1. A group of scientists reduce neurogenesis and report a memory deficit.
2. A second group repeats the experiment, with only a few minor differences in protocol, and fails to find a memory deficit.
3. A third group, using the same species as the first group but a protocol more similar to the second group, replicates the original finding but only when the experiment is performed on Wednesdays.
4. Faith is restored.
5. Five groups report no such neurogenesis-dependent memory deficit.
6. It is reported that developmental exposure to strontium reduces adult neurogenesis by 40% AND produces the much sought after memory deficit. In a technical tour de force follow-up experiment, artisanal cheeses restore neurogenesis and reverse the memory deficits. Causation is established.
7. BDNF.
8. Everyone proclaims the role of neurogenesis in memory and is totally confused at the same time.
9. Someone systematically examines all of the variables in the memory test to determine whether or not the whole thing is a hoax and they should just change careers**.
10. We have never gotten this far.

Even at level 8, the neurogenesis-fear conditioning story was one of the more convincing arguments of new neuron functionality. With this study by Drew et al. we may soon be jumping for joy as we appear to be graduating to level 9.

The contribution of adult neurogenesis to contextual fear conditioning was greatest when mice were only given a brief training experience – mice lacking adult neurogenesis showed reduced fear of a context where they previously received a single footshock during a brief (3 min) exploration session. With longer exposures to the context, or additional footshocks, neurogenesis-deficient mice showed normal memory. This finding could be explained by the fact that young neurons have a lower threshold for synaptic plasticity, allowing them to encode fleeting experiences that would be forgotten if left to mature neurons.

So, brief training protocols may now likely be my first choice, at least when using mice. In fact, the only times I have observed contextual fear memory deficits in mice has been after brief training protocols almost identical to those used by Drew et al. So we just might have taken a big step forward. If not, check back in 5 years for my revised “How progress is made” list.

*or any other field for that matter

**this is not entirely a joke because, in this case, it both 1) appears to not be a hoax, and 2) marks the launch of the next phase of Michael Drew’s career (congrats)

Reference
Drew MR, Denny CA, & Hen R (2010). Arrest of adult hippocampal neurogenesis in mice impairs single- but not multiple-trial contextual fear conditioning. Behavioral neuroscience, 124 (4), 446-54 PMID: 20695644

The main experiment is illustrated on the left. Groups of rats were either exposed to 4 different contexts (A,B,C,D) or a single context (D) over the course of several months (TRAINING EXPOSURE). Then rats were either exposed to all 4 contexts or the single context over the course of half an hour (TEST) and expression of the immediate-early gene, Arc, was used to identify “activated” neurons. The idea is that, if subsets of granule neurons encode memories at different times in an animal’s life, then recalling those distant memories at test may re-activate those granule neurons. Alme et al. provide two hypotheses that their experiment will test and I illustrate them below with black-eyed peas.

1) The selective tuning hypothesis.

According to the selective tuning hypothesis, different populations of newborn granule neurons (i.e. those in their critical period) encode the contexts explored at each point in an animal’s life. As these cells mature they become less active and no longer encode new information, causing subsequent experiences to be encoded in newly-added populations of granule neurons (top half of above figure; red cells for A, blue cells for B, green cells for C*). However, even when old and unexcitable, granule neurons that were originally involved in encoding an experience (back when they were immature), are reactivated during recall of that experience. In other words, the neurons are selectively tuned to memories for events that happened at a specific point in time. Thus, during the test phase, when group #1 rats are exposed to contexts A, B, C, and D, a relatively large proportion of granule neurons will be activated.

In contrast, group #3 (bottom half) will also experience all 4 contexts during the test but would be expected to have fewer activated neurons because the contexts are novel and will therefore all be encoded, for the first time, in the same cohort of granule neurons (those that are in their critical period at the time of testing – shown as orange cells).

2) The retirement hypothesis.

