New neurons are born in your brain every day, which we know because of…nuclear bomb testing?

Long before I started in neuroscience I’d heard that you are born with all the neurons you’ll ever have. I always found this a bit disconcerting, so was pleased when I first heard of studies showing that mammals are able to produce new neurons in adulthood. Surprisingly, the first of these studies was all the way back in 1967 by Joseph Altman, who first showed evidence of new adult neurons born in the hippocampus of guinea pigs (how cliché). The topic wasn’t picked up (or believed, I guess) by the neuroscience mainstream until the 1980s-90s though, maybe because these methods couldn’t be used (for ethical reasons) to show adult neurogenesis in humans. Another reason is that there wasn’t unequivocal proof that these neurons were new and not just being repaired. I’ll save you most of the biochemistry, but the methods involved injecting either radioactive or Brominated thymidine (the T in the A T C G of DNA) into the brain and then measuring how much of these special Ts were later incorporated into neuronal DNA. The problem with these methods is your DNA is always breaking, and instead of throwing away every cell with a DNA mutation, your body has repair mechanisms in place to fix most of these mutations. Meaning the neurons could have just been refurbished (which everyone knows doesn’t sound as good as new) with the injected special Ts.

Now, this is where the eye-catching title—and some really cool science—comes in. From 1945-1998 there have been 2,053 nuclear bomb tests worldwide. Here’s an eerie video made by Japanese artist Isao Hashimoto showing all of them in a time-lapse map (make sure the sound is on). A by-product of nuclear reactions is the breakdown product carbon-14, a carbon atom with 8 neutrons. Even though carbon-14 can occur via cosmic rays acting on nitrogen in the atmosphere, levels spiked sharply during the peak of nuclear bomb tests in the 60s (even though it’s still only 1 part per trillion of the atmosphere’s carbon). See the black line in this graph to visualize how carbon-14 amounts changed over time:

Image(from Cell http://www.cell.com/abstract/S0092-8674%2814%2900137-8)

Now, based on my intro, you might guess where this is going: can we measure how carbon-14 incorporates itself into our DNA? Indeed, since carbon-14 is mixed into all the carbon we ingest throughout our lives, if new neurons were being born, we should be able to compare how much carbon-14 is in our DNA with the carbon-14 in the atmosphere. Jonas Frisén’s lab at the Karolinska Institute in Sweden has pursued this work over the last decade, using mass spectrometry to measure carbon-14 levels in DNA amounts as small as 30 micrograms (about 15 million neurons worth).

The studies go like this: donated, post-mortem human brains are measured for the amount of carbon-14 in the neuronal DNA of different brain regions. The authors can then graph how much carbon-14 they found versus what year that person was born. For example, look at the blue dot in the graph above, which is the carbon-14 from an example person’s hippocampus. This person was born in 1928, and shows MORE carbon-14 in their brain than was in the atmosphere in 1928. If this person was born with all their neurons, they should have the same amount of carbon-14 in their neurons as was in the atmosphere at that time. Instead, this dot shows that this person’s hippocampus has excess carbon-14, which must* have come from the rise in carbon-14 from new neurons that incorporated the increasing levels of carbon-14 throughout their lifetime (again, the black line). Now, look at the pink square representing carbon-14 in a person’s cortex. This person was born in 1968, and their cortex has the same carbon-14 as the atmosphere did. Therefore this brain region DOES have the same number of neurons as they did when they were born (their first 2005 paper showed that adult neurogenesis does NOT happen in the human cortex this way). Just to make sure you get what’s going on, look at the red dot again from hippocampus. In this case, this person born in 1976 has less carbon-14 than was in the atmosphere when they were born. Therefore, some of these hippocampal neurons must have been created after they were born, when carbon-14 levels had dropped below the atmospheric level at the year of their birth.

