One of the fundamental building blocks of much of consciousness research, is that of Global Workspace Theory (GWT). One elaboration of GWT, which focuses on how it might be implemented in the brain, is the Global Neuronal Workspace (GNW) model in neuroscience. Consciousness and the Brain is a 2014 book that summarizes some of the research and basic ideas behind GNW. It was written by Stanislas Dehaene, a French cognitive neuroscientist with a long background in both consciousness research and other related topics.

The book and its replicability

Given that this is a book on psychology and neuroscience that was written before the replication crisis, an obligatory question before we get to the meat of it is: how reliable are any of the claims in this book? After all, if we think that this is based on research which is probably not going to replicate, then we shouldn’t even bother reading the book.

I think that the book’s conclusions are at least reasonably reliable in their broad strokes, if not necessarily all the particular details. That is, some of the details in the cited experiments may be off, but I expect most of them to at least be pointing in the right direction. Here are my reasons:

First, scientists in a field usually have an informal hunch of how reliable the different results are. Even before the replication crisis hit, I had heard private comments from friends working in social psychology, who were saying that everything in the field was built on shaky foundations and how they didn’t trust even their own findings much. In contrast, when I asked a friend who works with some people doing consciousness research, he reported back that they generally felt that GWT/GNW-style theories have a reasonably firm basis. This isn’t terribly conclusive but at least it’s a bit of evidence.

Second, for some experiments the book explicitly mentions that they have been replicated. That said, some of the reported experiments seemed to be one-off ones, and I did not yet investigate the details of the claimed replications.

Third, this is a work of cognitive neuroscience. Cognitive neuroscience is generally considered a subfield of cognitive psychology, and cognitive psychology is the part of psychology whose results have so far replicated the best. One recent study tested nine key findings from cognitive psychology, and found that they all replicated. The 2015 "Estimating the reproducibility of Psychological Science" study, managed to replicate 50% of recent results in cognitive psychology, as opposed to 25% of results in social psychology. (If 50% sounds low, remember that we should expect some true results to also fail a single replication, so a 50% replication rate doesn’t imply that 50% of the results would be false. Also, a field with a 90% replication rate would probably be too conservative in choosing which experiments to try.) Cognitive psychology replicating pretty well is probably because it deals with phenomena which are much easier to rigorously define and test than social psychology does, so in that regard it's closer to physics than it is to social psychology.

On several occasions, the book reports something like “people did an experiment X, but then someone questioned whether the results of that experiment really supported the hypothesis in question or not, so an experiment X+Y was done that repeated X but also tested Y, to help distinguish between two possible interpretations of X”. The general vibe that I get from the book is that different people have different intuitions about how consciousness works, and when someone reports a result that contradicts the intuitions of other researchers, those other researchers are going to propose an alternative interpretation that saves their original intuition. Then people keep doing more experiments until at least one of the intuitions is conclusively disproven - replicating the original experiments in the process.

The analysis of the general reliability of cognitive psychology is somewhat complicated by the fact that these findings are not pure cognitive psychology, but rather cognitive neuroscience. Neuroscience is somewhat more removed from just reporting objective findings, since the statistical models used for analyzing the findings can be flawed. I’ve seen various claims about the problems with statistical tools in neuroscience, but I haven’t really dug enough into the field to say to what extent those are a genuine problem.

As suggestive evidence, a lecturer who teaches a “How reliable is cognitive neuroscience?” course reports that before taking a recent iteration of the course, the majority of students answered the question “If you read about a finding that has been demonstrated across multiple papers in multiple journals by multiple authors, how likely do you think that finding is to be reliable?” as “Extremely likely” and some “Moderately likely”. After taking the course, “Moderately likely” became the most common response with a little under half of the responses, followed by “Slightly likely” by around a quarter of responses and “Extremely likely” with a little over 10% of the responses. Based on this, we might conclude that cognitive neuroscience is moderately reliable, at least as judged by MSc students who’ve just spent time reading and discussing lots of papers critical of cognitive neuroscience.

One thing that’s worth noting is that many of the experiments, including many of the ones this book is reporting on, include two components: a behavioral component and a neuroimaging component. If the statistical models used for interpreting the brain imaging results were flawed, you might get an incorrect impression of what was happening in the brain, but the behavioral results would still be valid. If you’re maximally skeptical of neuroscience, you could choose to throw all of the “inside the brain” results from the book away, and only look at the behavioral results. That seems too conservative to me, but it’s an option. Several of the experiments in the book also use either EEG or single-unit recordings rather than neuroimaging ones; these are much older and simpler techniques than brain imaging is, so are easier to analyze reliably.

So overall, I would expect that the broad strokes of what’s claimed in the book are reasonably correct, even if some of the details might be off.

Defining consciousness

Given that consciousness is a term loaded with many different interpretations, Dehaene reasonably starts out by explaining what he means by consciousness. He distinguishes between three different terms:

  • Vigilance: whether we “are conscious” in the sense of being awake vs. asleep.
  • Attention: having focused our mental resources on a specific piece of information.
  • Conscious access: some of the information we were focusing on, entering our awareness and becoming reportable to others.

For instance, we might be awake (that is, vigilant) and staring hard at a computer screen, waiting for some image to be displayed. When that image does get displayed, our attention will be on it. But it might flash too quickly for us to report what it looked like, or even for us to realize that it was on the screen in the first place. If so, we don’t have conscious access to the thing that we just saw. Whereas if it had been shown for a longer time, we would have conscious access to it.

Dehaene says that when he’s talking about consciousness, he’s talking about conscious access, and also that he doesn’t particularly care to debate philosophy and whether this is really the consciousness. Rather, since we have a clearly-defined thing which we can investigate using scientific methods, we should just do that, and then think about philosophy once we better understand the empirical side of things.

It seems correct to say that studying conscious access is going to tell us many interesting things, even if it doesn’t solve literally all the philosophical questions about consciousness. In the rest of this article, I’ll just follow his conventions and use “consciousness” as a synonym for “conscious access”.

Unconscious processing of meaning

A key type of experiment in Dehaene’s work is subliminal masking. Test subjects are told to stare at a screen and report what they see. A computer program shows various geometric shapes (masks) on the screen. Then at some point, the masks are for a very brief duration replaced with something more meaningful, such as the word “radio”. If the word "radio" is sandwiched between mask shapes, showing it for a sufficiently brief time makes it invisible. The subjects don't even register a brief flicker, as they might if the screen had been totally blank before the word appeared.

By varying the duration for which the word is shown, researchers can control whether or not the subjects see it. Around 40 milliseconds, it is invisible to everyone. Once the duration reaches a certain threshold, which varies somewhat by person but is around 50 milliseconds, the word will be seen around half of the time. When people report not seeing a word, they also fail to name it when asked some time after the trial.

However, even when a masked target doesn’t make it into consciousness, some part of the brain still sees it. It seems as if the visual subsystem started processing the visual stimulus and parsing it in terms of its meaning, but the results of those computations then never made it all the way to consciousness.

One line of evidence for this are subliminal priming experiments, not to be confused with the controversial “social priming” effects in social psychology; unlike those effects, these kinds of priming experiments are well-defined and have been replicated many times. An example of a subliminal priming experiment involves first flashing a hidden word (a prime) so quickly that the participants don’t see it, then following it by a visible word (the target). For instance, people may be primed using the word “radio”, then shown the target word “house”. They are then asked to classify the target word, by e.g. pressing one button if the target word referred to a living thing and another button if it referred to an object.

Subliminal repetition priming refers to the finding that, if the prime and target are the same word and separated by less than a second, then the person will be quicker to classify the target and less likely to make a mistake.

