Learning and adult neurogenesis: Survival with or without proliferation?

Neurobiology of Learning and Memory 81 (2004) 1–11 www.elsevier.com/locate/ynlme

Learning and adult neurogenesis: Survival with or without proliferation? Jos Prickaerts,a,* Guido Koopmans,b Arjan Blokland,c and Arjan Scheepensb,d a

CNS-Affective Spectrum Disorders, Johnson & Johnson Pharmaceutical Research and Development, Turnhoutseweg 30, B-2340 Beerse, Belgium b Department of Psychiatry and Neuropsychology, Brain and Behavior Institute, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands c Department of Psychology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands d Department of Pediatrics, GROW Institute, Maastricht University Hospital, P.O. Box 616, 6200 MD Maastricht, The Netherlands Received 24 October 2002; revised 11 September 2003; accepted 11 September 2003

Abstract Recent high quality papers have renewed interest in the phenomenon of neurogenesis within the adult mammalian brain. Many studies now show that neurogenesis can be modulated by environmental factors including physical activity, stress, and learning. These findings have considerable implications for neuroscience in general, including the study of learning and memory, neural network plasticity, aging, neurodegeneration, and the recovery from brain injury. Although new light has been shed on this field, many contradictory findings have been reported. Here we propose two principle issues which underlie these inconsistencies, with particular focus on the interaction between learning and neurogenesis. The first issue relates to the basic methodology of measuring the generation of new brain cells, i.e., proliferation, as compared to survival of the newly made cells. Mostly, measures of neurogenesis reported are a combination of proliferation and survival, making it impossible to distinguish between these separate processes. The second aspect is in regards to the role of environmental factors which can affect both proliferation and survival independently. Especially the interaction between stress and learning is of importance since these might counteract each other in some circumstances. Reviewing the literature while taking these issues into account indicates that, in contrast to some findings, cell proliferation in the dentate gyrus of the hippocampus as a result of learning cannot be ruled out yet. On the other hand, increased survival of granule cells in the dentate gyrus as a result of hippocampal-dependent learning has been clearly demonstrated. Moreover, this learning-induced survival of granule cells, which were born before the actual learning experience, might provide a molecular mechanism for the Ôuse it or lose itÕ principle. Ó 2003 Elsevier Inc. All rights reserved. Keywords: Learning; Memory; Stress; Neurogenesis; Proliferation; Survival; Hippocampus

1. Introduction 1.1. Neurogenesis The generation of new neurons within the postnatal rat brain was first described in 1901 (Hamilton, 1901), a report which includes hand drawn plates of what we now call the subventricular zone. This was later discovered to occur also within the adult brain by Altman and Das (1965) who called this neurogenesis. However,

* Corresponding author. Fax: +32-14-603-753. E-mail address: [email protected] (J. Prickaerts).

1074-7427/$ - see front matter Ó 2003 Elsevier Inc. All rights reserved. doi:10.1016/j.nlm.2003.09.001

only recently has neurogenesis become accepted as a general phenomenon in the brains of birds (e.g., Barnea & Nottebohm, 1994), rodents (e.g., Gould, Beylin, Tanapat, Reeves, & Shors, 1999a; Kempermann, Kuhn, & Gage, 1997b; Van Praag, Christie, Sejnowski, & Gage, 1999a; Van Praag, Kempermann, & Gage, 1999b), monkeys (e.g., Gould, Tanapat, McEwen, Flugge, & Fuchs, 1998), and humans (Eriksson et al., 1998). Two principal regions within the adult brain have been identified where progenitor cells are able to give rise to new neurons in adulthood namely; the subgranular zone of the dentate gyrus within the hippocampal formation and the subventricular zone lining the walls of the lateral ventricles within the forebrain.