Under the retirement hypothesis, again, only immature neurons are involved in memory encoding. However, unlike the selective tuning hypothesis, as neurons mature they become unexcitable to the point that they are never reactivated, even when recalling the memories that were formed during their critical period (top half of figure). So, during the testing phase when memories for A, B, C, and D are recalled, it is only the currently-immature population of neurons that is activated (the orange cells) – a much smaller population of granule neurons is activated compared to the selective tuning hypothesis. Additionally, one would expect that testing in A, B, C, D would activate the same number of neurons regardless of whether or not a rat had previously experienced the contexts (compare top and bottom halves of figure) because, at the time of test, neurons that may have previously been involved in encoding these contexts are no longer functional and it is only the currently-immature population of neurons that is activated.

What did they find?

The data generally aligned with the predictions of the retirement hypothesis: the same number of cells were activated regardless of whether rats experienced ABCD for the first time (group #3) or were re-exploring familiar contexts (group #1). So, it would appear that recalling distant memories does not reactivate additional subsets of granule neurons that would have been involved in the original encoding of those experiences. So, the selective tuning hypothesis is out.

Exploring four contexts at test activated twice as many neurons as exploration of only a single context. So, different experiences are capable of activating different populations of granule neurons, but to a much smaller extent than in other regions of the hippocampus (CA1, CA3). Alme et al. do a bunch of math to show that the probability that a granule neuron is activated in multiple contexts is about 40 times more than would be expected by chance, if random granule neurons were activated during different experiences.

What does this mean for my dentate gyrus?

Does this mean that these silent granule neurons were once active, but have succumbed to old age? Perhaps, but it hinges on one assumption that is not yet settled – that young granule neurons are preferentially involved in storing/processing information. Since no one has ever directly compared activation of young, adult-born neurons with activation of mature, perinatal-born neurons (with a birthdating marker such as BrdU), it remains possible that many of the activated cells in this study are perinatal-born, mature granule neurons (which Alme et al. acknowledge).

Here are some of the studies, and their limitations, that address the issue of whether young, adult-born neurons are more “activatable” than mature neurons:

1. Many electrophysiological studies have shown that immature neurons have enhanced plasticity and excitability. But does this mean they’re more likely to be active during behavior? The young neurons that are more likely to undergo LTP also have fewer, maybe weaker, synapses than mature neurons. So, maybe they’re even harder to activate. I don’t know.
2. Tashiro 2007 nicely demonstrated that environmental enrichment increased neurogenesis and the total number of young activated neurons. However, the proportion of young neurons that were activated was not different from the general population.
3. Studies that compare activation of BrdU+ cells to activation of the general population (e.g. cells stained for DAPI or NeuN) could introduce sampling biases due to the different methods used to quantify immature neurons and other/mature neurons. For example, Kee 2007 found preferential activation of BrdU+ adult-born neurons relative to NeuN+ cells but newer work from the same group, comparing CldU+ perinatal-born cells with IdU+ adult-born cells found no differences.
4. A similar sampling bias could explain the enhanced activation of young BrdU+ cells relative to the general population in the study by Ramirez-Amaya 2006. Then again, Ramirez-Amaya examined rats and my own (indirect) data from rats also suggests adult-born neurons may indeed be more “activatable”.

In short, the verdict is still out on what would seem like a simple question to answer – does behavioral stimulation preferentially activate young neurons relative to mature neurons? A definitive answer to this question will shed a lot of light on the function of adult neurogenesis and the dentate gyrus. In either case, thanks to Alme et al. for being the first to address the potential role granule neurons might play in encoding time, even if the only definitive conclusion is that most granule neurons appear to be doing absolutely nothing. Clearly there is a long way to go before we understand exactly what the dentate gyrus is doing.

*I only had so many beans and so many colored markers, so I apologize for not illustrating context D, but I think you get the idea.

