Ephemeral, ineffable, the ghost in the machine, since the days when we could begin to think about our thoughts, we have attempted to describe the experience of consciousness. We have to. Describing and agreeing on this sensation with one another is the only way we can reassure each other that we feel it too, that we aren’t the only ones experiencing sentience. As Descartes described in his “I think, therefore I am” thought experiment, our introspection proves only our own existence, and thus there is no way for us to prove that anyone or anything else experiences this phenomenal characteristic of life. But that may not always be the case. Neuroscience is racing, literally in some instances, to understand consciousness. Although we have not reached an answer yet, several popular theories have emerged over time that may help us to shed light on our existence.

Higher Order Theories

The highest on the list, pun intended, comes the collection of theories that rely on a top-down view of consciousness. Here, mental states are experienced as “conscious” when they are the target of specific higher-order so-called ‘meta-representations’. Your perception of a landscape, for example, is only felt consciously because lower-order signals in your visual cortex are targeted by certain higher-order meta-representations in your anterior cortex, especially the prefrontal cortex. ‘Higher-order regions’ refers here to brain areas dedicated to cognitive processes that are considered to be more advanced, such as analysis and evaluation of signals. The lower-order regions meanwhile are less complex and are usually involved in direct transfer, processing and reaction to incoming information. 

These Higher Order Theories are supported by a mixture of lesion studies and functional network studies that link the anterior cortex to metacognition. Furthermore, these theories explain why some signals are experienced consciously, and some aren’t: they can either be targeted by higher order meta-representations or simply cannot be. Take our landscape scene again; your visual cortex network that processes the view of the trees, hills and beautiful sky are targeted by higher-order functional networks that provide the meta-representation of the scene (making you experience it consciously), but the sound of the gate creaking behind you is not experienced consciously because it cannot be targeted at that time. 

Global Workspace Theory

First proposed by Daniel Bor, the GWT provides a very functional approach to consciousness. Here, a mental state is experienced as conscious when it enters a distributed network referred to as the Global Workspace. How does this happen? By subconsciously shifting our attention to signals, we raise them into the Global Workspace such that they enter the conscious mind. Where higher order theories rely on specific functional regions in the frontal cortex acting on incoming signals, the GWT is by definition globally distributed across the brain, thus promoting cognitive processes from working memory to perception. This theoretical “workspace” depends on both prefrontal and parietal cortices in the brain becoming active and communicating via ultra-fast brainwaves, resulting in a  widespread network interconnectivity. 

This theory is considered highly functional however, because although it explains effectively how processes become consciously experienced, it does not account for the phenomenal differences of experience between types of cognitive process. For example, GWT explains why a view of the sunset is felt consciously, but does not explain why the conscious feeling of seeing a tree differs from a sunset, or even why no two sunsets are ever seen the same way. 

Integrated Information Theory

Mathematically derived by Giulio Tononi, IIT attempts to understand consciousness as a measurable phenomenon with a unit of “phi” Φ that is expressed, like a computer, in bits. Phi interprets the amount of information generated as a whole entity in comparison to the parts of the system alone. Consequently, consciousness is a fundamental property of any system as defined by the complexity and state of the system. In the brain, this implies that consciousness arises more from the neuron-dense posterior areas, where by virtue of their network complexity, the value of phi should be greater. However, this theory would also imply that any system, if complex enough, could and already does experience a degree of consciousness, no matter how natural or synthetic. This implies a degree of panpsychism (the belief that everything experiences a degree of consciousness) where even a sufficiently complex n by n grid of XOR gates would produce a phi value greater than that of the human brain. Given that mycelial networks span tens of square kilometres and are deeply complex, where does that leave us on the consciousness sale?

The Attention Schema

Based on the discoveries of the models that our brains create to represent things in the world from our bodies to physical space, the attention schema describes an internal model generated by the brain to represent the brain. Here, attention is once more key to the theory, and this simplified description of the brain exists to control our attention. Without this attention model we would be overwhelmed by the sheer volume of raw information that enters the brain through various signalling pathways. Consciousness, as a simplified, descriptive model of the brain ensures that our attention is focused, thus ensuring that the information is used purposefully. 