There are indications that when this happens, the brain has parsed some of the prime’s semantic meaning and matched it against the target's meaning. For example, priming works even when the prime is in lower case (radio) and the target is in upper case (RADIO). This might not seem surprising, but look at the difference between e.g. “a” and “A”. These are rather distinct shapes, which we’ve only learned to associate with each other due to cultural convention. Furthermore, while the prime of “range” speeds up the processing of “RANGE”, using “anger” as a prime for “RANGE” has no effect, despite “range” and “anger” having the same letters in a different order. The priming effect comes from the meaning of the prime, rather than just its visual appearance.

The parsing of meaning is not limited to words. If a chess master is shown a simplified chess position for 20 milliseconds, masked so as to make it invisible, they are faster to classify a visible chess position as a check if the hidden position was also a check, and vice versa.

I have reported the above results as saying that the brain does unconscious processing about the meaning of what it sees, but that interpretation has been controversial. After all, something like word processing or identifying a position in check when you have extensive chess experience, is extremely overlearned and could represent an isolated special case rather than showing that the brain processes meaning more generally. The book goes into more detail about the history of this debate and differing interpretations that were proposed; I won’t summarize that history in detail, but will just discuss a selection of some experiments which also showed unconscious processing of meaning.

In arithmetic priming experiments, people are first shown a masked single-digit number and then a visible one. They are asked to say whether the target number is larger or smaller than 5. When the number used as a prime is congruent with the target (e.g. smaller than 5 when the target number is also smaller than 5), people respond more quickly than if the two are incongruent. Follow-up work has shown that the effect replicates even if the numbers used as primes are shown in writing (“four”) and the target ones as digits (“4”). The priming even works when the prime is an invisible visual number and the target a conscious spoken number.

Further experiments have shown that the priming effect is the strongest if the prime is the same number as the target number (4 preceding 4). The effect then decreases the more distant the prime is from the target number: 3 preceding 4 shows less of a priming effect, but it still has more of a priming effect than 2 preceding 4 does, and so on. Thus, the brain has done something like extracting an abstract representation of the magnitude of the prime, and used that to influence the processing of the 'target's magnitude.

Numbers could also be argued to be a special case for which we have specialized processing, but later experiments have also shown congruity effects for words in general. For example, when people are shown the word “piano” and asked to indicate whether it is an object or an animal, priming them with a word from a congruent category (“chair”) facilitates the correct response, while an incongruent prime (“cat”) hinders it.

Some epilepsy patients have had electrodes inserted into their skull for treatment purposes. Some of them have also agreed to have those electrodes used for this kind of research. When they are shown invisible “scary” words such as danger, rape, or poison, electrodes implanted near the amygdala - the part of the brain involved in fear processing - register an increased level of activation, which is absent for neutral words such as fridge or sonata.

In one study, subjects were shown a “signal”, and then had to guess whether to press a button or not press it. As soon as they pressed it, they were told whether they had guessed correctly (earning money) or incorrectly (losing money). Unknown to them, each signal was preceded by a masked shape, which indicated the correct response: one kind of a shape indicated that pressing the button would earn them money, another shape indicated that not pressing the button would earn them money, and a third one meant that either choice had an equal chance of being correct. Even though the subjects were never aware of seeing the shape, once enough trials had passed, they started getting many more results correct than chance alone would indicate. An unconscious value system had associated the shapes with different actions, and was using the subliminal primes for choosing the right action.

Unconscious processing can also weigh the average value of a number of variables. In one type of experiment, subjects are choosing cards from four different decks. Each deck has cards that cause the subject to either earn or lose reward money, with each deck having a different distribution of cards. Two of the decks are “bad”, causing the subjects to lose money on net, and two of them are “good”, causing them to gain money on net. By the end of the experiment, subjects have consciously figured out which one is which, and can easily report this. However, measurements of skin conductance indicate that even before they have consciously figured out the good and bad decks, there comes a point when they’ve pulled enough cards that being about to draw a card from a bad deck causes their hands to sweat. A subconscious process has already started generating a prediction of which decks are bad, and is producing a subliminal gut feeling.

A similar unconscious averaging of several variables can also be shown using the subliminal priming paradigm. Subjects are shown five arrows one at a time, some of which point left and some of which point right. They are then asked for the direction that the majority of the arrows were pointing to. When the arrows are made invisible by subliminal masking, subjects who are forced to guess feel like they are just making random guesses, but are in fact responding much more accurately than by chance alone.

There more examples in the book, but these should be enough to convey the general idea: that many different sensory inputs are automatically registered and processed in the brain, even if they are never shown for long enough to make it all the way to consciousness. Unconsciously processed stimuli can even cause movement commands to be generated in the motor cortex and sent to the muscles, though not necessarily at an intensity which would sufficient to cause actual action.

What about consciousness, then?

So given everything that our brain does automatically and without conscious awareness, what’s up with consciousness? What is it, and what does it do?

Some clues can be found from investigating the neural difference between conscious and unconscious stimuli. Remember that masking experiments show a threshold effect in whether a stimulus is seen or not: if a stimulus which is preceded by a mask is shown for 40 milliseconds, then it’s invisible, but around 50 milliseconds it starts to become visible. In experiments where the duration of the stimulus is carefully varied, there is an all-or-nothing effect: subjects do not report seeing more and more of the stimulus as the duration is gradually increased. Rather they either see it in its entirety, or they see nothing at all.

A key finding, replicated across different sensory modalities and different methods for measuring brain activation (fMRI, EEG, and MEG) is that a stimulus becoming conscious involves an effect where, once the strength of a stimulus exceeds a certain threshold, the neural signal associated with that stimulus is massively boosted and spreads to regions in the brain which it wouldn’t have reached otherwise. Exceeding the key threshold causes the neural signal generated by the sensory regions to be amplified, with the result that the associated signal could be spread more widely, rather than fading away before it ever reached all the regions.

Dehaene writes, when discussing an experiment where this was measured using visually flashed words as the stimulus:

By measuring the amplitude of this activity, we discovered that the amplification factor, which distinguishes conscious from unconscious processing, varies across the successive regions of the visual input pathway. At the first cortical stage, the primary visual cortex, the activation evoked by an unseen flashed word is strong enough to be easily detectable. However, as it progresses forward into the cortex, masking makes it lose strength. Subliminal perception can thus be compared to a surf wave that looms large on the horizon but merely licks your feet when it reaches the shore. By comparison, conscious perception is a tsunami—or perhaps an avalanche is a better metaphor, because conscious activation seems to pick up strength as it progresses, much as a minuscule snowball gathers snow and ultimately triggers a landslide.
To bring this point home, in my experiments I flashed words for only 43 milliseconds, thereby injecting minimal evidence into the retina. Nevertheless, activation progressed forward and, on conscious trials, ceaselessly amplified itself until it caused a major activation in many regions. Distant brain regions also became tightly correlated: the incoming wave peaked and receded simultaneously in all areas, suggesting that they exchanged messages that reinforced one another until they turned into an unstoppable avalanche. Synchrony was much stronger for conscious than for unconscious targets, suggesting that correlated activity is an important factor in conscious perception.
These simple experiments thus yielded a first signature of consciousness: an amplification of sensory brain activity, progressively gathering strength and invading multiple regions of the parietal and prefrontal lobes. This signature pattern has often been replicated, even in modalities outside vision. For instance, imagine that you are sitting in a noisy fMRI machine. From time to time, through earphones, you hear a brief pulse of additional sound. Unknown to you, the sound level of these pulses is carefully set so that you detect only half of them. This is an ideal way to compare conscious and unconscious perception, this time in the auditory modality. And the result is equally clear: unconscious sounds activate only the cortex surrounding the primary auditory area, and again, on conscious trials, an avalanche of brain activity amplifies this early sensory activation and breaks into the inferior parietal and prefrontal areas

Dehaene goes into a considerable amount of detail about the different neuronal signatures which have been found to correlate with consciousness, and the experimental paradigms which have been used to test whether or not those signatures are mere correlates rather than parts of the causal mechanism. I won’t review all of that discussion here, but will summarize some of his conclusions.

