Hierarchical Brain

Neuron

Neurons, and the connections between them called synapses, are the building blocks for the workings of the brain and the obvious components for the lowest level in my proposed hierarchy of levels of description of the workings of the human brain.

This page is a high-level description of the characteristics and capabilities of a neuron, but, like all living cells, a neuron is an incredibly complex piece of machinery that can be described at many levels of detail. A lower level of detail on the workings of both neurons and synapses depends upon the movement of ions.

Despite the potential for complex decision making in the many different types, sizes and shapes of neurons and their synapse connections, there is a basic functionality that they all provide that can be described as coincidence detection. This is the basis of my proposed hierarchical structure that describes the working of the brain.

Functionality

• A neuron is a special type of cell that typically receives signals from many other neurons, and then may pass a signal on to many further neurons depending on the result of a summation operation carried out on the signals it receives.
  • There are several different names or descriptions for the signals created and passed on by neurons: saying that a neuron sent or passed on a signal is the same as saying it fired, or spiked, or generated an action potential; these are all different ways of saying the same thing.
  • The signals are received from other neurons via synapses, which are joins or junctions between two neurons, where they touch, or very nearly touch.
• Whether or not a neuron passes on a signal is largely governed by the inputs it receives, so it can be said that there is form of coincidence detection being performed.
  • A neuron continuously analyses all the electrical signals it receives. If, at any time, the combination of signals takes the voltage above a certain threshold at a particular place within the body of the neuron, the neuron generates a signal itself which is then passed on to other neurons.
  • A different way of describing this is that a neuron sends a signal to other neurons when it detects a coincidence in the signals that it receives from other neurons.
  • A single neuron, at any given time, is capable of detecting many different coincidences in various combinations of signals that come from many other neurons.
  • These signals can even include ones from neurons that are not directly connected to it, because of the influence of neuromodulation, the concentration of chemicals in the fluid outside the neuron. The chemicals outside the neuron can sometimes have an effect on the activities inside the neuron, because some small molecules can get directly into the cell, but they can also change the way that synapses function, so signal inputs can be different depending on neuromodulation.
  • There is no inherent intelligence in a neuron; it has no knowledge of the meaning of the signals it receives, and it has no knowledge of the source of the signals; it simply processes the signals in the way outlined above.
• In order to be able to more easily explain a higher-level view of the functionality that neurons and synapses can generate, I have created the simplest-possible model of this coincidence detection ability.
  • I define an Absolutely Basic Coincidence Detection (ABCD) neuron to be a model neuron that detects a coincidence between just two incoming signals.
  • In the detailed description of an ABCD neuron, I show how the complex coincidence detection ability of a real neuron can be emulated or modelled by combining many such model neurons.
  • Using these very simple model neurons, it is then possible to draw diagrams and explain examples (see afferent processing examples) to show how the coincidence detection ability of neurons and synapses can provide the higher-level functionality that I propose is needed.
• The signals within a neuron are generated by tiny electric voltages.
  • These voltages are much smaller than the power that runs through computer chips in a mobile phone¹.
  • They are created and maintained by the movement of electrically-charged atoms or molecules (ions) through the membrane (the skin) of the neuron.
  • It is mind-boggling that all our thoughts, ideas, actions, dreams and desires are created by changes in the relative strengths of particles dissolved in water!

Physical characteristics

• A neuron has a cell body, called the soma, which contains the nucleus.
• It typically has many branching dendrites like the branches of a tree closely attached to the cell body that receive signals from other neurons.
• It usually has a single long fibre called an axon down which a signal from the cell body is transmitted;
• It normally has many small branches at the far end of the axon that allow the signal to be passed to multiple other neurons, although there are normally far fewer outputs than inputs.
• All neurons have a cell body and the ability to receive and pass on a signal, but there are many variations in all of the other characteristics².

