Posts Tagged ‘ technology ’

Neuroscience Friends!

I’ve just returned from a thrilling weekend at the BIL Conference in Long Beach, California (yes, the pun on “TED” is very intentional) where I met all kinds of smart, fun people – including lots of folks who share my love for braaaiiins!

The conference was held in... The Future!

So I thought I’d introduce you guys to some of the friends I made. I think you’ll be as surprised – and as excited – as I am.

Backyard Brains
Their motto is “neuroscience for everyone” – how cool is that? They sell affordable kits that let you experiment at home with the nervous systems of insects and other creatures. They gave a super-fun presentation where I got to help dissect a cockroach and send electrical signals through its nerves.

Interaxon
They build all kinds of cutting-edge tools that let home users study their brain activity, and even control machines and art projects with it. Their founder, Ariel Garten, has a great TED talk here – I’ve rarely met anyone else who was so excited to have weird new neuroscience adventures.

Deltaself and Dangerously Hardcore
Two blogs by the very smart Naomi Most – the first is about how scientific data is changing the way we all understand our minds and bodies; the second is about hacking your own behavior to stay healthier and live better.

Halcyon Molecular
Their aim is to put the power to sequence and modify genomes in everyone’s hands within the next few decades. They’re getting some huge funding lately, and lots of attention in major science journals.

Bonus – XCOR Aerospace
They’re building a privately-funded suborbital spacecraft for independent science missions. If there’s anybody who can help us all join the search for alien life in the near future, I bet it’s these guys.

So check those links out and let me know what you think. I’d love to get these folks involved in future videos, especially if you’re interested in any of them.

Beyond Perfection

If you continue to practice a skill even after you’ve achieved mastery of it, your brain keeps learning to perform it more and more efficiently, says a new study.

Believing you've reached perfection can lead you to engage in some...interesting...behavior.

As we perform a task – say, dunking a basketball or playing a sweet guitar solo – over and over again, we eventually reach a point that some psychologists call “unconscious competence,” where we execute each movement perfectly without devoting any conscious attention to it at all. But even after this point, our bodies keep finding ways to perform the task more and more efficiently, burning less energy with each repetition.

This story’s got it all – brain-hacks, mysterious discoveries, robots – but to put it all in perspective, we’ve gotta start by talking about this idea we call perfection.

“Practice makes perfect,” the old saying goes – but what’s this “perfect” we’re trying to reach? Isn’t it often a matter of opinion? What I mean is, how do we judge, say, a “perfect” backflip or a “perfect” dive? We compare it to others we’ve seen, and decide that it meets certain criteria better than those examples did; that it was performed with less error.

But where do these criteria for perfection come from? Well, some have said there’s a Platonic realm of “perfect forms” that our minds are somehow tapping into – a realm that contains not only “The Perfect Chair” but “the perfect version of that chair” and “the perfect version of that other chair” and “the perfect version of that molecule” and so on, ad infinitum. Kinda weird, I know – but a lot of smart people believed in ideas like this for thousands of years, and some still do.

Science, though, works in a different way: Instead of trying to tap into a world of perfect forms, scientists (and engineers and mathematicians and programmers and so on) work to find errors and fix them.

And it turns out that the human body is quite talented at doing exactly that. A team led by Alaa Ahmed at the University of Colorado at Boulder found this out firsthand, with the help of robots, the Journal of Neuroscience reports:

Seated subjects made horizontal planar reaching movements toward a target using a robotic arm.

These researchers weren’t interested in brain activity – instead, as the volunteers practiced moving the arm, the researchers measured their oxygen consumption, their carbon dioxide output, and their muscle activity.

As you might expect, the scientists found that as people got better at moving the arm, their consumption of oxygen and production of carbon dioxide, and their overall muscle activity, steadily decreased:

Subjects decreased movement error and learned the novel dynamics. By the end of learning, net metabolic power decreased by ∼20% from initial learning. Muscle activity and coactivation also decreased with motor learning.