Consciousness involves a neural signal activating self-reinforcing loops of activity, which causes wide brain regions to synchronize to process that signal.

Consider what happens when someone in the audience of a performance starts clapping their hands, soon causing the whole audience to burst into applause. As one person starts clapping, other people hear it and start clapping in turn; this becomes a self-reinforcing effect where your clapping causes other people to clap, and you are more likely to continue clapping if other people are also still clapping. In a similar way, the threshold effect of conscious activation seems to involve some neurons sending a signal, causing other neurons to activate and join in on broadcasting that signal. The activation threshold is a point where enough neurons have sufficient mutual excitation to create a self-sustaining avalanche of excitation, spreading throughout the brain.

The spread of activation is further facilitated by a “brain web” of long-distance neurons, which link multiple areas of the brain together into a densely interconnected network. Not all areas of the brain are organized in this way: for instance, sensory regions are mostly connected to their immediate neighbors, with visual area V1 being primarily only connected to visual area V2, and V2 mostly to V1 and V3, and so on. But higher areas of the cortex are much more joined together, in a network where area A projecting activity to area B usually means that area B also projects activity back to area A. They also involve triangular connections, where region A might project into regions B and C, which then both also project to each other and back to A. This long-distance network joins not only areas of the cortex, but is also connected to regions such as the thalamus (associated with e.g. attention and vigilance), the basal ganglia (involved in decision-making and action), and the hippocampus (involved in episodic memory).

A stimulus becoming conscious involves the signal associated with it achieving enough strength to activate some of the associative areas that are connected with this network, which Dehaene calls the “global neuronal workspace” (GNW). As those areas start broadcasting the signal associated with the stimulus, other areas in the network receive it and start broadcasting it in turn, creating the self-sustaining loop. As this happens, many different regions will end up processing the signal at the same time, synchronizing their processing around the contents of that signal. Dehaene suggests that the things that we are conscious of at any given moment, are exactly the things which are being processed in our GNW at that moment.

Dehaene describes this as “a decentralized organization without a single physical meeting site” where “an elitist board of executives, distributed in distant territories, stays in sync by exchanging a plethora of messages”. While he mostly reviews evidence gathered from investigating sensory inputs, his model holds that besides sensory areas, many other regions - such as the ones associated with memory and attention - also feed into and manipulate the contents of the network. Once a stimulus enters the GNW, networks regulating top-down attention can amplify and “help keep alive” stimuli which seems especially important to focus on, and memory networks can commit the stimulus into memory, insert into the network earlier memories which were triggered by the sight of the stimulus, or both.

In the experiments on subliminal processing, an unconscious prime may affect the processing of a conscious stimulus that comes very soon afterwards, but since its activation soon fades out, it can’t be committed to memory or verbally reported on afterwards. A stimulus becoming conscious and being maintained in the GNW, both keeps its signal alive for longer, and also allows it better access to memory networks which may store it in order for it to be re-broadcast into the GNW later.

The global workspace can only be processing a single item at a time.

Various experiments show the existence of an “attentional blink”: if your attention is strongly focused on one thing, it takes some time to disengage from it and reorient your attention to something else. For instance, in one experiment people are shown a stream of symbols. Most of the symbols are digits, but some are letters. People are told to remember the letters. While the first letter is easy to remember, if two letters are shown in rapid succession, the subjects might not even realize that two of them were present - and they might be surprised to learn that this was the case. The act of attending to the first letter enough to memorize it, creates a “blink of the mind” which prevents the second letter from ever being noticed.

Dehaene’s explanation for this is that the GNW can only be processing a single item at once. The first letter is seen, processed by the early visual centers, then reaches sufficient strength to make it into the workspace. This causes the workspace neurons to synchronize their processing around the first letter and try to keep the signal active for long enough for it to be memorized - and while they are still doing so, the second letter shows up. It is also processed by the visual regions and makes it to the associative region, but the attention networks are still reinforcing the signal associated with the original letter and keeping it active in the workspace. The new letter can’t muster enough activation in time to get its signal broadcast into the workspace, so by the time the activation generated by the first letter starts to fade, the signal from the second letter has also faded out. As a result, the second signal never makes it to the workspace where it could leave a conscious memory trace of having been observed.

When two simultaneous events happen, it doesn’t always mean that awareness of the other one is suppressed. If there isn’t too much distraction - due to “internal noise, distracting thoughts, or other incoming stimuli” - the signal of the second event may survive for long enough in an unconscious buffer, making it to the GNW after the first event has been processed. The use of a post-stimulus masking shape in the subliminal masking experiments helps erase the contents of this buffer, by providing a new stimulus that overwrites the old one. In these cases, people’s judgment of the timing of the events is systematically wrong: rather than experiencing the events to have happened simultaneously, they believe the second event to have happened at the time when the event entered their consciousness.

As an interesting aside, as a result of these effects, the content of our consciousness is always slightly delayed relative to when an event actually happened - a stimulus getting into the GNW takes at least one-third of a second, and may take substantially longer if we are distracted. The brain contains a number of mechanisms for compensating the delay in GNW access, such as prediction mechanisms which anticipate how familiar events should happen before they’ve actually happened.

Disrupting or stimulating the GNW, has the effects that this theory would predict.

One of the lines of argument by which Dehaene defends the claim that GNW activity is genuinely the same thing as conscious activity, and not a more correlate, is that artificially interfering with GNW activity has the kinds of effects that we might expect.

To do this, we can use Transcranial Magentic Stimulation (TMS) to create magnetic fields which stimulate electric activity in the brain, or if electrodes have been placed in a person’s brain, those can be used to stimulate the brain directly.

In one experiment, TMS was used to stimulate the visual cortex of test subjects, in a way that created a hallucination of light. By varying the intensity of the stimulation, the researchers could control whether or not the subjects noticed anything. On trials when the subjects reported becoming conscious of a hallucination, an avalanche wave associated with consciousness popped up, reaching consciousness faster than normal. In Dehaene’s interpretation, the magnetic pulse bypassed the normal initial processing stages for vision and instead created a neuronal activation directly at a higher cortical area, speeding up conscious access by about 0.1 seconds.

Experiments have also used TMS to successfully erase awareness of a stimulus. One experiment described in the book uses a dual TMS setup. First, a subject is zapped with a magnetic pulse that causes them to see a bit of (non-existent) movement. After it has been confirmed that subjects report becoming conscious of movement when they are zapped with the first pulse, they are then subjected to a trial where they are first zapped with the same pulse, then immediately thereafter with another pulse that’s aimed to disrupt the signal from getting access to the GNW. When this is done, subjects report no longer being aware of having seen any movement.

The functions of consciousness

So what exactly is the function of consciousness? Dehaene offers four different functions.

Conscious sampling of unconscious statistics and integration of complicated information

Suppose that you a Bayesian decision theorist trying to choose between two options, A and B. For each two options, you’ve computed a probability distribution about the possible outcomes that may result if you choose either A or B. In order to actually make your choice, you need to collapse your probability distributions into a point estimate of the expected value of choosing A versus B, to know which one is actually better.

In Dehaene’s account, consciousness does something like this. We have a number of unconscious systems which are constantly doing Bayesian statistics and constructing probability distributions about how to e.g. interpret visually ambiguous stimuli, weighing multiple hypotheses at the same time. In order for decision-making to actually be carried out, the system has to choose one of the interpretations, and act based on the assumption of that interpretation being correct. The hypothesis that the unconscious process selects as correct, is then what gets fed into consciousness. For example, when I look at the cup of tea in front of me, I don’t see a vast jumble of shifting hypotheses of what this visual information might represent: rather, I just see what I think is a cup of tea, which is what a subconscious process has chosen as the most likely interpretation.

