his head normally (as we can see from the video here).  We read that he could play Civilization VI (a PC strategy game) for hours before having the brain chip implanted. There are a variety of ways in which technology could pick up intended game movements from such a patient.  Without even having a chip inside the brain, you could have technology that could translate head muscle movements into the equivalent of game controller movements.  We should not be impressed by the ability of such a patient to play a video game after having a brain chip implant. What is probably going on is that some system is receiving a variety of inputs, only some of which are signals from the motor cortex.  Calling such a thing a case of "reading thoughts from the brain" is very misleading. 

What would be impressive would be if someone were to have a brain chip implant, and were then to silently imagine some novel scene, such as a blue sphere sitting on top of a green cube, resting on a red table, with a computer then creating exactly such a scene.  You'll never see that, because brains are not the source of our thinking and imagination.  

The latest untrue news on this topic comes in the form of an untrue headline at www.thedebrief.org, a headline of "ROUNDBREAKING NON-INVASIVE UNIVERSAL BRAIN-COMPUTER INTERFACE LETS PEOPLE PLAY VIDEO GAMES USING ONLY THEIR MIND." The story recycles an untrue press release issued by the University of Texas, one claiming "Universal Brain-Computer Interface Lets People Play Games With Just Their Thoughts."  A look at the scientific paper  tells us that "Subjects were instructed to mentally rehearse the kinesthetics, not the visualization, of a movement without overtly causing any contraction of their muscles."  Given such instructions, people will make small muscle movements corresponding to how they want to move in a video game, and it is those small muscle movements that are being mined, rather than "just thoughts."  The subjects were wearing EEG caps, and it is well known that EEG signals are very sensitive to muscle movements.  Lacking controls and laden with statistical fog, the paper does not even give clear intelligible evidence the subjects performed above chance.  

Post-postscript: The paper "Long-term independent use of an intracortical brain-computer interface for speech and cursor control" is one that was promoted by news stories claiming progress in so-called "brain-computer interfaces." A look at the paper reveals that what is going on is a lot more than just analysis of brain waves.  The paper confesses, "The system independently using neural decoding, supplemented by eye gaze tracking to facilitate user-interface control." The next sentence confesses, "The speech decoder software ran continuously in the background and displayed decoded words on-screen in real time (Fig. 1C, left)." This involved specialized software for decoding garbled speech, something much different from brain wave analysis. There was also hand movement analysis, because we read this of the disabled person using the system: "He could also control his computer by attempting to move or squeeze his hand." So we have here at least three different ways in which the system was getting data from the user other than picking up his brain waves. It is misleading to use the term "brain-computer interfaces" for systems like this that involve so much more than just inputs from brains. 

Carefully designed devices can pick up a wealth of information from scanning human eyes. For example, given the right type of computer screen viewed by a paralyzed person or a person not using his hands, a carefully designed device can pick up direction indicators from eye movements alone.  Imagine a computer screen showing a scene like the one below:

Through the right technical setup (such as something with a camera looking from this screen to the viewer), you can get a "drive without touching anything" effect displaying on the screen, in which a viewer's gaze at position A causes the screen car to turn to the left, a viewer's gaze at position B causes the screen car to drive straight ahead, and a gaze at position C causes the screen car to turn to the right. If such a system is combined with some EEG apparatus reading brain waves, someone can make a claim that "thoughts in the brain are being read to move the car in 3D space," even though the brain waves are superfluous, and the system is really working based on eye movements. 

There are endless similar variations that might leverage eye movements or eye focus. For example, a screen might show three rows of choices: Choice 1, Choice 2 and Choice 3.  A system might be able to pick up a person focusing his eyes on any of these choices, with a corresponding action occurring. If combined with some EEG reading of brain waves, a neuroscientist might pass this system off as something that is "reading your brain's decisions," even though all that is happening is that eye focus on a particular screen position is being picked up, with the reading of brain waves being superfluous.