Reference

Alme, C., Buzzetti, R., Marrone, D., Leutgeb, J., Chawla, M., Schaner, M., Bohanick, J., Khoboko, T., Leutgeb, S., Moser, E., Moser, M., McNaughton, B., & Barnes, C. (2010). Hippocampal granule cells opt for early retirement Hippocampus DOI: 10.1002/hipo.20810

With a 10x objective I could capture nearly the entire bulb (saggital section) in a single field. You can see newborn BrdU+ cells (green) scattered throughout, most co-labeled with doublecortin (red). In the bottom left area you can see about a dozen glomeruli – groups of neurons that represent different odors, located just one synapse upstream of the nasal epithelium. Whereas the majority of adult-born olfactory neurons are inhibitory interneurons, a smaller number of new neurons surrounding the glomeruli (periglomerular neurons) are dopaminergic. (click on the images for full sized versions – 2048 x 2048 pixels)

Zooming in with a 20x objective:

And then with a 60x objective. I apologize this photo could have been better but I can’t spend all day on this stuff.

If I had a confocal microscope at home I’d never stop.

Here’s what I came up with:

1) Unlike new discoveries, older discoveries have been validated and are perhaps even being expanded upon. While they’re not the latest & greatest findings, they are new fields. In fact, you could argue that, having been validated, an emerging field is actually more exciting since it reflects a definite advance in scientific knowledge (as opposed to an exciting new study that may or may not be replicated and is, at best, only potential).

2) As scientific disciplines become ever-more focused and specialized there becomes more and more background needed to understand them. For example, this issue of Journal of Neuroscience had two new articles on synaptic tagging. Neat! Maybe I’ll blog about them! But wait – the theory of synaptic tagging as a cellular basis memory is fascinating in its own right. So what’s more valuable – writing about the latest details or explaining the basics of the theory itself?

3) Say there already are a lot of great reviews on synaptic tagging out there. Well, it doesn’t matter because they’re all paywalled. I never really appreciated this problem until I began blogging and kept finding myself looking for decent references that my readers could actually access, often settling for Pubmed abstracts or Wikipedia entries.

4) Lastly, just because something happened in the past doesn’t mean it can’t be news. A fun example if this is when an old piece of news sneaks its way into someone’s twitterstream and they feel obliged to follow it up with an apology. Old news gets the shaft.

*sorry I really could NOT use twitterverse and blogosphere in the same sentence

It’s fun to zoom out and get the big picture sometimes. This is one such picture I took long ago when I wanted to see if staining for zinc transporter 3 effectively labels the mossy fiber axons of the dentate gyrus. You can see by the perfect overlap with calbindin that it does the job, though the staining wasn’t quite as bright and obvious as calbindin. The abundance of zinc in mossy fiber axons is one of the peculiarities of the DG and it underlies numerous synaptic properties of DG neurons.

I think the goal was to build on previous work by Lipp, Ramirez-Amaya, and Routtenberg showing that spatial learning causes “sprouting” of mossy fibers, though when I found out that this phenomenon does not occur in mice the project was aborted.

But what else can you see in this picture?

• clear differential expression of calbindin: DG (lots) > CA1 > CA3 (none), and a scattering of strongly-positive interneurons (e.g. 5 cells where CA3 and CA1 meet)
  • in CA1 you can see calbindin is expressed only in the lower band of cells (see hi res photo if needed; there is a ref for this, somewhere)
• a thin band of calbindin-positive fibers crossing the corpus callosum (CC)
• A small group of cells that are not contacted by the calbindin-positive mossy fiber axons (i.e. beyond CA3) yet do not express somatic calbindin (as seen in CA1). I’m guessing this may be mysterious and ambiguous field CA2.

A fundamental property of the hippocampus is its ability to rapidly encode memories while simultaneously keeping them distinct. Recording from hippocampal neurons one can clearly see that different populations of neurons are active as a rat explores two environments. This is thought to be one mechanism by which information is kept distinct in the brain.