Dehaene offers the analogy of the US President being briefed by the FBI. The FBI is a vast organization, with thousands of employees: they are constantly shifting through enormous amounts of data, and forming hypotheses about topics which have national security relevance. But it would be useless for the FBI to present to the President every single report collected by every single field agent, as well as every analysis compiled by every single analyst in response. Rather, the FBI needs to internally settle on some overall summary of what they believe is going on, and then present that to the President, who can then act based on the information. Similarly, Dehaene suggests that consciousness is a place where different brain systems can exchange summaries of their models, and to integrate conflicting evidence in order to arrive to an overall conclusion.

Dehaene discusses a few experiments which lend support this interpretation, though here the discussion seems somewhat more speculative than in other parts of the book. One of his pieces of evidence is of recordings of neuronal circuits which integrate many parts of a visual scene into an overall image, resolving local ambiguities by using information from other parts of the image. Under anesthesia, neuronal recordings show that this integration process is disrupted; consciousness “is needed for neurons to exchange signals in both bottom-up and top-down directions until they agree with each other”. Another experiment shows that if people are shown an artificial stimulus which has been deliberately crafted to be ambiguous, people’s conscious impression of the correct interpretation keeps shifting: first it’s one interpretation, then the other. By varying the parameters of the stimulus, researchers can control roughly how often people see each interpretation. If Bayesian statistics would suggest that interpretation A was 30% likely and interpretation B 70% likely, say, then people’s impression of the image will keep shifting so that they will see interpretation A roughly 30% of the time and interpretation B roughly 70% of the time.

What we see, at any time, tends to be the most likely interpretation, but other possibilities occasionally pop up and stay in our conscious vision for a time duration that is proportional to their statistical likelihood. Our unconscious perception works out the probabilities - and then our consciousness samples from them at random.

In Dehaene’s account, consciousness is involved in higher-level integration of the meaning of concepts. For instance, our understanding of a painting such as the Mona Lisa is composed of many different things. Personally, if I think about the Mona Lisa, I see a mental image of the painting itself, I get an association with the country of Italy, I remember having first learned about the painting in a Donald Duck story, and I also remember my friend telling me about the time she saw the original painting itself. These are different pieces of information, stored in different formats in different regions of the brain, and the kind of global neuronal integration carried out by the GNW allows all of these different interpretations to come together, with every system participating in constructing an overall coherent, synchronous interpretation.

All of this sounds sensible enough. At the same, after all the previous discussion about unconscious decision-making and unconscious integration of information, this leaves me feeling somewhat unsatisfied. If it has been shown that e.g. unconsciously processed cues are enough to guide our decision-making, then how do we square that with the claim that consciousness is necessary for settling on a single interpretation that would allow us to take actions?

My interpretation is that even though unconscious processing and decision-making happens, its effect is relatively weak. If you prime people with a masked stimulus, then that influences their decision-making so as to give them better performance - but it doesn’t give them perfect performance. In the experiment where masked cues predicted the right action and unconscious learning associated each cue with the relevant action, the subjects only ended up with an average of 63% correct actions.

Looking at the cited paper itself, the authors themselves note that if the cues had been visible, it would only have taken a couple of trials for the subjects to learn the optimal behaviors. In the actual experiment, their performance slowly improved until it reached a plateau around 60 trials. Thus, even though unconscious learning and decision-making happens, conscious learning and decision-making can be significantly more effective.

Second, while I don’t see Dehaene mentioning it, I’ve always liked the PRISM theory of consciousness, which suggests that one of the functions of consciousness is to be a place for resolving conflicting plans for controlling the skeletal muscles. In the unconscious decision-making experiments, the tasks have mostly been pretty simple, and only involved the kinds of goals that could all be encapsulated within a single motivational system. In real life however, we often run into situations where different brain systems output conflicting instructions. For instance, if we are carrying a hot cup of tea, our desire to drop the cup may be competing against our desire to carry it to the table, and these may have their origin in very different sorts of motivations. Information from both systems would need to be taken into account and integrated in order to make an overall decision.

To stretch Dehaene’s FBI metaphor: as long as the FBI is doing things that fall within their jurisdiction and they are equipped to handle, then they can just do that without getting in contact with the President. But if the head of the FBI and the head of the CIA have conflicting ideas about what should be done, on a topic on which the two agencies have overlapping jurisdiction, then it might be necessary to bring the disagreement out in the open so that a higher-up can make the call. Of course, there isn’t any single “President” in the brain who would make the final decision: rather, it’s more like the chiefs of all the other alphabet soup bureaus were also called in, and they then hashed out the details of their understanding until they came to a shared agreement about what to do.

Lasting thoughts and working memory

As already touched upon, consciousness is associated with memory. Unconsciously registered information tends to fade very quickly and then disappear. In all the masking experiments, the duration between the prime and the target is very brief; if the duration would be any longer, there would be no learning or effect on decision-making. For e.g. associating cues and outcomes with each other over an extended period of time, the cue has to be consciously perceived.

Dehaene describes an experiment which demonstrates exactly this:

The cognitive scientists Robert Clark and Larry Squire conducted a wonderfully simple test of temporal synthesis: time-lapse conditioning of the eyelid reflex. At a precisely timed moment, a pneumatic machine puffs air toward the eye. The reaction is instantaneous: in rabbits and humans alike, the protective membrane of the eyelid immediately closes. Now precede the delivery of air with a brief warning tone. The outcome is called Pavlovian conditioning (in memory of the Russian physiologist Ivan Petrovich Pavlov, who first conditioned dogs to salivate at the sound of a bell, in anticipation of food). After a short training, the eye blinks to the sound itself, in anticipation of the air puff. After a while, an occasional presentation of the isolated tone suffices to induce the “eyes wide shut” response.
The eye-closure reflex is fast, but is it conscious or unconscious? The answer, surprisingly, depends on the presence of a temporal gap. In one version of the test, usually termed “delayed conditioning,” the tone lasts until the puff arrives. Thus the two stimuli briefly coincide in the animal’s brain, making the learning a simple matter of coincidence detection. In the other, called “trace conditioning,” the tone is brief, separated from the subsequent air puff by an empty gap. This version, although minimally different, is clearly more challenging. The organism must keep an active memory trace of the past tone in order to discover its systematic relation to the subsequent air puff. To avoid any confusion, I will call the first version “coincidence-based conditioning” (the first stimulus lasts long enough to coincide with the second, thus removing any need for memory) and the second “memory-trace conditioning” (the subject must keep in mind a memory trace of the sound in order to bridge the temporal gap between it and the obnoxious air puff).
The experimental results are clear: coincidence-based conditioning occurs unconsciously, while for memory-trace conditioning, a conscious mind is required. In fact, coincidence-based conditioning does not require any cortex at all. A decerebrate rabbit, without any cerebral cortex, basal ganglia, limbic system, thalamus, and hypothalamus, still shows eyelid conditioning when the sound and the puff overlap in time. In memory-trace conditioning, however, no learning occurs unless the hippocampus and its connected structures (which include the prefrontal cortex) are intact. In human subjects, memory-trace learning seems to occur if and only if the person reports being aware of the systematic predictive link between the tone and the air puff. Elderly people, amnesiacs, and people who were simply too distracted to notice the temporal relationship show no conditioning at all (whereas these manipulations have no effect whatsoever on coincidence-based conditioning). Brain imaging shows that the subjects who gain awareness are precisely those who activate their prefrontal cortex and hippocampus during the learning.

Carrying out artificial serial operations

Consider what happens when you calculate 12 * 13 in your head.

When you do so, you have some conscious awareness of the steps involved: maybe you first remember that 12 * 12 = 144 and then add 144 + 12, or maybe you first multiply 12 * 10 = 120 and then keep that result in memory as you multiply 12 * 3 = 36 and then add 120 + 36. Regardless of the strategy, the calculation happens consciously.