But the volunteers’ bodies didn’t stop there. As people kept practicing, their gas consumption and output continued to decrease – and so did their muscle activation. In short, their bodies kept learning to move the arm with measurably less and less physical effort.

Though this study didn’t record any data from the subjects’ brains, it’s easy to see how this continual improvement is just one reflection of a very versatile ability. For instance, we know that when two neurons get really friendly, they become more sensitive to each others’ signals – and we also know that underused neural pathways gradually fade away, making room for new ones. Self-improvement impulses are woven deeply into our bodies – into our cells.

When I say that our brains and bodies are cities, I’m not just speaking metaphorically – you are, quite literally, a vast community – an ecosystem composed of trillions of interdependent microorganisms, each one constantly struggling for its own nourishment and safety.

And though your conscious mind is one part – a very significant part – of this great microscopic nation, it’s not the only part that can learn. At this moment, all throughout the lightless highways and chambers of your body, far below your conscious access, networks of cells are changing, adapting, learning, adjusting - finding errors and fixing them.

So, you can think about “perfection” all you want – but even at that magical moment when you achieve it, the multitudes within you are still hard at work, figuring out how to reach beyond that ideal.

What do you think they’re up to right now?

Podcast 1: Our Interview With Joshua Vogelstein

Here it is – the first Connectome podcast!


Click here to subscribe in iTunes.

Join us as we talk with Joshua Vogelstein, a leading connectomics researcher, about the Open Connectome Project, an international venture to make data on neural connectivity available to everyone, all over the world. It’s like Google Maps for your brain.

Here’s a direct link to download the mp3.

We’ve learned a lot while working on this first episode, and future ones will be much cleaner and higher-fi.

Anyway, enjoy!

Guiding Neuron Growth

Our neurons’ growth can be shaped by tiny cues from spinning microparticles in the fluids that surround them, a new study reports.

An axon gets all friendly with a spinnin' microparticle.

The branching and growth of neurons is based on several kinds of guides, including their chemical environment, their location within the brain, and the dense network of glial cells that support and protect them. But as it turns out, they’re also surprisingly responsive to fluid dynamics, turning in response to the rotation of nearby microparticles – a bit like the way a vine can climb a fence-post.

Since the early days of neuroscience, researchers have dreamed of growing and shaping neurons for specific purposes – to patch gaps in damaged neural networks, for example; or just to test their workings under controlled lab conditions.

But it’s only in the past few years that technologies like microfluidic chambers and pluripotent stem cells have enabled researchers to grow healthy, living neurons according to precise specifications, and study those cells’ responses to all kinds of stimuli. In fact, it looks like it won’t be much longer ’til doctors can implant networks of artificially grown neurons directly into living adult brains.

But as the journal Nature Photonics reports, the big breakthrough this time comes from Samarendra Mohanty at The University of Texas at Arlington, who found that neuron growth can respond to physical cues – spinning particles in fluid, for instance – as well as to chemical ones.

Mohanty’s team discovered this by using a tiny laser to direct the spin of a microparticle positioned next to the axon of a growing neuron. The spinning particle generated a miniature counterclockwise vortex in the fluid – and wouldn’t ya know it; the axon started wrapping around the spinning particle as the neuron grew:

Circularly polarized light with angular momentum causes the trapped bead to spin. This creates a localized microfluidic flow … against the growth cone that turns in response to the shear.

In short, this is the first time a scientific team has used a mechanical device – a “micro-motor,” as they call it – to directly control and precisely adjust the growth of a single axon:

The direction of axonal growth can be precisely manipulated by changing the rotation direction and position of this optically driven micromotor.

So far, the micromotor only works 42 percent of the time – but the team is optimistic that future tests will lead to greater reliability and more precise control. In the near future, micromotors like this one could be used to turn the growth of an axon back and forth – or even to funnel growth through “gauntlets” of spinning particles.

Most conveniently of all, the particles could be injected, re-positioned, and removed as needed – providing a much simpler, more modifiable architecture than any other neuron-shaping technology in use today.

