How does the order of our thinking develop and what disturbs it? It is possible that we can soon understand the principles of thinking and help sick people. But can we also read minds? A lot is actually possible with technical systems today, but more would have to be done to be able to read minds properly.
- Groups of neurons that are active together during a certain thought are probably the cellular correlate of thinking. These groups are flexible, short-term coalitions (so-called "assemblies") that can form new groups again and again.
- Assemblies do not necessarily have to be spatially adjacent, but are often distributed over the cerebral cortex. Pattern recognition methods, which are linked to an imaging system, can learn the activity distribution specific to a thought in the cortex and thus "read out" the thought later from the activity of the brain..
- However, it is unlikely that it will be possible to fully detect the full richness of individual thinking through such methods, because the infinitely many, in some cases not verbalizable, mental processes of a person are faced with an infinite number of combinations of neuronal signals.
Onur Güntürkun is a biopsychologist at the Ruhr University in Bochum. After graduating from high school in Turkey, he studied and obtained his doctorate in psychology in Bochum and was then a postdoc in Paris, San Diego and Constance. He is a member of the National Leopoldina Academy and has received many awards such as the Alfried Krupp Prize, the Wilhelm Wundt Medal, the Turkish Parliament Merit Award, the Leibniz Prize and the Communicator Prize. In his research, he tries to understand how thinking arises.
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How does the order of thought arise? It is possible that we will soon understand the principles behind it.
I always think. I’ve tried to stop my thinking many times; to create an emptiness in me and then to learn more about the structure of my thoughts by comparing this emptiness with my everyday thinking. I never succeeded. In meditation, it is said, this can be achieved after a long time To practice. One day I will probably have to undertake the meditation training to get to the bottom of my thinking in an empty space.
I observe in myself that my thinking constantly changes its character. Sometimes it is washed out beyond recognition; a dull chaos of splinters of thought and wordless images that line up and overlap. Sometimes, for short moments, I’m just seeing, feeling, or hearing. Sometimes my thinking suddenly jumps to something new and I don’t know why. And sometimes my thinking is crystal clear. A lucid thought then carries me through the complex network of arguments for hours and I easily recognize the inner structure of the object on which I am working mentally. In times like these, thinking is a lavish pleasure. As a psychologist and brain researcher, I try to understand the neuronal basis of thinking. For this research we need the entire methodological range of cognitive neurosciences. In cell cultures, for example, hybrid compositions of nerve cells and microchips are made in order to conduct a still primitive biological-technical dialogue with small groups of nerve cells. In animal experiments, a wide variety of animal species learn to solve tasks that researchers have devised, while simultaneously recording the activity of dozens of their nerve cells and trying to decipher the subtasks that the individual neurons perform.
These experiments reveal that neurons function like small cogwheels of a huge machine by taking on subtasks of a large functional structure. In other experiments, scientists reconstruct the complex processes in the human brain and manage to isolate individual building blocks of thought and their associated neural signatures. In clinical trials, paralyzed people are equipped with electrodes in or on their brains to enable them to control wheelchairs and robotic arms simply by the power of their thoughts, or to communicate with their environment by writing. All of these insights always help us better to understand how thinking, learning, remembering, deciding and acting works and why these processes sometimes fail. The basic research driven by curiosity makes the later clinical application possible. Once we have deciphered the psychological and neural signatures of thought, we can help many people with illnesses and disabilities. But can we also read minds? Could all these findings possibly lead to the fact that the touching folk song "The thoughts are free" can only be sung with a bitter aftertaste because we have become glassy in our thinking?
Nothing is more important to research than a theory that guides experimentation and helps the researcher convert the data obtained into real knowledge. Probably the most fundamental theory of cognitive neuroscience was formulated in 1949 by the Canadian psychologist Donald Hebb in his book "The Organization of Behavior: A Neuropsychological Theory". Hebb specifies three postulates that still serve as the basic pattern of today’s neuroscientific research.