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Under ÔnormalÕ environmental conditions it is estimated that at least 50% of the newly generated cells within the hippocampus or subventricular zone die within 1–2 months after birth (Cameron, Woolley, McEwen, & Gould, 1993; Gould et al., 1999a; Kempermann & Gage, 2002; Kempermann, Gast, Kronenberg, Yamaguchi, & Gage, 2003; Van Praag et al., 1999b; Winner, Cooper-Kuhn, Aigner, Winkler, & Kuhn, 2002). In the young adult rats it has been shown that approximately 9000 new cells are generated in the dentate gyrus each day and that within 5–12 days 50% of these cells can be double-labeled with neuron-specific markers (Cameron & McKay, 2001). Assuming that most of the new granule neurons were to survive for 4 weeks, the number of new neurons generated in the hippocampus could be as large as an impressive 6% of the total granule cell population. 1.2. Environmental factors involved in neurogenesis Various environmental factors have been found to modulate the rate of proliferation of new cells in the dentate gyrus of rodents. For example, physical activity (e.g., Van Praag et al., 1999b) and enriched environment (e.g., Kempermann, Brandon, & Gage, 1998a) were found to increase hippocampal proliferation. Also, it has recently been found that hippocampal-dependent learning can enhance proliferation of hippocampal cells (Lemaire, Koehl, Le Moal, & Abrous, 2000). Two other studies did not, however, observe an effect of hippocampal-dependent learning on hippocampal proliferation (Gould et al., 1999a; Van Praag et al., 1999b). A factor that negatively affects proliferation is stress (Czeh et al., 2002; Gould & Tanapat, 1999; Tanapat, Galea, & Gould, 1998; Tanapat, Hastings, Rydel, Galea, & Gould, 2001). Similar to proliferation, the survival of cells is also partly dependent on environmental conditions. For example, in rodents it has been shown that exposure to an enriched environment (Kempermann et al., 1998a, 1997b; Kempermann, Kuhn, & Gage, 1998b; Van Praag et al., 1999b), physical activity (Van Praag et al., 1999a, 1999b) or hippocampal-dependent learning (Gould et al., 1999a) can increase or prolong the survival of newly proliferated cells. On the other hand, in contrast

to the latter study no effect on the survival of new neurons was found by a different group using the same hippocampal-dependent learning task (Van Praag et al., 1999b). Stress has been shown to decrease the survival rate in the hippocampus of rodents (Czeh et al., 2002). 1.3. Functions of neurogenesis The principle of neurogenesis (i.e., proliferation and survival) has major implications for different areas of central nervous system research in which until recently adult brain plasticity was assumed to be related to changes in neuronal connections (neurobiology of learning and memory, neuronal network models) and compensation for neuronal loss (aging, neurodegeneration). These new insights have already led to the suggestion that physical and mental activities may reduce both the incidence and severity of neurodegenerative disorders in man (Mattson, 2000). We suggest that this may also provide a mechanism for the already proposed principle of Ôuse it or lose itÕ during aging and neurodegeneration (Swaab, 1991). According to the Ôuse it or lose itÕ hypothesis, activation of neuronal activity within the physiological range could preferentially stimulate the action of protective mechanisms during aging and in AlzheimerÕs disease. Enriched environment was identified as one possible activating stimulus. However, DNA repair was assumed to be the possible protective mechanism instead of new neurons. We assume that during non-pathological conditions the Ôuse it or lose itÕ principle might also be applicable since it might determine which new cells or neurons survive (used) or die (not used). 1.4. Aim of the review Although the studies available at present have increased our understanding of the factors which mediate neurogenesis, discrepant findings between similar studies, especially in relation to whether hippocampal-dependent learning and neurogenesis are directly related to each other, indicate that the precise nature of this phenomenon still has to be resolved. Table 1 summarizes the findings on the effects of hippocampal-dependent learning on neurogenesis.

Table 1 Effects of hippocampal-dependent learning on proliferation and survival of cells in the dentate gyrus within the hippocampal formation of rodents Behavioral task

Reference

Proliferation

Survival

Morris water escape task

Van Praag et al. (1999b) Gould et al. (1999a) Ambrogini et al. (2000) Lemaire et al. (2000) Gould et al. (1999a)

) n.m. n.m. + )

) +a +a n.m. +a

Trace eye-blink conditioning

n.m., not measured; ), no effect; +, increase in number of BrdU-labeled cells as measured by BrdU immunohistochemistry. a Additional double staining with neuronal markers revealed an increase in neurons.

