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— NEURONS —

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[ THREE KINDS OF NEURONS ]

 

While these diagrams are very noisy, there are really only three types of neurons, or four if we want to be precise.

Sensory Input, 

Association, and 

Motor output.

And fulfilling roles that are:

Excitatory, 

Inhibitory (about a 20-25% of neurons in the cortex)

and Dis-inhibitory (turns off inhibitory) 

Where inhibitory neurons slow or stop excitatory neurons.

 

In the Neocortex, 

Excitatory +, 80%,  which do the learning.

Inhibitory -, 20%   which are largely regulatory/throttle.

Of the Excitatory 

80% are pyramidal 

lots of lots of synapses, 30k isn’t unusual.

20% Spiky Stellate(Pyramidal without pyramid)

Of the Inhibitory

There are a at least a dozen different kinds of inhibitory.

Cells with inhibitory output connections

Large basket cells (two subtypes)

Columnar basket cells

Double bouquet cells

Chandelier cells

And more.

 

 

[ MANY VARIATIONS IN THOSE TYPES ]

 

While there are only three types of neurons, there are many variations on each of them depending upon what purpose they are solving, how many inputs they’re working with, and how much translation is needed to interpret the information, how far the information needs to be transported and whether it’s inhibitory or excitatory. 

 

 

[ BACK TO – THREE KINDS OF NEURONS ]

 

NEURONS CONSIST OF 

Trees of Dendrites that take input

A cell body that carries a voltage

An a axon with branches and axon terminals that distribute the voltage when released.

 

SENSORY NEURONS

 

Sensor input neurons consist of a cell body or SOMA, 

A single pole out of the soma

That divides into an input and an output axon.

With the input axon terminating in dendrites.

And the dendrites terminating in sensory cells.

The output axon terminates in axon terminals.

They are sensitive to touch > pressure > pain.

And within the body they can sense such things as blood pressure.

 

The single pole or unipolar neurons serve as relays.

 

ASSOCIATIVE NEURONS

 

Associative neurons are multi-polar with many dendritic branches for inputs, but only one output axon, terminating in axon terminals.

 

MOTOR OUTPUT  NEURONS

A motor neuron generally terminates in muscle.

 

 

DENDRITES

 

Dendrite Means Trees in Greek, and that’s what they look like.

They Serve as the input of the neuron;

Receive information from other neurons or the external environment;

Transfer information to the cell body 

 

Are numerous, relatively short, and branch extensively in a tree-like fashion

May have numerous spines on them to provide a greater surface area for other neurons to synapse on;

 

Receive information from other cells at these synapses. 

 

Can bypass the cell body and connect to the axons directly;

 

This principle is known as the all-or-none law. 

 

Dendrites grow longer when there is activity near their ends.

 

 

DENDRITIC SPINES 

 

Dendrites are covered with filaments like leaves on a tree. these filaments are listening or broadcasting, and if they receive information from an axon they will develop from a filament into a spine. a spine is a receiving port for a synapse.

 

They are extremely plastic and can appear and disappear over a number of hours. 

 

 

COMPUTATIONAL IN AND OF THEMSELVES

Different parts of the dendrite are now thought of as independent computational compartments. 

 

 

 

THE SOMA CELL BODY

The Soma can regulate Chemistry and Charge

Channels, Pores, or Gates of multiple kinds

1… Open all the time

2… open for +/- conditions 

3… open by nearby neurotransmitters

4… opened mechanically by mechanical deformation of the membrane.

 

 

MEANS OF INFLUENCING THE SOMA CELL BODY

1. Proximity to the axon hillock.

2. The Wider the Dendrite 

3. The More Neurotransnitter released

… Larger synapse, more pores, more reserve of neurotransmitters.

 

4. Pros++ and Cons–

Sodium and Potassium 

Calcium and chloride

 

AXON HILLOCK – FIRING SOMA OR NEURON

 

Neurons Fire by Competition between Positive excitatory and Negative inhibitory Inputs.

 

Increases increase voltage, and decreases decrease voltage.

 

Firing is called releasing an Action Potential into the Axon, through the axon, to the axon terminals, and to the synapses.

 

Firing Occurs at the Axon Hillock. The axon hillock consists of hundreds of voltage-regulated channels that function as gates. 