For the last 15-20 years it has been thought that the dentate gyrus (DG), a major subfield of the hippocampus, serves to take small changes in incoming sensory information and orthogonalize them (i.e. make them more different). This idea was built in part on the fact that there are many more DG neurons than upstream cortical neurons. Thus, the DG could use completely different populations of neurons to represent different sets of incoming information and then pass on these representations to CA3, which may bind them into coherent events/memories (the interconnectedness of CA3 neurons, via “recurrent collatorals”, is thought to be a mechanism by which the different components of a memory are bound together).

However, a “problem” arose when Leutgeb et al. found that it is always the same population of dentate granule neurons (~1% of the total population) that are active as an animal explores different environments, even very different ones. This was a bit of a surprise. Still consistent with the proposed role of the DG in orthogonalizing information, however, was the fact that the DG neurons fired (i.e. generated action potentials, which transmit information from neuron to neuron) at different rates/frequencies in the different environments. Thus, changes in sensory information were represented by changes in patterns of activity within the same population of cells, not by recruiting different populations of cells. This is but one study – the question of how the DG encodes and extracts information is far from settled (e.g. what are the other 99% of granule neurons doing? Surely there is a situation in which they are active, no?). But the findings were robust and raise many questions, namely: How does the same population of DG neurons activate different populations of downstream CA3 neurons, during different experiences?

Until now I had been in denial, fixated on trying to understand what types of behavioral experiences might activate different populations of dentate gyrus neurons. But maybe now it’s time to face the data.

The consensus, both in vitro (e.g. here and here) and in vivo (here), seems to be that if DG neurons are sufficiently active they can reliably activate CA3 neurons. Can a single population of DG neurons account for the amount of CA3 activity seen in the behaving animal? Well, 1% activation of the total DG population (1 million neurons) is 10 000 DG neurons. Each DG neuron contacts about 10 CA3 neurons. So if all active DG neurons activated all their downstream targets, then you’d expect about 100 000 active CA3 neurons – a third of the population. Indeed, about 20% of CA3 neurons are active when a rat explores a novel environment. So it’s possible. But it’s probably unlikely.

One reason it’s unlikely is that it doesn’t explain how different populations of CA3 neurons are activated by different experiences if it is the same population of DG neurons that are always driving them. In other words, since DG neurons are relatively hard-wired to CA3 neurons, how could a given DG neuron activate a CA3 neuron under some conditions and not others? One answer is that maybe it doesn’t – quite a while ago, McNaughton et al. showed that, even when the DG is lesioned, CA3 neurons are still able to selectively encode spatial locations as a rat traverses the environment, probably due to direct inputs from the cortex. And so perhaps the primary function of the DG is not to selectively activate different CA3 populations. However, the DG could certainly shape activity within CA3 or insert unique information into the CA3 network. How?

One possible mechanism, which may be dead obvious to electrophysiologists, is frequency itself. Leutgeb et al. found that frequency of activity is how DG neurons encode information and so frequency of activity may also be the way DG neurons transmit information to CA3 during different experiences.

It has been known for some time now that the output of DG neurons, the mossy fiber axons, show extraordinary frequency-dependent synaptic facilitation. Basically, as a DG neuron fires more action potentials over shorter periods of time, the amount of neurotransmitter it releases onto CA3 neurons increases (thereby increasing the likelihood a CA3 neuron will in turn fire action potentials and be recruited to participate in memory encoding). This means that at low firing rates, a DG neuron will activate some CA3 neurons and, at higher firing rates, it will recruit different or at least additional CA3 neurons.