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It is well known that the behavior and biology of rodents can vary considerably between strains. Further, given that the effect of a treatment is to a great extent strain dependent it is not surprising that recent studies have shown that neurogenesis also depends on the mouse strain that is studied (cf. Kempermann et al., 1998a, 1997a; Kempermann & Gage, 2002; Van Praag et al., 1999b). Other factors including species (cf. Gould et al., 1999a; Lemaire et al., 2000; Van Praag et al., 1999b), age (Kempermann, Gast, & Gage, 2002; Kempermann et al., 1998b; Kuhn, Dickinson-Anson, & Gage, 1996), and sex (Tanapat, Hastings, Reeves, & Gould, 1999) also seem to influence the level of both proliferation and survival. In particular the stage of estrus, i.e., fluctuating estrogen levels, appears to directly affect the number of new cells found. Examples can be cited where factors like sex and species may underlie discrepant findings in the literature. For instance, the effect of hippocampaldependent learning on survival was found using male rats (Gould et al., 1999a) and not with female mice (Van Praag et al., 1999b). The same applies to two conflicting studies with respect to learning and proliferation in which different species were used (i.e., female mice (Van Praag et al., 1999b) vs. female rats (Lemaire et al., 2000)). A valid comparison between studies can be made only if these factors are accounted for. Here we propose that, in addition to the factors strain, species, age, and sex, the differences in the detection methods used and confounding interactions between the environmental factors hippocampaldependent learning, stress, and physical activity, can explain the variable effects on cell proliferation and survival of new neurons found in response to stimuli. Moreover, because of these potential pitfalls the conclusions as formulated in the literature with respect to learning and neurogenesis may not be warranted. With differences in methods or confounded methods we will comment on the most widely used technique, BrdU labeling.

2. Methodological considerations 2.1. General BrdU protocols, as reported in most studies, do not solely reflect the true level of newly proliferating cells. A confounding factor might be that BrdU can also detect DNA repair, although there are strong arguments against DNA repair as the major source of BrdU labeling in the intact adult brain (Cooper-Kuhn & Kuhn, 2002). Also, changes in the integrity of the blood–brain barrier as a result of an environmental condition might influence the number of cells labeled, e.g., an increased number of labeled cells might merely reflect an increased leakage of BrdU into the brain (Cooper-Kuhn & Kuhn,

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2002; Scheepens, Van de Waarenburg, Van den Hove, & Blanco, 2003). But here we will focus on the more important issue of dilution of the label due to cell division which may contribute to an over- or underestimation of the number of newly formed cells. In addition, the timing of injection of the label is a critical factor to dissociate between the effects of environmental factors on proliferation and survival. Finally, we will discuss the significance of also measuring apoptosis and differentiation when assessing neurogenesis. 2.2. The problems of dilution, over- and underestimation 2.2.1. Dilution A crucial variable in the analysis of BrdU labeling studies is when the tracer is injected as compared to when the animal is killed. BrdU has a bioavailable time for incorporation of only about 30–60 min (Boswald, Harasim, & Maurer-Schultze, 1990). However, many studies have shown that in the days after a single BrdU administration, the numbers of BrdU positive cells increase peaking at around 1 week postinjection (e.g., Gould et al., 1999a). Similar results have been obtained with [3 H]thymidine (Cameron et al., 1993). This is due to proliferating cells which have taken up the label continuing to divide (see Fig. 1). Taking the cycle time of these proliferative cells to be around 24 h (cf. Cameron & McKay, 2001) means that on every day after the injection, the number of BrdU-labeled cells should double (assuming they survive and stay in proliferative ÔmodeÕ). The labeled cells may however either continue to proliferate and further dilute the label, or cease to proliferate and subsequently migrate out of the proliferative zone, or die. As mentioned, it should be noted here that under ÔnormalÕ conditions at least 50% of newly generated cells die. Since the peak in the number of labeled cells appears at around 1 week (Cameron et al., 1993; Gould & Tanapat, 1999), one can assume that by then the BrdU label is so diluted (around 1/128) as to be below detectable limits for immunohistochemistry. Thus although newly BrdU-labeled cells are produced after 7 days they are not detected and the net number of cells counted after 7 days represents those cells created over the 7 days which are the direct progeny of the initial cells which were in S-phase during exposure to the label, less those that have died or migrated out of the area counted. So the effect of proliferation alone, on every day after injection, is added to the number of cells counted as well as the survival of those cells which were labeled earlier in the week and have not continued to proliferate. After day 7 the number of cells dying is greater than the number of new cells being formed which contain enough label to be counted as immunopositive due to the label dilution dipping under the delectable level.

