Parallel processing psychology (and a new way to think)
As a BetterHelp affiliate, we may receive compensation from BetterHelp if you purchase products or services through the links provided.
Author bio
The Optimistminds editorial team is made up of psychologists, psychiatrists and mental health professionals. Each article is written by a team member with exposure to and experience in the subject matter. The article then gets reviewed by a more senior editorial member. This is someone with extensive knowledge of the subject matter and highly cited published material.
In this article, we are talking about parallel processing in psychology, as well as about parallel thinking and the innovative ideas of Dr Edward de Bono, one of the very few people in history who can be said to have had a major impact on the way we think.
What is parallel processing in psychology?
The brain thinks in parallel, like supercomputers, and has a cloud infrastructure to process information. Each neuron acts as the nodes of the AI deep learning networks.
Parallel computing is a programming technique that allows many instructions to be executed simultaneously. It is based on the fact that large problems must first be divided into small problems and then solved at the same time (in parallel).
This programming technique uses multiple computational resources and is particularly used in supercomputers, sets of powerful processors linked together to increase their work power and performance.
Blue Brain Project researchers have now discovered that the brain acts as a parallel computing unit when we think, thus our brain is capable of parallel processing. They have found that the terminals of neurons called dendrites work together dynamically depending on the workload to be performed.
Dendrites are extensions of neurons, in the form of filaments, that receive impulses from other neurons and forward them to other neurons to enable information processing.
Just like a supercomputer
The researchers have been able to observe that a neuron can handle different aspects of multiple (parallel) incoming signals, in the same way that a supercomputer does.
Also, each parallel computing unit of the brain (neuron) can learn by itself to adjust the signal that must replicate to another neuron, depending on the nature of the incoming signal.
Furthermore, each neuron acts in the same way that deep learning network nodes exploited in current artificial intelligence models do, the researchers note.
The thinking system also has a kind of cloud computing infrastructure, which allows a neuron to dynamically share with other neurons (other independent computing units) as much activity as the incoming signal’s workload demands.
Finally, this research shows how these parallel processing units influence learning: how a neuron learns depends on the number and location of parallel processors, which in turn depend on signals sent by other neurons.
For example, some synapses don’t learn independently when the input signal level is low, but start to learn when the signal is higher, the researchers have been able to determine.
The strength of a synapse thus determines the intensity with which a neuron perceives a neighbour’s electrical signal. This force is modified by the learning process. A “connectivity matrix” determines how these synapses communicate with each other.
Virtual model
In an article published in Cell Reports, the researchers explain that they performed their analysis on the cells of the cerebral cortex of a virtual rodent, designed by the Blue Brain Project team.
The researchers explain that other types of real neurons, non-cortical or human, should function in the same way as the neurons in the virtual model.
The researchers compare their results with the performance of some current computing technologies and conclude that dendrites act as parallel computing units.
“In the Blue Brain Project, this mathematical approach allows us to determine at what level of complexity we need to model cortical networks in our digital reconstruction and brain stimulation,” says Marc-Oliver Gewaltig, head of the simulation division of the Blue project Brain, in a statement.
Postsynaptic potential
Until now, conventional learning algorithms (such as those used in artificial intelligence applications) presuppose that neurons are static units that simply integrate and scale incoming signals.
However, this research shows that thought processes are more complex: the number and size of independent subunits can be controlled by an incoming signal of varying intensity or by a particular form of postsynaptic inhibitory potential called ‘shunt inhibition’ ( synapse that acts as an electrical shunt).
The researchers believe that this temporal control of compartmentalization is a powerful brain mechanism for learning the characteristics of an incoming signal through dendrite clustering.
“Our results show that the number of parallel processors varies with the level of these background signals, suggesting that the same neuron could have multiple computational functions in different brain states,” says lead author Willem Wybo.
Parallel processing – Human invention?
“This observation is exciting. With these new concepts, we can begin to search for algorithms that exploit the rapid changes in the pairing of processing units. This will open up new perspectives on this fundamental question: how the brain performs the calculations ”, concludes Marc-Oliver Gewaltig.
Until now it has been believed that the only common denominator between a brain and a computer is the storage and processing of information to execute cognitive tasks.
This research reveals an additional parallel that has to do with the way information is processed, a result that will help us better understand how the brain thinks.
It also shows that the human invention of parallel processing already existed in the brain before we replicated it on the machine in the 1950s.
