The Neuron – A Hackers Perspective

It’s not too often that you see handkerchiefs around anymore. Today, they’re largely viewed as unsanitary and well… just plain gross. You’ll be quite disappointed to learn that they have absolutely nothing to do with this article other than a couple of similarities they share when compared to your neocortex. If you were to pull the neocortex from your brain and stretch it out on a table, you most likely wouldn’t be able to see that not only is it roughly the size of a large handkerchief; it also shares the same thickness.

The neocortex, or cortex for short, is Latin for “new rind”, or “new bark”, and represents the most recent evolutionary change to the mammalian brain. It envelopes the “old brain” and has several ridges and valleys (called sulci and gyri) that formed from evolution’s mostly successful attempt to stuff as much cortex as possible into our skulls. It has taken on the duties of processing sensory inputs and storing memories, and rightfully so. Draw a one millimeter square on your handkerchief cortex, and it would contain around 100,000 neurons. It has been estimated that the typical human cortex contains some 30 billion total neurons. If we make the conservative guess that each neuron has 1,000 synapses, that would put the total synaptic connections in your cortex at 30 trillion — a number so large that it is literally beyond our ability to comprehend. And apparently enough to store all the memories of a lifetime.

In the theater of your mind, imagine a stretched-out handkerchief lying in front of you. It is… you. It contains everything about you. Every memory that you have is in there. Your best friend’s voice, the smell of your favorite food, the song you heard on the radio this morning, that feeling you get when your kids tell you they love you is all in there. Your cortex, that little insignificant looking handkerchief in front of you, is reading this article at this very moment.

What an amazing machine; a machine that is made possible with a special type of cell – a cell we call a neuron. In this article, we’re going to explore how a neuron works from an electrical vantage point. That is, how electrical signals move from neuron to neuron and create who we are.

A Basic Neuron

Neuron diagram via Enchanted Learning

Despite the amazing feats a human brain performs, the neuron is comparatively simple when observed by itself. Neurons are living cells, however, and have many of the same complexities as other cells – such as a nucleus, mitochondria, ribosomes, and so on. Each one of these cellular parts could be the subject of an entire book. Its simplicity arises from the basic job it does – which is outputting a voltage when the sum of its inputs reaches a certain threshold, which is roughly 55 mV.

Using the image above, let’s examine the three major components of a neuron.

Soma

The soma is the cell body and contains the nucleus and other components of a typical cell. There are different types of neurons whose differing characteristics come from the soma. Its size can range from 4 to over 100 micrometers.

Dendrites

Dendrites protrude from the soma and act as the inputs of the neuron. A typical neuron will have thousands of dendrites, with each connecting to an axon of another neuron. The connection is called a synapse but is not a physical one. There is a gap between the ends of the dendrite and axon called a synaptic cleft. Information is relayed through the gap via neural transmitters, which are chemicals such as dopamine and serotonin.

Axon

Each neuron has only a single axon that extends from the soma, and acts similar to an electrical wire. Each axon will terminate with terminal fibers, forming synapses with as many as 1,000 other neurons. Axons vary in length and can reach a few meters long. The longest axons in the human body run from the bottom of the foot to the spinal cord.

The basic electrical operation of a neuron is to output a voltage spike from its axon when the sum of its input voltages (via its dendrites) crosses a specific threshold. And since axons are connected to dendrites of other neurons, you end up with this vastly complicated neural network.

Since we’re all a bunch of electronic types here, you might be thinking of these ‘voltage spikes’ as a difference of potential. But that’s not how it works. Not in the brain anyway. Let’s take a closer look at how electricity flows from neuron to neuron.

Action Potentials – The Communication Protocol of the Brain

The axon is covered in a myelin sheet which acts as an insulator. There are small breaks in the sheet along the length of the axon which are named after its discoverer, called Nodes of Ranvier. It’s important to note that these nodes are ion channels. In the spaces just outside and inside of the axon membrane exists a concentration of potassium and sodium ions. The ion channels will open and close, creating a local difference in the concentration of sodium and potassium ions.