This theory aims to answer how consciousness would arise in the first instance; we evolved it to streamline our wandering attention and have control over our actions. Indeed, Michael Graziano, who proposed the Attention Schema theory, enforces this point by highlighting that the process of natural selection by which evolution occurs often generates the most efficient answer to a pressure. By nature of its simplicity (a model of the brain that controls our attention), the attention schema theory of consciousness is thus the most compelling explanation for the appearance of consciousness, he argues. How such a model of the brain could be quantified remains to be seen.

Predictive Processing Theories

Once more favouring a top-down model of consciousness are the predictive processing theories. Much like GWTs, predictive processing theories rely on studies that have demonstrated damage to prefrontal areas leads to changes in the subject’s conscious experience. Although not a theory of consciousness in its own right, PPTs are based on a well established notion of top-down predictions from higher-order cortical areas and bottom-up prediction errors arising due to signals from lower-order regions. How this works is relatively straightforward, our brains are always making predictions about its environment, these predictions are then compared against the reality of the environment. The predictions arise from so-called higher-order regions, hence they proceed from the top of the cognitive hierarchy downwards. This comparison against the reality of the environment is called prediction error. If the prediction error is low, then our prediction was correct, if it is high, then our prediction was incorrect and the information is updated for better predictions in the future. 

This relationship is similar to that of Bayesian inference, and it’s the established nature of the prediction error relationship combined with the mathematically familiar Bayesian probability that makes PPTs a compelling theory of consciousness for many. How this arises as our conscious experience has to do with our brain’s best predictions about the causes of its incoming signals. Our experience of feeling sad is the brain’s best guess based on bottom up signalling on the status of the body and our surroundings, as a result we experience sadness. 

Opinion

It is no doubt evident to many that there is a great deal of overlap between these theories, and this is not entirely surprising as much like religions, some of these are off-shoots and branches from one another. Some are built from a more pragmatic and mathematical framework, whereas others are theories that incorporate more elements of the human experience. It is easy to get lost in the empirical in neuroscience and taking a step back to observe how we perceive our conscious experience before trying to tie it down into one unifying theory is just as important as running the numbers. The attention schema, for example, captures the experience of feeling like the “ghost in the machine”, but this does not make you a separate entity from your body and brain, as this attention can be a part of other theories that incorporate the role of attention, namely the Global Workspace or Predictive Processing. Your beliefs in whether consciousness is unique to our species play a role too. Higher-order theories assume that consciousness is solely the quality of creatures possessing specific higher-order brain regions, while Integrated Information Theories indicate that anything with sufficient complexity may be considered conscious. In his recent book, Dr Anil Seth makes the point that measurement is often a great turning point in scientific fields, and one day perhaps we will be able to measure consciousness in all living things. Maybe then we can finally prove Descartes wrong. 

Author: Thomas von Rein

References:

• Theories of Consciousness https://www.nature.com/articles/s41583-022-00587-4#Sec9
• Being You: A New Science of Consciousness by Anil Seth, PhD
• The Essential Guide to Consciousness https://shop.newscientist.com/collections/the-essential-guide/products/essential-guide-12-consciousness?variant=40024822480993 

You have probably noticed that your mental state and the conscious experience of the world surrounding you feels different depending on the activity you are engaged in. For instance, being deeply focused on a task, about to fall asleep, dreaming, or running a 100-meter sprint go together with different “modes of consciousness”. Even if there is no clear and universally accepted definition for the word consciousness, it can simply be put as a term to describe the awareness or perception of your physical and mental experience. Those different “modes” mentioned hereinabove depict a few examples of normal, healthy states of consciousness. Nonetheless, other sorts of conscious experiences defined as altered states of consciousness can arise through meditation, somatic and mental illnesses, or drug consumption. In this article, I will focus on the particular altered state of consciousness induced by a specific class of drugs, referred to as hallucinogens or psychedelics. You have probably already heard of LSD or psilocybin, however, I will show you how they affect the human brain and how they can reshape our internal and external perceptions.