Now you can understand the main graph of their most recent (2014) paper:

Image

(from Cell http://www.cell.com/abstract/S0092-8674%2814%2900137-8)

Again, each dot is one person. And again, people born before the extensive rise in nuclear testing in the mid-1950s show increased carbon-14, indicative that some of their neurons were new. And again, people born after the peak of nuclear testing in 1965 show less carbon-14 than was present in the atmosphere at their birth, indicative that they had new neurons born after birth.

What’s extra fascinating about this most recent result from 2014 is where they found these new adult neurons: in the human striatum. No one had ever found newly born adult striatal neurons before (in any animal)!! In most mammals (largely rodents), new adult neurons had been found in the hippocampus and olfactory (smell) bulb. Frisén’s lab confirmed human hippocampal adult neurogenesis in 2013, and had surprisingly shown that humans—unlike their mammalian ancestors—had lost the ability to make new olfactory neurons. In fact what seems to have happened is that at some point in our recent evolutionary past, as our primate ancestors lost the smelling capabilities of their predecessor mammals, the neuroblasts (kind of like baby neurons) born in the lateral ventricle migrated into the striatum instead of the olfactory bulb. This means one unique feature of the primate (or maybe even just human) brain is new neurons in this region!

Now what does this mean, exactly? What’s a striatum (pronounced str-eye-ate-um)? Well, it turns out that this is a rather complex region with a lot of functions. Historically the striatum has been associated with motor control, but has more recently been shown to be important for a number of cognitive functions such as motivation, saliency in reward and working memory. In fact, a subregion of the striatum called the nucleus accumbens is considered to be the seat of substance dependency, including all addictive drugs like alcohol and cocaine, as well as a key region in reward for food and sex. What these new neurons do at this point is only speculative, although this paper gives us a few leads. First, as shown in previous work, these new adult striatal neurons were shown to be interneurons (I’ll trust you to read these graphs by now):

Image

(from Cell http://www.cell.com/abstract/S0092-8674%2814%2900137-8)

About 75% of striatal neurons are medium spiny neurons, but it’s the other 25% that show evidence of new adult neurons: the interneurons. Interneurons are typically inhibitory, meaning their job tends to be in more of a regulatory role to temper down excitatory motor/sensory neurons. And in fact, they looked at the brains of a few people that had Huntington’s disease and found a relative decrease in these new (tempering) interneurons in their striatums (striata?). This makes some intuitive sense, as the disease is first characterized by a lack of movement control until it progresses into higher cognitive decline. Therefore these results provide an interesting new avenue for therapies in such neurodegenerative disorders such as this and Parkinson’s, both of which are largely rooted in/near the striatum, wherein rescuing adult neurogenesis has the potential to reverse symptoms (as has actually been shown in mouse models).

One other novel finding from these adult neurogenesis papers you might find interesting is they can model the turnover rate of new neurons at various ages by comparing how many new neurons there are in the brains of people that died at various ages. And, with similar numbers as their previous work in the hippocampus, they show a notable decline in the turnover rate of neurons in the striatum as a person ages:

Image

(from Cell http://www.cell.com/abstract/S0092-8674%2814%2900137-8)

At the extremes, about 10% of a 20 year-old’s striatal neurons are turned over each year, while <1% of an 80 year-old’s striatal neurons are replaced with new ones. As shown in the 3rd graph above, only some types of striatal neurons are replaced by new neurons (the interneurons), and they estimate that overall within this “renewing fraction” 2.7% of neurons are turned over per year. I don’t know about you, but I feel younger already! Thanks, brain.

In the end, these papers that unequivocally prove and expand upon our knowledge of human adult neurogenesis might be the singular good thing to come from nuclear bomb testing (at least until we have to blow up an earth-targeted asteroid). And since adult neurogenesis has become a BIG topic with tons of implications in things such as exercise, antidepressants and new learning/memory, hopefully the future improvements in our lives will provide some solace in the fact we’ve nuked our own world over 2000 times.