Diagram via Washington U.

We all should know that an ion is an atom with a charge. In a resting state, the sodium/potassium ion concentration creates a negative 70 mV difference of potential between the outside and inside of the axon membrane, with there being a higher concentration of sodium ions outside and a higher concentration of potassium ions inside. The soma will create an action potential when -55 mV is reached. When this happens, a sodium ion channel will open. This lets positive sodium ions from outside the axon membrane to leak inside, changing the sodium/potassium ion concentration inside the axon, which in turn changes the difference of potential from -55 mV to around +40 mV. This process in known as depolarization.

Graph via Washington U.

One by one, sodium ion channels open along the entire length of the axon. Each one opens only for a short time, and immediately afterward, potassium ion channels open, allowing positive potassium ions to move from inside the axon membrane to the outside. This changes the concentration of sodium/potassium ions and brings the difference of potential back to its resting place of -70 mV in a process known as repolarization. Fro start to finish, the process takes about five milliseconds to complete. The process causes a 110 mV voltage spike to ride down the length of the entire axon, and is called an action potential. This voltage spike will end up in the soma of another neuron. If that particular neuron gets enough of these spikes, it too will create an action potential. This is the basic process of how electrical patterns propagate throughout the cortex.

The mammalian brain, specifically the cortex, is an incredible machine and capable of far more than even our most powerful computers. Understanding how it works will give us a better insight into building intelligent machines. And now that you know the basic electrical properties of a neuron, you’re in a better position to understand artificial neural networks.

Sources

Action Potential in Neurons, via Youtube

On Intelligence, by Jeff Hawkins, ISDN 978-0805078534

Yes/No Neural Interface Partly Works

It sounds like something out of a sci-fi or horror movie: people suffering from complete locked-in state (CLIS) have lost all motor control, but their brains are otherwise functioning normally. This can result from spinal cord injuries or anyotrophic lateral sclerosis (ALS). Patients who are only partially locked in can often blink to signal yes or no. CLIS patients don’t even have this option. So researchers are trying to literally read their minds.

Neuroelectrical technologies, like the EEG, haven’t been successful so far, so the scientists took another tack: using near-infrared light to detect the oxygenation of blood in the forehead. The results are promising, but we’re not there yet. The system detected answers correctly during training sessions about 70% of the time, where the upper bound for random chance is around 65% — varying from trial to trial. This may not seem overwhelmingly significant, but repeating the question many times can help improve confidence in the answer, and these are people with no means of communicating with the outside world. Anything is better than nothing?

journal-pbio-1002593-g001It’s noteworthy that the blood oxygen curves over time vary significantly from patient to patient, but seem roughly consistent within a single patient. Some people simply have patterns that are easier to read. You can see all the data in the paper.

They go into the methodology as well, which is not straightforward either. How would you design a test for a person who you can’t even tell if they are awake, for instance? They ask complementary questions (“Paris is the capital of France”, “Berlin is the capital of Germany”, “Paris is the capital of Germany”, and “Berlin is the capital of France”) to be absolutely sure they’re getting the classifications right.

It’s interesting science, and for a good cause: improving the quality of life for people who have lost all contact with their bodies. (Most of whom answered “yes” to the statement “I am happy.” Food for thought.)

Via Science-Based Medicine, and thanks to [gippgig] for the unintentional tip! Photo from the Wyss Center, one of the research institutes involved in the study.

Program Your Brain, Hack Your Way to Productivity

Most people wish they were more productive. Some buckle down and leverage some rare facet of their personality to force the work out. Some of them talk with friends. Some go on vision quests. There are lots of methods for lots of types of people. Most hackers, I’ve noticed, look for a datasheet. An engineer’s reference. We want to solve the problem like we solve technical problems.

It's got the cover equivalent of click-bait, but the centimeter thick bibliography listing research sources at the back won me over.
It’s got the cover equivalent of click-bait, but the centimeter thick bibliography listing research sources at the back won me over.