 

Firing either occurs  or doesn’t and releases the Action potential or doesn’t; there is no such thing as a “partial” firing of a neuron. It’s an all or nothing proposition.

 

Neurons always fire at their full strength. Firing at full strength ensures that the full intensity of the signal is carried down the nerve fiber and transferred to the next cell.

 

As the the neuron fires, the voltage equilibrates and the process of voltage increase and decrease continues.

 

FREQUENCY OR RATE 

I am not competent to judge the pseudoscience from the 

science from the mathiness in this field, although I’m comfortable making the following assertions.

 

1. The information conveyed in a single firing can be unfathomably complex.

 

2. Neurons seem to fire randomly and the reason for this is something that is either unknown or that I’m unable to separate from the chaff.

 

3. Neurons and groups of neurons fire by 

Frequency

Amplitude

Phase 

 

4. The frequency can include rate coding, such as the strength  of flexing any given muscle is determined by frequency.

 

5. It is possible that firing patterns also encode some information – – but everything I’ve seen so far is sketchy.

 

6. My current understanding is that regions and networks do some housekeeping constantly, that ocillation may be required for coordination of timing and sequence, and that motor activity might involve some more complex transmission than we currently understand.

 

 

 

AXONS

Axon – Means axis in Greek

 

They provide the output wiring for the neuron;

 

They transfer information to other neurons;

 

They Begin at the axon hillock, which is a swelling at the junction of the axon;

 

Most are myelinated. Myelin acts as insulator to help conduction of action potential.

 

Compared to the dendrites, they can be relatively long (some reaching several feet);

 

THEY CAN BRANCH.

 

They have axon terminals that branch from the end of the axon

 

at the end of the axon terminal are bulbs called boutons 

 

The swellings at the terminal bouton is where the neuron synapses with another neuron;

 

Just for some context, recall that our nerves are just axons- and that the longest axon in the human body extends from the tip of the toe up to the neck. It measures fifteen feet in length

 

BOUTON

The membrane contains channels for in and out.

 

They Contain numerous vesicles (containers) which hold neurotransmitters;

 

The space between the terminal boutons and the next cell is known as the synaptic cleft, and is approximately 20 nm thick;

 

Bigger boutons have more surface area for chemical transfer.

 

 

 

 

TYPES OF SYNAPSE

Axons Synapse on other cells in various forms;

 

1. To an axon: Axoaxonal: Axon is connected to another neuron’s axon; influences the axon only (independently of the neuron?)

2. To a dendrite: Axodendritic: Axon is connected to another neuron’s dendrites. Influences a dendrite, hence influences the graded potential of the neuron

3. To A Soma: Axosomatic: Axon is connected directly to another neuron’s soma. influences the graded potential of the neuron directly.

4. To a Muscle: In neuromuscular junctions, axons synapse directly onto muscles.

 

 

DENDRITES and AXON TERMINALS

 

synaptic potentials travel passively along membranes and is described by what’s called cable theory. 

 

The cable equation describes how the voltage will change over time and space along a cable. The theory was originally developed for signal decay in trans-Atlantic telegraph cables, but the principle holds for a voltage-independent length of membrane like a dendrite.

 

Voltage decays exponentially with increasing distance from the synapse.

 

The extent of the signal decay is governed by the axial resistance (influenced by dendritic diameter), the membrane resistance, and membrane capacitance, and the branching pattern.

 

connections can form and disappear in fairly short periods. Just a few hours.

 

 

SYNAPSE

 

While the neuron fires, The synapse also decides. And the synapse decides based on how much neurotransmitter it has in reserve, the physical size of the synapse, and how many spikes have recently occurred.

 

The way this plays out mechanistically is that neurotransmitter is packaged in units called synaptic vesicles, which are spheres containing around 5000 neurotransmitter molecules. The synaptic vesicles pile up inside the synapse, and a few of them dock on the surface where they form the “readily releasable pool.” When a spike comes in, a small integer number of these vesicles fuse to the synaptic membrane and release their neurotransmitter into the synaptic cleft. Often this integer number is zero.

 

If the synaptic strength is such that 0.3 vesicles should be released per spike, for example, then this means that most spikes need to release nothing.