 

References:

Humans cortex has no adult neurogenesis (2005): http://www.cell.com/cell/abstract/S0092-8674%2805%2900408-3

Humans don’t produce new adult olfactory neurons (unlike rodents) (2012): http://www.cell.com/neuron/abstract/S0896-6273%2812%2900341-8

Dynamics of hippocampal neurogenesis in humans (2013): http://www.cell.com/cell/abstract/S0092-8674%2813%2900533-3

The first proof of striatal neurogenesis (2014): http://www.cell.com/abstract/S0092-8674%2814%2900137-8

 

*Clever readers might have picked up a problem here: what about those pesky DNA repair mechanisms? Couldn’t the carbon-14 have been integrated into old neurons by those? They rebut this possibility in their method in the most recent paper (4th reference) by saying that:

A.) only some of the neurons have altered levels of carbon-14 (while all neurons should have had some DNA repair).

B.) they’ve looked for carbon-14 in many other brain regions in the past decade and found none, as you would expect if DNA repair mechanisms account for very little carbon-14 integration. This includes in the cortex of neurons after a stroke, when massive DNA damage would have taken place.

C.) they used other biochemical markers to show evidence of neuroblasts (baby neurons) as well as a lack of pigmentation that increases with aged cells (lipofuscin) in these newly born striatal cells.

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New neuroscience on why we dream.

I thought I’d write a post on a topic I love to talk about: dreams. You wouldn’t believe this dream I had last night: there was this nutria and he was riding on a surfboard made of cheetos and…wait sorry I’m getting off topic. What I really want to talk about is the neuroscience (not the usual pseudoscience) behind dreams. I study memory and a lot of work has shown the heavy importance of sleep in forming memories, but dreaming is a bit more of a mystery. Does it serve a purpose, or is it just an accidental offshoot from memory consolidation? To be honest: we really don’t know yet. But we do know some interesting pieces here and there that serve as first steps to unraveling the mystery of dreaming.

To talk about dreaming you have to start with sleep. We don’t even really know the purpose of sleep. For certain you don’t do very well without it and can even die from enough insomnia, but why sleep is so important that our brain uses approximately 1/3 of our lives doing it is a bit of a mystery. Oh, and this isn’t just true for us, as far as I know all higher animals sleep (including sharks and dolphins contrary to popular belief—they just do it half a brain at a time). A recent theory proposed that neurons need to be turned off at night for “prophylactic cellular maintenance,” which seems reasonable considering long-term sleep deprivation appears linked to higher mortality rates, and your brain IS shuttling around all sorts of charged ions all day. If you want to read more about why it’s a good idea for YOU to sleep more, check out my buddy Pascal’s pensees on sleep.

While we haven’t proven why you need to sleep, it is clear that it helps us form memories. As far as I know the first papers that linked sleep to memory were from the mid-90s out of the Weizmann Institute in Israel. Karni et al showed in 1994 that memory consolidation (the process of short term memories being stored) specifically happened during REM sleep. They did this by disrupting people as they entered REM, which led to their memories for a visual task being compromised. Many other studies have gone on to show how sleep improves memory, even when the memory tests are significantly further away in time. If you have subjects learn a finger-tapping task (e.g. press keys in the order 5-2-4-3-1 and remember to do it hours later) and then test them after 8 hours of being awake versus 8 hours awake plus 8 hours sleep, the group that slept will be both more accurate and faster at repeating the correct key order.