Dehaene holds that this kind of multi-step arithmetic can’t happen unconsciously. We can do single-step arithmetic unconsciously: for example, people can be shown a single masked digit n, and then be asked to carry out one of three operations. People might be asked to name the digit (the “n” task), to add 2 to n and report the resulting the number (the “n + 2” task), or to report whether or not it’s smaller than 5 (the “n < 5” task). On all of these tasks, even if people haven’t consciously seen the digit, when they are forced to guess they typically get the right answer half of the time.

However, unconscious two-step arithmetic fails. If people are flashed an invisible digit and told to first add 2 to it, and then report whether the result is more or less than 5 (the “(n + 2) > 5” task), their performance is on the chance level. The unconscious mind can carry out a single arithmetic operation, but it can’t then store the result of that operation and use it as the input of a second operation, even though it could carry out either of the two operations alone.

Dehaene notes that this might seem to contradict a previous finding, which is that the unconscious brain can accumulate multiple pieces of information over time. For instance, in the arrow experiment, people were shown several masked arrows one at a time; at the end, they could tell whether most of them had been pointing to the left or to the right. Dehaene says that the difference is that opening a neural circuit which accumulates multiple observations is a single operation for the brain: and while the accumulator stores information of how many arrows have been observed so far, that information can’t be taken out of it and used as an input for a second calculation.

The accumulator also can’t reach a decision by itself: for instance, if people saw the arrows consciously, they could reach a decision after having seen three arrows that pointed one way, knowing that the remaining arrows couldn't change the overall decision anymore. In unconscious trials, they can’t use this kind of strategic reasoning: the unconscious circuit can only keep adding up the arrows, rather than adding up the arrows and also checking whether a rule of type “if seen_arrows > 3” has been satisfied yet.

According to Dehaene, implementing such rules is one of the functions of consciousness. In fact, he explicitly compares consciousness to a production system: an AI design which holds a number of objects in a working memory, and also contains a number of IF-THEN rules, such as “if there is an A in working memory, change it to sequence BC”. If multiple rules match, one of them is chosen for execution according to some criteria. After one of the rules has fired, the contents of the working memory gets updated, and the cycle repeats. The conscious mind, Dehaene says, works using a similar principle - creating a biological Turing machine that can combine operations from a number of neuronal modules, flexibly chaining them together for serial execution.

A social sharing device

If a thought is conscious, we can describe it and report it to other people using language. I won’t elaborate on this, given that the advantages of being able to use language to communicate with others are presumably obvious. I'll just note that Dehaene highlights one interesting perspective: one where other people are viewed as additional modules that can carry out transformations on the objects in the workspace.

Whether it's a subsystem in the brain that's applying production rules to the workspace contents, or whether you are communicating the contents to another person who then comments on it (as guided by some subsystem in their brain), the same principle of "production rules transforming the workspace contents" still applies. Only in one of the cases, the rules and transformations come from subsystems that are located within a single brain, and in the other case subsystems from multiple brains are engaged in joint manipulation of the contents - though of course the linguistic transmission is lossy, since subsystems in multiple brains can't communicate with the same bandwidth as subsystems in a single brain. (Yet.)

Other stuff

Dehaene also discusses a bunch of other things in his book: for instance, he talks about comatose patients and how his research has been applied to study their brains, in order to predict which patients will eventually recover and which ones will remain permanently unresponsive. This is pretty cool, and feels like a confirmation of the theories being on the right track, but since it’s no longer elaborating on the mechanisms and functions of consciousness, I won’t cover that here.

Takeaways for the rest of the sequence

This has been a pretty long post. Now that we’re at the end, I’m just going to highlight a few of the points which will be most important when we go forward in the multiagent minds sequence:

  • Consciousness can only contain a single mental object at a time.
  • The brain has multiple different systems doing different things; many of the systems do unconscious processing of information. When a mental object becomes conscious, many systems will synchronize their processing around analyzing and manipulating that mental object.
  • The brain can be compared to a production system, with a large number of specialized rules which fire in response to specific kinds of mental objects. E.g. when doing mental arithmetic, applying the right sequence of arithmetic operations for achieving the main goal.

If we take the view of looking at various neural systems as being literally technically subagents, then we can reframe the above points as follows:

  • The brain has multiple subagents doing different things; many of the subagents do unconscious processing of information. When a mental object becomes conscious, many subagents will synchronize their processing around analyzing and manipulating that mental object.
  • The collective of subagents can only have their joint attention focused on one mental object at a time.
  • The brain can be compared to a production system, with a large number of subagents carrying out various tasks when they see the kinds of mental objects that they care about. E.g. when doing mental arithmetic, applying the right sequence of mental operations for achieving the main goal.

Next up: constructing a mechanistic sketch of how a mind might work, combining the above points as well as the kinds of mechanisms that have already been demonstrated in contemporary machine learning, to finally end up with a model that pretty closely resembles the Internal Family Systems one.

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The GNW theory has been kicking about for at least two decades, and this book has been published in 2014. Given this it is almost shocking that the idea wasn't written up on LW before giving it's centrality to any understanding of rationality. Shocking but perhaps fortunate, since Kaj has given it a thorough and careful treatment that enables the reader both to understand the idea and evaluate its merits (and almost certainly to save the purchase price of the book).

First, on GNW itself. A lot of the early writing on rationality used the simplified system 1 / system 2 abstraction as the central concept. GNW puts actual meat on this skeleton, describing exactly what unconscious (formerly known as system 1) processes can and can't do, how they learn, and under what conditions consciousness comes into play. Kaj elaborates more on system 2 in another post, but this review offers enough to reframe the old model in GNW-terms — a reframing that I've been convinced is more accurate and meaningful.

As for the post itself, it's main strength and weakness is that it's very long. The length is not due to fluff — I've compiled my own summary of this post in Roam that runs more than 1,000 words, with almost every paragraph worthy of inclusion. But perhaps, in particular for purposes of a book, the post could more fruitfully broken up in two parts: one to describe the GNW model and its implications, one to cover the experimental evidence for the model and its reliability. The latter takes up almost half of the text of the post by volume, and while it is valuable the former could perhaps stand alone as a worthwhile article (with a reference to a discussion of the experiments so people can assess whether they buy it).

My impression is that GNW is widely accepted to be a leading contender for explaining consciousness, an important problem. This is a nice intro, and having read both this post and the book in question I can confirm that it covers the important ground fairly. I wound up coming around to a different take on consciousness, see my Book Review: Rethinking Consciousness, but while that book didn't talk much about GNW, I found that familiarity with GNW helped me reframe those ideas and understand them better, and indeed my explanation of that theory puts GNW (which I first heard about through this post) front and center. I should add that I find GNW helpful for thinking about thinking in general, not just consciousness per se.

Also, having read both the book and the post, I probably could have just read the post and skipped the book, and wouldn't have missed much.

Promoted to curated: I generally think book reviews and summaries, in particular of books that are relevant to ideas that are currently being explored and people are thinking about, are one of the most robust and reliable ways to produce a lot of value with a post.

I think this book review in particular stands out with its thoroughness, as well as tying the concepts into other discussion of similar topics on LW. I also very much appreciate you going beyond a normal book review, and asking about the reproducibility of the general insights in the book.

Overall, I found this review to be quite useful, well written and to generally be a great example of how I would want a LessWrong book review to be like, and I am looking forward to the rest of your sequence.

Some things that I think could be done better (I expect these will be addressed in future posts of the sequence, but it still seems good to point them out now):

  • I think you could refer more to existing discussion on the topic, and I would greatly appreciate a list of links to existing LessWrong discussion in this space, of which there is plenty.
  • A lot of the post is a relatively straightforward summary of what the author said in the book. I've historically found reviews that contrast the opinion of the book, with your own opinion, to be more useful. Scott Alexander usually does this in his book reviews, and I've found that this makes it easier for the post to point out problems or inconsistencies in the book, which I think overall improves the understanding of the audience when reading the review.