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Fig. 1. Diagram illustrating the theoretical incorporation of BrdU into proliferate regions of the adult brain. Immediately after injection all (or most) S-phase cells are fully labeled within 30–60 min after which no more Ôfree BrdUÕ is available. Each newly made cells can then either remain in Ôproliferation modeÕ and continue to divide or can migrate out of the proliferation zone and either differentiate or die. Those cells which continue to proliferate, then dilute half their BrdU content with each division until the levels are below detectable limits, probably around 1 week. Therefore the total number of cells counted at any time point, except for 1–2 h after the label injection, is a summation of proliferation at the time of injection plus proliferation on each day after injection less the death rate (i.e., lack of survival) of the newly made cells. Also note that the number of cells labeled is dose dependent, i.e., not all cells are labeled after a single injection. As a consequence it has to be realized that the number of labeled cells counted is dependent on the dose and time after the injection. This makes it difficult to deduce the ÔtrueÕ rate of proliferation. Multiple injections with BrdU (per day or over days) further affect the accuracy of the proliferation measurements, i.e., over- or underestimation (see text for explanation). Abbreviations: Prolif., proliferation; DG-SGZ, dentate gyrus-sub granular zone; DG-GCL, dentate gyrus-granular cell layer.

2.2.2. Over- and underestimation In a recent study this phenomenon of dilution of label was thoroughly investigated in cells of the dentate gyrus of mice by using BrdU (Hayes & Nowakowski, 2002). It has to be noted that a single injection of the most commonly used dose of BrdU leaves unlabeled one-half to two-thirds of the proliferating population. Increasing the dose to a maximum level without inducing toxic effects (e.g., 300 mg BrdU/kg rat: Cameron & McKay, 2001) results in many more labeled cells. Even more cells of the proliferating population can be labeled using

repeated injections (e.g., 50 mg BrdU/kg every 4 h for 12 h in the mouse: Hayes & Nowakowski, 2002), although this protocol will also not measure proliferation accurately (Hayes & Nowakowski, 2002). Most studies investigating neurogenesis have used a labeling paradigm in which a single injection of a dose, which varied considerably between studies, of tracer (mostly BrdU) was repeated daily. Even when the daily injections are out of phase with the S-phase, relabeling of the same subset of cells will occur eventually. As explained by Hayes and Nowakowski (2002), the proliferating cells

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and the newly postproliferating cells intermingle and as a result, the actual number of cells in the proliferating population will be overestimated. This will be the case when shorter daily injection protocols are used (e.g., less than a week). In contrast, longer daily injection protocols will result in an underestimation of the proliferation since cell death becomes of prominent influence. Thus, the total length of the daily injection protocol may lead to either an overestimate (less than a week) or an underestimate (more than a week) of proliferation. 2.2.3. Retroviral labeling Another method to detect newborn neurons is the use of a retroviral construct which offers the advantage that only cells that have divided are labeled. Thus, DNA repair is excluded. In addition, there is no dilution of the label during cell division. This allows for the study of all progeny, regardless of the number of divisions. The introduction of a reporter gene such as green fluorescent protein, which fills the soma and the dendritic processes, allows complete structural analysis (Van Praag et al., 2002). Retroviral labeling offers an alternative future technique to study the effects of factors such as learning, physical activity, and stress on neurogenesis. However, there are some disadvantages. For example, stereotaxic injections are required thereby disrupting the blood– brain barrier and causing an injury response by the brain, and it is not guaranteed that all progeny of an infected cell will express the retroviral genome (CooperKuhn & Kuhn, 2002). In addition, the diagram as illustrated in Fig. 1 also partly applies to retroviral labeling which requires only a single injection. However, since new cells are always labeled the number of labeled cells remains constant as soon as the number of cells dying is the same as the number of new cells being formed. 2.3. Timing of injection(s) 2.3.1. Timing of injection(s) and measuring proliferation Only one study has found that hippocampal-dependent learning (Morris water escape task) increased the number of proliferated cells in the dentate gyrus (Lemaire et al., 2000). BrdU was given during the second half of training on the last 3 days and injected just before daily learning. The animals were killed 24 h after the last injection. Although there was some overestimation of the actual number of cells proliferating, it can be concluded that hippocampal learning increases proliferation. In contrast, another study showed that hippocampal-dependent learning in the Morris water escape task has no effect on proliferation (Van Praag et al., 1999b). In this study BrdU was given during spatial learning over 12 consecutive days. Unfortunately, the timing of the daily injections was not mentioned. These animals were killed 1 day after the last day of training in order to measure