Now we can start talking about dreams a little bit. Radiolab had a good episode on sleep with a segment on dreams that I’m referencing some anecdotes from. Robert Stickgold started things off in 2000 by publishing the first (real) scientific study on dreaming in decades (as Wikipedia points out the last notable one from 1977 has ‘compromised factual accuracy’, which sounds about right). Stickgold personally had noticed that when he went hiking when he later fell asleep he would dream of continuously climbing up slopes. Knowing that trucking a bunch of undergraduates to whatever mountains are near Harvard and then bringing them back to test them falling asleep wasn’t feasible, he sat on the idea for a while until someone mentioned Tetris to him. Apparently when you play Tetris a bunch you see falling blocks connecting to each other in your sleep. He quantified this with some undergrads and found that a large percentage of both ‘experts’ (I would have liked to see the signs posted for that: ‘Wanted: Tetris experts’) and novices had dreams about Tetris after playing for a few hours. More anecdotally, Stickgold also described how people had more abstract dreams when they slept longer outside the lab. As opposed to the more literal Tetris dreams measured by Stickgold when people were awoken soon after falling asleep (these quick dreams when falling asleep are referred to as hypnagogic dreams), subjects returning days later would describe things like ‘[I was] thinking about a project I have for work that involves designing a garden space indoors and as I was thinking about it in my mind little Tetris pieces kept falling down into the garden spaces’. This implies that the Tetris dreams are going from being replayed quite literally in the beginning of sleep to being incorporated into abstract episodic memories associated with other aspects of life later in the night. REM sleep is also enriched the longer you’ve been sleeping, which is taken as a reason for increased dreaming right before you wake up. I, for one, have tried on many occasions to fall back asleep in the morning to reenter a sweet dream!

Also interestingly, they got a group of amnesiacs to play. While the amnesiacs didn’t remember playing the game or the experimenter and didn’t get any better at the game like normal subjects did, some of them did still report Tetris-related dreams when awoken right after falling asleep. This implies that dreaming can take place outside the hippocampus/medial temporal lobe, which is the seat of the malfunctioning brain tissue in those amnesiacs. This is a bit of a surprise, since we think of the medial temporal lobe as the initiator of the short to long-term consolidation process of memory (see step 3 in a few paragraphs to understand what ‘consolidation’ is). Plus, studies of rats ‘dreaming’ find many of those seemingly dream-related signals in the hippocampus (the best part of the medial temporal lobe. Just kidding. ALL the brain is cool! But mostly the hippocampus).

Speaking of those rat studies: Matt Wilson’s work was also featured in that Radiolab episode. Wilson discovered a process now termed ‘memory replay’ back in the early 90s. He describes in the episode how he was training a rat to run around a track and the hippocampal neurons would fire spikes in order: one cell after another cell after another cell. As a neurophysiologist you get used to the signature sound of these events as the voltage measurements are attached to a speaker. While recording from these rats he was surprised to hear the cells firing in sequence when he hadn’t put any food in the maze to motivate the rat to run. When he looked over at the rat it had dozed off on the track. The ‘replay’ is these groups of hippocampal cells firing in order while sleeping in the same way as they were when it is awake. Here’s a visualization:

Image

(from: http://neuro.bcm.edu/jilab/?m=static&id=3)

“RUN” is what 9 hippocampal neurons do when the rat is running through a maze. Notice how they fire one after another, with each vertical tick representing a single neuron firing. “SLEEP” is from when the rat is sleeping. When the same 9 neurons are recorded, they fire in the exact same order, an indication what the rat is thinking of when it was previously RUNning. If you look closely you’ll notice the replay timescale is 0.2 s. while the running timescale is 1.0 s. This means the replay is done at approximately 5x the speed of the actual event, which is believable to me since dreams often seem like they’re not in real-time, but counter to some other dream research that I’m not even sure has been published.

If you had the rat run in a different enclosure those same cells might not even be active. And if they were they almost certainly would not be firing in the same sequence. This gives us some idea of why the “dream” is taking place—the order of cell firing must be important for memory and the rat is replaying the order to store them in memory. We don’t know exactly why the rat has to replay them for the memory to hold, but future work has indicated that these sequences of cell firing also takes place in the cortex, an indication that memories are being transferred to this region for long-term storage.