Wouldn’t this cause a problem where, as DG firing rates increase, it is not different populations of CA3 neurons that become activated, but more populations? Well, it is known that some DG neurons increase their activity, and others decrease their activity, as an animal has different experiences, so the net activity in CA3 could remain constant, while still activating different CA3 populations. However, the DG-CA3 circuitry is certainly complicated enough to allow for other mechanisms. For example, while the dentate gyrus projects to CA3, and it is connections between these hippocampal regions that are thought to encode memories, DG neurons actually contact more inhibitory interneurons than CA3 neurons. Furthermore, there is a wide variety of synaptic connections between DG neurons and interneurons and these connections can be made weaker or stronger in a state- and frequency-dependent manner. Suffice it to say, by firing at different frequencies, it is plausible that a given DG neuron could activate different populations of interneurons, which in turn could inhibit different populations of downstream CA3 neurons, making them less likely to participate in memory encoding.

This ties in loosely to a peculiarity of the dentate gyrus that, until now, has just been a source of pretty histological images (to me) – the variability of calbindin expression in dentate gyrus neurons. Calbindin is a protein that binds calcium, it acts as a buffer, and gives DG neurons their property of facilitation (briefly: A single action potential in a DG neuron will travel down the axon and trigger the opening of calcium channels in the synaptic terminal at a CA3 neuron. Calcium is necessary for neurotransmitter release and subsequent activation of the CA3 neuron. Calbindin will bind this small amount of calcium, thereby preventing neurotransmitter release and CA3 activation. However, as the number and frequency of action potentials increases, calbindin will fail to effectively “mop up” the extra calcium and neurotransmission will proceed.). If you look at the picture at the top of this post, you can see that the amount of calbindin varies greatly in DG neurons. Immature DG neurons, identified by PSA-NCAM expression, are devoid of calbindin (arrows point to clear examples) and even when they are quite mature (10w of age) 40% will still be devoid of calbindin (see my data in this montage). Lastly, calbindin expression can be modified by experience. So the variable and modifiable expression of calbindin might be yet another mechanism by which DG neurons are capable of shaping activity in CA3 neurons. Indeed, at least one study, from Robert Sapolsky’s lab, has shown that genetically altering calbindin expression in the dentate gyrus dramatically influences DG-CA3 physiology and impairs memory.

Thanks to A.P. for posing the question.

Reference

Leutgeb JK, Leutgeb S, Moser MB, & Moser EI (2007). Pattern separation in the dentate gyrus and CA3 of the hippocampus. Science, 315 (5814), 961-6 PMID: 17303747

Neurons are not born with dendrites and spines – they are acquired during a developmental process that takes many weeks (see here & here). During early development, the pattern of formation of dendrites and spines are sculpted by experience, as might be expected if dendrites and spines are anatomical structures involved in processing and storing sensory information. While a body of work has emerged suggesting adult-born neurons are involved in memory and behavior, no one has yet investigated whether experience is capable of altering the dendritic development of these new neurons. This paper by Tronel et al. is therefore very important because it is the first to look at this phenomenon. They show a dramatic acceleration of dendritic development in response to learning, suggesting a potentially powerful role for new neurons in storing and processing information.

It has been 10+ years since Gould et al. and Kempermann et al. showed that learning and enriched environments can enhance the survival of new neurons. These findings are logical precursors to the current study since, if these new neurons have all the necessary components,  they suggest experience could add to the mnemonic functions of the hippocampus. But subsequent studies indicated that experience could also decrease the survival of new neurons. So perhaps structural changes to new neurons that are more relevant to learning might be worth investigating. For example, in many of my own experiments, I have failed to observe learning-induced changes in the number of new neurons but, if the number of dendrites or spines is increased, then there could still be an enhanced ability to process information. Or there could be the removal of some spines and the formation of others, suggesting a transformation in the type of information processed by new neurons. To get at these possibilities, Tronel et al. used doublecortin (DCX) staining and retroviral-GFP labeling to visualize the dendritic structure of newborn neurons in rats that had either remained in their cage (non-learners) or had learned a spatial memory task, the Morris water maze.

Since the authors had previously shown that water maze learning enhances the survival of 1-week-old cells, they first examined whether water maze learning would also alter the dendritic structure of this same population of neurons. Training rats for 6 days and examining new BrdU+/DCX+ neurons the following day (i.e. when new neurons were 14-days-old) they found that the dendritic length and the number of dendritic branches was doubled compared to rats that sat in their home cage.