I am still confused about "one object in time" in consciousness. How its is related to the theory of working memory which has 5-7 elements? How I am capable to compare different perceived objects, like colors? Is seeing the whole picture - an illusion, and I see only a small dot every moment?

On the other hand, via introspection I can observe that I concentrate on just one "task" at every given moment. I can deconcentrate my attention, so it will include several objects, but I will still process one task of "deconcentration". And I can quickly multitask between these threads of processing.

That's a good question. Dehaene explicitly talks about the "objects" corresponding to chunks, so that one of the chunks would be consciousness at a time. There's also a finding that when people are asked to maintain a number of words or digits in memory, the amount of items that they can maintain depends on how many syllables those items have. And since e.g. Chinese has shorter words for various digits than English does, native Chinese speakers can maintain more digits in their working memory than native English speakers.

One standard interpretation has been that "working memory" is composed of a number of different storage systems, each of which is capable of rehearsing a memory trace for a limited time. It would be something like a submodule connected to the workspace, which can take items from the workspace and then "play them back", but its memory decays quickly and it has to keep refreshing that memory by putting object that it has stored back into the workspace in order to then re-store them. So consciousness could still only hold one item, but it was augmented by "caches" which allowed it to rapidly circle through a number of items.

The thing about seeing whole pictures confuses me a bit too, though change blindness experiments would suggest that seeing all of it at once is indeed an illusion to at least some extent. One of the things that people tend to notice when learning to draw is also that they actually don't really see the world as it is, and have to separately learn this.

If we're willing to move away from psychological experiments and also incorporate stuff from the theory of meditation, The Mind Illuminated also has the "only one item object at a time" thing, but distinguishes between objects of attention and objects of awareness:

... any moment of consciousness—whether it’s a moment of seeing, hearing, thinking, etc.—takes the form of either a moment of attention, or a moment of peripheral awareness. Consider a moment of seeing. It could be either a moment of seeing as part of attention, or a moment of seeing as part of peripheral awareness. These are the two options. If it’s a moment of awareness, it will be broad, inclusive, and holistic—regardless of which of the seven categories it belongs to. A moment of attention, on the other hand, will isolate one particular aspect of experience to focus on.
If we examine moments of attention and moments of awareness a bit closer, we see two major differences. First, moments of awareness can contain many objects, while moments of attention contain only a few. Second, the content of moments of awareness undergoes relatively little mental processing, while the content of moments of attention is subject to much more in-depth processing. [...]
Consider the first difference, many objects versus only a few, in terms of hearing. Our ears take in everything audible from our environment. Then our brain processes that information and puts it together in two different ways. First, it creates an auditory background that includes more or less all the different sounds our ears have detected. When that’s projected into consciousness, it becomes a moment of auditory peripheral awareness. The other way the brain processes that information is to pick out just some part—say, one person’s voice—from the total sound in our awareness. When projected into consciousness, that isolated sound becomes the content of a moment of auditory attention. So, the brain has two modes of information processing: one creates moments of awareness with many objects, while the other creates moments of attention with just a few.
These two modes apply to every kind of sensory information, not just hearing. For example, say you’re sitting on a cabin deck in the mountains, gazing out at the view. Each moment of visual awareness will include a variety of objects—mountains, trees, birds, and sky—all at the same time. Auditory moments of awareness will include all the various sounds that make up the audible background—birdsong, wind in the trees, a babbling brook, and so forth—again, all at the same time. On the other hand, moments of visual attention might be restricted just to the bird you’re watching on a nearby branch. Auditory attention might include only the sounds the birds are making. Even when your attention is divided among several things at once—perhaps you’re knitting or whittling a piece of wood while you sit—moments of attention are still limited to a small number of objects. Finally, binding moments of attention and binding moments of awareness take the content from the preceding sensory moments and combine them into a whole: “Sitting on the deck, looking out at the mountain, while carving a piece of wood.”

Thanks. Yes, this is how I feel it - I have low level attention to the whole field, and high concentrated cursor-pointer jumping over it constantly, may be few times a second. I've read and practiced a little a practice of "deconcentration of attention" which is attempt to make the the attention as wide as awareness, which is claimed to increase processing capabilities.

Thank you for this helpful summary Kaj. I found the part about what exactly the "conscious" and "unconscious" parts of the mind are capable of fascinating.

In the meditation training I've done, a late step on the path is to let go of consciousness entirely. I haven't experienced this directly so I can't speak much to it, but it certainly suggests that what my teacher means by consciousness is very different to that of this book.

Kaj_sotala's book summary provided me with something I hadn't seen before - a non-mysterious answer to the question of consciousness. And I say this as someone who took graduate level courses in neuroscience (albeit a few years before the book was published). Briefly, the book defines consciousness as the ability to access and communicate sensory signals, and shows that this correlates highly with those signals being shared over a cortical Global Neuronal Workspace (GNW). It further correlates with access to working memory. The review also gives a great account of the epistemic status of the major claims in the book. It reviews the evidence from several experiments discussed in the book itself. The review also goes beyond this, discussing the epistemic status of those experiments (e.g. in light of the replication crisis in psychology).

So kudos to both the book author and the review author. A decent follow-up would be to link these findings to the larger lesswrong agenda (although I note this review is part of a larger sequence that includes additional nominations).

There is a fascinating not yet really explored territory between the GWT and predictive processing.

For example how it may look: there is a paper on Dynamic interactions between top-down expectations and conscious from 2018, where they do experiments in the "blink of mind" style and prediction, and discover, for example

The first question that we addressed was how prior information about the identity of an upcoming stimulus influences the likelihood of that stimulus entering conscious awareness. Using a novel attentional blink paradigm in which the identity of T1 cued the likelihood of the identity of T2, we showed that stimuli that confirm our expectation have a higher likelihood of gaining access to conscious awareness


Second, nonconscious violations of conscious expectations are registered in the human brain Third, however, expectations need to be implemented consciously to subsequently modulate conscious access. These results suggest a differential role of conscious awareness in the hierarchy of predictive processing, in which the active implementation of top-down expectations requires conscious awareness, whereas a conscious expectation and a nonconscious stimulus can interact to generate prediction errors. How these nonconscious prediction errors are used for updating future behavior and shaping trial-by-trial learning is a matter for future experimentation.

My rough takeaway is this: while on surface it may seem that effect of unconscious processing and decision-making is relatively weak, the unconscious processing is responsible for what even gets the conscious awareness. In the FBI metaphor, there is a lot of power in the FBI's ability to shape what even get's on the agenda.

The most obvious example of this kind of thing is the "flash of insight" that we all experience from time to time, where a complex, multi-part solution to a problem intrudes on our awareness as if from nowhere. This seems to be a clear case of the unconscious working on this problem in the background, identifying its solution as a valid one still in the background, and injecting the fully-formed idea into awareness with high salience.

It's a bit like the phenomenon of being able to pick out your own name from a babble of crowded conversation, except applied to the unconscious activity of the mind. This, however, implies that much complex inter-agent communication and abstract problem solving is happening subconsciously. And this seems to contradict the view that only very simple conceptual packages are passed through to the Global Workspace, and that we must necessarily be conscious of our own abstract problem solving.

My own perceptions during meditation (and during normal life) would suggest that the subconscious/unconscious is doing very complex and abstract "thinking" without my being aware of its workings, and intermittently injecting bits and pieces of its ruminations into awareness based on something like an expectation that the gestalt self might want to act on that information.

This seems contrary to the view that "what we are aware/conscious of" is isomorphic to "the Global Workspace". It seems that subconscious modules are chattering away amongst themselves almost constantly, using channels that are either inaccessible to consciousness or severely muted.