There were three books that gave me the first hints at how to look objectively at my brain and start to hack on it a little. These were The Power of Habit by Charles Duhigg, Flow By Mihaly Csikszentmihalyi, and Getting Things Done By David Allen.

I sort of wandered into these books in a haphazard path. The first I encountered was The Power of Habit which I found to be a bit of a revelation. It presented the idea of habits as functions in the great computer program that makes up a person. The brain sees that you’re doing a task over and over again and just learns to do it. It keeps optimizing and optimizing this program over time. All a person needs to do is trigger the habit loop and then it will run.

For example: Typing. At first you either take a course or, if your parents left you alone with a computer for hours on end, hunt-and-peck your way to a decent typing speed. It involves a lot of looking down at the keyboard. Eventually you notice that you don’t actually need to look at the keyboard at all. Depending on your stage you may still be “t-h-i-n-k-i-n-g”, mentally placing each letter as you type. However, eventually your brain begins to abstract this away until it has stored, somewhere, a combination of hand movements for every single word or key combination you typically use. It’s only when you have to spell a new word that you fall back on older programs.

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How the Human Brain Stores Data

Evolution is one clever fellow. Next time you’re strolling about outdoors, pick up a pine cone and take a look at the layout of the bract scales. You’ll find an unmistakable geometric structure. In fact, this same structure can be seen in the petals of a rose, the seeds of a sunflower and even the cochlea bone in your inner ear. Look closely enough, and you’ll find this spiraling structure everywhere. It’s based on a series of integers called the Fibonacci sequence. Leonardo Bonacci discovered the sequence while trying to figure out how many rabbits he could make starting with just two. It’s quite simple — add the right most integer to the previous one to get the next one in the sequence. Starting from zero, this would give you 0-1-1-2-3-5-8-13-21 and so on. If one was to look at this sequence in the form of geometric shapes, they can create square tiles whose sides are the length of the value in the sequence. If you connect the diagonal corners of these tiles with an infinite curve, you end up with the spiral that you saw in the pine cone and other natural objects.

fib_01
Source via Geocaching

So how did mother nature discover this geometric structure? Surely it does not know math. How then can it come up with intricate and sophisticated structures? It turns out that this Fibonacci spiral is the most efficient way of squeezing the most amount of stuff in the least amount of space. And if one takes natural selection seriously, this makes perfect sense. Eons of trial and error to make the most copies of itself has stumbled upon a mathematical principle that permeates life on earth.

fb_02
Source via John Simmons

The homo sapiens brain is the product of this same evolutionary process, and has been evolving for an estimated 7 million years. It would be foolish to think that this same type of efficiency natural selection has stumbled across would not be present in the current homo sapiens brain. I want to impress upon you this idea of efficiency. Natural selection discovered the Fibonacci sequence solely because it is the most efficient way to do a particular task. If the brain has a task of storing information, it is perfectly reasonable that millions of years of evolution has honed it so that it does this in the most efficient way possible as well. In this article, we shall explore this idea of efficiency in data storage, and leave you to ponder its applications in the computer sciences.

Continue reading “How the Human Brain Stores Data”

Carbon Monoxide: Hunting a Silent Killer

Walt and Molly Weber had just finished several long weeks of work. He was an FBI agent on an important case. She had a management job at Houghton Mifflin. On a sunny Friday evening in February of 1995, the two embarked on a much needed weekend skiing getaway. They drove five hours to the Sierra Mountains in California’s Mammoth Lakes ski area. This was a last-minute trip, so most of the nicer hotels were booked. The tired couple checked in at a lower cost motel at around 11:30pm on Friday night. They quickly settled in and went to bed, planning for an early start with a 7am wakeup call Saturday morning.

When the front desk called on Saturday, no one answered the phone. The desk manager figured they had gotten an early start and were already on the slopes. Sunday was the same. It wasn’t until a maid went to check on the room that the couple were found to be still in bed, unresponsive.