Parallel processing and parallel thinking
According to the American philosopher Edward de Bono, the traditional method of reasoning is not very well designed to differentiate itself and provide value. For this reason, he proposes a new system: parallel thinking.
The problem of current thinking is the process of intelligent thinking itself. It is believed that if we have a high IQ, we are intelligent and we will be able to think well. But that is not true: there are many people who are very intelligent and who still cannot think. The thought is the motor ability of the mind. Thought needs to be taught, otherwise, we will be wasting intelligence.
We use a method of thought that was originally designed more than 2,400 years ago by three Greeks: Plato, Socrates, and Aristotle, but which is very limited.
Common goods
In the future of business, there are three things that will become commodities, which will be available to everyone: competition (all organizations will be equally competent), information (the idea that one may have more information than others), and technology (the value we extract from technology is still very limited).
In the future, the two things that will matter will be design and value delivery, and these two things will be the key to differentiation.
A new model
Traditional thinking is not very well designed for these functions as it is based on what it is. About 90 per cent of our behaviour and one hundred percent of our education have to do with this type of thinking: what is this.
This means recognizing standard situations and applying the standard remedy. This type of thinking has served us well so far, but we are operating well below the potential of our resources.
What is the other kind of thinking? It’s about what can be. In other words: design, creativity, constructive thinking. Design something that does not yet exist, instead of identifying what already exists.
We are not very good at this type of thinking, because all our effort is directed to what this is. Traditional thinking has satisfied us for more than 2,400 years, simply because we haven’t designed anything better.
What is better? The best is parallel thinking. Imagine that four people each look at one side of a building. Each one will say that what they see is the correct image of that building. Parallel thinking means that at any moment everyone alternates their positions to see what is seen from the other side.
The first benefit is that results are achieved much more quickly. Another advantage of parallel thinking is that it eliminates the ego in thought: if one opposes an idea, one will not seek the value that the idea has. And if you are favouring it, you may not be cautious enough.
The heart of parallel thinking is in the possibility of changing, at any time, your own position for that of others, to observe how reality is seen from a different angle. That is, they all look in the same direction, but they do it alternately.
If you want to learn more about behavioral psychology, you can read information on What is a Forensic Psychologist?
FAQ about parallel processing psychology
What is an example of parallel processing in psychology?
An example of parallel processing in psychology is our ability to identify certain objects. For example, while looking at an apple, you are able to process its colour, shape, remember its taste and even a memory associated with this object – all information that leads to you recognizing the object – an apple.
Where does parallel processing occur?
Parallel processing occurs in our brain. ur lives; these experiences and our brain. The terminals of neurons called dendrites work together dynamically depending on the workload to be performed. Dendrites are extensions of neurons, in the form of filaments, that receive impulses from other neurons and forward them to other neurons to enable information processing.
What is the purpose of parallel processing
The purpose of parallel processing is to help one receive and understand different stimuli, such as colour, shape, motion and depth.
Why is processing important?
In simpler terms, parallel processing is extremely important for humans to understand the world around them. We would not be able to process all the stimuli that we perceive without parallel processing.
Conclusions
In this article, we talked about parallel processing in psychology, as well as about parallel thinking and the innovative ideas of Dr Edward de Bono, one of the very few people in history who can be said to have had a major impact on the way we think.
According to the American philosopher Edward de Bono, the traditional method of reasoning is not very well designed to differentiate itself and provide value. For this reason, he proposes a new system: parallel thinking.
The brain acts as a parallel computing unit when we think, thus our brain is capable of parallel processing. Researches have found that the terminals of neurons called dendrites work together dynamically depending on the workload to be performed, just like a computer works.
If you have any comments, questions or recommendations, please let us know!
Further reading
The Little Book of Psychology: An Introduction to the Key Psychologists and Theories You Need to Know, by Emily Ralls and Caroline Riggs
Cognitive Psychology: A Student’s Handbook, by Michael W. Eysenck
Cognitive Psychology For Dummies, by Peter J. Hills
Cognitive Psychology: A Student’s Handbook, by Michael W. Eysenck
References
Electrical Compartmentalization in Neurons. Willem A.M. Wybo et al. Cell Reports, volume 26, issue 7, p1759-1773.e7, February 12, 2019.
epfl.ch
cell.com
edwddebono.com