This is in line with the canonical theory of how memories are consolidated, which I’ll describe briefly since it’s pretty interesting and will help explain some dream theory later:

1.) you experience the stimuli with the cortex on the outer parts of your brain (e.g. your auditory cortex first interprets Tubthumping by Chumbawumba).

2.) the stimuli are passed on to your medial temporal lobe (including the hippocampus) for contextualization. This region unites the disparate senses into episodes and also can link them to other important facets of the experience like emotion/reward/anxiety (e.g. you remember hearing Tubthumping at a super awkward but tasty middle school pizza party).

3.) the important stimuli are selected to be kept and the cortical region that originally experienced the stimuli then stores them permanently (i.e. your auditory cortex still remembers what Tubthumping sounds like, sadly, even to this day). This is called ‘consolidation’ of the memory.

Therefore, the replays might work as some kind of signal being sent from the hippocampus indicating which memory was important enough to keep, with the sequence of cellular firing possibly the code itself that represents that specific episode. There’s evidence the hippocampus then later indexes these memories so you can form associations with other memories, sort of like a really, really good Pandora Radio for your experiences that robustly finds the right memory when given a related experience as a suggestion. You know, much like Pandora Radio fails to do for music.

Anyway, in the Radiolab episode Wilson goes on to speculate that the actual physical replay of cell firing that happens when the rat is acting out the experience is a way to combine information from various memories for storage. He claims they’ve seen a rat run around one track, run around a second track and then have replays that combined the sequential firing from both tracks. Frankly, there has been no real scientific evidence of this from what I can find. I actually even emailed him once and he pointed to a Loren Frank paper that didn’t really describe this idea. So, while it’s a nice thought, we’re not really sure if these replays actually are done to help make connections between distinct experiences*. More on this later.

One thing that has confused these ideas is the discovery of more immediate replay. Rats won’t just replay events when they fall asleep, they’ll also do it right after experiencing the event when they’re standing still. Strangely, some of these replays are even in reverse, with the cells firing in the opposite order in the awake replays from when they were running on the track. So while replays are likely happening when you dream, they don’t seem exclusive to dreams themselves but are more ubiquitous in any kind of memory-related process.

A new paper from the Wilson group in 2012 took another step by actually biasing the rat’s ‘dreams’. They trained rats to go left or right in an enclosure for reward (often chocolate sprinkles—I’m told rats love chocolate sprinkles) depending on which of two sounds they heard. One sound would net them reward for going left, the other for going right. They found that while the rat was sleeping, if they played these tones they were able to get the rat to preferentially replay (or think about) running left or right in response to the left and right tones. Again, like in previous work, these replays were sequences of cells firing one after another. They were even able to estimate where the rat was running in its dream by matching up the replay to the sequences from when it was running in the enclosure. Here’s their graph showing this Inception-like dream-reading, possibly even colored to remind you of Inception:

Bias in Bayesian

(from http://www.nature.com/neuro/journal/v15/n10/fig_tab/nn.3203_F7.html …and IMDB)

I don’t want to go into details about their model, but the darker colors basically indicate that the neurons predict the rat to be on the right side of the track in this case. Again, this doesn’t tell us a ton about why events need to be replayed during dreams. But it does indicate that dreams can be influenced by external stimuli even while sleeping, which hints at your brain assigning valence to certain memories that it decides are important during sleep. Interestingly, all this ‘dream biasing’ happened during rat’s slow-wave sleep (SWS). This is a bit confusing since people usually remember dreams when awoken from REM sleep, again the reason you tend to dream right before you wake up as you get more and more REM sleep throughout the night. Apparently in humans it has been shown that biasing dreams doesn’t work during REM sleep, and even though you don’t necessarily remember dreams during SWS they’re still happening. This speaks to how ALL stages of sleep are important, and why all that crazytalk about the da Vinci sleeping pattern doesn’t make a lot of sense. But that’s really for another blog post.