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proliferation. Using this protocol, a substantial part of the (underestimated) proliferation measurement reflects survival. Thus, the number of BrdU-positive cells counted is in fact the sum of proliferating and surviving cells which were labeled after each daily BrdU injection. In the same study the effect on survival was measured by counting the number of BrdU-labeled cells 4 weeks after the last BrdU injection. The survival measurement is now influenced by the effect of learning on proliferation at the time of BrdU injection. As a consequence, one can imagine that multiple BrdU injections, as commonly used, over days or weeks make it impossible to differentiate between proliferation and survival aspects of newly formed cells in response to stimuli. To prevent misinterpretation of neurogenesis data, appropriate protocols for measuring proliferation and survival should be used. Proliferation should be measured using a protocol in which subjects are treated with a tracer and killed maximally within 24 h (i.e., before the end of one complete cell cycle) (cf. Hayes & Nowakowski, 2002). In addition, the time of injection should be immediately before or within hours of testing. Although such protocol was used, no effect was found of hippocampal-dependent learning in a conditioned trace paired eye-blink task on proliferation (Gould et al., 1999a). However, the animals were treated only once with BrdU on the last day of training after they had reached the learning criterion. This was probably too late. In summary, when assessing the effect of learning on proliferation, the number of proliferating cells should be measured for each training day separately. 2.3.2. Timing of injection(s) and measuring survival When investigating whether a stimulus has an effect on survival, the tracer should be given before the onset of the stimulus. In one study investigating the influence of learning on survival using such a ÔpureÕ survival protocol, BrdU was given 1 week before the Morris water escape task and the animals were killed one day after finishing hippocampal-dependent learning (Gould et al., 1999a). Thus, the effect of learning on survival of neurons that were recently produced during normal conditions is measured. It was found that learning had a positive effect on the survival of granule cells in the dentate gyrus. In contrast, it has also been reported that learning in the spatial Morris water escape task had no effect on the survival of neurons in the dentate gyrus, not using such a ÔpureÕ survival protocol (Van Praag et al., 1999b). In the latter study it was suggested that probably too few learning trials were given with two (Van Praag et al., 1999b) instead of four (Gould et al., 1999a) trials per day. Likewise, in a more recent study investigating ÔpureÕ survival during the Morris water escape task, learning with 10 trial per day was found to increase the survival of granule cells in the dentate gyrus (Ambrogini et al., 2000).

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However, besides the number of daily training trials, another explanation has also been offered by assuming that newly formed neurons go through a transient period of sensitivity to the survival-promoting effects of learning (Greenough, Cohen, & Juraska, 1999). The positive effect on survival could be found because the cells were labeled 1 week before training and were within this sensitivity period during learning. The finding of no effect on survival could then be due to the fact that the animals were trained before the sensitive period of the newly labeled cells since labeling was done during training. Thus, if cells are not exposed to the influence of learning during the sensitive period they will die (Ôuse it or lose it?Õ). 2.4. Apoptosis, migration, and differentiation Another important aspect when studying adult neurogenesis whether in relation to learning or not, is the migration and differentiation of the newly made cells into neurons and their eventual integration into a functional network. However, when studying proliferation with an appropriate protocol, which requires killing the animals within one complete cell cycle (24 h) after labeling with the tracer, investigation of differentiation will be of limited value. The newly generated cells are obviously immature to reliably express even immature neuronal markers, which were shown to co-label with BrdU only after more than 24 h of the BrdU injection (Cooper-Kuhn & Kuhn, 2002). Progenitor cells either die (about 50%) or differentiate into a neuron, glia or neither. It is assumed that especially young and immature cells, i.e., undifferentiated, are under pressure of elimination by programmed cell death (Kempermann et al., 2003; Winner et al., 2002). It is therefore useful to also measure apoptosis in order to determine to what extent changes in survival reflect differences in apoptotic rates (cf. Young, Lawlor, Leone, Dragunow, & During, 1999). After the first weeks of postnatal life the number of neurons remains stable for at least 1 year or even more (Kempermann et al., 2003; Winner et al., 2002). According to the literature, learning (but also physical activity) has no effect on the survival of glia (Gould et al., 1999a; Van Praag et al., 1999a, 1999b). However, due to the use of very different neuronal and glial markers within the literature the effects or the lack of effects on gliagenesis is still a matter of debate. Nevertheless, a role for (new) astrocytes in neurogenesis should not be ruled out since it has recently been found that new granule neurons in the rat hippocampus may arise from cells with the characteristics of astrocytes (Alvarez-Buylla, Seri, & Doetsch, 2002; Seri, GarciaVerdugo, McEwen, & Alvarez-Buylla, 2001). It is also worth mentioning that many studies are using immature neuronal markers and therefore may be missing mature