The first postulate is that neurons that are active together (and thus “fire” together in the jargon of neurosciences) develop more effective synapses with each other. I want to explain this using an example. Let us imagine that you have moved to another apartment and are cooking in your new kitchen for the first time. As the pan sizzles, lean forward to grab a spice. Part of the nerve cells in your brain are currently processing the situation: "I am standing in front of the stove", "Spices are in front of me", "I reach for the spice jars" and so on. At that moment, you painfully collide with the extractor hood. Other nerve cells immediately report: “Pain on the forehead”, “Extractor hood hangs lower than in the old kitchen” and so on. All nerve cells listed in this fictional scene now fire together for a brief moment. This strengthens the synaptic bond between them. A stronger synaptic bond means that the next time you cook on your new stove, the nerve cells that process your current situation (such as "I’m standing in front of the stove") will be active again. The activation of these neurons, however, is now able to activate those nerve cells that processed the painful collision at the time thanks to the strong synaptic contacts. This will help you remember how much it hurt when you cooked and that you need a new movement pattern to season your pan without damaging it.
Donald Hebb’s first postulate (neurons that fire together, wire together) has proven to be absolutely correct neurobiologically. As simple as this postulate sounds, the proposed solution to a fundamental problem in brain research is ingenious: how does the brain organize itself and how does it integrate life experiences without the existence of a higher-level control system that tells the brain how to do it should? Today we know that according to Hebb’s rule, synapses are strengthened by correlating the activity of simultaneously firing neurons. This organizes the memory formation of our brain through the common occurrence of events, which are then neuronically associated.
For you as a reader of this article, this means that I am currently changing your brain. Millions of neurons in your nervous system are currently processing the content of this page. The synapses on which both nerve cells involved are successfully active at the moment therefore go through a complex chain of molecular processes, at the end of which the strengthening of these synapses is achieved. If you remember this article tomorrow, I have successfully modified your brain.
The second Hebb’s postulate is that nerve cells form flexible, short-term coalitions (so-called assemblies), which then represent an object, an intention to act or a thought. At this point it is important to define exactly what is meant by a neural coalition. For example, a Neuron A can be part of the “Herd” assembly, fire a few minutes later in the “Desk” assembly, and remain silent shortly afterwards when you think of your car. On the other hand, a Neuron B could possibly remain inactive with "stove", but fire with "desk" and "car". However, should you learn something new about your desk, the compositions can change, so that Neuron A, for example, ceases to be a member of this assembly. If you have never heard the term assembly in this context, a new constellation of nerve cells may form in your cerebral cortex at this moment, which through your joint activity increases the synaptic efficiency within this group (first Hebbian postulate) and associations other similar terms established (that is, with assemblies that were created earlier in your brain).
Every time you hear or read the word assembly in the future or when you think about the neural correlates of thought, you will activate exactly this new constellation of nerve cells. And if you come to new insights from this thinking, your assembly for the term “assembly” will change in the composition of its neural members.
It is important to note that the neurons that form an assembly do not necessarily have to be spatially adjacent. On the contrary, it is likely that they are spread over different areas of your cerebral cortex. Let’s take the assembly for the stove in your kitchen. “Herd” is a word in the German language and so a number of neurons in the language area of the left hemisphere will be part of the “Herd” assembly.
Your hearth also has a certain appearance and therefore nerve cells in the area of your visual system will participate in this assembly. Since you often operate the buttons on your hearth, nerve cells near the motor centers of your hands will also be part of the “cooker” assembly. Donald Hebb probably also had with his second Postulate largely correct, although a final proof of Hebb’s assemblies is still pending. Even if the concept of assemblies is currently still partially controversial, neuroscientists agree that large groups of neurons are active in changing combinations in thinking. These activity patterns quickly migrate across the surface of the cerebral cortex, with the same thinking content usually being associated with similar activity patterns. This allows brain researchers to a certain extent to understand what a person is thinking about.
But since every brain is much more unique than a fingerprint, a computer first has to learn the activity patterns of a particular person’s brain. To do this, the person is placed in a scanner and the experimenter repeatedly shows either an A or a B on a monitor. Each of these letters leads to a specific activation pattern in the brain, which is learned by a computer. Now the experimental setup can be changed: the subject is still sometimes shown an A or a B, but the experimenter no longer knows which letter is currently appearing on the monitor. Now he has to guess that from the activation patterns of the brain.