Dehaene discusses the "flash of insight" example a bit in the section on unconscious processing. I think the general consensus there is that although solutions can be processed unconsciously, this only works after you've spent some time thinking about them consciously first. It might be something like, you get an initial understanding during the initial conscious information-sharing. Then when the relevant brain systems have received the information they need to process, they can continue crunching the data unconsciously until they have something to present to the rest of the system.

[The mathematician] Hadamard deconstructed the process of mathematical discovery into four successive stages: initiation, incubation, illumination, and verification. Initiation covers all the preparatory work, the deliberate conscious exploration of a problem. This frontal attack, unfortunately, often remains fruitless—but all may not be lost, for it launches the unconscious mind on a quest. The incubation phase—an invisible brewing period during which the mind remains vaguely preoccupied with the problem but shows no conscious sign of working hard on it—can start. Incubation would remain undetected, were it not for its effects. Suddenly, after a good night’s sleep or a relaxing walk, illumination occurs: the solution appears in all its glory and invades the mathematician’s conscious mind. More often than not, it is correct. However, a slow and effortful process of conscious verification is nevertheless required to nail all the details down. [...]
... an experiment by Ap Dijksterhuis comes closer to Hadamard’s taxonomy and suggests that genuine problem solving may indeed benefit from an unconscious incubation period. The Dutch psychologist presented students with a problem in which they were to choose from among four brands of cars, which differed by up to twelve features. The participants read the problem, then half of them were allowed to consciously think about what their choice would be for four minutes; the other half were distracted for the same amount of time (by solving anagrams). Finally, both groups made their choice. Surprisingly, the distracted group picked the best car much more often than the conscious-deliberation group (60 percent versus 22 percent, a remarkably large effect given that choosing at random would result in 25 percent success). The work was replicated in several real-life situations, such as shopping at IKEA: several weeks after a trip there, shoppers who reported putting a lot of conscious effort into their decision were less satisfied with their purchases than the buyers who chose impulsively, without much conscious reflection. 
Although this experiment does not quite meet the stringent criteria for a fully unconscious experience (because distraction does not fully ensure that the subjects never thought about the problem), it is very suggestive: some aspects of problem solving are better dealt with at the fringes of unconsciousness rather than with a full-blown conscious effort. We are not entirely wrong when we think that sleeping on a problem or letting our mind wander in the shower can produce brilliant insights.

I'm not sure why you say that the unconscious modules communicating with each other would necessarily contradict the idea of us being conscious of exactly the stuff that's in the workspace, but I tend to agree that considering the contents of our consciousness and the contents of the workspace to be strictly isomorphic seems to be too strong. I didn't go into that because this post was quite long already. But my own experience is that something like Focusing or IFS tends to create things such as weird visualizations that make you go "WTF was that" - and afterwards it feels like something has definitely shifted on an emotional level. Getting various emotional issues into consciousness feels like it brings them into a focus in a way that lets the system re-process them and may e.g. purge old traumas which are no longer relevant - but the parts of the process that are experienced consciously are clearly just the tip of the iceberg, with most of the stuff happening "under the hood".

This paper also argues something that feels related: Dehaene notes that when we see a chair, we don't just see the raw sensory data, but rather some sensory data and the concept of a chair, suggesting that the concept of a chair is in the GNW. But what is "a concept of a chair"? The paper argues that according to Dehaene, we have something like the concept of a chair in our consciousness / the GNW, but that this a problem for Dehaene's theory because we are never actually aware of an entire concept. Concepts generalize over a broader category, but we are only ever aware of individual instances of that category.

The primary function of concepts [...] is to abstract away [...] so that certain aspects of experiences can be regarded as instances of more wide-ranging, similarity-based categories. In fact, according to the conservative view, it is precisely because concepts always transcend the experiences they apply to that they always remain unconscious. Both Prinz (2012) and Jackendoff (2012) underscore this point:
When I look at a chair, try as I may, I only see a specific chair oriented in a particular way. … it's not clear what it would mean to say that one visually experiences chairness. What kind of experience would that be? A chair seen from no vantage point? A chair from multiple vantage points overlapping? A shape possessed by all chairs? Phenomenologically, these options seem extremely implausible. (Prinz, 2012, p. 74)
Now the interesting thing is that everything you perceive is a particular individual (a token)—you can't perceive categories (types). And you can only imagine particular individuals—you can't imagine categories. If you try to imagine a type, say forks in general, your image is still a particular fork, a particular token. (Jackendoff, 2012, p. 130)
Dehaene (2014, p. 110) expands on the notion that consciousness is like a summary of relevant information by stating that it includes “a multisensory, viewer-invariant, and durable synthesis of the environment.” But neither visual awareness nor any other form of experience contains viewer-invariant representations; on the contrary, possessing a first-person perspective—one that, for sighted people, is typically anchored behind the eyes—is often taken to be a fundamental requirement of bodily self-consciousness (Blanke and Metzinger, 2009). This is quite pertinent to the main topic of this article because, according to the conservative view, one of the reasons why concepts cannot reach awareness is because they always generalize over particular perspectives. This key insight is nicely captured by Prinz (2012, p. 74) in the passage quoted earlier, where he makes what is essentially the following argument: the concept of a chair is viewer-invariant, which is to say that it covers all possible vantage points; however, it is impossible to see or imagine a chair “from no vantage point” or “from multiple vantage points overlapping”; therefore, it is impossible to directly experience the concept of a chair, that is, “chairness” in the most general sense.
In another part of his book, Dehaene (2014, pp. 177–78) uses the example of Leonardo da Vinci's Mona Lisa to illustrate his idea that a conscious state is underpinned by millions of widely distributed neurons that represent different facets of the experience and that are functionally integrated through bidirectional, rapidly reverberating signals. Most importantly for present purposes, he claims that when we look at the classic painting, our global workspace of awareness includes not just its visual properties (e.g., the hands, eyes, and “Cheshire cat smile”), but also “fragments of meaning,” “a connection to our memories of Leonardo's genius,” and “a single coherent interpretation,” which he characterizes as “a seductive Italian woman.” This part of the book clearly reveals Dehaene's endorsement of the liberal view that concepts are among the kinds of information that can reach consciousness. The problem, however, is that he does not explicitly defend this position against the opposite conservative view, which denies that we can directly experience complex semantic structures like the one expressed by the phrase “a seductive Italian woman.” The meaning of the word seductive, for instance, is highly abstract, since it applies not only to the nature of Mona Lisa's smile, but also to countless other visual and non-visual stimuli that satisfy the conceptual criteria of, to quote from Webster's dictionary, “having tempting qualities.” On the one hand, it is reasonable to suppose that there is something it is inimitably like, phenomenologically speaking, to perceive particular instances of seductive stimuli, such as Mona Lisa's smile. But on the other hand, it is extremely hard to imagine how anyone could directly experience seductiveness in some sort of general, all-encompassing sense.

Which is an interesting point, in that on the other hand, before I read that it felt clear to me that if I e.g. look at my laptop, I see "my laptop"... but now that I read this and introspect on my experience of seeing my laptop, there's nothing that would make my mind spontaneously go "that's my laptop", rather the name of the object is something that's available for me if I explicitly query it, but it's not around otherwise.

Which would seem to contradict (one reading of) Dehaene's model - mainly the claim that when we see a laptop, the general concept of the laptop is somehow being passed around in the workspace in its entirety. My best guess so far would be to say that what gets passed around in our consciousness is something like a "pointer" (in a loose metaphoric sense, not in the sense of a literal computer science pointer) to a general concept, which different brain systems can then retrieve and synchronize around in the background. And they might be doing all kind of not-consciously-experienced joint processing of that concept that's being pointed to, either on a level of workspace communication that isn't consciously available, or through some other communication channel entirely.