neurons or vice versa depending on when the subjects are killed as compared to the time of BrdU injection (see also Cooper-Kuhn & Kuhn, 2002). Further, it is also worth considering whether a stimulus or condition, in this case learning, can change the amount of time it takes a cell to differentiate. Finally, a substantial population of new hippocampal cells (up to about 20%: Cameron et al., 1993; Czeh et al., 2002; Gould et al., 1999a; Kempermann & Gage, 2002; Lemaire et al., 2000; Van Praag et al., 1999a, 1999b) does not differentiate into either a neuron or a GFAP-positive astrocyte. It might be suggested that these undifferentiated cells Ôlie in waitÕ for some future function. This also applies to newly formed or even differentiated cells which may be recruited for function without that function being clear at the time of their formation/differentiation (cf. Kempermann, 2002). Further, it seems possible that recruitment of a young or immature cell might prevent it from being eliminated as in agreement with the Ôuse it or lose itÕ principle (cf. Swaab, 1991).

3. Interactions between learning, stress, and physical activity 3.1. Learning and stress Proliferation and survival data are influenced by the interaction of factors including genetics, learning, stress, and physical activity. The separate contribution of each factor and their interactions determine the net rate of proliferation and survival. Thus, the lack of a positive effect on proliferation or survival can be nullified by a counteracting factor (e.g., stress). This may explain why no effect of learning in the spatial Morris water escape task was found on proliferation in some studies (Van Praag et al., 1999b). The Morris water escape task has, besides a component of learning (platform location), a strongly aversive stress (water) component. It has been found that stress, when represented by a single exposure to a stressful odor for example, can decrease hippocampal proliferation rates by as much as 30–60% (Tanapat et al., 1998; Tanapat et al., 2001). In addition, exposure to daily repeated psychosocial stress resulted in a decrease of 29% of the proliferation rate in the hippocampus (Czeh et al., 2002). However, it has to be mentioned that odor stress and psychosocial stress may not be comparable to water stress. Assuming that learning within the spatial Morris water task, physical activity, and novelty (enriched environment) during the task increase proliferation while (water) stress decreases proliferation, then the resulting net rate of proliferation measured may well be zero. However swim-stress, that is swimming without platform, was also found to have no effect on either proliferation or survival (Van Praag et al., 1999b). Moreover, neither neurogenesis measures were

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different between controls, swim-stress animals or learners. It may also be possible that both the stress and learning components were not large enough due to the low number of two training trials per day. For example, four learning trials per day has been shown to increase proliferation (Lemaire et al., 2000). Further, cells were only labeled at the end of training and it was assumed that during this phase of learning the hippocampus would be activated. An additional or alternative mechanism could be that at the end of training the learning component overcomes possible effects of stress on proliferation, since animals can habituate to stress over time. With respect to survival, four or more trials per day has been found to increase cell survival in learners (Ambrogini et al., 2000; Gould et al., 1999a). Remarkably, the swim-stress subjects were not affected (Gould et al., 1999a). This led to the suggestion that swim-stress has no direct effect on the survival of recently produced neurons since the protocol measured ÔpureÕ survival. Recently, it has been demonstrated with a ÔpureÕ survival protocol that daily repeated psychosocial stress suppressed the survival of newly generated neurons in the dentate gyrus (Czeh et al., 2002). Of note, this type of stressor is different from water stress. Whether swim-stress could have an effect on proliferation is still not clear since the protocol used to study proliferation measured primarily survival (Van Praag et al., 1999b). Recently, it has been shown that daily swimming in a water tank for 1 min does not affect the number of BrdU-positive cells (Ra et al., 2002). In this study an injection protocol was used that measures proliferation appropriately although there was some overestimation of the actual proliferative rate. Surprisingly, longer swimming (even up to 20 min) increased cell proliferation. This is unexpected since this form of forced swimming could be considered as very stressful to the animal. However, the water temperature of 32 °C was relatively high. Thus, the water stress within this swimming task may be relatively low and the cell counts then reflect the positive effect of physical activity on proliferation. We suggest that the effects of learning on neurogenesis should be tested in tasks with a minimal stress component.

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rather limited. Moreover, the protocols used to measure proliferation and survival during physical activity also measure a mixture of both survival and proliferation (Van Praag et al., 1999b). Recently, this has been tested using a more appropriate proliferation protocol (Ra et al., 2002). It was found that both treadmill running and swimming increased cell proliferation in the dentate gyrus of adult rats. Conversely, too much physical exercise may be stressful and hence reduce proliferation, as found with treadmill running (Ra et al., 2002). Once more this reinforces the need to be aware that both stress and physical activity can influence the effect of learning on proliferation and survival.