Statistics

• There are estimated to be around 86 billion neurons in an average human brain^{3, 4, 5} - that’s 86,000,000,000.
  • This estimate is based on an extrapolation from different samples of different parts of the brain, because it is clearly not possible to count a number this big. So the actual number could be quite a bit more or less, and could vary between people quite a lot, but it is nevertheless a mind-bogglingly large number.
  • It is over ten times more than the total number of humans on the planet (at present around 8 billion).
  • However, the number of neurons in the brain makes up less than 0.25% of the total number of cells in a human body, which is estimated to be 37.2 trillion⁶ - that’s 37,200,000,000,000.
  • Although some new neurons are created during a human lifetime (more on this below), the total number of neurons does not change significantly during a lifetime.
• The cell body (soma) of a neuron is a few thousandths of a millimetre in diameter, similar to any other cell in the human body, but the dendrites and particularly the axon are long in comparison.
  • There can be as many as 40 dendrite branches on one neuron⁷.
  • Dendrites are usually just a few hundredths of a millimetre in length, although some can be up to 1-2mm long¹⁰. The incoming signals to a neuron come from the axons of many other neurons (it can be hundreds or even thousands) with many synapses on each branch.
  • The axon is usually a lot longer than the dendrites and can be many centimetres long to be able to reach to distant parts of the brain. So the output signal from a neuron usually goes to just a few other neurons that can be some distance away from the soma.
• A single neuron can fire up to 200 action potentials per second¹¹.
  • An action potential in a neuron lasts for around one-thousandth of a second⁸.
  • The action potential signal travels along the axon at a rate of around 100 feet per second, which is close to 70 miles per hour⁹.

External connections and support

• The junction or connection between two neurons through which a signal can pass, normally between the branches at the end of the axon on one neuron and a dendrite on another neuron, is called a synapse.
• The various types of glial cells in the brain assist neurons by providing energy, physical support, electrical insulation and protection from infection. They also perform other housekeeping roles, such as absorbing ions and neurotransmitters, and guiding new growth and branches.

Change over time

• Until perhaps the middle of the twentieth century, the general opinion was that neurons and their connections did not change significantly after childhood. Now it is known that, although the number of neurons in the brain does not change significantly, the connections between neurons are changing all the time over many different timescales and many different physical scales¹³. The overall term for this is neuroplasticity.
  • The most dramatic changes to connections are in the first two years of life; babies grow huge numbers of connections very quickly, but then later many of these are pruned.
  • Large-scale physical changes to connections within the brain take a long time (days, weeks or more), whereas tiny changes inside a neuron that can affect a connection happen very quickly (in a fraction of a second).
  • The low-level physical reasons for these changes are only recently being understood, but the high-level causes and results of those changes can only be understood from a higher-level view of the brain.
  • Many of these changes are caused by the inputs to the brain, and are the way that the brain adapts to changing environments, circumstances and requirements; they are the way that the brain learns and are the source of all knowledge and intelligence. This is generally called activity-dependent plasticity.
• It has been discovered only in the twenty-first century that new neurons do grow in the human brain, certainly in particular areas¹⁴, and even into old age¹⁵ (see adult neurogenesis), but the numbers that grow are very small compared to the total number in the brain, so the total number in a human’s brain does not vary significantly throughout their life.
  • This area is still under investigation, but current thinking is that new neurons are required in the hippocampus in order to create new episodic memories (memories of events).
  • It is well-known that the hippocampus grows larger with learning of various types, the classic example being in London taxi drivers as they learn the layout of the thousands of streets of London¹⁶ (known as “The Knowledge”).
• It is assumed that axons and dendrites of existing neurons can grow and branch, or even retract and reconnect elsewhere.
  • Until recently, evidence for these changes to dendrites has been scanty, but there have been some recent progress on this subject (see dendrite plasticity).
  • It is known that axons that are myelinated, which means they are insulated by oligodendrocytes (a type of glial cell), cannot branch or grow, but new branches can grow on the end of an axon, called telodendrons.
• New synapses can form (called synaptogenesis), strengthen or weaken, or be removed completely (called synaptic pruning) - for more details, see synapse.
• Changes within neurons, particularly to ion channels (see movement of ions), can change the strength of one or more synapses, or even all.