Psychedelics and the brain

Psychedelics drugs represent a class of psychoactive compounds producing significant changes in perception, mood, and cognitive processes. This umbrella term includes a few main substances, all found or derived from naturally occurring organisms. Among them LSD may be the most famous one, and is derived from a fungus that grows on rye. Then, psilocybin is a compound found in multiple so-called magic mushrooms. Finally, DMT, considered the most potent drug by many, is found in plants, but also in humans, in the pineal gland. The unifying characteristic of these various molecules is that they are all serotonin 2A receptor (also written 5-HT2A receptors) agonists. Are we going too fast? Let’s step back and have a look at how the brain communicates.

Our brain contains many neurons that secrete signaling molecules that affect other neurons across a kind of chemical bridge that we refer to as synapses. These molecules are called neurotransmitters, and you may be familiar with some of them, like dopamine, glutamate, GABA, noradrenaline, or serotonin. Each of these neurotransmitters are secreted and can bind to specific neurons of the same family through customized receptors placed on the surface of the second neuron of the “bridge”, called the postsynaptic neuron. Specifically, the serotonin system, which is of interest in psychedelics, includes 15 subtypes of receptors. Because the classic psychedelics mentioned before have a very similar chemical structure to that of the neurotransmitter serotonin, they are also able to bind to these same serotonin receptors, particularly to the 5-HT2A. Thus, when one ingests for instance a dose of LSD, the drug mimics the serotonin and binds to these various serotonin receptors, leading to a very complex and not yet fully comprehended restructuration of the brain function.

The work of different researchers including Dr. Carhart-Harris show that psychedelics induce a decreased activation in different structures of the brain, which are part of the “default mode network”, including the thalamus, the cingulate cortex, and the medial prefrontal cortex. These regions are not restricted to specific functions, but rather, act as important centers of information integration. Therefore, they can be compared to disciplinarians or important institutions holding and monitoring the system together in a balanced way. As a result, when such structures are inhibited, a subsequent sort of chaos emerges in the brain. This happens through increased functional connectivity, an indicator of the intensity in which brain regions interact with each other, between areas of the brain that do not often communicate, or at least not in the same manner. Eventually, this unique kind of interplay among brain structures gives rise to a myriad of psychological and subjective changes altering the normal state of consciousness, which will be discussed in the following section. That being said, this neurobiological explanation is conspicuously oversimplified, and much is still to be discovered about the precise operation of the brain in a psychedelic state.

Psychedelics and the mind

As we saw in the first section, consciousness refers to the perception of internal and external stimuli. As you can imagine after reading section two, when the disciplinarians of the brain are inhibited, and therefore many other brain areas start communicating differently, the subsequent perception and interpretation of one’s thoughts, feelings, or surroundings might change radically. The primary tool used to assess one’s conscious experience is the 5-Dimensional Altered States of Consciousness Questionnaire (5D-ASC). Unsurprisingly, it contains five overarching dimensions: oceanic boundlessness, visionary restructuralization, anxious ego dissolution, auditory alterations, and reduction of vigilance. Here I will discuss only the first three dimensions.

The first one, oceanic boundlessness, includes lower-order scales such as feelings of unity (with the world or other living organisms), spiritual or religious experiences, or a blissful state. Many tribes in Latin America for instance embedded psychedelic experiences into their cultures for many centuries. Some of them also organized religious rituals around the consumption of these compounds, and the experiences described in this dimension are presumably at the root of such practices.

Then, the most famous one, visionary restructuralization, basically refers to the visual hallucinations that can occur during a trip, but this is not everything. As described previously, the thalamus is one of the brain structures inhibited by psychedelic consumption. It can be simply defined as a sensory hub, and therefore all the input coming from the external world (visuals, smells, sounds, etc.) are processed differently by the psychedelic brain. Thus, it can result in the linking of different senses together. As a matter of fact, some people report hearing a color, or seeing a song. Such experiences are called audio-visual synesthesia.