4. Learning and neurogenesis, and vice versa 4.1. Does only hippocampal-dependent learning affect neurogenesis? As mentioned above, the increased survival of dentate gyrus granule cells has been found within a hippocampal-dependent learning paradigm, i.e., Morris water escape task and trace paired eye-blink conditioned response (Gould et al., 1999a). Conversely, non-hippocampal-dependent learning in variants of these tasks had no effect on the survival of hippocampal neurons (Gould et al., 1999a). Further, the increased proliferation of dentate gyrus cells has also been found in the spatial Morris water escape task (Lemaire et al., 2000). Thus, hippocampal neurogenesis seems to play a specific role in only hippocampal-dependent learning (Gould, Tanapat, Hastings, & Shors, 1999b). However, it is important to note that other mechanisms besides neurogenesis (e.g., synaptogenesis (Ramirez-Amaya, Balderas, Sandoval, Escobar, & Bermudez-Rattoni, 2001) and dendritic spine morphogenesis (Leuner, Falduto, & Shors, 2003)) or other brain structures besides the hippocampus, are involved in memory formation as well since animals can and do, learn within non-hippocampal-dependent tasks. 4.2. Does neurogenesis affect hippocampal-dependent learning?

3.2. Learning and physical acticity Even if the role of stress could be ruled out, the physical activity component of swimming in the Morris water escape task might contribute to neurogenesis during learning since physical activity itself is used to measure learning (cf. Kempermann, 2002). However, considering the level of physical activity as measured with wheel running in comparison to the relatively small amount of physical activity involved in the Morris water escape task, then the pro-proliferative effect of physical activity within the Morris water escape task is probably

4.2.1. Increased neurogenesis and learning With respect to learning it is intriguing that learning may increase cell proliferation, yet those newly produced cells are not ready for use until they have differentiated and integrated into a neural network. Thus it might be possible that the presence of new undifferentiated cells increase the ability for future learning as more cells are available for recruitment when necessary (cf. Kempermann, 2002). Likewise, an increased proliferation due to physical activity or an enriched environment may also increase the potential for future learning.

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The positive effect of a condition or stimulus on survival might also contribute to future learning although it seems plausible that these cells should not be too differentiated. Perhaps, as was already mentioned, the population of surviving undifferentiated cells, which are always observed, may be of particular importance. Thus, it has been hypothesized that there is a functional correlation between adult hippocampal neurogenesis and learning. Evidence in favor of this hypothesis comes from a study demonstrating that increased physical activity increased the survival of hippocampal granule cells, while at the same time spatial learning in the Morris water escape task was improved (Van Praag et al., 1999a). Additional evidence comes from the finding that an enriched environment increased the proliferation and/or survival of granule cells, which was paralleled by enhanced spatial learning in the Morris water escape task (Kempermann & Gage, 2002; Kempermann et al., 2002, 1998a, 1997b, 1998b). 4.2.2. Decreased neurogenesis and learning In contrast to an increase in the number of cells available for future learning and survival, the availability of cells can be reduced by a decrease in the initial rate of proliferation. This was investigated using the toxin methylazoxymethanol acetate (MAM) which causes newly proliferated cells to die. As expected, MAM treatment dramatically reduced the number of cells and impaired trace eye-blink conditioning (Shors et al., 2001) and trace fear conditioning (Shors, Townsend, Zhao, Kozorovitskiy, & Gould, 2002). However, hippocampal-dependent learning within the contextual fear conditioning test and the spatial Morris water escape task was not affected by MAM treatment (Shors et al., 2002). One explanation offered for these surprising findings is that the latter kind of hippocampal-dependent learning can still occur with a very small percentage of newly made neurons since MAM does not result in a complete depletion of proliferating cells. Another remarkable finding comes from a study that investigated learning in presenilin-1 conditional knockout mice (Feng et al., 2001). These mice show a deficiency in enriched environment-induced neurogenesis. The reduction in neurogenesis measured in these animals (mainly reflecting proliferation) did not result in deficits during hippocampal-dependent contextual fear learning. It was argued that hippocampal neurogenesis is not required for new memory formation. Surprisingly, it was found that postlearning environmental enrichment improved memory performance in the retention test of the knockout mice, whereas the control mice showed no retention of memory. It was postulated that adult neurogenesis in the dentate gyrus may represent a mechanism for the clearance of outdated hippocampal memory traces after the memory is consolidated in the cortex. This would then enable the hippocampal system

to be continuously available to process new memories. This theory implies that new neurons may even have disruptive effects on learning. Together, these findings and assumptions raise more questions about the role of neurogenesis in learning then they answer. Moreover, it emphasizes the possibility that more factors are involved then we are aware of which are interacting with each other in a complex fashion. Further research is clearly required to determine whether there is a direct causal link between neurogenesis and learning, and vice versa.

