in what ways are nerve cells similar to other cells

Abstruse

In the field of bogus intelligence, which has a large influence on our lives today, the term "neural network" has been gaining popularity. It usually refers to a dumbo web of unproblematic units, each of which may exist in one of 2 states (on/off) and impacts of the state of other units connected to it. What exactly is the relationship between the mode a nerve jail cell acts and the way artificial intelligence works? How is the action of an artificial neural network similar to a network of neurons in the human brain? This article tries to answer these questions. We volition summarize how thinking happens, provide a short description of how a nerve cell works, describe the similarities between a nerve jail cell and a basic unit of measurement of a logical organization, and finally show how connecting several such units is the basis for bogus intelligence.

Thinking Involves Linking Concepts Together

From the dawn of civilisation, humans have been intrigued by their power to remember, perceive, allocate, and brand decisions. A common notion in the fields of psychology and philosophy is that our thoughts and ideas are abstract, basic concepts that get linked to each other in different combinations as nosotros feel the world around u.s.a.. The name of this notion is associationism . Co-ordinate to associationism, thinking is a kind of roaming around inside an interconnected network of concepts that are joined to each other with diverse strengths. The trigger for roaming may be an external, sensory input such as sight, sound, smell, or bear upon.

For example, let united states of america imagine a grouping of concepts: sour, sweet, modest, big, red, lemon, strawberry, and watermelon (Figure 1). Associationism implies that when the image of a strawberry comes to mind, there is a co-activation of associated, strawberry-related concepts, such as red, minor, and sugariness (but not lemon, big, or watermelon). The strength of the connections between associated concepts is built upward past our interactions with the world around us. The more we experience a sweet taste occurring together with the sight of a fruit that happens to be red, the stronger the connexion becomes between those three concepts.

• Figure ane - The thinking process tin can be described every bit roaming effectually inside a network of basic concepts that are connected in various combinations and strengths, determined by our experiences.
• (A) Black lines connect basic concepts that, together, represent the concept of "strawberry." Gray lines represent weak connections to basic concepts that practise not belong to "strawberry." (B) Blackness lines connect bones concepts that represent the concept "watermelon." The grayness lines represent weak connections to bones concepts that do not belong to "watermelon" (Figure credit: Renee Comet; public domain, via Wikimedia Commons).

How Nerve Cells Work

Associationism is interesting to scientists who are trying to understand how the human being brain works. What happens inside the brain when nosotros grasp a concept such every bit "strawberry"? The journey toward an answer to this question began dorsum in 1835, following the evolution of methods that allowed high-quality microscopic observation of encephalon tissues. These early observations showed that the brain is made upwardly of nerve cells, also known as neurons , that are connected to each other through fine fibers [ane]. Over the years, these findings led to the development of a hypothesis chosen the neuron doctrine , which links associationism to the structure of the encephalon. Think about information technology this manner: a concept (such as red, or small, or sweet) is represented in the brain by the activation of neurons. Fibers connect clusters of neurons, and this supports the association between concepts. Unique groups of neurons become active when we recall of a circuitous concept or encounter an object in forepart of our optics, similar a strawberry or a watermelon (Figure ane).

But what actually happens in a nervus prison cell when the concept ruby-red comes to mind? The first clues came in 1926, with the development of avant-garde electronics that allowed identification and characterization of electrical signals in fretfulness. These electrical signals happen when a nerve cell is active [two], and they involve a tiny change in the voltage measured between the two sides of the nerve cell'southward membrane. Specifically, the watery solution between all the body's cells (neurons included) is like to sea water, with high concentrations of sodium ions (Na⁺) and low concentrations of potassium ions (K⁺). Na⁺ and One thousand⁺ are common ions that behave positive electric charges. Inside the nerve cell, Thou⁺ is in high concentration and Na⁺ is in low concentration. This difference betwixt the internal and external ion concentrations leads to a voltage difference between the inside and exterior of the cell, much similar the difference betwixt the two poles of a bombardment. Measuring the voltage showed that the electrical activity of a nerve cell is a very short (a fraction of a second) change in the electrical potential inside the nerve cell. This phenomenon was named a neural impulse or "spike" (Figure 2). Today we know that the spike results from the flow of Na⁺ and K⁺ ions through the jail cell'south membrane. To create a neural impulse, the nervus cell must receive a stimulation that is stronger than a certain threshold; if the stimulation is non stiff enough, nothing happens.

• Effigy 2 - Nerve impulse and nerve cell.
• (A) The shape of a nervus impulse. When a stimulation crosses a threshold, a neural impulse is created, with a fixed shape and strength (1; "all"). If the stimulation does non cross the threshold, no neural impulse will be created (0; "none"). (B) A painting of a nerve cell showing stimulatory signals moving toward the nerve jail cell's body where, if the sum of the signals exceeds the threshold value, a neural impulse is created, which is transferred to nearby nervus cells through a cobweb chosen the axon, generating inputs to those cells (Image credit: Karl Deiter, 1834–1863; arrows and English text added).

This "all-or-zippo" response of the nerve cell is similar to an on/off switch for a light. We can retrieve about it in numerical terms as 1 (all) or 0 (zippo). This ways that the strength of the stimulation causing the neural impulse does non affect the size of the neural impulse. These neural impulses allow us to feel, think, move, and more. Annotation that the electrical activity in the brain results from electrical impulses in many nerve cells simultaneously.