And for the slightly more distant future, Mohanty’s lab is hard at work on a system for providing long-range, long-term guidance to entire neural networks through completely non-invasive optical methods.

Until then, though, isn’t it amazing to stop and think about all the neurons that are growing and reshaping themselves – all the delicate intertwining lattices relaying millions of mysterious coded messages, right now, within the lightless interior of your own head?

Call me self-centered, but I think it’s just about the coolest thing on planet Earth.

The Colors, Man! The Colors!

Scientists have discovered direct neural correlates of synesthesia, a new study reports.

They sound like unicorns and rainbows.

Not only have they detected activation patterns corresponding to synesthesic activity (such as “seeing” certain colors when thinking of certain numbers or sounds) – they’ve isolated an actual functional difference in the brains of synesthesic people. And what’s more, they’ve discovered a way to crank up synesthesic activity.

Let’s break this down and talk about what they’ve done here.

To understand what’s going on, let’s take a quick glance at history. Synesthesia’s fascinated artists and scientists since way back - in fact, the first people to write about it were the ancient Greeks, who composed treatises on the “colors” of various musical sounds.

Centuries later, Newton and Goethe both wrote that musical tones probably shared frequencies with color tones – and though that idea turned out to be incorrect, it did inspire the construction of “color organs” whose keyboards mapped specific notes to specific shades.

The first doctor to study synesthesia from a rigorous medical perspective was Gustav Fechner, who performed extensive surveys of synesthetes throughout the 1870s. The topic went on to catch the interest of other influential scientists in the late 19th century – but with the rise of behaviorism in the 1930s, objective studies on subjective experiences became taboo in the psychology community, and synesthesia was left out in the cold for a few decades.

In the 1950s, the cognitive revolution made studying cognition and subjective experience cool again – but it wasn’t until the 1980s that synesthesia returned to the scientific spotlight, as neuroscientists and psychologists like  Richard Cytowic and Simon Baron-Cohen began to classify and break down synesthetic experiences. For the first time, synesthesic experiences were organized into distinct types, and studied under controlled lab conditions.

Today, most synesthesia research focuses on grapheme → color synesthesia - in which numbers and letters are associated with specific colors – because it’s pretty straightforward to study. And thanks to the “insider reporting” of synesthetes like Daniel Tammett, we’re getting ever-clearer glimpses into the synesthetic experience.

But as the journal Current Biology reports, today marks a major leap forward in our understanding of synesthesia: a team led by Oxford University’s Devin Terhune has discovered that the visual cortex of grapheme → color synesthetes is more sensitive – and therefore, more responsive – than it is in people who don’t experience synesthesia.

The team demonstrated this by applying transcranial magnetic stimulation (TMS) to the visual cortices of volunteers, which led to a thrilling discovery:

Synesthetes display 3-fold lower phosphene thresholds than controls during stimulation of the primary visual cortex. … These results indicate that hyperexcitability acts as a source of noise in visual cortex that influences the availability of the neuronal signals underlying conscious awareness of synesthetic photisms.

In short, the visual cortex of a synesthete is three times more sensitive to incoming signals than that of a non-synesthete – which means tiny electrochemical signals that a non-synesthete’s brain might consider stray noise get interpreted into “mind’s-eye” experiences in a synesthete’s visual cortex.The question of what, exactly, causes this difference in the first place remains a Science Mystery, ripe for investigation.

But wait – this study gets much, much cooler.

There’s a technology called transcranial direct current stimulation (TDCS), which changes the firing thresholds of targeted neurons – making them more or less likely to fire when they get hit with a signal. The researchers applied TDCS to specific parts of the visual cortex, and found that they could “turn up” and “turn down” the intensity of the synesthesic experience:

Synesthesia can be selectively augmented with cathodal stimulation and attenuated with anodal stimulation of primary visual cortex. A control task revealed that the effect of the brain stimulation was specific to the experience of synesthesia.

In other words, they’ve discovered a technological mechanism for directly controlling the experience of synesthesia.