5. Conclusions Besides that appropriate protocols should be used for measuring proliferation and survival independently, both processes should be measured within the same experiment since they are directly related to each other. For instance, changes in survival of cells supposed to be caused by an environmental factor may just be due to changes in the rate of initial proliferation caused by the same environmental factor. The complex nature of the interaction between proliferation and survival, and the environmental factors that can independently influence them should be carefully considered for as to have an accurate interpretation of the data. This is illustrated in Fig. 2 and explained in detail in the legend. Although stated otherwise in the literature, the generation of new cells, i.e., proliferation, as a result of learning cannot yet be ruled out. The available data mostly measure survival and is confounded by many factors including both environmental and genetic. Future research should make more use of behavioral tasks with minimal stress and physical exercise components. In addition, a protocol should be optimized to measure proliferation independently from survival, i.e., subjects are injected with BrdU or [3 H]thymidine either immediately before or within hours of testing and killed within 1–2 h of the injection. When measuring proliferation using retroviral labeling, the animals should be killed after 24 h since a cell must go through a complete cell division. In summary we feel that future studies should consider the following aspects. 1. Proliferation and survival of cells should be measured independently within an experiment. The dose, timing, and number of injections of thymidine analogue used should be standardized. The same applies to the volume and timing of retroviral injection. 2. The interaction between factors should be controlled for as much as possible, especially the influence of stress (e.g., housing, test-related stress, odors, etc.). 3. When investigating survival, also migration and differentiation endpoints (neuron vs. glia) of cells should be investigated with standardization of neuronal and glial markers across the literature. In addition, double labeling experiments need to prove double label-

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Fig. 2. The following factors must be considered when studying neurogenesis: (1) the proliferation of new cells, (2) the survival (and subsequent migration and differentiation into neurons or glia) of the newly generated cells, and (3) the differential effect of environmental factors on each process independently. This diagram illustrates the hypothetical rates of proliferation and survival in relation to different environmental conditions and demands. The upper line (—) of each shaded survival area represents optimal cell survival during exposure to specified environmental conditions. The middle line (

) of each shaded area represents survival under ÔnormalÕ (baseline) conditions. The lower line (





) of each shaded area represents decreased survival under stressed conditions. This clearly illustrates that a measure of survival means little unless proliferation is also measured. For example, the number of surviving cells counted at the end, in the upper shaded area of the survival box, can be a result of a high proliferation of new cells at the starting point and a subsequent low survival rate of these cells. On the other hand, the same total number of cells may be counted as a result of a normal proliferation and a high survival rate. Further, the differential effect of environmental effects can be explained with the following examples. Stress has been shown to decrease proliferation and survival. Therefore, if stress is not taken into account at any point in time between label injection and sacrifice, then the number of newly generated cells may be lower than under normal ÔunstressedÕ conditions. Thus, this stress effect can nullify any positive effect on proliferation or survival of the paradigm being tested. Conversely, a false positive effect on proliferation or survival can be caused for example by neglecting the pro-proliferative effect of physical activity or novelty during learning.

ing with cell type markers using confocal microscopy instead of light microscopy to rule out miss-labeling of newly made perineuronal glia as compared to true neurons. If possible, the total number of cells and the amount of apoptosis should also be measured. 4. The use of cell counting techniques, especially for thymidine analogue studies, should be standardized to allow cross study comparisons. 5. Another important and relevant aspect directly related to learning is the phenomenon of synaptogenesis, the formation of new or larger synapses. Hippocampal-dependent learning in the spatial Morris water escape task has also been shown to result in increased mossy fiber (axon of granule cells) synaptogenesis within the hippocampus (Ramirez-Amaya et al., 2001; but see also Rusakov et al., 1997). Apparently, both neurogenesis and synaptogenesis are increased after hippocampal learning although the individual contribution of either mechanism to new

memories is not know. Therefore, the respective contribution of both neurogenesis and synaptogenesis to learning and memory needs to be studied within the same experimental paradigm. Future studies from all disciplines of neuroscience, taking these aspects into consideration are needed to better understand the full nature and the implications that the fascinating phenomenon of neurogenesis may bring.

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