There's also been some work going under the name of the heterogeneity hypothesis of concepts, suggesting that the brain doesn't have any such thing as "the concept of a chair" or "the concept of a laptop". Rather there are many different brain systems that store information in different formats for different purposes, and while many of them might have data structures that are pointing to the same real-life thing, those structures are all quite different and not mutually compatible and describing different aspects of the thing. So maybe there isn't a single "laptop" concept being passed around, but rather just some symbol which tells each subsystem to retrieve their own equivalent of "laptop" and do... something... with it.

I dunno, I'm just speculating wildly. :)

The freedom to speculate wildly is what makes this topic so fun.

My mental model would say, you have a particular pattern recognition module that classifies objects as "chair", along with a weight of how well the current instance matches the category. An object can be a prototypical perfect Platonic chair, or an almost-chair, or maybe a chair if you flip it over, or not a chair at all.

When you look at a chair, this pattern recognition module immediately classifies it, and then brings online another module, which makes available all the relevant physical affordances, linguistic and logical implications of a chair being present in your environment. Recognizing something as a chair feels identical to recognizing something as a thing-in-which-I-can-sit. Similarly, you don't have to puzzle out the implications of a tiger walking into the room right now. The fear response will coincide with the recognition of the tiger.

When you try to introspect on chairness, what you're doing is tossing imagined sense percepts at yourself and observing the responses of the chariness detecting module. This allows you to generate an abstract representation of your own chairness classifier. But this abstract representation is absolutely not the same thing as the chairness classifier, any more than your abstract cogitation about what the "+" operator does is the same thing as the mental operation of adding two numbers together.

I think a lot of confusion about the nature of human thinking stems from the inability to internally distinguish between the abstracted symbol for a mental phenomenon and the mental phenomenon itself. This dovetails with IFS in an interesting way, in that it can be difficult to distinguish between thinking about a particular Part in the abstract, and actually getting into contact with that Part in a way that causes it to shift.

I'm not sure why you say that the unconscious modules communicating with each other would necessarily contradict the idea of us being conscious of exactly the stuff that's in the workspace, but I tend to agree that considering the contents of our consciousness and the contents of the workspace to be strictly isomorphic seems to be too strong.

I may be simply misunderstanding something. My sense is that when you open the fridge to get a yogurt and your brain shouts "HOW DID CYPHER GET INTO THE MATRIX TO MEET SMITH WITHOUT SOMEONE TO HELP HIM PLUG IN?", this is a kind of thought that arises from checking meticulously over your epistemic state for logical inconsistencies, rather esoteric and complex logical inconsistencies, and it seems to come from nowhere. Doesn't this imply that some submodules of your brain are thinking abstractly and logically about The Matrix completely outside of your conscious awareness? If so, then this either implies that the subconscious processing of individual submodules can be very complex and abstract without needing to share information with other submodules, or that information sharing between submodules can occur without you being consciously aware of it.

A third possibility would be that you were actually consciously thinking about The Matrix in a kind of inattentive, distracted way, and it only seems like the thought came out of nowhere. This would be far from the most shocking example of the brain simply lying to you about its operations.

To my reading, all of this seems to pretty well match a (part of) the Buddhist notion of dependent origination, specifically the way senses beget sense contact (experience) begets feeling begets craving (preferences) begets clinging (beliefs/values) begets being (formal ontology). There the focus is a bit different and is oriented around addressing a different question, but I think it's tackling some of the same issues via different methods.

When you look at a chair, this pattern recognition module immediately classifies it, and then brings online another module, which makes available all the relevant physical affordances, linguistic and logical implications of a chair being present in your environment. Recognizing something as a chair feels identical to recognizing something as a thing-in-which-I-can-sit. Similarly, you don't have to puzzle out the implications of a tiger walking into the room right now. The fear response will coincide with the recognition of the tiger.

Yeah, this is similar to how I think of it. When I see something, the thoughts which are relevant for the context become available: usually naming the thing isn't particularly necessary, so I don't happen to consciously think of its name.

Doesn't this imply that some submodules of your brain are thinking abstractly and logically about The Matrix completely outside of your conscious awareness? If so, then this either implies that the subconscious processing of individual submodules can be very complex and abstract without needing to share information with other submodules, or that information sharing between submodules can occur without you being consciously aware of it.

Well, we already know from the unconscious priming experiments that information-sharing between submodules can occur without conscious awareness. It could be something like, if you hadn't been conscious of watching The Matrix, the submodules would never have gotten a strong enough signal about its contents to process it; but once the movie was once consciously processed, there's enough of a common reference for several related submodules to "know what the other is talking about".

Or maybe it's all in one submodule; the fact that that submodule feels a need to make its final conclusion conscious, suggests that it can't communicate the entirety of its thinking purely unconsciously.

I really want to read a book focusing on vigilance. Conscious access seemed like the least interesting of the three by far.

Cognitive neuroscience is generally considered a subfield of cognitive psychology, and cognitive psychology is the part of psychology whose results have so far replicated the best.

I don't think it makes any sense to see cognitive neuroscience as a subject of cognitive psychology. In cognitive psychology scientists do well-controlled experiments. In cognitive neuroscience many people try to predict the trainings data of their models. The epistemic hygiene of the fields are very different.

"Cognitive psychology is the field that consists of experimental cognitive psychology, cognitive neuroscience, cognitive neuropsychology, and computational cognitive science" was the breakdown used in my cognitive psychology textbook (relatively influential, cited 3651 times according to Google Scholar). There's also substantial overlap in the experimental setups: as in many of the experiments mentioned in the post, lots of cognitive neuroscience experiments are such that even if you removed the brain imaging part, the behavioral component of it could still pass on its own as an experimental cognitive psychology finding. Similarly, the book cites a combination of neuroimaging and behavioral results in order to build up its theory; many of the priming experiments that I discuss, also show up in that list of replicated cognitive psychology experiments.

Re: the voodoo correlations paper - I haven't read it myself, but my understanding from online discussion is that the main error that it discusses apparently only modestly overstates the strength of some correlations; it doesn’t actually cause entirely spurious correlations to be reported. The paper also separately discusses another error which was more serious, but only names a single paper which was guilty of that error, which isn't very damning. So I see the paper mostly as an indication of the field being self-correcting, with flaws in its methodologies being pointed out and then improved upon.

The voodoo paper starts by noting that the social neuroscience papers regularly report values that are higher then the theoretical maximum.

I find a defense of neuroscience against the Voodoo paper that ignores that the charge of the Voodoo paper that the results of the claimed social neuroscience papers achieve impossible results (you could call them paranormal), to be no good defense.

Whether or not it causes entirely spurious correlations to be reported depends on the degrees of freedom that models have. If you have a dataset with 200 patients and 2000 degrees of freedom in your mathematical model. The neuroscience folks often use statistical techniques where there's no mathematically sound method to assess the degrees of freedom. Frequently, they run some simulated data through the model to eyeball the amount of the problem, but there are no mathematical guarantees that this will find every case when the degrees of freedom are two high.

Even if you grant it's only modest overstating. Scientists are generally not expected to modestly overstate their results but are supposed to remove systematic effects that make them overstate their results.

Even if you think that there's some value in predicting training data, they could still run a second test where they split their data into two a trainings data pile and an evaluation pile and run their model again and report the results. It's not much work as they don't need to create a new model. It's 4 lines of R (maybe even less if you write it concisely).

in that attentional blink experiment why is T2 visible ≈75% of the time at first when lag is 100ms ? I seem to be missing something because it contradicts the finding 

I remember wondering about the same thing. I don't remember it being addressed in the book, but I'm guessing that in that case, T2 comes so fast that the workspace mechanisms don't have the time to "lock on" to T1 very strongly and T2 manages to overwrite it before that.

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