Signals

• The basic capability of a single neuron is to pass on an electrical signal to one or more other neurons when a certain level of electric charge is exceeded in its cell body.
• Signals from other neurons via synapses can either be positive (called excitatory), or negative (called inhibitory), and it is in the cell body of the neuron that these signals are accumulated until a threshold is reached and the signal is propagated down the axon to other neurons.
  • In effect, the cell body is continuously adding up the positive inputs and taking away the negative inputs that are received, and making a decision to pass on a signal only when a certain threshold is reached.
  • Whether signals add to the charge or take away by contributing a negative charge depends on the neurotransmitter that is used and the behaviour of the synapse between the two neurons.
• Signals from other neurons are the principle reason for the electric charge in the cell body to build up, although some neurons fire spontaneously, without any incoming signal at all, and some fire regularly all the time^{17, 18}.
  • These neurons could act as noise generators, timers or counters.
• The summation of the many signals is done at the junction of the cell body and the start of the axon, and, if the threshold is reached, a single output signal is passed down the axon and then to other neurons.
  • The summation is purely down to the number of ions of positive or negative charge at any place within the neuron, making the charge different from that in the fluid outside the neuron, so creating a voltage (potential difference) across the membrane.
  • So in fact this summation is being done all the time at all the places where ions mix within the skin of the neuron, but it only makes a difference where there is a sufficient concentration of ion channels to initiate an action potential (more details in movement of ions).
• The passing of a signal down the axon is an all or nothing event^{9, 12} and is always triggered at the same voltage. When this happens, the neuron is said to fire, or spike, or to pass a signal, be active, or generate an action potential.
• Signals are indistinguishable from each other, so the only source of information from a neuron would seem to be whether the neuron fires or not. However, the intensity or strength of an input signal is generally indicated and passed on by the rate of firing of the signals; more frequent firing indicates a stronger or more important stimulus¹².

Concluding remarks

• The only functionality of a neuron that is required to satisfy the requirements of the next level of my levels of description outlined in these web pages is coincidence detection.
  • As detailed above, I propose that the most basic capability of neurons can be described as coincidence detection, and that this can be modelled using the very simple ABCD neuron.
  • When this relatively simple capability is combined with the ability of synapses to change strength based on past activity, and the additional capability of some synapses to create an inhibitory effect on the signalling ability of other neurons, much more powerful behaviour emerges that I describe as memory-enhanced coincidence detection and lateral inhibition, which is the next highest level (level 2) of my hierarchical structure.
• There are many different varieties of neurons in the brain in terms of their size, shape, length, number of dendrites and number of axon connections.
  • A recent theory has suggested that at least one type of neuron with many dendrites may have multiple sub-processing units¹⁹.
  • This would mean that summation of signals and therefore coincidence detection could potentially occur at many places within the same neuron.
  • However, equivalent functionality to this could be provided by many separate neurons with the correct configuration of connections.
  • So this additional complication should make no difference to my modelling proposal above.
• The functionality of a neuron can be usefully compared to certain concepts in electrical engineering:
  • A neuron can be thought of as a type of switch because its function as part of a neural network is to either pass on an electrical signal or not.
  • The cell body of a neuron accumulates both positive and negative electrical signals and adds up these values, so the processing of a neuron can also be called algebraic summation or can be thought of as an adder-subtractor.
  • In the same way, depending on the number and relative strength of the signals, a neuron could be described as an AND gate or an OR gate.

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References For information on references, see structure of this website - references