More remarkable is the duration that the increased dendritic complexity persisted. To get at this question a GFP retrovirus was used to label new neurons born 1 week before learning, since DCX is eventually downregulated and cannot be used to examine dendritic morphology in neurons more than ~2 weeks old.  They found that even 3 months after learning, maze-trained rats had longer dendrites, more branch points, and more dendritic ends. The differences were not trivial either – maze-trained rats had ~70% increases for all of these measures. The number of spines (and therefore putative synapses) was also elevated, 3-fold, and the proportion of spines that showed a mature, mushroom-shaped morphology was 6-fold greater than naive, untrained rats. Since the dendritic morphology of developmentally-born hippocampal neurons can be altered by learning, physiological changes in hormones, and exercise, it is also worth noting that in this study learning did not affect the dendritic complexity of mature granule neurons (though spines were not analyzed in mature neurons and it is possible that learning caused retraction and formation of spines in mature neurons with no overall effect in spine numbers or morphology), suggesting adult-born neurons are particularly sensitive to learning-related activity.

They go on to show that these structural changes in adult-born neurons are even more pronounced when rats learn a more challenging version of the water maze task, where the spatial location of the escape platform moves on a daily basis. They also show these effects require NMDA receptors, which are required for many forms of hippocampal-dependent memory. These additional experiments are notable but it is the basic finding – the magnitude and duration of the structural changes – that is most interesting to me. Here are some of the reasons why:

• previous studies have suggested that adult-born neurons reach a plateau in their functional development by ~8+ weeks of age. These data suggest that new neurons still have a long way to go before they become fully mature.
• the 8w developmental plateau in earlier studies could be normal for animals that have not had any significant life experience (what does this mean when the majority of scientific studies of the brain use naive, deprived animals as models?)
• when experience accelerates the dendritic development of new neurons, are those neurons now less plastic and less likely to contribute to future behaviors? In trying to understand why some studies report behavior deficits after neurogenesis ablation whereas others do not, I’m imagining that 6 weeks of neurogenesis ablation could have major effects on behavior if older (>6w) adult-born neurons are less plastic, perhaps because experience (experimenter handling, group housing, previous learning) accelerated maturation in the way Tronel et al. report. In contrast, if animals have been deprived of learning experiences, 6 weeks of neurogenesis ablation might not have any effects on behavior, because older neurons are still relatively immature and able to compensate.
• depending on how you look at it, it is valid to wonder how a relatively small population of new neurons can be important for behavior. If you now consider the fact that 3-month-old cells still have significant amounts of untapped storage capacity, the cumulative numbers of new neurons generated over 3 months no longer seems so small and insignificant

Reference

Tronel S, Fabre A, Charrier V, Oliet SH, Gage FH, & Abrous DN (2010). Spatial learning sculpts the dendritic arbor of adult-born hippocampal neurons. Proceedings of the National Academy of Sciences of the United States of America, 107 (17), 7963-8 PMID: 20375283

One positive thing that came out of looking at these very immature neurons was that I got the chance to see several examples of pyknotic (dying) cells. Older, adult-born neurons also die, particularly after an experience (see here and here), but it’s infrequent and hard to visualize. However, a relatively large proportion of new neurons die within a few days of their birth making them easier to find – the cluster of cells shown below is an example that caught my attention.

You can clearly see two BrdU-labeled cells (in green; marked with arrowheads) that also express doublecortin (DCX; red). The blue stain, Hoechst, stains DNA allowing for the visualization of all cell nuclei. Collectively, these 3 stains tell us that the cells are 1-day-old (because BrdU was injected 1 day before brains were collected), that they’re neurons (because they express the immature marker DCX) and that they’re dying (because BrdU and Hoechst both label DNA and show that the DNA is condensed in a ball, as is typically seen when cells undergo pyknosis). The arrow points to a lucky, neighboring neuron that is not dying.