Last but not least, feelings of anxious ego-dissolution can appear in the form of impaired control and cognition, disembodiment, or anxiety, and can hence provoke a “bad trip”. Indeed, a psychedelic adventure involves important contingencies, and two critical variables to control in order to diminish the risk of acute adverse psychological effects to classic hallucinogens are the set and setting. The set is defined as the mindset or the preparation of the individual toward the psychedelic experience, including personality and the current mood. The setting encompasses the atmosphere as well as the physical, social, and cultural environment in which the user lives his experience.

Future perspectives

Even if psychedelic drugs bear a contentious history and are still controversial today, their future seems brighter than ever. Indeed, many scientists have investigated their potential for treating psychopathologies characterized by reduced communication between different parts of the brain. Among them, LSD and psilocybin show encouraging evidence for reducing symptoms in obsessive-compulsive disorder (OCD), addictions, depression, and anxiety. At the same time, MDMA is already approved to treat PTSD in the USA and has demonstrated to be highly effective. Furthermore, Australia recently allowed the use of psilocybin for treatment-resistant depression, and of MDMA for treating PTSD. More research is being done but the future of treatments for mental disorders will presumably incorporate psychedelic compounds.

If this subject got you interested, you should definitely check this article; https://www.brainmatters.nl/en/tripping-terror-psychedelics-and-fear/

Author: Pablo de Chambrier

References:

• Carhart-Harris, R., Leech, R., & Tagliazucchi, E. (2014). How do hallucinogens work on the brain. Journal of Psychophysiology, 71(1), 2-8.

Did you decide of your own free will to read this article? Or is your decision the inevitable result of interactions between brain cells that proceed according to immutable laws of nature? French scientists shed new light on a classic study that decades ago dismissed free will as an illusion.

The idea that free will does not really exist was given a neuroscientific foundation by experiments conducted by physiologist Libet in the 1970s and 1980s. He asked subjects to make a wrist movement at a self-selected moment. Just over half a second before they felt the first urge to move, Libet noticed an abnormal signal on his EEG equipment, which measured electrical activity in the brain. It was concluded that the brain has already made its decision before we become aware of it.

Spontaneous activity

French researchers led by Aaron Schurger now say something else may be going on after all. They say the trigger to make the spontaneous wrist movement is due to involuntary variations in brain activity: noise that is always present in the system. They think a slow build-up of such spontaneous activity caused the increase in Libet's EEG signal. This does not mean that the decision to move the wrist has already been made unconsciously by the brain. It is only when the accumulation of noise exceeds a certain threshold that the intention to move arises.

To test that hypothesis, Schurger and his team repeated Libet's classic experiment, asking subjects to spontaneously make a hand movement whenever they wanted to. In addition, the researchers also played tones at random moments after which the movement had to be performed immediately.

Small chance

In cases where subjects responded very quickly to the tone, their EEG signal already showed a slow build-up of brain activity. Presumably, this allowed them to decide to move more quickly after hearing the tone. That buildup, according to Schurger, must in most cases have been the result of random fluctuations, since the chances of a spontaneous decision coinciding with a tone would, in fact, be very small. In short, there seems to be another (perhaps plausible) explanation for Libet's findings: In the absence of meaningful signals/reasons to move (such as hearing the tone), it could well be that this spontaneous higher activity is tipping the scale to make the decision to move the wrist.

Hard evidence for the existence of free will has still not been found. Aaron Schurger only shows another possible explanation for Libet's results. Scientists still disagree on whether free will exists or not, therefore we cannot give you an unequivocal answer to this question. So you are free to take your own position on this (or not?). 

Author: Daan Schetselaar (edited by Pauline van Gils)

References:

• Schurger, A., Pak, J., & Roskies, A. L. (2021). What is the readiness potential?. Trends in cognitive sciences, 25(7), 558-570.

Visual illusions are pretty cool! Whether it’s images of old ladies turning into young dames or colorful vortices seemingly revolving around themselves, people tend to be fascinated with the tricks that can be played on their brains with pretty simple 2D images.

One type of visual illusion are ‘bi-stable- images’, like the one below:

This is a relatively well-known bistable image called the ‘Jastow rabbit-duck’. As you may have noticed, it’s possible to see either a rabbit or a duck, but never both at the same time. Your perception switches between the two images, which is why it’s also called ‘bistable perception’.