Alright, so now that you’re up to speed on some recent dream research, you still probably don’t feel all that satisfied. Sure, dreams could be important for memory, but what’s the purpose of semi-consciously rehearsing only select events? And why are they so freakin’ weird? And what about all those stories of people having insights in dreams (e.g. Mendeleyev claims the layout for the periodic table came to him in a dream), isn’t that related in some way? I’ll start on the speculation train in a moment, but first one more supercool study to help answer this last question.

Jan Born’s group has a paper from 2006 titled simply: “Sleep Inspires Insight.” They had people learn a numbers game where they had to predict the next numbers in a sequence based on previous strings of numbers. What they were not told was there was a ‘hidden rule’ that once discovered would allow them to figure out the next numbers in the sequence considerably faster if they figured it out. And, as the title spoiled for you already, this rule was discovered significantly more often by people that were able to sleep on it for 8 hours versus people that did the task again after 8 hours of being awake. That is so cool—I love it when science backs up anecdotal intuition!

Now you can see where Matt Wilson was going with his idea about rats combining replays of different tracks together into single representations: he was trying to describe how these distinct memories could be combined and analyzed in an offline state while the rat was ‘dreaming’. This still doesn’t explain why the dreams have to be conscious, since a lot of our problem-solving takes place subconsciously, but it does assign them a useful enough purpose for us (and our wall-headbutting pets) to be actively rehearsing daily events during sleep.

I also think the word ‘offline’ is key in that previous paragraph. One idea is that your brain can only process so much remembered information when it’s currently engaged in inputting new information. Since, as I described before, the same bit of cortex that first experiences the memory is the place where the memory is stored long-term, there’s clearly going to be some interference screwing things up as your brain tries to pull double duty. For example, you probably have experienced how hard it is to remember how a song goes when loud music is playing. The reason is your auditory cortex is being engaged by the loud music, likely by many of the same cells that hold the memory of the previous song you’re trying to remember, and this makes pulling the song out of your head significantly more difficult than when everything is silent. It’s actually quite impressive you can do this at all—it speaks to the robustness of the cellular encoding process. But it would certainly be a lot easier for your brain to recall ‘true’ memories without distraction while nothing new is coming in–like when you’re sleeping. Further, it would be particularly useful for there to be no new interference coming in if you were trying to combine multiple memories together and form new insights. This includes stimuli like songs playing, but could also include such distractions as emotional reactions not necessarily relevant to a memory you experienced earlier.

This is in line with new work by Matt Walker (not Matt Wilson—I know it’s confusing) that postulates that REM sleep serves as ‘emotionally safe’ periods of reactivation. He found that people had reduced responses to emotionally charged photos after sleep, which also showed up as a reduction in activity in their emotional processing centers from fMRI scans. To directly quote him, “We know that during REM sleep there is a sharp decrease in levels of norepinephrine, a brain chemical associated with stress,” Walker said. “By reprocessing previous emotional experiences in this neuro-chemically safe environment…we wake up the next day, and those experiences have been softened in their emotional strength.” Could replaying such events with reduced emotions during dreams make ‘truer’, more objective memories?

Alright, over 2500 words later and maybe dreaming makes a bit more sense to you. As I said in the beginning (and harped on a few more times throughout), we still don’t really know why semi-consciously recalling daily events during sleep is useful. It’s even less clear why crazy, invented dreams occur. But the evidence at least points to some kind of process that both selects for important memories and does some problem-solving to boot while you’re not being distracted by new experiences. Further, more and more evidence seems to indicate that the brain is consistently biasing and predicting future events, so the possibility that these dreams might be some kind of exploration into the vast realms of ideas we form every day seems like a reasonable one.

*I stumbled upon this paper from David Redish’s group recently where they managed to show neuronal signatures of rats envisioning “shortcuts” on parts of a maze that they had never traversed. This is pretty good evidence that the brain is using hippocampal replays to collaborate past experiences to imagine future events, although doesn’t necessarily say that dreams have anything to do with such problem-solving “nexting”.