Why were these two cells born if they’re only going to die 24 hours later?

I can understand the speculation that neural activity influences the survival of more mature neurons in a “use it or lose it” manner – essentially, if a memory is stored in a young neuron there must be a mechanism to ensure that the neuron, and therefore the memory, survives. But is it possible that a similar mechanism also influences the survival of very immature neurons? It’s hard to imagine, since very young neurons do not have synapses and cannot participate in memory processing/storage. Consistent with this idea, Tashiro has shown that NMDA receptors (a synaptic ingredient essential for many forms of memory) regulate the survival of 2-3 week-old neurons, which are just beginning to form synapses, but not younger neurons that have not yet formed synapses. However, the possibility remains that learning could do something to these 1-day-old neurons – e.g. epigenetically imprint them – so that they have some sort of cellular memory that causes them to subsequently participate in certain behaviors but not others. Since information is typically thought to be stored at synapses, I can’t imagine that these memories could be terribly specific but they could bias a young neuron to be more involved in a general class of behavior (e.g. spatial memory vs. stress) that is associated with certain broad differences in activity (e.g. firing patterns, neuromodulators, hormones). It would be really cool if someone shows this.

Two recent papers have attracted a lot of media attention because they draw direct links between adult neurogenesis and behavioral disorders: Noonan et al. showed that rats lacking adult neurogenesis (stopped with irradiation) are more susceptible to cocaine addiction. Jin et al. showed that mice lacking adult neurogenesis (using a transgenic model) suffer greater infarct size and have more severe motor deficits after stroke.

While the papers themselves have important implications, what caught my attention was the angle taken by press releases: both articles studied the effects of reducing neurogenesis but the media focused on potential benefits of increasing neurogenesis. See speculation that antidepressants, by increasing neurogenesis, might be stroke-protective here. And, from Science Daily:

While the research specifically focused on what happens when neurogenesis is blocked, the scientists said the results suggest that increasing adult neurogenesis might be a potential way to combat drug addiction and relapse.

It may very well be the case that increasing neurogenesis is good in the same way decreasing neurogenesis is bad but it shouldn’t be assumed – maybe we have all the neurogenesis we need and, while completely arresting neurogenesis could be harmful, increasing neurogenesis beyond normal levels is just redundant.

Or, maybe the key is where you’re increasing or decreasing neurogenesis from:

In this model, assuming most of us have normal levels of neurogenesis, further increases will provide no benefit to behavioral performance, whether we’re talking resistance to addiction or recovery from stroke or anything else. However, decreases in the number of young neurons below a critical level would impair storing/processing of information, protection against stroke etc.

This speculation is under the assumption that we all have “normal” or sufficiently high levels of constitutive neurogenesis. However, in the case of addiction, covariables like stress, poor nutrition and narcotics themselves might all serve to reduce neurogenesis below healthy levels (see “unhealthy levels” in figure). In this case, increasing neurogenesis would cause dramatic improvements in behavior and is consistent with the authors’ speculation. For similar reasons, increasing neurogenesis might provide cognitive benefits to people in other situations where neurogenesis is known to be compromised: the aged, those experiencing chronic stress, patients undergoing cranial irradiation or chemotherapy.

It may be surprising that this idea is actually very hard to test, even in the laboratory. While many tools exist for reducing neurogenesis to unhealthy levels (irradiation, antimitotic drugs, genetics) there are no tools for selectively increasing neurogenesis beyond normal/healthy levels. Yet.