At this bespeak, there was still an of import unanswered question: how exactly does a spider web of on/off switches explain how humans retrieve and deed intelligently? The search for an respond to this question has given rise to an exciting field of research that influences our daily lives— artificial intelligence (AI). Artificial intelligence technologies help people in many fields, including science and engineering science. These technologies tin can be used to perform tasks ranging from identifying and sorting medical data and images, to the command of complex machines like autonomous cars. The origin of artificial intelligence may be traced back to 1943, where researchers suggested a possible connection between two very different scientific domains: mathematical logic and the performance of networks of neurons [3]. But what is the unique connection betwixt these two domains?

Logical Systems and Artificial Intelligence

A significant office of the thinking process may be described every bit a chain of statements that undergo true/false tests. To illustrate, allow united states of america use an instance of the thinking procedure a dr. uses when a patient comes to her part and complains of having breast pains. The md suspects that the crusade of the chest pain is a heart attack. Only to diagnose a middle attack, at least two of the post-obit statements must be truthful: [a] Pains in the breast—yeah or no? [b] Changes in the electrical activity of the eye—aye or no? [c] Changes in of the corporeality of a particular poly peptide in the blood—yes or no? This ways if the patient only complains about chest pain (meaning the reply to [a] is "yes"), this is not plenty to diagnose a heart attack; the md volition diagnose a eye attack only if the answer to statements [b] and/or [c] is "yes," in addition to the breast pain. The dr. makes the diagnosis based on a logical expression : "if [a] and [b] are truthful, or [a] and [c] are true, or [b] and [c] are true, or [a] and [b] and [c] are truthful, then at that place is a heart attack."

So, since a nervus cell responds in an all-or-nothing way and can but be in one of two states (0—not agile, or 1—active), could a network of nervus cells represent the process of diagnosing a center assail? Figure 3 shows such a network. This network has two layers. The starting time layer, chosen the input layer, consists of 3 cells whose action represents the three signs of a centre assail: cell [a] represents chest pains, jail cell [b] represents changes in the electric activity of the heart, and cell [c] represents changes in the protein concentration in the blood. The second layer (output layer) contains only one neuron, which receives the summed input of the iii cells of the first layer. The activity of this i neuron in the 2d layer decides whether the weather for diagnosing a centre attack accept been fulfilled (Figure 3).

• Figure iii - Artificial neural network that tin can diagnose a heart assault.
• If at least two of the three conditions—(a), (b), (c)—in the input layer on the left occur, and so the sum of their activeness (1 + 1 = two) is equal to the threshold (2), which is enough to generate a neural impulse in the output layer (the single cell on the right), and represents a diagnosis of centre attack.

Researchers plant that what a network can calculate is adamant by the relationships betwixt layers, by the strengths of the connections, and by the threshold value for activating the nerve cell. It seems that nigh every logical expression can be described in terms of a neural network. This discovery was the basis for artificial intelligence, which is based on the activity of networks containing thousands of "cells" and many "layers," and is at present part of near all areas of our lives.

Farther important progress was made equally researchers figured out how to "teach" the network—through experience—to identify objects presented to the input layer, group them, and make the "correct" decision in the output layer. Learning is performed by irresolute the connections strengths between cells or changing the threshold value. For instance, in Effigy iii, the network could be "trained" to identify a heart set on if, and only if, all 3 weather—[a] and [b] and [c]—were true; the "learning" could exist achieved by changing the threshold value of the cell in the second layer to 2.5 instead of 2.

Gazing Into the Future

Many challenges still face up researchers who are interested in making analogies betwixt the body'southward neural network and artificial intelligence. Several of these challenges result from the differences that exist between an abstract, mathematical representation of a nerve cell and a real nerve cell in the body. Yet, the biggest challenge of all keeps nagging our brains—is that all a person is? Are all our feelings, thoughts, and desires—our entire personalities—just a network of electrical and chemical components seated in the brain? This answer will probably not be supplied by artificial intelligence; we will have to keep pondering it ourselves.

Glossary

Associationism: ↑ The idea that, as nosotros experience the world, we connect abstruse, basic concepts to each other in different combinations. For instance, sweet, cerise, and minor brand up the object "strawberry."

Neuron: ↑ A brain cell capable of generating electrical impulses.

Neuron Doctrine: ↑ The idea that our ideas or concepts are represented in the encephalon by the activation of one or more nerve cells. Fibers connect nerve cells that stand for similar basic concepts.

Ions: ↑ Charged atoms or molecules. A positively charged ion is called cation; a negatively charged ion is called anion.

Neural Impulse: ↑ A pocket-sized, quick change in the voltage betwixt two sides of the cell membrane, which results from movement of ions between the within and exterior of the cell.

Bogus Intelligence: ↑ Behavior of a computer or other machine that reflects an intelligence usually only attributed to a person. For example, a computer that plays chess, completes sentences, or summarizes an article.

Logical Expression: ↑ A chain of operations such every bit "if-then," "and," "or," or "not," that is performed on data that is put into the system; the result is "true" (one) or "false" (0).

Disharmonize of Interest

The author declares that the inquiry was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

Thank you to Ido Marom for talks and remarks during the preparation of the article.

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References

[1] ↑ Chvátal, A. 2015. Discovering the structure of nerve tissue Part 2: Gabriel Valentin, Robert Remak, and January Evangelista Purkyně. J. Hist. Neurosci. 24:326–51. doi: 10.1080/0964704X.2014.977677

[2] ↑ Adrian, E. D., and Zotterman, Y. 1926. The impulses produced past sensory nerve endings: role iii. impulses set up past bear on and pressure. J. Physiol. 61:465–83.

[3] ↑ McCulloch, W. S., and Pitts, W. 1943. A logical calculus of the ideas immanent in nervous activity. Balderdash. Math. Biophys. 5:115–33.

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Source: https://kids.frontiersin.org/articles/10.3389/frym.2022.767989

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