At this simple level, mind reading already works quite well. You can push these experiments to the point where you can get an extremely rough picture of what a person is thinking about while they start dreaming, or which of two alternatives they will choose in a few seconds. For all of these studies to succeed, the subject must be confronted with a set of stimuli beforehand so that the computer can learn the individual activation patterns of each person’s brain for each stimulus. The third Hebbian postulate states that assemblies are arranged in sequences so that the end of one assembly’s activity marks the beginning of the next one’s activity. This could possibly represent the neural basis for the uninterrupted stream of thoughts that we all experience. Verifying the accuracy of this postulate is a difficult task. In fact, one observes that nerve cells in areas such as the hippocampus, which is important for memory formation, are organized in timed seasons and how assemblies in other areas of the brain could function as a clock. And there are many studies showing that neurons in small circuits are active in recurring sequence patterns. The problem with current brain research is not so much the small repetitive circuits. The question is rather, with which mechanism assemblies organize themselves again and again to new sequences in a flexible way. Most likely, many assemblies compete to be the next in the chain. How the next assembly is selected and how the constant overlay of different assembly chains can be prevented is part of the puzzles that have not yet been satisfactorily resolved.
Research into the neural foundations of thought is probably the most fundamental challenge in neuroscience. Our ability to think complexly has made us human, and thinking disorders are central to many brain diseases. A lot of basic science research is still necessary to understand the neural principles of thinking to such an extent that the causal core problems of the various diseases of the brain can be clarified.
In the meantime, most therapeutic neurology and psychiatric procedures must alleviate the symptoms rather than the causes of the disease. But neuroscientific research into thinking has also created a by-product in addition to many findings for clinical application, which can mean a dramatic increase in the quality of their lives for many patients. People with complete or extensive paralysis are currently dependent on their environment for their care and for the fulfillment of simple desires. As explained above, signatures of intention to act can be identified in every brain. You don’t even have to use a large scanner here, but can simply derive the neural correlates from intentions of action with simple electrodes that are glued to the scalp. By systematically training pattern detectors, technical systems will later be able to maneuver wheelchairs, for example. For more complex actions performed by robotic hands, for example, small electrodes have to be implanted either on or in the patient’s cortex. This gives the patient a technical third hand with which they can do many everyday things.
If we are already able to read simple images, words and decisions from the brains of test subjects today, do we have to fear that we will soon see glasses? What are the limits of the technical and scientific development of mind reading? Should the resolution of scanners or electrophysiological methods improve in the near future, the quality of the neural signal read out will of course also increase. Current scanners with very high magnetic field strengths are, however, already close to the physically reasonable upper edge of the resolution. Electrophysiological procedures will most likely never achieve this resolution. This means that we have not yet reached the limit, but are approaching the technical limits that these technologies bring. With the simultaneously increasing computing capacity of computers, it may be possible within the next one to two decades, not only rough categories of thinking ("man", "street", "car"), but also more differentiated thoughts, such as those of one to capture a specific scene, a specific person or a word. Complex lines of thought would still not be comprehensible. In addition, one has to mention a boundary condition in these considerations.
All previous investigations have only been carried out by highly cooperative test subjects who look at stimulus material motionless for hours so that the scanner can learn their corresponding brain activities. Later, in the actual test phase, these test subjects also stick to the test protocol and think, for example, exactly of the image or the word that the computer should capture in their brains. Once these systems are used to convict potential criminals, it will likely become clear what mental counter-strategies people can develop who do not want to reveal their thinking.
But what if a technical revolution tomorrow gave us a completely new tool that we could use to record the activity of practically all neurons? Such a fictitious scenario can hardly be answered reasonably. But I suspect that even such a high-resolution system cannot solve the problem of full mind reading. This problem lies in the correlation of the mental and the neural signal. In such a scenario, the theoretically infinite number of mental processes of a person are also contrasted by almost infinite combinations of neuronal signals. These must first be mapped onto one another. To do this, the test subject would have to think an extremely large number of different thoughts and communicate them precisely so that the pattern detectors learn the associated neuronal signals. How long does it take before you have thought and told so many different things, until the pattern detector can tell me what I want to keep to myself? And then there is another big problem, it was sketched at the very beginning: my thinking is far from clear enough that I can always communicate it precisely. I only become aware of part of my thinking and I can only express part of my conscious thinking in words. The rest of my thinking is inaccessible to myself, but it does contribute to the neural signals that future systems might capture.
I think it stays that way: thoughts are free.
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