Pretty awesome, right? Another kind of visual illusion out there is the ‘illusory contour’. Here, typically a geometric figure is seemingly observed even though no outline is given for such a figure. Let me demonstrate:

Most likely you see a second triangle on top of the outlined one, pointing downward, whose corners are defined by the three Pacman-like circles, like so:

This triangle is our illusory contour, and this specific figure is called a ‘Kanizsa triangle’.

But how does that work in the brain exactly? Well, a paper by von der Heydt and colleagues investigated this in the visual cortex of macaque monkeys. Using microelectrodes that directly entered the animals’ brains, the researchers were able to record the electrical activity of individual neurons in the primary (V1) and secondary (V2) visual cortex*. They then showed an illusory contour to the monkeys and tried to record some neurons whose receptive field included the real, visible lines and some whose receptive fields included the illusory lines (like the ones outlined in orange above). 

Never heard of ‘receptive fields’? Here’s a quick explanation: The receptive field of a neuron is basically the place in your field of view to which that particular neuron responds. Individual neurons in V1 only cover a tiny bit of your visual field, but together they cover all of it. That’s the same in V2 and other higher visual areas, but the receptive fields of the neurons actually get bigger, the higher up the visual area. So receptive fields in V2 for example are already a bit bigger than in V1, but not as big as in V4. 

Then, when appropriate neurons were found in V1 and V2, the researchers moved the stimulus back and forth across the cells’ receptive fields. When doing this with a visible, non-illusory line, neurons in both V1 and V2 reacted with bursts of firing since the light in their receptive fields was changing during this movement. But what do you think happened for the neurons whose receptive fields only had moving illusory lines in them? Well, this is where it gets interesting: Neurons in V1 did not change their firing in response to the ‘lines’ moving, but many V2 neurons did. So, the neurons recorded from V2 responded as if the illusory line had actually been a real one! This may be the case since V1 seems to be responsive mostly to the orientation of seen stimuli and acts as a sort of ‘edge detector’ that tends to detect the outlines of things seen, but not much more**. V2 in contrast can already detect more complex visual features such as whether a figure is part of the foreground or background of an image. In general, the higher the visual area, the more complex the features it is there to detect. Thus, V2 neurons react to illusory contours which V1 neurons do not seem to ‘see’. 

Alright, this concludes our foray into duck-rabbits, invisible triangles and our quirky visual system. Stay amazed, and ‘see’ you soon! 

*If you’d like to learn more about the visual system of the brain, check out this article in our database: https://www.brainmatters.nl/en/database/visual-system/

**At least this is true early in the response to a stimulus (first 100ms). V1 also receives slightly delayed feedback from higher visual areas that broadens its functions + higher visual areas also receive (feedforward) information from lower ones such as V1, which are incorporated into their own responses! 

Author: Melanie Smekal

References:

• Von der Heydt, R., Peterhans, E., & Baumgartner, G. (1984). Illusory contours and cortical neuron responses. Science, 224(4654), 1260-1262. https://ui.adsabs.harvard.edu/abs/1984Sci...224.1260V/abstract

Last year, I listened to one of my fellow Master students explaining that some people can control their dreams by realizing that they were dreaming. I got intrigued about this type of dreaming better known as lucid dreaming. It struck me that while you dream you have literally endless possibilities to give structure to these and do whatever you want! For this reason even if you have already read the previous article about lucid dreaming, I would like to elaborate a bit more on this intriguing idea of being ‘conscious’ while asleep.  

Besides me, many researchers became interested in studying the brain basis of conscious states and demonstrating how voluntarily training lucid dreaming can change these states. However, how to actually measure this dreaming condition remained rather difficult, since no tools to objectively measure this were available until the 1970s. The electrooculogram (EOG) which is a measure to pick up electrical signals caused by voluntary eye movements made it for the first time possible to do so. Based on prior research showing that participants can voluntarily move their eyes in a distinct sequence to show that they are lucid-dreaming at that time point, sparked the idea to measure these voluntary eye movements by making use of EOG. The most common eye signaling technique currently used in research is asking participants to signal when they realize that they are dreaming to  rapidly look left and right two times consecutively and then back to the center (left-right-left-right eye signals). In combination with subjective reports of the participant mentioning the lucid dreaming episode, measuring their electroencephalogram (EEG) while they are sleeping forms the golden standard to objectively indicate if a person is lucid dreaming.