How your glia make mice—and maybe you (and maybe Einstein)—smarter

It would be interesting to take a poll of non-neuroscientists on whether or not they are aware of glia.  I’m guessing <5% of people know they are the other half of the ~170 billion cells in your brain (besides neurons).  I for one had never heard of them until I took my first (and only, actually) neuroscience course.  And it turns out that since Prof. Lubischer (whose splendid class helped further my interest in neuroscience) studied glia, she gave us a running list of all the jobs they performed in the brain.  It’s probably a bit outdated 5 years later, but for those interested I put all 12 of them at the end of this post.

I think the main reason hardly anyone knows about glia is that they aren’t so easy to study.  Unlike neurons, which scream to be measured with their significant and persistent electrical discharges, glia act largely in a support role—almost like little helper robots to the master neurons.  Their main functions involve regulating ions, neurotransmitter levels and therefore the electrical signals of neurons themselves at various key points (e.g. along the neuronal axon, at the synapses between neurons).  And since these little chemists work with ~attoliter amounts of product, measuring their effects is tricky.

Now, for the crazy, mad scientist stuff I hinted at in the title.  Despite their passive role relative to neurons, glia potentially can have effects on a cognitive level.  In a paper published this year in Cell Stem Cell, a group of neuroscientists led by Stephen Goldman and Maiken Nedergaard at the U. of Rochester Medical Center took human progenitor glial cells (straight from ~5 month old aborted fetuses) and grafted them into the brain of immunodeficient (I presume so the mouse brain wouldn’t attack the invading human glia) baby mice.  Humans have notably larger and, frankly, better glia than mice when it comes to their role in regulating ions and speeding up neurotransmission.  Therefore, they probably went in thinking the human glia might alter the performance of the native mouse neurons.

The left picture below shows some of these human glia (in green; the nuclei of human glia are in white) that were incorporated into my favorite part of the brain: the hippocampus.  The authors note the human cells—after 14 months in the mouse brain—are particularly enriched in the dentate gyrus region of the mouse hippocampus.  Dentate gyrus granule neurons are the strong c-shaped band of blue cells in the left figure.  These neurons are one of only two groups that can be newly born in mammalian adults and are heavily implicated in memory and emotions (I study this region in primates as it is also thought to be an essential brain region for how we separately encode new memories).  Human glia also were expressed to a lesser degree throughout the mouse cortex (the cortex is kind of like a heating helmet for the important hippocampus underneath—haha I’m just kidding. ALL of the brain is important).

Image

(from http://dx.doi.org/10.1016/j.stem.2012.12.015)

In the right picture are a few of these human glia (green) compared to the native mouse glia (red arrows)—specifically, astrocytes.  As you can see, this subclass of glia are called this because of their distinctive star-like shape.  I’ll largely refer to the human glia as human astrocytes from here on since the authors used this obvious morphology to select for glial progenitor cells that had ‘grown up’ within the mouse brain into developed astrocytes.  And when these human astrocytes did grow up, they managed to grow to the size regular astrocytes do in the human brain—much bigger than the native mouse ones (see middle graph). This confirmed previous work that had shown how human glia incorporated themselves into mouse brains, performed a usual glia task as I explained above (in this previous case—insulating ‘leaky’ axons to heal congenitally deformed mice), and maintained their typical size and morphology in mouse brains as normally seen in human brains.  Basically: the human astrocytes are like the honey badger—they don’t care what brain they’re in, they’re gonna go regulate some neurons!  Already kinda sweet, right?