Continue reading “Carbon Monoxide: Hunting a Silent Killer”

Hacklet 105 – More Mind and Brain Hacks

A mind is a terrible thing to waste – but an awesome thing to hack. We last visited brain hacks back in July of 2015. Things happen fast on Hackaday.io. Miss a couple of days, and you’ll miss a bunch of great new projects, including some awesome new biotech hacks. This week, we’re checking out some of the best new mind and brain hacks on Hackaday.io

We start with [Daniel Felipe Valencia V] and Brainmotic. Brainmotic is [Daniel’s] entry in the 2016 Hackaday Prize. Smart homes and the Internet of Things are huge buzzwords these days. [Daniel’s] project aims to meld this technology with electroencephalogram (EEG). Your mind will be able to control your home. This would be great for anyone, but it’s especially important for the handicapped. Brainmotic’s interface is using the open hardware OpenBCI as the brain interface. [Daniel’s] software and hardware will create a bridge between this interface and the user’s home.

 

biofeed1Next we have [Angeliki Beyko] with Serial / Wireless Brainwave Biofeedback. EEG used to be very expensive to implement. Things have gotten cheap enough that we now have brain controlled toys on the market. [Angeliki] is hacking these toys into useful biofeedback tools. These tools can be used to visualize, and even control the user’s state of mind. [Angeliki’s] weapon of choice is the MindFlex series of toys. With the help of a PunchThrouch LightBlue Bean she was able to get the EEG headsets talking on Bluetooth. A bit of fancy software on the PC side allows the brainwave signals relieved by the MindFlex to be interpreted as simple graphs. [Angeliki] even went on to create a Mind-Controlled Robotic Xylophone based on this project.

brainhelmetNext is [Stuart Longland] who hopes to protect brains with Improved Helmets. Traumatic Brain Injury (TBI) is in the spotlight of medical technology these days. As bad as it may be, TBI is just one of several types of head and neck injuries one may sustain when in a bicycle or motorcycle accident. Technology exists to reduce injury, and is included with some new helmets. Many of these technologies, such as MIPS, are patented. [Stuart] is working to create a more accurate model of the head within the helmet, and the brain within the skull. From this data he intends to create a license free protection system which can be used with new helmets as well as retrofitted to existing hardware.

mindwaveFinally we have [Tom Meehan], whose entry in the 2016 Hackaday Prize is Train Your Brain with Neurofeedback. [Tom] is hoping to improve quality of life for people suffering from Epilepsy, Autism, ADHD, and other conditions with the use of neurofeedback. Like [Angeliki ] up above, [Tom] is hacking hardware from NeuroSky. In this case it’s the MindWave headset. [Tom’s] current goal is to pull data from the TAGM1 board inside the MindWave. Once he obtains EEG data, a Java application running on the PC side will allow him to display users EEG information. This is a brand new project with updates coming quickly – so it’s definitely one to watch!

If you want more mind hacking goodness, check out our freshly updated brain hacking project list! Did I miss your project? Don’t be shy, just drop me a message on Hackaday.io. That’s it for this week’s Hacklet, As always, see you next week. Same hack time, same hack channel, bringing you the best of Hackaday.io!

Museum Shows Off Retro Malware

There’s some debate on which program gets the infamous title of “First Computer Virus”. There were a few for MS-DOS machines in the 80s and even one that spread through ARPANET in the 70s. Even John von Neumann theorized that programs might one day self-replicate. To compile all of these early examples of malware, and possibly settle this question once and for all, [Mikko Hypponen] has started collecting many of the early malware programs into a Museum of Malware.

While unlucky (or careless) users today are confronted with entire hard drive encryption viruses (or worse), a lot of the early viruses were relatively harmless. Examples include Brain which spread via floppy disk, the experimental ARPANET virus, or Elk Cloner which, despite many geniuses falsely claiming that Apples are immune to viruses, infected Mac computers of the 80s. [Mikko] has collected many more from this era that can be downloaded or demonstrated in a browser.

Retrocomputing is an active community, with users keeping gear of this era up and running despite it being 30+ years old. This software, while malicious at the time, is a great look into what the personal computing world was like in its infancy. And don’t forget, if you have a beige computer from a bygone era, you can always load up our Retro Page.

Thanks to [chad] for the tip!