The eye signaling technique as measured by EOG in combination with EEG opened the gateway towards studying brain activity in lucid dreamers. At first, researchers thought that lucid dreaming was a rapid eye movement (REM) sleep (dream sleep) phenomenon, since it usually emerged during this type of sleep. However, research is slowly moving toward the hypothesis that lucid dreaming is a hybrid state between being awake and in REM sleep. Researchers have started exploring this hypothesis by comparing the brain’s electrical activity when a person is awake, in non-lucid REM sleep, and in lucid REM sleep. 

An example of such a study is a study by Voss and colleagues. They measured the EEG and EOG activity of 6 undergraduate students at Bonn University, who were able to lucid dream after following four months of weekly lucidity training sessions. Interestingly, the electrical activity measured in these 6 students during lucid REM sleep was not comparable to the electrical activity measured during either their waking state or while they were in non-lucid REM sleep. Normally when you are awake your electrical activity in the brain is characterized by high alpha power (one of the electrical brain waves or oscillations named after their frequency, other examples are beta, gamma, etc.). In this study, the researchers showed that when students were awake, they had significantly higher alpha electrical activity in their brains compared to when they were in lucid REM sleep or non-lucid REM sleep. Moreover, in the case of gamma power, this was significantly elevated when the students were in lucid REM sleep compared to when they were awake or in non-lucid REM sleep.

What does this mean you might wonder?  Normally, alpha power is often associated with a state of wakeful resting. However, when we are lucid dreaming our brain is quite active, since we have to control our own dream. This could explain why gamma power is increased during lucid REM sleep and not during eyes open resting or non-lucid REM sleep. This increase in gamma power was especially seen in the frontal parts of the brain. This is in accordance with the fact that lucid dreaming is a dreaming state characterized by regaining higher cognitive capabilities such as the awareness that you are dreaming. This is in contrast to non-lucid REM sleep, where neural activity in these areas is decreased, leading to visual hallucinations, emotional experiences or you seeing yourself randomly fighting a dragon for no reason. 

According to the research described above, it seems quite likely that lucid dreaming is a hybrid state of consciousness, since it shows measurable differences in electrical activity compared to awakeness and non-lucid REM sleep. However, a review by Dresler and colleagues points out that most studies investigating lucid dreaming,  like the study described earlier, have very few participants and therefore replication of findings remains difficult. Specifically, the increase in gamma power in frontal parts of the brain can be influenced by eye movements itself. This makes it difficult for researchers to interpret this increase in electrical activity, since fully filtering out the influence of these eye movements is not possible (yet). Therefore, we cannot be certain that lucid dreaming indeed is a hybrid state of consciousness. Maybe after a couple of years and more large-scale EEG studies including more participants, we can unravel this mysterious phenomenon of  lucid dreaming.. 

Author: Joyce Burger

Illustration: Joyce Burger

References:

• Baird, B., Mota-Rolim, S. A., & Dresler, M. (2019). The cognitive neuroscience of lucid dreaming. Neuroscience & biobehavioral reviews, 100, 305-323. 
• Dresler, M., Wehrle, R., Spoormaker, V. I., Koch, S. P., Holsboer, F., Steiger, A., Obrig, H., Sämann, P. G., & Czisch, M. (2012). Neural correlates of dream lucidity obtained from contrasting lucid versus non-lucid REM sleep: a combined EEG/fMRI case study. Sleep, 35(7), 1017-1020. 
• Hobson, A. (2009). The neurobiology of consciousness: Lucid dreaming wakes up. International Journal of Dream Research, 2(2), 41-44. 
• Voss, U., Holzmann, R., Tuin, I., & Hobson, A. J. (2009). Lucid dreaming: a state of consciousness with features of both waking and non-lucid dreaming. Sleep, 32(9), 1191-1200.