So Burning Question #1 is, Could TDCS be used to induce synesthesia – or create hallucinations - in non-synesthetes? With the right neurological and psychological preparation, it certainly seems possible. And Burning Question #2 is, could it be used to “turn down” the intensity of hallucinations in people with schizophrenia and other psychological disorders? It’ll take a lot more lab work to answer that question with any certainty – but I’d say it merits some lookin’ into.

In the meantime, I’m going to find some nice green music to listen to.

______________

1. This means synesthesia is somewhat similar to Charles Bonnet syndrome - in which blind patients see vivid, detailed hallucinations when their under-stimulated (and thus, hyper-sensitive) visual cortices catch a stray signal – and to musical ear syndrome, in which deaf people vividly hear singing. Here’s an amazing TED talk by Oliver Sacks on that very topic.

The Brain Lab Tour

This past weekend, I got to visit one of the coolest places I’ve ever seen: the UCLA Laboratory of Neuro Imaging (LONI). So just for today, I’m gonna take a break from news reporting, and tell you a little about what goes on inside an actual cutting-edge neuroscience lab. Sound good? OK, let’s go!

I'd be okay with just bringing a tent and camping out here.

I’m not sure quite what I was expecting to see as I stepped through the lab’s electronically locked door – certainly not the roomful of clean, open-walled work areas that greeted me. I might’ve been standing in a sleek law office, or an advertising agency – except that the flatscreens adorning the walls displayed colorful 3-D brain maps and reams of dense scientific data.

Imagine being five years old, celebrating Christmas morning at Disneyland - you get the idea.

But before I could start running around making googly-eyes at everything, it was time to meet my host – the delightful Eileen Luders, who’d offered to give me a tour of the lab when I’d gushed about my enthusiasm for her work. Eileen studies neural correlates of meditative states, and she’s also interested in isolating tiny structural variations that correspond to specific kinds of intelligence. More on this awesomeness shortly.

After introductions and a bit of happy chitchat, Eileen led me to a small screening room, whose entire front wall was an enormous wraparound high-resolution video screen. From the control booth, a lab technician dimmed the lights and played us a promo video that was ten minutes of pure heaven. We flew through huge, detailed 3-D brain atlases, watching neural pathways assemble and disassemble before our eyes. We plunged into the brains of schizophrenics and drug abusers and meditators, as data from fMRI and DTI and OTI exploded into multicolored digital sculptures of these brains’ structures and functions.

When it was over (all too soon), I asked Eileen what the lab normally uses this room for. “Mostly meetings,” she said with a chuckle.

As we strolled back to her office, she explained the principle on which this lab works: all the scans are processed by one huge supercomputer array housed in a well-locked room. All a team (or scientist) needs to perform a basic scan is the lab’s permission, about $600, and the time and technical know-how to program the scan they want and parse its results into meaningful data.

Researchers do most of this coding and data analysis from the comfort of the cubicle-esque work areas that fill most of the lab – and this non-centralization frees up more time on the scanners for other researchers, which keeps the lab more affordable and efficient for everyone.

And then we got to talking about some really cool stuff.

I asked Eileen what had gotten her so interested in the neuroscience of meditative states, and she told me she’s always been fascinated by the chasm between subjective experience (i.e., learning how to meditate) and objective science (i.e., what happens in our brains when we meditate). So, she’s been working to help narrow that gap – to study the brain activity of meditators as they meditate, give them feedback about the results – and essentially do her best to act as a fairly seamless translator between mind and machine (and vice versa).

I asked her what it was like having monks visit the lab. She told me two things: “They’re incredibly sharp; incredibly present,” she said. “And they were really excited to see if the bathroom was as cool as everything else.” In short, monks frickin’ rule.

Thinking about meditation, I wondered aloud whether singing and chanting might reflect an inherently different cognitive process from speech. There’s some (very preliminary) research suggesting that certain tones and vocalizations (such as chanting “aum” or humming a major scale) may help modulate patterns of neural activity far more directly than words can. Eileen mentioned that she’s done a bit of research on yogic chanting that might point in this direction. (Too bad we can’t time-travel back to 1968 and put these guys in one of her scanners.)