Well it gets better.  A quick overview of some nitty-gritty details: the authors then went about seeing if there were any biophysical changes in the human vs. mouse astrocytes by studying slices from the postmortem chimeric mouse hippocampus (a common in vitro method).  Indeed, they found waves of calcium (an important ion that astrocytes use to regulate neuronal transmission) were 3x faster in the human glia compared to the mouse glia. They also found excitatory postsynaptic potentials (EPSPs) were stronger in the chimeric brains.  Further, long-term potentiation (LTP)—a commonly measured signal in the hippocampus that is important in learning and forming memories through the strengthening of neuronal connections—was enriched in the mice with human astrocytes.  The authors were even able to show how the human astrocytes specifically did it: by releasing a chemical called TNFα that told the neurons to make more excitatory receptors (the place where neurotransmitters have their effect—more receptors equals easier excitation, hence the boost in LTP).  The human astrocytes essentially were able to improve the ability of the mouse brain to transmit signals.

So, you can probably guess what’s next: test these super-brained mice on some typical mousey tasks and see if their more potent brains lead to cognitive enhancements.  And amazingly: they did!  Chimeric mice showed better memory for a context they had previously been shocked in vs. a similar one where they had not: indicative of a learned, hippocampal memory.  In another test of hippocampally-dependent learning, the chimeric mice achieved greater success in the Barnes maze (where the mice must remember the location of a small, dark escape hole–mice hate open, well-lighted places.  And Hemingway.).  Finally, a third test of hippocampal learning showed the chimeric mice were better able to recognize a familiar object in a novel location.  These three tasks might not sound that exciting to prove your supermouse’s worth, but they’re standard tests that depend on the hippocampus.  Mice with lesioned hippocampi perform worse on such tasks.  Interestingly, these tests are similar to those used to screen for antidepressants (that often then work when given to humans—we’re not so concerned about mouse depression) as the hippocampus is also tied into emotional centers of the brain.

Crazy/sexy/cool right?  Okay maybe just 1&3.  But what does this mean for you, science-interested human that made it this far?  For one thing, we can no longer just think of glia as passive, boring helpers.  They’re more like strong lobbyists that may be essential for our cognitive function!  And the fact that all it took to enhance the learning and memory of mice was the strategic implementation of one chemical (TNFα), we can now start to target both this cytokine and glial functionality in disorders of cognitive processes.  Even better, Stephen Goldman’s lab has been able to induce pluripotent human stem cells from skin cells.  This not only eliminates the need for fetal stem cells, but also allows for stem cells already tailored for a specific person to be created (using foreign stem cells could cause an immune response; hence the use of immunodeficient mice in this study).  His lab is reportedly already using this system to study mouse models of schizophrenia and Huntington’s, and I’d bet you a greenback that Alzheimer’s won’t be far behind.  Depression seems like an awesome candidate for glial therapy as well.  Practically no new class of antidepressants has been made for 50 years—most work has concentrated on the same few monoamines in the same neuronal pathway.  But it is possible that glia could be used to modulate any number of factors, and do so with the attoscale specificity that popping in a pill of Prozac lacks.

Finally, as a fun aside, this isn’t the first time glia have been implicated in improving cognitive function.  Specifically, Marian Diamond’s lab analyzed tissue from Albert Einstein’s brain and found he had an enhanced number of glia compared to an average person.  This study was done a while ago and is under some debate (and is possibly not the only abnormality in Einstein’s brain), but it makes for a fun story.  Plus, when research started indicating glia could send long-distance chemical signals to each other, their potential role in cognitive functions was no longer that crazy.  I, for one, welcome our new glia overlords.  And can’t wait to hear about more glial therapies.

List of glial functions:

Glia can…

…regulate the extracellular milieu (e.g. potassium buffering).

…influence axonal propagation through myelin.

…direct localization of membrane proteins.

…uptake neurotransmitters at synapses.

…express neurotransmitter receptors and directly modulate synaptic transmission.

…synthesize neurosteroids.

…provide guidance for migrating neuroblasts (specifically radial glia).

…can provide chemical clues for axonal pathfinding.

…can modulate synaptogenesis.

…make trophic factors for neurons.

…mediate some forms of synaptic plasticity.

…influence the neuronal response to injury and disease.