1. ^ New Scientist article The amazing ways electricity in your body shapes you and your health - Sally Adee 22nd February 2023
   Around the heading “Electric signalling” : “We have long known that a neuron’s ability to relay messages hinges on electricity - specifically, a set-up that ensures different ions stay on different sides of nerve cell membranes. Neurons like to keep potassium ions inside and sodium ions outside. Both types of ion are positively charged, but, due to the vagaries of ion concentration gradients and head-exploding equations, the upshot is that the inside of a neuron is around 70 millivolts more negatively charged than the outside. This is called its resting potential. Although the resting potential is minuscule - around one-tenth the voltage that activates a transistor in the microchip that runs your phone - it is vital to the functioning of nerve cells.”
2. ^ Know your neurons - article published by Scientific American magazine 2012
   “Scientists have classified neurons into four main groups based on differences in shape. ... Researchers also categorize neurons by function. ... Neurons differ from one another structurally, functionally and genetically, as well as in how they form connections with other cells. ... So how many different types of neurons have scientists named so far? ...the answer is at least in the hundreds.”
   There are many different ways of categorising the different types: for example, see this list of different types, 302 different types listed at SciCrunch (the database takes over 20 seconds to load, and you then need to click the “children” tab), and many thousands at Neuromorpho.org by cell type.
3. ^ The human brain in numbers - a linearly scaled-up primate brain - Herculano-Houzel 2009
   doi: 10.3389/neuro.09.031.2009 downloadable here or see GoogleScholar.
   See table, top of page 7, which says that the total number of neurons in the human brain is 86 billion.
4. ^ How many neurons do you have? Some dogmas of quantitative neuroscience under revision - Lent, Azevedo, Andrade-Moraes and Pinto 2011
   doi: 10.1111/j.1460-9568.2011.07923.x downloadable here or see GoogleScholar.
   See seven lines from end of page 4: “...absolute counts yielded an average of 86 billion neurons in male human brains...”
5. ^ The search for true numbers of neurons and glial cells in the human brain: A review of 150 years of cell counting - von Bartheld, Bahney and Herculano-Houzel 2016
   doi: 10.1002/cne.24040 downloadable here or see GoogleScholar.
   This paper is a good summary of the history of counting the number of cells in the human brain and the different ways that have been used to count them.
6. ^ An estimation of the number of cells in the human body - Bianconi, Piovesan, Facchin, Beraudi, Casadei, Frabetti, Vitale, Pelleri, Tassani, Piva, Perez-Amodio, Strippoli and Canaider - 2013
   doi: 10.3109/03014460.2013.807878 downloadable here or see GoogleScholar.
   Near end of abstract on page 1: “Results: A current estimation of human total cell number calculated for a variety of organs and cell types is presented. These partial data correspond to a total number of 3.72 x 10¹³.”
7. ^ In Search of Memory - Kandel 2006 Norton & Company USA - see GoogleScholar.
   This very readable book by the Nobel prize winner is an autobiography, history and text book all in one.
   In chapter 2, page 65: “Some neurons in the brain have as many as forty dendritic branches.”
8. ^ Ibid. In Search of Memory
   In chapter 5, page 77: “The form of the signal and its role in encoding information were addressed in the second phase, which began in the 1920s with Edgar Douglas Adrian’s work. Adrian developed methods of recording and amplifying the action potentials propagated along the axons of individual sensory neurons on the skin, thereby making the elementary utterances of nerve cells intelligible for the first time. In the process, he made several remarkable discoveries about the action potential and how it leads to what we perceive as a sensation. To record action potentials, Adrian used a thin piece of metal wire. He placed one end of the wire on the outside surface of the axon of a sensory neuron on the skin and then ran the wire to both an ink writer (so he could look at the shape and pattern made by the action potentials) and a loudspeaker (so he could hear them). Every time Adrian touched the skin, one or more action potentials were generated. Each time an action potential was generated, he heard a brief bang! bang! bang! over the loudspeaker and saw a brief electrical pulse on the ink writer. The action potential in the sensory neuron lasted only about 1/1000 of a second and had two components: a swift upstroke to a peak, followed by an almost equally rapid downstroke that returned it to the starting point.”
9. ^ ^ Ibid. In Search of Memory
   In chapter 5, page 77: “The ink writer and the loudspeaker both told Adrian the same remarkable story: all of the action potentials generated by a single nerve cell are pretty much the same. They are about the same shape and amplitude, regardless of the strength, duration, or location of the stimulus that elicits them. The action potential is thus a constant, all-or-none signal: once the threshold for generating the signal is reached, it is almost always the same, never smaller or larger. The current produced by the action potential is sufficient to excite adjacent regions of the axon, thus causing the action potential to be propagated without failure or flagging along the whole length of the axon at speeds of up to 100 feet per second, pretty much as Helmholtz had earlier found!”
10. ^ Dendrite structure - Fiala, Spacek and Harris 1999
    in book Dendrites ed. Stuart, Spruston and Hausser pub. Oxford University Press 2017,
    article downloadable here or see GoogleScholar.