 

 

Several factors determine how many vesicles of neurotransmitter get released on each spike (including none):

 

The size of the synapse. A larger synapse has a larger surface area and more docked vesicles waiting to be released. Synapse size is one of the physical manifestations of “connection strength”

 

How recently other spikes have occurred. Vesicle release is caused by calcium concentration inside the synapse, and calcium goes up each time a spike occurs. So two spikes close together will generally release more neurotransmitter than two spikes spaced farther apart.

 

The number of vesicles docked in the readily releasable pool. If several spikes in a row have come in, so many vesicles may have been released that there are no docked vesicles left. Time needs to pass for new vesicles to dock.

 

Current models assume that a vesicle release event is in proportion to the above factors but otherwise random.

 

 

[ VIDEO ]

 

Here is a video of an axon in action. see how it’s searching for connections?  

 

( … MUSIC … )

 

That’s enough that you get the idea.

 

Here is another.

 

( … MUSIC … )

 

That video illustrates the Create, Read, Update or change, Delete or prune, transactions that are familiear to those of use who have worked with  databases, and combined with the search function in the first video, we see that the model we use in software is similar to that we use in our ‘wetware’ – our neurons.

 

[ NEURAL ECONOMY ]

 

But this proceess is more analogous to how paths form across a college campus for example. Despite knowing that people take the most efficient routes, architects put down these concrete sidewalks, but peole walk efficiently so new paths form, and if something incentive is changed, paths change and new paths form. 

 

Roads and rivers evolve by the same means.

 

So this pattern illustrates the neural economy. 

 

Those connections that are used get fed, those that are not are starved, and over time memory is consolidated, adapted, consolidated and adapted yet again, over and over again.

 

Because our memories are stored in these physical constructions and connections.

 

So along our journey, we’ll see, if we try to understand our memories and our minds that our brains out of necessity function as a neural economy.

 

 

PLASTICITY

Plasticity or change occurs

1. at dendtritic spines 

2. by dendritic branch growth

2. by dendritic proximity

3. by dendtritic connections

4. by chemical composition of the fluid.

4. by synapsing to the soma

5. by increase or decrease in soma channels.

6. by connection to the axon directly 

7. by axon branch, terminal, and bouton growth.

8. by axon terminal and bouton proximity. 

9. by axon terminal and bouton connection.

 

10. by local, regional, and inter-regional changes in connectivity of information

 

11. but most oddly, but regional appropriation in response to damage, trauma, stress, or excessive use.

 

(This subject is polluted with pseudoscience at present. As far as I know, contrary to desirable mythology we don’t really see any neurogenesis and this is why many therapies aren’t working. other than one or two tiny regions of the brain.)

 

[ GROWING UNIQUE FINGERPRINTS ]

 

GROWTH 

As you can see, when we’re born we have the cell bodies and major axons, but we do not have the network of dendrites and axon terminals we see develop over the first two years.

 

 

 

NEUROGENESIS

While we’re sure that neurons develop in utero and are largely extant by age two after which they taper off or stop. the debate over ongoing neurogenesis continues with both pro and con arguments, and these studies do not produce clear results because of the differing means they use to detect young neurons – all of which – at least to my read are questionable. So I can’t levy an opinion either way but I’m extremely skeptical of the idea.

 

 

 

 

MATURATION

 

Now, as we see, neurons develop in density as they learn to carry and make use of more information.

 

But it’s a hierarchy, right? neurons depend on nerves, and neurons on those neurons that attach to nerves, and so on.

 

And as we gain in experience we develop more connections that express variations, but we also discover generalizations. So the neuronsin our brains mature from the foundation of sense-perception, to motor ability, into higher level reasoning – and hopefully … well hopefully we eventually reach maturity… eventually. 😉

 

[ GROWTH PHASES ]

 

This means that there are growth phases to human cognitive as well as physical development.

 

And we can be harmed by poor training of our brains at a given age, by failing to exercise our facilities that are under development at that age.  The most studied example is vision. The next is coordination. the next are socialization and problem solving. Lastly it’s higher order reasoning and executive function.

 

My pet peeve is making boys sit in school, and prohibiting them from dominance play – which is why we should return to gender based schools, with gender based teachers. The other is putting children of one grade in the same classroom rather than many grades, boys girls, and lattitudinal races, both pairs maturing at different rates in the same classrooms. It’s harmful every single day.