References

Noonan MA, Bulin SE, Fuller DC, & Eisch AJ (2010). Reduction of adult hippocampal neurogenesis confers vulnerability in an animal model of cocaine addiction. The Journal of neuroscience : the official journal of the Society for Neuroscience, 30 (1), 304-15 PMID: 20053911

Jin K, Wang X, Xie L, Mao XO, & Greenberg DA (2010). Transgenic ablation of doublecortin-expressing cells suppresses adult neurogenesis and worsens stroke outcome in mice. Proceedings of the National Academy of Sciences of the United States of America PMID: 20385829

I’ve been interested in new neuron function since 1999 and so I’m actually quite surprised I missed this study until so recently. In 1999 the neurogenesis literature was so scant that it was easy to know ALL of the studies, even the early Altman, Kaplan and Nottebohm studies from the 1960s through 1980s. Even studies that were not interesting were interesting, because there was nothing else to read! So, had I known about it back then, I would have been pretty interested in this study by Okano et al. if only for its focus on cell cycle markers. But I really would have been interested in it because it has a small functional experiment that was way ahead of it’s time:

(Figure Legend) E, Thymidine-labeled/Fos-negative cells detected in the subgranular region 3 d after receiving ³H-Thy and 3 hr after pentylenetetrazolinduced seizure activity. Note the presence of many Fos-positive cells in the adjacent granule cell layer. F, Thymidine-labeled/Fos-positive cells detected in the granule cell layer 4 weeks after receiving ³H-Thy and 3 hr after pentylenetetrazol-induced seizure activity. g, granule cell layer.

(Results) To determine if the newly differentiated neurons were functional, we examined the expression of Fos-IR in response to pentylenetetrazole-induced seizure activity. In the absence of induced seizures, very few (< 1%) ³H-Thy-labeled cells in the dentate gyrus were immunoreactive for Fos-IR at any of the six time points examined. However, within 3 hr following seizure activity, an induction of Fos-IR within 21 .O% (at 1 week post-thymidine injection) and 81.3% (at 4 weeks post-thymidine injection) of the ³H-Thy-labeled cells detected in the granule cell layer was observed (Fig. 3E,F), suggesting that these cells had formed functional connections.

Fos is one of a number of immediate-early genes (IEGs) that are expressed following synaptic activity. IEGs allow short-term changes in synaptic function to turn into long-term changes (which is thought to be required for short-term memory to transform into long-term memory). IEGs can therefore be used to identify neurons that are contributing to memory formation. Okano et al. noted that < 1% of new cells expressed Fos when rats were not stimulated overtly. It could have been that the rats’ experience prior to death was not memorable or it could have reflected the fact that only a fraction of hippocampal neurons are activated by normal experiences. To get around this they activated all neurons that were possibly “activateable”, by using a convulsant. Therefore, all neurons that had synapses expressed Fos and a timecourse of neuronal maturation, one that fits nicely into the subsequent literature, was obtained. When I say subsequent literature I’m referring to examples like the next study which used IEGs to characterize new neuron maturation, 10 years later. And also the many electrophysiological studies that emerged beginning 10-15 years later. It’s funny that none of them referred to this study. Had I known about it I certainly would have cited it as potential evidence that new neurons in rats mature faster than in mice (21% of 7-day-old rat neurons expressed Fos – higher than I’ve observed here but consistent with a recent rat electrophysiology study?)

Now, this is a small experiment but how did it go unnoticed when so many people are curious about the function of adult neurogenesis? Well, the study does focus mainly on the expression of cell cycle markers and less on neuronal function – most of the 102 subsequent papers that cite it are cell cycle studies. But, a number of familiar papers do cite it – papers I thought I’d read thoroughly back when there was nothing else to read on the subject, so it’s just proof you can never totally be on top of things…hence the often-used “To the best of our knowledge, this is the first example of….”

Oh, and this is not the first example of functional neurogenesis. That title goes to Paton & Nottebohm who, to the best of my knowledge, demonstrated it for the first time in songbirds.

Reference:
Okano HJ, Pfaff DW, & Gibbs RB (1993). RB and Cdc2 expression in brain: correlations with 3H-thymidine incorporation and neurogenesis. The Journal of neuroscience : the official journal of the Society for Neuroscience, 13 (7), 2930-8 PMID: 8331381