    Page 2, second paragraph: “Dendrites are rarely longer than 1-2 mm, even in the largest neurons, and are often much smaller.”
    The table on page 3 quotes statistics for the “Principal cell of globus pallidus (human)”. Unfortunately, the globus pallidus has particularly large and strange-shaped neurons and very unusual dendritic arborisations, so this may not be a typical example.
11. ^ Cognitive Neuroscience: The Biology of the Mind - Gazzaniga, Ivry and Mangun, Fourth Edition 2014 Norton & Company USA
    A comprehensive text book edited by Michael Gazzaniga, Richard Ivry and George Mangun.
    Page 31, second column. Under the heading “The Action Potential”, having described the refractory period when the neuron’s internal voltage has not yet returned to its normal equilibrium potential, it says: “The refractory period lasts only a couple of milliseconds and has two consequences. One is that the neuron’s speed for generating action potentials is limited to about 200 action potentials per second.”
12. ^ ^ Ibid. Cognitive Neuroscience: The Biology of the Mind
    Page 32, first column: “Action potentials are always the same amplitude; therefore, they are said to be ‘all or none’ phenomena. Since one action potential is the same amplitude as any other, the strength of the action potential does not communicate anything about the strength of the stimulus. The intensity of a stimulus (e.g., a sensory signal) is communicated by the rate of firing of the action potentials: more intense stimuli elicit higher action potential firing rates.”
13. ^ Reorganization and plastic changes of the human brain associated with skill learning and expertise - Chang 2014
    doi: 10.3389/fnhum.2014.00035 downloadable here or see GoogleScholar.
    Start of introduction on page one: “Neuroplasticity, which refers to the brain’s ability to change its structure and function, is not an occasional state of the brain, but rather the normal ongoing state of the human brain throughout the life span. Plastic changes in the human brain lead to brain reorganization that might be demonstrable at the level of behavior, anatomy, and function and down to the cellular and even molecular levels.”
14. ^ Stable neuron numbers from cradle to grave - Nowakowski 2006
    doi: 10.1073/pnas.0605605103 downloadable here or see GoogleScholar.
    First page, top of second column: “In humans, only the dentate gyrus population contributes new neurons.” - the dentate gyrus is part of the hippocampus.
15. ^ Human Hippocampal Neurogenesis Persists throughout Aging - Boldrini, Fulmore, Tartt, Simeon, Pavlova, Poposka, Rosoklija, Stankov, Arango, Dwork, Hen and Mann 2018
    doi: 10.1016/j.stem.2018.03.015 downloadable here or see GoogleScholar.
    End of Introduction, page 591, third paragraph “Healthy elderly people have the potential to remain cognitively and emotionally more intact than commonly believed, due to the persistence of AHN into the eighth decade of life.” - AHN is Adult Hippocampal Neurogenesis, i.e. the growth of new neurons in the hippocampus.
16. ^ National Geographic article The bigger brains of London taxi drivers (anon) - 29th May 2013
    Navigation-related structural change in the hippocampi of taxi drivers - Maguire, Gadian, Johnsrude, Good, Ashburner, Frackowiak and Frith 2000
    doi: 10.1073/pnas.070039597 downloadable here or see GoogleScholar.
    Second sentence of abstract: “The posterior hippocampi of taxi drivers were significantly larger relative to those of control subjects. A more anterior hippocampal region was larger in control subjects than in taxi drivers. Hippocampal volume correlated with the amount of time spent as a taxi driver”
17. ^ A review of cell assemblies - Huyck and Passmore 2013
    doi: 10.1007/s00422-013-0555-5 downloadable here or see GoogleScholar.
    Last two lines of page 4: “The basic structure of the brain is a loosely coupled net of neurons where neurons are firing constantly at a low rate.”
    and beginning of fourth paragraph, page 14: “Neurons are firing constantly...”
18. ^ Response to the Edge.org question What do you consider the most interesting recent [scientific] news? What makes it important? - Lisa Feldman Barrett 2015
    First paragraph: “For many years, scientists believed that your neurons spend most of their time dormant and wake up only when stimulated by some sight or sound in the world. Now we know that all your neurons are firing constantly, stimulating one another at various rates. This intrinsic brain activity is one of the great recent discoveries in neuroscience.”
19. ^ Why Neurons Have Thousands of Synapses, a Theory of Sequence Memory in Neocortex - Hawkins and Ahmad 2016
    doi: 10.3389/fncir.2016.00023 downloadable here or see GoogleScholar.
    From abstract on page 1: “Pyramidal neurons represent the majority of excitatory neurons in the neocortex. Each pyramidal neuron receives input from thousands of excitatory synapses that are segregated onto dendritic branches. The dendrites themselves are segregated into apical, basal, and proximal integration zones, which have different properties. ... First we show that a neuron with several thousand synapses segregated on active dendrites can recognize hundreds of independent patterns of cellular activity even in the presence of large amounts of noise and pattern variation. We then propose a neuron model where patterns detected on proximal dendrites lead to action potentials, defining the classic receptive field of the neuron, and patterns detected on basal and apical dendrites act as predictions by slightly depolarizing the neuron without generating an action potential. By this mechanism, a neuron can predict its activation in hundreds of independent contexts.”

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Page last uploaded Wed Jan 31 07:25:03 2024 MST