Anyway, it’s easy to see why Eileen’s also interested in finding neural correlates for specific kinds of intelligence. This got us talking about one of her other pet projects: looking for neural correlates of gender differences. She pointed out that women’s brains are, on average, a little smaller than men’s – “But when you adjust a male and female brain to equal size,” she said, “the differences aren’t nearly as obvious as they might appear at first glance.”  (A few days later, she sent me a published, peer-reviewed paper she’s written on this topic; I’m looking forward to diving into it.)

By this time, it was starting to get late, so Eileen offered me a quick tour of the lab before rushing off to do more Awesome Neuroscience Stuff. We peeked through the window of the supercomputer room, where multicolored lights flickered on rows of imposing black towers. We poked our heads into the wet lab, where neuroanatomists actually freeze and dissect brains. We stopped by a few workstations where technicians were busy designing scanning programs or analyzing their output. I wish I’d been able to take photos.

And then it was time to say goodbye. As Eileen and I shook hands at the doorway, I couldn’t help feeling that I wanted to give her a hug – to hug the whole lab, and everyone in it. It just made me so happy to think that there are other people like us – people filled with a deep yearning to understand what’s going on inside our heads, and just how it works – people driven to dedicate massive amounts of time and money to finding the pieces of this crazy puzzle, and starting to fit a few of those pieces together.

But most of all, I’m so glad that those people are kind, and friendly, and every bit as geeky as I am. Neuroscience FTW!

Flexible Scanner

A new kind of non-invasive brain scanner uses ultra-thin material to record high-resolution maps of brain activity, a new study reports.

The scandalous new ultrathin array bares all.

The scanner is composed of an array of 720 transistors conducting activity from 360 electrodes - and it’s thin and flexible enough to cling to the surface of the brain, or even slip inside the brain’s fissures (folds), or between lobes. Needless to say, this will let researchers peek at the brain’s inner workings with an unprecedented degree of detail.

Brain scanning has come a long way since the first electroencephalograms (EEGs) began recording electrical activity from the scalp in the late 1800s. Nowadays, between advanced deep-scanning technologies like fMRI and precise implantable microelectrode arrays (MEAs), neuroscientists are getting ever-clearer glimpses of what goes on inside our heads. Even so, fMRI scanners are bulky and expensive; and MEAs require many separate wires.

But now, as the journal Nature Neuroscience reports, a team led by the University of Pennsylvania’s Brian Litt has created an electrode array composed of a single flexible sheet, which can monitor electrical activity deep within the brain at high resolutions – and non-invasively, to boot.

In short, this interface overcomes several longstanding problems in brain-scanning technology with one fell swoop:

We developed new devices that integrate ultrathin and flexible silicon nanomembrane transistors into the electrode array, enabling new dense arrays of thousands of amplified and multiplexed sensors that are connected using fewer wires.

The team has already used the new devices to record some high-resolution scans, and the results speak for themselves:

We used this system to record spatial properties of cat brain activity in vivo, including sleep spindles, single-trial visual evoked responses and electrographic seizures. We found that seizures may manifest as recurrent spiral waves that propagate in the neocortex.

In other words, on one of their very first test runs, the team discovered a new pattern underlying the spread of seizures. Not bad for a start, eh?

But this, of course, is only the beginning. If all goes as planned, this technology will soon be helping doctors and researchers around the world diagnose brain disorders more quickly and accurately than ever before.

I don’t know about you, but it’s already sparking plenty of ideas in my mind.

Silicon Synapses

A new kind of computer chip mimics the way a neuron learns, a new study reports.

Behold! The mighty Synapse Chip!

The 400-transistor chip simulates the activity of a single synapse – a connection between two neurons. Because of the chip’s complexity, it’s able to mimic a synapse’s plasticity – its ability to subtly change structure and function in response to new stimuli.