 

 

 

 

 

 

 

NEURONS SUMMARY

 

So what I want to get across to you is that millions of nerve fibers reach the cortex, and branch into a region, connecting to many neurons where unfathomable numbers of neurons, with unfathomable numbers of connections with many kinds of connections – only switching on and off like a transistor, doing so by positive and negative inputs of a range of positive and negative influences of greater and lesser potential both before and after the firing, and networked in series and parallel to one another, producing what is an infinitely complex self organizing logic. 

 

In database design, we sometimes sarcastically suggest that we can “normailze” down to ones and zeroes. That means, that we can start with a table with only two rows, one and zero and build the any entire database up from there.

 

When programming, some of us are keenly aware that all our human readable code is compiled into little more than on and off, or true and false switches – or at least, a minimum sized packet of those switches, where – like numbers – some combinations consist of some of operations (verbs) some of names (proper nouns), some of locations(nouns), and some of values(nouns, verbs, adverbs, adjectives etc.) – a very primitive language and grammar.

 

At the very smallest level we can recognize those switches, the vocabular, and the grammar, and we can slowly trace the story one step at a time.  But when we look at our own neurons, the complexity is such that we can recognize the switches we call neurons, we are beginning to understand that a grammar exists, and we can vaguely understand that a story is being told. But the vocabulary and the order it’s being told in are so complicated we cannot at present observe and trace it step by step.

 

The best we can say is that we have a fairly good idea today how the brain programs itself with the very basic logic of neurons, all of which turn on, or off, according to the very complex logic produced by the dendritic spikes, dendrites, soma, axon, axon terminals, and axon boutons, and the connectivity between the chemistry in the surrounding fluid, the electrial carges within and through the surrounding fluid, and the physical connections that are possible between pretty much every one of those points at by every other point, producing excititory and inhibitory stimulation affecting the firing of the neuron, the voltage that reaches the axon terminals, and stimulating the bouton to release whatever it can across that synaptic cleft.

 

However, what this means is that we while we may understand and describe in general how the brain works, despite functioning in just ‘on and off’ like our much simpler transistors, the complexity of these logic circuits is something that is infinite. It is probably impossible to compute with any accuracy how much information is transmitted by a single neuron firing in real world use. The logic of any given circuit, or how any given circuit develops its logic, simply because of the number of active dimensions of causality and the massive parallelism and redundancy involved.

 

 

 

 

[ DIMENSIONS – NEURONS ]

 

So lets cover the dimensions of Neurons.

 

FUNCTION 

… Supply energy (resources) to the parts of the neuron.

… 

ENVIRONMENT

… Fluidic 

… Very densely packed.

PARTS

… Dendrites (in), 

… … Filopodia (filament) <-> 

… … … Spine <-> 

… … … … Synaptic Port.

… Soma (Cell Body), 

… … A Voltage 

… … Neurochemicals that alter voltage up or down

… … Ports for in or out of neurochemicals

… … Synapses (axons that have attached to the cell body)

… … Axon Hillock 

(Switches on/off all or nothing, when voltage is reached)

… Axon (out), 

… … Axon Branch > Axon Terminal > Bouton > Synapse

TYPES OF NEURONS 

… Input, 

… Association, 

… Output 

INFORMATION

… Excitatory +, 80%, of which 80% are pyramidal 20 stellate,

… Inhibitory -, 20%

INFORMATION TRANSFER

… Electrical (body), 

… Chemical (gap), 

… Local (fluid)

INFORMATIONAL CONTENT

… Frequency

… Amplitude

… Phase 

… rate coding

CONNECTIONS

… To Fluid: Axo-ExtraCellular 

… To Bloodstream: Axo-Secretory

… To Axon: Axo-Axonic.

… To *Dendrite:  Axo-Dendritic* 

… To Soma: Axo Somatic 

… To Terminal: Axo synaptic

GENERATING RELATIONS

… Discover and Create

… Read and Reinforce

… Update and Change 

… Delete and Prune

WITH CALCULATIONS 

… dendritic = pre=somatic

… somatic 

… connective

GROWTH PHASES

… Sensory

… Motor

… Cognitive