For example, a synapse that repeatedly responds to an electric shock might, over time, become less sensitive to that shock. Thus, synaptic plasticity forms the basis of neural learning, well below the level of conscious processing.

The human brain contains approximately 100 billion neurons, and more than 100 trillion synapses. Ever since the anatomist  Santiago Ramón y Cajal discovered the function of neurons back in the early 1900s, scientists have dreamed of building a device that replicated the behavior of even a single synapse. For decades, they had to content themselves with mathematical models and digital simulations.

But now, as the journal Proceedings of the National Academy of Sciences reports, a team led by MIT’s Chi-Sang Poon has constructed a working silicon model of a synapse in the physical world.

The chip uses transistors to mimic the activity of ion channels – small “ports” in the cell membranes of neurons that allow various amounts of neurotransmitter chemicals and ions (positively or negatively charged atoms) to pass in and out of the cell. These channels form the basis for synaptic communication – and for some of the most hotly researched topics in neuroscience.

While ordinary transistors act as binary “on/off” gates, neural synapses conduct signals along fairly smooth gradients, allowing the signals to increase in strength until they finally trigger the neuron to “fire” a signal on to its neighbor(s). It was this gradient property that Poon’s team sought to mimic with their new chip:

While most chips operate in a binary, on/off mode, current flows through the transistors on the new brain chip in analog, not digital, fashion. A gradient of electrical potential drives current to flow through the transistors just as ions flow through ion channels in a cell.

Since the researchers can also tweak the chip’s properties to mimic different kinds of ion channels, this provides one of the most realistic models yet for studying how individual synapses actually work.

The researchers have already used the chip to study long-term depression (LTD), the process by which some ion channels can weaken the synaptic activity of others. They also hope they’ll soon be using chips like this one in conjunction with lab-grown biological neurons, to discover all kinds of exciting new things about how cells behave “in the wild.”

Who knows – by this time next year, we may be watching nature documentaries about Neuron Cyborgs – but my guess is that the SyFy channel will get there first.

Brief and tangentially relevant side-note: Connectome posts may be somewhat spotty over the next few weeks, as I’m currently launching a new project, the details of which need to be kept under wraps (or “on the DL,” as the kids say) for the time being. I’ll do my best to report on neuroscience breakthroughs as often as I can during this period, and things should be back to (relatively) normal soon. Thanks for stickin’ with me.

Clarke’s Third Law

Today I want to take a break from breaking news and tell you about the new love of my life: my Emotiv EPOC neuroheadset.

Love at first sight.

This thing costs $299, and it is worth every penny. It uses 14 sensors positioned around my scalp to create a wireless EEG interface between my brain and my computer. I can move objects onscreen by thinking about it. I can click the mouse by thinking “click.” I can watch real-time video maps of my brain activity as I think about different ideas. I can summon specific feelings to navigate through photo albums sorted by emotion.

In short, the future is here, and it is awesome.

Brain-machine interfaces aren’t exactly earth-shaking news anymore, I know. I’ve written here about thought-controlled cursors, and here about sensory feedback systems that allow monkeys to control virtual hands and literally feel virtual textures. But this device makes this technology available and (relatively) affordable for me – and for you.

And we can do anything we want with it.

Are ya with me here?

Anything.

For instance, I spent most of last night watching waves of neural communication coruscate across my brain as I meditated, imagined, planned, observed, understood, realized, believed and calculated. I watched my left and right hemispheres signal to one another, like two great whales exchanging songs across an ocean, as they worked together to complete tasks. I watched tsunamis of synchronized activation blaze across the screen as disparate thoughts coalesced into dawning realizations. I watched congeries of light dance in the darkness as I thought, “I believe” or “I trust” or “I love.”

And that was just our first night together.

This is what I was talking about when I said we need devices that create real-time feedback loops between our brains and our computers, so we can watch the patterns our thoughts generate as we’re thinking them - the most intimate link ever between human consciousness and technology. We’re hurtling toward the culmination of a process that began millions of years ago in Africa; when one ape, a little smarter than his cousins, looked down at a rock and thought, “I want to use that for something.”

So, guess what this device is being used for right now. Well, for one thing, it’s providing easy computer access to people with physical disabilities, which is fantastic – but other than that, it’s mainly being marketed as a new gimmick for controlling video games.

Come on, people – we can dream so much bigger than this.

By way of inspiration, here’s my all-time favorite short sci-fi story, Exhalation by Ted Chiang. It’ll tell you everything you want to know about my aspirations.

And here’s a little song to set the mood.

Welcome to the Age of Technosophy. Let’s see where our imaginations take us.

Digital Friendships

Those of us who have loads of Facebook friends tend to have greater development in several specific brain regions, says a new study.

"Guys, guys - I just felt my entorhinal cortex triple in size!"

Researchers have found a strong correlation between large numbers of Facebook connections and increased development of gray matter – tissue containing neuron cell bodies, where dense communication occurs – in several regions crucial for social interaction: the amygdala, the right superior temporal sulcus (STS), the left middle temporal gyrus (MTG), and the right entorhinal cortex (EC).

Intriguingly, the size of some of these regions seems to correlate only with the size of people’s online social networks – not their real-world ones. It’s not clear yet, though, which factor is cause and which is effect – whether increased development in these regions enables people to develop larger online social networks, or vice versa. Even so, this is one of the first studies to directly link neuroanatomical data with online behavior.

As the journal Proceedings of the Royal Society B reports, a team led by Geraint Rees at University College London (UCL) performed MRI scans of the brains of 125 university students, and correlated this data with information on the size of these students’ Facebook friend groups:

The number of social contacts declared publicly on a major web-based social networking site was strongly associated with the structure of focal regions of the human brain. Specifically, we found that variation in the number of friends on Facebook strongly and significantly predicted grey matter volume in left MTG, right STS and right entorhinal cortex.

The exact links between these regions and online communication remain to be studied – but many of them have been correlated with social interaction in other studies.

The amygdala helps us process negative emotions like fear and sadness, both in ourselves and others – and people with larger amygdalas tend to have larger social networks overall, both online and otherwise.

Though no studies so far have correlated the size of the right STS with social network size, this structure is known to be involved in our ability to think of some objects as alive, as well as in helping us understand what others are looking at, and what emotions they’re expressing. A malfunctioning STS is thought to be a major factor in autism.

The exact role of the left MTG isn’t precisely understood, but many neuroscientists think this structure is involved in our ability to recognize familiar faces, and to process the semantic associations (i.e., meanings) of words.

The right EC works closely with the hippocampus to help us form and consolidate explicit/declarative memories – i.e., memories of specific facts and events, and specific associations between them (e.g., “kitties and bunnies are both mammals”). The EC is also one of the first areas attacked by Alzheimer’s. The researchers found that this region correlated especially strongly with online friend group size, but not particularly with real-world friend group size:

The right entorhinal cortex is implicated in associative memory formation for pairs of items including pairs of names and faces. Such memory capacity for name–face associates would constitute an important function for maintaining a large social network as observed in social network websites.

In short, the ability to mentally “tag” photos and posts with the correct associations is a central skill for maintaining digital friendships.

It’s easy to see how all the brain regions above could play central roles in a person’s ability to maintain a wide-ranging network of online friends. What’s especially interesting, though, is that all of them deal with features of social interaction that port from the real world to the online interaction space in straightforward ways - social hierarchies, facial expressions, repeatable facts, and so on – but that many other vital aspects of real-world social interaction – such as body language, and tone of voice – don’t appear to be nearly as crucial in an online social network. It’s enough to make you wonder what natural selection may have in store for our brains.

I don’t know about you, but I’m picturing a future where men compete in flame-wars for the right to woo attractive females. So while you my competitors are out hitting the bars and clubs this weekend, I’ll be – ah – honing my skills on 4chan and Reddit. Which is basically what I’d be doing this weekend anyway.

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